From 021550d5119cfb6dbc3301b4b2982cce0900d7c9 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Sun, 26 Apr 2026 22:32:17 -0400 Subject: [PATCH 01/28] support Array and lambda diffusions (special support for scalar/diag/full matrix) --- .../integrations/cd_dynamax/utils.py | 75 ++++++- dynestyx/models/__init__.py | 2 + dynestyx/models/checkers.py | 33 ++- dynestyx/models/core.py | 29 ++- dynestyx/models/diffusions.py | 204 +++++++++++++++++ dynestyx/models/lti_dynamics.py | 3 +- dynestyx/solvers/sde.py | 74 ++++--- tests/test_bm_dim_plate.py | 149 +++++++------ tests/test_discretizers.py | 62 ++++++ ...erarchical_simulator_discretizer_smokes.py | 3 +- tests/test_models_core.py | 209 +++++++++++++++++- 11 files changed, 703 insertions(+), 140 deletions(-) create mode 100644 dynestyx/models/diffusions.py diff --git a/dynestyx/inference/integrations/cd_dynamax/utils.py b/dynestyx/inference/integrations/cd_dynamax/utils.py index f8b620c6..a3ccc2d3 100644 --- a/dynestyx/inference/integrations/cd_dynamax/utils.py +++ b/dynestyx/inference/integrations/cd_dynamax/utils.py @@ -22,24 +22,33 @@ LinearGaussianObservation, LinearGaussianStateEvolution, ) +from dynestyx.models.diffusions import diffusion_as_matrix, evaluate_diffusion type SSMType = ContDiscreteNonlinearGaussianSSM | ContDiscreteNonlinearSSM def _normalize_cd_dynamax_diffusion( - diffusion_coefficient, + state_evolution: ContinuousTimeStateEvolution, state_dim: int, ): """Return a diffusion coeff compatible with cd-dynamax's EnKF SDE solve. cd-dynamax's internal diffrax wrapper builds Brownian controls with shape - equal to `y0.shape` (state_dim). For non-square diffusion coefficients - (state_dim, bm_dim) with bm_dim != state_dim, pad/truncate columns so the - returned matrix is always (state_dim, state_dim). + equal to `y0.shape` (state_dim), so this path only supports diffusion + matrices with `bm_dim == state_dim`. """ def _wrapped(x, u, t): - L = diffusion_coefficient(x, u, t) + diffusion = evaluate_diffusion( + state_evolution.diffusion_coefficient, + diffusion_type=state_evolution.diffusion_type, + bm_dim=state_evolution.bm_dim, + x=x, + u=u, + t=t, + state_dim=state_dim, + ) + L = diffusion_as_matrix(diffusion, state_dim=state_dim) if L.ndim == 1: L = jnp.diag(L) if L.ndim != 2: @@ -47,15 +56,44 @@ def _wrapped(x, u, t): "diffusion_coefficient must return a vector or matrix for cd-dynamax." ) n_cols = L.shape[-1] - if n_cols == state_dim: - return L - if n_cols < state_dim: - return jnp.pad(L, ((0, 0), (0, state_dim - n_cols))) - return L[:, :state_dim] + if n_cols != state_dim: + raise ValueError( + "cd-dynamax continuous diffusion requires bm_dim == state_dim. " + f"Got state_dim={state_dim}, bm_dim={n_cols}." + ) + return L return _wrapped +def _validate_cd_dynamax_continuous_diffusion( + state_evolution: ContinuousTimeStateEvolution, + state_dim: int, +) -> None: + """Eagerly validate diffusion shape constraints for cd-dynamax continuous filters.""" + if state_evolution.diffusion_coefficient is None: + return + + probe_x = jnp.zeros(state_dim) + diffusion = evaluate_diffusion( + state_evolution.diffusion_coefficient, + diffusion_type=state_evolution.diffusion_type, + bm_dim=state_evolution.bm_dim, + x=probe_x, + u=None, + t=jnp.array(0.0), + state_dim=state_dim, + ) + bm_dim = diffusion_as_matrix(diffusion, state_dim=state_dim).shape[-1] + if bm_dim != state_dim: + raise ValueError( + "Continuous cd-dynamax filters require full diffusion with " + f"bm_dim == state_dim. Got state_dim={state_dim}, bm_dim={bm_dim}. " + "Use em_scan-based simulation for rectangular diffusion, or provide " + "a square full diffusion for this backend." + ) + + class _ConstantFunction(eqx.Module): value: Any @@ -198,7 +236,16 @@ def dsx_to_cdlgssm_params(dsx_model: DynamicalModel) -> ParamsCDLGSSM: # Extract constant L and use inferred Brownian dimension. x0 = jnp.zeros(dsx_model.state_dim) - L = state_evo.diffusion_coefficient(x0, None, jnp.array(0.0)) + diffusion = evaluate_diffusion( + state_evo.diffusion_coefficient, + diffusion_type=state_evo.diffusion_type, + bm_dim=state_evo.bm_dim, + x=x0, + u=None, + t=jnp.array(0.0), + state_dim=dsx_model.state_dim, + ) + L = diffusion_as_matrix(diffusion, state_dim=dsx_model.state_dim) if state_evo.bm_dim is None: raise ValueError( "state_evolution.bm_dim is not set on ContinuousTimeStateEvolution." @@ -273,8 +320,12 @@ def dsx_to_cd_dynamax( raise ValueError( "state_evolution.bm_dim is not set on ContinuousTimeStateEvolution." ) + _validate_cd_dynamax_continuous_diffusion( + state_evo, + dsx_model.state_dim, + ) diffusion_coeff = _normalize_cd_dynamax_diffusion( - state_evo.diffusion_coefficient, + state_evo, dsx_model.state_dim, ) shared_params.update( diff --git a/dynestyx/models/__init__.py b/dynestyx/models/__init__.py index 6b2f1f56..c7deab13 100644 --- a/dynestyx/models/__init__.py +++ b/dynestyx/models/__init__.py @@ -10,6 +10,7 @@ DynamicalModel, ObservationModel, ) +from dynestyx.models.diffusions import DiffusionType from dynestyx.models.lti_dynamics import LTI_continuous, LTI_discrete from dynestyx.models.observations import ( DiracIdentityObservation, @@ -27,6 +28,7 @@ "AffineDrift", "DiracIdentityObservation", "DiscreteTimeStateEvolution", + "DiffusionType", "DynamicalModel", "Drift", "GaussianObservation", diff --git a/dynestyx/models/checkers.py b/dynestyx/models/checkers.py index 28b2bd6d..d4881927 100644 --- a/dynestyx/models/checkers.py +++ b/dynestyx/models/checkers.py @@ -8,6 +8,10 @@ import numpyro.distributions as dist import numpyro.primitives +from dynestyx.models.diffusions import ( + evaluate_diffusion_value, + resolve_diffusion_metadata, +) from dynestyx.types import Control, State, Time @@ -100,27 +104,16 @@ def _infer_bm_dim( return None diffusion_shape = jax.eval_shape( - lambda: state_evolution.diffusion_coefficient(x0, u0, t0) - ).shape - if len(diffusion_shape) < 2: - raise ValueError( - "diffusion_coefficient must return shape (..., state_dim, bm_dim). " - f"Got shape {diffusion_shape}." - ) - if int(diffusion_shape[-2]) != state_dim: - raise ValueError( - "diffusion_coefficient penultimate dimension must match state_dim. " - f"Got diffusion shape {diffusion_shape}, state_dim={state_dim}." - ) - inferred_bm_dim = int(diffusion_shape[-1]) - if ( - state_evolution.bm_dim is not None - and int(state_evolution.bm_dim) != inferred_bm_dim - ): - raise ValueError( - "bm_dim does not match inferred diffusion_coefficient output shape. " - f"Got bm_dim={state_evolution.bm_dim}, inferred={inferred_bm_dim}." + lambda: evaluate_diffusion_value( + state_evolution.diffusion_coefficient, x0, u0, t0 ) + ).shape + _, inferred_bm_dim = resolve_diffusion_metadata( + diffusion_shape, + state_dim=state_dim, + diffusion_type=state_evolution.diffusion_type, + bm_dim=state_evolution.bm_dim, + ) return inferred_bm_dim diff --git a/dynestyx/models/core.py b/dynestyx/models/core.py index dc3cab02..6c8dc212 100644 --- a/dynestyx/models/core.py +++ b/dynestyx/models/core.py @@ -21,7 +21,15 @@ _validate_state_dim, _validate_state_evolution_output_shape, ) -from dynestyx.types import Control, State, Time, TimeLike, as_scalar_time_array, dState +from dynestyx.models.diffusions import DiffusionSpec, DiffusionType +from dynestyx.types import ( + Control, + State, + Time, + TimeLike, + as_scalar_time_array, + dState, +) class DynamicalModel(eqx.Module): @@ -298,18 +306,25 @@ class ContinuousTimeStateEvolution(eqx.Module): At least one of `drift` or `potential` must be non-None. use_negative_gradient (bool): If True, use $-\\nabla_x V$ (e.g., gradient descent on potential); otherwise use $+\\nabla_x V$. Default is False. - diffusion_coefficient (Drift | None): Diffusion coefficient $L(x, u, t)$ mapping to a matrix; - multiplies the Brownian increment $dW_t$. - Defaults to zero if None (i.e., deterministic ODE). + diffusion_coefficient (DiffusionSpec | None): Diffusion coefficient specification. + This may be a callable `L(x, u, t)`, a constant scalar/vector/matrix, or `None` + for deterministic dynamics. + diffusion_type ("full" | "diag" | "scalar" | None): Optional explicit diffusion semantics. + Use `"full"` for matrix-valued diffusion, `"diag"` for diagonal shorthand with + trailing shape `(..., state_dim)`, and `"scalar"` for scalar shorthand with shape + `()` or `(..., 1)`. If omitted, legacy behavior infers `"full"` from trailing + shape `(..., state_dim, bm_dim)` and otherwise infers scalar/diagonal shorthand + from the trailing dimension. bm_dim (int | None): Dimension of the Brownian motion $W_t$. - Inferred automatically from the output shape of `diffusion_coefficient`; - if passed by the user, it must match diffusion_coefficient(...).shape[1]. + Inferred automatically only for full matrix diffusion. Scalar and diagonal + diffusion require explicit `bm_dim`, which must be either `1` or `state_dim`. """ drift: Drift | None = None potential: Potential | None = None use_negative_gradient: bool = eqx.field(static=True, default=False) - diffusion_coefficient: Drift | None = None + diffusion_coefficient: DiffusionSpec | None = None + diffusion_type: DiffusionType | None = eqx.field(static=True, default=None) bm_dim: int | None = eqx.field(static=True, default=None) def total_drift(self, x: State, u: Control | None, t: Time) -> dState: diff --git a/dynestyx/models/diffusions.py b/dynestyx/models/diffusions.py new file mode 100644 index 00000000..0793d5bc --- /dev/null +++ b/dynestyx/models/diffusions.py @@ -0,0 +1,204 @@ +"""Helpers for evaluating and normalizing continuous-time diffusion specs.""" + +from __future__ import annotations + +from collections.abc import Callable +from typing import Literal, NamedTuple + +import jax.numpy as jnp +from jax import Array + +from dynestyx.types import Control, State, Time + +DiffusionType = Literal["full", "diag", "scalar"] +DiffusionValue = Array | float | int +DiffusionSpec = Callable[[State, Control | None, Time], DiffusionValue] | DiffusionValue + + +class EvaluatedDiffusion(NamedTuple): + diffusion_type: DiffusionType + value: Array + bm_dim: int + + +def evaluate_diffusion_value( + diffusion_coefficient: DiffusionSpec, + x: State, + u: Control | None, + t: Time, +) -> Array: + """Evaluate a diffusion spec and return it as a JAX array.""" + value = ( + diffusion_coefficient(x, u, t) + if callable(diffusion_coefficient) + else diffusion_coefficient + ) + return jnp.asarray(value) + + +def resolve_diffusion_metadata( + shape: tuple[int, ...], + *, + state_dim: int, + diffusion_type: DiffusionType | None, + bm_dim: int | None, +) -> tuple[DiffusionType, int]: + """Resolve diffusion semantics from trailing shape and user annotations.""" + resolved_type = ( + diffusion_type + if diffusion_type is not None + else _infer_diffusion_type(shape, state_dim=state_dim) + ) + + if resolved_type == "full": + if len(shape) < 2 or int(shape[-2]) != state_dim: + raise ValueError( + "Full diffusion must have trailing shape (..., state_dim, bm_dim). " + f"Got shape {shape} with state_dim={state_dim}." + ) + inferred_bm_dim = int(shape[-1]) + if bm_dim is not None and int(bm_dim) != inferred_bm_dim: + raise ValueError( + "bm_dim does not match inferred diffusion_coefficient output shape. " + f"Got bm_dim={bm_dim}, inferred={inferred_bm_dim} from shape {shape}." + ) + return resolved_type, inferred_bm_dim + + if resolved_type == "diag": + if len(shape) == 0 or int(shape[-1]) != state_dim: + raise ValueError( + "Diagonal diffusion must have trailing shape (..., state_dim). " + f"Got shape {shape} with state_dim={state_dim}." + ) + else: + if len(shape) != 0 and int(shape[-1]) != 1: + raise ValueError( + "Scalar diffusion must have shape () or trailing shape (..., 1). " + f"Got shape {shape}." + ) + + if bm_dim is None: + raise ValueError( + f"{resolved_type} diffusion requires explicit bm_dim. " + "For scalar or diagonal diffusion, bm_dim must be either 1 or state_dim." + ) + resolved_bm_dim = int(bm_dim) + if resolved_bm_dim not in (1, state_dim): + raise ValueError( + f"{resolved_type} diffusion requires bm_dim to be either 1 or state_dim. " + f"Got bm_dim={resolved_bm_dim}, state_dim={state_dim}." + ) + return resolved_type, resolved_bm_dim + + +def evaluate_diffusion( + diffusion_coefficient: DiffusionSpec, + *, + diffusion_type: DiffusionType | None, + bm_dim: int | None, + x: State, + u: Control | None, + t: Time, + state_dim: int, +) -> EvaluatedDiffusion: + """Evaluate a diffusion spec and resolve its semantics.""" + value = evaluate_diffusion_value(diffusion_coefficient, x, u, t) + resolved_type, resolved_bm_dim = resolve_diffusion_metadata( + value.shape, + state_dim=state_dim, + diffusion_type=diffusion_type, + bm_dim=bm_dim, + ) + return EvaluatedDiffusion( + diffusion_type=resolved_type, + value=value, + bm_dim=resolved_bm_dim, + ) + + +def diffusion_as_matrix( + diffusion: EvaluatedDiffusion, + *, + state_dim: int, +) -> Array: + """Convert a structured diffusion into dense (..., state_dim, bm_dim) form.""" + value = diffusion.value + if diffusion.diffusion_type == "full": + return value + + eye = jnp.eye(state_dim, dtype=value.dtype) + if diffusion.diffusion_type == "diag": + if diffusion.bm_dim == 1: + return value[..., :, None] + return value[..., :, None] * eye + + scalar = value if value.ndim == 0 else jnp.squeeze(value, axis=-1) + if diffusion.bm_dim == 1: + return jnp.broadcast_to(scalar[..., None, None], scalar.shape + (state_dim, 1)) + return scalar[..., None, None] * eye + + +def diffusion_covariance( + diffusion: EvaluatedDiffusion, + *, + state_dim: int, +) -> Array: + """Return L L^T while preserving scalar/diagonal structure when possible.""" + value = diffusion.value + if diffusion.diffusion_type == "full": + return value @ jnp.swapaxes(value, -1, -2) + + eye = jnp.eye(state_dim, dtype=value.dtype) + if diffusion.diffusion_type == "diag": + if diffusion.bm_dim == 1: + return value[..., :, None] * value[..., None, :] + return jnp.square(value)[..., :, None] * eye + + sigma_sq = jnp.square(value if value.ndim == 0 else jnp.squeeze(value, axis=-1)) + if diffusion.bm_dim == 1: + return sigma_sq[..., None, None] * jnp.ones( + (state_dim, state_dim), dtype=value.dtype + ) + return sigma_sq[..., None, None] * eye + + +def apply_diffusion( + diffusion: EvaluatedDiffusion, + dw: Array, + *, + state_dim: int, +) -> Array: + """Apply a structured diffusion to a Brownian increment vector.""" + value = diffusion.value + if diffusion.diffusion_type == "full": + return value @ dw + + if diffusion.diffusion_type == "diag": + if diffusion.bm_dim == 1: + return value * dw[0] + return value * dw + + scalar = value if value.ndim == 0 else jnp.squeeze(value, axis=-1) + if diffusion.bm_dim == 1: + return jnp.broadcast_to(scalar * dw[0], (state_dim,)) + return scalar * dw + + +def _infer_diffusion_type( + shape: tuple[int, ...], + *, + state_dim: int, +) -> DiffusionType: + """Infer legacy diffusion semantics from shape when diffusion_type is omitted.""" + if len(shape) >= 2 and int(shape[-2]) == state_dim: + return "full" + if len(shape) == 0 or int(shape[-1]) == 1: + return "scalar" + if int(shape[-1]) == state_dim: + return "diag" + trailing_dim = int(shape[-1]) + raise ValueError( + f"1D diffusion output with trailing dimension {trailing_dim} is treated as " + f"scalar/diagonal shorthand, so it must end in 1 or state_dim={state_dim}. " + "Use shape (..., state_dim, bm_dim) for full diffusion." + ) diff --git a/dynestyx/models/lti_dynamics.py b/dynestyx/models/lti_dynamics.py index e7c98776..e17972c3 100644 --- a/dynestyx/models/lti_dynamics.py +++ b/dynestyx/models/lti_dynamics.py @@ -175,7 +175,8 @@ def LTI_continuous( state_evolution = ContinuousTimeStateEvolution( drift=drift, - diffusion_coefficient=lambda x, u, t: L, + diffusion_coefficient=L, + diffusion_type="full", ) observation_model = LinearGaussianObservation(H=H, R=R, D=D, bias=d) diff --git a/dynestyx/solvers/sde.py b/dynestyx/solvers/sde.py index 09e0da53..f9dc101f 100644 --- a/dynestyx/solvers/sde.py +++ b/dynestyx/solvers/sde.py @@ -12,28 +12,16 @@ from jax import Array, lax, vmap from dynestyx.models import ContinuousTimeStateEvolution, DynamicalModel +from dynestyx.models.diffusions import ( + EvaluatedDiffusion, + apply_diffusion, + diffusion_as_matrix, + diffusion_covariance, + evaluate_diffusion, +) from dynestyx.types import State, Time, TimeLike, as_scalar_time_array -def _apply_diffusion(diffusion_term: Array, dw: Array) -> Array: - """Apply diffusion operator to a Brownian increment. - - Args: - diffusion_term: Diffusion coefficient with shape compatible with `dw`. - dw: Brownian increment vector. - - Returns: - State increment induced by the diffusion term. - """ - if diffusion_term.ndim == 0: - return diffusion_term * dw[0] - if diffusion_term.ndim == 1: - if dw.shape[0] == 1: - return diffusion_term * dw[0] - return diffusion_term * dw - return diffusion_term @ dw - - def _early_return_states(x0: State, saveat_times: Array) -> Array: """Build no-op solve output by repeating the initial state. @@ -61,21 +49,21 @@ def _require_bm_dim(state_evolution: ContinuousTimeStateEvolution) -> int: return int(state_evolution.bm_dim) -def _require_diffusion_fn( +def _require_diffusion_spec( state_evolution: ContinuousTimeStateEvolution, -) -> Callable[[Array, Array | None, Array], Array]: - """Get diffusion callable or raise if unavailable. +) -> Any: + """Get diffusion spec or raise if unavailable. Args: state_evolution: Continuous-time state evolution. Returns: - Diffusion function with signature `(x, u, t) -> diffusion`. + Diffusion callable or constant spec. """ - diffusion_fn = state_evolution.diffusion_coefficient - if diffusion_fn is None: + diffusion_spec = state_evolution.diffusion_coefficient + if diffusion_spec is None: raise ValueError("SDE solver requires diffusion_coefficient to be defined.") - return diffusion_fn + return diffusion_spec def _em_local_terms( @@ -83,7 +71,7 @@ def _em_local_terms( x: Array, u: Array | None, t_now: Array, -) -> tuple[Array, Array]: +) -> tuple[Array, EvaluatedDiffusion]: """Compute local EM drift and diffusion terms. Args: @@ -96,13 +84,21 @@ def _em_local_terms( Tuple `(drift, diffusion)` at `(x, u, t_now)`. """ drift = state_evolution.total_drift(x=x, u=u, t=t_now) - diffusion_fn = _require_diffusion_fn(state_evolution) - diffusion = jnp.asarray(diffusion_fn(x, u, t_now)) + diffusion_spec = _require_diffusion_spec(state_evolution) + diffusion = evaluate_diffusion( + diffusion_spec, + diffusion_type=state_evolution.diffusion_type, + bm_dim=state_evolution.bm_dim, + x=x, + u=u, + t=t_now, + state_dim=x.shape[-1], + ) return drift, diffusion def _em_moments_from_terms( - x: Array, dt: Array, drift: Array, diffusion: Array + x: Array, dt: Array, drift: Array, diffusion: EvaluatedDiffusion ) -> tuple[Array, Array]: """Convert local EM terms to one-step Gaussian moments. @@ -116,7 +112,7 @@ def _em_moments_from_terms( Tuple `(loc, cov)` for the EM Gaussian approximation. """ loc = x + drift * dt - cov = diffusion @ diffusion.T * dt + cov = diffusion_covariance(diffusion, state_dim=x.shape[-1]) * dt return loc, cov @@ -124,7 +120,7 @@ def _em_sample_from_terms( x: Array, dt: Array, drift: Array, - diffusion: Array, + diffusion: EvaluatedDiffusion, *, key: Array, bm_dim: int, @@ -145,7 +141,7 @@ def _em_sample_from_terms( key_next, k_step = jr.split(key) z = jr.normal(k_step, shape=(bm_dim,), dtype=jnp.asarray(x).dtype) dw = jnp.sqrt(dt) * z - x_next = x + drift * dt + _apply_diffusion(diffusion, dw) + x_next = x + drift * dt + apply_diffusion(diffusion, dw, state_dim=x.shape[-1]) return x_next, key_next @@ -405,7 +401,17 @@ def _drift(t, y, args): def _diffusion(t, y, args): u_t = args(t) if args is not None else None - return state_evolution.diffusion_coefficient(x=y, u=u_t, t=t) + diffusion_spec = _require_diffusion_spec(state_evolution) + diffusion = evaluate_diffusion( + diffusion_spec, + diffusion_type=state_evolution.diffusion_type, + bm_dim=state_evolution.bm_dim, + x=y, + u=u_t, + t=t, + state_dim=y.shape[-1], + ) + return diffusion_as_matrix(diffusion, state_dim=y.shape[-1]) k_bm, _ = jr.split(key, 2) bm = dfx.VirtualBrownianTree( diff --git a/tests/test_bm_dim_plate.py b/tests/test_bm_dim_plate.py index 77c367bd..9010b30e 100644 --- a/tests/test_bm_dim_plate.py +++ b/tests/test_bm_dim_plate.py @@ -3,18 +3,69 @@ import jax.numpy as jnp import numpyro import numpyro.distributions as dist +import pytest from dynestyx.models import ContinuousTimeStateEvolution, DynamicalModel -def test_bm_dim_inferred_outside_plate(): - """bm_dim is correctly inferred when not in a plate context.""" +def _make_diffusion_spec( + diffusion_form: str, + *, + state_dim: int, + sigma=None, +): + if diffusion_form == "full": + return jnp.ones((state_dim, 1)), None, None + if diffusion_form == "diag": + return jnp.ones((state_dim,)), "diag", state_dim + if diffusion_form == "scalar": + return jnp.array(1.0), "scalar", state_dim + if diffusion_form == "callable_full": + return ( + (lambda x, u, t: sigma[..., None, None] * jnp.ones((state_dim, 1))) + if sigma is not None + else (lambda x, u, t: jnp.ones((state_dim, 1))), + None, + None, + ) + if diffusion_form == "callable_diag": + return ( + (lambda x, u, t: sigma[..., None] * jnp.ones((state_dim,))) + if sigma is not None + else (lambda x, u, t: jnp.ones((state_dim,))), + "diag", + state_dim, + ) + if diffusion_form == "callable_scalar": + return ( + (lambda x, u, t: sigma[..., None]) + if sigma is not None + else (lambda x, u, t: jnp.array([1.0])), + "scalar", + state_dim, + ) + raise ValueError(f"Unknown diffusion form: {diffusion_form}") + + +@pytest.mark.parametrize( + "diffusion_form", + ["full", "diag", "scalar", "callable_full", "callable_diag", "callable_scalar"], +) +def test_bm_dim_resolved_outside_plate(diffusion_form): + """bm_dim is resolved correctly when not in a plate context.""" state_dim = 2 - bm_dim = 1 + expected_bm_dim = 1 if "full" in diffusion_form else state_dim + + diffusion_coefficient, diffusion_type, bm_dim = _make_diffusion_spec( + diffusion_form, + state_dim=state_dim, + ) state_evo = ContinuousTimeStateEvolution( drift=lambda x, u, t: -x, - diffusion_coefficient=lambda x, u, t: jnp.ones((state_dim, bm_dim)), + diffusion_coefficient=diffusion_coefficient, + diffusion_type=diffusion_type, + bm_dim=bm_dim, ) dynamics = DynamicalModel( initial_condition=dist.MultivariateNormal( @@ -25,62 +76,35 @@ def test_bm_dim_inferred_outside_plate(): x, 0.1 * jnp.eye(state_dim) ), ) - assert dynamics.state_evolution.bm_dim == bm_dim, ( - f"Expected bm_dim={bm_dim}, got {dynamics.state_evolution.bm_dim}" + assert dynamics.state_evolution.bm_dim == expected_bm_dim, ( + f"Expected bm_dim={expected_bm_dim}, got {dynamics.state_evolution.bm_dim}" ) -def test_bm_dim_inferred_inside_plate(): - """bm_dim should be inferred when model is constructed inside a plate context.""" +@pytest.mark.parametrize( + "diffusion_form", + ["full", "diag", "scalar", "callable_full", "callable_diag", "callable_scalar"], +) +def test_bm_dim_resolved_inside_plate(diffusion_form): + """bm_dim should be resolved when model is constructed inside a plate context.""" state_dim = 2 - bm_dim = 1 + expected_bm_dim = 1 if "full" in diffusion_form else state_dim M = 3 def model(): with numpyro.plate("trajectories", M): sigma = numpyro.sample("sigma", dist.HalfNormal(1.0)) - - state_evo = ContinuousTimeStateEvolution( - drift=lambda x, u, t: -x, - diffusion_coefficient=lambda x, u, t: ( - sigma[..., None, None] * jnp.ones((state_dim, bm_dim)) - ), - ) - dynamics = DynamicalModel( - initial_condition=dist.MultivariateNormal( - jnp.zeros(state_dim), jnp.eye(state_dim) - ), - state_evolution=state_evo, - observation_model=lambda x, u, t: dist.MultivariateNormal( - x, 0.1 * jnp.eye(state_dim) - ), + diffusion_coefficient, diffusion_type, bm_dim = _make_diffusion_spec( + diffusion_form, + state_dim=state_dim, + sigma=sigma, ) - # This is the bug: bm_dim stays None inside plate context - assert dynamics.state_evolution.bm_dim is not None, ( - "bm_dim should not be None after DynamicalModel construction in plate" - ) - assert dynamics.state_evolution.bm_dim == bm_dim, ( - f"Expected bm_dim={bm_dim}, got {dynamics.state_evolution.bm_dim}" - ) - - # Run the model with seed to trigger numpyro.sample - with numpyro.handlers.seed(rng_seed=0): - model() - - -def test_bm_dim_inferred_inside_plate_unbatched_diffusion(): - """bm_dim should be inferred even when diffusion doesn't use batched params.""" - state_dim = 2 - bm_dim = 1 - M = 3 - - def model(): - with numpyro.plate("trajectories", M): - _ = numpyro.sample("sigma", dist.HalfNormal(1.0)) state_evo = ContinuousTimeStateEvolution( drift=lambda x, u, t: -x, - diffusion_coefficient=lambda x, u, t: jnp.ones((state_dim, bm_dim)), + diffusion_coefficient=diffusion_coefficient, + diffusion_type=diffusion_type, + bm_dim=bm_dim, ) dynamics = DynamicalModel( initial_condition=dist.MultivariateNormal( @@ -94,8 +118,8 @@ def model(): assert dynamics.state_evolution.bm_dim is not None, ( "bm_dim should not be None after DynamicalModel construction in plate" ) - assert dynamics.state_evolution.bm_dim == bm_dim, ( - f"Expected bm_dim={bm_dim}, got {dynamics.state_evolution.bm_dim}" + assert dynamics.state_evolution.bm_dim == expected_bm_dim, ( + f"Expected bm_dim={expected_bm_dim}, got {dynamics.state_evolution.bm_dim}" ) with numpyro.handlers.seed(rng_seed=0): @@ -103,20 +127,17 @@ def model(): if __name__ == "__main__": - print("Test 1: bm_dim outside plate...") - test_bm_dim_inferred_outside_plate() - print(" PASSED") - - print("Test 2: bm_dim inside plate (unbatched diffusion)...") - try: - test_bm_dim_inferred_inside_plate_unbatched_diffusion() + for form in [ + "full", + "diag", + "scalar", + "callable_full", + "callable_diag", + "callable_scalar", + ]: + print(f"Testing {form} outside plate...") + test_bm_dim_resolved_outside_plate(form) print(" PASSED") - except AssertionError as e: - print(f" FAILED: {e}") - - print("Test 3: bm_dim inside plate (batched diffusion)...") - try: - test_bm_dim_inferred_inside_plate() + print(f"Testing {form} inside plate...") + test_bm_dim_resolved_inside_plate(form) print(" PASSED") - except AssertionError as e: - print(f" FAILED: {e}") diff --git a/tests/test_discretizers.py b/tests/test_discretizers.py index c73f5906..61881a4b 100644 --- a/tests/test_discretizers.py +++ b/tests/test_discretizers.py @@ -3,6 +3,7 @@ import jax.numpy as jnp import jax.random as jr import numpyro.distributions as dist +import pytest from numpyro.handlers import seed, trace from numpyro.infer import Predictive @@ -33,6 +34,52 @@ def _ctse_1d_zero_drift_unit_diffusion() -> ContinuousTimeStateEvolution: ) +def _ctse_2d_zero_drift(diffusion_form: str) -> ContinuousTimeStateEvolution: + if diffusion_form == "full": + return ContinuousTimeStateEvolution( + drift=lambda x, u, t: jnp.zeros_like(x), + diffusion_coefficient=jnp.eye(2), + diffusion_type="full", + bm_dim=2, + ) + if diffusion_form == "diag": + return ContinuousTimeStateEvolution( + drift=lambda x, u, t: jnp.zeros_like(x), + diffusion_coefficient=jnp.ones((2,)), + diffusion_type="diag", + bm_dim=2, + ) + if diffusion_form == "scalar": + return ContinuousTimeStateEvolution( + drift=lambda x, u, t: jnp.zeros_like(x), + diffusion_coefficient=jnp.array(1.0), + diffusion_type="scalar", + bm_dim=2, + ) + if diffusion_form == "callable_full": + return ContinuousTimeStateEvolution( + drift=lambda x, u, t: jnp.zeros_like(x), + diffusion_coefficient=lambda x, u, t: jnp.eye(2), + diffusion_type="full", + bm_dim=2, + ) + if diffusion_form == "callable_diag": + return ContinuousTimeStateEvolution( + drift=lambda x, u, t: jnp.zeros((2,)), + diffusion_coefficient=lambda x, u, t: jnp.ones((2,)), + diffusion_type="diag", + bm_dim=2, + ) + if diffusion_form == "callable_scalar": + return ContinuousTimeStateEvolution( + drift=lambda x, u, t: jnp.zeros_like(x), + diffusion_coefficient=lambda x, u, t: jnp.array(1.0), + diffusion_type="scalar", + bm_dim=2, + ) + raise ValueError(f"Unknown diffusion form: {diffusion_form}") + + def test_euler_maruyama_returns_gaussian_state_evolution_with_callable_cov(): cte = _ctse_1d_zero_drift_unit_diffusion() evo = euler_maruyama(cte) @@ -78,6 +125,21 @@ def test_euler_maruyama_loc_cov_single_pass_consistent_with_gaussian_state_evolu assert jnp.allclose(d_dict["cov"], d.covariance_matrix) +@pytest.mark.parametrize( + "diffusion_form", + ["full", "diag", "scalar", "callable_full", "callable_diag", "callable_scalar"], +) +def test_euler_maruyama_structured_diffusions_match_dense_covariance(diffusion_form): + cte = _ctse_2d_zero_drift(diffusion_form) + x = jnp.array([0.3, -0.1]) + t0 = jnp.array(1.0) + t1 = jnp.array(3.0) + out = euler_maruyama_loc_cov(cte, x, None, t0, t1) + expected_cov = (t1 - t0) * jnp.eye(2) + assert jnp.allclose(out["loc"], x) + assert jnp.allclose(out["cov"], expected_cov) + + def test_discretized_dirac_observations_preserve_state_dimension(): obs_times = jnp.arange(0.0, 0.05, 0.01) predictive = Predictive( diff --git a/tests/test_hierarchical_simulator_discretizer_smokes.py b/tests/test_hierarchical_simulator_discretizer_smokes.py index 9d50e8f5..89c6114c 100644 --- a/tests/test_hierarchical_simulator_discretizer_smokes.py +++ b/tests/test_hierarchical_simulator_discretizer_smokes.py @@ -102,7 +102,8 @@ def _plate_continuous_sde_model( alpha = numpyro.sample("alpha", dist.Uniform(0.1, 0.8)) A_base = jnp.array([[0.0, 0.1], [0.1, 0.8]]) A = jnp.repeat(A_base[None], M, axis=0).at[:, 0, 0].set(alpha) - L = 0.2 * jnp.array([[1.0], [0.5]]) + # Continuous cd-dynamax filters require full diffusion (bm_dim == state_dim). + L = 0.2 * jnp.diag(jnp.array([1.0, 0.5])) H = jnp.array([[1.0, 0.0]]) R = jnp.array([[0.25]]) dynamics = LTI_continuous(A=A, L=L, H=H, R=R) diff --git a/tests/test_models_core.py b/tests/test_models_core.py index 2f97300b..d58b9d2f 100644 --- a/tests/test_models_core.py +++ b/tests/test_models_core.py @@ -6,8 +6,18 @@ import pytest import dynestyx as dsx -from dynestyx.inference.integrations.cd_dynamax.utils import gaussian_to_nlgssm_params +from dynestyx.inference.integrations.cd_dynamax.utils import ( + _normalize_cd_dynamax_diffusion, + dsx_to_cd_dynamax, + gaussian_to_nlgssm_params, +) from dynestyx.models.core import ContinuousTimeStateEvolution, DynamicalModel +from dynestyx.models.diffusions import ( + DiffusionType, + diffusion_as_matrix, + diffusion_covariance, + evaluate_diffusion, +) from dynestyx.simulators import DiscreteTimeSimulator @@ -326,6 +336,203 @@ def observation_model(x, u, t): ) +def test_continuous_state_evolution_requires_explicit_bm_dim_for_diag_diffusion() -> ( + None +): + state_evolution = ContinuousTimeStateEvolution( + drift=lambda x, u, t: x, + diffusion_coefficient=jnp.ones((2,)), + ) + + with pytest.raises(ValueError, match="diag diffusion requires explicit bm_dim"): + DynamicalModel( + initial_condition=dist.MultivariateNormal( + loc=jnp.zeros(2), + covariance_matrix=jnp.eye(2), + ), + state_evolution=state_evolution, + observation_model=_observation_model_2d, + control_dim=0, + ) + + +def test_continuous_state_evolution_requires_explicit_bm_dim_for_scalar_diffusion() -> ( + None +): + state_evolution = ContinuousTimeStateEvolution( + drift=lambda x, u, t: x, + diffusion_coefficient=jnp.array(0.3), + ) + + with pytest.raises(ValueError, match="scalar diffusion requires explicit bm_dim"): + DynamicalModel( + initial_condition=dist.MultivariateNormal( + loc=jnp.zeros(2), + covariance_matrix=jnp.eye(2), + ), + state_evolution=state_evolution, + observation_model=_observation_model_2d, + control_dim=0, + ) + + +def test_continuous_state_evolution_rejects_invalid_shorthand_trailing_dim() -> None: + state_evolution = ContinuousTimeStateEvolution( + drift=lambda x, u, t: x, + diffusion_coefficient=jnp.ones((3,)), + ) + + with pytest.raises(ValueError, match="treated as scalar/diagonal shorthand"): + DynamicalModel( + initial_condition=dist.MultivariateNormal( + loc=jnp.zeros(2), + covariance_matrix=jnp.eye(2), + ), + state_evolution=state_evolution, + observation_model=_observation_model_2d, + control_dim=0, + ) + + +@pytest.mark.parametrize( + ( + "diffusion_coefficient", + "diffusion_type", + "bm_dim", + "expected_matrix", + "expected_cov", + ), + [ + ( + jnp.array(0.5), + "scalar", + 1, + 0.5 * jnp.ones((2, 1)), + 0.25 * jnp.ones((2, 2)), + ), + ( + jnp.array(0.5), + "scalar", + 2, + 0.5 * jnp.eye(2), + 0.25 * jnp.eye(2), + ), + ( + jnp.array([0.2, 0.4]), + "diag", + 1, + jnp.array([[0.2], [0.4]]), + jnp.array([[0.04, 0.08], [0.08, 0.16]]), + ), + ( + jnp.array([0.2, 0.4]), + "diag", + 2, + jnp.diag(jnp.array([0.2, 0.4])), + jnp.diag(jnp.array([0.04, 0.16])), + ), + ], +) +def test_diffusion_helpers_preserve_shorthand_semantics( + diffusion_coefficient, + diffusion_type, + bm_dim, + expected_matrix, + expected_cov, +) -> None: + evaluated = evaluate_diffusion( + diffusion_coefficient, + diffusion_type=diffusion_type, + bm_dim=bm_dim, + x=jnp.zeros(2), + u=None, + t=jnp.array(0.0), + state_dim=2, + ) + + assert jnp.allclose( + diffusion_as_matrix(evaluated, state_dim=2), + expected_matrix, + ) + assert jnp.allclose( + diffusion_covariance(evaluated, state_dim=2), + expected_cov, + ) + + +@pytest.mark.parametrize("callable_form", ["scalar", "diag", "full"]) +def test_diffusion_helpers_support_callable_shorthands(callable_form: str) -> None: + diffusion_type: DiffusionType + if callable_form == "scalar": + diffusion_coefficient = lambda x, u, t: 0.5 + 0.0 * t + diffusion_type = "scalar" + bm_dim = 2 + expected = 0.5 * jnp.eye(2) + elif callable_form == "diag": + diffusion_coefficient = lambda x, u, t: jnp.array([0.2, 0.4]) + 0.0 * t + diffusion_type = "diag" + bm_dim = 2 + expected = jnp.diag(jnp.array([0.2, 0.4])) + else: + diffusion_coefficient = lambda x, u, t: jnp.eye(2) * (1.0 + 0.0 * t) + diffusion_type = "full" + bm_dim = None + expected = jnp.eye(2) + + evaluated = evaluate_diffusion( + diffusion_coefficient, + diffusion_type=diffusion_type, + bm_dim=bm_dim, + x=jnp.zeros(2), + u=None, + t=jnp.array(1.0), + state_dim=2, + ) + + assert jnp.allclose(diffusion_as_matrix(evaluated, state_dim=2), expected) + + +def test_cd_dynamax_rejects_full_diffusion_with_bm_dim_not_equal_state_dim() -> None: + state_evolution = ContinuousTimeStateEvolution( + drift=lambda x, u, t: x, + diffusion_coefficient=jnp.ones((1, 2)), + diffusion_type="full", + bm_dim=2, + ) + with pytest.raises(ValueError, match="bm_dim == state_dim"): + _normalize_cd_dynamax_diffusion(state_evolution, state_dim=1)( + jnp.zeros(1), + None, + jnp.array(0.0), + ) + + +def test_continuous_cd_dynamax_rejects_rectangular_diffusion_early() -> None: + state_evolution = ContinuousTimeStateEvolution( + drift=lambda x, u, t: x, + diffusion_coefficient=jnp.ones((1, 2)), + diffusion_type="full", + bm_dim=2, + ) + dynamics = DynamicalModel( + initial_condition=dist.MultivariateNormal( + loc=jnp.zeros(1), + covariance_matrix=jnp.eye(1), + ), + state_evolution=state_evolution, + observation_model=dsx.LinearGaussianObservation( + H=jnp.array([[1.0]]), + R=jnp.array([[1.0]]), + ), + control_dim=0, + ) + + with pytest.raises( + ValueError, match="Continuous cd-dynamax filters require full diffusion" + ): + dsx_to_cd_dynamax(dynamics) + + def test_discrete_state_evolution_bm_dim_override_raises() -> None: def state_evolution(x, u, t_now, t_next): del u, t_now, t_next From 9652cbfa8563ac4b23fbef35a69533382ca61118 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Sun, 26 Apr 2026 22:59:18 -0400 Subject: [PATCH 02/28] adding back padding of diffusion-coefficient in CD-Dynamax integration --- .../integrations/cd_dynamax/utils.py | 25 ++++++++----------- ...erarchical_simulator_discretizer_smokes.py | 4 +-- tests/test_models_core.py | 4 +-- 3 files changed, 14 insertions(+), 19 deletions(-) diff --git a/dynestyx/inference/integrations/cd_dynamax/utils.py b/dynestyx/inference/integrations/cd_dynamax/utils.py index a3ccc2d3..5f349778 100644 --- a/dynestyx/inference/integrations/cd_dynamax/utils.py +++ b/dynestyx/inference/integrations/cd_dynamax/utils.py @@ -34,8 +34,9 @@ def _normalize_cd_dynamax_diffusion( """Return a diffusion coeff compatible with cd-dynamax's EnKF SDE solve. cd-dynamax's internal diffrax wrapper builds Brownian controls with shape - equal to `y0.shape` (state_dim), so this path only supports diffusion - matrices with `bm_dim == state_dim`. + equal to `y0.shape` (state_dim). For diffusion with `bm_dim < state_dim`, + pad trailing Brownian columns with zeros to match `(state_dim, state_dim)`. + Diffusion with `bm_dim > state_dim` is rejected. """ def _wrapped(x, u, t): @@ -49,18 +50,14 @@ def _wrapped(x, u, t): state_dim=state_dim, ) L = diffusion_as_matrix(diffusion, state_dim=state_dim) - if L.ndim == 1: - L = jnp.diag(L) - if L.ndim != 2: - raise ValueError( - "diffusion_coefficient must return a vector or matrix for cd-dynamax." - ) n_cols = L.shape[-1] - if n_cols != state_dim: + if n_cols > state_dim: raise ValueError( - "cd-dynamax continuous diffusion requires bm_dim == state_dim. " + "cd-dynamax continuous diffusion requires bm_dim <= state_dim. " f"Got state_dim={state_dim}, bm_dim={n_cols}." ) + if n_cols < state_dim: + L = jnp.pad(L, ((0, 0), (0, state_dim - n_cols))) return L return _wrapped @@ -85,12 +82,10 @@ def _validate_cd_dynamax_continuous_diffusion( state_dim=state_dim, ) bm_dim = diffusion_as_matrix(diffusion, state_dim=state_dim).shape[-1] - if bm_dim != state_dim: + if bm_dim > state_dim: raise ValueError( - "Continuous cd-dynamax filters require full diffusion with " - f"bm_dim == state_dim. Got state_dim={state_dim}, bm_dim={bm_dim}. " - "Use em_scan-based simulation for rectangular diffusion, or provide " - "a square full diffusion for this backend." + "Continuous cd-dynamax filters require bm_dim <= state_dim. " + f"Got state_dim={state_dim}, bm_dim={bm_dim}." ) diff --git a/tests/test_hierarchical_simulator_discretizer_smokes.py b/tests/test_hierarchical_simulator_discretizer_smokes.py index 89c6114c..4b20a9ba 100644 --- a/tests/test_hierarchical_simulator_discretizer_smokes.py +++ b/tests/test_hierarchical_simulator_discretizer_smokes.py @@ -102,8 +102,8 @@ def _plate_continuous_sde_model( alpha = numpyro.sample("alpha", dist.Uniform(0.1, 0.8)) A_base = jnp.array([[0.0, 0.1], [0.1, 0.8]]) A = jnp.repeat(A_base[None], M, axis=0).at[:, 0, 0].set(alpha) - # Continuous cd-dynamax filters require full diffusion (bm_dim == state_dim). - L = 0.2 * jnp.diag(jnp.array([1.0, 0.5])) + # Rectangular diffusion (bm_dim < state_dim) is padded in cd-dynamax integration. + L = 0.2 * jnp.array([[1.0], [0.5]]) H = jnp.array([[1.0, 0.0]]) R = jnp.array([[0.25]]) dynamics = LTI_continuous(A=A, L=L, H=H, R=R) diff --git a/tests/test_models_core.py b/tests/test_models_core.py index d58b9d2f..b66fa6a8 100644 --- a/tests/test_models_core.py +++ b/tests/test_models_core.py @@ -499,7 +499,7 @@ def test_cd_dynamax_rejects_full_diffusion_with_bm_dim_not_equal_state_dim() -> diffusion_type="full", bm_dim=2, ) - with pytest.raises(ValueError, match="bm_dim == state_dim"): + with pytest.raises(ValueError, match="bm_dim <= state_dim"): _normalize_cd_dynamax_diffusion(state_evolution, state_dim=1)( jnp.zeros(1), None, @@ -528,7 +528,7 @@ def test_continuous_cd_dynamax_rejects_rectangular_diffusion_early() -> None: ) with pytest.raises( - ValueError, match="Continuous cd-dynamax filters require full diffusion" + ValueError, match="Continuous cd-dynamax filters require bm_dim <= state_dim" ): dsx_to_cd_dynamax(dynamics) From 8c6726e2428a884f2df13fb3e65c7ba30cbbcabf Mon Sep 17 00:00:00 2001 From: Matt Levine Date: Sun, 26 Apr 2026 23:15:20 -0400 Subject: [PATCH 03/28] Update dynestyx/inference/integrations/cd_dynamax/utils.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- dynestyx/inference/integrations/cd_dynamax/utils.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/dynestyx/inference/integrations/cd_dynamax/utils.py b/dynestyx/inference/integrations/cd_dynamax/utils.py index 5f349778..a4182082 100644 --- a/dynestyx/inference/integrations/cd_dynamax/utils.py +++ b/dynestyx/inference/integrations/cd_dynamax/utils.py @@ -57,7 +57,8 @@ def _wrapped(x, u, t): f"Got state_dim={state_dim}, bm_dim={n_cols}." ) if n_cols < state_dim: - L = jnp.pad(L, ((0, 0), (0, state_dim - n_cols))) + pad_width = ((0, 0),) * (L.ndim - 1) + ((0, state_dim - n_cols),) + L = jnp.pad(L, pad_width) return L return _wrapped From 38df332a64356f7dd617e7d48bba0744fbd7cb51 Mon Sep 17 00:00:00 2001 From: Matt Levine Date: Sun, 26 Apr 2026 23:19:12 -0400 Subject: [PATCH 04/28] Update dynestyx/models/diffusions.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- dynestyx/models/diffusions.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/dynestyx/models/diffusions.py b/dynestyx/models/diffusions.py index 0793d5bc..9eeb377d 100644 --- a/dynestyx/models/diffusions.py +++ b/dynestyx/models/diffusions.py @@ -180,8 +180,10 @@ def apply_diffusion( scalar = value if value.ndim == 0 else jnp.squeeze(value, axis=-1) if diffusion.bm_dim == 1: - return jnp.broadcast_to(scalar * dw[0], (state_dim,)) - return scalar * dw + return jnp.broadcast_to( + (scalar * dw[0])[..., None], scalar.shape + (state_dim,) + ) + return scalar[..., None] * dw def _infer_diffusion_type( From aa50c386713fcb20620413f0fac5f0ec22718a47 Mon Sep 17 00:00:00 2001 From: "copilot-swe-agent[bot]" <198982749+Copilot@users.noreply.github.com> Date: Mon, 27 Apr 2026 03:22:54 +0000 Subject: [PATCH 05/28] docs: rename misleading test names to reflect bm_dim > state_dim constraint Agent-Logs-Url: https://github.com/BasisResearch/dynestyx/sessions/9646e756-8a5e-47b4-9c36-33cb58c2110e Co-authored-by: mattlevine22 <11492591+mattlevine22@users.noreply.github.com> --- tests/test_models_core.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/test_models_core.py b/tests/test_models_core.py index b66fa6a8..a6987a1d 100644 --- a/tests/test_models_core.py +++ b/tests/test_models_core.py @@ -492,7 +492,7 @@ def test_diffusion_helpers_support_callable_shorthands(callable_form: str) -> No assert jnp.allclose(diffusion_as_matrix(evaluated, state_dim=2), expected) -def test_cd_dynamax_rejects_full_diffusion_with_bm_dim_not_equal_state_dim() -> None: +def test_cd_dynamax_rejects_diffusion_with_bm_dim_exceeds_state_dim() -> None: state_evolution = ContinuousTimeStateEvolution( drift=lambda x, u, t: x, diffusion_coefficient=jnp.ones((1, 2)), @@ -507,7 +507,7 @@ def test_cd_dynamax_rejects_full_diffusion_with_bm_dim_not_equal_state_dim() -> ) -def test_continuous_cd_dynamax_rejects_rectangular_diffusion_early() -> None: +def test_continuous_cd_dynamax_rejects_diffusion_with_bm_dim_exceeds_state_dim_early() -> None: state_evolution = ContinuousTimeStateEvolution( drift=lambda x, u, t: x, diffusion_coefficient=jnp.ones((1, 2)), From ecd987e0e00d225ada9878e33ac0810d93e4ecf0 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Sun, 26 Apr 2026 23:25:07 -0400 Subject: [PATCH 06/28] plz lint --- tests/test_models_core.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/tests/test_models_core.py b/tests/test_models_core.py index a6987a1d..4ce5af18 100644 --- a/tests/test_models_core.py +++ b/tests/test_models_core.py @@ -507,7 +507,9 @@ def test_cd_dynamax_rejects_diffusion_with_bm_dim_exceeds_state_dim() -> None: ) -def test_continuous_cd_dynamax_rejects_diffusion_with_bm_dim_exceeds_state_dim_early() -> None: +def test_continuous_cd_dynamax_rejects_diffusion_with_bm_dim_exceeds_state_dim_early() -> ( + None +): state_evolution = ContinuousTimeStateEvolution( drift=lambda x, u, t: x, diffusion_coefficient=jnp.ones((1, 2)), From 375cf59f41b90558cc493f48a2b4e6fee0da5f46 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Tue, 28 Apr 2026 15:18:34 -0400 Subject: [PATCH 07/28] get diffusion info at init --- .../integrations/cd_dynamax/utils.py | 21 +++------ dynestyx/models/checkers.py | 46 +++++++++++++------ dynestyx/models/core.py | 40 ++++++++++------ dynestyx/models/diffusions.py | 17 ++++--- tests/test_models_core.py | 2 +- 5 files changed, 74 insertions(+), 52 deletions(-) diff --git a/dynestyx/inference/integrations/cd_dynamax/utils.py b/dynestyx/inference/integrations/cd_dynamax/utils.py index a4182082..6305f1a6 100644 --- a/dynestyx/inference/integrations/cd_dynamax/utils.py +++ b/dynestyx/inference/integrations/cd_dynamax/utils.py @@ -71,22 +71,15 @@ def _validate_cd_dynamax_continuous_diffusion( """Eagerly validate diffusion shape constraints for cd-dynamax continuous filters.""" if state_evolution.diffusion_coefficient is None: return - - probe_x = jnp.zeros(state_dim) - diffusion = evaluate_diffusion( - state_evolution.diffusion_coefficient, - diffusion_type=state_evolution.diffusion_type, - bm_dim=state_evolution.bm_dim, - x=probe_x, - u=None, - t=jnp.array(0.0), - state_dim=state_dim, - ) - bm_dim = diffusion_as_matrix(diffusion, state_dim=state_dim).shape[-1] - if bm_dim > state_dim: + if state_evolution.bm_dim is None: + raise ValueError( + "Continuous cd-dynamax filters require resolved bm_dim on " + "ContinuousTimeStateEvolution." + ) + if state_evolution.bm_dim > state_dim: raise ValueError( "Continuous cd-dynamax filters require bm_dim <= state_dim. " - f"Got state_dim={state_dim}, bm_dim={bm_dim}." + f"Got state_dim={state_dim}, bm_dim={state_evolution.bm_dim}." ) diff --git a/dynestyx/models/checkers.py b/dynestyx/models/checkers.py index d4881927..5124fe57 100644 --- a/dynestyx/models/checkers.py +++ b/dynestyx/models/checkers.py @@ -9,6 +9,7 @@ import numpyro.primitives from dynestyx.models.diffusions import ( + DiffusionType, evaluate_diffusion_value, resolve_diffusion_metadata, ) @@ -84,23 +85,30 @@ def _make_probe_state(initial_condition: Any, state_dim: int) -> jax.Array: return jnp.zeros((state_dim,)) -def _infer_bm_dim( +def _resolve_ctse_diffusion_metadata( state_evolution: Any, state_dim: int, x0: State, u0: Control | None, t0: Time, -) -> int | None: - """Infer bm_dim from diffusion coefficient output shape. +) -> tuple[DiffusionType, int] | None: + """Resolve diffusion metadata from one probe evaluation. Tolerates leading batch dimensions (e.g. from plate-batched parameters) by inspecting only the trailing two dimensions (..., state_dim, bm_dim). - Returns the inferred bm_dim, or None if there is no diffusion coefficient. + Returns the resolved diffusion type and bm_dim, or None if there is no + diffusion coefficient. """ if state_evolution.diffusion_coefficient is None: - if state_evolution.bm_dim is not None: - raise ValueError("bm_dim cannot be set when diffusion_coefficient is None.") + if ( + state_evolution.bm_dim is not None + or state_evolution.diffusion_type is not None + ): + raise ValueError( + "diffusion_type and bm_dim cannot be set when " + "diffusion_coefficient is None." + ) return None diffusion_shape = jax.eval_shape( @@ -108,25 +116,36 @@ def _infer_bm_dim( state_evolution.diffusion_coefficient, x0, u0, t0 ) ).shape - _, inferred_bm_dim = resolve_diffusion_metadata( + return resolve_diffusion_metadata( diffusion_shape, state_dim=state_dim, diffusion_type=state_evolution.diffusion_type, bm_dim=state_evolution.bm_dim, ) - return inferred_bm_dim -def _validate_continuous_state_evolution( +def _infer_bm_dim( state_evolution: Any, state_dim: int, x0: State, u0: Control | None, t0: Time, ) -> int | None: + """Compatibility wrapper returning only the resolved bm_dim.""" + resolved = _resolve_ctse_diffusion_metadata(state_evolution, state_dim, x0, u0, t0) + return None if resolved is None else resolved[1] + + +def _validate_continuous_state_evolution( + state_evolution: Any, + state_dim: int, + x0: State, + u0: Control | None, + t0: Time, +) -> tuple[DiffusionType, int] | None: """Validate the shape of the continuous-time state evolution w.r.t. state_dim and bm_dim. - Returns the inferred bm_dim (or None if no diffusion coefficient). + Returns the resolved diffusion metadata (or None if no diffusion coefficient). """ drift_shape = jax.eval_shape(lambda: state_evolution.total_drift(x0, u0, t0)).shape if drift_shape != (state_dim,): @@ -135,7 +154,7 @@ def _validate_continuous_state_evolution( f"Expected {(state_dim,)}, got {drift_shape}." ) - return _infer_bm_dim(state_evolution, state_dim, x0, u0, t0) + return _resolve_ctse_diffusion_metadata(state_evolution, state_dim, x0, u0, t0) def _validate_state_evolution_output_shape( @@ -150,16 +169,17 @@ def _validate_state_evolution_output_shape( ) -> int | None: """Validate the shape of the state evolution w.r.t. state_dim (and bm_dim for continuous-time models). - Returns the inferred bm_dim for continuous-time models, or None otherwise. + Returns the resolved bm_dim for continuous-time models, or None otherwise. """ if continuous_time: - return _validate_continuous_state_evolution( + resolved_diffusion = _validate_continuous_state_evolution( state_evolution=state_evolution, state_dim=state_dim, x0=x0, u0=u0, t0=t0, ) + return None if resolved_diffusion is None else resolved_diffusion[1] else: if getattr(state_evolution, "bm_dim", None) is not None: raise ValueError( diff --git a/dynestyx/models/core.py b/dynestyx/models/core.py index 6c8dc212..bc1ccd24 100644 --- a/dynestyx/models/core.py +++ b/dynestyx/models/core.py @@ -9,12 +9,12 @@ from numpyro.distributions import Distribution from dynestyx.models.checkers import ( - _infer_bm_dim, _infer_observation_dim_in_plate_context, _infer_vector_dim_from_distribution, _inside_numpyro_plate_context, _is_categorical_distribution, _make_probe_state, + _resolve_ctse_diffusion_metadata, _validate_categorical_state, _validate_continuous_time_flag, _validate_observation_dim, @@ -152,26 +152,20 @@ def __init__( self.control_dim = int(control_dim) self.categorical_state = bool(inferred_categorical_state) - # Infer bm_dim for continuous-time models + # Resolve diffusion metadata for continuous-time models if inferred_continuous_time and isinstance( state_evolution, ContinuousTimeStateEvolution ): x0 = jnp.zeros((inferred_state_dim,)) u0 = None if control_dim == 0 else jnp.zeros((control_dim,)) dummy_t0 = jnp.array(0.0) if self.t0 is None else self.t0 - inferred_bm_dim = _infer_bm_dim( + resolved_diffusion = _resolve_ctse_diffusion_metadata( state_evolution, inferred_state_dim, x0, u0, dummy_t0 ) - if inferred_bm_dim is not None: - if ( - state_evolution.bm_dim is not None - and inferred_bm_dim != state_evolution.bm_dim - ): - raise ValueError( - "bm_dim does not match inferred diffusion_coefficient output shape. " - f"Got bm_dim={state_evolution.bm_dim}, inferred={inferred_bm_dim}." - ) - object.__setattr__(state_evolution, "bm_dim", inferred_bm_dim) + if resolved_diffusion is not None: + resolved_type, resolved_bm_dim = resolved_diffusion + object.__setattr__(state_evolution, "diffusion_type", resolved_type) + object.__setattr__(state_evolution, "bm_dim", resolved_bm_dim) return x0 = _make_probe_state( @@ -188,8 +182,24 @@ def __init__( t0=dummy_t0, continuous_time=self.continuous_time, ) - if self.continuous_time and inferred_bm_dim != state_evolution.bm_dim: - object.__setattr__(state_evolution, "bm_dim", inferred_bm_dim) + if self.continuous_time and isinstance( + state_evolution, ContinuousTimeStateEvolution + ): + resolved_diffusion = _resolve_ctse_diffusion_metadata( + state_evolution, + inferred_state_dim, + x0, + u0, + dummy_t0, + ) + if resolved_diffusion is not None: + resolved_type, resolved_bm_dim = resolved_diffusion + if state_evolution.diffusion_type != resolved_type: + object.__setattr__(state_evolution, "diffusion_type", resolved_type) + if inferred_bm_dim != resolved_bm_dim: + inferred_bm_dim = resolved_bm_dim + if state_evolution.bm_dim != resolved_bm_dim: + object.__setattr__(state_evolution, "bm_dim", resolved_bm_dim) obs_dist = observation_model(x0, u0, dummy_t0) inferred_observation_dim = _infer_vector_dim_from_distribution( diff --git a/dynestyx/models/diffusions.py b/dynestyx/models/diffusions.py index 9eeb377d..c28bdd03 100644 --- a/dynestyx/models/diffusions.py +++ b/dynestyx/models/diffusions.py @@ -101,18 +101,17 @@ def evaluate_diffusion( t: Time, state_dim: int, ) -> EvaluatedDiffusion: - """Evaluate a diffusion spec and resolve its semantics.""" + """Evaluate a diffusion spec using already-resolved metadata.""" value = evaluate_diffusion_value(diffusion_coefficient, x, u, t) - resolved_type, resolved_bm_dim = resolve_diffusion_metadata( - value.shape, - state_dim=state_dim, - diffusion_type=diffusion_type, - bm_dim=bm_dim, - ) + if diffusion_type is None or bm_dim is None: + raise ValueError( + "Diffusion metadata must be resolved at model initialization before " + "runtime evaluation." + ) return EvaluatedDiffusion( - diffusion_type=resolved_type, + diffusion_type=diffusion_type, value=value, - bm_dim=resolved_bm_dim, + bm_dim=int(bm_dim), ) diff --git a/tests/test_models_core.py b/tests/test_models_core.py index 4ce5af18..eb0904a6 100644 --- a/tests/test_models_core.py +++ b/tests/test_models_core.py @@ -476,7 +476,7 @@ def test_diffusion_helpers_support_callable_shorthands(callable_form: str) -> No else: diffusion_coefficient = lambda x, u, t: jnp.eye(2) * (1.0 + 0.0 * t) diffusion_type = "full" - bm_dim = None + bm_dim = 2 expected = jnp.eye(2) evaluated = evaluate_diffusion( From 0fa5667f141e30315d41847ba90cdd4ad75e525b Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Tue, 28 Apr 2026 15:57:20 -0400 Subject: [PATCH 08/28] give discretizer fallback if dynamicalModel init hadnt been run (support direct API by checking if bm_dim or diffusion_type are None) --- dynestyx/discretizers.py | 66 +++++++++++++++++++++++++++++----------- dynestyx/solvers/sde.py | 29 ++++++++++++++++++ 2 files changed, 78 insertions(+), 17 deletions(-) diff --git a/dynestyx/discretizers.py b/dynestyx/discretizers.py index cb9a6d39..c14d1438 100644 --- a/dynestyx/discretizers.py +++ b/dynestyx/discretizers.py @@ -9,26 +9,47 @@ DynamicalModel, GaussianStateEvolution, ) -from dynestyx.models.checkers import _infer_bm_dim +from dynestyx.models.checkers import _resolve_ctse_diffusion_metadata from dynestyx.solvers import euler_maruyama_loc_cov from dynestyx.types import FunctionOfTime +def _ensure_ctse_diffusion_metadata( + cte: ContinuousTimeStateEvolution, + *, + state_dim: int, + control_dim: int = 0, + t0=None, +) -> ContinuousTimeStateEvolution: + """Resolve and set diffusion metadata on a CTSE when missing.""" + if cte.diffusion_coefficient is None: + return cte + if cte.diffusion_type is not None and cte.bm_dim is not None: + return cte + + x0 = jnp.zeros((state_dim,)) + u0 = None if control_dim == 0 else jnp.zeros((control_dim,)) + probe_t0 = jnp.array(0.0) if t0 is None else jnp.asarray(t0) + resolved = _resolve_ctse_diffusion_metadata(cte, state_dim, x0, u0, probe_t0) + if resolved is not None: + resolved_type, resolved_bm_dim = resolved + object.__setattr__(cte, "diffusion_type", resolved_type) + object.__setattr__(cte, "bm_dim", resolved_bm_dim) + return cte + + def _ensure_ctse_bm_dim(dynamics: DynamicalModel) -> DynamicalModel: - """Infer and set bm_dim when CT dynamics are built under active plates.""" + """Resolve diffusion metadata when CT dynamics are built under active plates.""" if not isinstance(dynamics.state_evolution, ContinuousTimeStateEvolution): return dynamics cte = dynamics.state_evolution - if cte.diffusion_coefficient is None or cte.bm_dim is not None: - return dynamics - - x0 = jnp.zeros((dynamics.state_dim,)) - u0 = None if dynamics.control_dim == 0 else jnp.zeros((dynamics.control_dim,)) - t0 = jnp.array(0.0) if dynamics.t0 is None else jnp.asarray(dynamics.t0) - inferred_bm_dim = _infer_bm_dim(cte, dynamics.state_dim, x0, u0, t0) - if inferred_bm_dim is not None: - object.__setattr__(cte, "bm_dim", inferred_bm_dim) + _ensure_ctse_diffusion_metadata( + cte, + state_dim=dynamics.state_dim, + control_dim=dynamics.control_dim, + t0=dynamics.t0, + ) return dynamics @@ -46,13 +67,24 @@ def __init__( # Accept these for reconstruction paths, but derive both from `cte`. del F, cov self.cte = cte + + def _loc(x, u, t_now, t_next): + _ensure_ctse_diffusion_metadata( + cte, + state_dim=jnp.asarray(x).shape[-1], + ) + return euler_maruyama_loc_cov(cte, x, u, t_now, t_next)["loc"] + + def _cov(x, u, t_now, t_next): + _ensure_ctse_diffusion_metadata( + cte, + state_dim=jnp.asarray(x).shape[-1], + ) + return euler_maruyama_loc_cov(cte, x, u, t_now, t_next)["cov"] + super().__init__( - F=lambda x, u, t_now, t_next: euler_maruyama_loc_cov( - cte, x, u, t_now, t_next - )["loc"], - cov=lambda x, u, t_now, t_next: euler_maruyama_loc_cov( - cte, x, u, t_now, t_next - )["cov"], + F=_loc, + cov=_cov, ) def __call__(self, x, u, t_now, t_next): diff --git a/dynestyx/solvers/sde.py b/dynestyx/solvers/sde.py index f9dc101f..75f28838 100644 --- a/dynestyx/solvers/sde.py +++ b/dynestyx/solvers/sde.py @@ -12,6 +12,7 @@ from jax import Array, lax, vmap from dynestyx.models import ContinuousTimeStateEvolution, DynamicalModel +from dynestyx.models.checkers import _resolve_ctse_diffusion_metadata from dynestyx.models.diffusions import ( EvaluatedDiffusion, apply_diffusion, @@ -66,6 +67,28 @@ def _require_diffusion_spec( return diffusion_spec +def _ensure_resolved_diffusion_metadata( + state_evolution: ContinuousTimeStateEvolution, + *, + state_dim: int, + u: Array | None, + t: Array, +) -> None: + """Resolve diffusion metadata for standalone low-level SDE helpers.""" + if state_evolution.diffusion_coefficient is None or ( + state_evolution.diffusion_type is not None + and state_evolution.bm_dim is not None + ): + return + + x0 = jnp.zeros((state_dim,)) + resolved = _resolve_ctse_diffusion_metadata(state_evolution, state_dim, x0, u, t) + if resolved is not None: + resolved_type, resolved_bm_dim = resolved + object.__setattr__(state_evolution, "diffusion_type", resolved_type) + object.__setattr__(state_evolution, "bm_dim", resolved_bm_dim) + + def _em_local_terms( state_evolution: ContinuousTimeStateEvolution, x: Array, @@ -83,6 +106,12 @@ def _em_local_terms( Returns: Tuple `(drift, diffusion)` at `(x, u, t_now)`. """ + _ensure_resolved_diffusion_metadata( + state_evolution, + state_dim=x.shape[-1], + u=u, + t=t_now, + ) drift = state_evolution.total_drift(x=x, u=u, t=t_now) diffusion_spec = _require_diffusion_spec(state_evolution) diffusion = evaluate_diffusion( From bf1f4564cd3cabf9c836d2a0d3b9c8ac2b6943f8 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Sun, 10 May 2026 09:28:28 -0400 Subject: [PATCH 09/28] new Diffusion class with subtypes. --- .../developer/models/core_models.md | 9 + .../core/continuous_time_state_evolution.md | 11 +- .../public/models/core/diffusion.md | 178 ++ .../public/models/core/dynamical_model.md | 4 +- .../public/models/core_models.md | 1 - .../public/models/specialized/affine_drift.md | 4 +- .../public/simulators/sde_simulator.md | 9 +- docs/deep_dives/fhn_sparse_id.ipynb | 1514 ++++++++--------- docs/deep_dives/gp_drift.ipynb | 2 +- .../l63_speedup_dirac_vs_enkf.ipynb | 768 ++++----- docs/faq.md | 7 +- docs/logo/make_logo.py | 18 +- docs/math_intro.md | 4 +- docs/quick_example.ipynb | 524 +++--- .../02_dynestyx_discrete_intro.ipynb | 1207 +++++++------ .../gentle_intro/06_continuous_time.ipynb | 990 +++++------ .../08_hierarchical_inference.ipynb | 4 +- docs/tutorials/quickstart.ipynb | 744 ++++---- .../sde_non_gaussian_observations.ipynb | 868 +++++----- dynestyx/__init__.py | 12 + dynestyx/discretizers.py | 70 +- dynestyx/inference/filters.py | 9 +- .../integrations/cd_dynamax/continuous.py | 16 + .../integrations/cd_dynamax/discrete.py | 14 + .../integrations/cd_dynamax/utils.py | 116 +- dynestyx/models/__init__.py | 16 +- dynestyx/models/checkers.py | 140 +- dynestyx/models/core.py | 203 ++- dynestyx/models/diffusions.py | 459 +++-- dynestyx/models/lti_dynamics.py | 4 +- dynestyx/simulators.py | 37 +- dynestyx/solvers/sde.py | 130 +- dynestyx/utils.py | 25 +- mkdocs.yml | 1 + tests/models.py | 9 +- tests/test_bm_dim_plate.py | 53 +- tests/test_discretizers.py | 80 +- tests/test_filters.py | 4 +- ...erarchical_simulator_discretizer_smokes.py | 9 +- ...hierarchical_simulator_inference_smokes.py | 4 +- tests/test_models_core.py | 190 +-- .../test_science/test_discreteTime_generic.py | 11 +- .../test_discreteTime_generic_auto.py | 11 +- .../test_discrete_time_l63_mcmc.py | 11 +- .../test_discrete_time_l63_svi_pf.py | 11 +- tests/test_science/test_hmm.py | 6 +- tests/test_science/test_l63_ODE_mcmc.py | 11 +- tests/test_science/test_l63_SDE_mcmc.py | 11 +- tests/test_science/test_l63_mcmc_dpf.py | 11 +- .../test_lti_continuous_simplified.py | 9 +- .../test_lti_discrete_simplified.py | 15 +- tests/test_science/test_lti_gaussian.py | 15 +- tests/test_science/test_lti_gaussian_dpf.py | 15 +- ..._discretized_hierarchical_multitraj_ekf.py | 4 +- ...st_ode_hierarchical_simulator_inference.py | 1 - 55 files changed, 4410 insertions(+), 4199 deletions(-) create mode 100644 docs/api_reference/public/models/core/diffusion.md diff --git a/docs/api_reference/developer/models/core_models.md b/docs/api_reference/developer/models/core_models.md index fdae00ea..1f86d15e 100644 --- a/docs/api_reference/developer/models/core_models.md +++ b/docs/api_reference/developer/models/core_models.md @@ -1,5 +1,14 @@ # Core Models +This page includes the developer-facing refined continuous-time state-evolution +classes: + +- `DeterministicContinuousTimeStateEvolution` +- `StochasticContinuousTimeStateEvolution` + +Most users should continue to construct `ContinuousTimeStateEvolution` directly and let +`DynamicalModel` canonicalize it internally. + ::: dynestyx.models.core options: filters: [] diff --git a/docs/api_reference/public/models/core/continuous_time_state_evolution.md b/docs/api_reference/public/models/core/continuous_time_state_evolution.md index bff371c8..4e25266a 100644 --- a/docs/api_reference/public/models/core/continuous_time_state_evolution.md +++ b/docs/api_reference/public/models/core/continuous_time_state_evolution.md @@ -1,7 +1,16 @@ # ContinuousTimeStateEvolution +`ContinuousTimeStateEvolution` is the public entry point for defining continuous-time +state evolution. Most users should instantiate this class directly and pass an optional +`diffusion=` built from [`FullDiffusion`](./diffusion.md), +[`DiagonalDiffusion`](./diffusion.md), or [`ScalarDiffusion`](./diffusion.md). + +Internally, `DynamicalModel` canonicalizes continuous-time dynamics to refined +deterministic and stochastic subclasses. Those specialized classes are intended for +developer-facing integrations and are documented in the developer API rather than the +public tutorials. + ::: dynestyx.models.core.ContinuousTimeStateEvolution options: show_root_heading: false show_root_toc_entry: false - diff --git a/docs/api_reference/public/models/core/diffusion.md b/docs/api_reference/public/models/core/diffusion.md new file mode 100644 index 00000000..669925be --- /dev/null +++ b/docs/api_reference/public/models/core/diffusion.md @@ -0,0 +1,178 @@ +# Diffusion + +`Diffusion` objects define the stochastic term in a continuous-time state evolution + +\[ +dx_t = f(x_t, u_t, t)\,dt + L(x_t, u_t, t)\,dW_t, +\] + +where: + +- \(x_t \in \mathbb{R}^{d_x}\) is the latent state, +- \(u_t\) is an optional control, +- \(W_t \in \mathbb{R}^{d_w}\) is Brownian motion, +- `bm_dim = d_w`, +- and \(L(x_t, u_t, t)\) is the diffusion coefficient. + +Dynestyx exposes three structured diffusion classes: + +- `FullDiffusion`: general matrix-valued diffusion \(L \in \mathbb{R}^{d_x \times d_w}\) +- `DiagonalDiffusion`: vector-valued diffusion \(v \in \mathbb{R}^{d_x}\) +- `ScalarDiffusion`: scalar-valued diffusion \(\sigma \in \mathbb{R}\) + +In practice, many models use a constant diffusion coefficient. In those cases, +pass the matrix/vector/scalar value directly. Reserve callable diffusion +coefficients for cases where the coefficient genuinely depends on state, +control, or time. + +## Mathematical Interpretation + +### `FullDiffusion` + +`FullDiffusion` represents an arbitrary matrix-valued diffusion coefficient: + +\[ +L(x_t, u_t, t) \in \mathbb{R}^{d_x \times d_w}. +\] + +The SDE is + +\[ +dx_t = f(x_t, u_t, t)\,dt + L(x_t, u_t, t)\,dW_t. +\] + +This is the most general case. The process noise covariance is + +\[ +L(x_t, u_t, t)\,L(x_t, u_t, t)^\top, +\] + +which may be dense. + +### `DiagonalDiffusion` + +`DiagonalDiffusion` represents a vector-valued coefficient + +\[ +v(x_t, u_t, t) \in \mathbb{R}^{d_x}. +\] + +Its interpretation depends on `bm_dim`. + +If `bm_dim = d_x`, the vector is interpreted as a diagonal matrix: + +\[ +L(x_t, u_t, t) = \mathrm{diag}(v(x_t, u_t, t)), +\] + +so each state coordinate receives its own independent Brownian driver and + +\[ +L L^\top = \mathrm{diag}(v_1^2, \ldots, v_{d_x}^2). +\] + +If `bm_dim = 1`, the same vector is interpreted as a column loading vector: + +\[ +L(x_t, u_t, t) = v(x_t, u_t, t) \in \mathbb{R}^{d_x \times 1}, +\] + +so all state coordinates share a single Brownian path. In that case, + +\[ +L L^\top = v v^\top, +\] + +which is rank 1. + +### `ScalarDiffusion` + +`ScalarDiffusion` represents a scalar-valued coefficient + +\[ +\sigma(x_t, u_t, t) \in \mathbb{R}. +\] + +Its interpretation also depends on `bm_dim`. + +If `bm_dim = d_x`, it is interpreted as isotropic independent noise: + +\[ +L(x_t, u_t, t) = \sigma(x_t, u_t, t)\,I_{d_x}, +\] + +so the process noise covariance is + +\[ +L L^\top = \sigma^2 I_{d_x}. +\] + +If `bm_dim = 1`, it is interpreted as a shared scalar driver applied equally to +every state coordinate: + +\[ +L(x_t, u_t, t) = \sigma(x_t, u_t, t)\,\mathbf{1}_{d_x}, +\] + +viewed as a column vector in \(\mathbb{R}^{d_x \times 1}\). The resulting +covariance is + +\[ +L L^\top = \sigma^2 \mathbf{1}_{d_x}\mathbf{1}_{d_x}^\top, +\] + +which is again rank 1. + +## Typical Usage + +```python +import jax.numpy as jnp +from dynestyx import ContinuousTimeStateEvolution, FullDiffusion + +state_evolution = ContinuousTimeStateEvolution( + drift=lambda x, u, t: -x, + diffusion=FullDiffusion(jnp.eye(2)), +) +``` + +```python +from dynestyx import DiagonalDiffusion + +state_evolution = ContinuousTimeStateEvolution( + drift=lambda x, u, t: -x, + diffusion=DiagonalDiffusion(jnp.array([0.1, 0.2]), bm_dim=2), +) +``` + +```python +from dynestyx import ScalarDiffusion + +state_evolution = ContinuousTimeStateEvolution( + drift=lambda x, u, t: -x, + diffusion=ScalarDiffusion(0.1, bm_dim=2), +) +``` + +## API + +::: dynestyx.models.diffusions.Diffusion + options: + show_root_heading: false + +### `FullDiffusion` + +::: dynestyx.models.diffusions.FullDiffusion + options: + show_root_heading: false + +### `DiagonalDiffusion` + +::: dynestyx.models.diffusions.DiagonalDiffusion + options: + show_root_heading: false + +### `ScalarDiffusion` + +::: dynestyx.models.diffusions.ScalarDiffusion + options: + show_root_heading: false diff --git a/docs/api_reference/public/models/core/dynamical_model.md b/docs/api_reference/public/models/core/dynamical_model.md index e437aba2..4c4acc42 100644 --- a/docs/api_reference/public/models/core/dynamical_model.md +++ b/docs/api_reference/public/models/core/dynamical_model.md @@ -33,6 +33,7 @@ from dynestyx import ( DynamicalModel, ContinuousTimeStateEvolution, + FullDiffusion, LinearGaussianObservation, ) @@ -47,7 +48,7 @@ ), state_evolution=ContinuousTimeStateEvolution( drift=lambda x, u, t: -x + u, - diffusion_coefficient=lambda x, u, t: jnp.eye(state_dim, bm_dim), + diffusion=FullDiffusion(jnp.eye(state_dim, bm_dim)), ), observation_model=LinearGaussianObservation( H=jnp.eye(observation_dim, state_dim), @@ -55,4 +56,3 @@ ), ) ``` - diff --git a/docs/api_reference/public/models/core_models.md b/docs/api_reference/public/models/core_models.md index 673d35b1..9abf8bdf 100644 --- a/docs/api_reference/public/models/core_models.md +++ b/docs/api_reference/public/models/core_models.md @@ -9,4 +9,3 @@ - ObservationModel - Drift - Potential - diff --git a/docs/api_reference/public/models/specialized/affine_drift.md b/docs/api_reference/public/models/specialized/affine_drift.md index 993c17ee..b9865e32 100644 --- a/docs/api_reference/public/models/specialized/affine_drift.md +++ b/docs/api_reference/public/models/specialized/affine_drift.md @@ -26,7 +26,7 @@ ??? example "Ornstein–Uhlenbeck (OU) process" ```python import jax.numpy as jnp - from dynestyx import AffineDrift, ContinuousTimeStateEvolution + from dynestyx import AffineDrift, ContinuousTimeStateEvolution, FullDiffusion # OU SDE: dX_t = -theta (X_t - mu) dt + sigma dW_t theta = 0.7 @@ -38,6 +38,6 @@ ou_sde = ContinuousTimeStateEvolution( drift=drift, - diffusion_coefficient=lambda x, u, t: jnp.array([[sigma]]), + diffusion=FullDiffusion(jnp.array([[sigma]])), ) ``` diff --git a/docs/api_reference/public/simulators/sde_simulator.md b/docs/api_reference/public/simulators/sde_simulator.md index 70b8e64d..8cd1f309 100644 --- a/docs/api_reference/public/simulators/sde_simulator.md +++ b/docs/api_reference/public/simulators/sde_simulator.md @@ -14,7 +14,12 @@ import jax.random as jr import numpyro import numpyro.distributions as dist - from dynestyx import ContinuousTimeStateEvolution, DynamicalModel, SDESimulator + from dynestyx import ( + ContinuousTimeStateEvolution, + DynamicalModel, + FullDiffusion, + SDESimulator, + ) from numpyro.infer import Predictive state_dim = 1 @@ -33,7 +38,7 @@ ), state_evolution=ContinuousTimeStateEvolution( drift=lambda x, u, t: -theta * x, - diffusion_coefficient=lambda x, u, t: sigma_x * jnp.eye(state_dim, bm_dim), + diffusion=FullDiffusion(sigma_x * jnp.eye(state_dim, bm_dim)), ), observation_model=lambda x, u, t: dist.MultivariateNormal( x, diff --git a/docs/deep_dives/fhn_sparse_id.ipynb b/docs/deep_dives/fhn_sparse_id.ipynb index 22a6b036..ad314a9f 100644 --- a/docs/deep_dives/fhn_sparse_id.ipynb +++ b/docs/deep_dives/fhn_sparse_id.ipynb @@ -1,784 +1,784 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Sparse identification of FitzHugh–Nagumo dynamics\n", - "\n", - "This **deep-dive tutorial** walks through sparse drift inference for a FitzHugh–Nagumo (FHN) SDE.\n", - "\n", - "**Goal.** Given noisy observations of the state, recover the sparse structure of the drift $f(x)$ by expressing it as with the elements of a polynomial library $\\Theta\\,\\phi(x)$ and placing a **Laplace prior** on the coefficient matrix $\\Theta$. This is a Bayesian SINDy-style approach. We fit via **SVI with AutoDelta** (MAP estimation) and then compare the recovered coefficients and filtered trajectories against ground truth.\n", - "\n", - "**What is known.**\n", - "- Initial state distribution: $x_0 \\sim \\mathcal{N}(0, I)$.\n", - "- Observation operator $H$ (identity here, observing both states).\n", - "- Polynomial library $\\phi(x)$ (monomials up to degree 3).\n", - "\n", - "**What is inferred.**\n", - "- Drift coefficient matrix $\\Theta \\in \\mathbb{R}^{2 \\times 10}$ via MAP (Laplace prior promotes sparsity).\n", - "- Diffusion coefficient $\\sigma_x > 0$ (HalfNormal prior).\n", - "- Observation noise standard deviation $\\sigma_y > 0$ (HalfNormal prior)." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## FitzHugh–Nagumo Model\n", - "\n", - "### State SDE\n", - "\n", - "The state $x_t = (v_t, w_t)^\\top \\in \\mathbb{R}^2$ evolves as an Itô SDE:\n", - "\n", - "$$\n", - "dx_t = f(x_t)\\,dt + \\sigma_x\\,dW_t,\n", - "$$\n", - "\n", - "where $W_t$ is a standard 2-dimensional Brownian motion and the true drift is\n", - "\n", - "$$\n", - "f(x) = \\begin{pmatrix} v - \\tfrac{1}{3}v^3 - w + I \\\\ a\\,(v + b - c\\,w) \\end{pmatrix}.\n", - "$$\n", - "\n", - "Parameters are fixed at $a = 0.08$, $b = 0.7$, $c = 0.8$, $I = 0.5$. The true noise values used to generate data are $\\sigma_x = 0.01$ and $\\sigma_y = 0.1$, but **both are treated as unknown during inference**.\n", - "\n", - "### Observation process\n", - "\n", - "Observations are collected at discrete times $t_1 < t_2 < \\cdots < t_n$:\n", - "\n", - "$$\n", - "y_k = H\\,x_{t_k} + \\varepsilon_k, \\qquad \\varepsilon_k \\sim \\mathcal{N}(0,\\,\\sigma_y^2 I),\n", - "$$\n", - "\n", - "where $H = I_2$ (both states observed).\n", - "\n", - "### Initial condition\n", - "\n", - "$$\n", - "x_0 \\sim \\mathcal{N}(0, I_2).\n", - "$$\n", - "\n", - "### Inferred quantities\n", - "\n", - "We do **not** know $f$, $\\sigma_x$, or $\\sigma_y$. We parameterise the drift as\n", - "\n", - "$$\n", - "f(x) \\approx \\Theta\\,\\phi(x),\n", - "$$\n", - "\n", - "where $\\phi(x) \\in \\mathbb{R}^{10}$ is a polynomial library (all monomials in $v, w$ up to degree 3). The full set of inferred quantities and their priors is:\n", - "\n", - "$$\n", - "\\Theta \\sim \\mathrm{Laplace}(0,\\; 0.1) \\quad \\text{(promotes sparsity)},\n", - "$$\n", - "$$\n", - "\\sigma_x \\sim \\mathrm{HalfNormal}(0.1), \\qquad \\sigma_y \\sim \\mathrm{HalfNormal}(0.5).\n", - "$$\n", - "\n", - "All three are inferred jointly via MAP (SVI with AutoDelta)." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import jax.numpy as jnp\n", - "import jax.random as jr\n", - "import numpyro\n", - "import numpyro.distributions as dist\n", - "from numpyro.infer import SVI, Trace_ELBO, Predictive\n", - "from numpyro.infer.autoguide import AutoDelta\n", - "\n", - "import dynestyx as dsx\n", - "from dynestyx import (\n", - " ContinuousTimeStateEvolution,\n", - " DynamicalModel,\n", - " Filter,\n", - " LinearGaussianObservation,\n", - " SDESimulator,\n", - ")\n", - "\n", - "import matplotlib.pyplot as plt\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## True system\n", - "\n", - "Define the true FitzHugh–Nagumo drift. We will later build the full DynamicalModel by piping in this drift and spreading shared arguments from a dict." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "# FitzHugh–Nagumo parameters\n", - "_a, _b, _c, _I = 0.08, 0.7, 0.8, 0.5\n", - "\n", - "def fitzhugh_nagumo_drift(x):\n", - " v, w = x[0], x[1]\n", - " dv = v - (1/3) * v**3 - w + _I\n", - " dw = _a * (v + _b - _c * w)\n", - " return jnp.array([dv, dw])\n", - "\n", - "state_dim = 2" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Model configuration\n", - "\n", - "Constants used for data generation and inference setup.\n", - "\n", - "| Symbol | Role | Value | Status |\n", - "|---|---|---|---|\n", - "| $\\sigma_x^{\\mathrm{true}}$ | true diffusion coefficient (data generation only) | `0.01` | **inferred** |\n", - "| $\\sigma_y^{\\mathrm{true}}$ | true observation noise std (data generation only) | `0.1` | **inferred** |\n", - "| $x_0 \\sim \\mathcal{N}(0, I_2)$ | initial state prior | covariance = `I` | known |\n", - "| $\\Delta t$ | observation spacing | `0.1` | known |\n", - "| $T$ | total time span | `[0, 50)` | known |" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "# True values used ONLY for data generation — both are inferred during model discovery\n", - "sigma_x_true = 0.01 # true diffusion coefficient\n", - "sigma_y_true = 0.1 # true observation noise std\n", - "\n", - "# observation times t_1, ..., t_n (spacing Delta_t = 0.1, span [0, 50))\n", - "obs_times = jnp.arange(0.0, 50.0, 0.1)\n", - "\n", - "observation_dim = 2 # observation_dim=1 also works (observe only v)\n", - "\n", - "key = jr.PRNGKey(0)\n", - "key, k_data, k_svi, k_nuts, k_filter = jr.split(key, 5)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## DynamicalModel construction helpers\n", - "\n", - "The Dynestyx `DynamicalModel` needs three pieces:\n", - "\n", - "- **Initial condition** — $x_0 \\sim \\mathcal{N}(0, I_2)$. Fixed; collected in `initial_condition_kwargs`.\n", - "- **Observation model** — $y_k = H\\,x_{t_k} + \\varepsilon_k$ with $\\varepsilon_k \\sim \\mathcal{N}(0, \\sigma_y^2 I_2)$. Constructed inside each model function because $\\sigma_y$ is inferred.\n", - "- **State evolution** — wraps the drift $f$ and the diffusion $\\sigma_x I_2$. Constructed inside each model function because $\\sigma_x$ is inferred.\n", - "\n", - "`make_state_evolution(drift_fn, diffusion_coeff)` is a helper that accepts whichever diffusion coefficient (true or inferred) is provided." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "# H in y_k = H x_{t_k} + eps_k (identity: observe all states)\n", - "H_obs = jnp.eye(observation_dim, state_dim)\n", - "\n", - "# Only the initial condition is shared and fixed; observation model and state\n", - "# evolution are constructed inside each model function because sigma_x and sigma_y\n", - "# are inferred.\n", - "initial_condition_kwargs = dict(\n", - " # x_0 ~ N(0, I_2)\n", - " initial_condition=dist.MultivariateNormal(\n", - " loc=jnp.zeros(state_dim),\n", - " covariance_matrix=jnp.eye(state_dim),\n", - " ),\n", - ")\n", - "\n", - "\n", - "from cd_dynamax import adjust_rhs\n", - "\n", - "def make_state_evolution(drift_fn, diffusion_coeff):\n", - " \"\"\"Wrap a drift f(x,u,t) into a ContinuousTimeStateEvolution.\n", - "\n", - " diffusion_coeff: scalar sigma_x in dx = f(x) dt + sigma_x dW_t.\n", - " adjust_rhs clips state and derivatives to [-100,100] / [-1000,1000]\n", - " to prevent SDE solver blow-up.\n", - " \"\"\"\n", - " return ContinuousTimeStateEvolution(\n", - " drift=lambda x, u, t: adjust_rhs(x, drift_fn(x, u, t)),\n", - " # sigma_x I_2 (isotropic, constant diffusion)\n", - " diffusion_coefficient=lambda x, u, t: diffusion_coeff * jnp.eye(state_dim),\n", - " )\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Data generation\n", - "\n", - "We simulate from the **true** FHN drift using an SDE simulator. The model observes the state at `obs_times` with Gaussian noise." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "# Data generation: simulate dx_t = f_true(x_t) dt + sigma_x_true dW_t\n", - "# y_k = H x_{t_k} + N(0, sigma_y_true^2 I)\n", - "# Uses the true (known) noise values — these are NOT passed to the inference model.\n", - "def model_with_true_drift(obs_times=None, obs_values=None, predict_times=None):\n", - " return dsx.sample(\"f\", DynamicalModel(\n", - " state_evolution=make_state_evolution(\n", - " lambda x, u, t: fitzhugh_nagumo_drift(x),\n", - " diffusion_coeff=sigma_x_true,\n", - " ),\n", - " # y_k = H x_{t_k} + N(0, sigma_y_true^2 I)\n", - " observation_model=LinearGaussianObservation(\n", - " H=H_obs,\n", - " R=sigma_y_true**2 * jnp.eye(observation_dim),\n", - " ),\n", - " **initial_condition_kwargs,\n", - " ), obs_times=obs_times, obs_values=obs_values, predict_times=predict_times)\n", - "\n", - "predictive = Predictive(model_with_true_drift, num_samples=1, exclude_deterministic=False)\n", - "with SDESimulator():\n", - " synthetic = predictive(k_data, predict_times=obs_times)\n", - "\n", - "# (num_samples, n_sim, n_times, dim)\n", - "obs_values = synthetic[\"f_observations\"][0, 0] # y_k shape (n_obs, observation_dim)\n", - "states = synthetic[\"f_states\"][0, 0] # x_{t_k} shape (n_obs, state_dim)\n", - "times_1d = jnp.asarray(obs_times).squeeze()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Data visualization\n", - "\n", - "Time series of the latent state and noisy observations, and the phase-space trajectory." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, axes = plt.subplots(2, 1, figsize=(8, 5), sharex=True, constrained_layout=True)\n", - "axes[0].plot(times_1d, states[:, 0], label=\"$v$ (state)\", color=\"C0\")\n", - "axes[0].plot(times_1d, obs_values[:, 0], linestyle=\"--\", alpha=0.8, label=\"$v$ (obs)\", color=\"C0\")\n", - "axes[0].set_ylabel(\"$v$\")\n", - "axes[0].legend(loc=\"upper right\")\n", - "axes[0].grid(True, alpha=0.3)\n", - "axes[1].plot(times_1d, states[:, 1], label=\"$w$ (state)\", color=\"C1\")\n", - "if observation_dim >= 2:\n", - " axes[1].plot(times_1d, obs_values[:, 1], linestyle=\"--\", alpha=0.8, label=\"$w$ (obs)\", color=\"C1\")\n", - "axes[1].set_ylabel(\"$w$\")\n", - "axes[1].set_xlabel(\"Time\")\n", - "axes[1].legend(loc=\"upper right\")\n", - "axes[1].grid(True, alpha=0.3)\n", - "fig.suptitle(f\"Generated data (observation_dim={observation_dim}): states and observations\")\n", - "plt.show()\n", - "\n", - "fig, ax = plt.subplots(figsize=(5, 5), constrained_layout=True)\n", - "ax.plot(states[:, 0], states[:, 1], color=\"C0\", label=\"Latent state\", linewidth=1.5)\n", - "if observation_dim == 1:\n", - " ax.scatter(obs_values[:, 0], jnp.zeros_like(obs_values[:, 0]), s=8, alpha=0.6, color=\"C1\", label=\"Observations (v)\")\n", - "else:\n", - " ax.scatter(obs_values[:, 0], obs_values[:, 1], s=8, alpha=0.6, color=\"C1\", label=\"Observations\")\n", - "ax.set_xlabel(\"$v$\")\n", - "ax.set_ylabel(\"$w$\")\n", - "ax.set_title(f\"Phase space (observation_dim={observation_dim})\")\n", - "ax.legend()\n", - "ax.grid(True, alpha=0.3)\n", - "ax.set_aspect(\"equal\")\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Polynomial library and true coefficients\n", - "\n", - "Library terms (monomials in $v$, $w$): $1$, $v$, $w$, $v^2$, $vw$, $w^2$, $v^3$, $v^2w$, $vw^2$, $w^3$. The true FHN drift uses only a subset. We build the coefficient matrix $\\Theta \\in \\mathbb{R}^{2 \\times 10}$ so that $f(x) = \\Theta\\,\\phi(x)$." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "True coefficient matrix (rows: dv, dw; cols: library terms):\n", - "[[ 0.5 1. -1. 0. 0. 0. -0.3333 0. 0.\n", - " 0. ]\n", - " [ 0.056 0.08 -0.064 0. 0. 0. 0. 0. 0.\n", - " 0. ]]\n" - ] - } - ], - "source": [ - "TERM_NAMES = [\"1\", \"v\", \"w\", \"v²\", \"vw\", \"w²\", \"v³\", \"v²w\", \"vw²\", \"w³\"]\n", - "N_TERMS = len(TERM_NAMES)\n", - "\n", - "\n", - "def monomials(x):\n", - " \"\"\"Evaluate polynomial basis at state x = (v, w). Returns (N_TERMS,).\"\"\"\n", - " v, w = x[0], x[1]\n", - " return jnp.array([\n", - " 1.0, v, w, v**2, v * w, w**2, v**3, v**2 * w, v * w**2, w**3,\n", - " ])\n", - "\n", - "\n", - "# True coefficient matrix (state_dim x N_TERMS) for FHN: dv = v - v³/3 - w + I, dw = _a*(v + _b - _c*w)\n", - "true_Theta = jnp.zeros((state_dim, N_TERMS))\n", - "true_Theta = true_Theta.at[0, 0].set(_I) # 1\n", - "true_Theta = true_Theta.at[0, 1].set(1.0) # v\n", - "true_Theta = true_Theta.at[0, 2].set(-1.0) # w\n", - "true_Theta = true_Theta.at[0, 6].set(-1.0 / 3) # v³\n", - "true_Theta = true_Theta.at[1, 0].set(_a * _b) # 1\n", - "true_Theta = true_Theta.at[1, 1].set(_a) # v\n", - "true_Theta = true_Theta.at[1, 2].set(-_a * _c) # w\n", - "\n", - "print(\"True coefficient matrix (rows: dv, dw; cols: library terms):\")\n", - "print(jnp.round(true_Theta, 4))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Model discovery" - ] - }, + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Sparse identification of FitzHugh–Nagumo dynamics\n", + "\n", + "This **deep-dive tutorial** walks through sparse drift inference for a FitzHugh–Nagumo (FHN) SDE.\n", + "\n", + "**Goal.** Given noisy observations of the state, recover the sparse structure of the drift $f(x)$ by expressing it as with the elements of a polynomial library $\\Theta\\,\\phi(x)$ and placing a **Laplace prior** on the coefficient matrix $\\Theta$. This is a Bayesian SINDy-style approach. We fit via **SVI with AutoDelta** (MAP estimation) and then compare the recovered coefficients and filtered trajectories against ground truth.\n", + "\n", + "**What is known.**\n", + "- Initial state distribution: $x_0 \\sim \\mathcal{N}(0, I)$.\n", + "- Observation operator $H$ (identity here, observing both states).\n", + "- Polynomial library $\\phi(x)$ (monomials up to degree 3).\n", + "\n", + "**What is inferred.**\n", + "- Drift coefficient matrix $\\Theta \\in \\mathbb{R}^{2 \\times 10}$ via MAP (Laplace prior promotes sparsity).\n", + "- Diffusion coefficient $\\sigma_x > 0$ (HalfNormal prior).\n", + "- Observation noise standard deviation $\\sigma_y > 0$ (HalfNormal prior)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## FitzHugh–Nagumo Model\n", + "\n", + "### State SDE\n", + "\n", + "The state $x_t = (v_t, w_t)^\\top \\in \\mathbb{R}^2$ evolves as an Itô SDE:\n", + "\n", + "$$\n", + "dx_t = f(x_t)\\,dt + \\sigma_x\\,dW_t,\n", + "$$\n", + "\n", + "where $W_t$ is a standard 2-dimensional Brownian motion and the true drift is\n", + "\n", + "$$\n", + "f(x) = \\begin{pmatrix} v - \\tfrac{1}{3}v^3 - w + I \\\\ a\\,(v + b - c\\,w) \\end{pmatrix}.\n", + "$$\n", + "\n", + "Parameters are fixed at $a = 0.08$, $b = 0.7$, $c = 0.8$, $I = 0.5$. The true noise values used to generate data are $\\sigma_x = 0.01$ and $\\sigma_y = 0.1$, but **both are treated as unknown during inference**.\n", + "\n", + "### Observation process\n", + "\n", + "Observations are collected at discrete times $t_1 < t_2 < \\cdots < t_n$:\n", + "\n", + "$$\n", + "y_k = H\\,x_{t_k} + \\varepsilon_k, \\qquad \\varepsilon_k \\sim \\mathcal{N}(0,\\,\\sigma_y^2 I),\n", + "$$\n", + "\n", + "where $H = I_2$ (both states observed).\n", + "\n", + "### Initial condition\n", + "\n", + "$$\n", + "x_0 \\sim \\mathcal{N}(0, I_2).\n", + "$$\n", + "\n", + "### Inferred quantities\n", + "\n", + "We do **not** know $f$, $\\sigma_x$, or $\\sigma_y$. We parameterise the drift as\n", + "\n", + "$$\n", + "f(x) \\approx \\Theta\\,\\phi(x),\n", + "$$\n", + "\n", + "where $\\phi(x) \\in \\mathbb{R}^{10}$ is a polynomial library (all monomials in $v, w$ up to degree 3). The full set of inferred quantities and their priors is:\n", + "\n", + "$$\n", + "\\Theta \\sim \\mathrm{Laplace}(0,\\; 0.1) \\quad \\text{(promotes sparsity)},\n", + "$$\n", + "$$\n", + "\\sigma_x \\sim \\mathrm{HalfNormal}(0.1), \\qquad \\sigma_y \\sim \\mathrm{HalfNormal}(0.5).\n", + "$$\n", + "\n", + "All three are inferred jointly via MAP (SVI with AutoDelta)." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import jax.numpy as jnp\n", + "import jax.random as jr\n", + "import numpyro\n", + "import numpyro.distributions as dist\n", + "from numpyro.infer import SVI, Trace_ELBO, Predictive\n", + "from numpyro.infer.autoguide import AutoDelta\n", + "\n", + "import dynestyx as dsx\n", + "from dynestyx import (\n", + " ContinuousTimeStateEvolution,\n", + " DynamicalModel,\n", + " Filter,\n", + " LinearGaussianObservation,\n", + " SDESimulator,\n", + ")\n", + "\n", + "import matplotlib.pyplot as plt\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## True system\n", + "\n", + "Define the true FitzHugh–Nagumo drift. We will later build the full DynamicalModel by piping in this drift and spreading shared arguments from a dict." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# FitzHugh–Nagumo parameters\n", + "_a, _b, _c, _I = 0.08, 0.7, 0.8, 0.5\n", + "\n", + "def fitzhugh_nagumo_drift(x):\n", + " v, w = x[0], x[1]\n", + " dv = v - (1/3) * v**3 - w + _I\n", + " dw = _a * (v + _b - _c * w)\n", + " return jnp.array([dv, dw])\n", + "\n", + "state_dim = 2" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Model configuration\n", + "\n", + "Constants used for data generation and inference setup.\n", + "\n", + "| Symbol | Role | Value | Status |\n", + "|---|---|---|---|\n", + "| $\\sigma_x^{\\mathrm{true}}$ | true diffusion coefficient (data generation only) | `0.01` | **inferred** |\n", + "| $\\sigma_y^{\\mathrm{true}}$ | true observation noise std (data generation only) | `0.1` | **inferred** |\n", + "| $x_0 \\sim \\mathcal{N}(0, I_2)$ | initial state prior | covariance = `I` | known |\n", + "| $\\Delta t$ | observation spacing | `0.1` | known |\n", + "| $T$ | total time span | `[0, 50)` | known |" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# True values used ONLY for data generation — both are inferred during model discovery\n", + "sigma_x_true = 0.01 # true diffusion coefficient\n", + "sigma_y_true = 0.1 # true observation noise std\n", + "\n", + "# observation times t_1, ..., t_n (spacing Delta_t = 0.1, span [0, 50))\n", + "obs_times = jnp.arange(0.0, 50.0, 0.1)\n", + "\n", + "observation_dim = 2 # observation_dim=1 also works (observe only v)\n", + "\n", + "key = jr.PRNGKey(0)\n", + "key, k_data, k_svi, k_nuts, k_filter = jr.split(key, 5)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## DynamicalModel construction helpers\n", + "\n", + "The Dynestyx `DynamicalModel` needs three pieces:\n", + "\n", + "- **Initial condition** — $x_0 \\sim \\mathcal{N}(0, I_2)$. Fixed; collected in `initial_condition_kwargs`.\n", + "- **Observation model** — $y_k = H\\,x_{t_k} + \\varepsilon_k$ with $\\varepsilon_k \\sim \\mathcal{N}(0, \\sigma_y^2 I_2)$. Constructed inside each model function because $\\sigma_y$ is inferred.\n", + "- **State evolution** — wraps the drift $f$ and the diffusion $\\sigma_x I_2$. Constructed inside each model function because $\\sigma_x$ is inferred.\n", + "\n", + "`make_state_evolution(drift_fn, diffusion_coeff)` is a helper that accepts whichever diffusion coefficient (true or inferred) is provided." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# H in y_k = H x_{t_k} + eps_k (identity: observe all states)\n", + "H_obs = jnp.eye(observation_dim, state_dim)\n", + "\n", + "# Only the initial condition is shared and fixed; observation model and state\n", + "# evolution are constructed inside each model function because sigma_x and sigma_y\n", + "# are inferred.\n", + "initial_condition_kwargs = dict(\n", + " # x_0 ~ N(0, I_2)\n", + " initial_condition=dist.MultivariateNormal(\n", + " loc=jnp.zeros(state_dim),\n", + " covariance_matrix=jnp.eye(state_dim),\n", + " ),\n", + ")\n", + "\n", + "\n", + "from cd_dynamax import adjust_rhs\n", + "\n", + "def make_state_evolution(drift_fn, diffusion_coeff):\n", + " \"\"\"Wrap a drift f(x,u,t) into a ContinuousTimeStateEvolution.\n", + "\n", + " diffusion_coeff: scalar sigma_x in dx = f(x) dt + sigma_x dW_t.\n", + " adjust_rhs clips state and derivatives to [-100,100] / [-1000,1000]\n", + " to prevent SDE solver blow-up.\n", + " \"\"\"\n", + " return ContinuousTimeStateEvolution(\n", + " drift=lambda x, u, t: adjust_rhs(x, drift_fn(x, u, t)),\n", + " # sigma_x I_2 (isotropic, constant diffusion)\n", + " diffusion=dsx.FullDiffusion(diffusion_coeff * jnp.eye(state_dim)),\n", + " )\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data generation\n", + "\n", + "We simulate from the **true** FHN drift using an SDE simulator. The model observes the state at `obs_times` with Gaussian noise." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Data generation: simulate dx_t = f_true(x_t) dt + sigma_x_true dW_t\n", + "# y_k = H x_{t_k} + N(0, sigma_y_true^2 I)\n", + "# Uses the true (known) noise values — these are NOT passed to the inference model.\n", + "def model_with_true_drift(obs_times=None, obs_values=None, predict_times=None):\n", + " return dsx.sample(\"f\", DynamicalModel(\n", + " state_evolution=make_state_evolution(\n", + " lambda x, u, t: fitzhugh_nagumo_drift(x),\n", + " diffusion_coeff=sigma_x_true,\n", + " ),\n", + " # y_k = H x_{t_k} + N(0, sigma_y_true^2 I)\n", + " observation_model=LinearGaussianObservation(\n", + " H=H_obs,\n", + " R=sigma_y_true**2 * jnp.eye(observation_dim),\n", + " ),\n", + " **initial_condition_kwargs,\n", + " ), obs_times=obs_times, obs_values=obs_values, predict_times=predict_times)\n", + "\n", + "predictive = Predictive(model_with_true_drift, num_samples=1, exclude_deterministic=False)\n", + "with SDESimulator():\n", + " synthetic = predictive(k_data, predict_times=obs_times)\n", + "\n", + "# (num_samples, n_sim, n_times, dim)\n", + "obs_values = synthetic[\"f_observations\"][0, 0] # y_k shape (n_obs, observation_dim)\n", + "states = synthetic[\"f_states\"][0, 0] # x_{t_k} shape (n_obs, state_dim)\n", + "times_1d = jnp.asarray(obs_times).squeeze()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Data visualization\n", + "\n", + "Time series of the latent state and noisy observations, and the phase-space trajectory." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Build a Dynestyx SDE model that jointly infers:\n", - "- $\\Theta$ — drift coefficients with a sparsifying Laplace prior,\n", - "- $\\sigma_x$ — diffusion coefficient with a HalfNormal prior,\n", - "- $\\sigma_y$ — observation noise std with a HalfNormal prior.\n", - "\n", - "The observation model and state evolution are constructed inside the model function so that the sampled $\\sigma_x$ and $\\sigma_y$ flow through to the likelihood." + "data": { + "image/png": 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", + "text/plain": [ + "
" ] + }, + "metadata": {}, + "output_type": "display_data" }, { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "def model_with_polynomial_drift(obs_times=None, obs_values=None):\n", - " # Theta ~ Laplace(0, 0.1) iid for each entry in R^{2 x 10}\n", - " # Laplace prior promotes sparsity: entries not supported by data shrink toward 0\n", - " Theta = numpyro.sample(\n", - " \"Theta\",\n", - " dist.Laplace(0.0, 0.1).expand([state_dim, N_TERMS]).to_event(2),\n", - " )\n", - "\n", - " # sigma_x ~ HalfNormal(0.1) — diffusion coefficient in dx = f(x) dt + sigma_x dW_t\n", - " sigma_x = numpyro.sample(\"sigma_x\", dist.HalfNormal(0.1))\n", - "\n", - " # sigma_y ~ HalfNormal(0.5) — per-component std in y_k = H x_{t_k} + N(0, sigma_y^2 I)\n", - " sigma_y = numpyro.sample(\"sigma_y\", dist.HalfNormal(0.5))\n", - "\n", - " # f(x) = Theta phi(x) approximates the unknown drift\n", - " def drift(x, u, t):\n", - " phi = monomials(x) # phi(x) in R^{N_TERMS}\n", - " return Theta @ phi # R^{state_dim}\n", - "\n", - " # Full model: dx = Theta phi(x) dt + sigma_x dW_t, y_k = H x_{t_k} + N(0, sigma_y^2 I)\n", - " return dsx.sample(\"f\", DynamicalModel(\n", - " state_evolution=make_state_evolution(drift, diffusion_coeff=sigma_x),\n", - " observation_model=LinearGaussianObservation(\n", - " H=H_obs,\n", - " R=sigma_y**2 * jnp.eye(observation_dim),\n", - " ),\n", - " **initial_condition_kwargs,\n", - " ), obs_times=obs_times, obs_values=obs_values)\n", - "\n" + "data": { + "image/png": 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", + "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(2, 1, figsize=(8, 5), sharex=True, constrained_layout=True)\n", + "axes[0].plot(times_1d, states[:, 0], label=\"$v$ (state)\", color=\"C0\")\n", + "axes[0].plot(times_1d, obs_values[:, 0], linestyle=\"--\", alpha=0.8, label=\"$v$ (obs)\", color=\"C0\")\n", + "axes[0].set_ylabel(\"$v$\")\n", + "axes[0].legend(loc=\"upper right\")\n", + "axes[0].grid(True, alpha=0.3)\n", + "axes[1].plot(times_1d, states[:, 1], label=\"$w$ (state)\", color=\"C1\")\n", + "if observation_dim >= 2:\n", + " axes[1].plot(times_1d, obs_values[:, 1], linestyle=\"--\", alpha=0.8, label=\"$w$ (obs)\", color=\"C1\")\n", + "axes[1].set_ylabel(\"$w$\")\n", + "axes[1].set_xlabel(\"Time\")\n", + "axes[1].legend(loc=\"upper right\")\n", + "axes[1].grid(True, alpha=0.3)\n", + "fig.suptitle(f\"Generated data (observation_dim={observation_dim}): states and observations\")\n", + "plt.show()\n", + "\n", + "fig, ax = plt.subplots(figsize=(5, 5), constrained_layout=True)\n", + "ax.plot(states[:, 0], states[:, 1], color=\"C0\", label=\"Latent state\", linewidth=1.5)\n", + "if observation_dim == 1:\n", + " ax.scatter(obs_values[:, 0], jnp.zeros_like(obs_values[:, 0]), s=8, alpha=0.6, color=\"C1\", label=\"Observations (v)\")\n", + "else:\n", + " ax.scatter(obs_values[:, 0], obs_values[:, 1], s=8, alpha=0.6, color=\"C1\", label=\"Observations\")\n", + "ax.set_xlabel(\"$v$\")\n", + "ax.set_ylabel(\"$w$\")\n", + "ax.set_title(f\"Phase space (observation_dim={observation_dim})\")\n", + "ax.legend()\n", + "ax.grid(True, alpha=0.3)\n", + "ax.set_aspect(\"equal\")\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Polynomial library and true coefficients\n", + "\n", + "Library terms (monomials in $v$, $w$): $1$, $v$, $w$, $v^2$, $vw$, $w^2$, $v^3$, $v^2w$, $vw^2$, $w^3$. The true FHN drift uses only a subset. We build the coefficient matrix $\\Theta \\in \\mathbb{R}^{2 \\times 10}$ so that $f(x) = \\Theta\\,\\phi(x)$." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Build the conditioned model via filtering + data conditioning" - ] - }, + "name": "stdout", + "output_type": "stream", + "text": [ + "True coefficient matrix (rows: dv, dw; cols: library terms):\n", + "[[ 0.5 1. -1. 0. 0. 0. -0.3333 0. 0.\n", + " 0. ]\n", + " [ 0.056 0.08 -0.064 0. 0. 0. 0. 0. 0.\n", + " 0. ]]\n" + ] + } + ], + "source": [ + "TERM_NAMES = [\"1\", \"v\", \"w\", \"v²\", \"vw\", \"w²\", \"v³\", \"v²w\", \"vw²\", \"w³\"]\n", + "N_TERMS = len(TERM_NAMES)\n", + "\n", + "\n", + "def monomials(x):\n", + " \"\"\"Evaluate polynomial basis at state x = (v, w). Returns (N_TERMS,).\"\"\"\n", + " v, w = x[0], x[1]\n", + " return jnp.array([\n", + " 1.0, v, w, v**2, v * w, w**2, v**3, v**2 * w, v * w**2, w**3,\n", + " ])\n", + "\n", + "\n", + "# True coefficient matrix (state_dim x N_TERMS) for FHN: dv = v - v³/3 - w + I, dw = _a*(v + _b - _c*w)\n", + "true_Theta = jnp.zeros((state_dim, N_TERMS))\n", + "true_Theta = true_Theta.at[0, 0].set(_I) # 1\n", + "true_Theta = true_Theta.at[0, 1].set(1.0) # v\n", + "true_Theta = true_Theta.at[0, 2].set(-1.0) # w\n", + "true_Theta = true_Theta.at[0, 6].set(-1.0 / 3) # v³\n", + "true_Theta = true_Theta.at[1, 0].set(_a * _b) # 1\n", + "true_Theta = true_Theta.at[1, 1].set(_a) # v\n", + "true_Theta = true_Theta.at[1, 2].set(-_a * _c) # w\n", + "\n", + "print(\"True coefficient matrix (rows: dv, dw; cols: library terms):\")\n", + "print(jnp.round(true_Theta, 4))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Model discovery" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Build a Dynestyx SDE model that jointly infers:\n", + "- $\\Theta$ — drift coefficients with a sparsifying Laplace prior,\n", + "- $\\sigma_x$ — diffusion coefficient with a HalfNormal prior,\n", + "- $\\sigma_y$ — observation noise std with a HalfNormal prior.\n", + "\n", + "The observation model and state evolution are constructed inside the model function so that the sampled $\\sigma_x$ and $\\sigma_y$ flow through to the likelihood." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "def model_with_polynomial_drift(obs_times=None, obs_values=None):\n", + " # Theta ~ Laplace(0, 0.1) iid for each entry in R^{2 x 10}\n", + " # Laplace prior promotes sparsity: entries not supported by data shrink toward 0\n", + " Theta = numpyro.sample(\n", + " \"Theta\",\n", + " dist.Laplace(0.0, 0.1).expand([state_dim, N_TERMS]).to_event(2),\n", + " )\n", + "\n", + " # sigma_x ~ HalfNormal(0.1) — diffusion coefficient in dx = f(x) dt + sigma_x dW_t\n", + " sigma_x = numpyro.sample(\"sigma_x\", dist.HalfNormal(0.1))\n", + "\n", + " # sigma_y ~ HalfNormal(0.5) — per-component std in y_k = H x_{t_k} + N(0, sigma_y^2 I)\n", + " sigma_y = numpyro.sample(\"sigma_y\", dist.HalfNormal(0.5))\n", + "\n", + " # f(x) = Theta phi(x) approximates the unknown drift\n", + " def drift(x, u, t):\n", + " phi = monomials(x) # phi(x) in R^{N_TERMS}\n", + " return Theta @ phi # R^{state_dim}\n", + "\n", + " # Full model: dx = Theta phi(x) dt + sigma_x dW_t, y_k = H x_{t_k} + N(0, sigma_y^2 I)\n", + " return dsx.sample(\"f\", DynamicalModel(\n", + " state_evolution=make_state_evolution(drift, diffusion_coeff=sigma_x),\n", + " observation_model=LinearGaussianObservation(\n", + " H=H_obs,\n", + " R=sigma_y**2 * jnp.eye(observation_dim),\n", + " ),\n", + " **initial_condition_kwargs,\n", + " ), obs_times=obs_times, obs_values=obs_values)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Build the conditioned model via filtering + data conditioning" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "def data_conditioned_model(obs_times=None, obs_values=None):\n", + " with Filter():\n", + " return model_with_polynomial_drift(obs_times=obs_times, obs_values=obs_values)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Run SVI for MAP estimation..." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "def data_conditioned_model(obs_times=None, obs_values=None):\n", - " with Filter():\n", - " return model_with_polynomial_drift(obs_times=obs_times, obs_values=obs_values)" - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 4000/4000 [27:25<00:00, 2.43it/s, init loss: 766.3178, avg. loss [3801-4000]: -911.7092]" + ] }, { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Run SVI for MAP estimation..." - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Inferred sigma_x = 0.0094 (true = 0.0100)\n", + "Inferred sigma_y = 0.0955 (true = 0.1000)\n" + ] }, { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 4000/4000 [27:25<00:00, 2.43it/s, init loss: 766.3178, avg. loss [3801-4000]: -911.7092]" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Inferred sigma_x = 0.0094 (true = 0.0100)\n", - "Inferred sigma_y = 0.0955 (true = 0.1000)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "# Note that we get \"close\" to a good model within 1000 steps, but the last 3000 steps are needed to get a high-fidelity final MAP estimate here.\n", - "num_steps = 4000\n", - "optimizer = numpyro.optim.Adam(step_size=1e-2)\n", - "guide = AutoDelta(data_conditioned_model)\n", - "svi = SVI(data_conditioned_model, guide, optimizer, loss=Trace_ELBO())\n", - "svi_result = svi.run(k_svi, num_steps=num_steps, obs_times=obs_times, obs_values=obs_values)\n", - "\n", - "median = guide.median(svi_result.params)\n", - "Theta_inferred = median[\"Theta\"] # (state_dim, N_TERMS)\n", - "sigma_x_inferred = float(median[\"sigma_x\"]) # scalar\n", - "sigma_y_inferred = float(median[\"sigma_y\"]) # scalar\n", - "\n", - "print(f\"Inferred sigma_x = {sigma_x_inferred:.4f} (true = {sigma_x_true:.4f})\")\n", - "print(f\"Inferred sigma_y = {sigma_y_inferred:.4f} (true = {sigma_y_true:.4f})\")" - ] - }, + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "# Note that we get \"close\" to a good model within 1000 steps, but the last 3000 steps are needed to get a high-fidelity final MAP estimate here.\n", + "num_steps = 4000\n", + "optimizer = numpyro.optim.Adam(step_size=1e-2)\n", + "guide = AutoDelta(data_conditioned_model)\n", + "svi = SVI(data_conditioned_model, guide, optimizer, loss=Trace_ELBO())\n", + "svi_result = svi.run(k_svi, num_steps=num_steps, obs_times=obs_times, obs_values=obs_values)\n", + "\n", + "median = guide.median(svi_result.params)\n", + "Theta_inferred = median[\"Theta\"] # (state_dim, N_TERMS)\n", + "sigma_x_inferred = float(median[\"sigma_x\"]) # scalar\n", + "sigma_y_inferred = float(median[\"sigma_y\"]) # scalar\n", + "\n", + "print(f\"Inferred sigma_x = {sigma_x_inferred:.4f} (true = {sigma_x_true:.4f})\")\n", + "print(f\"Inferred sigma_y = {sigma_y_inferred:.4f} (true = {sigma_y_true:.4f})\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### SVI loss curve\n", + "\n", + "The negative ELBO decreases as the MAP estimate is refined." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### SVI loss curve\n", - "\n", - "The negative ELBO decreases as the MAP estimate is refined." + "data": { + "image/png": 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", + "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(6, 3), constrained_layout=True)\n", + "ax.plot(svi_result.losses, color=\"C0\", label=\"SVI (AutoDelta MAP)\")\n", + "ax.set_yscale(\"symlog\")\n", + "ax.set_xscale(\"log\")\n", + "ax.set_xlabel(\"Step\")\n", + "ax.set_ylabel(\"Loss (negative ELBO)\")\n", + "ax.set_title(f\"SVI loss (observation_dim={observation_dim})\")\n", + "ax.legend()\n", + "ax.grid(True, alpha=0.3)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parameter recovery\n", + "\n", + "Compare true vs inferred values for all inferred quantities:\n", + "- **Drift coefficients** $\\Theta$: side-by-side heatmaps (red = positive, blue = negative). The Laplace prior shrinks unused terms toward zero, recovering the sparse structure.\n", + "- **Noise scales** $\\sigma_x$, $\\sigma_y$: bar chart comparing inferred MAP values against the ground truth used for data generation." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(6, 3), constrained_layout=True)\n", - "ax.plot(svi_result.losses, color=\"C0\", label=\"SVI (AutoDelta MAP)\")\n", - "ax.set_yscale(\"symlog\")\n", - "ax.set_xscale(\"log\")\n", - "ax.set_xlabel(\"Step\")\n", - "ax.set_ylabel(\"Loss (negative ELBO)\")\n", - "ax.set_title(f\"SVI loss (observation_dim={observation_dim})\")\n", - "ax.legend()\n", - "ax.grid(True, alpha=0.3)\n", - "plt.show()" + "data": { + "image/png": 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", + "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "vmax = max(float(jnp.abs(true_Theta).max()), float(jnp.abs(Theta_inferred).max())) * 1.1\n", + "\n", + "fig, axes = plt.subplots(1, 2, figsize=(10, 4), sharey=True, constrained_layout=True)\n", + "\n", + "im0 = axes[0].imshow(\n", + " jnp.asarray(true_Theta),\n", + " cmap=\"RdBu_r\",\n", + " aspect=\"auto\",\n", + " vmin=-vmax,\n", + " vmax=vmax,\n", + ")\n", + "axes[0].set_xticks(range(N_TERMS))\n", + "axes[0].set_xticklabels(TERM_NAMES, rotation=45, ha=\"right\", fontsize=11)\n", + "axes[0].set_yticks([0, 1])\n", + "axes[0].set_yticklabels([r\"$\\dot{v}$\", r\"$\\dot{w}$\"], fontsize=12)\n", + "axes[0].set_title(\"True coefficients\")\n", + "axes[0].set_xlabel(\"Polynomial term\")\n", + "\n", + "im1 = axes[1].imshow(\n", + " jnp.asarray(Theta_inferred),\n", + " cmap=\"RdBu_r\",\n", + " aspect=\"auto\",\n", + " vmin=-vmax,\n", + " vmax=vmax,\n", + ")\n", + "axes[1].set_xticks(range(N_TERMS))\n", + "axes[1].set_xticklabels(TERM_NAMES, rotation=45, ha=\"right\", fontsize=11)\n", + "axes[1].set_yticks([0, 1])\n", + "axes[1].set_yticklabels([r\"$\\dot{v}$\", r\"$\\dot{w}$\"], fontsize=12)\n", + "axes[1].set_title(\"Inferred (MAP)\")\n", + "axes[1].set_xlabel(\"Polynomial term\")\n", + "\n", + "cbar = fig.colorbar(im1, ax=axes, shrink=0.6, aspect=20)\n", + "cbar.set_label(\"Coefficient value\", fontsize=11)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Parameter recovery\n", - "\n", - "Compare true vs inferred values for all inferred quantities:\n", - "- **Drift coefficients** $\\Theta$: side-by-side heatmaps (red = positive, blue = negative). The Laplace prior shrinks unused terms toward zero, recovering the sparse structure.\n", - "- **Noise scales** $\\sigma_x$, $\\sigma_y$: bar chart comparing inferred MAP values against the ground truth used for data generation." + "data": { + "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "vmax = max(float(jnp.abs(true_Theta).max()), float(jnp.abs(Theta_inferred).max())) * 1.1\n", - "\n", - "fig, axes = plt.subplots(1, 2, figsize=(10, 4), sharey=True, constrained_layout=True)\n", - "\n", - "im0 = axes[0].imshow(\n", - " jnp.asarray(true_Theta),\n", - " cmap=\"RdBu_r\",\n", - " aspect=\"auto\",\n", - " vmin=-vmax,\n", - " vmax=vmax,\n", - ")\n", - "axes[0].set_xticks(range(N_TERMS))\n", - "axes[0].set_xticklabels(TERM_NAMES, rotation=45, ha=\"right\", fontsize=11)\n", - "axes[0].set_yticks([0, 1])\n", - "axes[0].set_yticklabels([r\"$\\dot{v}$\", r\"$\\dot{w}$\"], fontsize=12)\n", - "axes[0].set_title(\"True coefficients\")\n", - "axes[0].set_xlabel(\"Polynomial term\")\n", - "\n", - "im1 = axes[1].imshow(\n", - " jnp.asarray(Theta_inferred),\n", - " cmap=\"RdBu_r\",\n", - " aspect=\"auto\",\n", - " vmin=-vmax,\n", - " vmax=vmax,\n", - ")\n", - "axes[1].set_xticks(range(N_TERMS))\n", - "axes[1].set_xticklabels(TERM_NAMES, rotation=45, ha=\"right\", fontsize=11)\n", - "axes[1].set_yticks([0, 1])\n", - "axes[1].set_yticklabels([r\"$\\dot{v}$\", r\"$\\dot{w}$\"], fontsize=12)\n", - "axes[1].set_title(\"Inferred (MAP)\")\n", - "axes[1].set_xlabel(\"Polynomial term\")\n", - "\n", - "cbar = fig.colorbar(im1, ax=axes, shrink=0.6, aspect=20)\n", - "cbar.set_label(\"Coefficient value\", fontsize=11)\n", - "plt.show()" - ] - }, + "name": "stdout", + "output_type": "stream", + "text": [ + " sigma_x: true=0.0100, inferred=0.0094, relative error=5.8%\n", + " sigma_y: true=0.1000, inferred=0.0955, relative error=4.5%\n" + ] + } + ], + "source": [ + "labels = [r\"$\\sigma_x$ (diffusion)\", r\"$\\sigma_y$ (obs noise)\"]\n", + "truths = [sigma_x_true, sigma_y_true]\n", + "inferred = [sigma_x_inferred, sigma_y_inferred]\n", + "\n", + "x = range(len(labels))\n", + "width = 0.35\n", + "\n", + "fig, ax = plt.subplots(figsize=(5, 3.5), constrained_layout=True)\n", + "bars_true = ax.bar([v - width/2 for v in x], truths, width, label=\"True\", color=\"C2\", alpha=0.8)\n", + "bars_inf = ax.bar([v + width/2 for v in x], inferred, width, label=\"Inferred (MAP)\", color=\"C0\", alpha=0.8)\n", + "\n", + "# Annotate bar tops with values\n", + "for bar in bars_true:\n", + " ax.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.001,\n", + " f\"{bar.get_height():.4f}\", ha=\"center\", va=\"bottom\", fontsize=9)\n", + "for bar in bars_inf:\n", + " ax.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.001,\n", + " f\"{bar.get_height():.4f}\", ha=\"center\", va=\"bottom\", fontsize=9)\n", + "\n", + "ax.set_xticks(list(x))\n", + "ax.set_xticklabels(labels, fontsize=11)\n", + "ax.set_ylabel(\"Value\")\n", + "ax.set_title(\"Noise scale recovery: true vs inferred (MAP)\")\n", + "ax.legend()\n", + "ax.grid(True, axis=\"y\", alpha=0.3)\n", + "plt.show()\n", + "\n", + "# Relative errors\n", + "for name, t, i in zip([\"sigma_x\", \"sigma_y\"], truths, inferred):\n", + " rel_err = abs(i - t) / t * 100\n", + " print(f\" {name}: true={t:.4f}, inferred={i:.4f}, relative error={rel_err:.1f}%\")" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " sigma_x: true=0.0100, inferred=0.0094, relative error=5.8%\n", - " sigma_y: true=0.1000, inferred=0.0955, relative error=4.5%\n" - ] - } - ], - "source": [ - "labels = [r\"$\\sigma_x$ (diffusion)\", r\"$\\sigma_y$ (obs noise)\"]\n", - "truths = [sigma_x_true, sigma_y_true]\n", - "inferred = [sigma_x_inferred, sigma_y_inferred]\n", - "\n", - "x = range(len(labels))\n", - "width = 0.35\n", - "\n", - "fig, ax = plt.subplots(figsize=(5, 3.5), constrained_layout=True)\n", - "bars_true = ax.bar([v - width/2 for v in x], truths, width, label=\"True\", color=\"C2\", alpha=0.8)\n", - "bars_inf = ax.bar([v + width/2 for v in x], inferred, width, label=\"Inferred (MAP)\", color=\"C0\", alpha=0.8)\n", - "\n", - "# Annotate bar tops with values\n", - "for bar in bars_true:\n", - " ax.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.001,\n", - " f\"{bar.get_height():.4f}\", ha=\"center\", va=\"bottom\", fontsize=9)\n", - "for bar in bars_inf:\n", - " ax.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.001,\n", - " f\"{bar.get_height():.4f}\", ha=\"center\", va=\"bottom\", fontsize=9)\n", - "\n", - "ax.set_xticks(list(x))\n", - "ax.set_xticklabels(labels, fontsize=11)\n", - "ax.set_ylabel(\"Value\")\n", - "ax.set_title(\"Noise scale recovery: true vs inferred (MAP)\")\n", - "ax.legend()\n", - "ax.grid(True, axis=\"y\", alpha=0.3)\n", - "plt.show()\n", - "\n", - "# Relative errors\n", - "for name, t, i in zip([\"sigma_x\", \"sigma_y\"], truths, inferred):\n", - " rel_err = abs(i - t) / t * 100\n", - " print(f\" {name}: true={t:.4f}, inferred={i:.4f}, relative error={rel_err:.1f}%\")" - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/28/rfdjbzgj0bz_x56whkjmhl600000gn/T/ipykernel_65249/2550543806.py:38: UserWarning: Legend does not support handles for PatchCollection instances.\n", + "A proxy artist may be used instead.\n", + "See: https://matplotlib.org/stable/users/explain/axes/legend_guide.html#controlling-the-legend-entries\n", + " ax.legend(\n" + ] }, { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/28/rfdjbzgj0bz_x56whkjmhl600000gn/T/ipykernel_65249/2550543806.py:38: UserWarning: Legend does not support handles for PatchCollection instances.\n", - "A proxy artist may be used instead.\n", - "See: https://matplotlib.org/stable/users/explain/axes/legend_guide.html#controlling-the-legend-entries\n", - " ax.legend(\n" - ] - }, - { - "data": { - "image/png": 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wep//+cEHH4zhYPv27WJgFN/RFYTbj7+d26rt4KxbX3bF/Y20VYxC6G9jCjdejNmUxRO0u85auTfR3IOMgsWBN3N6W9mUx+acXJybKJtAeVFipz/eyHnysbmWzZLOAU5BwJOeN6Tu6KtJhk1BFIQU/GxGoXWCQoJesVzYnJuf/onbgvCkY7MVYfMbm8wp8HNvHFyXXDsK50ePYk8Mdb0GS+5yDhRHnPXUgYH+0d5gs/d5550ntiubsejB/shHPtJrk2cuvFmzuezNN9/s4gfsjx+NTeIU9mx+59Bbx66B4njK88+J3POBD448Jpym0NyLt/P9ULYb7RWTJk0S5xH9q7z50S7A6fJ/M3+7sPmxu+OQ53++OGF+Vj70vfTSS/s80PK8zr0xdYfjxWdzJ/sy5Pqy8+1bB5KBnp8UdgOxKPV1DXWOB3pPc+G1uTfrkgOn57U732LCfdoXfNjhAxU9u2x25sM5xSub9fvbWZTL2R/rh0N325nHO+1tI4mznfK3MwUexWn+eZm/37o713ujJ38rt1X+dYznEu9b+Z8R5/cGel3rz/1rIPf5nq6HDLTlQnsPr9n5nw8XdZngV3fHN6+xDADw93OPX2dfjLZc7lIcj0L4tO74YXujp57NzsHGk5UXWIol3th5geYJw6fTr371q+IG6cATlU977MD36KOPikgH/V705vKCwXF58DKy1t3v9tV7lZEfim5GwDl/erbolWVkiB7BgcATnMvKGwW9ouyUxGXi8jr+7P4y1PUaLN1FjXu6OOR3KHP2G329vHnk01cvcHo1uZ2cfU3/G2++7PhIr1hv0K/NByfOg8KKQpAChT4zeuP6wll2Png5Hbjy6a9Iz2eke/r3Z7txGShebr/9drF9KGJ5w+D6DhdcBgrvBQsWiAda3rgpCCmguTy553VPsIMgfbz08dP/zgdIihNGNPsz/f5ioOfnQFtj+rqGHki43uynwWswPeUUFtxfvFbzs/5cm3JbCIZzubrbPvnXqcHOeyT3m/Pg15Ow7Gm+ff3eQK5rA71/jeZjtKdl7e5Y4Gdc5vzvnH3h9DUYLUhxPI5hj2w2I1GA8sbukJ/1woE91zkw0syk/DTP88bPKCGFNQ9sPtk6kdyBQiHFTkMc+BTNjnjsbJMrjikknHRDDuysQ5xIDW8YjDhzvXIvpvn2CS4zbyhstuopejwc69Udg3kKdiICfKjJ7WSUHzVxolC8qA42AsDtwSZlDpFIRBwftIs4Iq+n5WfTIR+wuF1zn/4pjvPpbh5Oj31eIEcqetFXj2t21KPFKDeS61iM+P1QththiwgFDAUNRR3XuTtrRC4ch8KuO8vGhg0burznfBl9uf/++7tElbqz0/S0H3kOsXMpOwLlwmPvQNykelrOkTo/+4tzPLADGLeXA5vB2ZLV14Mcp6dwoujJjabl79PeYGsZB14r+QBKSwc7wfKYG+5oW3fHH6+/uVFyXqe6a9LPv04NZNmc7cTfd1pxnE5uPCb7Oi/7C88Xnmc93QMHy0Cua/29f41FZmdagp3raS78jPes/E6hzr7I3e+jAek5Hsc4T3G5T5jMLsCIVi60W/BinwtFMiMOTrM5e8dyfmziy39i5XvHy9UdvGDk+yB5krB5Oz9ND5cjN30Vl5fvefGhHaOn9aKfmU3MubBJkuNwmfNxph3IevU3lRuhuO+P97M70fvss89mP3PSoeVCocXWAEb/uvMi5qfzyyd/XzECxebM3H3hPJzkVyzjtuIFPffpnyKhu0p4nEd303O/UGTnp4jqz7IPFdp5uOy33nprl88ZceV69daK0Z/tRiiYODCyzPWkh7GvaD63C/crt+POnTuzn7OnPh9E8scluccrj7XuHlC62wfOPPKP93/+8599ppobKXo63oZy3RkO2ILHaCNbAnKvkbTN9KcJ3zmefvGLX3T5vD/VMzn//HV2Mhk4x5wjNIarsiCPv9xjgNkTeG3NPS94neJ1MPdcZQrA/FLMA1k2npfdbRe2jJD+ZPfoD2zl4j7NT+U5VAZyXevv/WskYOamkaxYWFFRIR7keM/KzZTB9HgMSnS3H9mXiDaV3rKMHAhk5Hgcw7RBfMpnMw9tErz5syk+/4JLPzJTzzB1DaMzvAlwPOeEdy6IjCBfd9112VRGfFLmUx+tEuwcyHRI3cEoHa0ZTH1D4z9FBU8UptRhhC0XCmbaLfgbXBYa+OltpY/L8Rcy1Q6fupkiiCcbl4ERbnbSYDTPgZEeekJ5Y2JEgh5RRidoDeB3XOeBrFd/U7kRCnkuO73czEvJde4r6Tw7LDCywdQ/bG7j9meKIl5wcgUThTFTDHHdGH2n+HLGYccVRvzzxV8u3E70L3IZGQnljcJJs5e7/ITHDUUbl4W/w+3NGxa3Je0DbAGgR54ikRfA/G3A/czxuV8Z/WNHFqbPYpSTf7OjE5eHF1LafTh+7kWVy8n8osPVhMh9wH3I1GPc3zweaZGgVYKWgt7Sj/Vnu+VGj53jpr+WCgrAhx9+WNiP2LrC85Apy3jTyN22PE5oo+C6sLMqj3mKNz5w7tmzp8s8uaw8VniMcx9xHHrVeQ7RasUIOK8TTNVFwZffB2Ak9kF3OMcb9wuPM57rXL+hXHeGA25nnutMicftRnsYl4Mig8vWV3SUYpYdZxmQ4AMMt/UTTzzRbS7lfCgwOB2vc/wtXke5n3n+O2KSUVAel7zW8HrJ45J++MGmxOIxwrRv7MRHAU6xyoeDa665JjsOrR08p3ld4LWK1wBef3mc5vZrGciy8TzkfYrXeccOyOsttwH3eW7UfqjQ/8/jjMvaV/+MgdDf61p/719DhYGV/BR4PcG+En2l6vvvf/+bzYPOoAyvSTw3Ca12TisKUwbyXOGxztYN9qXgPZitod3dN9khkOf6aPMcy1Ruo4j+loXuaTwnPVFuWpYXXnjBOuqoo0SKHqaYuuaaa7JpaJzxtm7dKlLI1NTUiFRSLBF50kkniZRy+dx7773WscceK1K5cFiwYIFI+7Vhw4Yel5dpa77yla+IVFjBYFBMx79//etf75NKh6mnVq5caR199NFiWZi259Zbb90nDdv3vvc98R3T9zBd1//+979uU0YxbQ7TRHE5PR6PVVFRYZ155pnW66+/PuD1Gkgqt0gkItI1MeUap3GWy5lHT2nzuFxHHnmkWNbp06dbP/3pT/dJ8ZS7PEzfxTRB3Fbcf5deeqnYfr3BNGZHHHGEWDYeF1xXpsTKLZXM7fa5z31ObC+mOMu9VPzhD3+w5s6dK7Y9p+XydZeGjmmQjj/+ePEb/C439U9DQ4PYvtOmTROlXJn65+STT7Z+97vfdZkH07Dxu77gvLnf8uluuZgKj6mpeD7wt7kuPEbyy/bmp3Lrz3Zz2LNnj0hBNm/ePGsgPPPMM2Kduf+Zlo1pybpbh/vvv99aunSp2O9MnfSDH/zA+uMf/7jPccL0fkw/x/MuN/UYU7kxrRJTT3FdjjnmGOull17qNk1Xf/fBUFK5ke985zvWlClTRMqn/PXoz/npXD+6o6dUbvnnoZP+Kj/t3i9+8Yvs9YbHAK+r3C4spdsXLJPMdJJMycVlP+ecc0Sazr5SuTEFIFMD8jrA32U6y7PPPnuf85upsJxjJneePZ0TvaVy43nAVJo8L/mbxx13nPXWW2/tM/3f/vY3cXzyN5lqk/eU7vZzT8vW3THNVHk33HCDNWvWLHFechmuu+66fUqP8ze6S6nYU4q5fHjtYRrAv/71r/tM393x09Pvcfnz05P257rW3/tXbyW9+3MfGu5UbpdkUgN2N+SfL7yO8XzltaWoqMg699xzrXXr1u0zT37mpK8dbSj870ALdInEiVDRstBds5Rk4sFIGaNNjF45hS3GCjyO6bFnwR12fBurjOV9MJKwBYqtNbR9MJorGVsw4k0vNVsRJQeOq6++WtgIaa0YbZFj6TmWSCSjEl40mZqLTZRjDTa709tM68tYZizvg+GCleLyY0isJMdm8v6Uj5aMPmiNo60v3yct2X+0tLSIfhm0Zow2YUxk5FgyapCRY8lYh/59ll9mtJg+SafUr2Tswg5MLBvNPhn039JDyiwf7F3PiNdAS79LJJLRj+yQJ5FIJMMEO7k5aRDZmU4y9mEaM+aSZqciJy0kO1yyA5YUxhLJ+ERGjiUSiUQikUgkkgzScyyRSCQSiUQikWSQ4lgikUgkEolEIskgPcf9SNnDksZMPD8ae1RKJBKJRCKRSPqGmWeYopKFqVgFuCekOO4DCmN2xpBIJBKJRCKRjH1qa2tF5d6ekOK4DxgxdjbkcJaaHE2RcdZ9Z0L73p6iJBMPeWxI5HEhkdcMyXi6n7BsOAOejrbrCSmO+8CxUlAYj1dxzCT3XDcpjiXy2JDIa4ZE3k8k411r9GWTPfBLKJFIJBKJRCKRjBKkOJZIJBKJRCKRSDJIW4VEIpFIJJJhzQig6zoMw5BbVZK1VfCYoLVipG0VmqbB5XINaR5SHEskEolEIhkWKIjZgT0ej8stKunywESBzDRqI50Wl/NnJorCwsJBz0OKY4lEIpFIJEOG4qetrQ0+n0/kkfV4PLI+gCQrjtPpNNxu94geE/wdZsXYtWsX5s6dO+gIshTHEolEIpFIhkwqlRKvkyZNQkFBgdyikv0ujgnTxW3fvl3YOAYrjmWHPIlEIpFIJMPGaEjVJZm4KMMgvuURLJFIJBKJRCKRZJDiWCKRSCQSiUQiySDFsUQikUgkY4n6NcDaf9uvkmHjiiuuwFe/+lXxNz2rbJ5vb28/oFv4kEMOwR133HFAl2EiIjvkSSQSiWTgNKwFWjYD5XOB6oPkFtxfUBA/+V0g1gIEyoAVX5fbf4CceOKJeOmll0Q+XIcf/vCHuO2223qc5tJLL0VxcTFuueWWwe87yZhBimOJRCKRDIy27cAbPwdizVKg7W+aN9nCuHIh0LjOfkCRDycD5gc/+AGuvvpq7C+YqYGZE0Y6U4NkeJC2ColEIpEMjM66vQKNrxRokv0DI/WMGFMY87VsjtzywwSjw90J5l/84hf4+9//jl//+teisMTixYvF50wVdv3116OmpgZlZWU499xzUVdXl52OQvjWW2/FkiVLRGq7SCSCLVu24JxzzhHpxmbMmIGbbrpJ5Id24PjTpk0T8/v617/e6/LSbkHbBZehvLwc1dXVuPvuu/HCCy+I3wyFQrjsssu6zH/VqlU46aSTUFpaijlz5uD222/PfvfGG2/g2GOPFd9x+T74wQ+ipaWlS8T9uuuuw+mnn45gMIhly5ZhzZrxae2RkWOJRCKRDIyiyVKgHSgYJaaVgg8kFMajPGp8+Z9fw46W2Ij/zoyyAH5/yeEjMu+rrrpKiMp8WwXF6+uvv47nn39eiNmvfe1r+MAHPoBnn302O86dd96JRx99VHzP6oEnn3yyEOD33nsv6uvrcdZZZ4m80BSxTz75pJjnww8/jOXLl+OGG27A2rVre102fv/xj39czOvPf/4zPvnJTwrx+swzzyCZTOLQQw/Ffffdh/e+971inFNPPRW/+c1vcMEFF2DdunU47bTTMHv2bLFcTMH3/e9/H0ceeSRaW1vxvve9D9dee20XAf3Xv/4VDzzwgHhAuPLKK/G5z30OTz/9NMYbMnIskUgkkoFRMhM46Trg6Cul5/VAQEG8+D2jXhiPZhgBpdh1hmg0OuCiFowk//SnPxXiltUAGQVm1Jblsx2uueYaUS3Q6/UKUVlSUiLEMcefPn06Pv/5zwsBTRidvvjii3H00UeL77/97W/3WUyFEV6KdxbXYKS3s7NTCG2Kcf7uCSecIIS9I2yPP/54XHTRRcLiwejyxz72sezvH3zwwSJyrGkaqqqq8MUvfnEf4fvhD39YjMffu+SSS8TDwXhERo4lEolEMnCqlgCTlsotJ+mVkYrmDpWbb755SJ7j5uZmIagpNnN9xBS1FMe0RhAKYAdmwGCkl2LcgZYHZ1xaMmhdcKBIpfDuDYpYh0Ag0O1ntHM4v//ggw92+X1Gs4877jjx9+bNm/GlL30Jr732mpiGy5bbaZHQuuHgWEXGI1IcSyQSiUQikQyg6h8jsxSer7zyChYsWNCv6SiCaZd4+eWXux2Xkd4dO3Zk39PTvGfPnmHbL/z997znPbjrrrt6TGU3b948Yc+ggKYdgz7siYi0VUgkEolEIpH0AqOxW7duFXYKIZ5UVYhJRlodGwU7r7FDXE+cffbZaGhoEHaMRCIhorYbNmzIWhdoi6C1goI7lUrhxhtvHLDdozc+8pGPCF8z/c4U3hzefPNNESkmtGSwo11RUZFYpx/96EcT9piQ4lgikUgkEomkFy6//HLs3r1bZHJYunRp1ppBf/CKFSuEqGRUmJ3veoKZLh5//HE88cQTmDlzpog+f+hDHxId5cgpp5yC73znO6KzHO0UtDXQFzxcTJkyBY888gh++9vfivlT8H/mM58RopjQP/2///1PiOPzzjtPLMdERbGcxyBJt/CgYTqUjo4OccCMN3jyNTY2orKycp9mI8nERh4bEnlcSAZCLBYT0VWmNvP7/XLjSbJQajLXMzvyjXSuZ0blt23bhlmzZsHn8w1K040pNcT0KMwPSF8ONy79ML3BpgqOlz84T2kSiUQikUgkEsmYFcf03jCFyK9+9asBTUdPD03tzsAoqUQikUgkklGMHgPibfarRLIfGVPZKs4880wxDBSK4dzUJRKJRCIZBurX2OWMWbVN5tyVDCcUxJ17ANMAVBdQNAnQ7FRlEslIM6bE8WBheUVWiqGxnUm1jznmmB7H5XgcHByjOv2XuSUYxwtcJ3qBxuO6SYaGPDYkvR4XFMZPf98uH80yxiwKwtzHkglL7n1kyN2Z9KQtjDUfoCeAdBJwSx/zWMbKHBMj3dWN83d0Tb626a/WGdfimL0xb7vtNhx22GFC8P7+978XCbaZJoU1wbuDvU9ZsjGfpqYmYfIeb/BAoTGdB5LskCeRx4ak39eMji1Q04VAxUKgoxao3QIo0rI2kWH6MR4fTBHGjlfdQpFr6IBLA9zenmemaIDLD6QN+xUakE6P2LJLRhbLskTqOjLSHfLY8Y/HIVPr5RcxCYfD/ZrHuBbH8+fPF4PDu971LmzZsgU/+9nPRBnFnkpKsmRibuSYibNZonG8Zqvggcr1k+JYIo8NSb+vGaEaqFsjQNPzduR4Wg09bHID7k8a1gLNm4HyOaMias9sFbxnUpB0K471OBBrBMw0oLqBYDWg9RAN5vQuFTCSgMvb83iSMYWWJ1ZHAh571DNMlZefrSL/fY/zwATjiCOOwPPPP9/j96x/ziEfbujxKh55oxvP6ycZPPLYkPR4XFQdBHXF14CWzUDZHOk53t/Q1vLU9/baWlZ8/YDvg9x7SLfRQQpdCmPHKsH3nl58xOI76TMeL5FjJXNMjHTk2MlM1p2u6a/OmXDimNVg+qpVLpH0iuyEJJHYUIzJjngHBnaEpDCuXAg0rrMfUoZrX4zUNY42CnauozDma2+2ConkADKmxHEkEsHmzZuz75nkmWKXFWumT58uLBGsYPOXv/xFfH/LLbeIJNCLFy8WfmF6jlk6sbcKNhJJnzeNJ787qqI1EolkAj74chl5DaIw5iuj96P5GsfsE/QbB0rt9xTGMvuEZJQyptrRV65ciUMPPVQMhN5g/n399deL98xhvHPnzi6dA1j3/KCDDsIJJ5yAt956S5RuPPnkkw/YOkjGUbSGr4zWSCSSsY8jCl/+jf3K96Od6UcBC88e3of0kbjGOWnZIk1ArHWvMD4AeYxZwtkZXC6XsFE67weTKna4YLIABvT6y/bt24V1oL29fUSXa6IypiLHPHh6SwFyxx13dHl/zTXXiEEiGfXRGolkNDKWIqmj2aYw3ORHd2tWjO5rXLqbtGzkAOQxZgt0rqY4//zzcfXVV++7yOm0EM8j7Y+VjE7GVORYIjng8GbJKM3RV0pLhWR8MxYjqf2F67L2313XaSw9+A5XdLe77dDTNa67cfuAwSxmsIilDMQSKcQ62uxXvu9sQywSQUy37Fe+57hDGIaaP5dC+NZbbxU1EQoKCoSQ5me0bzowuktR7dDY2IiLL75Y9GWaPHmyENq5tRJyaW1txXve8x6UlJSIwmTLly/Hjh07RAv3c889h69+9atdItg//elPMXfuXASDQdTU1Ihly00uQKZOnSqm+fvf/y7er1q1CieddJKwm86ZMwe33377kLbJRGVMRY4lklEROZOdkCQTgbEUSR0OT60jCsdC9o3hEPK9eYvzr3GD9CHH43Eh0Gws8Q8iEMv/LOYFtF/5XmQRGFqUln2SAoGhRZ/vvPNO0S+JacD6SjtGMX7uueeKwmJME8v1vfDCC3HTTTfhO9/5zj7j//jHPxYRafaNop1jzZo1Qvj+5Cc/weuvv75PFHvGjBminxQF8NNPP42zzjpLWEn5e6+++qroU7Vr165sBeD6+nqceuqp+M1vfoMLLrgA69atw2mnnYbZs2dLO+kAkeJYIukJ2flu7DCRmv/3F6M0kso8y+xgTSGSSCQRz/xtv09kh2QqmS0G4EwnqvvtfA3YsgZm4SQo4TVQt98OddoR2bRPLheHjVDVzdlmdec7Z6Ao4rxZ1ICD83f+eJyW+fEpEBlVHLZ0mcMh5Afy8JM/7pYnB3G+KTna1xHKme2RFcwHHloxua/62w9q06ZNePHFF8W+pTD/2te+hiuuuKJbcUyxzcIUnObggw8W1Xt7gwLXgdHg008/XYjknqr8sn7D8ccfj4suuki8ZwT8Yx/7mBD8sq/VwJDiWCKZaJGz8YZ8iBmGUqu2Vsm+52v5YuCE66C0bIZVNgdm6UJYyTTShoF4UkdnLAVFVWGaHH/vPPg3RaiRNmEIQWrASBtIpBKIhMPobG8Xr5FwJzo6OtEZ7kB7eyc6OzvEZywiEY/FkUwmkEomRRN1koI3mRCvrL42JMw0VD0CWJuFODO1RljqP/cZbSBSba8tde9U+R9ROM2pqcGcOXNFJLCqqhJVVVViYBEmCmmxrpmBAp9N44z6dZd732LRj6olg/fE9ufhx3noFCuQGZeV7TY+Yle56yOK7Pf7u2SY2ts5rz7Ha1w9bF5j/t5QYeargXSKY4c47qfuKsHl85WvfEXsV4pXVpl8//vfj+9///s9LjetEowq83d4TtE6wmhxb8vz4IMPZiPJhMty3HHH9XudJDZSHEskYyxyJhmfDzE9itTMB44AtcUoYJjO+DnilDdmEzAtyx5MIBaPo7WlRUSsWlqaxd/tbS1obW1DW2uLGMKdndnopxNhtf+23xuGCTP3fVrPLEtG/BoGLIvj2NP2uI7DvM0Y2fV4vdA8PvHq8Xjt95oHHp8fbpcbimpHLBXFjuRS0Hv0TnjSEaTdQSQ9RXZEmeti8dXKrhdXku+z32XWUXGiwy6XPagu+3e4D8R+4bj2a0dbKxp270R7ZwQr33hLDPniuau8VboEUlVFweQpUzC7Zg58Xo+9L5ub0NzcLDIy0W/KpnkOhYVBVFdXYebMWZgxcwZmzJgppq2uqspaBEQk3PlNZruguGaHvvxzJv+hc+lF9rhtO4D1D/TrfONv7WNziCcBn2dv5zyPC/CPnkIf+dF9eo8pSh2YFcuB1XMrKyu7fNYb3Fc/+MEPxMBUtOeccw5+/etfC89x/u8y89Yll1yChx9+WHicWfWNtgvHV91dKwSXh57mu+66a8DrLemKFMcSSU+MJQ/iROYAPMQ4AjVXxNp/ZyKnhi1ODWuvUOV3FLTib87DDrOK8R3SBsfbO74zbSwWRyQaQTQcRjTSiUg4IiKs4Qg/60RUfBdBNBpGZ0e7EGTOEI/H9v5CVmgPDvu+LFR4brh0X2knLKW5a2YTKAjCX1CIQCGHIvE+UBiEr6AQPv4dsL/3+P1C5HqF2PXB7fHA5bFFr1vzQvP64GGJYk0TQs+lUvApYlulxTazN7C9mLa/VXykWFAsRfREF+Nkv8lbz8x+5ToKJyz3hWI/eBis9MWvMmtLjWJm5mIJC23m9zPzYfQ8behoa9iDpl3b0Lx7Jzpam9HZ1oxwWws621sQaWsVM+Q6uzQPNM0Ll1tDuL0F8WgEW7fvFEPXJbSXIBJvRX1za1ZgiwcAe9G6fFZSWo7SsnIECgoQdOsoi27C5AIL1RWlqDpexVHvnoLioiJoLgWaS4Wa/9DJ7bj4PbZo3vny4M+3MVYIZNmyZcKuwA5wa9euFX/PmzdPfHf44YcLQfqNb3wDX/3i51Do07CzrhHvbNrWbVq4//3vf2Ja2mxot8kts80WBPqWHdgZkMcgxTeFMCPC9EJ/8pOfFN+ztYGfcxp27CMf+chHRCe+e++9V3ihydtvvy1aW7iskv4jxbFE0huy8924eIhxxGxP0Vjxdybqali0AziR2L2CVgggRmVzxBQjqmlH8HLcTPR27++aiMeiiEYiiETCiEWjQuDGorQVhMUNMEzBK/62BzG+GCeCKKeJRWGk013Wp09xmyeCXS43gsWlCIaKUcTX4hIEQyXZvylUbb+tKztYQlkxImpHRV2q/bnbpULRo1D9xSJqKqKoCqOojMyqomNVyqRQ5bayI7W0LyiKC1bGhiEeGkwTSYNRaUAXkdquMjVtmkiJSGxmPdIWVANQkgqUSBKmxcFCivvAsMTQ5UHEsqDzczFvwKup8Gsu+NwuBDwq/B43CrwuMXgoBhUlG7kXIlusgC10hRTNiHCXIhaly3fIfO+UyHXE9971cSNUOQ2F5VMw81DArahiPmZmOSnonfmJrU7Fz4csQAjopt070Vy3U0Tv/UWlKCwuhY/7TPMiGY8iGY9Bj0eQiEURaWlEZ8sedDTtQWfjHnS2NcJKp9HQ2IjGpkZ7/kYSbiMOS3FBsepg3v9NuK//MY469kSc8u5zceTRx6MMk1CtheCufxtqQTlURwQPNWhACwXTtjGd2xgoBPLLX/5SRHBpVaDXl3+/9NJL4jueDxS8X/3Kl7BwycHoDEcwfepkfOpTnwK6Ece0mFx11VVoaGgQUWR6ij/96U+L79gR79JLLxW/c+yxx4r5fv3rX8eKFStEywzFriN4Ca0Y3/rWt4QIZwsCI9Af+tCH8Mgjj4isF1wGnmMLFy7EjTfeuB+32PhAsYaa+2Scw+hMKBQS/iA+6Y03ePIwFY3zdCqRjKZjw46i7hW1Zq6VIEe4OqLWzLUUZC0IXUUXRQwju2LajD2BIjeRjNve1nhMdO7q+ncciXhcRHDZxJpIxHM+pzfW/l6IWUfURiNCDO+9xDpxPPv9gC68IoipwhcIiEhrgNHXgkI7CltQgILMZ3zvLwghWFyMUEkZiktK4fYH4QsUIG1CCMlU2kQybWb/FkPO57phIq4bSOgGUoYlPudnzng636cNpDLzs/fB3n01VqEeVR3LgXi1/+arkvPKwS062+0dPyf/QpcWASGmVQWaqoqILB8s+Opxq/BpFOWKEOtetyoGfq4oPLaVrNAm3MYpdv7jg0LmIYLz5ddpPhxgrxrnC6dS+EZVxENOcfNb8DStwx49gGZUoDCyDTPqHxVe790RYGVLAI1O9FkBfIFCzD/kSLxr6Rwcv7AU7upFsCqXIOTXEPS5UeDXxAOFx+0S20Csm6pCT8ZRu3OHSDs2HP7fMQMLmbDAiWMVKawA/CUHeqlGFVamEysj5SOdO5q+btpW6M/2+XyD0nQyciyRSPabn1YIUTYzm3ZkLituDcAA/ax2JM3d9DbcrZuRKq5BsnwR0noaLS2taKbXsqlJRFspXlOppOi0pac4pERHJn7mvOff4rNEUnTocjp4OdMx4pJKxMX7vtehmw/7eY13uzUhXgsKC+HzFwgbgd8RtYFCBIIUsEF4ORQE4fYVQPMH4PIEoHp8MFQNuuUWYlQI24xQdf7ma1PaEK8JftZuItnC79qRSrcKcTsU3crVpHBjczsFHQe/1y3eu117RaSLAy0OKrfXXjHJzx37gzMI7ZbznuM4gjPXqpLvx83+JUQkhOCksMydj0u14FIymSfEQkCI/YRuZl4NO9duig8A9vbjZ3b02X7AEi0JWdFvP4CpRhKKqSOtaNAVLePr3vtw4Ph5HSEtjnMRve7/1qfQLPS6xVDkc4vtq6mKENM+t729uc+FpSOzSWxbid1yIfzh/C6zqabpW3Be7B4U+joQDYRwf+ml2KEdAdU4HAv13ShWJ6NAm4323Zux/fWnseON5xDtbMWq5x8Xw69dbhRXTUWgqATBklIsPOIEHHTU8Qj5PGL5Cv0eeF0qyqMbEIjtgRGaCz3WDrdiQvX4hc3GPg5GRzaKEWGMWUUkfSPFsUQy2jnAacqEOMixJdhiwBYERo43lt8zimWLXed7027eTme+yzad2/+HOzrQ0tKEtpZmtLW0oLWlCeFd6xBb/yRa28NojFrYkw6iLTy4BP/ZWG1uitU+RqbP1esPwOf3w+v1iVf6XrXM4PP5xavLF4TqL4TiDUBh0zCjRh4/VM0HRfNCcWmwVDcM1Y20aQsaCtckRaxuoj1tokE3hLWA35kp1rwHkK0Gy3hgZ2boG7dqRySdCGSBx4XigB3hC5gRFFpRKN5CmP4S8RkFjZeCS6PgtacRQ0ZsOn/b0Uw+vGSiloYFNdWJtCfYo++Y9gUKxKKO9SiIbEN7wUy0FczLBDf37kdhp8gcK87+EWLQpWYeouzfzO/ix/GECFUV+zsunGKJ90KkM2IKRlv32hUoNrPR4YyYFNGsnN+nBSOdtkS0lcLTmR+FeKh9A47Y8Vv49XYkPMV4Zfqn0FAw1xbNmfk6pNKGHcHN+ZzHPtc3mjSyDzSJzLHASH08ZR8L4UQakWQau9riA36g4XqL40A8wKjieHteL0S7+0gs9TXhKOMthOI7ELOm421rGta7Ztgeed2AVjETC878GGpO/TDaazchsfZh1K1bhYbmdjTv3gZwAPDOi4/j2VmLcOgZH0DljNkoLavEHGsH5tT/AX430Lz8K1BZItqMIuGvAjR/lwcXbtNxxxizikj6RopjiWSCpCnLFbV8tee/FkrLJpilc2BULeniydX1NNqiSZjeBCxkPKR5ApWRXwoKimHqEFoL2tkRrL0NTc3NaG9ry75vb21GO7MjtNiv/JxZD/JhdE7VY0JYKmYahluH5fIKa0eopBTFpWUIFoUyWQqYocBjZyqgeNU8Iu0VP9f4OYWuzwe35hFi1eX2QPPycx8Ut4a06kFadcNkJBBupKAimbZERJGCJZZK23+nDCFq2pKZ93pOqiYjMyRy14LCtqtPmOLAaT7n4Kd4ZfO0I0Q5MJNCzntvvlgVzfG2d5biVxORRNsz63hYHduJQ2H7esx5+3fQkm1Iukuwfu7n0Fm0IPvEwOWwO7HZIlTs4sx32ewZjNCKUC9XhAeCCq/HLVY7dzoVFLa27SDYvh4LNtwKT6oNKU8J3pn/WXSGFtibLPN7LkuF6mEE1Da/iOUX1hhuL0aD7XlS+PL4oqwSUVIRjWRM0o7WOmKY62GZ9udcbiZCcLSYeIDjNBnbQxbNXi3G1vkbamaddY7PDpJiJAtzIq+hLLEdrQVzEEg1o0Lfhah3IVLMdCHEecbOoNA+wYfBvAPbBXhh7ysnkOx0nmMmDH5GIc0INuFre1xHMLoTWqIFe5Ry7DZKhY/antje6BTndisMWxPos7ZfI0k9s+wu3KcfifvEqXY2EOak7SgOuEUkWhyPwt6hYstz/0FkzzaUuJM4RNmIkxZZKCyajpeLzsCuZADh+h3Y+erDaNz2Dh79zfViIVyahukVQeyak8LJRx+C4oxXWkkn4Y43wUq4YLoD0H3FYv0o3jUzCdUcZ0JSPCCPk3WRSHEskYxq8nqMW82bhfcvv3NZbpov27Kw1wvK97atoauw1ZreRujlH0KJtwL+UnQceQ3iJQtt4cIbrqGjobEF2+ub0dnRgY62NnRS5La1ijKoHPi+o53i186QQKsDyff59kYwGEJJWbkYKHwrA8Ds6Ouo9KVRUlKK+LLL4Zq2HAVFxaIDTGHHeuGZjBXOQmtwXjbqFsu8RoWQTQsx25GyX6MUuTH7NZK0Ra9uULzG+1w+Bv4CFKNet/BbTgr5xN8Bjy1QKS7ZuSugqWI8zW0LII87N5LrEqIAmcgoP+urmTn7MJPjY3WKJziRTi5Dd7Nx/L+cPhTfDk+qHdHQPBR0bkRZYidQuTgTZbSXw8604HiwbQtGbsfFzE61MzGICKgbLr9mR3DZ344WiowH1pmkorkW/nQHosXzxe9Wp3fBHVgqlCgtDxT2FMV2Zz97JUTHPmHDcCK8meObipbh3My6i4wR9kayhXm2Q5x97Am5nZN32bFGCCduzkrZ39nRZwrUvWlH7Be7ZcSCv3UdatpfRCDdgUDH6+gsmge1fA5KAh7oWWHKFHf2NnTBharYBgSj29Hqm4HWwnmi3gVFuFdzZzp8ZvJdCFHtsqPksMTDBfWvz61genorTor9AQXpDkRcRXi44uNo9M+BKqwsiog888FULKtIQbe3RUe0VKQM7Ikk0dweQTjt6rIr22JdH94Ec04D5gCtpoEnIs0wO+phtdXC3Loe3mApqucdjGOOOgvbnr0XLVveQqK9GWk9hZ27G/GrXTH8d4sLPzkihfJYEv4CFR7LFuiW3oEojxtvMSwrAVe8EXyiUJhqjxFXKSolowwZOZZIRhFO9gNboFpAcCY83hIo9W/D9JUiFpiOdDSZFUSiWZg3HTHdXgGlJ5N2ei+RJcHuIBZlpoSc19SOlUhtew0dCCLWsQ4tf/gMOlBoZ1SIhBHu7BC940UGgjx6c7DSX1sUKhbZEOzsCMyKUCLSSJWUlmWFcElZBQpDJSKzgSNoY5nXdPsu7Ai34k21BB2pEKLvhBFNtiEeiyAZaUPYKELYisDEm/32cRZkshNUBr0o8AbE+wCzFVDcarbApdDle4pc5zNbyO6dF/9m5gMKy97IFajZjlr2F+IzRontvZWre/duVzY/F7ath79zK+JFsxErWbj3O8UW3rQfOL+VmXWXByfiKp8HJVCK4uhmGAXlKJy8AFrIiXB1vx8d/ehkXsjmxhVCzkS4PYGy8qCd3zdjcRAWAtF0zhzACty+Q+BpeAhF8W1AaTVCBy0HqiuH3Xuamx+6uwfGvdtlby7o7sYXx3Ted04hN29nA/yaBWP6sdBa18O7+CwsWXaciN5yvGx0Wjw4GFAa3kZo6x+hxluR9pWgbvoX0VG0wBbbFLAiNxyzXth5lYVQzkT+afOgqE2ZBiYlGlGqhNESmoviyGbMczfCDC4Rx484DnWX6CApOutlPP20L6mZhxXuh9leN2aU+MUDb1JPI5IyEU6mRVS6M9F9sQqRoaSoCmpRFTDt4Ozne/QkarfugH/WUVhwzPtRXBREOtyEjh3r0f7mA0im40ilLTRELDTFDZT6gFIRobag6DHE1EIEmCXDSEN3+eA2krBSCbjc/vHtSZaMOaQ4lgweWbK3X8LISS3V5QadEcL0IDoddnjz2ifeWjgf2uFfhta+FXrxbER8s7Bn/Ubs3lUrksTv3rUbe+p2ob5ul4je2hkSIqIimaCX+w0tC2oqwh1JeQND0wHVLhSQS0EwiJDIflCKUHEJikVKsBAKikpQSPEbKoFWWAzFF4TlKRCdx2I6vZWM2qbFjZjR253JNNYxwlufRmynjliqFsn0jl4OsIKMCbdJvPNrKoIuHcVKEhV+HSXmLrhLp0EtmSEiqIGMuM2N6Bb7NBQFPEIcDwVHUDlClzdyRj73jpD9Lyfaujc1WLZzmaWAaU0ZWe5NDPD3vM3voHr1LXAl2mD4StB0+JehVyzemzUhk1PY6fTmeGltX6fTQU4Fyg6DFfo6zLatsEpno7jStuU483A8oI5Xl5tKNPdnmvydxXSWV2QxMeOoLA70nsVkxqGA95sjnifcXtbsuxH5DUxfDGyuAGLNQMV8BBedhmCoay/4LtTVAUYnMPUg0eJT5GmCNfuYLlk9hL85m+2DvnxbWLNzKq8HCT0NU1kENJehMrENqYIyEa0uD3pR1LZBtJ40aNPQEJgD3VCR0u1jM2mwiqH9OylFsa8tUJBImaITpdcDlBRomGL6RIqwuG4hkkojHLdbX1K9dCCkl16rnicMQ3VJoK4pAStuweUqweTzv4mZRYA3EIBbU0QUvSXGQUexX0VRMAWocSQUDV6ocBkJ6IoLKcMFJZm2O3dmWhH6JZRZaW8oHt+hTi8Z10hxLBkcE7xkryOW7IitnXUhmw83R+Tmi11+J6YRHl37u6z4yJT6bGqsx55dtdhTtxt1u3ahbnet/Vq3C82NjflarEd4g2FGBJHqK1N4oSCTMUFkSCgsREiJokiJQiudBqV8Hnxi3KDokKb4CpFM6Uh7Q6KTUEdcF9EmvtbFMn93pNBer4ucswCH5h6Xh6KNkVuKVzZHTy7ORGkzwpbfsdNU0KeJz+1x3dlX3jQDbesw/c0/wZ1sQ9pbgp2HfAGxkhm9bgfedNnTv8cKdM77nEhj/kbe2wRueyYdW0SffQQVO2rtWBgc+0DeKNkiFo5Y5bbSmurgpcCavARK8zoU8CGm4ijbxpAnHvoUE4UsEmAXCtivjJc84QPN7dtNYRrhjc4pfeexc030ztTjgWklSNZvRDQ4AwtCC1Cz6y1UvH073IlW28u94LNoLpgrBC79yCndthZReNNmZLsurKwFgwM7/nFckx5ot4mg342yAl647AO6Mr4VR0afxDa9FGHLi7AaQpEVxtvGNKyzup5vir8Ipr8Iu+KA5XbB0grgL5kEt5VCItKJRCKJ9riJzmQnJhfrSASq0eoqE5aLtOKBYWjwpAzoLjPrR+a0KjvyeXsQraIE9Z6cEtQDtGYMdXrJuEeKY8mELtnbU2c1s6emWssS2QaEuO0u0tsL7GDTGY6K0q8tzY1orN+DPbt3oZ7Dnt2or9uNxvo6UZ42Szeaxx8IYNLkqaiomoyqKVMwecpUTJoyFaWl5V0EsM+/N7JH4c4e8BS2nRmB25lIi7/rKHpjKVv8tuloi+mIJFsBcCD7lkZl553igAeVRT7MrQqKrAgciryaELv+jAjOWhQ8bhEt7U9gj8KQ4lNYEfJEq16+GHXLvghf5zbEg7OQKl0o+ofl2xPsFzvPrGM96Bph7GHj5pEt/NCDuBWdxYSH1hY+dmoy2zfLGz3fO9FdZ358vzeXbi/CdvICoLAcaFkPsAhD5VzOtO8NKDnwQn84q2tWHwQvBwClPCfq6mGZnUhNWgytaR1qXI0IVixDPJUWYlhEnYX/2c6Gkcpcr5ysKHaxGysjnG0LB33T4pUCGgoWpvfgaPdGLPSUYGFqNTrVIiSUAJ3RWKUsRUPKg4f0ZdiaDCEBDWmtMLu4uglEDBfcnmKUlnowKdmEhjBbiizsaksgaLYDhZVIKl77YZA2EtOAaijwIQWv3gTFMmCqbiQDVXB7A9lzKnuuMOJLYevkFeb7gYjboU4vGfdIcSwZMyV7h4PcCK+R6+3tx3QiD2oP4zJLQ1NToxC+TQ0NaG5q7DI0sTpVY6OofNYXbs2NqkmTUT3ZFr0UwlWTp2DSlGnib1oamKKJ4rY1wqiMjo6Yjl3xNCIdOsLJMMKJVhHtDWcEMIVxX2sZ9LoRCmiYWRYQQpcJ/wuUNMqKgyii8PVrCGUiux7N9prm+l77S25Hs56itUKMuvZ2qsr5ClbVQYhX2WKjuzIDFKTMC+tixLaH6O7eqma2pzZrQ8hkfXB61TvFHvaW47UtC/vcrEcCWb58bNvBBhM172vZ6tdA7awFNA/8bRuBokpMrlmC8rIi8dBOWwQfciOJtF3ERTcQ4XVLN8WxmmAHRtE5AUIc85gW2TbYopVm2kU7a4Y3sADW7udQpbej3jcba3xHoslViSMiT+AgcxNm+IpQW3US/OpM4Zmml3nTm68i2c5Ofyuy18wm04+oqwrTShrR0JFCWwKi+IInHkcgVArLExQZT7xmEh5Dh8vSATONlMsLt5GCmUogpnjhVs0uObJVl1f4ogedV7iHvMRXXHGFKBDxgx/8ANu3bxdFJNra2kTVugPFIYcckq2ed6A58cQTcf7554vlefrpp8Xf7e127klW6jvnnHNw5ZVXYjwgxfF4Y39e+IcrMjKCiA4ymST/fBW9xHN8v/mdcxysnEo7jfX1qK2rF9HelqYmtFAEtzShpbEx+xnL/ubSo2RSINKOlVdUoryyWojd6slTUD1lKiqqp8BfWg3LF0RHPC0iuIzotkRT2My/30mhbeUWtMVSe9M59QCFG0UssytMK/ULYcu0YRS/RfTh+mzxW+R3i8/5fb7I5faIdbQgECrrUQRy+7odIZsndO2/8ztFAQpFa17ns+zmYScjZnvoI0Lq7CshYjM99+0oMf/ORIqdTAqOLzfzId9nbQyjvTjBeLEljBZGsx2st2Xjd5ufADY9Chg64NKAhWcDNSvEOB4+qGouBP1AVZFfnB8ig0vKQCSREh3vOhO6XU1PRJAtFHhZ+EQURUdSN2Bo9C2btmAuX4SV3k+jOL4TjdpU7PbPQSSuIxydibJELepdU9CmzUZQWDNMkY1l+buOg1W/Hla0FUanD+7SyWLRY/Di9g30Z/vgMWJIxSKwrJhI6K2obrg1DSGPKdLuEZGeD50woSLG64AaEQ+pzgMsT1qR0cRURNo9ke/P1YbzDul/5PfEU88SJaA1bW8fix/+8Ie47bbbepzGKe18yy23YLSwZ88eUSZ65cqV4u833nhDiOkDwUMPPYTxhBTH44n9feEfJTdup5nQSUHm5FDlBT/Oi383oUNWSRNR3UZGdRvsiG9jQzbKa782IJKJ9PbH4+vx2aK3rLwSZRUVKOVreQWCZZVQC8uhBkpgeQsQM1S0RlNojdK3m8L2mI62Oh2RbfTsdt9BjTcD2hhKAhqmlwaywjZX5Gb/9mkiC0Nu8QGxTWAJGwAtC3YVsp4zJfQXRmcpZCmOB4tT+EH4DZ2OapmKEHYmBEfM7rUiOJ3PRpWwlR1URz+j2Q7W07I51/Xmjfb3M48DIg1A8fQel53nRYDpBr1u0YGP8BoZS7BlSc9mh4kn7cgyr5UsRpLS0kI48xoRcy1ErGSBaOEpMSwUuF1IBRZje2q+6PBXkLY7/umGAbdqZ88IzlqIgpAHXr8fqdZaOw9yqCq7XClXAAgG7AfVZBRWMgo9aaAlaaHQ70WRh10HnZXItDIx/7RpimuEyHutZFIOKm4oqga3qcNlRG0f8QCsEYwOMwK6v2DpZKaiHM5rFm1zZ5xxBr7xjW/gyCOPHLb5SqQ4Hl+M5gv/MAkNp6c3fXR2NJjv7aZAOweqLfE6O8PYsn2H8PHS17tnd63t763bjaaGeoTD+1Yd6+mSxUhvRWWlqARVVlEp0pDxVQzlFSguq4DlC6HTcKOhM4mGzgQawkls6Ujgxc4EOrezbzeXKtfHa8POZsV+D2aUBVBaoKGUArjAK0QwrQ32e4+IAOdW4BoIospXztpxW/F3u7tI50bSTfacd9sV1Hjny33GoF2BNytRPa2HLdfd4ub7d52os5MVYVSJ3fESkZSMDTtYT8uWva4vArY/BzS9A5TNG/Cy83wLBjxiyA0qMGtGRGSqsPsihCmg42mRSYeRZD5YJ0XlQL53odDvRlK3EE+67BzjugK3YeZULVThKyyCP1SGRLgdVqwF7mQEOjRRTTKLtwCKtwBIp2AlOhGOJxFLAAUeFT6vB25WPLS4HO5MoRQ7ZZ5Tclw8VDObTapT3AOMjj0iZ7LqGbx3+NKPfhjFRYW45Wc/7fL5L37xC/z9738X16ff//73mDFjBt5++23ouo7vfOc74jvaC4455hgRfZ482Y6ac/xf/vKX4rNNmzahublZ2Osoyl9++WUEAgF84hOfwNe+9rVs/5Bbb71VCPdYLCZsHr1RVVXVq42By3fttdfi7rvvRkNDgxDoDj1VHL3rrrvwve99T2RDmjt3Ln7+85/jXe9616AsF9w2nBd/65Of/KQQ8WTbtm1ivV977TXxwLBw4UI89thjYnsw9SiX+f777xcttxT/3Ia0uzCo9elPf1p8x3WbNm0a/vSnP+Hwww/HcCMjx+OJ0XzhHwj1a2A9eROsaAusQBlSx12HdOXibCcSdh5hOqm63buwY9tW8UrhW7erFnUiw0OtSGvWV7SXldLKK6pE/t3yykzEt7wCpbQ8VFSitLxCvBYGg8K7S+HbGE6ivjOOuvYE1nYksGddAs2RBphWwz7zLy3wYGpJAFVFXlQWeVFW4MlEfz0oFeLX0619gPrQ9rvaDYx7U8HtTRVmDiHaa5cD7knQ7u08RnsCb0IcnxduRxDnd0wTt6lsDty86G5epHfcMp4eTMczo9kO1tOyOdd1RourFgPzTs/aKYaCXcnPfjj1aZQCdoTZtl2Yojqm8C+n0sK7TAsGAxK2XSMNM6CJojr0KtP6xSiv0zlWXBUUFf6iUlgohbupEaqhI52MAXocYFVKf8ge1e2Bwo6nFMDJKMKpGMLJuIh6w0f/ROY6lynWIvJE0/2h8PdSomOdoXpgGTpSiRhUepTZd8CIDyxVm55ZNt1lZ7LQmUbS5qqrrsKqVav2sVV8/etfx+uvv47nn38eZWVlQuR+4AMfwLPPPpsd584778Sjjz4qvmc2opNPPlkIyHvvvRf19fU466yzMGnSJFx22WV48sknxTwffvhhLF++HDfccAPWrl076H3861//Gv/85z+F8KypqcGNN96I3/3ud+J9dzz44IP48pe/LMQn7Rn33Xef8BFv3LhRLP9ACIfDYptt2bJFCO1TTz1VPFR8/OMfF+s4Z86crBWDItnNHJeA+J5/r169WtheLr/8cnz2s5/FX//6V/z5z3/GW2+9hc2bNwuxzAcOv7+7nidDR4rj8cRovvD3A16UhQdu9zp4w81Ily2Au2U9Eg0bkAjNx5ZtO/Hqyy/izZWvYtVrL6Oxgfl595IvvXjysEMbO7ZVTpqCag5TpqKyelJG9BZlRSIv+Iz41jPq25nEa3x9h39vEZ/zppAPszFMDvmwoDqIqiIfqkM+VAW9QgxXFPrgZsaFPnN97YudIs7KRniHowiCI2xpW3CEbe6iZfPkZsSxnVbMguVzi6IZblayyhG/Yz7SO9yMlwfTicAosYP1umxsiVj7770tZ/vxuk5hyYHidEomrzWrSjIbBl9Zlro9lkRLVIdHU0V+5gKvhkQqDZgpuKEjYEXFxUJXvHsjvi4NDBwHmF9dOJU70W54kWT9bqfQECPJHAwd0WQMZkc7XJoHbo8Pbi+91LbPWFRMpE3DcsMNFaqZgoEAUpYGSzfgTcXgjTdCsdLC19xdqrbrrrsO3/72t7Pvd29em6mB7rYzWRh7xXF38FpL8fnCCy8IcUtuuukmFBQUoLa2VkQ1yTXXXJONJFOolpSUZO0c06dPx+c//3khoCmOGYG++OKLcfTRR4vvuXyMJA8WitvPfe5zIjJLrr/+ehGF7ezct+WU/OpXv8JXvvIVLFu2TLx/73vfi5/85CdCNH/kIx8Z0G/zuGEEnNHgBQsW4DOf+YxYT4pfil56pNnpkdFpJzLd1NQkHhoYYXc6QVLQL168GHfccYeYjqJ73bp1wkYyb948jBRSHI83RvOFP4NT4tjxCTPywEiEkwlCK5gJl7cETVvfwku1Bp5+5X68uuan2FW7s0skmFkdps2cbYveTKc2dnCjIGa2B0Z8CcUgow1NkaSI+G7uSOD5t9uxp7PetkB02hGSfBi5pTBcNKnIFr5FFL4+VBfZfzMnr4iSMroqygWrPa6vI1ztsr9dO6l112mNg2036E+6sWxFCPt9po8KI7zCx0tPcCbrgj1+105qPaUU48Ut4XGLqFKvxR4kY/7BVDIGLDoH6JjiuV/EIh5+DVV5HZ07Yik0Rnj9TIkMGVrTO/BYfhQaYWhGAp3uciRVD5O9QeVgOcJYhdtKo8ClQVU1qEbMzgikZAqruDQogRCDxrASESRjYeiJGDyBQjv9msWCOhTfbkTUQrhhoM1VBt1ww20ZUM04NEOH5fbDbSagdJOq7eabb+7qOWbkmNdAM21nsHDZ9pOeoIBjtdHjjz++y7XT4/F0EccUwA4Ug4wE52a/4HXWGbeurk7YExwoBh3hPRgYmc79fS4b50dh2h1cPka/v/Wtb2U/o31h9+7dA/5tn8+HysrK7HtGjZ35/OhHPxLC/5RTThHbjp0dKdz5+9wezBKSfwxyXSjQuey0m3Abn3vuufjxj3+M8nK75WE4keJYsl+gAI7rdpJ6etwcjzAFI1OSkfa2Vryx8lW88drLePOlLdi5fTssPsWr2+2D1eXCgkVLcMjhR2LpsiOx+OBD4ctrUmH6ol1tcbyyK4Zdba3Y2RpDbWtMRIS7y8JGq8PUEj8Om1GSFb3M3VsV9IkqUt0VbciHNwrm6eT1sbu0ZnvtBEq/O6dxPr2lSBPiNpNf14n2OhkY+rPMkon5YHpAkB0Vx51Fh9c0r+pCZcgvBvYBYbrIeLgdrfDBcnvtCLIrDZelIGCGobBUdiYbhUY7hDByJKHDC5+Shk+NwUQESXjQYRVAF9IYohiRy1sgRDI9zJq/EB5/gbCc2RYzSm8NCXigULRbJuKWGx64oOpxpFU3fxGaKLndy7WR4lnz2wMjzeHGvHXuej2mzYBR0VdeeUVERnveVnunowimXYJ+4+5ghHnHjh1dhGlPQrY/UBhv3bo1+56eXQrUqVOndjs+l4+R5iv68Dr3B5HpqbExK5BprZgyhW0REJ8x6k7WrFkjLBcHHXSQ8Gxze/Ehgdu2OyjeOdBD/cEPflBYTxgNH26kOJYMOyKqkCmLTFFMX1p3+YHZKe71V1/Byy++iFUrX8G2TRu7fK+4/Zgzf6EQw4dSEB+6HKGiIiH+KIK3NkWxfUcjdrTGsKMlJoQwPcG5cFxaH46YVSrEryOAGQGuCjH6q2WrnQ3EssCmQvt78b/4nGnEGKndO23326fLT4niEXYvbIphRqDtLAz7RnellUEy5pAdFcevRSfnocdTfRBK3S7EpsxFW2PErnDnoh3CD5eesKPFjBCbOgxFEwLZEIYIU0R9TT7pW7QXmwggAa+iixRwbYbfjuLy+ucPwuULIB3rhJGKQ/MH4fbYPmnRgZjR5Iz4TsALk1X4oMNUPUDaDX8yjYJMa1+PMBjj9nXrUWbnN3bCs1JRKMmIyI9+xScvw5e+9CXR4Y7CsqWlBY8//jje//73dzv7s88+W9g5KAwdewH9sxTAjBhT7F1wwQW45JJLcOihh4oObYxO9yVCHVKplHjPCDFFJiOy9BDTN0z7AkUll7OnzBa0PjCafvjhhwtrRTwex4svvijEf0+CusdNqapiXWkLoTDmOn/zm98U391zzz046qijxLIwis5OefQZV1dXi4589BgztR4jwowYM+3ee97zHuHJLi0txZIlS4R9hdFpx6s83EhxLBk2mBqIKYFSBtOn8WJlIpw0sr7beCyGNW+uxJuvvYrXX30Zm9a/I5pQiBhDAWbWzMWhhx2JQw5jdPhwFBYVob4jga3NUdzzZjO2Nu8QQpgdQHKhMJ1WGsDiyUUir++0koAYJoV8orBDT53X2PGEQpflibuja1W17kv/ClHrtr28auNauFo3wyidA7NySZfOak6UN1twYrx3UpNIxkAUdNQxFiw6PT30UNi3b4QSKIVaEIRPC8BMqTh/cSksMw1LKUTCHYKmt0MxDVG+ukMrg8tMIaRTblpwwUBS8QmRG1ECiCYNdChFtkgWVIv/jc4mYRnzFpVAVe3y8LzW0pdsC2QPUqpX2C9UZt3I2PlohxsM7Bh20fsuRGnlZEybXIXVT/wLN3/lU/jh7fdgxYoVQsQxmswOdz2J48LCQiGe6UOml5ZClh3l6PMltBlQEFMgU5gygksh2Bu5HdIc0fvUU09lxTaX67zzzkNra6v4np3tKEa7gyKay/SJT3xCRJy9Xi+OOOII4UUeKMFgUHTqmz17trjPc56Ob5mdGL/4xS+KAiv0YNNvTYsEobeYtg4KdD5s8KGE25PimNFiCnhaKrje3F65FpDhRLEG02NoAkHjOjt2sapPUVERxhs8aJ2mj4H6ShkhphBmFJfZHJxoqgMPrdq6RrzwzBN44enH8forLyKt700lQ6bNnIXlRxyJw488SojiVsOHjQ2d2NQYxebGCLY1R0Ui+3wRzFy/0ymAS/2YXV6IGeWBflVqcyLBTso30f9CZfog+4LZfTU1+0PH/5tbcMLO5JApEdywBq6nvwclbt8wlBXfGJ03tv1wbEjGLwM6LmTkeHzCzoIv/2bvQ8/RVwKL3yPSj1FUUfB1ySKgx2DpSZguD9KqD2YqBiudRCpjh1DTCQT1JrjoSbbSMBU30nAjofoRMCNIWBqaImnEvWV2AZQc0m11cLs1+Ev2Ho+ieidS8FgppFX7N50ABYulFHpc8LLK50A7FMfb7EwWlnNPUgFm3QiUyvLTOeRXz3PuvUwlx0jvSHfkpsBnujh6lxldHoymk5FjyYChKGZ+S/rM+DTuRIedLAe7d9XimScew9NPPIrVb6wSCdydoC3LIFMEH3rEUZi9eDnqUh6s3d2BfzZG8KO/rhNiOzcbxJyKQtRUFqCGrxUFmFIcsAtY5EWBaeHQ+k7skI0EO3l/KXB92t6CGdnxMhFfNc/L22u0t20LEG+185HKKJlEMjaioJKRt35oAShaQLiIVXZMdhXCMAPCC6EydZzqR0ythGIks1a1lKj7B/jMOHyKjilBFxrNNMLRsEjdpvoKxffuEjsTRLylDkXFJUhrBfBaSZSYrSIKbZgutLOznuplNjimAkKYQs20WwwH1HrHtHAU5yLIk+k4k4zYKeO6yYghGbtIcSzpN3ae4TTCSXasy1gnTEt0xGDHgUf++2/83z//ga2bNojxnUvOwsVLcNxJp2DpUSehXSvD6t0duG9XB3bcvy077yKfW1giKISZHWJ+dRCTi/29Fr7IZn/IdLRgsYquWSC6h/PU3KwU5xKd3xxvr52+LLcD3Tj1Ckok+xPZUXH8MYSHHl6rXSLo4IKWYpaKBNyqhoTHj7ThExmMnAIlvI53uMuFh5lRZnb0K/AUwjQMxDtbu4hkhCYhnIggiCjcLhYQoT3DAy9S9vSWFy4zAY+hwzS9iJq+rM2i2wqfzF6RnyeZr6EpQDKcyYmcAFh0hK/dZMSQjF2kOJb0TxTrhshDzMwSuU4cVlF7/IH/4I+3/QoNdXaaFkVVsXTZYTj6xFNQuuBo7Iy58fKudvz98SZYaMoWyDhpfgWWTA5hyZQi4Q12mlooTvvjC3MuspS0LJfMdGX7jAPb45tfmW1EkFEyiUQyURjqQ48egxLeA7dpCKHsDlSLtG/MKU+BzKis6Nzt8kK3vEIos83Qw1zKSgq+UBGiKROJtlooJXYqNMtbiE6L9ywdQcUFr5WCobiEsNasJIqNFhFNNk0XOq1yxC2/uL+xo16XjtkUxrRPMN8xvc65UWGR1SKwdxwKY45DES0R0O+ca6kYi0hxLOkVkcsynhIXECZ7jyVtz7BlGXj60Yfwx9tuxc7tdgS4pKwMF1zySZQvOQFv1ifwz+1tiL9gV44r9ms4aUEFDp1WgkOmF2Naib+L78iJAjvV4Gh3yJSh6DUKTJ8xC2W4MsLYqcjWU+7eEUdGySQSiaRvGGml+NR8UHTRfQ4uL/uOsBKfIdJ+6ooJJePKYyI4zbQFrkq7BE0anlL4yioRbdkuCo4oxXZO4KipYQsqUeaKiywZScWLQjMCl2UgpXqEF5mdAOOGXaSE9ze/xyWsfOJekrNsPUaF+Z6ieSBV+CRjBimOJd1Cscpewm0sC5rj7+VF5I2Vr+AXP7wJ2zdvEt6JovJJOOYDV0KvXIR/7WhD6rldYtz5VYU4uqYMh88sFWKY3t7C9vXQWlZCN2qgVyzet6kNdoS3x+wR/F7kAVagqXZnOIlEIpGMHpwsRL1CQcmIa07kVfTv0FRxjWdgRk8rSBqmiCCzO4rHZPZjAynFI3Ila9Cha0EEK6fCTEQQ6diNtFYoCoiQFsMPt8UiTUBK0UQUmcKYwppTi2AMxbdlZy3ibwaFzcILJW/ZusWJIktGFcORZ0KKY8k+UACLhO6pdBdh3NHehlt+9H387757xaN8oHomas7+NHaiHM9ELKjRNhzu34NTfe9gRUkzvMd9BvHSGdlosKf5HZS8/mOo8VYYvlK0H3VNF4FMqHULMp0knHRne0sb21XjJBKJZFwzRgunML8uYd7eiooK8b7n1jtVRH5FmWZWozNUwNibs1dhXxLThNsyhTfYzo6kIM4CdlYCcUVF0gWo6bCogudWDYSCCvR0J3Y1NkMJVUNxUT5DDCnFhOEKwm3pSCsa0sxUhKQI8BhQkFYUpFQF6ZgOn5qGWy20s8d1s2xZ6Dt2lp/FQyQ9sr+yVfB3WIaav8E80oNFimPJPtBGwfRssaQhvMY8jp974hH87Hs3CIGslkzFjLOuQKOnGlsMYF5VAU5fXI3TXCsxd9Od0EsXQGvdhXD7NqQr9uZoLIxuh5Zsg1G5CJ7mdQjFdkD3H5KNCHs1tdeCHBKJRDLuGcPp75hKjXlr2UGbVc6GA6dzHoMszEpkGSkoZhppuGAhioARFingnBxGtFfQPlG/uRlwa1D8e0s1uxSrS4DFSc8pii0x+GKl4TejojgJI8eKLwTFnVdGmmLYyKQk1aMMk9v5QH2hPktOT2QsWidNUxwjI32P5/xZtKSnfM79QYpjSRdoo2DOYsIE62xmuvvvf8avf3wzlNAkhM69DqnSGtBJfPiMErz/sGlYNCnISwm8zbNg1JZCa10P01cKvXj23oOVF6aKuTD9ZXA1rxOvVtmcbJlk4TGWolgikUx0xnjhFAoSVjqjEDKMvTnqh0pnjPcmHXUdcdS3x9EcSaGy6Xkc1fRPeNNRKBbNEgY61WJ0uopQbQK3P70Tz9ea8L3763uzWsDCvMoC+N0uKJmO2iw7rWkqliZfx9Gdj6HNNxWTzDqklrwf1cvO3iuymjYCr/wWiLcDpg6YaaBqMdCyFTjkg8CsU4dtfccbpmmKoh4slDLSefMZMR6KMCZSHEuyxFJppPIuZn/+7S/wx9/+Bu6FJ8N35EXQFReOn1uOjxw9A/Oqgl3GtaYsRaLwWrjbtgphrFYshodNV4qdTUIrOgTKiq9DadsKT/kcUXJUIpFIJOMrJaTTpD2UZu0u1K+Br3kTSkpqUDZjAYoLY9jeEkEkNhl6nY6y6HYoMNGuhlDrnY6IUYRZ+gacd3QNavyr8K1ffByuRaeh6ISPidntDoexsCqAkE8TAllEjXULm/ViHBSPozz2Ojq1Yqxu8WNybRjLZ5Si0O8BOjYDTW8B/lKgczfgDQI7nrLLTis6kFdwQtJVHPN4YFGOsVBUSopjiYB+LpZ/Zjll+o0Z6X3m8Yfwp7/eCe+pV8M1ZTGqQj588ZS5WDCpCIW+fQ8d4ROuPgjWpKXiwPKo7AiRZ5WYcrA9TFBPnkQikUzolJADvXbn2Ey0QBmKV3wdRVOWoDrkw7bg0dhhfBCFG38DT7oTBWYM0/XtiKkFosreTHMnSg+ZjY8d+kU8+fIabL3rOpR/4GYx23UNMUwr8aKqwCNaSU2YqPXMxr+KPoKp5m60+WYgnJ6Ouh1tCMfTOGhaMaYx2BNpBNq22x3x5p4G7HzJtlmsvkfej8YRUhxLBJ2JFGIpu4exW1XQ0NiEH9/2F/jOuwGKtwDvXjoJnz2pRmSRYL5jd6Y5KrdTKL9jOpw+K8lNYE+eRCKRTNiUkIO5dndjM2EQpqLIj5ICL2KtxbB2FyNsVqC8Yy0SWjE8ZgJv+o9Bs1aNWmUS2rRZWHLGwZh28DF45o9fQfmHfiRmXduWRFM4iYMmh6CoEH1ttrlnY497jgjo+OO6SDHKOGdU12HFIpgWqICrsByItthGZfqMJx08Ji0wkp4Z/bFtyYhjp8yx09jw4kBJe/PPfo300ZdBdWv42hlzcc3p87Pp1dihgdXl+J7J0wt9GiqCPpQUeES6NnqIRzTFWu7Fkq+8IEkkEolkdDOYa3e+zYQRmbX/FkKb96KiaYtRVFaNcjUCSwsghA6kPCXYWXok1petQGvhXAS8bnFvqphWg6Mv+iya/nIV4htfELNnF5tVG7Yj7RQfMe08y2nTRMIwRW7/lmgStS0JvBGtQLtWhWQiAqt4KjD18DFvgZF0j4wcS0Qk2EobSKSYuM3C3/7vEbxT+i6xZb5wTAWOm1eV7ZDr4HSkY/llWif2a2e6ceDJk0gkkgnHYK7duTYTilfaF/Iiz8qKb8DbshmJVBqJcBLbUxWAOR0lSQMRVUE8ZcB0WUibwNSFh+LYD30Rz/3+W0jVrkXo5E/B8JfgnY2bsHDeXJG+lIVHDJgi934qDXQkAMNSYARmwJrySSz0NsA/aQHKa5ajkOvkWGAIhftg7H7SKjiqkOJYIqLFzNBIobtuex3u3mofFicHduK8484Qf/s1lme2BTBTrhV4h6mjxWAY7548iUQiGY90d+3ujyh0bCYUnt1l8sgM7A43xTCRaonA2xpHbUsUTZEkOmI6IkkdsZQBSwUmLVyGoz/8Zbz0tx8jEqpC4WHnI+KrwiuvrURR2wYsPu2DsOCCSzgNLbjSJhJKGiyIvFqbgnbvHMxxFyHSHMW00vkIOesxWLuftAqOOqQ4liBlmDBEWWgFP7rzEaBgLkrX34fP/ux7Irek6hTiUFmZjsJ4FBw249WTJ5FIJOOZ3Gv3QEVhPyLPLpeKWWWF8LndKPRqKGyNYnd7DO4o72M6yqMbUZqoxaaZIbxdPQOdK/8D1RtA4KDToFbNQ6RqHja9+DAWHPduYbOwWHwkTYnMZMhp6Aawq41FqVRx70xbFmbCQvFQUvCN8fR945FRoHIkg2KYmmDos6LXmM1IexqbsFubCqu9Dt+48iOiuhHtFG43yzm74HHbfmKJRCKRSIbMQEVhP1sNKZAnFfvtKqus/qwAmqoKYXx86x3wpztwpFIE/1Wfx1NvbMOqe38NffsqhM65VkzfOvVYtDQ2oKyyWqR6MxVLtLAyWMQWVMtKobYNMJ17qG5iQeFMBAdiGcm9h0ur4KhDiuOxyDA2wbBuPSwFSv1a/OqelVA881C26zkctvxDWTtFkV8TnRkkEolEIjngHuR+3O+YNWlSsQ9etyIyTgR8bugNexA0w6jzzkJFYhumogHzjz4d1WobXvrn7xD7w4cRuOxvYvoNUR/mdXSiMlSElA6wPzrLWFuMGCksSqLDNGOIJ3XohgWzaBqWHnst/OFttjeawtdZ3v7cw6VVcFQhxfFYZBibYOIpHWrHDiTf+BtWK+fCbNyM9y0uFE/ILkUV4lgKY4lEIpEMO31FgofYQsqO4mVBHzSXC1sVBfFpi2A0lmBKcgcs6Dgk9iL9EkgvmYSrihfg24+2YM1vLoD/E/8QZaM3tppo2PYaFiw5GJrqQxomDAWwdNaEZac9lkQ2YFm2xcJrdmJhbBu82x4HDH3f4JWzPu07972HL36PtFKMIqQ4HosMYxNMIm1Bi9bjlqaDRJWf9PO/Q9H0k0ThjgKPG0H/Aex4J5FIJJLxTU+R4GFsIS0KaKipKMRu93LU40sIrLsbc/Y8gMrULiyIv4FHghegsKQcv3yvG9fep+Op2y9D0QU3QquchY7QXLzw0H9wcHEcwWMugUdziUixqrI/jomoosAdS6E8shGVdb+DGd8JK9UKZdbxQKRhb/Aqd31cmj3IjEujFmkgHctP20dfOaQLBlO40W/c6KrE0/EaTAqvg9W4FRvrYyJa7M/kNZZIJBKJZL8yzPnsGeiZWhpA2ezlCPk1uC0dEU8FvGYC5Uo7Hiz/OJ4rfR8WX3IzqpYei7Z/fxuxVf8V07qXnI43233Y/u/vw6AVUbiNLcTTlkgTF02koLVvAWKtaC2YDYPpkhvf6Rq8yl0fRpXnnT7ke7hk5JDieKzCk2mIzTAGe+EaBl5qD8GAioOLkzC0AmxvCotevh63PDwkEolEMkAa1mYLdQyaEeikxoJV00oD0GYcJQqGBPUm6C4fav2LUB+YgzXFJ6EpOB/HXfo1rPjcjzA38gb0F+8Q02pLzsCWDqB+/Ur73pm2YBnMnWwhohvY4ZqMsFoEJdqAjuA8tC74IIwTv7b3Hp2/PjUr7HWiaB7KdpKMCDI0OIHRTRNuRcHOtqR4P3v+QaKpp7O1ZfiFsUxwLpFIJOOftu3AGz8HYs1Ds0OMUD57v9eNyiM/gEZ2SN/+CrZ5F2CH/3gUJHQk0qbwKXvcCqpmL8KyyVfB8/TNuG31A3AvfTcKVnwar97zdZw771CkVUUUFdFEjFFFrWc2Hiq/FIsTb6DQ5wYKD8OMwBxM7ml9yDDZRiTDjwwNTmBU2Cd3c1SHS1EwqbxEfN7S0jy8P+R4rV7+jf0qn5IlEolkfNJZN3x2iGFoIe0OTXOh+ugPwjz9u0jPPx8lfg1Br4aA2wWfWxVVX5lxYqdnNuInXIuLl7hhJaNi2rKLvoun7/kt2hv2QIHC/nxI6QZiCUPYLCZ3voGp9U9i8us/QcP6V9EeTXa/PsNsG5EML1IcjzYoHIfaHNVPWCrasuxmIVbHUwxd9MD1er3D+0PyIiCRSCQTg6LJw26HGAmYC3lKyI851UHMqyxCScAr+tq43SpU1a4Ey2xNdd452DPvgzhqdjn0xq1iWu3ID+GZO76Pd578lxDGhMVAyhM7EUo2IG554IvWoX33emxpjiCS0PddgNGc27h+/+mQ0Yq0VYwm9nMJSaZi5MWgvEDD6j0x1LeFRSW84uLi4f8xIwXseh0onja6LgISiUQiGT5KZgInXQe0bhlWO8RIWPPY6XxKSUD8bZgmTMsUKdmY/5/pTFO6KYp+MDzs8/txYrAez0VLoBaUoPSCb2PjfTehcs5BKJ02DyqnTZsIGq2o0HfDVN0wW3Zgc0MYlgkcNLUY3tx6ASNkGxkyspS1QEaORxP7OcLqUlUhhquDdrq2zqQpBDM9V8N6oq2+BzDTgMsNLL1o9FwEJBKJRDL8VC0ZXjvECFrzGCCaUuLH5JIA5lcVYlLIh0KPGwWaCwEvsza54FFVTNO34ovVr+Fdb34zO23p+d/Aqsf/g3Q6lcliAcTUAqQUD1Qzjfmtj8O38b9Ir/03Nr/1ImJJfb/YRoaEbOkVSHE8mtjPzSy0UvChmJFjYvA3AWzbtk3YLYaFzU8AzRuBklmAy0PlPTzzlUgkEsnEYIQFm09zY0F1EBVFfkwKBVAW9CIY8IjPWWlPZbW99C6ErE68f8XB8P7l/TA6m+xpT/gkamtrRdW8OvdkJBS/SBMXdoWgpaM4auftWPD2z1HxwrewefXLCMdTo9u+MJrtHvsRaasYTeznZhZ2wvO53ajMRI4NbxFcbjei0Sj27NmDyZOz/WwHB0/4TY/aF7PtzwFViyfsiSaRSCSS0SvYvB43aiqDIkcx++OpiiX64Cjsm6cArd7piMRCWOKtxy8uXYZrn/s7Wo+8UlTS222VItAWAUpm476CC3Bu5F64YYihVG+C4fLCF25H646nsKZkIeZUFaAyunl0ZqsYrXaP/YwUx6ONftaNH7QnK2cctfogEcgtD9jiuD2exrQZM1G7bQvefOo+TD64emj+Lv4Ok53PPM6+qDHp+QQ90SQSiUQyugWbKBRS4odpMqUb4FYSUKMqTCOJpsK5eND1MZTEa1EbmoSFH56F+775AVRccisUlxub2tJwG014ofg4NBZPwxSjDnNS7+DY2ONifiw27Wleh9Sut7DNdTC8Wx5GUfNGKJWLulbSG+s6ZJwwpmwVzz77LM455xwR0aQv9r777utzmqeffhrLli0TGRjmzJmDO+6wE3qPO/rjyepmHM2lwsvHZJaS1k0cftS7hD/4sb/9fOj+Ludpnyc+/2bSc4lEIpFIBsp+8udWhfwoK/KhWlgs/CgOaCJrBTvT7fHW4PXC47HHVyM66s2eOQPxv38mO+3m2nohqra4ZuEF77F4ruA07PbMgq56RRy5sHMD5r3zcwQ2/hfKxkdhRpvtVlWWkpatqqOKMSWO2dx/8MEH41e/+lW/xqd39t3vfjdOOukkvPnmm7j66qtx+eWX45FHHsGE9GR1Mw5P+IDH7kGbTBs46riThDh+fM1upErmDc3fNUxlriUSiUQi2V9MKaZA9iIU0FBd4kdZwINCj0t03vO4FLgZUFKAd5+4HJ54E5Kr7ECdHpqG3S3tos8O+/OwMMjfiz+NVYFj0eYuR61vIdR4Kzx7XodppNBRdRTS/lLZqjoKGVO2ijPPPFMM/eW2227DrFmz8JOf/ES8X7hwIZ5//nn87Gc/w+mnn44J58nqZhx2NuBQFfRiV1scC05ZhorKSjTt3oF7HnoGH16xZN95DSSljmyekUgkEskYwut2YUpxAHratIt8FPthwBJloxlEMkVWJxWemUfg82c9jR89ei/M+cdDLSjF7qiKyWWKEM+T45tRZdVhk7YAlXodSmNb0ektwe6CJSiK18IXaUC0cBa800+A70CvtGTsiuOB8tJLL+GUU07p8hlFMSPIPZFMJsXg0NnZKV7pGbJ9Q6OUysXASV8DWphbssZ+n7+83Y2TNuCL7MQsbxivtTCbhAuXfurz+NF3v4VfvJLEB264FmruvBrWAk/dvLcTAfNZMm2PZNzB450RkFF93Ev2O/K4kIz7Y6NhLTzNmzG9aBb0gpmIpwykDS8ShgHdcNODiDQs7PHNhvmuL2Npwx/w6r9vQOlHfi4mX7O7A+dUtuDC2N8QNMMIq0V4oXAFNLeKNt90WIHFiMycjtLULiilNShxzcAcPW1HpMcp5ig5Nvr7++NaHNfX16OqqqrLZ3xPwRuPx+H3+/eZ5uabb8YNN9ywz+dNTU1IJBIY1SiVQHml/XdjY7/GMVu3w9z6HOaafrxsLcS6tatwxDHHw4CKnU1hbOr0osSVM6+dm4F0IVCxEOioBWq32POUjDt4Eeno6LCbCFkySiKRx4VkvF8z2rbbufmTYcAbRNGiC9FuliOt6JjuTyOQTqHT1JFQMoVC1KlYfOE1eOumz6LtX99CyYU3IGEAmyNuIFiBbeoSVJgN8PgKscW3BJqqIBDvQHtxFaL+KfBCRceuPdDD7cLvPF4xR8mxEQ6H+zXeuBbHg+G6667DF7/4xex7Culp06ahoqICRUVFGG+YjS8indiJFaUV+Gsr8HZdJxYvWgRVsQuETJ8+vetDhDUH2BIBmp63I8fTGIGW4ng8YvfYVsSxP2ZvdJJhRx4XknF9bDS9CITX2gGgprWAchxK5y7D23vCUMIJxJUEGvQIOtNpUVVPZ2U8txeTDjkRm5+/H9EX/oaCYz6MN8IhPJcuwZnuFxFWirDVFUJzJtc/BXE6pgkxbGluuDU3OiwPJvuLRI7l8Yg5So4Nn69/BpZxLY6rq6vR0NDQ5TO+p8jtLmpMmNWCQz7cmWP2ZO+NijlQvIVYHnsFle5D8GRDIU4Px2GBOR4VsZ26rPekpcAKWjMmdg7EiQIvZuP22JcMGnlcSMbtsVHBvjmlQNM7dgCofA6CnZuwqO0dbLMmwwzNQspSsKs1iigr3imqKDs9/7izUbfyYeCtf0MvLIJ28Ln4efxMJCumosM7GbXabLjMvSKxM5GGV9NF1gtVUaC5Dexsi6Eo4OlaZnqES2hPtGND7edvj2txfPTRR+PBBx/s8tljjz0mPpdkqFoCa8lFiHYegTNDZfjzmgTeqE+IMtLsUBCLxVAY2db1hJSd7CQSiUQyEXIqkye/i2CsGXPcxdAXfBbRglkwTT/q24GYnoZpWCiumoIrL/sgfvvLXyL5wl+EOCa3NR2Eo2aEoLJrX8buStsrO/a1xVKi4Ag792mpNNrjKuo7EpheFhBCsttUrKOtaMg4ZUw92kUiEZGSjYOTqo1/79y5M2uJ+OhHP5od/4orrsDWrVtxzTXXYP369fj1r3+Ne+65B1/4whcwbhlEOUqtfCYS896N0484GF63ikfWtcIfKBB+qvo1z4xYTXuJRCKRSEZ1TuXNTwAs1lFYDZ/ejip9N4p8GiqDXpQV+lDk1+D3ukQuZNf05fjC2QugwkD0D3u1yFt1YSgWYFiW8NzqpinqCsR0A+1xHZFECkndRDSeFuI4Ek/v9xLakjEsjleuXIlDDz1UDITeYP59/fXXi/cseewIZcI0bg888ICIFjM/MlO6/f73vx9/adwGUgikG/iEGvJ5MLnEh6Nml2JDQxhTFhwCPuj+5S9/liekRCKRSCYevIduetS+B25/Di63B8HJC1DkcyPg1VAe9KA44BXC2O1m/mMFMw87Gd6CIiF+W+78iphNXDfRFE1lMzawZTZtAOm0iZRuoDmaFAKZ4rk9nkJDJAGT+eL2cwltyRi1VZx44oniwOqJ7qrfcZo33ngDE4LcJ0ueQAMoR+nTVHQmFbxrdjme2diM+Wdcgk2rXsAf/+9ZXDxnGeZDnpASiUQimUDwnmrowMzj7HvqvNMRmr0MlfWdIr3bpMQWTO3cjO2YjIip48T2P8Ovd+An75+Hy+5YB6OzCbE1jyJw0GnY2BjDQZMLUehxQ1HYq8eCYZiI6+zdo6AlkoJbdUFRFTR1JlFR4EWowLPfS2hLxmDkWNIHQ3iy9HncCPrcOLqmDKUBDavavTj6xFOgmwr+uH2yrHInkUgkkol5T4002H/XrBAtrdPLCjCz4TEsf/N6HLztDzih7neYF34NBUYn6jwzsazSxKc+/iExi8iL/8jObk1dBOlMnl2+GhZQFduMhW1PoiS8EZFUWkSSO+M6GsPxA1ZCWyLF8fhiiOWaWUaaEeT3HTYV7TEdgUPPEc0/q7c1yhNSIpFIJBMDp+8O4b104dnA9KOyX/ta12HG+ttREN0GTzqM4lQDAh4Nca0YU/QdiLlDmDt7Bq761IfgMnU033Vtdto3doWhG7a1YlpqK85u/ROObf0XTtn5Myzc8ico9WsQTelo6EwhkerGeyzZL4wpW4WkHwwhk4Tf40aB1413HzQJ97+1Bys7AKWgFOvfeQft7R0oLg7JXSCRSCSSsUl/UqHlZ4VYehGw4yX7/c6XbbHcvAkaDKS9xfAk25H0lKBt8jHYUHgYtPYtouz0UR2PYUWoA/7TpuDHj+5C67++hdILb0DatISFYkqJHxWxWgTSHWhzlWFB8k2EWlrRHl+Djb7PotO9FLWtMcytHn/1FcYC0lYh6UKhlx0N3Lj82FnQTSB0/EcRjUXxi1/9Rm4piUQikYzvDuv5WSF2vbZvp/TyuVCKp0MNlCBVXIPdiz4Js+ogGJWLsaPqVJH1qcjqRJ02ExcfWohF82fBat6C2Mu2xWJDU0x0uKtVJyPqCmGKvk18vsc7C95UG9CyFd7Wd2C+/W/Ed9rZuST7FymOJftYKzwuBUfMKsX8qiAwebFIePy73/4GGzZtkVtLIpFIJGOP/qZCc3zGu14HjBRQWLVvX56MhVE54SuIn3kLkvPPQ9DrQmmBB0V+DzoKZghrxbT0DiF+P3rxRSh2JaGsuif7M09vbsUubTbuL7kULxSdJf4O6i2IqCHE9TTmvf0LVL79J1hP3oT07rf233aSCKQ4lnRBc7sQ9GkiJc2SyUVImQrmHncuUqkUrvnqtUgx/4xEIpFIJOOxwzqFL60ULjdgpm0rBd/n9+WpPgjqkvegeNZyVAS9Ivex1+1CjbkN083dWF16Op4pvRD3l14q7qf/d+UiGHAhfrvdUY9saIxhh2c2Hi58H+4puxJPl16IB8ouRSplQE20orVgNoxoC1KNG0dVbYSJgBTHkn3gSe5SVZy0oBKqAvgOvwCa5sHLLz6Pf92b6aTgIE8siUQikYy3DusuDzBluR1lZrW6HrJEuFQFk0J+FPo8mJLcgmVbfoMjG/+JwzofR2dgOpoL5qLFPwOlPgvvX6wBehydD/xQTFsfTqKuLS5mT5H8ivd47PDUoM49FRG1CAUdmxB3h9Dmn45UOlNebxTURpgISHEs2QeXS0VJQMO8qkKcNL8SW1pTOOGSr7AmCL77nRvR2Rm2R5QnlkQikUjGCv1NhZYbZXZpQNuOXoWj5lYxoyyAssQOePV2RIrmCc/xNNTD41Yx2diNcqMBJ82g6DJg7HwDVqNt63inIYq4YcAyLZiWCcswscM9C49UXIaXKt6Pt+ZciTrvHESTI5C5Qlbd6xEpjsczQ4jqMuex5lLwwcOnic4FOwoWomryNDQ3N+O5F17Ye2K11wKa336V5SwlEolEMl6izEzhRtY/0Gdk1ae5UDHzICGqi6ObYfhKYJTMRqFXw5zkO3BbacyZPklUnnUjjZYHfpqddmNDVESPDZMlpoGUYWKLOhOvBY7DBsxAcySJPR3R4V9PWXWvR6Q4Hq8MMapL71SBV0NVyIuzl07C7o4EKo8+X0SPX3n1NXt+ta8C4d3A7teBaCNE4kaJRCKRSMaDQA5Nsyvk5Xfi6yHw5J9+CHDS11G/8OPYvORqoHKxyAC1u3AJUqoPCwo6cO9HK2EobqjJTkQf/bmYriGcQltUFxWAdcMEK0enYQmR3BbT0RlLYU97Ep3R1KiqjTCekXmOxysDLSXdsDaboobjsQoQo8dNEQUXLpuCf6/aDSVYDsXU8fLTjwJz3waaN9oXjvL5gJG0fVkSiUQikYwHuous5udBzhOVJbOXobFgLtCZQChlYAqAOvUMPAhgSvhtbKleiNAjv0W8cSeUzU/DOv4yKL5CvL6rE8fOLobmUmGZQDJlQoWCouQ6BDsboE5dgO2Fy3FQQBP359FQG2E8IyPH45WBNJe0bQeeunmfKDOLgvg1N8qjm1DtDgOqCy49itWr38LWHbVA5SJAdQPJdvsJO/c3ZEc9iUQikYxluous9uHTpXCdFPKhKui1W2A1DeUFXmyvOg2PTvscVodOxAfOXQEFJgzFhdSD38tOu6U5LmwVhmnBpQCTE5txcsMfsKTuH6hZ83PEat9ER3yYo8eSbpHieLwykOaSzroeT/YCrwta2xbUuJuww6rA4Qv4HAz8bVWnXW++ajGw7JKuvyE76kkkEolkvJBrGexH4Cnk96DQ70FJgYag34WKIh+qg17R0Z1VaKccegrOO7RS+JCN+nVIbHhWTLenM4n2mA63qopKeqXxnaKC3h5tJlyJVljNm7GnPQGzbrVMvzbCSFvFeKa/zSVFk3s82Qs8biQq5uKC0rvxfN1shI75EKwtv8afX+/E5754LUpmLd33NwZq6ZBIJBKJZLTRk4WCr7yvOQVBuqE0oCGRSkM3LShKCqWFPjAZW0K3RCf3q06djnW72rChKY3os3+CZ+ZyqN4CrK4L47gaN1yKggbPVETVIlQmtiLiKUadexLcO96EsflXUJNt3do6JMODjBxPdOg1ZuT4oPd1G2VmD1y3quDwWZWoCcTxsvdIVM9ZgnAshT+vCnd/UsoesBKJRCIZ6/RkoehHSjjaEisKvfC6VGgul7AoVoX8KCvwoCq9C0EPcN1FR6LQY0FLx9B+1zXZadfXR0StgZ3u2biv+BI8WXwBHir/ONabM6G0bIIeaeq70p9kSEhxPNGfiuk13vAQsOaf3T4FuxrXovy1H6Ok9lF8pPA1pAxgwRmXinQ0/73//0TP2i7zYw9eInvASiQSiWQsM8RAT9CvoarIj4DHDc0NEQ0O+TVobgV+I4KTfOtw6zlF0KwUfNE6pJ68VUzXFNXRFEkIa8Uuzxy8WXQiar01iOlp7HJPQcxVjHT924NaJkn/kOJ4IuM8FbMzXQ9PoErLZrgSbdDLFuAszxsIuCzs1qYACrDmrTex8o013fuMSX+SrUskEolEMhoZYqozds4rK9RQTK+xT0Oh14Wpqa1Y2vIovGYCKkzULFiCTx9TApWp29Y/AzXRLqZdXRcRlgxLsWCmLZG9Ip4ysV2dibXzPoNd8z8O48Sv7btMsjP8sCDF8UTGeSruqO35CbR8LlyFZfC2bYA3EMRps73Y1ZHCwrM+LqLH13zlS2gNx2SlHYlEIpFM3Kp6PaCqKqaWBFDi9yDUuQnTav+DolQ9mooWwVQ1lBpNuPjEeXC7XXAhjeiDdmlpUlvfiLRuojqxGYdGnhLZK6IpAw3+GtROOhUN/rx7dm+d4aVoHhCyQ95Ehif7SdcBtVuAaTXdn/zMebziGzDr1iPsn44L3bPw2I5VCM88HoHQfdiw7m38+9//xkdPOQieITQ/SSQSiUQyHnG7VExJbYGx8kZo4VooegxlFtAcmIO3g0dhtWcZPvV9HT/5yqeBhm3QdrwO94zl2BnTsKz1TZxr3YdCsxORcBGeVi9Ho3cJCn0etMdSwroR9Gm9d4bP7VjIcthzTwPmnCxbdntBRo4nOlVLgOlH2689UX0QPEsvQLpiCYJeDy5YNgWtsTSWXXCFiB4/8cSTaAvOkz5jiUQikUi6wb/jaQTa1kNNJ6GaaUSL52Ploq/i9ckfRktgLjqLF+H8G+8U4xqr/5ud7rWOIvjTHah1z0Ch0YnixE50Jgw0hRNojibREkmJynq9eqQd0VxYBTS8Dbzxl0FVzp1ISHEs6ReaW0WR342AV8Xpi6tFBovW4BxYsPDSC89i6846REsWSp+xRCKRSMYnQ7Qm0IOsqgq9FtDLFsGqWiL8yH6vix+hsKIax5z5Hhi1a2DsfltMs9soxkPG4Ziib0dELUK9NhXRtI62WErkRG7ojCPsFAbpySOdFc3v2O8rFslMF30gxbGk37DHraooKPJrOG5OObZ3mqg64WJEIxF8/4ZvojmcFJV9uiB9ThKJRCIZ6wy1uNWck6FULYbiD0EvX4TEjONF0Cno0UTKVI9LgdelYNa7P4uU4kHi5b9lJ/1t8jT8N/Be/F/JJdiuzkYqZSGSNBBLptEe1bGzLda7R9oRzcsvsQt3sYCXtD/2ivQcS/oNT2C/x4WkbuJTJ8zChsYw6mevgGv9q3jp2aewp74exQXTRaoaQR816CUSiUQiGRMMtbgVxz3zB1BbNkMPzIC3cB5CbTGkUyYqTAOMKyV0U2SzuOczh+Ijt74EM9wENViBmKHiX/FlWBgsgEdhxT4Tcd1AazQBj0tFfYeCySEWGvH0/vscalb0WcBEIiPHkgFSGvCiwOdGoU/DN45gFR8LviMuEvaK1WtWI5rUYTrR4z5q0A8aGY2WSCQSyf5kOIpbZaK6RbOWocDjQoGwUyjwam6EfC743S5MNnZhTjCFM4+cC2PtQ9lJ6zqSaAjTX2wiztRuuoFwwkAibUeQtzWH+3e/HGL2jYmCtFVIBoTPw+YfFb6Wd3D01p/j/MBbQPlsuKrn4ofXfga733xKnKwjVilvqE1bEolEIpH0937jCMsh5jzOpzzoQ0WhD16PChUKAl47F3K4cCZi7hCuP7kI+pv/RWrX2uw07zREhCCmbZmd8JIpQ9gZIwkDDZ1JNLTH9l1+eb8cFFIcSwZMSYEHJbEd0JJt+MiURrhhIHTEexDtaMGjv7kWidq37BGH+WIyotFoiUQikUh6E5bDGHV1qQomF/tRXugVdkXaFksCGjqK5uOxqsvwTOmFOO+KryL81B9h6UkxDRtltzTHROss7Y20VkR1A7F0Ggk9jZ2tMaSc4BSR98tBI8WxZMB43SqUinkwfCWYHV+N8wKrkSybD2XKwfjvyp0wmjbBqFu9t5R0TxeTwdgjRiIaLZFIJBJJLvtBWDL/cU1FoeiYJ8rOKgqCfjfagvPxdtFJ8C46BWasFbE3H8hOUx9Oojli2xdThiksFR3RFGIpQ2SwaOq0hbRA3i8HjeyQJxlUOprQrGWo17+KRP1GvDsM3PsC4Fp4CnY8vgYtHWGU8kk70dpzR7zBdtZzotGyQ4FEIpFIRor9JCxLCryYVhLAjrYo9LRJfYzyQqCRuYsVP7yBQsRWPwzfghPgCpaJaTY0RnD4jBB0Q0VCN9COJIJeF9rcqkjtxtbdgNct75dDQEaOJYNuEnJPXorWGWfBu/AMLCl3wTXrCBiFlVi7aSesWHPvT9xDeSqXHQokEolEMpKMhC2wByaF/CjxaQhoLhFFps2ikB3fvW7MXn4CkE4h+srd2fHb42k0RXSkLUukT02lTXQk0tB1E83RFOo74l3XQ3bAGzBSHEsGTUnAC6/mgtel4piF00VZSnX2UXjirVronpLen7hlc49EIhkDsOMTBzZjO4PzmWScs5+EZSn78RR4RId3r9sl7qvMZsG6Akef+1G43BqSW16FvmdDdpqt9B4bFtKGBd2wEE7piKbSwmbRFE4hnkyP6DKPd6StQtI9tD0wuksR28OFwcOqeT4NzWkDS6eGRFo31oN/5Jk/YvMnfotF/ha4KnqYXtojJBLJAYZC16DwFWKXHZ74t/1qmRApKvtV9YxFz8SrIprF+crWNQ4SSV+43SrKgl60xnQYsBAzTfi9bpRENmKxtg1vLTsUq159FZEX70Txe78FRVHRmWD0OIXqkBcwgFTKhLf5HVS018Mom4e64GGoqQzKjT9IpDiW7Et//cD1a1BZtx5p9xQkAnOxZHIIbxkL0BlN4pf/eBg33Xg9KoP+vpOSSyQSyX6ATdBp0xSvjLYNR/SX8zAs6pN956VAgculwJ0RynylmJZI8inxe1EaSMHVuBau1s2I6SZm7f4fvKk2uJYo+OgrBtLNO5DY8AL8C44T0+xsi6Oi0COOseLIRhzVdgdKEIZRV4Zd2hcwufhY+D3uYQ+MTQSkrUIyOD9wRkD7X/8tql//CQrb12HBpCJAdUGtmIV/3/kn/Ps/94tE5RKJRHKgIsPssBRhj/6YjnBCRzxlCI/m/rBFMPKcNkyxDFEuQ1xHZ0JHLJUWyyCRONBSMTmxGQvW/RLztv8dB++4A0WpenQE5+LwSRbOOs0WxLGV/4GV1sXfjBwzQwVrC1QmauHTO9Dsr4GHgrp1C3a2RAZ2nMu8yFmkOJYMzg+cEdBK1SJ4o3Wo2vZvHFrQIr6ac+IFvCvguWeeEjcCiUQi2d+CmEKY1x/+TYHaH4vE/kCk4EqbQiBTsPNVN6RQlgDF8Z3w6x2IheZCtQyYihsl0c1IeEpw/PkfwdLT3g8z2or42seym2tDY5RJ4NDomYawWoSiyGbE3SG0+qejLaajPZbq/6aVeZGzSFuFZHB+YEdA734drlgTive8hBXtOzE1eDn2YAaUwjLs2rkDrdGUSHIumxIlEslIwegYc77SKkEhPFagYE+lbbHMaySrj2q0Ybhk3GoiolbMhTtYjlDHFsQKpmB95RnCstPinYaENhvHnD8TppHG28/eD+/co+EqKBGZKxojKVjBWXig7GOYgTqgfA6UwDxY8TSaI0kEfVr/jinZUT6LPAMlg+ul6wjoWcdDLayCXr0MAb0NV85pgwEF3iM/gLdXv4E331yNSEL2mpVIJCMThRUR2LhtlxhLwjgfUQ44bVtAGPGWtosJSPVB0E75BuKHfRK7Drkae6adiV2TTkNn0XyR4q0k6MOR770c1TPmIvLC37KTsWqeZZqo1WZjZcHx2KLMFC0n4WQKbZEUOuP9bMHlfX3pRcDUw+xX6TmWSDDwCnY8cQ75EFA8Df72jTD8pZg7fQqWTy+Ge8YyqFXz8Jfbb0VrNCk6wEgkEslwwOtJdByLyFzRT8EsmTgok5aicNn74Jl2MELMfexxw6OpwjrhdSso0NxY8YmvI7X1degNW8Q0zFxR0boSB3c+haXtT6E0skk8LOppoD2hoz6c6N89mPf61fcAu1barwOpXjvOkLYKSfcMpILd9KNgmRbCFe9C2lODC5ZF8PrOdmjzjsOql/+KtmgKRX47j6NEIpEMFtG5LW2O6QjxQKPJFDkJ3YTXrYpBWtTGPxTEFYU+RGJpUTUvlbYznfg8bhT6gaRRjHnHnIUdax6BVnWlmKa1rQ1f9fweEXcpOsJVeF75JMKepfBrKtqjKeE9Liv09t9z3LjOtlZO0OixtFVIhpyxAusfgGfXKyLvMdN6VgR9mFnqFzmPdUXDA/+5B2FW75EREIlEMggY9aLdgMNEEcb5IpkdCzvjafEqGf+wr05xoQd+Ftpyu6C5VJSFN+HgjqcwQ9+Coy/8JPQdb8KMtonxn9CXIGUCnWoIoVQDFjU/AH/rO+JhMhxPo74j0XfmCuk5ziLFsWTIGSscAc2etj7NBbcKnLKoCormheegM3HvXX9DOMme49J7LJFIBh45pX9yIori7jrwCZEst8f4sCb2Mp173X2YktiCoM8t7qs1jY/j5E3fwVF1d+CMpjswS9mNMz7/AyTXPyMm0RUPfpy+CKXpRhQabZjVuQqHb7sN3pa3EU3qqO+M993/Zz+WzB7tSFuFZOgZKzIC2lM5DyWaBy2RJA6fUYr/vbUbexaciNq77kdTQwP82iSUBDSoah/PZDIJuUQy4aGXOK4bskxzD55kRtHZWsfIorRajHFrYu40m58ANj0KGDqKAmWoXvp5qNEkanbcgWBsBxLuIhSbFqrTu1E181hYf/kJjHnHwhUsx93pEzHVreD89GPY6V2AyakdcLVtRUfRAlEBcmtTGEunlfR+vMjiXAIZOZYMPWNFzlNmZdCLgMeFgEfFifOroXj8cE0/FN/+6hcQiSXFza5XZBJyiWRC4wg/dkjbH4U6xvoDBK0WstPeKGSgOYOde9+qvwANbwOFVWK6qWYdShLbocJAUgvBm+6EqbiQKJwh7BZLT34vws/8ITubv8aPQYtWierUdkTUIuxWJ4sWB5ZEb+hMiuDVoCPaEwgpjiXDKqDZYaC4wAO3puKEeWVwK4D34DPx9luv47//uRfRvpp1ZBJyiWTCYhfvmJi+4sFC4eNYT/hgIRklDNS/m733LbLfN70jpnNXzkP5jIOgF06B7gmiMzATq6Z9FB3FC+DzqKhZdiz03esQX/e0mKwx6cZvvR/D40XvxYMVHxPp3TpiKcTTrNSYRvPm12E9eRPw8m9sMS4FcrdIW4Vk2CkLeBFPGgj6PVixsBKPvgOoU5figfv+hfPedxFKC709JySXHQIkkgkHI8Qxpp6SonhInRb5YBHw2p23JGPAmtjdvS/SAFQtBuadDtSsENOFTAubj/oy2mo3oNE9GbWeGngtCwVeDclgMQ4582KsfuY/8C88UcxqXacHh5YBhsFKjGxd0FHk0xBLKTA7N0APN8MzafGEz0jRG1IcS/pmgB5gdiDgiWhYFs45eDIefacRnrnHYONTv8ETjz6KygvORWWRf3guKBKJZOznLE6lZdRzmKLIzP/MDlwcJAeYgfh3c+99eXYiVVVQUXM4dnpqkIikoLGoh26IyHGB14XFJ52PNx/6u8h7rFXVYHvMi2XKf1HhiuGJsg9gk/tktERTKIaCem06pmjFcDe8A7WgvOeIdv3A7vvjDSmOJcPeqcCruRAKeBBJpVEd8qKmogA7rEMQhwu/u+UHOPmUkxHwaCj09XD4yQ4BEsmEgF7ZRMoUok4yvPaUtGkhoLmEsJKMEZx7azf33FBAy7bK+tOm8MSaaQVT0+sxx9qKl+fOxe4NzwtxTP6bXI5rtX9gRctdaNSmIexeKDzKu/w18My9Ekt8zSietqj7+3n9IDoTjjNk24tk+DzAGZO/0rBWRI89LhdciorDZpQgrbgROvpCNNTX4Z5/3Ck8UL0iOwxIJOPcRpEWXlkpjEcG+rbDEzQv9Jgi/17Xwz2XWZ6qinwoEvdWFW6+j27EKXt+j+Pa7sX7Z4WR2vA0zFi7GP8f+vFosUJQzTTKErWIpnTR0ZWtNLs9NdhUdgrMyiXdL8vmJwbWmXAcIsWxpHf66wHOyzLhbXkHpQWaSDV07sGTMb3UD3PBqVAr5+LuP/8enUldVP7pz7xkhwGJZHwJY96kx2PZ59GG3NajnO7udb3cc9nZPRTwitZZ3lvLEjvh0zvQ7JuNU+d44DaSiL/xXzFuSvHg4fShiKmF2KlOQiRhCMsNH0hpsQjvWIWOlXfvvb/mLsumRwGX1v/OhLnrM06yYEhbhaR3+usB7qbsZNGchSJykdRMXH3yXFxz7xp4j/ogWu//DjrCcURCPpS4vd3Pq70WKCizXydwCUuJZNylaZP+4v2OSIsHu9KaZBTRXblmZn/q4Z7LstLFBRqaIm4kWQwmMAsJrRiTktvQXlKBqhlA49qHYC09A0qwArekL0CV63/Y5poJLW2KMtJMtVoZ3Yo5dbdDsTphbqqGevI39l2WhWcDxdP73/dnnFkxpDiW9E1PHuBcw343T7seeo/9GlK6gVnlBTh1YQUeMi24ao5CNBZBW6QQJYEear1HG4H27YAW2KdzgkQiGZvCmA/LMnfxgUFYWCzIjnqjiZ6ixL30u6ks9KGuJY645kK0bCHexJXwdG7DVqMaU458A43bb0H6xT9CO/2riCCAJ/TFME0gDRNpU0UynUYovgNasg0txfPgC2+Hj0I8f1lq7EwZQxL6UhxLJhzdPSXmPe0yRlHgcaPNzRPSxHkHVePBVdvgWfYehJMG2uIpxJJMPdTNM1phpT1fzr+3aj4SiWRMZKSIjHFhzGVnGmEWU+gNVVHAPnCjsWodO+px8f0eGUEeFQwiOxPvl1NK/GiN2/12mgvnIeapQTiewqLjp2LHC/cjvO01uE0DiurCQ7GFWJJOi/R+CV1BOJ5GvXsqYloxgp2bEC4og1o0C56hZooqH2Be51GOjBxLBkdPzUF5JxRP5JICj/AXh/wqUqsfgPfwi/Dkmlp8pLIcLdGk8E51yXvMkyw0zZ4/X8f4SSaRTGTYISyaHDsd7yjknYFCmAMF5UCXntKY+tgWywpUFXCpiuhIdaAzhHBfsIleMgoYRHamqpAPjZEk4km7qBb3J1P3hQp8OP/iS/GX718L451H4V5yJpKmisZwGlNCHqRNE9GEge1Fs/Ds5E+I6nueinmY5qvB7EEuy3hNwyrPDsngGMBTYqnfg1jSgGEGcES1hjeTUTz4dgcuPM4QXri2WAoVQd+4PckkkonKaBfGjAYz5VnaEcPm8C0p52NlI80WYNifKzBEejVbKNvD/o4yszOkZaVR0F2rnWTUww55M8oCaI+noPPYtUykVRVFhonZJQZuef8cXP3Us0Ick9ZYCpWFGhTFEuMn0gb2FMxBhzYf1T4f3O0JzCgtgGuoxWOqhyCuRxkyW4VkcDgC9ugr+zTe84SrCnpFR4ArPnMV9LUPI+0N4Y5nN4gbJ2u979NzPa8stUQiGYPFPUahMKYgZiU+Ppizohwr8/H6w+XdH0vK3+Bv8Tf5252JtMgiYAvW/betnG0gGXvwYYrV8aYUB4R10cleoXldaAvMwOKaaTi+uB5ma60YP5oyURrfKf62oIiWXGETAtCRTKMzoaMtph/YlRplSHEsGTw9Cdhu0rn4PG6UBb2YPmM6sOEpGA2b8OSWTmxujAgfXFu0j7zHEyB1jEQyrrJS0GM8ioRxviDWjdGzdIxcx/X9L5T5O7z+SsYewkbh10T2ClscK3BDQWvRfNxX8lEc++GrEX/j/uz4Le2tmKZvFedkygBShr3fDdNEeyyF5kjiAK7NOBDHmzdPvGTQkgHQS47ikM8j/McezY3US38Tn92zcpe4QLfFkz3nPR7Eb0kkkgOYWzc1OjrfcRko/hgZG22CuC+hTBHPZe+rA+BQ4W/QhywZW9CWw2JbAa9L+Mc1VYWpKPCoKhoD87AycCJOnluQjR6vMmqgxpuRSPPhMI1wbO85ygfHhs4E9N1vyWDTYMXx4sWLcc455+CJJ57AgeBXv/oVZs6cCZ/PhyOPPBKvvvpqj+Pecccdovkhd+B0kgNTUY8+u7JCL5YtPxxm2y5Umq1YuaMNte1xIYx5AxtQRHgg1fskEsl+IZoyROT4QEJB6QhMZsoZBTp9wHCRuexcB6ZhoxVjpOD8KZAkY4ugT0PQ5xG+dUaSNZcCl4t/q8JfPPnws6CvfiA7/ssdFUIQG7T06IbtWc4Epaw9a2E9cZMMNg0lcnzwwQfj4osvxpIlS3D77bcjkdg/4fi7774bX/ziF/Gtb30Lq1atEstx+umno7GxscdpioqKsGfPnuywY8eO/bKsE5Y+OuoxCf157zlf/N3ywt3i9cHVe5DQTdGsY/AC3d+I8DhLHSORjHUYkTqQ5Yopih3rhLAmYHyQMky79G8yPWIi2e40PV622MSAAb9pxX5oimp72Q1LDOz26VIU7PLUYEnNJJjJqBh/e9xr+40Vezw9bYiH2XjSgK9jC4yoDDYNWhxPmzYNN910E2pra/G1r30Nf/7znzF16lRcd9114rOR5Kc//Sk+8YlP4GMf+xgWLVqE2267DYFAAH/84x97PXiqq6uzQ1VV1Ygu44Siu+huXx316tfgA/OBqrJidGxeiVJXEs9vbhEp3ei3Y9OO1d+I8AA6BUokEox48/yBKgnt2CciibSwTow2uHzdDYOxXFAkMyo+3LYVGk7Gei7qCQHvt8/fYg/1a1Dg01AV8ooOeUIgi452FgKay86IcvD5SGxdaU/rKUBzcwvShiWsNAmaj/lgpBto9k1DXCuWwaYMA87jkkql0N7ejra2NsyePVsI5Keeegq33nqrEK/JZHKgs+z3777++utChDuoqopTTjkFL730Uo/TRSIRzJgxA6ZpYtmyZfje974nrCE9weXPXYfOzk7xyuk5jDe4TqLX6kDXrWEt8NTNe4uAnHQdULXE/q5ysT3YP7DPNFqsBZ88ogA3PdCM2FsPIrnkPXhmQxPeu3wKoqk0EqHZ8AbKgcb1AF9La7rOJ5eefkty4I4NyYQ7LhgtdnKu7m9oB4gzd+8B0nQiF3I2L7ItMp28yOK1l+VyMrjZRUMY71P25kZmXuSMHTCfpG4ipQM+t52lYLjgokYS1qBTvMlrxgjDe+jD1wEN79jvNz0GnHEzqoM1aOpMiOPIpWQevBT7WAz4AijVm+G07++qrUV1ZZnIWsGHLN3Q4bdU7HLXYMOCz2JZsA1a5Vz7vjqM1/7Rcmz09/cHfAbQs1tYWIjy8nJhWeAQCoVw7rnniteRorm5GYZh7BP55fv169d3O838+fNFVHnp0qXo6OjAj3/8Y7zrXe/C22+/LaLd3XHzzTfjhhtu2Ofzpqam/WYf2d8HCrcND1o+bPSbnZuBdCFQsRDoqAVqtwBKZb+nOeOoLfjlM01ofu1BBOedhkfW1uHcymYkko3YVTYNwUM/D4T3AMFJ9nx7sc5IRtmxIZlQxwVf2dltf3d14z2OdoP96W/mOtI1wt9kdM6OAI/sb7KvBuWxLZjt5nKHjozA9rpV8d1wQfsbK6oNFHnNGGHEPTQIFB1kP3UZBeLem5pUjoARRYERRcJIwlLSMFwWgn4DRWodFlTvxt8sE4qiwghNQZWWgp+RZZcBb8qAx52CR3Fht1WBsqK5KFK0Yb/njpZjIxwOj4w4vuiii/DYY48JMXzVVVeJ6PFo5eijjxaDA4XxwoUL8dvf/hbf+c53up2GkWn6mnMjx7SSVFRUiAeB8QYPWEYmuH4DOmCtOcCWCND0vB05nlYDVFb2e5ryYCl+9bMf4NPX3Ij424+j9dDzsPa5/+CDBSthhqbBe8rXoc0/b8jrJzkAx4ZkQh0X9Pj69rOdQqQgSxvw7KciIYwK85WCfChlM7LV9vjqRJYzkebuI8q2MLY7lGeq7okCInur7fGV+NyqELXDg4JCnzs7736vn7xmjCy8h74TBloykePAInHvNc0muMNr0ZQuwSazGpG0W0SFE3oa5eHtOG1yC/7aXA+leDIUjx+r61OYVBFEwKMh4dJgml6YqhselxfwFaLSqgWaNwPlc/a2CA+R0XJs9Dcpw4DP87vuugu7du0SNgpmizjmmGNw9dVX48QTT8RIwki1y+VCQ0NDl8/5nl7i/qBpGg499NBe09F5vV4x5MOdOV4FAg/YAa/fpKXAiq8NrIpdzjRq2Rws8tbgh7+Zhc99/EOw5h6DH5sn4lRlJSqxE7E9G1Ay9ZB9vVb0I7MjnvQXj95jQzJhjgtqYg7Kfjo+KCrtpmA2G6tCLI7Eb1AI065Bb+ZebIHa33k4NgunBDWF9cCj6/uOn1uOWlVMIWAZBRRRbcuE3+MS3w+VRNoU2RAGirxmjCC8h575fWDLk/b7mhXiRX3meygPN2G5XoBNBR9GszITibQFRXGhUZsKy1+MqfGNqCueLMZvjqdRbamiAzxLSqdM2pMUWAoQr10DZfOvoMRa7cAX+/OIiYZ+7x0Nx0Z/f3tQS0hLwve//32R+YHZIq644goccsghInXaSOHxeLB8+fIuKeT4JML3udHh3qAtY82aNZg0adKILeeEYjBV7HKmKQl4sGjRQnzk+DlIP/NbJFU//hg5EpbqRot3uuiZnUXmNJZIRhW0FjAF2P6CN/FwcuQ63HH+XB/R4S1l5Anjfkxv2AU1GEl3Os2x0xNFtl19b3iWm0JbCJpMAQ9eJ1uiKTR1JtEctofUMOQtNvbz/pUM4B56zOftgX9nOrArlQuhpVpRFNshWlWmpbbg8NgzQpDe6f8wgu69x1/UcCGRsjOfxHVT/E1SaQtWy2aYkZwO8RTiE7CewIAjx4wY07OROyxYsABPPvkkLrvsMlx66aUjs6SAsDtccsklOOyww3DEEUfglltuQTQaFdkryEc/+lFMmTJF+IbJjTfeiKOOOgpz5swRnQh/9KMfCUF/+eWXj9gySvoPy0mXhjfg6mU6Hnx8JTpatuMfxcfhvLnLYQXnQe1MYFppwPa+5WawYOo2Rqxl9FgiOWCw8yw79ewPRM96fWSsGxSZg/Eu50aYBxcVHj7EsnBImWK/tMVSKPJpKA96B+Udzt3ubpcypHlIRpiclKZhNYQ612RMTW7BBZ1/QdDsRFgN4q++D6MzMF2MbhlpKC43tI4tmKxoaPPOF30G0hZT+bnREZiOtK8ELidFKj0/E/DeO2Bx/Pe//x3FxcXZgVFY+njPPPNM8X4kef/73y86xl1//fWor68X0eqHH34420lv586dXULmzKjB1G8ct6SkRESeX3zxRZEGTnLg4RNtWWIndJ+Cq89bjutfvw/6yVfjZ1tKcOUcE5GEjtZIElUhv8xpLJGMIigovaYl/K8jTXwEUsRRTFIQ22WaMeAIMUUxI8ujtd4eI4IUyJGkjuKAR2SfoPWiu8wXfUHhVOTrPmuG5MCTrliM9iO/jOju9Xiq3o+d4SlYlnxaCONa9wxMN3ZghlWHLbOPQF19DPqOVXAXV2M1qvEJ15/xnPtCtAbnI8lWAj/QXDAPTYd9GVOtur21A3a+POFSvCmWTGrYK+yQxywc7GU5XjvksYhKZWXlgfEB1a9B6rHvINnRiEv+shWvLf0qXKXT8O1zFmCZrx7F8Z2omrUE3mmH2M05A/E4S8b2sSEZlaTTBnbs3oPSsvIR9xrTojCcNgohijOR4oGIYk7H5bCnG52CuCf2Vk9TRSc7lhoeaEc7dvSjl7kv5DVj/8Lzo74jjljSxJ72OHatexGJ+k3QTQvHxJ7MRI6LcE/hh8Xx+78tBhLJFIwX/wTt7OvxPvfzmF5ZjNWhE1ER9GJqSQAVAS8WTCnCokkhuJwWg2G4946WY6O/mm4oHW8lkqFTfRBcJ38DHVvX4rNzAvj4N2+FddLn8KP7XsMT8+9Fgd4Ga1s5cPr19kkpRbFEckARBShGOGJKAcrKXcNZsY32B3p0ByqKKYj19OiNEvcFo9wUUX6PG+0xHdGkgUKvCz6PS2S76K+9gvmUByqqJSMDz4twQkd7LCUi+zxGtea1OG73H0RHuk41iOcDJ4sjtt49Bbvcs7As8gyqDRM7ipfC3L0aZmcDHggsxXmuNHTdRCyuI+pPo6LAKzpjsnR5wBHHE/DeK8NBkgOOa/JSeJe+F8F5x+ELn70C+ppHENWK8ac1JqJFc2C174Sx6m8TpiOARDJaEZaCES4PzQ5n7NA2XMLYyIhDdi7rrzB2Ku5RSNplqMemMHbgprSj8PYDQlM4iYaOJFoiSSGyuG34vbOdxJDToZAD94nkwMP91xFPoZP7LfOwx06ZgfA2BNLt2OOdKSLGzHu9quB41Hlr4HG70OydhnlFKSiqC2agDKn1zyLmLsLLbSGRI5BntdjnlimyWPDviYyMHEtGBcXhDajetQYnLJqO5+ZVgcUu/9x+CK5sfAAuvRXWtmeB9h2yTLREcgAZ6RsmhTFv9MOhiylwGf0aqF+ZQpDTjTX7RD6ial9OGjn+HUE6m+qN+zKSVIRlgrYLr6ZmUsB1v96MUHLbeDMRZI5Ly4ZbdtbrdruTnvJXs5BLb0VbOA8rY0Vw8mzTXcS8xcwowXMknsmK4m15B56mjSJ1W9QVwuTEdnS6QtjjmpL5Pft3uM+UQCkQAxK+CqQ3vATv4Rdg65YtmFJeAl1z2VHolAXDYBVGY0KnT5XiWHLgqV8D7ZmbUR1uQpE7hKvOvQwX/34VEjMOxy3hJL5c/CRSZQejOLIZygTpKSuRjDYYRRxOm0O3VophEsZ2iipjQBkoOM1Ir+NIInIrZ/Iri86C3awGP2JU2BHITlQ9bbFFwAWP1nshEU5LQSxS02V+j8lxhVhm3mUh4Oz0cvm+UlHQJKdMNrWhU/VvLOLkshYPICLf98CylohtIHJVO/Oz9w/nweOQVoncY5Hb3kkVSNsD0/UF29Zj2tqfw5VoRcwdwsriU9GWSGOPOgV17tmZojMWpqe34sLwX/GUWYPHMBeqrxAL33UG6uo2QKuei3XPP4jlp74HOu0UeuZ4qFsNvHWLnanCyXc8ge69UhxLDjyZNG3u6kXw7nkbk5QWLPPuwZvJGP4em49PT1oPf/N6JIMV8E2QnrISyWjCthmYI+4xHg5dykgxxcVAAr9CjOznKn/DBUUZxTAjjP3RZdwuiYxAdjJQpHQTpsEos0vMi5HkXH+xEIGiqAk7NBrQ3Cwb3t28mWUoDV9Sh1dz9yvDhSMSnWg0Ow6OVm9zbpaToT5EpQwDiYQtgp2qiU4WFM1ld6J0th8fNjhw2/M8sTI5qEvbt8CdaEVzYDZKoltgKSreLDwxc65acMEu7DE5vQuFRgd0d6GYn8sXgK+oFKUpBRGXG42dcSGM0x7bTpHiudCyGVasGUrlor0p3P6/vfeAk+SsrsVPdVfnODntzM7sbI7KEhIoISQQ8AwmmGCLnAw8QPYzwYAfzwGDjU0GE4z9HvAnmYwJQgnltJJWu6vNOzM7OXfOVf/fvV9VT01vz0xP2knfWbV6OlSu7j7fqXPPJWwQJVmSY4lVk9OojByD3V8LraoTt71IweP/7z4oe2/Bzxrejau8vXDWb0OtfxtqVnp9JSQ2GOjHdjltBvSDvFiyYXbPm0/zDiJ7pMatNbWYG4EURMbyQg4LbS4dU7fDViRgRMwoI5mUY/KV243W1ES+rcvIQSjFMxFf3qecCEIZyYDTbpvVekFKK20L9aGgaYUqPUWWKWeZ/jZXwVwqt9Q2OwYSuS52Dpw/sbae2+W2i/bHYgozzYEF7WMiuERsrSksbOWhz5hl3tT/UVVt0HSN7Q60B+lY0Ft4IAQg4m1HyhFGOH4aCTWMEdcm2DXaF6JzJS2TpPohdRNnILfne8TMXUEMH3sMW657JY5OJKE37EAum0XBbUcyR+uXRzrYAd1TA8Wad0xNQEhJtjuAbTcDW5+/bkmyJMcSKw/6cNElm7FTsFd1wh9N44qRH0J78iD0XTfi20eA1pe+AAGPE4VoBg67HcHIsakRbCWj2Q3snZKQWIr4s+VCsR30BbZRlCMkqx1CuS1ta70wCBsJEWT7tLg6KkK02xW47DZWMIksWwkj7S/rdDOB3ke21RyRZJvwKhNJJoJXbK1t2BLKEnyLvV0oygoT7SnyO30ik1iTVKoo+jQCT2SRGtZM2SDEtPSeGVVqHcgUxLlprh9TfMMaYvBOBtF0+pvW05wnbSeRaR7AGOtHpNg6EDN98fSeUtBUkVQG0WReDARs1OVX44SRjKZBhYJx/3Y8seXP4Y6exZhrEwaxGYVYltViGiyYS+p1b8Uv7W+EPTnMnmM1UI3EibsQesV7kT34S7h3Xovu0ycQ2Lefu+UlsnnEGnYhd+2H4YqeFRFuZiMufwPQdR8QHxT5x+vUbiHJscTyYT6E1IiKoS+f2uEfIadEUetIY+KZX6H7opfh7hOj+KMDzfzDkOh+Ev6Dn4GNer/TCJZQyM3sizJbT29Q75SExGLAxWnLRCCJFCyWeJttn+ejoJJaXI6QbARSbAXNL6HnWaW0kjYuCOOHNhS0PNyO6dnIRPpcql6RbUIo+hqnK9DfRO6IfJvHi9XNGSAKBAUJzRUUpJCHTaHpp8ifSbL1EpuJqdaas6f303LL2TZoO2wQhJ3mxNYcHjiVB72fCDcRdSthL0b/0XHShZ+YXhO2FDrfppZrkuVy22+S5kS6MDVwyZJ6rcNmpzQJHVkoyGoaor6tSDu38DKUZBYk0isFoKDo/Htq7p8utQObPDpsugZHqAFapBeb86dRpceQ1DX0TCSxh1IrNJ0JeaaQR7Zhj+gxYII78R0Vf9ftBuJD0zvmrSMRSpJjieXBIgipq3EHNH8trtvixo8e/wF8e27ET57sw8WtYWyq9iA8eJx7v9sadwNd94svnPZrZm5tKVtPS0gsCPwjvUxeY1Z7qSvXBcwuNq0Xa8VGUWw+sgwdAs3W17TvXE4bVJImLcjnNaR14T+my+wuo5HIXOqxIJdi8EFebi5UMzy15nGioj5SpCuxQJgWElNxVgyyTLYPmodTFXYK07Yw07nAxYp5sS9NhVelzVEUXleTUFuLMhUzkaMklUO06xbMk+anGPMX62YlwEA6IyL0SF2mWVBjDSLqXBg5cRSe6BmkgluQrNpVnI4sL7R/recpbxvt95zOx8ahKjxIoYFHLlcwCh3B62kn/zgRZF1nywnltNF+acyeQ5OtEeeqWpDLFxCOn8HWq27C44eegbN1HwbPHEP13n2smJMv3UzdmHaF9/RdwInfCmJs7Zi3zkQoSY4llgeLIaSkIN/4Ubww83N8/5nPI3LX1+G+5S/w7w924fYXbMOEtw01agj+4aNQAo1imtlaW1p6z2+k9pcSEqtVNSZyQVX3i5kzkRIixvNZ5loixkQGWb3Ul55sl6rmVJBnd7I5YPo6FHSk9QLHvJn72iTINB+3Y6pYj24UNRZN5hBXsrOqyhxPRskXqgJ3mXQMTtwwyHDp8aJHtE+yuTxnNNPrRHRNbzMrp0RmSWGegXwL8i7mzUSbVkEDd5Yrv78AJaexh5pIOZHlYjGjERdofk6YeNtp+cq0xAn2Vmv0/jwT2lBEJE04shPIu6rQc9EHmCCb5JwK5KZZRowTgZRdziTOipg3kRoC1CVOoiV2Bn22FpyxdcBOAxLyHWtEkBU4FAXDzja4bSnYgo0gXflMwgtPSx182uPI22w4ceo0tu7ay+cDdd07z6ZkNgPpvPH8jnnrTISS5FhiebBIQkqXci599Q5c8ZsjeOT+e+EfOYIT2IP7T4zhhp07cGrv/8SOxBPwOmxAuE1ICTO1trR4mmXraQmJ+ZHj5QApY4vhqKZiXClmu4S92mBeUl9qC4XZzKN8ygTl2pZXgrn4i15z2nmf0z40Y+CIZBJRNFtrUy4vkbi5G00bnuQ8KZw6q9LmOpp2iJlApJmyfq3EjVVfKiJUdbjsgrhmoRnKL1kbSBkX5Le0qI6mjZF9gSLpjALCcoq21UMthhE6crStJYMAVrBzGiazhSJpN+fH56FxpcMVOQNbehzR0HYEoifhiZ5FNLiD1690H0yzvJgkmRV1oTBXx4/jef3fgDMzwe2if1b9RpxTtxixe8ZgwwbcH2vE6UIStqFDyNg86Er7uMC9JhzEEKViKB7e0jSlYmRyM3v4y3XMW2cilCTHEsuDJSCk9UE33v/Bv8YbHn0IA7/+Mqr/7LP43bNDuKazmr/Ic2fvh16IQvHVzn0JZwO2v5SQWAxYDVsGMslK2yL8vkQI5mPH0NcQMRbq6/z803NBJCTMfSx52QUN7jLJEkys0yLBgqLaSEkmBTmd01mtXcx5QvOmNAYyyFIR4GzrN1uEGiuzRCwLlPIgCgqF8gvkszkmkURkFSrsM5RfsyjTnEOe3sspG6XFfzNH/zEBN5bHczESUGiXFEk7FzYqRuqLmEci0IGcqwq+yAlkXFUYc7VxUw/yZJcq+9Zz19x8U0EnVCW74c5NYtDdgdrUGdRnetGjdqAlexqNuT5uIX3O0YnRZI4Jc/apX6CgqEA+x9NXN2xC/9gY4KlmO0XGKT6jdCWgYqwzEUqSY4nlg/Vyi/VxhaBR976d2/Duv/o4/uXvPorU8fuR23kDjg/HcWPhLBfkxRt2IxA5ueYv4UhIrDaQerTUMKPTFlV8twArxVogxtOJ2uJhFofNR4EuEPmktAVLvBsNRkxCarfrcKs2JNJ5NrgSkXM6dCaS8wVbB6zrR+KtRoV+U/FyBFIvS/23s4EJcU6HXhB2C1KLTQU0T+cBbRMVIFKbZF2Ho6RZCb+vhNSa62MWF1oVVXN5RMyJJFOxHNfelUTVpTI6F8mxsg0F8fBOnNrzPvjiXUj42zHq24ZCTkNWEXYJqyJN2x6OHkcg0YURVxunVFhP6TF3G5L2EOrSZ5FUwxh1bsKmzBm8dPw/4dci3Dnvp+E34q5UECGPilMDXTxduKWDj124sRW54/fAtfkSxKMRhLz1TIznXROwjkQoSY4llg9LYNCv8bvwquftxO82BXHsmV9D3XkD7j05iiv2tSPtrIJn+Flkg3VwVHeWuOUkJCQWCiJE84lFqxSsqC2ygG8+PHeteIxpvyyljcLM013ImIDaBpMqXM6CQUVcNGgi/yp/3zoBtUCm3crnPxvZpX1A1gyRvyxsPQvZLzQYimco2o8CjRS4SggwbQOd47xNlOrA0XXTPdcmqS1oChe/keLKtpIZxi9EkuOpPNsY7Or0ZXLaCPVkpnMyrxTXiQgy3TjSzhj0mVdWRMGhSPUIRY/jwKkvw5WdwGY1jMe3vAsD7inbwpB3O+5ueiv8iW4MOVow6OjEvsm7mBj3qu3YlO+CkhxBQQ/CVUgCuRRCTgV/4rgPTxcuRbejA/rQSSgdl6F7eAI1tXR1lq4kLG+7+NWM+Q/3JCQqhdWgT/dmh515wDFyBG2P/y1u3zsO+8gxKL0H8VTPJJ4utOLknv+J7u1vQP/FtyNZPVXpKyEhsTgsxvYwu+dVX1wB3zzj2lY7MTYtH0tJjIlQEsGdLzE24+KoE1u8zL4Wl9kLyFIMHjUGoecoXozbJusVeqmp/fHsx8UktrF0fkH7hQYGZp4wE9yckWhiDMs4QcNyfnNBW15DKqOxraS0AJVtEtkCJhPZWdeH5inadotl8joYO9GaNlJunayfN3PfUPQbFd3R5yaY7II7O4EJ31a4cxMIJbunNy5hgrwNR8I3oN+1lSvxRl1trBgTMY7bQjiUa+b3BkefgVtL4NKaFG6NfR9/GvkK2vNn4cmMQ89n0TeZ5jlSUd58rtKsN0jlWGL5MJtBv9I8xNGTcKVG8MIdAXRUx3H2gf+E89UX4fuP9WLzLdsRr9qJKo8LSjwDj0NdUHckCQkJTL9MzDlVSwfTh7lQmEVM8y0+W80od4l+sfMThY7zm5+ZyMCd8IznOCrMSK8wSbM11ouSFGwOYb8gK4hT1eGe5bt3PskbZvY1LdvpIMXWtujcbHHVgQr0hHJdDkRUKeqNlF2baacwtn/KQ6zB4VDOs2KYFhYreDqyJVAesy62p9w6kSOlXMGduU6prI5xz2a+UhpOnELKUYWId/O0ebEDw8hVFo9t6HF24L9r3oSa7DnukHdmMAibkoN+8l7OdL6o2QVqJRIujKMx34utV70AR/uPAy07kYpHUQi4QKtvpl1sNEhyLLF8mMmgPx+7Re02jmtTE6N4/9Ve/M9fdSN35A507b0F958cwzXbapDM5jAa0xGOHOcR9QUJIF9HYecSElZwR7Aljm8jNXOhHFAoffPwzWrLl828VDAJ10yX6Oc9PyqmW4CNophgUfI8Pc7kyY8r9n/Z13MFeJx23gbqqOZWnWWXQdNXOtiyHmvOS6Z6MYfoCjefacvBTHYgi0Q5n/HUtpHfWEdKI5IMzgs296tYJx0FFdMKF61d9EpBHefo3KcixtJkC74iktH4Gr7TRg1Xzv/k0dEZ9mxjK0U42c3+YvIci3y56e+lVA4FlOMsuvb1uDrRR7dIGhPJKKq9Dhw73cMxbpe32GFHHjG1BsOOTdi8twPHu38Gxe7Akw/cjeaXvwoaR9RtTEhyLLG8KGfQn08eIj3/ok+h8Pi38RL3HTgaHcFXHv023Nuvxvef6EWN34F9LSEEJp6FfuTz0LQobJWkVywG6yzsXEJiOS0VRAQXGglnKo7zLcBbzS2h9SUmxmbCxXyn4ei1Wdg0FWRlqWlFSXOQUgLtVhXDJkAtoqd3gGMlu4JREZ8jZVRvkyArzvMj04rvMc6vuawaJsnnGDgV5/mQy803mRbHSXiOp95PNow0FQ86bJwlPNNVCrNdNYG2r9SLTGDFnvKI7eV9rqZ9YsS7DUOercWugQTzL/Mpmp6IMbUjId847ZeeyRQO9cfgsWu4eOx3+MHYKNy+WqQvehXu9LhwzH0pBpTNPG1zSytHuvUPDhYbxZAST4OgjQbpOZa48JhvHmLjPqibr4TiCeOSSy6Bkkkg+at/hKro+Mb93fwFrE6eBpLjSIS2Q0+MLsjffCG91BISqxH8g7jE5HihKq7px53XspYpfm4pIQjjyhBjk0iSyjwbMTb94ZTAMPvyNfYfE8inbBJhWi/yFlfqRZ7NDiK6wpV/3Zx2Lm+5aNIxBbKNZOY4CNyGmhtumPtsuh+Z931W425yM8G6XiJqTszH+rr5DkrHSJVJiLGut5ktbcJM0bC22Z56jq4oaDg6GIdf1fB533+i/65vwa2lcODKq/FI8224p+pPMOrbyp0GabJNrcKukVEDSCeTovnIKrcnLRckOZZYObvFc/68YtXVVreNFeFr6yK4ZlsVCiNnEOy+l1WiZ/oiiPk6kHGEgZFnkXaGlzeAfJ2FnUtILFfTD1Glv7B5imze+UeDrWYsZZHgfImxeD8RPm3O/W4WTtIdRZ7NBvIfE8WjZh5mDjEXculLN6AxSXDpFYG51G/zPdPaIBsgokrFhOVg+qytMAvkrPuPzrc4qcszrEO5Y03zMWMSucHKHOtUOms6xWmbrDr6lIKsFP3B9HdfNMPLuD40iCeeeBKP9iThsOt4wRU7eJ9QAofDoXJkHR3mcG0t9EwC9qpmFB75JlxjR1f1VZjlhLRVSKy83aIS/27jPjhf8DEkDv0GH/0fOdz6L4/j3N3fgffPruVotz3XbUNu93vRlO2FrXYbGkI7EFzOdV9HYecSEiZyq0Q1XgipXkzB34UAka2lSqVgj/E8tpf2ZSXHltfxPMKmw+6YeRq2V1AraTulTORgyxXgJPuxsrSDBVa9LV38pmUkL3DAxC2aVeH3nU1pLq4Dq8g68nbhOTYTMYi4e5zk952eTTyTY9cc2JSSdi76y+tQVK2sL9qcO3mi6R+XDBZVYyr8E9nOxI/pOJ4ZSXJudCEyis/f1Q+7XsA7XrAdeuM+YcGwU1ElOLs6bizBpaWh+8IYevQX2L5jGLmWMOBzbrgaG0mOJVYW8/HvNu6Db/A4ttY4cfNlW/Hbx07BN/IMTmA/nuyZxIHWbSjU7IHHZYf7zEF4C31Q67cvz4d5HYWdS0gQOGt1CaPPFqMaz7dLHJGZ1dzow+zuthRgL2+FDVqKjUAqOK5MNsspnYZ6PJP3mN9DKRHGOeSpcAAwn8YepV38KGe5kv1ZyYCAkzdU0dCEwE1P5uomSLF2+lRzESbIWWqxPUWQ59rnZEehZZuts+lYTaWF6LCpIut45nUgIizsE7TLzXvyZhNBPjmSQDJXwHalDz/5939BWnfiwP6d8Lzodgx6tjEpphbYZMmgaR3UaloHat0F9DmrcfepJJAag3L6bmD08Q1XYyNtFRIri3n6d52NO6D6a3D7c/1wOlQM3vHvcCGP7z52DgOTGf6aco0eQfDhT0N76MvQ7/o7QcAlJCRmRSUE6kKoxpUogucRwCW2g6ymGLtSVBqJZvqLKzmu9J7ZMqgrUWipax6RRd7eOUip2XlvIcjnCkhwjMXssBbDzQUu0jPeW2kWN/uQLcWf7E22nPOlgzXqcNc2+Fu+F68LMkuFguZjE2bhYKmlwdo5UKw3JVOc7zuOZgo41BeFW0/j8L9/GHoqgivaPLj5z96NUd92OOwKWrNnsG/ybtQnT7K9QieSDMAXCHFiRUqz46FeNsxsyBobSY4l1lxxnv2mjyF843vxhnf8ObR0DIk7vsBfLN944CyG41moE2egJMcRC26DFt84H2YJicVgLi/qhVKN5+t7puWsZl+k8NQu3bwqUcjNpIhKyGElqjYdypmWax5ras2c04TiT62bZx/MFBbZ5GTuuMH5WIQ4FYMHEtqMVojy5Jui2qY80wXLwMDqow4bHe52dX2H7+lxcRqNbCnnr6sgyNOft8YNs42CP7diX5JarBjrdf/JUS7GG/3ZJ1FIxXDl7lZ89ZWNeG76XrRkTqM5fRovGP4mrh79Ea7v/zqaMmfgZClZgeauEusVbMavojsQaXoedG/1hquxkbYKiZXFAvy7jpYDcPi246WtL8T3f34HRnueweWOYTyZrMNPn+pD0442NDvDcI0dQ9JXA094S+UnuswvltigWGj3uvLzWrhqPJ+mGMvRsGQpYXZNW7p5aZXHolVA8kQDkMqOVY6iy4hAzVI4SZf68zYdDloHTSsbl7aYwYLV8kDzcavlI8Y4ZWGeC2Fim9FYVZ0L3FWvaKkQCSSi5bViWEymU3ezw92kfyvC8VMIJru5o11x2eyLKFe8JwatpuXDqhybRFnXFS7yIwsGFeP9/tFjiBb8SDz2X8gNncHLLtuEj98YRFifgCtxEHW5fnT79sGbj2DI1YGGzFnUZs/B4Wnn7wC/2/i1rNmCXKAZiapdKFz3EaiTZzZUjY0kxxIrjwX4d6t9TkymsnjJK16Lb33pX/HYf/4dtr3ry3jk7ASu3NwJZcd7EE6fg612K2q929Co6+ddkjoPMr9YYoOCC4uW0LO7UJvDfKdbjoYlSwXT1nAh5zUfYmzuv0rHIpRGAXs5r/fUY3oLv4+zgHXAWUZtXYR9xzqAM20T5fKP5xrokXJLhDXqbcdkcEdxfjRQIHvCbF5fQukmFAmy4Tmmv2kWpv+YlsMd7uKn+D7q3Xze540GeWTrPq+TXoFSJaYe0+bSpPR7Zv5NGB/sxa9/9TNEt92KXN+zcPU9hdf++ftxc0sMw6kzsGfOoMezC02ZLi7lS6ohJsZ0P+FuhZ2Wq+io8ghaqNa1I1hVI47xpr1AywFsJEhyLLEmQUUMNT4XXnfbm/HAPb/HiSOHEL/v/8K277X48dP96HjBdsTCu8QoOJFB0OuEzzXH6T6f5iQSEusIS5lSwZem9YVNN1/itNQNS5YSs3VNmy8qIcYmgZ6PLWA+PnNxCX9KxZxpeio0c5n2CU2blgSxGG84qcal25bllAj7eQOE2SxCpsWBlFwiqk9v/XMmyOa2kNfXU77Z37RllE3tyGpwOW1iHfI65wcTaP60HFKMiRjTY72MDz1HrbiNAr0iFIX3qZleQeTdVMXpb8fA47jvp/8Pdz96BN4//jvYchl02obxxx/5IG4Z/b/wxiLIwY6U3Y/GTBcSahAn/Zdh0tGIttQR9Pv3YsC9DQ7ycesQv5laHrZQE1KpJG8Z7XvnDCr9eoUkxxJrFjV+FxdmvPev/x5/+eZX4/Qjd6Cz8xr06m14pj+KvU0hJDN50Fh+zJOZmxzL/GKJDYqlTKlYqM1hvsSJfrBXa8OPxXiuS0GkrZLjU6kfeTEDIquKOXNXOAhSbLcLFdl4PzfUWMTxIltHKYgslxLwufZVOYvDRGD7NJsEeYBdlvbQpZhpMzSDsLO9wvBpm4VyRIhNlbq4oBLQ7rIOQAjsI87rUJ0iuo1TKQAkYxE884t/w4O//B7S2Rzc17wF9mA99lVpuOzaP0PLxJ3wFSIYNKwThwPPw7ijASPOTXxILoneAV8+wjaLcXcb+lxbOMGCbBoOLYuCvxo9px5Ajq03+oazHUpyLLFmQQUIzSEvOju24J1/9b/xuf/zQZz5+RcQePWn8LvDQ+io8ULRHVCUPHonkmgIOOFyzhLYKfOLJTYolsoXOx8PqxWstM1zHZY6XWMpwUR/iVavkkEDN9+YB/FkFXYB60eHiDu9zWHHoPUhcmzmABOpW0znRXE1ovwCSaHlXGUDcxHwchaH0m0hUq/bZrbizbYMjr4jDzApvpaotrlgLoq2R7Vsj0mGaV/adA2PPvY4Dh45idHJGGy+dthe9k/whBqgq260e9K4eu9OPj5jrjak1HDROnE6cDkGPaKYbn/kLibGw+4O1KfPoiZzDr2eLbwSql2Bz2lHxleFvoMnuZujvgFth5IcS6xp0BdPc9iNG25+EUZHR/Cdr3wG6UO/Qe+BW/GTJ/vx6ks3ATlASenoGU9hG47NPvKV+cUSGwwmgVkKCA/wQqbTVozQLzUWQvRn2y9zqePslZ1H0ggPYBYxsKikoI4Jvcv4W9PhIIK3RF7jskkTFvV4rl1RzuKglZx/nBRRIFtEeXI81/YXC+xstvOU4JnARNzwEFttFPT86EAPnrrnV3j63ASUi/8YSvPlcDbTxuYR1iPodA2g0ZFAR8c2FMhqYQeGvdtwd9NbUZ05hyF1EwbdncVlDTvbmDATMab7iHczVLG6fGXA43FBydkxNtQv8pdppTaY7VCSY4mVwxJdomkIeTCSyOCWl78OQ0ODuOPH34GjYSuexDa8eH8TNM24rHX2ILKnvgxnZmJDjHwlJC50hNtCvcvzJZNMGldpId5Skva5Csu4AG+esWii+HIR65SfvTkFrxf7kQUppFi3fAXd8mYCd5qba4BgFP/R+yrxXJdaHMrxdjOzuVQ9pmXoFdqLbE4dhYIgnOeBZquXf4q2x65qOH7wIdz/qx/gxNOPwX3ZH8Nz6augx0fRlj6Fiy69Eh2dO1ATP4FgMoJx9070uzqhklLPCrCNEzHMVAw7J30IZk8K8p1Nb0V9thcRbxtnH+dTGWhkqbDb4Ha6oNiBbDaHeCwGrSmw4WyHkhxLrAyW8BINqceNQQ8m4zn88RvehcGeLhw79SDsjdvxq/ufxh9fezEyecA+cQq52AjUln2wjaz/ka+ERCVYQm68IHWQY7cW0CltNcLsSLcUqMRTPR+l3kxoGHW2YdS/fcHrRcu0keVglv7QXLxn+JOZ3CoLP14V5TqT1WMRJ/JMBXazqcezgVMkzAQKVbR1njMtySiwSybjePLe3+DR3/4IY4N91OMZvuvfBue2qxGyZfGnt16CgPfqYsORicAODLgFUVWNzxI19SDbYX3yNMJ0zF1tTJLtrAKLfORR1zbE7Dt5mVohD6oPpKg+as89MjEJLZlFbV09fD6vONIbzHYoybHEymCJL9HU+l2o8TuRyLnx7o9/Gl/79P/GyfgoDuZ8uCmThd/pxJh7M19CUgcOwxWsX/cjXwmJSjDfPNjZ1dyFTTdfrFZyzD5o/cKoxiItorJ9ZyY0uLITSKphPL7lXRhfAEE2VWeTgM0GsW72oo3DtAksZJmVgMi4Wfw2H7ASPFOBncUzbWI+HxdT9c6WyYimvWFq/rSPBrpO4dG7/xuP3/VLZJIJft4TrkfNH30QCWc1ttT68JJ9W+B3i7oZ2v3mriGVmAZTRMDNaLu65Ek8r//r8OQmkbCH2GJBBNncRXRHBFrXdCSzwrNO+48SNuIFOwrj53DTy14Dh+qgMsDlsR2u4gI/SY4lVgazXaKZ6QMzyweJ1OO6oBsTySx/abzhPX+FD/7N38J1zRvw8weP4lXX7kckuAMnd78PDfle1LXvRnCVfRglJFYCS0U0F1ogN18bAhGJxaQerIVGKkTK5trG+QwqzISGMW8nwolTCCW7F0yOzfWbq78upRzwwMtokzxLKfSsqPRY07IWYrWZbfYivo6I/fxItyDpYsZ5sqHQ49KM6HQKzz71GI498SCOHXwQ0YkxY310VLd0YPMtb8GQuxWJnIZLWkN43rbaaZnORGzNTGkaqNDpwPnHxms1qW5485MY8WxBXfoMGvJ9GLOJY84ZybS3mBgXeB877TZugDISywB2JwrDp3HZa9/IPmTm9UtNZFd5gZ8kxxIrg5ku0Vg/MHYHsO1mYOvzxWtzfJAagm70jCWRyBTgDYRwSXstnh45i2e1zXj06SN4/uUXYYS8Vd7d0DweuKmiuqwZbO2NciUkFoJisc0SYKFpBPMluqtVNWa/6xKt21wFc5wJPY/9ZiY0VCVOIeWo4gKshcBcZiWCtU7d3UiNpEloe+wLLRatHKTQqvNUj+c6/61xdJXCyqXNeDZNt2F0oBdHH38Qhx97AKcOH0Q+ny++z+FyYev+K1B79StxNh9GV6YAv82GF++rx/6WINJGIaRp0dg2didqx59Cf3AfTtW+gJV509JDKXQTnna+SkDEmO4nPG2sMPM6aTrH1ZFtpCpxArXpbow4W5Gs3oWjg3F+T/7c07A7VCbb6sgR4IFPLS2RXeUFfpIcS6wcyl2iMT8w/gag6z4gNgT0PAy0XTXnB4k++C1VHq6UplHxS1//Npz59N8hGXotftNlx8WOn2P79h3IOPdiMpVDIJFBY8izLka5EhILwVIRTSaGC2z8MV9uvloj3JaStFMU2FKq7VR89tTWd8Ed7WJivGDV2FgsF43ppIjOwhpp4EUKOJQFnRtiFvObUKPCPIrGWEJwfJ3FM1wJ9zaTJ5LRCM4eOWjcHhceYhM6UN3QjJ2XPAc7L7kaubrteODMJJ5J5OB26Lh2Ww0u3hSCz7BRkDosIvR0bB35Pa4+8WmohRS2j/yOXyeCrOoKfz5ot0VCO/Cg8g6EUt2cYzzi3TbVQVHXUZc4gR3Jx7E98hAULYeUI4Q/ON6OE0NuaMlJaKPdCAd8bMBwTJ5eeiK7ygv8JDmWWF0ofmCOisf0YYwPiW+kCj5ITSE3JhJZJLN5+EIhfOAj/xuf/buPIHnVO/Hvj0/ix4Uv4JTtfUioezEczaDK44DLqa75Ua6ExEr6jRdKDBcy3Sp1VCxZSsVcaRJcwLiAnTDm34GsWyQXLIXCz2LwLESRXieOb1OE3cHaEGM2BCPHEEh0IeZrn3fhoODvsxcLlqKi5AmyHVSw7tlMGl3PPo2Thx7H8UNPYCSRh9q4A7ZALZSdL4FvvxueUC3cgSrY3T5Qi6pTeR1HhzRgaIStDdd0VuPApjBcKrWvmoLdJMd0lTTyNByFFBKuengzw2iMHRbk2G6jPc3vsRuDovHAdhaMKNWEkkbo/GpOn8aNg99Efa4H3lwEXf6LESyMIxEZQSTdgtyZR7Bl5x4uyCNSbpuLyC7kquoqL/CT5FhidcH8wJy+CzjxW0GM6cPYeaO4zfFBcqh2bKr2IpXTkMgV4LQHcPtL9uMTjz6C4S1X4odDA3hO6xlMVO1E1GbDQDSN9lr/0oxype1CYoMmVeQvJDlehRFupCwupQq/HL7mxVo+SicnVXg2uwG7KVg3FhSvEnJMxHj38S/CmZ1Alls7vxuj/soJPTco0TBvjzAdv3imAI/DVrQeTHvdYq2wbkMmlUTvmeOCED9zEL3jcSh1W6E27YB67fsRcBhhzwZo1vQbZVdt3IHPb1fgUG1Miqmg/Ir2Kk6LMJModMt+4xsV0OnAUOgAOod+C19mGDm7B0OBvcVlUBQblcaaNp9w7DiqUz0Yc7eiz7UV1AW6PnaOu+cNubagI3eQG4WMe9pwX7yJ55E99RCuff1rWQH3ulTYGw7MTGQXc1V1FfcVkORYYvXB/MCUI8MVfJCqfU40V7kwmcogkQVaL7oOTd96GwZrN+ML/ptQp3tRpyjI5vMYjWVR48sh4HHMTnLnGuVK24XEGsRSFbYtlHgtZLLV6KpYKgWe5zXHBs5luZgJi/WWl05fke+YGlroOheSVbLWpBgTMY76tyEYPwl/omte5Jh4OK9XhR7hVK6Ax7sm8GjXBCaSOX6OCLLPpcLvUhFwi3u6VXnsyEaGMX7uFPpPHMK5U89iLK3D3rhDkOHL3gqvKsiwohUQVrPoaHCjs6kGtX4nE+DaoHOaqk1FleUGO0SCzc+UdVDBhXe6jrP1L+DH9ZFDGA7tR0/dTTRC5QGL9fzxR47huX1fhzcfQdwexJ0Nb8WwbxtGXKIJCKnFI96tOBm6Gr8qXIWDXTbkB4/DFunnxloOVYGb2LT1d5l+6w7/eOr3cZ1eVZXkWGL1YoGjShrtNgQ8GPFn4e95CmqiCy9+0c340q/+DZ7/8TF85pE4PtpUgM9tRzyTw0AkBY/DDpWK82YjubOtzzr9gpBY31gqcrxQ1XQhhG2pCgjXYlb0fAvUrFjsXivd7dxPYg4LA59fBrGr5BQhKwUpxkSM6T62gMJBVrTnwFA0jUfOTuCpc5NclEbf/wc2hZisxtJ5xDN59E4kWYU+Hx1Aewf0tpfAbxPEUdHyCNnS6Gz0YWdbI1rCHlag07nCtP1WmnxBVoly5JhIMBUXEqybw9FrRhHtyZrn41j188XjvIZcroAkhRVDgdNO77WhMWsoxJ4tqE2dQU32HAZ9WzHg6cS9zW9DU6GfFeVDuVb84plBKNkYUnd9FTe86GVotY0gePYx+Fv3ADWXihUo9/u4yr3DC4UkxxLrEhTttqVwFtqxLwCpMbRuCWPo+ZfjJ4fvwMS+W/D9R0/h1Vd08hdT/0QSHoeK1hpv5SS3VF1ep18QEusbS0EzK+0Ydt6yZ8mXnW1ZG1mBX4xCvZhVnGlAQtttjRc7bzrzf2W6wZVDNLQTR3e8B/5EN+K+zZik7m7zWPHZFkMDi2ODMTx8dhxnR5P8XFPQhV1hDZ7YOYweP4tobzfG+7ow3NeNXCYDONyweUJQvCHYvFVwhesQbOqAu7oJTn8Ymxv82N5Sy7Uu5ewYpk+4uA55HQ7n1OvCLnH+wIGm40YiYgRSBBcGkp0jN5UpXps4gWCii9XgvGcrk2pOrcjrGHS2cqFdQ/oMEtQm2tPGqRZ0Hg15tiHh3oWBSBr/fXgAuqYh9pvPwlFI440vuxGtT/0rPPkInL21gO9jM6vEe16+qr3DC4UkxxLrFlWpbmQyA4irIfhSA7jtBS/Fg5/+HkYH2vEodiDoH8ILdtXzF87p0SioLq+hUm9xOXV5HX5BSKxvUNzWSqnGC5nsQnNj78Sz8ETPIBXcgmTVrhnft2R+47leX8RyFrOG+mzHY46iPLsyD3ZsEGS6MVgJFaAi61RWJC2I+GSRkGIOskQrbU2os1wpKFRWer5raBJPnIshkQcUXYMv2o3cs3fj9LP342QuA02xQ1Om0yG7qqKxtQ2tW3ejddtutO/Yg9bNHbARuaQotPKy8uzkeIb3mHnF055XgAx1QNSpuYfR9KWg8bYRqaZJiBhf2fVVePKTHNd236a3cypFQRP2i0H3VrZS1ObOYdTRihH/do66cxj2HKq5IcU4ly8gfecXoY2cwQv/5DZs88XgzE4iX7cTnsjJKZFopt/HVewdXigkOZZYeZTz+C5RcZszPYpwtgd5mxtupx1vfO//wv+5/Z3wvfiD+P2zQI3PgUs2V0NP5tE1loSjfgeqTZJL37i0DgTrOsykLq/DLwiJ9Y2lKG5bqGq6Gu0RpcS47al/hZqZQN5VhZ6LPlCWIC9EAS/FYCSNe06MoHcyhYaAiy/LN4fdaApOVyRXbF/P1EGugtlOz1yYv0Uuny/gruMjuP/U2KL85lpiAtlj9yB7/F5MpqKwaXmo+QQCDgVtdQF4t16BUMdFqN/UjoZN7RyzZlenalHoMBAxFutV2TJLleFygyiOaDMSSszCTtFZT0Qd0rK0HHmTteI+oXnmNA3++Fm4c1ONPqrTPUyOdQVwcvcOYCK4A6MapX6IRh8ESq544twkDp2LQNcKiP32c9D6jmDr7n149RvfjpQ+AM1dBe/ECSiBuukkeIOIQJIcS6wsyqmwhCXKFFZ8DVDqqqFHR+Bxqti15wAciobEb/8Fta//F9x9fBT7W0LIQOcIuNMjUXhbdsM92zpIC4XEOsBSNaxYqN92NRbWWUGKMRHjZGg7vJET8ETPzkCOF77/n+mP4O7jIzg6EOPnSBU8MSSaMBCIBDUG3WgmshxyozbgZMLsIVPphcRMZHCu5h5suVkYOc5lMzhydhC/ODaJyayCANIIZEeRTSeRTsSQScaRSsSQz2ZYXeUTUafcbGKZGivEvHx6LhWFJ9aLlsYWND7vBia/+30juKHwANzNuxFOnMah1luLhW7lt2VuO0Q5UHrElMoslGyTCJuTa5qGNOcPi+VwTDIpvHYbcoUCE2ETJjEne8SYezO3hq5JCdsE5Rnzeyxeby7mswHZPB0JDecmUnjg9DhimTzyY71I3v8fcKVG8cr3fQR/9PJXIexzAfZaTD7ng/Dke4H67dN/fzeICCTJscTKopwKSx/spShuIxIbboUtOQZnzWb4W3Yg7HDgqutuxn13/ALxQ3cgu+8WfPexXvzpFZuQoC8LigGyR7F38jhUcx16nwCe+i5w0eum1nn/q8WXzzofPUusXyyZT3ahauYqjGSzgqwUpBgTMab7VLCj7Pum3J+Vgb5nHjg9xkrxaFy0u7+kLYwbd9ShrdqDkVgWfZMpVpH7J9P89+PdE9PmEfY42OfaGHKhOeThe3rObFRRipmeXwpuPCsoAc0ShlzI5xGPRRCbHEcsMoHI+Bgmx0e5dbL1Pj4+jNz258Nx4KX8e5B56ueIPP1rylQruxivL4BwbT2q6hrhr6pDVV0D6uobEK5rQFVtA8I1dXA4p8eqhaPHUX3qNNzJ00g5w3N2DSzdVi6aqyBWj5InCKT8ciKcEcs2NV+diSt1wJt2KhGnJfsEZ0UXn5pWADnq24Z7W96GKopqc7VixNUJh+FLtoKI+JnRBJ7pj2I8kWPVPPnwD5A5eicuvvZmvPJtX0ZbUz1n/pPNw07Zxo174ai6onKZfJ1BkmOJlcVMKuxSFLdZLgHZaraiuWEv1Gga7/zgx5BMJfDEAz/iS0ZHcAme6YthX2uIPW5DkRTCtha0eaphI2KcGAbO/gEYeFrMt5CTXfIk1jyWippeSIp7IX+nSSUmKwUpxkSMZ/Icm2MD/+Qx+GJnkQh0IB42PLMWRFM5/OzpATx8dowLgSkm7MV7G3HttlpU+USVFqUbUBQl3fa1hIrTJrJ5nBtPomc8xQVU5BU9PhTDs4NCcSa4HTYmzKQsN4bcrDTXBVxMdAjFAq8FYCZyTaSL1Nt4ZELcJseRnhjEZCyJRCyCRGQcKYMMx6OTSMYic1o81OoWuG/6SxY09NEzcDz1I1S77AhecQ2CVTUIhGtQVVvPxLe6rgGhmnq4Pd7i9LQPFaMoezZQg4ynt/45gsluRLxtGJ9ngxQumiNPsGVfmAWILADrlLlsKMVklaBINu4WOBXNZvqkaQKzA97UzhW2CmrBrZByrFAKhe08O89EYAdGfNtF+3YqxiM7oTEgoeYfJ4bjeLo3gmg6z9YQz8izGPjtvwHpKF7wmrfj5lfehtqAm89H81xx2G18xWKxg6q1DEVf7cavFUY0GkUoFEIkEkEwGMR6A13OGR4eRn19fdFPtSLWilIPU7nnlginhqI8iv7WF/4Jv/vNf8P/ir+H3+3EJ65W0ZjtQTa0Bc6WA9iGbjSc/bEgxi2XAl33i7F7+zWCuD/nz0Wl7jrFqjg3JJYN9MNJRU7zBVW1j42NoKamDorNhmg6tyDSRb5Hs9nB/Jo1zH+dl3s/OkePYuuRz8GRmUDOVYVTe95XJMhEgO47OYofP9nPubrtNV5WiS/dXMUkxAoidjMV9xH5yRi+U1OJHIll0B9Js2eZSPNgNDOtUIzITn3AxaS5zu9kskyPqdHEbCjkc6zixibHEJsY5/vx0RHEjOeIBMejES5wgzsAm68aNl9V8aYYjxXVCT2Xhp5N8z3o71wKKjQ4bETo7fC4VPjcLvi9HhTcVTiW9oPaWLw6cATv8/4GJ9tfh+7Gm+d1PMiyQjUm8wEdm9nOY6KJpp3FbJdOx4u6zvEeL4lsY7JqARFd1a7ApdqLJNf0Gk+te2GaQk3TECgRhI63nadXmUjTZ8F6rMU66UimCzg3mULXeBK9EymeH3Xb2+LXcPIn/4rhU4egqg68+t0fxuU3vBBO1YaQx4G2Kh+r3JTxHPI4URuYrrSvl9+TSjmdVI4lVh7lPEzL6GtqyZwBhg/hna95IQb7zuHoYz+CcvWf4tv3n8BX6v4LBXcYZ9T3oXvTRQg3XgZX94NA3xNAoFHMQMa1SawDLJWt4ULKK6Rk0b/VZskgxZiIcTy4Df7oSfjiXUyOSe399qM9HB0W9jrwhue04eLW8JIockSs2Ysc9hSfI3JEzSxYXbaQ5oM9k9OmDTgAv5KBKzsJW2wI+dEuJEZ6ETfIbzKdhc0bLpJepUh6O2DbfClsu6tgcwcQKLdiuga1kIYLOTjsBSgeP3RbmFsl53RqviSOHvHquHEbMadNA60BBX/v/y/swWnOOk742+e1Xzj9YQGGdnWGzOHq+AmEk12Y9GzmYyrUYGNTOSWjDDkv86FQbTbuTUKDnxx0w2YhovDYxmB4jHkAZExelziJuuw5THg2c6EdCbtEunVd4fW1XpU4O5Zk0YcGSAR6mQo7t9Z5kTx6D37/zS+xj9vjC+D1f/m3OHDpVawW06L8Lgfsdhuvi9+tImhtirVBIcmxxMbC4DPw3P+P2BQdRtgWwl+//x348N99Fv0n7sNT25+Hf0i9Ah/Bj+GYPIOC3Ybs8e/CWchBsTuAy98qbCBWRVu2jJbYwFjMhcfZmkfMOt0i7AHLAaJ6ZKUgxZiIMd2PujfjB4/34s7jw/yem3bW438caJpTsV2sMpdJJZAZGYYyOgTv6DCqRof4b9dkFOM5O1J2PxBqxmRNG6KhJii2BiBAt/3QmmLQUzE4fGGEnVM2BSuoyM2JPLwqEaoCQj436sIBVPndCLpVBKiTnD2FvCPAB4qOsNepwuu0F+0EdM6QV5euHFARmnkFIZ0XDSx2NQaQizlwysg6jvm3E6OcddvJPxxMdiHqbWe7RH6egw+TzBLxLMbDkesvfgIXd/8b3LkJpNQwHmt/p1gfo9BNnItiWhrwzESMxetiQFMoaTdeMP4mMkuNO6jQjohzXfIkrun7OvxahGPaHmh7ByKBHfwaredoPIdTwwkmxWPUCtYg+J11Xmyt86O1yg2kYvjpv/0DTj71ML++Ze9leOk7PoTOzS0IugUBpkFbQ8ANt8vOx4mIspMaYm1wSHIssSELANWGPXD3H0ZddgDv/Mg/4m/e+nIUArX4BXbBp9+C6z2bERo9iUJ8FKnmi+GdPCG+3ayKtmwZLbHBsZjEiYWKp0RKVqIZCHXS7JtM49K285VfUhTJSuGNdeGe+Cb8xx/ymEwOo6PWi9df0Ya26vJk00Qul8XE2AiGh4YwNjKMyMQ40skEMukUspkU0im6JZFMpZCl59IpZNJpZNJJ43Ea2Wx69g0wvLAEf6gKvrpm+Fq2Q63dDC3QiLQniIK/AQGnirDfhSq/l5VFIlF0T8SJyFfptlOLYVJFxTJ02PLTXzcfEeEiTy1N71LpZkOQY4Fmzzq20bEuX4dXJMYHTn0Z7uwE0s4q9hGP+QSBnQlTcWlTKrCx+tNsLcFENxPjEbeISgumejBszNs8B+ntTFg1TZBcKmgrKbrj/WDsO7edjvf55y/NRyPrhE3h+L6aVDd3tzNj2mpS53Ak34bTI3GcGkmwh5jgVm3Y0eDnc6017IHLpqHr2adw938/gKMP38U+b7vDgVte9+e48pY/htNpLxJjj9MmBi8u8hsbf1/oJJRVCkmOJTZkAaA6dgyOQC2U2q2od9Thhpf9KX713U/D9/K/xY/03ajKbcIet8ZVzPbBI8iG6uEsLQyULaMlNjgWY29YKDleqRqh7z3Wi8e6JnBRawi3XbWZi954fYwGF11qB757UsXh/igTjNdf0Yqr2oOIjo/h5JFTTH6tt0m+H8XE6DDisahYiNHcYiZUsre9/iAXrFFyA6U0hGsbigVsnmAtgmWSGyoBqZ2k9M4XHEvGLY2JHM/CcmcAkUwimzN1ByTFmIjxhH8rwvFTbGkhcpzP65wkUoxLYwKrC55NSWeW9RP3ChTi+MYmkjo77Gpl1ZbIKSnHkx4RlXZeow9qSGdYMgoFWoZYABNdVpgVtlSI99sAVUO2UP54EsFWFB2T3nYcUzpwbCKEJwqvwqPPbkYi38fvocHKRZtC7F9vCLqQmBzD6afvwRNPPYSuI0/wgMlE4+ateOV7PoaW9k447XbU+p1wqDbebr/bwT5qWk9SkGm+G7kIzwpJjiU2Fkj1pRi23sfg3HQ5/A0XIzSRwMv+7G1Ip1O497EfwXbTe/Dv9xzFO69phXP7u9GQ7YO3aQeaq3bBZ52XzDuWkFgwSpW1SkE/5JbGaRcMb7p6M6ud1IzicN8zeOmBJvzRgWYmUb8+PIhfPjPAntUrO6rxqkta2Lf5T3/9Phx86A8VzV9VVSazwapahKpr4fH64HJ7xM3jgdPlgeJwFf8W9244zffw+3xwumYmvlTAtdBufkzwFuLn5enE9KQek/VgvmA7AtsuBKyq76izjQlsMHYSSUcVxtxtxeI1IqxmZ7m5V1u8IVsoGPYIIO3uxB+a34aa7Dn2HEdmUKTLnsn6FFGm/eZQ7VNXPox9Qes55V/WMZ7McXxff4RSSRxI5V5bnB2R2r21PnTW+VDrc2Co+xSO3/ML/O7Jh9B3+ti0RdM5tPPSq7H3imuw/cCVsDucPMCgQZvDYWP7i8dFhYEqGoJOLsCjPgASU5B7Q2JjgawQh37A1gpl/Cxar+1EwrsZkXQeb3nlCxA4/mP89qH/h8w1b8KnPvtF3HrpVrzs9W9F0GWHNpbElno/j7rn1S1I+pIlJJaUHK8Ewl4n/vz6Ttywow7/8WA3fvJkP+4/OcrEjRIjqLPd669sw87GqTK1qpraIumlv6tIya2pQ3VNHUI1taiuqUeY7mvr4QsEOQc3Mwvzp3SRxRhKaN8tptU1Z/vOmxwb1WEGySVCOF9XDE1OcWhZ0xNseW3Uvx2PbXkXQhzJthnj/u3cepluSaOddDlQ6+WqVDcXu41aSC/FrZkqMNH4Xlcnet2dnDTh1jQmmeerq2SFKIlimwYduTw1TJnyJ9N6DceyRbsOFU5y1rG5fj4ndjd5sanKg01hN5DP4vThx/HwnQ/ixJMPIzYxOrV/FWBT527sufwa7Lr0GjR3bONlmF5vUu5pHxIBJmJMxNytqpxeUut3TevCKCEgybHExoJphfA3AMNH4ei+B1svfzcS6TxsmR586o+asfd4FF+JD0C//FX41WM/RGPrXbjqedejoCVYVdha74fH5agsVWOhvmRJqCXWABZr/V1IcZ0ohBKFXSuBXU1B/P3L9+B3R4bxXwd7meT8j/1NuGVPw3nRbLe956/wlg98tOJL1bY5qC83hVjEdnMiwyKyqTnbd57HjAvNLJvvVO0zDgCK3ePon+H/pe5wHOFrdJEjlO7OYc9WDHu3CZ5oFP5R0d9Me52I8VXd/wZPbhIpRxgPb35HkSATlz6P6Bqd6+g5Gp6YvmJzoEYvk++6oJWPg6PnKHZvJJ7BWCKHoWiaG8CYb1UMZXhHmPKpPWgKuuB22jDZ343hZ+7Dfz32EE4+8wTyuezUfnR7sXX/5dh16dXYfdnVqKqu4cGVCdrnRIpZLbbb4FEVBH0uLvjzueyo8btQF5jB9C0hybHEOsNcpJKep+SJrvvE4xO/hafzRuxq2o4To9uQO1eN23ZO4ircizefuxXKla/B//3Vj1Hf2obOLZ0YimWgKcB2rZvby864nIX6kmn9T90JnPydbDYisaxYaFrEtHkschbs16ygy1ilsVsXCkSEbt3XiOduq+GcW8quLQfnPL29UwkIM7xOyu8it1t4ZPULdsyIRFpjx2j4QFPTfjNJMEeiWSg7kWQ6vqUqN6c8zLho3fIeHU6jSNDMCqYznlaD9jEpxkSMx7ydqEmeRjjVw+SYpqVllyO61isWZC2h9S0YkWrCdS6UcVL3I6k8xhNZJsCjiSz/bd0UUm+31vs4c7qBmrYEXbDrBZw79Sy6Hnoajxw/jL4TzyCTihc/pzR5TUMzK8PbL7kabTv2w+ZwwmFT4HLa+BxkCwlnJ+uGn5gykWm97Ah5ROEdF1h6HNxRUWJmSOVYYv2gEpWWHm+7GYgPAoEWINoHnL4LoU5gCwYw2PlyvrQ1qbbif128Gf/w40ehX/QyfPNb/4n/878/gVQ2j0zPMWSe/TxcWhQ2X+3savB8fMnm+o+eENvQ/jwgPrTw9tkSErNgNdTdEHFaiFFgpXzHpSCiQUQkkVm6lZlNHeZmEIucP6uii7RW8PRG5Bn9SaRMdGzTYdc0YZ0wEqmJBMdSed4mU+3n4j5ru2QircY9kX+ef5kTlC7/F+bwLDOhVop1dbzPRLOMqW0edrQi6QihJnkKKUdVsdDOuleI6Fr90dbBJHcGzGmYTGYxmcpxtjTdJpM5xEqa1JBPnfKGiQg3h0UHQ2q0oWcTOP3sMzj5yDO489gh9J46Ok0Z5lQPtxftO/Zi58WkED8X1U1t0/YLrQetJ6nDlFNMxX/02fBRsohqK5J7avJBHnhaLsUJ0r0svJsdkhxLrB9UqtJufb5QZgcPiceHf8wKcnUhC7caxold74Hm2YY6TcNbr92Gr97fg+i2F+Nn9z+Flz33Yjgjp6EnxxCp3YVg/BTsMy3HVLGpAJC+0Obq9ldc/91C2R45CtRsX3j7bAmJWbAKuPGC/cNCrVsdzUCYZJjS4RJgNl8w2xoWuSgi30WCOwfMFsVsdzCj+6gtMmftmjm9NL/iBExuM2SFIIutHUgVCmXJPq0D2SSsr9B8rVcE2CZh7F5OkzBINLVUnsmzTtvlsPg4aDp6bJ3vkHcb/tDydlSnezDuptbRW2Ezsoat+4keTxiEN54uYMJChq3d6Qi0SPKldwZ9CHEEnsp+3hq/AzbFhvjkGIZOP4Z7jx1C97GnMdRzujigMOELhrF55wFs33sRduy/GC3t2+B0UIMOcU7QcSDCLhItaJk2hLxUTGdnrzSvh00pdvKjbTBJMfuMHXZWmEvtPxLrgBx/6Utfwj/90z9hcHAQBw4cwBe+8AVcccUVM77/hz/8IT72sY+hq6sL27Ztw6c+9SnceuutF3SdJS4QKlVpTfU4NmQQ6aNANgZl83PhHTqKpsIAxuw7kdGBbZubsem/vodzNZfjngE30nc/gQ9sp9yeLNTBg0iF22APtGOqR9UMKjYRZCK/5vJnW39Sixv2ANtvATpvlKqxxKoqiFtKa8ZCyTERnsXaA5YSs0WNLWRes75us1msAuVR6scuxpkZZJeeoVg14e8l0EBDxJ3RdmgWQjzDArg4jqenbTcbWhQ0KHoBKeShKDZuE6wajTJKlUrO/FVtSBkkk6wKpVYZg4sXl2nCTJ9gm4QxULKeShyXVrLPNJ1ac089Rx3n6EbbGUsI0kud5iaSeW6JHknlEEuff13D7bChyuswbk6OQKvyiEg0jp0zWjuPDvSi9+AzePj4IZw7/gwmhvvO+7TUNLagfdcBtG7fxzaJmqZWbsbhtyRHOB3UWU/hdtsEr0McGzr3Pap9WptssoOQV5nIL91ItSYrBcXoeRwiso3WX9a0rDNy/P3vfx+33347vvrVr+LKK6/EZz/7Wdxyyy04fvw49+suxYMPPojXvva1+OQnP4mXvOQl+O53v4uXvexlOHjwIPbu3bsi2yCxjKg0PcJUj3seFkTU0hZa8dWivn032uxeDEXS/CX07ne+A5/5249guPNWPKQ1oOX47/DRnTnkbQ70trwYmrIZ27P56VE4VhWbWk8/8DnA7py9KG8+6y8hsUgQqVj0PBY5iwXHg/Flb5Evuxqw2BQIK2h/sLVCE6qq2a2N+DD9RYotdZMTPl0LETaIrkmAp5pU6CKZIdmDSe9UMgMRbDPqjGPRyBphZv7y/5Rpyq14Xik+JtWSiuV0TWEll9saQ4eb1lGsCceGpbnhhUnBxTnDx93w/zrtoniOrBiVwrQ8iMYZU/OneZoWDysZp8fJTAHDsQwnExERJvJrEuDSQ0fHk5RfyhEmS0LYqyLsEUSYSGYpcpk0hs6cQP+ZZ9F7/BmcO/EM4pHxaSo/bWtDWyc279zP6vCW3QdQU1dfXD/2CpN6bCG73Fa6zACUzhFSp8m7LFqqiyYrVOxogp6ndTUL8mhefnr/0OGFFYlvMCj6SpX8LgBEiC+//HJ88Ytf5MdUvdra2or3vve9+NCHPnTe+//kT/4EiUQCv/zlL4vPXXXVVbjooouYYJdDJpPhm4loNMrLmJiYQDAYxHoD7cORkRHU1dXxKH9Dgb4kxk4DNZ3isfl3w17+ou+fSKJnPI1YJotEPIkvfenz6Gq6AYrDjctif8AXOx/E2W1vwGjrC9EQcmNPYxAelzo177s/Kb6AClmgkAdaLgVGngWuehew+4+w2rGhz40Ngkhy/tkFuqZhbHwUNdW1UGw2VtkW8yOSyhYWXFwXz+RXLLXCCiKa6ezM5M4sEmOCa5DdYiqDQU45nUEXaizZDSgZh9hqua0jYmgSZ9p1ZiFZuV1RlzqF5/Z+Hd78JOcB37/pbRhydzL5zlhj1Uz7gnE9gEnwHCo2E2Kjwo6JL/lblRRiCnUEVFDlcU5TNmf7rkmQV9do+FGJH5bIPKnXVtB+iGbyfF6b9gfKDqb2yqXnGBHpkNvBhWpEgPmeHzu4g59mKLFOlQi8nck7Ee90Ms4Zw3Qb7D6Bwa6TGO3vga4bSRpmeoWqoqVzNzbv2MfKcPvO/XD7/MXlk6prHaDSvgt66PdjykJBanTp1RnaNS6HykSXCDF5yEttEjSF32VHwO0QBNskxjTxkZ8Cj3wVqNt1QX+PtFXye0KcrqqqCpFIZFZOt2aU42w2iyeeeAIf/vCHi8/RDr7pppvw0EMPlZ2Gniel2QpSmn/605/OuBxSmT/xiU+c9zwd1HR6jvacaxB0wtJJQl8qG44AKfVAreWKg/n38DDfqZqGKlsG+XwGul3De9/5dnzrK/+KZ7yX4PG6a/G2J8fxjl1NSEbG0RtTkI6OcwwPVQnzvC9+HxAbEL+CXfcDkRgQ2AvYm4rLWM3Y0OfGBgFV1s+7FbOmIx6LQKHJbAqT28XwUyICGUuDh3mtCimOc1gMlhO0fPrHXtBciSXBuDd9ulaYxJbr2gwF2AqKI1MMWbyUJtL7p4reBKkqVXqNufD/q3LDyLmq0ePfjWB2EOHsMCKOBn6N7GBEyIsrVYqikqxMJ89MnCEUYlZqp7bMpWSRh8Y+W1chCzVrE1cYZiC8gVQffJlhTNhrMO5oKj4/pTCfPx3tu1hWw2g8h5FEHmPJAkaT4p5UaCu8DgXNARW1XhU1XhXVHjuCLmqEYSszb9oXQhwjJTcWmcRAfxcGuk6jv+s0zp09ibHhgbLbEQyG0dyxFVu278GWXXvRumUH7KpIhCACy/MsxPmeuKxdsxcPPA0fXKTw5sT7nIpQx/WccViMTSLvMXm13Tq9V7xOw1trkaYZ31Yo2DGZEgSfiHjK3Fa1WfwOXeDfI22V/J7EYrGK3rdmyPHo6CgKhQIaGsSH2gQ9PnZsencYE+RLLvd+en4mEPm2EmpTOabRznpVjukLaKVHc6sVzQC6RmPoHkuhkMrhT9/z1/j3T30Ix71hHKq6Ht1ohs/uQ5a+d/IqHDkXQlU+1AQ8gNXq07Z1mjK9Ls8NUstHTwG1W9fMNm50xNK5eVsaSDmmy+/VhnIcz+YXbSlgb+cCZmEmRSymMM8sOhMX56eixQjCbqCB4nVJGeS8XUOlNS/fEzenx8ls4TySW1wGE2gxEGBvsmV1jR4O09sYK0DWRrYBkflAE4hppybKiCbF1oVMvzfgRA12pcbQEjuDhBrCAKoxrrl5vuzbhjZzPNxsu1UBq7FkizALxEyqOal74HaQUqlCJfpO/mAu0BPLNJXh6vgJXNL1NbhzE9ye+cHWt6LPKWpFiPzTlYF4psD7lpTleLbAsWjjZQriyEtLBXB1fieqfU62RVRZbBBEUIkomsecvM7CZ11AZGwI44O9xu0c34/2dyM6PlLG1KAgWFOPhs3b0Ni+HY3t29C4eRsCVbW8DPL3uoxl8sCTzhWbSLA2zzWFbDjG3GifkBJsNpey0WNq7zw1MuF50ryJzNP73DNEB5LViPzP5vLJZmEW5xVBv0th7wX/PdJWCddwu93rixxfKLhcLr6Vgg7meiWPwve3frdvsdhcE4DNZkfXaIL31cvf9UF84tNfgOfKP8FXfn8U77z1UrhVB+x5HeOpHE4Op+ByOBD0Oqdm0rRf3NbruUEFiHf/g/SxrTGodLl4Rko3M5jA2Wx8E8VO5VmUY+QIHJOnkQt3Ile3Z8b5UQ7rfDyn1vVwOkQF/2wgC4G4VC3+ZnVXE6qpqd4Khc7w4Bok1lSBxUuCnNJroehxVCW7MOltx6Tf9PBOLygjasMEmoixEU0mFF6TRJKflJ0T020ERQsxeXGpw9v0ls8mkabXRWGemK+ptJaCkhnubnoLQpTl69iEQWcnBDMT/mWaxOw6x/OosMiS7CCC+wnrB3eAU3QUSBDVhQeWvzeMdaI1pdXN0XSahlS+gNzwIO6NNaHb/hxEYnmcjGcxoPXzYKmU/JrwOGxMgGt8lARBRFhk9pLSSutv+m7peNHxECq+jonREUSGezE51I/RwXNshRgb6MXEcD8KZHubATWNm9C8hUjwdjQbZNgbCE1r/UygZdN57HQWtXwms0TahYdcJGyQiEz7jY8dE187p0goNrHPqEmHWdhn3kwQ6SWibAXtXtp2mgdZJ0wbBQ0KZkylWKHfI2UVcI1Kl71myHFtbS3sdjuGhoamPU+PGxuNgqoS0PPzeb/EOsAydJaj/Mi2ah/SObpkp6G+tgGXNjnx5OE7gL0vwHceOIXbO/ugVrVhrGoHew+pEnz3phBq/fPoQLSWu+LNt9mJxDpLrNDLEuPww5+GLT0OzV2Nyav+akaC7FAXnltMZIGImWYQXUpMIALGcWMULCMq2WaF2TzBbO5gwiTEJmHWDbXz0jNfYbUz7ajC41veJVoWW+LCrM0YLDMrWer5K2USXCa/GoqJEKVTFWvwjEK6IowiN6HiKsX59bk6cc6xpey2s5JJFgnKF6ZZKWYHONFKedbEEPbWiIQN3S4yiumW1gronUzzPiBlP5Et8FUKIr0UizaVC02/xf+jOE97GvC7dSa/RPTIHkD3frfw2JKPlqLIrCrw1DEkq0keo/19GDp3BsPnzmKkrwsjfd0YG+xDLpsub1Oh5aoOVDe0oLqxFVWNLahpbOW/27ZsQzAY4N8As2hOXDEQJFwsU+wvFyVEOEzHtrE9RnEl7UfyXptEl9/vsPF+I7LPiRt80MvHE9I86f0m2bUSZ7JZqEbXO85GpgQLh03mGC8Sa4YcO51OXHrppbjzzjs5ccKU6enxe97znrLTPOc5z+HX3//+9xefu+OOO/h5iXWIhbZqrgD05bWl1l8synjtS67H07d/AJnEGAaufA0+c8SPz9X+J3p3/BmSVbuQ6z+GkZ4+6Fv2om7rZSu67hcE82l2IrFqsBQCDs+jDLElxZiIca56Jxzjx+CYPDMjOaYfd0WZ27tsLWYT5FcUZcVSWSZgMxWlWZ8zxwMch2WkNdA/k1Ca9oAiESqJrAsnu5gYT/i2oipxCqFkN5Njc5CQZaKuoy55EjWpbox5NnNkWCUw/cm0naSG0zrQdjLJNTKOzfbZ5n6rTpxAXbYHI842DHq2WlR8IyGCiK9BoGeKiaM5k+DK5N5IgGDd1iDKFMfGudKGGss2h2wByXyBUyAS2bxxX0AqR8eh/PYRgaOEheaQm4vF+G8MoxWDcIWbka/ZzttmHlsi/uZxsCKbzWNifAij/V2CBPd2MSEmNbiQL98mha7+heoaUd/churGTahp2oTapjZWhr1VtdDMqA7z/XYFXtXGxNial0yOBR5EUQMOmx0eh7jCQMeHEjym9qlQuUlNNjsEcjGd084RbDQvIvylSqZZjGceRprG6zQUYco2tthS6JhQwSCpxvS8+T6JDUSOCeQFfsMb3oDLLruMs40pyo3SKN70pjfx67fddhtaWlq4qI7wvve9D9dddx0+85nP4MUvfjG+973v4fHHH8fXvva1Fd4SibWoXjoddi640waewSXRH+KhXS78+OD3kUuMYvDG9+Afxq/HGyd74IWC7We/Ak8hAnTVYEz5CGo6L1/RdV92yBi6NYm5MnUXoz6TlYIUYyLGdJ8LC+XS9OwatVxFwks2hnSWsminCKvp52VF2GgwwQqnQZ5MIkFI5aYyaUvrv6zEl9VgbaqT2nQbgZgnF7uVEDzTEjHiaGV/bDhO3dXC3F2NyTWUog2DiPHzer9WTIi4b9PbKybIBDPWi4iO2Ae8g4rryM0wFAVN6dO4ceSb8OQiSKoh3FH/FibI5ynDurAz0B4SKqVoWiHWmQoiNb4RsSXiaz4mgp6x3Oi1mbKlyXtMSm+d1wG3y8Uqb8jjNFRfO3wGcTNjxaYQRg7buajMLUYi3AnPbhPHITo2hIHu0xjqPYuhHlKDz2Ksrwe5XOY8FZhtNm436prbUdfagfqWdtS1bEZNcxuq6hrhdjqLDTXYImPxfwtlWPjKCV6D2JYDkV3uSGcQVVKy6R+dm/SP+DQ33LDbEYgcRyBxFtlwJ/LG4JCL6shKUeazw4qwsWX0Pk6sKNct0LBO0O8SXT0hS4bEBiXHFM1GqREf//jHuaiOItl+85vfFIvuenp6po3Crr76as42/uhHP4qPfOQj3ASEkipkxvE6xVKpl7PYG6r9LhTyvXDlInj7y69HNPEb/P74nQi0dOLpHS/Cp0/r+OvOM3BkJzAW2IaaxGn0nHgGhdo9qA95l3/dVxK0r9YSoZdYEpWJSJapdJnJDaQ8JoI7kLj4djgiZ5AOdCDh6YQeF5e2BUE1Pb1TShy1Z7de+Db9upRqZpJqIkzlCBopcRn2BUyv8J+CWCbHf81AfM1CO1OhtZJnc57Dvu14sO0dCKd6mBiPurYCWa1o56D0DPIje3KTGPFsQV36DHdimw85toLU4fMjy8RgoSpFy4lg0NWBhsxZ1GbPFdXjTE5DMieU3JSp9BrEl+Znkt/SdIdycBg2APL3Ug6vz6nyfcDjQMAt/qb9RXpznZpBHD5Wnst5XoW3XBBkzh+OTWJiZBCTwwOYHBlEfGIYE8MDfBsfGUDOiFbl4YKlllFVHahraUd9azsaWregafMWNLdtQVV9E/OA0m57dJ5SS2WelmwZxvPWZBFVt/H5ZsajWfeMYqZM2IQv2Iy6o6Yb5Bs2c5vZSsOeYcA3fgxbj30BruwE8q4q9Fz0AWRrdk/PxC8DYY8oT3jpNdrfpBLT61IpXh6sqZzjlQClVYRCoTkz8dYqyJoyPDzMTVTWRUEeEdvFNNGowN5Q6Hsaqd/9H2RjIxjK+vC8f3iIvxCvfPe/4mi+AZfUafh7+zdRpY0i46zCoW3vhqNlP3Y1B9FW5ZvZC7bYdV9irLtzQ6IsqBFCuZ8Bk4xaI8mEx1XDxNgoAuFqbh1MZJLmYVVxy8EsLBP+3fLvodzdPKUIGJfvaRqzyp8eUyEc2Rqivg5MBMnKIFRh02ebzRlpEGVApIfmP5P/mJYxUxEYL8MmPLhmR7ZSmJarnFZAbewkbhj4Brx5oej+YdPbMOYTloFKIKLhCuwBJpJHBJei4oh4s3JuFP9500NojT6BaMGBQb0KZ2zt/HdpW+Zp22Jk7BKxcpk3h010W3OIxybp4uQFKqybJsMLlVj4YKcrq5QPHFbSiMHL+ce0z1OxCJPeyOggInw/hMnRQURHBRmmBhrT9/X0fWRXVdQ1t6FhUzsa2ragflMHalvaEa5vhkLKrpGxXC5P2RyEMbGdpWWyIL7CNsFd5hxTucbclIUJ9flZwtTkhIjyeYqui3zRNtR2/Qq1R76FZGgbPJMnMLz3LUhtfeks60FpFEZaRel+IH+y4cEu3e9roa5FWyW/J5VyujWlHEtILLt6WYG9wd5yAN5bPo7x089gIN+Ivc/7Bp564G489PWPo+PtX8LBERUfqnkr3tnag5i3DWOuTvgjGRQKk4gm89jVGIBaLopnIyqva7kIcR3tX1ZjTauCYV+wdu01FVyz0C2RyiFlzxZ/wCkvmQXB6RwKeYo/M3y95nMo8fZaiSaRrkxWqJp6CWkNx8oXwhnvKs6DMpOL3lyD0NJ6smI5ixQ0WxodK7UFslazZMvPMVk2UgU4Fo0SCaAzuRIJEW9FTeYcRp2tOGfrQDqWYcWWb2xT0LnIl4gs3+fFPb1GxNfMMZ4dlIgjamhItyVSRzdqayzURfLEitbB4m/hdTXtH9ZtJrvBpvRp4V92tGHA08kFjedF/Rm7wGxnzHF6kXHERvsRHx1AYuAMhkZGMTHYi7GhPmRSydkilBkUgxaua0R1fRNqG5pRVd+Iarqva+SbmRdsVbIp0oytEHRc6RgUOwROdQ202+xQKTTYaHdtCsmiYYlR1MYqsThHyM5AxJae9ylqsQiPBiTWgZ9oxGGfZktib7ZddNYz7Rj5qq3QPNXwR09B99fC3bAdusNeHHiau5aWQ+tAEW1mcR7N2yTsRIqp0K7SwdW6rGu5wJDkWEJiAfYGW/MBNNOPxMmn8eH3vAGfhA1PPXAnRr73EbT+2T/i6TEbvh26GJeGw1CoDJ88f3Hh2aOq7f3qOfjjXStDClcLIZVf1st7nCz7V/dWI3/dR9jzaBKvvHFP52Ta4tedHrBgkAO2Ngg/JZ3MOSKgBZFbSiDSwSTFAM13rng1EzwLI+asYER8mRFjRD5JPSYSMVMhXCnocjhZCgSR5a3g53n9jOYVTJxL1N/5OkxI/aY2zpS+QHm84rOd546B0XQe6awP6fx2o5td3+z7gGO6RH6tz0XkSlzWp/tiIoGhjtPz/JjeQ5f4iTyRv5UTCkSkGseyEbGaYaPIYkBE0GwbTfu3PnESLxj7VlHtNv3LeSroI79xZByRkX5Eh/uYCNMtMtyPyeF+5C1JECJvwVI0pigIVtUgWNPABDhU24hwXRNqG5sRrm1CqKYeKnmBSZGeQxElPi4i4qbm7VRVeJwiF9jsMEg7gvZXcf8ax7x49YMaUZQhmqVK8LQiPKOAk84nIuacBmJJjKDjQsfB2vUuXbMbY5f/JfyJLuTDnSjU7eHhjBU0LSnFVmWat8vwES+ZbWKt17VcYEhyLCGxkMKywWeg3vtJtMVHEVIC+MDb34S/PHsCI/09OPpv70fjn30GD5wZR/d4ErfuboDuJEXOzl/Mwe6DSJ/+Khx6BK5A/fxH8ER6Tt0p/t76/PlNe/jHwAOfA7Q8EGqdvuwLTZrll/WSDxz4sj6nHGhA37NwxUaQqd4B++gxjJw9jIlCG0eVFZtcEGnMF0RDBCspZgIsPLSEaT/P9EYi1KmcqKCnQiRdKKGm79b0XTIpKRbIGdFiJaSUl2sU5ZktmEVhk1gTVrQL+vmFcN62svuAGyVYYtWsz095d8W1eC6sMtIfTEJivocbe2SmyC/diPzyPT1Oi2jHcnBTowaHnfN3TasCF2ip5//NHl6zte8MML3Q1FI6b/iqZ4JDFQSZvdpceDfzfDlmzC58sqHYKfT3D+DZVDXSIyfxSP7fcTLqYvJLpJij0IyCOTMroTgfmw3hugbUNLRwDVCoqQONrSIJgtRgh9NVPKfo1BRE3vDnmgVu5EE2r1QY50Nx/pSmwQMCy+V4Y/Gk4BIpJbHWYXcUI+xoPt6JZ+GNnUXC34FoeKelEFTsT6siTLYL5wyX+/ncoBbMHnHsdOP8NJVqQikxZj8yxbU170cK0zOFzcENnW987pGKTQMho7hvxnzixWA91LVcQEhyLCGxEHuDQezsjbsRGDiCTsc4PvD3n8d3vvwZHHnsfqR/+XfYfts/4MR4Gv/19ABeur8RITtgywHOydNQUmMYDe9AbewMHKOnYKuUjBJp+vUHgaEj4vHJ3wEv+lRlZJamJWJMxN8dFs+Z6kE5MlY/c9OGJYH8sl7wwIEtDgURo5Wm4qpcgdVS9knSVYpCAarWiE1KEOrgUaRcVRi0tSCeEMVNVlCeboKubhhJDqaybBLbIokyia3oYMAE2YyEIFoTzeSNYiujkM0kxiVKrUmUzTxfs5CJs3KN1AfyXVIkGoG7uGn6+YVwzq1QsgWxbmRxMDJlCUSiyONo9R+zkgpbsdkI7a8xJrl5xIwoMpMAk/JLHdnK0VBaX/J91gVEFi/dKJLMTGWgx0RuiMhqpFxXIPzRYGamZITi/jdIU1qh/Vy+LUyHoi4AAEYhSURBVLXYv7T/jKYcBijeLDE5htj4cPEWHx+Z9riQisGlJaGQ+qrYkLWNo6BMUQRqBx2obUC4voVv1Y0tqGrchPpmQYB9Hg+vj6cQR1b1w1lSdEbrRfYAOlbcLZysGUbnt3IDAybERrtk83wxzxXzntVaV/n9RsS47fDnoGamiuEoZtPqped9Q0SX1kUVzWysq2Iui5ZDJLyoNlsWaTb64HnRfDURi0fTiGYtAqa6LLrdCUWYb3z+XoD4NZkoNC9IciwhsUhipwZqUd22G9sLrXjHh/4ef/3ml2FioAeHv/peXPbeL+HQUAY/f3oAr7y4GarXjiFHK5L2EDwTxxH1ViNra0ZDvnC+D7mckkuPY4OATRWsIzZU+eUxmpY6QRExTk8Cvtop9aAcGTPJMbWFpsdLrSivxy/rpVLfLecXeRZT/nYko2lu1ZykS/gZUi1FnqzZyc0kWUSKmBQ6OzG54z3wxbuQ8LcjSmkJRGjLgMg1XZI2u5zN1iVN0XXYSWkmQs0d0AQ5FkVgovjpfBgJEAZbNqPESu0NZjybVcAzK/fJnjDq2863qbmaEW/C21GMcFNEtNtYPIcIkV+zAYVBfOnxTCkN5NGlDN6GoItV3SIBNhpR0OuVeD/Z3qFpnFogLvlPeWFLwY4PRTuvsUU5ELnKJGNIJWJIJ2JIJmLIJOJIJePI0N/JOLLJBFLxScQMAkzEeM5e0NTqOVjPqTre2hao9Z2oYiLcjDDlAtc3wuV0sfWF1HwHNeMwBiTU/ILILG2ejbaFWx1PHSMigGyHMIigwy1e5AGQqdzSAMkgy5yrTJ3UzBi+GfY3DaJmgid6holxMrQd3sgJeKJnmRwLwmvxuasKvIbqa7WZmCSa1num40Lr7DWab9A/nyVz2GwAckEJ8FzYiHUtC4QkxxISiyR2Ss1WNNbvQWo0gaym4QP/+BX864fehejkOHp/8Xlc8rL342B/Cj9//CT+bKcdQzXb8dDmd6Am3YtsVQccaEPq6KNo0/rgbNwxs5JLmOwRxDiXpF8goHa7IJaVkDJ6LdwKTFIafy1wzfum3juTijvRBTz5OSA5Wv7y/mLJ4Ep9WS+HhWQJPNS6kfUbcW9FZv8HoI2dQNS7GWPJJuRi48hy611+pzGBVUk+P+Is4eoE3J3iQSY/XdEtKmOi6QI1cihptsbg33TTF0zTkl+TYtE4xkKosGZEGqlwJgkuKn1GwRoTWcu6i4a9hrfY6Mgm4r0MWwAnNmhFZdjpIDVYeIen/L0G8bUovrFZVF+aP6m8DUF3MYLMZyq/Rgc289I9CblMiowCNDNurlKIxhoi+5YKDenv0gQQLvQjVTcyjmRkDOnoBOKTY4hPjCIenUA6EWeySySYb0SAUwlhO5hjVczjZ9pTbHYVgep6BGoaxH11PYI19QjVNiDEz9XB4Zre0ZMHMRbridiHNibGZB1hMkypFmbkGMWhwQ4XtTGm5heGdYD2Ke1K2p9W5Zfu2ctbrvBvDpxnsyhBKriFFWMixnSfCnacv4+4Q92UHcJU6DmJwrC90HusSSzmfqdF+13CxsF+cYcg0auCBEssGpIcS0gsFBZiR1/R7TU+QTr0HXjpbe/Edz7/Dzj19MM4d+R1aL70+Rjc/zp8//A4XnfgBAZqtmPIs40vMzb3HULgzFeQy0dgD9XBftFrgHOPApPngE2XCsJ6+i6g+yEgcg5IDAOugFCAL3+rWJdKSNlsSm2514iJRPtnvry/Vgvqlmu95+mhNrt/kRJMinAkmcNEIsNFXkQis4UWZANNwjsbN7Jey/AHJqZc9DX9krDJaa3thGcCJTyQGs2/60YnLtMOoVPnMGtwMNsqdOSo2s0grqIGyizYIzJheb+FABc7fFmzjDkJQjea7FGhlOjMFk3lMBzNYDyR46g4uhH5pfuZItcokYFIb2PQxakB3IXNTcVqwv9LJLicCsn+XMOHWtyvlE6haaJYyvB/mO2kzYiwcuCCr0IeuWwGmWQCE6zcjiMVGWfiGyPiSwSYSfAYkvEIFgLy8bq8fuPmg9sX4JvX64cnEITHF0DQIMA+Ir6eII9axOBFxJOZJ8xUL4ypQshShdUKt1E8yAWCNoV95mS7cNh1uG12BAJuLq6bskRM2WnKwWlc9TBj6uaK6eCrCWZcxgwglZisFKQYEzGmx+fZPAyVd+q56aS4XGMOAnvFDftMudg1ibUPSY4lJJYIdEmwoz7Awfj2V/wJfKEq/Prf/wVDPacwdP8PocRz6Ln6DfjOoQief3kGQbcLSl5jD7Ij3ouYsxr2oeOwPfA5KFQwRyS49wmh9kYHgNETgDsEFHJA434glxI/bvMhZbMpteVeCzbPXMSxXAV1y10YuFzrPYeHmoqRKPKMLveTsllMNkjlkczlhTXAUATNNInZwrwUM+bMjCgzm1YoM5Pi89Rgwx/My9QMldYMeWBYlGCT3FqbYhTVYEBVbEjkciAubZIvkwhbCTBpurRe6UIBsVQBk8kcJlNZ4z7H90SCy4GIb53fhZBHRcjjQJWPCK8DfredL42TqlkORNrJY0z7ihMgLG1+eX8YhYWUSkCkdmJsBNGxEUTGhxEdH2FFl56nTN6p+zTfZzOlz2egsdm4cqiqCn+4BsGqWo41o7/p+4PIrssbgJsIMJNfX/Gx6nCKNtNGe2lxCX+Gy//0NB2Dkrg9wnQyPAOBLcbuCStD2Ovk4+1zi+g4IsiacY4X4ln4PI55E0ZSXU0B2szE5sLMMh8BskJUMn8ixKWk2Op/Nokx3TmNls6zzZfIMJ17Hge1fZaEeD1DkmMJiSVGbcCNyzuqEbiiFe+2tWKoN4+7Dw/gs/f/FPlAPc7texH+467DuLnDje07dyGRKcCVHoMv0UsMBCkdsHc8F048BaXjWmDT5cBj3xCELj4E2B1AYkyQZpOA0XNd9wOBxqWtQq5qB274MDB++ny1eTkK6i6EGr1MhYB6w14Urvsw9LFTSAXakXR3IjEcQ5yjvXLcoazYkpfzbUWmrdHFmDN5CfQeUjKt5NYQdAUsJJjSIYhAmO8tWaPiXxZnhJjW9EFap+EQCm1qEQbB5UvrGnV0MJIrdA02vYC8TYNqKSLjS9ROm5FaQcQe3JmNtl0Q3zzGE1lMJIUKXK7LHSmSpPA2h90Ie5wIex1MRsjuQI+JkHBraUteLXtUjcvrIqZretczDs4wLn3HYgmMT44hOTnC1gUivpGxYUTpNj7Ct0SUfEfTYe7b4hpXaGmwEekNVSNYXQtvsAb+qhomviYBpoizqpo6eAOheTdGIGuLSdDIu2te9jcJrmlpMYdH5rEWWdaCMJdThq3JItxi2vDL0ntpH3odqiDElMJhsTXwYMihoOCys82CTqX52FDKEWWXKq6MMFGmSD9NFFsuJs3BtFIU4/Bm8RSb5xctz2t0pVt1KvFqieZcZ5DkWEJiGVDlc2GbfQiKHkV26xV4a90hpOoC+PnRRzHw4AjcV9+G33Yn0DP4ALbs1hBXq5FwhxDODSMPN9S+w8j4G+HZ+xo4Jk8Ltbj9eYLQbb8ZaL1iiqzSlyNhub6zG/YCTdOjiJatoO5CxLvNc71Nr2k2T0VwdMlco27BnAhB3lh6nlRgIoLpfB1yqEVmQkNqaMggvyLajOwRbJcw2veSUkuwJkKYRKCUCJvvIWWwSHQUoDp+AmHK+3W3TevAZvUJE30tdnWz5E+xgmu+zfBvkrbLQjRd2TYILoEsFEy6+PKycNzQtucLBfZokg+Y7A/DsTSGY1kmwWOJLO8XK2hZpPi2hD1F9ZduYY+KmgA1rpje7MEE2RuIANJ+4CgtM9osm8H42ATisUlk4xEmtnGyL0Qmjb8n2LsbnxT3pOqaLYhn+7iQKkv5u2RJCFbXIVxTA5fbC6fLBYfTzd5cp8sN1eniG/1Nz6sueiz+dlB2r2p2M6NoOcpvFgRe2EuEP9WMLTN5pHCwWNpgF88PQ+G1DGzMv+mwi5xpy/liRoQZx826vaINt7DBiAsI4vWZ7A9mgghlANPxJsJoJcZW0HvMhhVWYjuTDWUumMVtTtb2xfG3FsxZm35UMq+g28GE2EqwzW23FtHRY9NDLJqnrMIuoWvV2rYGIMmxhMQyjdpr2vYgergONfHTSHiasfdV70SVsxPj46P45ff+A2MdN+NIVMV/3vEMdl1UD78WxYizDUfrXsheyXxVJ9TJelzmySHkrYZCqjEt56LXTV8Wp1DkgM3PvfDh7ktdUDebqruUCknJeps/4qadIZ3PI5OjS/F5JsREgEXh0NSPPSm8VBjGSm+xWEcXJDmnnde1jfwGRGDMqLSG5EnUZHow5mrjjmr0fvbSWuPHSuwP1IONHhKxakqdxHMHvgFPbpLzf6kjG82n6Bs2yIBGU1i6uhFpEQ0ljFxZeoG73xGBEckTJinmlAXyRWcp31dEnVH0WSaTwmQ2xkV8sXSB2xtbQcut8jrQVO/ne6EACxWYVUGjTa9WKHCRWTI+gf6BCLLpGNJxUXiWSsQt9wkk41Ek43FkU+IxvVbIn0++Z89kUOB0u4ukt6quAaHqOr4Fa+rYoxuqrWc7g9gTU53npny5c4OIFV36n27fsIsmFZxMMd3qwtTUuBogChNF4ZoohhPJDUUCx9OSNeV8ek8Dr3KK/Eyg83CuTnym6s4knPy2TH7LE8XSKxhWYlvabW6+qjJtr5kqUQrrFQNrTJuV8JJHOuARyq+5L819XF5BNwvtFtiq+UJAZsUvGyQ5lpBYplG70rQfrhd8DMOnDqELjYg5tsCR07DVOYbvPK8Pf/n073Gk+Y9wMHcZXvTt47h2Zz0ue9FrMBbYxZXzXpsK70QKiWwD9ux9H1q1frisaRYmUSwllPTLQM0+KiWRF+qyXCXLmUnVXUKFhLq7FZ75MZTeR5FuvAyTW16MDKu+opEFEWGuTocOz9izcEfPIOZrx2Rwh/B45jWksnmhAhrNJAj0GimlVnJCLxEhpvkpFvJC3ciuG/5msRvZnY1vwaB3m2jeYYA5QGkxnAFSbAOJLrizkxh0d6A+fRbBZDd6nVt4QlUXpFh09IJQ+4gAaER2NQxzcZsobCMvLpF8uhHZNddREBkNKSb654NWz0d2B6+Kdq8XNV4nanxOVHnsUDJRjhFjq8K5YfSQXSEygWQsIkhuLIp0IsJpDKWq32yXrXl/c38RS7GUqsIXCMEfqkKoqprvA6GqaffeIL1eDV8wDKfbYzSgMIR0SwpBKV1jpdLovlZch5IGFVaYZJCIPw9COKFBPBYETEdaVPQZx1gQM5OoVY7y7+WWxlygWZgzzYJAaiitLw3YrOeeCdNKIag52UREe+WZjhGJqzP1RbR2mzNRLjqtnBJsFs+VI8ai2NMGhzFwMC0gpr2EB0RGxFolEO8X6ROrzkJRCpkVv2yQ5FhCYhlH7e62i1BbvQuD/RGEImmiK6hJn0NAj+J/X5rE547+AvdV3Qrt+v+JXz38Pdzzqc/gshe+Enuuuh4F3YdUlnJaM5j0NKIq0IbNWS/aTz+BwMOfhi01Loji/lcDbVeJXwnqenfoB7OTSCtJJZQjnfSekZOA2gzU1y/uHDE7+lHDElK45yK35dToBSgkRSJL/l7KB85p3CbZc+LnaHn4E7Dlk3Af/i+M7Iuhu+nmIgc1f6R9E8fQcfJLcOcmEXaEMdTxTgx5tjKhtP52mz+fqYwgxqWqICtzNE/62yCcgWQ3z7ff1YHGTBdCiR50O7awwGtefqZpN2VOoz57DqPuVgx4tgnV2PAh01UGItYN6bNI2EMYVFuEYm0ThVHsbeYGIToiafL55rngjZTfmXgTxW6RKkiEyeze1hSyc4OLoEuFWwVsmQSc8QFEIxHEx0fZrzs+PoKeSfF3fHK84oI0M8PW6fbC4w/A6w/CR0kL/iA8lLrg98Pl8fFr9Njt80N1eREIijQGt9fHr5tqYCmRnXG5UPi9dBxpcGCluyb5ZcWTsnlLkjVKZmS0+RW+1KLlYQY1kuClznvZysgrwT95DD7q8hboQDy8c873c7c5h53P00qsDEyAaf35yoYgyTSV2bCiuKnc/MQxK4knxbuypuFTy6aBWylKrSZUPEdXG3g9rAWmcwwq6FhYC+8qIcV03q+ZYrv1mBW/SiDJsYTEMo/aq/wu7GkJcYtdiotKBtqRUkNozJzFX28P4iuOJH7V50Hgujcj2/0Ufv/9r+P+H30d173mz7H7Oc+HaicN0MaXZBOpArSJp7BtchhK/S54Rp7idAvYnWId2vTZSWSpAkukuvT9BH7POBDYC4S95T3HlcBcHiVt0HLIN032kIVYPwrZqfQOY1/zpVoigEwG6fK+xlFoiQw1fSBPsLBJmMQ3U8hje/cjUHJJJJx18GRH4Bl+EonqG6fmZ7RgromcgSs7gTFvJ6oSp+GNdCGOdn5fqaJEZJqU53JZrbR+/Cz7QkVkWJ+9BVFbkBXfmD3Ij83WyabHuSV3Bi8Y/xYChSiT31/Wvhln7e1MrMi68WSuDr/NvRNaLo1UwYZk1I54oR9J6hlcBrTKFG+2KeyEIxeHHhtBITYGVctB1bKwa1m2bbA4a7CSbDrJqQ39EyOITYxwJBm9ZvayK6e0Emx2OxedkXWBvbvVdazcUsSY1x9i8usNBBEMhRAMhWFXhdfYJLhikFJe2WWriGFvsS6f2u9WSoyLaqiCqSJCQzklgmcOEPifYXegN1OfHiJjXKTF9pD5+1BF4aKdj+FcBJmI8dYjn4MjM4Gcqwqn9ryvIoIsWhfbeWBGg6RKQNtFJJ8sENwQw3oFRAFcTopvm3l7hTJsQ66ipc29/qabiLajmKM8D5htuitZltnKe9UrxeUgG3ssCyQ5lpBYjlG7qZYStj4f1Y37cGlrNY6qEZzV9+Jx/V1wTZ7FoGMT/M4teFldAQ+dHkH/5otQ1fQPmPzJ3+HXX/8HRMeHceCmP+YfaSJ/TkceDq0J9QjAM3CEyYGzkIWj7QCUkWfFr9hshL1UgS33fvM9dbuBSAwYO71wclxc3m6g6z6xHBpUzCchYvAZ6Ie+D72Qg25Tkdv1CkS8W5EcjnMcGFkcSDElzyyRT7YFsFprabRQJK8aen170WL7b7gzw8jZPej17eZoNQLxAZNMDDk2YYs9jHD8NOJqCEOOlhnzdYm2UXJEXeok6jK9GCGl1721+APPCh41TDCKlAZcnfh5+I2oz/Vi2LEJvfYOaNSlTtO5qxolmGRiCXwzeTW60ITxghsD4x4UMFKyXJX6ciGgpBFSYqi15ZAN1ENxB+Cg3OF0DNnoKNLDXYifO4qJ3jM4O9xfJJzz5QKsXKsqwpS6UNMgPLo11FiiDoGqOtTWi2YS/kAYOiVZzEL+2L9aovRyRJdBWqcERWverCBoRIvpmJsqP2XslhK388wPlNBgqLxFNdjYAR4nPWemNAuibbU7zBpztgDYKiTIpBgTMY4Ht8EfPcndDishxya4PbNN4QJQ02IzE7h4j8ixZZDBliDqiMhXEmanC7ScpYSp7s+3EI7Ww+xSNxtYGS8pzJOQMCHJsYTEUo/aiRj/+oPAwCEq+QeO/AT4oy8i2LgPOxtDUDTgeGEP+l1b+ZKuLZuHXbXh6q31ODeZxKNdQNWr/hbZ3iN47Mn78fivv4/Ney7B5Te/Am079uG0rR2p5reiPncODpsdO4b/G76ep+EK1sHZfj3snTfOTNipwx7FvplkmN5b7v30GpFtUo5rjA5ri1HXSS1u2ANsv0Usbw7V2CyOoxt6n4UzOoJk9X6oY8fQM5rAkCtqFMVRHBpZFkShWzpDbZCFX1gojeKeotNMIazXcy3GW7PYFD+CXv8eHPNdByWR5de4mYbBkCaVdsTq34zazDkmyoOqILAmgeKfVLMdMp0K6VO4afjf4c1HkVSD+HXtm5kgExEl8j2SyDKh41ueCvlqkM1XiQI9bbTMJfBGvjmRQ4MtiiZPATayHzhEpq+biGQmis0Dv0FLz29xLOZDYnwQh5K16JukrmvUMljAVM5NBZSiw+paOxGqa+Q4No4RM/yZpKASiWQl0OlmsmsWsNXUN8DnD8GnJ5Gy+6exayKUdBleJAooSOemiqP0kkvlPKgji4bh/aVpuIBtpkgt069qvM7EyWHjYkniQObzJVMV/zK7uIniK4MIsheYnheX7EWes7AWmE1VlhMmQaZIvzJ2XwZZKUgxJmJM99QGfL4QyihlERtdDMtc3aD97jRaQFtBqQ5+UtmNedDxnMmqsZQkU+QQz0+Z56I7x+xk17TK8Hm6FlViiQsGSY4lJJYapJZOdAN56mqmCUsBdbhr3Iewz4ndm8JIayLRQNOyrHIQ5aKv9JYqL56j2HByKIqRTXvgbNuP/EgXug7+HCc/eTtqW9rRUhvES6/dh9j2qzHm3oquukbUZnuR9rdB6wthc9iHra1bOajfUc5OQeR410umk9Ry3fJGTwH2JhHltoyeODOWi9MfMtQkQxSHUZGcNvQ0HF3Poo52Zf9hRB1hHE7XYqhvvOjbzBvMj1oNT1WqCwpLv3+iUYJeVCRJYR5xPBe26ueJqvVkln8oSakkpUyjIjgDp5R2nHa3M1HKJ3NMBq2d1ATREj/mWxJdsGfjeMy+F4VkAqeGoziqTTApLlfUxsSMCKVqg7dI1ES+q5pLwp6JoyZ+AoHYaQxm3BjIuJGJR9E/MYTE2BDi44PQ8jnY9TzcWgpUgkdnUdqWgaYY3cvcXoTqmlG7aQtqN3WgelMHNm/ZBm+wulj4ZCZHmOAoOeLKJUSp+D6W4qeeZ1JpEGPaH2RZoGltdo3HhlMcRPxB3IX9ucaggoi4aHZWxttLCjLNu4T8cswWXQq32/hzJGLMzGAPMV/23tJ+5dQIEVVXTICYxRMs/MMKn488OFtuguwgglyetJJKTFYKUoyJGM9HNT5vWaSo2uzFQksuEjWsFOVyfmn3mAosHS/TomASZLYIsbVF5GyL1t+LH1BwKkWFPmECHVsmvGWsF2YLb1r/uRp8SEhYIcmxhMRSg9RSp0+oxhTlVNKNizroXdNZy+kBR/tjiGdygnApOrR8Hk0hNxpDLr7kenI4jlPYjOAt/xNaOo7YQ/8fTjz2G3z+iXvw5hv/G/YbPoCj9ZfC7myHktPh6o/hzFAcj/eMoSnsRUvQg9YaHxoGj8NhtVOE22ZXb+m1+j3A8PCSquump5fJsEGCJxMZ9E2mMBHLIpLNIpGm5IgC/JPP4vr+b3CiQxQqDvuuwgnf5eiLNCI/ETMUXvPHTsy32DDDouoS6SWSo+gKHwqiO9ZLzJwXaxAzbqxhEGzxgz91WZ2tE3QJn0O5wAV+E4ksJo1itzszO5Eq7DKTY4Ek/S8Nj8OGlpAbVV5qZuGA32lnlS4Xm8D4QA8me3swOdyLiZEBREf7kRgf4fbDJs77PbekKpDi665uQX2VH00hF5x1HdAa97EiXN3QjFAoPI0QEEGitrcmMSTXsMNu533CxEYnqwMRw+kkp5RAm2DiZNgU+JK85T1E/CmZobiuytR8mJzStCWtpM3ttTFhFqTW+jwRaZEAMbUcIj5EZPOUg2w3Bh1GtzPz2FVKtKaWJS7NE+ESNh2zNfbSw/Qgc/51GdsOEeLFkOJSqIZFgj4XpZ+FaUTaUIwJVuJpFtGZdl76LPMghPOu9UWvG+2LSkisOZi0KsVmQaR5VWAhnnAJCT6/5G6QkFhiEBG8/kPAPf8I5JKCiJJKW9Iu9qrOOgQ8Thztj8Adz3KigCBfGmpTp1CXOofOmlacrGtH70QKp4Z12G54G5w7r0Dk0B342l2PIHPXXyLUvg+bdl6Cll0XY9OOfUjbbIikMtyM4ZQrCneXHR15H67Ke+E/9wxsvhpkPG1wZ/Nw07XtZQYV9lDqBjWFiHY/idzAcfSrLTiNzRiKZxBJaSjkNTRmT6I+24sxewu61A7cEr0fValu9Ng3o0qbwJlcDQ5mmoFMSvwIWzyg9IPIqrHxt6l8cp4vEzCd82V1I9xfEExDXTZ+8KdyhUUxUnP2FBrzvehWWnESraxoJ7JaMfLMqgYT0fC5nGh3p9Bgi8Du8iHlbmBibFN0RAfPYfTpYzjTexLRoR7Ehs8hl0oWmy4QphWXqSrcgSo4fQE4PaJ1MLUNppu/ugH+2kb4qxvhDdVCUdViNztTNGfyoorkALMkiVVdqsQ3t5UVXGoGPZWJTESDI8js1LCCyKbYh6YdQqjkOj9H5Ikux5Oyq5YjuUbjCBJEiahyvJlBiK2X70UUlzhOtB+pLXFxPxjPq4qxrsX22OIYm1FkpipYtMUsEcSlejt0VVgSqPHJcpFkTsawQSSOLJOjw7QVWAcLmipU4KkOdKJAzfxsmSr/bPOk6EnR0ESDxp3k6Nyjz5H4nFm7Gs4EZwUFdKx028UxIeJrNkAxybBUhiWWCpIcS0gsJawxaa/85qx2AlLB9raEOEHg2FAU50aT/EMSip7GDSPfYsU0bg8CNW+Co2YL6gNOnOkfwrmmffA0HYAtE4X28A8weuwBjHYdx5O/+S42X3IDLnnpG+AOkzKd59xTutw96mzGSM2b0JDrg161BbZYAzynRuBzq6jyuFAfdMHncpx/aXKiCxh5EKibXwZyvu9pJPuf5XznY+jASCwN5/ARPLfv6/DlJmG3BfGQ/zacsbcz62rNnsat8W8jqEU5xeEe5/XYn3oUgUIEewqH0GVvR5fexOTUJGimSGX6aBkGQZ56Svxoiu5iU00UqKkCF3yRYl9MqNA5+iyZSEDJRtGfi2FQb0cEfgDRqY3TNTi0DHz5OByZGAKqhqDPA7+7mglCbDyJZPdZxMbuxPi5UxjtOY58OlXCd4hp2uCraUKwsRXVDa2oaWpBsKYJgdomeKpqoSgiasy0nXDLX6pxM7mTdYY6DbgEQeUObEQgjGIss/0vEVoizELBnbI18GtmAZrxmNQ70RDEGDAYxJUtCbRPc1nYPC7hGTZXwfA0C/XOIFU2UqEL3AyD1XjjWJiKvlXVJWLIx4rX1UiLoNft5rLFOtP7BCk6n7ARAScP70K7sc3l23XajXNlBu/uYkHr7yXlfgabxULA+5iV3vJWEjOlwsX7XJwfZqMOwlxJEeYxm25lIHJ9/nRFD7o1qo3sG2UK46YGQcKyQ4TdPKckJJYbkhxLSCwVyjWq2PPyWSehy+LtdQHU+N3ororj1FAMnlg/gnoUQ95O1CRPoy7Xhx5nJwJuFfs6WnA1eVAjSTwSq4N23VsReO5t0AeexfDvvorug3fj3KH78dy3/A2ath+AZiiqRPqetbfilNoGW1KB4+y4uMQNcUmU9Gq/246g24n6oBNVPjcCk8/CffRHyMQPw+athn79X8O56cCMHapIWaMf9bFTj8F13z9CT45BRRCnqm7DSbTjkvgJ2NLjOGlrQ2umG279LEYpRxnA7lwPDwbotY58D7bgWdj0PA7a9mGL3oOH7JfiGNqg5DWLk4IK76bsAaYKa3RHNlowE5ER5Eb86Gs4PZZi4mdZ+TLehSD0jB3aRC/0iV5kJ4eQnRxGYXIAhdgoUCbH18rRS6G63Kht247a9h0INXUgWN8Kf/0mkniLBWqcK+ymy93TZ2IlEmQbIHJKyjaTZiPyjI4xcwtSaVW7iKYiv6ih2NLfFEPGdgbyVDPZJJJph2ITnlHRqIL6jggySipsUVU3VV0irLS7NAUKKZBEwI1iOeEdNr2dhveX9jl7d8V5Zk1/YIXfUJ1F04yp3FqTGM3XDmE3bCNEkCuNMJsPphpZ2ETHRENxXUqibBbq0blKCSsLUZF5UGEo6pXsQ7ZRqFM+X5cqzikz+5ezj2dYj/kWzVk/KER6S5ttmD5h80rGfM8BCYmlgCTHEhKroJUn+ZD3tlShvSaAHn0/9LHfoTF1BnFnmH88npO+D/2OFpxTOxELbIXbp+HyTAFnxpMYjduQ2nQAjW/+Ehfv5SYH8ehvfojAXf+Fxu0HkM+kkYpPIhUZQ8veq3FRewgdrgjGvR0459zCZEsQIKA9dwaZQi+ecbejFX3Yk57Aca0FDSNncPTRhzA8EITf6URtwIWgxw6fakdGA6KZHIYm0zjcM4Hqc/fhuokhdBEJzndDK5zGgKMRRwv1uEwLoLnQjXEE0KU1cjzdlkIXarUhZHU7Nhe6MaEEcUjfjgYMoEYfR7fSjAf1/UhTAR6vq6kqUTGeoapqQGpyBImRPuSio9A8IRRScWaTNncANk8AitMDe/D8hiaFvsPITgwgn5iAlpiAnpgEIn1wxPrY4kJLyto8sAXq4Q2E4arfA1V1QLGTncGGLLU4jo4jHZuErhU44ixQ0wBfVT1CjW1o7NyNmqbN/H6CSTLM4iVW6Og/Q8GlJAomvBp5QskOYnRUMzy3VpXcnI/TIQgxEUNS4ZgMM0kGPER6DLsEH2u2QBjkmJS4YqzZVLtdM0aNC9JIURSnh7BFULFaNAdf2A+7TbUouVNNPUSzEuHxpr8pms5c7oW49M2X3W0KW2GW0mYxUy6w1UtP90tRmEak08fKe2UxbHwcjGLD+RBKIqDlMn7p+NFgTajNU0kVnDFtdLITKSPz9/WazTnoSobpEbYWS0pIrDQkOZaQWEWtPKkT2e5Lr0WyNoChs4cxEU3jiu6fiSYAuh1HfFfhqOcydDs6mDRvrvJgU9CF4UQWo5MxoK4ekdp2OLddDS0VQXfvs4A9AN0bQmY8hol7f4bjPz4JNZ/CZVtrEbjubRj0dWLk1CH4Yt14xd4hNKhJ9Gbc+MlwKz5/8EFExsfYA4um78DZdgTpVBJOXxUaL70RiupFHgVOg8hndWQ1HVv1MHZqPjTnuzCqBHAsW4fJXA5PKZsQwysRGD+KM3E3Rmq82O07jTfp30dYjyEPO+6xXYHHbBfhtNKObnsTWvUB9NqacQptSCeTiMWiTKg1mwNwB6CQlFr8NgsDTWEO2KBnzaQOIqxaOsYFjfn+Y1BDDdBTESDSj+yR36N28jACrbuR33Id6tqfh6pNnXA6Pbg8cQ+eP/lDFAo5pD2N+GX1m3DO2cmkVDG9uNZOeYayyleKDRuDbnS5a8w8gGGHyD6esiEY5NZ4P6U8BN2OabFkRZ8v+WttlMQrpiBCS+/3eVSEPU6EPSqCHhd3tKPzwuNQDSI9HcJeYsnwNS0NFkuFFZFU7jyip2saxgoJ1AQ9PDioBJRDTET1QoLIpd8gl8uhIs/WGrlIJLk98lTXxYXMl9Ns7CJeTrQhNzz1loLRhRBKOtZEissVWhKEBUc5v5ud5SNH5xqpvyLGW4dWUJBWbTwgMy7dFL3o5sCLzs010ZpZYkND0ZdiiLuOEY1GEQqFEIlEEAwGsd5ATRGGh4dRX18vsk4lFm+tmMlnbPUjV6goJw/+AIUHv4xRpQqN448hbg9jxNWK39S+CWfVLYhRER9FKgF4Tupe3BL/Kf57bBN+2BNET81zYK9q4SIZq/9Pz6WRP/0QMNaF9Eg3co4AWwXU9CRchRgKmTQoXC4NN3SFTK5Ef+kZa7GMArvLg5Yb/xS+9oth8/oFcSPVTAG2owetWh8Onkvi6MlzyMXGkY+NIRcbQyHDMQ4MvwO4ZpOC5tZN2OWP4z7bZTgauAae+jZETzwCV10bEv7WaftEL+RRiA6zQk42hzwpxZk4kEvD39gOb0MHHKF6ON0eeJQ8tEIWWiYFKHa4/SHYHE7Ux47hxvgvsaemAGewFv/X9Tr0uzqNCCnha3xu5n48P/Jj9DnbsSnXhbvCr8BB33W8Duzvteb3mp5fXRBiQZIUNKdP4YWjwj9OrZ5/3/BWDHpE9jG9j5RiUn29RHQ5NsvwAhsFRkRQ6HI3FaSpRJ5dDoR9DlR7XfC7HcI6sYxqG9kT6HYeOR4bQU1NXcXkmBDP5CuyHzhGjsAxeRq5cCdydXuwFBBRgaLIcKXALcSNxU/lP89eqDZlMRFkmKZbrN+Z5kdpHtbW0Ocvlwbqjjnmo3C9RCXnhmnbWIjKLLE+oK0SrlEpp5PKsYTEhWjlWc6PXAFB9jbvAqob4Rs5joJdQSK0DeH0MNqVIYy5t8GuA1XJk9ideBzBwigKigO31vTimtog/j+vE6dsPv4hJUtCOq/Dnx+Dlo7i5M4beP7lfv705AT0dBzubBxuLYs8kUq3B+nJYaQGz0KLjyLWcxT5TBLdv/4aVEVD++ZN8LTuQV9URy4xiX6XD8m+Y8hMDAE2lWPt7L5qOFv2wB2shSPUwC2v7d4AnrLb8ZSu47/pCzPQAHugFqkcoDUdQN5NxXBTSB37A/Sep+Ctb0W4qROu5kuQmxyCViggvPUizvUlmKoUqbfT1FB6DB3JmkYcLmxGVB9An60Z5+wdsJNvV5kipSN6KxJqEK35Lu6QN+pq5fQF0QnMoqiximykRFisCuT3bc8OIqBFMeLtRF36DDbp/cj5dsNB6q7TDp9DFeodFRtR4ZHDbihrIo7M76LKfwcrbV6nWixSu1CgdSMf+VIkNFCeLxHkuYhx+OFPszddc1dj8qq/WhKCTPuN9h8RSyL7KyEJmVnavD4VtLkuB5qObBBmk5z5RszNZKEoBQ265gKlRlSi3hMJl6RYYq1BkmMJidXsRzaaaNhO3wXbid9iUzaKeKgBodad2Kz4oY4exXX9X0Zj+gy/fURtxGO+63HQeQkG7ZvhomIo+vkkF4KT+7jhzfZf4LLsoziqteN4oRmH1H04aN/LXkJbpBe6x4+MrxFp3QHRN86I7K3qhKvjOfzYjwJyY73QRs5Ai40g4nAj4q4hBgRPfQd7d32tBxD0huCo38K+gLI/yKRqF7Jc4EYXvrVUDKnTj/K9s34LciNdKKRi/CNb37kXLVc8H/arbhKTGukHaGifRoBNAsmpDIYCO9UueSryrN++BUO2TvYxu210iVhlW4ubuoU57YhjB+5xvw21uXMYdbUh6d2KsEFqiJBw9Bhd1taN3Feb6OjFsVIGKdftW4FoDRNsLVCH9h370NnYwOSDGxMQSTYK6KiQzmxTfKFJ8KwpDQ6RALFUMWKzWRxIMSZinKveCcf4MTgmzyyZeszz52YQYh2ogJTO+bUIcbVARMzNlZ4h7D6CoM4WyWbCLDicDWSVoHN2xteog6NDxLtJSKxFSHIsIbHa/cimGt15I9SxUwhVd+Ly0E5sSWSQeuoB1CECKJQ7ocCHNNLeFsS92+DLacipwutY9F1qOqL2GlQrCVxlP4bn2o/gu84QepyXCIuAf4uIceLMUw31bg3dcapWF2kQ9NOX4+5YCmw1m/lmhcO4tGr3heG0qaJLm4Ws8g+vGQ3G0V0OQHcViaCuh1Go8iMz2otgx1akx/qQGk7i8h3N2KwcY/8xZSBzAZsxT/79LSY2TC2raDfg5h/GzdpAw/DcEmkgBTfodXBeK0V2kaeYSXR4H8awjyPUGhURjSZa1CrwqCqrv+QJpbxopw2s/BIp8LlMxawDjpFm2CZO8zGvbtxXLFhbK8RhKdVjKhYkIjeTcktWClKMiRjTfS68ZVksGGZHNVoX08u7FlGanmHtXEcnu6ncVkKKeX6VqsZkIbK2DjeTJRQ7MlQU6rCvmfNbQqIcJDmWkLgQqKCNckXzIHLFQWNA0OuEvvcSaOdaoAxNQtM1ZINNaOjcgwNqFZKZAhI50awilc0jHDmOcKobUXcTegodqNLGMaFU46j7ErgoSouj0WwoKJQTa2fJqdarIKFT8wUjdsAMS6MfRo0ad5zDS3O/Qq02wT+Q33T8CU6jTSQsWFr0ihbDYhnFcASDJJJ6bOi6Qo111UEhzyI11mjegvYGBW/IfBchykDWg/j/nH/KKRtE1jgRgSY1umGp3DJ6KreXGC6RXE5kMMgzeXepcM3rUhFyO1Dtc6LG64KXKvNpLYx2xS6XUHXdDgecDsBjFz/6ZJcoVXVnVXlbLxK3NQrRYpi60BWWrDUwpVeUAxFcslKwYhzeMivhXQoLhqkkU2waKcmVNKtYrTAL5lyOqUzjqcJA0YxnLrid4urFXMshi4qpRFvbMtOAWkJiPUCSYwmJlfIjL6BAr3RapXYb7Ld+GiDbBYDqzhtxszEv+sGPp3JIZAvA0Z8gPPhlTl5I2Xzor92D7ryOcVsYzW43NLuHI9lEwZKZn1tASM0irJNL1yaydQ1yLPyTdqS8nXg09xI0a/3otzcjrW5BE13m1aibGEWv2aDRzGxC6TULi0QuseHBVFRWZM1GD4LQGvFOOrAvPYLaXBy9jg5syndjl2sYGf8u8cOsCjsDdU/jzl9ECsxiNlJ6KdbMKawBFEEX8jgQ9jpQ5XUyKSblV+UucZbip1VgZ1h2zPPcI7Wcu88tgXrMucuquJpRDkRwKyG5S2nB4IGVXUSyUSbzcjX5WC7wFRqD6M9UnClysc0mHFMFguYxpWnJF16aSWwmnJgNdDxOMUiUkFjPkORYQmIlYC3QszuAbTcDW59fGUkuV9x3zfvOexv92If9LoTp/Ue+BsS7AKcPwVQ/GrRh6PkMdG89brKfxdBlf4lR91ZEMnlEUmlEM3kk0xrsmQga8h72HheofS4VAFGUmaEyK+QUtl+E0fw+vny7jZpDkMhs09CUPI3qTA+naww4tiGvF5DL048xkSyjUYSmCUWZOtYZ7YaZKBuJES67glBmF5Se+7Aj14esvw6NW/bi6nAtHDbKsqXbVJc3+oGnjtgeh4MVSvoRJ5sEkeCAS2XbQ0XkdzEDl+XGYtdtAcWhHCnmtCFFA60lAMeTGZnACwGpxvZoL3Sbo2ILRuUquVDKrckQq1FRNgeBfKugEQdfUZnh3DdbQFeyTEmMJTYCJDmWkFjJAj1/A9B1HxAbAnoerizFYr7FffR+LQ+4w0BiRLRZ8zVAGT0OxV8LVzaCtolH0BbqF4Rr177zondEDzogl8sXC4DoXijNRCBEBwgmzlTENXYUwYe+B1t2Apq9GpnnfAhK4344Rg5DnTwLW+022JoP8DJyeY1VROriRwQkQ1FtREiosx2tiN4Gx7Z6KJEzsIe24ED9XvYAF7uA2YgAi3QH0RZ5kervApNFLgiWYt0WWBxKgww6TtO6Cy4CNHiJZfLzJp1WOwWR4+SWFyHddt2SFu4RSC2lbTZBV2LMRh8roSqbOcGkvBdtQ0sxX+NYVAKrsiwhsZ4hybGExIoW6B0Vj4moxIcqIyrzLe6j94eMrGCKVSOam54EHF5Bktwh4MRvgUJuRsJlFtfYXbNnnxbR3wNkI0DTHl5PV7IHiDiB+z81jdjZGvfB5STrwxzza7gKAN1Wd6fDNbFuiygOpe59sSXwHlfiP67UTlEIti45MZ7ZejH12GzyYb1fCnXZ2mLb7D64nOkldFWlEqJN2z9XioWExHqBJMcSEitZoHf6LkFMiRhXSlQqKe4rvfRuXRZ1h6NWxpfcJn6JB54BRp4FWi5dOjJYjoCtZtK5xJ0OV/W6LaI41PTmLhVIBfU4MK/uefNNtFgucBoK5w5Pf77o5TUavRQ741mJc7Fjt0hWEd7eC9de2wRHCFZ4PKVqLLGRIMmxhMRKwRLRNm+iMlOzkdkuvRM5JXV4k0GC6Ue4+yFg8hyQGAb6nhAKM/2YH/6xWB+lfuHbVo6ArVbSaQWt6/5XA72PAZsuX10EfilST8z5LHBaIklmS+ClgOnvnalAbzGJFiuBqWYfq7uwk2oEKvUPk71kubowSkisRkhyLCGx0pgvUZmrIGsmhbZUdSQSTO8jstz7BNBxrSCDh35gEOta4OL3Aew5XoLtmovYrZYiOFoPcx+Mn1359VlCYrsUIIvNUl9eJ5JGpyPFqVWCShMtJMqDivjITlEJuBjTIe0UEhsLkhxLSFxoLDbCba6CrJkuvVvtFcREwm1T7wu3Ahe9roRYHwNiA0u33ZW01yYVmywflL6x94+xIlgr9o8VBGfcUgfAJZwnkTU9K6LUJJYPopV25YV19N4NEW8oIWGBJMcSEmspbaAS4jaXQktWisg5UZy35+VA1eYZrA+1QKBpYQR/vgOAU3eKabQckE0AD3xu5RTb1ew5XkXwOVUkskuTfWyCmkskMiIRRWJ5iLFvHmSX7BSyCE9iI0KSYwmJtaRKVkrcZlJoaflEjFOTIrHiyE+AP/ri1HutxLq6s7zneC6CP98BAL3/5O+A1DiQz4hpKHpupRTbpfL1rnOQckxqbzKbX9L5klJJBXpSQV5ZYmweXwmJjQhJjiUkFov5qKSLVSUXS9xo+aQYEzGm3ONCGRJqEmtqBTs8PH+Cv5AcZioUbLkM6HscUF2iMHAlFdsV9vWuJXtFrkC3pWsbLCLeVG44UqkHWWJ2UItn2qcVHwMQkZb0QGLjQp79EhKLwXxV0qVQJRfThppeJz8v2RaIGIcXQELnIvgLyWGm99E+bL4Y2H6LSPCQ5HRNgJTeaFp0TlxKkGqp5FBxioXEzAOY+cawUTdEmU4hsZEhybGExIW2SSylKrkQDzMVuhEhXShBn4vgz3cAIG0Maxqk9NLl+nhmae0VZooF5f/OJwdZwrr/bNO6/FUC8hjPdxoJifUGSY4lJNZy8dZCPcyLJehzTT/f+Usbw5oGNQYhIpteBhJLyifZZMlmIcv0KoNiKO/zLaYzuxZKSGx0SHIsIbEYrLTqudLkXELCAJFjauaRXQYbBJE8u1thgiyTLGYH2SHIRjFfWwT5jP0uVca2SUhIciwhsQRYSdVzpcm5hIQFVPRV0HIoLEMUG9krfC6V1WnpQ146f7EJr0t2wZOQMCGVYwmJjUrOV0tHOol1BVIfY5k8tGXKKiaFWrUrSJLNQvosGGQ7IVK80EzihVgwJCTWMyQ5lpDYiFhsM5LSeUmSLWHxrfqdgiAvdYKFCdVmQ8ClIJ3XlsXGsZbgpAI6h42V9YUONmQBnoTEdEhyLCGx2rEc5HOpWiQvJcmWWDegBhKkIMfT+SXtoFdKwkktJXJIVouN5kUmTzGlUdBAYTE2DCLHEhIS0yGvo0hIrGaY5PPhr4h7eryaCvmsJJvuiWRLSJgd2Vx2LvRa/uWonLKwQPF0TVooaPCxGGJMNor5NAaRkNhIkJ8MCYnVjKVSeJerkE+mZUjMEfHmcwGJDMWwLa+yS2SPbpm8KNhbb35kxVB6XRxtt7hRAM1HEmMJiZkhybGExGrGcpLPpUjZWAzJll7lDUOQ/W6Fm4QslwfZCvLP0o28yESU17rbgngwEWKyjyyWFBNo31ABnoSExMyQ5FhCYjVjLUS1zYdkm4SYcOgH0qu8QUDWh4CRYnEhCLKpjtItVxBFe2vNk0z7jEjxUqZIkL9YeowlJOaGJMcSEqsd66V7nLV4r5AFtDzQcunS2kUkVnWRHhHkeHb5Yt5ms1tQ9jIRZbqtVp5MfTvM9Z1vE4+5IImxhETlkAV5EhISF94/XcgDNlV29tugBHmpiV/l6Q52BNwOLmYjVXYFVuM80DrQutA60brROi71/iEbhVSMJSQqh1SOJSQkLrx/OtwK7H+1MFSuVruIxPLlILtUpHKFFcsoJvJpt9mLLa9JVSbbBd2Tqq0v+7IVqMb9QvOJK93XlOIhG3xISMwPkhxLSEhcGKwF/7TEBYEgbaQgF5DOasueZDEbiJza7Aqscb95TYOmAQVdZ4802TDonuzSlawp8V2eryK2le6ZFCvKkhTVVRxx51RZrZeQkJgfJDmWkJC4sFhvGVsSi0pOoKzexAX2Ic8Fzg+ewXTIJLnMaUycl2johSK/s0H6iyUkNojneHx8HK9//esRDAYRDofxlre8BfF4fNZprr/+ev6ist7e+c53XrB1lpCQuAANTSTWRZLFWrn0L5RgYYmw3ui5lSbG1HCFGqJIf7GExOKwNr6NACbGR44cwR133IFf/vKX+MMf/oC3v/3tc073tre9DQMDA8Xbpz/96QuyvhISEiWQ3fQkZgCRSpPULXdHvXU9yHCvnUGGhMRqxpqwVTz77LP4zW9+g8ceewyXXXYZP/eFL3wBt956K/75n/8Zzc3NM07r9XrR2Nh4AddWQkKiLGQ3PYk5QOSYyB0V6+ULK1Ost9ZAgwm3kzrnycYeEhIbihw/9NBDbKUwiTHhpptugs1mwyOPPIKXv/zlM077ne98B9/+9reZIL/0pS/Fxz72MSbMMyGTyfDNRDQa5XuNCzTW35c1bRMXnKzDbZNYZedG/R7gho8AY6eBmk7xWJ53aw7L/Z1BurHXYUNWAZNk6VGfGQ7VBo9DdM5bDd/h8vdEYrWfG5Uuf02Q48HBQdTX1097TlVVVFdX82sz4XWvex02b97MyvKhQ4fwwQ9+EMePH8ePf/zjGaf55Cc/iU984hPnPT8yMoJ0Oo31BjpRIpEIn7Q02JCQWNZzQ6kHao3P8vCw3NlrEBfyO4OWkc3ryGmFZV3OWgP5mykb2W6zYfbKmwsL+XsisdrPjVgstvrJ8Yc+9CF86lOfmtNSsVBYPcn79u1DU1MTnv/85+P06dPo7OwsO82HP/xh3H777dOU49bWVtTV1XEx4Ho8YUl1oO2T5FhCnhsSq/E7g/KHk6ss0WJloMDlsK3agjv5eyKx2s8Nt9u9+snxX/zFX+CNb3zjrO/ZsmULWyKGS1SmfD7PCRbz8RNfeeWVfH/q1KkZybHL5eJbKehgrlfyyNXX63j7JBYOeW5IrIbzghYTUu3sQ07ntQ3nR1YMpZhuK52IMRfkd4bEaj43Kl32ipJjGkHQbS485znPweTkJJ544glceuml/Nxdd93FIxGT8FaCp556iu9JQZaQkJCQWFtQ7Tb47TZWktO5AnLrnCQTmXA7bHDaVz8plpBYT1gTUuGuXbvwwhe+kGPZHn30UTzwwAN4z3veg9e85jXFpIq+vj7s3LmTXyeQdeJv//ZvmVB3dXXh5z//OW677TZce+212L9//wpvkYSEhITEorq/uVQE3A441TXxMzYvUFc76iAY8jg4hUISYwmJC4s1UZBnpk4QISbPMMnir3jFK/D5z3+++Houl+Niu2QyyY+dTid+//vf47Of/SwSiQT7hmmaj370oyu4FRISEhISS0mSiUR6HDqyBQ3ZvMaq8loEEWBSiB12hRVyCQmJlcOaIceUTPHd7353xtfb29u5CtIEkeF77733Aq2dhISEhMTKenLtfKOiPSbKBYrf1Fd9RrFDVTjbWTbvkJBYPVgz5FhCQkJCQqISS4LbZudEB1KRyZec13QUCjro32pYP5VvQiWWlgkJidUHSY4lJCQkJNat7cJum4o9M8ky3RNhtl5tXC5lmIrjiQirZJewSTIsIbEWIMmxhISEhMSGJMtkuyhQ1y6diDL4npwY/FhDRUozx1MpojEH3ZTi3yJdQ0JCYu1BkmMJCQkJiQ0JsjjYuGF1eZjKcqnAbKaqSUuEhMT6hCTHEhISEhISZWCSXxkxLCGxsSCv+UhISEhISEhISEgYkORYQkJCQkJCQkJCwoAkxxISEhISEhISEhIGJDmWkJCQkJCQkJCQMCDJsYSEhISEhISEhIQBSY4lJCQkJCQkJCQkDEhyLCEhISEhISEhIWFAkmMJCQkJCQkJCQkJA5IcS0hISEhISEhISBiQ5FhCQkJCQkJCQkLCgCTHEhISEhISEhISEgYkOZaQkJCQkJCQkJAwoJp/SJSHrut8H41G1+Uu0jQNsVgMbrcbNpscK0nIc0NCfmdIyN8TifXJNUwuZ3K7mSDJ8Rygg0lobW1dqmMjISEhISEhISGxgtwuFArN+Lqiz0WfNzhotNPf349AIABFUbDeQKMoIv7nzp1DMBhc6dWRWEWQ54aEPC8k5HeGxHr6PSHKS8S4ubl5VgVbKsdzgHbepk2bsN5BJ6skxxLy3JCQ3xkS8vdEYj1zjdkUYxPSZCohISEhISEhISEhybGEhISEhISEhITEdEjleIPD5XLhb/7mb/heQkKeGxLyO0NC/p5IbHSuIQvyJCQkJCQkJCQkJAxI5VhCQkJCQkJCQkLCgCTHEhISEhISEhISEgYkOZaQkJCQkJCQkJAwIMmxhISEhISEhISEhAFJjiWK6Orqwlve8hZ0dHTA4/Ggs7OTq0uz2azcSxscf//3f4+rr74aXq8X4XB4pVdHYgXxpS99Ce3t7XC73bjyyivx6KOPyuOxwfGHP/wBL33pS7nrGHWS/elPf7rSqySxCvDJT34Sl19+OXcYrq+vx8te9jIcP34cawGSHEsUcezYMW6X/W//9m84cuQI/vVf/xVf/epX8ZGPfETupQ0OGiC96lWvwrve9a6VXhWJFcT3v/993H777TxoPnjwIA4cOIBbbrkFw8PD8rhsYCQSCT4XaOAkIWHi3nvvxbvf/W48/PDDuOOOO5DL5XDzzTfz+bLaIaPcJGbFP/3TP+ErX/kKzpw5I/eUBP7jP/4D73//+zE5OSn3xgYEKcWkBH3xi1/kxzSYbm1txXvf+1586EMfWunVk1gFIOX4Jz/5CauEEhJWjIyMsIJMpPnaa6/FaoZUjiVmRSQSQXV1tdxLEhIbHHT14IknnsBNN91UfM5ms/Hjhx56aEXXTUJCYm3wCcJa4BSSHEvMiFOnTuELX/gC3vGOd8i9JCGxwTE6OopCoYCGhoZpz9PjwcHBFVsvCQmJ1Q9N0/iq4zXXXIO9e/ditUOS4w0AutxJl7pmu5Hf2Iq+vj688IUvZJ/p2972thVbd4nVdV5ISEhISEjMF+Q9Pnz4ML73ve9hLUBd6RWQWH78xV/8Bd74xjfO+p4tW7YU/+7v78cNN9zA6QRf+9rXLsAaSqyF80JiY6O2thZ2ux1DQ0PTnqfHjY2NK7ZeEhISqxvvec978Mtf/pJTTTZt2oS1AEmONwDq6ur4VglIMSZifOmll+Jb3/oWewol1ifmc15ISDidTv5euPPOO4vFVnSplB7Tj5+EhISEFbquc7EuFWjec889HBO7ViDJscQ0Ynz99ddj8+bN+Od//meuLDUhlaGNjZ6eHoyPj/M9+U6feuopfn7r1q3w+/0rvXoSFwgU4/aGN7wBl112Ga644gp89rOf5VimN73pTfIYbGDE43GuUTFx9uxZ/o6gwqu2trYVXTeJlbVSfPe738XPfvYzzjo2axNCoRD3UljNkFFuEtNiumb6kaMRoMTGBdkv/vM///O85++++24eUElsHFCMG0U80g/dRRddhM9//vMc8SaxcUGqIF1xLAUNpOh3RWJjQlGUss/TVem5LH0rDUmOJSQkJCQkJCQkJAxIQ6mEhISEhISEhISEAUmOJSQkJCQkJCQkJAxIciwhISEhISEhISFhQJJjCQkJCQkJCQkJCQOSHEtISEhISEhISEhIciwhISEhISEhISExHVI5lpCQkJCQkJCQkDAgybGEhISEhISEhISEAUmOJSQkJCQkJCQkJAxIciwhISEhISEhISFhQJJjCQkJCQkJCQkJCQOSHEtISEhsUNTX1+Mb3/jGtOcee+wxuN1unD17dsXWS0JCQmIlIcmxhISExAbFvn37cPTo0WnPffCDH8Q73vEOdHR0rNh6SUhISKwk1BVduoSEhITEimHv3r3TyPFvf/tbPP744/jBD34gj4qEhMSGhVSOJSQkJDYorMqxruv48Ic/jP/1v/4XamtrV3rVJCQkJFYMUjmWkJCQ2MDKcW9vL+LxOH7xi19gYGAAt99++0qvloSEhMSKQirHEhISEhsURI4Jhw4dwsc+9jF8/OMfh8/nW+nVkpCQkFhRKDpdS5OQkJCQ2JCgwrvGxkaMjY2xxUJV5QVFCQmJjQ35LSghISGxwX3HZKmgIjxJjCUkJCSkciwhISEhISEhISFRhPQcS0hISEhISEhISBiQ5FhCQkJCQkJCQkLCgCTHEhISEhISEhISEgYkOZaQkJCQkJCQkJAwIMmxhISEhISEhISEhAFJjiUkJCQkJCQkJCQMSHIsISEhISEhISEhYUCSYwkJCQkJCQkJCQkDkhxLSEhISEhISEhIGJDkWEJCQkJCQkJCQsKAJMcSEhISEhISEhISEPj/AZcPUfpGhE9WAAAAAElFTkSuQmCC", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "result = Predictive(\n", - " data_conditioned_model,\n", - " params={\"Theta\": Theta_inferred},\n", - " num_samples=1,\n", - " exclude_deterministic=False,\n", - ")(k_filter, obs_times=obs_times, obs_values=obs_values)\n", - "\n", - "filtered_mean = jnp.squeeze(result[\"f_filtered_states_mean\"], axis=0) # (T+1, 2)\n", - "filtered_cov_diag = jnp.squeeze(result[\"f_filtered_states_cov_diag\"], axis=0) # (T+1, 2)\n", - "filtered_std = jnp.sqrt(jnp.maximum(filtered_cov_diag, 1e-10))\n", - "\n", - "# Align lengths: filter may return T+1 (includes prior at t0)\n", - "n = min(len(times_1d), filtered_mean.shape[0])\n", - "t_plot = times_1d[:n]\n", - "fm = filtered_mean[:n]\n", - "fs = filtered_std[:n]\n", - "st = states[:n]\n", - "obs = obs_values[:n]\n", - "\n", - "from matplotlib.patches import Ellipse, Rectangle\n", - "from matplotlib.collections import PatchCollection\n", - "\n", - "fig, ax = plt.subplots(figsize=(7, 6), constrained_layout=True)\n", - "\n", - "# 1-sigma uncertainty ellipses at each timepoint.\n", - "# Covariance is diagonal, so ellipses are axis-aligned:\n", - "# semi-axis along v = fs[i, 0], semi-axis along w = fs[i, 1].\n", - "ellipses = [\n", - " Ellipse(xy=(fm[i, 0], fm[i, 1]), width=2 * fs[i, 0], height=2 * fs[i, 1])\n", - " for i in range(len(fm))\n", - "]\n", - "ec = PatchCollection(ellipses, facecolor=\"C0\", edgecolor=\"none\", alpha=0.07)\n", - "ax.add_collection(ec)\n", - "\n", - "ax.plot(st[:, 0], st[:, 1], \"k-\", label=\"True state\", linewidth=1.5, alpha=0.9)\n", - "ax.scatter(obs[:, 0], obs[:, 1], s=4, c=\"C1\", alpha=0.6, label=\"Noisy observations\")\n", - "ax.plot(fm[:, 0], fm[:, 1], \"C0-\", label=\"Filtered mean\", linewidth=1.2)\n", - "ax.legend(\n", - " handles=[\n", - " ax.lines[-1], # filtered mean line\n", - " ax.collections[-2], # noisy obs scatter\n", - " ax.lines[0], # true state line\n", - " Rectangle((0, 0), 1, 1, facecolor=\"C0\", alpha=0.35), # proxy for ellipses\n", - " ],\n", - " labels=[\"Filtered mean\", \"Noisy observations\", \"True state\", \"Filtered 1σ ellipses\"],\n", - " loc=\"upper right\", fontsize=9,\n", - ")\n", - "\n", - "ax.set_xlabel(\"$v$\")\n", - "ax.set_ylabel(\"$w$\")\n", - "ax.set_title(\"Phase space: true state, noisy data, filtering distribution (mean ± 1σ)\")\n", - "ax.grid(True, alpha=0.3)\n", - "ax.set_aspect(\"equal\")\n", - "ax.autoscale_view()\n", - "plt.show()" + "data": { + "image/png": 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", + "text/plain": [ + "
" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv (3.12.11)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" + }, + "metadata": {}, + "output_type": "display_data" } + ], + "source": [ + "result = Predictive(\n", + " data_conditioned_model,\n", + " params={\"Theta\": Theta_inferred},\n", + " num_samples=1,\n", + " exclude_deterministic=False,\n", + ")(k_filter, obs_times=obs_times, obs_values=obs_values)\n", + "\n", + "filtered_mean = jnp.squeeze(result[\"f_filtered_states_mean\"], axis=0) # (T+1, 2)\n", + "filtered_cov_diag = jnp.squeeze(result[\"f_filtered_states_cov_diag\"], axis=0) # (T+1, 2)\n", + "filtered_std = jnp.sqrt(jnp.maximum(filtered_cov_diag, 1e-10))\n", + "\n", + "# Align lengths: filter may return T+1 (includes prior at t0)\n", + "n = min(len(times_1d), filtered_mean.shape[0])\n", + "t_plot = times_1d[:n]\n", + "fm = filtered_mean[:n]\n", + "fs = filtered_std[:n]\n", + "st = states[:n]\n", + "obs = obs_values[:n]\n", + "\n", + "from matplotlib.patches import Ellipse, Rectangle\n", + "from matplotlib.collections import PatchCollection\n", + "\n", + "fig, ax = plt.subplots(figsize=(7, 6), constrained_layout=True)\n", + "\n", + "# 1-sigma uncertainty ellipses at each timepoint.\n", + "# Covariance is diagonal, so ellipses are axis-aligned:\n", + "# semi-axis along v = fs[i, 0], semi-axis along w = fs[i, 1].\n", + "ellipses = [\n", + " Ellipse(xy=(fm[i, 0], fm[i, 1]), width=2 * fs[i, 0], height=2 * fs[i, 1])\n", + " for i in range(len(fm))\n", + "]\n", + "ec = PatchCollection(ellipses, facecolor=\"C0\", edgecolor=\"none\", alpha=0.07)\n", + "ax.add_collection(ec)\n", + "\n", + "ax.plot(st[:, 0], st[:, 1], \"k-\", label=\"True state\", linewidth=1.5, alpha=0.9)\n", + "ax.scatter(obs[:, 0], obs[:, 1], s=4, c=\"C1\", alpha=0.6, label=\"Noisy observations\")\n", + "ax.plot(fm[:, 0], fm[:, 1], \"C0-\", label=\"Filtered mean\", linewidth=1.2)\n", + "ax.legend(\n", + " handles=[\n", + " ax.lines[-1], # filtered mean line\n", + " ax.collections[-2], # noisy obs scatter\n", + " ax.lines[0], # true state line\n", + " Rectangle((0, 0), 1, 1, facecolor=\"C0\", alpha=0.35), # proxy for ellipses\n", + " ],\n", + " labels=[\"Filtered mean\", \"Noisy observations\", \"True state\", \"Filtered 1σ ellipses\"],\n", + " loc=\"upper right\", fontsize=9,\n", + ")\n", + "\n", + "ax.set_xlabel(\"$v$\")\n", + "ax.set_ylabel(\"$w$\")\n", + "ax.set_title(\"Phase space: true state, noisy data, filtering distribution (mean ± 1σ)\")\n", + "ax.grid(True, alpha=0.3)\n", + "ax.set_aspect(\"equal\")\n", + "ax.autoscale_view()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv (3.12.11)", + "language": "python", + "name": "python3" }, - "nbformat": 4, - "nbformat_minor": 4 + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/docs/deep_dives/gp_drift.ipynb b/docs/deep_dives/gp_drift.ipynb index 19c9c082..65502fbd 100644 --- a/docs/deep_dives/gp_drift.ipynb +++ b/docs/deep_dives/gp_drift.ipynb @@ -194,7 +194,7 @@ "def make_state_evolution(drift_fn):\n", " return ContinuousTimeStateEvolution(\n", " drift=drift_fn,\n", - " diffusion_coefficient=lambda x, u, t: diffusion_coeff * jnp.eye(state_dim),\n", + " diffusion=dsx.FullDiffusion(diffusion_coeff * jnp.eye(state_dim)),\n", " )" ] }, diff --git a/docs/deep_dives/l63_speedup_dirac_vs_enkf.ipynb b/docs/deep_dives/l63_speedup_dirac_vs_enkf.ipynb index 9dd69fd9..052da46a 100644 --- a/docs/deep_dives/l63_speedup_dirac_vs_enkf.ipynb +++ b/docs/deep_dives/l63_speedup_dirac_vs_enkf.ipynb @@ -1,401 +1,401 @@ { - "cells": [ - { - "cell_type": "markdown", - "id": "intro", - "metadata": {}, - "source": [ - "# Speedups with full observations: \"Gradient-matching\" vs pseudo-marginal MCMC\n", - "\n", - "This tutorial compares two approaches for learning SDEs when we have **fully observed** states with **low observation noise** and **high-frequency measurements** (so observations approach exact state measurements, i.e. Dirac):\n", - "\n", - "1. **EnKF + NUTS** (filtering-based continuous-time): Uses `Filter` with EnKF to approximate the marginal likelihood, then NUTS for MCMC.\n", - "\n", - "1. **Gradient-matching**: Discretizes the SDE (Euler-Maruyama), treats observations as exact states (`DiracIdentityObservation`), and runs NUTS directly on all states and parameters. This avoids filtering entirely and is typically much faster. This approach loses accuracy when the following assumptions fail to hold:\n", - " - **Fully observed**: $y_t = x_t$ (or $y_t \\approx x_t$ with low noise)\n", - " - **Low noise**: $R = 0.01^2 I_3$ (approaches Dirac)\n", - " - **High-frequency**: $\\Delta t = 0.01$ over $[0, 20]$\n", - "\n", - "The speedup comes from data-conditioned independendence of the Euler-Maruyama increments induced by these assumptions---this independence allows us to vectorize (stack) all time-steps together and form a more traditional regression problem.\n", - "\n", - "\n", - "\n", - "We report timing and posteriors for both approaches." - ] - }, - { - "cell_type": "markdown", - "id": "setup", - "metadata": {}, - "source": [ - "## Setup and Model\n", - "\n", - "We use the Lorenz 63 system with:\n", - "- **Learn**: $\\rho \\sim \\mathcal{U}(10, 40)$" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "imports", - "metadata": {}, - "outputs": [], - "source": [ - "import time\n", - "\n", - "import jax.numpy as jnp\n", - "import jax.random as jr\n", - "import matplotlib.pyplot as plt\n", - "import numpyro\n", - "import numpyro.distributions as dist\n", - "from numpyro.infer import MCMC, NUTS, Predictive\n", - "\n", - "import dynestyx as dsx\n", - "from dynestyx import (\n", - " DynamicalModel,\n", - " ContinuousTimeStateEvolution,\n", - " DiracIdentityObservation,\n", - " LinearGaussianObservation,\n", - " DiscreteTimeSimulator,\n", - " Filter,\n", - " SDESimulator,\n", - " Discretizer,\n", - ")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "8b98a625", - "metadata": {}, - "outputs": [], - "source": [ - "def l63_fully_observed_model(dirac_observation: bool = False, obs_times=None, obs_values=None, predict_times=None):\n", - " \"\"\"Model that samples drift parameter rho and uses it in dynamics.\n", - " \n", - " Default is noisy Gaussian, full-state observations.\n", - " If `dirac_observation=True`, uses Dirac observations (y_t = x_t)\n", - " \n", - " \"\"\"\n", - " rho = numpyro.sample(\"rho\", dist.Uniform(10.0, 40.0))\n", - "\n", - " state_dim = 3\n", - " observation_dim = state_dim\n", - " observation_model = DiracIdentityObservation() if dirac_observation else LinearGaussianObservation(\n", - " H=jnp.eye(observation_dim, state_dim), R=jnp.eye(state_dim)\n", - " )\n", - " # Create the dynamical model with sampled rho\n", - " dynamics = DynamicalModel(\n", - " initial_condition=dist.MultivariateNormal(\n", - " loc=jnp.zeros(state_dim), covariance_matrix=20.0**2 * jnp.eye(state_dim)\n", - " ),\n", - " state_evolution=ContinuousTimeStateEvolution(\n", - " drift=lambda x, u, t: jnp.array(\n", - " [\n", - " 10.0 * (x[1] - x[0]),\n", - " x[0] * (rho - x[2]) - x[1],\n", - " x[0] * x[1] - (8.0 / 3.0) * x[2],\n", - " ]\n", - " ),\n", - " diffusion_coefficient=lambda x, u, t: jnp.eye(state_dim),\n", - " ),\n", - " observation_model=observation_model,\n", - " )\n", - "\n", - " # Return a sampled dynamical model, named \"f\".\n", - " return dsx.sample(\n", - " \"f\",\n", - " dynamics,\n", - " obs_times=obs_times,\n", - " obs_values=obs_values,\n", - " predict_times=predict_times,\n", - " )\n" - ] - }, - { - "cell_type": "markdown", - "id": "data_gen", - "metadata": {}, - "source": [ - "## Generate Synthetic Data\n", - "\n", - "We simulate the L63 SDE and add small Gaussian noise to get observations. With low noise, these approach the true states." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "gen_data", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Observations shape: (2000, 3)\n", - "True rho: 28.0\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "true_rho = 28.0\n", - "obs_times = jnp.arange(start=0.0, stop=20.0, step=0.01) # high-frequency\n", - "rng_key = jr.PRNGKey(0)\n", - "data_init_key, data_solver_key, mcmc_key = jr.split(rng_key, 3)\n", - "\n", - "true_params = {\"rho\": jnp.array(true_rho)}\n", - "predictive = Predictive(\n", - " l63_fully_observed_model,\n", - " params=true_params,\n", - " num_samples=1,\n", - " exclude_deterministic=False,\n", - ")\n", - "\n", - "with SDESimulator():\n", - " synthetic = predictive(data_init_key, predict_times=obs_times)\n", - "\n", - "# f_observations / f_states: (num_samples, n_sim, T, ...)\n", - "obs_values = synthetic[\"f_observations\"][0, 0] # (T, 3)\n", - "states = synthetic[\"f_states\"][0, 0] # (T, 3)\n", - "\n", - "print(f\"Observations shape: {obs_values.shape}\")\n", - "print(f\"True rho: {true_rho}\")\n", - "\n", - "# plot the data\n", - "obs_t = jnp.asarray(obs_times).squeeze()\n", - "for i, label in enumerate([\"x\", \"y\", \"z\"]):\n", - " plt.plot(obs_t, jnp.asarray(obs_values)[:, i], label=label)\n", - "plt.xlabel(\"Time\")\n", - "plt.ylabel(\"State\")\n", - "plt.legend()\n", - "plt.title(\"L63 synthetic data (fully observed, low noise)\")\n", - "plt.tight_layout()\n", - "plt.show()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "956a8401", - "metadata": {}, - "outputs": [], - "source": [ - "num_samples = 100\n", - "num_warmup = 100\n" - ] - }, + "cells": [ + { + "cell_type": "markdown", + "id": "intro", + "metadata": {}, + "source": [ + "# Speedups with full observations: \"Gradient-matching\" vs pseudo-marginal MCMC\n", + "\n", + "This tutorial compares two approaches for learning SDEs when we have **fully observed** states with **low observation noise** and **high-frequency measurements** (so observations approach exact state measurements, i.e. Dirac):\n", + "\n", + "1. **EnKF + NUTS** (filtering-based continuous-time): Uses `Filter` with EnKF to approximate the marginal likelihood, then NUTS for MCMC.\n", + "\n", + "1. **Gradient-matching**: Discretizes the SDE (Euler-Maruyama), treats observations as exact states (`DiracIdentityObservation`), and runs NUTS directly on all states and parameters. This avoids filtering entirely and is typically much faster. This approach loses accuracy when the following assumptions fail to hold:\n", + " - **Fully observed**: $y_t = x_t$ (or $y_t \\approx x_t$ with low noise)\n", + " - **Low noise**: $R = 0.01^2 I_3$ (approaches Dirac)\n", + " - **High-frequency**: $\\Delta t = 0.01$ over $[0, 20]$\n", + "\n", + "The speedup comes from data-conditioned independendence of the Euler-Maruyama increments induced by these assumptions---this independence allows us to vectorize (stack) all time-steps together and form a more traditional regression problem.\n", + "\n", + "\n", + "\n", + "We report timing and posteriors for both approaches." + ] + }, + { + "cell_type": "markdown", + "id": "setup", + "metadata": {}, + "source": [ + "## Setup and Model\n", + "\n", + "We use the Lorenz 63 system with:\n", + "- **Learn**: $\\rho \\sim \\mathcal{U}(10, 40)$" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "imports", + "metadata": {}, + "outputs": [], + "source": [ + "import time\n", + "\n", + "import jax.numpy as jnp\n", + "import jax.random as jr\n", + "import matplotlib.pyplot as plt\n", + "import numpyro\n", + "import numpyro.distributions as dist\n", + "from numpyro.infer import MCMC, NUTS, Predictive\n", + "\n", + "import dynestyx as dsx\n", + "from dynestyx import (\n", + " DynamicalModel,\n", + " ContinuousTimeStateEvolution,\n", + " DiracIdentityObservation,\n", + " LinearGaussianObservation,\n", + " DiscreteTimeSimulator,\n", + " Filter,\n", + " SDESimulator,\n", + " Discretizer,\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "8b98a625", + "metadata": {}, + "outputs": [], + "source": [ + "def l63_fully_observed_model(dirac_observation: bool = False, obs_times=None, obs_values=None, predict_times=None):\n", + " \"\"\"Model that samples drift parameter rho and uses it in dynamics.\n", + " \n", + " Default is noisy Gaussian, full-state observations.\n", + " If `dirac_observation=True`, uses Dirac observations (y_t = x_t)\n", + " \n", + " \"\"\"\n", + " rho = numpyro.sample(\"rho\", dist.Uniform(10.0, 40.0))\n", + "\n", + " state_dim = 3\n", + " observation_dim = state_dim\n", + " observation_model = DiracIdentityObservation() if dirac_observation else LinearGaussianObservation(\n", + " H=jnp.eye(observation_dim, state_dim), R=jnp.eye(state_dim)\n", + " )\n", + " # Create the dynamical model with sampled rho\n", + " dynamics = DynamicalModel(\n", + " initial_condition=dist.MultivariateNormal(\n", + " loc=jnp.zeros(state_dim), covariance_matrix=20.0**2 * jnp.eye(state_dim)\n", + " ),\n", + " state_evolution=ContinuousTimeStateEvolution(\n", + " drift=lambda x, u, t: jnp.array(\n", + " [\n", + " 10.0 * (x[1] - x[0]),\n", + " x[0] * (rho - x[2]) - x[1],\n", + " x[0] * x[1] - (8.0 / 3.0) * x[2],\n", + " ]\n", + " ),\n", + " diffusion=dsx.FullDiffusion(jnp.eye(state_dim)),\n", + " ),\n", + " observation_model=observation_model,\n", + " )\n", + "\n", + " # Return a sampled dynamical model, named \"f\".\n", + " return dsx.sample(\n", + " \"f\",\n", + " dynamics,\n", + " obs_times=obs_times,\n", + " obs_values=obs_values,\n", + " predict_times=predict_times,\n", + " )\n" + ] + }, + { + "cell_type": "markdown", + "id": "data_gen", + "metadata": {}, + "source": [ + "## Generate Synthetic Data\n", + "\n", + "We simulate the L63 SDE and add small Gaussian noise to get observations. With low noise, these approach the true states." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "gen_data", + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "id": "dirac_section", - "metadata": {}, - "source": [ - "## Approach 2: **Gradient-matching**\n", - "\n", - "Discretizes the SDE via Euler-Maruyama, uses `DiracIdentityObservation` (y_t = x_t), and runs NUTS. No filter needed." - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Observations shape: (2000, 3)\n", + "True rho: 28.0\n" + ] }, { - "cell_type": "code", - "execution_count": 5, - "id": "dirac_run", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "sample: 100%|██████████| 200/200 [00:00<00:00, 337.80it/s, 1 steps of size 3.44e-01. acc. prob=0.95]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Discretizer + Dirac + NUTS: 2.20 seconds\n", - "Posterior summary (rho):\n", - "Dirac:\n", - " mean = 27.70, std = 0.03\n", - "\n", - "True rho: 28.0\n" - ] - } - ], - "source": [ - "# For Dirac, we condition on the states (or low-noise obs as proxy for states)\n", - "# With low noise, obs_values ≈ states; Dirac treats them as exact.\n", - "with DiscreteTimeSimulator():\n", - " with Discretizer():\n", - " mcmc_dirac = MCMC(\n", - " NUTS(l63_fully_observed_model),\n", - " num_samples=num_samples,\n", - " num_warmup=num_warmup,\n", - " )\n", - "\n", - " mcmc_key_dirac = jr.PRNGKey(1)\n", - " t0 = time.perf_counter()\n", - " mcmc_dirac.run(mcmc_key_dirac, obs_times=obs_times, obs_values=obs_values, dirac_observation=True)\n", - " t_dirac = time.perf_counter() - t0\n", - "\n", - "posterior_dirac = mcmc_dirac.get_samples()\n", - "print(f\"Discretizer + Dirac + NUTS: {t_dirac:.2f} seconds\")\n", - "\n", - "# print true vs posterior\n", - "print(\"Posterior summary (rho):\")\n", - "print(\"Dirac:\")\n", - "print(f\" mean = {float(posterior_dirac['rho'].mean()):.2f}, std = {float(posterior_dirac['rho'].std()):.2f}\")\n", - "print(f\"\\nTrue rho: {true_rho}\")" + "data": { + "image/png": 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", + "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "true_rho = 28.0\n", + "obs_times = jnp.arange(start=0.0, stop=20.0, step=0.01) # high-frequency\n", + "rng_key = jr.PRNGKey(0)\n", + "data_init_key, data_solver_key, mcmc_key = jr.split(rng_key, 3)\n", + "\n", + "true_params = {\"rho\": jnp.array(true_rho)}\n", + "predictive = Predictive(\n", + " l63_fully_observed_model,\n", + " params=true_params,\n", + " num_samples=1,\n", + " exclude_deterministic=False,\n", + ")\n", + "\n", + "with SDESimulator():\n", + " synthetic = predictive(data_init_key, predict_times=obs_times)\n", + "\n", + "# f_observations / f_states: (num_samples, n_sim, T, ...)\n", + "obs_values = synthetic[\"f_observations\"][0, 0] # (T, 3)\n", + "states = synthetic[\"f_states\"][0, 0] # (T, 3)\n", + "\n", + "print(f\"Observations shape: {obs_values.shape}\")\n", + "print(f\"True rho: {true_rho}\")\n", + "\n", + "# plot the data\n", + "obs_t = jnp.asarray(obs_times).squeeze()\n", + "for i, label in enumerate([\"x\", \"y\", \"z\"]):\n", + " plt.plot(obs_t, jnp.asarray(obs_values)[:, i], label=label)\n", + "plt.xlabel(\"Time\")\n", + "plt.ylabel(\"State\")\n", + "plt.legend()\n", + "plt.title(\"L63 synthetic data (fully observed, low noise)\")\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "956a8401", + "metadata": {}, + "outputs": [], + "source": [ + "num_samples = 100\n", + "num_warmup = 100\n" + ] + }, + { + "cell_type": "markdown", + "id": "dirac_section", + "metadata": {}, + "source": [ + "## Approach 2: **Gradient-matching**\n", + "\n", + "Discretizes the SDE via Euler-Maruyama, uses `DiracIdentityObservation` (y_t = x_t), and runs NUTS. No filter needed." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "dirac_run", + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "id": "8b64f820", - "metadata": {}, - "source": [ - "## Approach 1: **EnKF + NUTS** (pseudo-marginal MCMC)\n", - "\n", - "Uses the continuous-discrete filter (EnKF) to approximate the marginal likelihood, then NUTS MCMC." - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "sample: 100%|██████████| 200/200 [00:00<00:00, 337.80it/s, 1 steps of size 3.44e-01. acc. prob=0.95]\n" + ] }, { - "cell_type": "code", - "execution_count": 6, - "id": "a2dfeb74", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "sample: 100%|██████████| 200/200 [01:41<00:00, 1.96it/s, 3 steps of size 5.12e-01. acc. prob=0.94] " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "EnKF + NUTS: 108.71 seconds\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "from dynestyx.inference.filters import ContinuousTimeEnKFConfig\n", - "\n", - "with Filter(filter_config=ContinuousTimeEnKFConfig(n_particles=25)):\n", - " mcmc_enkf = MCMC(\n", - " NUTS(l63_fully_observed_model), num_samples=num_samples, num_warmup=num_warmup\n", - " )\n", - "\n", - " t0 = time.perf_counter()\n", - " mcmc_enkf.run(mcmc_key, obs_times=obs_times, obs_values=obs_values, dirac_observation=False)\n", - " t_enkf = time.perf_counter() - t0\n", - "\n", - "posterior_enkf = mcmc_enkf.get_samples()\n", - "print(f\"EnKF + NUTS: {t_enkf:.2f} seconds\")" - ] - }, + "name": "stdout", + "output_type": "stream", + "text": [ + "Discretizer + Dirac + NUTS: 2.20 seconds\n", + "Posterior summary (rho):\n", + "Dirac:\n", + " mean = 27.70, std = 0.03\n", + "\n", + "True rho: 28.0\n" + ] + } + ], + "source": [ + "# For Dirac, we condition on the states (or low-noise obs as proxy for states)\n", + "# With low noise, obs_values ≈ states; Dirac treats them as exact.\n", + "with DiscreteTimeSimulator():\n", + " with Discretizer():\n", + " mcmc_dirac = MCMC(\n", + " NUTS(l63_fully_observed_model),\n", + " num_samples=num_samples,\n", + " num_warmup=num_warmup,\n", + " )\n", + "\n", + " mcmc_key_dirac = jr.PRNGKey(1)\n", + " t0 = time.perf_counter()\n", + " mcmc_dirac.run(mcmc_key_dirac, obs_times=obs_times, obs_values=obs_values, dirac_observation=True)\n", + " t_dirac = time.perf_counter() - t0\n", + "\n", + "posterior_dirac = mcmc_dirac.get_samples()\n", + "print(f\"Discretizer + Dirac + NUTS: {t_dirac:.2f} seconds\")\n", + "\n", + "# print true vs posterior\n", + "print(\"Posterior summary (rho):\")\n", + "print(\"Dirac:\")\n", + "print(f\" mean = {float(posterior_dirac['rho'].mean()):.2f}, std = {float(posterior_dirac['rho'].std()):.2f}\")\n", + "print(f\"\\nTrue rho: {true_rho}\")" + ] + }, + { + "cell_type": "markdown", + "id": "8b64f820", + "metadata": {}, + "source": [ + "## Approach 1: **EnKF + NUTS** (pseudo-marginal MCMC)\n", + "\n", + "Uses the continuous-discrete filter (EnKF) to approximate the marginal likelihood, then NUTS MCMC." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "a2dfeb74", + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "id": "compare", - "metadata": {}, - "source": [ - "## Comparison" - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "sample: 100%|██████████| 200/200 [01:41<00:00, 1.96it/s, 3 steps of size 5.12e-01. acc. prob=0.94] " + ] }, { - "cell_type": "code", - "execution_count": 7, - "id": "timing", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "==================================================\n", - "TIMING\n", - "==================================================\n", - "EnKF + NUTS: 108.71 s\n", - "Discretizer + Dirac + NUTS: 2.20 s\n", - "Speedup: 49.5x\n", - "==================================================\n", - "==================================================\n", - "POSTERIOR SUMMARY\n", - "==================================================\n", - "EnKF:\n", - " mean = 28.01, std = 0.04\n", - "Dirac:\n", - " mean = 27.70, std = 0.03\n", - "\n", - "True rho: 28.0\n" - ] - } - ], - "source": [ - "print(\"=\" * 50)\n", - "print(\"TIMING\")\n", - "print(\"=\" * 50)\n", - "print(f\"EnKF + NUTS: {t_enkf:.2f} s\")\n", - "print(f\"Discretizer + Dirac + NUTS: {t_dirac:.2f} s\")\n", - "print(f\"Speedup: {t_enkf / t_dirac:.1f}x\")\n", - "print(\"=\" * 50)\n", - "\n", - "# print mean and std of rho from both posteriors\n", - "print(\"=\" * 50)\n", - "print(\"POSTERIOR SUMMARY\")\n", - "print(\"=\" * 50)\n", - "print(\"EnKF:\")\n", - "print(f\" mean = {float(posterior_enkf['rho'].mean()):.2f}, std = {float(posterior_enkf['rho'].std()):.2f}\")\n", - "print(\"Dirac:\")\n", - "print(f\" mean = {float(posterior_dirac['rho'].mean()):.2f}, std = {float(posterior_dirac['rho'].std()):.2f}\")\n", - "print(f\"\\nTrue rho: {true_rho}\")\n", - "\n" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "EnKF + NUTS: 108.71 seconds\n" + ] }, { - "cell_type": "markdown", - "id": "4dc69f9b", - "metadata": {}, - "source": [ - "Note that the speedup scales with T (number of observations), so a 10x longer timeseries would experience ~10x further speedup using Discretizer + Dirac. Feel free to experiment" - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv (3.12.11)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" + ], + "source": [ + "from dynestyx.inference.filters import ContinuousTimeEnKFConfig\n", + "\n", + "with Filter(filter_config=ContinuousTimeEnKFConfig(n_particles=25)):\n", + " mcmc_enkf = MCMC(\n", + " NUTS(l63_fully_observed_model), num_samples=num_samples, num_warmup=num_warmup\n", + " )\n", + "\n", + " t0 = time.perf_counter()\n", + " mcmc_enkf.run(mcmc_key, obs_times=obs_times, obs_values=obs_values, dirac_observation=False)\n", + " t_enkf = time.perf_counter() - t0\n", + "\n", + "posterior_enkf = mcmc_enkf.get_samples()\n", + "print(f\"EnKF + NUTS: {t_enkf:.2f} seconds\")" + ] + }, + { + "cell_type": "markdown", + "id": "compare", + "metadata": {}, + "source": [ + "## Comparison" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "timing", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "==================================================\n", + "TIMING\n", + "==================================================\n", + "EnKF + NUTS: 108.71 s\n", + "Discretizer + Dirac + NUTS: 2.20 s\n", + "Speedup: 49.5x\n", + "==================================================\n", + "==================================================\n", + "POSTERIOR SUMMARY\n", + "==================================================\n", + "EnKF:\n", + " mean = 28.01, std = 0.04\n", + "Dirac:\n", + " mean = 27.70, std = 0.03\n", + "\n", + "True rho: 28.0\n" + ] } + ], + "source": [ + "print(\"=\" * 50)\n", + "print(\"TIMING\")\n", + "print(\"=\" * 50)\n", + "print(f\"EnKF + NUTS: {t_enkf:.2f} s\")\n", + "print(f\"Discretizer + Dirac + NUTS: {t_dirac:.2f} s\")\n", + "print(f\"Speedup: {t_enkf / t_dirac:.1f}x\")\n", + "print(\"=\" * 50)\n", + "\n", + "# print mean and std of rho from both posteriors\n", + "print(\"=\" * 50)\n", + "print(\"POSTERIOR SUMMARY\")\n", + "print(\"=\" * 50)\n", + "print(\"EnKF:\")\n", + "print(f\" mean = {float(posterior_enkf['rho'].mean()):.2f}, std = {float(posterior_enkf['rho'].std()):.2f}\")\n", + "print(\"Dirac:\")\n", + "print(f\" mean = {float(posterior_dirac['rho'].mean()):.2f}, std = {float(posterior_dirac['rho'].std()):.2f}\")\n", + "print(f\"\\nTrue rho: {true_rho}\")\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "4dc69f9b", + "metadata": {}, + "source": [ + "Note that the speedup scales with T (number of observations), so a 10x longer timeseries would experience ~10x further speedup using Discretizer + Dirac. Feel free to experiment" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv (3.12.11)", + "language": "python", + "name": "python3" }, - "nbformat": 4, - "nbformat_minor": 5 + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 } diff --git a/docs/faq.md b/docs/faq.md index 59e90b03..21a52455 100644 --- a/docs/faq.md +++ b/docs/faq.md @@ -60,10 +60,15 @@ with ODESimulator(): ``` Despite the deterministic nature of an ODE, sometimes a filtering-algorithm helps a lot (especially for long timeseries rollouts, partial/noisy observations, systems with large sensitivities to intial conditions). You can modify the model definition to have a small diffusion coefficient to "relax" the ODE problem to an SDE. ```python +from dynestyx import FullDiffusion from dynestyx.inference.filters import Filter, ContinuousTimeEnKFConfig with Filter(filter_config=ContinuousTimeEnKFConfig()): - return model(obs_times=obs_times, obs_values=obs_values, diffusion_coefficient=0.01) + return model( + obs_times=obs_times, + obs_values=obs_values, + diffusion=FullDiffusion(0.01 * jnp.eye(state_dim)), + ) ``` diff --git a/docs/logo/make_logo.py b/docs/logo/make_logo.py index 7b21deed..484be407 100644 --- a/docs/logo/make_logo.py +++ b/docs/logo/make_logo.py @@ -15,23 +15,24 @@ import argparse import os -import dynestyx as dsx import imageio.v2 as imageio import jax.numpy as jnp import jax.random as jr import numpy as np import numpyro.distributions as dist +from numpyro.infer import Predictive +from PIL import Image, ImageDraw, ImageFont +from scipy import ndimage +from scipy.ndimage import binary_erosion + +import dynestyx as dsx from dynestyx import ( ContinuousTimeStateEvolution, DiracIdentityObservation, DynamicalModel, + FullDiffusion, SDESimulator, ) -from numpyro.infer import Predictive -from PIL import Image, ImageDraw, ImageFont -from scipy import ndimage -from scipy.ndimage import binary_erosion - # ----------------------------- # Fonts (cross-platform) @@ -286,9 +287,6 @@ def potential_fn(x, u, t): dist_to_boundary = bilinear_sample_jax(dist_grid_j, x[0], x[1]) return 0.5 * kappa * (dist_to_boundary - ring) ** 2 - def diffusion_fn(x, u, t): - return sigma * jnp.eye(2, dtype=jnp.float32) - dynamics = DynamicalModel( control_dim=0, initial_condition=dist.Uniform( @@ -299,7 +297,7 @@ def diffusion_fn(x, u, t): drift=drift_fn, potential=potential_fn, use_negative_gradient=True, - diffusion_coefficient=diffusion_fn, + diffusion=FullDiffusion(sigma * jnp.eye(2, dtype=jnp.float32)), ), observation_model=DiracIdentityObservation(), ) diff --git a/docs/math_intro.md b/docs/math_intro.md index ec905601..d1fe6f10 100644 --- a/docs/math_intro.md +++ b/docs/math_intro.md @@ -44,7 +44,7 @@ dynamics = DynamicalModel( initial_condition=dist.MultivariateNormal(...), state_evolution=ContinuousTimeStateEvolution( drift=lambda x, u, t: ..., - diffusion_coefficient=lambda x, u, t: ..., + diffusion=dsx.FullDiffusion(...), ), observation_model=lambda x, u, t: ..., ) @@ -136,4 +136,4 @@ Detailed API documentation is available for all modules, classes, and functions [^1]: We also allow for some more general state space models than are described here. For example, the state need not be real (see, for example, the Hidden Markov Model tutorials). -[^2]: As another example of support for general models, we also allow for deterministic dynamical systems (i.e., ODEs). \ No newline at end of file +[^2]: As another example of support for general models, we also allow for deterministic dynamical systems (i.e., ODEs). diff --git a/docs/quick_example.ipynb b/docs/quick_example.ipynb index 9944d2c8..5b34c480 100644 --- a/docs/quick_example.ipynb +++ b/docs/quick_example.ipynb @@ -1,277 +1,277 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Quick Example: Lorenz 63\n", - "\n", - "This notebook demonstrates simulation and inference on **Lorenz 63** with **partial, noisy observations**. We infer both the dynamics parameter $\\rho$ and the observation noise standard deviation $\\sigma_{\\text{obs}}$." - ] - }, - { - "cell_type": "markdown", - "id": "deff97e0", - "metadata": {}, - "source": [ - "## Setup and model\n", - "\n", - "Lorenz 63: \n", - "\n", - "$dx = f(x)\\,dt + dW$ with\n", - "$$f(x) = \\begin{pmatrix} \\sigma(x_2 - x_1) \\\\ x_1(\\rho - x_3) - x_2 \\\\ x_1 x_2 - \\beta x_3 \\end{pmatrix}.$$\n", - "\n", - "We observe **only $x_1$** with Gaussian noise: \n", - "\n", - "$y_t = Hx(t) + \\varepsilon_t = x_1(t) + \\varepsilon_t$, $\\varepsilon_t \\sim \\mathcal{N}(0, \\sigma_{\\text{obs}}^2).$\n", - "\n", - "\n", - "We fix $\\sigma=10$, $\\beta=8/3$. Here $H := [1, 0, 0]$ to observe the first component.\n", - "\n", - "Priors on the inferred parameters:\n", - "- $\\rho \\sim \\text{Uniform}(10, 40)$\n", - "- $\\sigma_{\\text{obs}} \\sim \\text{LogNormal}(0, 0.5)$\n", - "\n", - "Our goal is to recover the posterior $p(\\rho, \\sigma \\mid y_1, \\dots, y_T)$.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "474da346", - "metadata": {}, - "outputs": [], - "source": [ - "import jax.numpy as jnp\n", - "import jax.random as jr\n", - "import numpyro\n", - "import numpyro.distributions as dist\n", - "from dynestyx import (\n", - " ContinuousTimeStateEvolution, DynamicalModel,\n", - " LinearGaussianObservation, SDESimulator, Filter,\n", - " sample,\n", - ")\n", - "from numpyro.infer import Predictive, MCMC, NUTS\n", - "\n", - "def l63_model(rho=None, obs_std=None, diff_std=None, obs_times=None, obs_values=None):\n", - " # define priors\n", - " rho = numpyro.sample(\"rho\", dist.Uniform(10.0, 40.0), obs=rho)\n", - " obs_std = numpyro.sample(\"obs_std\", dist.LogNormal(0.0, 0.5), obs=obs_std)\n", - " diff_std = numpyro.sample(\"diff_std\", dist.LogNormal(0.0, 0.5), obs=diff_std)\n", - "\n", - " # define the model components\n", - " state_dim = 3\n", - " initial_condition = dist.MultivariateNormal(\n", - " loc=jnp.zeros(state_dim), covariance_matrix=20.0**2 * jnp.eye(state_dim)\n", - " )\n", - " observation_model = LinearGaussianObservation(\n", - " H=jnp.array([[1.0, 0.0, 0.0]]),\n", - " R=jnp.array([[obs_std**2]]),\n", - " )# observe only x1 with Gaussian noise\n", - " state_evolution = ContinuousTimeStateEvolution(\n", - " drift=lambda x, u, t: jnp.array([\n", - " 10.0 * (x[1] - x[0]),\n", - " x[0] * (rho - x[2]) - x[1],\n", - " x[0] * x[1] - (8.0 / 3.0) * x[2],\n", - " ]),\n", - " diffusion_coefficient=lambda x, u, t: diff_std * jnp.eye(state_dim),\n", - " )\n", - " \n", - " # define the model\n", - " dynamics = DynamicalModel(\n", - " initial_condition=initial_condition,\n", - " state_evolution=state_evolution,\n", - " observation_model=observation_model,\n", - " )\n", - " \n", - " # sample the model\n", - " sample(\"f\", dynamics, obs_times=obs_times, obs_values=obs_values)" - ] - }, - { - "cell_type": "markdown", - "id": "94a91967", - "metadata": {}, - "source": [ - "## Simulation" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "d891349e", - "metadata": {}, - "outputs": [], - "source": [ - "key = jr.PRNGKey(0)\n", - "rho_true, obs_std_true, diff_std_true = 28.0, 1.0, 1.0\n", - "times = jnp.arange(0.0, 20.0, 0.05)\n", - "\n", - "with SDESimulator():\n", - " samples = Predictive(l63_model, num_samples=1)(jr.PRNGKey(1), rho=rho_true, obs_std=obs_std_true, predict_times=times)\n", - "\n", - "states = samples[\"f_states\"][0]\n", - "observations = samples[\"f_observations\"][0]\n", - "times_arr = samples[\"f_times\"][0]" - ] - }, - { - "cell_type": "markdown", - "id": "57ce3cbc", - "metadata": {}, - "source": [ - "## Plot" - ] - }, + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Quick Example: Lorenz 63\n", + "\n", + "This notebook demonstrates simulation and inference on **Lorenz 63** with **partial, noisy observations**. We infer both the dynamics parameter $\\rho$ and the observation noise standard deviation $\\sigma_{\\text{obs}}$." + ] + }, + { + "cell_type": "markdown", + "id": "deff97e0", + "metadata": {}, + "source": [ + "## Setup and model\n", + "\n", + "Lorenz 63: \n", + "\n", + "$dx = f(x)\\,dt + dW$ with\n", + "$$f(x) = \\begin{pmatrix} \\sigma(x_2 - x_1) \\\\ x_1(\\rho - x_3) - x_2 \\\\ x_1 x_2 - \\beta x_3 \\end{pmatrix}.$$\n", + "\n", + "We observe **only $x_1$** with Gaussian noise: \n", + "\n", + "$y_t = Hx(t) + \\varepsilon_t = x_1(t) + \\varepsilon_t$, $\\varepsilon_t \\sim \\mathcal{N}(0, \\sigma_{\\text{obs}}^2).$\n", + "\n", + "\n", + "We fix $\\sigma=10$, $\\beta=8/3$. Here $H := [1, 0, 0]$ to observe the first component.\n", + "\n", + "Priors on the inferred parameters:\n", + "- $\\rho \\sim \\text{Uniform}(10, 40)$\n", + "- $\\sigma_{\\text{obs}} \\sim \\text{LogNormal}(0, 0.5)$\n", + "\n", + "Our goal is to recover the posterior $p(\\rho, \\sigma \\mid y_1, \\dots, y_T)$.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "474da346", + "metadata": {}, + "outputs": [], + "source": [ + "import jax.numpy as jnp\n", + "import jax.random as jr\n", + "import numpyro\n", + "import numpyro.distributions as dist\n", + "from dynestyx import (\n", + " ContinuousTimeStateEvolution, DynamicalModel, FullDiffusion,\n", + " LinearGaussianObservation, SDESimulator, Filter,\n", + " sample,\n", + ")\n", + "from numpyro.infer import Predictive, MCMC, NUTS\n", + "\n", + "def l63_model(rho=None, obs_std=None, diff_std=None, obs_times=None, obs_values=None):\n", + " # define priors\n", + " rho = numpyro.sample(\"rho\", dist.Uniform(10.0, 40.0), obs=rho)\n", + " obs_std = numpyro.sample(\"obs_std\", dist.LogNormal(0.0, 0.5), obs=obs_std)\n", + " diff_std = numpyro.sample(\"diff_std\", dist.LogNormal(0.0, 0.5), obs=diff_std)\n", + "\n", + " # define the model components\n", + " state_dim = 3\n", + " initial_condition = dist.MultivariateNormal(\n", + " loc=jnp.zeros(state_dim), covariance_matrix=20.0**2 * jnp.eye(state_dim)\n", + " )\n", + " observation_model = LinearGaussianObservation(\n", + " H=jnp.array([[1.0, 0.0, 0.0]]),\n", + " R=jnp.array([[obs_std**2]]),\n", + " )# observe only x1 with Gaussian noise\n", + " state_evolution = ContinuousTimeStateEvolution(\n", + " drift=lambda x, u, t: jnp.array([\n", + " 10.0 * (x[1] - x[0]),\n", + " x[0] * (rho - x[2]) - x[1],\n", + " x[0] * x[1] - (8.0 / 3.0) * x[2],\n", + " ]),\n", + " diffusion=FullDiffusion(diff_std * jnp.eye(state_dim)),\n", + " )\n", + " \n", + " # define the model\n", + " dynamics = DynamicalModel(\n", + " initial_condition=initial_condition,\n", + " state_evolution=state_evolution,\n", + " observation_model=observation_model,\n", + " )\n", + " \n", + " # sample the model\n", + " sample(\"f\", dynamics, obs_times=obs_times, obs_values=obs_values)" + ] + }, + { + "cell_type": "markdown", + "id": "94a91967", + "metadata": {}, + "source": [ + "## Simulation" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "d891349e", + "metadata": {}, + "outputs": [], + "source": [ + "key = jr.PRNGKey(0)\n", + "rho_true, obs_std_true, diff_std_true = 28.0, 1.0, 1.0\n", + "times = jnp.arange(0.0, 20.0, 0.05)\n", + "\n", + "with SDESimulator():\n", + " samples = Predictive(l63_model, num_samples=1)(jr.PRNGKey(1), rho=rho_true, obs_std=obs_std_true, predict_times=times)\n", + "\n", + "states = samples[\"f_states\"][0]\n", + "observations = samples[\"f_observations\"][0]\n", + "times_arr = samples[\"f_times\"][0]" + ] + }, + { + "cell_type": "markdown", + "id": "57ce3cbc", + "metadata": {}, + "source": [ + "## Plot" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "03a43c82", + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 3, - "id": "03a43c82", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "fig, axes = plt.subplots(2, 1, figsize=(9, 4), sharex=True)\n", - "axes[0].plot(times_arr, states[:, 0], label=\"$x_1$\")\n", - "axes[0].plot(times_arr, states[:, 1], label=\"$x_2$\")\n", - "axes[0].plot(times_arr, states[:, 2], label=\"$x_3$\")\n", - "axes[0].set_ylabel(\"state\")\n", - "axes[0].legend(loc=\"upper right\")\n", - "axes[1].scatter(times_arr, observations[:, 0], s=4, alpha=0.7, label=\"obs ($x_1$ + noise)\")\n", - "axes[1].plot(times_arr, states[:, 0], color=\"C0\", alpha=0.5, ls=\"--\", label=\"true $x_1$\")\n", - "axes[1].set_ylabel(\"observation\")\n", - "axes[1].set_xlabel(\"time\")\n", - "axes[1].legend(loc=\"upper right\")\n", - "plt.tight_layout()\n", - "plt.show()" + "data": { + "image/png": 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", + "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axes = plt.subplots(2, 1, figsize=(9, 4), sharex=True)\n", + "axes[0].plot(times_arr, states[:, 0], label=\"$x_1$\")\n", + "axes[0].plot(times_arr, states[:, 1], label=\"$x_2$\")\n", + "axes[0].plot(times_arr, states[:, 2], label=\"$x_3$\")\n", + "axes[0].set_ylabel(\"state\")\n", + "axes[0].legend(loc=\"upper right\")\n", + "axes[1].scatter(times_arr, observations[:, 0], s=4, alpha=0.7, label=\"obs ($x_1$ + noise)\")\n", + "axes[1].plot(times_arr, states[:, 0], color=\"C0\", alpha=0.5, ls=\"--\", label=\"true $x_1$\")\n", + "axes[1].set_ylabel(\"observation\")\n", + "axes[1].set_xlabel(\"time\")\n", + "axes[1].legend(loc=\"upper right\")\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "05aad6f0", + "metadata": {}, + "source": [ + "## Inference" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "cf579407", + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "id": "05aad6f0", - "metadata": {}, - "source": [ - "## Inference" - ] - }, + "name": "stderr", + "output_type": "stream", + "text": [ + "sample: 100%|██████████| 200/200 [06:13<00:00, 1.87s/it, 7 steps of size 5.87e-01. acc. prob=0.93] \n" + ] + } + ], + "source": [ + "# Observed data: times and values\n", + "obs_times = times_arr\n", + "obs_values = observations\n", + "\n", + "# Tells the model to marginalize over the latent states using a filter\n", + "# Default is Ensemble Kalman Filter (EnKF) for SDEs with linear Gaussian observation model\n", + "from dynestyx.inference.filters import ContinuousTimeEnKFConfig\n", + "with Filter(filter_config=ContinuousTimeEnKFConfig(warn=False)): \n", + " # Run NUTS with MCMC. The below is simple numpyro code.\n", + " mcmc = MCMC(NUTS(l63_model), num_warmup=100, num_samples=100)\n", + " mcmc.run(jr.PRNGKey(2), obs_times=obs_times, obs_values=obs_values)" + ] + }, + { + "cell_type": "markdown", + "id": "d2dccf59", + "metadata": {}, + "source": [ + "## Posterior" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "d1357ec7", + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 4, - "id": "cf579407", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "sample: 100%|██████████| 200/200 [06:13<00:00, 1.87s/it, 7 steps of size 5.87e-01. acc. prob=0.93] \n" - ] - } - ], - "source": [ - "# Observed data: times and values\n", - "obs_times = times_arr\n", - "obs_values = observations\n", - "\n", - "# Tells the model to marginalize over the latent states using a filter\n", - "# Default is Ensemble Kalman Filter (EnKF) for SDEs with linear Gaussian observation model\n", - "from dynestyx.inference.filters import ContinuousTimeEnKFConfig\n", - "with Filter(filter_config=ContinuousTimeEnKFConfig(warn=False)): \n", - " # Run NUTS with MCMC. The below is simple numpyro code.\n", - " mcmc = MCMC(NUTS(l63_model), num_warmup=100, num_samples=100)\n", - " mcmc.run(jr.PRNGKey(2), obs_times=obs_times, obs_values=obs_values)" + "data": { + "image/png": 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", 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", 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", 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import arviz as az\n", - "\n", - "posterior = mcmc.get_samples()\n", - "az.style.use(\"arviz-white\")\n", - "az.plot_posterior(posterior[\"rho\"], hdi_prob=0.95, ref_val=rho_true)\n", - "plt.show()\n", - "az.plot_posterior(posterior[\"obs_std\"], hdi_prob=0.95, ref_val=obs_std_true)\n", - "plt.show()\n", - "az.plot_posterior(posterior[\"diff_std\"], hdi_prob=0.95, ref_val=diff_std_true)\n", - "plt.show()\n" + "data": { + "image/png": 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", + "text/plain": [ + "
" ] + }, + "metadata": {}, + "output_type": "display_data" } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.10" - } + ], + "source": [ + "import arviz as az\n", + "\n", + "posterior = mcmc.get_samples()\n", + "az.style.use(\"arviz-white\")\n", + "az.plot_posterior(posterior[\"rho\"], hdi_prob=0.95, ref_val=rho_true)\n", + "plt.show()\n", + "az.plot_posterior(posterior[\"obs_std\"], hdi_prob=0.95, ref_val=obs_std_true)\n", + "plt.show()\n", + "az.plot_posterior(posterior[\"diff_std\"], hdi_prob=0.95, ref_val=diff_std_true)\n", + "plt.show()\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" }, - "nbformat": 4, - "nbformat_minor": 5 + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 } diff --git a/docs/tutorials/gentle_intro/02_dynestyx_discrete_intro.ipynb b/docs/tutorials/gentle_intro/02_dynestyx_discrete_intro.ipynb index 4eedb22f..145f15ce 100644 --- a/docs/tutorials/gentle_intro/02_dynestyx_discrete_intro.ipynb +++ b/docs/tutorials/gentle_intro/02_dynestyx_discrete_intro.ipynb @@ -1,621 +1,620 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Part 2: Dynestyx — NumPyro with better support for dynamical systems\n", - "We introduce **dynestyx** as an extension of NumPyro for **dynamical systems**, with a clear separation between *what* the model is and *how* we simulate or score it." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2.1 Separation of concerns\n", - "\n", - "**Dynestyx** extends NumPyro by giving you a standard way to work with dynamical systems. The key idea is **separation of concerns**:\n", - "\n", - "- **What** the model is: parameters $\\theta$, initial condition $p(x_0)$, state evolution (discrete or continuous time), observation model $p(y_t \\mid x_t, \\ldots)$. This is the `DynamicalModel`—you write it once as a generative model in code.\n", - "- **How** we simulate: *simulators* (e.g. `DiscreteTimeSimulator`, `SDESimulator`) unroll the dynamics step-by-step and generate state/observation trajectories. They interpret `dsx.sample(\"name\", dynamics)` as \"run the model forward in time.\"\n", - "- **How** we do inference: we can use either *simulators* (which sample latent states $x_{0:T}$ explicitly) or *filters* (which marginalize over them and compute $p(y_{1:T} \\mid \\theta)$). On top of that, we run standard NumPyro inference—**NUTS**, **SVI**, or others—to infer parameters (and optionally latent states when using a simulator).\n", - "\n", - "You write the model once; then you choose how to interpret it (simulator vs. filter) and which inference algorithm to use." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2.2 A first Dynestyx model\n", - "\n", - "For pedagogical purposes, we begin with a classic discrete-time linear-Gaussian system with controls. \n", - "\n", - "$$\n", - "\\begin{aligned}\n", - "x_{t+1} &= Ax_t + Bu_t + \\epsilon_t \\\\\n", - "y_t &= Cx_t + \\eta_t\n", - "\\end{aligned}\n", - "$$\n", - "with\n", - "$$\n", - "\\begin{aligned}\n", - "x_0 &\\sim \\mathcal{N}(m_0, \\ C_0) \\\\\n", - "\\epsilon_t &\\sim \\mathcal{N}(0, \\ \\Sigma) \\\\\n", - "\\eta_t &\\sim \\mathcal{N}(0, \\ \\Gamma) \n", - "\\end{aligned}\n", - "$$\n", - "\n", - "Written differently, we have:\n", - "$$\n", - "\\begin{aligned}\n", - "\\text{Initial Condition:} \\quad x_0 &\\sim \\mathcal{N}(m_0, \\ C_0) \\\\\n", - "\\text{State-transition:} \\quad x_{t+1} &\\sim \\mathcal{N}(Ax_t + Bu_t, \\ \\Sigma) \\\\\n", - "\\text{Observation model:} \\quad y_{t} &\\sim \\mathcal{N}(Cx_t, \\ \\Gamma) \\\\\n", - "\\end{aligned}\n", - "$$\n", - "\n", - "Furthermore, say we have prior belief about a subset of parameters in the model. Concretely, we will assume\n", - "\n", - "$$\n", - "\\begin{aligned}\n", - "A &= \\begin{bmatrix} 0 & 0.3 \\\\ \\rho & -0.2 \\end{bmatrix} \\\\\n", - "B &= \\begin{bmatrix} 1 \\\\ 0 \\end{bmatrix} \\\\\n", - "C &= \\begin{bmatrix} 1 & 0 \\end{bmatrix} \\\\\n", - "\\Sigma &= 0.1^2 I \\\\\n", - "\\Gamma &= 0.1^2 I \\\\\n", - "m_0 &= 0\\\\\n", - "C_0 &= I\n", - "\\end{aligned}\n", - "$$\n", - "\n", - "and place a prior over the single unknown, $\\rho$, in the system:\n", - "\n", - "$$ \\rho \\sim \\mathcal{U}([-0.9, 0.9]).$$\n", - "\n", - "This induces a generative model.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "At the highest level, the idea is to create a NumPyro model that samples from this dynamical system. To do this, we use the `DynamicalModel` class in dynestyx, paired with the `dsx.sample` statement. " - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "import numpyro\n", - "import numpyro.distributions as dist\n", - "\n", - "import dynestyx as dsx\n", - "from dynestyx import DynamicalModel\n", - "\n", - "\n", - "def fake_lti_model(obs_times=None, obs_values=None):\n", - " # sample the unknown parameter\n", - " rho = numpyro.sample(\"rho\", dist.Uniform(-0.9, 0.9))\n", - " # create the dynamical model depending on the parameter\n", - " rho_dynamics = DynamicalModel(..., rho, ...) # not real syntax\n", - " # sample from the dynamical model\n", - " dsx.sample(\"f\", rho_dynamics, obs_times=obs_times, obs_values=obs_values)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "At this level, you can think of writing `dsx.sample(...)` as rather abstract---at this point, we don't worry about HOW to sample the system. \n", - "\n", - "Why? Dynestyx allows us to have different \"interpretations\" of the `dsx.sample` statement, depending on the task at hand. To give a few examples of how we may interpret the dynamical system later, we may:\n", - "- Use algorithmic strategies (e.g., filtering or smoothing) to efficiently condition `lti_model` on available data.\n", - "- Specify key parts of *how* we simulate, which is particularly important when we use differential equations later on.\n", - "- Explore various approximations of the dynamical system (e.g., Gaussian states, linear observations, or discretizations of a differential equation), *without* modifying the underlying model.\n", - "- Freely experiment with these differing strategies as part of the Bayesian workflow discussed in the previous tutorial.\n", - "\n", - "Let's dive in a bit more how to build a `DynamicalModel`." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The `DynamicalModel` class can be instantiated with three main ingredients:\n", - "- `initial_condition`: can be any NumPyro distribution\n", - "- `state_evolution`: can be one of two classes\n", - " - `DiscreteTimeStateEvolution`:\n", - " - A callable $(x, u, t_\\text{now}, t_\\text{next}) \\mapsto \\ $ `numpyro.distributions` object (which can include things like categorical distributions)\n", - " - `ContinuousTimeStateEvolution`: has fields\n", - " - `drift`: A callable $(x, u, t) \\mapsto \\ \\mathbb{R}^{d_x}$\n", - " - `diffusion_coefficient`: A callable $(x, u, t) \\mapsto \\ \\mathbb{R}^{d_x \\times d_x}$\n", - " - `diffusion_covariance`: A callable $(x, u, t) \\mapsto \\ \\mathbb{R}^{d_x \\times d_x}$\n", - "- `observation_model`: A callable $(x, u, t) \\mapsto \\ $ `numpyro.distributions` object\n", - "\n", - "It also requires specification of the key dimensions in the problem:\n", - "- `state_dim`: $\\text{dim}(x_t)$\n", - "- `observation_dim`: $\\text{dim}(y_t)$\n", - "- `control_dim`: $\\text{dim}(u_t)$\n" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "import jax.numpy as jnp\n", - "\n", - "from dynestyx.models import DynamicalModel # noqa: F811\n", - "\n", - "# for convenience, we can define \"fixed\" things in the model outside of it.\n", - "# this is not required, but it helps keep the model clean.\n", - "state_dim = 2\n", - "observation_dim = 1\n", - "control_dim = 1\n", - "\n", - "# Create the known matrices B, C\n", - "B = jnp.eye(state_dim, control_dim)\n", - "C = jnp.eye(observation_dim, state_dim)\n", - "\n", - "# create the initial condition as a distribution\n", - "initial_condition = dist.MultivariateNormal(jnp.zeros(state_dim), jnp.eye(state_dim))\n", - "\n", - "# create the observation model as a callable mapping to a distribution\n", - "observation_model = lambda x, u, t: dist.MultivariateNormal(\n", - " C @ x, 0.1**2 * jnp.eye(observation_dim)\n", - ")\n", - "\n", - "\n", - "def lti_model(rho=None, obs_times=None, obs_values=None, ctrl_times=None, ctrl_values=None, predict_times=None):\n", - " # sample the unknown parameter\n", - " rho = numpyro.sample(\"rho\", dist.Uniform(-0.5, 0.5), obs=rho)\n", - " A = jnp.array([[0, 0.3], [rho, -0.2]])\n", - "\n", - " # create the state evolution as a callable mapping to a distribution\n", - " # Crucially, this depends on A, which depends on rho, which is unknown.\n", - " # Thus, the state evolution MUST be defined within `lti_model`, not outside.\n", - " state_evolution = lambda x, u, t_now, t_next: dist.MultivariateNormal(\n", - " A @ x + B @ u, 0.1**2 * jnp.eye(state_dim)\n", - " )\n", - "\n", - " # create the dynamical model\n", - " dynamics = DynamicalModel(\n", - " control_dim=control_dim,\n", - " initial_condition=initial_condition,\n", - " state_evolution=state_evolution,\n", - " observation_model=observation_model,\n", - " )\n", - "\n", - " # sample from the dynamical model\n", - " return dsx.sample(\"f\", dynamics, obs_times=obs_times, obs_values=obs_values, ctrl_times=ctrl_times, ctrl_values=ctrl_values, predict_times=predict_times)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2.3 Making \"data\": observation and control trajectories\n", - "\n", - "Dynestyx models take trajectory data as keyword arguments: `obs_times`, `obs_values`, `predict_times`, `ctrl_times`, and `ctrl_values`.\n", - "\n", - "- **`obs_times`** and **`obs_values`**: Always provided together. They represent **observed data** — times $\\{t_k\\}_{k=0}^K$ and values $\\{y_k\\}_{k=0}^K$ at which we have measurements. When provided, the model is conditioned on these observations.\n", - "- **`predict_times`**: Times at which to predict or simulate — defines the time grid for the solver/simulator. Use this alone for pure forward simulation (no data); use with `obs_times` when predicting at additional times beyond the observed data.\n", - "- **`ctrl_times`** and **`ctrl_values`**: Control inputs; provided together; must align with the union of `obs_times` and `predict_times`.\n", - "\n", - "Our first step will be to simulate data from the generative model. To do this, we define the times at which we should simulate (`predict_times`) and a synthetic control sequence." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "import jax.random as jr\n", - "\n", - "# For simulation: predict_times defines the time grid (no observed data yet)\n", - "predict_times = jnp.arange(0.0, 100.0, 1.0) # T=100 steps\n", - "ctrl_times = predict_times # same times for controls\n", - "\n", - "# create a synthetic control sequence as i.i.d. Gaussians\n", - "# (in practice, this would be an array of control inputs that we have observed)\n", - "ctrl_values = jr.normal(jr.PRNGKey(0), (len(ctrl_times), control_dim))\n", - "\n", - "# For an autonomous system, we would simply omit ctrl_times and ctrl_values." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2.4 Interpreting the model with a Simulator\n", - "\n", - "To generate data, we interpret `dsx.sample(\"f\", dynamics, predict_times=..., ctrl_times=..., ctrl_values=...)` using a **Simulator**. The `DiscreteTimeSimulator` unrolls the model step-by-step at the given times. For pure simulation (no observed data), we pass `predict_times`, `ctrl_times`, and `ctrl_values` directly to the model." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## How does this interpretation manifest under-the-hood?\n", - "\n", - "The `DiscreteTimeSimulator` simply \"unrolls\" the dynamical system into a normal NumPyro probabilistic program. This internally does something like the following, but more efficiently using `jax.scan`:\n", - "\n", - "```python\n", - "def simulated_program(...):\n", - " # Probabilistic program before dsx.sample\n", - " # ...\n", - " # dsx.sample(...):\n", - " \n", - " T = len(times) # times = predict_times for simulation, or union of obs_times and predict_times\n", - "\n", - " x_prev = numpyro.sample(\"x_0\", initial_condition)\n", - " y_0 = numpyro.sample(\"y_0\", dynamics.observation_model(x=x_prev, t=times[0]))\n", - "\n", - " for t_idx in range(T-1):\n", - " t_now = times[t_idx]\n", - " t_next = times[t_idx+1]\n", - "\n", - " x_t = numpyro.sample(f\"x_{t_idx+1}\", \n", - " dynamics.state_evolution(x=x_prev, \n", - " t=t_now, \n", - " t_next=t_next))\n", - " y_t = numpyro.sample(f\"y_{t_idx+1}\", \n", - " dynamics.observation_model(x=x_t, t=t_next), \n", - " obs=obs_values[t_idx+1])\n", - "```" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2.5 Predictive (for generating synthetic data)\n", - "\n", - "We use NumPyro's `Predictive` to generate samples from the model. With `DiscreteTimeSimulator` in place, we pass `predict_times`, `ctrl_times`, and `ctrl_values` to produce one trajectory—states and observations—at the given times.\n", - "\n", - "Here, we generate a single synthetic dataset with $\\rho = 0.3$\n" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "from numpyro.infer import Predictive\n", - "from dynestyx import DiscreteTimeSimulator\n", - "\n", - "rho_true = 0.3\n", - "with DiscreteTimeSimulator():\n", - " predictive = Predictive(\n", - " lti_model,\n", - " params={\"rho\": jnp.array(rho_true)},\n", - " num_samples=1,\n", - " exclude_deterministic=False,\n", - " )\n", - "\n", - " pred = predictive(rng_key=jr.PRNGKey(0), predict_times=predict_times, ctrl_times=ctrl_times, ctrl_values=ctrl_values)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Shape convention note:** simulator outputs now always include a leading `n_simulations` axis, even when `n_simulations=1`. Under `Predictive`, there is also a leading `num_samples` axis. In examples below we use a helper that removes only leading singleton axes for plotting/conditioning." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now extract and plot the generated data:" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "dict_keys(['f_observations', 'f_states', 'f_times', 'f_x_0', 'f_x_Tracedwith', 'f_y_0', 'f_y_Tracedwith', 'rho'])\n", - "shapes: (1, 1, 100) (1, 1, 100, 2) (1, 1, 100, 1)\n" - ] - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Extract observations and states for plotting (and for inference below)\n", - "# obs_times and obs_values are the data we'll condition on for inference.\n", - "print(pred.keys())\n", - "print(\n", - " \"shapes:\",\n", - " pred[\"f_times\"].shape,\n", - " pred[\"f_states\"].shape,\n", - " pred[\"f_observations\"].shape,\n", - ")\n", - "\n", - "# Expected with num_samples=1 and n_sim=1:\n", - "# f_times: (1, 1, T), f_states: (1, 1, T, state_dim), f_observations: (1, 1, T, obs_dim)\n", - "obs_times = pred[\"f_times\"][0, 0, :]\n", - "states = pred[\"f_states\"][0, 0, :, :]\n", - "obs_values = pred[\"f_observations\"][0, 0, :, 0]\n", - "\n", - "# Plot\n", - "import matplotlib.pyplot as plt\n", - "\n", - "fig, ax = plt.subplots(figsize=(10, 3))\n", - "ax.plot(obs_times, states[:, 0], label=\"latent $x_0$\", color=\"C0\")\n", - "ax.plot(obs_times, states[:, 1], label=\"latent $x_1$\", color=\"C1\")\n", - "ax.scatter(obs_times, obs_values, label=\"observations $y_t$\", color=\"C3\", marker=\"x\")\n", - "ax.legend()\n", - "ax.set_xlabel(\"time\")\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2.6 Inference: conditioning on data\n", - "\n", - "To do inference given data, we pass the observed values along with the times and controls to the model:" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "# obs_times, obs_values, ctrl_times, ctrl_values are already defined above" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In dynestyx, we perform inference using the same tools as NumPyro, just with the correct interpretation of `dsx.sample(...)`. This requires two things:\n", - "\n", - "1. Data: **`obs_times`, `obs_values`, `ctrl_times`, `ctrl_values`** are passed to the model to specify what data to condition on. When `obs_values` is provided, those sites become observed (not sampled).\n", - "2. An Inference Method: for now, we use **`with DiscreteTimeSimulator():`**, which tells us HOW to condition the model on the data (same as for simulation).\n", - "\n" - ] - }, + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Part 2: Dynestyx — NumPyro with better support for dynamical systems\n", + "We introduce **dynestyx** as an extension of NumPyro for **dynamical systems**, with a clear separation between *what* the model is and *how* we simulate or score it." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.1 Separation of concerns\n", + "\n", + "**Dynestyx** extends NumPyro by giving you a standard way to work with dynamical systems. The key idea is **separation of concerns**:\n", + "\n", + "- **What** the model is: parameters $\\theta$, initial condition $p(x_0)$, state evolution (discrete or continuous time), observation model $p(y_t \\mid x_t, \\ldots)$. This is the `DynamicalModel`—you write it once as a generative model in code.\n", + "- **How** we simulate: *simulators* (e.g. `DiscreteTimeSimulator`, `SDESimulator`) unroll the dynamics step-by-step and generate state/observation trajectories. They interpret `dsx.sample(\"name\", dynamics)` as \"run the model forward in time.\"\n", + "- **How** we do inference: we can use either *simulators* (which sample latent states $x_{0:T}$ explicitly) or *filters* (which marginalize over them and compute $p(y_{1:T} \\mid \\theta)$). On top of that, we run standard NumPyro inference—**NUTS**, **SVI**, or others—to infer parameters (and optionally latent states when using a simulator).\n", + "\n", + "You write the model once; then you choose how to interpret it (simulator vs. filter) and which inference algorithm to use." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.2 A first Dynestyx model\n", + "\n", + "For pedagogical purposes, we begin with a classic discrete-time linear-Gaussian system with controls. \n", + "\n", + "$$\n", + "\\begin{aligned}\n", + "x_{t+1} &= Ax_t + Bu_t + \\epsilon_t \\\\\n", + "y_t &= Cx_t + \\eta_t\n", + "\\end{aligned}\n", + "$$\n", + "with\n", + "$$\n", + "\\begin{aligned}\n", + "x_0 &\\sim \\mathcal{N}(m_0, \\ C_0) \\\\\n", + "\\epsilon_t &\\sim \\mathcal{N}(0, \\ \\Sigma) \\\\\n", + "\\eta_t &\\sim \\mathcal{N}(0, \\ \\Gamma) \n", + "\\end{aligned}\n", + "$$\n", + "\n", + "Written differently, we have:\n", + "$$\n", + "\\begin{aligned}\n", + "\\text{Initial Condition:} \\quad x_0 &\\sim \\mathcal{N}(m_0, \\ C_0) \\\\\n", + "\\text{State-transition:} \\quad x_{t+1} &\\sim \\mathcal{N}(Ax_t + Bu_t, \\ \\Sigma) \\\\\n", + "\\text{Observation model:} \\quad y_{t} &\\sim \\mathcal{N}(Cx_t, \\ \\Gamma) \\\\\n", + "\\end{aligned}\n", + "$$\n", + "\n", + "Furthermore, say we have prior belief about a subset of parameters in the model. Concretely, we will assume\n", + "\n", + "$$\n", + "\\begin{aligned}\n", + "A &= \\begin{bmatrix} 0 & 0.3 \\\\ \\rho & -0.2 \\end{bmatrix} \\\\\n", + "B &= \\begin{bmatrix} 1 \\\\ 0 \\end{bmatrix} \\\\\n", + "C &= \\begin{bmatrix} 1 & 0 \\end{bmatrix} \\\\\n", + "\\Sigma &= 0.1^2 I \\\\\n", + "\\Gamma &= 0.1^2 I \\\\\n", + "m_0 &= 0\\\\\n", + "C_0 &= I\n", + "\\end{aligned}\n", + "$$\n", + "\n", + "and place a prior over the single unknown, $\\rho$, in the system:\n", + "\n", + "$$ \\rho \\sim \\mathcal{U}([-0.9, 0.9]).$$\n", + "\n", + "This induces a generative model.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "At the highest level, the idea is to create a NumPyro model that samples from this dynamical system. To do this, we use the `DynamicalModel` class in dynestyx, paired with the `dsx.sample` statement. " + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "import numpyro\n", + "import numpyro.distributions as dist\n", + "\n", + "import dynestyx as dsx\n", + "from dynestyx import DynamicalModel\n", + "\n", + "\n", + "def fake_lti_model(obs_times=None, obs_values=None):\n", + " # sample the unknown parameter\n", + " rho = numpyro.sample(\"rho\", dist.Uniform(-0.9, 0.9))\n", + " # create the dynamical model depending on the parameter\n", + " rho_dynamics = DynamicalModel(..., rho, ...) # not real syntax\n", + " # sample from the dynamical model\n", + " dsx.sample(\"f\", rho_dynamics, obs_times=obs_times, obs_values=obs_values)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "At this level, you can think of writing `dsx.sample(...)` as rather abstract---at this point, we don't worry about HOW to sample the system. \n", + "\n", + "Why? Dynestyx allows us to have different \"interpretations\" of the `dsx.sample` statement, depending on the task at hand. To give a few examples of how we may interpret the dynamical system later, we may:\n", + "- Use algorithmic strategies (e.g., filtering or smoothing) to efficiently condition `lti_model` on available data.\n", + "- Specify key parts of *how* we simulate, which is particularly important when we use differential equations later on.\n", + "- Explore various approximations of the dynamical system (e.g., Gaussian states, linear observations, or discretizations of a differential equation), *without* modifying the underlying model.\n", + "- Freely experiment with these differing strategies as part of the Bayesian workflow discussed in the previous tutorial.\n", + "\n", + "Let's dive in a bit more how to build a `DynamicalModel`." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `DynamicalModel` class can be instantiated with three main ingredients:\n", + "- `initial_condition`: can be any NumPyro distribution\n", + "- `state_evolution`: can be one of two classes\n", + " - `DiscreteTimeStateEvolution`:\n", + " - A callable $(x, u, t_\\text{now}, t_\\text{next}) \\mapsto \\ $ `numpyro.distributions` object (which can include things like categorical distributions)\n", + " - `ContinuousTimeStateEvolution`: has fields\n", + " - `drift`: A callable $(x, u, t) \\mapsto \\ \\mathbb{R}^{d_x}$\n", + " - `diffusion`: A `Diffusion` object such as `FullDiffusion`, `DiagonalDiffusion`, or `ScalarDiffusion`\n", + "- `observation_model`: A callable $(x, u, t) \\mapsto \\ $ `numpyro.distributions` object\n", + "\n", + "It also requires specification of the key dimensions in the problem:\n", + "- `state_dim`: $\\text{dim}(x_t)$\n", + "- `observation_dim`: $\\text{dim}(y_t)$\n", + "- `control_dim`: $\\text{dim}(u_t)$\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "import jax.numpy as jnp\n", + "\n", + "from dynestyx.models import DynamicalModel # noqa: F811\n", + "\n", + "# for convenience, we can define \"fixed\" things in the model outside of it.\n", + "# this is not required, but it helps keep the model clean.\n", + "state_dim = 2\n", + "observation_dim = 1\n", + "control_dim = 1\n", + "\n", + "# Create the known matrices B, C\n", + "B = jnp.eye(state_dim, control_dim)\n", + "C = jnp.eye(observation_dim, state_dim)\n", + "\n", + "# create the initial condition as a distribution\n", + "initial_condition = dist.MultivariateNormal(jnp.zeros(state_dim), jnp.eye(state_dim))\n", + "\n", + "# create the observation model as a callable mapping to a distribution\n", + "observation_model = lambda x, u, t: dist.MultivariateNormal(\n", + " C @ x, 0.1**2 * jnp.eye(observation_dim)\n", + ")\n", + "\n", + "\n", + "def lti_model(rho=None, obs_times=None, obs_values=None, ctrl_times=None, ctrl_values=None, predict_times=None):\n", + " # sample the unknown parameter\n", + " rho = numpyro.sample(\"rho\", dist.Uniform(-0.5, 0.5), obs=rho)\n", + " A = jnp.array([[0, 0.3], [rho, -0.2]])\n", + "\n", + " # create the state evolution as a callable mapping to a distribution\n", + " # Crucially, this depends on A, which depends on rho, which is unknown.\n", + " # Thus, the state evolution MUST be defined within `lti_model`, not outside.\n", + " state_evolution = lambda x, u, t_now, t_next: dist.MultivariateNormal(\n", + " A @ x + B @ u, 0.1**2 * jnp.eye(state_dim)\n", + " )\n", + "\n", + " # create the dynamical model\n", + " dynamics = DynamicalModel(\n", + " control_dim=control_dim,\n", + " initial_condition=initial_condition,\n", + " state_evolution=state_evolution,\n", + " observation_model=observation_model,\n", + " )\n", + "\n", + " # sample from the dynamical model\n", + " return dsx.sample(\"f\", dynamics, obs_times=obs_times, obs_values=obs_values, ctrl_times=ctrl_times, ctrl_values=ctrl_values, predict_times=predict_times)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.3 Making \"data\": observation and control trajectories\n", + "\n", + "Dynestyx models take trajectory data as keyword arguments: `obs_times`, `obs_values`, `predict_times`, `ctrl_times`, and `ctrl_values`.\n", + "\n", + "- **`obs_times`** and **`obs_values`**: Always provided together. They represent **observed data** — times $\\{t_k\\}_{k=0}^K$ and values $\\{y_k\\}_{k=0}^K$ at which we have measurements. When provided, the model is conditioned on these observations.\n", + "- **`predict_times`**: Times at which to predict or simulate — defines the time grid for the solver/simulator. Use this alone for pure forward simulation (no data); use with `obs_times` when predicting at additional times beyond the observed data.\n", + "- **`ctrl_times`** and **`ctrl_values`**: Control inputs; provided together; must align with the union of `obs_times` and `predict_times`.\n", + "\n", + "Our first step will be to simulate data from the generative model. To do this, we define the times at which we should simulate (`predict_times`) and a synthetic control sequence." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "import jax.random as jr\n", + "\n", + "# For simulation: predict_times defines the time grid (no observed data yet)\n", + "predict_times = jnp.arange(0.0, 100.0, 1.0) # T=100 steps\n", + "ctrl_times = predict_times # same times for controls\n", + "\n", + "# create a synthetic control sequence as i.i.d. Gaussians\n", + "# (in practice, this would be an array of control inputs that we have observed)\n", + "ctrl_values = jr.normal(jr.PRNGKey(0), (len(ctrl_times), control_dim))\n", + "\n", + "# For an autonomous system, we would simply omit ctrl_times and ctrl_values." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.4 Interpreting the model with a Simulator\n", + "\n", + "To generate data, we interpret `dsx.sample(\"f\", dynamics, predict_times=..., ctrl_times=..., ctrl_values=...)` using a **Simulator**. The `DiscreteTimeSimulator` unrolls the model step-by-step at the given times. For pure simulation (no observed data), we pass `predict_times`, `ctrl_times`, and `ctrl_values` directly to the model." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## How does this interpretation manifest under-the-hood?\n", + "\n", + "The `DiscreteTimeSimulator` simply \"unrolls\" the dynamical system into a normal NumPyro probabilistic program. This internally does something like the following, but more efficiently using `jax.scan`:\n", + "\n", + "```python\n", + "def simulated_program(...):\n", + " # Probabilistic program before dsx.sample\n", + " # ...\n", + " # dsx.sample(...):\n", + " \n", + " T = len(times) # times = predict_times for simulation, or union of obs_times and predict_times\n", + "\n", + " x_prev = numpyro.sample(\"x_0\", initial_condition)\n", + " y_0 = numpyro.sample(\"y_0\", dynamics.observation_model(x=x_prev, t=times[0]))\n", + "\n", + " for t_idx in range(T-1):\n", + " t_now = times[t_idx]\n", + " t_next = times[t_idx+1]\n", + "\n", + " x_t = numpyro.sample(f\"x_{t_idx+1}\", \n", + " dynamics.state_evolution(x=x_prev, \n", + " t=t_now, \n", + " t_next=t_next))\n", + " y_t = numpyro.sample(f\"y_{t_idx+1}\", \n", + " dynamics.observation_model(x=x_t, t=t_next), \n", + " obs=obs_values[t_idx+1])\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.5 Predictive (for generating synthetic data)\n", + "\n", + "We use NumPyro's `Predictive` to generate samples from the model. With `DiscreteTimeSimulator` in place, we pass `predict_times`, `ctrl_times`, and `ctrl_values` to produce one trajectory—states and observations—at the given times.\n", + "\n", + "Here, we generate a single synthetic dataset with $\\rho = 0.3$\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "from numpyro.infer import Predictive\n", + "from dynestyx import DiscreteTimeSimulator\n", + "\n", + "rho_true = 0.3\n", + "with DiscreteTimeSimulator():\n", + " predictive = Predictive(\n", + " lti_model,\n", + " params={\"rho\": jnp.array(rho_true)},\n", + " num_samples=1,\n", + " exclude_deterministic=False,\n", + " )\n", + "\n", + " pred = predictive(rng_key=jr.PRNGKey(0), predict_times=predict_times, ctrl_times=ctrl_times, ctrl_values=ctrl_values)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Shape convention note:** simulator outputs now always include a leading `n_simulations` axis, even when `n_simulations=1`. Under `Predictive`, there is also a leading `num_samples` axis. In examples below we use a helper that removes only leading singleton axes for plotting/conditioning." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now extract and plot the generated data:" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The result is a standard NumPyro model: we can run **NUTS**, **SVI**, or any other NumPyro inference on it." - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "dict_keys(['f_observations', 'f_states', 'f_times', 'f_x_0', 'f_x_Tracedwith', 'f_y_0', 'f_y_Tracedwith', 'rho'])\n", + "shapes: (1, 1, 100) (1, 1, 100, 2) (1, 1, 100, 1)\n" + ] }, { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "sample: 100%|██████████| 202/202 [00:00<00:00, 246.21it/s, 31 steps of size 1.49e-01. acc. prob=0.93]" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Posterior rho mean: 0.3294023275375366\n", - "True rho: 0.3\n", - "dict_keys(['f_observations', 'f_states', 'f_times', 'f_x_0', 'f_x_Tracedwith', 'rho'])\n", - "f_observations: (101, 1, 100)\n", - "f_states: (101, 1, 100, 2)\n", - "f_times: (101, 1, 100)\n", - "f_x_0: (101, 1, 2)\n", - "f_x_Tracedwith: (101, 99, 1, 2)\n", - "rho: (101,)\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "from numpyro.infer import MCMC, NUTS\n", - "\n", - "with DiscreteTimeSimulator():\n", - " nuts_kernel = NUTS(lti_model)\n", - " mcmc = MCMC(nuts_kernel, num_warmup=101, num_samples=101)\n", - " mcmc.run(jr.PRNGKey(1), obs_times=obs_times, obs_values=obs_values, ctrl_times=ctrl_times, ctrl_values=ctrl_values)\n", - "\n", - "posterior_sv = mcmc.get_samples()\n", - "print(\"Posterior rho mean:\", float(jnp.mean(posterior_sv[\"rho\"])))\n", - "print(\"True rho:\", rho_true)\n", - "\n", - "# What did we infer? The Simulator unrolled the model, so we explicitly sampled latent states:\n", - "print(posterior_sv.keys())\n", - "\n", - "# Print the shapes of each of the keys in the posterior samples\n", - "for key, value in posterior_sv.items():\n", - " print(f\"{key}: {value.shape}\")" + "data": { + "image/png": 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+ "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Extract observations and states for plotting (and for inference below)\n", + "# obs_times and obs_values are the data we'll condition on for inference.\n", + "print(pred.keys())\n", + "print(\n", + " \"shapes:\",\n", + " pred[\"f_times\"].shape,\n", + " pred[\"f_states\"].shape,\n", + " pred[\"f_observations\"].shape,\n", + ")\n", + "\n", + "# Expected with num_samples=1 and n_sim=1:\n", + "# f_times: (1, 1, T), f_states: (1, 1, T, state_dim), f_observations: (1, 1, T, obs_dim)\n", + "obs_times = pred[\"f_times\"][0, 0, :]\n", + "states = pred[\"f_states\"][0, 0, :, :]\n", + "obs_values = pred[\"f_observations\"][0, 0, :, 0]\n", + "\n", + "# Plot\n", + "import matplotlib.pyplot as plt\n", + "\n", + "fig, ax = plt.subplots(figsize=(10, 3))\n", + "ax.plot(obs_times, states[:, 0], label=\"latent $x_0$\", color=\"C0\")\n", + "ax.plot(obs_times, states[:, 1], label=\"latent $x_1$\", color=\"C1\")\n", + "ax.scatter(obs_times, obs_values, label=\"observations $y_t$\", color=\"C3\", marker=\"x\")\n", + "ax.legend()\n", + "ax.set_xlabel(\"time\")\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.6 Inference: conditioning on data\n", + "\n", + "To do inference given data, we pass the observed values along with the times and controls to the model:" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "# obs_times, obs_values, ctrl_times, ctrl_values are already defined above" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In dynestyx, we perform inference using the same tools as NumPyro, just with the correct interpretation of `dsx.sample(...)`. This requires two things:\n", + "\n", + "1. Data: **`obs_times`, `obs_values`, `ctrl_times`, `ctrl_values`** are passed to the model to specify what data to condition on. When `obs_values` is provided, those sites become observed (not sampled).\n", + "2. An Inference Method: for now, we use **`with DiscreteTimeSimulator():`**, which tells us HOW to condition the model on the data (same as for simulation).\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The result is a standard NumPyro model: we can run **NUTS**, **SVI**, or any other NumPyro inference on it." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# use ArviZ to plot the posterior distribution for rho\n", - "import arviz as az\n", - "\n", - "az.plot_posterior(posterior_sv[\"rho\"], hdi_prob=0.95, ref_val=rho_true)\n", - "plt.show()" - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "sample: 100%|██████████| 202/202 [00:00<00:00, 246.21it/s, 31 steps of size 1.49e-01. acc. prob=0.93]" + ] }, { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### What the Simulator did: unrolling\n", - "\n", - "Using the **Simulator** effectively *unrolled* the model: instead of a single `dsx.sample(\"f\", dynamics)` call, the dynamics were expanded into explicit sample sites `states` ($x_0, x_1, \\ldots, x_T$) and `observations` ($y_0, y_1, \\ldots, y_T$). Pedagogically, the Simulator does something like:\n", - "\n", - "```python\n", - "# Conceptual unrolling (what the Simulator does internally):\n", - "x_0 = numpyro.sample(\"x_0\", initial_condition)\n", - "y_0 = numpyro.sample(\"y_0\", observation_model(x_0, u_0, t_0))\n", - "x_1 = numpyro.sample(\"x_1\", state_evolution(x_0, u_0, t_0, t_1))\n", - "y_1 = numpyro.sample(\"y_1\", observation_model(x_1, u_1, t_1))\n", - "# ... and so on for each time step\n", - "```\n", - "\n", - "So MCMC was inferring **both** the parameter $\\rho$ and the full latent state trajectory $x_{0:T}$ explicitly. The printed sample keys include `rho` and `states`, …." - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Posterior rho mean: 0.3294023275375366\n", + "True rho: 0.3\n", + "dict_keys(['f_observations', 'f_states', 'f_times', 'f_x_0', 'f_x_Tracedwith', 'rho'])\n", + "f_observations: (101, 1, 100)\n", + "f_states: (101, 1, 100, 2)\n", + "f_times: (101, 1, 100)\n", + "f_x_0: (101, 1, 2)\n", + "f_x_Tracedwith: (101, 99, 1, 2)\n", + "rho: (101,)\n" + ] }, { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For simple Gaussian problems like this one, unrolling can be an excellent strategy that NUTS can handle quite well! We obtain a `smoothing` distribution of the resulting data, without running a typical smoothing algorithm -- we will do this in later tutorials, and see its advantages and drawbacks depending on the type of data at hand. For now, let us compare the state recovery of the unrolled MCMC inference compared to the true states generated in the original model simulation." - ] - }, + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "from numpyro.infer import MCMC, NUTS\n", + "\n", + "with DiscreteTimeSimulator():\n", + " nuts_kernel = NUTS(lti_model)\n", + " mcmc = MCMC(nuts_kernel, num_warmup=101, num_samples=101)\n", + " mcmc.run(jr.PRNGKey(1), obs_times=obs_times, obs_values=obs_values, ctrl_times=ctrl_times, ctrl_values=ctrl_values)\n", + "\n", + "posterior_sv = mcmc.get_samples()\n", + "print(\"Posterior rho mean:\", float(jnp.mean(posterior_sv[\"rho\"])))\n", + "print(\"True rho:\", rho_true)\n", + "\n", + "# What did we infer? The Simulator unrolled the model, so we explicitly sampled latent states:\n", + "print(posterior_sv.keys())\n", + "\n", + "# Print the shapes of each of the keys in the posterior samples\n", + "for key, value in posterior_sv.items():\n", + " print(f\"{key}: {value.shape}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plot inferred states vs true states: posterior distribution over the latent trajectory,\n", - "# with a subplot for each latent variable/state dimension\n", - "inferred_states = posterior_sv[\"f_states\"] # (n_samples, n_sims, T+1, state_dim)\n", - "n_samples, _, T1, state_dim = inferred_states.shape\n", - "\n", - "true_states = jnp.asarray(states)\n", - "\n", - "\n", - "posterior_mean = inferred_states.mean(axis=(0,1)) # (T+1, state_dim)\n", - "q05 = jnp.percentile(inferred_states, 5, axis=(0,1)) # (T+1, state_dim)\n", - "q95 = jnp.percentile(inferred_states, 95, axis=(0,1)) # (T+1, state_dim)\n", - "\n", - "fig, axes = plt.subplots(state_dim, 1, figsize=(10, 4 * state_dim), sharex=True)\n", - "if state_dim == 1:\n", - " axes = [axes] # make iterable\n", - "\n", - "for i, ax in enumerate(axes):\n", - " ax.fill_between(\n", - " obs_times,\n", - " q05[:, i],\n", - " q95[:, i],\n", - " alpha=0.3,\n", - " label=\"90% credible interval (inferred)\",\n", - " )\n", - " ax.plot(\n", - " obs_times,\n", - " posterior_mean[:, i],\n", - " label=\"Posterior state mean (inferred)\",\n", - " color=\"C0\",\n", - " )\n", - " ax.plot(\n", - " obs_times, true_states[:, i], label=\"True states\", color=\"black\", linestyle=\"--\"\n", - " )\n", - " # Plot observations only on first subplot (if obs_values is appropriate size)\n", - " if i == 0 and \"obs_values\" in locals():\n", - " if hasattr(obs_values, \"shape\") and (\n", - " obs_values.ndim == 1 or obs_values.shape[1] == 1\n", - " ):\n", - " ax.scatter(\n", - " obs_times, obs_values, label=\"Observations\", color=\"C1\", marker=\"x\"\n", - " )\n", - " elif obs_values.ndim == 2 and obs_values.shape[1] > i:\n", - " ax.scatter(\n", - " obs_times,\n", - " obs_values[:, i],\n", - " label=\"Observations\",\n", - " color=\"C1\",\n", - " marker=\"x\",\n", - " )\n", - " ax.set_ylabel(f\"latent $x^{{({i})}}_t$ (log-variance)\")\n", - " ax.legend()\n", - "axes[-1].set_xlabel(\"time\")\n", - "plt.tight_layout()\n", - "plt.show()" + "data": { + "image/png": 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", + "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# use ArviZ to plot the posterior distribution for rho\n", + "import arviz as az\n", + "\n", + "az.plot_posterior(posterior_sv[\"rho\"], hdi_prob=0.95, ref_val=rho_true)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### What the Simulator did: unrolling\n", + "\n", + "Using the **Simulator** effectively *unrolled* the model: instead of a single `dsx.sample(\"f\", dynamics)` call, the dynamics were expanded into explicit sample sites `states` ($x_0, x_1, \\ldots, x_T$) and `observations` ($y_0, y_1, \\ldots, y_T$). Pedagogically, the Simulator does something like:\n", + "\n", + "```python\n", + "# Conceptual unrolling (what the Simulator does internally):\n", + "x_0 = numpyro.sample(\"x_0\", initial_condition)\n", + "y_0 = numpyro.sample(\"y_0\", observation_model(x_0, u_0, t_0))\n", + "x_1 = numpyro.sample(\"x_1\", state_evolution(x_0, u_0, t_0, t_1))\n", + "y_1 = numpyro.sample(\"y_1\", observation_model(x_1, u_1, t_1))\n", + "# ... and so on for each time step\n", + "```\n", + "\n", + "So MCMC was inferring **both** the parameter $\\rho$ and the full latent state trajectory $x_{0:T}$ explicitly. The printed sample keys include `rho` and `states`, …." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For simple Gaussian problems like this one, unrolling can be an excellent strategy that NUTS can handle quite well! We obtain a `smoothing` distribution of the resulting data, without running a typical smoothing algorithm -- we will do this in later tutorials, and see its advantages and drawbacks depending on the type of data at hand. For now, let us compare the state recovery of the unrolled MCMC inference compared to the true states generated in the original model simulation." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Lead-in to Part 3\n", - "\n", - "Sometimes it is too costly or difficult to infer these latent states explicitly via MCMC/SVI—especially for long time series or complex / noisy dynamics. That is where **filtering** comes to the rescue: it allows MCMC/SVI to focus only on **parameters**, while the filter **marginalizes** (averages) over the possible latent states and computes $p(y_{1:T} \\mid \\theta)$. In Part 3 we will see how to do that.\n", - "\n", - "**Next:** [Part 3 — Filtering and the marginal log-likelihood](../03_filtering_mll/)" + "data": { + "image/png": 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+ "text/plain": [ + "
" ] + }, + "metadata": {}, + "output_type": "display_data" } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv (3.12.11)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" - } + ], + "source": [ + "# Plot inferred states vs true states: posterior distribution over the latent trajectory,\n", + "# with a subplot for each latent variable/state dimension\n", + "inferred_states = posterior_sv[\"f_states\"] # (n_samples, n_sims, T+1, state_dim)\n", + "n_samples, _, T1, state_dim = inferred_states.shape\n", + "\n", + "true_states = jnp.asarray(states)\n", + "\n", + "\n", + "posterior_mean = inferred_states.mean(axis=(0,1)) # (T+1, state_dim)\n", + "q05 = jnp.percentile(inferred_states, 5, axis=(0,1)) # (T+1, state_dim)\n", + "q95 = jnp.percentile(inferred_states, 95, axis=(0,1)) # (T+1, state_dim)\n", + "\n", + "fig, axes = plt.subplots(state_dim, 1, figsize=(10, 4 * state_dim), sharex=True)\n", + "if state_dim == 1:\n", + " axes = [axes] # make iterable\n", + "\n", + "for i, ax in enumerate(axes):\n", + " ax.fill_between(\n", + " obs_times,\n", + " q05[:, i],\n", + " q95[:, i],\n", + " alpha=0.3,\n", + " label=\"90% credible interval (inferred)\",\n", + " )\n", + " ax.plot(\n", + " obs_times,\n", + " posterior_mean[:, i],\n", + " label=\"Posterior state mean (inferred)\",\n", + " color=\"C0\",\n", + " )\n", + " ax.plot(\n", + " obs_times, true_states[:, i], label=\"True states\", color=\"black\", linestyle=\"--\"\n", + " )\n", + " # Plot observations only on first subplot (if obs_values is appropriate size)\n", + " if i == 0 and \"obs_values\" in locals():\n", + " if hasattr(obs_values, \"shape\") and (\n", + " obs_values.ndim == 1 or obs_values.shape[1] == 1\n", + " ):\n", + " ax.scatter(\n", + " obs_times, obs_values, label=\"Observations\", color=\"C1\", marker=\"x\"\n", + " )\n", + " elif obs_values.ndim == 2 and obs_values.shape[1] > i:\n", + " ax.scatter(\n", + " obs_times,\n", + " obs_values[:, i],\n", + " label=\"Observations\",\n", + " color=\"C1\",\n", + " marker=\"x\",\n", + " )\n", + " ax.set_ylabel(f\"latent $x^{{({i})}}_t$ (log-variance)\")\n", + " ax.legend()\n", + "axes[-1].set_xlabel(\"time\")\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Lead-in to Part 3\n", + "\n", + "Sometimes it is too costly or difficult to infer these latent states explicitly via MCMC/SVI—especially for long time series or complex / noisy dynamics. That is where **filtering** comes to the rescue: it allows MCMC/SVI to focus only on **parameters**, while the filter **marginalizes** (averages) over the possible latent states and computes $p(y_{1:T} \\mid \\theta)$. In Part 3 we will see how to do that.\n", + "\n", + "**Next:** [Part 3 — Filtering and the marginal log-likelihood](../03_filtering_mll/)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv (3.12.11)", + "language": "python", + "name": "python3" }, - "nbformat": 4, - "nbformat_minor": 4 + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/docs/tutorials/gentle_intro/06_continuous_time.ipynb b/docs/tutorials/gentle_intro/06_continuous_time.ipynb index 944f97e2..05ad9451 100644 --- a/docs/tutorials/gentle_intro/06_continuous_time.ipynb +++ b/docs/tutorials/gentle_intro/06_continuous_time.ipynb @@ -1,515 +1,515 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Part 6a: Stochastic continuous-time dynamical systems (SDEs)\n", - "\n", - "We introduce **continuous-time** state evolution via **ContinuousTimeStateEvolution** and the **SDESimulator**, and run inference with **filtering** (e.g. EnKF) on a partially observed Lorenz 63 example." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6.1 ContinuousTimeStateEvolution: drift, diffusion, and SDEs\n", - "\n", - "In continuous time, the state evolves according to an **Itô SDE**:\n", - "\n", - "$$dX_t = f(X_t, u_t, t)\\,dt + L(X_t, u_t, t)\\,dW_t$$\n", - "\n", - "where $W_t$ is a vector Brownian motion. We specify:\n", - "\n", - "- **`drift`**: $f(x, u, t)$ — the deterministic part (vector of same dimension as state).\n", - "- **`diffusion_coefficient`**: $L(x, u, t)$ — matrix such that the diffusion term is $L\\,dW_t$. Shape is `(state_dim, brownian_dim)`.\n", - "\n", - "All three are callables with signature `(x, u, t)`: state `x`, control `u` (or `None`), and time `t`." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6.2 Generating data: SDESimulator\n", - "\n", - "To **simulate** a continuous-time model we use **`SDESimulator`** (instead of `DiscreteTimeSimulator`). It integrates the SDE and observes at the given times. We pass `obs_times` directly to the model." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6.3 Lorenz 63 with partial observations\n", - "\n", - "Lorenz 63 has state $x = (x_1, x_2, x_3)$ and drift\n", - "\n", - "$$f(x) = \\big(\\sigma(x_2 - x_1),\\, x_1(\\rho - x_3) - x_2,\\, x_1 x_2 - \\beta x_3\\big).$$\n", - "\n", - "We take $\\sigma=10$, $\\beta=8/3$, and sample $\\rho$ from a prior. We observe **only the first component** $x_1$ with Gaussian noise: $y_t = H x_t + \\varepsilon_t$ with $H = [1, 0, 0]$ and $R = 1^2$. This is **partial observation** and is specified via **`LinearGaussianObservation(H, R)`**. The matrix $H$ has shape `(observation_dim, state_dim)`; here we use `H = [[1, 0, 0]]` so we get one scalar observation per time. Using `LinearGaussianObservation` gives access to **structured inference** methods (EnKF, EKF, UKF) in CD-Dynamax; for more general observation models or non-Gaussian initial conditions, particle filters (e.g. DPF) are available." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import jax.numpy as jnp\n", - "import jax.random as jr\n", - "import numpyro\n", - "import numpyro.distributions as dist\n", - "from numpyro.infer import Predictive\n", - "\n", - "import dynestyx as dsx\n", - "from dynestyx import flatten_draws\n", - "from dynestyx import (\n", - " ContinuousTimeStateEvolution,\n", - " DynamicalModel,\n", - " LinearGaussianObservation,\n", - " SDESimulator,\n", - ")\n", - "\n", - "state_dim = 3\n", - "observation_dim = 1\n", - "\n", - "\n", - "def l63_model(obs_times=None, obs_values=None, predict_times=None):\n", - " rho = numpyro.sample(\"rho\", dist.Uniform(10.0, 40.0))\n", - " dynamics = DynamicalModel(\n", - " initial_condition=dist.MultivariateNormal(\n", - " loc=jnp.zeros(state_dim), covariance_matrix=20.0**2 * jnp.eye(state_dim)\n", - " ),\n", - " state_evolution=ContinuousTimeStateEvolution(\n", - " drift=lambda x, u, t: jnp.array(\n", - " [\n", - " 10.0 * (x[1] - x[0]),\n", - " x[0] * (rho - x[2]) - x[1],\n", - " x[0] * x[1] - (8.0 / 3.0) * x[2],\n", - " ]\n", - " ),\n", - " diffusion_coefficient=lambda x, u, t: jnp.eye(3),\n", - " ),\n", - " observation_model=LinearGaussianObservation(\n", - " H=jnp.eye(observation_dim, state_dim), # observe only x[0]\n", - " R=jnp.eye(observation_dim),\n", - " ),\n", - " )\n", - " return dsx.sample(\"f\", dynamics, obs_times=obs_times, obs_values=obs_values, predict_times=predict_times)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "synthetic shapes: (1, 1, 2800) (1, 1, 2800, 3) (1, 1, 2800, 1)\n" - ] - } - ], - "source": [ - "key = jr.PRNGKey(0)\n", - "rho_true = 28.0\n", - "T_forecast = 8.0\n", - "# Generate longer trajectory: training window + held-out future for rollout evaluation\n", - "obs_times_full = jnp.arange(0.0, 20.0 + T_forecast, 0.01) # 0..28\n", - "\n", - "predictive = Predictive(\n", - " l63_model,\n", - " params={\"rho\": jnp.array(rho_true)},\n", - " num_samples=1,\n", - " exclude_deterministic=False,\n", - ")\n", - "with SDESimulator(source=\"em_scan\"):\n", - " synthetic = predictive(key, predict_times=obs_times_full)\n", - "\n", - "# Simulators return (n_sim, T, dim); Predictive adds (num_samples,).\n", - "# With num_samples=1 and n_sim=1 we index explicitly.\n", - "print(\n", - " \"synthetic shapes:\",\n", - " synthetic[\"f_times\"].shape,\n", - " synthetic[\"f_states\"].shape,\n", - " synthetic[\"f_observations\"].shape,\n", - ")\n", - "times = synthetic[\"f_times\"][0, 0, :]\n", - "states = synthetic[\"f_states\"][0, 0, :, :] # (T, 3)\n", - "observations = synthetic[\"f_observations\"][0, 0, :, :] # (T, 1)\n", - "\n", - "# Training portion (0..20) for MCMC; future (20..28) withheld for rollout eval\n", - "mask_train_full = times <= 20.0\n", - "times_train_full = times[mask_train_full]\n", - "observations_train = observations[mask_train_full]\n", - "\n", - "times_test_full = times[~mask_train_full]\n", - "observations_test_full = observations[~mask_train_full]" - ] - }, + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Part 6a: Stochastic continuous-time dynamical systems (SDEs)\n", + "\n", + "We introduce **continuous-time** state evolution via **ContinuousTimeStateEvolution** and the **SDESimulator**, and run inference with **filtering** (e.g. EnKF) on a partially observed Lorenz 63 example." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6.1 ContinuousTimeStateEvolution: drift, diffusion, and SDEs\n", + "\n", + "In continuous time, the state evolves according to an **Itô SDE**:\n", + "\n", + "$$dX_t = f(X_t, u_t, t)\\,dt + L(X_t, u_t, t)\\,dW_t$$\n", + "\n", + "where $W_t$ is a vector Brownian motion. We specify:\n", + "\n", + "- **`drift`**: $f(x, u, t)$ — the deterministic part (vector of same dimension as state).\n", + "- **`diffusion`**: a `Diffusion` object such as `FullDiffusion`, `DiagonalDiffusion`, or `ScalarDiffusion`, which defines the coefficient $L(x, u, t)$ in $L\\,dW_t$.\n", + "\n", + "The drift is a callable with signature `(x, u, t)`: state `x`, control `u` (or `None`), and time `t`. The diffusion object may itself be built from a constant coefficient or a callable coefficient with the same signature." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6.2 Generating data: SDESimulator\n", + "\n", + "To **simulate** a continuous-time model we use **`SDESimulator`** (instead of `DiscreteTimeSimulator`). It integrates the SDE and observes at the given times. We pass `obs_times` directly to the model." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6.3 Lorenz 63 with partial observations\n", + "\n", + "Lorenz 63 has state $x = (x_1, x_2, x_3)$ and drift\n", + "\n", + "$$f(x) = \\big(\\sigma(x_2 - x_1),\\, x_1(\\rho - x_3) - x_2,\\, x_1 x_2 - \\beta x_3\\big).$$\n", + "\n", + "We take $\\sigma=10$, $\\beta=8/3$, and sample $\\rho$ from a prior. We observe **only the first component** $x_1$ with Gaussian noise: $y_t = H x_t + \\varepsilon_t$ with $H = [1, 0, 0]$ and $R = 1^2$. This is **partial observation** and is specified via **`LinearGaussianObservation(H, R)`**. The matrix $H$ has shape `(observation_dim, state_dim)`; here we use `H = [[1, 0, 0]]` so we get one scalar observation per time. Using `LinearGaussianObservation` gives access to **structured inference** methods (EnKF, EKF, UKF) in CD-Dynamax; for more general observation models or non-Gaussian initial conditions, particle filters (e.g. DPF) are available." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import jax.numpy as jnp\n", + "import jax.random as jr\n", + "import numpyro\n", + "import numpyro.distributions as dist\n", + "from numpyro.infer import Predictive\n", + "\n", + "import dynestyx as dsx\n", + "from dynestyx import flatten_draws\n", + "from dynestyx import (\n", + " ContinuousTimeStateEvolution,\n", + " DynamicalModel,\n", + " LinearGaussianObservation,\n", + " SDESimulator,\n", + ")\n", + "\n", + "state_dim = 3\n", + "observation_dim = 1\n", + "\n", + "\n", + "def l63_model(obs_times=None, obs_values=None, predict_times=None):\n", + " rho = numpyro.sample(\"rho\", dist.Uniform(10.0, 40.0))\n", + " dynamics = DynamicalModel(\n", + " initial_condition=dist.MultivariateNormal(\n", + " loc=jnp.zeros(state_dim), covariance_matrix=20.0**2 * jnp.eye(state_dim)\n", + " ),\n", + " state_evolution=ContinuousTimeStateEvolution(\n", + " drift=lambda x, u, t: jnp.array(\n", + " [\n", + " 10.0 * (x[1] - x[0]),\n", + " x[0] * (rho - x[2]) - x[1],\n", + " x[0] * x[1] - (8.0 / 3.0) * x[2],\n", + " ]\n", + " ),\n", + " diffusion=dsx.FullDiffusion(jnp.eye(3)),\n", + " ),\n", + " observation_model=LinearGaussianObservation(\n", + " H=jnp.eye(observation_dim, state_dim), # observe only x[0]\n", + " R=jnp.eye(observation_dim),\n", + " ),\n", + " )\n", + " return dsx.sample(\"f\", dynamics, obs_times=obs_times, obs_values=obs_values, predict_times=predict_times)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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ZNYmYUpNJ7JFdC2upfNzo6TYmMfu1yqdZ6/bY/vdm/6vxeFaDbmN7EIjRSvewYcOEa67xxgE3w9XuBx54QLiVHzp0iH788Ufq2LEjJQoHK6p9+wz1k/mqHfsjul0AgOjHWHGRyTuz54xBWCRRFxTGnm5pHOOUyYok0kwKKivdU1buitvsPvdiPqu41rKzbn6WuYzf6Sga8f8ofeP+2hek2iKRWz+OaF1Qy9kYPd3Rh5UxILNLn6H8yZxNlAjI6To8DtBfVJdoShaOYX5ZusP2tcpJ4G08V0h5P1867UwisfMaKwk78AV7KQ6zZXJhvEvPjAc73w8AkHhMWuYbYJohE3oHK6PHrVsN0OQILxU5s5sJdtTZf79b5vO4WZ6vakqtStz6wTyKR16fstZzf1S3Qnr8nN61qhyPnN0rZJM99f85pVezWr+/aJDWE5tga3JTif/fRnSo9XvZU4lKd/QgP4tUk6BbnrdmGAyq4j3orh8osEyw7zf7jchpIKrM3go7juOBXlM/TbtOcvxuR2lh55yrOvIDa7CX4jDoDqWyAwBITOws1vOytEry3rLomMX5y9LtPgY9tWSLwpjGW4UNVRZ/au9mCbfQ2LDbOx6OE7pmUm9+vrU+W9bpPp6zfq/nfmFOhmVfYlUiNn2Kqqm28m2am0G5+vfQtKcbRmpRV+mW/jqJzB69fcSs9USN6RLNKPHL+V5zxGJFMRRoP/pj6ZZSv79X58Sv21UW8P1qbGRCkpVjPITx4nFP/K8YEgi52MlAPwUAIASnXVMJILuD67LiPbo0MpqM3y4Y2NL0NZyElMZfoYwy4YSDsVfN7pzTWEZN4vpL6GbqC7lDDirdqmTy6A6N/LYRbNUdzhPVbMmq51NWU2GkFn2JTH99uokAV/UnL99pqUZSK6mJptT4bK436LbDrLWBe7Ef+mqJbbn5Pz5dGPD97ORBqpUXJaoayQ6JfSaIV3l5Gj5WAEBwqAXMgW0KTF9ToI/k2m0j217X+FvYNs3VxrBs2OOt2gbLsE5Naj3XwWBmFY+o/aj+Erre1oPgg+6fl2733B/SvpHfwHzJln0Jkeww8vOSbeLnvkPmrR0FekJsNTxcoi9Rklz7e3PVMW0dt73EGvM37q1lLmdVSU20oDtY3py2LqjX92zhO/rTiJ3ztZ3DU6rgpKlzvB/TTkF0FkfjRCp1d0i5+Ll2uDZXt3NRYhrPAADso2a/rcxapDSwrLwq6kzUmuf5zjdVkefAKYo7ezCZe+Yiw5xdpn2T+D63snx/yqpdnsdmvamSDL0KfsBBpXtLycFajvC1X+OtcC8JIJ+MR37RPRd2W6hMehdrs45hnBodbNhdRgs3lVrOtT+uS6HnfjQZU4aDFKUNRzUENGvTSRQ3dw5K6+I89uBpXk8TpxjN7dhM0wiP5/znaO3/OlxV42OMCbwg6I4TDiknKmmkVlA/PaQxAwAASpgFwMu/e+dRW50y5Bgxp2ZZ4cRsISA5sm1D8XP2evtjUoyLv0SUiKryfabSz4JY9s5PW+0N0u0iE8b+xs2ojumJVg3bvi+wpL6pbvI3b0NJwsx+jmb++vZsz/3OTbNNFSTS/M44Ii/eKKvwBmCtGtbuW+7fuiDhgu6Xf19Dt384P+h/17CB/bGYg9o1tBy32K6xdr3s0CSwWkutWg/p0MgykO/ZIs/TPrDbMOIQaCTeKiLOpeVc+ZGGKh43UwTdAAA/sGRXrbZYGafIhF60zOlWE4qNs2ubqBkXevw3sirIDnb/xnMHFFOi4G9BzM7mzIKNJUEH3nbM0U7v4zWx40pKIjH2tZkBX6OObVu+FWNCI4mqkmF5r9k4JVYW5egVcB7LlwjO5Uznopxav+d165VD2yZMQm3z3oO1erkfPrOn5esfUiZwqPvS6thL0df+VwxpY/m6s48oNp3hbYaqTjj3iJamRo611HBRmJiPBhB0xwly/ITqSihP9P6qEwAA8KPeLyrp2zLfdKdIIy1/c5TrCg6eZZa+fZMGtWaRqmTpI1KYAzal8TKRGYhBehU9X+93jwd4hM1lr86o9bxczJnRJNvrOP7RrI1B/X+qY7HVx8ifYb9W+QnncLzNYBxnHFunyjulYSDM1CLLAaWye9dJXSxfx58ZU3IwvqW4pfrfN6JLbV+M2u778b9efWf6+lrPdSy0blXqVZxH74wb6EkcL9xUYvnaGWt3e5KS0ufBDNmGqqpkrajQ369Ffia1NFEqmL1vtCTmow0E3fE2D1LJqMr7hxN0xAoAgGxJx35Y7A26ObCRFW0jWZ4LdVWtnue63uab359HK7ZrFb2z+/uvNqvZ/N9WBp5Hzu7s93+xyPP47P4tLF+bUk8/z8ZRheaNKWtpp4k88KQeTf3+u2M7Wy+q/bFq+wHP/S4mlTDj2LC3p6+jkigZWxduHvhisc/je07pZvnaQj3xgZaySPfq7vMEIGrCz4iU4sZ7pXvZtn2ecXeBDBt5bvmsdfE7u5yvm+qYS2ZAm4KAFecGyqi18R8vMH3NT0u20T8V53K1l95StaYkiKySz1NXaV4oo/s0p0B4gnkE3aYg6I4T5EVWDbplVUJmqQAAIJBkWHWrNpKVrl1QucVLrebUNSxdW7PTG6iZjaGx4vlfvb3rVjz83VLavNdbYbxoUGvL18rzbLxLnvu0zDOdsWtcPDL1ghjUyk7ky/VFOZt/WvUgqovIXfsr6NEfllEisH637xxdf9Ur77EYPwmgWIMTmA9+udjWeUn+fn8cm06xKmqO7qXRtrGf/mHla3/f576JpnhCNaaU2DE/9KfkYrj6/fiPKzyPB7fXFFh2K9Kc6NhuUNXwDPGznpvq8XjxZ6QZjWq4aARBd5wgjWhkJYBJjcMKDADAXW54d47P43Z+jFVUkyuzxUNdYXRw7trUujoqGdxOW4QU5lj3fjOLNpd4XIft4Al04khRZDaP26wv1cpoL5iEjLrQC7Sw3LW/3HN/zgbvGKJEwt+s9GR5zU8g+X20MfHPDZ77smc7UODzYZDtGLHExj1lYn3KS9P+enuIKQlyyO464D2HSUZ1K7L1b8ef0Fn8NKuKG6vfPZtr0wwCnUdY+s9yd050jH19pt8EdbqNa4A0HF2cgBMm7ICgO44r3akpupEagm4AgAXqKCbm9N6BJWTM0z+vjJqg2191VHKa/ncFCuzu/MhcumeFTG7ywjJeZpOatRf4M+WRSCltMCY6qgRSdTn2J1MFFvtS/x5AXh4d5ASodG/cc9Cj3IhXNuvXly5Nc/yee9lpOxFQx8fxOZV7/s/oa92+pNK7ZZ7n+83ybU4Qby05RE//7K1wG1VHds7x785Yb6pAMmKn0i3flxUf8XI9dBME3XFCpV5lUTNg3t6K6oj2XwIAYgOeZx1oNNZZSn/zTqXyWJes3hm8O3OanoRkox7u2XZrrJJqLhYvFUazFoOmudZz0CV5uqstV6TNFm1mqEosf2ZCjLpkj/f13N6yClq5fZ/tsXi+qos43zlRjBpoSKM0Ky48spXnfjzJcVku//uKneIcy8cxUxDAaJKDtSfP61Orfzne4J51yQndm4pxlnbHUfKaXiaYWfbNCeJxb8yk7xb5GqG+fvkAv9M85Hv54+Xfardhldo4p5/c0+v7YfcakEgg6I4TZD+hugBUDTzY+AgAAPzB420CcZGyUHxxcuD+aLfhkSmv/L7W8/h/Z/Wy9e/SkpM9VfKLX5khjNjcQF0w/bk2PgyAjOqoW0Z2tPXvCnMyhHyfY74Nhl5k6//LG6R0a+b/+AukUognLnn1T7rpPd9j9E5dXhq40h0/rQ6xBCf0VANC6SZvRe/iPI/MN57kuP/+Zgn959uldO3bs+ml39bYktoz+XrSjttT4rFQtKXkIP22YqenEm032FbPf3Yk3oESHOpIYSt+WVbbcLRDE/9JUZk4hYN5mILuiooK2rhxI61fv97nBuoeWS3w6elWvlSz1yVm/xsAwBp2OzWb3Wk38PE3tzl8pjzec9kNIzpQp6LACwHGuMBZv6t2UGi20PM3P1W8r7IImvD1UmGiFOuyOuPYHnUcWCBkdY/7VHmRaTfAV+dMW2GjiyBuMDsWm+X5VxugpzuyGGW+gSrdTLdmmh/Fgo3xs0abt0EbabWttNxUVm2FrHDz6XN/BI06w4XaRuC0BaTcpXZRqwSm1Xb1b50fcFyYJENPJPEscqNaJ9FxFHSvWLGChgwZQpmZmdSqVStq06aNuLVu3Vr8BHWPlJOp/XHql4qzjgAAoKK6nRqN0vxx2VGtbfUsus0lr87wOZcNbOu/by1QZl8NjjnI+X7x1lpSeu5FDGbxwvLBDbsDB5uxFHQHqoqoZKRq16BZ6/bQ396dG/D10oDOzv+RSJVuJ6QmiJN+tGKsDubYCLqlCeTuOBmBN321ucFmKxtJNV6/yirpvkPxF3Srpy+n0usG+gQRKwK5lgeCJ0mYtV4V59sLuBl5Kv9q/pZaap1Ex9GK6dJLL6WUlBT68ssvqWnTprgQRgGehUsilQIAAI4oPVRJH8x07pgrXarluJG6gINite+xWV6GrUWtxEzKx34XVTU1QiF03TtzaJthZErrhv57aOMRrjwbg4cmOfYr3Zmp3mWFenzwZ8eLuTxl5BWPuZHjgdSqmBWJfHk7o29gg0Pp6YKe7uggMy1wXathA+37wD4T8cC/vvbOiVYJlLxUJfl83tBmlwf2kYgV5m7YS98s3OJ5vEfvdQ+Wvw5rT//+xrqIdqZNUzbZmnXrB75B8e0fzqe7T+pS67XBGDKrLRbAhaB77ty5NGvWLOrc2X9/EYjAyDCLfo9exYF7NQEAicHjP6wIqf9YOpSySzUvjnihNaxTE9ujT5xgHEOlztG2g9nIq0/nbhLjUtg51xhwMxyQO6EixiZGsCHep3M20ck9m9FtH9auTNiRhhor3UYueWWGWEz/4+SudETrfJGsV8fc2JlVnORjpRa/GNsTOJa+2M+seAl6uqOLFH2ygT/kd4sToXFTzjU5b/obdadSX0jMy4V3Rzzxj08X+jx2Wuk+qn0jOqlnU1FFNiOYhBu3Zj17YV+65q3ZPs8/9FXtxImbibxflm0X288eFY0a+Dd8izccBd1du3alnTs1MwAQZUZqhlLAX4e1o/+btIrqK6ZqAIDExizgNpv9aYWUAM7fWEITZ2wQc635Fs6g+4t55osMu6i91xIOuJmpFjPHBwYYu2KFW87odQVXTpZt3Sd68KwcyYNVQRj7BGXVm3vendKnZV5E58OHm7U7D9BrU9bS2f19vRWGdGhsayyeTLqr5nQgPKzasZ++X7SNzh/QUgSU932xqNYkCHamtqsMiRf3cisDNLOJCP5eV14ZW4nLYK8HvVr4n6Md7DnWru+DkRY2ZePB+Ldw77fqmcLnf3V98ej3y8VPNtkLZA4Zbzjq6f7Pf/5Dt99+O02aNIl27dpFpaWlPjcQOXm56l7OpOtVB57pBwBIXLgi/fm8zZ4RLkb+NbqH7fdSJyPwe6r/x6a9B01NykI1ijTOEr3j+OAu1naCFpVP/jrY5+8MBpatxxIccFuZPNl1h7daxL36xxpdKho61x3bnuIZDty4F/6Oj+Y7mmEs9/N7f24Iy/YBjdU79tONE+fS1wu20POTV9EfK3fSgo2aeZjkodHdbblTZ0agVSccHhB83t+4pyxkPwa5z+rapDOc7DXp1//biA6O389sdOCEMT3opUv6B6VKCoZg5OUXKxNO5DXATEm2vzxO1B1B4GhFcdxxx4mfI0aMqCWJ4i9WVVXsnjxiv9Jdz9QYackWOAgCkMg8/fNKUSWctHS7aeW6q+6iawerxeT5L0733L/3lK7Uv7WzSrGRZdv21er7O7pDo6Df5+8ndhGyPh7Vw/NNrRjWqbFlq44Zg9s19KnAlsfwAto4R5jHgAXDqb2a0Zfzt3gWWR/P3kTtGjdwZXuMbtDb9x0Kylk9WuGk+PO/rvZxN7Yj2fe3f7jiGGyiCdjjbxO9BoFrdx2gzXt9jROfOb+vbVNKWbXkVp1Y5YEvF3kcy0NF7rdIBN2ctOKpC8d2bkJLtpQKJQO3w+TbGMEVTNDNEvFQ3vOodo1o/AlJIsE5b+NeERB3b+68hbQoN4O2lvhv1+Jrpl3SDTPAWUE1fc1uevHi/j7Px/iQj7oLun/55Rf3twSEhLT5NzrA1tOzi5xFLSmrpNwgpYIAgPhABoUrtu+v9bv/nuV/LJYTqeAPi7e5FnTL85i//mw7qBVDPldayXDHHh3cFA6uuu8rP0x3f7pQSIT5/qLNJdSlKMfVwIfP4ZyA6N8qv04CKrt9mCq8XX8/sbNPYPLf75YF/HfcChUs3Iv40TWDKdY567mpfn+fr5jPBUqSyF5PnvscykIceOHRdzyV4ITuTWslHM0mFdgdraT6Y3C12CjDjRXcCrgZuX/r2heD1VQyacyJQsl7MzfQ1ccEf27yNw0i1JGSfI4d3L5R0MeaFQ+e1l14eZhV5F+97AhaumWfSCyHsj7goL66usbHmyUBY25nQfcxxxzj/paAkKjU5eVyTqdaEZJsLT2EoBuABIXXclZeKHarMp7X26i8uWm8YmyPaZEfuqutv77XYFzR5SKIZX2F2eki6GZVAXPRka1szT63y60fzhOLl6uOaStMz8LJ0I6NqK2JjNFJpcMOJ/RoGvJiNh45u38LamtTKcBzjrmCxk7YbFL36bVHxWQQF238/eMFwpF5e2k5XTHE3bG40h9DFkfkrOp44o3LBwTtvfHaH2tEX3zHwmyqC6atNjcWdaO3vMKg/o226QJc6X7o9O5igocRNjo7ukO6K0n5B79aTDPX7knoSnc9x3KJvXvpkUceoSuuuELcHnvsMSopcS/bBZzJy42VbjkDkrHq5QQAxDcs9fV3nTd6QTgxJbNS37jBM79oQSzTvXkO/W1ERwonTqvIsmol+XC287FsZkgJ4G/L3TUyNbZbPnleH7ptVGfH40CDHV15XJdC26/ltgU3q0aRJNC282L4Ihuu5Srqrk+EpERdIEcgsevyAZdl4GrlfNOe2lXzWCdYKbXsHeak6C3vz6uz7+HegxWuXBvtJHjH2Bj/V9ewVD1Y08xgk64zlYBbjox02/8lLoPumTNnUrt27USgvXv3bnF79NFHxXOzZ/taz0eCZ555hlq3bk0ZGRk0cOBAmjFjBsU78kRlzGrzookXqXIMQCwvUAAAznjl9zW1nnv0bK9BVqqN0TbBVjLdDLrVGc4TxvSkxtnROWbEaDbDksW6+H9CxbisbKTPDnZKVhDVugFtCuiGEfYN0rhlgf+NOv82HHDAyk7rbJYVDj6YuYHOeX6akC1b4eRyrao0pMEqcId9hw7T/kPhG2VlnJkc7bBc+NHvzVtHHjy9O90wogPdPqpTUO/52wrfhCKPUnv426U0e71vwBaKako9L/++Yied+vQfwlPBDGMhywnqDPbhnZtQt2bR1/bBscPLlxzhynux4sto6GaVePn7J96xkYmAo6D7pptuolNPPZXWrl1LH3/8sbitWbOGTj75ZLrxxhspkrz33nt0880307333isSAL169aJRo0bR9u21zYPiCSlXMTP/YUmUJJ4cIQEA9jCbgazNQ9VITUlyvafb6YzrWMY4S9zNxINKpf6+H83aSPd9vijkmbbqZrKJnNGwLFhYIstyxVYB+g15YX7bqE5BV9TvOrGLR40QrqD756XbRED87KRVngBDXTyHGtC/MXWdkBP7G6HmRHChfjfDdfwlMlAPePl64Rb6ZdkO05YINt76S9fCoFVDqtyeefX3tSIQv/cz35FsTgPuc1+YRle/NUvc/2zuJvrPt0v9/hv+CvGEDu7rdwqP7ZUB/M1/Ca9KK1TVxWm9Q29b4jjkhYv7+Txnde4s0eeVby89RHd8OJ+mrIrvcdSOK9133HEHpaR4F218n8eI8e8iCVfcx40bR5dddpmYJ/7cc89RVlYWvfLKK5QQRmomJ7gTlV45tyskAIDohh2ejYvvp8/v42NOZjQqC0SKjYVUlUuzgtVK4JVD21I0Y8wzhCvmqdSTpzzTmUdMvTltXUjv10RRDtx0nDuLwl7FedS+iXUv8uVHtxYLc6Mk3w68kJdmd6rpkZsYx749++squviVGTRrnXVlOpjvpB2cqPtVtVtdm1ElAsb+XCO3BlnZDSfhVjZaVYeD9QhRueME3/3345Jt5OZsdb4WsnKKzQt5TnQg2Jjwxcmr6YZ3a/c7u+kjEi1cMaQtNQxR6cTwuM1exblBJSYWbymlCV/7T4IkZNCdk5ND69f7zkxlNmzYQNnZdWN6YEZFRQXNmjXLM9KMqVevnng8daq5O2h5eXlczBmXwbRZpXt0H2//yIHy2B1LAQAIjp37y2nsazNp0eZSn+piq4b1RaDFRjV8YbRTuVbhyuTg9g3DXul+6MvFPpXAUd2KyC1ev3wAFdRPo0sHB9cz6w+zyuLBMIwC4pm4/1McwXeHUIFdsW0fbd+nqaFu+ksHV13R1TEzTXO10V4juxaKmbKn9QqtrzEnw5v0X2niyB8qai8nS1y/XbhV3H97Wu21T7Ds0Pd3OFADdVXllmhMXr6DJs5Y70rgqX4lbnrPWgL+1tiBdEzHxiH9X24pN1iZcesH8/0qKUK9tljB3xendG0aPul1KIcCJ+F+W1G7qm/nc4g1gl0PWHHnCV1sVfaXbCn1OSfGc7Xb0Z4955xzaOzYsULKzYE23yZOnCgM1c477zyKFDt37hQzwgsLfU1Z+PHWrdoF08iECRMoNzfXcysuds9pNhqM1Bh1EcVjAQAAicE8kwWcNFfk88LDZ/YU40KcGGaNP6ELPXVeHzpvQEshIzSybOs++mLeZmHg6FSSybM9Jfz/WM0HdwIH3Bx4n9GvRa1Z3m5WMnj2azj4dfkOx0oFlZsVs6LmeaGPn1EZ2qGxkI+/dEl/+teYHmL0zrihbcUoq1CD+85FXpPQ5YY57qHAx+t3i7b6JFAuUObPOzWXU1s97rEplXVSMVSPBXYwj2b4vPDL0u303K+r6JHvl4UcoHCv7uod+8X78Ji6t6evdyUhw1W7QJxzRLEr02H+8elCV0xveX44fy9YKWQ8B7GUN5SWFE5kXPbqn7Wel87rwRgjBhPwvfen8yQKq0tC/T48/O0yevSH5eLaZpcdfpIT0Yos1PVrlR/S+/DxwD3swzv5T0Td/uF8H1VOPFe7Hc0m+N///icuPBdffDEdPqx9cVNTU+maa66hf//73xRLjB8/XvSAS7jSHYuBt+zpDjQexGwOHwAgPjEGuzzCSg1cQw0gWjeqL27s6stzuY28MHm1uDXLy6DnL+of1HsbF+DcJxhu+rTM85nlHSw8y9QYAIbqdswL8Od+XU1/6drE8jVuFacD9WAHCwfWQ5XK30k9gx8L5s/Zm5UaS7fuE33X01bvEot9rpic3qe541FZ93+xWARqVv881H3N7QD+OKVXU/pi3pZavgt2CfErXadM/HM9fTBzo08rXBdl4kqwPD95tUeRYKy6crDm9HzHIxIDxU6cxHPKtcPb+0xouOjlGXRs5yZ0Uwj9v+rfyu/H4/9WbN8v9rE0B/zfWb2oU1Hw6tQ9hnUkTxQozMmg4oKskPYz4y8Z99a09dS6YX0a2Db4czTPmnYDThLx7Yvrj3ac+I52WFHWrnEDV2aA2zVe3apP5oh3HJUN0tLS6IknnqA9e/bQ3LlzxY0dzNnNPD09cq6yjRo1ouTkZNq2zXfxx4+Lisxliby9LJdXb7GIdGO002sJAEgMjDI/aVriNrwQ8sfmvYdC3naz1hm3sTMKzR9mJjShmpx9vWAr/bFyJ933ubVMVG0fCAUn/dWRRA0Y5qzfK6qb3Of+VQiO47IyalV0DUVVwIkktS3AyFtXDKQrjm5LmWnJniROsCQbto/dmaMVo1N1qBgDbmbjnoO0YXeZqKax6aCTSqlUEvqD5xk7pUeL2pLqn5eGZv5brfydrNrggJtR3fiduqU/8MWiWhMFOOB2I5EbiHW7nY2YipSJMJslxhr8GXYozA6pN1/FaQI0HglphcEGZT169BA3vh9pOBnQr18/+umnnzzPVVdXi8eDBg2ihHAvtzH6B46mIJHhhS+7ZIar1y1UeIHIrtRuuOSWGaqs4VoPtWlUn/46rF2tMSGhjM8KZ99ruBYHZomBUINuO5vEPd1OnLXdcuOOFFZSVO7nDRcZqc6XTTPW+jdh4+8PV/qePLcP/W1EBzpJMUG1i9H3IJA7cyQxHtrhKBqwWdZf354tFBGsMgg2+Co/XGUrWdk8P9PxNjYOIWCPhMv6qh0HTH0b3OLlS/pbem2UOTyfhhL8mhmL2W1bUBM2qqlxIoGQ24tt7dKYMWPotddeE5Vgvu8PHiEWKVgqfskll1D//v1pwIAB9Pjjj9OBAweEm3k8I+dxquYvVrz422rRWwdAIrK55KBwyZQGhKl1UEENhpvfnytMW7hix7QsyBKJskfP6WWrt9Bf0D2mb/gk2if0aCoW/DySxWyBwzNurWZ1mrFzf90FhCxLZpfcs/qH3lrEUnq1ss/HmhM5pKSBYhjmj62lh8StU2G27X7pb0wqg7GEVSUmmJ7LYJm9fq9jCW2pIXjjz2niuCPp+ndn+8zuZek835xg1h7BAZibfghuYdyFdeG2zj31wSg6uEIeCDYHbJ7nPOjmz4al3sbKMzvl9ynOD9r/gI9Pt+ZaB+LSo9wzopQ0yckQrT6vTan9O6dd/4dCaPO5/Kg29N6fG2i9UmWfvW6P3+kM8liTigVOTEf79I1wwS0jX87XFBZHd2gU1eqbcGP7LMwmY/Iiw4G3aj5mvEUSNnnjnvN77rmHevfuLaTv3377bS1ztXjDa6RWz9YIBACA+9UANqzZuMeZ/I0pqzhca1QRX+jZrdqJ3JBnkTJcNeAetFD6Du3Ai8N/ju5uKRdnAx+5TcG4457Qwz3XcjNuGNGe3r9qUMBFlB3uPqkrDWxTQCO6NPGMtAql8mpXmcTBAd8mLd9e5y61kYJ7ba0Ih2u8ZJLJbGI7GKXpHEuxlPzFi/uH1L+rYpYMcMtojg3mHv52acijR9n/4Z7PFtZKCnJizil2ZePcqhEMq5Wq7rMX9vX53ZFtC8TouutHdCA3WiXGn9jZ5zluKfnSQavEgk0lNHHGBluv/Xj2Rnr65xWOTey49zccNM3N9BizqbDqYNHmkqDbBEKpdLMCw6iCspMI+edXSzyBetdmOQkrsx7SoRFdf2x7euLc3jRuSGImHiS2yyavvvqq5z5XvKOZ6667TtwSCemai55uAOz3/XHQXd+hso8XniwDZ4dP7n+SzrMsvXvyvD4isx0MvC3nPD/N8vdOTFvlotaJIZNTrBx82TmWF9V2TdVk0N2laTZdGeYLNQcqso82VLi38e6Tu9KkZdvppyVaAMy9xt2a5VBDBzJStTfTDmxMdWxne0lmO8qoaMbfrrnundn08qVHBPV+S7fa641nB+OORdlBVzcPVBw2TZaHuw+Wv3ufX3dUyP/P0z9rZl89W+TS8d2dS2Wf/GmFZZBi16BKhQMwNsCzKzfv2SIv6PMzw5/3/13QV3yfzx1QTIPbNSI36duytlv0j4u30am9antFuGXe9eofmqJqcPtGpv+/Gbzv1uw8IM7l4YLPxy9f2l8km9V54HxO5dt/z+rpM8HASdDNyiu1xYaneXCCVFZlJS3ys2qtre0I5BZuKvHcT+S1OZ93RuptL9XVNdSoQZpIQO48UOFJ9rB/xZRVuyjecZTmPvbYY2nv3tpfanb+5t+B6JOXP3J2rzreIlDXcAXRjZmk0YiahX9/5gaxaHP6t342d7Mr5ipsSMMjaeTIJa5Gy1431azGLn8G6PfkDP9Lv60W/49dZD9xlksBpR2aZGeYulTLKpZdUzUZdB/ZtmGdmKi5jbEVwOksbTsmTirBSGfVSuN1x7anWMPfPpWzx+3ClfHbPqgtJba6pl795iyRdAuGUkMl12zUnht0KGwQViOp3QeiawrKttLygK7wKk7VSBw8cFKNk6puB9xW310nsVp2RvCjy/YHoTKQLS/nD2xF4T6HnmCR3Fm13atAsIOZ8uW+U7rSY+f0EqN2eeQby6CvMrRePnh6d+Hize1TKq/8vlb4r9hlS4K4cweiXr0koex59sJ+IoHFo0DfvfJIGh/CqM5YwtFKZtKkSVRRUftid+jQIfrtt9/c2C7gcGFmZaTWUa/EgfiDg5PxH8+ns56bSo/9sJziDe6Luvz1P+mJH7XqyJtT1wl5IhvjBItRZjnujZl00cvTHUnr1u70XnDZFZcX4aHIJAPJiLmnjBMGf3t3ju33k9LIFiGY/DjBDc+IXXpPdyiuwJHEaLhldGO3S7DBUjAtEzLoHtO3eS0DrlhgVHf/2xzMjHSr1z53YT+xKPzX6B61fid9F4INbLhyedlRrcVCPxz8e0xPeuyc3j7Pudnjy+Zi4Uwec1DMc5XtYiV3tzJ2tJuEVK8L/B2JBE7m2QdSsLChV1ODZ0BVEEnsSv0ck1oH1VuWZJslp/KDnIlubGv67NqjqG3jBtS+STZNvHIQXXhkK1MDNWkU17ZxfUvlhx1gYOyFk+jsY8DKkfMHtvS0EajTP9xqiYnpoHv+/PnixixevNjzmG9z5syhl19+mZo3j8yJKdGxY6TGvUeq82IwmWEQPpz2Ukl4BM3CTZos8heHvYbRDJtucADGRldqdZv7n4OB50DeoleljbPrdwQawmqC+l0zfpdqHNi92JX62g3COBnDkjrO4gca6VVX1bZgkJXuWA265UQJM4WFXfgY52SLP4Z29K24BdM3KKWVOQ4qY9EAL9puHdXJ8vc8LsouVt8rlrnyopDHOoXi1MzJQ6mAaZKTLkwNebZxOOAFLfsTqGryCV87dzHnoPazuZvqxBmbpdHXvDWbxr4207aayexl/VvnW05rsCuzV48JrsjVBRPG9PA7Ai4Q/Nmocmw+xt64fAC9etkRNPHKI+mFi/vR5Ue3phxDQoJH7tlhS8lBT8K7rsz5eI756D7N/Z5fg5WXq8kMq79D3ff1TUxMg+kTj1cVopv0Us6v/6fMrY8ngvrGsDFZnz59xAmLZeT8WN54VNdDDz0kDMxA3VNlY2SY2hd003tzRXVu3a7gJDrAPfgkzIuw816c5tP7EyxuzeiNVtReKDbycSq7XbXDesTH4iD3Iffrms2E9eDg+hrK/F8ztpVqlaLG2emOqiWhEuxi0fjdkO7l3P8Vi7Q19Iw6+Y4v0V32rfoqnzm/L938l04+AcGesgpav8ue7FFWE5qGsTcz3Pirtm0OohXDyjk7U5H8HheCHPzDmd7kSbZNR/pQMVZ6p6921jP5xbzNohdaEqqRmj8e+mqJ8v/UOK68czV3QOsCv5XaYN43rY5aXLo3z/UxOAz2NDrN8BnnZKSI3mVOXrK3BxuUseu/sfL7i02jTjV5WFdtP5xINKoTZq7bY2uUm5m8vHtz/73gPP6Sv/dqQi8rPTnujCijea1XQ/FJUEfMmjVraNWqVWJBNGPGDPFY3jZt2iR6ui+//PLwbS0IbKTmp1rGC++cTN+L/VqbizM7BDuHN9F56ueV9OykVULi+e9vnFUhVIdnySWvzKCpIRhS8HvadZiuC9Qs9DO/rHIkh2OMTrlGY6RgeOR7/69nQ5BgFQzBLGTtvPf20nJPj3UkaO3AqEjCDu4ykWisyMQKeVlpPr3tnPwIFqOTPfeSvnXFQBFss+kP9xrygnRg2wIf5ca178wO2G/IgbnsM+zQJHbbj4wL/7fGDvSZ1GG375INq8xQJ4IYE0l8vbV73VN7Ohuk180xbRxRxAGtk3O7MSnJfzKr5cItmbWrZlIr0ke0LqDnLuonfo4d0obONpHw262Syoo+q4XqMnGp/j1Ltuyjuz5ZYPs4s1t9dWqqp/Z+12Uu1/iRcZLgBputVup+Obt/C7rn5G5+X8v926wK4B5vSZZJv30w5pth/qrEBUnKMZmfFZvJdleD7latWlHr1q2purpazMHmx/LWtGlTSk6uO7MeYC4vT/VT6WYKDQtwtyQvLK89+/mpotcW2EPdV5yxtZtpVoO0T+d4JX+qudC/vvZWC+wabt396QJ6Z/p60ed89VuzPCZcbvDcr6vEBdLNYD6YSjcvDq0cc8Ml/5q70b6DrD/JJo+ScbKwkkZShTmRkWdfMrg1DevU2NG/3Vde6QlqYrmawL3tf9cNYthAjufuBgPPgpXw3FqubnP1koNt1XSJx/ZcMcTbPsTwWJ1AMlGZHHGSEIgWWPItPQt4JA2758te6RXb99Nf355t632MjsVmlWL1/MWVMD4HbbApYW+mOJ13blo3SY6j2zcSUmIVJ72SxoCBW31YLffK797qdyjwjGqz89wBm2Pf1L9J9opKI66LjmwlnNvvPqlLUPJ4vr5O1Fs7rObBhwvuJVaZv7HEdjug3eRtksN/q6o0/CWy3cYsyR6MOaX87g5o09BWsGxMsnByzzgyrmEQo0+ClcMnInvLvJ9nfRNlQTwQ0mqG+7p5Bvbnn3/ucwORq3QnB+gLNc7pdSvO+O93PLszcGATa3DPI1dL3Jr5yhe1+79YRBNnrDettgZjUPP6lLWWfaLBZKA52Px07iaat6GE3p2xXiwkuYeas+tOAtGZa3eLv4+No1gey38v70MeMeKkAm+1QArmgs9/lxlHtff2wzoxZvPHvZ8tCur1xgUPB1jXDGtnOr9XSsf9IY2IIlXp5j7YW0Z2spzbbadKzwF3uMcphRsOkNW5u3bHUs3dsJe+VxJzgUaHGcf9BHIwlj4GRkOlWIODLHbB5VFTbIzkpnEgV0tV2Lla0qIg0yd5EQhZFT69T/M666Hn7063Zrk+z/E1eleQHhYzLZJFn88L3qfADDbFOk6fa6+ijnOyYsW2fZ6xV1bXPt4PA9s29HyedoJLltTLxHgoqh0n3D7Kd143Y/c8aLxeslGVXewkxdXgMRSPg2AJNSku1wtqu0iw8OgwtZUnmPXasZ1rH9/Alz7KNWzy8p1x2QfvKOhevXo19erVi7p3704nnXQSnX766eI2evRocQN1j5QeBXKTNI6k4JMGn6Q5UxyKoVeai5lg/qL9vHSb6MH928Q5dMpTv9N2G0GGlSPt3z9ZQI9+v8zRF/juTxeKKu2zv2qyZg4mP1B684Ll95U7aebaPWLUVCBHbH/B1LKt+/waM9n9KL9duIXOf3E6zVhTe1HF46+mrQ6uMsfHEM9L5b/vghen0+0fzhd/rxPjkUC9lsE4E1uZUd14XAfPfd7WUDDrE+NEgx04iFal88d3LxJSYu5LZGmjEZ5dGvg9tYV14whVuiU8E5fl0MHwjp4kOVAePW0OTmlgMOD5U/k++INnvqsEkvIazYACLaD3lGnfn7wgXYCjEWNA4tY4J+P5iqux40/oTE+d18dj8Ge32nZIX6AbXe3DTfvGDXxMqPi88NiPwbXT+Lt0BtM3z6jrDK4mcnKOiwFmfjQfz66t5DIywzBq0d885NSUJL/XFBW+xkrqevpD12Y5wvhMxW77tJqAYDfo/hZ97UZjMrs99OX6d4Ld94MZTxgqobQy8Gg/OVEkIy207x+raEboCaLfVuz0qc76YwSC7oCwsugCJUnELSzxhqOj729/+xu1adOGtm/fTllZWbRo0SKaPHmykJzzODEQQSO1AGdmo1STF/pnPTdFuDp/vTD42cKS+i7NAeYT2POTV9NjP6ygGyfO9Yw8Cqbnmd+DkwjzN+4VAeWCjSXC1fu/3y0L+sS9Xu8HZAOayct3iGDyjanr6IEvFtODXy4OOlGxMUB/oZ2glF1db/2gtgu3ETsVNf782VVX7udgZ0cb2Xmg3LW+ZU6S8GdoVdV1OvdYnV1v/D6EMgrHWBVj/vf9Mvp4duBZvs8oTp3HdSkUbq3+DHzs5I926JVuY0tJpKq9anAXqIJVFaRJXjRjlMnJRWuw6B1ElhiPE1Zu+Es0yvaRbH1cSzzhlquyWQA3uH0jUflsqKvGeCpCIPgc+82CrRGRKnNge/nRbeiYjt5WD74musVVb86y3TbE6qfTnvnD85hdtV+7/AixbikyUVzYkZgaPyN/FWH5HbHTmqT640SixYWTOuzALvnfd8sDrjeM51WjTF2FW38eP7e3T1uKnetzuf6aunIudyPoVkf7hVLpZthDo18r7+fyiUmLnxmRMDONRY5TzCpvfn9eUMWVWMDRt2bq1Kn0wAMPUKNGjahevXridvTRR9OECRPohhtucH8rgV/4RCzPR4HGDpnJz+W/ZTmVU7h3ShJKXzcHkyxFDsZ52gj38HES4a5PfCtFnJUMtm9alSZx0K4Go1wdlkG5Hd6ato7en+k/AHO6IGe3TeOIpi17nakDjLNdecEYrCzYinKDMVSg/5s/Q6tqh92g2yrw4Nn1xgUa990GCxuz8AxPnnP88V8H1zKr4spDoAuHWi0yyn3NFjd2kjOykmlsKYkUjytzg1lB4g8eqWQccxirGBOhrFBhtUywCbtA8vJUw3HC7vrfLdoW0BCpQR05aUeSQAt29RxxVv8WdMOIDqK94+JBtWf3qucPu5MP1CA32MqwW6iLfnaztoudpAKb99nhWz3xoAZAMgnRrVlOLaduO4FWsqFCfowfHwlpimenp1s10KvLiq7KP07q6rke8HV4sZ9pBmZBs7+JGHztYy+I03o398xJvuezhT4TQkz/j8M1derm7nYwHmrQzageGJi/7X6yaUiHRj4jY+MJR9+aqqoqys7WLjgceG/erAVrbKi2bJk3MAF1Q6VSAglkpOb2BZ8XKxzI7lIqnNwz5jQ7JSWxRoI5r0oZkRlPuNxzbnezSsoqA87bDWYGs9lFgA2bOjRpYHuRbgfu7X4sCGfvQJVimSUPxJfzN9M/ldExVg7hdhxdzZIGZpJtxol53IVHtqInzu0jxrGoCzWVQBdmdRt5ZIzvtnrfU16MAm0nf8/lwrKu5ax2EnOcrPJXHZPyT7uzy2MNVsv4Mzs0S1wGOgeaLYLV2cpWx1xdOWlHkg9n+T/3qv4QZ/cvpr90LRTtHU38zNFupffqy954fxys9H5fhyoV57pkt3KN5mDLDpwYYmPNQExesYPet9F2ZUwWqudhDgL/PaZn0NdDtdJ9Rt/mtbwNzCq/b05bFzBpq553I2XmyIkSVQq/cY//JH+l4SRhN8CU51lOOj/9s//5yBVVVVFV6f5qQXAKTTfGnDXWW0vqcvxfIlGtfNQZLqloowVHRx/3cs+bp8lbBw4cSA8//DD98ccfovrdtq3viAoQflSpFEtf/JFk6lnpHDbGYgMwDs78jbpxg0/mbLRlrFKX2N2b10+0N9oiUAbeqmrLmXjOEJ7S2zuL3Ykaa0zf5nRk2wKf/mSzfm+rLDsbRYVayedg4PlfV9fqLzOTZ7F6IRDsYGzk9uNrG9UwZm7wxgv/29PXBW1w4y//wUZAau+yrDqYLSplVfJAgFE6aj9wpKo0RoznJn9Bd7RVU8LBdD/fKzNDyoCVbpMEhb/PXgbd8eoSq/LWNHMPDXW2uQxS7H5fpLN56cHKgEkwGdRz9bwuzaesVEZ8Tmc1GCeD/bF6pz2F2ZtT14mb2gdtJwFqPHdyL/OjZ/fySM3ttPuo55WuBtM4I8X5XiO8N6Z6JcdmqIG23Xnh4UBdW/krKJitH4Z1smfeZVepoB5HdX1utkoUzdvgf0pIOGbKN1SCbjuqCRAcJQeVdX78dJoJHH1r7r77bjE2jOFAm+d0DxkyhL7++mt68skn3d5GEETQ7c9EJNBsYycBuZXcyY5RiZFADuGv/L6WPrLRHxuIYOTSdke1BcJusoAr8Zv8qBGsxk7I51XJqlrZsMIYL3KV4K6TulJXZT4l87/vlgm5qj9WbAu8QPNn/hYoGLvnZO/IF4mdKpMq7eQFL/cRHtm2YdCBEMPSu4kz/Fd0VHdTO+NCeF67ijEI4oWp7Ifuri8qAxmMyXFh0RS4Gs9N/qpYcqFklEzHKmyIFyqB1BJmyR9/KgcpL89OgEp3IPYc0IKO/Pr294UMuvljOfeFaX5NE2XQbbfCHA6M12T2PXnLkEAMdEzxjHiegW0cnWRMXpjB89LVa8jLl/Y3fV2Hwmxh0mW3HUlNRgUajzigje88e3+oS6X9+gjDSKD2XLNChr1lrFCTFMM7NQ5LNZr78iPRlsLu3zzN49ZRnXyeD9TipybE1M8/VIZ21FRngVoGQfCUK997J+a70Yyjb+SoUaNozJgx4n779u1p6dKltHPnTmGsduyxx7q9jcBm4Mdr2kBmDf5kUhzsBZu1s1oIOsn+PT/Z695sxa9+Ljh2+z+cOqGbUaFX5PxhRwKt8n+KqZbdrG2zvIxanwdXdwJVCoxV1fwsTX5nrPbwflfNvszwV/Dt2cJbgXjpt9Xivayq9lZBd56+bSo5Ni78csF77oBievD07rX6GY3zjf1VYNftCtzDzyNaeih/b6CAyTj6jGXqRl6+5Ah676ojPY7JwSSOosXAxbgd/pJs8jiPloRBqFx9TFv6zxm+0lm7yJmywzsHL0v2Z9ol1RKJUOkOhAwWg/E/YJmqev70N9VCnlMyQ3RODgWza4cMoKwSjEbFBScaeAY2j0662WSUoT81hvpe7NXgb5ShvP7YkZd/Mc8rL27V0P9oL37f24/XgrZA10Y1SWF2Tq4rTunZjE7u6U3aqd4yRsJddeVrtqy8y2tRXV4/OHnJhoCsxrPrOSDVAZyAUGe1h4o6lSWUyT+gNmz8KHFrXG+04OgK8NZbb9GBA75Z3YKCgpifpxqryCqanV6VK4b4l/9/E6SDuZWszomk56clgU3O/En/eGHzn29ru5wbR+KwWdt7f/qXG9rFX1Vasvdg7YXNR9cMpouONDfp8RdQmV1U/3tWT88CxrjoCSRHM/YjSVlfoMWLGYssDIV4/FV7pdecq91c8bB6vdVCS1aW7LxWRWZKMywCEDaS+eDqQZ7Hu/yoEuz2yd95Qmfbigg2YZOwaY5ZYowXDNwTLRf5TnrPow05QsnfcW7VIx9r8LUx1+ForkfO6kX3n9aNTutVe8RPINItKt28eJbnhkDzvOOFaat3Wf5O+m1kpgYXXKnXFn/nIjdmBIeKWa+zPxdv7u21mmrBDDcZgeRvH6jqm0BeDfIcaMcV3Wq6RaA1xMJNpX6DJfUcy9eISMHBpjTtC0SJstYIRxh4oKLK8xlH0qBz3FDfday/66FcT3FBwc0YRZ0wYrbOiscZ03VF9+a5NKqb5mKOSjcR3XTTTVRYWEjnn3++kJSzsRqIgqDbRkWLs9T+2KFcGAPx6h9rxCguO8GhVaWPT0wsl1prkOZZbae/v9BKivbqpb7zLrk/K1CPn3TPDgRn7wPNEjSTsXEQZeUg668v37hfWS7VucgrBT+6g281LNB5v75ibsULQilH66+MxLDL68pYDpU+LfNMP3+r5ILVQss06LYhP/RWmZL9LsSkWsBfK4BxkWqVOMkxBDL+Kt3yPXlU2HMX9vO7MJBVSV5kxPpF3Z9qQPbh17VZTzgxS6bYqZBwYMcBkx3Fws0jO1oa/qjwwlkek0a1S7zirz1GSlTX77YOMgMH3dbrIO77ZnJMzmF1BRs+XjpYk20H69dhF3/Bj5qwDJRMk+7QW0oOiRnLTv4/K9Tk6xfzzdud2GRtqp6k4YRXpL8jRuWUFQ9/662Ch+PyIA1y+VwWSa8Qo2Hwkz9bG+TKgNiOKi4YVENE1UjYzAfghYv7ufp/JwIN9O8cKt18ItyyhSZOnCgWh2effTY1bdqUrr32WpoyZUqkP6eERMqX7VaFnr+oXy1JrRMZldkoJ1kp5WqhzLryuK9zX5hay9101/5y0c/Kcqnr353jUxnlmxn+EpVm/eotC7IsFQC84OU+M6uF772fLSI7sAyPA/TLX/uT5pqYeviYQiioizS1D9hf8sTYlyelcuqJSh234E9xwDJ71WSsRb430cELfNVMLRSObNOQTu/T3LYUzsyEb0SXJqbHt51Rcmz2Z6fKJDP3PNPTKqA1HmNnH1Fs+X6q/NJf0C0rvr1b5gUMrOT3k9+O5zBbEa2iI+n4zLDxkhlq0iM5Wv8QB5gtUu14XwQz13l4pyY+qg0rZMKLj7docbd3m4GG/k07CeVzjqjtx+APNYi2SgDyeV4aPsr2nUgdf2f0a0EnKVJlt5E+AYGC7kAFAlZuFRdkBmwpe/n3NZ77J/QwXzMYUY/3l37z/ntjEoaToZyI7RMh4zsVJ8cNu/DbxW6vc7SMGTQqJaas3BUwMROOFgFZHDK2iBnP7XUtxY8HMvUiyefzNtPSrYHHMsYKjq62KSkpdPLJJ9Pbb78t+rgfe+wxWrt2LQ0fPpzatWvn/lYCv8iMmt3xOs3yMmlEl0LTCqLdRa5ZcMnzTWV/DRtvXfjSdFHF5gsbB1LGRfY1b882HY3D71OjiKOylAqlP7O3Kat2mppvWPHun+vFTO8XfltNoVZQOEDnRZ3qGm006TGimpWpVbAlW6yDKWOgarYgVyvlfuWDhh5tYxXmn6f3qPVv7FZXWbbOEiHuoeaFPV90BrdraCmFUzFWjG48rgPdeFzt/kE5NszffPm9qrFPkr2giB14raTvVTaN86T8Uo6o8Rt0e+TvgU/H6nFy+4fzLV8n2wNu+ksHiiZ4VrfcJ1b+ElsVuWg89Rubfb52gu5gq/18HJ+jJ4OsDPy8JmopcdsWduNfOgoJKLthG48rq0Csh2FcXyDyMr3BkFUSTJVoq9eySGFMXtr1HJH7UcWYvH97+nr62MTslP+P0oPegNxOC+ytIzsFNGdT1w+XH2VeSDBi53iX52RuvYiG74dR/WZWKDBem1sqCc5AjDe0Q1ld570TDyIbdJvNH7faZulbEI7RXvL7bBp062s1/ujsqFCBdZI6mLG10U7IKe6srCxhrHbCCSdQhw4dRPAN6hbZLxrMF1s1KHr6/D50mj5qis11HvpyMZ3y1O80f6NvYM0B9cJNJWIGsBpc8sL+w2sG0cWDfKVrDFexrWYiW8lGOMt9fLemImjhoG38iV7zC6vr36LNJWLMlMp9p3Y1rbBKpAv1V/O32DqB83v9bUTwQczaXdqiq0NhA3HxPLt/C/G4beMG9L+zetHrlw+o1QtnVaFepSzg7FSo/FWCjbJ3o/zarOpqtYg3yhQvHtSKJozp4TMex7jYs+r/M1aMAnkVvDB5tWVvvdqf3ai+/2yzOrfVytk2WKsC+Z00uygb/950G3I94wLQWi2g/X9Nc/23k9Q1/FleqftKWPUEqgkK/o7EC/y3G/tgw2V8JI87q2RPIowLY9UPK6ak+or3tdn+4HO9PBcFO4/Z2PKyOoDypothKkQkSDNcjwP5fqiu4kbMep1f/aP2GtCYXLfjjSHPD5ycNfvcjN8du3LnnMzAwZcnERqlKhCza6e6i4I9jo3XWKvzhlxj7TaMiK1rzFRr20rNlSxy0kc4EgVyhrRZ33GZblTJezIaEjexRqbyGdvx7okVHJ9RysrKRKX7xBNPpObNm9Pjjz9Oo0ePpkWL7ElygXvIamagGd3G6sm1w9vRVce0Fa7QMuDiIE2OTbrrE9+q7bg3ZtL4jxfQ/03yrZB2bZrrVwI5Z73/OYoq/fReYt4eludy0KYG7WYZTubOjxb4POZd0a9VQVD7RMXsJMqOqyxzlgkKM4ybxxnpH5doC44xfVrQ+1cNoouU5ESnomyxuGinmGn562veWuINLh84rXtAYy6eoW6FccQN9/xZ9dZJJuqGQyort++jB7/0nc89qlttqZ8x6LYKOIyVbjuByRaLoFtNHAWSy6v73MrVV61026kiy4XAv7+pbfAnjw/ZT2p3gfePk7va7osPdvFVF0hFhdW2y89fPY7jBT6n/d8Fff0vnl1wwpXnPXXGr4rc9w0SYFyYuniTC2GjUkzGgMGqCvIN5ngLNnnHExrPX9zqFOkKIZNs6Ic1Uxy57ca8xDBa1I5iSvpi8EvNzhXqdeJopaUqEP5c040tTsG0dtRla46Zf4CaqOc2gmBR+46tkuuyFcrf6Nm6gAsCNxgKIFaGW7IP3e2ebiZLP7ccNDmvSA+JGLdeiRgZynk70LjMWMLRiuzcc8+lJk2aCEO1tm3b0qRJk2jlypX04IMPUufOvjIVEF3u5SrHd29KJ/ds5mMuMm9D7UWDEeNr1EWNscc4GLh/Sh2NYRZoc4Bi5wtodOSVkla7qAsRXvxzcoL0jCU7wPMCygzjiCNeVMtMa//W+ZaLOu6pUoM44+xmyf5y7/grq6qJ/Ez9BfDGMRusKDAzr3vs7N4+/fXvmwTdZoZYZpld44K3wsJ4yBiISIMzhscusRO6cfSHleM4z3b3t02+21MdsNKtLv4KAlTOjf/OTL3w2TyvL4KVu7q//jurHkpZPY+k2U0ggxSroHvGmsAGhrFMsXLuYIdoI2t0ZUwoyIXen2t3m54vvc7lkQ8Cww1fF2Xi1kxdpbqah1rpNmvn8Yy/i8IEmFWC0Rh0sWrJiksM5mxmZBmSDXYUQxxYyc+t3OQapl53bjfMbg4VGdRGU6X74TO9Iwf/MOlh9gm6+wYfdKumi7JQYCRPP97NxsXVNX/pWkhvjh3gUetYFSrC2dMt5eUb99RO+vtTt4HAqMpLJ9OQohVHZ5Tk5GR6//33haHa008/TYMGBTZuAXVgpBZC30goCwJ14ab2uJlhleEe1K4hPX9Rf+rfurahh7FazX3igTDKJu8/tZunih5M0N0kO52eOLdPrUCWT/h2RvSoPZv+Zg5zQHhs58Ja5l9WFxB/bqrGirJx1iqz12DuZrXY5DFHfx3m36fBKEO/7ljvKA0VY5B16HC16fEg9z0nO/ji3q2Zt8+ya7Mceuyc3tSzRZ7rs9cHtvX2nJv1EU5fvUuMmZEE26fFbv9GPp/r7UcPJkCWiQizBTPvU1mRiOSIIiukCU/pIXMH9q8XaO0e/sYVxQvcrmPkxolzPffvO7Wbo/dVjwuz5MZu3W03kmN/6hIet2dWDePjT517HGzi2uiDYbY49I6/iw6JqXF8odprLVETNWzMx/4cVpzZr4Vo5fKH8Tizuy/kOdHMXJNVd5JQ5LvGqj4fE9JgzW4itK6OYan+kedIK0Whk2NNXWcZW/WMybpIGgKqsEqzsa5cMAu6+bOUE3bCMRpRJpN4DCqvD3x+pweNY/pGbtxcLFNfmawThJVO1BN0pFVZWUlbt24V/dscfIPYrXTbCbrlBclKbstO6GrQFejaZ2UcZKy8+qsmGCV8ZpUcoyyMjaWCWcCu3VlmOaaKOaVXMyE19/f/8gJMGkDwPrIz8icQcgEtF5F2kM65KpWHffeZvwAy0ILGaL5nJi0X/6fhs+de+n9+tcTnuV+WbacPZmpGPN2b5ZrOgjU7XtVgWL3gymQCV/IDccmg1h7zGTPJpVF9YNXqYMUX82ovlFSCqarIz99sobGnrNJT6YzGSrdM0vG5xWwxDbw4dU5Wx9WYBd1SGWI1tjDekN8DY/XJSm1hF6MxWqVZ73GUVbqNxp5m13b2SJHYmYpibFNQA1k+R6kmqt2a5dAxnXxHWwb63PyNYwsV45pks7IW8TdmMhLIljJW/BnP/WryyEkSws6/kceKnb74ujaoNDOgVRUB4fCvUNUBHxhG20nFXjReg2OBIt2Lg1GNlWOdoK8CqampNH++tWsuqHukpC2UTLpVFXbH/nLRj3XBi9Nr/e6aYe2EE3owyODaWH2VfTdmFOZk+MypZFMWHvXlT2IbygLnn18tpmd0Z2/OpFplhc0q53JuKweYY/5vCs1at8fUvMYp8qJXP8TFgFlvo1PUgH24n8WUmfSS/QPUauej3y+3VA34Uz8s3lJay4WXL7h84ePAu3NRbRMgI7zAOl8f3cZKA2MfonE6gKE10hGqjDOY/kGZTDDrCX5nuneBG4093fx3ynOVVTIvkVhs4ZTPOE3UqQtys1nGJXr7hLEnOV6xchkO1cjO6Hlh5gQuEyB2R3qGm4L6qaYzxFXu/8Lr0WHnEDSOkFJ7fr9XTNTYD+XfZ/S0fa6T64Kb35/nippJok7SmLl2j+X+sEr6RgruS5afR7jly8ZiBn9XZJI0HFVjp8hr4Lsz1tfaZnXUlPQICFdgWGu7otyML9rJV65NmUEUmaIdR0fDhRdeSC+//DLVJf/85z9p8ODBwi09L888+79+/Xo66aSTxGu45/y2226jw4fdCy6ilUpde+HUNMzfguCK12dajiZS50GbnYRevLh/rd9f984c4RJtdDM9EOACcpfiYM68Nc0bWJRVuhN08wmbpevTVnuduHl2shXqyC9JgR6kS3MsSYqDCM24j7gfcZU+V7t1o+BMpoxZ8T9W+la/rYxTgs2Q+3PgLrdQOVh99sFK+9TqNM+A/8+3mnnZkA6NbWeb1b4v43Fv/I74k/jbRe0dDyZAln/P9n21F6LblXnEbqgrwoGU5fpLtiUKd3zkfhJbthdYuVPzlAqmfhwtZuwE3cbz4CRdespI345g4OBDnXttlgSTVVp/7UV1yZi+LYRPR5em2bYSX3YqoMY2FjX4UZM+diY0qKhKmPsNZp2hoI6gfO7XVabqB/YOaRdl0xP4s5AqJzcT52bIc4REHid8SQk16e8mPKrVXwJJEg6lib81ALfPRZsZXyyRlJREFw1q5VdxGos4Ogo5kH322Wepf//+dNVVV9HNN9/scwsHFRUVdNZZZ9E111xj+vuqqioRcPPrpkyZQq+//jq99tprdM8991C8IyuITgI7p/INDvDNTjg8j5kNP9ihV1Z9A42XEu8X4MLOwRC7rZuZ35hJVK0WOHKhYca1b8/2kWgxI/xkuhs2SKdXLzvCp+Jdo5uNGYNauzJGOU7MTA3Afdi8luHMaSCFwdXH+PZhqzNkeayN7HMKZoSLWZB79Zuz6PUpXrMyfxfjU3s1CzhLW00c+at0m76PcsGdrfS3Nc+3r8bwpxZRjymWSLbIDzwH1ar330wyGUyALAN0NoqTVUtJ56KcqO3nltTXF45qgsuI037mWOBSG+ZTodCukTdYWLy5pFbvvEz2RMPc6EjKy19Tzl3HW7TFBEJNvpYZzvMss5b9sWpwEEm0a2l7GtyukWlPt9UoT38YFRNqElcNwENR3qw3Mex0iiobN0rIpXLOjaRqOJDfWSefUzB8v8g36S+Td5wwjaYRWOOGtrFsPVSD8IZhaKVR1yjGPYJKd+h01c+ta3ceiBszNUdnwIULF1Lfvn0pOzubli9fTnPmzPHc5s71msC4yf333y/c0nv0MHfR/P7772nx4sX01ltvUe/evcXccHZTf+aZZ0QgHs/IMUahyMuDjbnaNqpveeJlV2126LWqLkrptoSzWH83VLID9Y2pAYpZX+sFAzWZsJGHTu/h4wIq4ayx2aznQI6XnGTgBYyUL/NJ/81p6zx9ycFiHNvFi+U56/fQ3A17g3Lh5OrLa5cd4ZE/8na9M3292PcfGnqPtP/H/jayZItntU9atl3sM3W/+esRHdm1kJ44tzcda0hkqBXqFkqA3MOPeY8ZqrpAHe0VTIbbKlnDSRP1/e049jLXG0zl1GM1lNmT6uKVpfVmwfzIbtYBf6SR+/I9gxs+H+/yq91aGZETb1j1tNoZpWSH0/t4zXven7mRPp/nNezbub/c4/wcDSOs6gLZAvPz0m3Wr3FYiVavc0bVjlpFjrZ9Lftyjf4Vm5WxlHbhtcDn1x3lebxSV2QZj+lgg+6j2tsfBeaUPgY1m3eGfXR9XsYkgZnvSKiMVs4bajJdDWDDIdMOBdWA1ng9WadfZ7itgYskbuNPvRKNY+dijTTlfGFmHhiLODqr/PLLLxRtTJ06VQTkhYXeL+CoUaNEZZxnh/fp08f035WXl4ubpLTUur8uWpE9Y6EYqamVTl6wccZe7cUyEmwV0h9vXTHQ1uua5HhPmqlKVV8GL1xZ/9foHiIQtjJA4S9x64a1pdlzTWaJ++tPVuHA9sQeTUU1OdTsszGRwVL8ez5bJO7fcXznoBYDfJHhyvkzv6wSfaPSKblDk9qSuUDyHR5n9tgPWuX9tg/mO1ok8d/WtnEDIRn6eel2z/Nq9UlWRc4+oli81h8vXdJfVI9Y9cDuob8u20HDO2kBvaqWD6af3vgd4gUjbzePXlKxKzs0fp48WoRli8Z+0n+ODmz0ZjVr15gBlu8bjf3cZnCSQC5M2MRIfnbxbEBj9bepBmihwOe5K4a08bgw88/TejevpRKK531s9I6wMlwMlf6t8kWiiI9bVnHJc4bRpGvckODl6+EkV580wtcYFU6oOkE91/3j04X0xfVHm/hWBDvWtKiWaswtODH/9vT1Pgln/uymr9kVVcZ3RuS5ktdnZtNeQuGyo1rTJ3O8YyzNEkjROGawuCCTNuw+WEudIBMTw/R1gdv4a5eQ/3c07q9YIVVZj5mNZYtFQjqr8Gzu7777jg4ePOhqlt4J7KiuBtyMfMy/s2LChAmUm5vruRUXF1OsIUeAhDIyTJWijj26DXUo9B9U2P2oubJ566hOPrOendJU6RdXZcjzN2oBc5PsDFFhD+Q4aqoIMHnqSoNE2x+h9NP7Q+3HlD3KwXQCNMnJqDWaqMYw7oXHcqmzg804wsbFnaVAnPAIBL9GNReRlQUOFuWC7wQbxwsb7PEoG9njxqZ1v+tO7WoSKRiXceOxMVM3wlMDZB4BEsyCjLPs3m0h00q3cQRaMBiD7mifC8z0Vly5d+73LvpnKsmNeA4Isyz+toWKa7TZdIRgUPefen5Sz/WJYqR2XJfwqT5YdfXUeX1Nj2eZRGFJsJyMEC1IVRGrTk575g9asU1rQZo4w1stvPMELdHrFJbXfzzbG8QFW/ULZ/uDdxyZN+nLBprzNpS4an7qNjJBbrysSfXf4+f2dvzenDhprreuGR3KVXl5tCFHuvKIU5Wy8qqwHkdqEsn4echkVqKMZQwHacr+jZaRi6HiaFW2a9cuGjFiBHXs2JFOPPFEMa+bGTt2LN1yyy223+fOO+8UX3J/t6VL9UAjTIwfP55KSko8tw0bfOUpsYC8sKvVr2DhoIqN0TjgtjOSqm9LezOvuVp5TMfG1KiB+YknmC8Sm9bI6jMHanyxXLZ1n0fKbdcl0ixANjPgCMYsJNiZzXYxcyht3cj+4i3P5AKpBmn9W+fbcmi1s1gKZvxQkpLl4AsjB1tP/LRcVIs4MxxM/5W675/+ZYXlGDk7GM3SFmwsqTUCJ9j3PqOvt0//bxPnCpM3NZC38j7wh+qkbpw9zCPDoj3ovmVkR9Oe/u2l2r7p2zIvbImsaMDYvy+Pr9f+8Eo6/zaig2tBt/odefxHr1dEOCSX0YiclRsunwM1oFaNw37RFT3hdpp2Ou5IHhZ8/LFD+LOTVnlaPzhREYq8m1Vfa3cd8Hku2O+01eelTi9xilwvqOo0mWQNVTkYTo5qrzmvH1K2e92uA55ziJ3Etz+uH6G1RNU3rAHlGik7CmX3MvhVk+NiJOXhugu6VUUHr03ldRlBt3NSlfNFtEx/CBVH3x7urebRYewW3qWLtxf3nHPOEUZqjzzyiK334QD90ksv9fuatm3tSbKKiopoxowZPs9t27bN8zsr0tPTxS0ujNRCyATxIvB2Xb7sb6YhB+bdmuX6NYgywyohMLCtd3SHHa46pp3HBOzVP9b69HnYXdioMrhmeRm0ee8hT6Bi9bpAhMsl+qCJM3swMsV8k5Fnsp8zGEddTo6wLFrt1Qsl8aAeDkb32DZ+/ALMUBdyB8qrxIXXraBbXqzV+bvB9mJzMoJVGlv0cXnvzdxAfx3W3luRdnAxUS/2qhqCFxrSqFBpa486eBQf+yBwS4ZqBLdGX6QProNezmji1xU7aFjHxrRmpzdICdWsSM6vDfXaEA9IiScvwvk7Yjxfq2oUp8hriWqaaewxjSZ4H7QoyPIxKFOvpyf2CE2dxq0/xoRgsEG3VcCiKrfuO7Wro+2TiWRuPWDflD4t8322L1rc5q0SEep65xFl1GaoFcFs3TvHOPUgmivdMsGsmpPydVoK3sI1b10tRqgBv0y88eEUzYam0U5SUvwF3Y7+CjYt+89//kMtWngrOEyHDh1o3TrvKKdANG7cmDp37uz3lpZmr+I1aNAgWrBgAW3f7u0V/eGHHygnJ4e6dnV2Uk4kIzUjZpVuvgCyaRibdAVbRbPatr8Osy/hlv3MUpoairECu44/e2FfT3/3HqXaJgO/YLAKOD+4epBY0P3vrF6OttNoelaYk245O9yMQFVUuycyPvkF+ht+Xe7riO4P2V9qRrBZaWNAwbIu7u+S1IRwnMqLtTp/10kspF70q/QkmbxIO6lIq0G3Oqd+vzLmZauLc23DgVRGqAmvNTsOWPoOxBvXKSZ7nHhQkzn+piw4qXSbfc/ZhyJRkN8/XoRvUb4Xstop5amhIL02zOaiRyv+WtJCHZc1ecUOj1Tb6bnTyr9EPbYzU51VXtnwVSJ9U9SgO1rlrPJY5oSlXB+offmhTLFRZeU8MkxVeMmebqPsPBqQCZJyZZLNvnLviLNwJVDUY0Q9JuW4MH4umpzeY41spR8+WpNgweLorzhw4ICYhW1k9+7dYasac1WdndH5J48H4/t8279fq7yNHDlSBNcXXXQRzZs3T/Sa33333XTttdfGfCXbtpFaiCdblfomQffdJ3Vx7OhpleFmyXiwdLToNw/m1MYSLB75JC9g3yzw9v2zGcejZwcXJFtVuvmke8WQttRJdzcPFqPxj3G8SyD4hO9PPp4aRMAXqEohe8HscHb/Yo/ju5FgZ4Ybt4vdd39cYm0C6A9jcCLfW6pJmHP6B+/7oF4w5LEiF0xODEK6NvMuGNVZ12qbhJ2++GjoTeRReNITRM6ejae5nFaoTv18nKnBWqD2nmATPT493frzp7pQ3Y0V1O8fGy5KKlxQiUmkiZPd8ZDRwCiLMWkcTISq3uIq/7sz1vs8F4y/hqRXsTbFQt0eNelorKbbpUjxiDEbXRqtlTX1e80O4zyNQG0ZC7XVTa7xOEElk7icIJYz7WUlPJqQhmYrtu/3TFORiq/crLSwBb7q+opbHWUiXbYshKvCnihkpCZ7vv/BrgujFUdnlSFDhtAbb7zhc+BVV1fTww8/TMOHD6dwwPO22YH83nvvFYE23+fbzJkzxe+Tk5Ppyy+/FD+56n3hhRfSxRdfTA888ADFO4fDUelW5OUNG6SJsRqhZL57hWAUZcRqQerkxGp2YeUTZbD9XG72dI8/sXPAzzoY/PW6h2K+Z+SB0+zPVeYgwCoZoPZ723ovw+d+r161cFI5Nx4PH+mBcaW+37k66KQP1sztn43fnMKeCvJiVKpUumVShr+zgdzfI41UYciZ0XxRlddVf66w8YJqRvnC5NWiNUISyMjSDqqTrxrsxJq7vRvwtUGe6mSQxlU8WclTp2E4RcpIQxkFGImg2+y87WYCP9Sg+/pjNW8D/qxW79hfq92niT4W05XtU66H0drTbRzZxd9nVWoearKEr4HyWJZJXLU3Pxq9NtRz2WM/LPcxUQu3auoyZXwoj3ZlPpmjrRt2KaaKwBlSjZrQc7o5uH7hhRfELGyegX377bdT9+7dafLkyUJ2Hg5ee+01UQkx3oYNG+Z5TatWrejrr7+msrIy2rFjB/3vf/+jlJTok8JEo5GakfpKYMtjuB44rXtIJ/NA7tjBYFVtdyuZ6eSiYtY7bdUXH4jB7az7WZ1k+zL8mKAFm6i479TaC7SOhdlifJd0SrcLG/WwXD6cHNm2wO/+DPTZsxMxZ86lo6/TxFZasvczkC7BEhk8BwN/blISq/beyapxLJi35Okji/bo0ki1Jy5epGT+MC4iJv653tR8zylFyvdROjSz14H0O0ikoJs5pZf2ffl0ziZhPCUTaUxqSugXD9kmoh7H0Q5f07mX2eju7jSwCjSlpG3j4Nq2jLJdNqI07mM31xZq8lyVVkcT6hQXRqqD3ESOZ5W98+o0EB7PFW2o5zL2ElD7u3m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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "fig, axes = plt.subplots(2, 1, figsize=(10, 5), sharex=True)\n", - "axes[0].plot(times, states[:, 0], label=\"$x_1$\")\n", - "axes[0].plot(times, states[:, 1], label=\"$x_2$\")\n", - "axes[0].plot(times, states[:, 2], label=\"$x_3$\")\n", - "axes[0].set_ylabel(\"state\")\n", - "axes[0].legend(loc=\"upper right\")\n", - "axes[1].plot(\n", - " times, observations[:, 0], label=\"obs ($x_1$ + noise)\", color=\"C0\", alpha=0.8\n", - ")\n", - "axes[1].set_ylabel(\"observation\")\n", - "axes[1].set_xlabel(\"time\")\n", - "axes[1].legend()\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, + "name": "stdout", + "output_type": "stream", + "text": [ + "synthetic shapes: (1, 1, 2800) (1, 1, 2800, 3) (1, 1, 2800, 1)\n" + ] + } + ], + "source": [ + "key = jr.PRNGKey(0)\n", + "rho_true = 28.0\n", + "T_forecast = 8.0\n", + "# Generate longer trajectory: training window + held-out future for rollout evaluation\n", + "obs_times_full = jnp.arange(0.0, 20.0 + T_forecast, 0.01) # 0..28\n", + "\n", + "predictive = Predictive(\n", + " l63_model,\n", + " params={\"rho\": jnp.array(rho_true)},\n", + " num_samples=1,\n", + " exclude_deterministic=False,\n", + ")\n", + "with SDESimulator(source=\"em_scan\"):\n", + " synthetic = predictive(key, predict_times=obs_times_full)\n", + "\n", + "# Simulators return (n_sim, T, dim); Predictive adds (num_samples,).\n", + "# With num_samples=1 and n_sim=1 we index explicitly.\n", + "print(\n", + " \"synthetic shapes:\",\n", + " synthetic[\"f_times\"].shape,\n", + " synthetic[\"f_states\"].shape,\n", + " synthetic[\"f_observations\"].shape,\n", + ")\n", + "times = synthetic[\"f_times\"][0, 0, :]\n", + "states = synthetic[\"f_states\"][0, 0, :, :] # (T, 3)\n", + "observations = synthetic[\"f_observations\"][0, 0, :, :] # (T, 1)\n", + "\n", + "# Training portion (0..20) for MCMC; future (20..28) withheld for rollout eval\n", + "mask_train_full = times <= 20.0\n", + "times_train_full = times[mask_train_full]\n", + "observations_train = observations[mask_train_full]\n", + "\n", + "times_test_full = times[~mask_train_full]\n", + "observations_test_full = observations[~mask_train_full]" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6.4 Inference: NUTS + Filtering (EnKF)\n", - "\n", - "For continuous-time models we use **Filter** with a filter supported by CD-Dynamax. The **default** (and a good choice for nonlinear models) is the **EnKF** (ensemble Kalman filter). Other options include **EKF** and **UKF** (both Gaussian approximations), and **DPF** (differentiable particle filter) for non-Gaussian observation models or initial conditions.\n", - "\n", - "We pass the observed values `obs_values` along with `obs_times` to the model for inference." + "data": { + "image/png": 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JyPTOZTBgfmzBY3h0/qP4a99fKA/YfmK7maTNTZpbLuStLMaQEZyyewrunHOnNiZywJHMkkq+HWk7zuTHo+EltqaWnBlcHgzweA+yEEqFTFmMn/3n4D+YvHNyhVBpqCJKvdh64nF/+n7kF57766zGmUO5S7opHx8yZAgGDBhQ4vurVq1Cfn5+ie+3aNEC9erVw5IlS1y+Xm5uLtLT00t8lQcoi3v2bkeERCAuXJqpOWO66WheHgIsDQ2Nf68Ds0J6XrroeTyXYd8/+8v2X1AesOjQohKB9Iaj536/4crDK3Hg1AHxPLsgG8sPL0d5QVJ6Eubsm1MmiQrBJEVNK2kT30Y87jm5p0z+lkZg4Pj5lIee31l7Z+HjdR8LhQyT40C3u9w15y48s+gZoRyqCMaGROtqrRETGoOC4gLsTd97tg9L4xxCuUq6f/zxR6xevRqvvPJKqZ8dPnwYYWFhqFxZmoopVK9eXfzMFfhacXFx5lfdunVRHsCbmQi2BYvH6lHVSzHd8ZHxCAsKEwGW7uHT0KjYYJA/dNJQjP5zNE7lnQroa687ug4LDiwo0a8WSDj2vq0/KlnvcxFkLtYeXWv+e/PxzeWCpXEsZJSHgJ/n1vE6LA+gUoNjgyjnf2vVW2XyN07knhDFdBts6Fazm/ieTrr9w6Qdk0QSuOn4JpSlMoEKRWLTsbL5O4EEfTYU5uyfE9DX/jvp71Ku34EC1+Sy2q9c4WiWlJdzelDjyo3Fc93XrVEuk+6kpCQ88MAD+O677xARERGw133iiSeENF198e+UB6jqeUhQSAlWm2hWpZnZ7107trYZkGtoaFRcfLr+U+xL3ycCxt93/R6w191xYgdumH4D7vnrHjy35DmUBXaf3C0eEyMTxaOSmp+rMm2yrlEhUaLoyeSnPBQ1lbS8Q0IH8XiuqwmIPemSGawWWS3gSfd7q9/D5X9cXiaMP/vQFQs9cfvEMmG7VQLH4rra8/8tSTdNFwOdUHHk6pjFY4Tc+YmFT5RJIU1dE+fXO188bkndcsYTQ29hL4GnWV8gr+Ulh06rUBcfWizW1UCAsu6Lfr0Il06+1GSfz2RPd2JUIppUbiKe66Rbo1wm3ZSPp6SkoFOnTggJCRFfNEt7//33xXMy2nl5eUhLSyvx/+heXqOGdPN2hvDwcFSqVKnEV3lzLyfOrysX8d61e5sBCtE4TlbbdK+XhkbFBQNEBov2AUygMHX3VHO9+W3HbyXMmwIFlbRe1OAiU3Z4rmJ/xn7x2KJqCzOw2pxakpH11RyTSeWJnBMoi+uDBRlicMPB4jFQbB4/q7I4ZnsT0EsaXmIWCgIR9LOd4fMNn4sCCgtJgU6w1qSsMZ9nFWSVYuwDGeCTVWsY11A8/zdIWXkNnPfzeSKpCmSxa3XKaaM+Fi+2ndhWZkl3j5o9EBEcIZJMdV/6g4y8DFGICDSYsNpfU6fyTwU0llTFVoKqjUAV1b7Y+IU41zy3n677FGcKx7OPm4UwxXRX9EJYbkGueI8sApYHxdfZRrlJui+88EJs2LABa9euNb+6dOkiTNXU89DQUPz112lTm23btmH//v3o2bMnKhpUEKzk5cOaDMN3l3yH989/v8TvqQo4gwsNDY1zAzkFOfhy45eCEQsEGHwez5EbvuqFDZSPg6MM2Z6dCBQUG9GrVi/xyMTe3yCS55ZyexpwBZKdOZAhe4zrxNZB86rNxfPtqf6vr++vfh/XTrsWAycOLNHjHgjw2mCAzyLtBfUuMN+Hv+f4520/Y+SUkRjxxwik5ZQseAcCKqnqW6cvIkMikZmfiV0n/XcEXnBwgfmcydXCgwsRSDgmbPYS3UAhLVee7yoRVdCgUgPxPDUntUw+h3MJTKh4LdO0ioWTQMFR+RGotdmZOoHjXFVs5miu5i34eV/2+2W44JcLAt5+oeJGXl+9a/UOqPkbW6BO5p4Uz/vU7iMetxzf4vfrMvFbeOD0/UzVF13jzwRO5sn3UyW8ilkIq+hJN4t/3Ee4h9vHIBrlPOmOjY1FmzZtSnxFR0eLmdx8zn7sW265BQ8//DDmzp0rmPGbbrpJJNw9evRARYOjvJzBVLuEdggLDivxe2php0RUQ0PDtwT53r/uxag/RwkJYiDwwZoPRK8nX5eBsr9QGzuDo8rhlQW7Fij5sJLHnVfnPPG48shKBBKUVyqGgOtV1YiqKEZxCRbEl4Du/r/vF0zHooOLAiq3Vw619NFoXqV5QAJnBoU/b/9ZPGdCoZ4HulDAY64RXQPxEfHiHPsz0obM/Lur3xXPGXAxGQr0dZF8Klk8rxNTB22rtQ1Yv7/jvfHX/sA60KsizKAGg8TjsuRlCDRUwhIXFoeo0CjUjK5ZQpJfEcFe+XlJ88x/T9s9LWAFNZXwqZipLNovFNPN+5BKGfF3U/1LNL/YJFldFqReW/4aAj13mqgbWxftE9qL54FSbSgVCxPUTomdxPNAqAu4b3B8HpUEfG2up2VRQHF7T4bHmUk396CyMlM822CBgyoLBSqeNNtdQZJuK3jnnXcwdOhQXH755ejXr5+Qlf/222+oiHBkul2haZWm4pHBlZrtraGhYR0Td0zE/APzRbDxvyX/8/vUcZMiQ0gwOf5ig//Jigq0KWnrVqNbwNg1BiyqKHBpk0vFI+clB3JjZaCijCGZDKo1y59C4T+H/hFSSIU/dv2BQEFV89nGowJnf4NFqgcYNCvM3DszoL2e6pgpRSbMc+yHVJRJiX3ANWvfrIBeF7zu8oryhFFY9ejqwhE4EAUOe/XGTW1uMs9/oI6drM+hTJmsjGo+yvQoCPQEEcV0VwqXLXHnIrNGY6m3V74dsHn2vF55HmPDYhEbGouM/IyAXA/27ReXNpbrXKDN1LiWqs+M13PL+JYBYXftWV1e14FszVFJN5l5peoJ1OurpDvQr60K41zjlKqnLNRZzqA+XxbCWAQLDw4X16s6j74gkGsqJ4PQhd6+/cXfa5r7FNdom80mimI5hTk41/DDDz8gMjISycmyiEuQlG3Xrp3w8jqTKNdJ97x58/Duu7LSTtBg7aOPPkJqaioyMzNFwu2un7s8QyXQqqfbFSiBpCyPwYvqRdTQqOhgMqDYU3/x6/ZfzeeU1inW0FfwNew3ph+3/ei327gKtBl4d6/Z3fw7/iI5U25S0aHRQgJI112yKiqpCGRvKlmJ0OBQNK3c1O+WmHUpUmZ5Xl3JzjPICISigFDXFZNuFSwygLRPQL2FYmIub3q5WK95rLvTfGf6XR1z1ciqJZJuf86xGt/Vt3ZfhAaFinMQiP5URykuCwV8/RZVZIHD3ySLn5OSrV/X8jrx2rzOA3Xs6nrm59ipeieRIDI4DUQLgjNWjcqWczHpZrLwf/P/DxM2TRDz7O09J3yFartoVbUVutToIp4vO7wsIOeSCTwxsMFA8cjrgUlKoBUyvC5YMGhZtaV5PfuaWFFhopRIiom2Hw0YqMSYRr1qrWN7RyBmT5d4bUMxxGvXXym42puY9HZM7HjGTCOZcCojOBbCGJvXr1TfL/UJi/Ndvu2Ct1YGZgLC68tfF/PWr59+Pf7ef9o53hfwmiWzTSUgFbehtlDxnIU2Fh7L6qvYh3tl9OjRaNasGV5++WXx72effRZz5szB9OnThUr6TEJqkzXKLdOt5OWuwBufQSwr7QywGsU1OkNHqKFxdjB732z8d8F/xeL8wYUfmP1ivoAbCIMaVnLJalIKyNEmt7e7PSAJFqXaQgJ9aJEZ7PkCZW5WL7YeWsW3KmE6FRzkXg3jDkreywCGwSLPwcbjG4XE135iQiD6uWk+E6iWGCVNp8Ekkzd+bvOT5uOyppcF7HiZdFNGSLk2kziur52rd/bpNVXyyxYhBqNUKfDaaFJFGrUFiummkoBQhQ1/zrFKUhnYsqhLCTUTqwZxDQJ6zNWipDGoUhXwXPlzXat7hW0MCVEJIlnhueZXII7dvv2A+y9fn+eFe7Bi6wMtZSUaVpJJtz9tGYEEEw17Ro0mjP6sxY7FRX5Wc5PmYnnyctzc5ma/XlcREqr9gmsb70Oqm2h6FshxUnS2JivIe5tKRbKjLGTy73oL1cPNIhr3D/6b96G/58MZ010rupapLuA1ppJwf1+b55rnhMUjngvut63jWwfkmNtUk/Pruf77uxd6girQ8J5noU1dp1yveN32q9PPq9fjxKEXl74o2oC+3PQlbmx9o7lH+uroPmX3FPPfX2/+2lQC+AIWGAb9JttnziSWXb1MtNN4A95vL730EkaOHCmI2A8++AALFy5E7dq1hfn2gAEDUFBQIL44Jeu2224rs+Mv10z3vxlW5eVEIOSaGmcPDPKf+ucpPLnwSTPQ8pf1+mX7L34ztmWBQLRAjFs/Tki6KFnmObOX7XoL1b/MAOOK5lcExBlcyRaZoKk+ac7ADkigH11dOGpznBXft78BuGINGMCopDDQc7TtmeMSSXea/wkhe9xVoB+ovj77pJtQLI0/0kiVdPO9q8Q9UIZFRGp2qploir9T9bTBpq8sm0pe2e/Zp1YfU9YfcHbeOGayRsrx2R8HfXsjPHuGMFBsmOrbZUJPqAQi0DOZXTHd/vhOkKl6c8WbeH3F636PWlK910zUiKWHlvq9vqv1jO+1S3XJdDOx9/d1VdJdr1I98aiStUAypBwtqBQ9BKXHyuHa1z5pdXztqrUziwM8H4Fgoh0LSExc1LoRiN5re6abrx0oU0qlzmKhmOs/90KuGWVdjFL3Y6UwyXITyuDQF/XJGyvfEAm3gr9mj2zxoBSc8QFJBO4v6jP4N2Do0KFo1aoVnn/+eUyaNAmtW7c2/cIWLFggDLmXLVsm2PDjx8vOEE4z3eUUypjBSuXOlBIGWN6mUfZg8njzzJvNRVtU7Pq85PPrMci+bdZtQr7KTemnoT8J91tfQKnPy8teFgv3hfUuxLWtrvX5uJggjlk0RkiehjYeiv/1/J9PVWkyjsqYhgE6A50ftv6AW9ve6tNxqX47BuZdq3cVzznXlxI4Bk2+VpxV4Ejm8avNX4mEkMkPP19/pLg1omqI80bTKcoumRyr+99fpptom9AW2BrYOdr2o4+IRpUbiaCA1ygDf/sRiFYTB8V2kA2jlH/chnEBMYATEreCrJJJd9XmouffV6k2JXp8r3zPDMKVRJHH68814ZTpNpgSjpJkYEhmiedYJYi+XMd1K9UVgRyNAemaz+OnKsJfqHYAlXTzuua1zL7VrSe2+sxK2xcLCGXQ5ujSHwhG0z6BC3SPsNk/qphuI+k+cOqAkLo6mqpawTur3sH3W78Xz+fsm4PJwyZ7zSo5Jt33dLxH9JHyeMnE+qoGcWS6eS2QUWS7ACXa6jz7ArKKSilEtIlvI3wVAlkoUWP17Pdbqje4bvD4fWEd1TXLa5j3IO8V3jf8Plsb/AHXHsd1gwVGJmuiwCjrBX7fJywUq9cmS+9v+4g90801g8ovrqUsUPizF3p7P/rT8sFrWhXiL65/sfDL4P00vMlwn49P9bWPbj4as/fPFud6+p7pPsdGXON/HPKj2G+5B7C4wRyDhQKqONi2UxaI9HFvmTFjBrZu3YrCwkIxYlohODgYUVFyjcvNzRXXfVmawWmmu7zLy22e6yaq0s5AuSI6C7KqqxZwf2XJHL0xeOJgv1x91aLJ+ZD+utbStMp+waYhlD+mIJ+t/8wMZlkR/nHrjz6/Fse10BWaG9prK14TyaivoOsqNxay05N3ThbPfYHaqJgkP9PzGVPW6Cu2p51mIMm0MUmmlNZXBoRJm0oyyap0SOwgWkT4WTBY9vU1VT+iCvQVI+3vCBlHprt9tfZmMYKBfVkwx9xUFeOk+hW9Taq48TMgJ6vUIaGDUATxHPtjaGPPvvIYVTLir4O5YhuY+PJ1+dkxYOF5CZQPh/38WCIiJMJMMHwpFvCaUwE5k1cWCxIjE0UxKlDsoFqnlCSeUGzY1uO+B+bqPqMjOqGSNV5rgZh1rNhBdS+qdg8ybYGcpazkrCrI5/1DVplsli/96bw3ftr2k/lv3i8sWPoCMs/qOqDSpGctObbVn75uFqCVSoHJDItGnRNlAs9ijz9Q95kqxKg2ALbSlMWINwXV1+2rmZr6nJnksDjXtUbXgPW5sxCu+qvVPRhIw7NjOQ6KIXVv+5l02zPdZaVa8DRNQEEl+VQGeGOMyWI5Y3xejze3vdlU2Pna7877UcUC9HxhIk/429fNe5B7Cdn9mLAYxEXEiX8T3B/L4svmQxF69erVuPLKKzF+/HgxfvqZZ2RsqECJefv27VGnTh08+uijqFbNu0K/N9BJdzlnuk0jtZyTQJrzAI2bflhQmAhiAml0468hyrOLn/VbVsukdsCvA8SMyo/Xfuzz6zDwfGT+IyLwYlA2ZvEYn8c8sLDxxMIn8OHaD3HrrFuFXM9XqEXxsiaXYWijoX45MXMTVezDtS0lK82k2ReXZAaPihGxH4PlC7iBT9o5STB9qjJsH/x5A/b4KQOtC+peIJItJmG+yqiUcQ83Ty72/kp/1f1HRoIbFTcRxbT5Kn9WQT7NzrjxBVIGrphu9vMpSS4TWQbAgXANdpZ0E+o68MVMTDGwlPbxM+M5VoVHf9luFSg6SwS5dvgic1VJoOqRp4JCXROBkpg7S2D9GVmk2GImfLyOeZ7VNRcoxtiR6bZPUvxhje17SRXTxgSZ62AgxiGZSXekTLr52nzO1w/UPePolEyoPmFfP1O2HDHQZ1D+Qu8XzO/5sj/w+uAaQbUREwea7fmbdPM1WZRlYYpyZ0KZqfl7nzjKyxkzcT+icspfmb0j063aAQjTwdyHz4tFT6VwUteymlzBPnd/oYpqZDDNAqNKuk9s84vA4f81vTyMNYnmePb9176AcYm6L1ShuCwKKG7l5cY0AYIeSrwHGHt5E3uvPbpWPLJgzPPC9YMKIl8/VxareD+qgjZVFby+uVYrU0lvwbVCrQ1KVaNYaKXWOhewd+9eDBkyBE8++SSuuuoqIS+fOHGiSMQVKleujHXr1mHPnj34/vvvceSIvK/KAjrpLu893ZTg5mcDH3YD3m0H7CmdxPKGUNW+QI0K8AeUbF097WrBQHKWrq89smS37/v7PjM4G7tuLNamyMXKW0zaMUksIJRdqmTlm83f+PRac/bPEXJTBcqH5+6XyaC3UEkyF8krmsmeYr62Lz1bNGdipZRB0H0d7xNJGpNRsunegmZi3EjI/k4fMV2wtUuSl/jEditWmxL1cReNE4kygyiV8Hqz4apNib3STEBVIsB+Qm9BR3HVn0npnn2Q5yuzsi9DbryKZRSvafQm+pp0q2NUzBqhkjY6zfrjwKtYA2XyY59cBaqv21nSrfq6fZGxq3OsWCtCFUv8ZcScHSv/DoMN3lsq4fdVDqng73XmyUithOzZBwmtvXGfgmg9MNovApp0G47r9v3XDBZ9Dcwdk+5AS8wdmW6iVbVWAZWYM4BWXhX2SZw6P77sg6rAO7LZSGHKFRMaI/YHX9YlxaqxsENioFetXuLfLDr4qkpTnxsLf4rtMougKav8moXsKC/n3qgKf4GSmKuebvsiklLJcA33droC12Yqerj2qPtaJd08/5T9BtLgUu2DyvxNXee+gHuSKlCq1+f59rf/Wl0jVHwoMzO2CihiJVDqLCvKE4JxkeqD96agp6Zv8H7mtd6/bn/xb/u40hswDlCFaN6P3L/Ueu2rclLFoHyPivzj50eoFqyzjdTUVAwaNAjDhg3D448/Lr7XvXt3DB48WCThjqDsnIw3TdbKCjrprgjy8n2LgVOsVhUDKz53+vuUsRK+bKBcvCkzowSYyaM/FU4u1HfOudOshPF9kBX2pTI278A88f+4EQxuOFh879Xlr3pdmef7YaJM3N/pfozpOcZM4n2Ro07YOEE80uFaMcovLH3Ba2kQK5CU93KT42bKBZiLJaXrvsxgViwDWQdWrpXEyBfm/M/df4pHFgIYBA1uMNicae0tVGLRt05fwTqpMU8/b5ezrK2CST+l3wymlUGNMpfx5Xyp5E3INo0NXCXIrET7UvjYd3JfCUaF6FbTYCcOL/fp3nIW5DOQUUmnr7I6BkXqte0TwjORdJvn2YfkQSW+alyLfRKrxlwF8lgZcKgigS9MprMkUCUTq1O8L4g5goGmGmdmH0Ar2bMviaBiBpUZmX3iGqh+f2dMN+9rJhm+mgRyb3BW5PAnWbVyP5pmagFKuhWrRrZKrU2KGbNnyry5rnk++Xo9a/YU51jtqVQheQu15qi4g9edOge+FtnV56ZkwyqpZ6DP69uXVhRVrFUJsf01Eehe/LSctFJFEhaG1TrlbcvEwQxjznV0LbMIwdfidceijLfXgMuWFLtCHVU4yhzMH9WGWkepklEsKQkkk5X2cc8yx4XFnL5GuK7ynHM/C+QMc0/GhgqKwbeadLN4pNZQdf+omIgkjC8xglKMqbiI6F6ju197ImMtgmM+FRTTzZzBF4VMoFG1alXRx/3JJ5+U+P7UqVNFjzdBVjsjQ+6PnNlNU7Xmzf1z5ncHnXSXU6gqoWC6j9ttNnv/YRZZ6veVg69gSYusJwu8eW6ccaMwzPp2y7e4f+79eGjeQz5XDN9f/b6oklKuO/fKuWLDYHD1x07vE79/DsgkklX5x7o+Jirz3CBVQmgVXOCZ4HLzZkV+ZNORwg2UCb23MmcyQGRLGIhf1eIqPNj5QbEJso9XsdbesgUM6Jkk87O+qP5F4ns0efEGXKgXHZTzO3vX7i0ehzUZZr6WN0UPJptqU1RjMEY0HWEy4N4wq/y7il1SRmVXNr9SPE7ZNcWrHkhVHe5dq7cZhKheQrYheLsJmAmyHZunzGp43L4kFypZsU8IGSizh5fBui89vIrpVpJLBX/7unk8LIrx2OyTTDPpDlByZSayxmgoexmxL/OvHaWiKoll8Yqv549jqzP2x16qTYMvf+XlKgnkGsJj9VX+55i8skBrn6ApCS0ZM29n2jtjuplU8Zh53SjZayAd18V7CAo5ndz7UPTh+2SwyONUBk6EmudLJZi/stmU7NJJtz+qAmdIz5VrLD9Pe8PJ9omyeECVkDf3jf2UBsXUqTWdhmreqmVUcqPuC8e12Beo+8A+6eb1oD47X1tH7Ntz7O8PVSQIVC+w6V7uYFzqa5uHuW7Enl43uO8FSmLuaKIWiGKdq4kVCoqV9lVx4tgOpc6J2dddhhJzx3YPBW8LCWSlWVRkPKoUdmz5YELLvd6XYocqUNon3f4W+1UOwNZVBRZQuLby9fydt36msG/fPvTt21cw3Hy877770Lat3GPKAjrpLudMt5B1pNsFkVnHS/7bQKfETiJ44ebpjWSRzDEXV1YkKf8l/tr/F57850mv5VysBNItkRjTY4xYcK9vfb34N+cQevN6TPwUe0nmlq91S9tbTKbZm0WETo4qgaQJBBdpdVwz9szwqk9z1l4plaahCY+JleFhjWVyO233NHgDlSypJIewN8DwhmnlosvgmgukMlvhNcFAn1IglZBbARd9LqgMzlTVm0kNNwgmo3/usl70YODMIhADVMWakZ1mUnoq/5S41qxCBS0qKCC42XLzYsDjrVmNOXbKziXZ36Bmb/reUkk3rzn1GfuiRFEJTqmku5p/jLRiligtN70jjMCIyRoTQn/7HVnUU8mBfQBWOaKyKWn31uhLfW72CSEDahX8+BOMugoW1TXny7l2xrzyeFUw7m9LkAqeuf7bf44lJLReBtBKjmsv4WdhUAWJ/hr4cf12xnT7W/RRBRfeK/buukywuFZznVD3qC/g/1f7hXLjt78++NreFpGsOiWr65IGcZQdeyPzVzGBUpioc8LiONf62XvlHmkFLG6qe1bJp1XioBRJvgT5jqaOCv76bLgqWtoz3YEwoDXdy42RYaUKdl4mU87WOcLcn/xU9bha69Q66k/S7UwxFAjTM2dMdyBe19eebvtCgtVedVWwYr+/KqhxbaIChfCWvCGUMbBa7wNR7Ffknf2UBOWhQmSz7bUcoFu3bmJcGHu6169fjzvuuKNM/55Oussp1M0r5OXpsrpn4ljpIJU37/l1zxfPrSYyrCwradkb/d7Au+e/i0e6PGKyo45GWp5AV2qyDGRulZyPBmEMHFi1VRJvK2AgymSRAZkyIyFDygSLMjOrCxM307/2yfMxoP4A8/tMwHlcXMS9kdcpBprsu4J6XSF/9kIhoAJ4da4IVvUZzNGtmq9nFWoD5hgRJQHiAjmgnjw2b869kq2pfiP1WmqchTeOmCrJZCFAvRYTA3X+vPkcnbEr3FQoW/dFRu8sQbavEPviEOtM+kyoQogvgZL9LFV7qOuG15EvQaPq57ZnDZQkUlXM/e3fVQkhgwo1z9efYJRFH3U+HM+xktP54+zrKlhUgb8aJ2cV/FycyctVUSwQJlGOzuX28FX2bDLddmoC+2P217BO9HwWFzhPuo1iklK2+FvgUBJJdb35E5irfmUes73skv9W95GvTtVWpKz2klRvCh/267AC1+NBDQZ5HehT9sy9mQVe+4Ilrw3uPbyHNqdu9nt8obOk25d1zlXSTdaf8RWLP2otDEShhAVFZ/cgPy9vjt/VXqKKG7yOVd9/oHwgHBNYX4sRrhRDSsWy48QOn3rS1TXiuJb6y6Bbwcm8k04LYd72qqs2CVXAVDAl5ge8S7pZBFMTcJRnkWOx3xf1iYplHUeDnYtmaucSdNJdEYzUjF4hEy5czFXyx6TbSsXt953S2ZrV7161pRHKDa1vwFPdnzLdqlXw5QlcnJVU++oWV5sJFqtilGETX2z8wvIirvqTKSVW7A3Z+NEtRovn4zeOt/Q6e9L3iCofAwTlsKoWjjvb3Smev7f6PUvyOrI/rGZSxqpUAUoqy0SZi5By17ayoKkeIHum21eJuQrcHWekqmtiQdICy8y5CuZU/6AC3cJVwK2CQk9Qwbk9w0KoAtGiQ4ssFSqYaJFl4rm3l1ARqhjA8+VNkKCYBMegpkeNHuZ58GZjYU+fCrxcsRNqXre/PaQEDVyYzPLa9XWEkDPWIJASc5WkMIl1HAXiS9KtAlGuBY7Bj5K30lTP32DRMenm58l7nEVFb9huBrZM0rmGcca6PdScXX/7up0ZkjmyVpuPWU+CeD+qJMSe6bZP2nw1BXQM+FmIcZw3ra49X0wCTbbUoZAUqB5eZ6aGgWQIFdQ64siq+dLXzXOokgEl1XYM9FngtbrW0dma4DpM+bcCP0dlqDY/ab7fo6DsPzeuc7zOvZ2HXEIpZNduQPA11cgnf/0reO7U+XNkulkc9WVspGnK6VD4YkGJSSdjRH8Kdq4SY6oXVDHC19YXZ1MgCKqb+D0W3Hzyx1BMt8M1IggC2MT14Y8BnJWWD0d5uZoVbrWgp1hpxziG5AHfA+NCb9p3eF3lFOaI5Njeg8Pe88YXMzVnTLd90n2umKmda9BJd3lPum1Muo0EJ6a626SbTA8r41xMPbG3lMj9uuNX8fyyppeV+BkZZQZX3ESeWfSMpV5Zys2YoHMjUwYtCky6+X0uJlaDtYUHF5boVVe4rtV1YnFhQmTFFGfhAfk6fD9KFqMwqsUoUaVkAvnzNs+mXjP3zTRfy56dYTJxebPLxXOrjujccLio8fNyTNAubiAl5jS1s5IoM8FQDuWOSTcDWGHOlp9hiWXlaym5q2JUFOpWqitUDLw2p+6e6vG1WMlWwYw9w0Jwk+JxsVJvpR1CbdD8vNScSPuElmM7GMhbNdvh+zTl5YaEXoEbFzd13iPetGoo5pyMiuO1xs+BhR/em97KW81AP7pkoM/7wJ5FCRTTHQjpuhUWVrET3sirVRHQsVCiAi8GBLwOfJlN7S7p9nWcnJI7M0mzZ0btEyD251otYlk1RPKH6eYxO7omK6hzwPvMn2M2+7mdFAp4ragZ296y0ipJUK0L9ghED68qIjlLur0JvC07JTsE+PZ93WLWr4XiuuozZ6Lm2G/ctHJTcf+zMGR1AoRKutV4KXv0r9PfJ4msvamjY0LFoF8VYnxRWLhiuu0NGH0x4nRmosY1mW0d9rAfG2m19YWfq5pZ7mytU2y3P8UvdQ86rs3cX9VoOl97pF1J1+2nY/hSbDR7uh2ULFQXqPvbV7duy0oGJ+oT9fla2ctcMd32juPeuJirJJ7XiX0RzD5+5vXtjdcT4yMVe9r3dNsn3SzO+jJCs6JDJ93lFGozlUy3EdzUaOs26WZQR0dt4sM1H7o1qaLcmAEKk0d7qTRBVub5Xs+Lm4sB5vdbPMvMFcPLvhTHhIN/Q7GRVhyreVxcmOxHkdgvTP9p/B/xfPyG8ZaTbiVBtgc3yJta32Qmy55ko6qfWyXF9riy2ZWiSsnkx4ojun0/tyMDSCaDwS4TZSvBAKu/NHJjdVqxOQo8h4qVpwmaJzARZfDDc+P4WsTlTWVxgaoGT2wipV5c6MkQOhYWeFwqQLOiDlBJt7203D4oU6yh1bnwTMzYU87PzLE6zM9DbVbeBI+ukniCRScVLHsTKPH8qUTQWdDoj9O4FaabCYQ/o3rUsdv3vyrwM+N1wPNmlVEx+xwd2B/H68CXIJrFRVeSyxJjybwI/E25s5PCBtcyXitMcP0ZHebumJkYsXDL9cGqwZwqbJDldlybGKCr69sfJ3BX/dz+XtemGZeTa1ox0WxT8TVYVImhs+s5kG7YKsB3TJJVsE45K9cvK0VGdTzO1nN+vortttqCpNp87Pu5Hdk6KsK8YeuYGDszdQxEX7crptuRCfSnrzs19/T17HjP+NKHzYIo136eD0eFjH0R258E0926YRbrfDQGdJV0l5jc4OUoUyaBXMecFWbslU6+uuf72tNN9KjVw1RouruOGJOrddiR6VajUO3jVl+dy+1VmCwScK3wplWM1x73JV7Ljok8/63Yby0xLw2ddFcIptuQ2FU3Ns0TrqWko5uPFsESF9QJm+RoK2dQjOyo5qNEQuAIJiKqv5syc08yP5U4nV9PyoYdoZJuJkWeHKuVtJzVQ8f+KOLmNjeLYJ29L+5GRHAOM+d7EvbScntc0ugSsSgxCPxp609uZa3OpOUKCVEJZsBvJbl11s+twEKLSuyn7J7i8bVU8MuEVFUh7TG00VDTNE5V5F1BJStk4Zy91qWNLxWsMuWKnthVlVySTXAWiCiJOT9HTwGPYlecJd2EKhz9uv1XS8oMJVNmxdzZ9c+56eq6tuqKrhhs+z5Hf/u6Gbxw8+NG5yxB8cfB3B3T3SiukWBsKCFTM0B9gQqSnAVfdBL2dsyQ6VzuUMRRUGY03vgh2Cc6KhlzdryqRYK9xlZbNVSA5VjYUVBFRbZZ+JvAOlMT8B5Wa4xVM0VnzuX28KewYTXpVsfsbTHCZLqdJCosFjBZpRTT1znB7lhTe0d+T+usVVMuxxYKgmuBOj9W7hvFvCs2ztXaybY0K322pomaE6ZbsHXG31lw0FoBlFCsLtl4e7d2x3uPBS9vk2O3THf1LuJ8snBttZXOqhO/P+1Fan/iuuHsfHDdYAzEfVGxv96Ax+BWheSnG7grxZDjuERvJo7w3uZeyPjD2XlWaynXpUCPs+J6r+TUzphuXkdca7nfuZPNs92R4PE7ew9qWgzfg9Wed7U/2/dzK/DaUcUIFVe7Q1GRPG9qf2PRx1nsptQc/ngKnItQ798f6KS7IiTduYYbaoKxyWW67lkh2/1Q54fE8y83fmkGN/ZggM6kjzeUGt/kDJzRzKo6F5sftvzgdjGkdJwVbrVoOILBNTdUVsY8sYdqcXCUlitQRjOwvgwUPt/gfG65Mo9gEM3fd8aMEUy47u5wt8neulqsZ+2bZW6erjZWmsYRP2790aOUx5lzuT2UIzpNyzwVPFTS7SgHV2CAxoCQ/ai/7fzN7WupyrliABxBky1VEPhtx28+9XMrqDEZvH48JY3KnMhZoEewpYEbAXvmrLBjrvq5Ffg58/W4iVqVi1p5TW/7uk1peWRiCWdqR4kyA2Fn97or8O+76qFUm7UKvLxlJKwGX/bFMKsKBRWMurqfVYCx6vAqr8ceKhbT0SRLoVHlRiLgYtJmlc1USbejHFJBrXGeGBJ3UMGzq3VJjRC0mnSrc+zYz63Qr3Y/rz4zX5JudV2Q2fSmr/twlmt5Oe8flRD6OtZKFZGcycuZIKtChdWZvb4Yqdl7dfyw9QePCYZav1SByxHcN1h4YwDtycSJzuzqmlaz6x3Rv25/r/u6zaTbbjyWPbhPMjnmPepNX7R9IcZZ0k1VnuqR94c19lhESmwvZLq8fqy0F5mjJ2Od7yX8O+q4vTXeIhjTcR1zxXSrtZ9eEL4ksO7WfUUO8FqioZq3/dy8t50lgoxzWFTjZxHoed3KRI0xLkfXOoLMr4qZ3BVQXfVzK/Ce4nXKz8ZqcV4VEBtWPu1c7myPcXdcYWFhCAoKwqFDh8Qs61NZp1CUX4SgwiDk5OSU+gopDBE/z8jMcPrznHL2lZ2dLd433z/PA8+Hr9BJd7l3Lw8GFDMcZwRBme5nrtKxmkkWb9xx68e5ZLmHNBriMhgmuLDd2vZW07jMVSVYuVmr/mFXr6Vk4R+v+9hlUspAWW1+rthp4ua2N4vHGXtniC9nUC7u7l5HJbg09OFG5yxQYOJO0zlX0nL7xI+bIRMldw7yDByY8HABd8U+sD+QBQ9K3j0ZqqmEVcmXnZ17ZWZHNt+VXJjvU7HTKnlxBiUxZ1+3q/m/3FBVf5PqP3MEe8eUasDd7HVuoirQUmySI7iJK5mkFQM6ZcjjKkHmJqquG6tu7SbT7UReTvCzZpVeBAUGc++riZoC7zcGMWQAvJHV8Rh4bfEadJagECqI8GWEiRWZIdGvrkzgeOxWkmTT0ddFMMoeVf4trn3eyp89nWsmbaqAZJVJp9OzM7ddBapAGIxzPfDFJMqTTNT+c1xxZIWlVgFTXl7JedLN+5nFYK6XvhoteUpS+LfJ3NBwyWqxgAoqlay6uqaVEouzqf2Sl0eVlpfbJ7b+uii76x8lhjUZJoqCvG7c/S32oHM/4rVrP2rRHvwZFV+EJ68OxXIzMXDGwhOqbYhsnVX5qVrfVS+/s/VdeUB4o37g31fzs521HNjfH2Wp3LBvL7LS1+2ujUZB7Xf0fvE1KWaS6tgOqJJCkRjnZ3hteMY1Rp1zZyw6iyeqYOBTq46LAiYLpaqw7Y9yyJ2JGtVZzpQH9nGOu+tTFeNcFawYq6n7x8oUIhZqTXm5E6bbXgHAv+0qXmOi2bBhQ4SGhorEc+++vUg5kIKjB45iz549pb74M34l7UvCrt27nP7OnnL0tXfvXvG++f55Hng+fIVOussp1DiVYFb0DNYbccaGxDmgBa77j3njqt7ub7d8i9dXvG5WK2naowKOa1te6/E4Lml4iQg0uXk9/c/TTqueKulVM6Zd4fpW1wtnTyYnHC/mDFywWIVl4KxGhTkDE40bWt0gnr+36r1SPXoM4JXk3V2iTHDTuaL5FeY8cUewCMBjpmOyu9dioqaUA5+s/cRl36BKkmlW4mi6Yv8ZUspN/LLtF5fVZgaaKoFzdBt3LAgwgGO12NVizkWZmyw3FlfJrWJXmUCSOZ+4Y6LT3yFzx/dP4zNXiS2h3iPnu7vqqVfMNSXPrgI9QqkfqErwVJ1XvZCuNipCFQT+TvKcdPPvqYTQVdLN60NVna2ON1P9iK4SQeXwb1U+pqBYbvamOmN17d8/E0y1sQdSXu7o/O8pAGO7SEp2ittglPeNCqK97e1zZ5KloD4/qz13KplwlXQzsFVtB96Y51gxRFJgssWiIgthata91Z5uV2oXlcD5yhirJMVZz3KppMLiRAjFcnNN5RrmDGoCAwuCvsygV/ejq6ReqY18aW/wJulmEqeCc3czthXLzbXTWXKlMKThEHMNcdeLbfZzu1AcqYSC54fruVXjMFWccnXN+drXrYpC4ppwGFmooArMHDXoq3+Fp6Tb275uk+l2s3eq9iwW07ydDe9OWk5QBaladbxdl5hwcz9kMcfRyd2xB1oZ5vrjXG4P5d3jjwrHm3Fh9lAFWa4trtqPVCzjimwhBjUcZN7XnnyGWARkvzaLoK6uFVWY97Qukd2tV68emjRpgpnpM/HaztewO2i3SEIdv5o0boJvD3+LV3e+ipTwFKe/07CcffF98/37w3ITOukup1CLf5C95DC2BkDmm8jywHbXH4D7Ot5nMts3zrgRt8y8BZf9cZmQrrMq527jtA9iX+j9gqiIsgfnq01flao+cpEhY+ZoyOYIBkKqGEAG3tnCpKRSDCicyWntQVk4F3UGtkza7MGAm4sRA2hnfdOOuKblNaICy/eoWG0FxcJSGcDE2x1YyODCzD4bV6yBqoR2TizpNO4sIWVQzkDZlcSXI524wXEjchUIKlaZ/fuqR9+Z0kBV+umC76qa68ic0/XdWXFBBcoqcHYXiJA1oYTUVXCtGEtPnyPH3jG44kbkSWLuSealEixeE2QgPfWAMmjkBknW0hWjYj8p4M9df1pyEzVHILmo7qvjJBYfXGxZCuhJzkmwYEK2n69pxVvAXdLtihnkPa5aUjwFSuozYJLuLvhRlX1vk253JlmOQR3ZRU9JG9dwVdxwxeDZB89WmA13rJKrgJ/XsFWXZq7JKul2VTwizNFQPhYKPLUd2K8d/xz4x9K94q6fW4H3JtloKkOsJvMK7LFU59qZVNleWs090Z++bk/yckKNlpy9b7bL1gTVk+tKWq7AAjCTWq7lzgrPpfq5nZioOWPrrEqfPTHd9kk3k1arrRj2LTTOJMnq3KiilK8meO7G9inYFwM99et6aqNR3iG8R/mZWVWDWFXH+NomYJ/Q89p1FUcowzAWZaz2BXtiugmlTiOx4a+vgj3Ua7m7Hzl+jnsHSSNnexmJIKUacNVWqK5zxq0kQLj2WennZrHKcbSXs8K8p+uE9wjZ3q3pW5Gcl4yEuAREREQ4/WqW2Ez8zoKUBS5/J6IcffF9u1ojvIFOust5T3eIubfYAI5KiqpqKekmmOA+3u1xUbVkEKAqrLzhn+3xrOVjoZnHf7v9Vzx/f837Zn+tSuDM5MmJO6gjRjYbKRYmboa/bP+lxM+YeCkTMmVk5Q6s3F/f+nrx/J1V75RYvKftnmay756Sd4KLnJJNv7L8FTOA40Kv5MXKkMwdmAwoBp7FDsfCAoMFxQ45jtFyBKvQKrByJaFXUnxlbuQON7a+0VQa0HDMESogd9XPbQ8y/kpK71hcYICsNgvFLLkCN2XFdv+2/Tf3c8Nd9Kzbsz9WJOZUB6hk1nFshyOjpyRjniTmW09sNYNXR7dPx2SF543B+5ojawISaFC2yD4zvqbVXlJPbKbCpU0u9WkGukoIVQDGnnRPiSxl7O7+hpVCiX1CyGKVYq+tQLHo7phu/kyxvJ6SNibxDIh5Pbh7TSV55nXu7YxZMqIsirDo6Y41VkHXX/v+8ihr5d7D4pWrxNL+mMmMemJjnEF9Lu4KHGSDuF4x+LTSKuCJhXbsh/a2yKH8FVgIdVV8paKBwTc/E29YPHvwHjhhJHGVc10nJOzVZzGca5mngqU7Zk1BFcS5N7gqKCmmu1lV5/JYBbUOL0haYGndsFIEZOGI556xA4vN/o6Qs9+DutXs5pfEXCWx7phuxl28PkgGuNtPuGaY48JctNE43ofeFpA8Md0Ei6GMnViIUHJ3f43r7Au69D9grGC1l96dB4l9UU3df/8csq78ssp0O3MuV+C5UjHi77tKEjdqP+L75TXirrgk2j0aGu0ee9y3e6iWJCpZ3EH5erDgY8lo1oNhaYnXPLjYL+f/igaddJd3IzV1g1AaxipMlMEMZFqTxpHB/WrQVyKRIoPJUWDfDv7WZb+eK9AkjHJTbggPzXtIbL5kgPnFgE+Zt3kCGVe1uTNRtl/MmXSxws/qreOoMFfg3G4mDmTU3ljxhrj5afQye7+U3Kk+citgYYEyHCbv9/51L95f/T7u/fte0R/aKbGTpcBFObUzKKPs+53V75T4GYsfrE4yQXTV6+xM9sfz7ExCpgI7T33rKom8q8Nd4vkHqz8okZAwEVU92Er65Q48/htay+LCR2s/KhF4s5rKQJmbi5VzRvaX8ihKnxyDa25Sin1wJ593lJgzSXQlFVTJG6v8ztzx7aGKBp765lQF250sn2ACpphpK4GSSrpdyZMJFtVUocRqoK+SbnebvzLN4uvz95XzqlWwCMB1jEGEu2CUMkb+Dd637vqarSbdDCTVnHGr/fhW5eX2bTSevAMUe8cg0Z1yxF6N420iqBg2MjDuij0X1r9QfA5kPt2NDlNqAgZx7qr+raq2EsfNtgBvJebCOdlIUtwx3Txn9gUZf6X8jm0TPG5vTNrM0VNR1d2eG8Xi+eqFkJV3CgXG/h83+3mXv8cE9OqWV5fwabEH9zE1C9nKms77kOs19ztnr2ffnqD6q12BBWUeHwtZnuTgbBtRCgJ3nx1fTxXjVVE9EIlaiakHPpqpeXIvd0ym3K39dCNneyFVU56IDKWS4brvzRxmK/cff6biMHeeK74k3faj6qwWDKwUoANl9OhKeRIX5lphZR9vsv3I0dhUXVuMYzwxqlRVKpWBu9YB1SZHk0934N9UJnOeevT5XtX7dVeUp5ye+zaLflbMAf8tKDdJ9yuvvIKuXbsiNjYWiYmJGD58OLZtK2k2RJe5e+65B/Hx8YiJicHll1+OI0esz4Isl3O6YVSQQiPkY1S8ZaZboW1CW4y7eBw+H/i5SHB8kVDw//yv5/8EY8WgbeSUkXhi4RPiZ5c3u9ycgWoF7HumhIab+w3TbxA3ODdeNeKMjKy7ANIx+Xu6+9Mi8Wd/8a2zbsWgiYNEcYB/w5V5jDNwAXm176ticWLCPG7DOOGuyX8/2+tZy+eNUtqX+7wsnn+7+dsSUmf22BOsiLqTyNr3m5GNZQBFd3XHKj6Pj5u5YrI8gfPEKadjUvzNltOBFWWiPGdkBNxVN+1xdYurReDNwMZ+3JoK2Pge3SUbClzYVYXY8T1yo2Jgz2DG1Sgux+orzyuLMK6SAbVRuWO5HYMaMivuWEgrvY4K9nPTPY2eMt2vnYz18seh2ky6XYyysleTqF5EslbeQJ0vFjfcXQf8G6oA5a7XXUnpPFX17dlMVXzz5ng9Jt2GrwPbRFRw4u6z85QEEkrR4tgmEwiGTQXQSp7rrgdY+UN4KmxwLVT3hrcsG9cyZbDlLugnlEzZSgBtnm83bKli2YRJW1GBV4G56hn3lAipZIJmTlZHy9kjLVkWP8OLihC5Zz6Qn+N2wgjBxNZxfSJry/fI9dxdb7AzLxhO4HC8tqmUYxGNr+Vp3eC+rBJMTwmb+txYOHLVi68wuMFgS6oYBTVOy2PSbfR1rz261uNIU2dINZQB8Us+5dwhl7+nWmm4Trv6O0rCz3vQk0qPxUXe+0zMvCkYqAKjO3m5/brkTWHN3Vx0Z/cJE1RPvfSUZqsCiqf4xP4cu/LV8Tnp9hCzkWVnfMWiieN0F1WEU7J9d2D7Btco+ua42xOVss3VKFUF+raoPdZTjKBiA6qQ3PlA8GdKYRnoHvryjHKTdM+fP18k1EuXLsXs2bORn5+Piy++GJmZp+VVDz30EKZMmYJffvlF/D7d5kaMGIEKzXSrBVzNTDbl5dbHAwUKZAW/GPSFcEdXG+ttbW/Dk92e9Op1uJGoRJlBY58f+4gknlU4stxK0moV7OVV8ncloeeCwQTaW3Cj+33477inwz0i4Luz/Z2YNGySpUDfHlxYmUiyd/DxhY8Llo6LHfvvCMVQWAmEbmpzk3g+YeOEEsyMYjW58XpibBWY/ChHeo6BI7PF/rEXl74ovkept9XiAlULPE/EJ+s/EWZbDKD4GfCztWLUp6AM6Hh+lLSOmLRjkln5tdImwL4mxUS6CvaUNLFVtVaWCiiq/2rWXjk2zhkUA+Rp8yPI3jHZ4PXuzqSNgZT6vD1V9xV7zgKPFUdpxQp6kper4/U2gSWURNVVP7dj2wnBwpkzF3MG2KqwYaVYopJuuvG7cmz1NenmOaNZFNdod8GGJ4d8R6NDXt9UmySlJwVUJqqg7gtXrSre+CcQKulmMOnNWCHTOTkoFFFu5NMEmTYWYMmk7D251y+neEfm34rc3ql83U3PuBq3xGSGxQU1DcIbpB2S/yeuiG0DzJBcM1NcF2hsyX3G0W9F9eK6Gr3pDNzzuIaxL9Wx/YsyUsKqCk0ZQlFt4i6pstLPbc+gh9jkXG37fcIfebm6p1nYZJLmjVGbWptS1di+rdOBfa5lzVQS8G+x6O0qmVKtSlYKuNzPVXHD0YsmEAUkKqi4l3Ndsioxt8J0q3YxKgKpcvDULsDPmmsMCRBPhTru1yzgcO/0ZwycPdQ+bIUoUXsZfVvUusgYi4o9ew8Td2AMNrrFaJO4cXb/cJ9UBRpPng0l+ro9OLtbbT0jVC7gjRKioqPcJN0zZszAjTfeiNatW6N9+/b48ssvsX//fqxaJRdAzlAbP3483n77bVxwwQXo3LkzJkyYgMWLF4tEvaJBVehMeXlIuHyMNJKrHNcMS1mCAeQ757+D3y79DTMun4H7O93v0v3YHdj7+sPQH8xeT1Xt/r8u/ycYZ29BGf2zPZ8VQQMXF7L6njZaV+D/Y7L94YUfiqTSU8LjCo91fUxUobmIDf99OO6cc6f4PiuOrkZGuJKYM9Hgwv/CkhfMhVwFVSopsgpK9LiZUmlw/fTrcfPMm8VrMyBQTIdVMEmn1JAJ4rDfh2HkH3LDITvqzlDMEfzblPBTpv7s4mdFIEM5maoOU7JvFUqaxY1ASZLtoZQH7at5TiwIFdSwsOCM2WQSwYSNwYmVz5XXt5rp7hjYOpPT8RpyV3FW1ywDUgbfnoIvbtYqgbCysTJZY+LD82ZlBnqpJNZNP7e9JJfJLnuUnclyGXRRvcDjsKJe4ftiIMJ7hW72nkBpppIDJkz5PyA7zVLC6U6+rgIijjHzBL53JXH9Y7c1Z3tCHbMnxkoVItjGweDPWe8qz4H6fNX8d3fg9cbeb17/3sxyN/u5c7OALy4G3LDBbIlRrsCeTNvUHmIleVNqE/akWx1rZc579pCoMLA2ZdCGR4k3OHlEjgCrXGjs/Wmyv9IV7Nlptd7xs1QFPfVerYDBPvdS9XrKJ4XrsQrWrSbdVFYwSWFSpWTuzqCSZ0/sOcF1UBVBrTjEW5WX830rtttb1u5UXgbyIT+rKiRJ9i9zmySPbi6TKZdJ9/Gtlgu4anycUpy4U9744n/A2EfFF7wevHntxPQUj/ug1VYrJV9m/OmJFOAeoWIAV9NVfJ0m4ElertQB9FihMksl/V9s/EI8co33VDSw/1x5/7Ao5ez8sAjNPIEFBiuFRqWGY2H1RI5s5/DVxE9hUINB4nxTsq72u387fE6609LS8Pnnn+OJJ55Aaqrc2FevXo2DB133gwUSTLKJqlUls8vkm+z3gAGyskK0aNFCWLwvWeJ68c3NzUV6enqJr/IAlViZokzlTKgYzQA6M/oCymisLh6uwKB40vBJgi1nUvXJgE88ul17qjAyUf7kok+8ZqbLAjQ2+nrw12Z/KUEmn8UBb8CN+snuT4oKP1mqh+Y+JKqfKgj1ZFbmLCh8qc9LYkHnJs3KNDffd89/V6gXvAEX3PcueM+stNIkhq/hbfLOjfTFPi+KPjYy5WPXjcVzS54TMi1vixQM9hhoMgH9ZN0nJX7GIFLJy905iDqy8Lzeea6cOftuOiZ7znnNuRoB5wi2ZDBJp2xPbXKuGCBP0nIFlchzHJ875pGvy3ND1sCTLFkx1dxcvWVTVHJVTflQeLjGhzWWweOknVLdYI9VKbL4ygIPFRZWoAIvT7OHFWPMcxJSXIwqe/4B1sg2EFdQSRUTEVdOxCoI8WQ65dgPOGXXFMvMsWK63bkmK3C9HtF0hDmG0FkQx0Ic2SdKsK2oStTECm+C2+OHZQJWraAQSN0N7HPPvKg9gUmKK0kxi4bKKd9K8kbvBd5XfL9WXe4PZsrYx0oxV1177NH3dgxVqsHoiwSOOOme0WWRmQE1pagcD8pzxGuI6xWLMaqtwCr4mbJQxn1BGW6ycMyiBtd71W7iCUyqVH+7O68ClVBZKQDaJw+eRiTyHlKFEisFYCWlpnmVJ3dxe6Tul9dvdFERInh9HnOffHAmOotfnIDgOBXDnmm3jxvcgck590cWWjz5THirACDUpBKu/Vak98nGflbjn/eAjc7NUR2Ll54c0hXL7m6igj2UKS5f15fRgL7Ky9XvqELImyvfFF5DXB+53yvVohXQw4DtgISjiqXEZIJqrS2pE7kuct2jQkspLp1BebdYUWhRYalagMjsa/iYdK9fvx7NmjXDa6+9hjfffFMk4MRvv/0mkvCyRlFRER588EH07t0bbdpIw47Dhw+L+WmVK5eU0VavXl38zF2veFxcnPlVt653BmJn30jN+IbqcVZMtwcmpryAAR7Zco4lU5tpRQIXri8Hf4lHuzwqJPW/DfvNcnDhyCo91/s5sXCTwXhtxWvi+yxWUDXgLcisfXfJd6Lg8UiXR/Drf371KKt191osLrze73W81f8toYBQbrDegOdFGb0xWWYwzCDPqkmfPe5qL1+HQYh9BZYjStSINSuyZxU83tvhXvH8uy3flWITlLu6N74GrEyr6/37rd87/Z2dJ2RxwEovu2IymfQzqXYnkVTMUt2oRNg2TgQKSsu5HfGfRjIhnLlvpuU+VdMN3ALTba9m4OfuKJFX78ebBIKFAhaY+Pl4kiarc1K9oFBumrvdm2AxeGHASpbUWY8ck2HF9FuRw6tEnp8fkxurzLGnOeiueoCdsWLKSJGyTyutHMTIplLZwiDOKst29Ihk06sVGslosnv1BNt0GIDyPnY1y121HjCRthIYM0hVLQhWC0mmkV+c+353ZVxEtotFSCZX3uCYwRTGq4KYh6Sb7+Wp7k+JoizvnZeWvSRMQAkG+VZ8NezBc31nB6nK+mz9Z4L5VYocqpE8qW6ceivsne1y3dieahSnLBZWFTtKFtHddAL+jIUIJrhW9jYy3bx+qNqyoo5ROJEkSZ8q6npOcy/D5r2q3oO9F4qaq07pOa9hb/xolBrLStLN98fr0kqrhFI2sI+ax+VJRsy99aAak1hQAKwY7/b3uQfyulVtbp4KM1b3QhbJ2SLDoj2L0Gcy6VYGvxxDxwL/15u/Ft9jW58V81x7sA2R8Qe9BlSc4djuYcVg1r6NyZMCx5xQUMW7YjGLork+TLKoaPAp6X744YeF1HvHjh1ifpnCJZdcggULyr5hnr3dGzduxI8/WpOzuAOLBGTN1VdSkvV+uXNBXh4iu7qAYCPpjog7J5huDevgosnRZqNajPJJOm8v5f5x6I+iskiWkv00TJj9KQiw4EEXcqubiTvWiws6Tab8UUBwY3qmxzOiH0wY2PV81lK/kiPYD0dZtCPb/d3W70qwGlbBijw3ISZZ9qweWSVVNbYyas0e17W8TjzScMXZTFFlamVVZshgWTHS7gINxRrUObwVmHgLMNOzJwOLKGTNGHxYnc1szr22WNygnI1JNQM3R+mlSkKtjMZT4N9VfWzuZPzEPkPS2SDfSAz2LXZriMRER5k6/bjtR5e90Uy4PZlD2X9+qu/a6lx0k8nzIJ9VaBnfUpj0kBVzPCcq6bYiLbfvX2aAy2DLal/fMaMAkqCSlCPuZyNzbVLMMRlcf40MS7FhB+Z77A9moqLOtSeTOYKJrmLoPV17JZBzEkcLJZuYWNlIME4mWSpYPtj5QdOMkl4plNmPaj4KvoBFNqpKqCC45697TIWPNz4dKpGlvwoLcM4ULFQB7Ejb4VWQz4IXWWCqFH7e/rNHxo7nxsq+y0ITFUiEs5GarnAkxSgiKenxCc+9z0rCz2vDvsCoVBfcS7wplqj+eXoIKPM4T5J7Eh5WCig8L6q/+IetP7g1sOOaT6k9FUM1qGQ5sMJtUZdrY+canT1KzFXR1IrkuZRPyPaJXnlOOINiy614Z6ii+viB40VMxB7uF3u/iHs7ysK9N2Aspda+D9d8aH6figN1rVgZr+uYdLOI7WyKBddxda6bbZ/rtlXC3i2eBWiuOX+4MX1zBe6VH6/72KNypUIn3StWrMAdd9xR6vu1a9d2yyoHAvfeey/+/PNPzJ07F3XqnJaJ1ahRA3l5eSbrrkD3cv7MFcLDw1GpUqUSX+Ur6XZguiMqFtOt4R1Y/aaEftk1y0Rvvb/J8rkIyrlnj5yNpVcv9aqX2xnbTWUAk2L2HDEwp5ybzIcKeqyCSZYKOCn1Ur20NFBjFZ6Sem82PxWQMoBkIs9gxhFqtIc3iQSnEyjTN04EcAayKeJ1cw0J5eqvgDz3skEqDtRn4WwGqT8O6fZQ8mcWItQIHAYHnBvK4M/TrHZX0sift/3s1lBtb7I0r2pgiwBswQB7WU+53+tYROMxsT9aJX0KqoeVzKA3UDPryVhZ6TVWAbQ3/hXq2h+7dqzJnlBOSzd2b5kT3hcqebXKGCer3uhEY5zgEXk9uoOSsfO8OI7isb9XrBao1JgdsngMyB2nJrhiucmYWl1zVaLCY3Y39qcEju3E0WCZbFUzpLQFJ6wRBde3ut5UBUUERwjlkdVWDEfw/1GhxTWPLT9qWoW37V9cF29pe4vJmjsyYTQb5HXO37OaUPGaI5OokmNXo7JU8mCVHVUtOtwfWIByvKdd4UCalIjXUYozrhv57u9dJtX0KuCxf7r+U/P7SjVjtW/ePskzPT08rM+q6Gp1SglBuTSLgmRu3amokk7IAkqtggLZGsnPO7kkQ+sI1R7nqgWBhRlzL6xifS9kAZNqEyq/vB1r6Pj31ZQIFpCsggVO3oMfXfiROH9W1UOOuL3t7WL/5T7z5UZZ/Jqzf45QcbCwZsUzRIH7hPIOUa9Vqk+8uABxHFe34G1gwiAgw/0+SE8nrj3Ed5u/83pmN9VL3Itm7HFt8Fme4NOnzETVWe/z9u3bkZBg/aLzBvygmHBPmjQJf//9Nxo2LNlTRuO00NBQ/PXX6RuTI8Vottazp7yIKhJMeTlcyMvPkpGahsaZAAMrX0bb2YOye8UA3DbrNtw++3aT5fbFHI8VZ0pLGfSPWTRGrFmK3aP6wGo/twLf381tbjYl5vb9cpRGMmll0cDT7G97kAFibzlZIMeRJQobDLOsdrkGA0G38IOeHXvVWDdWpD1JiYXM0HCT9qadguoNGsMw0VbGPcpYjQxspZQdwNfDgE2lWTNnoIyTjB3Px1ebS/fFKew1JK712ctc2Tje1D0eA12lmPhgzQfOWePq1lljxeTzdek94GnGeImeVYtMN8HiCZUbDPgfnf+o+FscZUjDKwZl7SMSgZ+vB+a/zo3ZktEjmUQWoGjS5haF+UgqkOZcdesbCdyJvR7/DvuIeR/QVfv7Ld/7rQpxLEBQveKuX1Wxsd4EuLwXuV4w0XTnGF8CR7cixUi603OlvPzo4SSkZuZZXk8WjFqAWSNniVGh/oCJMKeCzB01F39f8Tee6P6ET2syGUcWK9gjTtbRHsoMjcUpq2NCCXp2UHlDBtJVsqamBzSs5NmfwF4doyTxzgqhpZB7Ckn5sqBSh/d6WIzlloD7Ot4nnk/eMVlMLOA6RxdvJv1WR4D64unhSzGCrLhiXN2dl6QD0qCxTnEw0FSqdnDYffsIi9XKIV35o5Q43vS94r5n0u+NVw9ZfLVnfb7hc6+TQQWuizyfPEYrHiiBRt1KdXFHO0mCvrXqLTENx5dpMwpqeg2VJ46FaGWW2C07V2pseR1tm2ZpT6EycdfJXU5NOt1B7WG+tjdWiKT70ksvxfPPPy+Mywh+qExu//vf/4rZ2GUlKf/222/x/fffi1ndZNT5lZ0tK4bsx77llluE9J0sOI3VbrrpJpFw9+jhnayzPECZr4SoOd0m011FPmp5uYaGRzzU6SFR0af7KJNlsjZq0/FFQv9av9fEa1CS2u7rduZMctXX5C0Y4DEp5fHZy9bVqCEmEd6oGbhWq6rz+I3jS7HddC1NMgza2jC5ai57AZEiR555KmKQaaAKx5OMjDJDVuLZr2elb9A+UHqg0wPi+UdrPxIbMllq4vxqHYDPL5D91r/dYWlsov3sYTKxrua27s2WfbQNanRAcRUZjBafcJ90E5xuwPfI60H12PG9KzWBct62CrIhKlB0JaVW4PXMxJn/x6qEX50TjlNkck+mvMf3PfDe6vfEz+jxEDrxVmDz78DclwDOibZgpqOKD87YkxI4th1JITIsqdPIMEXlNeqhiMz3qEyIqDSxd99lr7AyR/Q26WZRRvSr5mUIvwZXUP4KVvvz1XlWyhMa11kK+o9tw7EQmXSvSpIMc+XidHyz2L0ngaOBJ78CBSZc3lxfjhDGmm1vN5Mfe7ZbFdS8ZXbJrin5ME1FnZ1bxY5aaQdwVohhQdVZ208JHN2GA6EyNqtTtSlOBEv58Y7dpadmOCuwsaeZzOJ106/DfX/LJJytaJ4c8l3tJWR2WbB0N6rO7I+2aEqmoFzXWeRQDuWO2HFEFhsbRSQAVRudLqq5AQt9KqFnUun4WSrVEItu3voTsAilzFl9HR+mfAOYcHtTGAokmHQrRRGNQakOIWMt1kSer7QkSwVSgooITovhfUjjRXsopUXvdLu9dafnsYpsE1Dmcd87KYpaaUPzddpQhUi633rrLZw6dQqJiYki6e3fvz+aNGkikuGXXnop8EcJ4OOPPxY91+eddx5q1qxpfv3002nZ1zvvvIOhQ4eKxL9fv35CVk5zt4qI0yPDKraRmoZGWYKutT//52fc3/F+IZXkmDpv5NqO4P+lk7w9yHIrB09vwU38xtY3mmypqvouOyzlcN4arxCcc8+AikkZg1xnDGyDvHzENR0MVDOYu+OSybM6T52JsLskQknLqSjwNlCixJxBARnYi369SJjsMPAfkWpnmsTAfZO1tb9PnT6oEl5FnI+FB+Rse3vkF+TiQLFkEhvUPw9rT8mEZcbCpR4TJbp8KxnxU4ueEv2U0/dMFzJPMvO+BBJKYs6ePXcSV2U8RP8Db70iWNx4vtfzgr1RoPHQ5XEtgSQ7KaYHF3cFlRBT9uhOBZF+YBlOGkxuYXFtnCiW/e4zFq+wJDFn4E3Vgip2KRdf7pe8Rrxh/FUyr8wbx20Y53LGvUrqvTWt5GfJpJMqAEvzn49uM5nuVQclaxppy8OMNfLvl1fwnua9QOM/1Zu6O223SIb4GVzUwDuPDYL96kyo2CLh2A9K0oLnnPDWE4TtFbzOmJT8usNDb3fKJhwIkbHZzkPh2J4ZKZ7/Mm+VpSLL410fF0aTSr5MNvem1tYdru3B/6sM1Zz1zzsy3VYmFDjuffTcoArTlU/BDkO63rRqMxQZngRFqZ4LRmT9+VmyWODoDaHM4bwdjar2f7Vn0WDQVSuCFbNKfwpP/kKZJTL24HXP8/XBhR8gginepDuBd9sAv95s+bX4Olz7aaimCsQspCjTx97ZOUBtw7R0/xJLCb1q5Zp/YL5QbliFmuv+r2a6ySrPnj1b9Fa///77QvY9bdo0zJ8/H9HR3kkorYILlLMvGrop0NTto48+EiPMMjMzRcLtrp+7PIPVTyJEXetqFrbq6WaPWKFz1kZDQ+M0KPu+rd1tQirpzegxV6DZDt3eufmxAv1m/zf9ksJTFsjAkNXrcevHSffcvdI91+p4HnswAeO8e4LJib1hipK59uKm2mQAVmXKQOLwbmvzt8lI8HySLVGFAXdJty9O/QzCn+v1nMnwM5h8sdfziN1gKAFqGX3S22ZYPh/Dm8p+dBq2OEovt+6aiQKbDZU48iehB2YdlGPzMo/uw/ztrt2RFe5sf6dgQCl1HfXnKLy76l3xfcVYewv2tlL+zcSdfbCuoJg8X69pmuN9c8k3IjFkoM+RgcHrfypp2GnBSEcxzDwHTH7dmvgdXC4eqwWFY/yCQzhYLJnBv5et9pik8LpQqgXOvVVmdfZBuS/3IeXxlDfz/ntr5Vulfk4mXcnmvekpJcg4qyKK4/hCZ8g8ugXZQTJsy8iLRzbktXjqxGEcSbc+xupcA5npx7s9Lp7TzZnnU8mUWbC0MmfYEUyCVKD/6vJXSzDoLNTx8+Ta4W1yKfw7Wl1rsnZ5bL9xgfwjm5BsKBMWbSnG0WJ53+SfTMbuY7KNwh0o8WYhuHuN7qLQ+NlFn/mlUlDKijn75ggTPEfwHlMGc97IyxVUgZFJt+N54WvvKJB/s0mtHhi3Ua6zO7dtxME09z3uLM7e0V5KqF9Z9oqp0OKaqlh7ZRLqLbg+sxWBviC+jLVSJmr+jsgV4Bq3e74lZZmze4jX+9M9nhbroBjvunQssN4w8mQR+tgOywaYSp33xMInhKz/6UVPi72xU24+atDkcuAr0t8k6ziQfsjja/I+6127t9i3fthmoTXDgelm8fhfm3R//fXXYr41R3bdfffdeOyxx8R8bBqZ8WcaZ05eHlxKXn7aCC7NnvnR0NA4Y2DVn5sfHUl9NSuy30wf7fqoeM4+bI774UgXusvTbM0XMJBlIEeJNxMJBkRkIOcafcL/OZWJ7MQOeHetXF8Kj+7AxFXu+xAJJtwqmXQ2s9wfEzV70BGbfaSzLp+FuVfOxfl5RUBGMsB51P+RSS32LBA9lVZwc+ubxbGT/XKcUbrCMHDpEhSDPzcdw5FiWdisjlR8s8SzEzGLAxyVR/Mq9v+xYMokQrFOvkA53ZI5ViZeLueA+1FIIrv9Up+X8HCXh1EtvAqwXjJYBRe/Kn/h5H7MXb3Z8ngb4utNX7tklLYfl6/VKKImJq89iGQj6Q7LTMbWwxmWJLQ8r2Tb2Nt46NQhoSwgfD3fTLLYr8yknkUpR2kui0tUXTDo9kUlQ8k+FS18HWVW5xT52Ug5JYPbECbbxeHIC5c9pNWQjnVJ5Vvdxj5smlsxsB/952jT9V8lzr4mVDS3YkL1+vLTUlneNwSLKd4qbQhOJiDzRpZTeUs4Q3LKehTZbAi3hWDt3kIcNdaOaraTWGihYEfw73w+8HN8P+R7r40iHcHirZom4Oy4meCwqMtr3RsjNfvPkOebqiHHsWp7jqxBahAQVlSMAwWd8ctuGbPWKDqM9+a4n12upOBUaHE02dur3hbXyfgN48Vju4R2Pu8lXJ+VEofKLxVbeysv98ZEzSX+fAj4+lJgbE9gi7UJFW4T+FUOe/Ba1y0yjiBbTsk8C+ijp44WvdhBsOGu1FQgsgpQpyuyjb1l2RLXzvL2uKbFNWYcY8U8kvuE6iv/VzPd7JWm1NsRGRkZ4mcaZ5LpVkm33Dh2pebiVLEM8n9fZi0Y0tDQOLdB2R4TZd73KhilOYmvPWRMJB7p+ojp3n7XnLtw7bRrkVOYi8Z5eWgdVQNTduRiQ47c6GrbjmP83I0oKvIsI7uh1Q2ij5n9X656B3cYLrbeskyOPfSUBwqDui1GD3mbEciJb43jwYlCYj5lhmeTF9V3rHrd31n1TomAYMVxKa/rGtcMv646gCOQTFN12wks25OKQgvnhE7Y71/wvni/DHrHXTwOMcpUyQcwkWaAy4Dz3dVGkcEBSnrubR+zSyQtl87LEXF4/0g77CqSUu3vJ/+Boxme568OazxMBHEcDzU/yUkveGEBtmXJpDIyuLE4r7lGv39N23HM3uy8T9QRLHaxqEEFx8CJA0UCwH/7WqBS51DNMH9h6QslWFOyhspl2RcHYl7DI5pIV/6x68a6/sVjO5CspPf5kjENjpX3Z7wtHesPlH/z1DE9x5QwhmQS7u2oRXvwHuOISa5zHB/20tKXBDPJHnr7EUm+FEKZ0Ku2A1cme0mGc3l8SDUUFdtQaEiQE3AS/+yUDOmZBNf9W9rcYvorOLZ6rDm6xlRs+FIspmpIybWZENsnsAu3yXafLoU2/L41HweLJTNcyZaFuet2ISPHvbSbex39PPhZkklv/3V7YfBI+Dr6ToH3Ng06WZyxMsu8TOTlB1YBqyYY/yiWozpdzK63BJqf0neEY9+GGesKvTgsgu0eXwz8QhSL1b8/rTUYPXJygXo9sS0lEzOOyfe8YOF8bDzoef3pXbu3MLtjkdKVkas92I5FZpysfSB9KMpd0k1WxJlM68CBA0J6rnEGmW4z6Zby8ukbknESUuK/ZY/s6dPQ0Cj/oLmVMt4iQ+PtTFxniYTqP6crqRhtZgvGS0dTYavdGb+uPoA0xCIrRLIztuO7sO1IhiU3VTXPlgZczmTBW4771k/pFJyXvd1gVZpfgrdmb8eGPJkQLlm+FLuOWmO7OY9eJWvs7yMYlK7Kl6ZcLRJ6CTYxxUy603AqtwBbD5eWaToDk74/hv+B3y79zSdZvSMYgNLJmGZTjgwpZdyqz9gfj4IS2Cqll4VNBuKzxUnYXiyZpbqFBzD+nz2WiiRq5BvVFaWYjqNbsdkwUTuUIaWtlWvUF481bCewyGKSQtMe3is8NwSDxnfOe8frvnZnzA97/+l6fcfsO8Q5ZrKlXOSVq7UvYHsLj49FquXJUmJfCke3YU+YLLLl5VRDkI0WLtXNpHvdgfLNdCvW8ctBX+KRLo8IBcALvV/we0rF+fXOF+MhCRYsz//5fJEokTVVo+Z8bfvhSCaaXDrtkc48hqQCufYEQ65HlatJmXyCLQ1Ld6daKmIGGiw0sGhHxphmmvZYYxid0W/CV1CZEBsaK9Yf+/7rRYYTfa/YRli86ziyEYGCcLm3VClIwbQN7ueHq3uMrUWq2Mx7nEUV1aLhK+hhocbMsYjizdzugDHdi6VZJVoNB6LigbT9KKZay1eoVqAWQ5Fa50L5PHU3Pp7mYn1xApoM0vPmq0FfYcaIGehx1FB21e+FT+bvwq5Cuf7Utx3BuIWywOQOQbYgsc+q1jZPPfRqfB33S19Hqp1r8OpddOzYEZ06dRKL4IUXXiieq6/27dujb9++QmaucTaYbrkIcTFLL442Z5Rn53knldHQ0Dg3Qdbm84s/x+/Df8eEQRP8lq2rHjwmJAzEmNC/HVIPrfPykFmtHVbulQ6lwdWky2xdW4rlxIe97Ex2aGK08GBJczIyTWQ7yVgEooceh9dJBjYsBpk1e+DHFUnYXSyD3Ia2ZHxuIRggyJirZI0OsGRq3lv5DrJtQNO8PBwtlr3i8dVlIhhny0QEcrFq32mn7DMJsubKofnNlW+WCBRpiEdDMSYxgUjwhVRx61TxdHNcX+TkF+FIaF3zHP+yMgn5hZ4DVco4WdjgbNzLfr+sxEztjP2LsTFcOnJv2ycZ3HoNmphSfiaVeQXWgmHKcH8a+pMwSPzkok/ETFx/wXP5St9XxHOanp3383m4Zto1omWA/YZdanjnRG8PskjKffj9Ne87l7ge3YrdobJwUJSbiKaJsQiOkYF+VWQIpsnXsUfnEpgAMTC/v9P94nkgQDM8emuIPle7wow/aygTPyVLdtoykbIZayPk38vKkslJ9dpSsp0YlC4Kdlb6ugMNJi+8L1RPujLK8meUoeN9cnNbadr12orXTMn6yhzZm9u4Sl9k5BQgNiIEwZVl4a6W7TiW7Co5nspdXzo9Ux7u/DAmXjrRZNb9hX2xwNNkCHuQHSd8lbcLpO035eT5fR7Bmiipyvn2h2+weJcPiggy5Bulx0la08sw8qut2F0kVUNL/5mD9V4U6LjP0Ek/mKaaNE3jUlS1E6asO4T9xUbSHXQEczYfQU5+oSXfl6oRVYVBmmr98XRu2UpXUeBV0j18+HAMGzZMLOwDBw4Uz9XX6NGj8emnn4qxXhpngekODhWfy5bkdJPpji46hdX7z05AqKGhEXiw/5DyrEBWfckevN7vdUwY+AX6JUvZ99LcBiAJ07Z2HMLtkm6rgZG9iRHl2spsRrluE0y4AxJUbzfkgI3Px28bjomALj26vpkQTlx10JL8WSVrSjZK2fYvO2Xg8t+MfMwxDNQ6NK0PhEgX4kRbGlbuPXtrLBk8FgtoPMWRZwpqNvF5dc4LzLVCYx9KFYPD8WWKHLEUV7eVeGwechjHM/Ms9RTTQfyNfm+IhIVB18PzHjaTlSX7/0ahzYa6QdHIzIpDXGQo6tSVf6tWcJpI9Dcdsi6hJsNPBpmtGYEC5ZGv9X3NVEEwQGfxiH3v/jLpHFVIYy8WqpyO3Du6FbvMpLs62tWJk4yYwXSfyMrH0VPWrvN/I8hqs2D59nlvY/qI6WhdzX+VDRlWmnAdyjxUahRS0aG1WBIpk/rkw3I9atRQXs81gqU6ZsPBs6NO6Fenn2hXYpvEA3MfEH2zZKXpacH1onOif/cMiyZUMTHZvvCXC3Ht1KuQbwPq5+dje6Ec/9arcTxscXXNpHuDBXmyPQPLgoe3497cgYUYVSyg8R6lzVbicMXGejtirQSWfixnXjfsj8+2ReK7ZKmIaJG/Cc9M3miphakEds2VBmfRCXh9ew1R3NkRIieRtLHtwacLrBWiS+DoVjmKODQKX++JQ0FRMWJqytdsFJSCzLxCzNvm2acgPDjcLBZT8ZRT4NoAUp1bmodWFHi1Gz/77LPia8KECXjhhRfMf/PriSeewFVXXYWwMFmp1jgzI8NCFLsRFCwCS2686cVRJhOz+iyxMBoaGuUMqbuBjENAcBh+PCD77Qa1qQFUkQFjXdtR0cNcYIHRJBgUkfVgYnLV1KvMxHvSDinFZE9yQLBDSsuLmlyELxdJmXPL1pKVbhl6BHmFRfhri7V+YJX82PcIXp5xCt0S2mORUXDo0zQBiJWsQXWcwOZka/LyskB8ZLxQFRBjFo8RffR0JVZ9iQE7x0pa3vA8zNgmZeGt2spz3DREjtGy2qPaNqGtmbiSMaaigPj7pDRTahQk1Q9dG1RBUFwt8bymTe5jZ7PAoXBJo0vwwQUfoHFcYxFos0XDl9F9juDsZSWDpsTVcWZ8wbFt2GIoAYpya6Bz/Spm0l03Qro/bz9srZXi3wqqLDgzXk0+8BdkytnmQXy09iNzTB+xNWkhUoODEYkQ5J6qi/joMNQymO4qRWmwoeis9eFTrfpav9fE9UsmmqoNulQTbFvytz+ZBSgWojjmi9idvk8YqD2bH43ZSTLt6NOkGhBX2/Rs2HMs86wrMzmek6ZsNCrliEdPMnMaNbJoyETS23GEJrJPAKu+Ek8zu9wjZNsrimRLUDvbbhw4egJTLUjvna3XGY2G4IdV8v+27CCLHS2C9os21J0pnlvFSmCfnNFdVKcbflwt1/wLesrpKQlIFaqvv7da22dvaXOLKFZR6cS1zhWULwmJhooCn0rgN9xwgxjPpXH2QHfWkj3dIdh+RG64RcaGEodMy/2MGhoa/3LskeZWBbW6YN6eU3ZJt6zgNwo5KiSR6y0yEjQ++Xrw18IFl/ON7/vrPuEOu/LISsGmqPE1fiErFTi4WjxdHtwJu45mIiY8BL17SHlezaIjCEUBFu6wLtEjC0szLrqiTw5rjmePpSK1WjccTs9BWEgQujSoAlSqZZqp7T566qwGixxfpFiWR+Y/gksnXSoKHLWia6FXbRlo+Q1D+rilcj/BaNSuHIlmrWTSXaXgGKKQI1qbrOLiBhebI6KYrDz0132YGSxHDOXmys+ua4OqQCUZyEYWZyEa2Vi577Qc/WzivLrnYfLwyZhy2RRzTFIgwGIPpZd09y9hNJSfg20ZScgKCoKtMFww3Z2YdEfL4litMClTtuK5oBFYDGsyzBwp998F/zWZu8UnpG9F/RCaRYaIdcMWI9smglCIyjiFDWfR/I4KGY4BpE+BvQnmg50fDMjrk4WmqoCM+u1RjTH1wCF0rN3fbMfpzaS7kky6G4WmCmXV2b5+ufa/0ucVoTihvwL7jt2Bo+cUE+uLC77Aup+A/EwgsTU+2l9PKLUiE5ugODoB4bYCtLXttuSZUdLjRBZdp+d3FJ1BLHDUa9lVfK9TRLI411YmbzhLuvdEtRMEX7WYcPTv0NwcH1nPloJ/dhyz1OISFRpl+slwvKMyVrUHVRhqLrg/HgMVIukuLCzEm2++iW7duok52FWrVi3xpXEGmW5zZFgokk/KanexMaubrpAMQjU0NDQ8wjBt2RHdCfmFxWiaGIPGCTFAZcl0NwmVSdViL1x3WaF+vf/rggnYeHyjMFZTskz2sfqNXTSxKhYBy2drZbA7snMdxCTUA0KjRXBbz3ZEsLDeSvSqRcSjcdJqdrJhaVELk32NCA02me5GEelnPVgkq0SXWT6SoTmec1wEj+9d8J7Zw+oXTuwDDq8HbEH4/oSU5A5uUwO2KDKt1UwZ/9okSsCtFx+ubnG1aV4058A8MQu9fX4RlidJR/uuDasC4bFAWKz4dw1bKlbvL/9mYZ6CUTVrnG0ZLFYJHF6PleFSWp6f1RCxEWFownvTYLoTgmSRbLuFsWoagQULiC/2eVF4WHCNu2LKFfh4+Rv4PkzeCwV5sjjVpX5V0QYoxi2JsWHp2HQo3bJyqCzAxHj65dNFf/s3g78REy38bZOwR/+6/fHhhR/ivpRkMdt5W3QnoTyqFReBhtWi2aMifq9hmCw+sD3ybIMJtBrRyf3KWUKoQDm+cnv3GcbkjYxWozBhsUyE/29gC9jqSdf+LkHbpYFnumsZdgkkrxUeJ8VhMXh3p+y5vrZHPSBRtgPVLDiAMORjnsWRdQKFBcZeC8zMlnvhkLY1EMoZ9FXket04+CgOnczB3uPOnfwdcVH9i0SxirnMU/88VWoCwObjm4WKgEVIX8bXVaik+7nnnsPbb7+NUaNGidFhDz/8MEaMGIGgoCD873//C/xRarhmupXhSlAIUoy+RZuxqFfCKcHCVARzFQ0NjTIEq+NG0j0lvYmZWAkY8vKEgsNCEukNo0mwt+/bS74VLF7f2n1xZbMr8VDnhwJz3Dtl73Ja7X74e2sKaHR8Q68G1E8C8bLfr3VYCk5m51saaVKqh419cSGR+OOoPBd9mhiyy1jJwDaPlkXNzYfObrBIOei0EdOEIz2N0zgXPGCjwgwDtYI63TFxmwz8hraXTD+qyZ6+jlFHhcmZN+1MlLg+2uVRvNH/DZwXURP/ycjESxHtcTK7EBGhQWhTy5AAG2w3HczJsKRkWAw+yylGNx9tSlzpoi/27wMrsDBK+ggUZjVEx3pVEET7cqPoUalIXttnmyn8t4L33McDPjbnGo/d8jWOhoQgsciG3Qfait8RChkiWrLddUPTkZ1feNaJETLeNLfydwa4S2QckWspx1OeamKy3MKVXsnLIQu53ng2lCVGNh0p+t6Z9D2+8HHkFUoVjqspHPZj7rxC6h5gn/Q4eTupmbgeOtStjAEtE8VYLuKCaMmmc5qIJWyfIR7SavXFoVNFiA0PwQUtqkt1VkQcgooL0Tw4GfuOZwlJvyUcWAHknERxZBV8uU8W+i5qZcQHVWXS3bPqSa/ajGw2mzA3ZC89ixc0kLQHW48IJub+TjAo90n3d999h3HjxuH//u//EBISInq5P//8c4wZMwZLly4N/FFqWOrpPmJUwkKi5eJeOShLSAGPpGtzFQ0NDTdI2SQSzOLQaHyTJAP5gSrprlQHsAUjuDgfiUjDyn0nvGI0CSaAlGyPHTAWz/R8RgSnfoPV9x1SRvf7KRn0nNcsQTIodglh/3jJji7c4UVlnzCKEEV1u2HxnvTTfYiEwXQ3CJPf35x89oNFKgd++c8vIvm+oN4FgXthI+leG90HuQVFaFY9Bu1p4kXEyyC6bxV5jud7w54YgdegBoPwwYksvHzsOA5E9Rbf71i3ipDy2xc42lWSTAjZwYoMylSf6ynHInEcHB2g5+6dg2WREQgqtiE/ow061ZNqNkTJ+ygiX57/HUcyzsoYKg0I9/qpl03FvR3uRd3gaPTOysanEZ1xMjME4SFBaK2KSIbEvENVaSDojZN0uYQae1WjLWbvk++5T1NjHY2Tjt9x+ZxmUXROeDaodYmjySi9335iO57858lS/d0shinnd5+nI6z4XCi1TtXphwmbikSt+LlLW8sks65kujsUbxXnhnJwS2qtbdPEw0JIM7y+zarJtZSvmSiVSgMT5Hmet006ylt9zRM1+yIls1Ak8t2oRCKqyn7rDtHGPuvFHpAQlSCMNQkaEapEm/kNJ4gQPWrK8/CvTroPHz6Mtm1l9S4mJkaw3cTQoUMxdao8URpnyL1c3YTBoWbSHR5rzJENlXJzst0aGhoaLmH0gB2r2gkZ+UGoWzUSrWpWMtaWEDM46hBzwmtGs8ywd6EoFBRFxuPNbTKIu7mPrLoLxMuku32krLx709dtzxjsrdwDGbkFwgipVa1KJRJBzuo+F5juMkPmMWC/ZGI+TZHyxCu71D3NPBiFjdYRMniz4l5bChmHgcOyd29aVsvT0nIFo3++daxkZTZ5q1goh2hSpYmYU018t+U73J8nZ67XzGqO4vx4aaJGGD3dQfmZiAkuEEX2g2ly39c4O2Md72h/B6YVVMMnR45iT4FUm/RtaiQ+dkl3y1j5OXnj2l2evUKy6/QxC2a9GlezW0dtCCrKRzwysPVwBtKynLPKZxrVIqvh5b4vi/YBGlPeNecupNG92wCTcY6+ZFsBlSleIy8TWCN7xv8I/494HNS6BtrXNQpqNdsJlVVYfjo6RaYg+WQO5m/3kCSf2CvW0mJbEN7YK30+Lu9kN8osUV6PvSvJ16E6zFJxe/3P4umsYmkY2b95wunr2ZCXNww6YjLd3hTle9fuLWbeF6MYt826TUjNb555szBg5Qi3QQ0HAf/2pLtOnTpITpaOeI0bN8asWdI9dsWKFQgPD0APmYYXc7pLy8ujKskFLT5YLuraTE1DQ8MlKF81NtXZNilpG9ymZklJl2Gm1i9Bso3eSszLBJsni4dtVfojIw9oXj32NBNtlxDWKZKyPBr4pOc4zNJ1hdwMYO8/4unkTBlQXdy6BoIp6bVjuisVyESewaLXY13KA3hdFBchp1obzD4UjpAgG4Z3lJJQ+8JGjbwkQaRQ3uy1/NtoESis0QG/75CfT+/GUsJon3Q3DJcB+8aDFbTA4QAm3TS2ijAcoC/KysH+A5eJ82wG5uGVhJ8L0SFexgTbtcT87ILJVNJy8XTy8brm2mHCkJc3iJBr6dlyMD/TTPeSYsmytqgRi4RYI09gj7tRwOxSRRbV1lgYPXim0Kd2Hzzb81lz1OXIKSNxIEPuJzP2yqJst5rdfPPOWPeDlGxXaYg3d8ue5dHd7HqXeW7qdBFPb64nE9pvl552x3enSjpcpTOScqKE6uv85vJ6E0iQRc1mwYfE49Ldxz3viTtnyx7xqGp4dbdMsEd3tTtOQ14ek5WE6pXCkZVXKF7XGzza9VH0rNlTyPk5LpHz4oNtwXi+9/MBmzRQrpPuyy67DH/9JTfK++67D8888wyaNm2K66+/HjffLOfcaZwp93IlLw9FiiEjj46TgWecTS7qZ7tnSEND4xxG8jrg2DYUh0Tgg2TJZg60DxLt+rrbGxKy5XvPsot0frbpqP3JUZkU39ynQclCgSF9Dj+5G00SY8Rc0TmbLY4O2zkHKMwTAdF3O8NK9rgTRqAYmnkEkaFBItDYmVLBFEVUUy37RDz9O/oS8XhBi0ThWut4jkNO7EYbQxmxeKeXBRmeaxZPYrsLd/z68VHSudzhXKuxYRvPkb7PskZocKgwtppSbyTGJx/Bg/kNkVUUhy71q6BShGF2xevdMFNrV1XGBLqv+yxj93ygMBcFleph6mF5T5zX3G4EV0xCiVndHDmYfxbN1MoUZF7T9glS6LtkWTwb0cmuaEcYfd1dqmSdk6qhEU1HYPzF48W4uSNZR0TifdWfV4lJHOLnTUZ4/6IFecA/74qn62uPRmp2IapEhZYsNhKGmVq/iJ1gvZfMNFtInCIvyxw99ssp2Z9/U+8G0vtBIUEavkWf3IFGCdHCMNWjOmn11+Jha/UhSMsFGlWLRu8mdsdpyMttaftxUQv5/b+2WJStG2Bf96cXfSq+aLJ6c5ub8cfwPzCg/gBUNPiUdL/66qt48klp904ztYULF+Kuu+7Cr7/+Kn6mcQZ7utViHRQszIKImMoy6Y4qkjenZro1NDRcYv1P4uFQ9fOQnBsmqtUdFZPmwHTXD5YbtLdO1QHH6m+EtDwrshb+zGiMqtFhGNbBIZgzEkJb1nGMaBElnk+zOu9040TxsCdxAI5n5Qtmpqd9QBQjXWFt+ZnoWz/CKwOZcoNt00XAzGkYLya1N6Xlpa4LW7AYeTOontyLFvjoivvtsabm3ygRKBpMd1zBUZFjHjiRbd3JtwKgxr6l6JaTixk5srhUQmlAGEl3i1hZdN+mHczPLnbPlZ9DLKW4NtH7mhgbUYrpjik4gdiIENGuU2HVCZukGqmwTncs2Cfv2QtbyrXThNG61CpaFtO8Nrw8AyCbPe6iccJFOzM/U7jUExfUvcA3/4ylY4GTSSiOTsRDO+Xaelu/RggJDnKadMceWWmet59XJjl/TRZIj21DXlhljE/vKq6tEtJyIsEw1zyxF5e0kHv8H2sl6+2y9cdoPXsjRc7kvqpbvZLF7ZgaQgaP4kIMqStzkL+2HPHawNlms6FXrV5ivjuNVukiXxHhU9K9YMECFBTIpI/o0aOHcDAfPHiw+JnGmevpVvLyAgQLloCIiZObcFh+hjBg2K2Zbg0NDacLSQGw4Vfx9IuM7uamWiLpIYyxYTHZBwXTyUCRY0zOCnLSgfmviadfBQ1HIYJxbfd6cpSXPcJjgFiZsA2pJdU+C7Yf8yyn44gsJpwMNA61M8eQhdoHRHxtSnsBDKhd5JtR27kOg+VeUGkoDmXZxGzuEowdERJmFmQuSJSJw/SNh3Eyy6KM/8ByICcNhWFx+Cm5upDvX9HZIVA0mO7gU4fR2uipX+KlfLHcIjvNdDf+8URzIe+/pI08Hyai5X7fMEon3eeSnPq3E7Lod5ljkcTo6bZlpqCdYUh4Nud1lxkK84HVknndUm2QYFXpFUKmtASMWd0NQuR+QqPOc3HiTt1KdYVR5bUtrxVs7M9DfxZjGd06a/N9LPsMmPaY3Ge3/Als/h1Y8Kb48ZRqt2J3WpEodN/IqRuOqNNNjGpk8fO61lJx9dOKJDPWN5F5HFj4lng6IfIGnEQMRneti+jwkNLXHqcbFRdhVH25J87dlmL6QTmVwBcX4kR8R/x9nAqbEIzu5lB4DQoy2e7OMali8gRHh1HBoRGgpPv8889HamppeSEN1fgzjTPX0x3MUT+MQ4vkR8n7P7aKZLptKEYssoWxSnbeWWSlNDQ0zt3EKjMF+RHx+CqlsTBHua6HTLBLwDBLsZ3Yh14G4/u3VefTQIISuom3AlnHcDK6Ad463gNhwUG4tqeTYyaqycC3XvEBITHnjFiPEvN/3gaKCnC4Wk9MPxovGIPb+sqgogSMvu7uCdL4h31sZ5X9DyT2LhJGdcW2YIw5JNmWVy9vW5qJseudbxFyWPRrcuzNL6tcsDGOWPyBeNgQ20cUTyhfT6xkxwraMd04dQS9G0l2Zsm54ClwJrBinGhzOBrVBLuLa6J/swRUiZbBtyPTXSdcBtEssldYufK5jmM7xHgsGllNTG0g1qZSRRIj6capFLStLa/n9ecgu+s3Vn4BpO4WvcBP7ZRrxMWtapROUo1Z3dWLj4qEjWMBtx85N1t1okKj8N9u/xVsrCXH8uWfAdMfBZZ/Cky8BfjpGuDn64G8DByOaYUHtsl2rheGtUFUmEOCTERUMh3H+4TvEpLw9JwCTPhnT8nfW/IhkHcKaXEt8eqRrmIfF6MzHcFzX6ereFo3fY1oVaEXydi50qixVMGAijIAX2b1EY/X9KiPWNXaYo94uT+GndxrjtX0VmL+b4FPSTerUM6qO8ePH0d0tEMVS6Ns3cuN5DvbKHyx1ys4LBIIkYFLnQhZ/bY8j09DQ+PfgWM7TcZ4LK5AAShHq414+55dh55uZBzCIEOWNmuT9xIyn3rf6KDNv0OG++th5piwZ7NHiWN+ZGCzkvJNexhGX7ZjO3BJWxn8/rnejcQ8LQlY8514+syJIeLx/guaCvm6q6S7XsgJ1IyLQE4+Z5iXM4l5VqpkSew/x+wTwO93i6eLIs/HvoKq6NkovqRJnTMZ//GduNYo2Hy/bL/na4NeAtumiQTlf6kXiW9d5ciiENEJUsJeXIR+tYrPHSO/skbOSbPv88NcXos2XNrBKEDYw5jVXbk4HVFhwaKwtO+43u/PClZOEA9rI7ohDbG4pG0NxEWFOlVuMOluXyu6Yo4No0Jjnmw1nVfrVqxLKRJr6L3ny7XCWU93cMYh08uhQrTqkBAzGG2xhsWdlksfbTwSg48/gGIE4dGBzUsa7TnCkJgH7V9snr93/9px2qwsZatMurknpg0Rr3nf+U1Qp4psqSqFhv3k454FeGCA3B+/WrIPMzY67IurvgRSdyEvKBKfn+iAuMhQ52y83T6LlM24qJUsKs3ZYtE/5V8Gr5LuESNGiC8m3DfeeKP5b34NGzYMAwcORK9evcruaDXMhJv2+kSIwXRnFsgiSGW1wEfIwLhlFfl7uq9bQ0OjRLL1zXAgNx2pldvg3bQ+gmW49wJj83QE2bSwGPG0f/UcUUlnIa/MzMMKcoHJ9wAvJgBvNAbebgV8MUjIkYuDQvBKzOOYnNUeLWtWwk297caEOaJGG/l4aA0ubV/LnE3qcqzSX88DRfnYG9sZszMboV7VKFzfywWLbkjuyf5f1Kq6WYgoNzi0FninDfBGI3mOJ94GLPkI+KSf6PlLC66Gu1OvRGiwDS+PaOtaRqn6BA+vF/3G0WHB2H0s0z0bTcXCrGfE052JA7E2OxE1KkWgX1MH+ToRFGwWODpWzhYS6/2pWUhKlcZLFRYs/uSdQnJYfXyd2VVIc8kUloIxNsyWeRRNq8eK59sOn5tMYYVG+iHTdOr9k31Fq8SDA5qV/j32dAeHCdlu56rZpnlYaua5MSrLb7DYNvMpIDsVBfHNce82OV54zNBWpVUadj3dOHlAjFZTPcHlHodWCxWZaEN6aDPw0AZgzAkk3XsAF+8ZhRPFsaLn+h5nhQh7NDbUwxt/w2Vtq2F4h1qCnb5pwgqMn7kCxyeMEmqYvws74PfcjmhfJw539G/s+vVU0r1vEfo2qoxbjDGbD/+87rQfxMmDwGzp2v5u7n+QiUi8O7oDqjuqkBRqdzLf8/ktEk1Xfpey9X8xvEq64+LixBcr2LGxsea/+VWjRg3cfvvt+Pbbb8vuaDVKOJcTIQbjnZmvkm5jUYuUSXfTSpIC10m3hoaGyUJ8PkAYueRHVcdlqfeK6vgDFzYTfbtOwYTLkJhHp+82Wc8/1rkxYfEHZPjW2u0lGYeAlE0oDonEzfmP4tNj7QRz8tl1nUv2WjvCkNLh4Go0qRaJHo2qgpO9HvhhDbLy7PriWLxc+jGw4WcU2YLx8DE5N/WpIS0RHuLQK+4wKoUJqkqGWN0vF6PD2Mv/683CAE0g67h475j5JHByP04FxeK2rLuRjhg8eUlLMXrGJepKLwAcXIWY4CLT6GvsvF0ocCZzPnUU+PpSMb+3KDgcDyZLlvuO/k6MhBzYwaicFHNcVrlTFXiDlC3AvFfE0w8yByA4KBjvj+6IyDAn16JRkKD8vnl1WRjbelj3U55xTHtUyIY32ppiXlF7XN2tHho4u2/YA2v0MScWHhUtGVwyPM5gPlfAcYp0yeZ6SRWSGpOm1tE5/zPX7jeLrxGxKWXMw5ypNIhKRtJ96ggGt4w3PRvK/bx5w1BPJM30vhBxehGum7ASJ7LyxZSG/10q5eVu0XSg9CbJOgbb3Bfxyoh2wtsiJz8fjf75P8Rn78Wh4qp4PP82sQ99fXP30zO0naF6W8m8550CdszGE4NbiJYxTuAY/dkS/L1yE4q/HQHknsSO4joYVzgU1/aoV3L0mCNqGUn3kc1IDC8y1+jZVqeF/IvgVdI9YcIE8fXII4/giy++MP/97LPPomXLlujUqROqVXMhQdMIuHM5EczgSTDdMtCrHFmS6W5iJN3n2hgGDQ2NMkbGEeDHa4AfrpLGYEy2OcKFCY8hG7sl5wHsy6uENrUr4da+bhhjopYcQ4IDK01X1B+W73eeWPmDtP3Agjfk8/+8D9y3GrjkTWSf9z/cGfUW5uZL5uTly9qgblUXEjr7uaRk6PMyROL9/LA2okebZj23f73qdA/2lPuAGY+Lp58WDMXq4mZi3Eqp0Wn2MIoQOLEH3RtVFa977FQe1ibJ0VbnNLZOEdeAUDDcvwa44iug0XlAvZ5YUWMUeme9hRXFLfDsf1q5lhTa93RHVgUKckTizd8nO06J6EM/ryt5fVDKPu4C4MAKFAeH4/aCx7Apr4YIyt3+nUqGJDc9WfQ1Ez+vlPNyK6QK5fsrhQrlgK0mfivsIwoZHetVcf77Sq6cfght68h9f+XecnANViQs+xTY+qfwJfi/nFtQOSocj1wsxzM5RWWjjeJkEi5sqeS45SDpJsnzzQhgyv1yvXyvPfBxb+DlWrKQS/XUItkS8UHhCHxyqAkiQ4Pxv0tbu1bKUKkh5lwXo25ImiiMkiyftLqc399Ht8nHmnLfJFn534nrsfd4FmLCQ/DpdZ2d90c7IjgEuOR1+XzxB4j8+xn8el4qllV+BucHr0MhgjCv80d46fqLxGuWamdwVvRpP1o+X/ONKHR+eHUnoepql7MSjf8YDtvRrThaHIcH8+5Gl0bV8fQQD8UB+m7QxZyE4OENuMQYr/nxvF3I8GRc+i+DTz3da9aswddfSxlNWlqacC9/6623MHz4cHz88cc42/joo4/QoEEDREREoHv37li+fDkqoomavXv5KZPpDi3BdDeKkb+7oSIadWhoaDgHo5Y/7hOBIPtm8cNo4LX6MkhKXoe04mhclv0MFmQ1QOOEaHxzc3f3jLE9a3xgBS5uXV3MFWWSGfDeLY4wK8oH6vcBOl0PxDdGSsvrMGBpe8xMkesaWRO3CbF9wNJ8sPm6zarH4subuoneVyaFQ9+ejf0/PASskczMK/lX4Y38K9CtQVXB8LqFYrpT94hzRxMwYtKagzjnsf4X+djlZuk823o40q/8FQ9Fv4or9g4T7rdvXdFeSPfduvMS/HkTY57qpklC4jz2GioQbJiy7hBumLAcB46nI2vBByj4qIdg0onbip7AnNyWSIwNx8fXdnb/dwxmkEkKXXn52qv2ncCKQM6L5z1jKMcCjq3TgM8vAr4fDSx6HziwSrKCjmBhjEWxtP04hEQMzx6DqnFxeHqIm2tRJd0ZyejRUPbErt5/ArkFFcTU72yzulQd0FvCVYFk7ssoNgp27+SPwHbUw9ujOrhPflR/bxqTbtmasmDb0XPfAI/qC04cIEQx8xRwZKO5L1C9QrxZfC3eyh8pXLl/vasn2tSWLu1Owfve6OumrHlkZ1mQ+HXVgcB5hrBdafssue7R7I7/Lmsc215iNjaLKvQTYXvMlzd1RYsachKDJbT8D9DzXvl86UeI/O16JObsEaO6goe+hasvvUS0OHlcqxU6Xi8fWYzfNgNVd/6Gv6q+hq/CXkP9oBQcKK6GK/LGILpBJ3x2fefSk0Ecwb+rJOYHVwlvDybxVCvc/d1q69Ms/gXwOenu27eveM7Z3NWrV8e+fftEIv7+++/jbOKnn34S48vIvq9evRrt27cXveYpKeWgiuiliRoRbLDeWUZPN9kWgQi5yNWOyBX3Q/LJHKRk6P4KDY1/BTj7mIZjHDfSoC8QepoR3lDUANfkPQnUbIf3RnfAn/f1dd5r50aqHWorxpVdZXD0+G8bAquk2TpVPra7UmzmHE9229erxAbOouJPt/fAe6M7Wg8wVFV/468i2Opcvwo+v6ELOocfwMeZD6Peti/Ej9/IvxITbMPw2OBW+ObWbp6LEMaoLNG3l5eJUcYM64mrDp7bRlYMZJOWnpYuij2lGPd8t9osGPx3UAtc7ji6yx3aXnF6vnlhgQgAyZ5Q5dh4z/eo80FdRP39NEKyUrC3qDqG5L6MOdnNEB8dhp/v6CnmoLuF4ZBOZ2i6m3OEG/HenB0ICNKTgQ+7Ai8kyMcdsxEwsD/ylxtksrJ9OjD7GeDzC4CPewLLxwF7ForAl6ZLxR92EUzRseI43JD7CNJDqmD8jV1Pt425S7ozj6JJfLgoYuQWFOGfHRVYfn8msGuu9JIY2wN4u4XsU949X7ZmZB5D4ZSHgdcbCjNKW3ERfi7ojw8Lh+OOfo3dS3FLMN370b5OZXEfZOQWYPmeABaRAg0WiQyjOAx5C3hsD3Dl10gZ8D5+qvsM5ob0xY+hw3Fb/iP4MHcwOtStjHmPnI/Wtdwk3I5r6bHtGNymhiiKkhGeGQiPDBpwftoP+P4K4LdbAd5jL9cGZjzpvPAVCPB1mdwT1ZqL4sFHhkP49T0boIthGOcVLnpefinTspaXAveukIVTb5HQDOh4rVAX4IdRwKQ7EHpgifjRqbbXY2LXH/HAlYPw/a3drbHx9hLzA8vFqLK3rmwvfA0W7jiG/m/OrZhj8XyAE496z8jKyhI93cSsWbOEkVpQUJBgvJl8n028/fbbuO2223DTTTeJf3/yySeYOnWqkMM//risRlaUnu4gWxCCjARcuZebc/kMeXl4QQaaJMRgR8opbDx4Ehe0cGGEoKGhUbHkjkS324HBr+FkZh4+mL4S369KRlaxTFpeGdHWc2JpD1bsw2KlVPvwejw0oB3mbk0R412GffSPkKA5HVPiDcgcHVojnxsM9ZuztomZ4Ey4f7+nN+rHezkho9H5MjHJSJZGR62Go9f6Z9DL9gMNoZFXHIwXcBsKu1yLqb0amGZUHsF5p1xnc6Rsv2fjVujaoApW7D2B68Yvx/QH+paek+oNts8EVowHgkOBnvcA9QNkUnp8l+zhpqSzZnvxLTLSDI7YC8g++fM8JQ2OYN8iXbSzjgF75gnme+CpP7Az7NESvzahYCDeLbhcMOk8V48Pbum879UR1Q1DvCObxMPd5zXBLysPCLXC4p3H0MuVs7pVzB4DHN9xmqH6biTQ6z7gwv9JtYQ/oNKkME9eK1Ru8PxzlvPRrcC0R0r8KstI+4sScF/+fUiJaIg3hrUWZoFuwRaBoFChDrGdOoIh7WpiwqK9ooCiWNQKj8MbpPETp7bwc6vf0//JDpT483MjeL/QIXrJhygOiYCtIAeK+yMr+Hr+KCyKOA83da+Nxwa6kZU7moelJYnEhMqhH5YniXad3v5ey+p80P2ef0cltP6C9wfv75BIoNMNYl1aX6k/Rn6/BHkFPObTagwaolHq7NSDwBm4DrFQnLwW0V1uws29G+LDuTvx/JRNYnKCR8m0O9BFnfcaQQM7zg+nkmrpR+IrN7EdNjS+E63PG4Xk9BzhX2G5oOsK6QeB/Cx5X1ZpIFQ5a5PShFkpvSt8Ag0lez8A9LpfKjA4TswfXPKmyLlF/z3XJhanm1yEmKYD8IAvr0eDNraxcxZ5Vqpwov/8+i548Ye/UDk7GZeNzce7oztiSNua/p/fcgyfdpMmTZpg8uTJuOyyyzBz5kw89NBD4vtkkytV8vNC8AN5eXlYtWoVnnjiCfN7LAYMGDAAS5bIKo4jcnNzxZdCenp6uenpDuYYFcV0F8qLOEbN+jPk5ZSrseLIpJtushe0+JdswhoaZYnUPTJ4rtvVVJX4zYbtmAXU6SITDH82Jbro8rUYwne7XchMrx6/DJsEGx0hNr3XL2+HoCCb95t+g97A9hnA7nmIqNURn13XBU/8tkEY33w+5W98Nj0SYXE1RS+w14kboYIjyi9jEnEiMw9fGDNJXx3R1vuEWx03k9ZZT8skxz7Ria2JsBGf4QXl6Oot4hsLOR2O74StemvB7g7/aJFw135m8kbh+u1RmufqM/z1FlngINgmwJ5rOuF2vQVo2N/3a+TIBvlYo60w+CkqKha9dwRHzfj0ubEw0PoyOVf628tL/TivRkcc7j4Go1r3wxXFQHhIkHcFn8SWp4PZrFTUrVoVV3Wrh2+W7sP9P67Br3f2spa8O8P+ZdJEjiCTdHij/PfiD1CwbTaSB36Kus0MPwNfiydEnweBPjJW+mvNdmyc+AquC56FqjbpNL6iqBn+KWyL8cVD8dRlXYSM3lJwyh5NynPp15C2D5d3aiuSbjrp0xHb6bi7ioQ/H5IzoRW2TQUGvwF0v93311z2iUy4aRJIv4PVX6MwaTkK9yxCWIE0+DpWXAljC4bhYIPLcGn3Vni/ncM8bndQiTD3EEDIcZl0T9uQLFRDrWr5EUf//eJpTwwW1rhmkx0ls1mzne+vm7RMPlJGHBwq1o0xv28SSiQ661/TvT7a1o5DlagwtKwZ611iZfQ9q4LrXec1xs8rk3DoZA6uGrdUsKYei0/OQFKK7UoEP8fWw8X3UuZ9ioQFT8GGIoSnrEeXlLtxePFTiEcuUmzhmFr5Wmysfilyi0KE0R3dwN2akzni2LbT+0NwiKkg4gQNlw7gVsHz6m/CTYRGAsM/knsjizP+vmbdbnKiR9o+6SNz7UScn/MXzgv7P9hsmZhW2A1JPydgxa87MStiIKYW90Pd+BgM61hLeMT4tE/+W5LuMWPG4OqrrxbJ9oUXXoiePXuarHfHjh1xtnDs2DEUFhYKubs9+O+tW41gzgGvvPIKnnvuOZQnqKQ7JChEVu3sRoZFOTDdZGFo4f/LqgOip4R9iv/mKpOGht/gqKPFRhsNmZWutwLnPQGES+dgr0EZ2viLxYgVgTrdgJFfnJYgeguyaCxhU+4V3xgfzNwmEm5K9ijLHtAy0fc1oPEFMune+BvQ/io0mPs4vj8yDZlxlRGTewTZxWGYdbILxn3VH7+1vhD3X9QSTRK9OC/snyQS5Riq39ceREFRMVrVrIRBbbwIah3R/S7J/qgArFozoP9/gbYjfX9N9TpMug3THAZUL1/WFjd9uQK/rTmIw+k5+Prmbq5duV2BQTMTbprTkEVe94ModAhs+QM7m9yMjL5Po2N96fbrFZTs0eg1/HtrCrYdyRDmPtf7o1RgQrn2+9OO6Kp4MuRNhDUbiNNTan0AC1vVmstgln2jrS/Dfwe3EAzS5uR0EZh/dXM30bPvNebLecKChSaTxNpPte6IWfg8Io9vRcx3Q/B03JNo1Wsorupez7t7Jz/HuB9PS/k/X7gbL07lZzAS7xSMxJDa2biofhAiGvVCl/BgjIyP9mwQ6AgmVUy6j+1Amy59RPJDH5efViSJBOacAZUs634U44pE0YeMqTLJ8wW8J1TCTRfsdMN8a/qjQFRV3+5vysdVEea8x8Xxnej6EG7cuBx7skahkS0ZeQhBQZXGGHNZF/Qxxlx5hRpMfm3S3yDjCFrXqi4MAudvP4r7fliN6Q/08y7JU5j/+umEW7yXXMkg82v5p9gR1QETQy/Frso9cdeFLdHJlTmfMxxcLR9ZGAbwxaI9gr3liMCJd/YSbR8+w3hNsUZnHkd0dLzwebj1qxXi/r70w38Ec+41acQ+c7LzVCW14Kx7YOneNNw4tyFi8j/CoODluCvkD9S2HUcNmzQfjEMWbk77APtSf8L1+Y9j6oYa+GzBbnRvFI/zmicIlZjHBJFmoESVhkJazs+VGGQYjJ1TqG7BQd0KuC4O+0ia6bF96RXZp69Wy0uCT3trdcvbhmuKfsI3SRdjzN6L8dSkjejesKrwQnA5QeXf3NM9cuRI7N+/HytXrsSMGTPM7zMBf+edd1CeQFb85MmT5ldSUhLKi7xcMt0lR4bFhAeXYrr7NUsQzALn6tJgRUPjXwcmRhmH/X+dvYtOJ9wEHZspO6RRmRqb4i0Wvn064SbY+zn+ImDdTzJI9foYF8rHhn2Fj8NnC3eLf9IYyyuzFWdoMRRgse/weuCt5sI4y1aYKxJuItKWh2HBi/Fd2Ct4Y/tgvPjee/jfH5usG6kopjuhhQhWvli0V/xzdDcfCxAKlAiP+Ay4Zzlw61/A3cv8T7jt+9jY/2mARc6x13QSrr2Ldx3H05M3ClbIMk4eAFZ/I5+PHA9c9gk+avAhFha2QUGx3LKb7PwC2Z8PxZ2vfoqB7yzAy9O2WPfsUK66LBjQYXa+ZNuu6VEPcWr6hS8g23rHfMkyjvoOuG2unE3bTCabfqOpHC0mDJHEXheCL2/uKoo69CyhwoDXmlduuTRU4j1N9LzPnBHcfUZN9Dn1KtYWNUYV2ym8mP4kOk0bgkfe/8q7PZRFAiY+DPoTW+Jkdj7e+0sWPWi8x372j+4bieGXjhABed+mCd4n3HafpSqoXNdTzpBnH+k5M8/8yGbg/Y7AzCekcoOmXO+2lUoDX8DPbvLd8nmHa4GHN6F4zAkcbTRcfCtn4l2444V3RZHDqzF+nK9MaTaJi4b9xWjBG79cgXUHTuKULRq2ul3w4cM3YNZjg3xLuAmyikq9wcQQwIvD24gEdtfRTHy5WKp7vO4jXvWlfM5ixtMp2NXuERQYQviiYhuaZq3F4yefx4N77sRVY+cJlVKJ0YlWCqLV24qpD0od8+SQlv4l3ASZVkrMi4tEjzxB743J9/QWxYj8QnpOrPH+Wk4yEr0GfQQ7v2pfKq75fBly8otwjOl1+xux65plOHX/Nmy8+HukXfAajta+UPwXGorND38YE0JfQ928ncIwlGv5nd+u8mzwdsrwkIqtjt3HMnHgRDbCgoPQo5EPRdLyhIZ9gYFy1KEA5fUXPA1cM1GYwRXU7obM2IbID4lBw6AjGBP6jTjHw4L+wbI9qbji48VC3VaR4VPSTXAuN1ltyrcVunXrhhYtJENxNsBxZcHBwThypKT5Av/N43WG8PBwIYm3/yovRmqC6TZY70wjzjB7CDnCRfzgqAhO1IzEr5ec3Z57jQCByZhwwNUOtW7BOaJfD5Njit5tB6z/2b9zZoxDQYdrgGeOAQNflhsLE13OOPZFVr7BcJK+7W/ggfVyzBX7jyfdjpNvdcZ973yFN2dusz6aSzESdXtgxsbDQv7Xrk5cYKrsTKwu/1zKnO3Z71HfAnctAW74E2h+ifh2uC0f40Lewtolc3DJ+wsFK+IRZOuI+CbYeDBdyLSZvCrjLL9Bdpesit2+5ReUMzor+5w/TexZiEsOfYjfOqxCi6D9+HFFkmmiYwk0K2LPIQ3wGvTB1PXJeGNrVVyX/ySa5X2Lt8PvEoqCXsGb8UnOY+h57BfBxAx+dyH+XH/IuqtutaaiEEu2mI66t/T2MDLOCmh4Rllvy6Gn3WwDBZW802iP93XyeiQufAZTms3AU4lLEJp3El8u3ovOL8zBb1bHDTGRUElxtaY4fipXjPVhjpYZWgUbBnyL9BajkI9QtAhKwlsnHsArn3yBF//cbO1+TFFFpJaCCZqwaA8ycgrQrHqM6HfsZriN+w07ozmCcs2O9SrjVG4Bbv5yhfXEyhmYYPjrIk3G/+frpf8B18tG56OYHgC8zr+4GK99+gWu+mypyQhaAk3N2G7Az27gSyIReur3Tei+eST+KuyICOTho4LnsG/Ge+j16l/4acV+a27YZOEJtpwEBYtCDj0laFI77YG+mHR3bzRK8FHV5IzdNZJuFlueMkYzvTJ9qygWeOXenbxWng+6ig9+HRsO52Dwqi5okvMNGuR8j6HBH2Nq7JUogg2tg/bh/pDfRA/5o7+u91wU5HEcPa1C+mPtIRzPzEOtuAjTQNJvDDAUp8s/BT7uA8x5DvUXPIIJMWMxocqXaF+4AUPeX4jFu455V2wnancWbVYP/7xOFGCaJsZg+ZMX4u0rOwhSKqZqDbTpNQSV+92JhNt+Ax7eCtTvLf4rx3JNC38SXyd+j2AUYt62o7jlq5XuP5tTRg4SUx3zt8lrmvd6lGr/rMjg+v9sGvDoLuDx/UC/R4GmA0SMEHLbbET/31qEPrZdmvFFxKGO7SjeCxuLV2J/xuGTWWLaxaHyPqPdDQIUeZwbCAsLQ+fOnfHXX3+Z3ysqKhL/VhL4ijQyTDLdSl7ukHRXViMp9pmOiQR7hlLStYt5uQUTxnmvSYaADrjPVz3t9uwLKDsb2xMYPxBY9J7r0ShnA+ytnPGEcPUVM6d9NUhSslwG17/dhoJ32+P42EHISDaSD6tg9Xqnsbb0edg0uEq71HB0XfUlVi+e4x2rwt5BNR6rdmesz4zDpdlP4+9C2eMWV5iKl9Iex9x5c4Q5l8d7l8GtOR+0PaZvkOz+f9rVClxbCXt3710perbw5CHguklypAllaqx0X/UD8NRhoOnFCLUV4pPw9xB9cjvu+nYVjmbkeu5lJirVxp8bDpmM4DkbrLAFgP2IZGjGdpcuuV8NFeqHlhtex9TwZ9DBthNvzd5u9qZ7hJIjd7ga2w5n4P9+WSv+ed8FTbD7lSF4+IlXEXnPAmTXkG7y/wv9GvfFzhNB8L3frxFMrVswMCeqNBBFGaJn43j/2aqyRr2ecrxZ7kngjcbAp32B5Z8hcuVY3Jb+AVZH3YsnQ39AfmGBCK6513mEGndk+Cg88/tGMQaPSfHaMRfjun6tUGn0Zwh9ZDPyY2ThelzoW5ixaDnG/CFN3SwpNxJbiMRXXQP3X9jUe08FdzAM8QSzV5gvzLneH91RuMLTz4Vje1h882kN5hzmt1vKthpVRPAWlGvTiCumOvDIdpwc+Qtuif0YR4tl8e7BQ48hf88i3DhhubXPjdj8u3xsM1Io+75bth/fL9uPIgTh65pPYX/V3gixFeGF0C9xYeY0/HfiBjz7xybPiaxh1sdzyiLM5DWHTKWQV2OePIH94sTOOWZRY3Sn6rivczhCi/Px4tQtuO+HNdaZv73/yMcGfVEcEo5n/9iIvMIiMfd66v19MOXp0Rjyf+MQdIVkw+8J+QNXhcwVRT3+HbfjyqgSI/vPmDO+qShuETf2buB964wrsI2G+6rynfjnbWDd9wjaPAnnZ8/Cd6EvoUXuBlw9bhm+XmIUZ60WoGt1wo/Lk7DveJZw9594twc5PFsebpom3NlVEblf+p9YlfAcmtv2i5Yct6MhFdMdk4h5RiGJ0vR/DRhrcP56mAvVTli0bMt7eIv5mV+VPxkLIh7GjgNHhAKjoqJCJd0Ex4WNGzcOX331FbZs2YK77roLmZmZppt5RYBppEaDIOO5mtNNVlugipSXiYUy+4SYk9ilfhUh0xlnyE01ziC4qaYlyaDInxmR0x4F5r0s52Mq/Hg1Fv34Gv7eesQ7GSuZuYm3AimbJVPHBHXc+b7LpJnw0TWbQdqkO6XZmK9Y8hHwSR9g6Vjg7xeAt5qdNiTyRg2w4Vf5/LLPRGJbFByGkPQkxKcsQeYnF+P1n+YIV3/LQR5bO2p3Aao1ETJWBoldfwnGxEI5QtE2479o/7/pwuDJEjgnk+h+O7LzCvHYr+ux/pgNN+c/hrvrTsbh2LaoZMvCh2EfYPXuZFzy/j/uE2+yETzGyKo4FhSPZXuOl00vWWx1OZuZm6crk5YR4wRjXQPH8Vv4cwhOT8ItX61wH9wZCWFxpZoiGCToxnxO4/wnJXtHh+Pkdaf7d8NiEVycjy9jPkQ8TuKlaVuw6dBJz/2klO4Tdbrh9RlbhRSyfZ043HtBk9O/l9gSkXfMBno/KP75cMHnuDFRSoufm7JZyD+dgmsPj5OIrYmZm2TSbWnm+dkGi1yXjz9tXMhxeGSjKC2Oq4fgojzcHjwFf9b4HNHIxpjfNyItK89zUknUaCvWgWkbDgvWnwxYib7NmESE3r1IJByVbZl4MfQLkeB5LKTYtUv8tSUF6TkFYn7tJf74E7hKuqluow/AgZUmc/rxNZ2EYzLZuXu/X+3d7O4T+6TXRMomqbxhW83Y7tg4x2h98Ab0gCC63Y70oFgMH7sIf+/Lx2i8jpSopkIV8134q+hrWycKBDy3HvdTjl8jWl0q1k5OOSAeH9wCX919EerdNxXo95j43vNh36Bl0H6h9OP8Z0tJd/U2+GPdIZG4Uil0caDvESZzNDpj4Yd9sP+LQ9BLifi/TZdjY/TdeDrkG8xcn4QBb88XsmiP2G+YBdfvJUxzV++XbtmvXd5OjO1iIUaAZmJ0eOd5ifgejYOPYOqGZHxqtJm47VGuVBvJWcWiz5ovd4UxUztgGPAsMPp7aRTJlgmqDS56QdznwbZifBjzBWriuDBwo9+Hx/iGPfPsKq7VAZON36fHQSWrY7BaDZPHYxggVs7YiZ8qvScY77dmbXe9lxlJd15ENSzbLddbyuQ1HMD4gZ854zNueUjBrSEzheLFK0VDOUKFS7pHjRqFN998U5i9dejQAWvXrhV9547mauUZ+Qa7HcpAj0EaC5GGvJxmSebFHJ1wevNkZdMI2r5dul9UcM8pkK397Hzgx2uk5NZXkKndNFmaq/jbw7tlCvBqPeDt1sCc/50O0LwFj4M9uu+2kY+vNZSsgbczIhkMKNOYYWOxa8gv+Ce4m/hnly1v4J2vfsYd366yLiVc+KYMwGlAc54hjWYA8OPV5nXlFQM/8RZg+mPyNWj89H4HObfXW/B9sgAg5lmcRvb312PajD9FgGUJPAay2zStaXclXkx4A60zP8FT+XKuJY1Tum18HkM/WGhN/qvcW5sNFJvtBW/NF8EsC1nfxdyEbFskOgbtxEUFC4Rz9RO/rXfPerMooMYUNegremu3Hs4Q9/DEu3ph7C3no8Zdf4jkqKEtGU/G/Iljp3IFi+eyuKJMshJbYe62o0ImS1Mln/pE/QV9JW6ZLZjgGGThnvDpWH/gJMa7SlTys0WBkNiSGSv64Cgt9zjz9myDsufb58p5qQzOGEBc/RPw8GYROFbOT8E3cZ+guKgQt3210nVCTPB6oE9AaDSOh9fG3G0yeHtnVAeEhwSXZhMG/A/oeJ2YE/xs3tvoHJsmJPk/Lt/vXvYYHIbMoFisP5BmqgnKBShZv281MPoH4JEdko2iA++D66WJT1AoWqfNw8SoV3HiVDYe+WW9+yKPKZltJUzHiMFta4oidSnQmIs99kEhOC9oHTrZtuOV6Vvc95mqPtiEFmYRaWi7moFluQkW4MkUqhFlxPFd6HL4J/wwiE7xNszafAT3e2I07UHlE03xqjYGut6GtChZyG++8AG8/Pyj+HzBLmtrcebx0+qN1pdh7Nxdoq2BCeF7t1+CxAcXiCJVOOXgkZ+hEk7hhT83u591f2KPMfYuTDDGE1cfQFpWvnDRvq1vo9P3Bw0um16MkOI8fB/3MaKQI+Tih0+6KFzSmFa1X1RvJRhN5TodcPB66nSdfK7UWAbCCjNxa8h0vBP7PY5n5uL/fl7nXqnAWMIu6Z5gMNFMip1OfBjwvCjqhRZk4qvq0jSOhWKXsYNSx8TVxrLdsgDAe6RKWTjj0/Dshj/kDOobpgC975ftS5XqIDH/IGbEvoA4nBJtIHuPublG1OdYuR6O5keY7U2DvS14qXWW605IJCrnJuPKqDU4mJaNSasPul1nt2REIregSMjwvTIU/beh/SjZqgfglsh5CEM+nvtjs/W1qhyhwiXdxL333ivmhXMU2LJly9C9uyHjqSDIL7RLuhXTnVdckum2H0vBDYrylmYJomKbnV+Iu77zsupdlpjznEz0aGBCg5XP+uPYuhnYcOCkd8wtGVpWjH+5QY4RodHTd1ee7rX0tjL/07VSKUBH1H/ekX3BynTHKvhZsZdN9G0ZgRYDmcXv49dXbxSJmeq79Yi/X5KJaMtLMS/qIlw8qQDXZj6ABYVtBVMwPuxNLN68F89P2WyNlaaLLPGfd1HY7zFsv+hLFNJ0Zfc8bJlwpzj/lrHmG/nZ8QirnO4Nzf/1Ntz83LuYviHZek8yPzte182HoPjZNNzRYAYWFbZGJHLQYvH/YfBbc0SPnWUWueO1+HtbCj7/Zw+yEYHNtUfi4NXzUWgLwXnB6zAoaAXemLlNHKMlqVrtTvhq8V5TKv3e6A6Y+NgIRF4gWZXnon5GFaSLETDTN7p5TYORIhucExqHbw12/NXL2wkTGTMwu0S60V5fNBntQuVsYo7ocu+aWh/L98jgyGezn0CAx3/hM+Lp5aGLZWA9d6foNXUpLQ+NxopkuTZRGml51uvZBJ2Yh74jgzMGEGqsC4PFsBi0yl2HO2IWihE46nN2Crr3itdrg1lbZNGkTe1KrntI+XfYG1enK2w5J/Fp1FjBwny1ZJ/ztVMVImNrYN3Bk+L1GRDWKk+OsZQttrhEPtqfB45Eun6ykMC2KNqBp8O+F+ZH780xClFuilSF8c0w3ZDau/UPIKPMebYAnqo8UxTcPl2wy/Xab7R35VZpjHnbZQJ3SdsyUm7Q5JAgI/1STeCDTsCMx9Fx9pWYW2ecuPdmbjpibX+gt4Iy5frPuxgfdw+6pL6A2YWdRcvIk0WfIXbWwxj96WLsOmqnunLVI031TWIr7CqqLlyviY+u7iSLG5Sg8j6p1hyxhSfwZtU/RIxCxYZL0M+EqNEORUFhpuKA851NRpegd8PwT0Thskr2PrxZ5Tdk5hWaZnZOTQy59wSHIzuypjB3KlNp8KBXgb6PyBaVxNaydYctO5yhDBuG5s/ANdErsPd4lnnenCJ1lyxYhkTiRKWWmGsUC5ShXinwvFz2ifgbdVKXoGtsKo6k57pWGJhtP7XMc0K36TO6j9z4p1C5xOWn4JlqC4QC6Pk/3VwjRtzLlhSej2KjAF0jzsc2Go7/6mMoi6IZWxSLWeJO19lMGXNuSg8Xjx3rV9FTgzyh841AVDVUzj+CUZErxEQNl8XjcowKmXRXdOQVSclcGKu8RtKdYcjLzZ5uQrljGpJH9nS+OqIdYsNDREBOxsyyq7A9yETPfAr4/CLhRlr8Sl0c+/Ia/LNoPo542y/OuYzs3SFa/gc5VZuLBavapFFY8cnt+M8HC/H27O2ej5Mr6i83yQ2eRiIctUPsmImjb/XA2O9+EbIyp8G+s8q8muVLFpjyRaIwF3k/Xo+UlCPWDU44oogMaXgcCu5ejpc7LcAz+TeKH43M+x3nrXkI9327DIPeXeC+35VJ8i6jn7j/f8U5IYvKERot7/5eLFaJtjQx/oLGTR4NlTjLlKY2lWrjUHxPDH5vAS6eEob78+4RLqctD/yCZz/6Ak9O2uD5nFGyOl8mhgUXvYSRYWPROOcbGaChEK8VvYXXvp+KGyes8NzvzJ5Bni8WlIa8JdiZmVtTcV/+fTheHItGQYdxZea3uHrcUqzY60Zyl3sK2L9UHlOjC/HMZCkZvKJzHTHepHazDgjuK3uJXqg0WSQqlHa7ZK3ISjOwYcdGYgd8ukC2aLwyoi2GdagtN1TOu6zaCJUKjuOjhMni5x/+vdN1sYEu5USdbkIqx5m6HJdxiaMUnP3SLYbCVlSAt+Kk6ZpLad1JY/pCXB0sN85PwMyafEWj84HYWgjLT8cVlbcLI6mfDVbReWBXE+sPcqY40K6OMYWhvILGbRfIosODth9RCZkYO2+X63tKydNrtDOTQI/MTEi4nEEbEYdqJzdiSPh6wSTO3+Gk2EiZMBFbE6v3SVVBJ1XgqQigSzEZbxapQuagMjJE/2ems/Odm2EyeOtzEoWKpFJECHo19uAw3EuOFeuUvVSYAP284gCST2Y7P9fs9Q8Ow/q0CJEkVIsJQ2t/ZjC7AxO2tlfK5/lZsv82sZVg5usc+Rvz6srEm4zmPENB4RKrvpKJcqPzsbS4NV6auhkFCMGmvh/hYLenUIRgjAqZh5rJczD8w0Xu9y4afBG1O+OtWdtEgblno/iS6oqQMFk84qj0nBlChUSW2WXrj2rBqN1JqEHoEE2jsyucmXpFxwPDx4qng3JnoSrSxQzo3c6KBapoWbkulu45IY6Va3LjQBinuWqZYFGSrv93LwbYb02VYrfb5EhDuoOH/SQ+N5olco9w703QCjO3HhdjFjnX2u0IPSaRhjnh8zUlS84YyWlso9bm2JpYbrQsdWt4hp24qzYEhkoj0xHZv6Bx0CFxjexMyXD++6q9rWpDUXwjBrT0U/Ha9TZR2EjI2ILeEXuEqmilsY6WUGzx/qPY7rgsGHPkpYYH8Lrvfod4emcVaS7osRWkHEIn3eW4p9ue6S40PsoSTDd7T+0ZNd78tSrhtZHtBDFAuVuf1/7GDV8sx+KdFvsnmPx9fakck8SkIXU3bLnpqLb3T3SbdRkefvV93PHNSmtmbXlZwO/3yuftRuHb+i+hz9HH8XNBf/Gtm0NmoPmRqXj/rx24+asV7pM/zm7dMVMEOPnXTMIrrX7DsNznsauoJhKKj+H67ffivV9nYeTHi50HYPbgKBNK1xJbI++eVXii6E40z/lSvFZYzjEs/+A6DH1vPnameKjwKydiou9DeHZRLj5bfADfFF6M9yDZkoHBK/FG5JfYfeyUMI9wmczzXFN2GlsTC04mCpkuJYOvj2yHhJr1gP+8J37tztBpaGBLFgWV/cfdyB7XfCseittfhTFTtmD7kVOilzGl3mAsjZEjM14NHYdfl+3C4xONAMddrzPVADE18G5aH+GGHBwSij8aP4cDoQ2QYEsX7pRLdh4R0j63BYtNRu9fkwuxL7+SkGkT11zQCfHD5SiRW0NmIDrvmOhR5Agep2DxhW0YletjzuFoIQWLjw7DC8PbnJZ29rpXON8m5OzFf6stRkZugWkQ47Q4RFRpiD+2ZYsgk8FYCVaMyQ9ZFRpTnZqNthHHhFx8zpYUt6xmca2OpuT6xl4ujGkovbIFo+mpFWht2ysSMqdKFTI1fAivIUxj+FZN1vxsgdJX9hHys6sizyPfbynpmB2bsuGgVDJQmVPuQcOYhBYIzz+JR2Nni8B5/MI9bpOJrPjW5po82Eo/Pl3lOWeaSq/KMoD+0hi35orp5n1KeDWrtzygw1WiaBFclI9bKy0XfdRO3cxVK0Z0Av7aK5OZ/s0TEerJGCqhmUhGbSjGo1UXip5fmjS5uhdZ2Fy+N80sgAXM0NARfF2OxXtokxyL99gu4O4lwPV/AKFRqHl0EX6vzvakYsF2u21zUOacHa8VyhTWSkd0qo0HLmqB2pc8hqC+kvF7IHQycnJz8PDPa10XVA/JpDs7oa25Fj41pGXp80ATxnq9RHHx1RpyBB/3fqdINXxp4ptggnGdX92tXsn4x7HwV6sjgory8GjNNeJY2WbnOumubxYm+jdPODssJWfGx9ZCdHYy7o3+W6wbT092YTClWt+qtxb92aqNwVISSZHEkSmoHJIn9ivOdy+FDLk2nwqvLkaaif/a4CysGywsNb4AQYW5eLWKVNaxv9tpTGEw3YWVG4ged+L8Fn4qFljAaT5IPL2hmmxJK0VwqDGfQSFYc0TeYy1ruil+aJxGO1k0rJW6HIm2E2JMn9OCZjmGTrrLIfIKSzPdrEJTVsV53CbqdD09NoEJLk2lPjsfl8zsjz3hV2NF5H14oHAClm4/iOu/WI5JazxUldjnO+kO4PhOkazsbP8YHg56DGPyb8CKomYIsxXi3dAPsHHTRgz94B+zX9AlFrwuK7RR1fB7/K1iBuKx/HC8GnYv9jSTfbevRH6L+iGpIkC8/Ws3Yxro6E3yov31uHp6AT5dsBfripvg8oIXcTC2HWJsOXg15HNsPZyO0Z8tde0ISrMzo2+6aNCreOjXzWKsRi7C8GLwXWLm5dDgZbj+2Du4bOwiLHTGJtnPJT24UrC2E4vOE+6qxAvDWuP+Zz8BrvpRmAENL/4bd4f+Kaqxv7iq7KmeuIb9MM5I0K7pXh/VYsJP90E1vhAhxfl4t9IPyCsoxAd/73DN5BtzhaeFXCACIV47v97VC7/c2Qu97hyL4uhENAs6iNtDpuHP9cmYs9mNI7Jxvg40Ho2P/pHMEZ1zP7ixL+rcO1Ww/O1tu3BryDTBsqi5wKXAz9Yw3CloORw3fbkCKRm5aJwQjbvPayLcnDkGKwx5eDL2TyGHe3W60TPpzJWdaHwBvjScTq/sWrekORINmc5/Sjy9rugPBIHB837nBSO2PhC1O+NPI6i5qlvd0gF6ve6iP9FWXIhXqsneynfnbHd+3RomS1uL6oiiB3u5eYxOQWNEBhxGzxPZYqcuv7x+WQfJlJV1sh2WTWPKEq1HiIf6xxagVlSxKIIoCaQJg3XMj65pFrQoByz34IxwzirlNVP0p2BfaWZZag3iNWIUYpZk1hZsVfPqsdbHE3WUSXfT9CUiYKEZTSnpr1HYKI6tiTVGi8ZZL8qUBYwCxNWhslfWqdOwGk9XtbE5qootWJZgMDKD82aLtpcfV+wvrWhJs1OdGJLcrg3KWHXC5JAzjzmOiqO0iAa95V4TEoEWJxdgdNQqwQy7LPJSbcH54kGhWBPRFQt3HBMv+9CAZqeTz+53inW9pW0vbg+bKX6H+2Qp8PUNpntZTl3BHHNck0u2v9//iYf+Jyejhi1VKJ22JEvVi7PPLi2iDhYZhkvX9qjv/ryw/YD92YWzhbKJxlqlCn9GOwDXW9N1+mwZYFF2b6wbdwVPFn3MLLY67XU3zN8yK7fAYiPBHGKljYHjHqs2EsTJ47Xl2kMVQCkY68b2bJk8tqgRi8pRZdDP7Qn8HGmsRh+brIWoF5om3q/yvnDGdO8vri4K6lSx0FDOb/Cc8RYoltc1P5MS91G2vNeLI6tg17Escx/WsAC2xNZsLwqaVyXK9WTWJh8n15yj0El3uTdSk88LioNE0F6iIkt5OUeHUeryck1pdMXkwTB5SCg+Lsw6fqj8sZj9/dBP69w7Qi7/DNgsZbMbOr+EAcs64LesDvin6gjE3PonUL2tYDW/i3oTJzMycOWnS1yP/6C0b/nn4unGzs/jgelHTcOSFU9fhIaj3hBFg/DCU/ij7g8ID7GJxVW57Zaq8u5fLCqL7+YMwYq9JxAdFozb+jbE3KcuRe2bvhKSoN7Bm3BL5AJRyX1uyibXTCtldfV7Y+zemqJqTEb5ixu7YMKzDyBk1NcotgUJaV3rvPVCMk3XcKfYKJ2zcxpeiKdnHzGdM6/r2UB+TpzxO/h18f3/C/kVdWwpwnF3x5EMl0n34fhuIsAhg3lLH7u5unw9vlZwGDrkrsSwoEX4bc1B533Zu5lwFwt31o/WyqDj4YuaoUNdQ8obWx22gewfBx4Im4xaOCZk5k5bB2gUtH8Jim3BuH9bWxFjUcJtumUzADRe66HI6cLI5uO5u5zLuFmAoZFUcDi+S2uN3UczRVHhh9t7yL5evkcjCLm0cA4SkCb6pp1KEPcsFA8HqnbH0t2poqhwnbOgjIFYZBVEZh3EzYk7RL8f+7Rc9XNnJ7Q3GUiXvZl0s2aeeWwmWocmC/aAx1BKgmYYHE4/LDfkQa1rIC7STYLcbpR4GBDK4MgJU8OTb7Bry1Kjzw1puQKTgLi6sOVn4oH68n2XCpQMFvaYrapg1mpUijj3x1h502+b2BohhVm4vupmodr5yTG4peMt+zJtQfjtgEy0B3rjOk8Gtm53UfB5qIZkvn53TDaNc3w8KF4YT7FIWyEDwrZXiKSxauYuNAk6KJycSyl/jAQrJ7aOye71bWbR/6DpxYINDcs/iaFRm0QBUJluObZ6FMXVNVUFZZ50u0Kj/kBfmdD+L/JnRAbli0KESiydsdxFzQbjocmSUb6sY+2SZowxicDAF8XTu6L+FknsazO2lpY/8xxQNRYUgp/3VzaN6lwyx5yIYLDdT9aSqhi2Y5Ra54yEau7RaPFPziT3aBYpRotVQXT6bgyL2iCOdamjN4bBdKeGSqUQ9/5eTc6iJwb9A7hu5KXjueoLxHt1qsYyku7lWTUFi8+iRoNqLiZLOPZ2d7lFPP1PLj/3YjGDu5QKwki6V6dFnf19pUYbUXznOvdMfVm4/nLxPpdM94r0yqYcvkS/v59Jd6XU9UgIyRKqtxKqR2M6RF5oZfFZcE/nXqZhEcZ89IExcu1xGvOXY+iku7wh8xjy2E/NpDvYXl4eXFpapVwX7VGnGzDiczl6xeg17JSzDH/Hv4VQFOCRX9Y5r3SSgZktfz+53d24Yr5cdOtUicSf9/VBy3rVgat/FHM4GxQlYWy1iaKHjeM/nL4ee53zMlBYtTFuWSIrydwoXh7RVi6MZIco1Q2JRFzyInzaYL74HbrRlkr+Vn8tHrIaDcK4tfJnn9/QFU8NaSXdNTnb9UK6YQNPhnyH6kjF5LWHxDiQUjDcto/UH4p3DQOeF4e3Eb3TAi2HwkaXYgBvxv4gHInZL+yUtTJea1pxb2EMw8Dg0Yubl5aeNuwvRgu9XuV3cc7U6JMSBQqqFbi5HJLz1y9uVaN0kFGtiTki5fHoKSgqKhQzfktV8w2W+2hibzH6g4HFaEeGlUFr/d4ILcrF4zF/CsaZ10YpZmTzH/K1avbH6rRI0Vc35j+tSv5O+6sEmxSRn4bHq/0jqs40QCn1WgbLndvoQrw5XxZrHhvYHImxESUliLU7I6goH4/VkxtuqbE97Oc2XIm/3C/7BlkEcGoWxdFWHaWD7D3Rkh3/bfXB0i0IRtK9JLe+YCBZ6XfJQNbqIHuwUYwxibJYQuO10tLWYhRHVsUfO+S1M6CVh34zMlbBYaiUm4xGtmSs3n+iZC8lEzaa9AH461DomTe7cQeuRRy/QharWPayz916tOQ1YBQD9+ZKNqVtRZCWl3j/l4qnV8ZKRolu2SXev+G2W1y5HubvloW3AS29dBVvJWX8FwbJlqL5O4457enemSWv3fZ1KiPMXh1VUUDnfCaaAG6rJteCUgVlo+i1tyDB7LsssdZ4apmguoiKo3i5Tyj3c8ek+1hwgiiy0EvlrBY4et4r5MoRmQfwVgN5fVCaXWod3i332n/QXhh4sS3nf5e2Lv167B+PikdMTjJujN8i1DelTAINaXlRQkv8tfOkWVy0olIYmD9HrJE0uCyxzrE4xXXOFoRfdgZZZ3V5TRhs9y2x0u+DI+KcXRPrT8m1p0v9qq4l62cCvM4M75FB+XOEGuuXlQdKxhuMD8RoLGDGMdlnfaE30wg6XiNUENFpWzGg0gHRjlEi0aEzurFuzD8cem4Uc9tdIR76584VS+sCR1UP90JjEsasZLnv9/Tk1WAVJBKqNRcTI65NlPu6UhfYy8tPBct7na7lZ6U9obyiXk/x0CRH7pM07vM4+rEcoQLuthUf+ZlyQQy1cQGUG2Y+gkuaqCm0uVwmrxxAf8cC4NbZcsFqOxLo94gYPUU0zFyDzxN+REFhoRjFoOR2Jv56QST42YkdMHR9H5Ec9muWgLmPnIeosJDTi5HB3F54agpeayKrrzSoovGXCW7yK6QkeVLwIBw5lY8G8VFiTFKJDY5JpMGS9k/+AhfWyhfBy1h7JpJM/wZj5EVuP5EQ9W1arfQCSzlgna4Izj+F8YnSjIqsconRacd3CWkdWdsntjQQr3VRq+oY1VUmuiY4XisiDnVyd+HOSouFVHaMY68yFQUn9qIoJBLPbZcJ7QMXNi09KoaL8cWSMeiZPR+1bceEw6wabyFAQ7CiAhTG1ccXm2QF+pa+diy3PXpQ9lcJNfOTMDhS9mp/s8QuEOIxGtLrn1KbmIxtvJKp2x+XwdgOxUIkBGcJhn2KMfbGhGHu9kdWO/F4ZZe6iHWUM7OA0u9R8fTqgt8RZcvB7M1HSrK/PC6jn3tSXncRwLEIc7kzJ2Fe0zzuYslmT1l/qKQ6gP3XxUUoiq2FrzfJxfrm3oaTvzN0ZaXfhirJC9GnyglxjU2xL8hwEz0l77lfD1S25kDc+Sb5kMPgrhizNh/GgRN2TNtRWVjJqdwEe1OzERYcJO4nj0YjxoZ0VVVK1mEaxNizNEXRCdhwRF7XXc4Ws+YMTS8SD9WPLkFEqA2H03OECsBxtum2U5EVR1ruOJeXHQqpSxEbXCDMzkowJMb4uLSoBuIaZLLTxls5JNUzJL1TVwvZM1t8SrCPBtO9IT2y4pmouTjfA4JkwZJy4hJrtMF0r8moZPbueoXG0vuidTYT2GKxZ5bYTwzVybZsuWZ0blAlMEybP3Ll/rIoe1Hmn2CnDZMV9k2WKFiyJQrA27vkGvfggKbOW1RCI4BON4int0fL4iJN60qwpIa0/GBkczE6qX58lOf+VhbnQiIQnr4Pl9Y8KfbhEgVy1asbWxtL9mWY7LklGC06zbLWwoYisX6WcJ821tAFR6PK1rXcG9BIM7IqIrIO49r47WJtmGDvZM64hVdgVDXM3iPv9d7esPNsQzAM1W6qIV+XiX0JJ+6iAqHwW5oi27O6ne19pdVlQj0RdnQDrmooiZYS47sMJURxTHUs3i97gmneFzAYBb3zI+WaXWKmtCEvP1Esr/NGVhQHGqdRv5d4CDu+FV0Ti4VaoJSKqBxDJ93lDUEhyDNGT4XZTn98ha6SbmUswwH0HHfirMo56juRdPTPmIafa/4ggvnHfrVzNmdv8o6ZKLIFY+SRG3E8h+Y7lfHJtZ1K97Ryw6T1PxOwQ6/jhc5ZpiGKyTQkLQdSNqEgKALPJ7UXBl5vj+pQst9Wgaxy/T6wFebh5SpTxLe+XrrvtCxs7z+iopkXXhWv7ZCzNB9xZJPFeQuWZmNBIWiTPh+j43cLeeXL0yRbKmAkfYfju+PvpGIhUX/OWYWfZhr9HxdPHwr6ScwVZZJWwiTMYG3XR/fCyYIwURnu7yqpqtlO9Gqzcvq/2jLgeXnqltOvRZM4qv4iO4qeOJpLdXEVLIfHSmYZwBOJsprP3m5z/iaTvYxDKAoOxwe7EkzzLpcyn+ptEFSQjQ8aSXOm16ZvPR1UZaeZJn0TDjcUefr1rkaUkDmv0hAhOcfxZgMZBH9mP2rHrkjxglGkGDO0lfMgVUhHQxB9dA2ua5QpxvaUmLNtBI2HY9uI89UoIdq9WRT7iCgXBfDfanIk3Pf2/YkGA1lUqTZm75JM8iVta3h2UQ6NRkjmEVxT94SQS5eQgxv93HtssqjQo3G8NUbFCI4uCZHnsAQjYQT5GeEyAGUvvNnzfy6ABYOQSNgyj2Bk3azSEnOD6V57IrziMd1qrJiQ2Gfh5loy4WPPqolj8hreUSg/PxYPvZ7nTIffSnWE9HJYtWSxlpfwnTCS7iUpsh+T63iFhXGvVD25AfEhOcIAatOh9FKs5qJjkvXv462MmMqTkAiEnjqEgYkyOVxgf66N+3H1yZizKy13XDvDYhF6cg/uaygLqD/Yj4nat1gkWOkRtbE2o7JYP1z6TBAGc5x4dAlaVcrFsVN5JRUFBtO9JKuuyXJ7ZP1YHGjYTzy9Pl4WJ0uMczQSqqOhtcT13b5uZWFqaQk12ot1OTQ/He3DDwsGfZ3ynmEB32B0Zx6URYbzmp8D8+tp0Ek/Exqlxi0TjxNXHzxdLDCmamTF1hcFNrYZdvTWHNGQ9HayyfPNPnmzSGx4beRFJCC/OESoG8962w9jMKPodUOsdLouMZ7T6PnPjKqLrLxCVIkKFeq0gLOx2YYHx67jp40EsyTDfrRQFm4se3JoSHAUZDUZw4+qIYttygivIkAn3eUNQSHINzatULukuwBBiAn3cZ5ty6HAiHFCrtX1xFSMrrxV9Khd8//tnQd0E1f2xq9xN7hSbIrpvbdAIIFAyEJ6Aum9EFI2ZdMTNtn0XXazm57803sjvfdGSEILvffeuw0YbGP7f+6bedLTeEYajUZW+37n6FiShRiPRjPv3vvd7748jRZv2Elb3v2reNm3h/vRovImQib9yqVHeCvctebGPipmLCdVV9JFB98SfcwMO6aKvjqeec0VyqojqZQa0C0jO1kHRUIif6+4W7jqQ7q6435xob33s0Wacc0SLRD/urIvVVM9unJoW3ERNqWwm6cCeU/6u5SUVEMfzd7o/ULrgfL/7dSSE7xdlvNreaRHww6UemgXfV78nniKZ+PyxVDIsQzvdecJnf0vNnTJ+rFl31L9lGox7snTb6f3c7+zQwuOuZfb/3tpf2OL7ZOoT94h2lNW6R3RtFozFlqU3FWYw43sWmh9geb/g9UQLBTY/Tk1z04RVX2PhJC3q6aKtqe1pE3UmEZ1LaJWDS2yuqLarb3XqL3vUWZSOf2ybIfXJEffXzNSB9CBmgwR1A60ykxzP6Fe0ftb/hTxkyvwnqrhBu0iPKW8rcf9OeBCb8CV4ke37V9Sg+TDwh3e0yuuB8g70luLAJ+NgNo3CXAB5ypQe63367LG2r9nsyVPwoKNilg6ta9xcDJifRZvs9I5ItkzZeUurxRel7NupsaRGeliZ/HYvK+4e2KBFpBMWrqjVqV7fkl6fFa6pY8Dq0cytGCEJ0h4kmt6cmfqXu37ODwYiahKyyPFjxNztYWnR7VUcYCoXDumZ+xKi/9KNyuvGrYXycxxxdrizRMQVld5qppc6ebchsfTwi7cmqJXZc7O1z6735brFS/+THUjtUlb06NDksukN/A4BF+YoimePpi1wTt2SU/w/laljRv967B2lJ6S7H/sVNPeIsnz99baOe2l39Zox7RiovbxtsbBeRToSdAeB7Ugk8cybS055FPpXqm3BQwPphrN1yH2l+AFfaF2LLDqyhtc1oi535sqs6lxdjp1LIySgKm7ZkTZdOcflJ9B4jo8TR/dJSvd66mZp6IbdMtI8UDxI3PrLBrYKld8dJOW7fDp596T0ii6ph1wAokPlW3fUlpykkiqeRRvetC9kbSWrSPbNgw+gWkj6M7cs5SaplcISf5imdDTK92byjM9yW8QJK20/TugnrZ2kuNP4wEE3bFGcqon6E5TPj52L69vFgTbhSXnR2rB9b8qH6Z+WTwjs5T+eP56arp3DlXWJNMTh8eIasC7447071zJVeUT/i0SBBzk3dh8mciO7jpQQQ+98j7R8m9EgPx0xUmi0sKBsl+KB3jcj2/Km0x5Wam0bNs+euT7pVSjm758eqgPtSzIEoZgfuHALy2bsnYvons7axeTuz5ZQIc2LSLavpgqKYU+O9RHJBYusaoAM9xPf8ZLYoxT6x0/0d97aRKm8R/Pp9ffmyiqyfsoiyZV9RKBbcALVaeTiOo3oeSy7fRAZ20xKHrKWdq8RRsj9P2BDlSYkx54bi8b6OlGI/e10CqiL/6mj2gSJmpEXx7oLC7Md59k6L82C/LqN6GkAzvo4R7aIuWJH1doF7fl34nH3xzUFmhXHRPgc2QjsLxWlHxwJz3Y4k9PIob74mmRZtD3akkfIbUef4I+Y94KXdbYaNUndGz7HJFlFtVuXi3o868/2q7tp4D7S5qjZDejeuWldF1r7biQbvO0Q1tQzy8vsictl3TUAqx2uyeLSgwrK9gJXntPbYH6yy7tuBhhd34ou5jntxGBxF9yN4lxRZ5Kpr7IX3ZQC1YHtImSxZFK837iR0/Sqrqz1u/Rxr5xQFihLZi2V+eK/RVVVXq30IOJtqUzxfePPRU8I3p0efnU0gKh8BjWMbSgu0fVYu39Vu3SgiC9yn04pT7tpyzR0hOX+1hFr5ieUH+Zp4dX2xdbxEjB6qQU2kINqXNRjrVSzO/7azLTPlWacd3kFTu191f8FRaX5YjPOmrG3+lKtIL139MZndKECue/3y3z6ef+7kBn4fZ8Zn+T9h4j3KrGgU3ZJKHWWbF9v5Yw5kp/2S6xj+eUNxNmUr1b2ExssKEa5wi2zKTBLdJ8VT36uLCZukFW0AoF/ftxdJr2ffO06HiUQnyeT6I+xXnR04vbtI92Ha7YT9e23eE7w1gPuuccKHCerCvsTpTWgKi8lE4q0ir/0vxPBt2bq7TriWVRo67pfKIYhVdv7xo6v+Vej5O4GnQvOpjvbj+3JKepUMjxdfisIu2aPl0mQfSe7nVl2rkVlW4HtNKUF81L5oiEKJsa2hpDHAMg6I7JSrd2N1WXmctKt6NFg8qwO8WJpF7VIZrY4FG6Nusnuiz5W/Gr79vfRWPPOJlevrS/uQzcCLum6wZV6Z+Oo49HNxAmW0NKtMr0t1X9aTU1p3tP6Wavz40ry/xeSz6mh0/QFgLTJn9PSfu30r6aTJpBPcTM6oDbll1E1E8L2C6s/oIaNUgT41O+eOcZ8dykqp6U1qAhvXBR/8DbxYZZerb1isPv0kk9ikQltMHid7S/8XB/altUQA+N7h7470tJI+qr7a9TKjlzW4/mbdhLy2fw/q+hdfWKaQfl08WDWtvLYuuV857bP6Um9ZNFZvyZH5ZQDcvx2SSnurtw827ZMIDjKycXuAWBx1qXfi1mc7IR2tWv/UFViz4Tz391eICo1AaUtPF76Q66ow98SDkph2nq6l305defiznfByiDJlX3pnFD2wR2ouUgObeY6NBeuquNtnhiif+6VYtFD1pVUgrNrmxFbRrVtx5PY3Rx5Ys4b1vWXE9VbN+hSk+l+9c9BUEG3SxvTaKkrfNpXG/tAvzhrA1Ehys8C8fl1c2FgZNteSSjV2pOaagthn5YvN2n0j1vX3b0yFkttr3BzrnCYIaTJb+z2Zde5T5cL532U2b8VbnVCkm9FEouWUcXdtQq3OzAT4fLPZXXVdXNRPtIbpbDUW961SpvzwJRAdpSckgYYsmguzSlYXRVrMKJHhQX7/1TnDf5PCjmDOsS5T1pTUUCuG8rh4EEGztyLmznn1Q/NYl27i/XfAr07+KhtAKhKOIqut+KcV3C7Uyc/KqupPFNZ4lFLfuIfDl1PtE2TS47pbobnda7ub1xg3qfdMrG6TS2t1bVe/yH5VTD3hpcbUxtJfbBOUcU2682cpsEt/1UH6ZLmmvnOc8kFP2zW1reSAT5QQeBetDdvHSeaG1j3xP2V5BB9xbSgvje0dR6wdcn3RPjlEztM/pmwVbR3y1GuLIkfE+e8z50oQDQRswOStWupzPX7faZ0b2qXLuOdrdzPa0L2ONE/36fnr/aNOievjfH/X5uSbM+4seR9bX/U45glJXubVX1xRqSi0HAmZIgees86lWY6lG7xAMIumONeslUocvK0/SgmxcNNSLoDvGizv3Al35NlNuSUkvX023VL1NKUjXVtB9JJ110izDJCmrhcMJ/tIx1VTk1+WYcvTIylc5K1jLpP2WfSq9eeoT9CyZ/CbknsrKMRm58UlTHRyXrDr3VvemhM/sJCZH9GatJlLJuMj1zYkPKrXeQhu7XKuZfVh1JT57XW0jLbCGcRZOo3qof6emM5+jtoXvpjGTN4GtO4Rn03lWD7DviiuptEqWtm0xXdNUcx+f9qlWAJ1V0poL6aXTBQIOpmxXcW5+ZT0mlm+jx/loG9rdfvxOZ8t01DWhdalshHbSFnjxJWvUTvXBinriIdCyZQsmV+2hzTQFtz+8jevJtwf3muS1FRf+pjloFv2Tam+Ln91X9qFvLJnT9sR0Cvw+rKfR+wrYbPhISQ+6p/OizT8RzC6tbi4Ue/422qxW6G3GTzT9Rh0YZoheMncxl0L3kcDPRH25bcsi9SazS4IVS+jzxc+baPbRz3WLNlDApi7ZSQWDXciPNtcC1V5K22OKRdaKfTF/ob6xuSE1zM4IL5OsKfdvZJ2Jk+wbevm496C5J5kAwKf76uVV5r74PztOdb79duIUqd64S5n8HKJN2UC6d3qe58/+DlS7J6WL27vHNDnqNfvR+1W3VefEvLTdUuuvtXEp/aZnkldvrSa+VVU1Ca8XQe4STDpXQ6BaaUkMoT/QAbns9vdUj2hJgeptVo2Xv0tl9tWPth6+1EZdLq4tpJ+XSaP15WzL+Ztw2UkNXNFkieorZnG3jYs0HZNrB4uCSlZK2w8SPo5IWeCSmQmKuy8vX1RTSkW0LavvKBEIEl0lUr3QDHd9aOya+5WBNVwqtrNC+H0G3G4QbvfrfZMcUYc7FE1FEr7ve0726ukhcm1rkOwzy9GRE67IFohNmw+6DWnVRr3SvPKSdk7tGS9CtyJC7ViwUAS63q4k55rpJ4urDjYSahxO8rtNEUwm2J+24mbt+r0+le29NA7FWisvpEOEmr1grqtRU0SmNtKTGn3EiMcfREINU6kG3zEGzwRkTcqWbyW1OdNlXRL0vJGrchaj3BZR09uvOezhZgp3TQmQej/h+NGUkVdLBwn708C3XBmdSwleBkx8XF0ua9y6Nz/yUxmVoztmdhp9PY/rakMGpVXjdfXLg9OtpXtpYKkzaS+upiM646Foa3C4IuVrjTkQnPaJt4oL36agZmkT/cIfj6aFrL/E/d9lMOqxns2/M/4O6Nk6l46o1Y69fa/rS/87q6V/Wb+wp7qWZrwze84WYWS4THr9V96T/nd23tmO5v749XrzWVFP+Hw/RW5cPoBsyvha/+iFlGD138RH2KiKyoj/kJnF36I636e9H59LpKVpf9o72ZwuvAFtKCoaD7qR6lLT2d7p7ULoYfdZ0j5aImVnVQVTlzwjmuGh1NFF6rpDS39RVW0C/8fMcj5HMsppiOrG7nxmzZnQ8XvxouOlnsfDmxMDPv2tJmeXV3IOXFPxYKL1anLd7HuVn1BM9+zw+TC4aN9U0Eq7lUSONNJ5fspuKi+mJDTVZJ/cOVusmalurtIVd3Fa6lUCw3b4/hdKGP78F87TjdmV1U8pOT6VTe2n9mY5gRQn7V7BxVcFW70gbffG8Sh/JlhCV7qwCz+L49Eba93iyEnQvOdRQVDstTS7tVAh1n4Lj87TvH095kN/F1RXaPj4iGvq5jT3C6TniuvxAr53Ur1U+HUNaK9Jv1T1Ecpfl1UH5wrCQbPXXNEYP1ncu1VRV86rbikpjp2CNrPSgu8Gm38W5k1X7H05Z7JmDvL6mSfDScllc4Os2EZ1RtN1bRdeD+aWHGorlRk+7Uvi6QuyPJEravpgu7q6tA76avsgzGmttTSEND8X4TVfIpG7+kzoVZnuri/p5Y0tNgXCfrzWdJJK01J2uN02nQW20z+u7+Rs9378NNU1EYiYs10JObvK1vWyVOF5YRSOSFIp7OZzLQ6BQu4b1r79dXCejRikUIgi6Y5CKZO3gS9X9d6pJe9wglJ5uY1B6+jNE104jOv3/NDdRp/A4ijHPC9diQcvBlHnuq5QcbHZaBhsDrxZ3k379NyUfLiNq1JE6HKO5dQfFiHu1nvNtWi8e3y++5CUa2iWIIE0dOcWj1zgzx+Q0p5TRzzoz7tBl4WkL3qUPBq6h/KT9tCetiG666mrvrHDb76VVM9h5/u8dNtI5aVoAf9T548Xc6qA48RER4NKyr6jld5dRl+oVVJWcQWdd9y/RDxkUnNBhh+V9W+jKmSdRAzpI1KQbXXnxJfaTCrLComf/2234iB4e3ZVG6uqHaSn96eEzewX3GXBCoKPWc8sqiibZ6dSkTJPara9uTIdTG9D5dpUGhrFFbDp341AtkNq2SpNdLq1qITLhQQeYPIUgs4CSDu6mscVa9fLH+WuJyjQTp401jUTCIWrR+7o7Vy8XEwJYkrt1kyat3liZrS944zjo1oOJemsm0zn9tQBl0Xwt4FlTUyQqjCEnUPVJFb3TtIrrNO7rLtWOlY1V+WK/Bx0ExSp6Ba+/7szMVf+yrSuUamnD4JKjRnQ1S4+a5Z65sod1Z/QVFQWiVYiD2qiCpbm6oVrarFfoqbO70V+SZ4vHW5oeJ6Z2BBWo6PPhuSd8XN8cqp9aQx0rtf09s7ojXXesNp4yKIR0OIloxxK6oo+2fpg2Szu/76zJEaqQgGMWA5yDBqatFRVS9lU4tF1TDq2vKaSOTbIjO5/bKoGkS5pH5y4XSeZ9Gxd7AuKDlEEjA81A94f+3tzmMqRFPW9ft5503lZTEPwIw3DD57nULBHont1aU/XMXLBQJHUrKJW2Ux6NCDapbRcuSnHebedy6tykvldirle6d1M2tQtHhT1RaKT5M3VP30Z/3nWcMCOOBxB0x0Gl+7Cble5wwOOTOIC/8leiy77WKrpO+cv9RB1Gec0/LvhAq+wEC1cnLvxYq5by+1z4ESXp/XmO4L7na6dr1fjLv9UukE6NlnJbiotI/R+1mar5Q66iHi0dvF+jDtr71VRT0jtnCTd5rrI16qJV2oKicUfP2BIO4pnkI8ZSVn6QkkEZ3J72lBbES3geu5NsdN+LtZ9z3qbRGbOpYdI+MT7u3zdfI/q5g0aXmCcv+4quG96OuiVpEuAlNa3oyqHtrN3sreCKCvcmVpXTIJonjAPb1WhZ+OU1zWl0n+bBZ+H5eG+vjUs5MVuTFk6drcnX2fm9lOpHZz+3oVKfsmWOZ57sxg3aft5Rkyt63INKvsQaLG/lhWLZTrq8gzajPb1Eq7Ktrm4WfGLHT5Wg6NAqykxNFiaW+3ZqiY1tNfnCfyGiM6Mj0B+Yt3OWqJiy70bpZi1AXltTFLz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+ "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axes = plt.subplots(2, 1, figsize=(10, 5), sharex=True)\n", + "axes[0].plot(times, states[:, 0], label=\"$x_1$\")\n", + "axes[0].plot(times, states[:, 1], label=\"$x_2$\")\n", + "axes[0].plot(times, states[:, 2], label=\"$x_3$\")\n", + "axes[0].set_ylabel(\"state\")\n", + "axes[0].legend(loc=\"upper right\")\n", + "axes[1].plot(\n", + " times, observations[:, 0], label=\"obs ($x_1$ + noise)\", color=\"C0\", alpha=0.8\n", + ")\n", + "axes[1].set_ylabel(\"observation\")\n", + "axes[1].set_xlabel(\"time\")\n", + "axes[1].legend()\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6.4 Inference: NUTS + Filtering (EnKF)\n", + "\n", + "For continuous-time models we use **Filter** with a filter supported by CD-Dynamax. The **default** (and a good choice for nonlinear models) is the **EnKF** (ensemble Kalman filter). Other options include **EKF** and **UKF** (both Gaussian approximations), and **DPF** (differentiable particle filter) for non-Gaussian observation models or initial conditions.\n", + "\n", + "We pass the observed values `obs_values` along with `obs_times` to the model for inference." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "sample: 100%|██████████| 200/200 [03:07<00:00, 1.07it/s, 7 steps of size 8.62e-01. acc. prob=0.96]" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Posterior rho mean: 28.189029693603516\n", - "True rho: 28.0\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "from numpyro.infer import MCMC, NUTS\n", - "\n", - "from dynestyx import Filter\n", - "from dynestyx.inference.filters import ContinuousTimeEnKFConfig\n", - "\n", - "with Filter(filter_config=ContinuousTimeEnKFConfig(n_particles=50)):\n", - " nuts_kernel = NUTS(l63_model)\n", - " mcmc = MCMC(nuts_kernel, num_warmup=100, num_samples=100)\n", - " mcmc.run(jr.PRNGKey(1), obs_times=times_train_full, obs_values=observations_train, predict_times=times_test_full)\n", - "posterior = mcmc.get_samples()\n", - "print(\"Posterior rho mean:\", float(jnp.mean(posterior[\"rho\"])))\n", - "print(\"True rho:\", rho_true)" - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "sample: 100%|██████████| 200/200 [03:07<00:00, 1.07it/s, 7 steps of size 8.62e-01. acc. prob=0.96]" + ] }, { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6.6 Rollout: Filter + Simulator with `predict_times`\n", - "\n", - "To evaluate **rollout quality**—especially forecasts into the future—use **Filter + SDESimulator** with `predict_times`. Use a dense time grid from `obs_times[0]` to `obs_times[-1] + T` to show fitting between sparse data points (relevant for continuous time) and rollout past the final filtered time. The filter conditions on observations; the simulator rolls out trajectories at `predict_times`, producing `f_predicted_states` and `f_predicted_observations`. With `n_simulations > 1`, you get multiple trajectories for uncertainty bands.\n", - "\n", - "**Shape convention:** simulator outputs always include a leading `n_simulations` axis (size 1 by default). Under `Predictive`, there is also a leading `num_samples` axis. The helper code below normalizes shapes for plotting." - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Posterior rho mean: 28.189029693603516\n", + "True rho: 28.0\n" + ] }, { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "rollout shapes: (2, 30, 799, 3) (2, 30, 799) (2, 2001, 3) (2, 2001, 3)\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rho_post_mean = jnp.mean(posterior[\"rho\"])\n", - "n_sim = 30\n", - "num_samples = 2 # Change this to 1 or >1 to test both cases\n", - "\n", - "predictive = Predictive(\n", - " l63_model,\n", - " params={\"rho\": jnp.array(rho_post_mean)},\n", - " num_samples=num_samples,\n", - " exclude_deterministic=False,\n", - ")\n", - "with SDESimulator(n_simulations=n_sim, source=\"em_scan\"):\n", - " with Filter(filter_config=ContinuousTimeEnKFConfig(n_particles=50, record_filtered_states_mean=True, record_filtered_states_cov_diag=True)):\n", - " samples = predictive(\n", - " jr.PRNGKey(99),\n", - " obs_times=times_train_full,\n", - " obs_values=observations_train,\n", - " predict_times=times_test_full,\n", - " )\n", - "\n", - "pred_states = jnp.asarray(samples[\"f_predicted_states\"]) # (num_samples, n_sim, T_pred, 3)\n", - "pred_times_arr = jnp.asarray(samples[\"f_predicted_times\"]) # (num_samples, n_sim, T_pred)\n", - "filtered_means = jnp.asarray(samples[\"f_filtered_states_mean\"]) # (num_samples, T_train, 3)\n", - "filtered_cov_diag = jnp.asarray(samples[\"f_filtered_states_cov_diag\"]) # (num_samples, T_train, 3)\n", - "\n", - "print(\n", - " \"rollout shapes:\",\n", - " pred_states.shape,\n", - " pred_times_arr.shape,\n", - " filtered_means.shape,\n", - " filtered_cov_diag.shape,\n", - ")\n", - "\n", - "# flatten_draws merges (num_samples, n_sim, T, D) → (num_samples*n_sim, T, D).\n", - "# Filter outputs (f_filtered_states_mean, f_filtered_states_cov_diag) are (num_samples, T, D) — no n_sim.\n", - "pred_draws = flatten_draws(pred_states)\n", - "pred_t = flatten_draws(pred_times_arr)[0]\n", - "filtered_mean_med = jnp.percentile(filtered_means, 50.0, axis=0)\n", - "filtered_std_med = jnp.sqrt(jnp.percentile(filtered_cov_diag, 50.0, axis=0))\n", - "\n", - "# Plot: true states, filtered means, observations, predicted CI\n", - "fig, axes = plt.subplots(3, 1, figsize=(10, 7), sharex=True)\n", - "lo = jnp.percentile(pred_draws, 2.5, axis=0)\n", - "hi = jnp.percentile(pred_draws, 97.5, axis=0)\n", - "state_labels = [r\"$x_1$\", r\"$x_2$\", r\"$x_3$\"]\n", - "for i, ax in enumerate(axes):\n", - " ax.fill_between(pred_t, lo[:, i], hi[:, i], alpha=0.3, label=\"95% CI (rollout)\")\n", - " ax.fill_between(\n", - " times_train_full,\n", - " filtered_mean_med[:, i] - 2 * filtered_std_med[:, i],\n", - " filtered_mean_med[:, i] + 2 * filtered_std_med[:, i],\n", - " alpha=0.25,\n", - " color=\"green\",\n", - " label=\"Filtered ±2σ\",\n", - " )\n", - " ax.plot(times_train_full, states[mask_train_full][:, i], \"k--\", label=\"True (train)\", lw=1)\n", - " ax.plot(times_test_full, states[~mask_train_full][:, i], \"k:\", lw=1.5, label=\"True (future, held-out)\")\n", - " ax.plot(times_train_full, filtered_mean_med[:, i], \"g.-\", markersize=4, label=\"Filtered mean\")\n", - " if i == 0:\n", - " ax.scatter(times_train_full, observations[mask_train_full][:, 0], color=\"C3\", marker=\"x\", s=30, label=\"Observed\")\n", - " # ax.scatter(times_test_full, observations[~mask_train_full][:, 0], color=\"C4\", marker=\"+\", s=30, label=\"Future (held-out)\")\n", - " ax.set_ylabel(state_labels[i])\n", - " ax.legend(loc=\"upper right\", fontsize=8)\n", - " ax.axvline(times_train_full[-1], color=\"gray\", linestyle=\":\", alpha=0.7)\n", - "axes[0].set_title(\"Filter + SDESimulator: rollout with predict_times\")\n", - "axes[-1].set_xlabel(\"time\")\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "from numpyro.infer import MCMC, NUTS\n", + "\n", + "from dynestyx import Filter\n", + "from dynestyx.inference.filters import ContinuousTimeEnKFConfig\n", + "\n", + "with Filter(filter_config=ContinuousTimeEnKFConfig(n_particles=50)):\n", + " nuts_kernel = NUTS(l63_model)\n", + " mcmc = MCMC(nuts_kernel, num_warmup=100, num_samples=100)\n", + " mcmc.run(jr.PRNGKey(1), obs_times=times_train_full, obs_values=observations_train, predict_times=times_test_full)\n", + "posterior = mcmc.get_samples()\n", + "print(\"Posterior rho mean:\", float(jnp.mean(posterior[\"rho\"])))\n", + "print(\"True rho:\", rho_true)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6.6 Rollout: Filter + Simulator with `predict_times`\n", + "\n", + "To evaluate **rollout quality**—especially forecasts into the future—use **Filter + SDESimulator** with `predict_times`. Use a dense time grid from `obs_times[0]` to `obs_times[-1] + T` to show fitting between sparse data points (relevant for continuous time) and rollout past the final filtered time. The filter conditions on observations; the simulator rolls out trajectories at `predict_times`, producing `f_predicted_states` and `f_predicted_observations`. With `n_simulations > 1`, you get multiple trajectories for uncertainty bands.\n", + "\n", + "**Shape convention:** simulator outputs always include a leading `n_simulations` axis (size 1 by default). Under `Predictive`, there is also a leading `num_samples` axis. The helper code below normalizes shapes for plotting." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6.7 Back-tested real-time forecasting: sparse observations, dense predictions\n", - "\n", - "We generate a **new** synthetic dataset and apply the learned model in a \"real-time\" scenario: observations arrive at sparse times (e.g., every 50th timepoint), and we produce dense posterior-predictive trajectories by setting `predict_times` to a finer grid than `obs_times`. The filter conditions only on past and current observations; the simulator predicts at the dense times, effectively **interpolating** between sparse data points. This back-test mimics online forecasting where we would not have future data.\n", - "\n", - "**Note:** A **smoother** (which uses future observations to refine past estimates) would yield more accurate interpolations than a filter, since it can leverage information from both past and future. Here we use filtering to reflect the causal, real-time setting." - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "rollout shapes: (2, 30, 799, 3) (2, 30, 799) (2, 2001, 3) (2, 2001, 3)\n" + ] }, { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "backtest synthetic shapes: (1, 1, 1500) (1, 1, 1500, 3) (1, 1, 1500, 1)\n", - "interp shapes: (3, 50, 1500, 3) (3, 50, 1500)\n" - ] - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Generate a NEW dataset for back-testing (different trajectory)\n", - "key_backtest = jr.PRNGKey(123)\n", - "times_backtest = jnp.arange(0.0, 15.0, 0.01) # shorter window for demo\n", - "with SDESimulator(source=\"em_scan\"):\n", - " synthetic_backtest = Predictive(\n", - " l63_model,\n", - " params={\"rho\": jnp.array(rho_true)},\n", - " num_samples=1,\n", - " exclude_deterministic=False,\n", - " )(key_backtest, predict_times=times_backtest)\n", - "print(\n", - " \"backtest synthetic shapes:\",\n", - " synthetic_backtest[\"f_times\"].shape,\n", - " synthetic_backtest[\"f_states\"].shape,\n", - " synthetic_backtest[\"f_observations\"].shape,\n", - ")\n", - "states_backtest = synthetic_backtest[\"f_states\"][0, 0, :, :]\n", - "observations_backtest = synthetic_backtest[\"f_observations\"][0, 0, :, :]\n", - "times_backtest = synthetic_backtest[\"f_times\"][0, 0, :]\n", - "\n", - "# Sparse observations: every 50th timepoint (as would arrive in real time)\n", - "downsample = 50\n", - "obs_times_sparse = times_backtest[::downsample]\n", - "obs_values_sparse = observations_backtest[::downsample]\n", - "\n", - "# Dense predict_times: full grid (interpolation between sparse obs)\n", - "predict_times_dense = times_backtest\n", - "\n", - "# Apply learned model: posterior-predictive with Filter + SDESimulator\n", - "predictive_interp = Predictive(\n", - " l63_model,\n", - " params={\"rho\": jnp.array(rho_post_mean)},\n", - " num_samples=3,\n", - " exclude_deterministic=False,\n", - ")\n", - "with SDESimulator(n_simulations=50, source=\"em_scan\"):\n", - " with Filter(\n", - " filter_config=ContinuousTimeEnKFConfig(\n", - " n_particles=50,\n", - " record_filtered_states_mean=True,\n", - " record_filtered_states_cov_diag=True,\n", - " )\n", - " ):\n", - " samples_interp = predictive_interp(\n", - " jr.PRNGKey(42),\n", - " obs_times=obs_times_sparse,\n", - " obs_values=obs_values_sparse,\n", - " predict_times=predict_times_dense,\n", - " )\n", - "\n", - "pred_states_interp = jnp.asarray(samples_interp[\"f_predicted_states\"]) # (num_samples, n_sim, T_dense, 3)\n", - "pred_times_interp = jnp.asarray(samples_interp[\"f_predicted_times\"]) # (num_samples, n_sim, T_dense)\n", - "\n", - "print(\"interp shapes:\", pred_states_interp.shape, pred_times_interp.shape)\n", - "interp_draws = flatten_draws(pred_states_interp)\n", - "pred_times_interp_1d = flatten_draws(pred_times_interp)[0]\n", - "\n", - "# Plot: sparse observations (scatter) vs dense posterior-predictive interpolation (bands)\n", - "fig, axes = plt.subplots(3, 1, figsize=(10, 7), sharex=True)\n", - "lo = jnp.percentile(interp_draws, 2.5, axis=0)\n", - "hi = jnp.percentile(interp_draws, 97.5, axis=0)\n", - "state_labels = [r\"$x_1$\", r\"$x_2$\", r\"$x_3$\"]\n", - "for i, ax in enumerate(axes):\n", - " ax.fill_between(\n", - " pred_times_interp_1d,\n", - " lo[:, i],\n", - " hi[:, i],\n", - " alpha=0.3,\n", - " label=\"95% CI (interpolation)\",\n", - " )\n", - " ax.plot(\n", - " times_backtest,\n", - " states_backtest[:, i],\n", - " \"k--\",\n", - " label=\"True state\",\n", - " lw=1,\n", - " )\n", - " if i == 0:\n", - " ax.scatter(\n", - " obs_times_sparse,\n", - " obs_values_sparse[:, 0],\n", - " color=\"C3\",\n", - " marker=\"x\",\n", - " s=40,\n", - " zorder=5,\n", - " label=f\"Observed (every {downsample}th)\",\n", - " )\n", - " ax.set_ylabel(state_labels[i])\n", - " ax.legend(loc=\"upper right\", fontsize=8)\n", - "axes[0].set_title(\n", - " \"Back-tested real-time forecasting: sparse obs, dense predict_times\"\n", - ")\n", - "axes[-1].set_xlabel(\"time\")\n", - "plt.tight_layout()\n", - "plt.show()" + "data": { + "image/png": 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", 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" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "rho_post_mean = jnp.mean(posterior[\"rho\"])\n", + "n_sim = 30\n", + "num_samples = 2 # Change this to 1 or >1 to test both cases\n", + "\n", + "predictive = Predictive(\n", + " l63_model,\n", + " params={\"rho\": jnp.array(rho_post_mean)},\n", + " num_samples=num_samples,\n", + " exclude_deterministic=False,\n", + ")\n", + "with SDESimulator(n_simulations=n_sim, source=\"em_scan\"):\n", + " with Filter(filter_config=ContinuousTimeEnKFConfig(n_particles=50, record_filtered_states_mean=True, record_filtered_states_cov_diag=True)):\n", + " samples = predictive(\n", + " jr.PRNGKey(99),\n", + " obs_times=times_train_full,\n", + " obs_values=observations_train,\n", + " predict_times=times_test_full,\n", + " )\n", + "\n", + "pred_states = jnp.asarray(samples[\"f_predicted_states\"]) # (num_samples, n_sim, T_pred, 3)\n", + "pred_times_arr = jnp.asarray(samples[\"f_predicted_times\"]) # (num_samples, n_sim, T_pred)\n", + "filtered_means = jnp.asarray(samples[\"f_filtered_states_mean\"]) # (num_samples, T_train, 3)\n", + "filtered_cov_diag = jnp.asarray(samples[\"f_filtered_states_cov_diag\"]) # (num_samples, T_train, 3)\n", + "\n", + "print(\n", + " \"rollout shapes:\",\n", + " pred_states.shape,\n", + " pred_times_arr.shape,\n", + " filtered_means.shape,\n", + " filtered_cov_diag.shape,\n", + ")\n", + "\n", + "# flatten_draws merges (num_samples, n_sim, T, D) → (num_samples*n_sim, T, D).\n", + "# Filter outputs (f_filtered_states_mean, f_filtered_states_cov_diag) are (num_samples, T, D) — no n_sim.\n", + "pred_draws = flatten_draws(pred_states)\n", + "pred_t = flatten_draws(pred_times_arr)[0]\n", + "filtered_mean_med = jnp.percentile(filtered_means, 50.0, axis=0)\n", + "filtered_std_med = jnp.sqrt(jnp.percentile(filtered_cov_diag, 50.0, axis=0))\n", + "\n", + "# Plot: true states, filtered means, observations, predicted CI\n", + "fig, axes = plt.subplots(3, 1, figsize=(10, 7), sharex=True)\n", + "lo = jnp.percentile(pred_draws, 2.5, axis=0)\n", + "hi = jnp.percentile(pred_draws, 97.5, axis=0)\n", + "state_labels = [r\"$x_1$\", r\"$x_2$\", r\"$x_3$\"]\n", + "for i, ax in enumerate(axes):\n", + " ax.fill_between(pred_t, lo[:, i], hi[:, i], alpha=0.3, label=\"95% CI (rollout)\")\n", + " ax.fill_between(\n", + " times_train_full,\n", + " filtered_mean_med[:, i] - 2 * filtered_std_med[:, i],\n", + " filtered_mean_med[:, i] + 2 * filtered_std_med[:, i],\n", + " alpha=0.25,\n", + " color=\"green\",\n", + " label=\"Filtered ±2σ\",\n", + " )\n", + " ax.plot(times_train_full, states[mask_train_full][:, i], \"k--\", label=\"True (train)\", lw=1)\n", + " ax.plot(times_test_full, states[~mask_train_full][:, i], \"k:\", lw=1.5, label=\"True (future, held-out)\")\n", + " ax.plot(times_train_full, filtered_mean_med[:, i], \"g.-\", markersize=4, label=\"Filtered mean\")\n", + " if i == 0:\n", + " ax.scatter(times_train_full, observations[mask_train_full][:, 0], color=\"C3\", marker=\"x\", s=30, label=\"Observed\")\n", + " # ax.scatter(times_test_full, observations[~mask_train_full][:, 0], color=\"C4\", marker=\"+\", s=30, label=\"Future (held-out)\")\n", + " ax.set_ylabel(state_labels[i])\n", + " ax.legend(loc=\"upper right\", fontsize=8)\n", + " ax.axvline(times_train_full[-1], color=\"gray\", linestyle=\":\", alpha=0.7)\n", + "axes[0].set_title(\"Filter + SDESimulator: rollout with predict_times\")\n", + "axes[-1].set_xlabel(\"time\")\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6.7 Back-tested real-time forecasting: sparse observations, dense predictions\n", + "\n", + "We generate a **new** synthetic dataset and apply the learned model in a \"real-time\" scenario: observations arrive at sparse times (e.g., every 50th timepoint), and we produce dense posterior-predictive trajectories by setting `predict_times` to a finer grid than `obs_times`. The filter conditions only on past and current observations; the simulator predicts at the dense times, effectively **interpolating** between sparse data points. This back-test mimics online forecasting where we would not have future data.\n", + "\n", + "**Note:** A **smoother** (which uses future observations to refine past estimates) would yield more accurate interpolations than a filter, since it can leverage information from both past and future. Here we use filtering to reflect the causal, real-time setting." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6.5 Full observations and high-frequency, low-noise data\n", - "\n", - "A common special case is **full observations** with **high-frequency, low-noise** measurements. Under that assumption we can **accelerate inference** dramatically at the expense of some bias (depending on how valid the assumption is). See the [deep dive on this topic](../../../deep_dives/l63_speedup_dirac_vs_enkf/) for details." - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "backtest synthetic shapes: (1, 1, 1500) (1, 1, 1500, 3) (1, 1, 1500, 1)\n", + "interp shapes: (3, 50, 1500, 3) (3, 50, 1500)\n" + ] }, { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Next:** [Part 6b — ODEs](../06b_odes/)" + "data": { + "image/png": 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+ "text/plain": [ + "
" ] + }, + "metadata": {}, + "output_type": "display_data" } - ], - "metadata": { - "kernelspec": { - "display_name": "Python (dynestyx2)", - "language": "python", - "name": "dynestyx2" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" - } + ], + "source": [ + "# Generate a NEW dataset for back-testing (different trajectory)\n", + "key_backtest = jr.PRNGKey(123)\n", + "times_backtest = jnp.arange(0.0, 15.0, 0.01) # shorter window for demo\n", + "with SDESimulator(source=\"em_scan\"):\n", + " synthetic_backtest = Predictive(\n", + " l63_model,\n", + " params={\"rho\": jnp.array(rho_true)},\n", + " num_samples=1,\n", + " exclude_deterministic=False,\n", + " )(key_backtest, predict_times=times_backtest)\n", + "print(\n", + " \"backtest synthetic shapes:\",\n", + " synthetic_backtest[\"f_times\"].shape,\n", + " synthetic_backtest[\"f_states\"].shape,\n", + " synthetic_backtest[\"f_observations\"].shape,\n", + ")\n", + "states_backtest = synthetic_backtest[\"f_states\"][0, 0, :, :]\n", + "observations_backtest = synthetic_backtest[\"f_observations\"][0, 0, :, :]\n", + "times_backtest = synthetic_backtest[\"f_times\"][0, 0, :]\n", + "\n", + "# Sparse observations: every 50th timepoint (as would arrive in real time)\n", + "downsample = 50\n", + "obs_times_sparse = times_backtest[::downsample]\n", + "obs_values_sparse = observations_backtest[::downsample]\n", + "\n", + "# Dense predict_times: full grid (interpolation between sparse obs)\n", + "predict_times_dense = times_backtest\n", + "\n", + "# Apply learned model: posterior-predictive with Filter + SDESimulator\n", + "predictive_interp = Predictive(\n", + " l63_model,\n", + " params={\"rho\": jnp.array(rho_post_mean)},\n", + " num_samples=3,\n", + " exclude_deterministic=False,\n", + ")\n", + "with SDESimulator(n_simulations=50, source=\"em_scan\"):\n", + " with Filter(\n", + " filter_config=ContinuousTimeEnKFConfig(\n", + " n_particles=50,\n", + " record_filtered_states_mean=True,\n", + " record_filtered_states_cov_diag=True,\n", + " )\n", + " ):\n", + " samples_interp = predictive_interp(\n", + " jr.PRNGKey(42),\n", + " obs_times=obs_times_sparse,\n", + " obs_values=obs_values_sparse,\n", + " predict_times=predict_times_dense,\n", + " )\n", + "\n", + "pred_states_interp = jnp.asarray(samples_interp[\"f_predicted_states\"]) # (num_samples, n_sim, T_dense, 3)\n", + "pred_times_interp = jnp.asarray(samples_interp[\"f_predicted_times\"]) # (num_samples, n_sim, T_dense)\n", + "\n", + "print(\"interp shapes:\", pred_states_interp.shape, pred_times_interp.shape)\n", + "interp_draws = flatten_draws(pred_states_interp)\n", + "pred_times_interp_1d = flatten_draws(pred_times_interp)[0]\n", + "\n", + "# Plot: sparse observations (scatter) vs dense posterior-predictive interpolation (bands)\n", + "fig, axes = plt.subplots(3, 1, figsize=(10, 7), sharex=True)\n", + "lo = jnp.percentile(interp_draws, 2.5, axis=0)\n", + "hi = jnp.percentile(interp_draws, 97.5, axis=0)\n", + "state_labels = [r\"$x_1$\", r\"$x_2$\", r\"$x_3$\"]\n", + "for i, ax in enumerate(axes):\n", + " ax.fill_between(\n", + " pred_times_interp_1d,\n", + " lo[:, i],\n", + " hi[:, i],\n", + " alpha=0.3,\n", + " label=\"95% CI (interpolation)\",\n", + " )\n", + " ax.plot(\n", + " times_backtest,\n", + " states_backtest[:, i],\n", + " \"k--\",\n", + " label=\"True state\",\n", + " lw=1,\n", + " )\n", + " if i == 0:\n", + " ax.scatter(\n", + " obs_times_sparse,\n", + " obs_values_sparse[:, 0],\n", + " color=\"C3\",\n", + " marker=\"x\",\n", + " s=40,\n", + " zorder=5,\n", + " label=f\"Observed (every {downsample}th)\",\n", + " )\n", + " ax.set_ylabel(state_labels[i])\n", + " ax.legend(loc=\"upper right\", fontsize=8)\n", + "axes[0].set_title(\n", + " \"Back-tested real-time forecasting: sparse obs, dense predict_times\"\n", + ")\n", + "axes[-1].set_xlabel(\"time\")\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6.5 Full observations and high-frequency, low-noise data\n", + "\n", + "A common special case is **full observations** with **high-frequency, low-noise** measurements. Under that assumption we can **accelerate inference** dramatically at the expense of some bias (depending on how valid the assumption is). See the [deep dive on this topic](../../../deep_dives/l63_speedup_dirac_vs_enkf/) for details." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Next:** [Part 6b — ODEs](../06b_odes/)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python (dynestyx2)", + "language": "python", + "name": "dynestyx2" }, - "nbformat": 4, - "nbformat_minor": 4 + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } + }, + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/docs/tutorials/gentle_intro/08_hierarchical_inference.ipynb b/docs/tutorials/gentle_intro/08_hierarchical_inference.ipynb index 721e37d8..7e3c92f4 100644 --- a/docs/tutorials/gentle_intro/08_hierarchical_inference.ipynb +++ b/docs/tutorials/gentle_intro/08_hierarchical_inference.ipynb @@ -246,7 +246,7 @@ " # for the drift and diffusion, and make sure they're both batch-compatible.\n", " state_evolution = ContinuousTimeStateEvolution(\n", " drift=OUDrift(mu_i), # eqx.Module\n", - " diffusion_coefficient=ConstantDiffusion(0.1, state_dim=1), # eqx.Module\n", + " diffusion=dsx.FullDiffusion(ConstantDiffusion(0.1, state_dim=1)), # eqx.Module\n", " )\n", "\n", " # We now define the DynamicalModel, which uses a single initial_condition.\n", @@ -551,7 +551,7 @@ " # for the drift and diffusion, and make sure they're both batch-compatible.\n", " state_evolution = ContinuousTimeStateEvolution(\n", " drift=OUDrift(mu_i), # eqx.Module\n", - " diffusion_coefficient=ConstantDiffusion(0.1, state_dim=1), # eqx.Module\n", + " diffusion=dsx.FullDiffusion(ConstantDiffusion(0.1, state_dim=1)), # eqx.Module\n", " )\n", "\n", " # We now define the DynamicalModel, which uses a single initial_condition.\n", diff --git a/docs/tutorials/quickstart.ipynb b/docs/tutorials/quickstart.ipynb index 5b64310c..bc6c3e86 100644 --- a/docs/tutorials/quickstart.ipynb +++ b/docs/tutorials/quickstart.ipynb @@ -1,386 +1,386 @@ { - "cells": [ - { - "cell_type": "markdown", - "id": "752beec6", - "metadata": {}, - "source": [ - "# Quickstart: Writing dynestyx models\n", - "\n", - "This quickstart gives a fast and direct introduction to `dynestyx` for those who already know about Bayesian inference for dynamical systems. If you would like a more conceptual introduction, please see the [Mathematical Introduction](../../math_intro/). If you would like a step-by-step introduction to `NumPyro` and `dynestyx`, please see the [Gentle Introduction](../../tutorials/gentle_intro/00_index/). The tl;dr is that `dynestyx` is an extension of `numpyro` designed to make the specification and inference of dynamical systems simple, fast, and reproducible. In this notebook, we show how models are built in `dynestyx`, building upon an example of a simple linear, Gaussian dynamical system." - ] - }, - { - "cell_type": "markdown", - "id": "2b986e62", - "metadata": {}, - "source": [ - "## In math\n", - "\n", - "For this tutorial, the simple dynamical system we use a simple linear time-invariant (LTI) dynamical system, with linear, Gaussian observations. In particular, we have a two-dimensional state $x_t \\in \\mathbb{R}^2$ that evolves through a simple SDE that couples the two states via a parameter $\\rho$.\n", - "\n", - "We will place a uniform prior on $\\rho$,\n", - "$$\\rho \\sim U(0.0, 5.0),$$\n", - "and specify the SDE as\n", - "$$dx_t = \\underbrace{\\begin{bmatrix} -1.0 & 0.0 \\\\ \\rho & -1.0 \\end{bmatrix}}_{A} x_t \\, \\mathrm{d}t + d\\beta_t,$$\n", - "with unit covariance in the diffusion. Observations $y_t$ will be Gaussian-corrupted versions of $x_2$,\n", - "\n", - "$$y_{t_k} = \\underbrace{\\begin{bmatrix} 0.0 \\\\ 1.0 \\end{bmatrix}}_{H} x_{t_k} + \\varepsilon_{t_k}; \\qquad \\varepsilon_{t} \\sim \\mathcal{N}(0.0, 1.0).$$\n", - "\n", - "We will specify an initial condition $p(x_0) = \\mathcal{N}(0.0, I)$." - ] - }, - { - "cell_type": "markdown", - "id": "0b7a48fa", - "metadata": {}, - "source": [ - "## In code\n", - "\n", - "To specify this system in `dynestyx`, we write it down as a `dynestyx.models.DynamicalModel` in part of a `numpyro` program, and then use `dsx.sample`. We'll also use the convenience class `dynestyx.models.LinearGaussianObservation` here, but this is not necessary, in principle." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "bb6e5186", - "metadata": {}, - "outputs": [], - "source": [ - "import numpyro\n", - "import numpyro.distributions as dist\n", - "import jax.numpy as jnp\n", - "from dynestyx import DynamicalModel, ContinuousTimeStateEvolution, LinearGaussianObservation\n", - "import dynestyx as dsx\n", - "\n", - "def continuous_time_lti_gaussian_model(rho=None, predict_times=None, obs_times=None, obs_values=None):\n", - " # Sample rho using normal numpyro sampling\n", - " rho = numpyro.sample(\"rho\", dist.Uniform(0.0, 5.0), obs=rho)\n", - "\n", - " # Create the dynamical model with sampled rho\n", - " A = jnp.array([[-1.0, 0.0], [rho, -1.0]])\n", - "\n", - " dynamics = DynamicalModel(\n", - " initial_condition=dist.MultivariateNormal(\n", - " loc=jnp.zeros(2), covariance_matrix=1.0**2 * jnp.eye(2)\n", - " ),\n", - " state_evolution=ContinuousTimeStateEvolution(\n", - " drift=lambda x, u, t: A @ x,\n", - " diffusion_coefficient=lambda x, u, t: jnp.eye(2),\n", - " ),\n", - " observation_model=LinearGaussianObservation(\n", - " H=jnp.array([[0.0, 1.0]]), R=jnp.array([[0.15**2]])\n", - " ),\n", - " )\n", - "\n", - " # Use dsx.sample to sample from the dynamical model\n", - " return dsx.sample(\"f\", dynamics, predict_times=predict_times, obs_times=obs_times, obs_values=obs_values)" - ] - }, - { - "cell_type": "markdown", - "id": "72c025ae", - "metadata": {}, - "source": [ - "## Simulating from the model\n", - "\n", - "To generate from the generative model, we have to tell `dynestyx` *how* to simulate from the model. Pass `obs_times` (and optionally `ctrl_times`, `ctrl_values`) as kwargs to the model. We simulate with a `dsx.simulators.SDESimulator`:" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "d23cf87f", - "metadata": {}, - "outputs": [], - "source": [ - "from dynestyx import SDESimulator\n", - "import jax.random as jr\n", - "from numpyro.infer import Predictive\n", - "\n", - "obs_times = jnp.arange(start=0.0, stop=100.0, step=0.01)\n", - "\n", - "prng_key = jr.PRNGKey(0)\n", - "sde_solver_key, predictive_key = jr.split(prng_key, 2)\n", - "\n", - "predictive_model = Predictive(continuous_time_lti_gaussian_model, num_samples=1)\n", - "\n", - "with SDESimulator():\n", - " synthetic_samples = predictive_model(predictive_key, rho=2.0, predict_times=obs_times)" - ] - }, - { - "cell_type": "markdown", - "id": "6b493b1f", - "metadata": {}, - "source": [ - "The `samples` object now comprises a dictionary that contains all the outputs of the `numpyro` program:" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "6513da83", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "f_observations (1, 1, 10000, 1)\n", - "f_states (1, 1, 10000, 2)\n", - "f_times (1, 1, 10000)\n", - "f_x_0 (1, 1, 2)\n", - "rho (1,)\n" - ] - } - ], - "source": [ - "synthetic_samples.keys()\n", - "\n", - "# print the shapes of the variables\n", - "for k, v in synthetic_samples.items():\n", - " print(k, v.shape)\n" - ] - }, - { - "cell_type": "markdown", - "id": "9604e5cc", - "metadata": {}, - "source": [ - "In particular, `observations`, `states`, and `times` all correspond to our dynamical system." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "42650716", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "\n", - "plt.figure(figsize=(10, 5))\n", - "\n", - "times = jnp.squeeze(synthetic_samples[\"f_times\"])\n", - "states = jnp.squeeze(synthetic_samples[\"f_states\"])\n", - "observations = jnp.squeeze(synthetic_samples[\"f_observations\"])\n", - "\n", - "plt.plot(times, states, label=\"states\")\n", - "plt.scatter(\n", - " times,\n", - " observations,\n", - " label=\"observations\",\n", - " marker=\"x\",\n", - " color=\"black\",\n", - " alpha=0.5,\n", - ")\n", - "plt.title(\"Synthetic Data: States and Observations\")\n", - "plt.xlabel(\"Time\")\n", - "plt.ylabel(\"State / Observation\")\n", - "sns.despine()\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "1c8c8a86", - "metadata": {}, - "source": [ - "## Bayesian system identification\n", - "\n", - "Performing Bayesian inference for system identification (in this case, obtaining posteriors of $\\rho$) also becomes simple. Recall that to obtain posteriors of $\\theta$, we must compute posteriors with respect to \n", - "\n", - "$$ p(\\theta \\mid y_{1:T}) \\propto p(\\theta) \\underbrace{p(y_{1:T} \\mid \\theta)}_{\\text{marginal likelihod}}. $$\n", - "\n", - "We can accomplish this by appropriately **interpreting** the `dsx.sample(..)` statement. We will proceed with the normal numpyro tools, but wrap it in a `Filter` context for marginal likelihood computation. Inference over $\\theta$ is then a standard Bayesian inference problem." - ] - }, + "cells": [ + { + "cell_type": "markdown", + "id": "752beec6", + "metadata": {}, + "source": [ + "# Quickstart: Writing dynestyx models\n", + "\n", + "This quickstart gives a fast and direct introduction to `dynestyx` for those who already know about Bayesian inference for dynamical systems. If you would like a more conceptual introduction, please see the [Mathematical Introduction](../../math_intro/). If you would like a step-by-step introduction to `NumPyro` and `dynestyx`, please see the [Gentle Introduction](../../tutorials/gentle_intro/00_index/). The tl;dr is that `dynestyx` is an extension of `numpyro` designed to make the specification and inference of dynamical systems simple, fast, and reproducible. In this notebook, we show how models are built in `dynestyx`, building upon an example of a simple linear, Gaussian dynamical system." + ] + }, + { + "cell_type": "markdown", + "id": "2b986e62", + "metadata": {}, + "source": [ + "## In math\n", + "\n", + "For this tutorial, the simple dynamical system we use a simple linear time-invariant (LTI) dynamical system, with linear, Gaussian observations. In particular, we have a two-dimensional state $x_t \\in \\mathbb{R}^2$ that evolves through a simple SDE that couples the two states via a parameter $\\rho$.\n", + "\n", + "We will place a uniform prior on $\\rho$,\n", + "$$\\rho \\sim U(0.0, 5.0),$$\n", + "and specify the SDE as\n", + "$$dx_t = \\underbrace{\\begin{bmatrix} -1.0 & 0.0 \\\\ \\rho & -1.0 \\end{bmatrix}}_{A} x_t \\, \\mathrm{d}t + d\\beta_t,$$\n", + "with unit covariance in the diffusion. Observations $y_t$ will be Gaussian-corrupted versions of $x_2$,\n", + "\n", + "$$y_{t_k} = \\underbrace{\\begin{bmatrix} 0.0 \\\\ 1.0 \\end{bmatrix}}_{H} x_{t_k} + \\varepsilon_{t_k}; \\qquad \\varepsilon_{t} \\sim \\mathcal{N}(0.0, 1.0).$$\n", + "\n", + "We will specify an initial condition $p(x_0) = \\mathcal{N}(0.0, I)$." + ] + }, + { + "cell_type": "markdown", + "id": "0b7a48fa", + "metadata": {}, + "source": [ + "## In code\n", + "\n", + "To specify this system in `dynestyx`, we write it down as a `dynestyx.models.DynamicalModel` in part of a `numpyro` program, and then use `dsx.sample`. We'll also use the convenience class `dynestyx.models.LinearGaussianObservation` here, but this is not necessary, in principle." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "bb6e5186", + "metadata": {}, + "outputs": [], + "source": [ + "import numpyro\n", + "import numpyro.distributions as dist\n", + "import jax.numpy as jnp\n", + "from dynestyx import DynamicalModel, ContinuousTimeStateEvolution, LinearGaussianObservation\n", + "import dynestyx as dsx\n", + "\n", + "def continuous_time_lti_gaussian_model(rho=None, predict_times=None, obs_times=None, obs_values=None):\n", + " # Sample rho using normal numpyro sampling\n", + " rho = numpyro.sample(\"rho\", dist.Uniform(0.0, 5.0), obs=rho)\n", + "\n", + " # Create the dynamical model with sampled rho\n", + " A = jnp.array([[-1.0, 0.0], [rho, -1.0]])\n", + "\n", + " dynamics = DynamicalModel(\n", + " initial_condition=dist.MultivariateNormal(\n", + " loc=jnp.zeros(2), covariance_matrix=1.0**2 * jnp.eye(2)\n", + " ),\n", + " state_evolution=ContinuousTimeStateEvolution(\n", + " drift=lambda x, u, t: A @ x,\n", + " diffusion=dsx.FullDiffusion(jnp.eye(2)),\n", + " ),\n", + " observation_model=LinearGaussianObservation(\n", + " H=jnp.array([[0.0, 1.0]]), R=jnp.array([[0.15**2]])\n", + " ),\n", + " )\n", + "\n", + " # Use dsx.sample to sample from the dynamical model\n", + " return dsx.sample(\"f\", dynamics, predict_times=predict_times, obs_times=obs_times, obs_values=obs_values)" + ] + }, + { + "cell_type": "markdown", + "id": "72c025ae", + "metadata": {}, + "source": [ + "## Simulating from the model\n", + "\n", + "To generate from the generative model, we have to tell `dynestyx` *how* to simulate from the model. Pass `obs_times` (and optionally `ctrl_times`, `ctrl_values`) as kwargs to the model. We simulate with a `dsx.simulators.SDESimulator`:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "d23cf87f", + "metadata": {}, + "outputs": [], + "source": [ + "from dynestyx import SDESimulator\n", + "import jax.random as jr\n", + "from numpyro.infer import Predictive\n", + "\n", + "obs_times = jnp.arange(start=0.0, stop=100.0, step=0.01)\n", + "\n", + "prng_key = jr.PRNGKey(0)\n", + "sde_solver_key, predictive_key = jr.split(prng_key, 2)\n", + "\n", + "predictive_model = Predictive(continuous_time_lti_gaussian_model, num_samples=1)\n", + "\n", + "with SDESimulator():\n", + " synthetic_samples = predictive_model(predictive_key, rho=2.0, predict_times=obs_times)" + ] + }, + { + "cell_type": "markdown", + "id": "6b493b1f", + "metadata": {}, + "source": [ + "The `samples` object now comprises a dictionary that contains all the outputs of the `numpyro` program:" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "6513da83", + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "id": "69e749ec", - "metadata": {}, - "source": [ - "The `Filter` object gives us some control over the way we solve for the marginal likelihood, including the method and its hyperparameters. By default, we use an ensemble Kalman filter (EnKF); the EnKF is biased for nonlinear state space models, but still generally accurate for high-quality inference. To change the filtering method, pass a config, e.g. `Filter(filter_config=ContinuousTimeDPFConfig(n_particles=2500))`.\n", - "\n", - "After specifying the marginal likelihood computation, inference can proceed in the standard way for `numpyro` (although, MCMC quality may vary based on what approximation to the marginal likelihood we take). The EnKF provides a very smooth marginal likelkhood, so we can often use NUTS in state space models that are not overly complex. " - ] - }, + "name": "stdout", + "output_type": "stream", + "text": [ + "f_observations (1, 1, 10000, 1)\n", + "f_states (1, 1, 10000, 2)\n", + "f_times (1, 1, 10000)\n", + "f_x_0 (1, 1, 2)\n", + "rho (1,)\n" + ] + } + ], + "source": [ + "synthetic_samples.keys()\n", + "\n", + "# print the shapes of the variables\n", + "for k, v in synthetic_samples.items():\n", + " print(k, v.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "9604e5cc", + "metadata": {}, + "source": [ + "In particular, `observations`, `states`, and `times` all correspond to our dynamical system." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "42650716", + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 6, - "id": "14756201", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "sample: 100%|██████████| 200/200 [07:39<00:00, 2.30s/it, 3 steps of size 1.02e+00. acc. prob=0.94]\n" - ] - } - ], - "source": [ - "from numpyro.infer import MCMC, NUTS\n", - "from dynestyx.inference.filters import Filter\n", - "\n", - "obs_values = synthetic_samples[\"f_observations\"][0,0] # shape (T, obs_dim)\n", - "\n", - "mcmc_key = jr.PRNGKey(0)\n", - "\n", - "with Filter():\n", - " nuts_kernel = NUTS(continuous_time_lti_gaussian_model)\n", - " mcmc = MCMC(nuts_kernel, num_samples=100, num_warmup=100)\n", - " mcmc.run(mcmc_key, obs_times=times, obs_values=obs_values)\n", - "\n", - "posterior_samples = mcmc.get_samples()" + "data": { + "image/png": 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", + "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "\n", + "plt.figure(figsize=(10, 5))\n", + "\n", + "times = jnp.squeeze(synthetic_samples[\"f_times\"])\n", + "states = jnp.squeeze(synthetic_samples[\"f_states\"])\n", + "observations = jnp.squeeze(synthetic_samples[\"f_observations\"])\n", + "\n", + "plt.plot(times, states, label=\"states\")\n", + "plt.scatter(\n", + " times,\n", + " observations,\n", + " label=\"observations\",\n", + " marker=\"x\",\n", + " color=\"black\",\n", + " alpha=0.5,\n", + ")\n", + "plt.title(\"Synthetic Data: States and Observations\")\n", + "plt.xlabel(\"Time\")\n", + "plt.ylabel(\"State / Observation\")\n", + "sns.despine()\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "1c8c8a86", + "metadata": {}, + "source": [ + "## Bayesian system identification\n", + "\n", + "Performing Bayesian inference for system identification (in this case, obtaining posteriors of $\\rho$) also becomes simple. Recall that to obtain posteriors of $\\theta$, we must compute posteriors with respect to \n", + "\n", + "$$ p(\\theta \\mid y_{1:T}) \\propto p(\\theta) \\underbrace{p(y_{1:T} \\mid \\theta)}_{\\text{marginal likelihod}}. $$\n", + "\n", + "We can accomplish this by appropriately **interpreting** the `dsx.sample(..)` statement. We will proceed with the normal numpyro tools, but wrap it in a `Filter` context for marginal likelihood computation. Inference over $\\theta$ is then a standard Bayesian inference problem." + ] + }, + { + "cell_type": "markdown", + "id": "69e749ec", + "metadata": {}, + "source": [ + "The `Filter` object gives us some control over the way we solve for the marginal likelihood, including the method and its hyperparameters. By default, we use an ensemble Kalman filter (EnKF); the EnKF is biased for nonlinear state space models, but still generally accurate for high-quality inference. To change the filtering method, pass a config, e.g. `Filter(filter_config=ContinuousTimeDPFConfig(n_particles=2500))`.\n", + "\n", + "After specifying the marginal likelihood computation, inference can proceed in the standard way for `numpyro` (although, MCMC quality may vary based on what approximation to the marginal likelihood we take). The EnKF provides a very smooth marginal likelkhood, so we can often use NUTS in state space models that are not overly complex. " + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "14756201", + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "id": "c0a63174", - "metadata": {}, - "source": [ - "Plotting the posterior values of $\\rho$ shows a posterior centered at the true value of $2.0$." - ] - }, + "name": "stderr", + "output_type": "stream", + "text": [ + "sample: 100%|██████████| 200/200 [07:39<00:00, 2.30s/it, 3 steps of size 1.02e+00. acc. prob=0.94]\n" + ] + } + ], + "source": [ + "from numpyro.infer import MCMC, NUTS\n", + "from dynestyx.inference.filters import Filter\n", + "\n", + "obs_values = synthetic_samples[\"f_observations\"][0,0] # shape (T, obs_dim)\n", + "\n", + "mcmc_key = jr.PRNGKey(0)\n", + "\n", + "with Filter():\n", + " nuts_kernel = NUTS(continuous_time_lti_gaussian_model)\n", + " mcmc = MCMC(nuts_kernel, num_samples=100, num_warmup=100)\n", + " mcmc.run(mcmc_key, obs_times=times, obs_values=obs_values)\n", + "\n", + "posterior_samples = mcmc.get_samples()" + ] + }, + { + "cell_type": "markdown", + "id": "c0a63174", + "metadata": {}, + "source": [ + "Plotting the posterior values of $\\rho$ shows a posterior centered at the true value of $2.0$." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "5745525c", + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 7, - "id": "5745525c", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import arviz as az\n", - "az.style.use(\"arviz-white\")\n", - "\n", - "az.plot_posterior(\n", - " posterior_samples[\"rho\"], \n", - " hdi_prob=0.95,\n", - " ref_val=2.0\n", - ")\n", - "\n", - "plt.show()" + "data": { + "image/png": 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", + "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import arviz as az\n", + "az.style.use(\"arviz-white\")\n", + "\n", + "az.plot_posterior(\n", + " posterior_samples[\"rho\"], \n", + " hdi_prob=0.95,\n", + " ref_val=2.0\n", + ")\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "d5016e81", + "metadata": {}, + "source": [ + "## Likelihood sweep\n", + "\n", + "As a quick diagnostic, we can sweep over fixed values of $\\rho$ and evaluate the marginal log-likelihood $\\log p(y_{1:T}\\mid\\rho)$ using the same `Filter`-based model. This is useful for checking identifiability and seeing whether the inferred posterior mode aligns with the likelihood peak." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "27699b7e", + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "id": "d5016e81", - "metadata": {}, - "source": [ - "## Likelihood sweep\n", - "\n", - "As a quick diagnostic, we can sweep over fixed values of $\\rho$ and evaluate the marginal log-likelihood $\\log p(y_{1:T}\\mid\\rho)$ using the same `Filter`-based model. This is useful for checking identifiability and seeing whether the inferred posterior mode aligns with the likelihood peak." - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/28/rfdjbzgj0bz_x56whkjmhl600000gn/T/ipykernel_8806/2187872338.py:35: UserWarning: The figure layout has changed to tight\n", + " plt.tight_layout()\n" + ] }, { - "cell_type": "code", - "execution_count": 8, - "id": "27699b7e", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/28/rfdjbzgj0bz_x56whkjmhl600000gn/T/ipykernel_8806/2187872338.py:35: UserWarning: The figure layout has changed to tight\n", - " plt.tight_layout()\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from numpyro.infer import Predictive\n", - "\n", - "from dynestyx.inference.filters import (\n", - " Filter, ContinuousTimeEKFConfig\n", - ")\n", - "\n", - "def marginal_loglik_at_rho(rho_value, *, obs_times, obs_values):\n", - " with Filter():\n", - " predictive = Predictive(\n", - " continuous_time_lti_gaussian_model,\n", - " params={\"rho\": jnp.array(rho_value)},\n", - " num_samples=1,\n", - " exclude_deterministic=False,\n", - " )\n", - " out = predictive(jr.PRNGKey(123), obs_times=obs_times, obs_values=obs_values)\n", - " # Keep this robust to scalar vs singleton-shaped return.\n", - " return jnp.ravel(out[\"f_marginal_loglik\"])[0]\n", - "\n", - "\n", - "rho_grid = jnp.linspace(0.1, 4.5, 20)\n", - "loglik_grid = jnp.array(\n", - " [marginal_loglik_at_rho(r, obs_times=times, obs_values=obs_values) for r in rho_grid]\n", - ")\n", - "\n", - "rho_hat = rho_grid[jnp.argmax(loglik_grid)]\n", - "\n", - "plt.figure(figsize=(8, 4))\n", - "plt.plot(rho_grid, loglik_grid, lw=2, label=\"marginal log-likelihood\")\n", - "plt.axvline(2.0, ls=\"--\", color=\"black\", alpha=0.8, label=\"true rho\")\n", - "plt.axvline(rho_hat, ls=\":\", color=\"C3\", alpha=0.9, label=f\"argmax ~ {float(rho_hat):.2f}\")\n", - "plt.xlabel(r\"$\\rho$\")\n", - "plt.ylabel(r\"$\\log p(y_{1:T}\\mid\\rho)$\")\n", - "plt.title(\"Likelihood sweep\")\n", - "plt.legend()\n", - "plt.tight_layout()\n", - "plt.show()" + "data": { + "image/png": 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8HTY8+O92hAMYWbI+Ei1eCAwEqlX1xrXXJOL7jSNRrJgFS157BaGhGddiiIiIZ1NgISKShziScOiQDTt2JQURO3cmmtGJwsTicOCGqBNm/f0S9QALEB0Ns7/bd8Tgt6PbzW233PEPrqkSjBrVk0Y1qlf3NiMcxYopq1ZERBRYiIjkqqhoB37+OSWI2PVzgjlJz4jFAlSt6mVGB3x9AS8r4OVlgdXLuZ70fdJXwHrhdue6N7/ye273TnqM+f7C4/k83ny+5OdK/Xjz1WFHwtrGCA93oF+FIBw4bMcvB204eTJ1AMQ0qiNHbWb55NP45O3lylpRrZoXalwINBhwlL/KCgvfnIiIeAyNWIiI5MDp0zbs2JmYFEjsSsDBQzZzAp6RAH+gTh1v3FjXBzfW9cYNdbwRElIIrvjXvcF8udtl0/lwO3bv9kGPHlbExiYFQL/9xvqM1A/lCAyXDd8lJG8LDragWtWkkQ3nCMc113jB11fBhohIUaXAQkQkC2lNvFrvWh+R9qp+WqVLW1DvxqQggsEET7Z9fNzj5JrF3A0b+KBkiaTA553lxeDl5Y+jx2w4cCARBw7acOBg0tfISEeqx/L77TuYSpUShXh7A1WqXEijulAkXr26l3kdERFxfwosREQyEB3twJ69SSMRDCJ27U686ATaFTN/rr3GC/VuTBmRuMoNUoIcdgfiTkaadb8rg2G5RDcojjgw5YlL8uMdDvz5pz05yPjlQtBx6lTqoIsjHaw34fLxJynbr7wypRsVA5kG9b3VkUpExA0psBARueDMGbtLkXWCOTlOm/bjyt8fuL62N2680Qf1LqQ1hbrh1Xd7bCJ23b3SrDfc3cNMmJcVDJzKl/cyS9MmKdvPnbMnj2ocvBB0cLQjbaoYR324rP+GqVQxuOIKK1q19EOr+/1Q5WqvXHmPIiKS9xRYiIhHpzaxLuDLr+JMMHHij0unNZUsaUkeieCoBIuUfd0krelyrAEZ/zvwZwSVDewWdVNjLimBSlxcUjqZayoV61KiolJGgv76y45Fi2PMUruWF1q38kOL5n4oXtz9gjYREU9icXAM2w2sXr0a27dvx969e3Ho0CEkJCRgypQpaNeu3WUfe+LECbRu3RrR0dHo1KkTJk6cmOr2P/74A02auFxmS2Pw4MF47LHHLtr+999/Y+bMmfjuu+9w/vx5XHnllWjbti369u0LH5+Mr/jt2LED9evXN++nXr16l91/Ecn9zk0frY7F8rdi8fvvGQcT11Txwo0mrYmBhA8qlC/8aU3uiJP3/fEnC8UTsfazOGz6IeGiUQ3WZ9x+m48JMu66w1dF4CIihZDbjFjMmjULf/75J4oXL44yZcqY9cyw2+0YPXp0pu5bvXp1NG3a9KLtjRo1umjbmTNn0LFjR5w6dQr33nsvKlWqhG3btplA4+eff8a8efN0AiJSyJw6bcNbb8di1XtxCI9IfU2FrV5NWtOFIuu6db1RLExXyPMDZ/iuWMHLLEx/+udfO9aui8PHn8ThlwNJEQZT0r75NsEsoaEWNG/ma4KMujd462+tiEgh4TaBxaRJk8zJ+1VXXYVFixZh2rRpmXrcsmXLsGvXLowYMcKMcFxKjRo10h2ZSM/LL7+Mv/76C+PHj0fnzp3NNg7+DBs2DJ9++qlZ7r///kw9l4jkrX37E/H6mzH4/Iv4i2ommKbTras/brnZR1fBC4lSJa3o/nCAWQ4dTsTHa+Lw6adx+PtMUjDI+TbefS/OLBUqWNH6/qR6jArlVY8hIlKQ3OZy3C233GKCiqw4evSoGUHo16+fCRpyS2RkJNauXYsKFSrgoYceSt7OFAkGFvTuu+/m2uuJSPbqJ9Z/E48evc+jY+fz+HRtSlDBtJq2rf3w/rtheG1RKO6607NTa+zxNhwbs9EsXHcVHx+PIUOGmIXr+a3qdd4YPjQIX31eHK8uCEGrlr5mLhCnEyfsmDs/Bs1bnkO3nuex6v1YhIcXrpnNRUQ8hduMWGSVzWYzKVAc5Rg4cCB27tx52cewZmLFihWIiIhAyZIl0bhxY1SsWPGi+3EEhP9gGeykzbdm8HP11VebOgrugxentRWRQlE/UayYBZ06+KNzJ3+ULu0211XynCPRjr9XHTTrlcbeBPim/N3i37FNmzYlrxcUzhZ+y82+ZuHP+Kuv402q1I9bE+CsFOREhVwmT43CPXf5mlGMW2/xcZt5Q0RE3F2RDSwWLlyI/fv3Y+XKlfBl8nQm8J+n8x8oMWho1aoVJkyYgMDAwOTtx48fN18rV66c7vNw+6+//oqTJ0+aUQ0RKdj6CbYs7fawv2lhGhCgk8y0LD5WVBhaP3m9sAsKtKBNKz+z8Oe+5tN4rP4kDseOJQU+HFj57It4s5QobkGLFn4mXapmDS/VY4iI5KEiGVgcOHDAFE/36dMHtWvXvuz9AwICMGjQIFO4zREKFnwzKJkxYwY+/vhjxMbGYs6cOcn354gGhYSEpPt8QUFBqe4nInlbP/HGmzHmJDK9+oke3fxx260+mnDtEqw+Xrhq0I1u+TEtV9YLfXsHoE8vf+z/hRPvxZnC77P/JQWX/Lp8RaxZ2OWLBd/3t/Q1jxMRkdxV5AILpiiNGjXKBAhsE5sZTHti/rCrm2++GXXr1sUDDzyAL774Avv27UOtWrXyaK9FJDvzT7Ag+6ftqaMJ1k+0bOGH7g/7m5mcxTNwhLlWTW+zDH8y0LSsZdH3N9/GmxEM4uR8M2ZFY+bsaDRulNS6tmkTXzMCIiIiOVfk/uuyYxTnuXjnnXcynQJ1qZGMNm3amAJw1kw4AwvnSEVGIxJRUVGp7iciuSOa9RMfx+HNFTGqn8hF7GiXeDbWrHuX8Hf7dCHWVLAgnwsLuT//Mqkeg/UXxJqMLT8mmOW5ScC9TZPqMRhssJZDRESyp8gFFkxhYioT55hID2suuHBCPKZLXQ7nzaCYmJjkbSwIp99++y3dx3A7J8i74oorsvkuRCTd+on340yrUVdXV05qTcoTQ9VPZI89JhHbb1ph1hvu7gGvwIwn+HQ3oaFWdGjvb5bfT7AeI86MZLCbFMXEAh+viTdLmdIW3N/SDx0e9DdzaoiIiIcHFrfeemtyMJB2QrsNGzagSpUqZrbrmjVrZur5du/ebb66trplihQDhx9++MFc6XO9useJ+1i4zY5S3szJEJFsU/2E5CYGC4MGBGJg/wDs2p1oRjE++zw+udif82QsWRaL19+MNe2IB/QLwJVXKsAQEcmsInfm27Vr13S3//jjjyawaNiwISZOnHjRKAfnuUg7/M/aio8++ghhYWG44447krcHBwejZcuW5jamXLlOkDd9+nSzntGIiYhcmuon8h9HKG463DfDlNCffvoJRQn/1nN2dS6jRzqwYWNSqtTG7xNMAwB21X3/wzjTaerB9n7o3zcQZcoU/m5ZIiIFzW0Ci1WrVmH79u1mnTUUzm1bt2416/Xr10eHDh2y9dyckfv33383IxHlypUzvdoZbPD1WKfB29PWS3AiPAYrbEW7efNmUyy+bds2M8fF3XffbQIPEck81U9IQfDzs6BZUz+znD1rxzvvJo1YREY6TJDxzso4fPhRnJn/hN2nSpZUgCEi4vaBBU/yP/zww1TbWFDNxSm7gUXr1q3x+eefm7Snb7/91tRolC1b1jxfr169cM0111z0mDJlypjZtVnYzZGQ9evXm3Qpdpfq27ev2xc/iuQX1U9IYVGihNWkSnXp7I/X34g1TQJYXhcXB7yxnHOkxKJrF3/06hGAYsUUYIiIpGVxMH9H8hWDIY6wMFhivYeIJ4qIsGPO3BisXBWr+ScKmD3eht9fTBr9rTiyEawuM2+zhfe4cePM+nPPPZfjbnvuhCMYry2NwdsrY01w4RQUZDHtjDlHSkiIAgwREScFFgVAgYV4Ml7L4EzJL02Pwr//plzX0PwTBccWnYBtN7yeblcodsS7/fbbzfrGjRtNzYWnOXPGjkWLY7Dq/VgkJKRsDw21oFcPf3TtEqC5MERE3CkVSkTc35EjiZg0JQrbfkqZ1C7AH+j2cAC6POSP0qV19bcgWHysuHLADcnrkho/l08/FYRePf2x6NUYfLg6zoyysfXxrDkxeHN5LPr0CsBDnfzh7680WBHxXBqxKAAasRBPExXtwPyF0eYEjCdkTk3uZleeILX0LMQ0YnGxE3/YMH9hDD5ZEwd70nQYRunSFjzSJ8DMmeHrqwBDRDyPLk2JSJ6mPX3xVRxatz2HpctSgooK5a2Y/0oIZs8MVVAhbqdCeS9Mfi4Yqz8ohvua+8LZq+PMGQcmT43Gfa3OXUibUgmjiHgWBRYikieOH7eh/6AIDB0WiVOnky7rsu530IAAfPR+Mdxxu+cUAbtDAMg6Cy7q55F5Va72wssvhOCDVWFoek/K5/nUKTvGT4xCq7bnzFwYnJtFRMQTKLAQkVwVG+vAK/Oi0ab9OWz6IaXS9bZbfUxA8ejAQOWhFzL2mERTvM2F65I1Va/zxqwZIVj1ThjuvD2l8P3EH3aMGRuJNu3OYe06pk0pwBCRok2BhYjkmu82xqNt+3Mm/9zZPadcWStmTgvGgrkhqFQxpY2pSFFTs4Y35r0SihVvhOLmm1ICjF9/s2PE6Ei073geX6+P16iQiBRZKt4uACrelqLm5Ekbpr4Yha+/SUjVPpa9/gf0D1QrzkKO6U/OkQprgHeqCT55W2xsrFn39/fX5J9ZsO2nBMyZG43tO1KPAtWq6YXBgwJx+20+Op4iUqQosCgACiykqIhPcJgZihcsisaFc0+jYQNvjB0ThGuvUUdr8WwMzH7YzAAjBnv2pg4w6t7gjcceDUTjRqmDORERd6X/+iKSLVt+TMDzU6Jw7Fdb8raSJS0YOSwILVuwU45OlET4e3DrLb645WYfbPguaQTjwMGk35lduxPRp1+4CcQZYNSvl5I+JSLijhRYiEiWZyF+cVoU1q6LT95mtQKdO/njsUcDEBKi0i13Y0+w4Y/ZO8x6+cfrweqTUgsTHx+PyZMnm/UxY8bAl629JFsBxl13+uKO233w1fp4zJ0XgyNHkwIMThjZvVe4CT74O1TnegUYIuKedAYgIpmSmOjAG8tj0LLNuVRBRZ3rvfHuW2EYMzpIQYWbciTYcXLBbrNw3ZXNZsOaNWvMwnXJGavVgmZN/UyL2hemBKNSxZR/w0yZ6vxwOB59PBxHj6k7l4i4H41YiMhl7diZgOcmR+HQoZQTy7AwC558IhDt2vqZkyVxXxZvK8r1qJW8LnnPy8uC+1v4oXkzXzODNzup/XkyKaj7dkMCNv1wHv36BqBv7wDN4i0ibkOBhYhk6OxZO6bPjMaHq+NSbW/fzg9DHw9E8eI6CS0KrL5eqDz25oLeDY/k7W3BA2390bKlHz76KA4LFsXg9N9206557vwYfPZ5PCY8G4Qb6yo9SkQKP50ViMhFOFPwu6tiTdqTa1BRo7oX3nozFBOfDVZQIZKLfH0s6NjBH2s/KYa+vf3hdaHM5egxG7r1DMekyZGIjEydpiYiUtgosBCRVPbtT0SXbucxYVIUwsOTZgoODrZgzOhArHwrDDfU0ZVTkbzi72/B0CFB5neN812QwwG8vTIOrR84j/XfptQ3iYgUNgosRMQ4H27Hc5Mj0anLeezdl1JL0aqlL9asLoaunQNMXrgUPbboBGy5brFZuC4Fr0Z1b7z1ZhhGDAtEgH/SNqZIPTYkAk+OiMCZfzR6ISKFjwILEQ/HCbxWfxKH+1ufwzsr48zVUbqmiheWLg7F1MkhKF1KfypECqL+omf3AHz0fjHTitbp8y/i0brtObz/Qaz5/RURKSw083YB0MzbUlgcPpxouj1t35HS2jIgABg0IBDduvrDx0cjFJ6AJ6eJZ5OmTvcu4Z9qckPedu7cObNerFgxTXxYgD+jNZ/GY+pLUTh3LiWY4OR6E54JRqVKKXOPiIgUFF2GFPFA8QkOzH4lGu07nU8VVNzb1BeffFQMvXsGKKjwIAwkfEoGmCXtjOn8vnjx4mbRbOoFh8e+1f1++OTDYiY90YmT67V98BxefS0GCQkavRCRgqXAQsTDHDiYiIe6nsfCV2PgnO+sYkUrFs4LwcxpIbiinK58ihRWJUpYTXoif1+vujLpX3h8PDBzdjQ6djmPPXs1sZ6IFBwFFiIeNHP2gkXRpjj74MGkiMLbGxjYPwAfvVcMt92achVUPIs9wYY/5+00C9ddxcfH44UXXjAL16Vw4O8ray96dPOH9cJ/ck5gyY5uTJeKitbohYjkPwUWIh7gyNFEdOl+HnPmxiDxwgXNqtd54Z3lYRg8KBB+fqql8GSOBDtOzNhuFq67stlsWLVqlVm4LoVHYKAFI4cH4e3lYahWLWmk0W4H3lwei7btz2HjJgWCIpK/FFiIFPGJ7pa+HoMOD53HvgstZHl1s1/fANMnv0YN74LeRSkELN5WlOlQzSxcF/dSu5Y3Vq4Iw9AhvEiQtO3kSTsGDIrAqKcicPasWtOKSP7QfxCRIur4cRt69A7Hy9OjTQ42XV3ZihWvh2LIY4Hw9dUohSSx+nqhyuTbzcJ1cT/s4Na3dwA+fK8YGjVMuWCwZm08Wj1wDh9/wlbSSo8SkbylwEKkiLHbHVjxdgzadTyHnbuS8p7Y6Ie52O+tLIY6mjlbpMiqVNELS14NxaQJQQgNTbp4wPa0T42NRL8BEfjjD6WziUjeUWAhUoT8+acNffqFY/LUaMQmTUuACuWteH1JqMnF9vfXKIWIJ7SmfaCtv2kdfd//Upoy/LAlwdReLHudtVYavRCR3KfAQqQIYIrDqvdjTT/7rdtS2k0+1MkP768qhvr1UmbtFUnLFp2ArXWWmYXrUjSUKmnFyy+GYO7sEJQrm/TvPiYWeGl6tOke9csvak0rIrlLgYWImzt12oYBj0Zg/MQoREcnbbviCiteWxSKcWOCERSoUQq5PHtMolmk6LnrTl98/GExdHmIs6onbdu334ZOXc9j2owoxMRo9EJEcofFoWqufLdjxw7Ur18f27dvR7169fJ/B6RI4K/ux2viMeWFKEREpJwYtH/ADyOHByI4WNcNJJOfJbsDcScjzbrflcGwWFOCUbvdjlOnTpn1cuXKweqcNEHc0q7dCXh2QhSOHE2ptahQwYrx44JxU2ONbIqIhwQWq1evNifie/fuxaFDh5CQkIApU6agXbt2l33siRMn0Lp1a0RHR6NTp06YOHHiZR/zyCOP4LvvvoOvry/27Nlz0e3dunXD1q1b033sVVddhfXr12f43AosJKf++deOCc9FYv03KWkrpUtbMOGZYNx5hya6E5GMxSc48NqSGCx8NQYJLplvD7Txw/BhgSgWpuBRRLLHbZrYz5o1C3/++SeKFy+OMmXKmPXM4NW20aNHZ+m13n33XXz//ffw8/O7bHu+wYMHX7QtJCQkS68nkhWffR6H5yZHmU4vTve38MVTo4N0QiAil+XrY8HA/oH4XzM/PDshEjt2JqXAfbg6Dt9tjMfokUG4r7mvKQIXESmSgcWkSZNQqVIlMxqwaNEiTJs2LVOPW7ZsGXbt2oURI0aYEY7L+eOPPzB16lT07NkTn3/+Oc6cOXPJ+z/22GOZfg8iOfHff3ZMmhyFz75ImU23RHELnh0XhKZNLsyKJZIN9gQbTi//xayXfbgGrD4pc1lwdHjevHlmfdCgQfDxUbpMUVHlai/TMe699+MwbWY0IiMd+PesAyNGR2LNpz4Y/0wwypTR6IWIZJ7b/MW45ZZbTFCRFUePHsXMmTPRr18/1KhR47L35+jEmDFjULp0aQwZMiQHeyuSu9Z/E4827c+lCirubeqL1R8UU1AhOeZIsOP45C1m4bqrxMREvPnmm2bhuhQtVqsFHTv445MP+bckJY1yw8YEtO94Dhs3pfzNEREpMiMWWWWz2UwKFEc5Bg4ciJ07d172MfzHuW3bNixfvhz+/v6Zep1PPvnEpGXx/gxeGjZsqOJGyTXh4XZMeTHazJrrxEmvxo4JQgulKkgusXhZULLVNcnr4nk4MjFregi++joOk6ZE4cwZB87+58CAQRHo1dMfQwYHmtm9RUQ8MrBYuHAh9u/fj5UrV5oC7Mv57bffMH36dFOUzY5NmTV8+PBU31euXBkvv/wyrr/++mztt4gTrxQ+Oz4Kp/9OuYJ85x0+pkC7dGm3GWwUN2D188Z10+8u6N2QQoBplZz35ulnIrHhu6TK7qXLYrF9eyJemhqM8uVT0uRERNIqkmcnBw4cMDnBffr0Qe3atTNd4M0UqKFDh2bqNZo0aWKCF3aO2r17N9auXYvu3bubDlS9e/fGyZMnc+GdiCeKinLg2YmR5kqhM6gIDrZg0sQgM9GVggoRyUvFi1vN35pRIwLhfeHy4897EvHgQ+fx+Zcpo6ciIkU+sIiPj8eoUaNQsWLFdDs2pWfx4sWmwPv5559HQEBAph7D4u677roLZcuWNWlQ11xzDZ5++mn0798f4eHhWLJkSQ7fiXiiH7cmmNmzWUzpdMtNPvjo/TA80IaTWykVQUTyHv/WdH84ACveCDPzXBDny3lyeCQmTopEbKxbdKoXkXxW5AILdoziPBfsAJWZFKhff/0Vc+bMQZcuXdCoUaMcv/5DDz2UPFeFSGZFRzsweWoUej8SjpMnk0YpGOM+OzYIixaE4IpySj+QvGOLTsBPjZabhesiTrVreeO9d8JM+1mnlavi0Pnh8zh6TMX8IlLEayxYV8HUpo4dO6Z7O2suuDCVielS7BzFUY4VK1aYJT3VqlUzX1nYHRoaesnXL1asmLnSw8n4RDJj564EjBkXid9/T6mlaNjAG89NCEYF5TNLPkn8L1bHWtIVHGw19RU3N47D5BeiEBsLHDpsQ6fO5zFmdBAeaOun0VQRKZqBxa233mom0UuL81Fs2LABVapUQb169VCzZk2znS1sH3zwwXSfi3UTcXFxeOCBB8z3mRkB+fnnn03b2qy2xhXPExfnwJy50Vj2Riyc8zD6+QFDhwSia2d/0wZSJD9Y/b1R59P2yeuuOFEoJw11rotn4gWz9u38cUMdbwwbGYkjR22IiQXGjY/Clq0JeHZsMIKC9DdLxNMVucCia9eu6W7/8ccfTWDBdrATJ05M3s4WsaytSM/mzZtNQJL2dhZoc3Ztjk64On36NCZMmGDWW7VqlQvvRoqqbT8lYOLzUTh2zJa8jf+wn38uGFdXVtqT5C+L1YLAqhdfkCGr1WouyIjQtdd6450VYXjhpSisulAL9unaeOzZew7TXgxBzRpF7rRCRLLAbf4CrFq1Ctu3bzfrrKFwbtu6datZZ4vYDh065Mu+MCVq/PjxaNCgAcqXL2/SozhjNwMXpkAxqGjTpk2+7Iu4l7//tuPlGVHmH7ETJzIePCgQvXr4w0tzCIhIIRcQYDGzcjdu5IPxz0WZGbuZytml23kMHxqIrl3UaELEU7lNYMGg4sMPP0y1jQXSrkXS+RVYMI2qefPm2LdvH/bs2WOCCY5gMMWqffv2aNGiRb7sh7iPhAQHVrwdi7nzo+FaflOrlheenxCM665zm19FKYLsCTac+eCwWS/d7jpYfVJGzRISErB06VKz3qtXL/gwEhYBcF9zP9SuzdSoCOzbZ0NCAsyEnkyNmjQhGMWKFbn+MCJyGRYHCwIkXzEY4ggLgyUGI1K0bd2WgOenRJmcZKewMAueeDwQ7R/w0yiFFDh2gtp2w+tmveHuHvAKTAkeYmJicPvtt5v1jRs3Zrolt3iO+AQHZs1OqhdzKlfWihenBpvJ9kTEc+T4Mik7Kh07dgxnz5418zcwLahEiRImJzczxc4iRTnt6aXpUVi7LiXtidNQPNjOzwQVuponhYXFy4LiTSomr4tkha+PBSOGBaFRQx/T4e7cOQdOnbajZ59wPDowAI/0CdAFFBEPka3AgkHEBx98YGoK2AWJwUVaDCrq1KljJpFjVyUGGyIek/b0VizmLkid9lS7lhfGjgnG9bWV9iSFi9XPG9UWNCvo3RA3d+cdvvjg3TCMGhOJbT8lwm4H5syNMaO2L0wOQenSSo0SKeqylAp1/PhxzJo1C19++aXJuyW2dr366qsRFhaG4OBgREREmJELjmKcO3fO3Ic5uc2aNcPjjz+OSpUqwdMpFapoz5zNtKejx1KnPbGFLNOe1EJW3I1SoSSrbDYHFiyKMQuDCypR3IIpzwfjtluVySBSlGX60ilbtLKXOSefa9y4Me6//34zU3WFChUyfAzbsm7ZsgVr1qzBunXr8Pnnn6NTp04YN25cbu2/SKFw+rQNL02PxrrPUqc9dWjvhyGPKe1JRDwHu9s9OjAQDRv4YNRTEfj7jANn/3Og/6AI9O7pj8cHB8LHRyl3Ih49YnHDDTeY2az79u2LsmXLZvmFOMfDq6++ivfeew+7du2CJ9OIRdFKe1r+VizmpUl7YrrT2DFBqF1LaU9S+NliEvHzfe+Z9TrrHoRXQMrnViMWkhNnz9rx9DOR+G5jUpaDc84ezuR91VWas0ekqMn0Wc9XX32F0qVLZ/uFGIyMHTsW/fv3z/ZziBQmW35MwPNTU09yV6xYUtpTu7ZKexI34nAg7s/I5HWR3FKihBVzZ4fgjeWxmDErGomJwO6fE9G+03lMHB+EZk01m7tIUaJ2swVAIxZFIO1pWjTWfZ467anjg354nGlPYSpQFPfisNkRte9fsx5UqyQsXimfYaa/HjhwwKxXr17dzMQtkh179iZi+MgI/PHnhcILAJ06+mHU8CD4+Sk1SqQoUGBRABRYuG+v9uUrktKeYmJStte53htPP6W0JxGRy4mIsGP8xCh89kXKhZmqVb0w7cUQVLlaqVEi7i5HCeCxsbGmMHvnzp1mvVSpUqhRo4aZTKlkyZK5t5cihSHtaUoUjv2akvZUvLgFQx8PxANKexIRyZSQECtefjEYN90UhykvRCEuDjh0yIaOD53D02OC0La1HywcAhYRzwosTp48iZ49e5rOT6713/yD4OXlhebNm2P48OEoV65cbu2rSL47xbSnl6NTXV0zaU8d/ExnE6U9SVHgSLTj30+PmfWSLavA4p2S7sTW4m+//bZZ79y5s2kfLpITPE/o0N4fdet4Y9jISNOeOyYWGPtMFH78MQHjng5GUJCCCxGPSoUaPHiwKei+5ppr0KZNGzM/xfnz57F371588803OHPmDIoVK4b58+fjxhtvzP09d2NKhXKPtKc3l8di/sKL057Y7alWTXV7kqLDFp2AbTe8btYb7u4Br8CU4EFdoSQvxcQ4zMjF+x/GJW+rVNFqUqNq1NDfWRF3k+3fWs5PwdQnzm0RFBSUvJ0taRmrLF26FLNnz8aAAQOwevVqjVyI29i8JR6Tp0ZflPb05JBAtG2jbk9S9FisFoTdcmXyukh+CQiwYOL4YDRu7IMJz0UhKsqB47/b0bnbeYx4MhBdOvsrNUrEjWS7vQevYnGCPNegwnWYs3fv3pg2bZoZxZg3b15O91Mkz/11yoYnR0Sgb/+I5KCCDXA6d/LDpx8XQ7sH/DVzthRJVn9v1Hi9hVm4LpLfWt7nh1XvhKFWzaQC7oQEYPIL0RgzNhJxcWqBLFLkA4vixYuboOFSmjRpguuvv96kRokU5rSnxUti0KrNOXzuUktR9wZvvPtWGMaOCUZYqFpsiojkpUoVvbD8jTB0f9g/edvHa+LRo3c4/v47pUWtiBRe2T5bYuenbdu2meLtS6lYsSLCw8Oz+zIieeqHzfFo9+A5M3ETiwepRHELJk0IwpvLQpXjKyKSj3x9LBg1IgjTXw5GgH/K/BedupwzX0WkiAYWw4YNg7+/Px555BH88ssvGd7v8OHDJrgQKUxO/mXD0OEReGRABH79zZ4q7WnNx8XwQFulPYnnsMUkYvd975mF6yIF7X/3+uHN18NwxRVJpyl/n3GgR+/zWLM2pchbRIpQYMHC7RkzZpi2sx06dDCtZdetW4fTp08jPj4ev//+O8aOHYtDhw6hT58+ubvXItnAPN3Pv4jDwMHh+F+Lc/jiS5e0p7reePdtpT2Jh3I4EHPknFm4LlIY1KjujZUrwnBj3aS6H855MeqpSMyYFQWbTZ9TkSI58zbby44fP958TW9Sm65du5rOUAxEJInazeYffrw5fP7Rx3FYty4e4RGpP+5Me3pyaCDatFK3J/FcDpsd4dtOmfXQhuVg8Uq55mS3280kqMTW4VYO7Ynkcx3cpOdTt6S98w4fvDglGMHB+jyKFKnAgvgU27dvx9dff42tW7eaUQpOqmRe4EKwwcCiVq1aqFmzplmaNm0KT6XAIu+dPm3DJ5/GY/XHcanaxjqVK2c1M7z26OaPUBVmi4gUajzPeOvtWLzwcjRsF/6kV6nihVdmhZiibxEpQoFFWomJiaa2Yt++fdi/f79ZDh48aFrUmhe1WC5Zl1HUKbDIG7GxDqz/Jt6MTmzekgB7miYi/v5As6a+aNPaH40aeqt1rIiIm+E8Q0+OiER4eNKpS2ioBTNeDsFNjTUjvEhhkCcNy729vVGjRg2zuA6nHzt2zKRMeXJQIbmLcfHunxPx0eo4fPZFPCLSpDpRg/reJtWp2b2+GjYXSe/3KNGO/7753awXv7siLN7WVBeKPvjgA7Perl078/ddpKDcfJMv3lkehsFPRODYMZsJMPoNDMeoEYHo8pAm0xMpkiMWcmkascidyew+WRNnAgrO0prWVVda0aa1H1q38kOF8homF7kUW3QCtt3wullvuLsHvAJTrv5ypJntxWnjxo0ICAjQwZQCFxFhN4XcGzYmpV3Tg+398PRTQaZlrYgUDF16ErcRE+PA1+uTUp22/JhwUfManu+wRSEDCo5SWK365yKSGRarBcE3lkleFynsQkKsmDMrBLPmROO1pUmTEL33fhx+/dWGmdNCUKKEirpFCoICCynUOKC2Y2eiKcJmqlNU1MUDbKyXYDBxb1M/BAXqpEgkq6z+3qj9bmsdOHErXl4WPPlEEKpe541x4yMRHw9s35GITl3PY87MEFSvplMckfym3zoplE6etGH1J3FmOXHi4lSnCuUvpDrd74errlKqk4iIp7q/pR8qVfLCY0+E48wZB06etOPh7ucx+flgNGvqV9C7J+JRFFhIoREd7cCXX8fjo9Wx2Lrt4tl/g4IsaN6MXZ38UO9G73TnTREREc9zfW1vvPtWMRNc7N1nQ0wsMHRYJB4daMOAfgFKjRXJJwospEDZ7Q4zdM0i7C++ikN0dOrbGTuwjSC7OjW5xxeBSnUSyf3fw9hE7OuyxqzXeut+kxol4m7KlLHi9SVhGD8x0sxjRHPnx+DQYRsmPxes/x8i+UD/PaRAnPjDho+Z6vRxHP48eXGqU6WKVrRt44dW9/vhinJKdRLJSw67A1F7/kleF3FX/v4WTHk+GFWrxmL6zGjT5OPLr+Lx+4nzeGVmCK68Uv9PRPKSAgsP9O+/dpwPdyA+PmnhJOlJC79H8rb4hAtfzf2Sbr/c/RJ4v8SU+5v7ud7Ox8c7zDB1WsHBFtz3v6RUp7o3KNVJJL9Yfb1QbVGz5HVXvr6+mDlzZvK6SGHHNNnePQNw7TVeGDE6EpGRDhw8aEOnLucxc3oI6tfTZHoiBT6PRfXq1XM1p71Zs2aYNWsWPFFBzmOxeEkMZs5OuopTGFitnPDIxwQTTe72NVebREREcsPRY4kYPCQCv1+Y74jzO457OggPtvPXARYpyBGLtm3b5mpgUbt27Vx7Lsm8bT9dPP9DXuEfcB8fXuW0gBc6fXws8PVJ+srRibvu9EWrlr4oW1ZD0yIikvuuqeKNt5eHYfjISGzekoDERODZCVE4dMiGkcMD4e2ti1kiHjnz9urVq80V/r179+LQoUNISEjAlClT0K5du8s+9sSJE2jdujWio6PRqVMnTJw48bKPeeSRR/Ddd9+Zof89e/ake59ff/3VpAhs2bLFzE5buXJlPPTQQ+jcufMlg7CCHLE49qsNb70dg5gYpJzs86uvBT7eSUGAMxgwX523u3xNdXvy/VJvY1ChCepE3IPDZsf5zX+Z9bCbr4DFK2VyscTERKxbt86s33ffffDmL7eIm0lMdOCl6dFYviIlD5eNQaa9FIxiYZpMTyS3uM1/CKZN/fnnnyhevDjKlClj1jPDbrdj9OjRWXqtd999F99//z38/PzMBG3pOXLkiAkiYmNjzT9b7tOGDRswYcIEHD16FOPGjUNhVOVqL4wdE1zQuyEihYg9zoYDvZKCh4a7e8ArMOVEixdx+HeNmjZtqsBC3BJHJp4aGYSq13ph4vNRZuRiy48JeKjrebwyKwTXXuM2p0MihZrbhOmTJk3C+vXrzegAT+gza9myZdi1axeGDBmSqfv/8ccfmDp1Knr27IlSpUpleL/x48cjIiICc+fOxUsvvYQRI0bggw8+QIMGDbB8+XLs3Lkz0/soIlKQLFYLAquXMAvXRYqq9u38sXRxKEqWSPqccwLWLt3C8e2GpPa0IuIhgcUtt9yCq666KkuP4cgBU5X69euHGjVqXPb+HJ0YM2YMSpcufclAhClQ27ZtQ+PGjXHnnXcmb2falPNxHPUQEXEHnLeiziftzKI5LKSoq3ejD955KwzVqyXV90VFOUyBN5ubuEl2uEih5TaBRVbZbDaTAlWpUiUMHDgwU4958803TcAwefJk+Ptn3DFi69at5uttt9120W2snQgMDDTPIyIiIoXPlVd44c1lYfhfs6QWyownZsyKxugxkYiNVXAhkl1FNrBYuHAh9u/fbwq8M9N7/bfffsP06dPRrVs3Exxc7r7EoCUtLy8vlC9f3tSAsOhRRERECp/AQAumvRiMwYMCkretWRuPHr3P4/RpW4Hum4i7KpKBxYEDBzBv3jz06dMnU21tnQXeTIEaOnToZe8fGRlpvoaEhKR7e1BQkHnOqKiobOy9iEj+sscmYn/XNWbhuoinYAfHgf0DMWt6MAIuxBd799nQqet5/LwnoaB3T8TtFLnAIj4+HqNGjULFihUxePDgTD1m8eLFpsD7+eefR4DzL4uIiIdw2B0I33rKLFwX8TRNm/hhxRthuPLKpNOiM2cc6NE7HJ+siSvoXRNxK7nSX61Dhw6YNm2aOZkvaIsWLTLzXLzzzjuZSoFiIfacOXPQpUsXNGrUKFOvERyc1K6VXaHSw5EKXgXhyIWISGFn9fXCdbPuSV53xb+j7JTnXBcpqqpV9cbKFWEYOjwCP21PRHw8MPrpSJz8y4Z+fQNydZJgkaIqVwILTiB37ty5QhFYsK6CaUgdO3ZM9/aVK1eapUmTJiZdip2jOMqxYsUKs6SnWrVq5isLskNDQ81EeHT8+PF0i8bZspZ1FppISkTcgcXbipItqqR7G+vGOH+FiCcoUcKKVxeGYsrUKLz7XtJoxexXYnD6tB1PPxUELy8FFyKXUuRmhLn11lvNJHppnTlzxkxgV6VKFTPbdc2aNc12trB98MEH032utWvXIi4uDg888ECqq3UNGzY0XzmJHlvZuuJs2pzhu3nz5rn+3kRERCRv+fpY8MzYIFSo4IVpM6LNtpWr4nDmHztenBKCgAAFFyIeE1h07do13e0//vijCSwYFEycODF5O+e3YG1FejZv3mwCkrS3Mzjh8zif0zmXBUc+OEO4Mz1MRMQdOGx2RO7626wH1y0Di5c11SjsN998Y9bvvvtuM4IhUtQx7al3zwCUKWPF0+MizUzd679JQN/+4Zg7OwTFihW5ElWRwhVYjB07FrVq1ULVqlVx7bXXmq9ly5bNrafHqlWrzGgAsYbCuc05pwRbxObnyfyzzz6Lzp0749FHH0WLFi1MRykGGYcPH8bDDz9sRkVERNyBPc6GfQ+tMesNd/eAV2DKSRMvmLBrHm3cuFENLsSj3N/CD6VKWvH40Agzkd6u3Yl4uMd5LJgbivLlFWSL5FlgUbJkSfzyyy/49NNPzT8iRvsscr7mmmuSg43rrrvOLKVKlcry8zOo+PDDD1Nt27Fjh1mc8jOw4Pvg7Nqc2ZsBBdOfWHvxzDPPmEJwERG3YbHAv2Jo8rqIpLipsQ9eXxKKgYPDTbeoX3+zo0v3pOCiZo0il/ghkiMWRy7MX1+9enVzkl2nTh1TOM2i5iNHjpir91y4zu5LnDCOAQcDEE/GYIgjLAyWNLIhIoVZTEwMbr/9drOuEQvxZCdP2tB/UASO/Zo0eV5gIDBzWghuvUXd0kSccj3UtlqtuPrqq81y7733Jm9nUMHggkGGiIiIiDu58kovvPl6KAY/HoGduxIRHQ0MeiwCz40PRutWfgW9eyKFQr5VH7H1KtOH7rvvvvx6SREREZFcUyzMisULQ9H0nqRRChZ1PzU2Eq++FoNcSAARcXu5ElgsX74clSpVyo2nEhGRfGaPS8SBRz43C9dFJGP+/hZMfzkYD3VKGaWYOTsaz0+Jgs2m4EI8W66kQjVo0CA3nkZERAqAw+bAuW9PJK+LyKVxoryxTwWhXFkvE1TQ2yvjTHH3C1OCTfAh4onUzkBExMNZfKyoMvWO5HVXPj4+pr22c11ELvzeWCx4pE8AypaxYtz4pLkuvlofb+a6eIVzXYRprgvxPLnSFUqyRl2hREREio5NP8TjiWERpqCbqlzthYXzQkzBt4gnyZNwetu2bfjpp58u2s5tvE1ERESkqGDL2TeWhKFkyaQUKLak5VwXvxxQzZJ4ljwZseC8FuwCtXfv3lTbOTM357nQPBaax0JECg+HzY7oQ/+Z9cCqxWHxSrnmZLPZsHnzZrN+8803w8tLV2BFMvLHH5zrIhy/Hbeb74OCLJg9I8RMsifiCfKkxuKNN94wuYdpLVu2TO3YREQKGXucDXtaf2jWG+7uAa/AlMAiPj4eTzzxhFnXBHkil1a+vBeWvx6GRx+PwO6fExEV5TCBxvMTg3F/S811IUVfngQWjRo1Snd7w4YN8+LlREQkJywW+JQJTF4XkewrXtyK1xaFYsToCHzzbYIp6h41JhJ/n7GjVw//dC+8ihQValkgIuLhvAK8UX9TF7NwXURyJiDAgpnTQtDxwZRRimkzojH1xWjNdSFFmgILERERkVzm7W3BM2OD8PjggORty9+KxfBRkYiLU0NOKZoUWIiIiIjkAaY99X8kEJMmBsHZ9+CLL+PxyIBwnA9PKvAWKUoUWIiIeDh7XCIOPfa1WbguIrnrgTb+mDs7BAEXBi+270hEtx7hOPmXTYdaihQFFiIiHs5hc+DsZ7+ahesikvtuv80Xy14LQ8kSScXbR4/Z0LXbeRw8pGBeio58DSy+++47NGnSJD9fUkRELsPiY0XlZ242C9dd+fj4YOTIkWbhuohkX+1a3lj+RhgqVkz6Pfv7jAPde4Xjx60JOqxSJORrYBETE4OTJ0/m50uKiMhlWH28UK5bLbNw3RUnO+3YsaNZuC4iOVOxghdWvB6G62sn/T5FRibNdbF2XZwOrbi9XPkvMWvWrEzd7+jRo7nxciIiIiJuq0QJK5a8GorhIyOwYWMCEhKAEaOT5rro2T2li5SIRwYW8+fPR2hoKIKDgy95v9jY2Nx4ORERyUUOuwOxv4ebdf+KobBYUybwstvt2Llzp1m/8cYbYbWqNE8kNwQGWjB7ZgiemxyF995PGq14aVo0Tp+2Y8SwQFhdfg9FPCqwqFixIurXr48pU6Zc8n6fffYZhg4dmhsvKSIiucQem4jd964y6w1394BXYEotRVxcHPr372/WN27ciABnWxsRyZW5LsaPC0LZMlbMnR9jtr2xPBZ//23HlOeD4eur4ELcS65ceqpbt27yFa3L9XN2ONRxRESksPEK8TWLiOQvnhsNGhCIic+mzHXx2Rfx6DcwHOGa60I8ccSie/fu2LFjx2Xv17BhQ7zxxhu58ZIiIpJLOELRcEd3HU+RAtS+nT9KlbJi2IgIxMQC235KNB2jFswLQbmyqZsqiBS5EYtvv/02eb127domuLicEiVKoFGjRtl9SREREZEi6847fLFkcSiKF09KgTp8xIau3cNx/Lgm0pMiHlgMGDDA5N0eP348d/dIRERExEPVud4HK94IQ4XySadop07Z0a3XeRw6rIn0pAgHFs2aNcOGDRtw//334+WXX0Z0dHTu7pmIiOQLe7wNR0dtMAvXRaRgVaroZSbSq1o1KQXq338d6NE7HD/v0UR6UkQDi9mzZ2Pp0qWoVKkSFi9ejObNm2P16tW5u3ciIpLnHIl2nPngsFm4LiIFr1RJK5YuDkWd65PKYcPDHejTLxzbflJwIUW0K9TNN99sgonRo0ebWbX5tXPnzti3b1/u7aGIiOQpi48VFUc2NAvXXXG27ccff9wsmnlbJH8VC7Ni8cJQNGyQFFwwOYSzdG/8Pl4/CimULI5c6v969uxZvPTSS/joo49M67T27dubOStYsC2psYMW5/3Yvn076tWrp8MjIiIiGYqNdWDo8Ah8tzFptMLbG3hxSjD+18xPR00KlVybQpUBBCfIW7lyJWrWrIlVq1aZ9Ci2l+XMrSIiIiKSdf7+FsyaEYL/NUuaayYxERg+KhIfro7V4ZSiGVg41alTB/Pnz0eTJk0QHh5ugo02bdpg8+bNuf1SIiKSCxx2B+JPR5mF6654YWj//v1m0UUikYLj62PBS1OD0a5t0igFr9mOfSYKK95OmrFbpEhMkBcfH29qKnbv3o2ff/7ZfD158mTy7cy0Onz4MHr37o0WLVpg3LhxKFasWE5fVkREcok9NhE7bnvbrDfc3cNMmOcUFxeXPE/Rxo0bERAQoOMuUkC8vCyY8GwQAgMtWP5W0mjF5KnRpvbikT763RQ3DiwmTJhgAomDBw/CZrMlBxEs7qtRo4apHbjxxhvNwsLuF198EZ9++il27dqFZcuWoUKFCll6PRaJsyZh7969OHToEBISEsxoSLt27S772BMnTqB169amJW6nTp0wceLEVLcfO3YMS5YsMc996tQpREZGokyZMrjuuuvQs2dPU6SeVrdu3bB169Z0X++qq67C+vXrs/T+REQKksU7aUIuESncrFYLRo8MRGCQBYteTRqtmDk7GpGRdjzxeKCpcxVxu8Di7beTrm6FhYWhbt26yUEEU6HSu6K1cOFCvPfee2bE4oUXXsArr7ySpdebNWsW/vzzTxQvXtyc9HM9Mzh0z25Vl8JA5csvv0x+H8HBwTh9+jS+/vprM8P4E088gYEDB6b72MGDB1+0LSQkJJPvSkSk4HGEovEvfQp6N0Qkkxg8DBkciOAgC6bPTJpHbPGSWERFOTBmdJAJPkTcKrCYNGmSOQm/5pprMv2YBx98EOvWrcvwSv/lXo9zZnA0YNGiRZg2bVqmHsfREY6SjBgxwoxwpOeee+7B//73v4uifAYXDzzwAObOnYuuXbsiNDT0osc+9thjWX4vIiIiIjnVp1cAgoIseO75KPP92yvjEB0DTHw2CN4ahRR3Kt5mkJCVoMKpXLlyiIiIyPLjbrnlFhNUZMXRo0cxc+ZM9OvXz6RnZcTX1zfdocOyZcualC6mXbnWjYiIiIgUBg919MeUScGwXjijW/1xnOkYFR+fK7MJiORv8XZWsYib7WjzGus+mALFUQ6mMe3cuTPLz/Hff/+ZYnSmdpUvXz7d+3zyyScmLcvf398ELw0bNoTV+dstIuIG7PE2HJ+8xaxXGnMTrL5eBb1LIpIFrVv5gVnoDCjYivbLr+LxWEwEZk4LQUCA0qKkEAYW7OzEYuacYs0D04ryGms62B6R82pwRCIzfv31V6xZs8YEJX///bcpwOboyvjx403dRXqGDx+e6vvKlSvj5ZdfxvXXX58r70NEJK85Eu04veIXs15xZCNAgYWI27m3qR/mzrZgyJMRiI0Fvt+UgAGPhmPu7BAEB+uCpxSywIJdle677z6TVlS9evUsvxBP8nmyzyJpruelAwcOYN68eejTpw9q166d6cf99ttvqYrKAwMDMXnyZDMPR1qcp4PPz1EKFrBz1OKdd97BihUrzKgMu1hdeeWVufaeRETyisXHivKP1Uted8VOf/y771wXkcLrtlt9sWh+KAYOjjCF3D9tT0TvfuFYNC8UxYopuJC8l+n/Eo8++qhpycri66pVq6Jly5Zo1KiRSWtKb0SAvc8ZQLBQm6MAR44cMSlFfJ68xHk1Ro0ahYoVK6bbselS7r77btM+l8/BQOHdd981z7Vnzx6MHTs21X3ZhtYV602efvppM7LBoIbHKu1jREQKI6uPF8o/nhRYpOXj45McWIhI4Ve/ng+WvBqK/oPCce6cA/v22dCjdzgWLwxF6dIKLqSQBBY8Se/cubOZVZtX46dPn24Knr28vHDFFVeYjklBQUGIiorC+fPnzXwQTCni3BZsv8oJlvr3748SJUrk6Rtixyi2j+XoQWZToNLi466++moTVMTGxuLNN9/E7bffjjvvvPOyj33ooYdMYLFjx45svbaIiIhITtSu5Y3XXwtFn/7h+OcfB44ctaF77/N4bWEorrxSNVSSd7I0rl2yZElzFZ51BRy5+Oabb8wJNCegS6tUqVJo0KAB7rrrLpNC5eeXNAV9XuMoCes4OnbsmO7trLngwlQmBgCXc+utt+Ktt94yIy+ZCSw4qzgDLk7GJyLiDngByBYRb9a9QlJ3yePfU6aJOmvI1JxCxD1ce6033lgahr79w3HypB2//25Ht17hJrioXFnBheSNbCXMsgMS53fgQmfPnsW///5rCp05OsEAJK9HJi4VCHASvbTOnDmDDRs2oEqVKqaFbGY7U7GIOyu5xZyNnP+ks9oaV0SkoNhjEvFT/TfNesPdPcyEea5prc4LNRs3bkx3AlQRKZwqVfTCG0tD0bdfOH47bsepU3Z073Uery4MRbWqqpmS3JcrnyoGEQUVSKSVUcepH3/80QQWbAc7ceLEVLft3bsXtWrVumguC9ZZMLWK7rjjjuTtHKFhAMXRibQT6k2YMMGst2rVKtfek4iIiEh2XFHOC68vDUO/geE4eNCGf8860LN3OBbOC0GdOikXEUQKRWDBq1nHjx83IxYcKWBtQl6kPa1atQrbt28366yhcG5zzuJdv359dOjQIVvP/cILL5j3cMMNN5h6EQ71//777/juu+/M5Hjs8sTnd9q2bZtpQctUL85vwfqSP/74wwQuTIFiUJFeJykRkcLIGuCNRvt7mXWLt4o7RYqaUiWtWLo4FAMGReDnPYkIj3CY+ou5s0PRqKGCCykEgQXTfebOnYulS5emqidgUMFZsvv27WtSjnILg4oPP/ww1TbWd7gWSWc3sOAoB2tG9u3bh++//94EExyBYZcopgCwcNsV06iaN29u7s+OUXz/HMHg+23fvj1atGiRzXcpIpL/OFpr8VHOtUhRFhZqNZ2hBg8Jx9ZtieCpG+e5mPFyCO68I3vNbkTSsjgYIWTDnDlzTGBB1apVMzNcx8TEmJNt1lzwHxVPsp955plsd2cqqhgMcQSEwVJuBl8iIrmNf9edF1dUYyHi/mJjHXhyeAQ2bEww37OE9MUpwfhfs/xpsiNFW7ZHLD744AOTMjRz5kw0a9Ys1W2bNm3C7Nmz8d577+Gvv/7Cq6++qk4iIiKFlD3BhhPTfzLrFZ5sYOa1EJGiyd/fglkzQvDU05FY93k8EhOB4aMiER3twANt/Qt698TNZTuZll2WWGOQNqhwdmbiPBLsGvXDDz/g7bffzul+iohIHnEk2PHX4j1m4bqIFG0+Pha8MCUY7domjVLY7cDYZ6OwfEVMQe+aeOqIBVvKptfW1YmpUOyQxAJojlxk1K1JREQKlsXHiiv6Xp+87oqttrt165a8LiJFg5eXBROeDUJgkAXLV8SabVNejEZUtAP9+gZc1ClTJDOy/V+CbVs5GsGuUBl1gWJtBWsJ2C1JREQKJ6Y+VRrVON3bfHx8MGTIkHzfJxHJe1arBaNHBCI4yIIFi5JGK2a/EoOoKAeGDglUcCH5lwo1cOBAU9THtquXEhkZaTomiYiIiEjhwpGJxx4NxLChgcnbXlsai+cmR8Fuz1Z/H/Fg2Q4sRo8ebeas+Oijj8ww+a5duy66D+eY4HLvvffmdD9FRCSPsDkgC7i5pG0UaLfbcfLkSbNwXUSKpt49A/DM00FwZkCtfDcOT4+LRGKiggvJh1Qozt/gOmFc586dUa5cOTODdXBwsJm1mu1UmzRpglGjRmX3ZUREJI/ZYxKx7YbXzXrD3T3gFZgyYRbTXVu3bm3W1W5WpGjr1NEfgYEWPP1MJGw24OM18YiOicRLU4Ph66uaC8nDwIL1Fb/88gv2799vvnL+Cs5WzfayrnjbyJEjzaRyNWrUMIFHqVKlsvuyIiIiIpJHWt3vh4CApBa0CQnAV1/H4/GhEZg1PQR+fgouJI8myEtPVFQUDhw4kBxo8OuRI0eQyCbJF/L4iIEFr3x5Kk2QJyKFCf8N2CLizbpXiG+qgk1NkCfimTb9kBRQxCY1jMJtt/pg9gwFF3Jpudo7MCgoyHSB4uKUkJCAw4cPJwcaHOE4ePBgbr6siIjkAAMJ71DNuisiKW69xRcL54ViwKPhiIkBvt+UYAINBRdyKXnelJytCpkGxcUpFwdJRERERCQPNKjvY4KL/oNSgovHnojAnJkauZBc7gqVE5p0RUSk8GA3qD9m7zAL10VEnOrXSwouWHdBm35IwOAhTJHSRWIpJIGFiIgUHo4EO/6Ys8MsXBcRSS+4CLww1cUPmxPwmIILSYcCCxERD2fxtqJs1xpm4borLy8vdOjQwSxcFxHPdFFwsUXBheRxVyjJHHWFEhEREXe0Y2eCqbmIjk76/pabfDBnVgj8/dWKVnJQvM0ZtzNbvF2sWDFUr14dJUuW1DEXERERcVP1bkwp6GZwwZEL1lywoDsgQMGFp8v2iAUDhawUYfO+N998M8aNG4fKlSvDk2nEQkTcBf9FnDt3zqzzIpGab4gI7dzFkYsIREUlnUbe1NgHr8xScOHpsh1YzJkzB3/++acZuQgMDMRtt92GK664wtzG2bc3bdpkJsxr06YNfH19sXPnTjNZHkctPvjgA5QtWxaeSoGFiBQmtugE/FT/DbPeYHt3eAX6JN+mCfJEJCO7dieg38CU4KJxI2/Mnc0OUhq58FTZToViwMBivvbt22P06NEICQlJdXtkZCSmTJmCr776Cu+++y4qVKiAF198EcuWLcOiRYvMyIWIiBQOjkSV24lI1tS9wQeL5ockBxc/bk3Eo4+HK7jwYNnuCjVt2jSEhobiueeeuyiooODgYHMb7zN9+nRYrVY8+eSTKF26NDZu3JjT/RYRkVxi9fdGve87m4XrIiJZCS5eXRCCoKCkUQoGF4Me44R6uljhibIdWPz444+oU6eOCRgyfHKr1dxny5Yt5numRLE24/Tp09l9WRERyWUWqwW+ZYPMwnURkay4oU5ScBEcnPT3Y+u2pOAiOlrBhafJdmARGxuLf/7557L3433i4+NTjWSoF7qIiIhIEQsu5iu48HTZDiyqVq2Kn376Cdu2bcvwPs7beV8nFnaXKFEiuy8rIiK5zJ5gw8lXd5uF6yIi2VEnTXCx7SeNXHiabAcWffv2hc1mQ58+ffDMM8+YLlBHjx41C9e5jbex6RTvSxEREdi3bx9uuOGG3HwPIiKSA44EO35/cZtZuC4ikqPgYkEIQkIUXHiibFfpNWvWDE899RRefvll0/Vp1apVqW5nQMHJ8Xife++912xjL/THHnvMzGchIiKFg8XbitLtrkted8XU1fvvvz95XUTkcupcz+AiFI8MCEdEhMOMXAwcHI55r4QiKFB1XEVZtuexcDpx4gTee+89M0/FmTNnzDZ2fqpXr55pRcs2s5Ka5rEQERGRom7P3sTk4ILq1/PG/LkKLoqyHAcWknUKLERERMQTKLjwLNmusRARkaKP1544+zYXXYcSkay6vrY3Fi8MReiFmovtOxIx8NFwRKkVbZGUKzMhMQ2KHaCc81OULVsWDRo0wI033pgbTy8iInnIFp2AHbe9bdY5SZ5XoE+q1uK33367WefkpgEBAfpZiEiW1K7ljcWLQtG3XzjCIxwmuBgwKBwLmBZ1YWI9KRpyFFj8+uuvGDlyJPbu3Wu+d17NsliSPiS1a9fGSy+9hMqVK+fGvoqISB6xRaTMNyQikttq1bwQXPQPR3i4Azt2JqL/oHAsnKfgoijJdirU33//jW7dumHPnj2mWJvr7AA1ZswYdO/eHWXKlDG3cTvvm1OrV682LWzbtWtnApZq1arhgw8+yHSBOUdP+Bg+R1rHjh3D2LFj0bZtW9x0003m+e+55x70798fmzdvvmRgNWTIEDRu3NjMMN66dWu89dZbSheQdGeq5+dvzpw5+Xp0Ro8ebV73jz/+yNT9+bnnUpikt0/83U/vbwC38W9Obsvo9dLbN/6MeV/+zAs7fi64r2MmjMUNX3Ywi9U/VwayRUTSDS5eWxSK0NCkC9A7dyUFF1FRKvctKrL9H2T+/PlmVu2ePXviySefhK+vb6rbhw8fjunTp2Pp0qVYuHAhxo0bl6MdnTVrFv78808UL17cBC1czwy73W5Ori7l0KFD+PLLL1G3bl0TgHB2cKZ1ff311/j222/xxBNPYODAgakec+TIETz00EMmTeC+++4z+7RhwwZMmDDBzOWR0/crIpJfOMocUDlMB1xE8lzNGknBRR+mRYU7THDRjyMXczmxnkp/PTaw4En01VdfneFJO+ewYJoUT8y/+eabHJ9oT5o0CZUqVcJVV12FRYsWYdq0aZl63LJly7Br1y6MGDECU6ZMSfc+vOL4v//9LzmFy4nBxQMPPIC5c+eia9euCA0NTb5t/PjxZsI/7sudd95ptnH0olevXli+fLnp+64aE3HiiNbatWtNYCw5x7lxONEmA/qCxL8vIiKSs+Bilxm5iMDCeQou3F22Q0POWVGzZs1L3ocn6ryPc36LnLjllltMUJEVHDmYOXMm+vXrhxo1amR4P462pA0qnEXonI8jISEBJ0+eTJUCtW3bNpMC5QwqnM/D4II4aaCIEwter7nmGpQoUUIHJReEhISY48mvBalixYpmcXcOuwOn3txnFnuCraB3R0Q8JLhYsigUYWFJ51+7dicFF5GR9oLeNSmIwILpQqdOnbrs/Xgf3je/2Ww2M5rCUY60aUyZ9d9//2H37t3mpLB8+fLJ27du3Wq+3nbbbRc9pn79+ggMDDSBh+ReXQLn/mDuPEeBWAfDESOmoRFHxTp16mRS2RiAvvjii0hMTEz1XM7RpYcfftj83FhHw68cVfv9998vem3XPHnm1XPkilfIXfP3Dxw4gEceecTsE3/uXGdaXXp1DRnVWDhz9KOiosyonHPfWrVqhc8+++yi/WJQy/fH/WFge/3115vRtpdfftk8R16Jjo7G7Nmz0bx5c/OajRo1MgH79u3b073/2bNnzSjlzTffbI4bJ8tkumFGtQpZlZXnYVOJyZMnm/sPGzbMXChwbufknkxp5AUE7idruLgtsy5Xk/LJJ5+gTZs2ZsSKP1v+jJ2f27Tef/99dOjQwXyeuHD9Uu8vK/fn30N+/jnSw58fvzJFNbl9rN2B3yZuNosjQf/URSR/1LgwcqHgoujIdioUT+J4QsflrrvuyjBdiieEd999N/Ib/2nu378fK1euvKj+IyM8aVuzZo35J8yC8/Xr15sTUp7EugZHv/32m/nKoCUtLy8vE4SwBoMnt97eKoTMKQZ3r776qjkx40kgT9LffvttREZGmpM6nsg3adIk+TP52muvmeBu8ODBqUaveGLMk3GeVDFYZNE+f978nPKELL0RMT4XX4/Pf+utt5qfrzOo6NKli+ntz+dj5zN2R+O26tWrZ+n98US3T58+OH/+vAkS+JxMm2Jtz+LFi1MFsDw55wkl3wdP7llD5Dw+DGaZhsc0xNwUFxeHHj164Oeff0atWrXM+r///mv28fvvvzdpiawzcmKAwwCMvwM84W3YsKG5wDB06NB0g/G8xGPLzwd/ztxvNpjg6CRPqFkHxu382TF1kX8nNm3ahKefftp8XkaNGpWj116xYoVpz8rPKINhrr/55pvmgkXaVE4GHLyNo6QMwuiLL74w+8u/Y2wukZP7M8jj54Z/m5jWyZ8p69/YKtywACWaX5206pV69JafeX7+nesiIrmpRvWUtKjz5x1m5KLfwKS0qJAQ1Vy4HUc27dixw1GzZk1HrVq1HMOHD3d8++23jiNHjphlw4YNjpEjR5rbeJ+dO3c6ctPChQsdVatWdbz//vvp3v7LL7+Y1542bVryti1btpjHjBs3LsPnXb9+vbmPc6lbt67jo48+uuh+Y8eONbdv2rQp3efp1KmTuf3cuXPp3r59+3ZeJjRfJWPOnxmXL7/8Mnl7fHy8o1WrVo5q1ao5Gjdu7Ni9e3fybREREY6bb77Z0ahRI3M/p/DwcMd///130Wts3rzZUb16dcfTTz+davvs2bOTPwMHDhy46HGdO3c2t3/88cepts+cOTN5n0+cOHHRe+Hzurr77rvN9oEDBzri4uKSt//www9me+/evVPd/9SpU6nu5zRnzhxz/9WrV6faPmrUqIv25VK4P1zSe+5hw4Y57HZ78vZ9+/aZ37MGDRqY4+40Y8aMdH/XnO/pUr+7md0nPj695+G2hx9+2KxHRkaa48dt/JvhauXKlWb76NGjU31OeGz79+9vbtuzZ89lXy+9fXN+durXr+84evRo8vaYmBhHs2bNzOeNP0enrVu3mvvfd9995nPqxL8fvD9v27ZtW7bv7/zstW7d2hEVFZW8nfvA3x/exs+JiEhB+uVAguOWO/511Kzzj1ke6nrOER5u0w/FzWT7cjqvRDK94NlnnzXD/bzylyZggb+/v+mSxCvJ+SU+Pt5caWTes+sV68zgyMrBgwfNc7DrFOsk+Fxsm5v2CmBh8PkXcXhlXkyhbdPGSW8GPxqA/93rl6Pn4dX5pk2bJn/PK/K8ss+fFX9mTDNx4sgSR9B4dZZXyStUqGC2Z5SLzyvJ1157LX744Yd0b+/YsaNJoXHFzwZTgDgywZQlV0yH4pVqjj5kBa80u46sMYWIIyjOOWKceIU6PUzxYpoV2yOz7XFu+uijj8wx5xV+11ok1k8xJYu/J1999ZVp10wff/yxuf/jjz+e6nn4njhiwVGOvMZULKZq8eo9/045r+o7cWSHo1r8++U6wsOfAUdW2HDi008/NWlp2cW221WqVEn+nn8POTLyyiuvYN++fck/yw8//NB85d8r189pWFiY2cbjzhE1Tjqanfvz50ePPvqoec9OfH3uIzvuiYgUtOrVUkYuzp1z4Oc9SSMXi+Zr5MKd5ChPh7nDPOnjiQVPtJzzVbBTC/+pPfjgg7jiiiuQn5hHzDz3d955J9MpUGnxcex4xaCC+dBMOeDMs85CbWdaFNOk0sNUEJ6ABQUFIS8tWRaDY78W7kLLpcticxxYpFd47+wGlN5tnFeF+Hl0BhbElKbXX3/dpPQwHcW1DiOj9CHXoMWJaVDEvPy0eOLGgCMrcxiw25jrfrqe+LGjWdqAnUETTy4PHz5sPoNMh3LKjTljXDHdjPPAsFC6XLlyF93u/P13HhPen4EXg7VSpUqle0EibWDBzkppf5cYsLjWNWUF22B37tzZBJY8iU9bA8FUM/6N4GeIKWRpOT8XTJXLCaaNpeU8huHh4cnbfvnll+RjmZZzm/P4Zuf+DMDJGWi4Sm+biEhhCi4eGZAUXISGKi3KHeS4AID/KNNemSxIvELJEy1eaU4Pay64MGd43rx5l30+5tVz0jsWbDsDC+dM4sePH7/o/qzPYNEuT4ryur6id68AvDK3cI9Y9Orpn+PnSa/435nrnd5tzuPuGjisW7fOXInmiT+vmnM0gHUWDAB5kp7RvCglS5a8aBtPnjO6jdI7ob6UjEZT+D5cgwZnbj2vtjNg5wkzgyhnAM2TaI625abLvVdnEOe8n/NrRt2v0js2b7zxxkXHn/Uj2Q0s2IWO+8EaKBZkp8WTegZobCfNY3apgvW8+ty6/ly5r1arNd1jxuPFz6jzuGbn/gzaeP/0Wh07f66ORDu23/qWWa/7VUd4BXinCsR4YYVYJ8LfGxGRvAwulryaFFz8958De/YyuAjHqws4sZ6Ci8KuyFUWMxBI7x8oTzZYpMvUBF5pvlyr3LRXgF2DBBajEq+8Mt3CFUdueELC7jl5jSMBOR0N8BQ8gfTz8zMpIs7A0IkpLxlJrw2x84SRBcwZXTHPC3w9plkxNYvBsesJHj/flzpJzq7Mvlfn/ZxfmYp0qfu7YpOE3MRRLKZlMX2RqT4cpXINaJwjiRxRyGl3qtzAY8ZAg8csbQDH484gyDVIyer9Gbjy/hylSxuMuP5cE/6+EEg5O0WJiBSQalWTgovejyQFF3v32TDg0QgTXPCipRSBwMLZFSQ7eHLGHOz8wI4n6WFqCgMLBgUTJ05MdRvz2HmSkfYkkldRmVpFd9xxR/J2Bid8HudzOkcyeLXYma/M1o9SeLCl7HXXXXdRUMHA0bUtbGY4uz4ld9Rxwau7ztST3MaUJJ40sqVu2qvGP/30U568Jk9QmabF48cr/GlrPJwpX85jwvtzNIijeTxpTXvim94xywusqeDoAGtXGFxwVMQZXHAfmdrFVCeOXrhOfFkQGAhxpJXHskWLFqluc7a2du00ltX7MxBlTQc/I82aNUv/c+NlwfUfP2BWrX7q/CQiBa/qdamDi90/J2LQY+FYMDcUAQEKLgqrTI8p8SQ7u0tWT9zSs2rVKtM2kouzv7/rNq5n1wsvvGCCg8cee8wUek6dOhWDBg0yBcJ//fUXevfubeYpcMWiT14JZEEk50J46aWXTA98/qNmIW16+fdScK688kpzsut6xZwtN9lK2DmvQWbxxJk/X+a6s+Vq2va0586dQ169B+fJuWsqDWsJpk+fjrzCq/88RmyRmjzvwYU8fqaR8ffAtbieBe28P9v7uuKJcH4Ubrvu95QpU0wbaba/dZ2ok98zCOSoRnopTwzicuPvVmawnoTmzp17UQqTcxTKeZ/s3J+1cM77u75XBooMuMjUhNUoaRaLl1INRKTwBBeLFzIFKimQ+Gl7Ih5/IgJxcRpZdfsRC9diwILAFCNnNxQnzpHBxSm7owQc5WAOPq/q8cSHJ0VMGWDHIdZqOPOLXfHqN4tWObM3Ry34D5tXw5955hkzl4EULjyRfO6558zJJtPUWH/BTlA8UebV3ax+vjkvAD837MDz+eefm3x+fn44pwRHszinBPPacxOLjRns8vV4RZ4drTgqwLk7uJ7eRH+5gZ2u+BlfvXq1md+B3Z34uvydYU0Rj6tr6g3vzzkV2ECBBeYsEGbww/vzd4odl3L72GSEP2++Fi8+8DPAE2keR86Hwp8V/6bwbwhHgbid74sjGbyNgVR26zyygp8X7hubRLBrFEcV+LnkMeRx423O9Mvs3J+fDV70YNoXgz7Ou8LRVQbF7NjHn4eISGGuuVg0P6nmgjWlP2xJwJMjIjBjWgh8fTRyUdi4TY0FRxG4ZBe7pWSUosITzezURDAlKu1VWSmcGASwToaFzwwImf7CUSrOxDxkyJAsPx9rdFjUzxmvv/vuO3PFl6Na3OYcPciLGed5BZ4jJgwu+F44itGzZ09zMs9teYG1KaxTYAclnoyyixNTsXjy2r9//4s6C/F9sxaEJ+Zff/21STVklygeF44E8EQ2L45NRth+l8EFRxadNRdM6eLfE6Y4crSTwRkvDvCCAoNEdoRjAJVfOHLCFCdO/MjPJ/GYsTFG2la52bk/i/7Z6Y735eeGTTd69eplJjbkz8Nhd+Dv9w+Z+5ZqfQ2sPkqHEpHC4/ra3pj/Sgj6DwxHTCzw7YYEjHoqEi9NDYa3t4KLwsTCySwKeic8Da+Q8iSUozBKmSpaeAWfV4TZpjijuTE8GUd4OO8NAxTWOUjhYItOwLYbXjfrDXf3gFdgSvtldYUSkcJiy48Jps4iLi7p+1YtffH8c8Hw8lJwUVgomVYkG5hKlV7nIxb7s67ItebAE6U3nwYLixlQ8Mq5gorCxeJlQbG7KpiF665YBM9ue1yc7XJFRArCTY19MGtGCJyNOj/5NB4TJkWlqv+TgqURiwKgEQv3x25CzMvnyRZraxhoMC+fs7Rzbgfmszsn8fNErG3gTNOsX2HaFGszOAcCT0wXLlxojpuIiEh2fL0+HkOHR8B2YY7grp398dSowHRbxEv+cpsaC5HChCfNnFl+y5YtplCbxbAMKDp16mQ6hXlyUOEMLJwpT5yJnp2jWLjNmoz0Jq0TERHJrCb3+GLq88EYNSYSbJK44u1Y+PkBTz6h4KKgacSiAGjEQkRERCRnPvo4Fk+Pi0r+ftCAADw6MFCHtQCpxkJExMPZYhKxq8m7ZuG6KxZv33bbbWbhuohIYdG2tT+eeToo+ft5C2KweIn+ThUkpUKJiHg6hwOxv4cnr6fFLmciIoVRp47+iIt34IWXkiYAnTErGv5+wMNdAwp61zySAgsREQ9n9fNCrXfuT14XEXEn3R8OMC1oZ85OCi6mvBgNXz8LOj7oX9C75nEUWIiIeDiLlxUh9csV9G6IiGTbI30CEBPjwMJXk1KhJk6Kgr+fBa1b+emo5iPVWIiIiIiI23vs0QD07O6fnNX59DOR+PyLC7PpSb5QYCEi4uEciXb8u/aYWbguIuKOOI/F8CcD0blT0igFW9GOfCoS67+NL+hd8xgKLEREPJw93obDQ9abhesiIu4cXIwZHYR2bZOCi8RE4MnhEfh+k4KL/KAaCxERD2exWhDaqFzyuiur1Yp69eolr4uIFHZWqwXjnwky3aI+XRuPhATg8aERWDA3FI0a+hT07hVpmiCvAGiCPM/2448/onv37hg8eDAee+yxgt4dERGRIikx0YFhIyPx1ddJoxUBAcDihaGoe4OCi7yiy09SqE/Aq1Wrhjlz5hT0roiIiIib8fa24KUXgnHn7UmBBOf47D8oAvv2p54IVHKPAgsRERERKZJ8fSyYMS0EN9+UFFxERjrwyIBwHDqs4CIvKLAQEfFw9thE/NzqA7Nw3VVMTAyaNm1qFq6LiLgbPz8LZs8IQf16SaXF58870LdfOI79qmYVuU2BhRRKTH9iHQK98sorJiXKufzxxx9m++jRo833J06cwJIlS9CiRQvUrl3bbHe93Xn/tM/P25hulda2bdswYMAANG7c2Dxfs2bNMGPGjCydVPG5u3XrhtOnT2PkyJG49dZbUb169Yteb8+ePejVqxduvPFG1K9fH48++mi6+0vbt29Hv3790KhRI1x//fVo3rw5Zs+erZM9yTGH3YHoA2fNwvW0zp07ZxYREXcVGGjBvDkhqHN9UnDx71kH+jxyHr+fUHCRm9QVSgolnjw/8MAD+PDDD806F6fQ0NBU933uueewe/du3Hnnnbj77rtRsmTJbL/uW2+9hYkTJ5rX4HOVKFECe/fuxYIFC0xQ8MYbb8DX1zdTz8UTsU6dOiEsLMwEPXFxcQgODkZkZGRyULF48WITwDz00EPYv38/vvrqKxw6dAhr1qyBn1/KbKHr1q3DsGHDzGvfd9995j1u2rQJc+fOxffff48333wz1f1FssLq54XqS+9LXhcRKYqCg61YMC8EvfuG48BBG/4+40DvR8LxxtJQXHmF/vblBgUWUijxZJucgcWluicdPHjQ3O/KK6/M0WseOXIEzz//vBltWLZsGYoXL55826JFizBt2jQsX74cvXv3ztTzMUBo164dJk2aBC+vlD9YzlGLDRs2mJEQBh1OHN1YvXq1CTBatmxptjEQGTdunHmOd955x4x80JNPPmmCjbVr15oAhaMdItlh8bKi2G1X6eCJSJEXFmo1naF69gnHkaM2/PWXPSm4WBKGMmWUyJNTOoJujuk5GS3x8fGZvi+vpmf3vrGxseneL7/06dMnx0EF8aQ9MTHRnMS7BhXUt29fM3rBkYTM8vHxwYgRI1IFFa4aNmyYKqig9u3bJ49mODHIiIiIMLc5gwrnnAJ8fm9vbxNYiYiIyOUVL27F4kWhqFQx6TT4xAk7+vQPx7//2nX4ckgjFm7u9ttvz/A25vXPmjUr+ft7773XBAHp4QRYvCrv1KpVqwxzqmvWrGlSgpw6dOiAv/7666L7/fTTT8gPderUyZXnYToVbdy4EZs3b77odp7A//rrr5l+vvLly5tgJCO1atW6aFu5ckmTlIWHhydv++WXX8xX13QwJwZUfJ3ffvvNjGww1UokqxyJdpzbmFTbU+z28rB465qTiBRtpUtZ8dqroejRKxx/nrTj2DEb+g4Ix9LFoSgWpr+B2aXAQtxeTmoqXJ0/f958ZT1FbihVqtQlb08vCHCObtjtKVdNnDUZGT1fmTJlTGARFRWlwEKyxR5vw8F+X5j1hrt7wEuBhYh4gCvKeWEJg4ve4Th12o5Dh2zoNzAcry0MRUiIgovsUGDh5nh1PSNpU3C+/PLLDO/LtBpXn3zySabvu2rVKjgcF3eSyS8Wi+WS2222izs+MLUooxN9dl/KjSv/Ge1XVjn35Z9//kn39jNnzpivQUFBufJ64nksVguCri+VvJ72952jlM51EZGipHx5L7y2KBQ9+pzHP/84sG+fDQMHR2Dh/FAEBebO/3FPosDCzQVwfvoCvq+/vz/ygjMwSi8wyAx2YyK2fK1UqVKq25zpRWlTqvbt22dSophGVljUqFHDfN26detFNRlMQWO73QoVKmi0QrLN6u+N6z9om+5t7DbmmvooIlLUVK7sZUYpevQJx7lzDuzclYjBj4dj/iuh8PdXcJEVuvwkhZYzMDh16lS2Hs+5HihtYfNnn31mTtLT6tKli6mjYPvakydPXnQ76x7YEja/cWKykJAQfPDBBzh8+HDydo4Svfzyy6bgnK15RUREJHuuvdYbixeEIjQkKZDYui0RQ56MQHx8wWVkuCONWEihVaVKFVM/8Omnn5r5G8qWLWvSizjxHE+0L6dJkyaoWLGiOSHnlX1e+T927Bi2bNli5rxgu1dXVatWxbPPPovx48ebyed4H44EsHaBk9YxGOEJPOe5yE9MhWKww9ayHTt2NPNYsCj8hx9+MCMsHGlh1yoRERHJvho1vLFwXgj6DohAVJQD329KwPCREZj2Ugh8fDRykRkasZBCi6lQnHW7bt26ps0rZ5lmlytnkXVmUrSWLl1qrvj//PPPpp0sW+VyLgrnaEZaPHHn/fiYXbt2mRSQzz//HP/99x969uyJHj16oCAwmOC+NGjQwNTKcJ4NBjyDBg3C66+/rsnxJEfssYnY2/Fjs3DdFTvJsUscl4y6yomIFBV16vhg/ishCLiQ5f31Nwl4amwkbDaNXGSGxVGQVbceaseOHahfv74pEmabVxGRgmSLTsC2G15P6QoV6JN8G+ekcba1ZrOIrNRfiYi4q81b4jHoMaZCJX3fprUfJk0IgjVNgwtJTSMWIiIezurrharzmpqF6yIinu7mm3wxc1oIvC8UDaz+OA5TXogu0C6Y7kCBhYiIh+OEeCXurWwWTY4nIpLkzjt88fILwXB273/rnVjMnR+jw1MUirdXr15tUof27t2LQ4cOISEhAVOmTEG7du0u+1i242zdujWio6PRqVOni4pv2XqUefQshuV9OccBC4U5/D9w4ECznhYLiNPrLERXXXUV1q9fn4N3KyIiIiIF7d6mfnhuAjBmbNJktfMXxiA01ILuDyst1K0DCxbt/vnnnyhevLjpFMT1zOAMxqNHj77kfdgJiHMXsLtOy5Yt4ePjY4p93377bdOadMWKFbjmmmvSfezgwYMv2paZjkUiIoWFw2ZH+Lakts6hDcvB4qXBbBERpzat/BAebsfUF6PN9y+8FG2Ci7at82YeL3fmNoHFpEmTzCRnHA1YtGgRpk2blqnHsXsOu/uMGDHCjHCkh91OXnrppYsmUXO+zgsvvGDW0/PYY49l492IiBQe9jgbfum21qV4W4GFiIirbl0DEB7uwLwFSalQz4yPQkiwFU3u8dWBcuE2/z1uueUWE1RkxdGjRzFz5kz069cvefbi9DCtKW1QQX369DEtS7dt25atfRYRcQsWCwKuLWYWrqe+yWLmlOHCdRERTzVoQAAe7pI0SmGzAcNGRmDLjwkFvVuFituMWGSVzWYzKVAMGFgnsXPnziw/B/+JcibmS/0z/eSTT0xaFgMQBi8NGzaE1eo28ZqICLwCvHHDugfTPRL82/buu+/qKImIx+P54KgRgSYt6uM18UhIAAYPCceSV0NR5/qUNt2erMgGFgsXLsT+/fuxcuVKM2tzdrC+IjIy0szCnJHhw4en+r5y5cp4+eWXM5yATURERETcE+exmDg+GBGREfjm2wTExAADHo3AG0tCce21Rfa0OtOK5KX1AwcOYN68eSaVqXbt2tl6jr/++gvPP/+8uVo3ZMiQi25v0qSJCV6+++47U/i9du1adO/e3XSV6t27N06ePJkL70REREREChMfHwumvRiCRg2TAonz5x14ZEA4/vjDBk9X5AKL+Ph4jBo1ChUrVky3Y1Nm/Pfff6Yu499//zWtaZlbnFbPnj1x1113mVa0DD7YNerpp59G//79ER4ejiVLluTCuxERyXv22ET80mOtWbjuKjY2Fh07djQL10VEBPDzs+CVWaGoVStpkou/zzjQd0A4zvxj9+jDU+QCC3Zv4jwX7ACVnRQoBhUMGg4fPozx48ejTZs2WXr8Qw89ZL7u2LEjy68tIlIQHHYHzv9w0ixcT3Wbw4Fjx46ZRTPOioikCAqyYOHcUFSpkhRcnDhhR78B4Tgf7rnBRZFLBmNdBeeu4NW19LDmggtTmZgulV5QwVSqZ555JjlIyIpixYqZ4h5Oxici4g6svl649uW7ktdFRCRzihe34tUFIejWMxwnT9px6LANgwZH4NUFoQgM9LxOekUusLj11lvNJHppnTlzBhs2bDBpTfXq1UPNmjUzDCrGjRuHrl27Zuv1ObEer+pltTWuiEhBsXhbUarNtfoBiIhkQ7myXli8IBTdep7Hv2cd2LU7EUOejMDc2SHw9fWs4KLIBRYZBQQ//vijCSzYDpZ1E67OnTuHXr16maCCdRIPP/zwJV+DBdqcXZujE65Onz6NCRMmJE+6JyIiIiJFX6VKXli0IBQ9+4QjIsKBHzYnYPTTkXhpajC8vDwnuHCbwGLVqlXYvn27WWcNhXPb1q1bzXr9+vXRoUOHbD03Z8/+5ZdfzGjG+fPnMWfOnIvu06NHD4SGhpp1TpjH+osGDRqgfPnyZvsff/xhAhemQDGoyGpthoi7Wb9+PTZt2oR9+/aZoDwmJsY0TMjObPT8vVuwYAG++uor05EtODgYjRo1Ms913XXXpTuppfN3Py2OFnLfJPMcNjui9v1r1oNqlYTFq8iV34mI5Lnq1bwxb06I6RDFXheffxGP4OAoTHgmyGMmGHWbwIJBxYcffphqGwukXYuksxtYcII7YnHiK6+8ku59HnjggeTAgmlUnNuCJ1R79uwxwQRHMJhi1b59e7Ro0SJb+yHiTpYuXWpO7hkElClTBsePH8/W8zANkfVMv/32G2688UZT/8TUxc8//9y0c3799ddxww03pPvY9Dq/8XdRssYeZ8Pe9qvNesPdPeAVqMBCRCQ76t3og5nTQzD48QgkJgLvfxCHsFALhg0N8ogD6jaBxdSpU82SXY0bN8bBgwfTvS2rVzerV6+OF198Mdv7IlIUcH6XUqVKmdntOY/Lk08+ma3n4QghgwqmI44ePTp5O1MSmdo4ZswYM8N9ejPaZ2d0RNJhscDvquDk9dQ3WXDFFVckr4uIyKXdfqsvpj4fjBGjI+FwAEuWxSI01IpH+gQU+UOny1JSqOckefPNN81Eh3feeaeZ7PDmm282V6nZ/SutDz74ANWqVTNfGSzyKjivgN9zzz3J92HK2hNPPGHSbHgbT16Z2saTWz6WtThOXOc23saRMabf8DE33XSTSYVz9vT/9ttv0alTJ9StWxe33HKLCToTeZnCRUREhGmFzNe77bbbzHvh15EjR+L333+/6Ar+HXfcYV4r7SjApW7Lb0wF5EzzOT3Z/Prrr03QkDZI4Hu8++67ceTIkQzTniR3eAV448ZvHzIL111xnh4Gdly4LiIil3dfcz88MzZllGLm7Gi8u6rozwWkwEIKLebdT5482QQYDCzYtYsBAWtZGDSwA1d6PvvsM3OSWrJkSXTp0gW33357cnE9H7du3TrUqVPHBArsIMYr5Zw9PSO8ja/NFBs+/sorr8Tbb7+NsWPHmiv1jz/+uNnG4IL3ee2110y9gKujR49i9uzZ8PPzw7333mtmaWdwsWbNGpPC50zHI+7TCy+8YAKXYcOGISEhIfk2Nhfg+2A7ZI4UFAX//POPec9BQRcPE7OGibZs2ZLuY3myy2O9bNkyEwiy1bSIiEhh0PFBfwwdEpj8/cTno7DuszgUZW6TCiXps0UnnXRaA7yTrxzbE2xwJNhNC0nXnvTJ9/X3hsWa5r5eFlj9vLN335hEzqIFq59XctGnIzHp9XMiLCzMjAZwdnNXnLyQ85TMmDHD5PmntXHjRnNyz9EDVy+//LLJ3R86dCgGDBiQvP29994zJ+wZ4fPNnTsXTZs2Nd/zRJ+1NAwKvv/+eyxfvtwEKsSAplmzZmakhbOw+/j4mO2cmZ33TdtJjCfMDGzmz5+PSZMmJW/nyEzfvn3NKMfMmTMxYsQIrFixwlzdv//++03NT15gEJediSVzgkEFZ7mPioq6KLjgCBMxVSo9w4cPT/U9R1D4c77++uvzcI9FREQyp2/vAJw/bzfpUEyLYqeo4GALbr8tf//X5heNWLi5bTe8bpbEsynDa3+9+rPZ9tv4H1Ldd/tNK8z2uJORydtOL//FbDv61MZU991510qzPebIueRtZz44bLYdHpK6JuXn+94z251dZejfT4/l+L3xBDdtUEHsEsSaGaYwuV7Nd2Lxb9qggifMHMngKEbv3r1T3cYg4eqrr85wP/hazqCCGCz873//M/OVMFXHGVQQC5nvuusu08L41KlTydvTa09MTKu69tpr8cMPqX9WxJEQniAvWbLEBCpMsWLHI2dL48xiyhRrF3hMmF7EUReOuPBEPu3IDNPE8htHlDjSkLZxAveHgaUzlSztz3jhwoWmuJv348gRR4HYCpo/35MnT+bre3B39rhEHBzwhVm47iouLs4cWy5cFxGRrHnyiUA82N7PrDNT+olhEdi+4+Lzl6JAIxZSqLEN8OLFi01XMKbMpA0kWHPAjkSuXE/0ndjxi8EF04/SXpHnSA9PuH/99dd096FGjRoXbXO+Znq3lS5d2nz9+++/UaFCheTtTNVhhyOmcHG/XeswnCMbrrht+vTppnUxRzO8vLzM1XgGL5n1008/mRoVBlTsVsYT+M2bN5saEQYqTDFjuhFbOHNkhqMhBVEEztdmALVr1y5Tq8Jjx65QHOlh04W0dRxMTXPF+3HUicdm3rx55rmYqiaZ47A58N/Xvyevu+JnxlnTpFQzEZGss1gseObpIDO/BVvQskTz0ccjsHRxKGpUL1qn4kXr3XggtoZ0pkI5XfFIHZTrWfuiVKT6W7ompzc5lX24Bsp0qmbSm1zd+G2ni+5but11KNXqmovuW2fdg8mpUE4lW1bJ8XtjwTTnD3HOqM40l8DAQPMLyvkOOHcCg4W0eBKdVmRkZIa3EbsbZSS9E3me5Gd0m7d30jFzDRxY18EULO4/i7Y58hAQEGDeC9sou9ZYuGJgwi5kPBa1atUyLY2zgqlEDCwGDhyYKnhhwMF5YDgPBQvdq1atiilTphTI/CvlypXD+++/b2pQOALBFs7cxhEbBj08bhn93NLiaAwDC9c21HJ5Fh8rrp50W/K6iIjkLi8vC6ZODkZkZAQ2/ZBggoz+A8PxxtIwVK6ccv7k7hRYuDmvwIuvdFt9vAAu+XXfNF1kKKf1FcSiXAYOrC1gByJXvLKdkfS6FDkDAObyp4ejIXmJaT4s3GbHKgZIrj799NMMH8caEp4kM42KIx08FhnNLp+e++67z7xuWjyeaY9pQWLK2/PPP3/RdudklRxpygweJ/78ObeMZB5/t8t2qq5DJiKSh3x9LJg5LQSPDAzHrl2J+PesA30HhGP566EoV7ZoBBe6NCWFFtuw8kQx7QkwZ3hOr93spXBWdaZAcVLDtKMcrJW4VKCSW++F6Tppgwqm/DgLlNPie2QqFOs/2P2IV++ZvsTi9cxKL6hwFzabzQRdHAFiQXxmMPjiz5MjQiIiIoVNYKDFzM5dtWpSIPHXX3Y80j8C//1XNLoaKrCQQosnh2w563oizZNNtmI9e/Zslp6LQQULrjkywdakrj766CNTg5GX2I6WRdSuIyMshGWtQ3oF6Lzi7pxwjsEFazqmTZtm0qu43R2LaFmAzba7DKZc8f075wRxYi4/f86se+HcH65F/CzQZnF8WmzD6yxsb9WqVZ69j6LIYXcg+tB/ZuG6iIjknbBQKxbND0XFikmn4cd+taH/oHBERrp/cKFUKCm0eELJFq2ci4IpPQwOOFEaTyA5n0VWJ03jnBAsXOYJOjtK1axZ05y4fvPNN6YzEQuI05vdOTdwzoznnnsObdu2RfPmzU2AwE5QvLrOGgrWi7hiWhD3bdSoUWY/iUXNjz76KGbNmmVGLsaNG4eCxDoXLuQcdeH3znoRjhL169cv+f5ffvklnnrqKdMqd+rUqcnbmZ7WsmVLU0fDURkGGvy5M9hjhy3+3FzxZ8eAjCNZvH9oaKh5fc5vwoCMQUVB1Iq4M3tsIn5u+X5y3VZ6qZAiIpJ7SpeyYvGCUDzc4zz+PuPAvv02DB4SgQVzQ+Hvn7OJZwuSRiyk0GIrVxb0soD5448/NvNG8GSV805kJ9XliiuuwDvvvGNO7Hfu3Gk6NPGklh2EnJPNZaXjUlawLoJX05na9e6775oT8IYNG2LlypXmxNgVuyHxPfJEm3NcuOL8G3wc585gQFTQHbtYeM6FJ/vEAMm5jYFaZvCYs30sU7/4vljIzTlM2AmL83uk7eLFQIs/QwaYLIpnHQrnA2FhO+c2YeesnM4G7om8i/ubJT383KbXLllERLLvqqu88OrCUBQrlvQ/a9tPiRg2MgIJCe47cmxx8JKp5CsW49avX9+0UM1qlx/JG507dzZ1FuyWlN4M0CIiIiJ5Yc/eRPR+5DycfUdatfTF5EnBsF6YoNidaMRCPEra/H5avXq1CfY4gZyCChEREclP19f2xiuzQuEcoP/k03hMfTHapEu7G9VYiEdh/j0nteNs16ynYDoPazUYUIwcObKgd09EREQ8UONGPpj2YoiZldtmA1a8HYuwMAseHRgId6IRC/EonECNdRXsBMU5IVggzdmmOVlctWrVCnr3RAqEPS4Rh5/8xixcd8UOZCzC5+KO3chERNzFPXf74rkJKbWe8xbE4M0VMXAnGrEQj8JZnLmISAqHzYF/Pzlq1qtcmIHbtfWvcyZzrouISN5p08oP4eF2kwpF/BoSYkHb1uk31yhsFFiIiHg4i48VlcbclLwuIiIFp1vXAISHO8yIBT0zPgohwVY0uSd1l8TCSP9BREQ8nNXHC1f0qm0WrouISMEaNCAAD3dJGqVgzQXb0G758eIJdQsbBRYiIiIiIoWIxWLBqBGBaH1/0ihFQgIwdFgEYmMLd6coBRYiIh7OYXcg9o8Is3BdREQKntVqwcTxwbj7Lh/zfUysA1FRhftvtGosREQ8nD02EbvuXmnWG+7uAa/ApH9iIiJSsHx8LJj+cgi++CIe5ctbUbJk4R4TUGAhIiKwBmT878Df3z26kYiIFEW+Phbc39IP7kCBhYiIh+MIRaOfe6Z7W0BAAL7//vt83ycREXE/hXs8RURERERE3IICCxERERERyTEFFiIiHs4eb8OxMRvNwnVX8fHxGDJkiFm4LiIikhHVWIiIeDhHoh1/rzpo1iuNvQnwTZkkz2azYdOmTcnrIiIiGVFgISLi4Sw+VlQYWj95XUREJDsUWIiIeDirjxeuGnRjQe+GiIi4OV2aEhERERGRHNOIhYiIh3M4HEg8G2vWvUv4w2KxFPQuiYiIG9KIhYiIh7PHJGL7TSvMwnUREZHs0IhFAYiJiTFff/nll4J4eRGRVGwxiTgYe9yse+3cCa+AlH8NsbGxiI6ONus7d+6Ev7+/jp6IiAeqXr06AgMDL3kfi4Nj4JKvVqxYgYcfflhHXURERETcwvbt21GvXr1L3keBRQH4559/8Pnnn6Ny5coICAgoiF0QEREREck0jViIiIiIiEi+UPG2iIiIiIjkmAILERERERHJMXWFckM///wz5syZYzq0JCYmomrVqujZsydatGhR0LsmhdDq1atNwdXevXtx6NAhJCQkYMqUKWjXrl1B75oUUqdPn8a6devw3Xff4dixY6YuLCwszBTt9e3bFzfccENB76IUQnFxcZg+fbr5W3P8+HGcP38eoaGhqFChAjp06IDWrVvDx8enoHdT3MCiRYswbdo0s75y5UrUrVu3oHdJMkmBhZvZsmWL+cfu6+uLli1bIigoCF988QWGDh2KU6dOoXfv3gW9i1LIzJo1C3/++SeKFy+OMmXKmHWRS3nzzTfx6quvomLFirj11ltRokQJc6L41VdfmYX/8HUhQ9KKiorC22+/jTp16uCuu+4ynxsGFxs3bsSYMWOwdu1a87myWpUsIRnjBTBePGVbU2era3Ef6grlRjg6cd9995kA4t1330WNGjXM9oiICDz44IPmhJHdpq666qqC3lUpRH744QdUqlTJfC6cV4E0YiGXwosVxYoVQ6NGjVJt/+mnn8zoKP/hf//99+YCh4iT3W43/6fSfi64rVevXti6dSsWLlxogg6R9HBEvVOnTvD29jb/tz7++GONWLgZXTZws9GK33//Hffff39yUEEhISEYMGCA+YX88MMPC3QfpfC55ZZbFGxKljRr1uyioIIaNGiAxo0bm6vQBw8e1FGVVDgSkV6wyZPEe++916xz5EskIwsWLMDhw4cxefJkeHl56UC5IQUWboRXe+i222676Dbntm3btuX7fomI5+BJoutXkcyMZDAdilgTKJKeffv2mcBi8ODBuPbaa3WQ3JT+M7iR3377zXzl8GBapUuXNukJuhokInnl5MmTJrWOf290gigZiY+PNylPDocD586dw+bNm00TADaMuPnmm3XgJN3PzKhRo8wEbKwjFfelwMKNREZGJqc+pSc4ONjUW4iI5DamWo4cOdKcAAwfPlxpCnLJz8orr7yS/L3FYjGNRYYNG6ajJhk2GeHF0w8++EB/W9ycAgsREblsKsvo0aNNqmXHjh3Rtm1bHTHJELsVsgaHn5u///4b69evx4wZM7Br1y7TFYoXwUSc2Dp/yZIlJgVKI6HuTzUWbsT5xzijUQmOaGQ0miEikh08OWSr0DVr1ph5CCZMmKADKZku5i5Xrhy6dOmCiRMnYseOHZg/f76OnqTqGMaLFtWqVUO/fv10ZIoAjVi4kcqVK5uvrKOoXbt2qtvOnDlj+j2zf7iISG4FFU899RQ++ugj041u6tSpmoNAssXZYMTZhESEeN7irB9Ne17jxPazNHfuXDRt2lQHrpBTYOFGGjZsaAri2D+ek+O54jbnfUREcjOo4GR4L774onKfJduYEkXqJiau2J6Y83Clh/PmMOi45557zGSLmqPLPSiwcCPsplGhQgWTktC9e/dUE+SxRZuPj49yn0Uk19KfGFQ0b94cL730koIKuawjR46Yk7+AgIBU22NiYsyknHTnnXfqSEoyf39/PP/88+keEaZIMbDo378/6tatq6PmJhRYuBFe6Zk0aZJpxda1a1czasEiOc6Sy1m32aqtfPnyBb2bUsisWrUK27dvN+uHDh1K3uZMSahfvz46dOhQoPsohQtTDjjZJltYMwUzvbx4piS4TtQpsm7dOixdutT8TWGAwbrA06dP47vvvjNtZznBImduF5GiS4GFm7npppvw1ltvYfbs2Vi7dq0pfGIXBbZ/ZLqCSFoMKtLOyM4iSi5OCizEFS9UOPOfORqaHp44KrAQV3fddZdJeWKXH3aA4ueHwQULc3khrH379kqFEiniLA7OYCMiIiIiIpIDajcrIiIiIiI5psBCRERERERyTIGFiIiIiIjkmAILERERERHJMQUWIiIiIiKSYwosREREREQkxxRYiIiIiIhIjimwEBERERGRHFNgISIiIiIiOabAQkREREREckyBhYiIiIiI5Jh3zp9CRESk4J05cwbTp0/Hxo0bcfbsWQQEBOCmm27CmDFjcNVVVxX07omIFHkWh8PhKOidEBERyYlNmzbhiSeeQExMDBo1aoTQ0FBs27YN//zzDypUqICPP/4YgYGBOsgiInlIIxYiIuLW9u7diwEDBuCKK67AqlWrULlyZbM9MjISHTt2xNGjR/Hpp5+iQ4cOBb2rIiJFmmosRETEbdntdowfPx42m82kQTmDCgoODkabNm3M+o4dOwpwL0VEPIMCCxERcVvbt2/Hnj170Lx5c9SuXfui2ytVqmS+xsbGFsDeiYh4FgUWIiLittavX2++Nm3aNN3bz58/b76WKlUqX/dLRMQTKbAQERG39eOPP5qv9erVS/f2ffv2ma81a9bM1/0SEfFECixERMQtJSQk4NChQ2a9ePHi6dZfcETD29sbt912WwHsoYiIZ1FgISIibunw4cMmuKC//vrrotuXLVtm5rb43//+h9KlSxfAHoqIeBYFFiIi4pacaU60aNEiuE7L9PXXX2PWrFkICwvD8OHDC2gPRUQ8i+axEBERt7R//37ztWvXrlixYoXpDlW1alUcP37crHOSvHnz5uHKK68s6F0VEfEIGrEQERG3Diw4Od7UqVNNTcUXX3yBU6dO4cEHH8Tq1avRoEGDgt5NERGPYXG4jh2LiIi4AU6IV79+fTMJ3vfff1/QuyMiIhqxEBERd3Ts2DHExMSojayISCGiVCgREXE7mp9CRKTwUWAhIiJuW19Rq1atgt4VERG5QDUWIiIiIiKSYxqxEBERERGRHFNgISIiIiIiOabAQkREREREckyBhYiIiIiI5JgCCxERERERyTEFFiIiIiIikmMKLEREREREJMcUWIiIiIiISI4psBARERERkRxTYCEiIiIiIjmmwEJERERERJBT/wfumc7gTgM29gAAAABJRU5ErkJggg==", + "text/plain": [ + "
" ] + }, + "metadata": {}, + "output_type": "display_data" } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv (3.12.11)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" - } + ], + "source": [ + "from numpyro.infer import Predictive\n", + "\n", + "from dynestyx.inference.filters import (\n", + " Filter, ContinuousTimeEKFConfig\n", + ")\n", + "\n", + "def marginal_loglik_at_rho(rho_value, *, obs_times, obs_values):\n", + " with Filter():\n", + " predictive = Predictive(\n", + " continuous_time_lti_gaussian_model,\n", + " params={\"rho\": jnp.array(rho_value)},\n", + " num_samples=1,\n", + " exclude_deterministic=False,\n", + " )\n", + " out = predictive(jr.PRNGKey(123), obs_times=obs_times, obs_values=obs_values)\n", + " # Keep this robust to scalar vs singleton-shaped return.\n", + " return jnp.ravel(out[\"f_marginal_loglik\"])[0]\n", + "\n", + "\n", + "rho_grid = jnp.linspace(0.1, 4.5, 20)\n", + "loglik_grid = jnp.array(\n", + " [marginal_loglik_at_rho(r, obs_times=times, obs_values=obs_values) for r in rho_grid]\n", + ")\n", + "\n", + "rho_hat = rho_grid[jnp.argmax(loglik_grid)]\n", + "\n", + "plt.figure(figsize=(8, 4))\n", + "plt.plot(rho_grid, loglik_grid, lw=2, label=\"marginal log-likelihood\")\n", + "plt.axvline(2.0, ls=\"--\", color=\"black\", alpha=0.8, label=\"true rho\")\n", + "plt.axvline(rho_hat, ls=\":\", color=\"C3\", alpha=0.9, label=f\"argmax ~ {float(rho_hat):.2f}\")\n", + "plt.xlabel(r\"$\\rho$\")\n", + "plt.ylabel(r\"$\\log p(y_{1:T}\\mid\\rho)$\")\n", + "plt.title(\"Likelihood sweep\")\n", + "plt.legend()\n", + "plt.tight_layout()\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv (3.12.11)", + "language": "python", + "name": "python3" }, - "nbformat": 4, - "nbformat_minor": 5 + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 } diff --git a/docs/tutorials/sde_non_gaussian_observations.ipynb b/docs/tutorials/sde_non_gaussian_observations.ipynb index 1b2d0263..50814299 100644 --- a/docs/tutorials/sde_non_gaussian_observations.ipynb +++ b/docs/tutorials/sde_non_gaussian_observations.ipynb @@ -1,451 +1,451 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Inference in SDE-Driven State Space Models with Non-Gaussian Observations\n", - "\n", - "One challenging but common problem in practice is state space models with non-Gaussian observations. In this tutorial, we show how to write these and use them in `dynestyx` for a state-space model with a Poisson observation process. We'll use a differentiable particle filter (DPF) combined with stochastic variational inference (SVI) to infer model parameters." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## The System\n", - "\n", - "We'll model a system with continuous-time stochastic dynamics and discrete-time count observations. The latent state follows a one-dimensional Ornstein-Uhlenbeck (OU) process:\n", - "\n", - "$$\\mathrm{d}x_t = \\kappa(\\mu - x_t) \\, \\mathrm{d}t + \\sigma \\, \\mathrm{d}W_t,$$\n", - "\n", - "where $\\kappa$ is the mean-reversion rate, $\\mu$ is the long-term mean, and $\\sigma$ controls the diffusion strength.\n", - "\n", - "At discrete observation times $t_k$, we observe Poisson counts that depend on the latent state via an exponential link function:\n", - "\n", - "$$y_{t_k} \\mid x_{t_k} \\sim \\text{Poisson}(\\Delta t \\cdot \\exp(x_{t_k} + b)),$$\n", - "\n", - "where $b$ is a bias parameter and $\\Delta t$ is the observation time step. We will place a uniform prior on $b$ and infer it from data using stochastic variational inference with a differentiable particle filter." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Specifying the Full Model in `dynestyx`\n", - "\n", - "Now we'll write the complete model as a `numpyro` program. We'll place a uniform prior on the bias parameter $b$ and use fixed values for the dynamics parameters. To specify the Poisson-process observation model, we can simply pass in the correct distribution as a callable -- dynestyx will turn it into the appropriate equinox module under the hood." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import jax.numpy as jnp\n", - "import jax.random as jr\n", - "import numpyro\n", - "import numpyro.distributions as dist\n", - "from dynestyx import DynamicalModel, ContinuousTimeStateEvolution, ObservationModel\n", - "import dynestyx as dsx\n", - "import equinox as eqx\n", - "\n", - "# Fixed dynamics parameters\n", - "kappa = 0.8 # mean-reversion rate\n", - "mu = 0.0 # long-term mean\n", - "sigma = 0.4 # diffusion strength\n", - "\n", - "# Observation parameters\n", - "dt = 0.1 # observation time step\n", - "\n", - "def ou_poisson_model(bias=None, obs_times=None, obs_values=None, predict_times=None):\n", - " \"\"\"\n", - " Ornstein-Uhlenbeck process with Poisson observations.\n", - " \n", - " The bias parameter controls the mean count level and will be inferred.\n", - " \"\"\"\n", - " # Sample bias from uniform prior\n", - " bias = numpyro.sample(\"bias\", dist.Uniform(2.0, 10.0), obs=bias)\n", - " \n", - " # Define OU drift function\n", - " def drift(x, u, t):\n", - " return kappa * (mu - x)\n", - " \n", - " # Create the dynamical model\n", - " dynamics = DynamicalModel(\n", - " initial_condition=dist.MultivariateNormal(\n", - " loc=jnp.zeros(1), \n", - " covariance_matrix=0.5**2 * jnp.eye(1)\n", - " ),\n", - " state_evolution=ContinuousTimeStateEvolution(\n", - " drift=drift,\n", - " diffusion_coefficient=lambda x, u, t: sigma * jnp.eye(1),\n", - " ),\n", - " observation_model=lambda x, u, t: dist.Poisson(rate=dt * jnp.exp(x[0] + bias)),\n", - " )\n", - " \n", - " dsx.sample(\n", - " \"f\",\n", - " dynamics,\n", - " obs_times=obs_times,\n", - " obs_values=obs_values,\n", - " predict_times=predict_times,\n", - " )" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Generating Synthetic Data\n", - "\n", - "We'll generate synthetic data using the `SDESimulator`. We'll set the true bias to $b = \\log(50) \\approx 3.91$, which corresponds to a mean count rate of about 5 when the state is near zero." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from dynestyx import SDESimulator\n", - "from numpyro.infer import Predictive\n", - "\n", - "# Generate observations at regular intervals\n", - "T = 1000\n", - "obs_times = jnp.arange(start=0.0, stop=T * dt, step=dt)\n", - "\n", - "# Set random seed and true bias parameter\n", - "prng_key = jr.PRNGKey(0)\n", - "sde_solver_key, predictive_key = jr.split(prng_key, 2)\n", - "\n", - "true_bias = jnp.log(50.0) # approximately 3.91\n", - "\n", - "# Generate synthetic data\n", - "predictive_model = Predictive(ou_poisson_model, num_samples=1)\n", - "\n", - "with SDESimulator():\n", - " synthetic_samples = predictive_model(\n", - " predictive_key,\n", - " bias=true_bias,\n", - " predict_times=obs_times\n", - " )" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can visualize the latent state and the Poisson count observations:" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "\n", - "# f_* : (num_samples, n_sim, T, ...) under Predictive + SDESimulator\n", - "t = synthetic_samples[\"f_times\"][0, 0]\n", - "states = synthetic_samples[\"f_states\"][0, 0]\n", - "observations = synthetic_samples[\"f_observations\"][0, 0]\n", - "\n", - "# Compute expected count rate\n", - "expected_rate = dt * jnp.exp(states[:, 0] + true_bias)\n", - "\n", - "fig, axs = plt.subplots(2, 1, figsize=(10, 6), sharex=True)\n", - "\n", - "# Plot latent state\n", - "axs[0].plot(t, states[:, 0], color=\"C0\", label=\"Latent state $x(t)$\")\n", - "axs[0].set_ylabel(\"State\")\n", - "axs[0].legend(loc=\"upper right\")\n", - "sns.despine(ax=axs[0])\n", - "\n", - "# Plot observations and expected rate\n", - "axs[1].scatter(t, observations, s=5, color=\"C1\", alpha=0.6, label=\"Observed counts $y_k$\")\n", - "axs[1].plot(t, expected_rate, color=\"C2\", alpha=0.8, label=\"Expected rate $E[y_k | x_k]$\")\n", - "axs[1].set_ylabel(\"Count\")\n", - "axs[1].set_xlabel(\"Time\")\n", - "axs[1].legend(loc=\"upper right\")\n", - "sns.despine(ax=axs[1])\n", - "\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Bayesian Inference with Differentiable Particle Filters\n", - "\n", - "For non-Gaussian observations, the standard ensemble Kalman filter (EnKF) may not be appropriate since it assumes Gaussian observation distributions. Instead, we can use a **differentiable particle filter (DPF)** to compute the marginal likelihood. \n", - "\n", - "The DPF provides unbiased gradient estimates with respect to parameters, making it compatible with gradient-based inference methods like stochastic variational inference (SVI). While the DPF is more computationally expensive than the EnKF, it can handle arbitrary observation distributions.\n", - "\n", - "To perform inference, we'll:\n", - "1. Wrap all our inference code in a `Filter` context with the DPF\n", - "2. Use SVI with an automatic guide to infer the posterior distribution of the bias parameter" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 50/50 [21:51<00:00, 26.24s/it, init loss: 84395.2344, avg. loss [49-50]: 3331.3447] " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "True bias: 3.9120\n", - "Inferred bias: 4.3293\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "from numpyro.infer import SVI, Trace_ELBO\n", - "from numpyro.infer.autoguide import AutoDelta\n", - "from jax import random as jr\n", - "import optax\n", - "from dynestyx.inference.filters import Filter, ContinuousTimeDPFConfig\n", - "\n", - "# Extract observations from synthetic data\n", - "obs_values = synthetic_samples[\"f_observations\"][0, 0]\n", - "\n", - "# Use an AutoDelta guide (point estimate - similar to maximum likelihood)\n", - "# For a full posterior, you could use AutoNormal or AutoDiagonalNormal\n", - "guide = AutoDelta(ou_poisson_model)\n", - "\n", - "# Set up SVI with Adam optimizer\n", - "optimizer = optax.adam(learning_rate=0.05)\n", - "\n", - "with Filter(ContinuousTimeDPFConfig(n_particles=2_500)):\n", - " svi = SVI(ou_poisson_model, guide, optimizer, loss=Trace_ELBO(), obs_times=obs_times, obs_values=obs_values)\n", - "\n", - " # Run SVI optimization\n", - " svi_key = jr.PRNGKey(1)\n", - " num_steps = 50\n", - "\n", - " svi_result = svi.run(svi_key, num_steps)\n", - "params = svi_result.params\n", - "\n", - "print(f\"True bias: {true_bias:.4f}\")\n", - "print(f\"Inferred bias: {params['bias_auto_loc']:.4f}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can visualize the ELBO (evidence lower bound) during optimization to ensure convergence:" - ] - }, + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Inference in SDE-Driven State Space Models with Non-Gaussian Observations\n", + "\n", + "One challenging but common problem in practice is state space models with non-Gaussian observations. In this tutorial, we show how to write these and use them in `dynestyx` for a state-space model with a Poisson observation process. We'll use a differentiable particle filter (DPF) combined with stochastic variational inference (SVI) to infer model parameters." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## The System\n", + "\n", + "We'll model a system with continuous-time stochastic dynamics and discrete-time count observations. The latent state follows a one-dimensional Ornstein-Uhlenbeck (OU) process:\n", + "\n", + "$$\\mathrm{d}x_t = \\kappa(\\mu - x_t) \\, \\mathrm{d}t + \\sigma \\, \\mathrm{d}W_t,$$\n", + "\n", + "where $\\kappa$ is the mean-reversion rate, $\\mu$ is the long-term mean, and $\\sigma$ controls the diffusion strength.\n", + "\n", + "At discrete observation times $t_k$, we observe Poisson counts that depend on the latent state via an exponential link function:\n", + "\n", + "$$y_{t_k} \\mid x_{t_k} \\sim \\text{Poisson}(\\Delta t \\cdot \\exp(x_{t_k} + b)),$$\n", + "\n", + "where $b$ is a bias parameter and $\\Delta t$ is the observation time step. We will place a uniform prior on $b$ and infer it from data using stochastic variational inference with a differentiable particle filter." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Specifying the Full Model in `dynestyx`\n", + "\n", + "Now we'll write the complete model as a `numpyro` program. We'll place a uniform prior on the bias parameter $b$ and use fixed values for the dynamics parameters. To specify the Poisson-process observation model, we can simply pass in the correct distribution as a callable -- dynestyx will turn it into the appropriate equinox module under the hood." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import jax.numpy as jnp\n", + "import jax.random as jr\n", + "import numpyro\n", + "import numpyro.distributions as dist\n", + "from dynestyx import DynamicalModel, ContinuousTimeStateEvolution, ObservationModel\n", + "import dynestyx as dsx\n", + "import equinox as eqx\n", + "\n", + "# Fixed dynamics parameters\n", + "kappa = 0.8 # mean-reversion rate\n", + "mu = 0.0 # long-term mean\n", + "sigma = 0.4 # diffusion strength\n", + "\n", + "# Observation parameters\n", + "dt = 0.1 # observation time step\n", + "\n", + "def ou_poisson_model(bias=None, obs_times=None, obs_values=None, predict_times=None):\n", + " \"\"\"\n", + " Ornstein-Uhlenbeck process with Poisson observations.\n", + " \n", + " The bias parameter controls the mean count level and will be inferred.\n", + " \"\"\"\n", + " # Sample bias from uniform prior\n", + " bias = numpyro.sample(\"bias\", dist.Uniform(2.0, 10.0), obs=bias)\n", + " \n", + " # Define OU drift function\n", + " def drift(x, u, t):\n", + " return kappa * (mu - x)\n", + " \n", + " # Create the dynamical model\n", + " dynamics = DynamicalModel(\n", + " initial_condition=dist.MultivariateNormal(\n", + " loc=jnp.zeros(1), \n", + " covariance_matrix=0.5**2 * jnp.eye(1)\n", + " ),\n", + " state_evolution=ContinuousTimeStateEvolution(\n", + " drift=drift,\n", + " diffusion=dsx.FullDiffusion(sigma * jnp.eye(1)),\n", + " ),\n", + " observation_model=lambda x, u, t: dist.Poisson(rate=dt * jnp.exp(x[0] + bias)),\n", + " )\n", + " \n", + " dsx.sample(\n", + " \"f\",\n", + " dynamics,\n", + " obs_times=obs_times,\n", + " obs_values=obs_values,\n", + " predict_times=predict_times,\n", + " )" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Generating Synthetic Data\n", + "\n", + "We'll generate synthetic data using the `SDESimulator`. We'll set the true bias to $b = \\log(50) \\approx 3.91$, which corresponds to a mean count rate of about 5 when the state is near zero." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from dynestyx import SDESimulator\n", + "from numpyro.infer import Predictive\n", + "\n", + "# Generate observations at regular intervals\n", + "T = 1000\n", + "obs_times = jnp.arange(start=0.0, stop=T * dt, step=dt)\n", + "\n", + "# Set random seed and true bias parameter\n", + "prng_key = jr.PRNGKey(0)\n", + "sde_solver_key, predictive_key = jr.split(prng_key, 2)\n", + "\n", + "true_bias = jnp.log(50.0) # approximately 3.91\n", + "\n", + "# Generate synthetic data\n", + "predictive_model = Predictive(ou_poisson_model, num_samples=1)\n", + "\n", + "with SDESimulator():\n", + " synthetic_samples = predictive_model(\n", + " predictive_key,\n", + " bias=true_bias,\n", + " predict_times=obs_times\n", + " )" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can visualize the latent state and the Poisson count observations:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10, 4))\n", - "plt.plot(svi_result.losses)\n", - "plt.xlabel(\"Iteration\")\n", - "plt.ylabel(\"ELBO Loss\")\n", - "plt.title(\"SVI Optimization Progress\")\n", - "sns.despine()\n", - "plt.tight_layout()\n", - "plt.show()" + "data": { + "image/png": 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", + "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "\n", + "# f_* : (num_samples, n_sim, T, ...) under Predictive + SDESimulator\n", + "t = synthetic_samples[\"f_times\"][0, 0]\n", + "states = synthetic_samples[\"f_states\"][0, 0]\n", + "observations = synthetic_samples[\"f_observations\"][0, 0]\n", + "\n", + "# Compute expected count rate\n", + "expected_rate = dt * jnp.exp(states[:, 0] + true_bias)\n", + "\n", + "fig, axs = plt.subplots(2, 1, figsize=(10, 6), sharex=True)\n", + "\n", + "# Plot latent state\n", + "axs[0].plot(t, states[:, 0], color=\"C0\", label=\"Latent state $x(t)$\")\n", + "axs[0].set_ylabel(\"State\")\n", + "axs[0].legend(loc=\"upper right\")\n", + "sns.despine(ax=axs[0])\n", + "\n", + "# Plot observations and expected rate\n", + "axs[1].scatter(t, observations, s=5, color=\"C1\", alpha=0.6, label=\"Observed counts $y_k$\")\n", + "axs[1].plot(t, expected_rate, color=\"C2\", alpha=0.8, label=\"Expected rate $E[y_k | x_k]$\")\n", + "axs[1].set_ylabel(\"Count\")\n", + "axs[1].set_xlabel(\"Time\")\n", + "axs[1].legend(loc=\"upper right\")\n", + "sns.despine(ax=axs[1])\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Bayesian Inference with Differentiable Particle Filters\n", + "\n", + "For non-Gaussian observations, the standard ensemble Kalman filter (EnKF) may not be appropriate since it assumes Gaussian observation distributions. Instead, we can use a **differentiable particle filter (DPF)** to compute the marginal likelihood. \n", + "\n", + "The DPF provides unbiased gradient estimates with respect to parameters, making it compatible with gradient-based inference methods like stochastic variational inference (SVI). While the DPF is more computationally expensive than the EnKF, it can handle arbitrary observation distributions.\n", + "\n", + "To perform inference, we'll:\n", + "1. Wrap all our inference code in a `Filter` context with the DPF\n", + "2. Use SVI with an automatic guide to infer the posterior distribution of the bias parameter" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Full Posterior Inference\n", - "\n", - "The `AutoDelta` guide gives us a point estimate (similar to maximum likelihood). To get a full posterior distribution with uncertainty quantification, we can use `AutoNormal` or `AutoDiagonalNormal` instead:" - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 50/50 [21:51<00:00, 26.24s/it, init loss: 84395.2344, avg. loss [49-50]: 3331.3447] " + ] }, { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 50/50 [21:46<00:00, 26.13s/it, init loss: 4887.0552, avg. loss [49-50]: 2773.0498]\n" - ] - } - ], - "source": [ - "from numpyro.infer.autoguide import AutoDiagonalNormal\n", - "\n", - "# Use AutoDiagonalNormal for full posterior approximation\n", - "guide_normal = AutoDiagonalNormal(ou_poisson_model)\n", - "\n", - "# Set up SVI\n", - "optimizer_normal = optax.adam(learning_rate=0.05)\n", - "\n", - "with Filter(ContinuousTimeDPFConfig(n_particles=2_500)):\n", - " svi_normal = SVI(ou_poisson_model, guide_normal, optimizer_normal, loss=Trace_ELBO(), obs_times=obs_times, obs_values=obs_values)\n", - "\n", - " # Run SVI\n", - " svi_key_normal = jr.PRNGKey(2)\n", - " svi_result_normal = svi_normal.run(svi_key_normal, num_steps)\n", - "\n" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "True bias: 3.9120\n", + "Inferred bias: 4.3293\n" + ] }, { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Draw posterior samples from the guide using its learned parameters `svi_result_normal.params`." - ] - }, + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "from numpyro.infer import SVI, Trace_ELBO\n", + "from numpyro.infer.autoguide import AutoDelta\n", + "from jax import random as jr\n", + "import optax\n", + "from dynestyx.inference.filters import Filter, ContinuousTimeDPFConfig\n", + "\n", + "# Extract observations from synthetic data\n", + "obs_values = synthetic_samples[\"f_observations\"][0, 0]\n", + "\n", + "# Use an AutoDelta guide (point estimate - similar to maximum likelihood)\n", + "# For a full posterior, you could use AutoNormal or AutoDiagonalNormal\n", + "guide = AutoDelta(ou_poisson_model)\n", + "\n", + "# Set up SVI with Adam optimizer\n", + "optimizer = optax.adam(learning_rate=0.05)\n", + "\n", + "with Filter(ContinuousTimeDPFConfig(n_particles=2_500)):\n", + " svi = SVI(ou_poisson_model, guide, optimizer, loss=Trace_ELBO(), obs_times=obs_times, obs_values=obs_values)\n", + "\n", + " # Run SVI optimization\n", + " svi_key = jr.PRNGKey(1)\n", + " num_steps = 50\n", + "\n", + " svi_result = svi.run(svi_key, num_steps)\n", + "params = svi_result.params\n", + "\n", + "print(f\"True bias: {true_bias:.4f}\")\n", + "print(f\"Inferred bias: {params['bias_auto_loc']:.4f}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can visualize the ELBO (evidence lower bound) during optimization to ensure convergence:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "True bias: 3.9120\n", - "Posterior mean: 3.9546\n", - "Posterior std: 0.0833\n" - ] - } - ], - "source": [ - "# Get posterior samples\n", - "posterior_samples = guide_normal.sample_posterior(\n", - " jr.PRNGKey(3), \n", - " svi_result_normal.params, \n", - " sample_shape=(20,),\n", - " exclude_deterministic=True\n", - ")\n", - "\n", - "print(f\"True bias: {true_bias:.4f}\")\n", - "print(f\"Posterior mean: {posterior_samples['bias'].mean():.4f}\")\n", - "print(f\"Posterior std: {posterior_samples['bias'].std():.4f}\")" + "data": { + "image/png": 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", + "text/plain": [ + "
" ] - }, + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10, 4))\n", + "plt.plot(svi_result.losses)\n", + "plt.xlabel(\"Iteration\")\n", + "plt.ylabel(\"ELBO Loss\")\n", + "plt.title(\"SVI Optimization Progress\")\n", + "sns.despine()\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Full Posterior Inference\n", + "\n", + "The `AutoDelta` guide gives us a point estimate (similar to maximum likelihood). To get a full posterior distribution with uncertainty quantification, we can use `AutoNormal` or `AutoDiagonalNormal` instead:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's visualize the posterior distribution:" - ] - }, + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 50/50 [21:46<00:00, 26.13s/it, init loss: 4887.0552, avg. loss [49-50]: 2773.0498]\n" + ] + } + ], + "source": [ + "from numpyro.infer.autoguide import AutoDiagonalNormal\n", + "\n", + "# Use AutoDiagonalNormal for full posterior approximation\n", + "guide_normal = AutoDiagonalNormal(ou_poisson_model)\n", + "\n", + "# Set up SVI\n", + "optimizer_normal = optax.adam(learning_rate=0.05)\n", + "\n", + "with Filter(ContinuousTimeDPFConfig(n_particles=2_500)):\n", + " svi_normal = SVI(ou_poisson_model, guide_normal, optimizer_normal, loss=Trace_ELBO(), obs_times=obs_times, obs_values=obs_values)\n", + "\n", + " # Run SVI\n", + " svi_key_normal = jr.PRNGKey(2)\n", + " svi_result_normal = svi_normal.run(svi_key_normal, num_steps)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Draw posterior samples from the guide using its learned parameters `svi_result_normal.params`." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import arviz as az\n", - "\n", - "az.style.use(\"arviz-white\")\n", - "\n", - "az.plot_posterior(\n", - " posterior_samples[\"bias\"], \n", - " hdi_prob=0.95, \n", - " ref_val=float(true_bias)\n", - ")\n", - "\n", - "plt.show()" - ] - }, + "name": "stdout", + "output_type": "stream", + "text": [ + "True bias: 3.9120\n", + "Posterior mean: 3.9546\n", + "Posterior std: 0.0833\n" + ] + } + ], + "source": [ + "# Get posterior samples\n", + "posterior_samples = guide_normal.sample_posterior(\n", + " jr.PRNGKey(3), \n", + " svi_result_normal.params, \n", + " sample_shape=(20,),\n", + " exclude_deterministic=True\n", + ")\n", + "\n", + "print(f\"True bias: {true_bias:.4f}\")\n", + "print(f\"Posterior mean: {posterior_samples['bias'].mean():.4f}\")\n", + "print(f\"Posterior std: {posterior_samples['bias'].std():.4f}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's visualize the posterior distribution:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Summary\n", - "\n", - "In this tutorial, we demonstrated:\n", - "\n", - "1. **Writing custom observation models**: We created a `PoissonObservation` class that can be used with `dynestyx` by subclassing `ObservationModel` and returning a `numpyro` distribution.\n", - "\n", - "2. **Using differentiable particle filters**: For non-Gaussian observations, we used `Filter` with `filter_type=\"dpf\"` to compute the marginal likelihood needed for parameter inference.\n", - "\n", - "3. **Stochastic variational inference**: We used SVI with automatic guides (`AutoDelta` for point estimates and `AutoDiagonalNormal` for full posteriors) to efficiently infer the observation bias parameter.\n", - "\n", - "This workflow generalizes to other non-Gaussian observation models (e.g., binomial, negative binomial, von Mises) simply by changing the observation model class. The DPF enables gradient-based inference for these challenging problems where traditional methods like the EnKF may fail." + "data": { + "image/png": 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", + "text/plain": [ + "
" ] + }, + "metadata": {}, + "output_type": "display_data" } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv (3.12.11)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" - } + ], + "source": [ + "import arviz as az\n", + "\n", + "az.style.use(\"arviz-white\")\n", + "\n", + "az.plot_posterior(\n", + " posterior_samples[\"bias\"], \n", + " hdi_prob=0.95, \n", + " ref_val=float(true_bias)\n", + ")\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Summary\n", + "\n", + "In this tutorial, we demonstrated:\n", + "\n", + "1. **Writing custom observation models**: We created a `PoissonObservation` class that can be used with `dynestyx` by subclassing `ObservationModel` and returning a `numpyro` distribution.\n", + "\n", + "2. **Using differentiable particle filters**: For non-Gaussian observations, we used `Filter` with `filter_type=\"dpf\"` to compute the marginal likelihood needed for parameter inference.\n", + "\n", + "3. **Stochastic variational inference**: We used SVI with automatic guides (`AutoDelta` for point estimates and `AutoDiagonalNormal` for full posteriors) to efficiently infer the observation bias parameter.\n", + "\n", + "This workflow generalizes to other non-Gaussian observation models (e.g., binomial, negative binomial, von Mises) simply by changing the observation model class. The DPF enables gradient-based inference for these challenging problems where traditional methods like the EnKF may fail." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv (3.12.11)", + "language": "python", + "name": "python3" }, - "nbformat": 4, - "nbformat_minor": 2 + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } + }, + "nbformat": 4, + "nbformat_minor": 2 } diff --git a/dynestyx/__init__.py b/dynestyx/__init__.py index b5f21e51..e93bd086 100644 --- a/dynestyx/__init__.py +++ b/dynestyx/__init__.py @@ -9,9 +9,13 @@ from dynestyx.inference.filters import Filter from dynestyx.models import ( ContinuousTimeStateEvolution, + DeterministicContinuousTimeStateEvolution, + DiagonalDiffusion, + Diffusion, DiracIdentityObservation, DiscreteTimeStateEvolution, DynamicalModel, + FullDiffusion, GaussianObservation, GaussianStateEvolution, LinearGaussianObservation, @@ -19,6 +23,8 @@ LTI_continuous, LTI_discrete, ObservationModel, + ScalarDiffusion, + StochasticContinuousTimeStateEvolution, ) from dynestyx.simulators import ( DiscreteTimeSimulator, @@ -31,6 +37,12 @@ __all__ = [ "__version__", "ContinuousTimeStateEvolution", + "DeterministicContinuousTimeStateEvolution", + "Diffusion", + "FullDiffusion", + "DiagonalDiffusion", + "ScalarDiffusion", + "StochasticContinuousTimeStateEvolution", "DiscreteTimeStateEvolution", "DynamicalModel", "AffineDrift", diff --git a/dynestyx/discretizers.py b/dynestyx/discretizers.py index c14d1438..bd75c6d2 100644 --- a/dynestyx/discretizers.py +++ b/dynestyx/discretizers.py @@ -1,85 +1,35 @@ -import jax.numpy as jnp import numpyro.distributions as dist from effectful.ops.semantics import fwd from effectful.ops.syntax import ObjectInterpretation, implements from dynestyx.handlers import HandlesSelf, _sample_intp from dynestyx.models import ( - ContinuousTimeStateEvolution, DynamicalModel, GaussianStateEvolution, + StochasticContinuousTimeStateEvolution, ) -from dynestyx.models.checkers import _resolve_ctse_diffusion_metadata from dynestyx.solvers import euler_maruyama_loc_cov from dynestyx.types import FunctionOfTime -def _ensure_ctse_diffusion_metadata( - cte: ContinuousTimeStateEvolution, - *, - state_dim: int, - control_dim: int = 0, - t0=None, -) -> ContinuousTimeStateEvolution: - """Resolve and set diffusion metadata on a CTSE when missing.""" - if cte.diffusion_coefficient is None: - return cte - if cte.diffusion_type is not None and cte.bm_dim is not None: - return cte - - x0 = jnp.zeros((state_dim,)) - u0 = None if control_dim == 0 else jnp.zeros((control_dim,)) - probe_t0 = jnp.array(0.0) if t0 is None else jnp.asarray(t0) - resolved = _resolve_ctse_diffusion_metadata(cte, state_dim, x0, u0, probe_t0) - if resolved is not None: - resolved_type, resolved_bm_dim = resolved - object.__setattr__(cte, "diffusion_type", resolved_type) - object.__setattr__(cte, "bm_dim", resolved_bm_dim) - return cte - - -def _ensure_ctse_bm_dim(dynamics: DynamicalModel) -> DynamicalModel: - """Resolve diffusion metadata when CT dynamics are built under active plates.""" - if not isinstance(dynamics.state_evolution, ContinuousTimeStateEvolution): - return dynamics - - cte = dynamics.state_evolution - _ensure_ctse_diffusion_metadata( - cte, - state_dim=dynamics.state_dim, - control_dim=dynamics.control_dim, - t0=dynamics.t0, - ) - return dynamics - - class EulerMaruyamaGaussianStateEvolution(GaussianStateEvolution): """`GaussianStateEvolution` backed by Euler-Maruyama moments.""" - cte: ContinuousTimeStateEvolution + cte: StochasticContinuousTimeStateEvolution def __init__( self, - cte: ContinuousTimeStateEvolution, + cte: StochasticContinuousTimeStateEvolution, F=None, cov=None, ): # Accept these for reconstruction paths, but derive both from `cte`. - del F, cov self.cte = cte def _loc(x, u, t_now, t_next): - _ensure_ctse_diffusion_metadata( - cte, - state_dim=jnp.asarray(x).shape[-1], - ) return euler_maruyama_loc_cov(cte, x, u, t_now, t_next)["loc"] def _cov(x, u, t_now, t_next): - _ensure_ctse_diffusion_metadata( - cte, - state_dim=jnp.asarray(x).shape[-1], - ) return euler_maruyama_loc_cov(cte, x, u, t_now, t_next)["cov"] super().__init__( @@ -95,7 +45,9 @@ def __call__(self, x, u, t_now, t_next): ) -def euler_maruyama(cte: ContinuousTimeStateEvolution) -> GaussianStateEvolution: +def euler_maruyama( + cte: StochasticContinuousTimeStateEvolution, +) -> GaussianStateEvolution: """Discretize continuous-time state evolution via Euler-Maruyama. Euler-Maruyama is a first-order discrete approximation of a continuous-time @@ -105,7 +57,7 @@ def euler_maruyama(cte: ContinuousTimeStateEvolution) -> GaussianStateEvolution: (depends on `t_next - t_now`) and passed as a callable `cov`. Args: - cte: `ContinuousTimeStateEvolution` to discretize. + cte: `StochasticContinuousTimeStateEvolution` to discretize. Returns: GaussianStateEvolution: Discrete-time Gaussian transition with the same Euler–Maruyama semantics as before this refactor. @@ -156,6 +108,7 @@ class Discretizer(ObjectInterpretation, HandlesSelf): ContinuousTimeStateEvolution, DiscreteTimeStateEvolution, DynamicalModel, + FullDiffusion, ) def model_with_ctse(obs_times=None, obs_values=None): @@ -167,7 +120,9 @@ def model_with_ctse(obs_times=None, obs_values=None): ), state_evolution=ContinuousTimeStateEvolution( drift=lambda x, u, t: x, - diffusion_coefficient=lambda x, u, t: jnp.eye(state_dim, bm_dim), + diffusion=FullDiffusion( + lambda x, u, t: jnp.eye(state_dim, bm_dim) + ), ), observation_model=lambda x, u, t: dist.MultivariateNormal( x, @@ -209,8 +164,7 @@ def _sample_ds( ctrl_values=None, **kwargs, ) -> FunctionOfTime: - if isinstance(dynamics.state_evolution, ContinuousTimeStateEvolution): - dynamics = _ensure_ctse_bm_dim(dynamics) + if isinstance(dynamics.state_evolution, StochasticContinuousTimeStateEvolution): discrete_evolution = self.discretize(dynamics.state_evolution) dynamics = DynamicalModel( initial_condition=dynamics.initial_condition, diff --git a/dynestyx/inference/filters.py b/dynestyx/inference/filters.py index 2184730e..3e382975 100644 --- a/dynestyx/inference/filters.py +++ b/dynestyx/inference/filters.py @@ -54,7 +54,6 @@ from dynestyx.types import FunctionOfTime from dynestyx.utils import ( _array_has_plate_dims, - _ensure_continuous_bm_dim, _leaf_is_plate_batched, ) @@ -374,8 +373,6 @@ def _add_log_factors( if obs_times is None or obs_values is None: raise ValueError("obs_times and obs_values are required for filtering.") - dynamics = _ensure_continuous_bm_dim(dynamics) - config = ( self.filter_config if self.filter_config is not None @@ -401,8 +398,10 @@ def _add_log_factors( if not isinstance(config, ContinuousTimeConfigs): valid = [c.__name__ for c in ContinuousTimeConfigs] raise ValueError( - f"Invalid filter config: {type(config).__name__}. " - f"Valid config types: {valid}" + "Continuous-time models require a continuous-time filter config. " + "If you want to use a discrete-time filter, nest `Discretizer()` " + "inside `Filter()`. " + f"Got {type(config).__name__}; valid continuous-time config types: {valid}." ) return _filter_continuous_time( name, diff --git a/dynestyx/inference/integrations/cd_dynamax/continuous.py b/dynestyx/inference/integrations/cd_dynamax/continuous.py index 47345e69..c6cb2b31 100644 --- a/dynestyx/inference/integrations/cd_dynamax/continuous.py +++ b/dynestyx/inference/integrations/cd_dynamax/continuous.py @@ -40,6 +40,14 @@ ) +def _inexact_tree_dtype(tree, fallback) -> jax.typing.DTypeLike: + """Return a representative inexact dtype from a pytree of parameters.""" + for leaf in jax.tree.leaves(tree): + if isinstance(leaf, jax.Array) and jnp.issubdtype(leaf.dtype, jnp.inexact): + return leaf.dtype + return fallback + + def _config_to_cd_dynamax_filter_kwargs( config: ContinuousTimeFilterConfig, params, @@ -156,6 +164,10 @@ def _run_linear_kf( ) -> PosteriorGSSMFiltered: """Run exact continuous-discrete KF (AffineLinearDrift + constant diffusion + LinearGaussianObservation).""" params = dsx_to_cdlgssm_params(dynamics) + dtype = _inexact_tree_dtype(params, obs_values.dtype) + obs_times = jnp.asarray(obs_times, dtype=dtype) + obs_values = jnp.asarray(obs_values, dtype=dtype) + ctrl_values = jnp.asarray(ctrl_values, dtype=dtype) cd_model = ContDiscreteLinearGaussianSSM( state_dim=dynamics.state_dim, emission_dim=dynamics.observation_dim, @@ -226,6 +238,10 @@ def compute_continuous_filter( ) params, _ = dsx_to_cd_dynamax(dynamics, cd_model=cd_dynamax_model) + dtype = _inexact_tree_dtype(params, obs_values.dtype) + obs_values = jnp.asarray(obs_values, dtype=dtype) + obs_times_arr = jnp.asarray(obs_times_arr, dtype=dtype) + ctrl_vals = jnp.asarray(ctrl_vals, dtype=dtype) filter_kwargs = _config_to_cd_dynamax_filter_kwargs( filter_config, params, obs_values, obs_times_arr, ctrl_vals, key ) diff --git a/dynestyx/inference/integrations/cd_dynamax/discrete.py b/dynestyx/inference/integrations/cd_dynamax/discrete.py index 3386c0ea..aab3a547 100644 --- a/dynestyx/inference/integrations/cd_dynamax/discrete.py +++ b/dynestyx/inference/integrations/cd_dynamax/discrete.py @@ -33,6 +33,14 @@ from dynestyx.utils import _should_record_field +def _inexact_tree_dtype(tree, fallback) -> jax.typing.DTypeLike: + """Return a representative inexact dtype from a pytree of parameters.""" + for leaf in jax.tree.leaves(tree): + if isinstance(leaf, jax.Array) and jnp.issubdtype(leaf.dtype, jnp.inexact): + return leaf.dtype + return fallback + + def _lti_to_lgssm_params(dynamics: DynamicalModel): """Build dynamax ParamsLGSSM from LinearGaussianSSM.initialize for an LTI model.""" state_dim = dynamics.state_dim @@ -109,10 +117,16 @@ def compute_cd_dynamax_discrete_filter( if isinstance(filter_config, KFConfig): params = _lti_to_lgssm_params(dynamics) + dtype = _inexact_tree_dtype(params, emissions.dtype) + emissions = jnp.asarray(emissions, dtype=dtype) + inputs = jnp.asarray(inputs, dtype=dtype) return lgssm_filter(params, emissions, inputs=inputs) # EKF and UKF share the same nonlinear params representation. params_nl = gaussian_to_nlgssm_params(dynamics) + dtype = _inexact_tree_dtype(params_nl, emissions.dtype) + emissions = jnp.asarray(emissions, dtype=dtype) + inputs = jnp.asarray(inputs, dtype=dtype) if isinstance(filter_config, EKFConfig): return extended_kalman_filter(params_nl, emissions, inputs=inputs) diff --git a/dynestyx/inference/integrations/cd_dynamax/utils.py b/dynestyx/inference/integrations/cd_dynamax/utils.py index 6305f1a6..3063a8c0 100644 --- a/dynestyx/inference/integrations/cd_dynamax/utils.py +++ b/dynestyx/inference/integrations/cd_dynamax/utils.py @@ -15,20 +15,20 @@ from dynestyx.models import ( AffineDrift, - ContinuousTimeStateEvolution, + DeterministicContinuousTimeStateEvolution, DynamicalModel, GaussianObservation, GaussianStateEvolution, LinearGaussianObservation, LinearGaussianStateEvolution, + StochasticContinuousTimeStateEvolution, ) -from dynestyx.models.diffusions import diffusion_as_matrix, evaluate_diffusion type SSMType = ContDiscreteNonlinearGaussianSSM | ContDiscreteNonlinearSSM def _normalize_cd_dynamax_diffusion( - state_evolution: ContinuousTimeStateEvolution, + state_evolution: StochasticContinuousTimeStateEvolution, state_dim: int, ): """Return a diffusion coeff compatible with cd-dynamax's EnKF SDE solve. @@ -40,16 +40,7 @@ def _normalize_cd_dynamax_diffusion( """ def _wrapped(x, u, t): - diffusion = evaluate_diffusion( - state_evolution.diffusion_coefficient, - diffusion_type=state_evolution.diffusion_type, - bm_dim=state_evolution.bm_dim, - x=x, - u=u, - t=t, - state_dim=state_dim, - ) - L = diffusion_as_matrix(diffusion, state_dim=state_dim) + L = state_evolution.diffusion.as_matrix(x=x, u=u, t=t, state_dim=state_dim) n_cols = L.shape[-1] if n_cols > state_dim: raise ValueError( @@ -65,17 +56,10 @@ def _wrapped(x, u, t): def _validate_cd_dynamax_continuous_diffusion( - state_evolution: ContinuousTimeStateEvolution, + state_evolution: StochasticContinuousTimeStateEvolution, state_dim: int, ) -> None: - """Eagerly validate diffusion shape constraints for cd-dynamax continuous filters.""" - if state_evolution.diffusion_coefficient is None: - return - if state_evolution.bm_dim is None: - raise ValueError( - "Continuous cd-dynamax filters require resolved bm_dim on " - "ContinuousTimeStateEvolution." - ) + """Validate continuous cd-dynamax diffusion compatibility from resolved metadata.""" if state_evolution.bm_dim > state_dim: raise ValueError( "Continuous cd-dynamax filters require bm_dim <= state_dim. " @@ -213,32 +197,24 @@ def dsx_to_cdlgssm_params(dsx_model: DynamicalModel) -> ParamsCDLGSSM: - initial_condition is MultivariateNormal """ state_evo = dsx_model.state_evolution - if not isinstance(state_evo, ContinuousTimeStateEvolution): - raise TypeError("dsx_to_cdlgssm_params requires ContinuousTimeStateEvolution.") + if not isinstance(state_evo, StochasticContinuousTimeStateEvolution): + raise TypeError( + "dsx_to_cdlgssm_params requires StochasticContinuousTimeStateEvolution." + ) drift = state_evo.drift if not isinstance(drift, AffineDrift): raise TypeError( f"dsx_to_cdlgssm_params requires AffineDrift, got {type(drift).__name__}." ) - if state_evo.diffusion_coefficient is None: - raise ValueError("dsx_to_cdlgssm_params requires diffusion_coefficient.") - # Extract constant L and use inferred Brownian dimension. + # Extract constant L and use resolved Brownian dimension. x0 = jnp.zeros(dsx_model.state_dim) - diffusion = evaluate_diffusion( - state_evo.diffusion_coefficient, - diffusion_type=state_evo.diffusion_type, - bm_dim=state_evo.bm_dim, + L = state_evo.diffusion.as_matrix( x=x0, u=None, t=jnp.array(0.0), state_dim=dsx_model.state_dim, ) - L = diffusion_as_matrix(diffusion, state_dim=dsx_model.state_dim) - if state_evo.bm_dim is None: - raise ValueError( - "state_evolution.bm_dim is not set on ContinuousTimeStateEvolution." - ) Q = jnp.eye(state_evo.bm_dim) ic = dsx_model.initial_condition @@ -295,34 +271,48 @@ def dsx_to_cd_dynamax( ## Map state evolution ## state_evo = dsx_model.state_evolution - if isinstance(state_evo, ContinuousTimeStateEvolution): - if state_evo.drift is not None or state_evo.potential is not None: - shared_params.update( - { - "dynamics_drift": state_evo.total_drift, - } - ) - else: + if isinstance( + state_evo, + ( + DeterministicContinuousTimeStateEvolution, + StochasticContinuousTimeStateEvolution, + ), + ): + if state_evo.drift is None and state_evo.potential is None: raise ValueError("Both drift and potential are None; define at least one.") - if state_evo.diffusion_coefficient is not None: - if state_evo.bm_dim is None: - raise ValueError( - "state_evolution.bm_dim is not set on ContinuousTimeStateEvolution." - ) - _validate_cd_dynamax_continuous_diffusion( - state_evo, - dsx_model.state_dim, - ) - diffusion_coeff = _normalize_cd_dynamax_diffusion( - state_evo, - dsx_model.state_dim, - ) - shared_params.update( - { - "dynamics_diffusion_coefficient": diffusion_coeff, - "dynamics_diffusion_cov": jnp.eye(dsx_model.state_dim), - } - ) + shared_params.update( + { + "dynamics_drift": state_evo.total_drift, + } + ) + if isinstance(state_evo, StochasticContinuousTimeStateEvolution): + _validate_cd_dynamax_continuous_diffusion( + state_evo, + dsx_model.state_dim, + ) + diffusion_coeff = _normalize_cd_dynamax_diffusion( + state_evo, + dsx_model.state_dim, + ) + shared_params.update( + { + "dynamics_diffusion_coefficient": diffusion_coeff, + "dynamics_diffusion_cov": jnp.eye(dsx_model.state_dim), + } + ) + elif isinstance(state_evo, DeterministicContinuousTimeStateEvolution): + shared_params.update( + { + "dynamics_diffusion_coefficient": jnp.zeros( + (dsx_model.state_dim, dsx_model.state_dim) + ), + "dynamics_diffusion_cov": jnp.eye(dsx_model.state_dim), + } + ) + elif isinstance(state_evo, LinearGaussianStateEvolution): + raise NotImplementedError( + f"State evolution of type {type(state_evo)} is not supported yet." + ) else: raise NotImplementedError( f"State evolution of type {type(state_evo)} is not supported yet." diff --git a/dynestyx/models/__init__.py b/dynestyx/models/__init__.py index c7deab13..2085abe9 100644 --- a/dynestyx/models/__init__.py +++ b/dynestyx/models/__init__.py @@ -5,12 +5,19 @@ from dynestyx.models.core import ( ContinuousTimeStateEvolution, + DeterministicContinuousTimeStateEvolution, DiscreteTimeStateEvolution, Drift, DynamicalModel, ObservationModel, + StochasticContinuousTimeStateEvolution, +) +from dynestyx.models.diffusions import ( + DiagonalDiffusion, + Diffusion, + FullDiffusion, + ScalarDiffusion, ) -from dynestyx.models.diffusions import DiffusionType from dynestyx.models.lti_dynamics import LTI_continuous, LTI_discrete from dynestyx.models.observations import ( DiracIdentityObservation, @@ -25,17 +32,22 @@ __all__ = [ "ContinuousTimeStateEvolution", + "DeterministicContinuousTimeStateEvolution", "AffineDrift", "DiracIdentityObservation", + "Diffusion", "DiscreteTimeStateEvolution", - "DiffusionType", + "DiagonalDiffusion", "DynamicalModel", "Drift", + "FullDiffusion", "GaussianObservation", "GaussianStateEvolution", "LinearGaussianObservation", "LinearGaussianStateEvolution", "ObservationModel", + "StochasticContinuousTimeStateEvolution", "LTI_continuous", "LTI_discrete", + "ScalarDiffusion", ] diff --git a/dynestyx/models/checkers.py b/dynestyx/models/checkers.py index 5124fe57..de0a3e56 100644 --- a/dynestyx/models/checkers.py +++ b/dynestyx/models/checkers.py @@ -8,11 +8,6 @@ import numpyro.distributions as dist import numpyro.primitives -from dynestyx.models.diffusions import ( - DiffusionType, - evaluate_diffusion_value, - resolve_diffusion_metadata, -) from dynestyx.types import Control, State, Time @@ -85,119 +80,46 @@ def _make_probe_state(initial_condition: Any, state_dim: int) -> jax.Array: return jnp.zeros((state_dim,)) -def _resolve_ctse_diffusion_metadata( - state_evolution: Any, - state_dim: int, - x0: State, - u0: Control | None, - t0: Time, -) -> tuple[DiffusionType, int] | None: - """Resolve diffusion metadata from one probe evaluation. - - Tolerates leading batch dimensions (e.g. from plate-batched parameters) - by inspecting only the trailing two dimensions (..., state_dim, bm_dim). - - Returns the resolved diffusion type and bm_dim, or None if there is no - diffusion coefficient. - """ - if state_evolution.diffusion_coefficient is None: - if ( - state_evolution.bm_dim is not None - or state_evolution.diffusion_type is not None - ): - raise ValueError( - "diffusion_type and bm_dim cannot be set when " - "diffusion_coefficient is None." - ) - return None - - diffusion_shape = jax.eval_shape( - lambda: evaluate_diffusion_value( - state_evolution.diffusion_coefficient, x0, u0, t0 - ) - ).shape - return resolve_diffusion_metadata( - diffusion_shape, - state_dim=state_dim, - diffusion_type=state_evolution.diffusion_type, - bm_dim=state_evolution.bm_dim, - ) - - -def _infer_bm_dim( - state_evolution: Any, - state_dim: int, - x0: State, - u0: Control | None, - t0: Time, -) -> int | None: - """Compatibility wrapper returning only the resolved bm_dim.""" - resolved = _resolve_ctse_diffusion_metadata(state_evolution, state_dim, x0, u0, t0) - return None if resolved is None else resolved[1] - - def _validate_continuous_state_evolution( state_evolution: Any, state_dim: int, - x0: State, - u0: Control | None, - t0: Time, -) -> tuple[DiffusionType, int] | None: - """Validate the shape of the continuous-time state evolution w.r.t. state_dim and bm_dim. - - Returns the resolved diffusion metadata (or None if no diffusion coefficient). - """ - drift_shape = jax.eval_shape(lambda: state_evolution.total_drift(x0, u0, t0)).shape + x_probe: State, + u_probe: Control | None, + t_probe: Time, +) -> None: + """Validate the drift shape of a continuous-time state evolution.""" + drift_shape = jax.eval_shape( + lambda: state_evolution.total_drift(x_probe, u_probe, t_probe) + ).shape if drift_shape != (state_dim,): raise ValueError( "State drift shape is inconsistent with state_dim. " f"Expected {(state_dim,)}, got {drift_shape}." ) - return _resolve_ctse_diffusion_metadata(state_evolution, state_dim, x0, u0, t0) - -def _validate_state_evolution_output_shape( +def _validate_discrete_state_evolution_output_shape( state_evolution: Callable[[State, Control, Time], State] | Callable[[State, Control, Time, Time], State], state_dim: int, - x0: State, - u0: Control | None, - t0: Time, - *, - continuous_time: bool, -) -> int | None: - """Validate the shape of the state evolution w.r.t. state_dim (and bm_dim for continuous-time models). - - Returns the resolved bm_dim for continuous-time models, or None otherwise. - """ - if continuous_time: - resolved_diffusion = _validate_continuous_state_evolution( - state_evolution=state_evolution, - state_dim=state_dim, - x0=x0, - u0=u0, - t0=t0, - ) - return None if resolved_diffusion is None else resolved_diffusion[1] - else: - if getattr(state_evolution, "bm_dim", None) is not None: - raise ValueError( - "bm_dim can only be set for continuous-time models with " - "diffusion_coefficient." - ) - t_now = t0 - t_next = t0 + 1.0 - transition_dist = state_evolution(x=x0, u=u0, t_now=t_now, t_next=t_next) # type: ignore[misc,call-arg] - inferred_state_dim = _infer_vector_dim_from_distribution( - transition_dist, "state_evolution(x, u, t_now, t_next)" + x_probe: State, + u_probe: Control | None, + t_probe: Time, +) -> None: + """Validate a discrete-time state evolution against the inferred state dimension.""" + if getattr(state_evolution, "diffusion", None) is not None: + raise ValueError("diffusion can only be set for continuous-time models.") + t_now = t_probe + t_next = t_probe + 1.0 + transition_dist = state_evolution(x=x_probe, u=u_probe, t_now=t_now, t_next=t_next) # type: ignore[misc,call-arg] + inferred_state_dim = _infer_vector_dim_from_distribution( + transition_dist, "state_evolution(x, u, t_now, t_next)" + ) + if inferred_state_dim != state_dim: + raise ValueError( + "State transition shape is inconsistent with state_dim. " + f"state_dim={state_dim}, inferred={inferred_state_dim}." ) - if inferred_state_dim != state_dim: - raise ValueError( - "State transition shape is inconsistent with state_dim. " - f"state_dim={state_dim}, inferred={inferred_state_dim}." - ) - return None def _validate_continuous_time_flag( @@ -251,21 +173,21 @@ def _infer_observation_dim_in_plate_context( observation_model: Callable[[State, Control | None, Time], Any], inferred_state_dim: int, control_dim: int, - t0: Time | None, + t_probe: Time | None, observation_dim: int | None, ) -> int: """Infer observation dimension in plate context, falling back to explicit value.""" if observation_dim is not None: return int(observation_dim) - x0 = _make_probe_state( + x_probe = _make_probe_state( initial_condition=initial_condition, state_dim=inferred_state_dim, ) - u0 = None if control_dim == 0 else jnp.zeros((control_dim,)) - dummy_t0 = jnp.array(0.0) if t0 is None else t0 + u_probe = None if control_dim == 0 else jnp.zeros((control_dim,)) + t_probe = jnp.array(0.0) if t_probe is None else t_probe try: - obs_dist = observation_model(x0, u0, dummy_t0) + obs_dist = observation_model(x_probe, u_probe, t_probe) return int( _infer_vector_dim_from_distribution(obs_dist, "observation_model(x, u, t)") ) diff --git a/dynestyx/models/core.py b/dynestyx/models/core.py index bc1ccd24..4d8059d9 100644 --- a/dynestyx/models/core.py +++ b/dynestyx/models/core.py @@ -1,7 +1,7 @@ """Core interfaces and base classes for dynamical models.""" from collections.abc import Callable -from typing import Any, Protocol +from typing import Any, Protocol, cast import equinox as eqx import jax @@ -14,14 +14,14 @@ _inside_numpyro_plate_context, _is_categorical_distribution, _make_probe_state, - _resolve_ctse_diffusion_metadata, _validate_categorical_state, + _validate_continuous_state_evolution, _validate_continuous_time_flag, + _validate_discrete_state_evolution_output_shape, _validate_observation_dim, _validate_state_dim, - _validate_state_evolution_output_shape, ) -from dynestyx.models.diffusions import DiffusionSpec, DiffusionType +from dynestyx.models.diffusions import Diffusion from dynestyx.types import ( Control, State, @@ -136,6 +136,52 @@ def __init__( # batched parameters produce shapes that don't match unbatched expectations. _inside_plate = _inside_numpyro_plate_context() + def _canonicalize_continuous_state_evolution( + *, + x_probe: State, + u_probe: Control | None, + t_probe: Time, + ) -> None: + if not inferred_continuous_time: + return + diffusion = state_evolution.diffusion + if diffusion is None: + if not isinstance( + state_evolution, DeterministicContinuousTimeStateEvolution + ): + object.__setattr__( + self, + "state_evolution", + DeterministicContinuousTimeStateEvolution( + drift=state_evolution.drift, + potential=state_evolution.potential, + use_negative_gradient=state_evolution.use_negative_gradient, + ), + ) + return + + resolved_diffusion = diffusion.resolve_metadata( + state_dim=inferred_state_dim, + x_probe=x_probe, + u_probe=u_probe, + t_probe=t_probe, + ) + if ( + isinstance(state_evolution, StochasticContinuousTimeStateEvolution) + and state_evolution.diffusion is resolved_diffusion + ): + return + object.__setattr__( + self, + "state_evolution", + StochasticContinuousTimeStateEvolution( + drift=state_evolution.drift, + potential=state_evolution.potential, + use_negative_gradient=state_evolution.use_negative_gradient, + diffusion=resolved_diffusion, + ), + ) + if _inside_plate: # Cannot validate shapes with batched parameters; trust the user. # Infer observation_dim from observation model if not explicitly provided. @@ -144,7 +190,7 @@ def __init__( observation_model=observation_model, inferred_state_dim=inferred_state_dim, control_dim=control_dim, - t0=self.t0, + t_probe=self.t0, observation_dim=observation_dim, ) self.state_dim = int(inferred_state_dim) @@ -152,56 +198,44 @@ def __init__( self.control_dim = int(control_dim) self.categorical_state = bool(inferred_categorical_state) - # Resolve diffusion metadata for continuous-time models - if inferred_continuous_time and isinstance( - state_evolution, ContinuousTimeStateEvolution - ): - x0 = jnp.zeros((inferred_state_dim,)) - u0 = None if control_dim == 0 else jnp.zeros((control_dim,)) - dummy_t0 = jnp.array(0.0) if self.t0 is None else self.t0 - resolved_diffusion = _resolve_ctse_diffusion_metadata( - state_evolution, inferred_state_dim, x0, u0, dummy_t0 - ) - if resolved_diffusion is not None: - resolved_type, resolved_bm_dim = resolved_diffusion - object.__setattr__(state_evolution, "diffusion_type", resolved_type) - object.__setattr__(state_evolution, "bm_dim", resolved_bm_dim) + # Plate-batched parameters prevent reliable unbatched shape probes, so + # we resolve continuous-time diffusion metadata from synthetic vectors. + _canonicalize_continuous_state_evolution( + x_probe=jnp.zeros((inferred_state_dim,)), + u_probe=None if control_dim == 0 else jnp.zeros((control_dim,)), + t_probe=jnp.array(0.0) if self.t0 is None else self.t0, + ) return - x0 = _make_probe_state( + x_probe = _make_probe_state( initial_condition=initial_condition, state_dim=inferred_state_dim ) - u0 = None if control_dim == 0 else jnp.zeros((control_dim,)) - dummy_t0 = jnp.array(0.0) if self.t0 is None else self.t0 - - inferred_bm_dim = _validate_state_evolution_output_shape( - state_evolution=state_evolution, - state_dim=inferred_state_dim, - x0=x0, - u0=u0, - t0=dummy_t0, - continuous_time=self.continuous_time, - ) - if self.continuous_time and isinstance( - state_evolution, ContinuousTimeStateEvolution - ): - resolved_diffusion = _resolve_ctse_diffusion_metadata( - state_evolution, - inferred_state_dim, - x0, - u0, - dummy_t0, + u_probe = None if control_dim == 0 else jnp.zeros((control_dim,)) + t_probe = jnp.array(0.0) if self.t0 is None else self.t0 + + if self.continuous_time: + _validate_continuous_state_evolution( + state_evolution=state_evolution, + state_dim=inferred_state_dim, + x_probe=x_probe, + u_probe=u_probe, + t_probe=t_probe, + ) + _canonicalize_continuous_state_evolution( + x_probe=x_probe, + u_probe=u_probe, + t_probe=t_probe, ) - if resolved_diffusion is not None: - resolved_type, resolved_bm_dim = resolved_diffusion - if state_evolution.diffusion_type != resolved_type: - object.__setattr__(state_evolution, "diffusion_type", resolved_type) - if inferred_bm_dim != resolved_bm_dim: - inferred_bm_dim = resolved_bm_dim - if state_evolution.bm_dim != resolved_bm_dim: - object.__setattr__(state_evolution, "bm_dim", resolved_bm_dim) - - obs_dist = observation_model(x0, u0, dummy_t0) + else: + _validate_discrete_state_evolution_output_shape( + state_evolution=state_evolution, + state_dim=inferred_state_dim, + x_probe=x_probe, + u_probe=u_probe, + t_probe=t_probe, + ) + + obs_dist = observation_model(x_probe, u_probe, t_probe) inferred_observation_dim = _infer_vector_dim_from_distribution( obs_dist, "observation_model(x, u, t)" ) @@ -316,26 +350,15 @@ class ContinuousTimeStateEvolution(eqx.Module): At least one of `drift` or `potential` must be non-None. use_negative_gradient (bool): If True, use $-\\nabla_x V$ (e.g., gradient descent on potential); otherwise use $+\\nabla_x V$. Default is False. - diffusion_coefficient (DiffusionSpec | None): Diffusion coefficient specification. - This may be a callable `L(x, u, t)`, a constant scalar/vector/matrix, or `None` - for deterministic dynamics. - diffusion_type ("full" | "diag" | "scalar" | None): Optional explicit diffusion semantics. - Use `"full"` for matrix-valued diffusion, `"diag"` for diagonal shorthand with - trailing shape `(..., state_dim)`, and `"scalar"` for scalar shorthand with shape - `()` or `(..., 1)`. If omitted, legacy behavior infers `"full"` from trailing - shape `(..., state_dim, bm_dim)` and otherwise infers scalar/diagonal shorthand - from the trailing dimension. - bm_dim (int | None): Dimension of the Brownian motion $W_t$. - Inferred automatically only for full matrix diffusion. Scalar and diagonal - diffusion require explicit `bm_dim`, which must be either `1` or `state_dim`. + diffusion (Diffusion | None): Diffusion coefficient object. + Use `FullDiffusion`, `DiagonalDiffusion`, or `ScalarDiffusion` to define + the stochastic part of the SDE. Pass `None` for deterministic dynamics. """ drift: Drift | None = None potential: Potential | None = None use_negative_gradient: bool = eqx.field(static=True, default=False) - diffusion_coefficient: DiffusionSpec | None = None - diffusion_type: DiffusionType | None = eqx.field(static=True, default=None) - bm_dim: int | None = eqx.field(static=True, default=None) + diffusion: Diffusion | None = None def total_drift(self, x: State, u: Control | None, t: Time) -> dState: base = self.drift(x, u, t) if self.drift is not None else None @@ -356,6 +379,56 @@ def total_drift(self, x: State, u: Control | None, t: Time) -> dState: return base + grad_term +class DeterministicContinuousTimeStateEvolution(ContinuousTimeStateEvolution): + """Refined continuous-time state evolution with no diffusion.""" + + diffusion: None = eqx.field(static=True, default=None) + + def __init__( + self, + drift: Drift | None = None, + potential: Potential | None = None, + use_negative_gradient: bool = False, + diffusion: None = None, + ): + if diffusion is not None: + raise ValueError( + "DeterministicContinuousTimeStateEvolution does not accept diffusion." + ) + object.__setattr__(self, "drift", drift) + object.__setattr__(self, "potential", potential) + object.__setattr__(self, "use_negative_gradient", use_negative_gradient) + object.__setattr__(self, "diffusion", None) + + +class StochasticContinuousTimeStateEvolution(ContinuousTimeStateEvolution): + """Refined continuous-time state evolution with resolved diffusion.""" + + diffusion: Diffusion = eqx.field(static=True, default=cast(Diffusion, None)) + + def __init__( + self, + *, + drift: Drift | None = None, + potential: Potential | None = None, + use_negative_gradient: bool = False, + diffusion: Diffusion, + ): + if diffusion.bm_dim is None: + raise ValueError( + "StochasticContinuousTimeStateEvolution requires diffusion with " + "resolved bm_dim." + ) + object.__setattr__(self, "drift", drift) + object.__setattr__(self, "potential", potential) + object.__setattr__(self, "use_negative_gradient", use_negative_gradient) + object.__setattr__(self, "diffusion", diffusion) + + @property + def bm_dim(self) -> int: + return cast(int, self.diffusion.bm_dim) + + class DiscreteTimeStateEvolution(eqx.Module): """ Discrete-time state evolution via Markov transition distributions. diff --git a/dynestyx/models/diffusions.py b/dynestyx/models/diffusions.py index c28bdd03..066576ea 100644 --- a/dynestyx/models/diffusions.py +++ b/dynestyx/models/diffusions.py @@ -1,205 +1,332 @@ -"""Helpers for evaluating and normalizing continuous-time diffusion specs.""" +"""Diffusion objects for continuous-time state evolution.""" from __future__ import annotations +import copy from collections.abc import Callable -from typing import Literal, NamedTuple +from typing import NamedTuple, cast +import equinox as eqx +import jax import jax.numpy as jnp from jax import Array from dynestyx.types import Control, State, Time -DiffusionType = Literal["full", "diag", "scalar"] DiffusionValue = Array | float | int DiffusionSpec = Callable[[State, Control | None, Time], DiffusionValue] | DiffusionValue class EvaluatedDiffusion(NamedTuple): - diffusion_type: DiffusionType + """A diffusion object evaluated at a specific `(x, u, t)`.""" + + diffusion: Diffusion value: Array - bm_dim: int - - -def evaluate_diffusion_value( - diffusion_coefficient: DiffusionSpec, - x: State, - u: Control | None, - t: Time, -) -> Array: - """Evaluate a diffusion spec and return it as a JAX array.""" - value = ( - diffusion_coefficient(x, u, t) - if callable(diffusion_coefficient) - else diffusion_coefficient - ) - return jnp.asarray(value) - - -def resolve_diffusion_metadata( - shape: tuple[int, ...], - *, - state_dim: int, - diffusion_type: DiffusionType | None, - bm_dim: int | None, -) -> tuple[DiffusionType, int]: - """Resolve diffusion semantics from trailing shape and user annotations.""" - resolved_type = ( - diffusion_type - if diffusion_type is not None - else _infer_diffusion_type(shape, state_dim=state_dim) - ) - - if resolved_type == "full": + + def as_matrix(self, *, state_dim: int) -> Array: + return self.diffusion._value_as_matrix(self.value, state_dim=state_dim) + + def covariance(self, *, state_dim: int) -> Array: + return self.diffusion._value_covariance(self.value, state_dim=state_dim) + + def apply(self, dw: Array, *, state_dim: int) -> Array: + return self.diffusion._apply_value(self.value, dw, state_dim=state_dim) + + +class Diffusion(eqx.Module): + """Base class for diffusion coefficients in SDEs. + + A diffusion encapsulates both the numeric coefficient `L(x, u, t)` and the + structural interpretation of that coefficient inside the SDE + + `dx_t = f(x_t, u_t, t) dt + L(x_t, u_t, t) dW_t`. + """ + + coefficient: DiffusionSpec + bm_dim: int | None = eqx.field(static=True, default=None) + + def __init__( + self, + coefficient: DiffusionSpec, + bm_dim: int | None = None, + ): + object.__setattr__( + self, + "coefficient", + coefficient if callable(coefficient) else jnp.asarray(coefficient), + ) + object.__setattr__(self, "bm_dim", None if bm_dim is None else int(bm_dim)) + self._validate_init() + + def evaluate_value( + self, + *, + x: State, + u: Control | None, + t: Time, + ) -> Array: + if callable(self.coefficient): + return jnp.asarray(self.coefficient(x, u, t)) + return cast(Array, self.coefficient) + + def resolve_metadata( + self, + *, + state_dim: int, + x_probe: State, + u_probe: Control | None, + t_probe: Time, + ) -> Diffusion: + raise NotImplementedError + + def evaluate( + self, + *, + x: State, + u: Control | None, + t: Time, + ) -> EvaluatedDiffusion: + return EvaluatedDiffusion(self, self.evaluate_value(x=x, u=u, t=t)) + + def as_matrix( + self, + *, + x: State, + u: Control | None, + t: Time, + state_dim: int, + ) -> Array: + return self.evaluate(x=x, u=u, t=t).as_matrix(state_dim=state_dim) + + def covariance( + self, + *, + x: State, + u: Control | None, + t: Time, + state_dim: int, + ) -> Array: + return self.evaluate(x=x, u=u, t=t).covariance(state_dim=state_dim) + + def apply( + self, + dw: Array, + *, + x: State, + u: Control | None, + t: Time, + state_dim: int, + ) -> Array: + return self.evaluate(x=x, u=u, t=t).apply(dw, state_dim=state_dim) + + def _with_bm_dim(self, bm_dim: int) -> Diffusion: + new_self = copy.copy(self) + object.__setattr__(new_self, "bm_dim", int(bm_dim)) + return new_self + + def _constant_shape(self) -> tuple[int, ...] | None: + if callable(self.coefficient): + return None + return tuple(int(d) for d in jnp.shape(self.coefficient)) + + def _validate_init(self) -> None: + if self.bm_dim is not None and int(self.bm_dim) <= 0: + raise ValueError(f"bm_dim must be positive. Got bm_dim={self.bm_dim}.") + + def _value_as_matrix(self, value: Array, *, state_dim: int) -> Array: + raise NotImplementedError + + def _value_covariance(self, value: Array, *, state_dim: int) -> Array: + raise NotImplementedError + + def _apply_value(self, value: Array, dw: Array, *, state_dim: int) -> Array: + raise NotImplementedError + + +class FullDiffusion(Diffusion): + """General matrix-valued diffusion coefficient `L(x, u, t)`.""" + + def _validate_init(self) -> None: + super()._validate_init() + shape = self._constant_shape() + if shape is not None and len(shape) < 2: + raise ValueError( + "Full diffusion requires a matrix-valued constant coefficient with " + "trailing shape (..., state_dim, bm_dim). " + f"Got shape {shape}." + ) + if shape is not None and self.bm_dim is None: + object.__setattr__(self, "bm_dim", int(shape[-1])) + + def resolve_metadata( + self, + *, + state_dim: int, + x_probe: State, + u_probe: Control | None, + t_probe: Time, + ) -> FullDiffusion: + shape = jax.eval_shape( + lambda: self.evaluate_value(x=x_probe, u=u_probe, t=t_probe) + ).shape if len(shape) < 2 or int(shape[-2]) != state_dim: raise ValueError( "Full diffusion must have trailing shape (..., state_dim, bm_dim). " f"Got shape {shape} with state_dim={state_dim}." ) inferred_bm_dim = int(shape[-1]) - if bm_dim is not None and int(bm_dim) != inferred_bm_dim: + if self.bm_dim is not None and int(self.bm_dim) != inferred_bm_dim: + raise ValueError( + "bm_dim does not match inferred diffusion output shape. " + f"Got bm_dim={self.bm_dim}, inferred={inferred_bm_dim} from shape {shape}." + ) + return ( + self + if self.bm_dim == inferred_bm_dim + else cast(FullDiffusion, self._with_bm_dim(inferred_bm_dim)) + ) + + def _value_as_matrix(self, value: Array, *, state_dim: int) -> Array: + return value + + def _value_covariance(self, value: Array, *, state_dim: int) -> Array: + return value @ jnp.swapaxes(value, -1, -2) + + def _apply_value(self, value: Array, dw: Array, *, state_dim: int) -> Array: + return value @ dw + + +class DiagonalDiffusion(Diffusion): + """Vector-valued diffusion with diagonal or shared-driver interpretation.""" + + def _validate_init(self) -> None: + super()._validate_init() + if self.bm_dim is None: raise ValueError( - "bm_dim does not match inferred diffusion_coefficient output shape. " - f"Got bm_dim={bm_dim}, inferred={inferred_bm_dim} from shape {shape}." + "Diagonal diffusion requires explicit bm_dim. " + "For diagonal diffusion, bm_dim must be either 1 or state_dim." + ) + shape = self._constant_shape() + if shape is not None and len(shape) == 0: + raise ValueError( + "Diagonal diffusion requires a vector-valued constant coefficient " + "with trailing shape (..., state_dim). " + f"Got shape {shape}." ) - return resolved_type, inferred_bm_dim - if resolved_type == "diag": + def resolve_metadata( + self, + *, + state_dim: int, + x_probe: State, + u_probe: Control | None, + t_probe: Time, + ) -> DiagonalDiffusion: + shape = jax.eval_shape( + lambda: self.evaluate_value(x=x_probe, u=u_probe, t=t_probe) + ).shape if len(shape) == 0 or int(shape[-1]) != state_dim: raise ValueError( "Diagonal diffusion must have trailing shape (..., state_dim). " f"Got shape {shape} with state_dim={state_dim}." ) - else: - if len(shape) != 0 and int(shape[-1]) != 1: + bm_dim = self.bm_dim + assert bm_dim is not None + if bm_dim not in (1, state_dim): raise ValueError( - "Scalar diffusion must have shape () or trailing shape (..., 1). " - f"Got shape {shape}." + "Diagonal diffusion requires bm_dim to be either 1 or state_dim. " + f"Got bm_dim={bm_dim}, state_dim={state_dim}." ) + return self - if bm_dim is None: - raise ValueError( - f"{resolved_type} diffusion requires explicit bm_dim. " - "For scalar or diagonal diffusion, bm_dim must be either 1 or state_dim." - ) - resolved_bm_dim = int(bm_dim) - if resolved_bm_dim not in (1, state_dim): - raise ValueError( - f"{resolved_type} diffusion requires bm_dim to be either 1 or state_dim. " - f"Got bm_dim={resolved_bm_dim}, state_dim={state_dim}." - ) - return resolved_type, resolved_bm_dim - - -def evaluate_diffusion( - diffusion_coefficient: DiffusionSpec, - *, - diffusion_type: DiffusionType | None, - bm_dim: int | None, - x: State, - u: Control | None, - t: Time, - state_dim: int, -) -> EvaluatedDiffusion: - """Evaluate a diffusion spec using already-resolved metadata.""" - value = evaluate_diffusion_value(diffusion_coefficient, x, u, t) - if diffusion_type is None or bm_dim is None: - raise ValueError( - "Diffusion metadata must be resolved at model initialization before " - "runtime evaluation." - ) - return EvaluatedDiffusion( - diffusion_type=diffusion_type, - value=value, - bm_dim=int(bm_dim), - ) - - -def diffusion_as_matrix( - diffusion: EvaluatedDiffusion, - *, - state_dim: int, -) -> Array: - """Convert a structured diffusion into dense (..., state_dim, bm_dim) form.""" - value = diffusion.value - if diffusion.diffusion_type == "full": - return value - - eye = jnp.eye(state_dim, dtype=value.dtype) - if diffusion.diffusion_type == "diag": - if diffusion.bm_dim == 1: + def _value_as_matrix(self, value: Array, *, state_dim: int) -> Array: + assert self.bm_dim is not None + if self.bm_dim == 1: return value[..., :, None] - return value[..., :, None] * eye - - scalar = value if value.ndim == 0 else jnp.squeeze(value, axis=-1) - if diffusion.bm_dim == 1: - return jnp.broadcast_to(scalar[..., None, None], scalar.shape + (state_dim, 1)) - return scalar[..., None, None] * eye - - -def diffusion_covariance( - diffusion: EvaluatedDiffusion, - *, - state_dim: int, -) -> Array: - """Return L L^T while preserving scalar/diagonal structure when possible.""" - value = diffusion.value - if diffusion.diffusion_type == "full": - return value @ jnp.swapaxes(value, -1, -2) + return value[..., :, None] * jnp.eye(state_dim, dtype=value.dtype) - eye = jnp.eye(state_dim, dtype=value.dtype) - if diffusion.diffusion_type == "diag": - if diffusion.bm_dim == 1: + def _value_covariance(self, value: Array, *, state_dim: int) -> Array: + assert self.bm_dim is not None + if self.bm_dim == 1: return value[..., :, None] * value[..., None, :] - return jnp.square(value)[..., :, None] * eye - - sigma_sq = jnp.square(value if value.ndim == 0 else jnp.squeeze(value, axis=-1)) - if diffusion.bm_dim == 1: - return sigma_sq[..., None, None] * jnp.ones( - (state_dim, state_dim), dtype=value.dtype - ) - return sigma_sq[..., None, None] * eye - - -def apply_diffusion( - diffusion: EvaluatedDiffusion, - dw: Array, - *, - state_dim: int, -) -> Array: - """Apply a structured diffusion to a Brownian increment vector.""" - value = diffusion.value - if diffusion.diffusion_type == "full": - return value @ dw + return jnp.square(value)[..., :, None] * jnp.eye(state_dim, dtype=value.dtype) - if diffusion.diffusion_type == "diag": - if diffusion.bm_dim == 1: - return value * dw[0] + def _apply_value(self, value: Array, dw: Array, *, state_dim: int) -> Array: + assert self.bm_dim is not None + if self.bm_dim == 1: + return value * dw[..., 0] return value * dw - scalar = value if value.ndim == 0 else jnp.squeeze(value, axis=-1) - if diffusion.bm_dim == 1: - return jnp.broadcast_to( - (scalar * dw[0])[..., None], scalar.shape + (state_dim,) - ) - return scalar[..., None] * dw - - -def _infer_diffusion_type( - shape: tuple[int, ...], - *, - state_dim: int, -) -> DiffusionType: - """Infer legacy diffusion semantics from shape when diffusion_type is omitted.""" - if len(shape) >= 2 and int(shape[-2]) == state_dim: - return "full" - if len(shape) == 0 or int(shape[-1]) == 1: - return "scalar" - if int(shape[-1]) == state_dim: - return "diag" - trailing_dim = int(shape[-1]) - raise ValueError( - f"1D diffusion output with trailing dimension {trailing_dim} is treated as " - f"scalar/diagonal shorthand, so it must end in 1 or state_dim={state_dim}. " - "Use shape (..., state_dim, bm_dim) for full diffusion." - ) + +class ScalarDiffusion(Diffusion): + """Scalar-valued diffusion with isotropic or shared-driver interpretation.""" + + def _validate_init(self) -> None: + super()._validate_init() + if self.bm_dim is None: + raise ValueError( + "Scalar diffusion requires explicit bm_dim. " + "For scalar diffusion, bm_dim must be either 1 or state_dim." + ) + shape = self._constant_shape() + if shape is not None and len(shape) != 0 and int(shape[-1]) != 1: + raise ValueError( + "Scalar diffusion requires a scalar constant coefficient or trailing " + "shape (..., 1). " + f"Got shape {shape}." + ) + + def resolve_metadata( + self, + *, + state_dim: int, + x_probe: State, + u_probe: Control | None, + t_probe: Time, + ) -> ScalarDiffusion: + shape = jax.eval_shape( + lambda: self.evaluate_value(x=x_probe, u=u_probe, t=t_probe) + ).shape + if len(shape) != 0 and int(shape[-1]) != 1: + raise ValueError( + "Scalar diffusion must have shape () or trailing shape (..., 1). " + f"Got shape {shape}." + ) + bm_dim = self.bm_dim + assert bm_dim is not None + if bm_dim not in (1, state_dim): + raise ValueError( + "Scalar diffusion requires bm_dim to be either 1 or state_dim. " + f"Got bm_dim={bm_dim}, state_dim={state_dim}." + ) + return self + + def _scalar_value(self, value: Array) -> Array: + return value if value.ndim == 0 else jnp.squeeze(value, axis=-1) + + def _value_as_matrix(self, value: Array, *, state_dim: int) -> Array: + scalar = self._scalar_value(value) + assert self.bm_dim is not None + if self.bm_dim == 1: + return jnp.broadcast_to( + scalar[..., None, None], scalar.shape + (state_dim, 1) + ) + return scalar[..., None, None] * jnp.eye(state_dim, dtype=value.dtype) + + def _value_covariance(self, value: Array, *, state_dim: int) -> Array: + sigma_sq = jnp.square(self._scalar_value(value)) + assert self.bm_dim is not None + if self.bm_dim == 1: + return sigma_sq[..., None, None] * jnp.ones( + (state_dim, state_dim), dtype=value.dtype + ) + return sigma_sq[..., None, None] * jnp.eye(state_dim, dtype=value.dtype) + + def _apply_value(self, value: Array, dw: Array, *, state_dim: int) -> Array: + scalar = self._scalar_value(value) + assert self.bm_dim is not None + if self.bm_dim == 1: + return jnp.broadcast_to( + (scalar * dw[..., 0])[..., None], scalar.shape + (state_dim,) + ) + return scalar[..., None] * dw diff --git a/dynestyx/models/lti_dynamics.py b/dynestyx/models/lti_dynamics.py index e17972c3..a0a5bcb5 100644 --- a/dynestyx/models/lti_dynamics.py +++ b/dynestyx/models/lti_dynamics.py @@ -6,6 +6,7 @@ ContinuousTimeStateEvolution, DynamicalModel, ) +from dynestyx.models.diffusions import FullDiffusion from dynestyx.models.observations import LinearGaussianObservation from dynestyx.models.state_evolution import AffineDrift, LinearGaussianStateEvolution @@ -175,8 +176,7 @@ def LTI_continuous( state_evolution = ContinuousTimeStateEvolution( drift=drift, - diffusion_coefficient=L, - diffusion_type="full", + diffusion=FullDiffusion(L), ) observation_model = LinearGaussianObservation(H=H, R=R, D=D, bias=d) diff --git a/dynestyx/simulators.py b/dynestyx/simulators.py index 4d403931..f1af7ee6 100644 --- a/dynestyx/simulators.py +++ b/dynestyx/simulators.py @@ -21,10 +21,11 @@ from dynestyx.handlers import HandlesSelf, _sample_intp from dynestyx.inference.integrations.utils import WeightedParticles from dynestyx.models import ( - ContinuousTimeStateEvolution, + DeterministicContinuousTimeStateEvolution, DiracIdentityObservation, DiscreteTimeStateEvolution, DynamicalModel, + StochasticContinuousTimeStateEvolution, ) from dynestyx.solvers import solve_ode, solve_sde from dynestyx.types import FunctionOfTime, State, Time, TimeLike, as_scalar_time_array @@ -32,7 +33,6 @@ _array_has_plate_dims, _build_control_path, _dist_has_plate_batch_dims, - _ensure_continuous_bm_dim, _get_val_or_None, _has_any_batched_plate_source, _leaf_is_plate_batched, @@ -248,8 +248,6 @@ def _run_single_member_simulation( **kwargs, ) -> dict[str, Array] | None: """Run simulator logic for one unbatched member and return trajectories.""" - dynamics = _ensure_continuous_bm_dim(dynamics) - if ( filtered_times is not None and filtered_dists is None @@ -759,7 +757,7 @@ def _simulate( Args: dynamics: A `DynamicalModel` whose `state_evolution` is a - `ContinuousTimeStateEvolution` with a non-None diffusion coefficient + `ContinuousTimeStateEvolution` with a non-None diffusion and inferred `bm_dim` (set during `DynamicalModel` construction). obs_times: Times at which to save the latent state and emit observations. Required. @@ -778,16 +776,12 @@ def _simulate( parameter inference for SDEs, because it introduces an explicit, high- dimensional latent path. Prefer filtering (`Filter`) or particle methods. """ - if not isinstance(dynamics.state_evolution, ContinuousTimeStateEvolution): + if not isinstance( + dynamics.state_evolution, StochasticContinuousTimeStateEvolution + ): raise NotImplementedError( - f"SDESimulator only works with ContinuousTimeStateEvolution, got {type(dynamics.state_evolution)}" - ) - - if dynamics.state_evolution.diffusion_coefficient is None: - raise ValueError( - "SDESimulator requires diffusion_coefficient to be defined " - f"(got coeff={dynamics.state_evolution.diffusion_coefficient}). " - "Use ODESimulator for deterministic dynamics." + "SDESimulator only works with StochasticContinuousTimeStateEvolution, got " + f"{type(dynamics.state_evolution)}" ) if obs_times is not None: @@ -1182,7 +1176,7 @@ def _simulate( Args: dynamics: A `DynamicalModel` whose `state_evolution` is a - `ContinuousTimeStateEvolution` with deterministic dynamics. + `DeterministicContinuousTimeStateEvolution`. obs_times: Times at which to save the latent state and emit observations. obs_values: Optional observation array. If provided, observation sites are conditioned via `obs=obs_values[i]`. @@ -1306,11 +1300,14 @@ def _simulate( **kwargs, ) -> dict[str, State]: if self.simulator is None: - if isinstance(dynamics.state_evolution, ContinuousTimeStateEvolution): - if dynamics.state_evolution.diffusion_coefficient is None: - self.simulator = ODESimulator(*self.args, **self.kwargs) - else: - self.simulator = SDESimulator(*self.args, **self.kwargs) + if isinstance( + dynamics.state_evolution, StochasticContinuousTimeStateEvolution + ): + self.simulator = SDESimulator(*self.args, **self.kwargs) + elif isinstance( + dynamics.state_evolution, DeterministicContinuousTimeStateEvolution + ): + self.simulator = ODESimulator(*self.args, **self.kwargs) elif isinstance(dynamics.state_evolution, DiscreteTimeStateEvolution): self.simulator = DiscreteTimeSimulator(*self.args, **self.kwargs) else: diff --git a/dynestyx/solvers/sde.py b/dynestyx/solvers/sde.py index 75f28838..cc1a2958 100644 --- a/dynestyx/solvers/sde.py +++ b/dynestyx/solvers/sde.py @@ -11,15 +11,8 @@ import jax.random as jr from jax import Array, lax, vmap -from dynestyx.models import ContinuousTimeStateEvolution, DynamicalModel -from dynestyx.models.checkers import _resolve_ctse_diffusion_metadata -from dynestyx.models.diffusions import ( - EvaluatedDiffusion, - apply_diffusion, - diffusion_as_matrix, - diffusion_covariance, - evaluate_diffusion, -) +from dynestyx.models import DynamicalModel, StochasticContinuousTimeStateEvolution +from dynestyx.models.diffusions import EvaluatedDiffusion from dynestyx.types import State, Time, TimeLike, as_scalar_time_array @@ -36,61 +29,9 @@ def _early_return_states(x0: State, saveat_times: Array) -> Array: return jnp.broadcast_to(x0, (len(saveat_times),) + jnp.shape(x0)) -def _require_bm_dim(state_evolution: ContinuousTimeStateEvolution) -> int: - """Return Brownian dimension or raise if unspecified. - - Args: - state_evolution: Continuous-time state evolution. - - Returns: - Brownian motion dimension used by EM sampling. - """ - if state_evolution.bm_dim is None: - raise ValueError("SDE sampling requires state_evolution.bm_dim to be set.") - return int(state_evolution.bm_dim) - - -def _require_diffusion_spec( - state_evolution: ContinuousTimeStateEvolution, -) -> Any: - """Get diffusion spec or raise if unavailable. - - Args: - state_evolution: Continuous-time state evolution. - - Returns: - Diffusion callable or constant spec. - """ - diffusion_spec = state_evolution.diffusion_coefficient - if diffusion_spec is None: - raise ValueError("SDE solver requires diffusion_coefficient to be defined.") - return diffusion_spec - - -def _ensure_resolved_diffusion_metadata( - state_evolution: ContinuousTimeStateEvolution, - *, - state_dim: int, - u: Array | None, - t: Array, -) -> None: - """Resolve diffusion metadata for standalone low-level SDE helpers.""" - if state_evolution.diffusion_coefficient is None or ( - state_evolution.diffusion_type is not None - and state_evolution.bm_dim is not None - ): - return - - x0 = jnp.zeros((state_dim,)) - resolved = _resolve_ctse_diffusion_metadata(state_evolution, state_dim, x0, u, t) - if resolved is not None: - resolved_type, resolved_bm_dim = resolved - object.__setattr__(state_evolution, "diffusion_type", resolved_type) - object.__setattr__(state_evolution, "bm_dim", resolved_bm_dim) - - def _em_local_terms( - state_evolution: ContinuousTimeStateEvolution, + state_evolution: StochasticContinuousTimeStateEvolution, + diffusion, x: Array, u: Array | None, t_now: Array, @@ -106,24 +47,8 @@ def _em_local_terms( Returns: Tuple `(drift, diffusion)` at `(x, u, t_now)`. """ - _ensure_resolved_diffusion_metadata( - state_evolution, - state_dim=x.shape[-1], - u=u, - t=t_now, - ) drift = state_evolution.total_drift(x=x, u=u, t=t_now) - diffusion_spec = _require_diffusion_spec(state_evolution) - diffusion = evaluate_diffusion( - diffusion_spec, - diffusion_type=state_evolution.diffusion_type, - bm_dim=state_evolution.bm_dim, - x=x, - u=u, - t=t_now, - state_dim=x.shape[-1], - ) - return drift, diffusion + return drift, diffusion.evaluate(x=x, u=u, t=t_now) def _em_moments_from_terms( @@ -141,7 +66,7 @@ def _em_moments_from_terms( Tuple `(loc, cov)` for the EM Gaussian approximation. """ loc = x + drift * dt - cov = diffusion_covariance(diffusion, state_dim=x.shape[-1]) * dt + cov = diffusion.covariance(state_dim=x.shape[-1]) * dt return loc, cov @@ -170,12 +95,12 @@ def _em_sample_from_terms( key_next, k_step = jr.split(key) z = jr.normal(k_step, shape=(bm_dim,), dtype=jnp.asarray(x).dtype) dw = jnp.sqrt(dt) * z - x_next = x + drift * dt + apply_diffusion(diffusion, dw, state_dim=x.shape[-1]) + x_next = x + drift * dt + diffusion.apply(dw, state_dim=x.shape[-1]) return x_next, key_next def euler_maruyama_integrate_state_to_time( - state_evolution: ContinuousTimeStateEvolution, + state_evolution: StochasticContinuousTimeStateEvolution, x_init: Array, t_init: Time, key_init: Array, @@ -202,7 +127,8 @@ def euler_maruyama_integrate_state_to_time( dt0, dt0 <= 0, f"EM integration requires dt0 > 0, got dt0={dt0!r}." ) - bm_dim = _require_bm_dim(state_evolution) + diffusion = state_evolution.diffusion + bm_dim = state_evolution.bm_dim def _cond_fn(carry): _, t_curr, _, t_end = carry @@ -212,9 +138,11 @@ def _body_fn(carry): x_curr, t_curr, key_curr, t_end = carry h = jnp.minimum(dt0, t_end - t_curr) u_t = control_path_eval(t_curr) if control_path_eval is not None else None - drift, diffusion = _em_local_terms(state_evolution, x_curr, u_t, t_curr) + drift, evaluated_diffusion = _em_local_terms( + state_evolution, diffusion, x_curr, u_t, t_curr + ) x_next, key_next = _em_sample_from_terms( - x_curr, h, drift, diffusion, key=key_curr, bm_dim=bm_dim + x_curr, h, drift, evaluated_diffusion, key=key_curr, bm_dim=bm_dim ) return x_next, t_curr + h, key_next, t_end @@ -224,7 +152,7 @@ def _body_fn(carry): def euler_maruyama_loc_cov( - state_evolution: ContinuousTimeStateEvolution, + state_evolution: StochasticContinuousTimeStateEvolution, x: Array, u: Array | None, t_now: Array, @@ -259,10 +187,13 @@ def euler_maruyama_loc_cov( the time axis to the front as a side effect of `vmap`. """ x_arr = jnp.asarray(x) + diffusion = state_evolution.diffusion def _step_interval(_x, _u, _t_now, _t_next): - drift, diffusion = _em_local_terms(state_evolution, _x, _u, _t_now) - return _em_moments_from_terms(_x, _t_next - _t_now, drift, diffusion) + drift, evaluated_diffusion = _em_local_terms( + state_evolution, diffusion, _x, _u, _t_now + ) + return _em_moments_from_terms(_x, _t_next - _t_now, drift, evaluated_diffusion) if x_arr.ndim == 1: loc, cov = _step_interval(x_arr, u, jnp.asarray(t_now), jnp.asarray(t_next)) @@ -349,9 +280,9 @@ def _solve_sde_scan( """ if key is None: raise ValueError("PRNG key is required for em_scan SDE solves.") - if not isinstance(dynamics.state_evolution, ContinuousTimeStateEvolution): + if not isinstance(dynamics.state_evolution, StochasticContinuousTimeStateEvolution): raise TypeError( - "SDE solver requires ContinuousTimeStateEvolution, got " + "SDE solver requires StochasticContinuousTimeStateEvolution, got " f"{type(dynamics.state_evolution)}" ) @@ -416,13 +347,14 @@ def _solve_sde_diffrax( """ if key is None: raise ValueError("PRNG key is required for diffrax SDE solves.") - if not isinstance(dynamics.state_evolution, ContinuousTimeStateEvolution): + if not isinstance(dynamics.state_evolution, StochasticContinuousTimeStateEvolution): raise TypeError( - "SDE solver requires ContinuousTimeStateEvolution, got " + "SDE solver requires StochasticContinuousTimeStateEvolution, got " f"{type(dynamics.state_evolution)}" ) state_evolution = dynamics.state_evolution + diffusion = state_evolution.diffusion def _drift(t, y, args): u_t = args(t) if args is not None else None @@ -430,17 +362,7 @@ def _drift(t, y, args): def _diffusion(t, y, args): u_t = args(t) if args is not None else None - diffusion_spec = _require_diffusion_spec(state_evolution) - diffusion = evaluate_diffusion( - diffusion_spec, - diffusion_type=state_evolution.diffusion_type, - bm_dim=state_evolution.bm_dim, - x=y, - u=u_t, - t=t, - state_dim=y.shape[-1], - ) - return diffusion_as_matrix(diffusion, state_dim=y.shape[-1]) + return diffusion.as_matrix(x=y, u=u_t, t=t, state_dim=y.shape[-1]) k_bm, _ = jr.split(key, 2) bm = dfx.VirtualBrownianTree( diff --git a/dynestyx/utils.py b/dynestyx/utils.py index bb600ba8..fbc8df6c 100644 --- a/dynestyx/utils.py +++ b/dynestyx/utils.py @@ -9,8 +9,7 @@ from cd_dynamax import ContDiscreteNonlinearSSM as CDNLSSM from jax import Array, lax -from dynestyx.models import ContinuousTimeStateEvolution, DynamicalModel -from dynestyx.models.checkers import _infer_bm_dim +from dynestyx.models import DynamicalModel def flatten_draws(arr: Array) -> Array: @@ -121,28 +120,6 @@ def _has_any_batched_plate_source( return False -def _ensure_continuous_bm_dim(dynamics: DynamicalModel) -> DynamicalModel: - """Infer and set bm_dim when continuous dynamics were constructed in plates.""" - if not dynamics.continuous_time: - return dynamics - - state_evolution = dynamics.state_evolution - if ( - not isinstance(state_evolution, ContinuousTimeStateEvolution) - or state_evolution.diffusion_coefficient is None - or state_evolution.bm_dim is not None - ): - return dynamics - - x0 = jnp.zeros((dynamics.state_dim,)) - u0 = None if dynamics.control_dim == 0 else jnp.zeros((dynamics.control_dim,)) - t0 = jnp.array(0.0) if dynamics.t0 is None else jnp.asarray(dynamics.t0) - inferred_bm_dim = _infer_bm_dim(state_evolution, dynamics.state_dim, x0, u0, t0) - if inferred_bm_dim is not None: - object.__setattr__(state_evolution, "bm_dim", inferred_bm_dim) - return dynamics - - def _should_record_field( record_val: bool | None, shape: tuple[int, ...], max_elems: int ) -> bool: diff --git a/mkdocs.yml b/mkdocs.yml index 68b30d89..f16f5940 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -49,6 +49,7 @@ nav: - Core Models: - DynamicalModel: api_reference/public/models/core/dynamical_model.md - ContinuousTimeStateEvolution: api_reference/public/models/core/continuous_time_state_evolution.md + - Diffusion: api_reference/public/models/core/diffusion.md - DiscreteTimeStateEvolution: api_reference/public/models/core/discrete_time_state_evolution.md - ObservationModel: api_reference/public/models/core/observation_model.md - Drift: api_reference/public/models/core/drift.md diff --git a/tests/models.py b/tests/models.py index 5eb8612f..ab09e4e1 100644 --- a/tests/models.py +++ b/tests/models.py @@ -7,6 +7,7 @@ ContinuousTimeStateEvolution, DiracIdentityObservation, DynamicalModel, + FullDiffusion, LinearGaussianObservation, LinearGaussianStateEvolution, ) @@ -173,7 +174,7 @@ def continuous_time_stochastic_l63_model( ) + (10 * u if u is not None else jnp.zeros(3)) ), - diffusion_coefficient=lambda x, u, t: jnp.eye(3), + diffusion=FullDiffusion(lambda x, u, t: jnp.eye(3)), ), observation_model=LinearGaussianObservation( H=jnp.array([[1.0, 0.0, 0.0]]), R=jnp.array([[1.0**2]]) @@ -229,7 +230,7 @@ def continuous_time_stochastic_l63_model_dirac_obs( ) + (10 * u if u is not None else jnp.zeros_like(x)) ), - diffusion_coefficient=lambda x, u, t: jnp.eye(3), + diffusion=FullDiffusion(lambda x, u, t: jnp.eye(3)), ), observation_model=DiracIdentityObservation(), ) @@ -290,7 +291,7 @@ def continuous_time_LTI_gaussian( ), state_evolution=ContinuousTimeStateEvolution( drift=lambda x, u, t: A @ x + (10 * u if u is not None else jnp.zeros(2)), - diffusion_coefficient=lambda x, u, t: jnp.eye(2), + diffusion=FullDiffusion(lambda x, u, t: jnp.eye(2)), ), observation_model=LinearGaussianObservation( H=jnp.array([[0.0, 1.0]]), R=jnp.array([[1.0**2]]) @@ -543,7 +544,7 @@ def jumpy_controls_model_sde( ): state_evolution = ContinuousTimeStateEvolution( drift=lambda x, u, t: x + u, - diffusion_coefficient=lambda x, u, t: 0.01 * jnp.eye(1), + diffusion=FullDiffusion(lambda x, u, t: 0.01 * jnp.eye(1)), ) dynamics = DynamicalModel( control_dim=1, diff --git a/tests/test_bm_dim_plate.py b/tests/test_bm_dim_plate.py index 9010b30e..6521da44 100644 --- a/tests/test_bm_dim_plate.py +++ b/tests/test_bm_dim_plate.py @@ -5,7 +5,13 @@ import numpyro.distributions as dist import pytest -from dynestyx.models import ContinuousTimeStateEvolution, DynamicalModel +from dynestyx.models import ( + ContinuousTimeStateEvolution, + DiagonalDiffusion, + DynamicalModel, + FullDiffusion, + ScalarDiffusion, +) def _make_diffusion_spec( @@ -15,34 +21,30 @@ def _make_diffusion_spec( sigma=None, ): if diffusion_form == "full": - return jnp.ones((state_dim, 1)), None, None + return FullDiffusion(jnp.ones((state_dim, 1))) if diffusion_form == "diag": - return jnp.ones((state_dim,)), "diag", state_dim + return DiagonalDiffusion(jnp.ones((state_dim,)), bm_dim=state_dim) if diffusion_form == "scalar": - return jnp.array(1.0), "scalar", state_dim + return ScalarDiffusion(jnp.array(1.0), bm_dim=state_dim) if diffusion_form == "callable_full": - return ( + return FullDiffusion( (lambda x, u, t: sigma[..., None, None] * jnp.ones((state_dim, 1))) if sigma is not None - else (lambda x, u, t: jnp.ones((state_dim, 1))), - None, - None, + else (lambda x, u, t: jnp.ones((state_dim, 1))) ) if diffusion_form == "callable_diag": - return ( + return DiagonalDiffusion( (lambda x, u, t: sigma[..., None] * jnp.ones((state_dim,))) if sigma is not None else (lambda x, u, t: jnp.ones((state_dim,))), - "diag", - state_dim, + bm_dim=state_dim, ) if diffusion_form == "callable_scalar": - return ( + return ScalarDiffusion( (lambda x, u, t: sigma[..., None]) if sigma is not None else (lambda x, u, t: jnp.array([1.0])), - "scalar", - state_dim, + bm_dim=state_dim, ) raise ValueError(f"Unknown diffusion form: {diffusion_form}") @@ -56,16 +58,14 @@ def test_bm_dim_resolved_outside_plate(diffusion_form): state_dim = 2 expected_bm_dim = 1 if "full" in diffusion_form else state_dim - diffusion_coefficient, diffusion_type, bm_dim = _make_diffusion_spec( + diffusion = _make_diffusion_spec( diffusion_form, state_dim=state_dim, ) state_evo = ContinuousTimeStateEvolution( drift=lambda x, u, t: -x, - diffusion_coefficient=diffusion_coefficient, - diffusion_type=diffusion_type, - bm_dim=bm_dim, + diffusion=diffusion, ) dynamics = DynamicalModel( initial_condition=dist.MultivariateNormal( @@ -76,8 +76,9 @@ def test_bm_dim_resolved_outside_plate(diffusion_form): x, 0.1 * jnp.eye(state_dim) ), ) - assert dynamics.state_evolution.bm_dim == expected_bm_dim, ( - f"Expected bm_dim={expected_bm_dim}, got {dynamics.state_evolution.bm_dim}" + assert dynamics.state_evolution.diffusion is not None + assert dynamics.state_evolution.diffusion.bm_dim == expected_bm_dim, ( + f"Expected bm_dim={expected_bm_dim}, got {dynamics.state_evolution.diffusion.bm_dim}" ) @@ -94,7 +95,7 @@ def test_bm_dim_resolved_inside_plate(diffusion_form): def model(): with numpyro.plate("trajectories", M): sigma = numpyro.sample("sigma", dist.HalfNormal(1.0)) - diffusion_coefficient, diffusion_type, bm_dim = _make_diffusion_spec( + diffusion = _make_diffusion_spec( diffusion_form, state_dim=state_dim, sigma=sigma, @@ -102,9 +103,7 @@ def model(): state_evo = ContinuousTimeStateEvolution( drift=lambda x, u, t: -x, - diffusion_coefficient=diffusion_coefficient, - diffusion_type=diffusion_type, - bm_dim=bm_dim, + diffusion=diffusion, ) dynamics = DynamicalModel( initial_condition=dist.MultivariateNormal( @@ -115,11 +114,11 @@ def model(): x, 0.1 * jnp.eye(state_dim) ), ) - assert dynamics.state_evolution.bm_dim is not None, ( + assert dynamics.state_evolution.diffusion is not None, ( "bm_dim should not be None after DynamicalModel construction in plate" ) - assert dynamics.state_evolution.bm_dim == expected_bm_dim, ( - f"Expected bm_dim={expected_bm_dim}, got {dynamics.state_evolution.bm_dim}" + assert dynamics.state_evolution.diffusion.bm_dim == expected_bm_dim, ( + f"Expected bm_dim={expected_bm_dim}, got {dynamics.state_evolution.diffusion.bm_dim}" ) with numpyro.handlers.seed(rng_seed=0): diff --git a/tests/test_discretizers.py b/tests/test_discretizers.py index 61881a4b..05dc2067 100644 --- a/tests/test_discretizers.py +++ b/tests/test_discretizers.py @@ -17,9 +17,12 @@ from dynestyx.inference.filters import Filter from dynestyx.models import ( ContinuousTimeStateEvolution, + DiagonalDiffusion, DiracIdentityObservation, DynamicalModel, + FullDiffusion, GaussianStateEvolution, + ScalarDiffusion, ) from dynestyx.models.observations import LinearGaussianObservation from dynestyx.solvers import euler_maruyama_loc_cov @@ -27,57 +30,68 @@ def _ctse_1d_zero_drift_unit_diffusion() -> ContinuousTimeStateEvolution: - return ContinuousTimeStateEvolution( + cte = ContinuousTimeStateEvolution( drift=lambda x, u, t: jnp.zeros_like(x), - diffusion_coefficient=lambda x, u, t: jnp.ones((1, 1)), - bm_dim=1, + diffusion=FullDiffusion(lambda x, u, t: jnp.ones((1, 1)), bm_dim=1), ) + dynamics = DynamicalModel( + initial_condition=dist.MultivariateNormal(jnp.zeros(1), jnp.eye(1)), + state_evolution=cte, + observation_model=LinearGaussianObservation( + H=jnp.array([[1.0]]), + R=jnp.array([[1.0]]), + ), + control_dim=0, + ) + assert isinstance(dynamics.state_evolution, ContinuousTimeStateEvolution) + return dynamics.state_evolution def _ctse_2d_zero_drift(diffusion_form: str) -> ContinuousTimeStateEvolution: if diffusion_form == "full": - return ContinuousTimeStateEvolution( + cte = ContinuousTimeStateEvolution( drift=lambda x, u, t: jnp.zeros_like(x), - diffusion_coefficient=jnp.eye(2), - diffusion_type="full", - bm_dim=2, + diffusion=FullDiffusion(jnp.eye(2), bm_dim=2), ) - if diffusion_form == "diag": - return ContinuousTimeStateEvolution( + elif diffusion_form == "diag": + cte = ContinuousTimeStateEvolution( drift=lambda x, u, t: jnp.zeros_like(x), - diffusion_coefficient=jnp.ones((2,)), - diffusion_type="diag", - bm_dim=2, + diffusion=DiagonalDiffusion(jnp.ones((2,)), bm_dim=2), ) - if diffusion_form == "scalar": - return ContinuousTimeStateEvolution( + elif diffusion_form == "scalar": + cte = ContinuousTimeStateEvolution( drift=lambda x, u, t: jnp.zeros_like(x), - diffusion_coefficient=jnp.array(1.0), - diffusion_type="scalar", - bm_dim=2, + diffusion=ScalarDiffusion(jnp.array(1.0), bm_dim=2), ) - if diffusion_form == "callable_full": - return ContinuousTimeStateEvolution( + elif diffusion_form == "callable_full": + cte = ContinuousTimeStateEvolution( drift=lambda x, u, t: jnp.zeros_like(x), - diffusion_coefficient=lambda x, u, t: jnp.eye(2), - diffusion_type="full", - bm_dim=2, + diffusion=FullDiffusion(lambda x, u, t: jnp.eye(2), bm_dim=2), ) - if diffusion_form == "callable_diag": - return ContinuousTimeStateEvolution( + elif diffusion_form == "callable_diag": + cte = ContinuousTimeStateEvolution( drift=lambda x, u, t: jnp.zeros((2,)), - diffusion_coefficient=lambda x, u, t: jnp.ones((2,)), - diffusion_type="diag", - bm_dim=2, + diffusion=DiagonalDiffusion(lambda x, u, t: jnp.ones((2,)), bm_dim=2), ) - if diffusion_form == "callable_scalar": - return ContinuousTimeStateEvolution( + elif diffusion_form == "callable_scalar": + cte = ContinuousTimeStateEvolution( drift=lambda x, u, t: jnp.zeros_like(x), - diffusion_coefficient=lambda x, u, t: jnp.array(1.0), - diffusion_type="scalar", - bm_dim=2, + diffusion=ScalarDiffusion(lambda x, u, t: jnp.array(1.0), bm_dim=2), ) - raise ValueError(f"Unknown diffusion form: {diffusion_form}") + else: + raise ValueError(f"Unknown diffusion form: {diffusion_form}") + + dynamics = DynamicalModel( + initial_condition=dist.MultivariateNormal(jnp.zeros(2), jnp.eye(2)), + state_evolution=cte, + observation_model=LinearGaussianObservation( + H=jnp.eye(2), + R=jnp.eye(2), + ), + control_dim=0, + ) + assert isinstance(dynamics.state_evolution, ContinuousTimeStateEvolution) + return dynamics.state_evolution def test_euler_maruyama_returns_gaussian_state_evolution_with_callable_cov(): diff --git a/tests/test_filters.py b/tests/test_filters.py index 45f2ca96..57192ed6 100644 --- a/tests/test_filters.py +++ b/tests/test_filters.py @@ -21,7 +21,7 @@ from dynestyx.inference.integrations.cuthbert.discrete import ( run_discrete_filter as run_cuthbert_discrete_filter, ) -from dynestyx.models import ContinuousTimeStateEvolution, DynamicalModel +from dynestyx.models import ContinuousTimeStateEvolution, DynamicalModel, FullDiffusion from dynestyx.simulators import DiscreteTimeSimulator from tests.fixtures import ( _squeeze_sim_dims, @@ -102,7 +102,7 @@ def model(): initial_condition=dist.LogNormal(loc=jnp.zeros(1), scale=jnp.ones(1)), state_evolution=ContinuousTimeStateEvolution( drift=lambda x, u, t: -0.3 * jnp.sin(x), - diffusion_coefficient=lambda x, u, t: 0.1 * jnp.eye(1), + diffusion=FullDiffusion(lambda x, u, t: 0.1 * jnp.eye(1)), ), observation_model=lambda x, u, t: dist.Poisson(rate=jnp.exp(x[0] + bias)), ) diff --git a/tests/test_hierarchical_simulator_discretizer_smokes.py b/tests/test_hierarchical_simulator_discretizer_smokes.py index 4b20a9ba..6749f046 100644 --- a/tests/test_hierarchical_simulator_discretizer_smokes.py +++ b/tests/test_hierarchical_simulator_discretizer_smokes.py @@ -30,6 +30,7 @@ ContinuousTimeStateEvolution, DiracIdentityObservation, DynamicalModel, + FullDiffusion, GaussianStateEvolution, LinearGaussianObservation, ) @@ -132,9 +133,7 @@ def _plate_continuous_ode_model( initial_condition=dist.MultivariateNormal( loc=jnp.zeros(2), covariance_matrix=jnp.eye(2) ), - state_evolution=ContinuousTimeStateEvolution( - drift=drift, diffusion_coefficient=None - ), + state_evolution=ContinuousTimeStateEvolution(drift=drift), observation_model=LinearGaussianObservation( H=jnp.array([[1.0, 0.0]]), R=jnp.array([[0.25]]) ), @@ -558,7 +557,7 @@ def _plate_continuous_dirac_for_discretizer_model( loc=jnp.zeros(2), covariance_matrix=jnp.eye(2) ), state_evolution=ContinuousTimeStateEvolution( - drift=AffineDrift(A=A), diffusion_coefficient=lambda x, u, t: L + drift=AffineDrift(A=A), diffusion=FullDiffusion(lambda x, u, t: L) ), observation_model=DiracIdentityObservation(), ) @@ -593,7 +592,7 @@ def _nested_plate_continuous_dirac_for_discretizer_model( loc=jnp.zeros(2), covariance_matrix=jnp.eye(2) ), state_evolution=ContinuousTimeStateEvolution( - drift=AffineDrift(A=A), diffusion_coefficient=lambda x, u, t: L + drift=AffineDrift(A=A), diffusion=FullDiffusion(lambda x, u, t: L) ), observation_model=DiracIdentityObservation(), ) diff --git a/tests/test_hierarchical_simulator_inference_smokes.py b/tests/test_hierarchical_simulator_inference_smokes.py index 9eeb46d0..5105592a 100644 --- a/tests/test_hierarchical_simulator_inference_smokes.py +++ b/tests/test_hierarchical_simulator_inference_smokes.py @@ -123,9 +123,7 @@ def _hierarchical_ode_model( initial_condition=dist.MultivariateNormal( loc=jnp.zeros(2), covariance_matrix=jnp.eye(2) ), - state_evolution=ContinuousTimeStateEvolution( - drift=drift, diffusion_coefficient=None - ), + state_evolution=ContinuousTimeStateEvolution(drift=drift), observation_model=LinearGaussianObservation( H=jnp.array([[0.0, 1.0]]), R=jnp.eye(1) ), diff --git a/tests/test_models_core.py b/tests/test_models_core.py index eb0904a6..0fe4896b 100644 --- a/tests/test_models_core.py +++ b/tests/test_models_core.py @@ -11,12 +11,17 @@ dsx_to_cd_dynamax, gaussian_to_nlgssm_params, ) -from dynestyx.models.core import ContinuousTimeStateEvolution, DynamicalModel +from dynestyx.models.core import ( + ContinuousTimeStateEvolution, + DeterministicContinuousTimeStateEvolution, + DynamicalModel, + StochasticContinuousTimeStateEvolution, +) from dynestyx.models.diffusions import ( - DiffusionType, - diffusion_as_matrix, - diffusion_covariance, - evaluate_diffusion, + DiagonalDiffusion, + Diffusion, + FullDiffusion, + ScalarDiffusion, ) from dynestyx.simulators import DiscreteTimeSimulator @@ -243,14 +248,14 @@ def test_categorical_state_override_incompatible_raises() -> None: def test_continuous_state_evolution_infers_bm_dim() -> None: state_evolution = ContinuousTimeStateEvolution( drift=lambda x, u, t: x, - diffusion_coefficient=lambda x, u, t: jnp.eye(2, 3), + diffusion=FullDiffusion(lambda x, u, t: jnp.eye(2, 3)), ) def observation_model(x, u, t): del u, t return dist.MultivariateNormal(loc=x, covariance_matrix=jnp.eye(2)) - _ = DynamicalModel( + dynamics = DynamicalModel( initial_condition=dist.MultivariateNormal( loc=jnp.zeros(2), covariance_matrix=jnp.eye(2), @@ -260,21 +265,21 @@ def observation_model(x, u, t): control_dim=0, ) - assert state_evolution.bm_dim == 3 + assert isinstance(dynamics.state_evolution, StochasticContinuousTimeStateEvolution) + assert dynamics.state_evolution.diffusion.bm_dim == 3 def test_continuous_state_evolution_bm_dim_override_compatible() -> None: state_evolution = ContinuousTimeStateEvolution( drift=lambda x, u, t: x, - diffusion_coefficient=lambda x, u, t: jnp.eye(2, 3), - bm_dim=3, + diffusion=FullDiffusion(lambda x, u, t: jnp.eye(2, 3), bm_dim=3), ) def observation_model(x, u, t): del u, t return dist.MultivariateNormal(loc=x, covariance_matrix=jnp.eye(2)) - _ = DynamicalModel( + dynamics = DynamicalModel( initial_condition=dist.MultivariateNormal( loc=jnp.zeros(2), covariance_matrix=jnp.eye(2), @@ -284,14 +289,14 @@ def observation_model(x, u, t): control_dim=0, ) - assert state_evolution.bm_dim == 3 + assert isinstance(dynamics.state_evolution, StochasticContinuousTimeStateEvolution) + assert dynamics.state_evolution.diffusion.bm_dim == 3 def test_continuous_state_evolution_bm_dim_override_mismatch_raises() -> None: state_evolution = ContinuousTimeStateEvolution( drift=lambda x, u, t: x, - diffusion_coefficient=lambda x, u, t: jnp.eye(2, 3), - bm_dim=2, + diffusion=FullDiffusion(lambda x, u, t: jnp.eye(2, 3), bm_dim=2), ) def observation_model(x, u, t): @@ -299,7 +304,7 @@ def observation_model(x, u, t): return dist.MultivariateNormal(loc=x, covariance_matrix=jnp.eye(2)) with pytest.raises( - ValueError, match="bm_dim does not match inferred diffusion_coefficient" + ValueError, match="bm_dim does not match inferred diffusion output shape" ): DynamicalModel( initial_condition=dist.MultivariateNormal( @@ -312,77 +317,51 @@ def observation_model(x, u, t): ) -def test_continuous_state_evolution_bm_dim_without_diffusion_raises() -> None: +def test_continuous_state_evolution_without_diffusion_is_allowed() -> None: state_evolution = ContinuousTimeStateEvolution( drift=lambda x, u, t: x, - bm_dim=2, ) def observation_model(x, u, t): del u, t return dist.MultivariateNormal(loc=x, covariance_matrix=jnp.eye(2)) - with pytest.raises( - ValueError, match="bm_dim cannot be set when diffusion_coefficient" - ): - DynamicalModel( - initial_condition=dist.MultivariateNormal( - loc=jnp.zeros(2), - covariance_matrix=jnp.eye(2), - ), - state_evolution=state_evolution, - observation_model=observation_model, - control_dim=0, - ) + dynamics = DynamicalModel( + initial_condition=dist.MultivariateNormal( + loc=jnp.zeros(2), + covariance_matrix=jnp.eye(2), + ), + state_evolution=state_evolution, + observation_model=observation_model, + control_dim=0, + ) + + assert isinstance( + dynamics.state_evolution, DeterministicContinuousTimeStateEvolution + ) def test_continuous_state_evolution_requires_explicit_bm_dim_for_diag_diffusion() -> ( None ): - state_evolution = ContinuousTimeStateEvolution( - drift=lambda x, u, t: x, - diffusion_coefficient=jnp.ones((2,)), - ) - - with pytest.raises(ValueError, match="diag diffusion requires explicit bm_dim"): - DynamicalModel( - initial_condition=dist.MultivariateNormal( - loc=jnp.zeros(2), - covariance_matrix=jnp.eye(2), - ), - state_evolution=state_evolution, - observation_model=_observation_model_2d, - control_dim=0, - ) + with pytest.raises(ValueError, match="Diagonal diffusion requires explicit bm_dim"): + DiagonalDiffusion(jnp.ones((2,)), bm_dim=None) # type: ignore[arg-type] def test_continuous_state_evolution_requires_explicit_bm_dim_for_scalar_diffusion() -> ( None ): - state_evolution = ContinuousTimeStateEvolution( - drift=lambda x, u, t: x, - diffusion_coefficient=jnp.array(0.3), - ) - - with pytest.raises(ValueError, match="scalar diffusion requires explicit bm_dim"): - DynamicalModel( - initial_condition=dist.MultivariateNormal( - loc=jnp.zeros(2), - covariance_matrix=jnp.eye(2), - ), - state_evolution=state_evolution, - observation_model=_observation_model_2d, - control_dim=0, - ) + with pytest.raises(ValueError, match="Scalar diffusion requires explicit bm_dim"): + ScalarDiffusion(jnp.array(0.3), bm_dim=None) # type: ignore[arg-type] def test_continuous_state_evolution_rejects_invalid_shorthand_trailing_dim() -> None: state_evolution = ContinuousTimeStateEvolution( drift=lambda x, u, t: x, - diffusion_coefficient=jnp.ones((3,)), + diffusion=DiagonalDiffusion(jnp.ones((3,)), bm_dim=2), ) - with pytest.raises(ValueError, match="treated as scalar/diagonal shorthand"): + with pytest.raises(ValueError, match="Diagonal diffusion must have trailing shape"): DynamicalModel( initial_condition=dist.MultivariateNormal( loc=jnp.zeros(2), @@ -396,108 +375,81 @@ def test_continuous_state_evolution_rejects_invalid_shorthand_trailing_dim() -> @pytest.mark.parametrize( ( - "diffusion_coefficient", - "diffusion_type", - "bm_dim", + "diffusion", "expected_matrix", "expected_cov", ), [ ( - jnp.array(0.5), - "scalar", - 1, + ScalarDiffusion(jnp.array(0.5), bm_dim=1), 0.5 * jnp.ones((2, 1)), 0.25 * jnp.ones((2, 2)), ), ( - jnp.array(0.5), - "scalar", - 2, + ScalarDiffusion(jnp.array(0.5), bm_dim=2), 0.5 * jnp.eye(2), 0.25 * jnp.eye(2), ), ( - jnp.array([0.2, 0.4]), - "diag", - 1, + DiagonalDiffusion(jnp.array([0.2, 0.4]), bm_dim=1), jnp.array([[0.2], [0.4]]), jnp.array([[0.04, 0.08], [0.08, 0.16]]), ), ( - jnp.array([0.2, 0.4]), - "diag", - 2, + DiagonalDiffusion(jnp.array([0.2, 0.4]), bm_dim=2), jnp.diag(jnp.array([0.2, 0.4])), jnp.diag(jnp.array([0.04, 0.16])), ), ], ) def test_diffusion_helpers_preserve_shorthand_semantics( - diffusion_coefficient, - diffusion_type, - bm_dim, + diffusion, expected_matrix, expected_cov, ) -> None: - evaluated = evaluate_diffusion( - diffusion_coefficient, - diffusion_type=diffusion_type, - bm_dim=bm_dim, - x=jnp.zeros(2), - u=None, - t=jnp.array(0.0), - state_dim=2, - ) + evaluated = diffusion.evaluate(x=jnp.zeros(2), u=None, t=jnp.array(0.0)) assert jnp.allclose( - diffusion_as_matrix(evaluated, state_dim=2), + evaluated.as_matrix(state_dim=2), expected_matrix, ) assert jnp.allclose( - diffusion_covariance(evaluated, state_dim=2), + evaluated.covariance(state_dim=2), expected_cov, ) @pytest.mark.parametrize("callable_form", ["scalar", "diag", "full"]) def test_diffusion_helpers_support_callable_shorthands(callable_form: str) -> None: - diffusion_type: DiffusionType + diffusion: Diffusion if callable_form == "scalar": - diffusion_coefficient = lambda x, u, t: 0.5 + 0.0 * t - diffusion_type = "scalar" - bm_dim = 2 + diffusion = ScalarDiffusion(lambda x, u, t: 0.5 + 0.0 * t, bm_dim=2) expected = 0.5 * jnp.eye(2) elif callable_form == "diag": - diffusion_coefficient = lambda x, u, t: jnp.array([0.2, 0.4]) + 0.0 * t - diffusion_type = "diag" - bm_dim = 2 + diffusion = DiagonalDiffusion( + lambda x, u, t: jnp.array([0.2, 0.4]) + 0.0 * t, + bm_dim=2, + ) expected = jnp.diag(jnp.array([0.2, 0.4])) else: - diffusion_coefficient = lambda x, u, t: jnp.eye(2) * (1.0 + 0.0 * t) - diffusion_type = "full" - bm_dim = 2 + diffusion = FullDiffusion(lambda x, u, t: jnp.eye(2) * (1.0 + 0.0 * t)) + diffusion = diffusion.resolve_metadata( + state_dim=2, + x_probe=jnp.zeros(2), + u_probe=None, + t_probe=jnp.array(1.0), + ) expected = jnp.eye(2) - evaluated = evaluate_diffusion( - diffusion_coefficient, - diffusion_type=diffusion_type, - bm_dim=bm_dim, - x=jnp.zeros(2), - u=None, - t=jnp.array(1.0), - state_dim=2, - ) + evaluated = diffusion.evaluate(x=jnp.zeros(2), u=None, t=jnp.array(1.0)) - assert jnp.allclose(diffusion_as_matrix(evaluated, state_dim=2), expected) + assert jnp.allclose(evaluated.as_matrix(state_dim=2), expected) def test_cd_dynamax_rejects_diffusion_with_bm_dim_exceeds_state_dim() -> None: - state_evolution = ContinuousTimeStateEvolution( + state_evolution = StochasticContinuousTimeStateEvolution( drift=lambda x, u, t: x, - diffusion_coefficient=jnp.ones((1, 2)), - diffusion_type="full", - bm_dim=2, + diffusion=FullDiffusion(jnp.ones((1, 2)), bm_dim=2), ) with pytest.raises(ValueError, match="bm_dim <= state_dim"): _normalize_cd_dynamax_diffusion(state_evolution, state_dim=1)( @@ -512,9 +464,7 @@ def test_continuous_cd_dynamax_rejects_diffusion_with_bm_dim_exceeds_state_dim_e ): state_evolution = ContinuousTimeStateEvolution( drift=lambda x, u, t: x, - diffusion_coefficient=jnp.ones((1, 2)), - diffusion_type="full", - bm_dim=2, + diffusion=FullDiffusion(jnp.ones((1, 2)), bm_dim=2), ) dynamics = DynamicalModel( initial_condition=dist.MultivariateNormal( @@ -535,15 +485,15 @@ def test_continuous_cd_dynamax_rejects_diffusion_with_bm_dim_exceeds_state_dim_e dsx_to_cd_dynamax(dynamics) -def test_discrete_state_evolution_bm_dim_override_raises() -> None: +def test_discrete_state_evolution_diffusion_override_raises() -> None: def state_evolution(x, u, t_now, t_next): del u, t_now, t_next return dist.MultivariateNormal(loc=x, covariance_matrix=jnp.eye(2)) - state_evolution.bm_dim = 2 # type: ignore[attr-defined] + state_evolution.diffusion = ScalarDiffusion(0.1, bm_dim=2) # type: ignore[attr-defined] with pytest.raises( - ValueError, match="bm_dim can only be set for continuous-time models" + ValueError, match="diffusion can only be set for continuous-time models" ): DynamicalModel( initial_condition=_initial_condition_2d(), diff --git a/tests/test_science/test_discreteTime_generic.py b/tests/test_science/test_discreteTime_generic.py index 31444a61..ea73b6b7 100644 --- a/tests/test_science/test_discreteTime_generic.py +++ b/tests/test_science/test_discreteTime_generic.py @@ -31,14 +31,17 @@ def test_mcmc_inference(data_conditioned_discrete_time_l63, num_samples): # noq if SAVE_FIG and OUTPUT_DIR is not None: import matplotlib.pyplot as plt + states = synthetic["states"] + observations = synthetic["observations"] + plt.plot( - obs_times.squeeze(0), - synthetic["states"].squeeze(0)[:, 0], + obs_times, + states if states.ndim == 1 else states[:, 0], label="x[0]", ) plt.plot( - obs_times.squeeze(0), - synthetic["observations"].squeeze(0)[:, 0], + obs_times, + observations if observations.ndim == 1 else observations[:, 0], label="observations", linestyle="--", ) diff --git a/tests/test_science/test_discreteTime_generic_auto.py b/tests/test_science/test_discreteTime_generic_auto.py index 6aa0b7a0..d881e78d 100644 --- a/tests/test_science/test_discreteTime_generic_auto.py +++ b/tests/test_science/test_discreteTime_generic_auto.py @@ -31,14 +31,17 @@ def test_mcmc_inference(data_conditioned_discrete_time_l63_auto, num_samples): if SAVE_FIG and OUTPUT_DIR is not None: import matplotlib.pyplot as plt + states = synthetic["states"] + observations = synthetic["observations"] + plt.plot( - obs_times.squeeze(0), - synthetic["states"].squeeze(0)[:, 0], + obs_times, + states if states.ndim == 1 else states[:, 0], label="x[0]", ) plt.plot( - obs_times.squeeze(0), - synthetic["observations"].squeeze(0)[:, 0], + obs_times, + observations if observations.ndim == 1 else observations[:, 0], label="observations", linestyle="--", ) diff --git a/tests/test_science/test_discrete_time_l63_mcmc.py b/tests/test_science/test_discrete_time_l63_mcmc.py index c2e4d186..959dbd74 100644 --- a/tests/test_science/test_discrete_time_l63_mcmc.py +++ b/tests/test_science/test_discrete_time_l63_mcmc.py @@ -34,14 +34,17 @@ def test_mcmc_inference(data_conditioned_discrete_time_l63_filter, num_samples): if SAVE_FIG and OUTPUT_DIR is not None: import matplotlib.pyplot as plt + states = synthetic["states"] + observations = synthetic["observations"] + plt.plot( - obs_times.squeeze(0), - synthetic["states"].squeeze(0)[:, 0], + obs_times, + states if states.ndim == 1 else states[:, 0], label="x[0]", ) plt.plot( - obs_times.squeeze(0), - synthetic["observations"].squeeze(0)[:, 0], + obs_times, + observations if observations.ndim == 1 else observations[:, 0], label="observations", linestyle="--", ) diff --git a/tests/test_science/test_discrete_time_l63_svi_pf.py b/tests/test_science/test_discrete_time_l63_svi_pf.py index 1504432f..6c3bd9e6 100644 --- a/tests/test_science/test_discrete_time_l63_svi_pf.py +++ b/tests/test_science/test_discrete_time_l63_svi_pf.py @@ -36,14 +36,17 @@ def test_svi_inference(data_conditioned_discrete_time_l63_filter_pf, num_steps): if SAVE_FIG and OUTPUT_DIR is not None: import matplotlib.pyplot as plt + states = synthetic["states"] + observations = synthetic["observations"] + plt.plot( - obs_times.squeeze(0), - synthetic["states"].squeeze(0)[:, 0], + obs_times, + states if states.ndim == 1 else states[:, 0], label="x[0]", ) plt.plot( - obs_times.squeeze(0), - synthetic["observations"].squeeze(0)[:, 0], + obs_times, + observations if observations.ndim == 1 else observations[:, 0], label="observations", linestyle="--", ) diff --git a/tests/test_science/test_hmm.py b/tests/test_science/test_hmm.py index d78d889f..130a72b4 100644 --- a/tests/test_science/test_hmm.py +++ b/tests/test_science/test_hmm.py @@ -27,9 +27,9 @@ def test_mcmc_inference(data_conditioned_hmm, num_samples): # noqa: F811 if SAVE_FIG and OUTPUT_DIR is not None: plot_hmm_states_and_observations( - times=obs_times.squeeze(0), - x=synthetic["states"].squeeze(0), - y=synthetic["observations"].squeeze(0), + times=obs_times, + x=synthetic["states"], + y=synthetic["observations"], save_path=OUTPUT_DIR / "data_generation.png", ) diff --git a/tests/test_science/test_l63_ODE_mcmc.py b/tests/test_science/test_l63_ODE_mcmc.py index f91cdc77..37476a59 100644 --- a/tests/test_science/test_l63_ODE_mcmc.py +++ b/tests/test_science/test_l63_ODE_mcmc.py @@ -37,14 +37,17 @@ def test_mcmc_inference( if SAVE_FIG and OUTPUT_DIR is not None: import matplotlib.pyplot as plt + states = synthetic["states"] + observations = synthetic["observations"] + plt.plot( - obs_times.squeeze(0), - synthetic["states"].squeeze(0)[:, 0], + obs_times, + states if states.ndim == 1 else states[:, 0], label="x[0]", ) plt.plot( - obs_times.squeeze(0), - synthetic["observations"].squeeze(0)[:, 0], + obs_times, + observations if observations.ndim == 1 else observations[:, 0], label="observations", linestyle="--", ) diff --git a/tests/test_science/test_l63_SDE_mcmc.py b/tests/test_science/test_l63_SDE_mcmc.py index bc6d8b4e..cf67de30 100644 --- a/tests/test_science/test_l63_SDE_mcmc.py +++ b/tests/test_science/test_l63_SDE_mcmc.py @@ -37,14 +37,17 @@ def test_mcmc_inference(data_conditioned_continuous_time_stochastic_l63, num_sam if SAVE_FIG and OUTPUT_DIR is not None: import matplotlib.pyplot as plt + states = synthetic["states"] + observations = synthetic["observations"] + plt.plot( - obs_times.squeeze(0), - synthetic["states"].squeeze(0)[:, 0], + obs_times, + states if states.ndim == 1 else states[:, 0], label="x[0]", ) plt.plot( - obs_times.squeeze(0), - synthetic["observations"].squeeze(0)[:, 0], + obs_times, + observations if observations.ndim == 1 else observations[:, 0], label="observations", linestyle="--", ) diff --git a/tests/test_science/test_l63_mcmc_dpf.py b/tests/test_science/test_l63_mcmc_dpf.py index 8cc70995..fe531e5f 100644 --- a/tests/test_science/test_l63_mcmc_dpf.py +++ b/tests/test_science/test_l63_mcmc_dpf.py @@ -29,14 +29,17 @@ def test_mcmc_inference(data_conditioned_continuous_time_l63_dpf, num_samples): if SAVE_FIG and OUTPUT_DIR is not None: import matplotlib.pyplot as plt + states = synthetic["states"] + observations = synthetic["observations"] + plt.plot( - obs_times.squeeze(0), - synthetic["states"].squeeze(0)[:, 0], + obs_times, + states if states.ndim == 1 else states[:, 0], label="x[0]", ) plt.plot( - obs_times.squeeze(0), - synthetic["observations"].squeeze(0)[:, 0], + obs_times, + observations if observations.ndim == 1 else observations[:, 0], label="observations", linestyle="--", ) diff --git a/tests/test_science/test_lti_continuous_simplified.py b/tests/test_science/test_lti_continuous_simplified.py index d8130e52..529e71fe 100644 --- a/tests/test_science/test_lti_continuous_simplified.py +++ b/tests/test_science/test_lti_continuous_simplified.py @@ -40,19 +40,22 @@ def test_mcmc_inference( if SAVE_FIG and OUTPUT_DIR is not None: import matplotlib.pyplot as plt + states = synthetic["states"] + observations = synthetic["observations"] + plt.plot( obs_times, - synthetic["states"][:, 0], + states[:, 0], label="x[0]", ) plt.plot( obs_times, - synthetic["states"][:, 1], + states[:, 1], label="x[1]", ) plt.plot( obs_times, - synthetic["observations"][:, 0], + observations if observations.ndim == 1 else observations[:, 0], label="observations", linestyle="--", ) diff --git a/tests/test_science/test_lti_discrete_simplified.py b/tests/test_science/test_lti_discrete_simplified.py index bb8aaaad..e7715a06 100644 --- a/tests/test_science/test_lti_discrete_simplified.py +++ b/tests/test_science/test_lti_discrete_simplified.py @@ -40,19 +40,22 @@ def test_mcmc_inference( if SAVE_FIG and OUTPUT_DIR is not None: import matplotlib.pyplot as plt + states = synthetic["states"] + observations = synthetic["observations"] + plt.plot( - obs_times.squeeze(0), - synthetic["states"].squeeze(0)[:, 0], + obs_times, + states[:, 0], label="x[0]", ) plt.plot( - obs_times.squeeze(0), - synthetic["states"].squeeze(0)[:, 1], + obs_times, + states[:, 1], label="x[1]", ) plt.plot( - obs_times.squeeze(0), - synthetic["observations"].squeeze(0)[:, 0], + obs_times, + observations if observations.ndim == 1 else observations[:, 0], label="observations", linestyle="--", ) diff --git a/tests/test_science/test_lti_gaussian.py b/tests/test_science/test_lti_gaussian.py index a603a616..5ec6c061 100644 --- a/tests/test_science/test_lti_gaussian.py +++ b/tests/test_science/test_lti_gaussian.py @@ -36,19 +36,22 @@ def test_mcmc_inference(data_conditioned_continuous_time_lti_gaussian, num_sampl if SAVE_FIG and OUTPUT_DIR is not None: import matplotlib.pyplot as plt + states = synthetic["states"] + observations = synthetic["observations"] + plt.plot( - obs_times.squeeze(0), - synthetic["states"].squeeze(0)[:, 0], + obs_times, + states[:, 0], label="x[0]", ) plt.plot( - obs_times.squeeze(0), - synthetic["states"].squeeze(0)[:, 1], + obs_times, + states[:, 1], label="x[1]", ) plt.plot( - obs_times.squeeze(0), - synthetic["observations"].squeeze(0)[:, 0], + obs_times, + observations if observations.ndim == 1 else observations[:, 0], label="observations", linestyle="--", ) diff --git a/tests/test_science/test_lti_gaussian_dpf.py b/tests/test_science/test_lti_gaussian_dpf.py index eeac060d..f564796e 100644 --- a/tests/test_science/test_lti_gaussian_dpf.py +++ b/tests/test_science/test_lti_gaussian_dpf.py @@ -33,19 +33,22 @@ def test_mcmc_inference(data_conditioned_continuous_time_lti_gaussian_dpf, num_s if SAVE_FIG and OUTPUT_DIR is not None: import matplotlib.pyplot as plt + states = synthetic["states"] + observations = synthetic["observations"] + plt.plot( - obs_times.squeeze(0), - synthetic["states"].squeeze(0)[:, 0], + obs_times, + states[:, 0], label="x[0]", ) plt.plot( - obs_times.squeeze(0), - synthetic["states"].squeeze(0)[:, 1], + obs_times, + states[:, 1], label="x[1]", ) plt.plot( - obs_times.squeeze(0), - synthetic["observations"].squeeze(0)[:, 0], + obs_times, + observations if observations.ndim == 1 else observations[:, 0], label="observations", linestyle="--", ) diff --git a/tests/test_science/test_nonlinear_discretized_hierarchical_multitraj_ekf.py b/tests/test_science/test_nonlinear_discretized_hierarchical_multitraj_ekf.py index efdd2360..82bae61d 100644 --- a/tests/test_science/test_nonlinear_discretized_hierarchical_multitraj_ekf.py +++ b/tests/test_science/test_nonlinear_discretized_hierarchical_multitraj_ekf.py @@ -16,7 +16,7 @@ from dynestyx.discretizers import Discretizer from dynestyx.inference.filter_configs import EKFConfig from dynestyx.inference.filters import Filter -from dynestyx.models import ContinuousTimeStateEvolution, DynamicalModel +from dynestyx.models import ContinuousTimeStateEvolution, DynamicalModel, FullDiffusion from dynestyx.models.observations import LinearGaussianObservation from dynestyx.simulators import DiscreteTimeSimulator from tests.test_utils import get_output_dir @@ -43,7 +43,7 @@ def _make_ct_nonlinear_dynamics(beta: jnp.ndarray) -> DynamicalModel: initial_condition=dist.MultivariateNormal(jnp.zeros(1), 0.35 * jnp.eye(1)), state_evolution=ContinuousTimeStateEvolution( drift=_PlateNonlinearDrift(beta=beta), - diffusion_coefficient=lambda x, u, t: jnp.sqrt(0.06) * jnp.eye(1), + diffusion=FullDiffusion(lambda x, u, t: jnp.sqrt(0.06) * jnp.eye(1)), ), observation_model=LinearGaussianObservation( H=jnp.array([[1.0]]), diff --git a/tests/test_science/test_ode_hierarchical_simulator_inference.py b/tests/test_science/test_ode_hierarchical_simulator_inference.py index f48d122b..b751e318 100644 --- a/tests/test_science/test_ode_hierarchical_simulator_inference.py +++ b/tests/test_science/test_ode_hierarchical_simulator_inference.py @@ -64,7 +64,6 @@ def hierarchical_ode_model( ), state_evolution=ContinuousTimeStateEvolution( drift=_DampedNonlinearOscillatorDrift(alpha=alpha), - diffusion_coefficient=None, ), observation_model=LinearGaussianObservation( H=jnp.eye(2), R=(0.05**2) * jnp.eye(2) From 20d1d37e72686d7a9e205e29cc515f21b4827c34 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Sun, 10 May 2026 21:23:30 -0400 Subject: [PATCH 10/28] dont use cast, just assert bm_dim is not None (fight w linter...could also push it up with a new resolvedDiffusion class) --- dynestyx/models/core.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/dynestyx/models/core.py b/dynestyx/models/core.py index 7f88859d..b0c1c6b3 100644 --- a/dynestyx/models/core.py +++ b/dynestyx/models/core.py @@ -1,7 +1,7 @@ """Core interfaces and base classes for dynamical models.""" from collections.abc import Callable -from typing import Any, Protocol, cast +from typing import Any, Protocol import equinox as eqx import jax @@ -428,7 +428,7 @@ def __init__( class StochasticContinuousTimeStateEvolution(ContinuousTimeStateEvolution): """Refined continuous-time state evolution with resolved diffusion.""" - diffusion: Diffusion = eqx.field(static=True, default=cast(Diffusion, None)) + diffusion: Diffusion = eqx.field(static=True, kw_only=True) def __init__( self, @@ -450,7 +450,9 @@ def __init__( @property def bm_dim(self) -> int: - return cast(int, self.diffusion.bm_dim) + bm_dim = self.diffusion.bm_dim + assert bm_dim is not None + return bm_dim class DiscreteTimeStateEvolution(eqx.Module): From bc41705375be3ae713f74db5d845807e14fe260e Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Thu, 14 May 2026 11:48:23 -0400 Subject: [PATCH 11/28] please lint --- dynestyx/utils.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/dynestyx/utils.py b/dynestyx/utils.py index fd51fc07..7490ad41 100644 --- a/dynestyx/utils.py +++ b/dynestyx/utils.py @@ -169,8 +169,6 @@ def _has_any_batched_plate_source( return False - - def _should_record_field( record_val: bool | None, shape: tuple[int, ...], max_elems: int ) -> bool: From 3f37300d702068eb141c7f190f607e92132a87f0 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Thu, 14 May 2026 13:30:02 -0400 Subject: [PATCH 12/28] rename as gram --- dynestyx/models/diffusions.py | 18 ++++++++++-------- dynestyx/solvers/sde.py | 2 +- tests/test_models_core.py | 2 +- 3 files changed, 12 insertions(+), 10 deletions(-) diff --git a/dynestyx/models/diffusions.py b/dynestyx/models/diffusions.py index 066576ea..7fb752c1 100644 --- a/dynestyx/models/diffusions.py +++ b/dynestyx/models/diffusions.py @@ -26,8 +26,9 @@ class EvaluatedDiffusion(NamedTuple): def as_matrix(self, *, state_dim: int) -> Array: return self.diffusion._value_as_matrix(self.value, state_dim=state_dim) - def covariance(self, *, state_dim: int) -> Array: - return self.diffusion._value_covariance(self.value, state_dim=state_dim) + def gram_matrix(self, *, state_dim: int) -> Array: + """Return the diffusion Gram matrix ``L L^T`` at the evaluated point.""" + return self.diffusion._value_gram_matrix(self.value, state_dim=state_dim) def apply(self, dw: Array, *, state_dim: int) -> Array: return self.diffusion._apply_value(self.value, dw, state_dim=state_dim) @@ -98,7 +99,7 @@ def as_matrix( ) -> Array: return self.evaluate(x=x, u=u, t=t).as_matrix(state_dim=state_dim) - def covariance( + def gram_matrix( self, *, x: State, @@ -106,7 +107,8 @@ def covariance( t: Time, state_dim: int, ) -> Array: - return self.evaluate(x=x, u=u, t=t).covariance(state_dim=state_dim) + """Return the diffusion Gram matrix ``L(x,u,t) L(x,u,t)^T``.""" + return self.evaluate(x=x, u=u, t=t).gram_matrix(state_dim=state_dim) def apply( self, @@ -136,7 +138,7 @@ def _validate_init(self) -> None: def _value_as_matrix(self, value: Array, *, state_dim: int) -> Array: raise NotImplementedError - def _value_covariance(self, value: Array, *, state_dim: int) -> Array: + def _value_gram_matrix(self, value: Array, *, state_dim: int) -> Array: raise NotImplementedError def _apply_value(self, value: Array, dw: Array, *, state_dim: int) -> Array: @@ -189,7 +191,7 @@ def resolve_metadata( def _value_as_matrix(self, value: Array, *, state_dim: int) -> Array: return value - def _value_covariance(self, value: Array, *, state_dim: int) -> Array: + def _value_gram_matrix(self, value: Array, *, state_dim: int) -> Array: return value @ jnp.swapaxes(value, -1, -2) def _apply_value(self, value: Array, dw: Array, *, state_dim: int) -> Array: @@ -245,7 +247,7 @@ def _value_as_matrix(self, value: Array, *, state_dim: int) -> Array: return value[..., :, None] return value[..., :, None] * jnp.eye(state_dim, dtype=value.dtype) - def _value_covariance(self, value: Array, *, state_dim: int) -> Array: + def _value_gram_matrix(self, value: Array, *, state_dim: int) -> Array: assert self.bm_dim is not None if self.bm_dim == 1: return value[..., :, None] * value[..., None, :] @@ -313,7 +315,7 @@ def _value_as_matrix(self, value: Array, *, state_dim: int) -> Array: ) return scalar[..., None, None] * jnp.eye(state_dim, dtype=value.dtype) - def _value_covariance(self, value: Array, *, state_dim: int) -> Array: + def _value_gram_matrix(self, value: Array, *, state_dim: int) -> Array: sigma_sq = jnp.square(self._scalar_value(value)) assert self.bm_dim is not None if self.bm_dim == 1: diff --git a/dynestyx/solvers/sde.py b/dynestyx/solvers/sde.py index cc1a2958..ddd04c5d 100644 --- a/dynestyx/solvers/sde.py +++ b/dynestyx/solvers/sde.py @@ -66,7 +66,7 @@ def _em_moments_from_terms( Tuple `(loc, cov)` for the EM Gaussian approximation. """ loc = x + drift * dt - cov = diffusion.covariance(state_dim=x.shape[-1]) * dt + cov = diffusion.gram_matrix(state_dim=x.shape[-1]) * dt return loc, cov diff --git a/tests/test_models_core.py b/tests/test_models_core.py index 0fe4896b..1da23b26 100644 --- a/tests/test_models_core.py +++ b/tests/test_models_core.py @@ -414,7 +414,7 @@ def test_diffusion_helpers_preserve_shorthand_semantics( expected_matrix, ) assert jnp.allclose( - evaluated.covariance(state_dim=2), + evaluated.gram_matrix(state_dim=2), expected_cov, ) From 657a1903c50b798af35239a85960e1538e84d2f6 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Thu, 14 May 2026 13:40:06 -0400 Subject: [PATCH 13/28] rename func to _coerce_to_param_dtype --- .../cd_dynamax/continuous_filter.py | 28 ++++++++++--------- .../cd_dynamax/discrete_filter.py | 22 +++++++-------- 2 files changed, 26 insertions(+), 24 deletions(-) diff --git a/dynestyx/inference/integrations/cd_dynamax/continuous_filter.py b/dynestyx/inference/integrations/cd_dynamax/continuous_filter.py index bd5100de..cd15a416 100644 --- a/dynestyx/inference/integrations/cd_dynamax/continuous_filter.py +++ b/dynestyx/inference/integrations/cd_dynamax/continuous_filter.py @@ -39,12 +39,16 @@ ) -def _inexact_tree_dtype(tree, fallback) -> jax.typing.DTypeLike: - """Return a representative inexact dtype from a pytree of parameters.""" - for leaf in jax.tree.leaves(tree): +def _coerce_to_param_dtype(params, *arrays): + """Cast arrays to the first inexact dtype found in a parameter pytree.""" + dtype = None + for leaf in jax.tree.leaves(params): if isinstance(leaf, jax.Array) and jnp.issubdtype(leaf.dtype, jnp.inexact): - return leaf.dtype - return fallback + dtype = leaf.dtype + break + if dtype is None: + return arrays + return tuple(jnp.asarray(arr, dtype=dtype) for arr in arrays) def _config_to_cd_dynamax_filter_kwargs( @@ -163,10 +167,9 @@ def _run_linear_kf( ) -> PosteriorGSSMFiltered: """Run exact continuous-discrete KF (AffineLinearDrift + constant diffusion + LinearGaussianObservation).""" params = dsx_to_cdlgssm_params(dynamics) - dtype = _inexact_tree_dtype(params, obs_values.dtype) - obs_times = jnp.asarray(obs_times, dtype=dtype) - obs_values = jnp.asarray(obs_values, dtype=dtype) - ctrl_values = jnp.asarray(ctrl_values, dtype=dtype) + obs_times, obs_values, ctrl_values = _coerce_to_param_dtype( + params, obs_times, obs_values, ctrl_values + ) cd_model = ContDiscreteLinearGaussianSSM( state_dim=dynamics.state_dim, emission_dim=dynamics.observation_dim, @@ -232,10 +235,9 @@ def compute_continuous_filter( ) params, _ = dsx_to_cd_dynamax(dynamics, cd_model=cd_dynamax_model) - dtype = _inexact_tree_dtype(params, obs_values.dtype) - obs_values = jnp.asarray(obs_values, dtype=dtype) - obs_times_arr = jnp.asarray(obs_times_arr, dtype=dtype) - ctrl_vals = jnp.asarray(ctrl_vals, dtype=dtype) + obs_values, obs_times_arr, ctrl_vals = _coerce_to_param_dtype( + params, obs_values, obs_times_arr, ctrl_vals + ) filter_kwargs = _config_to_cd_dynamax_filter_kwargs( filter_config, params, obs_values, obs_times_arr, ctrl_vals, key ) diff --git a/dynestyx/inference/integrations/cd_dynamax/discrete_filter.py b/dynestyx/inference/integrations/cd_dynamax/discrete_filter.py index 0690830b..c7e74638 100644 --- a/dynestyx/inference/integrations/cd_dynamax/discrete_filter.py +++ b/dynestyx/inference/integrations/cd_dynamax/discrete_filter.py @@ -35,12 +35,16 @@ from dynestyx.utils import _should_record_field -def _inexact_tree_dtype(tree, fallback) -> jax.typing.DTypeLike: - """Return a representative inexact dtype from a pytree of parameters.""" - for leaf in jax.tree.leaves(tree): +def _coerce_to_param_dtype(params, *arrays): + """Cast arrays to the first inexact dtype found in a parameter pytree.""" + dtype = None + for leaf in jax.tree.leaves(params): if isinstance(leaf, jax.Array) and jnp.issubdtype(leaf.dtype, jnp.inexact): - return leaf.dtype - return fallback + dtype = leaf.dtype + break + if dtype is None: + return arrays + return tuple(jnp.asarray(arr, dtype=dtype) for arr in arrays) def _lti_to_lgssm_params(dynamics: DynamicalModel): @@ -113,16 +117,12 @@ def compute_cd_dynamax_discrete_filter( if isinstance(filter_config, KFConfig): params = _lti_to_lgssm_params(dynamics) - dtype = _inexact_tree_dtype(params, emissions.dtype) - emissions = jnp.asarray(emissions, dtype=dtype) - inputs = jnp.asarray(inputs, dtype=dtype) + emissions, inputs = _coerce_to_param_dtype(params, emissions, inputs) return lgssm_filter(params, emissions, inputs=inputs) # EKF and UKF share the same nonlinear params representation. params_nl = gaussian_to_nlgssm_params(dynamics) - dtype = _inexact_tree_dtype(params_nl, emissions.dtype) - emissions = jnp.asarray(emissions, dtype=dtype) - inputs = jnp.asarray(inputs, dtype=dtype) + emissions, inputs = _coerce_to_param_dtype(params_nl, emissions, inputs) if isinstance(filter_config, EKFConfig): return extended_kalman_filter(params_nl, emissions, inputs=inputs) From 958a2a730079e6eda694a611270e82e2d88c0465 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Thu, 14 May 2026 14:55:20 -0400 Subject: [PATCH 14/28] simplify edit to Quick example --- docs/quick_example.ipynb | 524 +++++++++++++++++++-------------------- 1 file changed, 262 insertions(+), 262 deletions(-) diff --git a/docs/quick_example.ipynb b/docs/quick_example.ipynb index 5b34c480..6a72a506 100644 --- a/docs/quick_example.ipynb +++ b/docs/quick_example.ipynb @@ -1,277 +1,277 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Quick Example: Lorenz 63\n", - "\n", - "This notebook demonstrates simulation and inference on **Lorenz 63** with **partial, noisy observations**. We infer both the dynamics parameter $\\rho$ and the observation noise standard deviation $\\sigma_{\\text{obs}}$." - ] - }, - { - "cell_type": "markdown", - "id": "deff97e0", - "metadata": {}, - "source": [ - "## Setup and model\n", - "\n", - "Lorenz 63: \n", - "\n", - "$dx = f(x)\\,dt + dW$ with\n", - "$$f(x) = \\begin{pmatrix} \\sigma(x_2 - x_1) \\\\ x_1(\\rho - x_3) - x_2 \\\\ x_1 x_2 - \\beta x_3 \\end{pmatrix}.$$\n", - "\n", - "We observe **only $x_1$** with Gaussian noise: \n", - "\n", - "$y_t = Hx(t) + \\varepsilon_t = x_1(t) + \\varepsilon_t$, $\\varepsilon_t \\sim \\mathcal{N}(0, \\sigma_{\\text{obs}}^2).$\n", - "\n", - "\n", - "We fix $\\sigma=10$, $\\beta=8/3$. Here $H := [1, 0, 0]$ to observe the first component.\n", - "\n", - "Priors on the inferred parameters:\n", - "- $\\rho \\sim \\text{Uniform}(10, 40)$\n", - "- $\\sigma_{\\text{obs}} \\sim \\text{LogNormal}(0, 0.5)$\n", - "\n", - "Our goal is to recover the posterior $p(\\rho, \\sigma \\mid y_1, \\dots, y_T)$.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "474da346", - "metadata": {}, - "outputs": [], - "source": [ - "import jax.numpy as jnp\n", - "import jax.random as jr\n", - "import numpyro\n", - "import numpyro.distributions as dist\n", - "from dynestyx import (\n", - " ContinuousTimeStateEvolution, DynamicalModel, FullDiffusion,\n", - " LinearGaussianObservation, SDESimulator, Filter,\n", - " sample,\n", - ")\n", - "from numpyro.infer import Predictive, MCMC, NUTS\n", - "\n", - "def l63_model(rho=None, obs_std=None, diff_std=None, obs_times=None, obs_values=None):\n", - " # define priors\n", - " rho = numpyro.sample(\"rho\", dist.Uniform(10.0, 40.0), obs=rho)\n", - " obs_std = numpyro.sample(\"obs_std\", dist.LogNormal(0.0, 0.5), obs=obs_std)\n", - " diff_std = numpyro.sample(\"diff_std\", dist.LogNormal(0.0, 0.5), obs=diff_std)\n", - "\n", - " # define the model components\n", - " state_dim = 3\n", - " initial_condition = dist.MultivariateNormal(\n", - " loc=jnp.zeros(state_dim), covariance_matrix=20.0**2 * jnp.eye(state_dim)\n", - " )\n", - " observation_model = LinearGaussianObservation(\n", - " H=jnp.array([[1.0, 0.0, 0.0]]),\n", - " R=jnp.array([[obs_std**2]]),\n", - " )# observe only x1 with Gaussian noise\n", - " state_evolution = ContinuousTimeStateEvolution(\n", - " drift=lambda x, u, t: jnp.array([\n", - " 10.0 * (x[1] - x[0]),\n", - " x[0] * (rho - x[2]) - x[1],\n", - " x[0] * x[1] - (8.0 / 3.0) * x[2],\n", - " ]),\n", - " diffusion=FullDiffusion(diff_std * jnp.eye(state_dim)),\n", - " )\n", - " \n", - " # define the model\n", - " dynamics = DynamicalModel(\n", - " initial_condition=initial_condition,\n", - " state_evolution=state_evolution,\n", - " observation_model=observation_model,\n", - " )\n", - " \n", - " # sample the model\n", - " sample(\"f\", dynamics, obs_times=obs_times, obs_values=obs_values)" - ] - }, - { - "cell_type": "markdown", - "id": "94a91967", - "metadata": {}, - "source": [ - "## Simulation" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "d891349e", - "metadata": {}, - "outputs": [], - "source": [ - "key = jr.PRNGKey(0)\n", - "rho_true, obs_std_true, diff_std_true = 28.0, 1.0, 1.0\n", - "times = jnp.arange(0.0, 20.0, 0.05)\n", - "\n", - "with SDESimulator():\n", - " samples = Predictive(l63_model, num_samples=1)(jr.PRNGKey(1), rho=rho_true, obs_std=obs_std_true, predict_times=times)\n", - "\n", - "states = samples[\"f_states\"][0]\n", - "observations = samples[\"f_observations\"][0]\n", - "times_arr = samples[\"f_times\"][0]" - ] - }, - { - "cell_type": "markdown", - "id": "57ce3cbc", - "metadata": {}, - "source": [ - "## Plot" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "03a43c82", - "metadata": {}, - "outputs": [ + "cells": [ { - "data": { - "image/png": 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", - "text/plain": [ - "
" + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Quick Example: Lorenz 63\n", + "\n", + "This notebook demonstrates simulation and inference on **Lorenz 63** with **partial, noisy observations**. We infer both the dynamics parameter $\\rho$ and the observation noise standard deviation $\\sigma_{\\text{obs}}$." ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "fig, axes = plt.subplots(2, 1, figsize=(9, 4), sharex=True)\n", - "axes[0].plot(times_arr, states[:, 0], label=\"$x_1$\")\n", - "axes[0].plot(times_arr, states[:, 1], label=\"$x_2$\")\n", - "axes[0].plot(times_arr, states[:, 2], label=\"$x_3$\")\n", - "axes[0].set_ylabel(\"state\")\n", - "axes[0].legend(loc=\"upper right\")\n", - "axes[1].scatter(times_arr, observations[:, 0], s=4, alpha=0.7, label=\"obs ($x_1$ + noise)\")\n", - "axes[1].plot(times_arr, states[:, 0], color=\"C0\", alpha=0.5, ls=\"--\", label=\"true $x_1$\")\n", - "axes[1].set_ylabel(\"observation\")\n", - "axes[1].set_xlabel(\"time\")\n", - "axes[1].legend(loc=\"upper right\")\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "05aad6f0", - "metadata": {}, - "source": [ - "## Inference" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "cf579407", - "metadata": {}, - "outputs": [ + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "sample: 100%|██████████| 200/200 [06:13<00:00, 1.87s/it, 7 steps of size 5.87e-01. acc. prob=0.93] \n" - ] - } - ], - "source": [ - "# Observed data: times and values\n", - "obs_times = times_arr\n", - "obs_values = observations\n", - "\n", - "# Tells the model to marginalize over the latent states using a filter\n", - "# Default is Ensemble Kalman Filter (EnKF) for SDEs with linear Gaussian observation model\n", - "from dynestyx.inference.filters import ContinuousTimeEnKFConfig\n", - "with Filter(filter_config=ContinuousTimeEnKFConfig(warn=False)): \n", - " # Run NUTS with MCMC. The below is simple numpyro code.\n", - " mcmc = MCMC(NUTS(l63_model), num_warmup=100, num_samples=100)\n", - " mcmc.run(jr.PRNGKey(2), obs_times=obs_times, obs_values=obs_values)" - ] - }, - { - "cell_type": "markdown", - "id": "d2dccf59", - "metadata": {}, - "source": [ - "## Posterior" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "d1357ec7", - "metadata": {}, - "outputs": [ + "cell_type": "markdown", + "id": "deff97e0", + "metadata": {}, + "source": [ + "## Setup and model\n", + "\n", + "Lorenz 63: \n", + "\n", + "$dx = f(x)\\,dt + dW$ with\n", + "$$f(x) = \\begin{pmatrix} \\sigma(x_2 - x_1) \\\\ x_1(\\rho - x_3) - x_2 \\\\ x_1 x_2 - \\beta x_3 \\end{pmatrix}.$$\n", + "\n", + "We observe **only $x_1$** with Gaussian noise: \n", + "\n", + "$y_t = Hx(t) + \\varepsilon_t = x_1(t) + \\varepsilon_t$, $\\varepsilon_t \\sim \\mathcal{N}(0, \\sigma_{\\text{obs}}^2).$\n", + "\n", + "\n", + "We fix $\\sigma=10$, $\\beta=8/3$. Here $H := [1, 0, 0]$ to observe the first component.\n", + "\n", + "Priors on the inferred parameters:\n", + "- $\\rho \\sim \\text{Uniform}(10, 40)$\n", + "- $\\sigma_{\\text{obs}} \\sim \\text{LogNormal}(0, 0.5)$\n", + "\n", + "Our goal is to recover the posterior $p(\\rho, \\sigma \\mid y_1, \\dots, y_T)$.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "474da346", + "metadata": {}, + "outputs": [], + "source": [ + "import jax.numpy as jnp\n", + "import jax.random as jr\n", + "import numpyro\n", + "import numpyro.distributions as dist\n", + "from dynestyx import (\n", + " ContinuousTimeStateEvolution, DynamicalModel, FullDiffusion,\n", + " LinearGaussianObservation, SDESimulator, Filter,\n", + " sample,\n", + ")\n", + "from numpyro.infer import Predictive, MCMC, NUTS\n", + "\n", + "def l63_model(rho=None, obs_std=None, diff_std=None, obs_times=None, obs_values=None):\n", + " # define priors\n", + " rho = numpyro.sample(\"rho\", dist.Uniform(10.0, 40.0), obs=rho)\n", + " obs_std = numpyro.sample(\"obs_std\", dist.LogNormal(0.0, 0.5), obs=obs_std)\n", + " diff_std = numpyro.sample(\"diff_std\", dist.LogNormal(0.0, 0.5), obs=diff_std)\n", + "\n", + " # define the model components\n", + " state_dim = 3\n", + " initial_condition = dist.MultivariateNormal(\n", + " loc=jnp.zeros(state_dim), covariance_matrix=20.0**2 * jnp.eye(state_dim)\n", + " )\n", + " observation_model = LinearGaussianObservation(\n", + " H=jnp.array([[1.0, 0.0, 0.0]]),\n", + " R=jnp.array([[obs_std**2]]),\n", + " )# observe only x1 with Gaussian noise\n", + " state_evolution = ContinuousTimeStateEvolution(\n", + " drift=lambda x, u, t: jnp.array([\n", + " 10.0 * (x[1] - x[0]),\n", + " x[0] * (rho - x[2]) - x[1],\n", + " x[0] * x[1] - (8.0 / 3.0) * x[2],\n", + " ]),\n", + " diffusion=FullDiffusion(diff_std * jnp.eye(state_dim)),\n", + " )\n", + " \n", + " # define the model\n", + " dynamics = DynamicalModel(\n", + " initial_condition=initial_condition,\n", + " state_evolution=state_evolution,\n", + " observation_model=observation_model,\n", + " )\n", + " \n", + " # sample the model\n", + " sample(\"f\", dynamics, obs_times=obs_times, obs_values=obs_values)" + ] + }, { - "data": { - "image/png": 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", - "text/plain": [ - "
" + "cell_type": "markdown", + "id": "94a91967", + "metadata": {}, + "source": [ + "## Simulation" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "image/png": 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", - "text/plain": [ - "
" + "cell_type": "code", + "execution_count": 2, + "id": "d891349e", + "metadata": {}, + "outputs": [], + "source": [ + "key = jr.PRNGKey(0)\n", + "rho_true, obs_std_true, diff_std_true = 28.0, 1.0, 1.0\n", + "times = jnp.arange(0.0, 20.0, 0.05)\n", + "\n", + "with SDESimulator():\n", + " samples = Predictive(l63_model, num_samples=1)(jr.PRNGKey(1), rho=rho_true, obs_std=obs_std_true, predict_times=times)\n", + "\n", + "states = samples[\"f_states\"][0]\n", + "observations = samples[\"f_observations\"][0]\n", + "times_arr = samples[\"f_times\"][0]" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "image/png": 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", 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" + "cell_type": "markdown", + "id": "57ce3cbc", + "metadata": {}, + "source": [ + "## Plot" ] - }, - "metadata": {}, - "output_type": "display_data" + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "03a43c82", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axes = plt.subplots(2, 1, figsize=(9, 4), sharex=True)\n", + "axes[0].plot(times_arr, states[:, 0], label=\"$x_1$\")\n", + "axes[0].plot(times_arr, states[:, 1], label=\"$x_2$\")\n", + "axes[0].plot(times_arr, states[:, 2], label=\"$x_3$\")\n", + "axes[0].set_ylabel(\"state\")\n", + "axes[0].legend(loc=\"upper right\")\n", + "axes[1].scatter(times_arr, observations[:, 0], s=4, alpha=0.7, label=\"obs ($x_1$ + noise)\")\n", + "axes[1].plot(times_arr, states[:, 0], color=\"C0\", alpha=0.5, ls=\"--\", label=\"true $x_1$\")\n", + "axes[1].set_ylabel(\"observation\")\n", + "axes[1].set_xlabel(\"time\")\n", + "axes[1].legend(loc=\"upper right\")\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "05aad6f0", + "metadata": {}, + "source": [ + "## Inference" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "cf579407", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "sample: 100%|██████████| 200/200 [06:13<00:00, 1.87s/it, 7 steps of size 5.87e-01. acc. prob=0.93] \n" + ] + } + ], + "source": [ + "# Observed data: times and values\n", + "obs_times = times_arr\n", + "obs_values = observations\n", + "\n", + "# Tells the model to marginalize over the latent states using a filter\n", + "# Default is Ensemble Kalman Filter (EnKF) for SDEs with linear Gaussian observation model\n", + "from dynestyx.inference.filters import ContinuousTimeEnKFConfig\n", + "with Filter(filter_config=ContinuousTimeEnKFConfig(warn=False)): \n", + " # Run NUTS with MCMC. The below is simple numpyro code.\n", + " mcmc = MCMC(NUTS(l63_model), num_warmup=100, num_samples=100)\n", + " mcmc.run(jr.PRNGKey(2), obs_times=obs_times, obs_values=obs_values)" + ] + }, + { + "cell_type": "markdown", + "id": "d2dccf59", + "metadata": {}, + "source": [ + "## Posterior" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "d1357ec7", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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daNu2LT755BPUqlVL3f7++290794dP/74I958803069cPYWFhKrCViYIrVqxQ6RRpnT17Fs8//zymT5+OM2fOqOC5bt26OHDggAqOx4wZc8W2yEixBMjBwcG4++671S02NhaLFy9Gy5YtVZ50ZiQQl+eSDwS33347brvtNvU8sk3vvfcefIXJJJMlw2AyARu+SMaWH1h7m4j8CydIElHAWb4yEUeOulCwkIaoE8Dvv/+OevXqYdOmTSpVQqxbtw6DBw/GyJEj1Qiy5Cjfeuut6menTp1SI9+ffvopevXqhVKlSqn75fF79+5VaRb9+/eHTbq3ACrw7tSpE1auXKlGzu+///7UbenWrZsKlCMiIlLvS05OViPn7777LpYtW6aC/oy++uorNG7cGBMnTkx9Htl+Wd/8+fPVKHxaL730ErZu3Zqj/SQj/c2aNYO7Va1iwYstg9XrMm58HD5aZ0VQEPPnicg/MNgmooBy8pQTCxcZtZ07tAvB+HEyumpSQXVKoC0kDURGnQ8dOoQuXbqkBtripptuUmkfMuK9bds2FWzv2bMHmzdvVo+ToFvWmaJw4cJqVFsC9HfeeSddsC3Bd0YSPA8ZMgTvv/++GrnOLNgODw/HsGHDUgNt0bBhQ1SqVAn79u3D0aNHcfPNN6f+rH79+ihZsmSO9lXp0qWRV7p3DcWGjUnqQ9CbyxPQqcPl14KIyJcx2CaigDJtRjwSEoHatS14sIFVBdsShN5yyy3pHifBcokSJXD+/HmVOpJRymh2VFSU+vr999+nBrxpA+0U1apVU8H8rl27rviZjJRLUC1pIJJCIpM3hdVqxcGDBzP9O6pXr44CBQpccX/ZsmVVsC3blTbY7tixI7xZWJiGvn3CMHBwLBYvScCTTYJQvJjZ05tFRHTDGGwTUcD49Tc7Pl+fDE0DXhsUBk2LSR2pzozkaGf185RRcEn5EMeOHVNfZ8yYoW5ZSXl8CkkTmTZtGux2e47+lmLFil11mzM+jy9o/JgNa96z4NffHJg6LR7TplxOrSEi8lUMtokoILhcOsZPNCYbPtMsCNWqWnD0qPGzzEai09IkOr/m+o2ydTJZMbvpFzt27FA515KvLWkmd955J4oUKZKaGiIj6ikj5xlda5szWrRokRo5z4lnnnlGTfDMK7KfhwwKw7MtLqrJks89a8ddd1rz7PmJiNyBwTYRBYRPP0vG33udiIjQ0LN77ucDp4w0SxpJu3btsvU7X375pfoqXRklnzstKSsoEytzy5YtW3I8QVKC/7wMtkWVyhY892wQVr+bhAmT4rD23XywWDhZkoh8F4NtIgqIUn+z5xmTIl95OQQFC+Z+1dN7770Xs2bNUgF0doPtlDramaWpbNiwITV3OzdIqUJf0aObTJZMxj/7jc6SL7YK8fQmERFdN9bZJiK/987qRJw44cJNRU14qVWwW55DanNLwP3bb79h1KhRaqJjRlK7+7vvvks3mVFIne20Odv79+9XTW0CVf58Jrx66erD3NcTcPYsO0sSke/iyDYR+bWL0S4sXJKglrt3DUFwsPtSEqZMmYL27dtj1apVqgZ3lSpVULRoURV4S/3tEydOqBrcKaX/pIa1TJD85ptvVNdIKRt48eJFVU7woYceUpVLUiZeegspkfjXX3+pZak/Lr799lvVJTPFmjVrbvh5mjcLwpq1idjztxOz5sRj9MjwG14nEZEnMNgmIr+2ZGkCoqN1VChvxlNPBrn1uQoVKqSa30iw+dlnn6na29IwR+psS6lAaSwjjWhSSOk+GdWWIF0CbCn/J+X6evbsiVdeeQUPP/wwvM2///6LnTt3prtPyiPKLTeZzcZkyZfaRmPdh0l49plg3FqDb1lE5Hs0PTeTAomIvMiJk0483uQCpArevNkR+N8DlxvAkG8YNCQGn3yWrALtVSsiVXt3IiJfwpxtIvJbc+clqEC77u0WPHA/S8j5or69wyAlzXf96cBHHyd5enOIiHKMwTYR+aV9/zjw0SdGcNa3V2i2amWT9ylSxIQunYzJkjNmxSMmhpMlici3MNgmIr80c1Y8JEmu0cM21KzJUW1f9mKrYNxS1oSz53TMW2BMdiUi8hUMtonI72zbbsfmLXZYLECvHrnfwIbyls2qYdAAow39qncSsX+/gy8BEfkMBttE5Fdkzve0GUYDm2eaB6FMGbOnN4lywX332vBQAyucTmD8pLhcbfhDRORODLaJyK988WWymkwnk+pScn3JPwzoF4agIOCXrQ71OhMR+QIG20TkN+x2HTPnGKPaL7cJQeFCPMX5k5tvNuOVl43W7ZOnxSM+nqPbROT9+E5ERH5j7bokHD7sQqGCGtq0NoIy8i8SbJcoYcLJky4sfoOTJYnI+zHYJiK/kJCgY8EiY1S7c6dQhIWy1J8/Cg7WMLCfkR607M0EHDrs9PQmERFdFYNtIvILb7+TiDNndNxc0qQmRpL/euhBG+6pZ4XdDkyaEufpzSEiuioG20Tk86KjXVi6zEgp6NYlVJWKI/8lDYoGDwpTpR03f2fH5u84WZKIvBeDbSLyeW8uT0R0tI7y5cxo/LjN05tDeaDcLWa81CpYLU+cEofkZE6WJCLvxGCbiHza2bMuLF9pjGr37B4Cs5mj2oGic8cQFCmiqUmxb61I9PTmEBFlisE2Efk0qUiRkABUr25WubwUOMLDTejby+gsuXBRPE6c5GRJIvI+DLaJyGcdP+HE6neNEU1pyy65vBRYnmhsw211LEhIBKZNN6rREBF5EwbbROSzFixKUBUp7qhrwd31rJ7eHPIA+YA1ZFAYTCZg/cZk/LLVzteBiLwKg20i8kkHDzrx4UdJavlVjmoHtKpVLHjuWaPc44RJcaqTKBGRt2CwTUQ+ae7r8XA6gQfut6JObY5qB7oe3UKRP7+Gf/Y7sXoNJ0sSkfdgsE1EPufvvQ6s32DUVu7Z3egmSIEtfz6TusIh5s5PwJmzLk9vEhGRwmCbiHzO7LnGRLjHHrWhSmWLpzeHvETzpkGoXs2M2FgdM2dxsiQReQcG20TkU37fIR0D7TCbge5dOKpNl0mN9dcGG6UAP/goCX/8wcmSROR5DLaJvISu6+pGV99Hs+YYI5ZPPxWEsmXN3F2UTq2aVjz9pDFZcuzEOLhc/J8iIs9isE3kJUGk65up6saAO2s//WzHtu0O2GxAl04hefgKkS/p3SsU4eEadu92Yt2HRsUaIiJPYbBN5A2cydDPHFA3WaYryYeQmZdGtVs8F4zixTiqTZkrXMiEbl2MD2MzZ8fjYjQnSxKR5zDYJiKfsOmrZDVSGRoKdHiFo9p0dS88H4zy5cw4f17H3HkJ3F1E5DEMtonI6zmdOmZfCphavxiCggV56qKrs1qNzpJC6m7v3efgLiMij+A7FhF5vU8/T8aBA05ERmpo2zrY05tDPqLeXVY80sgGlwsYNyGO8yGIyCMYbBORV0u265g338jVbt8uBBERPG1R9vXrE4qQYODX3xz4bD3nQxBR3uO7FhF5tffXJeHYcRcKF9bQsgVHtSlnShQ3o0N7I8d/yrQ4RHOyJBHlMQbbROS1EhJ0LFhkjGp37hiKkBDN05tEPujlNiG4pawJZ87omHWp+ygRUV5hsE1EXmvV6kQVIJUsYULzZkajEqKcstk0DHstXC2/u4adJYkobzHYJiKvFBPjwpI3jAok3bqGwmblqDZdv7vutOKpJ4MgTVpHjImD3c7OkkSUNxhsE5FXenN5IqKjdZQrZ8YTj9s8vTnkB/r3CUW+fBr27XNi5apET28OEQUIBttE5HXOnnXhrRXGqHbPbiEwmzmqTTeuQAGTCriFVLg5ftzJ3UpEbsdgm4i8jqSPJCQA1auZ0fAhjmpT7nn6qSDUvd2ChERgLGtvE1EeYLBNRF7lxEmn6vgnenYPhaZxVJtyjxxPw4eGwWIBNn9nx6avWHubiNyLwTYReZUFixKQnAzcUdeCe++xenpzyA+VL2fBKy8btbfHT4xDbKzL05tERH6MwTYReY1Dh5z44MMktcxRbXKnju1DUKqUCaejdMyZZ8wPICJyBwbbROQ15r4eD6cTeKC+FbfV4ag2uU9wsIbhr4Wp5bffScSfux3c3UTkFgy2icgr/L3Xgc/XG/mzPbobFSOI3Omeu21o/LhN1d4eNSYWDgdrbxNR7mOwTUReYc48o432Y4/YULWKxdObQwFiQL8wREZo+GuPEyvfZu1tIsp9DLaJyON27LTj2812mExGt0iivFK4kAl9L9XenjM/HocOs/Y2EeUuBttE5FG6rmPmbGNU++kng3BLWTNfEcpTzZsG4a47LUhMBEaMioXLxXQSIso9DLaJyKN+/sWObdsdsFqBLp2McmxEeV17e9SIcAQHQx2La9cZFXGIiHIDg20i8opR7eefDUaJEhzVJs8odbNZlZsU02bE4+QpppMQUe5gsE1EHvP1N3b8uduJkGCgQ3uOapNnvdgyGDVvtSA2VsfosXHqwyAR0Y1isE1EHuF0SjMRY1T7pRdD1EQ1Ik8ymzWMGXm5lfvnG9jKnYhuHN/diMgj1m9Ixj/7narsWts2wXwVyCtUqGBB547GVZYJk+Jw7hxbuRPRjWGwTUR5zm7XMXe+Mard7uUQ5IvkqYi8xyvtQlCpohnnz+uYMDnO05tDRD6O73BElOc++DAJR466UKighlYvcFSbvIvNqmHMqHBV9126mn7zLdNJiOj6MdgmojyVmKjj9YXGqHanDiEIDdX4CpDXqVHdgjatjQ+Co8fGIiaG6SREdH0YbBNRnlr9biJOR+koXtyEZ5/hqDZ5r+5dQlG6tEkdr1NnGB8QiYhyisE2EeWZ2FgXFr+RoJa7dQ6BzcZRbfJewcFSnSRcLa99P0k1YCIiyikG20SUZ5avTMSFCzpuKWtCkyeCuOfJ69W93YrnnzOO1ZGjYxEfz9rbRJQzDLaJKE+cP+/Cm8sT1XKPbqGwWDiqTb6hz6uhKFbMpCb1plTRISLKLgbbRJQnli5LQFycjiqVzXi4oY17nXxGeLgJI4aGqeUVbydi5x9MJyGi7GOwTURud+qUE6tWG6Par/YIhcnEUW3yLffXt6FJYxtcLmDI0FgkJDCdhIiyh8E2EbndwsUJSEoC6tS2oP59Vu5x8kmDBoahaBENBw+5MHM200mIKHsYbBORWx0+4sT7HySp5V49Q6FpHNUm35Q/nwmjRxnVSVauSmR1EiLKFgbbRORW81+Ph8MB3HuPVVV2IPJl9e+14blnjOokrw1nsxsiujYG20TkNv/848Cnnyen5moT+YN+fcNQ6mYTTp50YeJkppMQ0dUx2CYit5k7PwG6DlV9pHo1C/c0+YWwUA3jxoRDMqI+/DgJX39jfKAkIsoMg20icotdfzqw6etkmExA964h3MvkV26/zYq2bYJTm92cO+fy9CYRkZfSdF3GnYjIk3RHEpzreqllc7OZ0Cye666oH9sJ1/5voR/ZDv3ob0Dc2dSfaXWeg6XZ7Mx/L+ofuH5bDf3Y79DPH0biufMwIwnJpgiElyoPrcL/YLrrZWhhha5vuxxJcP28FPqfH0M/ewBw2oF8JWGq+CBM9btDiyh6xe+4DnwP1zfToB/fCanZpt1URT3WVP2JTNafDMfcBsDZf2FuOhOm21rA116DPNu+84fVayH7F+cPAfYEwBoC5C8F0y33wnR3e2gFy6b7Hfu0usCFo9la//X+ja4/P4br11XQT+wCEmOAsMLQytaD6Z6OMJWsfeXfce4QnF+Oh35gC5AUA+S7Wb3u6ngyma94vGNdT+i/r0ndvqQkHc+3vIh/9jvR8CEbZk6T0W5OACai9Hhdl4jScX47A/rfG3K8V1z//QjX9/NSvw++dN3MivNG0HhkO1xb34Sl3TpoRSvlaN16bBQcy54FTv+d/gdn9sMlt99Xw/zS2zCVvuPy9vz7HZxvtQB0F2ALA6zB0I/tgHN1e6DZbJjqPJd++39YoAJtrVRdaHWehy++BnnBdfBnOFe0BJIz5ConxQKn9sAlt1/fhrnVcpjK18+TbdJdTjjXdoO+68P0P4g+Dv2PdXDu+hD646Nhrtf+8u/EnIZjUWMg7gxgsgChBYFz/8G1aQL0c//B0nRmulW5Dm+DvuM9IDgS5kbD1H1BQRomjA1HixcvYtNXyfj0s2Q0ecJzH5SJyDsxjYSIshaSP+d7J6wQ9ifVxuaTD+CUVjX9z+LOwLl+RI5WJxffnO92SBdoayVrQSt/vxEkicRoOFe2hp5mBFhGtFWgXbAsLP1/h2XATmiXgnHnV5PSP8fF43B9NxPQTDA/Md67Riev5zVwI+fHA9IH2pEloFVqqK4ypLInwPlx/3S/Z6r0ELRqjTO9oUDpdI/VStTM0Ta5vpmaPtAuUNrYpuB8xve6C67Phhoj8Sm/88uyS4G2GZbOG2Ed+AdM93Y2Hi5XaM4dTH2s7nLB+ekQORhhatAPWniR1J9VrWpBl05GmtS4iXE4ecqZo20nIv/HkW0iSsdUowlQ82loN9+mvndMvzNbe8hU+k5onT7Hd/uro9ursQgOBjaMLwDz2U1wvt069XH64V9ytMf1v7+AfvDny89zb2eYHx2pll17v1BBtpJwHq7vZsP82Cjj947/YTy+yiPQgiPVslbjKeiHtwEXj0GPOwMtrLC637lhpAogTXe0znGgd710px36vq9Umoj54SG58hrk1vNn+Tvx54CofZfvKFwBlq6boMlVA0nDmfegutqgnDuYbh+bm0zKfJ0uFxwz7rp8R1A4THWyn8Ijz+HacvmKinygMr/8PjSLTX2IUqlBiRfVz5wbR8PU5Qvj9yS1SNxUDVrx6mrRVPs54wrHpeMnJRXGtX05IKkpRSvDdFe7K7ahfbsQfLvZruYpDBseh0ULIrzrAxsReRRHtoko/UmhVnOYbn0aWobRxmvRilUFStTBrHkJ6vtWLwSjSBETTFUapR+dtRiTyrLLtfO99Nt3X7fLy5UbqYDv8mPfVyPhWUv7MyMYktFOyQNHSAGYGg6Cu0kQ5/xsKByTa8G5qi1c+77Ktdcgt54/S2Zbum+1opVVoK2WLTb1/eUfakb6zrW2Z++XwIUjqd9LwKsFGY1jspunDeflaiCmeq+obVGbkK8ETLc+dfnBx/+Afnrv5e27YmOuPD7kA4Zrk/FBwdx4HDTzlWNUFouGCePCERQE/PizHavXGE2ciIjUeYm7gYhyy2efJ2PfPifCwzW0ezkkdfQZCRcuhzDlH8jROvUjv17+JrJ4ukv4an1pR6IlLUAm7Kn7axnP//dG6InRauRVBdUi/81qoqbudBjpAXIybDgQmuTtuoEecwrO7+fDPud/cLzeCK6flwAySizbaXN//fHcen4JglNG29V6//1O5err9kS4Dv6kvk99bKWHocmkyWtw/fJGmifQMh05vhr9cJrjI83rfvn7mpkeT6n3n/oL+ond6T/YaRq0ksbPZQKlXDXRajwJU7n7styOW8qa0edVY19Omx6HQ4eYTkJEBqaREFGuSEzUMWtuPO6/6Rv0afApwj9xwi7VJ07tSZdrnZLmkR265AZHn7j8+5lUHJHgO+14pH7mX3X539SgjzFB8txBOKbUAczW1KDf/NBA9VUFnZIWUfxWmOpeTnXJDRKAyiRH1+9roP+7GXClCb5sodCqPApTzabQKjTI1ed19/Obm86AY3lLlYojFTycbzS74jFaxQaqqs41tzFqP/QDaQL08g9AK3L5SkW2nDuQ/vuMx0h4+u/l+BCmO1+Ga9sK9QHNseARY4Jk7GljO+q0gFagDFzHdkD/dZXaXympS1fT8oVgfPVNMrZuc2DIsFgsXxYJs5npJESBjsE2EeWKlasSceKEC81qHULZ+A3QL12tTyEl2MzN52YaMGdJyrGlZclkpNSaYWRWSr5JMCUTKNuuuVz6z54IrWTt1NJ/Uo1CTaLUNGNSpMkE11/rjbQECbrCi8Iko5nVHsv+9qZUrfh9DVx/fqQmbqYyW1UwaarZDFrVR6BlI8Xierj7+SVVxNLxMzhWvmTkMWckH1we6J2tqwSurcvSpW6Y6uVsVFvoCWn+xsyOkYyj65eOKTkO5e9wfjkO+r9b1Og1Ct5ilP67r5tKR3KpSZEumO7vpVJS9BN/wrVtuVF60hYGrXx9mOq+lFqq02Qymt00feYidux04I03E9HhFdaYJwp0DLaJ6IadP+/C4qVGrvZ991mByym4qWSSo2Pu/2BusRSmCjlLJUmzlmzeZ5DL/lld+pfJchJ4abWeUSUDpUqK68eF6R+z6wPoaSZkXoukVKQb6ZV0BJk4WrOpCtzdlaaSl8+vSiqu7pA66VCqkEgALnXWVe71iV1wLn0K+qMjYb6nU5br0ZPi1Kh7qoJloVVseMPbd+XxkPXxoRUsA8vzizL9marXLTXOJQC/txNcuz+Dc00nwOW4vGZJUdr1Ecwvr00NuEsUN2PQgFAMHR6HufPjcX99KypX4lstUSBjzjYR3bAFixIQG6ujSmUzarTvAeuYk7AM/w+WnltSy6kpSbFwvt/DSA/JjqCI9N9L85SMMt4XnOF3MuE6tBX6zrVq/eZHhsN19PfUQNt0ZxtYhvytKpOox/6wQP08e9IHdlrN5qoKh/nOtm4PtPPi+aW0oqpTfinQ1io+CEvvn2FpvQqWXj8a5fbUA3W4vhirmsZkxbVjTborF6rhkbQbzSEt4+ttT7z69xmPqUzoCRfViLcwNx6jRrdVKUOXQ6VCWQbugrn5HOOxh7epBj9pPf1kEBr8zwqHAxj0WiySk9k7jiiQMdgmohsiE8FWrzECmv59w9SldCGT47QiFdWosKqlnCL2tDFimA1q8l5k8XQT/TLKeJ9WuPy1G6CkTIps0FelE0h5wRSqe2BIfvU19Xdkkmd2tldqTpe8PEFPAnoZzbfPfRDO7+ZAz2YHxevl7ufX921Kl5piur0VNMmFl+c2W2G67YXLD5bSgmnqWmek6lynsIXmqNxfOoUyvN4xJ9Nvc4bvr3V8qG2TOuxxZ6FVbgRTpYbQD29PnVAqEzhlnoCp9rNqoq16jjTHj3oOTcPI4eEoUEBTE4bnL8jkQyIRBQwG20R0Q2bMjlcjePXvs6LeXUbgldEVedpSNSSbtFK3X/4m5tQVwbV+PE3esNR0LlDmqutzbXsLOPknUKQSTJc6CuqXJsYpEcWMr2mD/Nio7G1roVtUgxRLj81GicKUdZ36C64vx8Ex/Q44ljwF59Y30zXgyS3ufn49+lTOHn8pQM1INZdJU6/bVOsZaCGXGtDkkFb69qyPhzT11jM9njKhn/zLOEYsQTA/Psa4M7PjQ324KX7l8XNJ4UImDB9q5MUvXZaAHTvt2f6biMi/MNgmouv2+w47vtyUjDBrHMbeOwX66TQNT9IEO65dH6W/M0P9aPu0urAPK6ZujqVN05+kaj2b7nvX9/MvL+/ZqFqsX35s86s2E5EA0/XV5CtqJqc0vVHiz1/6ejlQTPfzbJAcZvMjw2Dp9yvMrd+BdmtTY6KerkM/9AtcnwxSda4dK1rB9dfnOVq3J59fi7wcaArXb++o5jhCvsr36R6fv1Sm63H9nKbc36Xa2FfjWNcz9fiQW7rfrfFkuvrfUmFGdxh1rmUkP7Xcoyh+a/pa4JlQVz1cTpju7apyupXMjg91PJ276vHRqGEQmjS2weUChgyNRXw800mIAhFnbRBROs5vphvpAhJMOC43C1Hf790Ex8LHjWUAU38wgqunnrAg357FcOxZbEyYK1JRVb+QDn44adQwTlWsOrSSdbK917UqjaCVqQf9kNFFUnKr1XJwPuj//Xj5gdKU5v4eV12XysNNuACt+hMwla9/+TluuQf44XVj/b+thvmBnukm72ll776uo0QzmVUZPFPFBtATY1TgJ7nKEvBK/q90cHRGn4Sp2uPX9RoIS6fPc/35s1xfpYdUh0fJvVfbsm8THDPvNiZIygetNM1ppJGRPHdGunTv3Lvx8jrL1b9mAHzVbQorrEbxXZtnGOs/sh2O2fWhFalkdAtNk/Yi+flX49qx1ji28pWE6YGe6UfDZQKkI0ntP6m5rVKhLn3Qu9rxMWRQmCoFeOiwCzNmxeO1we6pQkNE3ovBNhGlo58/mHVOdfy5dKkBUt4sJBjo1D4ESCnkIcGU1GDOjLT3fmFpjlpZy2PNLRbDsewZ4FL3P/3YpVbbKYIjYX5xeWpr8MzIJEddRl6tIVfU+tYqPgTtlnuh//cDXJvGw/XzYuBS6ojcnzrx7wbIRD6tbiuY6raCfu6gCuZdMknzBl8Ddzx/lusIKwTz0zPgXNvtctdGGT3OmAsu+7j5nExTQ1xb30pX8/tao9rZIbn3Uo5Pl3KH4vxh6OcPp9lwE0yPj073ASsjXSbvfmGkjcjxkbYhj0wulRx+VUbyn6/hmFTjchAvJSLv7ZLleiMjTRg7OgwdOsdg1epENXHynrvTd+IkIv/GYJuIbkjbNiEoVNwG/enpRhdByZmNiwISLhqNZMKLQLupGkxVH4UmNZ4vtdLOCZmQJrnIrl+WqtFZ1ZjE6TBGICs9aExqjLgpy983aiYPVmkUpvtfhZavZPr1m0wqWHd9PQWuXZfqbEeWgKlGE5geGpijDwfZ+nsKloX5oQEwPdg/9QNEXrqR55d9ohWvriY4ug78AFw4DEh1GZnMmr+0UW5RWqanpGCkIekdrl/fvnxH/lJqEuIN/z1mCyzPL4Sr2uNGyT6p/y2VTsIKq6siUrrPVLL2Vdfh+maqmhOglb9f1WHPyCz7Kryo0fFS6mxLN83y98Pc6LVr1o6X4LrF80FY/W4Sho2Iw7q1FuSLZBYnUaDQdHkXIiKPkiDEua6XWpbOeyk1e73VircTMHFyPAoV0rD+0wIIC2WXPKKrkXztZ56/oNJJGj9uw+QJ1y5BSET+gR+tiShHLlx0pZYy6941lIE2UTaEhmqYMC4cUkr8s8+TsWGjMYmTiPwfg20iypHXFyQgOlpHpUpmNG/q3SPwRN6kVk0rOsr8BgCjxsbh1KnLuetE5L8YbBNRth3473IDm4H9wmA2M32EKCc6dwxB9Wpm9YF12Mg4NZ+AiPwbg20iyrap0+JUA5v/PZB1AxsiyprVaqSTBAUBP/xox+o1TCch8ncMtokoW378KRmbt9hhsQD9+7BWMNH1Kl/Ogt6vhqrlqdPjcPAg00mI/BmDbSK6JodDx+Sp8Wr5hRbBKFvWzL1GdANavRCsrg4lJgKDh8aq/zEi8k8Mtonomt5fl4R/9juRL5+GLp0uN/sgout88zVpqtlNeLiGP3Y5sOwtYy4EEfkfBttEdFUxMS7MnW+ManfrEsJmHES5pHgxMwYNMNJJ5H9s3z8O7lsiP8Rgm4iuauHiBJw7r6PcLWY890ww9xZRLnr6ySA14VgmHg8ZGgu7nekkRP6GwTYRZUkmbq1427i8PaBfqKqkQES5R9M0jBwerlK09vztxKIlRsMoIvIfDLaJKEuTpxql/h6ob0X9+2zcU0RuUKSwCUMHh6VeSdr9F9NJiPwJg20iytSW7y+X+hvQj6X+iNzpsUdteKSRDU6nkU6SnMx0EiJ/wWCbiK6QbNcxcXKcWn6pFUv9EeVFOsmwIWEoVFDD/n+dqZOSicj3MdgmoiusWpWIg4dcKFRIU+2licj9ChQwYcSwcLUspQB37LRztxP5AQbbRJTOmbMuvL7ImKTVu2cowsN5miDKKw89aMOTT9jgchnpJAkJTCch8nV8FyWidGbNjkdsrI7q1c146skg7h2iPDZoYBiKFtFw6LALM+cwnYTI1zHYJqJUf+524IOPktTykIFhqssdEeWtfJEmjB5lpJOsfDsRW7cxnYTIlzHYJiLF6dQxbkIcdB1o0tiG2rWs3DNEHlL/XhueaW5cWRo6PBZxcUwnIfJVDLaJSHnv/ST8scuB8HANfXqx1B+Rpw3oG4YSJUw4dtyFqdON6kBE5HsYbBMRos64MHO2kRvas3sIihblqYHI08LCNIy9lE6yZm0Svv8h2dObRETXge+oRKQ6RcbEGJMiWzwXzD1C5CXuutOKVi8Y/5PDR8YhOtrl6U0iohxisE0U4H74MRmfr0+GyQSMHBYOs5mTIom8Sa+eoShd2oRTp12YOIXVSYh8DYNtogCWmKhjzHgjF7TlC8GoVtXi6U0iogxCQzWMHxOuPhB/9HESvv6W6SREvoTBNlEAW7gkAUeOuHBTURN6dgv19OYQURbq1LaiTWsjnWTk6FicP890EiJfwWCbKEDt3efAG8uMTpGDB4aqyVhE5L16dA1F+XJmnD2rY+ylK1JE5P0YbBMFIIdDx7CRsXA4gIYP2fBwQ3aKJPJ2QUEaxo+VeRXAhi+SsWGj0YCKiLwbg22iACRd6XbvdiIyQsPQwaypTeQralS3oMMrIWpZ5ltI2U4i8m4MtokCzOEjTsyZb1Q06NcnFEWK8DRA5Es6dQxBlcpmXLigY/TYWOjS9pWIvBbfZYkCiLwpy+SqxESp32tBs6ZMHyHyNTarkU5isQBff2PHl1+xOgmRN2OwTRRA1n2QhF+2OhAcDIwcHg5N46RIIl9UuZIFr7xspJOMn8hmN0TejME2UYCIinJhynQjfaR711CULmX29CYR0Q3o1CEEZUqbEBWlY+ZsNrsh8lYMtokCJH1ESoWpluzVzHipFVuyE/lDdRK5QiXefS8Jv/1u9/QmEVEmGGwTBYANG5Ox6etkleM5eqTkejJ9hMgf3HmHFc2eNuZejBgdh+RkTpYk8jYMton83LlzLoybaDTA6NheqhiwJTuRP+nbJxSFCmo4cMCJxUuNRlVE5D0YbBP5uXET4nD+vI5Klczo0N6YUEVE/iN/PhMGDzTq5S9akoD9/zo8vUlElAaDbSI/9uWmJNVpTjrOjRsdrkqGEZH/efQRGx6436q6wko6icvFdBIib8Fgm8hPXbjgwphxRvrIK+1CUK0q00eI/JWU8Rz2WhhCQ4EdOxxqwiQReQcG20R+asKkOJw9p6NCeTO6dGT6CJG/K17MjF49Q9XyjFnxOHnK6elNIiIG20T+6etvk/Hp58kwmYCxkj5iY/oIUSBo8VwwatW0IC7OKPfJVu5EnseRbSI/c+asCyNGxqrltq2DcWsNpo8QBQqzWcOo4WGqzOc339rxxSa2cifyNAbbRH5ERrGGDo/FuUvVR3p0My4pE1HgqFjxciv3yVPiERfPyZJEnsRgm8iPrFqdiC3f22GzAVMmMH2EKFBJTf2SJUw4ecqFhYvYyp3IkxhsE/mJ/fsdmDbDeFPt1zsUFSowfYQoUAUHaxh0qfb2WysSceA/TpYk8hQG20R+QFo09x8ci6Qk4L57rWj5QrCnN4mIPKzBA1Y8UN+ovT1+IidLEnkKg20iPzBrTjz27XOiQAFNVR+RmrtEFNjkPCCj25JW9tPPnCxJ5CkMtol83E8/J+PN5YlqeczIcBQpzH9rIjKULmXmZEkiD+O7MpGPl/kb9JpR5u/5Z4PQ4H82T28SEXmZ9u0uT5ZctJiTJYnyGoNtIh/lcukYNCQWZ84YXSL79zUmQxERZTVZUq6C/XeQkyWJ8hKDbSIftXhpgsrDDA4Gpk0JR0gI87SJKOvJkvenTJacwMmSRHmJwTaRD/rtdzvmzk9Qy0MHh6FCeZb5I6KrT5YcfGmy5I+cLEmUpxhsE/mY6GgXBgyOhcsFPPG4DU8/FeTpTSIiH5wsGc/OkkR5gsE2kY+1Yx81Jg4nTrhQ6mYThr0WxjJ/RHRdkyUXcrIkUZ5gsE3kQ9Z9kIQNXyTDYgEmTwxHeDj/hYko+zhZkijv8Z2ayEf8scuOsRPi1HKPbqGoeavV05tERD6IkyWJ8haDbSIfEBXlwqu9Y5CcDDzYwIp2bdmOnYhyZ7Lkl18lc1cSuRGDbSIvl5ys49U+MTgdpaN8OTMmjouAycQyf0R0Y5Ml27U1JktO4mRJIrdisE3k5RMix4yLw84/HIiM0DBnVgTCwhhoE1EuTpY86cKiJUYpUSLKfQy2ibzYqtWJWPdhEkwmYOrkcJQpbfb0JhGRn5BGWIMGGJ0ll72VgIPsLEnkFgy2ibzUL1vt6vKu6NsrFPfeY/P0JhGRn2nwv8udJcdNZGdJIndgsE3khWSEqVffGDidQJPGNrRpzQmRROSeyZIyum21Aj/+ZMf3P9i5m4lyGYNtIi9z4bwLXXpEIzpaR81bLRg5PJyNa4jIbSQ97cVWxgf6ydPi4XDo3NtEuYjBNpEXkRbsffrH4vBhl5q4JBMipQkFEZE7dXwlBAUKaDhwwIm165K4s4lyEYNtIi+ya5cdv+90IDxcw/w5EShciP+iROR+kZEmdOsSqpbnzo9HTIyLu50ol/CdnMhL/LPfgWPHXTCbgRlTw1GhgsXTm0REAeTZ5kEoV86M8+d1lgIkykUMtom8wOfrk/DPP061PHhAKO65m5VHiChvWSwa+vcxRrdXvJ2Io0eNcxIR3RgG20Qe9v0PyRgxOk4tl7vFjObNWHmEiDyj/n1W3FPPCrsdmDHLKD1KRDeGwTaRB/2+w45efWJUjdvixU2oUoWpI0Tk2VKA/fuFqkZaG75IVucoIroxDLaJPGTfPw507R6DhESokaRatax8LYjI4ypVtKBZ0yC1LI21XC6WAiS6EQy2iTzgyFEnOnaJRnSMjtq1LJg6KRwmVvgjIi/RvWsoQkOBXX86sH5jsqc3h8inMdgmymPHjjnRrkM0oqJ0VKxgxrw5EQgJZaRNRN6jSGETOrwSopYldzsxkaPbRNeLwTZRHjp+womX20fj+HEXypQ2YfGCSOTPx39DIvI+rV8MQbFiJpw44VLVSYjo+vBdniiPnDjpxMuvRKta2qVLm7BsSSSKFOG/IBF5J+le2/tVoxTgoiXxOHOWjW6Irgff6YnywMlTxoj20WMulLrZCLRvusnMfU9EXu3xR224tYYF8fHA3HksBUh0PRhsE7nZ6dMutGsfjSNHXLi5pAlvLIlEMQbaROQDTCYNA/oZo9vvf5CkqigRUc4w2CZyo6goF15ufxGHDrtQsoQxol2iOEe0ich33FbHikca2eByAVOmcXSbKKcYbBO5SdQZI9A+eMilGtaoQLsEA20i8j2Su22xAD/+ZMcPP7IUIFFOMNgmcgOZSCTl/f476FKz+SXQLlmSgTYR+aZSN5vxQotgtTxtJhvdEOUEg22iXHb2rAuvdIjGgQNOFLvJCLTljYqIyJd17hCCiAgNe/c68clnHN0myi4G20S56Nw5F9p3isb+f50oWkRTkyFLl2KgTUS+L3/+y41uZs9loxui7GKwTZSLkyEldWTfP04UKaLhzaX5UKY0A20i8h+tXghWqXEnT7qwchUb3RBlB4Ntolxw9KgTL7W9iH/2GyPay5bkQ5kyDLSJyP8a3fTsbpQCXLw0AefPs9EN0bUw2Ca6Qfv/dahA+8hRo2HNijfz4ZayDLSJyD81aWxDlcpmxMbqWLAowdObQ+T1GGwT3YA/dzvQpl00TkfpqFDejOXL8uFmToYkIj9vdNO/b5haXr0mEYcOOz29SURejcE20XX68adktH3lIi5c0FGjuhlvvRGJokX5L0VE/q/eXVbUv88KhwOYOZuNboiuhpEB0XX4bH0SunSPQUKC8abzxuJ8aqY+EVGg6NsrFCYT8MWXyfh9h93Tm0PktRgdEOXQ8pUJGDAoVo3oPPaIDa/PjUBYmMb9SEQBpWJFC5o+FaSWp06Ph67rnt4kIq/EYJsom+SNZPrMOEyaYlwyfbFlMCZPDIfNxkCbiAJT966hCAkGdux04Muv2OiGKDMMtomywW7XMXR4HJYuM+rK9uoZikED5BIqA20iClwyT6VNa6PRzYxZ8Ui2c3SbKCMG20TXkJio49U+Mfjw4ySYzcCYkWGqi5qmMdAmImrXNgSFCmo4fNiF995joxuijBhsE11FbKwLnbpGY/N3dgQFAbOmR6BZ02DuMyKiS2TOiqSTiPkLExATw0Y3RGkx2CbKwrlzRvv17b86EB6uYfGCSDT4n437i4gog2ZNg1CunFmVQl3yBhvdEKXFYJsoE9KkoVWbi9j9lxMFCkj79UjcfpuV+4qIKBMWi4berxqj2ytXJSLqDEe3iVIw2CbK4I8/7GjV+qLKPyxZwmi/Xq2qhfuJiOgqGjxgRa2aFiQmAosWc3SbKAWDbaI0vv4mGS93iMb58zqqVzPj7RX5cEtZM/cREdE1yKTxV3sYo9tr1ibi2DG2cSdisE2UxjvvJqqqIzIqc399K5YtzYcihfl5lIgou+6604q76xlt3Ocv4Og2EYNtIgAul9GsZuz4OLhcwDPNgzBnZgTCQlnaj4gop3p2N+puf/xpEv75x8EdSAGPw3YU0JKTdQwcEpvarKZHtxCMHBamJvsQEVHO1bzVioYP2dTgxdQZRsddokDGYJsCVnS0Cx27ROPz9cmwWIDxY8PRuWMom9UQEd2gPr1C1Xn1+x/s+OFHtnGnwMZgmwLS8RNOvNQ2Gtu2O1RDhtfnRuCpJkGe3iwiIr9QprQZL7QwGoBNnR4Pp5Nt3ClwMdimgLPnbwdavXQR+/91omgRDcuXReKeu9mshogoN3XuGILISA37/nHig4+SuHMpYDHYpoDy08/JaNMuGqejdFQob8aqlflQpTJraBMR5bb8+Uzo0smYLDl7bjzi4ji6TYGJwTYFjA0bk9C5W4w64d9R14IVb0aieDHW0CYicpcWzwejdGkTzp7VsXQZSwFSYGKwTQFh9ZpE9BsYq2q/PtrIhkWvRyIykoc/EZE72awa+lxq4/7WigScPMVGNxR4GG2QX9N1HQsWxWPMuDjoOvD8c0GYPDEcNhtL+xER5QUpA3j7bUYb91lzOLpNgYfBNvl1s5qJU+IxZ55xcpfcwWFDwmA2M9D2d//++y/69u2L++67DzVq1MCDDz6I0aNH49y5c5k+ft26dahcuXKWt969e1/xOy6XC7NmzVLPUbNmTbz00kv4+++/M12/w+FAkyZN0KJFC/UBMKdStuNqUv6GQYMGXfNvq127ttpu2eYpU6bgn3/+yfF6iXLSxr1/3zC1/PEnSdj9FxvdUGDhzDDyS3a7jmEjYvHJZ0Z918EDQvFiK2OiDvm3n376CV26dEFCQgLKlSuHOnXqYN++fXj77bfx1Vdf4d1330WxYsUy/d0qVaqgatWqV9wvwXRGixcvxvz589VzSED//fff4+WXX8aXX36J8PDwdI9duXIl9u/fj/fff99jddxLly6N22+/XS3b7XacP38ef/31F7Zu3YolS5aoDwMjR468YtuJcsOtNSx44nEbPv08GVOmxWHZkkj2NKCAwWCb/E5Cgo6+/WOweYtdNVUYNzocTzRmDe1AIAF2v3791Ndu3bqhZ8+e6n4ZTZ48eTLeeOMNvPbaa1i6dGmmv9+wYUP06NHjms8jwaoEqBKcv/fee7DZbPj444/Rv39/Fcy/8sorqY89c+YM5syZg+effx7VqlWDp0igPXHixHT3yX759ttvMWbMGHzyySc4deqU2kdWq9Vj20n+69Weofjyq2TV3+Cbb+14sAFLrlJgYBoJ+V1XyA6do1WgHRwMzJkZwUA7gHzxxRcquL3lllvQvXv31PtlNLlPnz4oWbKkGoHOKt0ju44dO4bo6Gg0btxYBdriiSeeQFBQEPbs2ZPusZKmYbFY0KtXL3gb2S8NGjRQHxiKFi2qRrnfeecdT28W+akSxc1o/aJxhXHajDh1BZIoEDDYJr8RFeVCm1ei8fsOByIjNCxeEIn763PkJJDs3r1bfb3jjjtgMqU/vclo7W233aaWN23adEPPI4G2iIyMTL1Pni8iIiL1Z+K3337DRx99pPLH8+fPD29VqFCh1KsAK1as8PTmkB9r3y4YhQpqOHjIhTXvJXp6c4jyBINt8guHj0j79YvYt8+JwoU1vPlGJG6rw0vhgUbSRzIGwWmlBLx79+7NMlifNGkShg8fjtmzZ6uR3swUL15cfT148GDqfRcvXlQTMFN+JhMoJT2jevXqeOaZZ+DtHnvsMfWB4fDhwzh58qSnN4f8VHi4Cd27GqUA5y1IwMVol6c3icjtGGyTz/t7rwMvtrmII0ddKHWzCSvfyofKlTgdIRAVLFhQfT1+/HimPz969GhqGkhmvvnmG5WzLHnX8+bNU9U65CapKWkVKVJEBdFSqWP79u0q0JZ8aAmw//e//6nHSDqGpJSMGDHiilF2byQTI0uVKqWWZTInkbs0axqE8uXMuHhRx6LFLAVI/o8RCfm0nX/Y0alrDGJidFSubMbC+ZEoUtj7Axtyj7p166qvMulPRplTgm8hk/9+/PFHtRwXF3dF8CwTIx966CEVcCYmJuKPP/5Q+dYyut2pUyesWbMGZvPljqMDBw5UEyFbtWqVet8DDzygcqCl0oeMjDdv3jxdJZOkpCSVznK9wfe1yv/dqAIFCuDQoUPpUmGIcpvFIqUAQ1VH37ffSVRdJkvdzG6+5L8YbJPP+vU3Ozp3i0Z8PFCntgXz50SwK2SAk9rRMuIs6SAdOnRQo8rly5dXpf8kNcTpNLrXZQx269evr25pR3mlNvddd92FZs2a4c8//8T69evVJMgU8rMPPvhA5WRLcFqrVi089dRT6mfTp09XlT4kVzulHOHYsWPViHFwcLB6nFRFkQmVOdG0adMsfyZBsuSI34jrqQFOdD3uu9eKe+pZ8ePPdsyYFY/pUyK4I8lvMdgmn/TLVju69YhGQiJw150WzJ0VidBQNqsJdFJdQ8rsyUi0BMjPPvts6s8KFy6sKpTMnDkT+fLly9b6wsLC0Lp1a9UQR6qYpA22RcWKFVWpwbR27dqFtWvXYujQoWpkXUbUO3furB4r2yYB99y5cxESEoLBgwfn6O/LWLovLUlpudFgW0bkhTdP5iQ/anTTLxTNn7uIjV8k47eWds6zIb/FYJt8ztZtdnTtEa1a/957jxWzZ0QgOJiBNhmkvN+HH36omsv8/vvvKiVEAl1p2iL3iQoVKmR7d5UpU0Z9jYqKytbIsATmku4h3SKFNNOR9BEJ8m+++WY0atRITUKU+6UcoATd3iA2NhZHjhxRy3I1gMjdKlW0oOnTQXh/XRKmTIvHqhVsdEP+icE2+ZRt2+3o2t0ItOvfZ8Ws6REICmKgTelJXWupriG3tFJGfu+8885s77KU/OXsBMUyoi0j2xJIp+R3HzhwQOVCS6Cd4tZbb1UpKJL6IY1xvIGkyciHhbJly+Kmm27y9OZQgOjRLRSfr0/CH7scWL8hGY8/xgZk5H84k4x8xvZf7ejSzUgdkXw/BtqUEzIyvXHjRpUiIaPL2SW/I67V/VGCcsnVlnzslLboKWR0PbMShd5SpeTs2bOYNWuWWpa0GaK8IhPaX3nZ+CA7Y3Y8kpI4b4D8j3ec6YmyORkyIU3qCEe0KTMyGVLSNtKSutFdu3ZVVUgGDRqkJimmtXDhQlW9JGNLdsmt3rBhg3q8VBa5GkkTSU5OVi3b05KUlfj4+NRGOrJeWad0nixdurRHX0QZyd68ebPKbZcPI/Xq1VNt5YnyUtvWIbipqAnHj7uw4m02uiH/wzQS8nq//S7l/aIhg4H33G1VLdgZaFNWpE625GbLSLS0IJdR219//VUFwhJwZ1bRQ0akJbCuUaOGakoj+ctSI/v06dOqYoiUALxaaoW0f1+9ejUGDBigJmKmJaUB33rrLfTu3VtVS5F8bZkk2bFjxyuCfneSfSAfNFIC/gsXLqiqLSmTImVEXiq2SAoOUV4KCdHwas9QDBkai8VLE9Ds6SAULMixQPIfPKuSV/tzt0PVYpVA++56DLTp2ho2bKhGaaVLpEyQlG6SUtavTZs2qlxfZrp164YdO3bgv//+w19//aVGfIsVK6ZGedu2bYty5cpd9TmlU6RMKnzxxRev+JnU8F66dCkmT56MLVu2qO1p165danv0vCJBvtyEBPnSWl5G3aVk4dNPP60mkRJ5SpPGNqx824y/9jgxb0E8hg0J54tBfkPTWViVvNQ//zjQ5pVo1WXsjroWvD43Uo2A+CPdkQTnul5q2dxsJjQLJwkRUeBVmnq5fTRkbvEHa/OhfDmOB5J/4HUa8kqHDjvRvrMRaN9aw4J5s/030CYiIuDOO6xo8D8rpPfUtBnx3CXkNxhsk9c5ecqJ9p2iceaMjkoVzVgwPwJhYQy0iYj8Xd/eYZBpA5u/s+PnX+ye3hyiXMFgm7zK2bMutO8YrWallyltwuKFkcifj4cpEVEguKWsGc8/a0wcnjwtDk4nSwGS72MUQ17jYrQLHbpE47+DLhQvbsKSRZEoXIiHKBFRIOnSKQQRERr27nXi40/Sl/Ek8kWMZMgrxMXr6NItRp1cCxXSsHRhJEoUNzrwERFR4ChQwIROHYxGN7PmxiM+nqPb5NsYbJPHScewHq9GY+cfDuTLp2HJwkiUKcNAm4goULV6IRg3lzQhKkrHsreMjqtEvorBNnmU3a6jd78Y/LLVgdBQYOH8SFSqyHJPRESBzGbT0KdXqFp+480EHD/h9PQmEV03BtvkMTLxZfDQWDXrPCgImD8nUpX5IyIiavSwDXVvtyAxEZg6naUAyXcx2CaPkF5Ko8bGYf2GZFXmadb0CNxR18pXg4iIFE3TMHhgGEwmYOMXyfhlK0sBkm9isE0eCbQnT43H++uS1El08sRw1L/PxleCiIjSqVLZgueeNTrqTpgUB4eDkyXJ9zDYpjw3f0EClq9MVMujR4bhkYfZmpyIiDLXo1so8ufX8M9+J1a/a7x3EPkSBtuUp1a8naCCbTFkYCiaPmU0LyAiIsqMNDZ7tbsxWXLu6wk4d87FHUU+hcE25ZkNG5MwaYoxyaVn9xC0amnUUSUiIrqa5s2CULWKGTExOmbO4WRJ8i0MtilPyMSWQa/FQteBli2C0bE9A20iIsoes1nDkEFhanndB0n4c7eDu458BoNtcru9+xzo2TsGdjtUKadBA0LVLHMiIqLsuq2OFU0a29SgzfiJcXC5OFmSfAODbXIraUTQuWs0YmN1VS914rhwNUJBRESUU316hakGaNJx+ONPk7gDyScw2Ca3uXDRhU5dY3A6SkeF8mbMnhmBoCAG2kREdH2KFjWhc0djsuT0mfGIieFkSfJ+DLbJLRITdXTrGYMDB5wodpMJC1+PQL5IHm5ERHRjXnoxGGXLmHD2rI4Fi4zqVkTejNEPuaUN+4BBMdixw4HICA0L50eg2E1m7mkiIrphNquGQQONyZIrVyXi3wOcLEnejcE25Xp3yHET4vDVN3bYbMDc2RGoUMHCvUxERLmm/r02/O8BKxwOYOKkePXeQ+StGGxTrlq4OAHvvpcEKTYyeUI4br/Nyj1MRES5bmD/MDWo8+PPdnz1dTL3MHktBtuUa9Z9kIg58y51hxwUhocbsg07ERG5R+lSZrRtY/RsmDglHnHxHN0m78Rgm3LF5u+SMXJMnFru8EqIalxDRETkTh1fCUHJEiacOOHC3HnsLEneicE23bA/dtnRt38MnE7gqSeD8GoPdockIiL3CwnRMGzo5cmSu//iZEnyPgy26YYcPOhE1x4xSEgE7rvXilHDw9gdkoiI8nSy5GOP2uByASNHx8LhYDoJeRcG23Tdos5I05ponD+vo3p1M6ZPjYDVyqY1RESUtwYNCFOlZv/a48Tb7yRy95NXYbBN1yUuTkfX7tE4esyFUqVMeH1OJMJCGWgTEVHeK1zIhD69jc6Sc+bF4/gJJ18G8hoMtinHku06evWJUSMIBQtoWPR6JAoV4qFERESe07xpEG6rY0FCAlS/B9beJm/BCIlyRE5eI0bGqrqmISHA6/MiVfklIiIiTzKZNIwcHgaLBfh2sx1ffsXa2+QdGGxTjsydn4CPP02G2QzMmBaBGtXZHZKIiLxD+XIWtG9nVMQaPzEOMTEuT28SEYNtylnTmgWLjKY1I4aGqRngRERE3qRj+xCULWNCVJSOmXNYe5s8jyPblC3f/3C5aU2nDiFo3oxNa4iIyPsEBWkYPjRcLa9+Nwnbtts9vUkU4Bhs0zX9vdeB3v2MpjVNGtvQoxub1hARkfe6604rnmkepJaHDo9VFbSIPIXBNl3V8eNOdO4Wjfh44I66FoweFc6mNURE5PUG9A1TrdylRO3U6caVWSJPYLBNWbpwUZrWxKi8t4oVzJg9IwI2Nq0hIiIfEBamYcwoI51kzdoklQ5J5AkMtilTiYk6uveMwYH/nCh2kwkL5kcgMpKHCxER+VY6yYstjTlGw0fGITqa1Uko7zF6ois4nToGDo7F7zsciIjQsGBeBIrdxFraRETke3r1DEWZ0iacOu3ChMmsTkJ5j8E2XdG0ZsKkOGz6OhlWKzBnZgQqVmQtbSIi8k0hIRrGjw2HyQR8/EkSvvqa6SSUtxhsUzpLlyXinXeToGnAxHHhuKOulXuIiIh8Wu1aVrzcxkgnGTUmFufOMZ2E8g6DbUoln/hnzDIusQ3oF4pHHzHKJhEREfm67l1D1WT/s+d0jBoTp67kEuUFBtukfLclGcNGxqrltq2D0fpF1tImIiL/YbNpmDAuHBYLVKrkR58keXqTKEAw2Cbs2GlXTWscDuCJx23o2zuUe4WIiPxO1SoWNcItxk+Mx7FjTk9vEgUABtsBbv9+B7p0j0FiIlD/PivGjpZJJJqnN4uIiMgt2rUNRu3aFtVV8rXhsXC5mE5C7sVgO4AdP+FExy4xiI7WUaumBdOnRMDKpjVEROTHzGYNE8aGIyQE2LbdgeUrEj29SeTnGGwHqPPnXejYOVrVHS1fzoz5cyMQGsoRbSIi8n+lS5kxoF+YWp4xOx5/7LJ7epPIjzHYDkBx8To6d4vGfwddKFbMhEULIpA/Hw8FIiIKHM82D0LDB21qvlKf/rG4cIHlAMk9GGEFmORkHb16x+DP3U7kz69h8YJIdockIqKAo2kaxo4OQ6lSJpw44cLgoczfJvdgsB1Aku06evWNwY8/21Wu2utzI1DuFrZhJyKiwBQRYcKMqREICpISuHYseSPB05tEfojBdoCw23X0HxCLzd/Z1Ull7qxI1LyV3SGJiCiwSTnAoYON/O058xLwy1bmb1PuYrAdABwOHYOGxKoi/lYrMGdmBOrdxUCbiIhINGsajKefDILLBfQfGIPTp5m/TbmHwbafczp1vDYsFhu+SFZds2bPiMC999g8vVlEREReZeiQMFSqaLRz7zsgRqVeEuUGBtt+TAr1Dx8Zh08/NwJtyUu7vz4DbSIiooxCQjT1PhkWpuG33x0YNyEOus6Am24cg20/DrRHjonDhx8nwWwGpkwKx4MNGGgTERFlpWxZM6ZOkk7KwNr3k7ByFRve0I1jsO2H5JP4uIlxeH9dkjphTBwXjkYNgzy9WURERF5PrgD37R2qlidPjceWH5I9vUnk4xhs+2GgPXFKPFa/mwRNA8aNDsfjjzHQJiIiyq42LwWj2dPGhMl+A2Lx7wEHdx5dNwbbfhZoT5sRj5VvG5e9Ro8Iw5NNGGgTERHltOHNsKFhuP02C2JjdXTpFoOoKFYooevDYNuPAu3Z8xKw7C0j0B4xNEyVMiIiIqKcs1k1zJwWgdKlTTh23IWOXaMRE8OAm3KOwbafBNpTp8dj0WKj89WQQaF47lkG2kRERDeiYEETFr0eiUKFNOzb50SPXjFISmKFEsoZBtt+UEd7xKg4vLncGNEeNCAUrV4I8fRmERER+YVSN5uxcH6kKgm4bbsDffrHqK7MRNnFYNuHJSfr6DcwFu9/YFQdGTsqDC+1YqBNRESU2y3d582OQFAQ8O1mO4YMi1WDXUTZwWDbR8XH6+jWMwZffGm0YJ8+JRxNn2bqCBERkTvcUdeqcrilSdzn65MxZhyb3lD2MNj2QRejXejQJRo//mRHSDAwf04EHmYdbSIiIrfX4J403mh68977SWq+FLtM0rUw2PYxUWdcaPtKNHbscCAyQsOSRZG45252hiQiIsoLjz4ShFHDw9SyzJeaPpMBN10dg20fsmePAy1aXVQzomVm9JtvRKJ2LaunN4uIiCigSGnd1wYbAfcbbyZyhJuuisG2j9j4ZRJeansRJ0+6ULaMCSvezIfKlSye3iwiIqKA1LJFMIa9dnmEW7o3M6WEMsNozcu5XDpeX5iA+QuMGtr33mPF1EnhiIzk5yQiIiJPavFcsMrfHjUmTnVvdjh0DBkYBrNZ4wtDqRhse/lEyMGvxWLzd3b1fZuXgtGnVygsFv4TExEReYPnnjEC7pGj47D63SScOaOrSZTBwXyvJgOHR704P/u5FhdVoG2zGTW0B/QLY6BNRETkZZ5pFowpE8NVKd5NXyXjlU7RuHCBrd3JwGDby0i+19p1iWjZ+iKOHnPh5pImvL08H2toExERebHHHg3CkoWRqlKYVAxr1foijhx1enqzyAsw2PYicfE6hgyNVe3Xk5OB/z1gxZrV+VCtKrN9iIiIvF3d261Y8VYkihc34eAhl6og9vMvRiooBS4G215i7z4HWrS8iI8/TVa5X716hmLOzAjk40RIIiIin1GhvAXvrMiHGtXNuHBBR8cu0Vj5dgIrlQQwBtseJjOXFy2Jx3MvXMSB/5woWkTDsiWR6PBKCEwmTq4gIiLyNUWKmLB8WT482SQITicwYXI8hg6PQ1KS7ulNIw9gsO1B+/91qNzsWXMS4HAADf5nxftr8qvLUEREROS7goI0jB8ThoH9Q9UV6w8/TjIa0/3j8PSmUR5jsO0BCQk65r0ej2eev4jdu51qMsXEceEqbaRgQb4kRERE/kDTNLR+MQSLXo9AoYIa9v3jVFey31yeoPpoUGBgZJfHlUa+2JSEJk0vqCY1djtwf30rPlqXH02eCFL/lERERORf7q5nwwdr86vCB/LeP2VaPNp3isaxY6xWEgg0nb1F3SoxMRELFy7Ehx9+hhMnTkDXI6GZ70Kx4p0weGBZNHrYlqMge8eOHWp9v/32G+Lj41GiRAk8+uij6NSpE0JDQ694fOXKla+5zrvuugvLly/P8d9GuUd3JMG5rpdaNjebCc0SxN1LROQmTqcTGzduxK5du/DHH39g9+7dSEhIQNOmTTFx4sQcr0/ej7/44ovU9e3Zswd2ux3du3dHjx49Uh8nIdd77ydh8pQ4JCQCIcFAj+6heLFlMLtO+jHWlHOjpKQktGzZGrt37wS0wtC0+jBpJ+ByfobEuJ9QreoaaFqpbK/v448/xqBBg9RJonr16irQlhPEggUL8M0332DVqlUIDw9P9zty4sjKt99+i/Pnz6Nu3bo39HcSERH5kri4OPTu3TvX1nfo0CEMHDjwmo+TwTXpOHnXHVaMGB2LbdsdmDw1Hp+vT8KoEeGoUplhmT/iq+om58+70LnLrEuBdg2YbTPx0IP5VBfITV8uV5+chwwZghUrVmRrfSdPnsTQoUNVoD1u3Dg888wz6v7k5GQMHjwYn376KSZPnozRo0en+72sPqFHR0fjs88+U8tPPvnkDf+9REREvsJiseCpp55CjRo1cOutt+K///5T76XXKywsTL0vy7rkJoNZs2fPzvLxZcqY8cbiSLz/QRKmzYjHn7udeL7lRbzcJgQd2ocgLJRppf6EOdu5LDbWpSY/Nno8Cjt+f1fdV63GQLz1RjHMmRmJUjeb8fLLL6v0jq1bt+LPP//M1nrXrVunRsrvvffe1EBb2Gw2DBs2TP2jv//++2qkOjs2bNigAvXatWujbNmy1/nXEhER+R5Ju5QBqtatW6NOnToICrqx1L3SpUurgbAWLVqoK89W6dt+DVLe99nmwfjkg/x4uKFNVSVbvDQBjz5+Hm+tSEBiIidQ+gsG27lE/imWvZWARxobkx9jY3ZK6I0iRUph3Xt34I666f/xHnnkEfVV0j+yQ9JFxJ133nnFz/Lnz6+Cd4fDgc2bN2c7JUVwVJuIiMizNblnTovArOnhKF3ahHPndZVa8niTC3jn3UTExzPo9nUMtm/QyVNOzJknI9nnMXV6vOoWdUtZE55qclj9/Pbbq2c6AVI++Yq9e/dm63lk4oaIjIzM9OcScIu///77mus6fvw4tm/frj55P/7449l6fiIiInKfhg8F4eN1+TF6RBiKFTPh1GkXxo6Pw0ONzmPSlDgcOszKJb6KOdvXwW7X8fNWO9auTcI3m5NVdyhRooQJXTuFqDJ+U6ZEqfuKFSuW6TpS7pfANzsKFChw1ccfPXo02+v75JNP1Izo+vXrp66XiIiIPMtq1dC8WbCKI957PxEr3k7EkSMuLF+ZqG7177Pi+WeDce+9VtiszOv2FQy2c9BWffuvDqzfmIRNXyWrEewUd9S1oMVzwXjwQVvqwS9lgERwcHCm6wsJCUmdEZ0dd9xxh5oEKZMae/bsqXK1U0ipoX379mV7fSkpJDI5hIiIiLyLzaah1QsheOH5YPzwox2rVidiy/f21Js0w/vf/2xo1NCGe+62qm6V5L0YbF+F02kE2NKI5ssvk3H23OUAu2ABDY8+EoTnnw1ChQru341NmjTB66+/rkauu3TpokoMSek/qbstEyRlZrXkbF+rZrfkfu/fv1+lozz44INu324iIiK6PjKJsv59NnWTNJJ31yTis/VJOHNGx8efJKlbWJimGuTdWdeK226zoHw5M5vkeRkG2xkcP+7Ez7/Y8ctWO378ya4mKqTIl09Dw4dseOwRm5rwaLFkHdimNJiRpjZXy8GWKiLZIY+TZjbSvOb7779XtxRlypRRFU4WL16MfPnyZWtUWxrhpB0dJyIiIu9VprRZlQ/u2zsUO3Y68MWXyfhyU7LK7V6/IVndRP78GmrVtKByZQuqVDKr2t2lSplU4O7rXC5dVW2BBlgtRt1yXxDQwfbFaBf273eq2+49DmzdaseRo650j5EA+6EGNjRqZEO9O60qnyo7ihcvnlofOzMp98vodHZVqVJFlexbv349/vrrL1Vzu1q1amjcuLEKxEWFChWy/H15PGtrExER+S6zWcPtt1nVbWD/UPyxy4Hvf7Dj19/salnSXDd/Z1e3FJK5WqmiBZUqmtX8sptuMuOmovLVpL6G5nJdb5kXFhenq4yA8+ddiInVERerIzZOR6x8vbSc9j6pupKcbATTcpNldbOnLBv3p1XsJhPefMMoq+zNAiLYjo524eBBJ/b/68Q/Elz/KwG2A6ejriynYzYDt9aw4K47rep2Wx1LtgPsjIGxkKD4aqX8stNOPWOud7NmzdQtrd9//z3L0oApfvrpJ0RFRaFkyZLsGklEROTjZLS6di2ruolku449exz4c7cDe/c58fdehxpQlIvpO/9wqFtmJAdcAu+ICA0yWGy6VKtOvqaMHsvcNbvdKBIhQe/lr8ay/dJ98n3GoNhdLlx0ISHB+0sj+nSwLZ+cZB7iufMunDnjQpTcomRZV1+PHnPiwH9OnD2b9QtRvLgJFcqbUbGCWaWGyCdFyX+6UbfddhsiIiJw+PBh7NmzB1WrVk33840bN6qvDRo0uOHnknJ/27ZtQ8WKFXH77bdfM4VE8r995dILERERZY8UaahV06puKSRIlnzvvXud+PeAE6dOudTt5GkXTp92qVHl6Bi55X5pQcmoLVjACOLDwzUVX4WHaQgLN75GRJgu3xemQbJbLRa5Gcvy91jlqy3N91aJ/4yAPjhYy/VR+YANtuWT2VsrEnHxgsu43BCn4+JF49JEUlL21lGkiIby5SyoUMEIrOUmkwjCw91TalzyoVu1aoUFCxZg1KhReOONN1LzuJctW6bqa8sotLSKTWvlypXq9vDDD6Nv377pfiZBuwTUMhkyxb///quqk8gHD2nnnhXJEf/yyy/VMquQEBER5VybNm1w6tQp1X2yZs2aPrELJXCV+EduWXW+lrxvCcAlvpJAFrrkRxtBrevSeKUEuVaLEezKFX8JRWRZ1p/2a8qytJwPCfH+QDgv+ESwvea9RDXjNitSXa9wIRMKFzGhSOFLtyIaihcz45ZbzChbxuS2oPpqunbtqlI3JMWjUaNGKnVDqons3LkTBQsWxPjx46/4HWm3/t9//6l0j4zk8VJJRFJU5PdPnDihqpHIKPXo0aNRr169LLdl06ZNqhzhrbfeinLlyuX630pERORLRo4cmZrqeeHCBfX122+/xXPPPZf6mDVr1qT7nSNHjuDYsWOpRQ7S6tatW+p79+nTp9XX9957D1u2bFHLRYoUwbx58+BtJD6SW3mGBoEdbHfpHIpKlSxq5qlchpCbXJIoVNCEAgVyP7E/twQFBWH58uVq8qLUyJaAVzo9Sr71q6++mmXDm6xIa3VJBZG0kZiYGNWQ5rHHHkP79u2vSFPJiO3ZiYiIkO7KsAx+ZRzwktv1kKvPEoinJaPgchMyX4oCk6ZL/gEReZTuSIJzXS+1bG42E5oliK8IERGRH8j73AoiIiIiogDBYJuIiIiIyE0YbBMRERERuQmDbSIiIiIiN2GwTURERETkJgy2iYiIiIjchME2EREREZGbMNgmIiIiInITBttERERERG7CYJuIiIiIyE0YbBMRERERuQmDbSIiIiIiN2GwTURERETkJgy2iYiIiIjchME2EREREZGbWNy1YvIvUVFRnt4E/+ZIRmhSolqMjzoDWGye3iIiIp9VpEgRT28CUSpN13X98rdEmdM0jbvGjWxmYEmTSLXc/pNoJDu5u4mIrhdDG/ImTCMhIiIiInITBttERERERG7CYJuIiIiIyE2Ys03ZwgmSeTBBctNQtRjfcCwnSBIR3QBOkCRvwmoklC08cbmX7kiCMyhYLYcWKQzNEuTmZyQiIqK8wDQSIiIiIiI3YbBNREREROQmTCMh8gZmG7TC5VKXiYiIyD9wgiSRlzVhYAMhIiIi/8GRbSIvwSCbiIjI/zBnm4iIiIjITRhsExERERG5CYNtIiIiIiI3YbBNREREROQmDLaJiIiIiNyEwTYRERERkZsw2CYiIiIichMG20REREREbsJgm4iIiIjITRhsExERERG5CYNtIiIiIiI3YbBNREREROQmDLaJiIiIiNyEwTYRERERkZsw2CYiIiIichMG20REREREbsJgm4iIiIjITSzZeZDdbseZM2fctQ1ERERERD6pcOHCsFqtNxZsS6C9aNGi3NwuIiIiIiKf17FjRxQvXjzLn2u6ruuBNLItf8e6devQrFkz9UmEuD+9BY9N7ktvxOOS+9Jb8djkvvSrkW1ZwdUidl/dMf72N3kS9yf3pTficcl96Y14XHJ/eisem+7BCZJERERERG4ScMF2eHg4HnjgAfWVuD+9CY9N7ktvxOOS+9Jb8djkvvQV2crZJiIiIiKinAu4kW0iIiIiorzCYJuIiIiIyE0YbBMRERERuQmDbSIiIiIiN2GwTURERETkJtlqapPX/vjjD8yZMwe///47HA4HKlWqhLZt2+Lxxx/P9jr+/fdfzJ8/Hz///DMuXryIIkWK4KGHHkL37t2RP3/+Kx5fuXLlLNfVtGlTTJw48Yr7Y2Nj1XZ+8cUXiIqKQtGiRfHII4+o5wgLC0Mg7kt5rrlz5151fc2bN8f48eNTvx80aBA++OCDLB+/d+9eeNpHH32EX3/9FX/++Sf27dunuqpOmDBBdSLNCZfLhbfffhtr1qzBoUOHEBoainvuuQe9e/dGqVKlMv2dLVu2YOHChdi9ezc0TUP16tXRtWtX3H333Zk+/r///sPMmTPV65WQkICyZcuiRYsWeOGFF9TvB+K+PHjwIDZs2KD2pTz2woULKFSoEO666y506tQJ5cuXv2L9vnBcevLY9Mdzpif2Jc+ZWTt79izWrl2rzn3ymhw7dixb/3s5fd87ffq0Omd+99136j2uRIkSePrpp9G+ffurdgX053156tQprF+/Xu2TAwcOqG6d+fLlw2233ab2S61ata74nWsdy1999RVuvvlmBCKvC7YlQJAX0mazoXHjxuoELCdmOUmdPHkS7dq1u+Y6duzYgZdffhmJiYkqKJST299//40VK1aoN9vVq1ejQIECV/xeyZIl1ZtERlWrVr3ivvj4eLz44ovYs2cP7rvvPrWtsvzGG29g27Zt6kQbFBSEQNuXd955p3rjzMx7772n/oFlf2WmdevWiIyMhDeaNWuWOjnJ3yoBQsqJKqeGDx+u9kPFihXx0ksvqZO8nNB++OEHvPvuuyowzniSHTBgAAoWLJh6Yv3888/VayJvDo8++mi6x+/fv18F1vJ6PfbYY2pbN2/ejFGjRqkPTcOGDUMg7kt5Ttlv8qYrx7HU55U3Ldm/GzduxJIlS3DHHXf43HHpyWPTH8+ZntiXPGdmTc5n06dPV4MEZcqUQUhIiBpAyM33PfnQ99xzz6mfPfzww+p55HiU86sE7TLQ5OlBCk/sS3mPX7x4MUqXLo17771XvQfJB8dNmzap27Rp07L88CLnBDk3ZBTpxedRt9O9iN1u1xs2bKjXqFFD/+uvv1Lvj46O1hs1aqRXr15dP3r06DXX88QTT+iVKlXSN23alO7+xYsXq/uHDRt2xe/I/S+++GK2t3XWrFnqd6ZMmZLufvle7l+wYIEeqPsyM1FRUXq1atX0O++8U09KSkr3s4EDB6p1HTlyRPdWP/zwQ+r+Wrhwodre999/P0fr+Omnn9TvtWrVKt0++Pbbb9X97dq1S/f4Cxcu6HXr1tXvuusu/cSJE6n3y7LcJ7eYmJh0vyPrlnXJOlPIc7Vs2VLd/9tvv+mBuC9l/bt3775iPZ9++ql6/OOPP37Fz3zhuPTU/vTHc6Yn92VmeM409sHWrVtTz3OPPPKI2oe5+b43YMAAtc5Vq1al3udyufTevXur+z/55BM9EPflxo0b9V9++eWK+7dt26b24x133HHFe/ns2bPVOn/++eccbVsg8KqcbflEevjwYTzxxBPpRkYiIiLQuXNndenkapd1hfy+jFjdeuutagQrLflEK2kPH3/8sRpluV7SB0hGLeTSoFzOT0u+l/vl557kbftSnksu5z311FNqxMHXyCXgzD6p50TKMfHqq6+m2wfS0VRGt77//nscP3489X5Je4iOjlajgcWKFUu9X5blvvPnz6sRhrTpIzIiI6kRss4U8lzynEIuawfivpSrAtWqVbtiPTLyJaOMMupz7tw5+CJP7E9/PGd6277kORMoXLiwuuKU3Y7POX3fk7QmueIlV2zlimAKGf3t27evX50zc7ovGzVqpI7XjOrWraveYyTdxltS6XyBVwXbW7duVV8zSzNIuU+CiauRS0Iis7wgk8mkcrHk0snOnTuv+LkENnKJb8GCBXjnnXeyPJAk/1MuC0rukrxJpCXfy/1HjhzBiRMnEKj7MiPJFRPPPvtslo/59ttvVW7ysmXLVOpDcnIy/Mkvv/ySenxkVL9+/XSvW3Zfw+w+/vbbb1fPfa3X3F/35dWk5GRaLJaAPC5vZH/60znT245NnjPd/74naZLy/yzBbMZUEQlub7nlFvz2229wOp3XsTX+K+VcmdU5U/bxokWLVHqeDAjFxcUh0HlVzrackIXkE2Ukk/LkBCY5Q1eTkj989OjRTCetpIwoyChgxglmkossuXYZT46TJk1Sk6lSpGxDZjmMKffL6IX8PcWLF0cg7su0tm/frrandu3aKocxK2PGjLliO2USSMoblC+T0X/58CI5w2az+Yqfp7xOaV+Tq72GOX28PKd8aJIRXLnCkNVJ0l/3ZVYkJ/Off/5RV2+yyif05+PyRvenP50zvenY5Dkzb973snNcyvubvNdlNYE90Mi++PHHH9X+lOM8MzJRMq3IyEi89tpratJpoPKqkW25pJNyySczcvkjJibmquuQT6LyT7Fr1y41IpXWW2+9paoQiIzrkbQImewnl6Fk1q8s33///WoSoFQrSPvJNuV3s7ock3J/yt8TaPsyqxGaZ555JtOfy2UpmYwizyHBj0xm6dmzp1pvly5d1PP7uuweM2n35dVew5w+XshEIfmQ5OujDNezL7Naz8CBA9VVmv79+wfkcXkj+9PfzpnedGzynJk373spy1c7Z2bn9QoUkoYjE/blakC/fv2u+EBZpUoVVWlMRrPlnCnVR2RSvqZpqrqTfB+ofHd4Kwvyoo4YMUK9GcqtYcOGKmCUy5syciKfxCQPOeMlI3nTTatOnTrq0nGbNm3UpSk5SCSHKZBc777MePKT3GMZUchq5nLGIFxGJbp164abbrpJfRqeN2+eukxNlFukWoscY1LSSqoUSA4ij8uc4TnTPXjOJG8kAzUSMEuKiFRvyWyUWqq5pCVXU2V+Ufny5VMraGWc/xUovGpk+1qf+uUklNUn0IyXMaWMlIyyyKiLlLCRyWQStKUk/Ke9xJkVGfFKyTGWvK0UKduQ1ShMyv3ZnYjgz/vys88+U3ndEmjntI6ulA+SUmBSK9XXZfeYSfuaXO01zOnjhYxoywcjb6hnnNf7Mq2kpCQ1KU9ya2UEViZOBepxmRv701/Omd6yL3nOzLv3vZTlq50zr/V6BUqgPWTIEHz66ad48sknVSnZnLj77rtVCUEZnPP1q1d+MbKdkjcleVQ1atRI9zPJg5N8uJo1a2ZrXVJwXUamM5L0B5Fx/dfKW05bcSMlHywlPyyjlPuzygMLpH2ZMjP/ahMjsyKXqCTXS2Y9+zoZ2ZccN8l/l8vrGS+/peQOps01lNdQmg/IzzLWhc/q8Wl/lpY8pzy3jDT4cr729e7LtCPaEmhLvWOpxdunT5+APi5vdH/60znTW/Ylz5l5976XneNSJlD78jyC3Ai0Bw8ejA8//FBVeZFmVfKhOqcKFCigXhcZfPP1D9U+P7Kd0lRCUhQySrkvq8YT2SGF4CW3sEKFClftfpZWSqWNtBU55B9aCsvLyE3Gsnfyvdwvj/fkP6g37EtJN5G8VpkUKZMjr2cihpwgb7TkkbeQKwEpx0dGkuea8TXJzmuYtjTT1R4vr5U894285r68LzMG2pJvnFmediAel9e7P/3tnOkN+5LnzLx935P3JQmmZcKflKfM+B4nkyOlqoyvD1DkRqAtV6cnT56c6cTfa4mPj1cT0eXDaGYNBQOBVwXbcqlBcoLlUoV0Fkshl3gkZ1f+KdLmCUkpKemKl/ESkFz6yfiPI4+RxH4Zbcg4miUnOEn8z0hOllK6Rp43bac+uRQvI7VyAEl3qbTke7lfcpoCcV/mZJKPkKBFukpmVlJM8sOEfJr2JVKvWfZlxrrNKceEdANLWz5OysnJvAApTZU2gJMOkHL5cuXKlaq7WQpZlvvkpCV59CnKlSun3kgkPULWmUKeS57zeq8w+MO+TEkdkUBbcgcz5hsHwnGZm/vTH8+ZntqXafGceS5P3/dkhFVq7UvZSZngm0Le86TbYtrX09ePy+tNHZFAW/6Xp0yZctVAW9JD5MNJRjLIMWzYMBVLyHoC9YOLJp1t4EWyarUqnzLlDTJtq1V505MC9VKGK6WVtZAWzDNmzEC9evXUaMrZs2fx9ddfq4NPGg1kbKog65GKA1KLWEZW5GCQT2HyxixvElLa6oUXXkj3O/LmIPdJ6Ss5eUrDjL/++kt9epYyYhIMBQcHI9D2ZQp5k5F8b/kHk9GcrD7NSmAo2yETUuWSnrSElVq78jtS7USeV+p1erqNs1zaldFhIXlnu3fvViMeKZch5dhJCWSl7NHcuXNV2/oePXqkW8/QoUNT2zhLkwsJ6qSpgrw2crKXCjBZtWtPmWAqj5e8eXldJCBPS45bOS7lBCePl0va8iYv98tEFW9o1+6JfZlyfMv+eP7557PMxU4ZjfWV49KT+9Mfz5me+j8XPGdmvi9TPtyKL7/8UgV18r+aokOHDmoC3vW876UMNKW0a5ciCJJbLJMApQZ3gwYN8Prrr3u8Xbsn9mXKemQ0unXr1pkGyTLYk9I8SFKn5Hv5X5Z1SBMdiRfkqsHJkydVQYXly5cH7Mi2133EkDexVatWYfbs2erkJDWB5UWSMjNZVbPISNIapASNnMTljVE+vcrlorZt26r1ZySzY2XESt4E5MCQERs5UOQfVaqRZJbbLAegvDnIASn/yPLmLG/k8o8sVQ48/abhqX2ZQkr/yOMlGLzaP5ec2OSfXdJN5Hfkn1/2rTyvjBzKCeR6LlvlNjnRZey4KaN4aS8VZ2fUePTo0eo1kK5kcuKRv1VmcEtFDNkXGUnHTdl/kjO/bt06dZ/kIkp1GGnEkJG8ucu6Zda3BNkS4MglfAl+WrZsCW/giX0pb7RCgh55A8nq8n9KsO0rx6Wn9qe/njM99X8ueM7MXGadjtPeJ/+naYPtnL7vySBS2nOmDCbJlQcZTJKg3dOBtqf2Zco5U95DsqoGJvspJdiWjtLyHiMl/2Q/yvlBBiNkfS+99JIa7PGG/3FP8bqRbSIiIiIif+FVOdtERERERP6EwTYRERERkZsw2CYiIiIichMG20REREREbsJgm4iIiIjITRhsExERERG5CYNtIiIiIiI3YbBNREREROQmDLaJiIiIiNyEwTYRERERkZsw2CYiIiIichMG20REREREcI//A/4v8Ko/spmGAAAAAElFTkSuQmCC", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import arviz as az\n", + "\n", + "posterior = mcmc.get_samples()\n", + "az.style.use(\"arviz-white\")\n", + "az.plot_posterior(posterior[\"rho\"], hdi_prob=0.95, ref_val=rho_true)\n", + "plt.show()\n", + "az.plot_posterior(posterior[\"obs_std\"], hdi_prob=0.95, ref_val=obs_std_true)\n", + "plt.show()\n", + "az.plot_posterior(posterior[\"diff_std\"], hdi_prob=0.95, ref_val=diff_std_true)\n", + "plt.show()\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.10" } - ], - "source": [ - "import arviz as az\n", - "\n", - "posterior = mcmc.get_samples()\n", - "az.style.use(\"arviz-white\")\n", - "az.plot_posterior(posterior[\"rho\"], hdi_prob=0.95, ref_val=rho_true)\n", - "plt.show()\n", - "az.plot_posterior(posterior[\"obs_std\"], hdi_prob=0.95, ref_val=obs_std_true)\n", - "plt.show()\n", - "az.plot_posterior(posterior[\"diff_std\"], hdi_prob=0.95, ref_val=diff_std_true)\n", - "plt.show()\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv", - "language": "python", - "name": "python3" }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.10" - } - }, - "nbformat": 4, - "nbformat_minor": 5 + "nbformat": 4, + "nbformat_minor": 5 } From 0e04441a2473435b13819783557158b1c4ed3370 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Thu, 14 May 2026 14:57:56 -0400 Subject: [PATCH 15/28] dont change faq --- docs/faq.md | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) diff --git a/docs/faq.md b/docs/faq.md index 21a52455..59e90b03 100644 --- a/docs/faq.md +++ b/docs/faq.md @@ -60,15 +60,10 @@ with ODESimulator(): ``` Despite the deterministic nature of an ODE, sometimes a filtering-algorithm helps a lot (especially for long timeseries rollouts, partial/noisy observations, systems with large sensitivities to intial conditions). You can modify the model definition to have a small diffusion coefficient to "relax" the ODE problem to an SDE. ```python -from dynestyx import FullDiffusion from dynestyx.inference.filters import Filter, ContinuousTimeEnKFConfig with Filter(filter_config=ContinuousTimeEnKFConfig()): - return model( - obs_times=obs_times, - obs_values=obs_values, - diffusion=FullDiffusion(0.01 * jnp.eye(state_dim)), - ) + return model(obs_times=obs_times, obs_values=obs_values, diffusion_coefficient=0.01) ``` From 2cfab462eae6c16a751e218ddade3c1360291f90 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Thu, 14 May 2026 15:01:38 -0400 Subject: [PATCH 16/28] simplify notebook changes for PR --- .../02_dynestyx_discrete_intro.ipynb | 1206 ++++++++--------- .../gentle_intro/06_continuous_time.ipynb | 991 +++++++------- 2 files changed, 1099 insertions(+), 1098 deletions(-) diff --git a/docs/tutorials/gentle_intro/02_dynestyx_discrete_intro.ipynb b/docs/tutorials/gentle_intro/02_dynestyx_discrete_intro.ipynb index 145f15ce..e23ad9a0 100644 --- a/docs/tutorials/gentle_intro/02_dynestyx_discrete_intro.ipynb +++ b/docs/tutorials/gentle_intro/02_dynestyx_discrete_intro.ipynb @@ -1,620 +1,620 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Part 2: Dynestyx — NumPyro with better support for dynamical systems\n", - "We introduce **dynestyx** as an extension of NumPyro for **dynamical systems**, with a clear separation between *what* the model is and *how* we simulate or score it." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2.1 Separation of concerns\n", - "\n", - "**Dynestyx** extends NumPyro by giving you a standard way to work with dynamical systems. The key idea is **separation of concerns**:\n", - "\n", - "- **What** the model is: parameters $\\theta$, initial condition $p(x_0)$, state evolution (discrete or continuous time), observation model $p(y_t \\mid x_t, \\ldots)$. This is the `DynamicalModel`—you write it once as a generative model in code.\n", - "- **How** we simulate: *simulators* (e.g. `DiscreteTimeSimulator`, `SDESimulator`) unroll the dynamics step-by-step and generate state/observation trajectories. They interpret `dsx.sample(\"name\", dynamics)` as \"run the model forward in time.\"\n", - "- **How** we do inference: we can use either *simulators* (which sample latent states $x_{0:T}$ explicitly) or *filters* (which marginalize over them and compute $p(y_{1:T} \\mid \\theta)$). On top of that, we run standard NumPyro inference—**NUTS**, **SVI**, or others—to infer parameters (and optionally latent states when using a simulator).\n", - "\n", - "You write the model once; then you choose how to interpret it (simulator vs. filter) and which inference algorithm to use." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2.2 A first Dynestyx model\n", - "\n", - "For pedagogical purposes, we begin with a classic discrete-time linear-Gaussian system with controls. \n", - "\n", - "$$\n", - "\\begin{aligned}\n", - "x_{t+1} &= Ax_t + Bu_t + \\epsilon_t \\\\\n", - "y_t &= Cx_t + \\eta_t\n", - "\\end{aligned}\n", - "$$\n", - "with\n", - "$$\n", - "\\begin{aligned}\n", - "x_0 &\\sim \\mathcal{N}(m_0, \\ C_0) \\\\\n", - "\\epsilon_t &\\sim \\mathcal{N}(0, \\ \\Sigma) \\\\\n", - "\\eta_t &\\sim \\mathcal{N}(0, \\ \\Gamma) \n", - "\\end{aligned}\n", - "$$\n", - "\n", - "Written differently, we have:\n", - "$$\n", - "\\begin{aligned}\n", - "\\text{Initial Condition:} \\quad x_0 &\\sim \\mathcal{N}(m_0, \\ C_0) \\\\\n", - "\\text{State-transition:} \\quad x_{t+1} &\\sim \\mathcal{N}(Ax_t + Bu_t, \\ \\Sigma) \\\\\n", - "\\text{Observation model:} \\quad y_{t} &\\sim \\mathcal{N}(Cx_t, \\ \\Gamma) \\\\\n", - "\\end{aligned}\n", - "$$\n", - "\n", - "Furthermore, say we have prior belief about a subset of parameters in the model. Concretely, we will assume\n", - "\n", - "$$\n", - "\\begin{aligned}\n", - "A &= \\begin{bmatrix} 0 & 0.3 \\\\ \\rho & -0.2 \\end{bmatrix} \\\\\n", - "B &= \\begin{bmatrix} 1 \\\\ 0 \\end{bmatrix} \\\\\n", - "C &= \\begin{bmatrix} 1 & 0 \\end{bmatrix} \\\\\n", - "\\Sigma &= 0.1^2 I \\\\\n", - "\\Gamma &= 0.1^2 I \\\\\n", - "m_0 &= 0\\\\\n", - "C_0 &= I\n", - "\\end{aligned}\n", - "$$\n", - "\n", - "and place a prior over the single unknown, $\\rho$, in the system:\n", - "\n", - "$$ \\rho \\sim \\mathcal{U}([-0.9, 0.9]).$$\n", - "\n", - "This induces a generative model.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "At the highest level, the idea is to create a NumPyro model that samples from this dynamical system. To do this, we use the `DynamicalModel` class in dynestyx, paired with the `dsx.sample` statement. " - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "import numpyro\n", - "import numpyro.distributions as dist\n", - "\n", - "import dynestyx as dsx\n", - "from dynestyx import DynamicalModel\n", - "\n", - "\n", - "def fake_lti_model(obs_times=None, obs_values=None):\n", - " # sample the unknown parameter\n", - " rho = numpyro.sample(\"rho\", dist.Uniform(-0.9, 0.9))\n", - " # create the dynamical model depending on the parameter\n", - " rho_dynamics = DynamicalModel(..., rho, ...) # not real syntax\n", - " # sample from the dynamical model\n", - " dsx.sample(\"f\", rho_dynamics, obs_times=obs_times, obs_values=obs_values)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "At this level, you can think of writing `dsx.sample(...)` as rather abstract---at this point, we don't worry about HOW to sample the system. \n", - "\n", - "Why? Dynestyx allows us to have different \"interpretations\" of the `dsx.sample` statement, depending on the task at hand. To give a few examples of how we may interpret the dynamical system later, we may:\n", - "- Use algorithmic strategies (e.g., filtering or smoothing) to efficiently condition `lti_model` on available data.\n", - "- Specify key parts of *how* we simulate, which is particularly important when we use differential equations later on.\n", - "- Explore various approximations of the dynamical system (e.g., Gaussian states, linear observations, or discretizations of a differential equation), *without* modifying the underlying model.\n", - "- Freely experiment with these differing strategies as part of the Bayesian workflow discussed in the previous tutorial.\n", - "\n", - "Let's dive in a bit more how to build a `DynamicalModel`." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The `DynamicalModel` class can be instantiated with three main ingredients:\n", - "- `initial_condition`: can be any NumPyro distribution\n", - "- `state_evolution`: can be one of two classes\n", - " - `DiscreteTimeStateEvolution`:\n", - " - A callable $(x, u, t_\\text{now}, t_\\text{next}) \\mapsto \\ $ `numpyro.distributions` object (which can include things like categorical distributions)\n", - " - `ContinuousTimeStateEvolution`: has fields\n", - " - `drift`: A callable $(x, u, t) \\mapsto \\ \\mathbb{R}^{d_x}$\n", - " - `diffusion`: A `Diffusion` object such as `FullDiffusion`, `DiagonalDiffusion`, or `ScalarDiffusion`\n", - "- `observation_model`: A callable $(x, u, t) \\mapsto \\ $ `numpyro.distributions` object\n", - "\n", - "It also requires specification of the key dimensions in the problem:\n", - "- `state_dim`: $\\text{dim}(x_t)$\n", - "- `observation_dim`: $\\text{dim}(y_t)$\n", - "- `control_dim`: $\\text{dim}(u_t)$\n" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "import jax.numpy as jnp\n", - "\n", - "from dynestyx.models import DynamicalModel # noqa: F811\n", - "\n", - "# for convenience, we can define \"fixed\" things in the model outside of it.\n", - "# this is not required, but it helps keep the model clean.\n", - "state_dim = 2\n", - "observation_dim = 1\n", - "control_dim = 1\n", - "\n", - "# Create the known matrices B, C\n", - "B = jnp.eye(state_dim, control_dim)\n", - "C = jnp.eye(observation_dim, state_dim)\n", - "\n", - "# create the initial condition as a distribution\n", - "initial_condition = dist.MultivariateNormal(jnp.zeros(state_dim), jnp.eye(state_dim))\n", - "\n", - "# create the observation model as a callable mapping to a distribution\n", - "observation_model = lambda x, u, t: dist.MultivariateNormal(\n", - " C @ x, 0.1**2 * jnp.eye(observation_dim)\n", - ")\n", - "\n", - "\n", - "def lti_model(rho=None, obs_times=None, obs_values=None, ctrl_times=None, ctrl_values=None, predict_times=None):\n", - " # sample the unknown parameter\n", - " rho = numpyro.sample(\"rho\", dist.Uniform(-0.5, 0.5), obs=rho)\n", - " A = jnp.array([[0, 0.3], [rho, -0.2]])\n", - "\n", - " # create the state evolution as a callable mapping to a distribution\n", - " # Crucially, this depends on A, which depends on rho, which is unknown.\n", - " # Thus, the state evolution MUST be defined within `lti_model`, not outside.\n", - " state_evolution = lambda x, u, t_now, t_next: dist.MultivariateNormal(\n", - " A @ x + B @ u, 0.1**2 * jnp.eye(state_dim)\n", - " )\n", - "\n", - " # create the dynamical model\n", - " dynamics = DynamicalModel(\n", - " control_dim=control_dim,\n", - " initial_condition=initial_condition,\n", - " state_evolution=state_evolution,\n", - " observation_model=observation_model,\n", - " )\n", - "\n", - " # sample from the dynamical model\n", - " return dsx.sample(\"f\", dynamics, obs_times=obs_times, obs_values=obs_values, ctrl_times=ctrl_times, ctrl_values=ctrl_values, predict_times=predict_times)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2.3 Making \"data\": observation and control trajectories\n", - "\n", - "Dynestyx models take trajectory data as keyword arguments: `obs_times`, `obs_values`, `predict_times`, `ctrl_times`, and `ctrl_values`.\n", - "\n", - "- **`obs_times`** and **`obs_values`**: Always provided together. They represent **observed data** — times $\\{t_k\\}_{k=0}^K$ and values $\\{y_k\\}_{k=0}^K$ at which we have measurements. When provided, the model is conditioned on these observations.\n", - "- **`predict_times`**: Times at which to predict or simulate — defines the time grid for the solver/simulator. Use this alone for pure forward simulation (no data); use with `obs_times` when predicting at additional times beyond the observed data.\n", - "- **`ctrl_times`** and **`ctrl_values`**: Control inputs; provided together; must align with the union of `obs_times` and `predict_times`.\n", - "\n", - "Our first step will be to simulate data from the generative model. To do this, we define the times at which we should simulate (`predict_times`) and a synthetic control sequence." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "import jax.random as jr\n", - "\n", - "# For simulation: predict_times defines the time grid (no observed data yet)\n", - "predict_times = jnp.arange(0.0, 100.0, 1.0) # T=100 steps\n", - "ctrl_times = predict_times # same times for controls\n", - "\n", - "# create a synthetic control sequence as i.i.d. Gaussians\n", - "# (in practice, this would be an array of control inputs that we have observed)\n", - "ctrl_values = jr.normal(jr.PRNGKey(0), (len(ctrl_times), control_dim))\n", - "\n", - "# For an autonomous system, we would simply omit ctrl_times and ctrl_values." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2.4 Interpreting the model with a Simulator\n", - "\n", - "To generate data, we interpret `dsx.sample(\"f\", dynamics, predict_times=..., ctrl_times=..., ctrl_values=...)` using a **Simulator**. The `DiscreteTimeSimulator` unrolls the model step-by-step at the given times. For pure simulation (no observed data), we pass `predict_times`, `ctrl_times`, and `ctrl_values` directly to the model." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## How does this interpretation manifest under-the-hood?\n", - "\n", - "The `DiscreteTimeSimulator` simply \"unrolls\" the dynamical system into a normal NumPyro probabilistic program. This internally does something like the following, but more efficiently using `jax.scan`:\n", - "\n", - "```python\n", - "def simulated_program(...):\n", - " # Probabilistic program before dsx.sample\n", - " # ...\n", - " # dsx.sample(...):\n", - " \n", - " T = len(times) # times = predict_times for simulation, or union of obs_times and predict_times\n", - "\n", - " x_prev = numpyro.sample(\"x_0\", initial_condition)\n", - " y_0 = numpyro.sample(\"y_0\", dynamics.observation_model(x=x_prev, t=times[0]))\n", - "\n", - " for t_idx in range(T-1):\n", - " t_now = times[t_idx]\n", - " t_next = times[t_idx+1]\n", - "\n", - " x_t = numpyro.sample(f\"x_{t_idx+1}\", \n", - " dynamics.state_evolution(x=x_prev, \n", - " t=t_now, \n", - " t_next=t_next))\n", - " y_t = numpyro.sample(f\"y_{t_idx+1}\", \n", - " dynamics.observation_model(x=x_t, t=t_next), \n", - " obs=obs_values[t_idx+1])\n", - "```" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2.5 Predictive (for generating synthetic data)\n", - "\n", - "We use NumPyro's `Predictive` to generate samples from the model. With `DiscreteTimeSimulator` in place, we pass `predict_times`, `ctrl_times`, and `ctrl_values` to produce one trajectory—states and observations—at the given times.\n", - "\n", - "Here, we generate a single synthetic dataset with $\\rho = 0.3$\n" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "from numpyro.infer import Predictive\n", - "from dynestyx import DiscreteTimeSimulator\n", - "\n", - "rho_true = 0.3\n", - "with DiscreteTimeSimulator():\n", - " predictive = Predictive(\n", - " lti_model,\n", - " params={\"rho\": jnp.array(rho_true)},\n", - " num_samples=1,\n", - " exclude_deterministic=False,\n", - " )\n", - "\n", - " pred = predictive(rng_key=jr.PRNGKey(0), predict_times=predict_times, ctrl_times=ctrl_times, ctrl_values=ctrl_values)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Shape convention note:** simulator outputs now always include a leading `n_simulations` axis, even when `n_simulations=1`. Under `Predictive`, there is also a leading `num_samples` axis. In examples below we use a helper that removes only leading singleton axes for plotting/conditioning." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now extract and plot the generated data:" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ + "cells": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "dict_keys(['f_observations', 'f_states', 'f_times', 'f_x_0', 'f_x_Tracedwith', 'f_y_0', 'f_y_Tracedwith', 'rho'])\n", - "shapes: (1, 1, 100) (1, 1, 100, 2) (1, 1, 100, 1)\n" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Part 2: Dynestyx — NumPyro with better support for dynamical systems\n", + "We introduce **dynestyx** as an extension of NumPyro for **dynamical systems**, with a clear separation between *what* the model is and *how* we simulate or score it." + ] }, { - "data": { - "image/png": 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" + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.1 Separation of concerns\n", + "\n", + "**Dynestyx** extends NumPyro by giving you a standard way to work with dynamical systems. The key idea is **separation of concerns**:\n", + "\n", + "- **What** the model is: parameters $\\theta$, initial condition $p(x_0)$, state evolution (discrete or continuous time), observation model $p(y_t \\mid x_t, \\ldots)$. This is the `DynamicalModel`—you write it once as a generative model in code.\n", + "- **How** we simulate: *simulators* (e.g. `DiscreteTimeSimulator`, `SDESimulator`) unroll the dynamics step-by-step and generate state/observation trajectories. They interpret `dsx.sample(\"name\", dynamics)` as \"run the model forward in time.\"\n", + "- **How** we do inference: we can use either *simulators* (which sample latent states $x_{0:T}$ explicitly) or *filters* (which marginalize over them and compute $p(y_{1:T} \\mid \\theta)$). On top of that, we run standard NumPyro inference—**NUTS**, **SVI**, or others—to infer parameters (and optionally latent states when using a simulator).\n", + "\n", + "You write the model once; then you choose how to interpret it (simulator vs. filter) and which inference algorithm to use." ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Extract observations and states for plotting (and for inference below)\n", - "# obs_times and obs_values are the data we'll condition on for inference.\n", - "print(pred.keys())\n", - "print(\n", - " \"shapes:\",\n", - " pred[\"f_times\"].shape,\n", - " pred[\"f_states\"].shape,\n", - " pred[\"f_observations\"].shape,\n", - ")\n", - "\n", - "# Expected with num_samples=1 and n_sim=1:\n", - "# f_times: (1, 1, T), f_states: (1, 1, T, state_dim), f_observations: (1, 1, T, obs_dim)\n", - "obs_times = pred[\"f_times\"][0, 0, :]\n", - "states = pred[\"f_states\"][0, 0, :, :]\n", - "obs_values = pred[\"f_observations\"][0, 0, :, 0]\n", - "\n", - "# Plot\n", - "import matplotlib.pyplot as plt\n", - "\n", - "fig, ax = plt.subplots(figsize=(10, 3))\n", - "ax.plot(obs_times, states[:, 0], label=\"latent $x_0$\", color=\"C0\")\n", - "ax.plot(obs_times, states[:, 1], label=\"latent $x_1$\", color=\"C1\")\n", - "ax.scatter(obs_times, obs_values, label=\"observations $y_t$\", color=\"C3\", marker=\"x\")\n", - "ax.legend()\n", - "ax.set_xlabel(\"time\")\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2.6 Inference: conditioning on data\n", - "\n", - "To do inference given data, we pass the observed values along with the times and controls to the model:" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ - "# obs_times, obs_values, ctrl_times, ctrl_values are already defined above" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In dynestyx, we perform inference using the same tools as NumPyro, just with the correct interpretation of `dsx.sample(...)`. This requires two things:\n", - "\n", - "1. Data: **`obs_times`, `obs_values`, `ctrl_times`, `ctrl_values`** are passed to the model to specify what data to condition on. When `obs_values` is provided, those sites become observed (not sampled).\n", - "2. An Inference Method: for now, we use **`with DiscreteTimeSimulator():`**, which tells us HOW to condition the model on the data (same as for simulation).\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The result is a standard NumPyro model: we can run **NUTS**, **SVI**, or any other NumPyro inference on it." - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "sample: 100%|██████████| 202/202 [00:00<00:00, 246.21it/s, 31 steps of size 1.49e-01. acc. prob=0.93]" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.2 A first Dynestyx model\n", + "\n", + "For pedagogical purposes, we begin with a classic discrete-time linear-Gaussian system with controls. \n", + "\n", + "$$\n", + "\\begin{aligned}\n", + "x_{t+1} &= Ax_t + Bu_t + \\epsilon_t \\\\\n", + "y_t &= Cx_t + \\eta_t\n", + "\\end{aligned}\n", + "$$\n", + "with\n", + "$$\n", + "\\begin{aligned}\n", + "x_0 &\\sim \\mathcal{N}(m_0, \\ C_0) \\\\\n", + "\\epsilon_t &\\sim \\mathcal{N}(0, \\ \\Sigma) \\\\\n", + "\\eta_t &\\sim \\mathcal{N}(0, \\ \\Gamma) \n", + "\\end{aligned}\n", + "$$\n", + "\n", + "Written differently, we have:\n", + "$$\n", + "\\begin{aligned}\n", + "\\text{Initial Condition:} \\quad x_0 &\\sim \\mathcal{N}(m_0, \\ C_0) \\\\\n", + "\\text{State-transition:} \\quad x_{t+1} &\\sim \\mathcal{N}(Ax_t + Bu_t, \\ \\Sigma) \\\\\n", + "\\text{Observation model:} \\quad y_{t} &\\sim \\mathcal{N}(Cx_t, \\ \\Gamma) \\\\\n", + "\\end{aligned}\n", + "$$\n", + "\n", + "Furthermore, say we have prior belief about a subset of parameters in the model. Concretely, we will assume\n", + "\n", + "$$\n", + "\\begin{aligned}\n", + "A &= \\begin{bmatrix} 0 & 0.3 \\\\ \\rho & -0.2 \\end{bmatrix} \\\\\n", + "B &= \\begin{bmatrix} 1 \\\\ 0 \\end{bmatrix} \\\\\n", + "C &= \\begin{bmatrix} 1 & 0 \\end{bmatrix} \\\\\n", + "\\Sigma &= 0.1^2 I \\\\\n", + "\\Gamma &= 0.1^2 I \\\\\n", + "m_0 &= 0\\\\\n", + "C_0 &= I\n", + "\\end{aligned}\n", + "$$\n", + "\n", + "and place a prior over the single unknown, $\\rho$, in the system:\n", + "\n", + "$$ \\rho \\sim \\mathcal{U}([-0.9, 0.9]).$$\n", + "\n", + "This induces a generative model.\n" + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Posterior rho mean: 0.3294023275375366\n", - "True rho: 0.3\n", - "dict_keys(['f_observations', 'f_states', 'f_times', 'f_x_0', 'f_x_Tracedwith', 'rho'])\n", - "f_observations: (101, 1, 100)\n", - "f_states: (101, 1, 100, 2)\n", - "f_times: (101, 1, 100)\n", - "f_x_0: (101, 1, 2)\n", - "f_x_Tracedwith: (101, 99, 1, 2)\n", - "rho: (101,)\n" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "At the highest level, the idea is to create a NumPyro model that samples from this dynamical system. To do this, we use the `DynamicalModel` class in dynestyx, paired with the `dsx.sample` statement. " + ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "from numpyro.infer import MCMC, NUTS\n", - "\n", - "with DiscreteTimeSimulator():\n", - " nuts_kernel = NUTS(lti_model)\n", - " mcmc = MCMC(nuts_kernel, num_warmup=101, num_samples=101)\n", - " mcmc.run(jr.PRNGKey(1), obs_times=obs_times, obs_values=obs_values, ctrl_times=ctrl_times, ctrl_values=ctrl_values)\n", - "\n", - "posterior_sv = mcmc.get_samples()\n", - "print(\"Posterior rho mean:\", float(jnp.mean(posterior_sv[\"rho\"])))\n", - "print(\"True rho:\", rho_true)\n", - "\n", - "# What did we infer? The Simulator unrolled the model, so we explicitly sampled latent states:\n", - "print(posterior_sv.keys())\n", - "\n", - "# Print the shapes of each of the keys in the posterior samples\n", - "for key, value in posterior_sv.items():\n", - " print(f\"{key}: {value.shape}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "import numpyro\n", + "import numpyro.distributions as dist\n", + "\n", + "import dynestyx as dsx\n", + "from dynestyx import DynamicalModel\n", + "\n", + "\n", + "def fake_lti_model(obs_times=None, obs_values=None):\n", + " # sample the unknown parameter\n", + " rho = numpyro.sample(\"rho\", dist.Uniform(-0.9, 0.9))\n", + " # create the dynamical model depending on the parameter\n", + " rho_dynamics = DynamicalModel(..., rho, ...) # not real syntax\n", + " # sample from the dynamical model\n", + " dsx.sample(\"f\", rho_dynamics, obs_times=obs_times, obs_values=obs_values)" + ] + }, { - "data": { - "image/png": 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", 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" + "cell_type": "markdown", + "metadata": {}, + "source": [ + "At this level, you can think of writing `dsx.sample(...)` as rather abstract---at this point, we don't worry about HOW to sample the system. \n", + "\n", + "Why? Dynestyx allows us to have different \"interpretations\" of the `dsx.sample` statement, depending on the task at hand. To give a few examples of how we may interpret the dynamical system later, we may:\n", + "- Use algorithmic strategies (e.g., filtering or smoothing) to efficiently condition `lti_model` on available data.\n", + "- Specify key parts of *how* we simulate, which is particularly important when we use differential equations later on.\n", + "- Explore various approximations of the dynamical system (e.g., Gaussian states, linear observations, or discretizations of a differential equation), *without* modifying the underlying model.\n", + "- Freely experiment with these differing strategies as part of the Bayesian workflow discussed in the previous tutorial.\n", + "\n", + "Let's dive in a bit more how to build a `DynamicalModel`." ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# use ArviZ to plot the posterior distribution for rho\n", - "import arviz as az\n", - "\n", - "az.plot_posterior(posterior_sv[\"rho\"], hdi_prob=0.95, ref_val=rho_true)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### What the Simulator did: unrolling\n", - "\n", - "Using the **Simulator** effectively *unrolled* the model: instead of a single `dsx.sample(\"f\", dynamics)` call, the dynamics were expanded into explicit sample sites `states` ($x_0, x_1, \\ldots, x_T$) and `observations` ($y_0, y_1, \\ldots, y_T$). Pedagogically, the Simulator does something like:\n", - "\n", - "```python\n", - "# Conceptual unrolling (what the Simulator does internally):\n", - "x_0 = numpyro.sample(\"x_0\", initial_condition)\n", - "y_0 = numpyro.sample(\"y_0\", observation_model(x_0, u_0, t_0))\n", - "x_1 = numpyro.sample(\"x_1\", state_evolution(x_0, u_0, t_0, t_1))\n", - "y_1 = numpyro.sample(\"y_1\", observation_model(x_1, u_1, t_1))\n", - "# ... and so on for each time step\n", - "```\n", - "\n", - "So MCMC was inferring **both** the parameter $\\rho$ and the full latent state trajectory $x_{0:T}$ explicitly. The printed sample keys include `rho` and `states`, …." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For simple Gaussian problems like this one, unrolling can be an excellent strategy that NUTS can handle quite well! We obtain a `smoothing` distribution of the resulting data, without running a typical smoothing algorithm -- we will do this in later tutorials, and see its advantages and drawbacks depending on the type of data at hand. For now, let us compare the state recovery of the unrolled MCMC inference compared to the true states generated in the original model simulation." - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The `DynamicalModel` class can be instantiated with three main ingredients:\n", + "- `initial_condition`: can be any NumPyro distribution\n", + "- `state_evolution`: can be one of two classes\n", + " - `DiscreteTimeStateEvolution`:\n", + " - A callable $(x, u, t_\\text{now}, t_\\text{next}) \\mapsto \\ $ `numpyro.distributions` object (which can include things like categorical distributions)\n", + " - `ContinuousTimeStateEvolution`: has fields\n", + " - `drift`: A callable $(x, u, t) \\mapsto \\ \\mathbb{R}^{d_x}$\n", + " - `diffusion`: a `Diffusion` object, e.g. `ScalarDiffusion`, `DiagonalDiffusion`, or `FullDiffusion`\n", + "- `observation_model`: A callable $(x, u, t) \\mapsto \\ $ `numpyro.distributions` object\n", + "\n", + "It also requires specification of the key dimensions in the problem:\n", + "- `state_dim`: $\\text{dim}(x_t)$\n", + "- `observation_dim`: $\\text{dim}(y_t)$\n", + "- `control_dim`: $\\text{dim}(u_t)$\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "import jax.numpy as jnp\n", + "\n", + "from dynestyx.models import DynamicalModel # noqa: F811\n", + "\n", + "# for convenience, we can define \"fixed\" things in the model outside of it.\n", + "# this is not required, but it helps keep the model clean.\n", + "state_dim = 2\n", + "observation_dim = 1\n", + "control_dim = 1\n", + "\n", + "# Create the known matrices B, C\n", + "B = jnp.eye(state_dim, control_dim)\n", + "C = jnp.eye(observation_dim, state_dim)\n", + "\n", + "# create the initial condition as a distribution\n", + "initial_condition = dist.MultivariateNormal(jnp.zeros(state_dim), jnp.eye(state_dim))\n", + "\n", + "# create the observation model as a callable mapping to a distribution\n", + "observation_model = lambda x, u, t: dist.MultivariateNormal(\n", + " C @ x, 0.1**2 * jnp.eye(observation_dim)\n", + ")\n", + "\n", + "\n", + "def lti_model(rho=None, obs_times=None, obs_values=None, ctrl_times=None, ctrl_values=None, predict_times=None):\n", + " # sample the unknown parameter\n", + " rho = numpyro.sample(\"rho\", dist.Uniform(-0.5, 0.5), obs=rho)\n", + " A = jnp.array([[0, 0.3], [rho, -0.2]])\n", + "\n", + " # create the state evolution as a callable mapping to a distribution\n", + " # Crucially, this depends on A, which depends on rho, which is unknown.\n", + " # Thus, the state evolution MUST be defined within `lti_model`, not outside.\n", + " state_evolution = lambda x, u, t_now, t_next: dist.MultivariateNormal(\n", + " A @ x + B @ u, 0.1**2 * jnp.eye(state_dim)\n", + " )\n", + "\n", + " # create the dynamical model\n", + " dynamics = DynamicalModel(\n", + " control_dim=control_dim,\n", + " initial_condition=initial_condition,\n", + " state_evolution=state_evolution,\n", + " observation_model=observation_model,\n", + " )\n", + "\n", + " # sample from the dynamical model\n", + " return dsx.sample(\"f\", dynamics, obs_times=obs_times, obs_values=obs_values, ctrl_times=ctrl_times, ctrl_values=ctrl_values, predict_times=predict_times)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.3 Making \"data\": observation and control trajectories\n", + "\n", + "Dynestyx models take trajectory data as keyword arguments: `obs_times`, `obs_values`, `predict_times`, `ctrl_times`, and `ctrl_values`.\n", + "\n", + "- **`obs_times`** and **`obs_values`**: Always provided together. They represent **observed data** — times $\\{t_k\\}_{k=0}^K$ and values $\\{y_k\\}_{k=0}^K$ at which we have measurements. When provided, the model is conditioned on these observations.\n", + "- **`predict_times`**: Times at which to predict or simulate — defines the time grid for the solver/simulator. Use this alone for pure forward simulation (no data); use with `obs_times` when predicting at additional times beyond the observed data.\n", + "- **`ctrl_times`** and **`ctrl_values`**: Control inputs; provided together; must align with the union of `obs_times` and `predict_times`.\n", + "\n", + "Our first step will be to simulate data from the generative model. To do this, we define the times at which we should simulate (`predict_times`) and a synthetic control sequence." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "import jax.random as jr\n", + "\n", + "# For simulation: predict_times defines the time grid (no observed data yet)\n", + "predict_times = jnp.arange(0.0, 100.0, 1.0) # T=100 steps\n", + "ctrl_times = predict_times # same times for controls\n", + "\n", + "# create a synthetic control sequence as i.i.d. Gaussians\n", + "# (in practice, this would be an array of control inputs that we have observed)\n", + "ctrl_values = jr.normal(jr.PRNGKey(0), (len(ctrl_times), control_dim))\n", + "\n", + "# For an autonomous system, we would simply omit ctrl_times and ctrl_values." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.4 Interpreting the model with a Simulator\n", + "\n", + "To generate data, we interpret `dsx.sample(\"f\", dynamics, predict_times=..., ctrl_times=..., ctrl_values=...)` using a **Simulator**. The `DiscreteTimeSimulator` unrolls the model step-by-step at the given times. For pure simulation (no observed data), we pass `predict_times`, `ctrl_times`, and `ctrl_values` directly to the model." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## How does this interpretation manifest under-the-hood?\n", + "\n", + "The `DiscreteTimeSimulator` simply \"unrolls\" the dynamical system into a normal NumPyro probabilistic program. This internally does something like the following, but more efficiently using `jax.scan`:\n", + "\n", + "```python\n", + "def simulated_program(...):\n", + " # Probabilistic program before dsx.sample\n", + " # ...\n", + " # dsx.sample(...):\n", + " \n", + " T = len(times) # times = predict_times for simulation, or union of obs_times and predict_times\n", + "\n", + " x_prev = numpyro.sample(\"x_0\", initial_condition)\n", + " y_0 = numpyro.sample(\"y_0\", dynamics.observation_model(x=x_prev, t=times[0]))\n", + "\n", + " for t_idx in range(T-1):\n", + " t_now = times[t_idx]\n", + " t_next = times[t_idx+1]\n", + "\n", + " x_t = numpyro.sample(f\"x_{t_idx+1}\", \n", + " dynamics.state_evolution(x=x_prev, \n", + " t=t_now, \n", + " t_next=t_next))\n", + " y_t = numpyro.sample(f\"y_{t_idx+1}\", \n", + " dynamics.observation_model(x=x_t, t=t_next), \n", + " obs=obs_values[t_idx+1])\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.5 Predictive (for generating synthetic data)\n", + "\n", + "We use NumPyro's `Predictive` to generate samples from the model. With `DiscreteTimeSimulator` in place, we pass `predict_times`, `ctrl_times`, and `ctrl_values` to produce one trajectory—states and observations—at the given times.\n", + "\n", + "Here, we generate a single synthetic dataset with $\\rho = 0.3$\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "from numpyro.infer import Predictive\n", + "from dynestyx import DiscreteTimeSimulator\n", + "\n", + "rho_true = 0.3\n", + "with DiscreteTimeSimulator():\n", + " predictive = Predictive(\n", + " lti_model,\n", + " params={\"rho\": jnp.array(rho_true)},\n", + " num_samples=1,\n", + " exclude_deterministic=False,\n", + " )\n", + "\n", + " pred = predictive(rng_key=jr.PRNGKey(0), predict_times=predict_times, ctrl_times=ctrl_times, ctrl_values=ctrl_values)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Shape convention note:** simulator outputs now always include a leading `n_simulations` axis, even when `n_simulations=1`. Under `Predictive`, there is also a leading `num_samples` axis. In examples below we use a helper that removes only leading singleton axes for plotting/conditioning." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now extract and plot the generated data:" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "dict_keys(['f_observations', 'f_states', 'f_times', 'f_x_0', 'f_x_Tracedwith', 'f_y_0', 'f_y_Tracedwith', 'rho'])\n", + "shapes: (1, 1, 100) (1, 1, 100, 2) (1, 1, 100, 1)\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Extract observations and states for plotting (and for inference below)\n", + "# obs_times and obs_values are the data we'll condition on for inference.\n", + "print(pred.keys())\n", + "print(\n", + " \"shapes:\",\n", + " pred[\"f_times\"].shape,\n", + " pred[\"f_states\"].shape,\n", + " pred[\"f_observations\"].shape,\n", + ")\n", + "\n", + "# Expected with num_samples=1 and n_sim=1:\n", + "# f_times: (1, 1, T), f_states: (1, 1, T, state_dim), f_observations: (1, 1, T, obs_dim)\n", + "obs_times = pred[\"f_times\"][0, 0, :]\n", + "states = pred[\"f_states\"][0, 0, :, :]\n", + "obs_values = pred[\"f_observations\"][0, 0, :, 0]\n", + "\n", + "# Plot\n", + "import matplotlib.pyplot as plt\n", + "\n", + "fig, ax = plt.subplots(figsize=(10, 3))\n", + "ax.plot(obs_times, states[:, 0], label=\"latent $x_0$\", color=\"C0\")\n", + "ax.plot(obs_times, states[:, 1], label=\"latent $x_1$\", color=\"C1\")\n", + "ax.scatter(obs_times, obs_values, label=\"observations $y_t$\", color=\"C3\", marker=\"x\")\n", + "ax.legend()\n", + "ax.set_xlabel(\"time\")\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2.6 Inference: conditioning on data\n", + "\n", + "To do inference given data, we pass the observed values along with the times and controls to the model:" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "# obs_times, obs_values, ctrl_times, ctrl_values are already defined above" + ] + }, { - "data": { - "image/png": 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", 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" + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In dynestyx, we perform inference using the same tools as NumPyro, just with the correct interpretation of `dsx.sample(...)`. This requires two things:\n", + "\n", + "1. Data: **`obs_times`, `obs_values`, `ctrl_times`, `ctrl_values`** are passed to the model to specify what data to condition on. When `obs_values` is provided, those sites become observed (not sampled).\n", + "2. An Inference Method: for now, we use **`with DiscreteTimeSimulator():`**, which tells us HOW to condition the model on the data (same as for simulation).\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The result is a standard NumPyro model: we can run **NUTS**, **SVI**, or any other NumPyro inference on it." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "sample: 100%|██████████| 202/202 [00:00<00:00, 246.21it/s, 31 steps of size 1.49e-01. acc. prob=0.93]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Posterior rho mean: 0.3294023275375366\n", + "True rho: 0.3\n", + "dict_keys(['f_observations', 'f_states', 'f_times', 'f_x_0', 'f_x_Tracedwith', 'rho'])\n", + "f_observations: (101, 1, 100)\n", + "f_states: (101, 1, 100, 2)\n", + "f_times: (101, 1, 100)\n", + "f_x_0: (101, 1, 2)\n", + "f_x_Tracedwith: (101, 99, 1, 2)\n", + "rho: (101,)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "from numpyro.infer import MCMC, NUTS\n", + "\n", + "with DiscreteTimeSimulator():\n", + " nuts_kernel = NUTS(lti_model)\n", + " mcmc = MCMC(nuts_kernel, num_warmup=101, num_samples=101)\n", + " mcmc.run(jr.PRNGKey(1), obs_times=obs_times, obs_values=obs_values, ctrl_times=ctrl_times, ctrl_values=ctrl_values)\n", + "\n", + "posterior_sv = mcmc.get_samples()\n", + "print(\"Posterior rho mean:\", float(jnp.mean(posterior_sv[\"rho\"])))\n", + "print(\"True rho:\", rho_true)\n", + "\n", + "# What did we infer? The Simulator unrolled the model, so we explicitly sampled latent states:\n", + "print(posterior_sv.keys())\n", + "\n", + "# Print the shapes of each of the keys in the posterior samples\n", + "for key, value in posterior_sv.items():\n", + " print(f\"{key}: {value.shape}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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FARJIJCUlYd++fYiKilI///vvvwgKCqqyfRCbkokZ80PUcJmzg61aOXFIq1pV9nlE5aYjqkLxKZm6zm/9qWvw4lrdp3+e5r62IpmZmbqgoCCZe6f75JNP8u9PSkrS9ezZU90/b968Ur/f+fPn1aWwyMhIXZs2bdT7ffnllwUei4+P1+3bt0+Xk5NT4P60tDTdlClT1GvGjBmjq2opGVm66fP2qu9B0EtrdYuCw6r8M4nKij0EVKVkqODn3WFo7OeK9U/2VWvLk3VYunQpJkyYgPbt2+PQoUMFHjtw4AA6d+6MNm3a4OjRoxX+rIULF2LKlCm45557sGLFilK9JiIiAvXr10fNmjURGxuL6phl88rKo2rtDvHkoKZ4anBTrpRIJoM5BFRlzkcn49fgcHX77VFtzT4YuHjxovrn3b9/f6SkpOCZZ55RDYqMi3fq1Alr1qzJf+6yZcvQvXt3uLq6olatWnjiiSdUt3lhqampeO+999CxY0e4ubmpi4yRL1iwoNht2LFjhxpHb9eunWrI5LNbtGiBl156CfHx8UWe//fff6ttnjZtmmr0Hn74YdSpU0eNv0tjPHfuXFSVdevWqeuxY8cWeUz2V6NGjVSXvuzXinJw0IpbGQ4XVMVrKsLezhYfjGmnlkwWsoyyVOzMyilbLgVRVWFAQFXmw42nkJOrU2sV9GzsYzF7OjMzU42L//rrr6rxlsvhw4fV2emWLVvw6aefYvLkyXB3d8ftt9+OnJwclfR2//33F3gfGcOWhLhXXnlFjanLGPhtt92GU6dOqQZcxssLe/755/HTTz+pQEC2QS6JiYn44IMP0KdPHyQnF5/JLsGCfNbq1avRt29f9O7dW33OzJkz8eOPP1bJfpJ9om/8i6O/X5IFK0ISBz/++GN1e8SIEaV6jSQgzp49u0yvqQwSnD0ztLkqdSyzbpfsu4QpPwUjLiWz2raBqERlHmQgKoWQ0Ov546VnIhMtYp+FhoaqMWe5DBw4UJecnJz/mIyFy/1NmjTR1axZUxcSEpL/2OXLl3X+/v7qccMx8OHDh6v7nnzySV16enqBMfEuXbqoxzZs2FBgG9avX6/GxQ3Ja2fNmqWe/+abbxZ4bNu2bfnbPHHixAKfs3LlSnV/YGBgkd+1X79++a8r7aVwPoDsB7n/8OHDxe7Pp556Sj3+xRdf6MrizJkzuqlTp6ocgKFDh+rc3NzU+zz00ENFcgUMzZgxQ73u7rvv1gUEBKjX9O7dWxcTE6Mzhq0nI3WtX9+ovid9P/jLYr4nZL6YQ0BVMs1wzDe7cCA8Xq0GJ0vEWgLp2pZsdFtbW5w8eRLNmjXLf0ym0MnQgExje+211/DWW28VeK0ML0jPwbx589TZv4ypyzBB165dsWfPHvWehg4ePKjOoO+++26sWrXqltsmwxEeHh5qKGH//v0FhgwGDBigHrtw4QJ8fAr21EgGvnTbh4aGqhkAeu+//77qQSgL6QGRXgo96YqXM/GzZ8+qWQGFyX5655131EV6SUpLZgVIL4chGZKRfS6/Z0ns7e1Vb42eDP3I8TD8vavbmWtJmLkgBJdi0+DmZI8vJ3XEgBb+Rtsesm72xt4Asjwbj0WqYKCGgx2eHtwUlkYaEMNgQEiDLtPhJCAYOnRokdfIeLm4evWqupbpcWLUqFFFggGhzynYu3dvkccuX76s8hWkwZbhAv18fmmApfEtjiTwFQ4GhPweEhDIdhk2jJKTYKok6JCgUxr38PBwrFy5Em+++SY2bNig9mtJDXx2dra6lt9VpipKfQIJiJYvX66GdoyhWS13rHq0Dx5auB97Q2MxY0EIXrmjJe7vG8RkQ6p2DAioUkmC1AcbtTPLB25rBH8PZ4vbwwEBAcXeLw14SY/rH8vIyFDX+kS6V199VV1KIvPrDX3yySeqsS6uCM/N1KtXr9j7Jc/BcLsqk/zOMr4viZPFkcRMw20oKzs7O9VjI70vEgSMGTNG5V0YJncWR5IqJdFRemckIJAem3PnzqkEUGPwdnXEwpnd1YycxSGX8M76k6rn4O172ph9Ii6ZFwYEVKl+2xuOi9dT4evmaLGLFxV3Rl+Wx4X+rF7Odhs3blyqz5WhhWeffVZV5/v8889Vl3ft2rXVjAEhRXb0PRDl2SZDlTFkEBgYqAICmd4nQxmFyf1CelYqShI6JQDZuHGjSvoszcwB+VwZeli/fj2Cg4MxcOBAGIujva0aWpMeg7fXncCy/RG4eD0F3/ynsyp/TFQdGBBQpUlKz8LnW7Qu66cGN1NjonTzM3YZMpBGvjSka1zImPvUqVOL5BDITIXKIg3r9u3by/QaCVAMAwKpPyAzDaTmwPDhw4s8X+4XxQUL5cnel2qEMoQgQYjkc5SGr6+vupaKh8Ymv8OMPkFo7O+GxxYdQMjFOIz8aid+nNoFLeuUnBtBVFk47ZAqzXfbL+B6SiYa+bliQleuV3AzQ4YMKdDIl4Y0dCV1/0vdAxlXryySjCjvV5aLdL0b0k/nkzH6wiRpUpIcpRZCZST1yXtdunRJJRXqG/lbkRwESVAUpe2lqQ79mvlh5SO90dDHRa2BIAm6m49XXrBHVBIGBFQpIhPS8eO/F9TtF4e1gIMd/7RuRooWSVAgyW2PPvqoSg4sTM6u5UxdT5/IKHUIDHMITpw4gRdffNHk/pKlG1/G+OX3kBkWhrkD8juL4npHpLaCFFsqnFAptRyK6wU5ffq0qvsgQcl9992ncgv0Fi9eXGwlRCnSNGvWLBVISB6BJF2akib+bvjj0d7o1dgHqZk5eHDhfnz119lKDfqICmOfLlWKT/48jfSsXHRpUBNDuXBLqcvtDhs2DHPmzMGiRYvQoUMHlQeQkJCgivXIGe+TTz6pniOmT5+uCvBI0lzz5s1VUpw0bNK1L0MP0oCGhYWZzF+0VAKU31FWGpTEP1nISMbtpdqi5DpIYl/hoQ9x/vx59XsUTkaU3/2pp55SQxEyjVEaR3meTLOUnAwp6iRVHw1JQDVp0iQ1y0MaflnpUGZpyHCFFHGSBNCyLLBUnbxcHLFgRjf8d80J/LInDB9tPoNjlxPx0fj2HI6jKsHTOKqwU5GJWL5fSxB7ZURLk/znaor8/f2xa9cufPHFF2jVqpXqRpfudQkGpAH73//+h+eeey7/+TJtMCQkRJ0NS+KcVB2Uxk3m3//2228wRb169VLbLDMAJJNftlnG+mW2RFkbYsmdmDhxouph2LRpk6rPIDkD0tMyf/58bNu2LX82h2Gi4yOPPKJmMkhvjAytyP6VoQp5P1mauWXLljBV0tP21qg2KuFQVgvdeDwSo77eiQvRxVekJKoIFiaiCrt/QQi2nIzC8La1Mede0+p6JbIUB8Lj8PDC/biWmAF3J3t8NrEDBrXkMspUedhDQBVyMDxOBQNSl/25oc25N4mqSKfAmljzeB81LJeUkY2ZC/apWT25ucwroMrBgIAq5JM/z6jr0Z3qoZFfwe5aIqpc/u7OWPRAD0zpodVu+HTLGZVwKFN+iSqKAQGVW8jFWOw4GwN7Wxu1tjsRVU8RI8kr+HBMO5VX8OeJaxj59U6ci2JeAVUMAwIqt2/+Pq+ux3Wph/reLtyTRNVofNf6WPpQT9T2cMaF6BSVbCjBAVF5MSCgcjl7LQl/nYqCJInPus10iroQWZMO9b1UXkG3IG8kZ2TjgZ/34ett51ivgMqFAQGVy487QtW11BwI8jXOojBEBPi5O+HX+7tjak8tr+B/m07jxd+PIDNbWy+DqLQYEFCZRSWlY+XBy+q2pS5gRGROpF7BmyPb4M27W6sZP0v3RWDavL1ISGOyIZUeAwIqs593hSEzJxedAr3QuYE39yCRiZjaqyF+mtoVro522HX+uloH4VJs8ctPExXGgIDKJCUjW5VRFewdIDI9A1r45ycbysyDe+bsxJGIeGNvFpkBBgRUJsv2XVLdkLIS25BWtbn3iExQ67qeanGkVnU8EJOciXt/DGZQQLfEgIBKLTsnFz/t1JIJZ/ZtBDsZrCQik1Tb01n1FHRtWBNJ6dn4z4/BOBqRYOzNIhPGgIBKbdPxa7gUmwZvV0eM7VSPe47IxLk52WPe9G6q3HFiejbu/XEPgwIqEQMCKhVZavb7f7RCRFI2tYbjjTXnici0g4L5M24EBf/5KRjHLrOngIpiQEClsjc0FocjEuBkb4spefOdici8goLODWqqHCDJKWBQQIUxIKBS+SGvENGYzvXg6+bEvUZkjkHB9K5qujCDAioOAwK6pfDrqdh6SquRPqN3EPcYkZlyd3bAghnd8oMCGT44foXDB6RhQEC39Muei9DpgNua+aGJP5c4JrKEoKBjoBfiU7Mwde5ehF1PMfZmkQlgQEA3lZqZjSUhl9Ttab2YO0BkSUGBvk7BlJ/2qpLkZN0YENBNyZoFkpncwMcF/Zv5W9/ekq6R7AztIreJLISHswPmz+iKQG8XhMemYtrcECSlc+0Da8aAgG461XDBrovq9n09G8LWGgsR5WQCfzyiXeQ2kQXxd3fGzzO6wdfNESeuJmLWz/u5SqIVY0BAJdp9/jrOXEuGi6MdxnVhISIiS9TQ1xXzp3dTsxB2X7iO//vjmDoZIOvDgIBKND+vd2B0pwDVvUhElqlNgCe+mtxRLZ28ZN+l/O8+WRcGBFSsiLhUbDmpTTWc2rMh9xKRhevf3B+vDG+pbr+19gR2nI029iZRNWNAQMVavPcScnVA7yY+aFrLnXuJyArM7BOEsZ3rqe/+k4sPISqRMw+sCQMCKiIrJxdL92lTDSd341RDImthY2ODd+5po6YjxqZk4tllh5Er0QFZBQYEVMRfp6IQlZShMo+HtKrFPURkRZzs7fDFpA5q3ZIdZ2Mwj/kEVoMBARXx295wdT22c3042vNPhMjaNPF3x2t3tlK3P9hwCievJhp7k6ga8L89FXApNhXbz2jJRBO71ufeIbJS/+keiMEt/ZGZk4snfjuI9KwcY28SVTEGBFSA5A7o8pIJZX4yEVlvPsEHY9qp1U3PRiXjvfUnjb1JVMUYEFC+7Jzc/HULJnUL5J4hsnI+bk74aFw7dXvB7jBsOxVl7E2iKsSAgPJtzUsm9HF1xNBWtblniEjVJ5jeW6tF8vzyw4hOyuBesVAMCKhoMmGXekwmJKJ8Lw5rgRa13dXKiC8sP8zSxhaKAQHlVya8kUzI4QIiusHZwQ6fT+yoThS2nY7GmiNXuXssEAMCUpaGaMmEvRr7IIjJhERUSPPa7nhsQBN1+79rTiAhjUslWxoGBIScXB2W7Y9Qe2IikwmJqAQP9muERr6uiEnOwEebTnM/WRgGBKSWOb6akA4PZ3sMZWVCIrpJFcO3R7VRtxcGh+HQpXjuKwvCgIDw+wGtd+Cu9nXVWCERUUl6NfHFPR0D1BDjG6uOca0DC8KAwMolpWdhwzEtQUhWOSMiupWXh7eAq6MdDkckYM2RK9xhFoIBgZVbf/Qq0rNy0djPFR3qexl7c4jIDPi7O+Ph/o3V7Q83nmZZYwvBgMDKLc9LJpSFjKRUKRFRadzftxHqejrjcnwafvo3lDvNAjAgsGIXY1IQcjEOtjZQY4JERKUl+UbPD2uubn/z93lcT2YFQ3PHgMCK6ZMJ+zb1Q21PZ2NvDhGZmZHtA9AmwAPJGdn4YutZY28OVRADAiuVm6vDigOX1W0mExJRedja2uCVO1qq278Gh+NCdDJ3pBljQGCl9ly4rsb+3J3tMYS1B4ioAtMQB7bwR3auTiUYkvliQGDlyYR3s/YAEVXQy3e0ULlIG49H4mB4HPenmWJAYKW1B9bn1R4Yw9oDRFRBTWu5Y0wnrY7Jx5vPcH+aKQYEVmjD0UhVe6CRnys6svYAEVWCJwY1hYOdDf49F6PKoZP5YUBg1bUH6rH2ABFVivreLvlLp3/6J3sJzBEDAitzKTYVey/GQmoQsfYAEVWmRwc0gaOdrfofsz8sljvXzDAgsDKrD2t1x3s28kEdzxrG3hwisiBSz0R/ovHN3xeMvTlURgwIrIhOp8MfB7XaA6M6sDIhEVW+Wf0aqR7ILSev4ey1JO5iM8KAwIqcuJqIs1HJcLS3xbC2tY29OURkgRr7uWFoXm2T7/5hL4E5YUBgRVYd0oYLBrXwh4ezg7E3h4gs1EP9tJUQVx26jKsJacbeHCol+9I+kcxbTq4Oq/MCgpFVPVywfz5wcSdw7RiQEg2kxQF2joBbLSCgE9B+EtB0SNHXZaYAJ1YDESFAxF7g2glAl3Pj8SePADUblH175o0Awv4t3XMb9AGmr7vxc+gO4MLfQHoccGot4N8K6PMU0Gpk0ddmZwLf9ASunwNGzgE63gujys0FDv4MHF4CRJ8EMlMB99pAo/5A7ycBH+2fdplE7AeOLQcu7wcSLgOp14HcbKBGTcCvOdBsGNB5GuDkBqOKOgXs/R4I3Q4kSs0NHeDqC/i1ABr2BXo/UfQ1145rrwnbDSReBrLSAEc3wDsIaDwQ6PEw4OZftu2IPgMcWghcPgDEhQFpsUB2OuDkAfg0AZoMAro+ALj6FHxdTjbw76fA4UVA/CXAyV07boPfAGo2LPo58ne64E7tODx+AHDxhjF1DKyJ7kHeCA6NxU87QvHana2Muj1UOjY6GVgmi7frfAwm/xAMD2d7hLw2GE72dlX3Yf9rCqRE3fw53WYBw/9X8L6rR4Dv+pb8muoOCM5vAxaOBnS5gK291jikx2uPjfoW6DCp4Gt3fAxs/S9QrxswczPUQKqxSHC1aAJwcUfxj9s5AWN/AlreVbb3/fMNYOdnN3+OdyNg+kbAXes2rnbSkG59q2AwWdjshII/H1sBrHhAC25K4uIDTF0D1Gpd+m0J+QlY98zNn+PqB0xbpwVUeisfAg7/pt2WQFofeMnth3YCbn4Fg4dv+2hB34hPgK4zYQq2nY7C9HkhcHW0w66XBsHThb2Spo5DBlZi1UGtd2B42zpVGwzoSQPq21w7s5IzG2fPgo/LmdilkJu/XhrgytCwN9Dy7uIvftrCLPnqdrhxe/sHWjDg6Ao0HwE8dRSo3117bNs7BV8nZ8v/fAzY2GqBjjGDAbH2mYLBgJwZNxkC2OfNLMnJAJbP0M5gy8O9LlC/B9D0dsCnacHHYi8Af78Ho9jzLbBl9o1gQI6H9Oo0HQrU7Vj831R2BrD26YLBgHdj7TXSWOtJo7zx5fJtl4svUK+r1oNSq23Bx6QXzfB9r5+/EQz0fAx47gzwwDbAxg5IvqZ9dwzt/U4LBuq0BzpPh6no38wPLWq7IyUzB7/suWjszaFS4JCBFcjIzskvVVzlwwVixMdAwz4Fuy3ljHXhWCB81437wncD9bve+Fm6dIe+A9Trov1zk0ZNukwrasArJT82944bt6Xx6Hr/jZ+vHLrR+Nk5APZOQOvRwKVgIOESkBKjbbPY/CqQlaL9QzYMKqpSThZwdjMQsU/rStaLPAYcWXzj51ajgHHztSDl6mHgh4Fa45eTCfz1X2DCwtJ/Zos7gXYTgFqFuoCDvwM2vHDj5/A9FfnNgKiTwKFF2vBDaYc2EiKALW8U7KkYO6/g8ZB9dm5Loc86caPnR8iQwn2rZSk/bbjri47atZDhrLII7AHc/5c2VGYYJJ7eAPw2sfj9JcdIT4bXRJ12Ws9E5BHgat7fpUiOAv5+X/54geEfadtsImxsbFQuwVNLDmHezou4v28jODtUw8kIlZvp/PVQldl2KhpJ6dmo4+msxvWqXKu7i45hyll24XF3h0J1EDzqAr0e0/6JFn6sKkjDaRigyBmhjBfrFXuWbzjClvd46D/A8ZXa+O2g11HlJFDZ8CLwcXNg8WTg7J8FHzcMBkSvx2/8LhJoBfW78djpjUCaQWN4KxLAFQ4GDBsuPQdnlFnKdS2w+K4fMKcHsOsLLZAsS/e8jM/rjf6haHAmgV3zOwrd51jwZ9lH+oZVjqmXwTCVjOWXhTTi9ToX/VuSbXD2Kn5/ldi7pP/bM3j8z9eBjESg/USgfjeYmjvb1UGAVw1cT8nEsrwKqWS6GBBYAcn01a9sKOuXG4UktJ1cfeNn6f4Mug1GVbjrVfIaDNXJa0ySrmhnlnJGLQ2/8AzUEsFk/Hb989p9A1+rumSupEhg5xfAnJ7A9/2A4G+1Lmzh6FLwuQWGYmyA2u0KPm7YSOZmFTzjLK/DhYKQRgNK9zrZryfXAovv1QIc6WXQb48MG0mvTGmd+7Ng74D03mz/EPj9AWDVo1qwkVpM9TwZ8vDQFuZRTqzS8lmy0oGTa7TkWMPelsoggZhhr4Th/pKARE8/dBB5VEuyFTL0IcKDtf0uCYpD/gtTZG9niwf6akH2D/9cUMnNZLo4ZGDhEtOzsPVUVPUNFxhaMUvL1JZ/fHJWK2cywtYBuOP9gklU1U3Oio8uK9goSL6DoX4vaEmFcpZ6eh3w6fYb/8QHvqpdS8McfUprdDvPqNxtlAZJPvfQb8D5vwomyTm4Ai2GA23HAY0HFXxd7PkbtyVAsS90BiyJaYZkVoTkeZTFgZ+1ngk5I5cxb8PPlFyFvs/e/PWSdS+N3dHlWua9IRlrl99LhmcMk+duRgIzfYMp0hOAL7toAY+hv94GRn9fsJdA9o/ct3iS9joZDiqS3GoDtBsPDHkT5SJDBDIEIkGlzBqIOn7jMWngb3+3YDAjPS6yf3Z/pf2dSiAjx1+OnQxryQyS9c9pvQb9Xyr77IdqNL5rfXy+9SzCY1Ox4dhV3NmurrE3iUrAgMDCbTwaiczsXDT1d0PLOmXs7qwoOfOTcXVD9s7AHR8CHafAqA4uBLJSC/YOFO6qbTwAmLwMWPmgNu1QGr+6nW5MO0y6piUeGo7fyu8svQiS/CX/vFvfA7S8s2zbps78FgHHVgIZBtnwEkhJ0CKNpQQDMgxTHGnU9PRJhIYKD8ek5wVqZSFn0IY9PnqSqHnX58VPO5Tpf0eWaA2dBFGGJOmxzVig7diCwzalJYGaYcCk7z0pTILSpVOBB7YCtdsWTDydsRlYNA6IDy/6OunNkqma5R3Kijlb/P5q0Bu457uiMzLu/kpLbMyfduim9SJIrogESXt/0PIJZL91k7/PRCDkRy0vR4IOSaTs9oAWXBiZi6M9pvZqiM+2nMW3289jRNs6XFTNRDEgsHB/5A0XjOoYYBpfQmlU1zwBnNmoJbqVpUu4sshMW/nnqSddrh0mF//coL43zp5HzSm4vfrx23YTgcDuwKZXtTM6QzJnXzLFby80K6EkF/8F5o8wuMNGy6mQhlLOmMs8JFFMF21VzjSWRk+SLu9driXCGZo7tGBj6xEAtBkNtB1f9LllJY1gYTLkM3auts9k6GDPnLznZmhTROXvT09qNax+XHtMSI2AmkFaoyvBndQz+L6/1njLNleWsJ3aMNCEnwv2UNnZA/2e1y7F5VpIT4eQ4Fr+Bn8aovX06EntDOnFmbLSJHILpvZsiO+2X8Cxy4nYee46+jTNS8Ylk8IcAgsWmZCO3Reu5+cPVLtXrwBvxAPPnQMm/lZwetrp9dpZjjFIV3dc6I2fJRgoayEdyQo/YjB+K4V69MFAl5nAixeBLnlDCHK/PF4ahRtr6aa+81Otm7i0wYBsk54M2RRmmHgnnA2eX1ojPtLm8r98GXhwR8GkQmlA/3ik6O9i+KOcuUqvyqA3Kh4MlJTsN+BVbYaCJAYOfrPgfpHAS0+mXq565EYw0Gkq8Ng+4D/LgScO3sjBkKBDpieWp0dFCiHJ/no1Eng0RAsS9TKTtLoDkmdTGltnaz0iks/QqJ82BVaCAcnLkdkRUq9Dclwyk4HVxRRgMoKaro6Y0LW+ui29BGSaGBBYsDWHr6j/yV0a1FRrlRuF9EpIF6d0cY9fUPAxCQqMnkxoo1WKK4vcnLzxW8kzeFHr7pUxYj0ZUpBGqPdTBZPISkNmWuiTxoR0sUvG/Te9tYI70n18K3J2qyfT5WSevaGkqyU/v6wkkJIG/Z5vbyRhimtHgfiwgs+VqnwyZKSvVSBj9h81BdY8qTXQFem5kIBACgcZMhx6kDwBT4PEQcOZFcdXFKxBIIGcvjdNhmVkmqWeNMSlDe6KI0MOfs20HiPDolASRF3ed+vXS+6FDHc5uNzoddL/7TXopQUIUrxL3+Ml9QliDYJfI7q/bxDsbG3w77kYHI0oVBiKTAIDAisYLhiZtxyp0bnVLlqQpbpJQ2Q4D10aKd8yNoj75mpZ3zJ+2/2hG//Q9dzr3Gjc9Qwfvxk5o531N/BIsDZmrX8vyXSXgjuftQXmDtOGPKTruDiGtR3ktFzG+w3p6yvo8xIMG/KKKJysKHUaDN31mVZk587PbhR4koBFSl3LMMmnrYHNrxWch18WkoxoqPB0Sn0tAaGvH1FcgHQrJeUnVPX3QQImCUSlWJYkbeoDHP3flpSl1vPI+7tRj9+iamg1qVfTJb+n8tt/2EtgihgQWKhzUUk4fiUR9rY2Komn2hz4RcscL9xVLWep2/LGPfUM53dX1Kdtgdme2kVKFZdkr+QOGJyJ6hv00iowfvuBNtYrDCsx6qe2GTYchSs13op/C20o4unjwH9+1xLuVIKgTkscW/cs8HEz4Ndx2tQ4Q4ZntELm8+vPviUYMKxg2Ox2oIbBfPiDv97Yj3KRGvl6Mptg23vFJ91JkCXj7PlsAE+ti7gA2Q9dpmulnaXm/m0vAF6B2mOyfsCuL4HvbgO+6qqN+2eUYflcGV4xZFjUSrbPsOGX4kN6UnjKkAQo+v0lM0ykl6akv1vZP4b7S/afXkYysPEVIPp00W2V43Ds90LvW8waBYYO/qL1Tshwi9SWKPy3ZTilsiJ/e1Vo1m1akuOGo1cRdr0MNSaoWjCp0EL9kVequF8zP3i7Fpp2VpVkgZjgb7SuYSnKImeN8k9dznANz9BE56lF59rLfHQ9w3F+seRerQa/6HRf0dffiozRykIzepLF3WRw2d5DKuGp8duRBafqSQMjjZmQz5AzOJlmlv94H5SLrZ22jXKRsWuZwSBZ+hIUSDe3VCqU7H3D7mfJnpegQN+QSaKfDDtIAy1d8/rucSnIU5ZCStI4bn9fu0ijJPtPutbjLgIxhUogy7S+W61lIL0hMn1TKknKdsnvJTUAZOxb3k/GxqXUb2lzDFrdAwR8faNLX3pypLKgDN8YVgKUXhHpfcl/3ci8MtV5sxT2z9O2RxYR0icV6snvLVUHS0P2856vtYvse9+m2j6XMtcypGJIyhnf7H3lu7Mlb8rjsPcLJrfK35bst7Bd2vCA9CrJDBXh6g/4NoOpaFnHA/2b++Hv09H4YccFvD2qUBlnMioGBBZI1qtaddjIwwWSuFbSWKuUCO73UtGFdaQX4WbjqNJNr1fWhlxIA2k4JU+mZZVl5sWVgwbjtwbzxtX2DNGCAjn7lgWOpKa+foEnuV+qIFaUJP9JECQXGfqQojSFCwLpSSKiNDz6RZ1kmp/hVD8JrMb8WP5aEPL5cimOLO4k0+ZKS46BzOaQi6wDIT0eEkyVtDBTSWTa5/hfgJ/vvpFxb/g3o/+9ZbZI7TYFe2NkPH7TK1p3vLh+VrsYksBC9pkEaWUltQ3kUhxJtpVZBjf7W/zrHSA1RguQpFfHkHyXzm7Rpvh+3V2reqj/Ox8826TKGet7CSQgWHHgMl4Y1oJLsZsQBgQW6EB4PC7FpqlVxoa0rOYV5zpN0RK85AxWksqki12yt+U+mcYliU9Sg0D+CVc3w6mGsshNhzIsTyxdyBtf0rrs+z5TMEFNyD/dyUuAbe/eqEMg0+qkDoFku1f2lE85U5Uz6/4vF53Tr0+Gm7pam3omgZDU65dhHP3yx72eLHvuhCTpycwAmSonPUGSIyANj/QGyZi1ZOPL2bbUIihvIyTbLWV45SJrE5S1VLBngDbrQXqpjv+hBS1SDVG2T0o2S3a/JPUVJksbB/bUehXkb1c+WwJU+TuRngyZEijDS6UtlKR+Fzfg7i+1M3fJi5CxfOldkh4KKSRUqw3QYoRWV6Jw8ShDEtTIdkkwM6yYRaOklPSMjcBfb2lLN0tBK8kL6fM00LqSKitWop6NfNCslhvOXEvG7/sjML13OepOUJXg8scW6PVVx/Dz7jCM7hiATyZU00I7lkoaBZlCV1wdAiIql4V7wvDaH8fQyNcVW57pZ7yS6lSAafUlUYVl5+Ri3ZGrpjW7gIjIwD0dA+DuZI8LMSlqGiKZBgYEFmbn+etqZTEfV0f0blxoXjYRkQlwdbLH2C7asNuCXReNvTmUhwGBBRYjEsPb1lErjRERmaIpPbTpm3+djkL49VJWaaQqxRbDgqRn5WDTsUh1+y5jlComIiqlRn5uuK2Zn8rXXRhcqKolGQUDAguy/Uw0kjKyUcfTWZUrJiIyZVN7ar0ES0IuIS3TYLVKMgoGBBY4XHBnuzrM2iUik9e/uT/q1ayBhLQsrDtaxhLSVOkYEFiIlIxsbDmpVVTjcAERmQNZ7GhSN6109eK9xZTEpmrFgMBCSDCQnpWLBj4uaBtgOrXLiYhuZlzneiow2BcWhzPXyrB2BVU6BgQWYs1hrbtNVhOzqeyqeEREVcTfwxmDWvir24v3lmJ5b6oyDAgsQEJqFraf0ermc7iAiMyNfthgxcEINVuKjIMBgQXYdDwSWTk6NK/ljma1ylj7nYjIyGT6YV1PZ8SnZqn/Z2QcDAgswOq82QV3d2DtASIyP5JDML5rfXV7UTCTC42FAYGZi0pKx67zWi3wu9oxICAi8zS+S33IGkfBobG4EJ1s7M2xSgwIzJwsZJSrAzrU90Kgj4uxN4eIqFzqetVQdQnE4hAmFxoDAwJLGS5gqWIiMnMT84YNVhyIQFZOrrE3x+owIDBjl2JTcTA8XnWzSXVCIiJzNqCFP3zdnBCTnIm/Tmkzp6j6MCCwgN6Bno191FxeIiJz5mBnizGdA9TtpRw2qHYMCMzY6kMcLiAiyzKuszZssO10FK4lpht7c6wKAwIzdToyCaevJcHBzgbDWnO4gIgsQxN/N3RuUFMlS/9+IMLYm2NVGBCYqdWHL6vrfs384eniYOzNISKqNBO6aL0Ey/ZFQKfTcc9WEwYEZki+IPq1C0ayGBERWZjh7erAxdEOoTEpCLkYZ+zNsRoMCMzQoUvxCI9NVV+YwS1rGXtziIgqlZuTff7MqaX7WJOgujAgMEOr8pIJh7SqhRqOdsbeHCKiKqlcqC++lpSexT1cDRgQmJmcXB3WHb2x1DERkSWSxMJGfq5Iy8pRQQFVPQYEZmbPheuITsqAZw0H9G3qZ+zNISKqEjY2Nvm9BEs4bFAtGBCYae2B4W3rwNGeh4+ILNfoTgFqJUSpyHr2WpKxN8fisUUxIxnZOdhwjMMFRGQd/N2dMSBvwSMmF1Y9BgRmZPvpaCSmZ6OWhxO6BXkbe3OIiKrc+C711PWKA5e54FEVY0BghmsX3NmurupGIyKylgWPrqdwwaOqxoDATKRkZGPLyWvqNosREZFVLXjUiQseVQcGBGZCgoH0rFw09HFB2wBPY28OEVG1GZc32+DvM9FqlhVVDQYEZriyoUzHISKypgWP2tf3UnVY9EOnVPkYEJiBuJRMbD8TrW7fzbULiMgK6YcNVnAFxCrDgMAMbDgWiexcHVrW8UATf3djbw4RUbWTZGpZ7v34lUScikzkEagCDAjMaKljJhMSkbXydnXMr0mw8oD2P5EqFwMCExeZkI7g0Fh1+y6uXUBEVmx0J60mwcqDl1U+AVUuBgQmbu2RK9DpgC4NaiLAq4axN4eIyGgGtPCDl4sDopIysPNcDI9EJWNAYOL0GbVMJiQia+dkb4e72tXN7yWgysWAwISFxqTgSESCqkooixkREVk7WfBIbDwWieSMbGNvjkVhQGDC1uT1DvRu4qtKdxIRWbsO9b0Q5OuKtKwcFRRQ5WFAYKJ0uhsFOKQYERERQRVmG92RNQmqAgMCE3XyahLORSXD0d4Wt7euZezNISIyGaPyAoLdF67jcnyasTfHYjAgMFH63oGBzf3h7uxg7M0hIjIZ9b1d0D3IW83A+oPJhZWGAYEJys3V5ecPcHYBEVFRY/JqEkgpYxlipYpjQGCC9N1g7s72GNhCq8xFREQ33NG2NpzsbXE+WpuNRRXHgMAELdt3KT+Z0NnBztibQ0RkcmQo9fbWtdVtLnhUORgQmJjE9Cy1mJHhGuBERFRyTQLJucrMzuUuqiAGBCZm3ZGryMjORVNZ/7uep7E3h4jIZPVp4gs/dyfEpWblLxFP5ceAwESHC8Z2rqfm2xIRUfHs7WwxMq9OC4cNKo4BgQmRugMHwuNVqeJ78rrCiIjo1isgbj0ZhfjUTO6qCmBAYEJ+PxChrvs384O/u7OxN4eIyOS1quuBFrXdkZmTi7VHrhp7c8waAwITIWt767u8ZLiAiIjKVpOAKyBWDAMCE/HP2WhcS8xATRcHDGrJUsVERKU1skNd2NoA+8PicDEmhTuunBgQmIjl+7TegZEdAtT6BUREVDr+Hs7o09RP3V7BUsblxpbHBEgizJ8nrqnbHC4gIiq7MXmJ2DL0KuXfqewYEJgAVVQjJxct63igTQBrDxARldXQVrXh6miHiLg07AuL4w4sBwYEJmBZ3nDBOCYTEhGVSw1HOwxvW0fd/n2/9j+VyoYBgZGdikzE0csJsLe1UYkxRERUPvoh1zVHriA5I5u7sYwYEBjZ4r1aZcLBLWvBx83J2JtDRGS2ugV5o5GvK1Izc7A2bwl5Kj0GBEaUnpWTP292YjcuZEREVBFS7n1CV+1/6eIQ7WSLSo8BgRFtOh6JhLQsBHjVQN+8KTNERFSxUsYyBHvoUrwakqXSY0BgRL/tDVfX47rUU+sXEBFRxcjqh0Na1SowJEulw4DASEJjUrDnQqyqrjW+C4cLiIgqi37YQIZkZWiWSocBgZEsyRvf6tfMD3W9ahhrM4iILI4MwcpQrAzJytAslQ4DAiPIysnF8rx5shO6BhpjE4iILJYMwcpQrOCwQekxIDACWbc7JjkDvm5OGNTS3xibQERk0cZ1qQ8bG2D3hetc8KiUGBAYweKQG8mEDnY8BERElU2GDG7Lm721dB+TC0uDrVE1uxKfhu1notXtCUwmJCKqMhPzkguX7Y9QQ7V0cwwIqplEqjod0LORDxr6ulb3xxMRWY1BLWvB180R0UkZ2HYqytibY/IYEFSjnFwdlubNLmBlQiKiquVob4sxneoVmNlFJWNAUI12nI3GlYR0eLk44PbWtavzo4mIrNL4vGGDbaejEJmQbuzNMWkMCKrRwj1h6vqejgFwdrCrzo8mIrJKjf3c1KJHuTpZap69BDfDgKCaXIpNxda8MawpPRpU18cSEVk9fXLhkn2XkCuRARWLAUE19g5IMuFtzfzQyM+tuj6WiMjq3dGmDtyd7RERl4Zd569b/f4oCQOCapCWmZO/FOfUnuwdICKqTjUc7dRQrfgtrw4MFcWAoBqsPnxZ1dSu710D/ZuzMiERkbEWPNp8PBKxKZk8AMVgQFDFdDodFuwKy88d4DLHRETVr3VdT7QN8ERWjg4rDmhryVBBDAiqWHBoLE5cTYSzgy2XOSYiMoFeAqlJICdrVBADgir2wz8X1LUUx/BycazqjyMiohKM7FAXNRzscDYqGQfC47ifCmFAUIXORSWpqYay4tb9fRtV5UcREdEtuDs7YES7Ouo2l0UuigFBFfpxR6i6HtqqFoK4bgERkcnUJFh75CqS0rOMvTkmhQFBFYlKSseKA5fV7Vm3sXeAiMgUdG5QE0383ZCWlYPVh68Ye3NMCgOCKvLL7jBk5uSiU6AXOjfwrqqPISKiMrCxsblRuZALHhXAgKAKpGZm45e8dQvYO0BEZFqkSJGDnQ2ORCTg2OUEY2+OyWBAUAWW7YtAfGoWGvi4YEgrrmpIRGRKfNycVDljMX/XRWNvjslgQFDJMrJz8O328+r2/X2CWIiIiMgETe/dUF2vPnQFMckZxt4ck8CAoJItDbmEqwnpqOXhhHFdtHEqIiIyLR0Da6J9fS+V67UomOsbCAYElSg9KwdfbTunbj82oAmcHewq8+2JiKgSzcjrJZDVaDOzc61+3zIgqESL94bjWmIG6no6Y3xeFisREZkmySPwd3dCVFIGNhy7CmvHgKASewe+/lvLHXh0YBM42bN3gG44efIk7r33XtSpUwdOTk5o2LAhHnvsMcTExBS7m+bPn6+mR5V0mThxYpHX5Obm4vXXX0fdunVRo0YN9O/fH0eOHCn2/bOzs9G2bVv06tWrXDXd9dtxM/rfYdq0abf83VxdXdV2yza/+OKLOH78eJnfl6isHO1t8Z8e2pL0c/8Ntfr1Dez5J1Q5fg0OR3RSBgK8amBcZ/YO0A1//fUX7rrrLqSmpqJFixaqET527Bi+/vprrFq1Crt370a9evWK3WXt27dHhw4ditzfvXv3Ivd98MEHeOutt9RndOnSBZs2bcLgwYNx/vx5uLu7F3jul19+iRMnTmDfvn23bNirSuPGjdGnTx91OzMzUwVHBw8exPbt2/Hhhx+qAGrOnDnw8PAwyvaRdZjcPRBfbzuHwxEJ2H3hOno19oW1YkBQCdIyc/BNXu/A4wObqKiTSEgQMHnyZHUtZ+9vvvmmul/Oyl944QV89NFHmDlzpmq8izNq1CjMnj37ljszKytLNaISQAQHB6teiF9//RX/+c9/8N133+G5557Lf+61a9fUez744IPo2LGj0Q6UBANytm9I9su6devw+OOPq+2PiIjAn3/+CQcHB6NtJ1k2XzcntQriz7vD1P9xaw4I2HJVAklIkWkr9b1rYEzn4s/0yDqtWLFCNcDNmzfHG2+8kX+/nJW/++67auhg8+bNOHz4cIU+5+LFi4iPj1dDCRIMiEmTJsHZ2RmHDh0q8FwJRKSBffvtt2FqZL/ceeedKqiRIQTpLfjmm2+MvVlk4R7o20hNEd9xNgZHI6y3UBEDgkqoSqivO/D4wKZwsOMupRv279+vrm+77TbY2hb825BGuXfv3uq2DB1URFyctpRrzZo18++Tz/P09Mx/TOzatQu//PIL3nvvPXh7m25JbX9/f/z3v/9Vt7/44gtjbw5ZuPreLrgrbxVE/f9za8TWq4Kkm+l6SqaqSji6Y0DlHBWyGCkpKUUaakM+Pj7quqQeAgkonn/+edW9Lz0McsZcnMDAQHV95syZ/PskEIiOjs5/TJIOJZGxc+fOapjC1I0fP14FNZIDIUMHRFXpof6N1fX6Y1cRGqN9b60NA4IKSM7Ixnd50eQTA5vCnr0DVIifn5+6DgvT1rYoLDQ09KaPr127VuUZfP/99+qMWbLw5SLDEIZq166NTp06Yd68efj3339VMPDMM8+oIGDEiBHqOd9++60aPpBkxsK9FaZIEiEbNdJWCpUESKKq1KK2Bwa18IdMupmTV0/G2pj+fwUTtmDXRcSlZqGRrytGdqhr7M0hEyRDBUIS5QpPMbx8+bJKmBNJSUkFHpPpiZL4J1n3CQkJiIyMxOrVq9UMAuklkHH2nJycAq/5+OOPVY9E37591XCAJOwNHz5cPff69ev4v//7P8yYMQPdunXLf016eroKGsrrZlMjp0+fjory9dUSvAyHPYiqyiMDmqjrlQcv41JsqtXtaM4yKKfYlMz8saYnBrF3gIo3dOhQdeZ+4MAB3HHHHersvFWrVjh69KgaBpB6AKLwGfvtt9+uLnoy9U6mLg4YMEB1+ct0waVLl6rEQT3pOZDPkRwBSTCUqYlTpkxRj7388ssqg//9999XP2/duhVPPPGEOvOWmgXyvM8//1wlIZbF1KlTS3zs3Llz2LlzZ4X+NPQ1Eow1NZKsS+cGNdGniS/+PReDb7afx7v3tIU1YUBQTl9sPYuk9Gy0rOOBu9qzd4CKJw2ZzDSQbntpxA3rB9SqVUv1Arz22msl5hgU5ubmphpyyQWQqYqGAYFo3bp1fqOvJ5/7008/qeQ8OeOWngkJLtq0aYPff/9dBQWyHVIc6JNPPinToSw8bbDwYxUNCPS9KqacAEmW5YlBTVVAsGzfJVWCvq5XDVgLBgTlcCE6WU01FK+NaMkVDemmGjRooMbuV65cqbL809LSVMMthXckWBDyc2k1bdpUXV+9erVUZ9iPPvoo2rVrh4ceekjdJ70UMlQgPQwy7XH06NHqbF7ul6mILi4uJnFEExMTceHCBXVbelWIqkO3IG90D/JGcGisyhF7c2Qbq9nxDAjK4b0Np5Cdq1MJKL2bWG8RCyo9e3t7jBs3Tl0MSYCg7+4vLf14upzR38rcuXMREhKCHTt2wM5OK6d96tQp1VMgwYCe5BUsWLBABQYSPJgCCVgkoGnWrJmqSUBUXZ4c1BSTfwzGbyGX8OiAJvD3KNtQmrliUmEZ7Tofgz9PXFO9Ai8Pb1k1R4WsgiQKLl++XE09lLP00pJufiG5CTcjeQSSOyD5Afp6B3rSS1Hc9EhTmX0QFRWlKjuKJ5980tibQ1amZ2MflU8gKyB+94/WS2UNTOPbbyaycnIxe7W26Mq93QPRxN/N2JtEZkDWLZAuekMyr37kyJFqdoHMDpDEPkNSOKjwrAQpTyylj5ctW6aef6ssfslNyMjIUCWNDcnwRHJycn4xJHlfeU+pcCjrCxiT9AisX79e5VrIkMjAgQMxa9Yso24TWWfuzxODtKG5X4PDEJVU8PtrqThkUAbzdobizLVkeLs64pkhzaruqJBFkToCkj8gZ/QynVDOfqVWgDTWMhWwuEz9V155RTX+skhR/fr11Xi65CFcuXJFzQRYuHAhAgJKLoQlhY6k7oB8tiQvGpKcgs8++wwTJkxQMxlkmEASC1966aUigUlVkn2gX7FQFjeSqZEyS0IfCEnPhuQ1yHALUXW7rakvOgZ64WB4POZsO4/Zd5c+z8dc8ZtWSlcT0vDZlrPq9kt3tICXi2NVHheyILJAkQwPSCMtWfcyo2DYsGF46qmnSswdkO5yWQXx9OnTqpGUM2dZEVGmKj799NNqbYSbkcWBWrZsqWYjFCZFjGSGgix4tHHjRnh5eanb+lLB1UUqEMpFSCAi2yHJgz169MB9991XpkRLoqroJXhuaHPc+2MwFgWHY9ZtjSx+xoGNrjyLoVuhR389gHVHr6JToBeWP9QLtracF20VsjOAPx7Rbo+aA9hrCwcRkeXT6XSY9MMe7LkQi0nd6uO90aaRcFtVmENQCttOR6lgQGKAt0a1YTBARGRFvQRiScglnI4sWFHU0jAgKMV6Ba+uOKpuT+8dhNZ1PavjuBARkQno0tAbd7SpjVwd8Pa6E/nVMy0RA4Jb+N/GU7iSkI763jXw7FAmEhIRWZuX72gJRztb7Dgbo3qMLRUDglvUHFiwW6tIKDWtXRyZg0lEZG0CfVwwvbdWyOvtdSfVFHRLxICgBInpWXhuqbZG/aRugejbVFvGloiIrM+jA5vAx9URF6JT8kvXWxoGBCV4c/UJNVQQ6O2i1isgIiLr5eHsgGfyho1lCnp8aiYsDQOCYmw8FonfD0SoWQWfjG8PVycOFRARWbsJXeqjRW13JKRl4YONp2FpGBAUEp2UgVdWarMKHuzXWGWYEhER2dvZ4s28ioW/7Q3H/rBYi9opDAgMyEIWUoAoNiVTRYFPDdZqWRMREYnujXwwrnM9dfvVlcdUu2EpGBAYeHPNcey9GAt3J3t8NbkTnOy15WKJiIj0ZKXbmi4OOBWZhC//0kraWwIGBHkka/TX4HDY2ABfTOrIlQyJiKhYssDd26PaqttfbzuHg+FxsAQMCAD8fToqf1njF25vgQEt/I19XIiIyISNaFcHIzvUVRUMn116GGmZOTB3Vh8QHL4Uj0d+PYDsXB1GdwzAQ/0aGfuYEBGRGfjv3W1Qy8MJF2JS8M76EzB3Vh0QXIxJwYz5IUjNzEHfpr54f0w7tZgFERHRrXi6OODDse3V7YV7wrFs3yWYM6sNCEJjUtSyltdTMtEmwAPf/KczHO2tdncQEVE59Gvmlz8j7dU/jqleZ3NllS3g2WtJGP/dblxNSEdjP1fMm9YNbiw+RERE5fDEwKYY3LKWmoL44C/7EZWYDnNkdQHB8SsJmPD9HlWASGoNLHmwJ/zcnYy9WUREZKZsbW3w6YT2aOTnisjEdNw3dy8SUrNgbqwqINhxNhqTvt+jCg+1q+eJxbN6wNeNwQAREVWMu7MD5k3rqk4wpT7BjAWSn5YNc2IVAYFOp8Ocv89h6ty9SEzPRpcGNbHw/u7wcnE09qYREZGFaODjip9ndIOHsz32h8Wp4QNzmo5o8QFBUnoWHlq4Hx9uPK3mi8riFBIMyMpVRERElallHQ/Mm94NNRzssONsDKb8FKwWQzIHFh0QnItKwsivd2LT8WtwtLPFe6Pb4oOx7eDswJLERERUNTo3qImfZ3aDu7M99oXFYew3uxB+PdXkd7fFBgQbj13FyK924kJ0Cmp7OGPJgz0wqVugsTeLiIisQNeG3lj6YE/4uzvhbFQyRs3Zib2hpr06osUFBJLZ+dLvR/DQwgNIycxB9yBvrH2iDzoG1jT2phERkZUNH6x+rI+qdSPJ7Pf+uAdfbD2L9CzTzCuw0UnGnQXIydWpKlEfbT6NmORMdd/9fYLw0h0t1BrWROWSnQH88Yh2e9QcwJ6zUoiobCSx8Lllh7Hu6FX1c0MfF/zfna0woLm/mrJoKiwiINh9/jr+u/YETl5NVD9LsaH3RrdDtyBvY28amTsGBERUCaSpXXvkKt5aewJRSRnqPqlbMLZzPQxtVQuN/dyMXjrfrAOCsOspeHf9SZU0KCSB48lBTXFfz4YsQ0yVgwEBEVXyzLev/jqHX4PDkZxxo06Bj6sjHritER7q1xjGYg8zI/FLyMU4LAoOU90vWTk62NnaYHK3QDw9pJlap5qIiMhUCxi9PLwlHh/UFKsPXcHmE5HYde66WlfH3sjDB2YTEFxLTMfKg5exfH8EzkUl599/WzM/vDaiJZrVcjfq9hEREZWWrJ8zuXugukiS4YmriajrWQPGZG/KPQEyVeOvU1HYdioKIRdjVWEhIQUf7m5fV+3I9vW9jL2pRERE5Sa1cTqZwEw4e1PKwjx4KQ5HIxJw5HICDoXH43J8WoHndG1YE2M61cPwdnVYaZCIiMhSAoLNxyOx+cQ1VcHp2JUEpBaq+exob4uejXwwqKW/mp5R39vFaNtKRERkyYwaEBy/kqhyAvTqeDqjY6AX2gbIxROdGnjBxdFkOjGIiIgsllFb29ua+aqsykAfFzUHs3VdD6PPwyQiIrJGRg0IOjfwVhciIiIyLtb0JSIiIgYERERExICAiIiIGBAQERERAwIiIiJSmFRIREREDAiIiIiIAQERERExICAiIiIGBERERKQwqZCIiIgYEBAREREDAiIiImJAQERERAwIiIiISGFSIRERETEgICIiIgYERERExICAiIiIGBAQERGRwqRCIiIiYkBAREREDAiIiIiIAQERERExICAiIiKFSYVERETEgICIiIgYEBAREREDAiIiImJAQEREROaVVJiWlobXX38dzZo1g7OzM+rWrYsZM2bg8uXLZXqf+Ph4LFq0CJMmTUJQUBAcHR3h7u6O7t274/PPP0dWVlaxr5s2bRpsbGxKvHz77beV9JsSEVFFHD9+HOPGjYOfnx9q1KiBtm3b4rPPPkNubm6Fd+xbb72V/39/4cKFxT5n3bp1ePXVVzF48GB4eXmp5/bv3x+mzh5mID09HQMHDsSePXtQp04djBw5EhcvXsS8efOwdu1adX+jRo1K9V4fffQR3nnnHXWAOnTooAKB6Oho7Ny5E3v37sXy5cuxadMmuLi4FPv622+/HbVr1y5yf/PmzSv8exIRUcXs3r0bgwYNUieR3bp1Q8OGDfHPP//g6aefxq5du7BkyRL1/788Tp8+nd9+6HS6Ep937733IiEhAebGLAKCt99+WzX6PXv2xObNm+Hm5qbu/+STT/Dss8+qnoK///67VO/l6uqKF154AY8++igCAwPz7z979qyK5v7991/1ee+++26xr3/ppZfMItIjIrI20sMrjbEEA9I+SBAgkpOTMXToUCxbtgzDhw9XPb5lpdPpMGvWLHXG36NHD6xatarE544ZMwYtW7ZEly5d1DbJZ5sFnYnLyMjQeXp6SiimO3DgQJHH27Vrpx7bt29fhT9r0aJF6r0aNmxY5LGpU6eqx7Zt21bhzyEzkpWu0y2boV3kNhGZrCVLlqj/0+3bty/y2P79+9Vjbdq0Kdd7f//99+r1CxcuzG8Pfvnll1u+bvfu3eq5/fr105k6k88hkK586Xpp3LgxOnbsWOTxsWPHqus1a9ZU+LPat2+vrq9cuVLh9yIiouolY/eG7YKhTp06qaHlY8eOqSHnsoiMjFQ9yzIUIT0QlsrkhwwOHz6cfzCLo7//yJEjFf6sCxcuqOvicgT0VqxYgd9//x05OTkqKfGuu+5CixYtKvzZRERU9e2F/J+X9kJyC0rriSeeUMMQ33zzjUUfIpMPCMLDw9V1vXr1in1cf39YWFiFP0tmGQhJWizJl19+WeDnF198EQ8//LB6rb29ye9OIiKLVRXtxdq1a1XuwZtvvommTZvCkpn8kIEkg4iSsv4lSVAkJSVV6HNk2uCWLVtUwogkDhYmwxXynDNnziA1NVVFmV9//bV6/pw5c/D8889X6POJiMi02ovk5GQ88sgjarq7nPxZOp7SAtixYweefPJJNZVk7ty5qsZBYfK4IRkukD+Ufv36qW6or776Cs888wzq169ffUePiIiqzCuvvIJLly5h69atcHJysvg9bfI9BPophnJWXpyUlBR1LcWFykMSTGSIIDMzU3X733PPPWV6fevWrXH33XcjOztb/dEQEZH5txd79+5VvcBTpkxRdXCsgcn3EOhrBURERBT7uP7+Bg0alPm9Q0ND1fzQuLg4zJ49G48//ni5tlE/rnT16tVyvZ6IiCqnvZD/59IutGvXrkLtxfr161Vlw6NHjxapPXPq1Cl1LUWKfvzxRwwbNqzYoWZzY/IBgX4q4IEDB4p9XH9/cQf/ZqTxHjJkiLqW4YA33nij3Nsof4CG41NERGSc9kJmGki7IAWIKqO9OHToUImPSWAgl7LMWDBlJj9k0Lt3b3h6euL8+fPFHhgpNSxk+l9ZGnApQSzvOX36dHz66afl3r6MjIz8ua8lTXUhIqKqN2LEiALtgqGDBw+qZPA2bdqUqgGfPXu2qk5Y3GXq1KnqOb/88ov6ef78+bAEJh8QyOJDjz32mLot5Yb1Y0BCSlPKfFJJ7OvcuXOB10mSn9QHePnllwvcL2NL8kcj3UDjx4/HDz/8cMu61hIByoGXxt+QrIEwceJElXQikakEL0REZBySAyYJ39JLYHiiJ+2GtB9Cyt0XJgWHWrRoofIGrJnJDxmI1157TU0JlIUpZLy+b9++ah5pcHCwWs1KZgYUFhMToxaiKDyuLytQyeIXdnZ2qm7AzJkzi/1Mw4hPqlTdd999amhBalPLZ0o1w/3796vpKzK3denSpeVeMIOIiCrOwcFBrUAo69LIrC9ZyEjyBWQmmbQFUsFQf3ZvSHqLw8LCSkxGLM+KiPqeY/1USBmukDUQ9FauXKkW6zMlZhEQyHLH27Ztw3vvvaeWLv7jjz/g7e2tFqiQHV9SEYqbjfdLpUF5r5IYBgQyB/Wpp55SCyxJz8L169fVFBS5X4YqJFCoWbNmBX9LIiKqqF69eiEkJETlhcmid9JbIKXvpVaMfnp5VTt//rw6YTUkJ4+G9xXucTYFNrKggbE3gshkZWcAfzyi3R41B7C3/LnIRGSdTD6HgIiIiKoeAwIiIiJiQEBEREQMCIiIiIgBARERETEgICIiIoVJhURERMSAgIiIiBgQEBEREQMCIiIiYkBARERECpMKiYiIiAEBERERmcnyx5YkOjra2JtAZZGTAfe8ZUqTYqIBO652SGQsfn5+3PlViMsfV7PqWIubKo+jHTBvZA11e/qqNGTmcO8SGYtOp+POr0LMISAiIiIGBERERMSAgIiIiJhDUP2YVGiGSYVbX1I3kwa9z6RCIiNiUmHV4iyDasY/aDOTnQE4aTMLnH39AHvOMiAiy8SkQiIiImJAQERERKxDQHRzMu85J1O7becohSS4x4jIIrEwEREREXHIgIiIiBgQEBEREQMCIiIiYkBARERECusQEBEREQMCIiIiYkBAREREDAiIiIiIAQEREREpTCokIiIiBgRERETEgICIiIgYEBAREREDAiIiIlKYVEhERESwL80+0Ol0yMzM5O4iIiIyQ46OjrCxsal4QCDBwPvvv19Z20VERETV6KWXXoKTk9NNn2Ojk9P/W2APQfWIjIzE/PnzMW3aNNSuXbuaPpVuhcfFdPHYmCYeFwvuIZA3uVVkQZVzwPTX3N+mg8fFdPHYmCYeF/PEpEIiIiJiQGBK3Nzc0K9fP3VNpoPHxXTx2JgmHhfzVKocAiIiIrJsHDIgIiIiBgRERETEgICIiIgYEBAREREDAiIiIlKYVFhJQkJCMHz4cHh5ecHV1RU9evTA0qVLS/VameixYcMGPPzww2jXrh08PT3h4uKC9u3b491330V6enqJBaNKuki1Q6rYcRFyXCZOnIgWLVqo95DjIrdnzpyJM2fOlPi6TZs2qSmk7u7u8PDwwIABA7B161YeEiMeF35fqufYFBYXF4eAgAC1/4cNG1bi8/idMT5OO6wE27Ztw+233w5nZ2f1T0oagd9//x1hYWH46KOP8Oyzz9709dLg16hRQ1Un7N+/P9q2bavuky/I2bNn0bVrV/z999/qn16Bg2djgwYNGhTb+Hfo0AGjRo2CNavocRGPP/441qxZg+7du6Nu3bpwcHDAyZMnVYNkb2+P9evXY+DAgQVes3DhQkyZMgV+fn6YMGGCum/JkiWIiYlR/1jHjh0La2as48LvS/Ucm8LuvfderFq1CikpKeq9N27cWOQ5/M6YCKlDQOWXlZWla9y4sc7JyUl38ODB/Pvj4+N1zZo10zk6OuouXrx40/fIzMzUvf3227rY2Ngi9991111SJ0L34YcfFnmd3N+vXz8evio6LiItLa3Y+7ds2aL2f5cuXQrcL8fQy8tL5+vrq7t06VL+/XJb7pNLYmKi1R4zYx0Xwe9L9RwbQ8uXL1f7/auvvlLXt99+e5Hn8DtjOhgQVNCmTZvUH/r06dOLPDZ//nz12Jtvvlnu99+1a5d6jxEjRhR5jP/gjHdcRM2aNVXjb+i7774r8b1nz56tHluwYIHOWhnruAh+X6r32ERFRen8/Px0U6ZM0YWGhpYYEPA7YzqYQ1BB0pUvhg4dWuQx6R4T27dvL/f7S1eokG7Q4sTHx+P7779XuQbffvstjh49Wu7PsiRVfVx2796txkbbtGlTrZ9r7ox1XPT4fam+Y/PQQw/Bzs4On3/++U2fx++M6SjVaodUMhnjF02bNi3ymCxhLDW99c8pj7lz55b4JRWHDx/Ggw8+WOA+SdxZsGAB/P39rfbQVfZx2bx5M3bt2oWMjAz1urVr18LX1xeffvppqT9Xf19F/h7MnbGOix6/L9VzbCQnYMWKFfjjjz9Qs2ZNJCQklOtz+Z2pXgwIKkj/hy4zA4ojGeY3+zLcjCRIfffdd2jZsqXKni5MEnzGjBmDZs2aqeVGjx07hrfeeku97s4771RnSxKhW6PKPi7S8Hz88cf5Pzdp0gSLFy9G586dS/258pmGz7FGxjougt+X6jk2V65cwRNPPIFJkyZh5MiRt3w+vzOmg0MGJjz1RzLU5cu5bNkyNQOhMMn67dmzJ3x8fFQ2sNyWMySZ7iavl8xeqhyyr2UYOikpCcHBwWjevDl69+6NRYsWcRebyXHh96V63H///Wqo84svvqimT6TKwoCggvTRdEmRc2JiYokRd0n27dunhghsbW3V1MPWrVuX+rXymgceeEDd3rlzJ6xVVRwXId2m3bp1U12hMu991qxZiI6OLtXnymcaPscaGeu4lITfl8o9NjJUKT2UX3/9tRq6KQ1+Z0wHA4IKutkYV2RkJJKTk4sdG7tZMDBkyBDk5uaqYEBqEJSV/oso836tVWUfl8IkyVOKDck+lmNWms+92ViptTDWcbkZfl8q79gcPHhQXY8bN65AIaigoCB1v/xPk5+lTooevzOmgwFBBUn3vH4sszD54zd8TmmDgZycHFW8Q4qulId0nYqGDRvCWlXmcbnZWKnhTJDq+lxzZqzjcjP8vlTesZFhS8l3KnzRF+iqV6+e+nn06NH5r+F3xoQYe96jJRTzaNSo0U2LecgcXL0rV67oTp48qR43tG/fPjV32s3NTffvv//e8nOPHDmiChcVtnPnTp2Li4vOwcFBd+7cOZ21qqzjEhISUuz7b9y4Ue1jOWbJyckFiqx4enqyMJGJHRd+X6rv2BTnZnUI+J0xHQwIKsFff/2l/gm5u7vrHnjgAd0zzzyja9CggfoCfPTRRwWeO3XqVHX/vHnz8u+7fv26KqYi9w8bNkz3xhtvFLl8+umnRd5Hqt6NGjVK9/jjj6vPlC+bjY2NztbWVvfNN9/orF1Fj4uQ+9q0aaObPHmy7oUXXtA9+uijur59+6r75b1XrFhR5HN/+eUX9bgUZXnsscfURW7LsVm6dKnO2hnjuPD7Un3HpqwBgeB3xjQwIKgkwcHBqjH38PDQ1ahRQ9etWzfd4sWLizyvuC+R/stys4t8KQ3JP7yRI0fqgoKCdK6urupLXL9+fd2kSZPUtlDFj4t49913dUOGDNEFBASoMyRnZ2d1tjRr1izdiRMnStzNGzZsUA2UHBvp9ZES03/++ScPi5GOC78v1XdsyhMQCH5njI+LGxERERGTComIiIgBARERETEgICIiIgYEREREpLAwERERETEgICIiIgYERERExICAiIiIGBAQERGRwqRCIiIiYkBAREREDAiIiIhAwP8DHqs2ZqCnV+oAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# use ArviZ to plot the posterior distribution for rho\n", + "import arviz as az\n", + "\n", + "az.plot_posterior(posterior_sv[\"rho\"], hdi_prob=0.95, ref_val=rho_true)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### What the Simulator did: unrolling\n", + "\n", + "Using the **Simulator** effectively *unrolled* the model: instead of a single `dsx.sample(\"f\", dynamics)` call, the dynamics were expanded into explicit sample sites `states` ($x_0, x_1, \\ldots, x_T$) and `observations` ($y_0, y_1, \\ldots, y_T$). Pedagogically, the Simulator does something like:\n", + "\n", + "```python\n", + "# Conceptual unrolling (what the Simulator does internally):\n", + "x_0 = numpyro.sample(\"x_0\", initial_condition)\n", + "y_0 = numpyro.sample(\"y_0\", observation_model(x_0, u_0, t_0))\n", + "x_1 = numpyro.sample(\"x_1\", state_evolution(x_0, u_0, t_0, t_1))\n", + "y_1 = numpyro.sample(\"y_1\", observation_model(x_1, u_1, t_1))\n", + "# ... and so on for each time step\n", + "```\n", + "\n", + "So MCMC was inferring **both** the parameter $\\rho$ and the full latent state trajectory $x_{0:T}$ explicitly. The printed sample keys include `rho` and `states`, …." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For simple Gaussian problems like this one, unrolling can be an excellent strategy that NUTS can handle quite well! We obtain a `smoothing` distribution of the resulting data, without running a typical smoothing algorithm -- we will do this in later tutorials, and see its advantages and drawbacks depending on the type of data at hand. For now, let us compare the state recovery of the unrolled MCMC inference compared to the true states generated in the original model simulation." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot inferred states vs true states: posterior distribution over the latent trajectory,\n", + "# with a subplot for each latent variable/state dimension\n", + "inferred_states = posterior_sv[\"f_states\"] # (n_samples, n_sims, T+1, state_dim)\n", + "n_samples, _, T1, state_dim = inferred_states.shape\n", + "\n", + "true_states = jnp.asarray(states)\n", + "\n", + "\n", + "posterior_mean = inferred_states.mean(axis=(0,1)) # (T+1, state_dim)\n", + "q05 = jnp.percentile(inferred_states, 5, axis=(0,1)) # (T+1, state_dim)\n", + "q95 = jnp.percentile(inferred_states, 95, axis=(0,1)) # (T+1, state_dim)\n", + "\n", + "fig, axes = plt.subplots(state_dim, 1, figsize=(10, 4 * state_dim), sharex=True)\n", + "if state_dim == 1:\n", + " axes = [axes] # make iterable\n", + "\n", + "for i, ax in enumerate(axes):\n", + " ax.fill_between(\n", + " obs_times,\n", + " q05[:, i],\n", + " q95[:, i],\n", + " alpha=0.3,\n", + " label=\"90% credible interval (inferred)\",\n", + " )\n", + " ax.plot(\n", + " obs_times,\n", + " posterior_mean[:, i],\n", + " label=\"Posterior state mean (inferred)\",\n", + " color=\"C0\",\n", + " )\n", + " ax.plot(\n", + " obs_times, true_states[:, i], label=\"True states\", color=\"black\", linestyle=\"--\"\n", + " )\n", + " # Plot observations only on first subplot (if obs_values is appropriate size)\n", + " if i == 0 and \"obs_values\" in locals():\n", + " if hasattr(obs_values, \"shape\") and (\n", + " obs_values.ndim == 1 or obs_values.shape[1] == 1\n", + " ):\n", + " ax.scatter(\n", + " obs_times, obs_values, label=\"Observations\", color=\"C1\", marker=\"x\"\n", + " )\n", + " elif obs_values.ndim == 2 and obs_values.shape[1] > i:\n", + " ax.scatter(\n", + " obs_times,\n", + " obs_values[:, i],\n", + " label=\"Observations\",\n", + " color=\"C1\",\n", + " marker=\"x\",\n", + " )\n", + " ax.set_ylabel(f\"latent $x^{{({i})}}_t$ (log-variance)\")\n", + " ax.legend()\n", + "axes[-1].set_xlabel(\"time\")\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Lead-in to Part 3\n", + "\n", + "Sometimes it is too costly or difficult to infer these latent states explicitly via MCMC/SVI—especially for long time series or complex / noisy dynamics. That is where **filtering** comes to the rescue: it allows MCMC/SVI to focus only on **parameters**, while the filter **marginalizes** (averages) over the possible latent states and computes $p(y_{1:T} \\mid \\theta)$. In Part 3 we will see how to do that.\n", + "\n", + "**Next:** [Part 3 — Filtering and the marginal log-likelihood](../03_filtering_mll/)" ] - }, - "metadata": {}, - "output_type": "display_data" } - ], - "source": [ - "# Plot inferred states vs true states: posterior distribution over the latent trajectory,\n", - "# with a subplot for each latent variable/state dimension\n", - "inferred_states = posterior_sv[\"f_states\"] # (n_samples, n_sims, T+1, state_dim)\n", - "n_samples, _, T1, state_dim = inferred_states.shape\n", - "\n", - "true_states = jnp.asarray(states)\n", - "\n", - "\n", - "posterior_mean = inferred_states.mean(axis=(0,1)) # (T+1, state_dim)\n", - "q05 = jnp.percentile(inferred_states, 5, axis=(0,1)) # (T+1, state_dim)\n", - "q95 = jnp.percentile(inferred_states, 95, axis=(0,1)) # (T+1, state_dim)\n", - "\n", - "fig, axes = plt.subplots(state_dim, 1, figsize=(10, 4 * state_dim), sharex=True)\n", - "if state_dim == 1:\n", - " axes = [axes] # make iterable\n", - "\n", - "for i, ax in enumerate(axes):\n", - " ax.fill_between(\n", - " obs_times,\n", - " q05[:, i],\n", - " q95[:, i],\n", - " alpha=0.3,\n", - " label=\"90% credible interval (inferred)\",\n", - " )\n", - " ax.plot(\n", - " obs_times,\n", - " posterior_mean[:, i],\n", - " label=\"Posterior state mean (inferred)\",\n", - " color=\"C0\",\n", - " )\n", - " ax.plot(\n", - " obs_times, true_states[:, i], label=\"True states\", color=\"black\", linestyle=\"--\"\n", - " )\n", - " # Plot observations only on first subplot (if obs_values is appropriate size)\n", - " if i == 0 and \"obs_values\" in locals():\n", - " if hasattr(obs_values, \"shape\") and (\n", - " obs_values.ndim == 1 or obs_values.shape[1] == 1\n", - " ):\n", - " ax.scatter(\n", - " obs_times, obs_values, label=\"Observations\", color=\"C1\", marker=\"x\"\n", - " )\n", - " elif obs_values.ndim == 2 and obs_values.shape[1] > i:\n", - " ax.scatter(\n", - " obs_times,\n", - " obs_values[:, i],\n", - " label=\"Observations\",\n", - " color=\"C1\",\n", - " marker=\"x\",\n", - " )\n", - " ax.set_ylabel(f\"latent $x^{{({i})}}_t$ (log-variance)\")\n", - " ax.legend()\n", - "axes[-1].set_xlabel(\"time\")\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Lead-in to Part 3\n", - "\n", - "Sometimes it is too costly or difficult to infer these latent states explicitly via MCMC/SVI—especially for long time series or complex / noisy dynamics. That is where **filtering** comes to the rescue: it allows MCMC/SVI to focus only on **parameters**, while the filter **marginalizes** (averages) over the possible latent states and computes $p(y_{1:T} \\mid \\theta)$. In Part 3 we will see how to do that.\n", - "\n", - "**Next:** [Part 3 — Filtering and the marginal log-likelihood](../03_filtering_mll/)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv (3.12.11)", - "language": "python", - "name": "python3" + ], + "metadata": { + "kernelspec": { + "display_name": ".venv (3.12.11)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/docs/tutorials/gentle_intro/06_continuous_time.ipynb b/docs/tutorials/gentle_intro/06_continuous_time.ipynb index 05ad9451..c0164462 100644 --- a/docs/tutorials/gentle_intro/06_continuous_time.ipynb +++ b/docs/tutorials/gentle_intro/06_continuous_time.ipynb @@ -1,515 +1,516 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Part 6a: Stochastic continuous-time dynamical systems (SDEs)\n", - "\n", - "We introduce **continuous-time** state evolution via **ContinuousTimeStateEvolution** and the **SDESimulator**, and run inference with **filtering** (e.g. EnKF) on a partially observed Lorenz 63 example." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6.1 ContinuousTimeStateEvolution: drift, diffusion, and SDEs\n", - "\n", - "In continuous time, the state evolves according to an **Itô SDE**:\n", - "\n", - "$$dX_t = f(X_t, u_t, t)\\,dt + L(X_t, u_t, t)\\,dW_t$$\n", - "\n", - "where $W_t$ is a vector Brownian motion. We specify:\n", - "\n", - "- **`drift`**: $f(x, u, t)$ — the deterministic part (vector of same dimension as state).\n", - "- **`diffusion`**: a `Diffusion` object such as `FullDiffusion`, `DiagonalDiffusion`, or `ScalarDiffusion`, which defines the coefficient $L(x, u, t)$ in $L\\,dW_t$.\n", - "\n", - "The drift is a callable with signature `(x, u, t)`: state `x`, control `u` (or `None`), and time `t`. The diffusion object may itself be built from a constant coefficient or a callable coefficient with the same signature." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6.2 Generating data: SDESimulator\n", - "\n", - "To **simulate** a continuous-time model we use **`SDESimulator`** (instead of `DiscreteTimeSimulator`). It integrates the SDE and observes at the given times. We pass `obs_times` directly to the model." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6.3 Lorenz 63 with partial observations\n", - "\n", - "Lorenz 63 has state $x = (x_1, x_2, x_3)$ and drift\n", - "\n", - "$$f(x) = \\big(\\sigma(x_2 - x_1),\\, x_1(\\rho - x_3) - x_2,\\, x_1 x_2 - \\beta x_3\\big).$$\n", - "\n", - "We take $\\sigma=10$, $\\beta=8/3$, and sample $\\rho$ from a prior. We observe **only the first component** $x_1$ with Gaussian noise: $y_t = H x_t + \\varepsilon_t$ with $H = [1, 0, 0]$ and $R = 1^2$. This is **partial observation** and is specified via **`LinearGaussianObservation(H, R)`**. The matrix $H$ has shape `(observation_dim, state_dim)`; here we use `H = [[1, 0, 0]]` so we get one scalar observation per time. Using `LinearGaussianObservation` gives access to **structured inference** methods (EnKF, EKF, UKF) in CD-Dynamax; for more general observation models or non-Gaussian initial conditions, particle filters (e.g. DPF) are available." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import jax.numpy as jnp\n", - "import jax.random as jr\n", - "import numpyro\n", - "import numpyro.distributions as dist\n", - "from numpyro.infer import Predictive\n", - "\n", - "import dynestyx as dsx\n", - "from dynestyx import flatten_draws\n", - "from dynestyx import (\n", - " ContinuousTimeStateEvolution,\n", - " DynamicalModel,\n", - " LinearGaussianObservation,\n", - " SDESimulator,\n", - ")\n", - "\n", - "state_dim = 3\n", - "observation_dim = 1\n", - "\n", - "\n", - "def l63_model(obs_times=None, obs_values=None, predict_times=None):\n", - " rho = numpyro.sample(\"rho\", dist.Uniform(10.0, 40.0))\n", - " dynamics = DynamicalModel(\n", - " initial_condition=dist.MultivariateNormal(\n", - " loc=jnp.zeros(state_dim), covariance_matrix=20.0**2 * jnp.eye(state_dim)\n", - " ),\n", - " state_evolution=ContinuousTimeStateEvolution(\n", - " drift=lambda x, u, t: jnp.array(\n", - " [\n", - " 10.0 * (x[1] - x[0]),\n", - " x[0] * (rho - x[2]) - x[1],\n", - " x[0] * x[1] - (8.0 / 3.0) * x[2],\n", - " ]\n", - " ),\n", - " diffusion=dsx.FullDiffusion(jnp.eye(3)),\n", - " ),\n", - " observation_model=LinearGaussianObservation(\n", - " H=jnp.eye(observation_dim, state_dim), # observe only x[0]\n", - " R=jnp.eye(observation_dim),\n", - " ),\n", - " )\n", - " return dsx.sample(\"f\", dynamics, obs_times=obs_times, obs_values=obs_values, predict_times=predict_times)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ + "cells": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "synthetic shapes: (1, 1, 2800) (1, 1, 2800, 3) (1, 1, 2800, 1)\n" - ] - } - ], - "source": [ - "key = jr.PRNGKey(0)\n", - "rho_true = 28.0\n", - "T_forecast = 8.0\n", - "# Generate longer trajectory: training window + held-out future for rollout evaluation\n", - "obs_times_full = jnp.arange(0.0, 20.0 + T_forecast, 0.01) # 0..28\n", - "\n", - "predictive = Predictive(\n", - " l63_model,\n", - " params={\"rho\": jnp.array(rho_true)},\n", - " num_samples=1,\n", - " exclude_deterministic=False,\n", - ")\n", - "with SDESimulator(source=\"em_scan\"):\n", - " synthetic = predictive(key, predict_times=obs_times_full)\n", - "\n", - "# Simulators return (n_sim, T, dim); Predictive adds (num_samples,).\n", - "# With num_samples=1 and n_sim=1 we index explicitly.\n", - "print(\n", - " \"synthetic shapes:\",\n", - " synthetic[\"f_times\"].shape,\n", - " synthetic[\"f_states\"].shape,\n", - " synthetic[\"f_observations\"].shape,\n", - ")\n", - "times = synthetic[\"f_times\"][0, 0, :]\n", - "states = synthetic[\"f_states\"][0, 0, :, :] # (T, 3)\n", - "observations = synthetic[\"f_observations\"][0, 0, :, :] # (T, 1)\n", - "\n", - "# Training portion (0..20) for MCMC; future (20..28) withheld for rollout eval\n", - "mask_train_full = times <= 20.0\n", - "times_train_full = times[mask_train_full]\n", - "observations_train = observations[mask_train_full]\n", - "\n", - "times_test_full = times[~mask_train_full]\n", - "observations_test_full = observations[~mask_train_full]" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Part 6a: Stochastic continuous-time dynamical systems (SDEs)\n", + "\n", + "We introduce **continuous-time** state evolution via **ContinuousTimeStateEvolution** and the **SDESimulator**, and run inference with **filtering** (e.g. EnKF) on a partially observed Lorenz 63 example." + ] + }, { - "data": { - "image/png": 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" + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6.1 ContinuousTimeStateEvolution: drift, diffusion, and SDEs\n", + "\n", + "In continuous time, the state evolves according to an **Itô SDE**:\n", + "\n", + "$$dX_t = f(X_t, u_t, t)\\,dt + L(X_t, u_t, t)\\,dW_t$$\n", + "\n", + "where $W_t$ is a vector Brownian motion. We specify:\n", + "\n", + "- **`drift`**: $f(x, u, t)$ — the deterministic part (vector of same dimension as state).\n", + "- **`diffusion`**: a `Diffusion` object representing the SDE diffusion term.\n", + "\n", + "All three are callables with signature `(x, u, t)`: state `x`, control `u` (or `None`), and time `t`." ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "fig, axes = plt.subplots(2, 1, figsize=(10, 5), sharex=True)\n", - "axes[0].plot(times, states[:, 0], label=\"$x_1$\")\n", - "axes[0].plot(times, states[:, 1], label=\"$x_2$\")\n", - "axes[0].plot(times, states[:, 2], label=\"$x_3$\")\n", - "axes[0].set_ylabel(\"state\")\n", - "axes[0].legend(loc=\"upper right\")\n", - "axes[1].plot(\n", - " times, observations[:, 0], label=\"obs ($x_1$ + noise)\", color=\"C0\", alpha=0.8\n", - ")\n", - "axes[1].set_ylabel(\"observation\")\n", - "axes[1].set_xlabel(\"time\")\n", - "axes[1].legend()\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6.4 Inference: NUTS + Filtering (EnKF)\n", - "\n", - "For continuous-time models we use **Filter** with a filter supported by CD-Dynamax. The **default** (and a good choice for nonlinear models) is the **EnKF** (ensemble Kalman filter). Other options include **EKF** and **UKF** (both Gaussian approximations), and **DPF** (differentiable particle filter) for non-Gaussian observation models or initial conditions.\n", - "\n", - "We pass the observed values `obs_values` along with `obs_times` to the model for inference." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "sample: 100%|██████████| 200/200 [03:07<00:00, 1.07it/s, 7 steps of size 8.62e-01. acc. prob=0.96]" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6.2 Generating data: SDESimulator\n", + "\n", + "To **simulate** a continuous-time model we use **`SDESimulator`** (instead of `DiscreteTimeSimulator`). It integrates the SDE and observes at the given times. We pass `obs_times` directly to the model." + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Posterior rho mean: 28.189029693603516\n", - "True rho: 28.0\n" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6.3 Lorenz 63 with partial observations\n", + "\n", + "Lorenz 63 has state $x = (x_1, x_2, x_3)$ and drift\n", + "\n", + "$$f(x) = \\big(\\sigma(x_2 - x_1),\\, x_1(\\rho - x_3) - x_2,\\, x_1 x_2 - \\beta x_3\\big).$$\n", + "\n", + "We take $\\sigma=10$, $\\beta=8/3$, and sample $\\rho$ from a prior. We observe **only the first component** $x_1$ with Gaussian noise: $y_t = H x_t + \\varepsilon_t$ with $H = [1, 0, 0]$ and $R = 1^2$. This is **partial observation** and is specified via **`LinearGaussianObservation(H, R)`**. The matrix $H$ has shape `(observation_dim, state_dim)`; here we use `H = [[1, 0, 0]]` so we get one scalar observation per time. Using `LinearGaussianObservation` gives access to **structured inference** methods (EnKF, EKF, UKF) in CD-Dynamax; for more general observation models or non-Gaussian initial conditions, particle filters (e.g. DPF) are available." + ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "from numpyro.infer import MCMC, NUTS\n", - "\n", - "from dynestyx import Filter\n", - "from dynestyx.inference.filters import ContinuousTimeEnKFConfig\n", - "\n", - "with Filter(filter_config=ContinuousTimeEnKFConfig(n_particles=50)):\n", - " nuts_kernel = NUTS(l63_model)\n", - " mcmc = MCMC(nuts_kernel, num_warmup=100, num_samples=100)\n", - " mcmc.run(jr.PRNGKey(1), obs_times=times_train_full, obs_values=observations_train, predict_times=times_test_full)\n", - "posterior = mcmc.get_samples()\n", - "print(\"Posterior rho mean:\", float(jnp.mean(posterior[\"rho\"])))\n", - "print(\"True rho:\", rho_true)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6.6 Rollout: Filter + Simulator with `predict_times`\n", - "\n", - "To evaluate **rollout quality**—especially forecasts into the future—use **Filter + SDESimulator** with `predict_times`. Use a dense time grid from `obs_times[0]` to `obs_times[-1] + T` to show fitting between sparse data points (relevant for continuous time) and rollout past the final filtered time. The filter conditions on observations; the simulator rolls out trajectories at `predict_times`, producing `f_predicted_states` and `f_predicted_observations`. With `n_simulations > 1`, you get multiple trajectories for uncertainty bands.\n", - "\n", - "**Shape convention:** simulator outputs always include a leading `n_simulations` axis (size 1 by default). Under `Predictive`, there is also a leading `num_samples` axis. The helper code below normalizes shapes for plotting." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import jax.numpy as jnp\n", + "import jax.random as jr\n", + "import numpyro\n", + "import numpyro.distributions as dist\n", + "from numpyro.infer import Predictive\n", + "\n", + "import dynestyx as dsx\n", + "from dynestyx import flatten_draws\n", + "from dynestyx import (\n", + " ContinuousTimeStateEvolution,\n", + " DynamicalModel,\n", + " LinearGaussianObservation,\n", + " SDESimulator,\n", + " ScalarDiffusion,\n", + ")\n", + "\n", + "state_dim = 3\n", + "observation_dim = 1\n", + "\n", + "\n", + "def l63_model(obs_times=None, obs_values=None, predict_times=None):\n", + " rho = numpyro.sample(\"rho\", dist.Uniform(10.0, 40.0))\n", + " dynamics = DynamicalModel(\n", + " initial_condition=dist.MultivariateNormal(\n", + " loc=jnp.zeros(state_dim), covariance_matrix=20.0**2 * jnp.eye(state_dim)\n", + " ),\n", + " state_evolution=ContinuousTimeStateEvolution(\n", + " drift=lambda x, u, t: jnp.array(\n", + " [\n", + " 10.0 * (x[1] - x[0]),\n", + " x[0] * (rho - x[2]) - x[1],\n", + " x[0] * x[1] - (8.0 / 3.0) * x[2],\n", + " ]\n", + " ),\n", + " diffusion=ScalarDiffusion(1.0, bm_dim=state_dim),\n", + " ),\n", + " observation_model=LinearGaussianObservation(\n", + " H=jnp.eye(observation_dim, state_dim), # observe only x[0]\n", + " R=jnp.eye(observation_dim),\n", + " ),\n", + " )\n", + " return dsx.sample(\"f\", dynamics, obs_times=obs_times, obs_values=obs_values, predict_times=predict_times)" + ] + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "rollout shapes: (2, 30, 799, 3) (2, 30, 799) (2, 2001, 3) (2, 2001, 3)\n" - ] + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "synthetic shapes: (1, 1, 2800) (1, 1, 2800, 3) (1, 1, 2800, 1)\n" + ] + } + ], + "source": [ + "key = jr.PRNGKey(0)\n", + "rho_true = 28.0\n", + "T_forecast = 8.0\n", + "# Generate longer trajectory: training window + held-out future for rollout evaluation\n", + "obs_times_full = jnp.arange(0.0, 20.0 + T_forecast, 0.01) # 0..28\n", + "\n", + "predictive = Predictive(\n", + " l63_model,\n", + " params={\"rho\": jnp.array(rho_true)},\n", + " num_samples=1,\n", + " exclude_deterministic=False,\n", + ")\n", + "with SDESimulator(source=\"em_scan\"):\n", + " synthetic = predictive(key, predict_times=obs_times_full)\n", + "\n", + "# Simulators return (n_sim, T, dim); Predictive adds (num_samples,).\n", + "# With num_samples=1 and n_sim=1 we index explicitly.\n", + "print(\n", + " \"synthetic shapes:\",\n", + " synthetic[\"f_times\"].shape,\n", + " synthetic[\"f_states\"].shape,\n", + " synthetic[\"f_observations\"].shape,\n", + ")\n", + "times = synthetic[\"f_times\"][0, 0, :]\n", + "states = synthetic[\"f_states\"][0, 0, :, :] # (T, 3)\n", + "observations = synthetic[\"f_observations\"][0, 0, :, :] # (T, 1)\n", + "\n", + "# Training portion (0..20) for MCMC; future (20..28) withheld for rollout eval\n", + "mask_train_full = times <= 20.0\n", + "times_train_full = times[mask_train_full]\n", + "observations_train = observations[mask_train_full]\n", + "\n", + "times_test_full = times[~mask_train_full]\n", + "observations_test_full = observations[~mask_train_full]" + ] }, { - "data": { - "image/png": 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", - "text/plain": [ - "
" + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axes = plt.subplots(2, 1, figsize=(10, 5), sharex=True)\n", + "axes[0].plot(times, states[:, 0], label=\"$x_1$\")\n", + "axes[0].plot(times, states[:, 1], label=\"$x_2$\")\n", + "axes[0].plot(times, states[:, 2], label=\"$x_3$\")\n", + "axes[0].set_ylabel(\"state\")\n", + "axes[0].legend(loc=\"upper right\")\n", + "axes[1].plot(\n", + " times, observations[:, 0], label=\"obs ($x_1$ + noise)\", color=\"C0\", alpha=0.8\n", + ")\n", + "axes[1].set_ylabel(\"observation\")\n", + "axes[1].set_xlabel(\"time\")\n", + "axes[1].legend()\n", + "plt.tight_layout()\n", + "plt.show()" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "rho_post_mean = jnp.mean(posterior[\"rho\"])\n", - "n_sim = 30\n", - "num_samples = 2 # Change this to 1 or >1 to test both cases\n", - "\n", - "predictive = Predictive(\n", - " l63_model,\n", - " params={\"rho\": jnp.array(rho_post_mean)},\n", - " num_samples=num_samples,\n", - " exclude_deterministic=False,\n", - ")\n", - "with SDESimulator(n_simulations=n_sim, source=\"em_scan\"):\n", - " with Filter(filter_config=ContinuousTimeEnKFConfig(n_particles=50, record_filtered_states_mean=True, record_filtered_states_cov_diag=True)):\n", - " samples = predictive(\n", - " jr.PRNGKey(99),\n", - " obs_times=times_train_full,\n", - " obs_values=observations_train,\n", - " predict_times=times_test_full,\n", - " )\n", - "\n", - "pred_states = jnp.asarray(samples[\"f_predicted_states\"]) # (num_samples, n_sim, T_pred, 3)\n", - "pred_times_arr = jnp.asarray(samples[\"f_predicted_times\"]) # (num_samples, n_sim, T_pred)\n", - "filtered_means = jnp.asarray(samples[\"f_filtered_states_mean\"]) # (num_samples, T_train, 3)\n", - "filtered_cov_diag = jnp.asarray(samples[\"f_filtered_states_cov_diag\"]) # (num_samples, T_train, 3)\n", - "\n", - "print(\n", - " \"rollout shapes:\",\n", - " pred_states.shape,\n", - " pred_times_arr.shape,\n", - " filtered_means.shape,\n", - " filtered_cov_diag.shape,\n", - ")\n", - "\n", - "# flatten_draws merges (num_samples, n_sim, T, D) → (num_samples*n_sim, T, D).\n", - "# Filter outputs (f_filtered_states_mean, f_filtered_states_cov_diag) are (num_samples, T, D) — no n_sim.\n", - "pred_draws = flatten_draws(pred_states)\n", - "pred_t = flatten_draws(pred_times_arr)[0]\n", - "filtered_mean_med = jnp.percentile(filtered_means, 50.0, axis=0)\n", - "filtered_std_med = jnp.sqrt(jnp.percentile(filtered_cov_diag, 50.0, axis=0))\n", - "\n", - "# Plot: true states, filtered means, observations, predicted CI\n", - "fig, axes = plt.subplots(3, 1, figsize=(10, 7), sharex=True)\n", - "lo = jnp.percentile(pred_draws, 2.5, axis=0)\n", - "hi = jnp.percentile(pred_draws, 97.5, axis=0)\n", - "state_labels = [r\"$x_1$\", r\"$x_2$\", r\"$x_3$\"]\n", - "for i, ax in enumerate(axes):\n", - " ax.fill_between(pred_t, lo[:, i], hi[:, i], alpha=0.3, label=\"95% CI (rollout)\")\n", - " ax.fill_between(\n", - " times_train_full,\n", - " filtered_mean_med[:, i] - 2 * filtered_std_med[:, i],\n", - " filtered_mean_med[:, i] + 2 * filtered_std_med[:, i],\n", - " alpha=0.25,\n", - " color=\"green\",\n", - " label=\"Filtered ±2σ\",\n", - " )\n", - " ax.plot(times_train_full, states[mask_train_full][:, i], \"k--\", label=\"True (train)\", lw=1)\n", - " ax.plot(times_test_full, states[~mask_train_full][:, i], \"k:\", lw=1.5, label=\"True (future, held-out)\")\n", - " ax.plot(times_train_full, filtered_mean_med[:, i], \"g.-\", markersize=4, label=\"Filtered mean\")\n", - " if i == 0:\n", - " ax.scatter(times_train_full, observations[mask_train_full][:, 0], color=\"C3\", marker=\"x\", s=30, label=\"Observed\")\n", - " # ax.scatter(times_test_full, observations[~mask_train_full][:, 0], color=\"C4\", marker=\"+\", s=30, label=\"Future (held-out)\")\n", - " ax.set_ylabel(state_labels[i])\n", - " ax.legend(loc=\"upper right\", fontsize=8)\n", - " ax.axvline(times_train_full[-1], color=\"gray\", linestyle=\":\", alpha=0.7)\n", - "axes[0].set_title(\"Filter + SDESimulator: rollout with predict_times\")\n", - "axes[-1].set_xlabel(\"time\")\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6.7 Back-tested real-time forecasting: sparse observations, dense predictions\n", - "\n", - "We generate a **new** synthetic dataset and apply the learned model in a \"real-time\" scenario: observations arrive at sparse times (e.g., every 50th timepoint), and we produce dense posterior-predictive trajectories by setting `predict_times` to a finer grid than `obs_times`. The filter conditions only on past and current observations; the simulator predicts at the dense times, effectively **interpolating** between sparse data points. This back-test mimics online forecasting where we would not have future data.\n", - "\n", - "**Note:** A **smoother** (which uses future observations to refine past estimates) would yield more accurate interpolations than a filter, since it can leverage information from both past and future. Here we use filtering to reflect the causal, real-time setting." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6.4 Inference: NUTS + Filtering (EnKF)\n", + "\n", + "For continuous-time models we use **Filter** with a filter supported by CD-Dynamax. The **default** (and a good choice for nonlinear models) is the **EnKF** (ensemble Kalman filter). Other options include **EKF** and **UKF** (both Gaussian approximations), and **DPF** (differentiable particle filter) for non-Gaussian observation models or initial conditions.\n", + "\n", + "We pass the observed values `obs_values` along with `obs_times` to the model for inference." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "sample: 100%|██████████| 200/200 [03:07<00:00, 1.07it/s, 7 steps of size 8.62e-01. acc. prob=0.96]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Posterior rho mean: 28.189029693603516\n", + "True rho: 28.0\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "from numpyro.infer import MCMC, NUTS\n", + "\n", + "from dynestyx import Filter\n", + "from dynestyx.inference.filters import ContinuousTimeEnKFConfig\n", + "\n", + "with Filter(filter_config=ContinuousTimeEnKFConfig(n_particles=50)):\n", + " nuts_kernel = NUTS(l63_model)\n", + " mcmc = MCMC(nuts_kernel, num_warmup=100, num_samples=100)\n", + " mcmc.run(jr.PRNGKey(1), obs_times=times_train_full, obs_values=observations_train, predict_times=times_test_full)\n", + "posterior = mcmc.get_samples()\n", + "print(\"Posterior rho mean:\", float(jnp.mean(posterior[\"rho\"])))\n", + "print(\"True rho:\", rho_true)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6.6 Rollout: Filter + Simulator with `predict_times`\n", + "\n", + "To evaluate **rollout quality**—especially forecasts into the future—use **Filter + SDESimulator** with `predict_times`. Use a dense time grid from `obs_times[0]` to `obs_times[-1] + T` to show fitting between sparse data points (relevant for continuous time) and rollout past the final filtered time. The filter conditions on observations; the simulator rolls out trajectories at `predict_times`, producing `f_predicted_states` and `f_predicted_observations`. With `n_simulations > 1`, you get multiple trajectories for uncertainty bands.\n", + "\n", + "**Shape convention:** simulator outputs always include a leading `n_simulations` axis (size 1 by default). Under `Predictive`, there is also a leading `num_samples` axis. The helper code below normalizes shapes for plotting." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "rollout shapes: (2, 30, 799, 3) (2, 30, 799) (2, 2001, 3) (2, 2001, 3)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "rho_post_mean = jnp.mean(posterior[\"rho\"])\n", + "n_sim = 30\n", + "num_samples = 2 # Change this to 1 or >1 to test both cases\n", + "\n", + "predictive = Predictive(\n", + " l63_model,\n", + " params={\"rho\": jnp.array(rho_post_mean)},\n", + " num_samples=num_samples,\n", + " exclude_deterministic=False,\n", + ")\n", + "with SDESimulator(n_simulations=n_sim, source=\"em_scan\"):\n", + " with Filter(filter_config=ContinuousTimeEnKFConfig(n_particles=50, record_filtered_states_mean=True, record_filtered_states_cov_diag=True)):\n", + " samples = predictive(\n", + " jr.PRNGKey(99),\n", + " obs_times=times_train_full,\n", + " obs_values=observations_train,\n", + " predict_times=times_test_full,\n", + " )\n", + "\n", + "pred_states = jnp.asarray(samples[\"f_predicted_states\"]) # (num_samples, n_sim, T_pred, 3)\n", + "pred_times_arr = jnp.asarray(samples[\"f_predicted_times\"]) # (num_samples, n_sim, T_pred)\n", + "filtered_means = jnp.asarray(samples[\"f_filtered_states_mean\"]) # (num_samples, T_train, 3)\n", + "filtered_cov_diag = jnp.asarray(samples[\"f_filtered_states_cov_diag\"]) # (num_samples, T_train, 3)\n", + "\n", + "print(\n", + " \"rollout shapes:\",\n", + " pred_states.shape,\n", + " pred_times_arr.shape,\n", + " filtered_means.shape,\n", + " filtered_cov_diag.shape,\n", + ")\n", + "\n", + "# flatten_draws merges (num_samples, n_sim, T, D) → (num_samples*n_sim, T, D).\n", + "# Filter outputs (f_filtered_states_mean, f_filtered_states_cov_diag) are (num_samples, T, D) — no n_sim.\n", + "pred_draws = flatten_draws(pred_states)\n", + "pred_t = flatten_draws(pred_times_arr)[0]\n", + "filtered_mean_med = jnp.percentile(filtered_means, 50.0, axis=0)\n", + "filtered_std_med = jnp.sqrt(jnp.percentile(filtered_cov_diag, 50.0, axis=0))\n", + "\n", + "# Plot: true states, filtered means, observations, predicted CI\n", + "fig, axes = plt.subplots(3, 1, figsize=(10, 7), sharex=True)\n", + "lo = jnp.percentile(pred_draws, 2.5, axis=0)\n", + "hi = jnp.percentile(pred_draws, 97.5, axis=0)\n", + "state_labels = [r\"$x_1$\", r\"$x_2$\", r\"$x_3$\"]\n", + "for i, ax in enumerate(axes):\n", + " ax.fill_between(pred_t, lo[:, i], hi[:, i], alpha=0.3, label=\"95% CI (rollout)\")\n", + " ax.fill_between(\n", + " times_train_full,\n", + " filtered_mean_med[:, i] - 2 * filtered_std_med[:, i],\n", + " filtered_mean_med[:, i] + 2 * filtered_std_med[:, i],\n", + " alpha=0.25,\n", + " color=\"green\",\n", + " label=\"Filtered ±2σ\",\n", + " )\n", + " ax.plot(times_train_full, states[mask_train_full][:, i], \"k--\", label=\"True (train)\", lw=1)\n", + " ax.plot(times_test_full, states[~mask_train_full][:, i], \"k:\", lw=1.5, label=\"True (future, held-out)\")\n", + " ax.plot(times_train_full, filtered_mean_med[:, i], \"g.-\", markersize=4, label=\"Filtered mean\")\n", + " if i == 0:\n", + " ax.scatter(times_train_full, observations[mask_train_full][:, 0], color=\"C3\", marker=\"x\", s=30, label=\"Observed\")\n", + " # ax.scatter(times_test_full, observations[~mask_train_full][:, 0], color=\"C4\", marker=\"+\", s=30, label=\"Future (held-out)\")\n", + " ax.set_ylabel(state_labels[i])\n", + " ax.legend(loc=\"upper right\", fontsize=8)\n", + " ax.axvline(times_train_full[-1], color=\"gray\", linestyle=\":\", alpha=0.7)\n", + "axes[0].set_title(\"Filter + SDESimulator: rollout with predict_times\")\n", + "axes[-1].set_xlabel(\"time\")\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6.7 Back-tested real-time forecasting: sparse observations, dense predictions\n", + "\n", + "We generate a **new** synthetic dataset and apply the learned model in a \"real-time\" scenario: observations arrive at sparse times (e.g., every 50th timepoint), and we produce dense posterior-predictive trajectories by setting `predict_times` to a finer grid than `obs_times`. The filter conditions only on past and current observations; the simulator predicts at the dense times, effectively **interpolating** between sparse data points. This back-test mimics online forecasting where we would not have future data.\n", + "\n", + "**Note:** A **smoother** (which uses future observations to refine past estimates) would yield more accurate interpolations than a filter, since it can leverage information from both past and future. Here we use filtering to reflect the causal, real-time setting." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "backtest synthetic shapes: (1, 1, 1500) (1, 1, 1500, 3) (1, 1, 1500, 1)\n", + "interp shapes: (3, 50, 1500, 3) (3, 50, 1500)\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Generate a NEW dataset for back-testing (different trajectory)\n", + "key_backtest = jr.PRNGKey(123)\n", + "times_backtest = jnp.arange(0.0, 15.0, 0.01) # shorter window for demo\n", + "with SDESimulator(source=\"em_scan\"):\n", + " synthetic_backtest = Predictive(\n", + " l63_model,\n", + " params={\"rho\": jnp.array(rho_true)},\n", + " num_samples=1,\n", + " exclude_deterministic=False,\n", + " )(key_backtest, predict_times=times_backtest)\n", + "print(\n", + " \"backtest synthetic shapes:\",\n", + " synthetic_backtest[\"f_times\"].shape,\n", + " synthetic_backtest[\"f_states\"].shape,\n", + " synthetic_backtest[\"f_observations\"].shape,\n", + ")\n", + "states_backtest = synthetic_backtest[\"f_states\"][0, 0, :, :]\n", + "observations_backtest = synthetic_backtest[\"f_observations\"][0, 0, :, :]\n", + "times_backtest = synthetic_backtest[\"f_times\"][0, 0, :]\n", + "\n", + "# Sparse observations: every 50th timepoint (as would arrive in real time)\n", + "downsample = 50\n", + "obs_times_sparse = times_backtest[::downsample]\n", + "obs_values_sparse = observations_backtest[::downsample]\n", + "\n", + "# Dense predict_times: full grid (interpolation between sparse obs)\n", + "predict_times_dense = times_backtest\n", + "\n", + "# Apply learned model: posterior-predictive with Filter + SDESimulator\n", + "predictive_interp = Predictive(\n", + " l63_model,\n", + " params={\"rho\": jnp.array(rho_post_mean)},\n", + " num_samples=3,\n", + " exclude_deterministic=False,\n", + ")\n", + "with SDESimulator(n_simulations=50, source=\"em_scan\"):\n", + " with Filter(\n", + " filter_config=ContinuousTimeEnKFConfig(\n", + " n_particles=50,\n", + " record_filtered_states_mean=True,\n", + " record_filtered_states_cov_diag=True,\n", + " )\n", + " ):\n", + " samples_interp = predictive_interp(\n", + " jr.PRNGKey(42),\n", + " obs_times=obs_times_sparse,\n", + " obs_values=obs_values_sparse,\n", + " predict_times=predict_times_dense,\n", + " )\n", + "\n", + "pred_states_interp = jnp.asarray(samples_interp[\"f_predicted_states\"]) # (num_samples, n_sim, T_dense, 3)\n", + "pred_times_interp = jnp.asarray(samples_interp[\"f_predicted_times\"]) # (num_samples, n_sim, T_dense)\n", + "\n", + "print(\"interp shapes:\", pred_states_interp.shape, pred_times_interp.shape)\n", + "interp_draws = flatten_draws(pred_states_interp)\n", + "pred_times_interp_1d = flatten_draws(pred_times_interp)[0]\n", + "\n", + "# Plot: sparse observations (scatter) vs dense posterior-predictive interpolation (bands)\n", + "fig, axes = plt.subplots(3, 1, figsize=(10, 7), sharex=True)\n", + "lo = jnp.percentile(interp_draws, 2.5, axis=0)\n", + "hi = jnp.percentile(interp_draws, 97.5, axis=0)\n", + "state_labels = [r\"$x_1$\", r\"$x_2$\", r\"$x_3$\"]\n", + "for i, ax in enumerate(axes):\n", + " ax.fill_between(\n", + " pred_times_interp_1d,\n", + " lo[:, i],\n", + " hi[:, i],\n", + " alpha=0.3,\n", + " label=\"95% CI (interpolation)\",\n", + " )\n", + " ax.plot(\n", + " times_backtest,\n", + " states_backtest[:, i],\n", + " \"k--\",\n", + " label=\"True state\",\n", + " lw=1,\n", + " )\n", + " if i == 0:\n", + " ax.scatter(\n", + " obs_times_sparse,\n", + " obs_values_sparse[:, 0],\n", + " color=\"C3\",\n", + " marker=\"x\",\n", + " s=40,\n", + " zorder=5,\n", + " label=f\"Observed (every {downsample}th)\",\n", + " )\n", + " ax.set_ylabel(state_labels[i])\n", + " ax.legend(loc=\"upper right\", fontsize=8)\n", + "axes[0].set_title(\n", + " \"Back-tested real-time forecasting: sparse obs, dense predict_times\"\n", + ")\n", + "axes[-1].set_xlabel(\"time\")\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "backtest synthetic shapes: (1, 1, 1500) (1, 1, 1500, 3) (1, 1, 1500, 1)\n", - "interp shapes: (3, 50, 1500, 3) (3, 50, 1500)\n" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6.5 Full observations and high-frequency, low-noise data\n", + "\n", + "A common special case is **full observations** with **high-frequency, low-noise** measurements. Under that assumption we can **accelerate inference** dramatically at the expense of some bias (depending on how valid the assumption is). See the [deep dive on this topic](../../../deep_dives/l63_speedup_dirac_vs_enkf/) for details." + ] }, { - "data": { - "image/png": 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DyR/GPj6HGjMsmJD+B6MCaZ/awHaQ9oaFoxxIUwVIf8W5EFKIxQsTfRDS9MTb1/U4kb6KlE2knmNBKq5ZxmfUgZRs/AjASFV3vNpAaqp0sYiFK8699DUg1Ebi+qMWEKUH+NF0rvUB1wV1v0IKuwCcAML7ms6/PvuF5wHXW6qPIEWXZwvG8erVq9niF6m1cLAgpRNpu8YI6yHdU4xggAvXQTgfcNZIwWuGOm+gNYDUYKStwghC6i0W8NApkII6XzEYB5B6K9YmgMEGxx0MM0H3QN29ju1J1aLhREBqNcpjkHaLEgwYaHBuwUgXnj18FzQg9L0fhfMo9/zj3kOJg1SsS3rcGEtwrYXjNuU9IeyfdJvCPouvs77nQXqPCfeZuA4a6fGob4f2AWrJcR/079+fOSWEFHWMX5MmTWI/6rYrV/IgRu74sE3ci2LwzErT6nU9bnXnEmOo2MElh6D1gHNgKaB2XTr+Y7xWN7aLryvOGTQ9tM2X+owHHE5xhRvdHM4rBhZriHaj1g0TJmruUCeMmlPUdKFlFBa8iDzBmJMTTtEFfC+MF9SkodZLatxA0ElsAKF2WVN7FCHSg/pNda3EBKMdkzm87xAJQh0j/gbRdkT3MelrAttBhG/BggWy70uNSWMRR/CE7et6nIi04BohaoI6OyyIsEhC5FlTZAw1jDA+BCCQY6j4Ggx2fV4XHAPC/qHmVp2DQViQmxN1599U+6Xrs4X9QFQI0TQ4qyDotmXLFpZhgXtY3fnUhrbrYC5guMDJAGMT2QX4wTHD+YWacH3AOAKjGeJLMN5gnMJQgKEIp570XpdeU4DnAjoPqJ1Gu0TsF0TU5s+fz17DM4XvwX6jplUOQx1TuiI1cMx1T2hD3/Ogyz2G+x8GJ6L22Hc4E+D8QJ0wnArCNYS2BSLbcsg5hgwFjhap46Kwr39hYegYLpwzZAZAaFQOODxMPR5wOEUVbnRzOK8gEJEBQrQTabJYxGJCFKI+AJOiGCx2MclCpEtbD22k3WKRC6EaRGggTIYIpAAWNojUCghRaHUpdkJEGQtvpK5pA8YNvOv4gbcdAmoQ3hKMbk3buXLlCttnTel+MFRxLoRopwCEoIxBn+PE+YVhCMNBAOJBMFI0gYUOrouckVJQKY6C4juyHXS5nrqC64L0T6SoiqPdQgoy3jfVfuFaoYwB6crqBLZ0fbYAjADcd/iB02fGjBlMyAhGF/bFHNdGOB+INEqRe00fEG1Gmj5+8KzgWfzxxx9ZJFNsQMH5B0egAMYlpEMjQwVAUA1pxnCawXgTQJquvkAgDz8YC+D0gEgUhO1g+OF64t6BmJec4a7LeZR7/nHvYTyUtqTCcYudkTjfOE/i1H1t94S++yeX3i3dZ2POgyaQdo+0f/zgGuNawtGKcy+M/3iOjBkP5I4PApjayiH0OW7xuRRnTyFLRpvKvTC+Q2hR03Ea86wXZJo6jgfXUpdrput4wOEUV3hNN4fzigEDAZEGTIBCyi082pioxeneiHyKlboB0jGxCES0SRpdkoucIT0NixgY1/CGY+EsgIUNJmrhR1i8CAtTqeGINHFM8IjSilOjxQsegGOQppvCyw6DX5zai+3IpWAjSo5U7VWrVqm8h+NAiigQjHcoDosR1FoNRdfjFK6b9LxDLVnaRkkKzrX43ONaiM+LNqPdFGDfke4Lo1Ta0kd6nPoAQw3HD8VhMYiq4R7Xlumgz37hc6hflG4LCNdF12cLNa1SBMeWcN+qezaMAc8FUl2h+iy+31AeglpvKbq2DBM/6wDjhpAhIG29hzR+8fdBvRyOQeFaCRE38b2OmlpkDugKjCHpsyI9v3j2cZ3QUUAK9kfTeYeTD9+HqJ34c7iHMN4KDgQxQlsm8bMLhOPW5Z7QFfH+icc91NjCiSrGmPOg6/2AzAIYWsJxYIxGyj+MMNxjho4HeK7Etd9nz55ljjFtz70+x40xE84BXC/xPaXL2A/nLxwt+Kz0PIq/y5hnXd3cZg5wzk6dOsWcilKw74KDX5/xgMMprvBIN4dTzEEalxDlQ8QX0R146FEjiGgqQNsiRFFQX4UaR3wOC0IsilCvJYDfEWXBogTp26gvRPQOrauweBdaN4nB32DRiQUV0gZRkylsVw4YnBBdQdohIo5YQEAIBwsVpCRi8YTUdURLUBuGBRaiPvhOpI0iwgljH3WPtWvXZos7GP7YR3FEGMYtUjXRggip7vgcPPCoM0TtGVpd4XthkGIhhnOI17G4QI08FrCoj8fCHwsctG5C6yhjo4NYjOhynAA1+UjfR1o56uyx+MGxogeuoeC8wOhBDTKuHRbDgoicqZk1axY7JlzfIUOGsGOAoYG0YRyHnNGhDVxDRE1xn8K4xT2A+w9prUjDl9bgG7NfyBiAsYp7CIt7PBNwyuAziOKghlXXZwuOLKQS4/OIpOFzuLdwLwtZCZqeDWNA9BT7insd9xsMVDgSYIxLHT+6tgxD9BLnCfcOjgGlJDBS8NwIzj6xAY1ILhbwiLriuHHMSMsHeLZQK4usDgjkwYmB+16fFHnsM74XbadwHjFOwLGG50kwiJHCjlIYjGNIhUXdKYwrjJcQjEJJDsYVdaAkBM8tSj3QPktoGYbnU650BucQx4h7A8+u0H4Q96yu9wTA2AonibbzgePCd+FvkVqP64P9wzgjvs7Gngc58AxhPzG+IOKNdmFCW0cBPBfYN5T34LmDcxDt+3Bu0AILGUjawHOF74BIGow5GLcYD9WlP4vR9biRDYM0eHwOYzDuHwikYa5FRoO28R3jK8YpPAt43uAQwfwC3QLBeMV5ArjfMW/C8SQWrNSEurnNHECvBX3UcR6ENnEYA+Gww/XFGIxzos94wOEUWwpbPp3D4RRcyzAHBwfWNmbFihVK7UnAzz//zNqyoNVLlSpV2N8LrW2koFVS3bp12Wc9PT1Zm579+/fLtgwTt25xdXXNbdWqldZWUGgVVK1atVwbGxuVFieXLl3K7d69O2uFhO1jW7169co9ePAgez89PT33q6++Yi1qsD20M8H/L1++XGkbSUlJrL2Xh4eHSssctC+aPXs2a0clHCPaGk2dOjU3Pj5e8bnU1NTckSNHsn3Bdt55553ckJAQvVqGbd26VfZ9bccptHb58MMPc318fHJdXFxYmzG0dcFnNbWt0cSLFy/YtcO5w98I7cPUtQyTtuxSd/0B/l7ayi08PJy9FhQUlGtra5vr7+/PWgf99NNPWvdV3fbR+gotgkqVKsW+E/f13LlzVe55uf3Rd79wL3/zzTesDZDwObQne/DggV7PFq5r165d2T6jHRH+7du3r0orHnXPhrqWYThuKXL3J1oDYd+wj2hn9tdff+X26NGDvWZIy7Bt27blduzYkbXQwvGUKVOGtfgKCwtTGaOOHDmSO3ToUPac4T7u16+fUtstgFZ9TZo0Ya2McG6+/vprRRs6Xe7JixcvsvOJ/cAxYr/efvvt3PPnz6t8FtcYzzu2hecAbaywvefPn+dq48CBA7nNmzdnf4sWSRgTbt68qfQZ4drjddwr2AaOfcSIEWxM0feewL7ivtOF7du351atWpWdA9xHO3bsULl39DkP6p51XAdx60G08GvUqBEbb/F9uK++//57pVZxAM8N2qvhePA8lS5dml0n3E+aEN/v8+fPZ88tjrFly5aKFmwCOF6M1+rQ5bjRMhPzAVqw4XNt2rTJvX79us5j7/Hjx1n7R2GOqlWrVu6SJUsU76O11meffZbr6+vLWnfps1xXN7epaxkmdy70Gdsx3o4fPz63YsWK7D7FfIQ2b/PmzVNcX13GAw6nuFMC/ylsw5/D4XA4HI5lgSgUonrmavOD9mOI9CELRdxhgaM7iNgjcoyIrrQF2asEIqrI+EC2AaLQHA6HY2nwmm4Oh8PhcF5hUE8t1F4KQLwM6bxICeZYLkg/R/kJ0rE5HA6HY7nwmm4Oh8PhcF5hoBcAcSi0SYM2A+pLUTfu7+/PtA04lgtqtPHDKf6gJhr6B+pA3XdxbWvG4RQHuNHN4XA4HM4rDETKIIAEAT+oREOgDYYcBOWMEeXjcDimA8KlEMxTB8T2kGbP4XAsE17TzeFwOBwOh8PhWDAXLlzQ2AccvcXF7R85HI5lwY1uDofD4XA4HA6Hw+FwzAQXUuNwOBwOh8PhcDgcDsdM8JpuCTk5OfT8+XNydXWlEiVKmOu8czgcDofD4XA4HA6nCIPu22jfCCFSKyv18WxudEuAwR0UFGTu68PhcDgcDofD4XA4nGJASEgIBQYGqn2fG90SEOEWTpybm5t5rw6Hw+FwOBwOh8PhcIokCQkJLGAr2JDq4Ea3BCGlHAY3N7o5HA6Hw+FwOBwOh6MJbWXJXEiNw+FwOBwOh8PhcDgcM8GNbg6Hw+FwOBwOh8PhcMwETy/ncDgcDofD4XA4FkV2djZlZmYW9m5wOAxbW1uytrYmQ+FGN4fD4XA4HA6Hw7EYkpKSKDQ0lLVj4nAspWYb6uQuLi4G/T03ujkcDofD4XA4HI7FRLhhcDs5OZGvr69WgSoOx9zA+RMZGcnuy0qVKhkU8eZGN4fD4XA4HA6Hw7EIkFIOIwcGt6OjY2HvDofDwP34+PFjdn8aYnRzIbVXgIjENIpMTC/s3eBwOBwOh8PhcHSCR7g5xel+5Eb3K0BCaiaFJ6QV9m5wOBwOh8PhcDhFjn/++YcaNGhAtWrVoiZNmtCVK1cU77Vp04bKlStHderUYT8LFy5UvPfxxx9TzZo1qV27dhQfH89eQxT/zTffpAcPHmjc5pYtW9g2K1euTPXr16d33nmHrl27xt4rW7YsXb58WfbvUlJS2N8lJiay39966y26c+eO1mPcuXMnnT59mgrDmI2Li9P6uSlTplBaWr49M3nyZNq4caNR2166dCnNmDGDCgKeXv4KEJ+aRSkZWYW9GxwOh8PhcDgcjt4cuBlutrPWvlpJje/HxsZSv3796OjRo1S9enU6duwY+/369euKz8DQfvfdd5X+Du/fu3ePGcrfffcdrV+/nkaMGEGrV6+mtm3bUoUKFdRu85dffqGZM2cyQ7hatWrstQsXLtDz58+ZEa/NkOzatSu5urqy3//++2+dzgO2BacBnAqG1OEbo+ytC1OnTqXPP/+cHBwc2O84p8YydOhQqlq1Kn366afk7u5O5qRIRbpx8zVs2JDdRH5+fuzmlnpu4AHBifP29mbqcj169KDwcPM9qEWBpPQsSs/MoewcrgDJ4XA4HA6Hw+HoCiLSsCtgcIOWLVvS06dP6eLFi1pbTKWnp1NOTg4lJyeTnZ0dhYWF0W+//UZjxozR+LfffvstLVq0SGFwA0S7O3XqpHV/f/zxR3r//fcVv4uj4ojKf/nll+wYYPQPGzZMYZj/9ddfNHfuXGZ4wzEA4Cho3Lgx1atXj1q1aqWI8K9du5Y5DmBnwQlw9uxZ9t2fffYZs9UqVqxIX3zxhUJ9/v79+9S+fXuWKYDvh4EvB/YNf4/PYHuCnSfsJ/Yb70VERNCgQYPYORLU7j/66COqUaMG+4GBLqDumAGuSceOHWnTpk1kboqU0X3kyBFmUCP1Yf/+/ayQHScKN7LA6NGjadeuXbR161b2eXiEunfvTq8q6VnZlJmVw/4/LTO7sHeHw+FwOBwOh8MpMkCtOjo6mk6ePMl+h3GK1G2IagmMGzeOGZ+9e/emhw8fsteQFg7DFAYrXvvggw+YnQLD1sZGfbIxDMqQkBBq2rSp3vuKv0Mau6YoOpwIhw8fZpH4f//9l06dOsVS0Lt06UJfffUVM9D/97//0YkTJ5iDABF+OBi+//57JWP+zJkzLDUbkXxhX2/evMnO09WrV5kdhr8H/fr1o/fee4+9Dhtt8ODB9OTJE5V9Gzt2LJ07d47tw/Dhw2nUqFHs9ZUrV7J/kWWA9xB8FTNt2jTm4MD3Y79g1CM9X9MxC2DfDx48SObGpqjVU4iBlwUnHekW8IbgJvv555+ZtwK1E0J6BtIGYKgbki5R1ElJzze0UzOzydm+SF1yDofD4XA4HA6n0EDa8bZt22j8+PEsogojDRFowXBGNDgoKIhFdZctW0Zvv/02Mz7B9OnT2Q/4888/2ecQef7www8pISGBevXqxQx1U4GWViVLak6Xx/aw7/hB1BgGqZyBj/1FZBuRboGYmBhKTU1l/9+sWTPmWBAzYMAAFuHHD5wMBw4cYLXoFy9eZEa84MRo0aIFM6CDg4OV/h5B1SVLljCnBjIEsD1dwHbmz59PVlZW5OzszPYD3yWcW03H7O/vz86buSnSFpggSODl5cX+hfGN6DfSFwSqVKlCZcqUYR4NOaMbXhH8COABKE6kv4xyg9QMHunmcDgcDofD4XD0ARFr/LC1dXo6M9SE1G8Y0oIgGGq2kcqMyDhS0sX2xbx581iUFeWyrVu3ZkZp7dq1WYRZ3BoNAcXAwEBFBFof0NtcLDYmh1ATDVCHnZUlr/sEJ8LAgQPVCo2hjNdQxe8SMq8jZR/nD5FuROoRtUZQ1RCk36/pmHG+CqI1XZFKLxcD7weK6Zs3b85y98GLFy9Ybr6Hh4fSZ+HxwXty4MaHB0v4ER6c4kKG2Ojm6eUcDofD4XA4HI5eoBZbnMqMjFrULcN4E2tHbd++ndkdYoNbSD+H2jaMYpTFwijED4KFGRkZskrdqPu+ffu24rVLly7Rvn37NO4nIs9ITxei0frg5uamCGgCOAM2bNjAjGHB9jp//rzG78DncUzYPjKPEQiFFle9evVY9rFQ3338+HEVgxrbRoQ8ICCAGfwQhBOD7xHvnxhsB9nO+DucX2QfoARZF27dusWcH+amyBrdqO1GXv7mzZuN+h6kiuACCj+ohShOZGTnR7cT0zILdV84HA6Hw+G8emRl5wcAOJyiCAxmZM/C0EYtMgw8IerduXNnVs8Nw2358uWs5lsM0qphhHbo0EFhwyANHX/Tv39/WdVs1Dxjm6iFhiENETeIq5UuXVrjfiKiC2Pz0KFDeh8j9uX333+nunXrMiE1CI/NmTOHunXrxo4N+6DN7kJJLwKiODb8fZ8+fdjrGzduZDXW+J6ePXuy70cmshj8DT6P7UBMTfo+hNlwDgUhNTGTJk1iBju+A+nwcBggdV/X8mXsk7kpkSvIyhUhkHqAOgMU9qMvngBusNdff51J+4uj3agXQFQc4gXaQPoHbn4Y4PD4FHVuPk+g53F53i4b6xLUprKy8ACHw+FwOByOucjJyaXTj6LJ18WeKpXMa2HE4WgC6b6PHj1ia3xxWrC5EUwidSnRRQUoiaOd1u7duwt0u1AJh70lbZ1mydy8eZP1Ukd9uaH3pa62Y5GKdONhgMH9xx9/MANbbHALUvrwcogV6CA1j7QIQxQAiwMZIu9yVnYu79fN4XA4nAIhLiWDZVgVQd8+x4Q8i0tloq5PolN4xh3HokEZZnHo9NOoUSPWuQliZBzNIMMZLdYKgiIlpIZ0DNQHIMqNvH6hThveBRTA41+kY6AGAuJq8DagXxwM7ldRuVxa0w1iUzLJya5IXXYOh8PhFDGik9Lp0tM49v8eTrZUP9izyEePOIatQUJiUxS/349IorplPPmp5FhkRgaCU8AhN7fIj1foWV3Q/Pfff1TU6KRD33NTUaQi3StWrGChe6QvoMhe+BH3YVu4cCGT6kezdhToQ11wx44d9KoiraOKTVYVa+BwOBwOx5SExeer58alZNKZRzEUn8p1RV41boUlKLUujU7Ky37gcCyNrBxRZmgOz87hmJ4iFfLUJUUNOfYQJ8APRzm9HMSmcKObU3SQttzgcDhFI7oZmZjfihMkpWXRuUcx5Odmz/7f09mOKpd0JSuroh1N4qgnKT1L5T4A4Qnp5Opgy08dx6LIfBnlFgJWttZFKi7JKQLwO6oYAyeFkCojkJ6Zw73MnCIB1D7Lli1L/x05SjHJGXQ5JI4JA/L6UA7Hsnkak0LZaiJFEQnplJKRTc9iU+lyaBzLvopI1NxTllM0CYnJTyuX1ngjlZfDsRQwXuEnOSmBkhLjWaSbrzU4r3Skm6Mf6tJjwhPSuJeZY9GgBQfaZNSuU4fsA16jPccvU0BQsCJ7w8aqBFUq6UL2NtaFvascDkcEFqqhohpeTcQkZTCxNSSxtalsT9Y86l2s7oMImSg3yMzKoZiUDPJxsS/w/eJw5MjMzqHE+DgKC33Cfi9dphw5eHuSrTXPxOGYDh7pLuaDiBxRSTzFnGPZQKcBXQeGjp9Je/fspkGdm1FYSN5kGJWYTi/i09hCncPhWBYJqVkqGVbhz0PURo1QRom3YHxzig/IToJxrQ7UdnM4lgDGpvTMbAoPCyVXNw9ydHahyPAwjfcvh2MI3Oh+RepTxCSnY1HEBxOO5fL771upZr1GVKpsJWrU6nVycHSiA7u2Kn0mh1vdHI7FgQimmD2/r6cPOjSkySMGUsij+2r/juuNFC/URbkFLE1UD06fR1HJ9CAyiSIS0opF2yiO7lmhUCoPLFuBfPxLkV9AaQoILMNeF8og6tSpw36qVatG1tbWit979+5doKd5ypQprFe0Lqxdu5Zu375t9n3i6A43ul/BSDdslcfRyQW+P0Ud1PvAIwoPflGgqCrEwiGU6+hG7d7uyX6Hwd24VXs6cfAfpc/xkkAOx/KQjo+x0ZFk7+BID27foK8Hv0epKfJzT0xy0RyvOKrAUEEZmybg/C/Mmtn0rGw68zCazj6KYcb2+cex9CAiiR5FJtPV0Hg6fi+Kvc55dVrrOjg4kq2tLdnbO7AxC6RkZjMH/+XLl9nP33//zVoWC7+LuydlZWWZfV+nTp3Kje4iDDe6izHSFD8xj6NS1IqccOR7zh69F0lH7kbSxSexFBafypRZLXUCuRueqOiRK+eMeRKdbLFCNi8S0mj01AXUuVd/xWuIdj+4fZ3iYqIUr/FIN4djWWBMiU9VNro/+GQM7b7wiOav3cEM8OMH/lbrJFQnvsYpWiSybDrN15KJVmUUTjQZ2778NI4S07IoITWTGdty4PXTD6Pp/OMYJv5WGI6B4hBxzxP1zbHYMSstLZ2ePLhL6en5jiI4B588vMsMacEolwNir2PHjqVGjRrRwIEDWZ9qRMAFrl+/zj4j8O+//1KLFi2ofv367G8OHz4s+73Tp0+nqlWrKiLqT548oWHDhrH3WrZsyV6LiIigTZs2UePGjalu3bpUu3Zt2rVrF/vM6tWr6fz58zR69Gj2WTgLwLx589h269WrR2+88Qb7Xk7BwYXUXsFItwAMs1Iejly8RocJ+sbzBMoWLSJuPEtg/5b1caaKfi5kCTyMTGKqweLFDiYUaUue+xFJTDkYC47qpdxYWpUlcejEOXL29CV3z/xWYbUaNCVvP396EfqUPLx82GuW6jTgcF5V4lIzWY02yMhIp91b1tHrb3dnzzKEEDfsP08+fv6yf4ugJ1KOvZztCnanOSYh6ehRsq9UiWwDApixKMY6KoJsnj6i9HqNVRwtLvYFvwxFCvmjJyH06O4tatiyncbPor2d0GseWiK1At3N3koKhjayEcPi0qhBWU9ysC06gqHoRIDzZFWiBHumHWytKDQulYmfBrg7UEZWLltzYn1azseZnPW4/mFhYexHjKenJ5UrV45Ff2/evKnyNzAuwZ07dyg5WTlzAcaws5s7PXn8kCJfPKegchUU71lZW1N6aiqlpaaSlZU12dlYsWNS19r0zJkzbC0Fo1sdDx8+ZOnhMLzd3Nzo/v37zIB+/Pgx2dvniwrGxsYy4xjH6ujoSCkpKWRlZUXLV6ygH3/8kY4ePcqOG3Tq1In69u3Lto3vadKkCTOk//e//9GGDRvo888/p3fffZd9FgY6zsOpU6dYivz69etp+PDhtGfPHh2vAMdYuNH9CqqXC2BARLTW3dHWYiZr8DQ6hXIpl9KzcsgrKZYcnj0ml1atCm3/opPT1Xo6H0clk4+LHXk4Fd5CERMcItcwosWe5Yz0NKb07WCVP2Hj3MLgFv7OxroEVfF3I0shPiWTvh0zjKrVbkCjp85TvI4aq98OXVJyEHCbm8Ox3NTy88f/oxWzJlG9pi0VDjTB4Mb4JOfsQ9SRG91FD8zhIcM/ZXN48LpfKcPBXcng9pn0OVlHhVP0+BlKhjfmrID8jxYImMtDYpJp2pghVL1uQ2Z0w0FkZ6ddSR3t7ZAhWN7XfI72lIwsuhISz9LvixJ4ph9GJdOd0GgaN7QPfTZxJpWrVFXxPoIWyLAU4+Zgq5fRDYMT6dVi0OUExmVoaCiLHsvtFxg0aBCdPn1a6T0Ynd179aEd235nhm7TVvkOGNwPMHTTUlPIydmF3TfqnB/4bl2CF//88w8ztFuJ1rPYBkRjK1WqpHgNBjl+/+CDD6hjx47UuXNnCgwMpIyXzixxRtCjR4/YOcDx29jYUExMDHutSpUqKtvfuXMnnTt3TnGesrOLfhZFUYMb3cWYbCHkoIHkAjC6WfpOVjY9j0ujQE9HpYFLOlnj38ikdDa5YbJOfzlZl/xhCXm/3pYKg/D4fEGYhLhYcnX3UBpgrz9LoLplPPSaPExFVFI6XX8Wr/j90b1bbKL794/f6OdFM+jffQepUb1abOLBfkrr7GCAB3k6Fcq+y3HryTN6cv8O9RyYl0YlBuc8KSGeXNzyVmk8vZzDsbwyHAEIH5Z/rRqVrZi/+EtJTqIRvd+ggZ99Ta07dVH5+4QiqkPxqiM4zTNDQujJgIF07+OR9Mm4L8gtPY1+DSpDNjFRlFWyFGWVKafiZCloMAeeO36Ebl4+TwM/G8vmxhlfDiOfkgE04psZRgczjAGRf5SFiZ38RSGfC5kNc5etpgo1G5GNrS0lxsXS5x90oaWb91JQuYpq/07fOfzjjz+mLl2Uxw0h4guj9MKFC6rbyMkL4CxduYpys9KVotWIdGdmZVPr1q0VGXTi9Ya9oxMzugGuCaL1cri45DthYPiKjVmx6BnutQ4dOrCIsyYQhYaD4OTJkyxyjuj1b7/9RvUbN2XvZ4vOW58+fWjWrFnUs2eeBo6Xl5famm9sf/z48TR06FCN2+eYD17T/Qqql4tBypS5JjbU8MBri5qok/ejWVT4ZlgCpYrquMST9f1+/SnxaSiLvgvecZvw55TtU5LuOPppTZc3l6IpjuXM0QM0un9X6tmiGv0wbaxKKti1Z/EFLgqD7d0Lz69Fu37hDK3v9zbd3r+batRrTK7unvR6mxYUGRlJ9yKSKOrhU7K/eEbyHZbTugWT4z/7DrDjqtdUNbPh5KF/qUfzqoq6bnMZ3YVxn3E4RR2Mg0K2DZyTpw/vow5deyl9BhEjLCjPn/hPYyovp2ihcJoHBbG5vOzyRfRe/cY019aGHF4a3FHTFlG2j5/S3+F+Kch5E3MM0ra3//ojVapWi+o2bsFer9WwGf25aQ2bQ7V+hxnnHanBDSy9SQeu3/5zt2jKlyNo/19bydPblxZv2sMEUP/YsNqk5zIgIICli4t/kFoOHBwcVN5DnTOE0HBuK71WmerVVX7f3cODUpKTydPDg8qWz08tF3AQGd0gTYcWYuXLl2fp3Vh3CdF0AaSCHzhwgK5evap47ezZsyrfkZiYSOHh4Sz1fNKkSawG/NKlSyzCDRG3uNj8QAsi9MI5QMQfv4sj5vHx+Z9FmvnKlStZNBxkZmay7+UUHNzoLsZoEzIB5uiNCqP5Wmg8XQmNo3OPYylFZGTHJGXQqYdRrCUHouyYrJ2X/8QmZXr+jHnJow/tI88JI5jBLUzWKR4+9CS64IXfQmNTmcDG9DFD2OTS7u0e1LLjO7KLRXy2IMH5EFLQosLD6PDEUbQsMIha79hIwS6uNOfnrZSamkqLflxLz+48Zk4M75kTVAxvS2nVE5WcziIQQeUrka9/KZX3K1WrSTk5OXT13CmjFiMwDsQLGziHkJ4fmZhOF57E0LF7kUUutY/DsaTU8iP//EnZOdn0+ts9VD5Xp3ELunL2hOx3YK7gTi/To0kIylRgLi/z61rK8vFhc/lHV85RGTs7epqRQYff7aticAMYERBdK8g2Zndu3aTzJw5T9wFDWTQTP90++B/5B5ZhRqM2dEggNAhorcheJws3ukNiUmnjmp9YOnbXvh8qnGtvdn+fDu7aRqmSOmox5iwRwziC8USs/ZIrs0Z2cnZmrcKgWC7F3dOL/EuXyd/fHO2CcKVKlaKvv/6aiZUhQo3Is0DFihVZlBsRe4ieQSht0aJFKt8BQ7l79+5Us2ZNqlWrFjOOP+g/gK15Roz8nN5+6w2FkNrixYtZlBsOBhjQZcrk7y8i2jNmzFAIqSENHanwbdu2ZdvH64cOHdL5nOafNx6YMJQSuYXZs8ECSUhIIHd3d3bTw0tUlLn0NFanKGZpT0eqXNJVRXDLUO5HJKrU7sjh7mRL3s52FBKbSrG3b1L5+VPJNjxfJCPazp4ylqyjHN+S7Hdr6xLUoqKP2UVMxClTJ+5H0dTPh9Dje7dp6ZZ/yNHJmb2H9KGUpESWai6A+ugGZb0KRBgG2QLIIBBqe1YvmE5nt22g7dVrkkN0pMJZMXHq10QvntNKHx8lJ4Z4AYTz2qqSb6EL6sFR8+VnH7M0ryFfTJL9zMA3mjAl808nfE/VS7tRgHteWw91k+7N5wlM7A7XBMcnpO/hHqrg68z+lWZfgJJuDlQzsICLDTmcIgyeX6F85er5U3TrygXqPXiEyueO7d9D330+mDbuP09+pQJV3kepjreL9vpaju7Aye3npmpUmJoDhw/TV291pk3BwYrXJjo4k2PTVjToM+UMMYHK/q4U5OVEBQGcqqdPn6VNPy2mifN/Ilu7fC0WlGOhp/yW/64ovS7F392BapQ23dxw50Ui07AJjZF32kNIrTA1YzQBI3TPuTvUq209eveDITT48wmK9yKeh9LYIb3Zea5Qpbrs35f1caKKfq6y7yFFGrXJiOIiiq0rMGkQkc6UcWA421uTtVX++hHOdX07JmCd52SnusaDwwTGKATXsNYwtUAtvl9QssdXuzoUjhYTshNw3gpr+4WNuvtSV9uRR7qLMbrWHqGuFx5gU4BBQdeIL0SzHkYmU1RkJA0Z2pcWWSkPZJ/du0sHzpxQEuJ4XoBtO3Be4NX+cvoimr5ig8LgBpNHDKCFU75U8Zqix2dBAK+4MFmkp6WyGu7ab/eguJnLmGENAxuR7Y/adqT5DnZqDW7hvEIsrrAnb0S6v/p+sVqDG7xWow7du3kt72803N6oDUXfVUSvzz2KoZMPouhWWAKdfxLLJi9MGujFeuFJrIrBDWA8oEUMSiKgqFwc2rZwOOZEnDGDbgNyBjeo3bApW5BeOXdS9v0EnmJucmIKIJsJWUhzxo6neaJIG/jWzY0Gv4yAyoHxtSBAqVtsciZVrlmXpi5Zq2JYt33zXVaP+/zpIyoo4ASGMJs6g9vSQXvPP7dsoOzsHOo58GOl9+BQW7P7uFqD2xyRbhjcmM/lDO6895U/m5WdTc+ePlJKIZeCcraEuLx0bGGdly6TLYc1AtbciK7D6Dd1dolYownHgfWfLrpNpgbHzkO1hsON7mKMPml6z+NTTRIZRvRVl7R2gazMTJo6ajC5p6fTyExlw29RufJ0+JflSjVfBdUrE0YgFE7hrYWxHRCY77kHzV9/i47t282Ey6TCZuZO5YPBiLYcAljAvv/xaOr2wRBmUMOwFgzvZht+IvfkJLUGtwAWI4Xdaig+No7dD5pAinnIo/vsnlDXMgyLK/RSF6eIp2fmMCeKuO2bNm49T2DODRjtMNg5HI48eNaEcQ9j4sHd2yk7Sz5t2M3Di37ccYjade5eqEbYqwKMEIx/5mbjip/oi6hIKlWiBJtvImcsZf/aRoSR98RRdOGPzbL3REGJqcEBe/3iWbpw8ojs++Veq0q/Hb5MwRUrF1hNN1p8asNSDRwYfY+ikqlJmw70+bdzlFp8itcmoY8fUGJ8nNnPJdYE6Puua7AJ+5+akkLJiQl5oWM1QPwxPi6/ThpAmA3rXWH/8bsYGP2mTsGWRuRh5CenF2wfd9gUumhFcdTDje5ijD5pM6i1Do1NYQ8V/u5ySByLAsITq8ukjlT2s49i9DK4AWqrIq+cp82VK5N9VITSZO2Xk03z7GwoJyxU8fmU9GxWM25uYDwfO7iP+ndqRKFPHqq836HLe1SyVCBtWb1U6XWcu3sRiWbdN0x04rnKzt6B1aSVKlM2bx98/Ch2VH6aF/jVL4AyZCZFS6nrjklOp3XL5tEnPdtr/Nw7fQax9D9M5urm69svEvW+D7XBpxkOR7PTTODgru3045wprM+tOmDgWNvIl+Fwo9u04Hyae/yKfviESv+wmNVwCw7ejCo1FA5gGN51fv6Bbu77S+VvERk0h7aMFGTzbVixgDb+uFD2fcwpEPmLjYpk7TbNHZ3FugltO4vq3IMIPY4B3Qk6vttb9jMwaAd3aUX//fOn7PumDNTC8FXniBcQvwsF8NSUZNaDW66eWyymlp6aoiL4h1/hbExKy5Rda5vyuuG4pJsQtllQGhg4fkS5OcbBje5ijK4P46O7edHa22GJdPRuJJ16EE1RiXltu849jmH/auLG83hWO26IN/38jk20sXxFco6LlZ2svdLTqNS0sUzNXECXicpYwhPSmfLma9VrU2BweZX3kZr21nv96cTBvSy9W/lv01jqvLmuqTjKffq/fbT4u6+VIsQ4V56LlVufdLhwiu4e3Kv2eyEEV5gp1FFJGawOFIqymkDWAVqSqPOSIxMCDiRTY6nRBg7HEhAbTdcunKHajZpprGlE9GvMgHcpLPSJynuIEiFbhWO6CK85pXtgENw9eZH8rEpQiqe3UkaVOPOqlK0tPdj9h9p9NCcwji5dukIXTv5Hb/bop/ZzECTt07Y2nTlyQO1nTBWdfRiVpNO8YomySzD4nsSk0LKZE5lGgzqcXd2oZr3GdObIfrOeS0SVdcowzJVEupOTyNHZWeNYBaMbpRMZ6ar3KHbfnGJwAuIWYfL7YP6dQIS7II61uMON7mIKBiF1XkQM4hDeCn8eQtGR4TSsZ3v69rNBbCGEZ1dsfOE70GNbHTByjGk79k7DZlTS2kop/Rk6F8JknennTyUiwijh4ukCM7oxGJ+7fIUunjrKUralQCijop8LtezwFnn6+FKMyCEgnDMot+sr0KELYXFpStf1t1U/MHV1wRAVt1oTZw0gAlHvl6VKzouCXvioA2laz8LC6cHt61S3SUutn5/x1Se0fvl8lYkGGRB3X5g3y4DD4agizAEZGel07+ZVqlanocbT5ObhSdcunGa9kuVISOVGt6nG1sikNLNGS9GCK7leM4r9ZhYlzF7B5m4nO2tqWsGbmlf0IftSAWwu/7NhC1p95jhL1y3o7AasU7b8vJRlp6F2Wx3o1V2hSg06vHen2s+Ywr7BGksQHSyKoFQrLjaOdm/+laIj8sVv5WjSpiNdOn1ctm7aFOeSCafpGDDIlayRU1NTlLR61BndIC21YPR65NCWMq8twm+Kc5whsQMs0RlUFOBGdzElQ0OU++yxg2wCenD7Jrm6udMHw8awOryx/+uVV98iQV2qLiZ01LwaQ3D/oRQzYaaSdzzY25kcbK3Z788mzqYvoqNp/eULir/BAKst+m4M0UnptGPdavLyLUktO76t8j6UVqGI/XqTevTLnpMq9d4AXldzGLHimvb7t66zRWvPgcNkDW6cU7s6ddi/UIJH1gDeV2d4h8Qa15LN0EEY5+nyyxZCaCekDaT+YcEuzDPYLr4DddzmcHS83IqZvpfDKRrAqSUnOpgsev3K2ZOUmZFONeo10vhdqOtGmx51RrcuZU0c3dpKwklrrvUx1gDLVvxIP86dQun1GivmcHRCcba3IUc7a6oV5EF2pQKo/KBPWFbYcZnIKPp1m8twwPzw4Fkki8h2ff8jhYNaHW3fepdFuuWcA8L3GUtYvLLzvCjNPDh+1KIjyy8rK5OatXtT4+dR8405+/KZ4yrvmSJCy9LKdf6avA/iXsOm/UsFkYubZiV6Kysr5oyxd1DfKcXcQKhOE+aOdMOe4FFu08CN7mKKulQbCJn88N1YFlFs2rYjqwfuP/wLmrdmOyUlJtDs8Z+xdljavGwYeNF6SZ1KpDaQrvPDtHEspVg8WQNbKysq87KFiG1gMHl17U17t29SmgQxaZkCuTRGtDArYVWCuvcfoqJwamtjRYGeeYNvGW8n8nN3ZJFmqaAaMLXRjWiAWBxs384t5OntS41b5dVB2zx9RNZR4UpZA8HeTuQWXJpOvz+E9Uu1igxnn5MD9fKG1tYhnd7QPuXw+Ic8vE9B5SrK9ueWUrFqTeZwEJQ7cS9cCYkzq4Add+pyXnUeRiZRloylIG5L6eDoSG9078ueUW1UrV2ftRVT132gOGPuyJQwR+dHU3PNcgxoybhz4xoKfxai9J44WRftGgPcHZiaNYxeF7f8NpsCcJaa65ojayIjM5sGjviKWr/RVevn4WiHkaguxdzYS4frok8XFkube1Abj8AH1mT1mrYiv4DSGj8P51r1uo0oQSJGZgpjUee08pcIW8M4hpRytHxFf3FtePn4sYh3RkYGTZ44nurUqEoN69akpg3r0qYN6xSfO3b0CLVo3IBMCZ4NbfecvhI2S5cuZf261fHll1/S5s2bRVFuy+jL/d9//5GjoyPrLy78pKbmP0s///wzVapUiSpUqEBDhgxh/c3B5cuXFccjgOsfFycv8Pfee+/RyZPy3TWMhRvdr1ik+8r5UxQR9owGj/5GqY4FE+KEuSuYkZmdpTz5ybUleBydwuqADeWP9ato1+a1ZFVC9RbEbqF3OAxc0KXvh8xDvm9n/kMTnphmtIBETHIGEyWTRnMQRR81eY5syxv0Mxf3CS/r7Uwzvx5OvyyeJSvGZkoFSwjdiZ0nh//eQa+/00MhSATnRfT4GUpZAyWoBPm5OlCVDm/RztYd6fHwL9nnNLUA0QcMyFh4nX8SY9D1QKQEqakffDKGVmyTr/uSUrFqDUqMj6XQkCcFpmhvYesejh73Z0EJzRRn4PCLSEiXzSQRt6OqWb8JfTFtoWyNJMpy0ONWoFqdBvTgzg0mZiRnKBXn9EXUw5rb8MY5FHRWTH0q8UyhhOrk6bP08O5N6tS9r8bP+7rmGTYjvplBzdp1kv1MtJmy15DBhdpizOfaDETgX7oM1WrYlCJEAq6mNBShXyKXMaIO9PC2FFjWQGQSPX14j65fPENv9nhfp79btOEvWbE1Y44M1yFVlFaedvwYZb14IftZvI73hQ2iPhnrYE2twsRkZ2dRfGwMDRvyET188IBOnDlP5y5do83b/qCF8+fSurW/qPyNqa6asP7OUtMNAphyLHn27Bn9/fff1Lt3b0UmgTmH4iwNxyVH5cqVmREt/MAIB+idPWnSJDp27Bjdv3+fwsPD6aefflJrdGvim2++oXHjxpE54EZ3MUWdZ+rwnh3kXzqICYRJQcR00oJVLPotRtoiAIYk+hcbSnxsNP3ywyx694P/UY36qgYgUtOsrUpQWe+8aDeiny07dKa/flurWIih9ZOhkVVh0QABOOmxhUYn0YFd21TE0YCLgw35uyufGw8nW3r3/UFMKAQ18mKwQDVVRF5aAwZDe8G6P6l7/6FKn5NmDQj7CC9tj6+mkL2WVDAsrPVZ7D6ITGZee0MFRcLj0ykrC30fc3VO36r08t69dvkyc2yYS7SOU/S58TzBKOcgJ28cg2MNSI1uPLdC54Mn9++w0iVkMclRzseZPJ3yM4eatO5A3y1ZK6tiju0URJeKwgAGF+ZPc6eEip0hptwSrg1KeZDhgGgnUm8bNG+r9Bmp0wXRbsHhcvvqRaaXIoW1dDSxIwLz5o37j2nFrMmykVZ1zPtlh9o+88ZeN72dxLmWFeVGRlzpMuXou6XrqNnrmtcT0nUffkxlLGKNK1wKGNTRo0dR1JCPVAxv/I7X8X7ysWN5rcWSk1n/bWlWpzogVHvu9Anas3sX/bB0BTk759WBBweXpe9nzqHZM6bnfzY7iz7+34fUqF4dql+/PjP4wL1796h58+ZUu3ZtqlmzJk2cOJG9jmgsDLxGjRqxyG2vXr0oNjbvXkU0+n//G0xvdmhHTRrUobmzZ9KXo0cptpWUlETBpUtSeHgEO6558+ax76lXrx698cYb9ORJXmAiMTGRGdEwWFu0aEHXrl1Te6xr1qyhHj16sGcY1yc5NZ2+nTSB2rZsxqL4Az/oy/YvJCSE/Pz8WPRfAPu7ePFi9v/nzp2jdu3aUYMGDahu3bq0detW9vrjx4/Jw8ODxo4dy/YT++zv78++T2DChAnsfX3Ytm0bdenShX0X9n3YsGH022+/UUREBE2ePJkOHz7Mzi9eF1i+fDk7X+XKlaNffsl3nOBzkZGRdOuWagarsXCju5iirpfehyPH09czl2hUa0Ta8ta1KxS/SydCLGSNmRyhCo7N9/9kjOz7Vi93rbSHo2Ki7vO/kfTphO+VPhdmRITzzotEFgUQR6IxaO348y+aPW4ESxmXUt5XVXAD57FXn77k4ORMe7dtMqgPpy7AwSBdy+qSjo3zLCx4UpOTaePKhUwwT9NEFqujEYuWIWLniyGRqbD4VDr89x/Ur30DnbzO9hfPkF+JEjTjx9+oSv1mdC00XvEeatXxvjkoxkG3YktEQhoTXeSXzjiQDSSUtUhVdBEBhwMU7Nm6gRZN+Urt3IJoJ+p8BWCsNW7dQW16Z3FsHYZF7PXn8TqljBoLMrnMMX7dCktgNdhIwYYTv1O3PqzVlhjpLYB7wscl7zpjbYGWcnJzD0oYTAkcwlvXrKB9f25R26JODuwvHO/JSTLCnLnGOQGgGVNUyVuH5LBzycoTdUjNBjBuP3yrOe3a/KtJTiWeI3FgyaZiJbL296fs0FAlw1swuPE63rerVJGNYYhao7bfydlFp+0hEHX37l0qW7YseXkrt15t2LgJhYaGUFRkJPv91s2b1Ldffzp74RIzHPv06cPWRkjpfvvtt+nKlSvM6B0zJm/9O3fuXGbEnz17lhnoYoMcXLp4kX7f8Sedv3yd+vb7gP7YsY3SXyqp79yxnVq2ak0+vr60ceNGunPnDp06dYouXrxI/fr1o+HDh7PPfffdd2Rvb0+3b9+mPXv20NGjqk4vcQp348aNFRmzixfOJ2cnZzp87CQdP3OeqlevQdOnfktBQUHMOP3rr78UDgD8/wcffMDStocOHcr26fz587R//3764osvWBQdxMfHU/Xq1dl+wuEwePBgWrEiz+bAscEAFvZdyoMHD5ix3rBhQ2Y0Czx9+pSCg/P1lXCt8BocAzj+tm3bsvO7cuVKxWdwTnDe9+7dSyNHjlSKujdt2pQOHjxIpoYb3cUUdSmVXr5+LAVQEyGPH9C6pXMoNjpSpaYbdcrG1CpjwD7yz1/0Vs/+TExHDqREAxtrKwpwz4t+VqhSneo3a620oEN/T0MUQFG3LCigi9PwEZXetm41S3uUZgK4OtiwNG05gvw8qXWnLnRw9zaVKA+iGsbWqmHAhnGq2P+YKPpfl1Z053qeB1UTOFs4Z26OtmRta0M71q+iPVvXa/wbRBy0gQXx3XDlBYm+i0jU02PxBoEV1FYJKqHqgEHtPXMCE4NrUqU62Ti4KJw/gogc3jeH4V2cU12LI1jc3nl5f/JrZziINj+NyXesSR1/yDTJez2HTh7aS41atZc1ujH+QBwTDkAxR/79i3Zu/PmVUDBHKQ1acAqZOeaMdMOZHJ+ab3SbalswGIW5E4bIoo27qEufD1U+J+d2KemWN3+2f+c9lpL+8M5NWSe1qTIc8NzffhJGe7auY7Xkzi6uOv8tjMR+7euzEjgpxjhLhKwwfbCUmQfihii9m/vNSJoz/jO9/hZOmTqNm9O544dMEumWlk/a+PuTz6o1ZB0YqDC805EJJxjcgYHs/RJ+/qzXdGJCHLm5e2oMPonB51B6mauD+l2Z4LLUpm079v+IWr948YJFcVu1akWrVq1iqcv79u1j0V6wc+dO2rBhg6JGGdFZpEoLz+273XqQq2vevRsYGES1atehv/fsYr+jnvyD/gPzvufPP+nAgQMsuo7vmTNnDjM6AYxHGLY4Dnd3d3r/ffVlAaGhoVSyZEm2toJjY8+uv2jL5k0syo2fbVu30JPHj9l9+eGHHyoixIhkI7Lt7e3N6qEfPnxIb775JtuX9u3zdIfu3LnD/rW1tWXGuQAM7F9//ZUZ3PgeRJ/FBrQAjG3sH4z1P/74gxnQv//+OxkKHBOgSpUqZGNjw66VACLm2Jap4Ub3K5RejsXNmsUztf7te4OGUQsnZ/p35QL2uxANhiF/MyzBqIgilCBRu4saXrWfEY2D4nRuRGjHDumtcAaAe+FJeg3cmIjvhiepKLOzweXwSbp0+hh17fuRyt+Vk4lyC3g52zHxIERt0kWiDqZqcRaZlK7UA/3Qnj/o2ZNHFBBYRufvcHe0ZV7pDl3eo/1//k6ZopQgKXBkCOmkcucPivXnHsWoLB70XdjByYHvQ6phXR1Uy7PKlKNsn5JMnd197Cf001fD2OJIrNqO9/E5U2MpCx+OdmDUwLhR1LPyk2YwDyIwvub/Lo10hyfkGd0XTh6h8OehsnWbwO9lTS/GSrSEFLh56TxtX/ej7N8Up17dcPSeexTLnIwFAbKVdFXH1hXMs/dE3UowdperVJU58nXB29mOlY01aN6GOdwP7tqm8hncXlJnrjGp0Lu3b2Hpu3JzujYjsXLNurJp8MY4MAxZC1iKv/dhZDJdv3CGDvy1jWo3aq7339dt2opuX7uklD1giM2NGme59a2K4f3hgDyDu1Rp8lnxI3sfhmRiYhLlZGfnqZZnZVIJGU0JOerUrcfStWOilVPkz505zYxhRJvFCIcGQxc/SNk+ceIES/EWot7sc7m5tGTJEkWN8s2bN1lNdd57RM4uytH4DwYMpI3r1tGjRw9ZfXn7jp0U3zN+/HjF9yCari6NXJOzwcnJidLS0piTUPjeOfMXsSg3fs5evErbduZFt7t168YixWFhYbR27VpmhAt/g0i2uPYaDoB27doptgFbQKB06dLMKbFlyxZatmwZjRghX9rh5ubGnAYgMDCQ+vbty2q4QZkyZRTp9EIaO17ThIODg9IzL4504xwI9eKmhBvdr5CQ2rH9uyn00X2tf+v78B4t9PWl3meOUfbzEEWk+0l0MuW8eGFwRBHiGy+ePWURTUQ21SEeENxfRkgAJuqbl84qeZ8R0dKn1RVaqCSI0hYFNd774Qk0Y+wIKv9aNZU2YUiJVBflBvY21izFCCIxji9rfaQCaMaoP2KfBRBR2rt9I+t9qS5TQImXp9LNIa9NSvsu77HUKqFFlyaPPARTxFFCHMPFp7Fq6/n1WYzgexFRv3v9MkW+eM7aimhD6N0OdXbH2GgafOsqxR/+V6VNmrSmnfPqgJTaC0/zDW5LWrQWNfCcS7OaxA5ORL0EQSiIXAZXeI2q1qon+13eLnYKMTXxWApNjxehT9kYIMV87f8KFkRuMW5KewmbM9IdnZxu0m2hvOByaJxCHwFRamRbhT55KPt5uTU9tFrcnWxZxBBtuZDyLSeiF5OUYbROB+YXpKrv+X0dtWj/Fnn6KBtEulC/aWu6fvGsir6LoecSzwuy8/SlIITUcL7hbFeXZQAHGLJa1q+Yz9ZIHbr2Muh8wti9cOI/xWuGZCGlicZ2KTCsPafNUHrNd/gn5JCdyQxsYO/gQH4BgeRga0s2z0LIJuyZToZ3tRq1qG3bdjRyxCeUkpK3Jnvy5DF9M/5r+mrcBMXnnj55TEeP/KeoM0bUGAYiarrx/wMGDGBR6NOnT7PPvPvuu7Rw4ULFd+LfGzduqD0/b7/TlS5ePE8L5s6hXn37sggt6NKlK4v8xsTEsN/hbLp06RL7f0SaEZHG9yUkJLBoujpq1apFN27eUgSkOr/ThZYv+UFp/27dvKEwWqH0PWXKFJb2jTpy0KxZMxatR+RdAIZ3hoZgz6hRo1gWAFLThci4FBj3QjYp6tR3797N6sUBnBpIb0e0GseJc4HUfsFYR0q7PqCeG/X3poYb3cUUaSsvCEHcuXaZqtVpqPVvESnM9PKhQBsb8prwGaWGPqcT96Mo9M5jgyOKiEgiJQlK39oGWnGkG/i45i3Y3Dw86Y3u79Ofm35Rqv+FB1aX+j+kRz2MUq4Zw/OLKMTz+DQa8OlX9NWMxSptwiqV1F734+Nix/Zp29qVKgtIbMPQaLdUKOz0f/vo8b3b1H3AEL2+B+nxQpp+QFCwbK9UKY8ik+m/O5F09G4ka8l1/nEMxSarP8/6zJ8wjmDEXzh1lDkPtJU8SA3vDD9/KmNnRzWXzykQg7ugDTdLadFRlMAYAEVlaYTPktR/iwoYE+F002QIiwWhMK9AeEouggKnqetLp5+g1SFQ86WQJlpHqmyrGHhLYGhj7JSLOpvTpxCVKFncGrEtzF1nH8UwY1jgjw2rWAtP9DmWRz6SBic66DloGHXs2psZYXLcjUjU2SCTy3RDBkZyejaNn7OC+n/yBRkCytnQc17aX9rQU/nQCPFZc4+bcFRCH0WskSIGGYWn/9vPIv/IUhRHKXWlVJmyrHUYAi+GPgOYFzU541DDHTsp3wAGUUuWUPaLMGZgw/C2trYhDzc39nuJrEzKtbGhXMmaTw6UJ/y6aQuVLVeemjasx1qG9e7xLo38/Asa9NFgxeeqVqvG0r6bNKhLM2fOZAYuxkUY4KjXhpEIUTOhthh136hPRh01DN4mTZowA5X1EpfZD9Qhd+vek9atXaNILQd93+/HhMxQuwxjEWndhw7lpfND1RuttZBG/dZbbzExNXV079GD/v33X8Xvo7/4iurVr0+vt25OzRrVo/ZtWtC1q1cU7yO6DZVwpIsL2g6enp6sdnzGjBlsX6pVq8Zqt3M0pN/guBHFRqq5dB4RxoLt27ezc4jvxOc7dOigiK6XL1+epk6dysTqKlasSL6+vvTxxx+z915//XWWuo7zKxZSUweE9pAloM74N4YSubzgTQl4gXDh4RWBd6SocvxelJJnHfW/I3q/QYs37mY1y9pAyq7r18PIOS6GGTSxoyaQ5+IZBhs4u7b8yvqDL9qwi6rX1Wz41w/2JE9nOyVBpKsvJ4Ow0Cc06M2mLKr8Tp/8PoPW1iWodqAHS19UN7FAcRUDNiL0eanKeftvTdmUTdaK40Yfa6GtFnpxv1bSVScj8vjNEPqgfQNq27kbfTZROY0fQmZNynsrova6gEH39KNophYq8P2XwygmKpzmr/1Dp++oHeShaNcC4xmT1rH9e8jd04tqNWhKpsTPzZ5qBarPYBAD5fiwuLz08qjwMJ36c4uxu32dfCfkpyBFzlhKGVVqkLlwsremZhV8qCCAQB3uF0HPgKMZPNPIJoHgl+CdF1Mr0J38XtaTcrSDMeL0w2hZxw/KbCr4urBSo2P3InVKYQ72dqJKojEU49rhO1Dbzft98DstmdPt8ylzlf7O0c6amlcsmGfOHMDJe+1ZvNL4LaZReS9FBpI5yivEONlZUzMdzyWuT1xqJtt/tPESG9sgOjKc+ndsRP2Hf0F9h4yU/Q7M35jHpUQkptHVEN0iTqU8HKlaKe1rsNsvEqiKf/7nMKecvB/Fosq61uzKge8Z0rU1te3cnfp9/Lniddib7aqU1LsW/tJT+Z7A2sA5wLkwB0ghhkNFyAxCm9bWr/nK7vufm9aw8rtvF68x+LzC6BIb7Mh8aSXZnji9F9FSKEsjooqsRJYpoMbmVhJNCwxkEW8Y4PjdpmRJ8p86haxKlqRoWzvyycp6aXDbUlbpICIbW51bhyGApIuAHE6R2NmoLxlZ2Rqj+lKwtsT5NJaktAxq2awpbdqyjUoHBqr9HPQ5kL1iKp49e8aUziFYJ9SwC5klmG+QUVpQwCGCeu7p0/NV6dXdl/rajjzS/YoIqT24fYMNdoh06gIM0sQ5K5mBDUMbBo6hBjdqsH9ZNJPVPWszuIF0PPdwslO8FhAYzNK/d29Zp+QJh4IuolxCVBhpj0iNvB+RyCZgRGkFg1sQ44KBDeZO/prmTBipIsaFhQoWmLrg6WRLHu5u1HfoSJb+fu/mVaX3YQzcfpGoV9/usIQ0lQXbuNnLaOL8vN6DuiA+lxAzAmi/ZmqDWx+vNe5NtCaDmjomb30NblwnOIDE4HfhepqFAgi6CfXyUNYvBkE+s4PnGecLBiIiMXIGN+CnUndgcMEhpi7TQogqirspYDGuLs0YlJS0WcRCTaxi3ud/n1HDlnm1fsUlvRzlOTB81RncwFzPuFxLKn1OJRwFcFDjmZIa3GDZjG9YnWnn9/qr/Q51Npmrfb4RkpGRzrpp3Lh0Tu05vPQ0VqNmy73wRAqNSVVa7yBr7dKF8yz9HU56Q8HctHzrPiWDG+hbKy9o4RhKrlmf9QSlUhysT8TrKgQrrj7Lc5JAjM4YgxtgDQrV+7CQJ3ql6mMsSNXD4EZtt32dOooa76zwcHrx7RTKCQ8n37RUgwxuEP4slCKehxbIdVM3n5lvi3kZsjm5JWjRkuX09Knhz46+TJ48mUX6Z82apWRw435MSc8ye6cHufsU9fFm+W6zfCunUMFgKl2w1GrQhL6YtlDnXsgAhvWZ9sr1zYh465vCu25ZXgRj8OhvdPq8dFCH907sMfx0/PcsYi79HAxvpEkdvh1BJx9EsbS+x1EpzDsqjO1iMS4Y2PcP72M10g0qVlZKnc8OLke1gjyY8Iuu+4yWKN0HfEz+gWXo9zX5rQwEohLTdW6Dg2uIGnoBTIQQkkP6jqe37vVp4r13e5liDo788yft/n0dmRJdJ1AspjKzsumLD7vRoqlf67UNsWhasocX7erUVeEYEjtSTI25x3xc70vsfs275ubu4VvUQfQFxjbOl1BXrA5+KnXn1osE1n9ZHUj5xkJIaIWIxfPS7yfQnWt5tYNSYFzLRXPFr6E+tLlMv9+imF4u9DTHjzbjzBxJhrg2ch09dC2xeBqdorE7SXJiAnPgDx//PSv3Uoe6WRPZC/a2ectOW1s7OrRnByvJUgfuRTgBpOsZHCcE1wS9E8FJhHP6JCqZ1i6Zw6Kqfv6lyRig0I7vSYhTzhzQR7wVjkGxYasv5kpGRRBA6lTBpgQ9IJzjG8/iKTUllTb9tJgJoBljcAvMGjeCZo7Nawely6FBOC01I0vjZ7Pu36PsFy8UBjdqu6XiallRUZTxNL8XdHbJAL0MbuAAkbHUFN2uiRGXDfO/uGtQQYDrnfoyO7ZuvXrUtJn+YnmG8t1337HI8sCB+enyyNTF2r0wfK9odyb0Yjc13Oguhsg9rIFlK6hVllUHDJhG+/NaExgTUewxcBh9MX0heXjplt4mZ+cKQjxsH3x8mWBZ+PMQlcEPCx1M0OrGRLEYFwy1ioun07s161Cfc8eVIvkBlcqqtLfRBlLbYRR37z+Uju7bJesRTdexVheecXGU5N+dm+nDzs3p/q3rZChCPR24deUi/bp0DmWL1BqNRZeJCIsVLNhRG3bvxlUmqGOIwY3rhEyMeh+PVrqe5jS8zQXOG6IJ4gVQEbQ3Cgyk3yPdUZuxLcBrunUDKfoo+dAExlak8QuaIRiXHJ2cqVm7PAEdKSjP0aQxwa5Pbi5rHXbr6kXl61bEHgLsL7Kt4FTUBXMsJqHYLZchoMupRB3//UjNyuHOrm70446D1ObNrgbvo6dT3lwOA65b/yGs1ZymiDScAJdDYlmZGQS98O/JB9HMQSAgGN0hMal04ugRunDyP/po1Hi9enOr49sRA2nBZOW6cF0vHZzsut4P6jDHY4CMQHX7lZmdq4iCw+hBm1EETmJNNK/2rlKdYm9coedPH+cZl6IshcywMEp62UMazxNSyjHOa3tWHFq0JO+Fi5UMbgFmeK/4kXzHjyenenmiW8A6PEwhrqYrEAGGEwZZGuZEn4xIAWNuE5a6LxF6LEwysrKLra4NN7qLIdJJF4ME0rgQKdXXwLGNCKNEV3d6/8kTinVw1MuwuXL2BBNbCQwuLxvJUIeVjDfV6+VELQAxjsHvtGLiHvoCwzvyu4UUZWtHpa2saEZGGtmGhykM7lw/Pwr01L+GytM5z6jt1K0PTV++gXwDShtkdCN6JxZeiwh7RitmTWYRoYpV9atblirBC7/iu+Kio+jg7u1kKnRZRCItNTU9izav+oGpHeuT5o5ae+uocKUSh+MH/qbLTx4qDG+8j8+ZGnOu/+FgQRZEQW2vKIMFN9Lv9aEIZykXGDBgbofJn1eU2gjjPYwIIcodFxNFJzetoZHt3mCGtxTUhwaoqaUXG90Yo37/eRltWrlQxYFalAxvRF3l0rHVYepsFpwrdZ0ltG0JjpTzj5HKrf67N6xYQE/u32GGh7aIp6b3xc7f9u/0JGdXd9q5Qb5XuwAEPKHrcvJ+NPtXuiBHdBbG2fUn4fTTvKlUpWZdatGhM5mCOo1b0NmjByWtrnJ1qpe+GhpnkWO5XAmCAM4tMl7g7EAmy6YfF9E7vQeywI2xYCxpe2A3rQsuS2e3bXjZIi5JYXA/GTCQQoZ/ygxvTSVD6gxvqcHNyMpk6uXOdWoTQgxZpcuw1HKkmAviajpv42ULqbSXSt7mIkPv1HLDrW6UP2hK3S9oMrJy9KplL2pwo7sYIk3Lw8C5dslseoEBxoCIYtK8n6jU2z3ovds3Kd7ZRSfD+9qF0zT+4/dpy+qleu+/3HyNiVosmFmyVBBVrlmHpoz6kFbNn6b3NnJ8S9I/dfPE0sSp8zm+fkyQTVxzqCsQekDdNBagDVu0Za8lxMUqfUbofahp8StVWIfB7eTsQsPH6X+c4lNpY52fpo/a/tZvdGHRbk2KkvqgLeUOx45jgxrslXMn6eOvp+qVrgZxu+jxMxQGN1L/f1+zjPb8vl6RwYD3BRE8U2KuaClKCOSiizw6qwqiXIbURhYlw62gQUQFtcfqeiNLNTCQfSOczl2LZ9KPvr404OFt2faRZbzQi1X++cY4JH70ofdx9thBio+NLpJ13ci+QBqxPpj6toxMSlfbkkrTM4A0zkeSOUfKn5t+ZnNFiI6Oe02juodTvtENAx4GHUq84KDXFbEjSEhDR5ZBdFQkuaWl0uRe/U2SCg1adHiLmtjZ0vW/dypeExv94uis+L69/ky5XtpSgJEVnpim9lziXsCchFZpyz8fTB18fWnQyHEm2bZQ3ofOON2O7ieryHAWcb977T497j+AMkNCyNrfnyK8S7POLbnGjt8vDWsY2DnWNpQREEi5Do6sltsQw9vKyprdsxBU0wVD9h1jsj7lC4aCbaAVIAxuQ06xOfYwnYnHWU7E3RzrCeNzbzgWB2qbxTy8e5P9W6FydYMiirm+fjRuxgIKHzWOUrKzyXnyaDZY4nNy9d071v1EqxdMZ6Jp/T4Zrff+y0W6sXiDoJoQScCEOn3ZBtq6djmtXz6f1aw3bq291zN48uAulXf3oD5PHqikzrv/uIq8XfRTJhXj52qv6AO+fNYkFhmYvfp3xQJAkwfvVlgC610tBoJsxw/soS+mLSAXN3cyFgi+CfuHNPhR/7zNjOB6TVsZ/d3a5gksSuG5xuKqTqPm1KB5G723ITaoocperVY9On30IPsd92JRahmGFD91C/UiYmsUGJiMkVKuv7gMzxrQ5MRA1FDovSyHVAND4fCKiqDPnz8lBxsbypJpH4koN4xudcBh5mRnwxZ9oNnrb9IP08bRueOHWfRT7EC29EUKaqjVOS0K0hmE1Gq129Lwd9h3TX7XqIgX9MviWaxbCHpeGwscLujOIDzLaH9Zs0ET5ljWBcERhPtSuB9huEFVOtDBkX4JCiKb336m6LIVTOKALfPiOS0LDKLYbesou10ntj2kXtcJ8qASkeEsOgvDO2j5MnJp1YoZ5BBuNaQnd0HMPcg2E9aIcudSaAt6Zdc2mpqRSqWdnCjm7k2TnEvBOe729TAqFRdDGRNHUvzoSZT+sjNOtn8pejF5AWWXwL2A9mBE8bExrNuKIU6UEqmplJORwdqCZfuVpBI21kzIDWT4+pF1+AsqkZFB2UlJlPsyiq0Nf4iv4e9ffo8m0shG7/1G/bohzsbcLCvKzbbW2eBOzdRcJ68N61wbnTWPdBkL0zKz1R53TpYVldDx2MwJ9jMyMpJdU1tbw5TpLX0+45gg0h3y6D65unmQh7ePXhFFoa0WazdSwYfuujmwSOyJXgPpt3Gfku/+v2lIrfpKdVN/b91AK2ZPpnc/+B8NGTNRp9YKUtSNUb4u9krpe6jr7j/8S7p67hRdOn1cJ6N7384ttHHqV7Szdj2ySYhTaYeW8dkwylz3K9kGBJAhBHg4sP62uAT1mrSinRtW05N1K6lC5x7sXEIACoqriIiz9mYR4RRx9SY9r1xXqR+3QNmKVZi67+tv5y9EjTmXaOUiiM9UrV2fJi74iWo3bEamQNMiMiw+VRHRxcLNFIs3OGcaNGxI29evYhkFmoR9LA1MLkjhU3fKeHRW+VzAONS1hpujGRgFGKNQwqJtcScskoXMJ/wbMfxL8lo6h+yiI9V2syjr7aR1QebmmG90e/uWpNeq16YzR/YrGd2WnqSAcgeovRuyn6Z0rKG9V2yyhtT2XPV/h04S6kBK9fihfcjOwYHVSOuKNjsDmWuCYJ+7pzdzwOI537N1PXXs2osJmOnjCPrn5BE6+dsaWuruTrYRL9h9KXUE6Qoy6sROCHxPkqMz+aYmU9bL7SX4+NHVS3fIY8IoFp21DQoi+0qVWJTy4tNYkxnc5sh6ChOllmtyqr1zaC/Z2NpSlq+/wedSDnx//OwVZDd5NNm97IzD9gVjyXeisaSEFSXZuKEXEyUkJWnMntBESkwMZWRnk3tWNtlYlWDPqqI8AH3ioWsTqV+9ujA/azOo7W2s9DK6sV+G1jJjvLW11p68jF1HtoOx5S0QOJYLkOlLrg77o+uxFQS4noGBgYqe5PrCje5iCEQRxIQ+uk+B5SroncorIDxY6FeNASGndQeqNGQU/bJ4Jp09fog8vX1Y1BR12+npadRz0DAa+uW3Bqd3qXuQ/d0d6H5kklIkH9v4fOo8cn0ZBUZae6ky5Sg1OYkZ/H6lAhWD5I9zptCJTT/T71WqkctLg1uo4fZZ/TMlDx/KJlB4roMNNLyRYg7DFs6BJm060IA6Dajxzs2Ue+oIRU//gU0ogtFrE52Xxo+sgbTxM4hE5xwRH3h3sRDVVfVdjhKSqcrjZZo+bhGcu9adurDXIQxiiINEl0UkFtZCveixfbupSq16ercJU0eTxo3Yv3dvXDEocq4rpl77Q5FXU4SRR7rzQQ2xnENKVyzdcCvoqCxUiwUhNF2QGt6lvh3DXs8sGUDRMgY31KkDPdVHucWGl7i0ovuAoZSellZk0sthsF5/Hq93CylT13RjbnsYmaz5M2pGMGEuUkfIw3tsLp2xcpNemVbSeUcKstakKvnPnjyklbO/ZSKb38z7Ue2iVno/Oo7+iPbdvEE/VKxEdi8Nbn3bmorBOicsPk0x5uB74mYvJ5fvxymMUzjq7RfPoMyXJXjRUxZQRq4zxTyMMXl6rCnHLxyT2CEg51TbXbMutTnxH9nAyWDkuRQbTTVKu7NsPraG9C1JMSPHk983n2nsjJNtZU/xtt5klWvYOX3y4A599/n/qN+w0dSuc3e2hizt4UiXQ+Py1pGw4/QMWMbHxNC4ob3p46+mUJ3GmhW+GwZ76WUsXn8WRwk5honblvZ0pGBvzYrbyemZdON5ImWVwAKQjIKVYdrZmKTE7gUyPDXsD65bOR3b95obRLgNNbgBN7qLIdJFQKXqtalCFf0EuMSIn4XK/q4Uk5zBoq9B5SrS+ROHKSUpSdGKrNsH/yNjUWd0Y/DCgClWLQUQagPXL5yhMQPy1bBRezPjx01UvW4j+vLD7nTt/Gma1u8j8r50RmkyaVjGi9ydbFmEW0gVS793z+Bot7+bAzO6YdS2GTGWwmaMo6CIF+Q9aRRFT1us8CR7o07y5aQt9iT/vPB72rx6CVOIxeLDlKCuG+164kRGDFq2QIV45bYDRqm9yi0iMcGidRsWz2i7gn7o6Pf5vzETyVhwm9SuXoX1bbezN85hoA1TRp6RCikVTpPZosm2V5SBYYOorDHw+vh8g/taaF7PXX1hi/PPxpH/xJGK1+JGfSO7GK9c0lWntEMYXmJef7uH6nYt2GOiLS1bG6Y6ssda2nyxbclsDGNzhKi2Vw44SNf9e5b1rdUHbf52ZHlJq8Mh1DVh7kqaOupDWjT1Kxozdb5ax71gLMLgdk9Ook3BwUSZGUYbiRX8XJjDCPev2NFnGxhMUdMWk/u44eQojc5ie56+RquUFwQhsapOFqnh/W74c/a6qQxuUMHXhZWDZeW40I1nCWz9g+xCMfhddnslrCinhP5RzttXL9L3Xw1jwYSWb/agHCsbsra1J3dXZ6oYYEW3nhvWO93F248SkpLp2OH9VKupZke/vb0DiwjrAp7FuPQSRFaGpS2XsLEjBwf1GSJJ6Vl09UUCZedaE1kZn6qN8+og0w5SH9Iys+lZYhblaDlmK1vNx1aUsIx4PceskW4Ywj0Gfmzw94knPhi+tYM8WLQUke1Rk+fQ+DnLTRpl1DRfl/V2ZvVgctSo35h+3HGIOQTGfLeAKZjmZGezBYOPXwDz1jeZMENJjEvoHcqOLSCARbiF2ixDKenmQNYv9zGoaUt6NmEmE6CDQrrLl0Pp2Lyp5D1xlFKLslRXN1o17zv6pGcHZnD3HTqKvvp+MRmNbPs1ZQMV9XRPH9yl7euMM/ClRjcGeSHV7ur5U/RZn7fYvWTMvSgGt6W7ox1NWbxaLxX0wlwgozb5jg71nxYc4CtQboUZZ9iAgrLbUCcHFWhLdV4gymQoWCQ7zpygtX1koJcj+alRLJeCloyo/RZz88oFOv3fPsXvBSEoZAhoryXUvhqKKY4NKeUPdXBKyT0DKC+Qe7ayMjPpr99+oQkf92Xp5foa3LqALAc5Y6RZu0705fRF9M/2TUy4DaA16MXTx1Q+m+DgSKMfK3eqkIuW6kpZH2cq55MXKfRzdVBZZyTYO9AnN6+bbHu6YqonAEaduCuKGBzD1a69zHJsPq72itaBJV0dyDEuUtEZJ87Jmfo9fUIpHl4mbfmJXtrfjvyQCZ99MW2hIpggLGXRVcHQ2xprmHpNW9OFU8riecZks6AsQVu2ijY0bQpjzc3nCSp6T5YgQJljeVqDZoUb3cUQ8U2cmpLMxLiM6SsoDVpgwqxeyt3gQUvAwdaaTXSInvu55RuC6hRvASbqKv5uat8vX7kaS8d+s8f7NPeX7VS7UV76z4S5K6hhy3aK1HnxZCLeHAxvYwxuAC85JheBoKatKHXhGmZgI629z8nDbMKJtLahrU3bUGhqKtna2VNSYgJrozVx/o+sfk5TXZuuyAUKfEQ9z0HlGnVYaufaJXNY/b8pBn0oj0JMBinU+//aSuOG9CFvP39a8tvf5OntS6YAKYy4V5xsSrD2dInxcWTpPI9L02nis+AAX4GBBaIg+mcMBXEq0UoLDiakylkaiGheDjFMhA5gEez1zUgWUYy2s6fIGUvZWCZeJGPMg54Fotz6IG0FCc2NZTO+UWSWWGp6uSbRMl0x9hnHGIsyFV2/R5qtI1awFnh45yYN79WRXQMnF1fKNeOK2Efi/BVAO8vBn3+jaHGK7hpjB79H77WqwfZt6qjBdOSfP5lK+ZJKlbU6gnQBzqKKfvnpq7ifpW1D3dLTaGG58ibZXkFnWcG4uf5MfZZL6Onj5Ld8nsmPDXpANUrlr9eyw1+Q18T8zjjJ81dTRpWaNDQigpWrmMrwRpbj8q37aOX2A1StTgOV97FuQMafodRr1oqVXmjqL6/P9b0UEqex3Eyn79Ew0yFbzBRzqfL2jCM7J5dCi0B2iKnhRncxj3TD4B7+XkcKe/rYpIYborkNynqRl4udIqqrK/g80riaVfBmE12QlxMFe+V5mHUx5FHf4SLq82osphCDkBLk5ah03pgq6CjlSNHM9AyaNnsy3bpygXlPR0+dR+NmL6PWb3Q12X6UUKMeK0T3BQaO+JrVWc+fNMbgFmKCVxfRviuiRT4cCV3f/5Bmrd5CwRWVF0nGIJzfnNQE+vLDHnT6iP4923XGRGt/qTp9QfXwLWrk1akmmey7zAnEEWFwo2TD0oxERDjQSsnQ1kUpD++Sx7jhZBf5glI9vSlt8VrKqFKDZecIhrfv5M+puk0qc8Tqq+OB+UNMmze6sNaWV8+dVPRftkQnRmSSduVicz7jiLRjjNVHdEm8OYgSSnUSoiPDacKw99n/L9m8lybO/8kkHTPU4eOqfO3F9BnyGY2fvZz9f0BgMIt+V6/TkP1/6OP7ZB8Xx4wz57gYdh/KOYJ0xdvFTtZZhPpYIRovtFH1TE2hMCIaZ21HWSY0EjVh7IiCe+RehHzGUFJCPNOUqfvLUtbGK8PX36hzKQZZLPWCPVlJmwDK9iAeK2T4WQUE0MiJ39PFR/dpc6MW7HV0zkFnHEMj3BtXLmTHBXFGtG8VIx6dmJCtgTRq8Toz7K9fPKvxc7o84tBVMEazREDdsg0OYeiimBpTOA2zLSzyXhAUS6N72bJlVLZsWVYD0LhxYzp7VvODUdwQT+ahjx6w9LCAMmUN/j51Cyl4CuuV8aQ2r/lSnTIebICtWsqNqpd2Y4ax+M9gaCPFqGFZL/Z5pHGJI9qoqS7v66yzAQwRB3Vp5vqiKbJuKDBsEcUXkKthmlM6kP7+9wy16vQOFTRobSYGEwjakpUqU1avhbO4xyduu2P3Imnv4RO0YcVCmve/XpT8719MDA6iI8YKtamjcrkghfKxuTBFXTCMM11Fdl5xm5teJKSZruUOmQ+UUKB9kLB4EJRYLYVH0ckGLeiQVoxyl8X9u5JtbDRbDENxmEoGKNWBosUPnn+n54ZFfLwlC99G1tbUuHJ1+nXpXOYsuReONoM5avshFwbq0rIL6r5E/TYiY/qOEbmS+n4pj+7eYtosM3/azMZTY9BlCvF2ttdY+y/WF+nUrQ9N+eEXmrRgFa35eSt1PfKvUnmW1BGkq7FYysORrSXk5jyU0lUNcCPrl4KnwvbufDaO/rp5lXa06mAS49TccwE6h8jdr1fOnaTJ73Ug+5EDmVMNxxLz/Q8Gn0sxns621CDYk2UzikEWIcr3bH5YycYQCM+2a9GYvl28hpr2GsS2Gzl2mkHtydA554uB3ei3VT/Q5bMnZD8jvsy6lsHIgc45vx26RB26vGfwugGlZsgGVNc2VF/UbQvdcsyynjCmfXp2Dj0w0XEXNYqdkNqWLVtozJgxtHLlSmZwL1q0iDp16kR37twhPz/z1t5YClmiaEvYs6fkUzLAKINH2/yJCUuaKhbg7sjSxrFwRtsETGDaxHXKvxTb0AVEaiuVdDVYDCN/38lslPdxZguk1NDnSpO2uEVZ4PfjTSZWIoc6AxrnWapci7romvWbsL+ByjhOTqOW7RQieVLkenxu37iWFk/9mvVL3VixInmvWkQxviVN0uNT5dhEgkxN23akrWtXsnpEtDkxNaaYtJBarisFGemGI0C6OCpMYGw9MrK+Tfn7yCwkpGXShSexKt56RLst4XTiukpFJ7Xx7Mkj+nnR93T5zAlKT0uld/sNpsd16pNz7Qbs+YZzFLoaWOC5VfIh6982sOiVoSU5uO9cHWwoMS0rbzyZPZGWuLtSl4vn6fzxw6wkCFGaoKxElX7IhQWMGFOg7zPO6jLDEtTW5eqW8ZE3akYnp6u8B12Wn/86apLxU5t6OcB6AOsGOQeAJhAFRTRUKvQlFgQToqXSedXDyZZ1F/F0smOpz9rGPcyTvpGhZCXaXiUfP5q5aBm91rAtRXV4W+P2ChuMRdJSCMyRG1YuYBHhD2rVI4/MdIPOpRw4v5X8XNk4oQ48u6XTMunZwxi2NoTjQ2gh+jgijMaN+4zqNmnJxFY9vLS3uc3MyKCpn39EZ44coHrNWtP05eupTuMWaj5dQklTAhmThqZ1IwsEveGTEuJY2zs51CU+Ye64ZuI2mHLDCbQ8xKK5lhKIuP48waRt9YoSxc7oXrBgAQ0ZMoQ+/PBD9juM7z179tCaNWto3Lhx9Cogrt2LeB5KJUsFGfV9hrb+gqHt7mild4RYVwQlc6HXq6WklovPWw3bVHo0Od/gFiY2aZsOcxne6o4OhioWHNLIK/YZC7C9OzbRuWOHWPu1TydMp7qNW5KtnR17D+J00REvKC0tjdx9/Mj25TH80aoDLZ4+nvp1601fRYUr2reYssen8r7mL946vfUOi46dOvwvUzO3NBD9NEVKqqnB9b/0NI4allVOAyxM4Kgy7YRseqs7JSOLnTe59Dhca0twYqDtkS7p7lD5Xb1gOk1etJo8vLwpITaG2nXuxgQp4bAFwtVwtLVWdowGBBjc5UEccUpMS1L0DHYJf05/1KpDL/zzvjfk9mPKnjqaskJDFf2QCwssYuEgKKiyBzyfuI6Y49A1xNAevmx7L//FPYGUU5CRnkZzvxnFMp0+nzLPLA5LbW2O9DW64cCFGGre/SJpMfVybrULeUR2TZuTfYkSLH0cWXl2WI9oMAbVUeHtjnQxNZMygvK2h/nmixHD6Pj9KIqKiKDsKfPJ/tlTsziWjR2/UM4knuORdj1m4Lv0+N5tGvTZWCbYGnP5nMZzCYNb07GhRSDKA2HA6pqyjeuBa4FIt5OdDcuMhDPJ0dmFZf7t//N3OnFwL3064Xtq/05PVvJ2+r/9FBMVTvEx0XTk37/oyYO7tODXnayLzsM7t+jzb+dS5179NW5XutwLcHege2mGR1ynjvqI6SbN+Xmr7DpZ7hnH/HbjebzBGhvqkBtO7rzQLtpa0EQkpOnQvSWfR/duUTilU5Wunag4UKyM7oyMDLpw4QKNHz9e8RpSq9u3b0+nTp2iVwVxemNWViaVDjbO6DFjMNhoqvi7MpEgQ2spzRnpZjx6SDaREQqD2y04kHnYn5FhnmRTL3jkUnwweUxbuo6uXzrLotbfDOtHXj5+tGH/eSYcMvidlorPNnytCi10dCSv8OfU9b9/yO2ryfT6mWNkY4J+qdrJv3gtGten9l16Uk6ueVJ7jY2WIqtAn5TUgoh0Y0HA1OXTs1ntrKUY3c9MLK5ijjJrKMGq63VtKXXdmoyZB7dv0J+b1rCuAmEhj6lC1RqUEBfL2jbNW7ujQPezpJs9G4fEzkj38OfkvGAaRY0YS15LZ1NW+HNmcKO7hLFGvjEYGmWWQ7hNBBXz5IwsFvmyt7Vm9Y6o20aUylRDgfA9sSkZbCyCwT1l1Ed05exJpidiTO9ZQ+dVGGmYD/V1skmNQERLYUBl5uRQakkX8m9WjRl0pgBZdf4d2ymyb1DWxjL3EsJp0FvNqWSpQGZ0eZB5MPT6476SjqUwat/o/j7VqNdIUUIgPZeIVqPkDk6KNKfSlOzvTza5uWxdgHIQvJ+elcMcQGW8nMjZ3jAzoqKvC0UmpStaimG88vHzZ6VoaCv6y+JZNHvcCCbmB3G9LT8vYQ5CV3cP8isVSJ9NnMlE0jCPrd93Vqf7V3pbwoGIEhZD6fhub2Z4nzz0D+vmIyVXsi6HmJ20P725Is+sBZmZotyG3peZ2Tl0V4/zvfi7r+nfHZupUbMW1I8b3ZZHVFQUS/coWbKk0uv4/fbt27J/k56ezn4EEhKMS1e2tPRy1EAZizmjwcaCVLEapd3p2rM4g+rszH1srIZpxTJ64VWKcqxdyZPVrruwieu2VQmdPMnGoOnwoM76ODpZNlqHerraDZuxFmyP799mXmVEut08PGn01PnkU9KfpRD++dsaWlu6DI0MfUx24c+p01+/s783v8GtKuw3btZSs9ZCY3I3JOsjL8VPvzTfgsguvxeRxAxukJmVS2SnfvGGfslYaCElT1fwd4Jegvj/NYGoDCJ6psTU5xKGl6bFTKaaCAbq2BAlxbMv3Ed4Df+vS19rfWvNNaVNnj9xmClA12/ehnoPHkFt33qXRTu1YY7hEpEuIcVcmgXkP2mUYjx5MWk+RSTbUhDSzb2076s5nn9oDRgDUuiFqCLuI/zAeMF5tYqMMOtcICzKWcRcZHBPW7aO6jU1bbq+PvcJysQgCmcMuH+wFjAXKKkIjU1ljjYY3KBlgxq08Jff6euh/WjGV5/Q9BUbzKJbYsjwBR0HlCKIswDReg1Zj937D9H4tzCkjal31hVcL0GXB44NzOGCU8u/dBkmKouSh+YvU8/h2LCxtVMxrvWZk6WfFY89hgBDu1Gr12n5zInsGZIKtwkxAFwHCFoK8605kM5zj6NML56mtD0D/uZeeJJWXRt00EHGDUQTS5SwYt2Ihn0yjIoLxSrSbQgzZ86kqVOnUnHC1EI+FmxzK7yVzPAO1b19SkE6FGB4V0RKVUKaYtBHzTtSrCJ8nCmsVABkes2ybU21dVg8BHk60WMNvYVhaFeqVov9ANRYvdWzn+J9oQ1b7O3r5DthRIH2LxVfOqjMojTh+o2b9OjuTZMqwAvg3jLkdkH9pL7RT3NHupHiJa73Tc/G/ZefeglDAItz1J4hFUyIRLk52rLIlHD/IN02LTOHLegRGQFYSCF1DgsZXBf8IIKH5xQLHERG1LULQuqdqQ/dFCJ4YrQpwaJ7BAy01MzsPAM9FXV1edFFQVTS1d6G3RMwjnEekZqJOtNgLyeTCDvKRbkT4mLowK7tbNHdc9An1K3/EL2NBF1qdQ3t5SssfIVOD+Lx5FrX3uTn48fuQ6RM4viEFH60sMR9hfHUHKKYAnC0GKoCL6eBkSFuWxkZoch6Quq0OQxv4blCavnOjT+bzeDW9z7BuICWoREJhrc1Nfc0DqdYOW9nuhueSDYv7zHM5b3fep0SF66i8UPfp8/7vUMT5q2kwGDltmIFDcYaCO2Jnekvnj2lIV3b0MQFP1HjVu01f0EBrvfE5YQQ0sX4L8yVOL+IcAuo05bRB7lDQ5aEoWnY2McRE2bQ/7q2pk0/LmIGohg4q+FwV6ceb0rEawaItpq6RZixIPL+XEMW28lD/9KyGRMoKuIFDft6KnX74H80ctIs9p69g/mdQAWFZeQTmggfHx/mBQsPD1d6Hb/7+/vL/g1S0ePj4xU/ISEhVNQRIi1hIU+od+taLCWnOBvdwM/VgRne+rYvM+MaTQV4j8U9smF8QMUdrdcqlXRh6d6mbIWmC9i+sfWncsrsBdG/tIRMqiJqumeO/ZTuXL9MloIhKanmNLlhEEIxVaw8L4wZMI7hhDl1+ibd27WPGebi1E9M5EKEDosJGCLwXMMYgdGEn9jk/LpXGO+IuGIhhb+Bp1tT2rOQbmja4zVv73DxeRRKCY7cjaST96Ppya1HlHz0mNKCC4thnDecI+wbc3AkZbAU62P3o+jo3UhW8xebnMEMJPyrr+AOFq9ikAE2Z8JI2rzqByakhHnSkKicLi0dDcHH2V7jeOK9dDbtmDdV0c4Q50+4D7FgPv84Nu+cP4ii0NgUs6T4I+XbGISadakitNCOCq/jfXNpYAjPPhxl7304nFb/dcQsBrchIL3YmHVGQTjPkRkGB6IQ6QaoS+75dif6fsVG8gsoTR4vBbX2bt9E+//ayroAZGfhOTf8ftTnT2HUyIk7rls6l5ycXahW/aYWm9mIqDMMb3Mid2gwutHezFACgoKZ6NtrNeqovHfpaSwbn8xtcKt2J0g3//b0uDGh1H4rTN6x8fzpY/rmk340ZeQgKvdaVRrxzQyWtl9cKVZGt52dHdWvX58OHjyoeA2TNH5v2lR+sLG3tyc3Nzeln6KO0GIF/U5joiLIxd24aiNzRTdMDdKT0MJMHyPSUJE4Q5HbHiZy9ARFe5LG5fIMcFOlm2o7PGynrI/hqZriBaOx/VKNPZdwaHTvP5QqVa1JE4d/QDGRpt22IcsmGKSGLNbN2VsaE3L26ZMs6iZco/TMbHoQmcSMlkc3H5LXN6PY+zAoTY26Q0OGDqI0BbU9Q3gSnSwbvRTf63AyINIvPBv6nEekr8IID4tLY4vnc49i2L8n7kfRqQfRrAYfRrgmBEeHOF1v3JDeTBjxi+kLjRLLMtdcwESVbK1kx5NMvwAqY2dHPU8epuzQp2q/A4Y20jdvhyWy1oUwQEz5HEXrWPaQmpxMOzeupplfD6eNPy5iOhhP7t9hEfwj3d+nOCdnxfhod/u60vGasyQHpyIhLYvu3rjGxk6kb5oLfadVOKBfK+lqsOFdEIYisihQ1iBtVYq5u2vnjqylGRStkxMTaO0Ps2jO+M/o3caV6M06QdSlYQVmfJszUwfijrdfJKiMd7j3DuzaRv2GjWatrrRRmKs9pLY72ZtPhFJu/MIaCKK8xoCobMsOncn+wmlKe3Rf8br4WmBsM8d8KrctaXeCwgaOB3UaKFlZmWw8gpDjd0vX0Tu9B5KziysVV4qV0Q3QLmzVqlX066+/0q1bt+iTTz6h5ORkhZp5cQcGt/DwhYflRe39/EsV+0i3AFINW1TyoVav+bKe4ZYU6dYFDD6YxBuX92K9LguCUu6OBkW7pQtkY/qlmuraOzs5sIEbzJs4ikX4TIUhC/hHUckGebnNZXPjGB5G5StFC9cIEVkIBQlpruaMuqk7NgjMmCMiYKr0ctRJSmv/xOfRftQgOrh6CXv93LYNZPPpByY9j0zBOimDGeEPI9WL0QjK1EIUYeT7nenZk4esJlJramkhzgW+qfEq4wnVqEXR0xez3yGfFjhzAj0+foi+/WwQhT5+oPa74PSA2N25x7EmacuD71BXIw/H/v1b1+nOtUvs9wd3btDKOVPo+dNHtGH5fBrQqTFtXbsi773YWOp58zqFZmWx40QKfUEY3MJzcODwUfqkZwfWo9mcGHKbwKCtFWhYgKCg5vGy3k7kK1MaA4cBFLiBs6sbbTlylYl7Qexr4IivWbosdFLgCN7y81LmmDHlXIB1HwRl5cbPX5fOYWJvb/bILwuzVA0frH8qlyx4gyvY28moaDeAQe05Yzy5fDmUSkS8UHrPEAesoesTlIUZUwaj8/Z0/Bwy4tSVjmRlZlKZ8pVo+vINrGwRwtfFnWJ3hL1796Z58+bR5MmTqU6dOnT58mX6559/VMTViitiETW0C4PqtJ29Q7EVUlMHosfwXlbwc9H4OXPWABqbalU/2Is5Dsw9DuEcVA3Qf6KT65cKcRRBDAmvC8rs5qCEzISNhY+njy99/f0PdPvqJZMuLvU13VCvq6mGSRPmEsBm7bjSs5WuUUFH3dTVqxubvmtuB0ZIbIpKjfT2f3fRyMQkCsnIIM/UFOpx4hA7j23/3EI+mRns9bE5ORRna1qRJzhz1GUFiI1ub7+S9FbPD2jVzv+odqPmRm/XnKOlR/hTlfEE43eOr/J4knHrGisfQRcFRPA0gVKA04+i6VZYglFaJ5ruTSgsf9KzPS2a+jX7HcrQGw9coCWb99Lqv44yJ+D7Qz9n76Gl0ZiVm2hvnYZK31EQGhh4Djb/tomlQddqoD3NuDBAfbdgvOpDQWWsYTvqRMaqBbixVGUBiIF16fshizALrawunTlGaxbNoAFvNmYp6KYav26/SJQV6YJDyN3LmwaNHMf0WXShsJd73i72FOBhnhpedceGkoHage5GZRjCsZrq6k4loZ72cW+KunaxQMtHcs3QYcHY+xLZR8igk+PcsUNsDDd1RqKlU+yMbjBixAh68uQJUyU/c+YMNW5srv6JlofYwxUdEU7eJeVr2fWhsAdhY2uWNaVPW6jNrQCOg4ZlvQyu9db12mGi07eeSuiXKiyQ4RyoV8aD6gV7knNQafa6uUSB1B0b2sYIAm+INtRrkt/erKBB3bShBp+50stDYvOdAFLDW4i6Jbm5045W7en681Cz7EOunum7rG/89k20edUS1uKqMEDKNoRgxOzb+TutmD2Zkl1c6HC39yndpyQ5x8ey8+ienEgZfv50rOcAOn7tCo0d0kuv6JY2cHsgkiunBCsYiHAKQHxoyBeTWPTNFJjTuPHv0I7SpsxWcva4OdiwsiHhXsV48tqQUbRm93Fq+1Y3ZvCuWzZX4/OC+lb0Kz7zMMbgPtfqFPVPHd5Hh/bsYHWIU3/4RfG6t2+ekx/tOpu27UilypRVvFevfCX6MFJZd8Z94TSKvp4XKTcXSSmptH/PTtYH2dxGqjFfjzlbXyxhHofzulopN6oZ6K72+F9/uwet/fsU1WnUnBZMHsME7UzhSFVnaCFyOGryHLZdSy25kwPRbkGws6DwcLKjphW8DXL6AIxRSfN+ohRPLyoF58y3Yyjl1JECKx9BhxCMg9J5Cq9dOXuC9T0Hx/btprFDerOSBxi+5swgw70p1488KzOTVsz5lnz9S7EgyatEsTS6X2WgmCvQd+hIGjN1gdHfaQkTmjFU9HNlImtyhqslTDC6KHw2KuvFFp/mrMFEK7My3vrVd8OgFiYRnEv8QNCsfrAnOQaWMpvBre7YcK6EvqHw7GdkpLNej1BvNRZ97GCkIkP121DMEelGzZ+0HlhQihYz9NpVmjJ9Ap0+vC9vX0yc8y0X6ca+ydV8XTx1lLo1rcwWqD8v+p6+GNiNCRTpgyn8F1jUCqdBOB89Bw2jbcdu0IyVm+j1wSMoYcwkpb+J/3witR40jOau2UZVatQlK2srVu5gqvMJgTu0MRIDIxxp0KFPHlL/jo3o0d1bZErMPVyW7vS60qLUxsqKpe6ijhavC+MJRKHGzlpKH44aT5fPntDJSYVzg5p4cSaArkCBXsq/f2ymySMGUM0GTeidPoNY72BDNTDsIsPJb/JoyjLBOKWOLdu2U3xsDMt8MD+G3yisu4GrfZHNxsM8XSfIQ23UFMJb38z7kemP/PLDLOYcM8a4gXNXHXAKxcdGU1Fb79lYW1GtIA+V+nlj0XaboMyueik3lmFjSMkdxqiE2Ssp1cuHlcNUmvttAZaP5AlMCkYuxsR//viNujerQl9+2INuvyx/uXvjCqUmJ5Gnjx9NGPY+fTGoG6Wlmqe9WFi8fKbfX5vX0rPHD+iTcdOKxBrclHCjuxgb3Uhvqli1hgm+teg/FPBeNgj2ZII9RfHI4EWvUdqNtVYxJ1jgVvY3rKZKvPDBggOGd0GrsQOxKEpyQgJdPHmUvhzUnR7euVlgtcH3I1WVOiGohJ7nAtO/GMrSqxDFlRoNpm5zBaQGmjql6LUNGtE/+89R/+FfsN/HDn6Pjvz7l8n2Q85AkjOE8DmkRH80ajwtXP8X7bn4mD6dMJ2VzID9f/5Oxw/8rX17JjiXkUn50YN534yiPzasZv/v+lKkUpOCf4Uq1Wnk5Nks6nz47z9oRJ83WFsUc5xLIVvg3x2/kbW1jVKE1RSYe7z0c7VXWuxi0Y1SIbnoJxZr7w8dReNmLWMRPbScefLgrsbvh0Pi4hP9DG91DqH2Xd5jDpe5a7ar1CLKrSM1aWCkeHoTctKsP+lHT08eIVMgVdWPiE2mlh3fpqByFc0u6mSKSKc+qb6WZHQLmWO1tKQrD/1yMq3cfoDcPLw0fpcmfxJKTMS9uMXERkcyRWg8F/pgKUaQi70Ny5ozZXmdLseGz2C8ga4OjG8IPOod8f5yitJrjwZ8XCDlI8L4j3lh2YxvaP7E0VS3cQv6dvEaGvTZWPYe2pr9sGkPyxYaP3s5lQoqSw6OTkzo7+dFM3TPyMrVroMBnRYp8bHRtH75PHqz5wdsbnzV4EZ3MUMsGrN6wXS6ePqY0d9pIWOwSbynNSVtxSxtstY2GVQv5a7XJGDI4UHQBj/6Il1f2L483+aqSVd3bKU8HNhCHSB1ae4v28nFzYNG9XubpVkZiq4RU7TEQtssgXPHD9P4oX1p8DutWK/U//buZK9jAVy2UhUWxZ37zSilyc7U2eVIPRPXlyPa+sf878jqk/cVRkDE90sUUbdS08aSfXws+5yDkzMtnjqWLeJMgdyxJaRmKaWezfjqExalQWsr1EWiThbaFO/2+x/Vb9aafQ71+t99PpgtFNLT1NfOG3suce4EI+3GpXMs0o5FiiEK/kFlK1BsVCRN+LivSaLQ6AMrBpkMWHAd3bebWkBN1wS9bcWYPy25BFMwFhB6Igd5qlc1Ro0y7pnVC6bR3Akj2f9rqzO8Fhqvc6q5VDwvKSGebl4+z+5NlLHgXwG0fawV5M7SVCv6uSjts1QDw6tcEEuhzYuOrWDRMX9rK/pj6ldKzjlDkFPVb/N2T5q8cHWBiDoZe5s42lmzNmK6Yon6SzC8NRmNEFaDgjwEAX+cO8WgDJjncerrdzF+ApQ3FLVIt4Cbgy0TljUV+hwa1i8wvptX8KEqAXnZNrog54B1mjWRMp8+JnOCcT/2pc4HxtHwZyE09KtvadLC1dSi/VtK4xTbT2travd2d/pi2kL2+6N7t2nHup9o5tjhOinta5tWpWnuAuHPQ9l9P+izPA2MVw0LHKo4xgCvvPAA4gF6qsXzrwtFyTDVBqIotWB4v5xZitqxYb+xmNMVQ4/utZIu5C3qKa4L1jLnEqmC5X10319TOVcQsRcvyheu/5Mq16hDs8d/RinJ6tPxTAHUOgWiI8Ppu88/YimEaCvy6YTvyd4hz6ho3akLTVqwitWDHtu3i/4aOUCxQJamYGeGhVHS0aMG7xP6X4trq/YsmU1dDv9DftlZlOHrT/EzFlPZNk3Jd/UasiodqDAYbWOiaMx389kkvmred2QK5FLn0TsYwGCaNe5TVnemzcAb890CJlC1/dcfadyQPpSaIu+hN9Z/AaML62GUKiz9fgK9Vr22oo+oXPTSqV5divl+sazhXblmXRYdzcrKok97dTJa6E+6Tkd6IcZ8KGc3f/0NMjUFsSBHVhIMFYx1wj3A6mUD1ItKog3aVzN+oAe3b7BrpEuq+fXn8UqvqYsYSvuy/7FhFX31UU9KiItVeh1RMbR99HN1YEKYZREtK+fNxDCRYSXVwEC3hfplPZmBid/jZy2nx8O/opCAQEpNMS7dU9qdIPbGFQp/HlJgok6muE1Q6qSroJalzuO4xnCUa4p44z7atnYlnTt+SG9noDrDBpw8tJeq12tEHl4+RbpFbHkfZ5N1cjHkNsHYE+jpRC0r+bLsvXK+zmq/R84Bm+btS6Wtrcnlq6Em7+QizmaBiDLGKsF5892kWfRBrXo6O0qRFTt50Wo6c/QAfdb3LQoLeaLx89qc2erEJ1+rXpuWb92n931ZXOBGdzECHvyEl4tXeOMzMzMUqZjGYFlDsGk80FgcAQudqzUS4O7IVMLNCQZq1KUh1VzXKIK6wR2LTw9JWr8p0HTtsHAXp+I7OjnT1zOXULf+Q1g9qLmA4BIMH7Gg0uipC2j+r38wQat3+w1WiTx0ff8jWj1uGn0eHyvqm51DT6NTFAb3kwEDKWT4pwYb3mEioR2k2V/e9DOVtrdnC4OY73+gUq+VZREF/0rBVH7DOrINCiKbqAjyjgwlT29f+nDUOBbh3fyyJZYxSB0KcBDCsIVRi2wEpIxPXPCT1ggNUnoHjRxL89buoAe3r7PMHl22py8YU7GQmT5mKEtfRhsgIWogp+APMaXmTauR8/KfZBX8y71WlaWVYkH8+5plRu2b+NhgSOLn1tUL7B6vawYRwYJYkCNLBXWx0sgShI6qBbir/buqterRp998T3u2rteqag7Qfi365cIwIiFNrVgaelsLoAfzjvWrqPN7/cnNw1PxupeLnWwKvNADGGKYiJaJNTDQosjexprNRRjL8Lpjh7dZZg6OxRikIokB08fS6kHdC0zUyVQZEXAw65JmbqlGN8C9DOeKul2sWrs+M0QwFsiV3qgbviLUiFQBOJZRVtXi9bf03l9LO5VChp8p+ncbM37hPsS6CxkYyGhReV/GAZtVrQbFzVxGCS6urJuFy1cfm8zwlmazIHMHmg0fd2tL1/fuJP/vvtI7mwUtJX/YuJuNc+OGqndkayM9K1tpHSRw9N9drG/8qww3uosRSIEUIh8xLx9skxjdFjYImwIYZa4ONhY9WWsCYh/iNHlzLH7wt0gzr1fGU5GurQlNayMY76Y+1dqOrYq/m0JUTYh4vzfoE/b/KLvQVzxEF9vtSXTeJIXFE0TA8G+7zt2U0pHlKNWmI+X4+rMJ23ZEf3p29gTdDU+ke9fuM4M7MySEbAMCyL5SJdIX9HCNSc4zLiDkNX/SaHroU5Kivp6mWHgjlU4A2wle9ysFrVhGtXq8SZVKutDbvfrTgE+/Msl4Ij2PaK0Gh+Ef61cxh8C8Ndup+etv6vx91WrXZz2o0Q/XXOMqnJjwzH+7aDVVERlEMKJiJ8wgt5WrqE79yuw+R5QT2Rblq1cgj59WU4yMgr+dnT1NWbyGpfuayugWFjlvdH+fNh26ZHSrSDkKariEASu+J8XjtjiLRQpEwjp160M7N6xm97o2nr7MSnn80sElh5CFAVDLn56WRr0Gf6p4DZFqROG1gWiZuGzH9uX4DeFJ8TFhXLt/6xptWLHAqC4GYsPbOz2Nlrs4F5iok6mAUwIiqNruO0ufxpEmLW4nJgbXe8CIr+jquVN0eM8fOmlS4L5A20B1JMbHstKHpu066b2vlngukaHIxFmNVDQ31bHBkSb9LjkHbEVfV9byMHn+agq3siaHuBhKfSloZizSbBYY3nO/+ZxsY6OpzR+bDM5mQTbWrFVbmFAoghWGaKWgL7d06MpIT6MF337BxN1eZbjRXYwQi8PEvjS6oVBoLEXVMNUG0v6EhU9RA5NQkIy3VYopjg4RpkblvLSKuGnqeQ5VcTnvsDmBo6B6adXF8POnj2nisH40ZuC7erVx0ibIhUiZIBzy787NNPZ/vRSKoboukDP9/Mk7I53KzJ5ENjevUtqIj5nBjZRvGMIwiA1JLReccYjQDh8/nSbO/4myGrdQLLylUUVsx6VVK/b/iICjZ/ygEV8q0qqNMQakfyuMW2gBNX7OcqpRX3/FexjCiDzCWNn6y3KN29MXGLP4bqTZN27dQek9RDhrdHuTgquWZ1EQqRZCUOVyVP7tDrKLPbTxQs016oORXmoIcFYo9jM1g9Xi4XidXQwTQ9RGQU0FLD1bTS0n0o7VjSXIfkDZweyft6rUMMqB5/VKSFxeWqbMfQKNFCGamJyUyEq2Or/3Afn4+SvOR41S7jorHcMpI7QkshM5FXDfiCN5qHv8dekctj1jwPN9s0e/Au8JXsLEvbubV/Rh/xblNQrE4dTpsSDCiFZuvyyZpVJPKzd8PY9PU1sOAUqWCqKpS9ay2ll9sdRzKThgjMFUR4b1DJ5lceBDWj4CcM8iMp7jW5LiZi6lvxq1IBvJHGKqbBa3sZ9Q2uljtKF8BbKPijDKuQaF/Xd6D9Q4f2qaVuVEW8+f+I9F0OEUfpXhRncxAkqWAkgJ7fbBEPLytXxvdmF6n/VtkWVJwBhCimJBgEUlRNFgZKhDWxYgFtEmVSLV8Roj3Ve8XSg6L9q4i549fshEQ0zVE/thZF6teETYM1oxazJ16NpLrzRRTI7R03+gZA9P8s/NoZITRyoiU9HTFpFVybyFvr4IAmqZGXkiW9XrNlRRDUVrJk3AoEQaLP5+4bdfst7IhpKrRkQNmQhYeBoDnByr5k9jxrdie0ZcXixsnz59Srt/X6ci1hbo5ciyQKQdEaQgwoV7UB23rlygVfO/M0hdX1wfjzZ1/+7cQv3aN2Cp+uagIJWNNfXLreTnotYIg+ENp8O1C6cVKvPaesmq1RpIF6VI5ubS230GUu/BI5RKZ7Rdfyl52RDWKpF8iMUJINMDKey/rVpsVH93RL/KSJxQgqq+OTH1bcK0WALd1Tp+LUn8S5NTWpM43Kfjv2ftBSGwps3R9lhDlBvj/On/9rHIokH7aaFGt1AjH2zMms2Eh4bMFZSNiDu0iMtHBGc29hcZdy6VqlLj8d9TTnY2Hdq9wyTaMmLD2yk2mjYFB5NrQrzJslkWTfmKqaDrW44l5xA6c+QABZWvRMEVXqNXGW50FyPEKqvBFSvT8PHTNKaH6IqmCGZRB97TogoWbWKlXzlMOX9iwV3V301tqrm2BTkWTqhHN93+6PY5GD21Aj2UUs1RQzd21jI6dfhfOrh7u07fo8l4w0QjpPciQmVnb0/Dx00jfcEkmfL1NJXIVIqHD914Hq+3gwC1VYKS+saVC1mfa7nv0CXjA0ZQoJcT+fqXok0/LmJK3oYgjSgifRdCaBBP0wUsZBDxaFvFjxqU9VQyvt7s/j4Flq1AZ2ZNUhgW0qPVR5QO2Qv/7NhEP82dSjnZ+apliFhV8tM9moz7HgaaHFBnLx1cnlbMmqT39RXOJUSVkjOy6MLJ/8inpD9LXzcHljITIH2/dpCHRm0LODNw3S6fOa7Td8qde7QYE2cmoH2dT8m8bBMYzhB5MmTcrljSRcXoxjgljpj3HTqSCar9tvoHMgShxtQjNZmibO00quoXBTC/YByHOrx07LdkQ1F6jVHjLQcCJGjzCieLWMRKfFdmZufQpaexSl1qpFy7eIYmfTqAQh49MGgfLf1Mos7f3Jo2+rQ1g/aNujURui8ILcgEnj15SIunjaVZYz81icMfa4aYkePNks1SOrgc7dq8VnYMVbfnL0T6MWLwHXUbt6BXHW50FxMwGItboEDwxxQtaYrCIPwqE6AhGmSOyBRqqmDoyNWT67LwgdfXVLukjyiKj4s91S3jobSobdauE7V581068o9uPag1TY+hMXlR0GdPHjERp77/G0kubupT4dwcbalhOS+VBZimfs+ok3qiofZUjqiX6e6IeuzZuo7KV64me0/I1c+qS5Ec/NkYqlC1Bi3+7muD2oiJI4pYdBw5dIAZi26emvvVCgY3FjlwAEDYBqUPiIAJSvuIEk3s0ZdGJ8SS60vRGnjdUdduiCjd8+gE1kcdqe+Ozs4G9xEWFos+MtFZWzs7+vjrKXT57AlFmx9908sT07MoMzObLp06pmipZg4szbiBtgWMXzmQ6YVShTkTYLxqjxbLRbqhNwB2bfmVNq9SFhGEE8XQ8dXXxV5loY77qbyvs1KKcK+PhtOe39eztEx9kIo6ZS3bQA5161LW/GUFYnibU3AP6vDIuiqqgQFoZGi6bb4b/T+W+SIgGGb4986LRFmBKjE3Lp4lVzcPJthoCJZ+LgWRV0MUzc1xX2JNgTWROOINsEYSxgc/V3tFaQECYmNnLmEO/392GF/fjGfY64eZZslm6d5/KBtDf5g+XqWlnbzoXy5rmSoFJRNoYdmyQ2d61eFGdzFBms6xZfUSWjTVNMJCFrbO4kgGfFO109Cn3lIuwqPLXI2/hXBQYSBMjuL65dFT59GUH37R6e/VeaURqQ2LzzO6EWUcMeF76tyrv+xnkcVd1gfidB4v28m4KSKg0oVyyKS5KgvkB5FJLI1YV6DQDA7/vZPiYqKZerocuvYgxYKscoA7jZo0m6JehNHymRNJX8TnMTUzm7asWc4yD2o1aKrx72BcNSnvzQxtMVjY1C3jSTUD3dlnKr7dk6KtrMn5pRp8bng4PY5OVhjcuorSIXq8eeN6iokMZ6IyArhefmqiVdqo4i/f7xU1ndXqNGBRdUMi3SgtunfjCiUmxFH9Zm3IXFjaXIBnGs4rOYElODNGT5lH0REvdMpmkXu+oTeA1yHMJu6dnZe1Y7hQnTpjXara3nfISNqw7xyLsuuDIOqU4edPj76awqJeSMmv26AKE/2TU9UvSuD5Q+smS+3RrQncO+pE1UC9pi3pzNGDTENAyGDE830rLFFtFFHMrSvnqUrteqzMoqg/3+qAg6pOkP7CauY6PqxrGgR7KjlVbUXnH/OmODOqWbs36I0e77P5E638DEV5zRBg8mwWOLE/HDmeQh7eY+nhumSGofOK3Pege0sdHunmRndxIVmSbhQTFWkSpWFLjG5wVGu75TDnZUNau9TY1/U+0bTg0AdDjg8LHnHfcLRWguDSrasXKS4myqD9gAIy1utQS4Yw1jt9BrF/pcDzjRrgin4wvKwUkzEioJWtU1TajVjVbUgRUxdQnGOe6jDet4qMoHOPYxT149qMxuhkqIjmsjZHULNF6rUc4gWCLpGmls2bsP7iZcq/pneKnPjjZy9eYSrvPQd9ojFqiN2rI8lUkDNYYHxbBwRQ1HcLKd3HT3Hewk6epcf9B+QZ3EFBOonSxaVm0u7f11OTNh0pqFxFxTU0pqYQ+y/XWgp8MW0hi4DogxB8iE7OYGmlTi6uVKVmXTIXljgTIEsD2Q5ytzD0G5q27cRqKLUhvYvRfg0LSNTaP314j9q93V3xHmqLzVHfDmMCz5cAFOiRYREfG62iKaAJQdRpc4Pm1Ou9TixlWdD/KFOlHKXOWcLel6rqm4qCWDKgPtqYbIPCBA4QdRkarTt1ocY21nR511b2OzIYzz+OVWhzwJBS1wYK0UjMZdVqNyj2az08K+gaoM8um/PoMKcjA0PIupI6V5GdJc5s+2Tsd2z9sW/n70Yb3E8zMmj/2z0po0oN5VaBU0eTf3q8UcdVo14jtnZAWrwYuWkfbezkuHDyCIVK/v5VpYj5CDnqSM1QjnQj7dPTx9ckJ6zoDMOvJt7OdrLRM3POn0J9nXjhoOuEjdRKXdqdad0HA/8u0FO5djIxPo4mfvIBrZwzRePf5aqJcgvRh++/GEobf1ykPi0/2FMlSivgGR7C+mLnBOQZ3ORXkhkRuX7+9GVGJkVYWytFph5GJtO98ESNBu+LhDSmvAxPelx0JPX+KL/NkRioJuubUggxqA5de1D/4V/ovegVq8Dv3rWLpUK2aP+W1gU2ognawHmuHehOPjXrUOyMpZTxsg2bz7gRlBUaqrPBDaKT0liksff/PlNqFaNrKr468B1y93+Z8pVYRFMfJwYi3fg8sh96DhxGP/91lGxszZj5YqGTAdSE0SJQDjiHZvy4SW+tASiag0N7dpC7pxfVa5Kn5i+ki5oL3B9iEPEc8EYTOrx3p17fA4N63+ljVLN+E2a4lxCP3fUqk3XTZlTUgcOylAl1QgoKGGhCpF5K0ItntCwwiNps36gSqRQMLXX9l9EqrGzFKlSzQZNi9XyrA7Xd6oIOcpjbQQNHANZFHk62sjop4msOg3vJb3/TB5+MMWhbQjZLtJ09fZ6cQjXe6MKM+grVK1CFDevYXIcsr7KJL6hJBW8lTRt9mbFyk1K2lzqE7i1iMD+hTenuLb8avP3iBDe6iwkpkkg3WoaZKtJd1AbiVw1MJOLoSEEB46OCX37UWNdgKQw8GN6FdV9i++Jopau7Bw367Gs6tHs7HT/wt9q/k7OF7kUksdfR8/vssUNkq8bggfI3DAN1oD0X+mK/tmkDeZQNZJO2kI7WoGc/ev/+PXr0yZdKkSnUd2vqLyzUVkGcZ/2+s1S7UXP5fVNjrGgTIES2Q0JcDK39YbZeCsvi0rD3h46kldsPsFRgtduytVJSdtYGHBtQC4+ztaNhN68pvzfte53brkUnZzI1dfQBB1ivwWFjigV3oJpsj307t9DQbm1V6uc0GYrIckJtN8YBQeRLH3BciM6oa2dUVCJhyKCRy6LBOXFwdNJa1y095QlpWew6oDSjVacuCmcGHJwoDTEXUEMXL5ChxF6xag06slc37QkBZN7cvnqRajdspnLt4HSsXko+O8AUFORtgqhxUcTfzUE22o2+ysnOLuSXk03ek0YpDG9xZFNd/2V3T29auP5PxTXXF0t+vtWBzCFdW/YVxNEJhrfcmgzCa+Ixyq9UIBu3DelcgbXAiy++pYFPn1CdLu+Ri6MDK7FCRx6noNLMuRy0fBlbW2C79YI9mNEvrT3XlaSEeKYVpW49hAAEsoOkhD5+QJEvnlMdmfWHlWj8gSPaFMEYS4cb3cXQ6MZCAWmGaMFjLIgcmXOBwTFfex1zitkIwLMqDOL6TNiaeq4WBIgmiRc86B2JOqsZXw5TL0AomWSQ7ifUTJ84uJelfzZ/XTVi6+qgWx07JkcYhK+VdGWGI/YRhlC7t7qxGuVVp46p/M2T6GSFSJjSrubmsvRoTJRhoU9Ymqq6+8ZQJVgY3RnpqbTl56X012bd6uLFqe+pqamUlJ7NFh7atqNvJB73ZWVHK5opabMWMX48q+3WRkp6Jk0b+7lS6zFEVHSJtusC+jLLGTz+gWXo8b3bTHlbV6MbEVkIsH3c/XW9BbewCGtawZul5bes5Mv6IWtawFr6kgg183BYSbly9gT1bFGdIp6H6h7pTstkC+KJ83+k7v2HKIkymjtiJo12t3mjK108fZQ5uXTl6cO7rC1R1dp5bQulu5ynKWFc32NLwNKFv9SBe0iu3zzrYLHgZ5YibBsexgxtu9vXVcqP5NSpo8LDVPp867VPVPSAkYuMB10oKJ8CRBIxxqsT0hNnJl46fZw+7t6O7ly7pPd29kVG0MP4OOrUva/KmIS1BNYUYkc5MsbQ5gxrEn2ZN2k0zftmlNr3wxPkU8tPH9nP1h9ip7+TvTXrQtDmNT8WhW9RyYeaV/ChNq/5sq4UWB8a6hx4pYzuM2fk60w45kfsYYKAxtq/T1LHd3sb9Z3oQ9usgneRbqv1quDpZKvatqJEwS10gT5rH08nO6MnQGOcClioVS+dH+lBpHXCvJXMANz260qtadEgJCY/yvzP9k0suoAWG1LE2QC6gChX8EtDM9jLmaUcD/zsa/pz0xoV0RWkj6OmXEpsSiZlZ+fSHxtW0Sc9O8hG+bAd1MQZk+lQv1ol1o8cNePoD6srOJNd332XZn+jObUO94ghbeZgWNt99SmVzMlm9W573urOFqslwp7RI9R2azG89x48Sn9v20BpqS/rKCXZEcYCw7a0h+r31ajXmLz9/Ok/DanESCsVol+IzkK8BurvKcmJ5JaeprbeUwwWfVjcSNP24WTVtIC19PpZ9lyXcldRlq9UvTbb90N//6Hzd0HACn8DgTuxFoI5U8sFSrrDsM//vUX7ziy0dHy/+kwcKWg7hQj/a9XrsN/lLh2cUwEeps+SsvT7xFLA+Zc7VTm+JZmeR6qXDzO0fSeM0Gpwg3FDetMyA8Qti3KkO995rD04VBCBCF3mTbGuTK2GTdn4oq40TRNWJayoQ5f3KDC4vM7dNJgIXRkPlg2ma4YAgPP/9rVL9OjeLZX1EFqThsTKZ92dPXKA6jRurmhfXNbHiZpV8GGZABivEYXHfmD9inEDBjfmpkZlvZh2RnHDpEb3e++9Z8qv4+gRNcLi25R4udixGjk+eRahFPNCGqAQlcWEp8+9ggHW2F6bxq4PEOmBAqrwPehtPH35ehr17Rytf4tUKizKQUJcLN28coHe7NlP1rBFZMzQ6A3SmRGRf7vXAFq8cTf5BahGhZ/EpLCWgdLUcqSXot0V2qIJE54YfLexUaJATydW6wWF78N6GDThERF06OBBljar7Rqp64GqDrFKuVXpQFoWXInmb91A4d/OY4vW7NDQvPc1GN5/7NhOXr4lmcElLI6NreWWAiNeGu2GwxRRTbSxw/WTAoMa9ZxiZdqopHS6dPoYta3bWGO9pwDud6Q/qss20ZT9UBSCinAcSKNMqJ9s2rYjHd7zh06RbjixM7NyaOn3E+jkoX+VnBWGPM/6Ake3+BpAn6Vuk1b0TA+1cWTu7Dx9V9HqTp1BhcwafVWgtVEEbhOLAMaGuvvp4NmT9L/LF3Tuvyyk/xojpFhEbW6G2JBVi4Ucn1hXBkKu/Yd/yVqIod2oPkDc8euX4pv6jM0YX5DmXjXAVedrjvEEJatoYQjEiUGRienMyS+XcRdYrgJbg7B9tELmmm41+FibYJ6CWKJNUWtRoAG9j6RXr16yPzC4Y2J0T33imI4MyYL7yrmT1KtVTYoIe2bQ9+H+NqTOk1P4NWKFNb9AkdtazxnbWAEcUxwf0r7FKX7wOMP4Rg2SFGGSgZPrbni+eribhyet/uuIrBiYNE1UXzDxoB4cRjMMQDg2pEJbmOyQZi4AAxziboh+4jje7N5X1tstV5KgL1is16pRjRq3bk9b167QWQRs+7a8xUXLjm9r/Jy3AQZO+r17zKCGkEz5DevofxMnMpGyWBtbhbIr3sfn5ICxu2/Pn6ynqNB2xxTnStfWQW3e7MqEMNECTArqOFHPKW4J8yIsjDKePqLPw55qrPcU10BqK3eoG+Qhm/pqCZEiXQjygkNJ+bW2b3Wnh3dvKiI1UsS3LlL2kaq/a/NaJkIofp4LKp1Zqnvx/YoNrO2OrqDMDK16BNTtNZxJ6HssqJtzChZ1mQbNa9SmWQGldO6/LJSkCI5CXXBztFVqc1WUjW44qaCHoAlLOT6MIYg0C/vTrnM3ZtSi1a+uc+i544fp2ZN8J5whATLMr1V0zHaDpgXS2OEYyEhP0yqgJuzTqMlzWDQeeDnb6+1ER+aVruUDRQG9k+YPHDhA69evJxcX5ZOAG+Xo0aOm3DeOgUY3Wh9h0QbvviHgwTC155tTMBFn1AALfRILMksBEUl7PQdTHxc7tjDWUTNKBVMdX1lvZ1afLezHvZtX6bO+b9HSzXupYtWais8JU+H9yCSKTc5QRBfsHBwoIDBY1rA1ReomFhNYGD2PTqAvBnajd3oPVCkdeRyVwp5bGFNhcWlMWAsp7+Veq0qv1chLLxUDI9JUkVsYjh+NmsAmYl2vye+/b6GGzVuTh5ePxs95qVF71wQTpVu+jPXhRl1bl4AAKvPaNoqCNx6R4WmLqGT0M6V6NzGHj59izgrBIYB71Fy6FigfeBabqmTwVa5ZlzbuPy9b644oF/ZfqO/Ev5caNKO1QWXINTFea/op7qPyvi46LQoRAUUUXanvqoUsWnWJ5KAsAedWoGGLtuTh5U13rl+mcpWqaox0Q0Tt6vnTzHCt26Qlew23tro6TXMgtB4SgAENh1BSQhwTzNIExqV+7evTN/N/pEYtX9eaOoyMHKj+ozWVKbAU46Yo4PPSEEFrMAEY1mVmT2KGzgsqQdYzljCDW3jm5Z7xm1fOk5uHF5UOLq9xe9hW7UAP9q+DbV5KLzI7bjxPUMmYKmq85ufKWmqqw5JuS8zVmDuFMeq9QZ/QlfOnKCszU6OwKEDdPuqrW3ToTJ9NnMleM9QXCEciMvdCY7S3JHz97R704PZ1io+NodygvLkbaw2UOMmBtZSPX4Cik5K/JDD0KqL3qqtNmzbk6upKrVu3VvrB67Vq1TLPXnI0Ih6shRZIVtbWrBbUEEqZocaLUzAUROqjOvSpDxJUnL2dC79mB/stVhrFgtzN3ZP+/WOz0ucQTb4VlkBPRYrhSD8d0fsNWe80Fs2mMmwxMSICb2/vQAd3b5f9zOWQWLocEkePo5PZ/ji7uVOXvh+qGMI4XlN6jjGRVq5eg6rUyhNs0gbEnW7evEktO3XV+DlE3twcDRNTEUTpFPvoasvExqIiXrDFaliVupScLi845OYXSCMnzWL11QAGt671cvoC56b0mWWlIqUCmcEnp2IuGN5CL9Y392yjMnZ2Wg1u3AavlXTRuw9uUUsvF0f0xbc+FrIb9p+nN7qpZn6AHNEjjEUoUvZLlgpk4nYA10nfMc4YUGsvVZSf9Gl/Wvjtl1r/Fo4FPGdiZ6C2CD2ctuI+wsZQVDIiLAFcF3HGi1ilPMHFjfo9vE+xpQOVnnlxeYlA+PNQRTaUJiDkhYgwxh7hs7ivkd0CB3RRBscldVaJsbRyyfK+zgrF7hr1G1O/jz/XanCD//75k2KiIujNHvklbcbMUZVLujINJ228Fh9Ls6YtJF//Uoo1T0RinpNfrn/87HEjaM0PeU4BOHn8CllA1xLQeUWYmJjI/t2xYwe1UhMh2L9/v+n2jGOw0Y0aU1c3d4MGGKgaFkb7KY5pEA9qljW9yGNMHbopjw9tNgQQXUA6VMq+XZT59LFSCpXglcYEk35wL6tj7vxef9lnzZTPEbICsABv36UnMwbkVJhhnyGai/EA+/PFdwtYLbgY1Ec1Lu9l0vpkLBpLeziwtiej+r1D8bHRGj+PDJw9p65Tm7fy6rw0HbOpFkmOJbJoxlfDaO+2jex3rBfuhufNaWKwkEi3caZ3+gxitXZ5+2HehYLcQhfZSv07NqTzJw7L/g0Ma9R36lrvCRD51Vd9HemH4mfU0hat+tbL2js4skhSbFR+yriA2HEGvYZLZ45RncYtFMdckFFuseCkmKq16rPyMbl6f2mqsaubhyLqqetlgzOuGJVPFhlQ4ytcI6H/Mgzsx19PJYfgcmSdEqvkbMP7+JyYr2f8QJMXrta4Hcwh6qKNGMfNUUZT0KDbhTpKWGBGTpCojAcZKqvmfUehTx6q/RsIlv66dA41bdtJSRPFGBE8jHHQcIITQO2+vtQT8Z44iq7//QdlZWWxzIj7EUmy/eOhpA+NgfpNW4k6dpSgVx2dh9eWLVvSixcvzLs3HBNFumNZmpEh6Ku0zLEssEgT2lEUhfVxXvsdw/7WlMfn5mCrFOXpV6suzfX0JNevP1aJKAgTTPCy2dTGzZ3av9NT5fvgdTZlWzRMihAtQ79gdy9v+nnRDLWfRVshiJ1Ie2ejRheLalMLggkGnZevH925fon1NVanuA3DBk7BpMwSLHIP5DzkcgaHMbi7u1Pnbj3onx2bFAYLnChCL3OB7bv+pQVTxyspsZvbCYnojFS4DOnDNja2dPrwPtm/wTlDuqmu9Z4wpDQtqDSBaDdavIAiMKQoIWcof/NJP1o+S1XhWTC5UzOyKT0zmz4cOU7htGLCj1rqRc2B9L6ACjAW5g/v3ND4d7euXqAqteoqNAl0XZAz9XrfvG4UxlAU5h5LcxAJ8w/6L0ePn8EMbO8adWnXkbPUrnlenbZgeON9fE7qMNIWJUVEvSg5zgwBjkJhvJJiiYeOeV3YL5SQHDuwh5ZMH6/28wd3b6MXoU/pw1HjTH5sKD2qW8ZD9vwJeiK2EWFUdflc2r91O51+GE1ZYS9k+8dfOHmE3WtCeQ7PoM1D59VX3bp1qXHjxnT79m2l1y9fvkxvvaUqIMQpOKR1ON0+GELj5yxX+3koTWMBhkW4+EHF/GzKhS6n4IEnsShdQxiAhtbLmjqFUWyUuNZrTMnOLuSdka6UyidO/XuWkUGthn8pW8aBWm5TpyQjGuLi6kKDR39Dl8+eUNuz97+9f9IP08dRWlqKSYwunducBQaw+tH9f/6uVnH7yYnD1Lt1LUX/azkPuYCp66iHfzyMiUtCYE4A5QJIJQaoa9y05XfWVxTZDsJYWRD6FhD+EoPFSuPWHej0kQMqpQviezDe2ZU+CA2hLD9/tWmnglPE0NRolIE0CPZiokuWuGjVVjeJe1MM+sWe/m+/ilMKAokgPjWvPzeEjYSSCaSsFoaxItU0qFKzHovWXz5zXO3f4H5Bz9+qtevnv1hCv6wfOYE/fShit4lFgCwk4RaDQS1krUC5OTYynD1/AK+LDW7w99YNNOitZhp7dCOLsVwRTx83qZK5BWbkQDAV8/vFk0dYiYgcyHYZPn6aii6Fqdq9wWmBmn9pL29xpgXKmWpD9O3aVbX94y+eOkoVq9VkDmT03Oath/U0un/55RcaNGgQtWjRgo4fP053795lquX169dXpOFxLENIzS+gNFWqpr6+HoJL8GhBFVkc3UNNl7lqFzkFh1DTVFTq6kxVR2gsWJwLkTFMHGmLflGqobO7fV0xwaR6etOOFu2peb/BKt+DuU9TipsxDgpMzh279qa1f59Um80CoxeiUZ7eeeIlgtFl7kkPToE3ur9Pd29cYV5uOcXtKktnU0Vvbyr3WjUl41GquI1sDamxZCxtWzalilWr0+4t6/L3LTuXzj6KoYeRSXTpSQwdP7SPGrZopzCwCureRDRdWFQLNGnTgSJfPGNp+wLic4Z7c6a7F9nXqkVVtmyi3IDSsoY3DsXYWk1EehEBsTNDloS5EZeOgPZv96CMjHTauz2v1EBa0w2j+5fFs5QM28LSnoDDR+wsQSSzVoMm9PTRfbV/g3t39V9HWYmEoQty9NI1Ks28aEw9FgX6FctlR6GTQmBgINlnqZbDiEXUULYjVquX6mOg9/Grkt6LNHmp0WjJayKxk6tF+85Uqkw52rwqrxWYlOCKlendfv9Ted2Ua3fMvY3KeVGN0u5KY4FgeMfYO7CAhKb+8bgXm7d7k/1/UQoEmRu9htWpU6fSmDFjqEOHDlSjRg1W533q1CnatWuX+faQo5VMSX+8LT8vpSP//qX2886iyA0W8cIDVdRFNDh5CF7TohKVQs2oQftqhuND+rUQ2cQE8mLyXBZNxMQiTDAZvv4UP3sFvTfuO7UpofrWzuoK6vGQMgqPOKK2UAcVc/3CGbp97RK91bO/0mQMUSlzg31r1zEvOvjbT4tZ7ax4ok7z9mUT9ZpSpcnx3i21HnLBAWhqYIyM/GIs1W/WWul1BJIfRibT/n/2MiO3Y9de7HWMiwXpEILImfg5qFm/CVtIXzyd3xVEXO8ZNmkOHTh7gmWaQTSu3PpfKdtftd4T/cBNEa2H0wdR76JGgJuDUrokROrQomfbryuVygiEjIKHT0Pot1WL6cXzEMV7yHgoLKTt3SYv+pnpNWgCXQHEnQH0XY9j/Krk58ocFh5OtoqSJY55gXNUSoNGeVHt2xfPqHWE3Lx8Xm2rMPxNrdLuBSoCaAnIiYVa6prI2zm/LBBBTAiqnTj4Nz19mN/WEo7CmV8Pp9P/yZccmdqfgvkSzgu0g21YNi/TCWCevtfnQ616ItAY6DdsNPt/QwVRiyM6z6Dh4eE0atQomj59OlWrVo1sbW1Z5LtRo0bm3UOO3unl+3ZuoVuX83o2yuEkiiBhQkUqSc1Ad629WzlFA0yuqBO10PlFBURgDenHbI4JFAYq1F1hpGCxkunlTUslo+TkmBjKEkWR5VrAmNOhIkzOM776hH5b9YOKwy24wmssSio2ugpiwYVJupK/G837ZTvN/WW7IkUbYEL+6bXqFJqVRR4pyRo95MDDTC26BvTtQ13f/4gZWFKD65fFM6hWw6asZZcQfTZH/bs64GhAfZ84qvnTzsPUc+AwxWvies9Ljx8wheouXbqw9xwDS1PZ9b9SyuRZivRTGIsVdGgRVpxBdK96AIRF81/r9dGnLO0RreEEYHJDhXfvrp1kbS2K0jjbFWpqJAQFxTg45t0j4vtXzPrl81Q0HwyJ8CHrB23jGpT1ouYVffIyHV62hcSYgghYrSB32b67lhpRtHQEwUwxgaVLU+XKlenQoYPk7qi6RoNwZejjB1SttrzRjTFFqg3wKoA1RVHRKMIYJRZ97NC1Fy3fup/KlK+kcAYu+vZLOrZvN9m+1EKRYs7yF1cHW6of7MkMb2RR1f9np0Y9kZBH95V6eUMzh5OHziuKcuXKsT7cW7dupQsXLtD27dtp6NChNHfuXF2/gmMmMqXq5fGx5OruIftZGGNIYxLAYhyDk6Wk+HJMQ8kipkBfygDVVHNNMTC2Gpfzosr+blTBJpOmeLgrvf+NkyPZRKuqHwv4uNqZdXJGGjeAYX18/x6aM2EkJSflpR6+03cQDRo5TiGghBS7gsxgwTji7ZEnxHTj0jmlutnI3Fz6q2otnRS3zdUXGx53pFr+OGcKLZvxjdKCBRHE0VPnKxYvhaHki7p7cVSxZKkgtj9itWqh3hMZBd8vXUs1a+b3kncJCqRaPd5imgIwiuoEeRZ74SRdwLwndj6gHnLFtv1UqkxZpT7dcSkZ9N/eXVSvWSvFHFrYAkCYn6URzvFD+9KymapicODY/j0UHxNt0igYnE/YD0S8qpVyo0olXVkEDGNlg7J5i3GsJZxeZlTwW84w8KwGezmrOILfeOMN2rt3L3nJiPlBqR5Uq6vO6DauPr8ogwwvBJQw5lv6fSkuLcB9ICiTL576NfVpW4f2/7WVRk6epZKpZeqabo0tJG1SyGcyMtTCmMM8csZSlTZ2cBJ8O/JDhRgczr2pS8VeCaN7zZo1dOnSJercuTP7HYPA4cOHaeHChfTpp5+acx85etR044ZHn243D0+Vz8EjDQ81p/jD2vxY8AQjBV5eYWK0BJBG65caR9ZjhlNmSCjZBgVR/JzlbIJxTYxXK1iFRae5UsulKYjdPvgfde03mNVwj3q/M3v2IWTWon2esCXm4CoBbgVex1cnyINiI8NozICu9O/O3xSvf/rRpzQ0IU6r4jb2W1rfbCqwmEE0Cb2X92xdT7+vWUYnDu6l6MhwCipXkQJftljCvYiUv4IGxk2wyEmCa/rVRz1p048LVT7r7OJKbd7orGJUY5yvXsqdGUVco0NZqErci1YQHBPa7yGgdPbydbp+8Qy16vgOew09dAu7hSauoTTCGRAUzFoHSoGy+eN7t6lGPUkGoomGAGQASUXWMN6h/rNFJR9qVtGHZQoVoanH4oCRLDgvhOv/5ptvUmpqKmUlqYpnNmz5OsuIgYNO7nqZez6ydOAIrlna3eIzMLAGkmY5YIzCvNS4VXsaPWUederWV+3fW5vZ6M4MC6MXH31ENi+eM/0QZFvdsbKmE70GKhne4ZfOUsjDe9T89bxMocKYRy0ZnVe5ffr0UXmtXr16dPLkSTp06JCp94ujI3gokRIngHRDKFhKI90YfJEiVtgLCE7BgKhDURKvgGGob7TbnBE8TDBPBgykzJAQZnAHr/uV7OvUUah3qlOKLog0PniNEcGGivGn46fT0s17qW7TVmzBLYDIGCJS5ooYa7v3mtepQq+/05N++WE27dq8lvaumK9Uwy3nIRdAJo45jUWMgRCZqt+sDa2aP42mjPyQNq5QrpEtyXQGCmeBBhE+4T5idXWBZejfPzZTDhqxv+TJ/TusvCA+OqpQ9rGoUrmkK4t6g8zMDPrny49p7cTRLJMA86iNuz+N+GYGtX3rXXZP+t64YBGOC+nCFW14nj99pHAYiAW1sCaoXrdRgUbBxMBpVJTmHkucC+EsVbSRsipB7du3Zy17K5Uro1IqhBpgZG7IjVfSPvWvKiidRKmEJUe6cZ2RSSII4QJc0x4DP6bRU+fRW+99oHFOMvexpd+7x9ZFWA9V2LCOSpQsST8v+p7mLplDkd8tVPSPD9m3m+zsHahO4xbs73jZqjJGh5bKli3LDG9O4ZCVk8s89Apyc6nHgI+ZwqHUe2oJiwdOwQFhq6KEvm1qShTQBAODG0JVWMCI22ZIBauAuSK0UsSpz6hBhvEtdrTVLO0hK8pTUJT2cKRJM+ZS6TLl6PeZE+mdg3uUargzqtRQ68AQLzrMZcDY2drQrFWbadPBizR3zTb69BvlGlhxbXVBg3G6Rmk3Vo+NqPUb3fpS+PNQpcjmiUP/MEEdDw/5MiKOPFi01ijlnqdufP0yzXJ1oS8jn9Fv08ZSyONHVMLahrr0/ZAcExPy7slJX1PS0Xwhu8IC+yteVNdu2IysrK3p3PHDSp+7duEMeXj7KKXNF7TRzbbH1xpGAUMFhjewsSrBDGv8JCcnK42PCLB8Oai72hZyKDPhiNbAlmx1v3RYI0vJkLW6uZ85l1atKGj5srwAROlSLB0eKuoP79yg8w/usvk84suptPjgXtZuUdCe4A44ZUySz+npqZrKzCkY0PJGDHoGDxs7VamHH1JWggpxEckpHCCSV5RABFcfg8uc86d4goHBLa65EgxvCFpJ+6XKtSkxl4MCqa9yoIRErvVMQdOyWhnaf+AArV+whPxKlFASTUPtsjoHhrnbM2FxImhY+PqXYh55cdtLGLti3YvCAMJd9YO9WOSjdoNGTFDn720b2HuIyh755y8WqXdy5ItqfUHWF1rh+NeuRrl+/hRka0d9z5+k8V1bMRFScVs221IBZF+pEhU2gvaKAMrHatZrTFfOKQc83u7Vn76cvkglImbhtgZHjeMS2UpCx4Bt27aRj48P2WTlC1ShewXuARsb1bkeYxwXsFIe94uCMwiOVkPm74JwKGBdJKyHoJHRqGUbqlq7Pi2a8iUlODjSs6Bg8vTxo37DPlfYHqbonFGcsJwiSo5BZIpSDkFcTBTdvHJB0a5HMGaKwmDDMS1FUUAJveN1NbzNXZ8lnmCEha9gVMNglBrcMIJdC8hYQ+2vXC9wpNBB5MhSCA7wpfafDaOcaXMVBjcm4fK+LuTjaq/iwGBlEQWQog+RMXX4F2KGgBScq6YVvOm9/h/R86ePWWQL6tSP792i7gOG8OwlI6hUsyKV37COtVkrY2dHf9VtQJ0qVFIY3FSqtJLTzRKMMDETF/xE42YvU3oNdb2o/5TCp/+iCZyrggOwfv36lJaWRudPHVG8D3Etr5eiilIswfHKMUKTR08K+hnHXI1SrXGzljHhxp0bf2bjz5Lf/qayFauwz/Aotyrc6C5mke6Lp44xUSX09BNwKMR2JxyOvgM5hLgKKk3blCnwmGAK0tEBo1usdI2JGn11LZEqXTtRxRoVmKEtOFUq+bkwwTKxA6Og0iEhLiTU9opBLbyfhS1WEfWeOHo4zV/5C6WmJNPuLb/SgBFfsz7evGTIOJxetlmzKh1ITnExVOrbMXllEP6lKOjXtRZjcAMIAIrbc6EPN7oUJCcmsN93bfmV1i+fX2wcsBzVDkJVqlSh/f/sZeN+WmoKHdy9nTp266PUnlGA90YuuqDtKNYauqp+I6JsSNtVYwlwd2ClLIs37abKNeoU+WzLgoAb3UWcLEmP7oS4GLK1tSNHp3wFXAeJIiKHY8lggVgr0J1ctKRqF8Y6EtEmdT2vC1qlE9Fu1B7DUMT5qhVoufW9SJFE3184VKr459UqYkFRxV85Kl+qAKPMcg4UpLYXZG9uXfFwd6MurepT8+rBtP/YWRo26gtFvSfHONBmLWjuHOXXpkxnr1sSecr7ygvrPzetoffb16fdv6+jX5fMpoiwUPm/LaB95JiX/v3704YNGyjm2SOm6ZCSlEhvdn9f5XNwZr7qquVFGWSmorSgXrAHm6fExivWH9K1DzLHCsMBC0Mf2ViIbDdo3kb1fTOXihVFLG91wdGLTJFyuWB0u3oo92a1V2MkcDiWCiaW2oEeSq1TLGUyrCwxFAXMLQCmLtrdpLw3+RUx0Txx3aEgCoeFRUHWfwW4OZCTvfL25FL2LQmkjDasXoHqBXuxFHlLzQgpSkAw8fnYsUqvZX//LXvd0pAqAbd9qxuVrViZ9fJ1dHahQSPHyf5dQQupcczDmDFjqGLFivTgxmVq/UZXmv/rHyqiecCLq8cXC5DlBOO7QVkvpkOBiDY0W2oHeSiCElgrYS4rLNDpQw7MrbyeWxXuCiviZEvSyxPiYlV6dDtYUP9jDkdXMGBXL+1O5x/HsLTKjKwcptSP1DqUVRTWOhKGD6K0yelZitcwGRZGZAHnxa6I+05Rh56QmlngtehwoCDyfj8iiSIS0lkkviDqyU0BovHow80xXWtA68BAovFTyGrWVPY7Xrekmm5B5A/jntCxBHP94o27mbPd0cmFbO1U718sznVNU+VYNg4ODnTlyhVKzMili09iWYmJHF6F4ADmmBc4p+GYtrexYkE1D0dbuhuexF4vTM0mOM4fR6XItg7kqMJH4mImpGZlZU3+pcuopBpxOEUR9Jlu9Zovi9TEp2ZSYlomi0ZisinsiJPY6C6MftjFBTgOmlX0KZRtw1GCtHw4dMT1spxXy+BGa8AyL2u4s6r9qnjd0gxvRL7g9IOTSIybhxf7F06j+NQMEpYFmPvrlvHgke5ihK2tLblb5zmdldrFWrAuBcc0iEvbULKFKHhh4+pgy/RR4lPyxZtxb/J7UB5udBczIbXh46epfMbOAmsUORxdEWpsYegK6ZXqUrwLCk8nWwqJEf/OIwtFGW5wv3qk37vHDG8Y3GLDGv/id2Z4h4Wxz1mK0Q3gJLr5PIGex6WyKDZiXIhko7MCWoNGJ2fQtWdxzPCu4OvMDHVO8QL1u1A1T0zLd/wKQOfDEnUpOMUXpLxfTYlX/I57k9+D8nCju4iDCI02+M3P4ZgWaS0tb8/C4RQt0BIwaPky1odbalQLhjcMbnzO0kCfewikQkBJCsYi1H+iZAMGGKd4guiinNENRWkOpyBB6zBn+2RF9l9hKKkXFbg7rIiTIVEv/7RXJ9r+649KqUa8rQyHY/o0LyHVC6261CmaczgcywUGtbooNl63RIMbYLyRM7jFi2Be81+8cXNQLWmC3onQ15vDKUgg7Club8gpwkb348ePafDgwaxPoaOjI1WoUIG+/fZbysjIUPrc1atXqWXLlkxsIigoiObMUW4D8ipEukMe3adcUaEPj3JzOOYBESU4tCAExuFwOBxOQSGnIwJRLd6TnVMY+Ls5UKWSLqzUxYOX26mlSLjEbt++TTk5OfTjjz+ydgnXr1+nIUOGUHJyMs2bN499JiEhgTp27Ejt27enlStX0rVr1+ijjz4iDw8PGjp0KBVXMkWR7syMDEpNSVZSL+dGN4djvjomtMvgUW4Oh8PhFCRop2ltXUKpg01ZrhjNKSTg7IFiuaW33SxsioTR/cYbb7AfgfLly9OdO3doxYoVCqN748aNLPK9Zs0asrOzo+rVq9Ply5dpwYIFr4zRnRAfy/7lRjeHU7Ap5hwOh8PhFKSR42pvQ3EvVaOhM8LnI05hwzMtikF6uRzx8fHk5ZXXJgOcOnWKWrVqxQxugU6dOjHjPDY2zxiVIz09nUXJxT9FBaFvsQB6dYrbhwBb68Lr38fhcDgcDofzf/bOAzqqqovCh3RIA0LovQiCooCCIiAggtgRVJoCIkURpKiA/lIERSkiYgELqIiIFQuKFFFBqvTeew3pJKTzr33DG95MZiYzk+nsb61ZyfQ3r9x7T9uHOB+0iNOIYR0tIV6PTxrdBw8elJkzZ8qAAQMMj509e1bKlStn9DrtPp6zxKRJkyQ6OtpwQy24r5Bj0qO7fMWqMu3zH6V6nXqGx4KgpEYIIYQQQvyGMldUopFmXpp1tIR4PR61yEaNGqVSEazdUM+t59SpUyrV/NFHH1V13UVl9OjRKmqu3U6cOCG+Qk6ecY/u4uHh0vCW26VE+FVVU0a6CSGEEEL8T0wtNDhAGlaKNop6E0K8E4/WdI8YMUJ69+5t9TWo39Y4ffq0tGnTRpo3by4fffSR0evKly8v586dM3pMu4/nLBEaGqpuvoheQAPs2LRONq5eKU89P9rwWFAgI92EEEIIIf5GvfJR7ItMiI/gUaM7NjZW3WwBEW4Y3E2aNJG5c+dKgEna9O233y6vvPKKZGdnS3BwfiuFZcuWSd26daVUqatq3v6EaaR75+YNsvibecZGdwBrugkhhBBC/LF1JSHEN/CJMCgM7tatW0vVqlWVWnlcXJyq09bXanfv3l2JqKGf965du2ThwoUyY8YMGT58uPgreXoVtStCatGlroqogSAKqRFCCCGEEEKIx/CJlmGIWEM8DbfKlSsbPXf5iuEJEbSlS5fKoEGDVDS8TJkyMmbMGL9uF2Ya6U5OTJDIaOOoPoXUCCGEEEIIIcRz+ITRjbrvwmq/QcOGDWXVqlVyrWBa052alGjUoxtQSI0QQgghhBBCPIdPGN3EtpZhTe5oLaFhxY0eo5AaIYQQQgghhHgOGt0+TK5JevnDPfoWeE0I1csJIYQQQgghxGP4hJAasa2me+/2zUpMTQMC7yFBPMSEEEIIIYQQ4ilokflJpDs3J0cGd7tX/l2xxPBYSGCgh7aMEEIIIYQQQgig0e0nRjeUy0HJ0mUMj4UG8/ASQgghhBBCiCehVebD5Or6dCclXFB/S8bojG6mlhNCCCGEEEKIR6HR7cPk5ZkxukvHGB5jPTchhBBCCCGEeBYa3X6SXp5x6ZJEREVLyVJXI91ULieEEEIIIYQQz8KWYX6SXt68bQf5ce0+o+cZ6SaEEEIIIYQQz8JItw+Tl2f9eUa6CSGEEEIIIcSz0Oj2k0j3rLfGysQR/Y2eZ6SbEEIIIYQQQjwL08t9mDyd0X3q+BER3X1Ao5sQQgghhBBCPAsj3X6kXq5vFwaCA3l4CSGEEEIIIcST0CrzYYNbH9hWRnfpq0Z3sWI0ugkhhBBCCCHE09Do9oN6bpCcEG9kdDPKTQghhBBCCCGehzXdftCj+/Lly/LGrK+kbIVKhsdodBNCCCGEEEKI56HR7QciasWKFZMbmjQzej4kqJgHtooQQgghhBBCiB6ml/tBpHv/rm3y8bQJkplxyfAYI92EEEIIIYQQ4nlodPsoOptbdm/dKD/O+1iCQ0INj9HoJoQQQgghhBDPQ6PbD9qFnT15QspWrCwBAVcPJ3t0E0IIIYQQQojnodHtB+rlxw7tlyrVaxk9Hx7Ccn1CCCGEEEII8TQ0uv0g0n14/26pWbeB0fMlQgM9sFWEEEIIIYQQQvQwHOqjaDZ3bm6udHyku9xyR2uj50sE0+gmhBBCCCGEEE9Do9vH08sDAwOl95CRBaLcQYFMYiCEEEIIIYQQT0PLzMfTy//+42c5fviA0XNlIq6qmBNCCCGEEEII8Rw0un24T3dWVqa8/epwWbX0V8Pj0SWC5bpykR7dNkIIIYQQQggh+dDo9lHyLl+WP35YIOlpF6X5XfcYHi/OWm5CCCGEEEII8RpodPsoySnJ8uk7b8i9XXpKjTrXGx4Po9FNCCGEEEIIIV4DjW4f5feff5JLaRfliWdHGD1ePISq5YQQQgghhBDiLdDo9lFuaHSLDHn1LSlTroLR42FBPKSEEEIIIYQQ4i2wZZiPUrNOXSlRtlqBxxnpJoQQQgghhBDvgWFRH+Ty5cvyxccfFGgVBsKCmF5OCCGEEEIIId4CjW4fJDU1VaaMf1kO79tl9HhwUIAEBBTz2HYRQgghhBBCCDGGRrcPcvr0afU3pmx5o8dZz00IIYQQQggh3gWNbh/h4j//SPaZM8ZGd2y+0R144byEbl7PdmGEEEIIIYQQ4mVQSM1HDO4Tzw6S4AoVpNoXnxuM7tKxZZXBXebVoRJ44ZxI+FSRKvd4enMJIYQQQgghhFyBkW4fILROHWVwZ584Icee7CVlAwKkzT33S3jaRWVwB507Lbllyklw7dqe3lRCCCGEEEIIITpodPsAWoQ7uEoVZXjXnPuZTBn8gsHgzilXUS5MeEfCKlX09KYSQgghhBBCCNFBo9tHDe8SwwcaGdy5ZcpKSBAPJyGEEEIIIYR4Ez5npWVmZsrNN98sxYoVk61btxo9t337dmnZsqWEhYVJlSpVZPLkyeJvhnfFt94yeizx+ZeVwQ1CaXQTQgghhBBCiFfhc0b3Sy+9JBUrFkyjTklJkfbt20u1atVk06ZNMmXKFBk3bpx89NFH4i9Avfz0yJFGj5Wa8YYSUwOMdBNCCCGEEEKId+FTRvfvv/8uS5culalTpxZ4bv78+ZKVlSVz5syRBg0aSNeuXWXIkCHy9ttvi78Y3BBRQ2o5Uswvv/uxSi1Hinm+evl5CQsK9PRmEkIIIYQQQgjxRaP73Llz0q9fP5k3b56UKFGiwPNr166VVq1aSUhIiOGxDh06yL59+yQxMVH8yeBGbXfFFk0lZdIMg+EdO2ao5J476+lNJYQQQgghhBDia0b35cuXpXfv3jJw4EC55ZZbzL7m7NmzUq5cOaPHtPt4zlqNOFLT9TdvI/PAAWV4awY3arujwoIlqmoVJaIGwzsg7px6HSGEEEIIIYQQ78GjRveoUaOUIJq12969e2XmzJmSmpoqo0ePdvo2TJo0SaKjow03CLB5GxGtWkmVD943GNwgIKCYFA8JVCJqyvB+bYp6HSGEEEIIIYQQ76HYZYSRPURcXJzEx8dbfU3NmjXlsccek19++UUZ4Rq5ubkSGBgoPXr0kM8//1yefPJJFaVetGiR4TUrV66Utm3bSkJCgpQqVcpipBs3DXwGDO/k5GSJiooSb+ZM8iXZdSo/Ml+xZHGpX9G7t5cQQgghhBBC/AXYjgjcFmY7BokHiY2NVbfCePfdd2XixImG+6dPn1b12gsXLpRmzZqpx26//XZ55ZVXJDs7W4KDg9Vjy5Ytk7p161o0uEFoaKi6+SIlgq8evpCgqw4JQgghhBBCCCHegUeNblupWrWq0f2IiAj1t1atWlK5cmX1f/fu3WX8+PHSt29fGTlypOzcuVNmzJgh06dPF3+lROhVtfKgAJ8ozyeEEEIIIYSQawqfMLptAWF9tBMbNGiQNGnSRMqUKSNjxoyR/v37i78SHBig6rovZeVKcBCNbkIIIYQQQgjxNnzS6K5evbpSNDelYcOGsmrVKrmWgIq5MroDmV5OCCGEEEIIId4Gw6M+TkRYvt8kJJCHkhBCCCGEEEK8DVpqPk54SH5ddxCNbkIIIYQQQgjxOmh0+zjhofmRbqaXE0IIIYQQQoj3QaPbxykeHCghQQESGnRVyZwQQgghhBBCiHdAo9vHCQgoJuWjwzy9GYQQQgghhBBCzECj2w+oQKObEEIIIYQQQrwSGt1+QGRYsKc3gRBCCCGEEEKIGWh0E0IIIYQQQgghLoJGNyGEEEIIIYQQ4iJodBNCCCGEEEIIIS6CRjchhBBCCCGEEOIiaHQTQgghhBBCCCEugkY3IYQQQgghhBDiImh0E0IIIYQQQgghLiLIVR/sq1y+fFn9TUlJ8fSmEEIIIYQQQgjxUjSbUbMhLUGj24TU1FT1t0qVKq46NoQQQgghhBBC/MiGjI6Otvh8scuFmeXXGHl5eXL69GmJjIyUYsWKibd6VOAUOHHihERFRXl6c4gd8Nj5JjxuvguPnW/C4+a78Nj5JjxuvguPnWeBKQ2Du2LFihIQYLlym5FuE7CzKleuLL4ADG4a3b4Jj51vwuPmu/DY+SY8br4Lj51vwuPmu/DYeQ5rEW4NCqkRQgghhBBCCCEugkY3IYQQQgghhBDiImh0+yChoaEyduxY9Zf4Fjx2vgmPm+/CY+eb8Lj5Ljx2vgmPm+/CY+cbUEiNEEIIIYQQQghxEYx0E0IIIYQQQgghLoJGNyGEEEIIIYQQ4iJodBNCCCGEEEIIIS6CRjchhBBCCCGEEOIiaHQTQgghhBBCCCEugkY3IYQQQgghhBDiImh0E0IIIYQQQgghLoJGNyGEEEIIIYQQ4iJodBNCCCGEEEIIIS6CRjchhBBCCCGEEOIiaHQTQgghhBBCCCEuIshVH+yr5OXlyenTpyUyMlKKFSvm6c0hhBBCCCGEEOKFXL58WVJTU6VixYoSEGA5nk2j2wQY3FWqVHH18SGEEEIIIYQQ4gecOHFCKleubPF5Gt0mIMKt7bioqCjXHh1CCCGEEEIIIT5JSkqKCthqNqQlaHSboKWUw+Cm0U0IIYQQQgghxBqFlSVTSI0QQgghhBBCCHERNLoJIYQQQgghhBAXwfRyQgghhBBCiFeTm5sr2dnZnt4Mco0SHBwsgYGBDr+fRjchhBBCCCHEa7l48aKcPHlStWcixFM121Anj4iIcOj9NLoJIYQQQgghXhvhhsFdokQJiY2NLVSwihBnA2dPXFycOg/r1KnjUMSbRjchhBBCCCHEK0FKOYweGNzFixf39OaQa5TY2Fg5evSoOh8dMboppOaHnExMl4uZOZ7eDEIIIYQQQpwCI9zEl88/Gt1+SFxqppxJuuTpzSCEEEIIIcTvWLJkidxyyy3SsGFDue2222Tbtm2G51q3bi01atSQm2++Wd2mT59ueG7AgAFy4403Stu2bSU5OVk9hih+x44d5dChQ1a/c+HCheo769atK02aNJEHHnhAduzYoZ6rXr26bN261ez70tPT1ftSU1PV/XvvvVf27dtX6G9ctGiRrFu3Tjxh3CYlJRX6unHjxklGRobh/pgxY2T+/PlF+u733ntP3njjDXEFTC/3Q9KzciUzJ0/qeHpDCCGEEEIIcTLLd59zyT5tV79coa9JTEyUHj16yD///CMNGjSQVatWqfs7d+40vAaG9sMPP2z0Pjx/4MABZSi/9tprMm/ePHnuuefkk08+kTZt2kitWrUsfufcuXNl0qRJyhCuX7++emzTpk1y+vRpZcQXZkg+9NBDEhkZqe7/9ttvYgv4LjgN4FRwpA6/KErftjB+/HgZOnSohIWFqfvYp0Wlf//+cv3118ugQYMkOjpanAkj3X5GXt5lycjOlYsZOZKdm+fpzSGEEEIIIcRvQEQ6JiZGGdygZcuWcvz4cdm8eXOhLacyMzMlLy9P0tLSJCQkRM6cOSMLFiyQ4cOHW33v2LFj5Z133jEY3ADR7g4dOhS6vbNnz5bu3bsb7uuj4ojKv/DCC+o3wOgfOHCgwTD/+eefZcqUKcrwhmMAwFHQrFkzady4sbRq1coQ4f/ss8+U46Bz587KCbBhwwb12YMHD5Zbb71VateuLSNGjDCozx88eFDatWunMgXw+TDwzYFtw/vxGnyfFqHXthPbjefOnz8vvXv3VvtIU7t/6qmn5IYbblA3GOgaln4zwDFp3769fPXVV+JsaHT7GenZuaJ1U0DEmxBCCCGEEOIcoF4dHx8va9asUfdhnCJ1GyJbGqNGjVLG5+OPPy6HDx9WjyEtHIYpDFY81rNnTxk2bJgybIOCLCcfw6A8ceKE3H777XZvK96HNHZrUXQ4EVauXKki8X/88YesXbtWpaA/+OCD8uKLLyoD/emnn5Z///1XOQgQ4YeD4fXXXzcy5tevX69SsxHJ17Z19+7daj9t375d/v77b/V+gMyARx99VD3+7bffSt++feXYsWMFtm3kyJGyceNGtQ3PPvusPP/88+rxWbNmqb/IMsBzZcuWNXrfhAkTlIMDn4/tglGP9Hxrv1kD275ixQpxNkwv9zMQ5da4lJUr0cWDPbo9hBBCCCGE+AtIO/7uu+9k9OjRKqIKIw0RaM1wRjS4SpUqKqr7/vvvy/3336+MTzBx4kR1Az/99JN6HSLPffr0kZSUFHnssceUoe4s0OKqXDnrKfP4Pmw7bogawyA1Z+BjexHZRqRbIyEhQS5dyteRat68uXIs6HnyySdVhD84OFg5GZYvX65q0WG0w4jXnBgtWrRQBnS1atWM3r9s2TKZOXOmcmogQwDfZwv4nmnTpklAQICEh4er7cBnafvW2m8uX7682m/Ohka3Pxvduv8JIYQQQgghRQcRa9wAIqow1LTUbxjSmiAYaraRyozIOFLSNWBgT506VUVZUat95513KqP0pptuUhFmfWs0RHErV65siEDbA3qb68XGzKHVRAPUYefkmO+ABCdCr169LAqNRUREOKwAXszM40jZx/5DpBuRekStkWLuCKafb+03Y3+5ojWdT6WXQ6UOO01/q1evntFOQuE7TmoceNQVnDvnGqEFbyUjO88o0k0IIYQQQghxHqjF1qcyQ40cdcsw3vS2x/fff68izXqDW0s/h9o2jGLUd2t2DXpAZ2VlmbWBUPe9d+9ew2NbtmyRpUuXWt1ORJ6Rnq5Fo+0hKirKoLAO4Az48ssvlTEMEHn+77//rH4GXo/fdOnSJVUnjTpuCLohxR7icFp99+rVqwsY1PhuRMgrVKigDH4IwunB5+i3Tw++59NPP1Xvw/5F9gFqtW1hz549yvkh13qkG6IFSBnQ0NdAoC5i8eLFqjYAqR/wjjzyyCOG9IVrLdKdmUOjmxBCCCGEEGcCgxnp0DCykZYMA0+tvTMz5b777lN/kdpcpkwZVfOtB3YJjNC7775b3UfAsFu3bvLWW2/JE088YVY1GzXPiL6iFhop7bB/EP1FlNwaiOjC2Pzzzz/VdtkDtgXiZKiHxjairnvy5MnSqVMn9bvhHMBnoh2ZJaAEfscdd6i0cCiod+3aVT2O1l4QMIMhDWcDhNqqVq1q9F7UxOP1sP3gtDBVg4cwG/YhHBemzodXX31VhgwZYlB2R/04UvdtbQcHR4qzKXZZk5HzAeDlwYE314cOno7Y2FjlRenSpYt6DN4gHGykY9gqd490D5zs+Dx4eHyNzccTJeFivocsMixImtU09qwRQgghhBDiKyCT9ciRI6r3tT4tmNgGlMTRTuvXX3916y6DSjhaepkay94Mau/RSx0OFVvPQ1ttR59KLwfob1exYkWpWbOm8vZoKQ7oVYf0BaQTaCD1HF4TvSKdKfBEYWfpb76AJV9Jbt7Vx7PYMowQQgghhJBrlqZNm6rMX4iRkcLV3tFizRX4VHo51PLQBw71CailQM819FiD3PvZs2dVb7WSJUsavQd1FHjOEkjL0Pdu8xVgXAcFFhQdyMm9anSzTzchhBBCCCHXNuhZ7W7++usv8TU62ND3/Jowujt27Gj4H83UYYRDWv6bb75xWGUOcv/6hvSIdGuqg96MLqBtMdKdlyeSlZMnIUE+l9BACCGEEEIIIX6BT1tjiGpfd911SvUOUv0o6E9KSjJ6DRQE8ZwlQkNDVf69/uYL5FlIL8+Bpa2DKeaEEEIIIYQQ4jl82uiGeh+amUNKvkmTJkpWfsWKFYbn9+3bp2q+zTV493UsGd36SDfIZK9uQgghhBBCCPEYPpVejubyDzzwgEopP336tIwdO1Y1NIfMPlTjIKePVPHSpUuriPXgwYOVwW2rcrkvYS69HAa3qS2ekWMc+SaEEEIIIYQQ4j58yug+efKkMrDj4+NVe7AWLVrIunXr1P9g+vTpqide586dlSo5iuE/+OAD8UfMRbrNCafp+3YTQgghhBBCCHEvPmV0f/3111afR8+0999/X938nTwzoW5zhnhmNiPdhBBCCCGEOIObb75Z/YWWFEpZb7zxRnUf3ZUWLlzotp08btw4GTVqlE29y9H9CZm/aKdMPINPGd3Eenp5tq5dmMYlRroJIYQQQghxClu3blV/jx49qgxw7b6enJwcCQpyrZmFlsdDhw612eiGADWNbs/h00Jq1zLmotqmImog+VKW2ccJIYQQQgghzqF69eoycuRIadq0qfTq1Uv1qdai4mDnzp3qNRp//PGHKpWFGDTes3LlSrOfO3HiRLn++uvVZ+F27NgxGThwoHquZcuW6rHz58/LV199pdopN2rUSG666Sb55Zdf1Gs++eQT+e+//2TYsGHqtb/99pt6fOrUqep7GzduLPfcc4/6XOI6GOn2o/Ry03Zh+a8TSUrPkpiIUDdtGSGEEEIIIa7jzJkz6qanVKlSUqNGDcnIyJDdu3cXeA+MS4CU8LS0NKPnYAxDiLmoQHdq/fr1UqxYMWV0W+Lw4cMqPRyGN8Sf0f4YBjSi52hnrJGYmKiMY/zW4sWLS3p6utKvmjVrlsyePVtWrVqlItgAWlbQvsJ343OQTg5D+umnn5Yvv/xSRcUffvhh9VoY6NgPa9euVaLU8+bNk2effVYWL15c5H1AzEOj28/Uy82RnpUrMa7fJEIIIYQQQlwODE6kV+vp0aOHMi4hvIzosSmXr2SJ9u7dWwkx64HR2bNnzyJvFz4bRm9hLFmyRBnarVq1MjwGYxqtjuvUqWN4DAY57mPb2rdvL/fdd59UrlzZ7GceOXJE7QP8fqS2JyQkqMfMpZQvWrRINm7caNhPubkUXnY1NLp9lFwz6eU5Zmq6NaObEEIIIYQQf2DAgAHy4IMPFoh0AxilmzZtslrfbC7S7QwiIiIM/8Pw1RuziMDrHQB33323ijhbA1FoOAjWrFmjIueIXi9YsEBFxU3p2rWrvPnmm9KlSxd1H5F7/XfqwfePHj1a+vfv79DvJPZDo9uP0sstRbrTsnLcsEWEEEIIIYS4ngoVKqibOSAspqWSmwMq4+6gZs2aKr07Li5OtTdGNF0DqeCI1G/fvl0aNmyoHtuwYYOqsdaTmpqqbjCycdu1a5ds2bJF/R8ZGSnJycmG9HKkoiO9HiDij/v6iDleq4E082nTpikDHcZ5dna2qjlHPThxDTS6fRQzgW7JsWB0X2KkmxBCCCGEELdRsWJFeemll5QhXa5cOenYsaPhudq1a6soNyL2qNNG+zEYvKaRbxjKMIwRmUfaOlLNIdIGRowYoaLlJUqUkKVLl8qMGTPUa2GEt23bVqpWrWr4HES08frp06fLG2+8odLQUX/epk0bg9r6U089RaPbhRS7rBU4EEVKSopER0erkxxeIW/lyIU0qVEm3OixfWdT5URCeoHXorSkTd2yEhBQeI0JIYQQQggh3gJSpFGbjCiuLe2xCHHneWir7ciWYX7UMsycejnASzNyWNdNCCGEEEIIIe6GRrePYi5BwVo/boqpEUIIIYQQQoj7odHto+Tm2V7TDdIyKaZGCCGEEEIIIe6GRrePYi6qbS3SnZpBo5sQQgghhPgmlKEivnz+Ub3cj2q6s3LM13SDlIxsF28RIYQQQgghziU4OFgpd2utt/A/Ie42uHH+4dzD+egINLp9FNOoNk6GTCtiaemZuZKakS2RYY6dKIQQQgghhLibwMBAqVy5spw8eVKOHj3KA0A8AgxunIc4Hx2BRrePkmsS6c7MyRML4uUGTiVdknrlaXQTQgghhBDfISIiQvWozs5m5ibxDIhwO2pwAxrdPkqeSaQ7M7sQi1tELqRmiZR34UYRQgghhBDiAmDwFMXoIcSTUEjNR7lsYnjb0oc7IztX0rMoqEYIIYQQQggh7oJGt5+kmGeb6yFmhuRLTMshhBBCCCGEEHdBo9tPxNQKq+fWSLnESDchhBBCCCGEuAsa3X7SNizHRqub6eWEEEIIIYQQ4j5odPtLpNvGhu2Xsguv/SaEEEIIIYQQ4hxodPsw+uB2jomauSVsUTknhBBCCCGEEHINGt2TJk2SW2+9VSIjI6Vs2bLy8MMPy759+4xe07p1a9W8XH8bOHCg+LuQmj7qbfU9eZcl0walc0IIIYQQQggh15jR/ffff8ugQYNk3bp1smzZMsnOzpb27dtLWlqa0ev69esnZ86cMdwmT54s/oje0LbV6AbpmTS6CSGEEEIIIcQdBIkPsWTJEqP7n332mYp4b9q0SVq1amV4vESJElK+fHnxd/TiafYY3WlZOVIqPMRFW0UIIYQQQgghxCcj3aYkJyerv6VLlzZ6fP78+VKmTBm54YYbZPTo0ZKenm7xMzIzMyUlJcXo5iuk6SLWdhndjHQTQghxERkU7CSE+AiXL1+W86kZkmfHOpoQv49068nLy5OhQ4fKHXfcoYxrje7du0u1atWkYsWKsn37dhk5cqSq+/7hhx8s1omPHz9efBF9+y97jO6LmezVTQghxPmcSroke8+kSK3YCKleJpy7+Bo3ZrA2CQr06fgO8XNOJFyS/edSpU65CKkWwzGLuA6fNbpR271z505ZvXq10eP9+/c3/H/jjTdKhQoV5K677pJDhw5JrVq1CnwOIuHDhw833Eeku0qVKuIL6I1nGt2EEEI8SUJaluw5nZ8tdvD8RYlPy5JyUaFSqWRxJWpKrh2wJtlzJkUS07OkfoUoiYkI9fQmEWLWMXQsIV8XKjWDASniWnzS6H7uuefk119/lX/++UcqV65s9bXNmjVTfw8ePGjW6A4NDVU3X0Tf/kuvZF4Y2Tl5Kv0vLDjQRVtGCCHkWuN00iWj+4lpWep2LiVDKpUsIcGBxaRUiXw9kYAAGuH+bHAfuXBRziZnqPtbjifJrdVLS3SJYE9vGiFGXLiYZVhLp2Rkc+8QlxLkax6pwYMHy48//ih//fWX1KhRo9D3bN26Vf1FxNsfJ7bs3DwJDgywK9KtefRodBNvLBtBSUhERISMHTtWTYJpmTlSPipMRcowBjBiRoj3kZObJ3GpmWafS0zLlsS0fA0WULJEsNxUpaQEBeS39ST+xcWMHDl6wVhL50RiukSXiPbYNhFiyvmUDNl7NtWosw8DUsSVBPlaSvlXX30lP/30k+rVffbsWfV4dHS0FC9eXKWQ4/l7771XYmJiVE33sGHDlLJ5w4YNxR/BAOGI0Z18KVtiI30zwk/8l2+++UamTp0qH3/5jaw/HK+U9iHSD/G/S1m5ygiPCA2SyqWKS3hoEB1HhHgJp5MybJ6HktKzZfXBC3JLtVISGcbop7+RlXs1C08DQlVZOZESEsT6buJ5ktKzZMepZMnKzJJ3xr8o6RcvSr8Rr0pc+UipUrqEpzeP+Ck+Nfp9+OGHSrG8devWKnKt3RYuXKieDwkJkeXLl6ve3fXq1ZMRI0ZI586d5ZdffhF/JSM7Tyku2pFdrmAaDfE20Elg1KjRcleH+6R6o1ayZ+8+OXn0qHru6IU0laIKwxvRNKQr6ssrCCHeURcJ0lJT5IcvPpLpY1+QrMz8FGNTcnMvK+cv8e92php4CGM4Id4AItxYN//45ceydNFCOXvquMSdOy3nLWTrEHLNRboxsVsDAmh///23XEtk5uRKjgNtDrDYYaquf+NraVJzPp8nx44dlVff/Vydmy8P7C6NmrWUYeOnmn19Zi5a5jFKRoingSNMc4JlXEqXl/o+Kvt3bZPK1WtJVmamhISGmX1fyqUckVJu3ljicrJzLltcd3iTTC3mmZSMHEPGYKkSwSx3uAZITs9WJRBZWZny/eez5d4uPQ3rDETAUzOymYFDXIJPGd2kIJk5eZJnb5j7SpQB6udM7bNtgEZmQPnoMDUxezMQLUJqHxRjsRBuWSdWfAEsen5d/pfc1rq9VKtdVz12Z4cHZfG3X8rg/02SoOCCxjUj3YR4B6jX1fhoyng5fviAvLdwidS94War72P7Sv90wJpLLwcpHs5syMrJk20nkyQmPETKRIbKrlMpSjNET1Rx6A1EqyzC6OLBHttOtLACtctG+JTz3BfQMj3X/71cEi6cl0eezO96tGf7Zjmyf48Ed31CmtYozf1OnA6Nbh8Hg7MjkW7N60yj23r7m12nkw3G3ZnkDKlfMUrVFHvbggqLGWyfqZARaiwDfUAl+Fh8ugwbN01FyTSa39VRvv5kphzYs0Oub9jYrMOJEOJZUPIBoTSQmXFJ/vztR+k+YKjB4F752yI5deyw9HzmamtODRg8zLhyLdi/xxPS5bpykeLJ9HKQnpVrEH91N+lZObL1eJLahtPnEyQiMkIuXy44N2IuXXsoXnJyL0u1mBJKO6RCdL6QpzuAI2rHyWSDMwDb4CtGt3YtIwMTkWTU7+vXmCiF9ETXAmzXrtMp6hrANmlGd4t298qH3y2XarWuU/e3rFslCz6aIe0e6CzHE8Lces1Y23as1Ute6fpAfBvvDtuRQoHhgai1Kev+Wqrq6VCrknbxqjqjHtbTWedQ3EWjaCom4w1H4mXbiaRCSx3c4WzBIgLe8B9XbZdnhwyV6ZMnSXZWVgGD3BcW7f/t3KP2aVjxqwImterWl8CgIDmwa5vZ9/nCbyPE3zmTfLVNWGhYcZn767/yYNfehscO79sli+Z/IrmqHEQKOAUv8Tp2KZjn3Z1RYCm9HMAY8wSH49LkXFy8DO52rzzcrI4882gHSUq4YPa1MLg1Z/Du0ylyMtG4FZ4rwHx+8Hyq/Hc0wSj67mBMxW1kZGYp4dOth8/KqgMXZM3BC7Jq/wWlu7LxaIKsOXRBBS9WHYiTv/aflxMJ6eq3urOrwubjSap9HZwBWlkLHIRwENS+/gbDa2+7827l+N+zbZOcTEz3ijVGfFq+4Jun15zEOdDo9nFgfJn26N7+31p5ddCT8t+/K2XKK8/Lj/M+tlxP54XAE46bJzlyIU2llZsCBz6iyScSXD8JW2tzsfpgnKw5GC/H49Pl7TEjZOmPC2XeB1PltaF9jYSLMGlgX2LC+Xt/nKw+cEGloHsTB88kyIBH7pZv5rxv9DjqQDEJBgSa9/LjOHj6PCHkWufsFXGsnOxstZAtVSZWwiOjDM83u/NuSU5MsOg8o/PXtUAYChFGd4E5BzWx1tqVuhtsD0TcIqKipc29nWTImLck7swpeWfcizavB1y1D/G5cJ4juo42a5rBb8CLba2ff/5Fate5Tvo/8bgypvODAblG6yW04TqTlKECGLi/72yqcmS4Gqxzdp5Kln8PxRvWPAhSwQiH0T9xxAAVmNJTvU49iYwqKdv/W6e2Fb/J0yhnQbbxfvU02IfEMWh0+4WQmvEF8NXsGVKnfkOZt3SjzF++Se5//En1OKINMMg14E3FIOmKCxKTCAYs/LVkGMFzZ+7ixYC84UiCS7bNFuIvZsqh8xflwO7t8kLvR2RUv65y8ugho9ccjEv1iAI8jvfuMylqQtAY884n8ukvq2TCB/Nk478r5QedkwWLBRjamHyyc/LUgmjn6av9cj0Nzo0ff1ms1I5Rz23KuHfnyv2P5Z+/5qJk8Re9y4FAyLUEIqhYVIO///hZerRrIilJiUavQZo5IuA7N2/wKeevr6NFxuCctLelqL2kpaVJt27dpGKlStJ74BA5eeqMxdd6Yt7EOuTwvj0qsvnIE/3kgcd7Sf8Xx8m/K35X+gOFgbVI3EXnq1rD+Pv30AXlPLcUyLzspVb3n6vXy6OPPSrlq9SQD75dKsVLhMultDSL3QpMWwYiw80VYE2JNeSmY4nKYMW6R38c4eQ7d+qkbPhneQHNiYCAALmhSTPZsWmdQasCwmqeAg6ZC1fOO2/Qv8D+w5oNugjEMWh0+0NNt4lntHOvATLgpXFqAClboZKULF1GTcD/Lv9dRvTqJPNnv2N4LQS3nGUMIi0KhjZSeTCJwKOJvzCg9SmI2mSz8WiizPl5pfQZ+Jw0vrWZ/L3jqDJ4UUuNAXnvWdd7Q03B4gStJHZv26QM7uSkBMnOzjSK3AAYvXvPmE/bd+UADONZO95/Lv5RThw5qCY7RJeatrxL+gwZJdVq5QuRaZOb6YILXlNrkQh3glrD5b98L7Xq3WCoqzIFKYCIopkD54ojoGestvjDNWR6fhJCCkffAmrRl59I7esbSlRJYzny4JAQqXdjI9m5xYLR7SVjkT9mIGDBjrnUNBvO2fTt21e1Zm14awv5ZeEX8vSDrSQh7rxXRLqxD3756Sfp36mNEsrSuLPDAzLqrffVGsnWz3H2fI4648IEQb0xvXz/8XPyRPeuaq3x2vufqyAPDO4n72kqS3/6xqbPMNWfcQY4Rv8dS5TTSebnc0S6oX3z2/fzlSMQWQ+m3PVAZ2l8WyvDOg9BDk+RkJ5lWO95IkNED9LtUSLw9744ta4kjuFdilDEbjCXml4At7ZoU+B18PC+MXuBfPnh2/LZu2/KdfUbyq0t28qppEtSLsp8Oxd7gIGN7TB3MWLS33MmRdVHlSoRIlHFg+TQuVQZ/+IgWf7zdxJVsrR07NxdsgOLqzogjfMpmcrL6E4BiYPnL8q2LZtldP+uyhB8/cP5Ujw83GD8paWmSqVqNQw13vCgu0tsY9+5VINgEYztKS8PUaqb/Ua8anjN432fs+mz8DmeFtGDR3rv8XNKQbTXc+bT/NB2aNBjHSwqISP6oBdnwWdisVk+KkwJyGmiLqeTMqRsZKgUDw5U9VHahB9dIlhlfGBiw7VUsWTxAt+Bzz+TkiGVzDxHyLWEqeiZZnRD8Xfvji0qM8Ucj/UdZLEmEQ5Aiqk5HxgeUOAGFnTNnALKsPqNnCB3dnlK6tS/Sfq9OFaN6XAEmwMOd3cJfOK82rTvuLz72ki5vU0H5fzRly/ddX9nmz/LUQevJUcTAhLmSthM8bZaXmTL7TubrPbng936SEhIqHoc66SGtzaX7z6bpVpwIehjDczdVWOuargUBawxMa8Xpo6PY5iQmi5Lflggbe/vbFjb6UHXFD3I5IExXyYi/3fqQQ1+RGiw6mzjChCp1/BkxB3boQ8yedkp6VMw0u0H6KPVG1evlF+/+cLs6xBx6DX4JWWUT35liCReiJOEi1lG0QotAmrPQH847qIykK2BSR8CKoiEo03Hwi8+VQb3sPHT5Ju/t8vTw/+nhHZQ17tz03rD+47Gu6+mBsbZqaR01Vv2sacGGRnc4LVhT6saeT2YOJ3tAbc0WZzSibnMffdNKR1b1qyxum/nVvni/SmFRno9DTzOJ44ekdJlYqX1PQ+ZfU3VmnXUIv/wvt1mn8/Wpf3BAbLhaIKaHP7aFyfrjySo9Pr1hxNUucD2k8lGBjfAokfzJOP9WBCqfZ10SV0LWBweOH/R6Boh5FoEmUdpupTQNF1q+R8/fi0lY8pIs1btzL4XWTiWnlNzgxekTvoTyN7Rp/C6KtK9ZccuWb55n1wOjVIGN4guFSPtH35cjdu5OQWPKzbFXZlWmBven/K6ZGdnyfNjJxdQIE9NTpJJLz0r+3ZsKfSzEJF2xnmK9dKGwwlGBpUvRboR+S0eES0DR46XilWrGz3XqWc/1alg+8Y1hX5O8qUsp5Q9oF4bqeS2tKPDa48eOqC0J+5/7AmLr0Om47GD+4wy8pCFqS+HxBoKNfi7zySroBKuNZwfcNJjXYE1RFHA5+hLGpAWj7WJu50w+E78Rm93BvkKNLr9AH1tzMrFP6gFkCXgfXzx9XeVNy8wKF+gCu0pkAIOIQ8YKFhMIe0JkwM+21xtNQaUoxfSlBENVVB7qX/zLSpCe2+XHkqhWmP18t/k7bEjJCsrf7C5kJpZoI+ms8CgBlEyDUTi0y6mSYnwCOkxYGgBL2iXXgNl15YNKvqqx9bJsygcuNKzE+D7Vy39VZ4Y9ILy1pty5sRRmffBNDlz4pjFz8MA7kxlTiyiMCnZA+qlal9/o3zxxwYpW7Gy2ddAzbxStZpyeL95oxscOHdRnY9KFfWKEQDg5IGxrZ2/OI+spbTB+IY43eZjibLndIq6Fv7ZH6c+lxOMb4JrnGJ7RQfOxZMJl0wWnVevpVPHj6ioYVCw5eyZJT98JdssLMY9nTrpbjD2unJMgUGg/3hXiIAlX0yXRx99XF5/8Vmzz8+cOFomjMjvf+ypOv4N2/fL799/pTLAYmLLFXi+RESkbFrzl1p32IK9c5w5o8/e9ZI31XRjHBj70lB1LZujQaNbpWKV6rL8l+8K/Sw424oqoojo79aTSXatZWrUuV4W/rVNrT0sMe1/Q+Xnrz8z3EdwClmYCBRoWkQHz100/A4ERP49eEHWHYpXCu1QbS+qox6q5frORLiesTb592B8kc9DW8F+RaDCXKYMbW7HoNHtZxw9uE8pMFoDaV/PvfKGSuvWJn54CTXjFhENGCeYHNRAcjjeYJwiGowUbBgl+Iu0cntIT7uoan9QA4Rosp7AwEAZNm6qSp1evXSxkZfRFRy+kGbwRmJw+Wf9JulxVxPZq6v70oNITWz5ivLrwi8KGN2YjFyZJqhflM6fNV1FgO9+4FHz23nn3RJWvLj8teQni5+Jw15YdoKt4LzBhGTPBArvadyFRDl76nih/U9rXHe9HN2/x+LzOHY4H10xCWieeE4wvgkEXzzVoshfgKFw4Hz+OJ+jM970C78J738hfYe+YvVzFs2fo1pYXutGN+ZQLJ5dGcE0dQTnOXkAw5j7zPCRcuzQfun/wlizr6lSo7ZqXYqMOlOcpSVTmCM4OyBUug94Xh7q9pTZ12DNgSyMdX8vs+kzLxRBuBNrLejF2P8+8QqwP39e9leB9Y8ezOXtHuwiCXHnbHIqFWVsxhpi8/FEsy1zLXH+zClJTow3G6zQU7NufVUyYwrWvH/tj1OZdJbUxDUDtaiOLkt16bj2nFnqYAlsP9rj6oXojJ73lhPTx6DR7WecOXlMKlXNrzkujI2r/pTBXTuqVBvTel992g8ihYh8bzqWIP8dTVQRbkeAGNaEYf1kzOBeFgdkGFg3N71DFn83z2gB4ewWBYgEHItPM/SIxW+aMX6UlCwTq2q5zYGIPGqVVv72g1LbNlUzd0XvSeVRPZ/vUdUY/Oqb8tIb7xplCOiBsNptrTvIX78tsvrZRU1/0hbkSOnGOWLPIIzo8Z+Lf5De9zaXiynW1dRrXldfTp84Kp6E04vvAeEXqNtzcVC0SBIcF9qlrZViIHsATjaM40jNxV+UL1njhsZNZdeWjWaf8xZhR/csZJPVgt1ViuLITjPVVsHxc1a0G58/59vF8vUn70vvISON+hzraXtfJykmxeTvPwo6f+PTjFN1XQGCBpHRJeWJZ18wW7urga4ZRw/sVQ5gW1KiHd1ulUnnQNaeN9g2OFe3n0ySD98aKzXrNpC7H3rc4mt7DByu9IMKc6YD08479oxL2B573z7nnTeUmHBhDoHqda6XIwf2FHgd9oOtRn5Rrm8Y1tbKFt1RjnMkPs2qM9QLTkufhEa3H5F2MVUZMGUrmE/VNaVClWqqVnbBx+/aNIDAGC9Km4ePpr4mW9avkm79n7c6IN/76BOyfeNaQ5sufHdRPMzmjE2k1GM8xeCGAWzu55/Jzs3rZfArkwosHgMDi8mt1UtLtZgS0rFLd2nSvLWkphi3TMDg74qI/MG4q+nRSLnHMS5TtrzU1QnCmKN1x4dUSrZpqzM9WAAUJb0L+277qWTDJGTrHIP9jUyKlb8tkkbNWqreqdZ4tM8zqv2dJ/GGhQ+xHZxfmvALD51jYKyHDoK+O4aWqg9nBq6JXZs3yHNdOxpa7FijXsPGqt7TnJMNizt/L+HA70M9rFZ76gpnEAxCRP/M4Yy6bhz//45ckDdeHiY3NG4mXXo/Y/G1yKS7pUUbWfHrDy5JLbYGMvOe799LFn9z1XlviSZ3tFYO7A3/rCj0tdjuJAe2G9cS9EUcoajnCebponYIOBR3UX7/6QfZvfU/1RkHGQLWShjz8vKslrcV5bchYILMugL9zAsh7uxplf2H9WWh2XV1rlfjFN7jKEXxcWGNam3XpOnK6FwBnBqFBdf8fLh2GTS6/Yic7Czp2LmH1LjOenq5BgTDOvceqNQmLbX3cBZb16+WH7/8WPqPGCONb2tp9bV3tOsoU+Z8JxV1EXsoUjtrMt575moqMibRf3cfk4+mTpDWHR+WRre1MHp9cFCA3FKtlFK5rlMuUpo2qK0UestXqlrgs8+l5CtpOwukb6KOUgPHqe8DLeVSeuGT9y13tFbidKatzkxxpB4dvxFZAqhb0qce2ToJQivg5LHDaqHe5t6HC309WnsUpoTqahgt9R0gYqPvRc/FgWOgzMhUz0NLL9fG4x/nfyJVataRG5vcVujnXdcgX2jLVBNDc6zqRdr8EWSL6cdbV4wpWKxbcowXNbKeH+1MFqz3/zdttrw06V2rxhe46/5HVBQZKb2mpLiopACOgQU//yF/L/lZIqKtO3RBeESkvDJllop424Ij7ZJwLTm6/4ty1FD+t/rABSXchpaujtQCI5sNmWnr/lomzdveU+j6DXw79wMZ2KWdZGdZD5boy1VsHdshxOvIvlw0/1OlEXPPI90KfW3NuterDDsI7TmKo9c3nHOWUsv1jhRXZYogYxN13IVtPtdEjkGj24+Aaujw16YpL52tPNbnWSV+s+CTwqPdjpKVmSHTXh0mN95ymzzc8+lCX48WFDc3a6EMLS36gcmiqOnbqIPBYtx0MImPT5J6NzSSAS8WrE2rUzbCqLVW5VLF5fLlXCVkdmjvLqPXwgBFaylngElFXy9//PAB1e7trvseUenjthiqEI8pFWO+bYujvTLz+6snKPEy0/6itgzCmDRRS77goxlSOracisjbwsh+j8uPX34inoKGm/cDYwMK9KZ1fv4eQXUFKGlBNNuU3Lw8lQoOgUuk40KA6uHuT5mNHIUGBxi14IOTt0OnrsrIudZSzBHlLFhn7dzvgDP0hM5JW+D5y3g+/cr4nWqXwxVO1tUHL8jmLduUIQURKnOOZw34SMNDg6T5XR3lm392qLWJKc6qSzVdF+w+lSRvj31RGjRqKi3vvt+mz2jZ/n6b+3XbK8yI/WzuWrIVR8cvBBhwvPXOAkSIkeVna5YBnG7ammn4hLdl5Jvv2fS+W1u0lfSLqSrYYg17otWI1m8+keiQwQ0docXfzpP7uvRUQrmFgXN79o9/Sq16DcRRHDVKkdVZWO92V0W7sY9RQmrL97uTPG+T8C8CNLr9CESr9W0ObAE1T4/2eVYO7t6hWna5AohWDHhpvLw4cYbNEUsY6iN6d5KVi39U9zF+2SvapgeTjLkaIExoUM6e8ME8KVOugtFz6F9u2rc5ODBASoeHyifTX5fvPv+wwPfoJ7miLno1oQ4cFzgtsCh40kI/a3MguvDJ2xPl3OkTVj2mti524fiAyr2lOp/CJhkMnPD4Y5/DKdC9//OFCpoYtjM93aa2Lq7CmxRkifl0OGgLQNDQdFHGI2f/2GMptTA797JBffmr2TMkKrqk3P3QY2ZfW6NMuFQqdXX8xNj/wsR3LJbG+KPgnTbmoYuCKc6u6UY3CGsqzqgpxhwKxyf+33kqWaUNW1vQ4jn0IoaT9eyZM/JCn87y2cy3Ct2WEiFBUrtshHKgw0kMo8fUeEQEtahpz/i9aBelRf2gGP3F558rJ/XAl8bZtd748M0xsnPzhkJfa89xg9G6T9d5xBEc9RlaKnfDPoI+T2GtTnHssWZa+cfvqhUtjqUtBqumzYP1yoZVK5ximKIUbuvxJLtE0/SkJidKw1tul4d69LX5PThfTbV77MHR6xvXsS1cdLKGEK5FXEvmuhWZwx2+7Nwr4yfatvoLNLr9CCjDDnuy8HRdUx5/apC8/cWiQlPFHAE14xi8WrS7V9WQ2wqMsaCgYPlh3ke6aHeWUYsveyJgUGE09apCdO6ZLnfL0YN7C7ynREig1K9oPjW7TGSYitisXrZYqbGbLhyLWquGRRFEoDR+mv+p7Nm2SV6YMF0Zq7YSHBIqP8z7WP5d/rvV153U9f+2NOFhgbbVzD60Z5JBfToMdkTFhrz6pjzU3byirKV0L2ttw1yOmyYYGI+I1npDH3VfAAsE7C9EcCyprDLQbTtIa0RU0xJQndayY9AaqNfgkWYzbxDlrFSyuH1nwngAAPU1SURBVEQXD5aQoKvLDKRrYgFvjlQ/6tWN8xJlNOuPJBiVCOlxZgYGxo6jhXTQQFsjU47EpcmaQ/FqW2EEa0Y75jA4X1YdvKB6EWNb4fjFGuGxp8y3CNODvIeY8BApERqoVKAfbXWD7N+5tcDrHBVlBdhWZLUgKpeeDfG4LNl1Olk2r/1Hzc/QELBnrly9fLH888cvTjWm4OSwNC7ZiiOnCfaNtTR4BB9gxMKJjuMMZ+WZ5EsqIwPHGgY3Itzr12+Q118YICt++c6u8xVzfNNWdxVaJ29LejmuJRxnW41BcyCw8tp7n9uczQDghBn2pG2ZeM46bqoXt41ZEUVtSaYH+xYZEPY4NVwZiMjJzVMBrPWH49X46U9BDxrdfgTEvSILEaUyB9LLMUhCJAOGqLNY8+cSefax9rL8528dev8jT/STfTu3KoNTY8/ZVLt6MmIRuf5IfIEBG4Jk4wb3kfS0VCldplwB4bSGVUpKYIB5sY3S4SHS7v7OkpmRoQxvU4rSPgztZEzraZCW33vIKLmhSTO7Pgte6ca3tyy0Byn2kblUPy3KgZZxSJErSo0PoukYRJGSjzTx3Bz7Ftior0L0orAaMVfhiNMazh4YMNr+xbE12ys+NUNFFNATHKldOH8QUSTWF77Yr1g0motuGx877svCwHkIA2F3Ia330nUpjV37DZb7H3uywGuQaV6/QpQh5Twm4qow5eZ1/8jLA7pJYnycz0S6sW9gkMARiuggFsaWzjfMTdiHqw/GqYwAa2rVzox0Y5xx1LjDNmNbEeVC/e+KPedk45EEZRBrn7nwk/dUt5MRE6ebTRU3Bcc+IKCYVClVQrW3xFxkTlANpUaOGN5am0rtfFQ6DqdSlDH58pQP5fkxk+36PGzvrS3vKjQya08dMsYlZxhGjoxftpaNQdQP+x+OS9RKIyMDYn/IGtq1/4iMGdxbpVijbNEWNXI9TVu2U8ZSSpJ5YT9b0oZhfKF7QlHSnaGFg3PXXipVqyEnDh9UXXccwZHrG5kntgLjHKUVOPeLAsolEFCxVyTZVRnfx+PTVSkL5iNLbdl8GfM9h4hPArXF8CjrwlmWgDEzYXg/qXdjYxk749Mib8v3n8+Wj6a9Jnfc1VHa3NvJoc/AJFipWk0V7a5/8y3525mTp6LWjauVUqne1gYSTCRnkgpOekkJF+Tlgd3l3JmTMn3eTxJVspThuaDAYnJjpWiJCLV8aaDGu3r1anJT0zvk9++/kvYPG7fPwERbNiVUpafbQ346V7LBqbB53Sqpf1MT1dMcN0e44657ZfrYEWqRa6m+G3M6JrbrykVKyeLBapKHyA0WcvpFdmFYKnXT+pNmZWbJuxNGSmpKslqs25NXUeO6+spQRw939NB0N/Z6WuFkyE97vPo+ZDri3AkLCpSw4AD1iThXzC0o/KmGyRbgFIu7mKkiZBrYN7gOoXYfVTxYLWKwSMzMyVMODFvbxVxbe9I+cJ5BFA2LPVsXtj99NUf1u4VQo7mFOFLKITypd1Jq47BBTG3nVml2590FzgEc19Ag52dcOQoW/VtOJBVY2OJaRhQft+IhQWrBivZH+J22LraddYljvkC6uLMwtfFQ1vPpO69LjwHDpFmrdjZ9hnZalAoPUcrgECn96/dFSjfFtNUlIq2lSoQYnTPW5nUYiaa/d/+5FJn26guqNvvWFm0KbV9nDvTrXvzNF0rks3K1mhZfZ8vxhSMVbUSdgSOniSNibxo4h7GWHDu4twQGBsn4dz+zuQxMT7M728ltre+2aqxbc2DAoMR6qCjOOGTVfDR1vDw19GW5tWVbu96LdUZOTracOHrQLp0k0/EVzidbgEPP1ii3xp4zqWpORFamvetNgOwWCDzaE8jSsCfzQRvXs3PzVGYlShXV/bw8CQkMkOIhgRIUUEzVs2Ob/BlGuv2Ii6nJEhlV0qH3YpLq/8JYlWIFQ9JR0Cpi/qzpMmvyWOn8ZH95efKHKpJuDxFh+ZMy6rE69XxatQ/TK3YjRRmeOXOCJvliMkhLSTBrcGOg+N8zPVUriKlzfzAaTJES2axGjMREhBa6jeWjw6RbvyGqFyl+syn2eu8xkW85kWhY3KHVyainH5NfF34hRaF52w4SEBiohN+sfn/uZdlzOkXWHopX+w7/22Nwa7/BHDC48bs+ePN/sn/nNhnx2tt2L4rQC/atT7+1q0TBmdgbbMBvNk3FV21y0rOVMYlFIzy6lgydayk4iwkf4k4453brbignwX7CX6TBYn9hMQkDx57+rNeaAwPnGKKxcPxYWkwh8wJqxn/tP6/2ta0G96ljR+TjaRMkM+OS2cU0Fk+1Y43rPmFQ6QWK0ErKnIK5N0a7D8WlmY0k4fxDC02kXuO8xXiPNEh7olvOSi/HWOOqnt8ANfgoP+s1+CWb36OdGXCawZENFXM4frdYENZC3XNh+0OJeB5JKGBwY/799J035ffv56vabEdp1KyFBAeHFBoVLay3NNYfSNV1sAW1UyLdRa2VR9kcnNwT3v9CSpWxLsZqCazfMEaYU64vbGxGVgnWIUUZD7BmnDH+RWl0W0t57KlBdr+/eu38LkBH9hcsP7QVW9v0wSjdc8b++nEYqLj2oblgj+GM96CkBGn7jhjcwJ6zElkpWFuuOxyvsimSrqyD4GRAFiXmd/wGfze4ASPdfsTlvDwpWbqMw+9H+6ZtG/6VmRNGSY069eyqidJvw9GD++SJZ0fIE8++YHdKEigbGWoYbDt26aEUrk3rBrEQQirujZWjJT0zR+LTslSkBDWH1uqOsT39XxyrlLP13uzSESFyU2XLKeWmQGCtSfNW0vj2Vmafh2MAg4ot3kc4DxC917zTiCS99/rL8mC3PvLIk/2lKCAV8LlX3pAGN98qrsbc4gCG0smEdKW8DgfC8NfelgaN7N8WtPqwpVWJq7Bn4QNjp6gpX87oqesLYNG1zYHUNlIQLJ5ggEFZXE9YcH5mBRZa+B8GuSP1kUiznPq/oVI6tqz0HfZKgecR/b2hYrQEmWQg4TvRehFZShh/695wkyobsjRu2uL0dFeUu7DWPZ6+xlGDa3q8ncWyn7+VjPQ0eaBrb5tawunRz/vIUrnuhpuVuNaB3dtVO0tTEK2DIx0RO9NMB4wRhy9cVMa26S6DQNt7b7wsy376Rvo8P1pl1jlK8fBweX7sZKlnQehPw5KDA9uJ1GxH2nBaw97TBNe2o+MpovwQR0Tt84ffLy9yq06cQ9PHjJD5KzaZzbQzjXRjbEJdvr0Of1PgiJnx2khJjL8gkz/9zqHfAZHhchUr2y1ObLQdNhw8OJvgpClKCj3GfkSs4eRClgX2a5nwUAkOKqbOBWSF4rxFunZwYDGln+GoKN3V7bbtdSjN8TZnqieh0e1HjHmn6Gnhz748UQlWQfV66mcFa7DMAXGcvds3q/+RwoOaKkeMbb3yKSZqTMRQzMQNKeHwOOr7aKOua90hy15UPRBXWfrTN/LixHeUiqWeuuUjpUrpEnZtIxaSJUuEyIXkdHl77AiVNmkqDIbJAxElDIQYBDHoVSwZpn6fBgZIePgwMMIzO+a5XqrNRucnB8iAl8YVaT9qmKu7dAWmixF4qw+cT1WLdUS2ej33knTs3N3hz/93xe9q0dZ78EhxN/ZMT0VpD3Ot1SGjr7AlNXxn4axdicVRVm6eZGTlqcVMQLFi6rpGBA7tWzAeYcxqXttxx6ejYBsg2mVuIYUFmRbNcHRfI910zOBeapyfPOdbs+JptWMjLaYIR4YFGVInG97aXA7u2eGSCJ0zOZNse6q4IxT1ozF3mFNFLyq7tmyU+bOnq4gvSqfuf7yX3fOQ/uUoWcKxn/Hlr8qwtTZu/nvwgpofw0OCVMs5XGP4nZaMsIkv9JdtG9bIi6/PsKiibw8QYCsMcynRMHShy1GUtG7L2HeixKdlOnR9r135h8yeMk6l2b80aWaRDW6AcoRiAQGy5IcFKjPQnOMJzgqUFuF6Q9qxM8ZrRNcxVr34+jtSsWp1hz/nvYVLbNIwsIQt2Q7IpnHGeYMosT5S7EyhtaJk6hQm1HutQaObGAEDd+yMOeqvdmGZm3DhYV7524/yz9JfZfPav9Xr0Fv7lhZtimwoIh0tNjJULWA1ECld/st3MueX1SrSYgtINYOhDQXvE4cPqFqv7OysAjVljtTC5L8vVA1yEZHR8sGk/6mWY3pPOwZcU8VY1K9UjQlS6USqDYvOK46F7H2P9pR7Hukmbe97xCkGt8av33yhosXtHugirkJvKKJG9M9//5OUpARV+w7l0KL+Hoia/DjvY3ly0ItOWRDYhR0LgYT0ohvd10pvaXdMyEV1YMCgRQq2LQsjnOKWxkxXgvZARY1cWKNERKTUqneD9Br0otmoZ+XSxaVqjGXHZVRYvuEFuj492OLrXO2A8aZzsyhlD4hwF0X52xw4b6HY/NOCORITW16GjHlLOWwdOZf174ADHcDgRgQS4qO3t+lgtsQIcyaiYtYiY3Dixp07LRUqV5PB/5skuTm5SvTKWUCPBlHZtvc/YtNxQ2YTxE+LGp21hD2nCSLFmpAr1mjY50pTZccWlS6ONRF6rGs6NhfOn5WvZr8jq5b+IkkJ8dKkeWsZOPI1p207vgcZlL8u/Fwe6/NsgbUXxqy/98c5zbmF34r2ojh+Hy3Kb3NWFIqSOWrL3OOK69hd2DKtqlInlziifBe/rOl+//33pXr16hIWFibNmjWTDRsK773oD0Ap/I8fvy7y58TEllOpNRiQ+z7QUr6Z875qq4U6Yxi+4ODeHTJjwkjJuJSulEJnfb9CJn/6rVMWmxBUQIq5HhhawcHBMn3cCzarSb7U9zF597WRUq3mdfLSG+/Ka+/lG56m2JhRXoAyV9IgEZGGgMsbLz4jOzats/oeeO0RAYdHHwY3JsZ5H0xTYh8AgjN33d/Z6Yt2RANQa2+vari9Ewwiat8v+1f69Ogq/Tu1UfWfWGg54/fUadBQ1ZqdOnZYvFVIDQsyZ0wyzgyw4ZhgIYaaMbR+Qy0XzkNEFZBhYU5V3R1gsWpN3dlZFGVXQtwGtYW2RiKwEHG38jwWrM5OacW4DiFHXL/r/lqqnFyDRk9UDjRTkCVUr7x1Ac+oKzodeuFOzC+m4HwsSmsgZwHxPlefm444g5DyjjRsRLhtNVQQxXxtaF+DYjzm8W8/+1DW/71MCVPu3rZJEuLOqzE6ulRplZE074/18oADEW4N/fsgNqeB75v00rNKmM1eMHdh/YE1CUS+YGBBI8BRgxulZLXKRkjZKOO1xq4tG2TBJ+9adHziYex7rZUmOii4yuDWvs8WUKZ24Fyq7D94SJ7v8YCM7Jcf+cecOaTbvTLsiQdl5NOPSZ/77pDJL+dHncPDI1VmQ8u775cv/lgvb378tZGwrCPAH14zNlxKXsl6ebjH00p48c/F5jMnnWVwnzx6SEb06qTafGVlZRbZ4AbxcedkQKe2sv2/tU4tIcGcDE0NV2SquIvCjhoCUqgZJ34e6V64cKEMHz5cZs2apQzud955Rzp06CD79u2TsmVti5D6IjBsDu3ZqSK5ziInO0vVN82ZMUktviDI1fLu+1S0FNGO71btUsa5s8FkCFEzCKppHm9MBMNfm64WD5hMnh01UbWy0H77sUP75NPpr6uWVEPHTVFpTX2GjJSYsuWlcvVaVr8PKWyOgBRzpFPCyEI61isDe6h2OB9+v8Ki+ikW77glXoiTue++Kf8s/UWyMjJU7bYrImTIGkCNe5feA+W5x++RZb98K/d06iauICUpWdrf11dWLVss5StXVfXbdz/4qNOi0nXq36j+Hti1XarUqC3uxFZRHES5nbGIcNZCBJM70o4LayfUok4ZdT67EyiVugNHI93o+4uUUXsFkZCCru9N7WpUDZ+JoY/UYESnocuB3sr21GD+vGCuHNy9Qyn3QvQsNCxMbmvdvsBrMVTVqxCl+nEXBlT79WAcz83NkTdmLzAbrUOmkydxVZ20HnsvcZQq7T2TYlcbHTio0ZUEbTezM/N/E1ov/rLwc8nOuvobh46dIvc99oT0GDhMnIF+FkM9Kfp1wzCtVus6JciGuQ9lXs3b3lPoZ2Fe/OL9KbJ00UJlvN12591KjdrRuRLTUdXS4VK5VHE15sHBgtZlGh0791DdTaDabknXZuuJRCWk503jF9q+nU9MlVH9uipLHaWCICysuMz+4U91PSPo8PXH70p4RKR6DpHw2T8U3ibNVqBWX7NMuPpbNipHNhyJVyKoyNyz1jqsKMAZ89nMt1RGY2z5iir7wRkGtxbpRpebHZvWFyhLtAXTeRdORYzXhy+kuTQzyR1Yy8ZDaSG6BzlLTNCf8Duj++2335Z+/fpJnz591H0Y34sXL5Y5c+bIqFGjxF9BPTCMz4hIx1qGmQNeZBiTEESDwAYEsNBvU8Oawa2M5tAgKR4SIBnZecoLC+PWlv6RQVeMtArRYXIg46on8PY27eX1WfOVMnrmFZVSDLQwtpE2BWVr1GSVr1hFPWcuKmMOW1s6mAPbCKMbgzxSqJFGValqDTUgfffZhyq6kJWZKQEBgZKakigjJ72n3jewSzsV7Xmo21Ny76M9pNyVbXY2UA7GPq97w83SqsMD8sV7U+TO9g9ara2zFURHkpPilRGMejos8nNzc1Uv13b3d7Fbtb4wYADAmEeqnKXUP1dSmFME5zh6SzoDZ9V0Y+KzpX8v0nrdbXQnOFB76AiO7Eo4PZBS7siiQUVq3WQz4pxDLaQpqM+EYYXrJbpkaeV4bN+pqxIjPHf6hGxd/6+qe4QzEx0FoPCLbJ0yZStI5eo1lWP1pqbNpWrN68w6zaBSfkOlaKMopjXwek1MTRubYXghom6afeQNRrczSkSc4VhDZDsxPVtlMjhSowln+baNa+TNj76WshUrq8eeGfWaEhNNiDunRE8R3a5eJ1+p2VmYDpMli4dIemZ+uj4czLu3/qei1XDKvvD6DLV+wXl49tRx2bJulbqP8w6lbuC3b7+U29veo8qvHGmfCec4dAWwJkGGmn6sU49FhhocLY2b36mExJDhZ0knx10Gt63jF7KVIFj13eez1fUNIxsODoCUbn2bTazpnHmc0RIwJjxUSoYHqzIS/X6tUSZCRXNHvfW+0wIKmIePHtgrVWtdpxyKH7z5qiqf697/eXm0z7NGa9Sigs9H21ZkPzgCVLtxrsHplJGV61d9py0NX8gAMTW4kXmwc9N6JTyMDKe5MyZJ/PlzyiETGlZc2RaaKDHsmIQL5+XMiaNqjYz13ogXXxR/wa+M7qysLNm0aZOMHj3a8BgG7nbt2snatY6lh/gKF1OS1N8IB1uGWQPGrL5VU2BgMZUumJVzWRkHiEzDg4fINIy8MhEhSmTMknDS/kJanCA6qymEH41PNzIacGFiQtHXQUNJFylmNze9Q13A9lDUIGz5qDDVZxSRJmwLBn1w+vhRmT/7HSXCkZ6Wb4g1uf1Ow/t6PjNc7uzwgDIkXQkmRM3R8fSw/8nTD90py37+Rimj2wrqshFhQC0YeKnvoyoKgLQ1gB6emODRWmb8zM/ElSASA8PAE2DxY23doAniOeu7igoW6voIjjXgfQcwotwRpcX1D+PKHThSH48UfEcXSOZaGTqb/FTSi8oQ0xw0GG8QvYTQ4MBRr0mLu+9T9bOXLqXJ2ZMnVMRL647w7dwP1ViJ1l/o5FC1Vh31HIQq9WKV5sbLuuWjpGJ0mN2LaMwZmsjgbW3aK9EmiCOinEYPjIdqMSVUhNQT4HyxViKCkqCQ0NAC9alFcazBuEaGBM45PH4hNUsycnLVdjia9YKI9qL5n6j5EXorpsYEooK4uQLT7LFS4cEGJXg4qDFPoDXp7q0b1RoN0cpR/R+XvNxcZVQjQ03NnRdTJTwySr7+a5vN5xteBqcN5r7iwYEqAFCYQ7FO2QjlBIShgH3Td9j/ZNJLzyjnQP2bbxFPYskBq8pKrrRdggDhxYtpsvCTmfJw974Gg9tZYJ9iP2rzA7RpsE9LlQgu0K1AT/WYEmq/ak4KZE1ijEJ7WtPjmXYxVY7s3yOH9+2Sc6dOqMxKrJMwTkHTB511EHWGsx/j1sQPv1QZjViXoLTxplubiyto0LiZfDv3A2UMOpK1pxey9CfMldzB4bzNJDsM4+XoAd2kRHi4cu7i+j9+aL8S2Ptj0deSm52jSg/mLv5XBW0euKWmURYOrv9u3R6XBpWKVvbgLfiV0X3hwgV10MqVK2f0OO7v3Wu+115mZqa6aaSk2N8rzxu4eGW7nRnpNgXjTfmo4lKrbHiBth62glTE0iVCJDUzfzGBwTvrSoRQS5EMvDIYY9FVu2yE6oOqRz9YF0UNW/2mIou+BUit2IgCEU4oZi5at99o0a/fbtTLuQMowMLDj0gmHCfT5/1kMJ5/+26+3NC4qUqhwiJSH3FCX29EQVBDd/r4EQkKCpZ5Szcosbgmze9U74PYTpWatdXnOdO7bA1XpcbbwuVC6pNhLDgLZ6SXw3C0FfS0x01bXEFXAddfvjBYfso0DL3QoACJCA1Wiy9470sEB6prwJ7SCHjCsQhxV+qZI3sSi1kAYwDRWEz8F86dUX2GYRggglyxSnVlHJguxNCnFyKQ2B3Yh0itRpsWjeArC9ailJOgPYw+BXrJjwvks3ffVPW4AAsbOCjNtTTsPWSUMsyDQ0JV+jGMR1sXk4gS2pJObg6cM5rRjfIbGIJoI2hqdKN1zqoDcVKpZAm5rlyE20XpUjJyzF5/h/ftlg/fGqO6S8DRuHjzUfX4q88+oSIz7R58VEVuI6KibfoeGKHYH5eyc1xyLZw8eliq1a4rD/d8WjwNDGA9OKb3dumhbgAZF/OWrFfnpCN9oSGGWqV0cXWtqXWFnY5DjHlIOddErSD+VaZcebn+piZm529PAycp1hz6NlOYv2d89WuRxb8AxnZc61g7wHGBTBVH1nzYZ/UrRMv6I/FqfVe6TFl5/41XVJSz7X2dpEy5iiraibZc/R9pq8ZWjEdwuGBNgjICcHDvTokqVVp1icGYiyCLFsQo6hqwMG5s0kyNreicgoxBYnliRYTbVN8AGU2H9u6Qtz79Tp0PuNZnfv274Xk4M5LiL6j/4fAaMuZNiYoupdbQWHdWrFpDqpQpemamt+BXRrcjTJo0ScaPzxex8mXKV6oiEz+Y55JaVy26US4y1KpX01YwgOOmB+lJqFk7nXzJKN0bERX0eXaVqm1RjW6A2jBE8C0prnpyssbvQ+qctv8waQGklmLyQ1q+el1AgBrc5vy6Wm3v3JlvSfz5s6qn6iNP9FOTjdZn8/G+z4kn+ev3RRJVKsbtfbtVVodRteLVKBWMIGcKjhc1vfx8SobZSC3a+2GBg6wEc+rB+FprysGYUBG1OKF7TDPMsdDNb6OVp9r+wEBHBAbPlQhBr+j8ax7bhWwYfYRj0fxP5b/VK5VOA0oVnLm4sXdXYpuxmEWbwpcHdFfe+X4jXpVD+3bJ5NHGyts1r6svs3/Mz7z5+pOZ0qr9AyJVq9ssvIaxNTwkSGX3aPsMas/IGEIGkTkggKc3uBH5mT15nDL4EBkqDH29o7lzwOr2FmEsw28SuarUe//jT8rCT98zqCzrgREK5wXq6kPR5zuwmNo3WPhnqn7f+Z0gMFfgOThqMafo2zHaCoyq08kZ6nPKRoYZdc3Qnp/yyvMqGgNnwbDx0wxZA6BB46YqBRKR+1lvjVGR2slzvivUEQkjJCfXdWJtzdt2UCVZnph/TL8Sx03TP7GElv7uCBDt0rLrLF03hYFaZFxbmCuxz7Qa3h+//ESJCTZq1lI5MVB2gdIpXEcI8pw/fVIunD8jwcEhanyFoW6r48WR8UuppZ9MNjuuVa9d9DIB9EpHlqGzwHV5XblIVa7zcI++at/MnjxWdb/BNfLNPzvUfn3r44USGV1KqtasU2BcGnelzMAT1L/pFnn7i0VSu94N4u1grEpNTlT70dXXvalfEs500xIYiNv9/PVc6TNklErTNwfWnvqORJ4MrHit0X3p0iVJSEiQSpUqGT2+a9cuadAgX9zKE5QpU0Z5Ss6dO2f0OO6XL1/e7HuQig7hNX2ku0oV19TXuhJEYprdebdLPhsLGUejG7aCBXv56DDVhksPBo4GlaJlI3rQuqBnqjOMbmwj6hu3Hk8qNI0IAiPwyIcGBirjBAtIrS0RajP1nmtnUOxK3fmROOO2FPAkf/77WtWTHS02UpIT1YIBQnxYTLz39e9ui17bC6JjSE1yt9FtbpGDSQ7pVHpDNS01RRlocWdPq32ZmpKsMgOwmHCX0Y0WUhqI1EK4D5kOB/bskJF9H1UOFCjll6tYWTlWsOhxFG1T9arTpoZL/nPZBkNTi/yi3vT1EQNUqQLSONf/s1wtymB0H9yzU5b99I3KpsBE7KhGgL37MiktW6UvQpAIda+t2t+vHm98Wyv55b/DapFw5uRxOXvymOReSSVHDeqCj2bInHfeUPXKJUvHSINGTeWBrr2tCpnBuNQcYvo6URgOKNeJjQiV0hEhhlpJqONDhEcPDNdixQJUFwVXU5TxEpFu/C5tHIeD4s4OD1p9D/aNPQ5X1I1jvEPk05Z6cxgwe86kqvMVWVUSWbBXuKbq3X/EGCU2ZlrCpLVAg9Ix0vk3rv7TkDU0/vm+KlOoxnXXKzFLOMXtLYFyBHQbCY+Icln6eGEUM+OchCHnqvZBjhraeuDAualKSdX+S7+dqO/OuHRJ9S7HWAr6Dn1FuvYbLB9PfU2+/2K20efgOA94cZzKjIk7d0aq1qit1meOYjp+oa+z6ZCGKOykkYPk9Q++NCoFdAStvM+Z4NijzA036EW0ubeTJF44r+ZKZI0A0xIIV60z7e2OgHnHXJtEbwOdejb+u1LOnjyuHECxFSopnSGUGpw5cUzNsZhLnSUyZ5pejvZnpuclBO7QDamTF2Tb+KzR/d1338nQoUOVgYu0gI8//liphIMnnnhCNm/eLJ4iJCREmjRpIitWrJCHH35YPYZtxP3nnjMfnQsNDVU3X2fv9s2yac3f0n3AUOcrYDthQrMVc9sOQQ4YtXvPpqgBE9F2RBcxSWIRWhT7xFntnrGNzWqWVn25kTaIaB4+W79IRQpbLdVKw3x0qXbZSOUtxMR0IjHdKQY4vh9OExj7aOGgB6niuJnDWw1u0LFLD3lz5CC1sHSGZ78oNUzIcDAV1Zn6v2GyevniArXoSOlFjeDxIwfk7gcfs26MFeGchhqvFmmFqM7o/t0krEQJeX/hH8rbPHPBb0oJGC2DIGqyf9c2GT35AxVx3LzuH6VUbY/itb3A0ERWC0CvXQgX9R36cgED4b9/V6r9CD0BiCXe2qKtPNC1l90LIHvHB4hooT4adWfvLVxiECFC9CVY8q9dLGT0dZPQc1iwcqtq2bjil+9Um6ac7BwV2XEkjVzVvGs9Ts/nd0qAEQ4j0XRcyLucp9J04UhzNUUZLzFe6zUmtH2CtO0PJv1PHujWWxnhSHmHUCYUlpFtgChjaFgJaXjr7So91aqYYU6eao+HG1JkEV1HJpKpejqA/sKmY4mGsiY4QUHKpXwjH1HMnZvzVYthRJnWKKOsCPPR+dRMdT5jcflQ96fUTW1LVpZKg4VKO2rXV/z6vXIooesHUmid1dbIHLMnj1dq1VPm5Lf4dDfmDhH0T9DSylRp31uMboDrrEnVUrLmULzBgX7HXR3VDRw7tF+2b1wjd97zkLrf6YmnVbkVdBFwPHHO5uXlv+/vJT8r0VeAeRZOpkf7PGNxzrXEZZNz1pyy/qZ//5YLZ0/b/dnm0Mr7nA0i6AieYG2E+cXa+sNVIGX+XGqG3crhcA68OuhJaXNfJ7eVBtoC5mzM7RgTU1OSVMo9xquU5AQ5ceSQVKhcVZ2XUONH1BnO4Nvb3CPN7mynnO1FcQDq59X8cbCg0COyIuGQ1hwrRKTYZTtVZm6++Wb5448/VJ00RMt69eolL7/8snTv3l0aNWokW7Zs8XjLMGzT7NmzpWnTpqpl2DfffKNquk1rvc2BSHd0dLQkJydLVJTr6qOLysajCUbe2O8+m6Xaavy88ZDTvwuRlsZVvUPEwHQBi/uIFmviRZeyc9WiDr1ykZpY2ASPhextNZ2/WMUgBK8qnAKOqKNj0Y1o5ZELF4tU73dL9VLKyIfBjQWmP4DFbM/2t6rWMcPGT3Xb95q21cI5h8UZFvp7tm9W9b+IaCPCnXYxRcpVqCLZ2ZlSIhyq7jlqgoMKL3rNI/I16OXXLYq/oJaumYPnJeqqYHRgPz3XtaMS8nv9w/lmI+14DSJx9erXlyU/fy8TRwxUSte9B78kLds/4LR2b6Zg8Ypouy09YY8c2CP//PGLMlx6DBhqWPDaCjJo4LSzBVyvX63YKH3ubSHdBzyvOjcUlZW/LVJOjhET3nb7ItPZVI1BnXV+uyFHxf3Q21jPxtUr5Yv3JqsUbZyjyLh58rkX5f7HnlRz2vxZ05XzHMBo7dJroHJioQUR2pkVtnDEdAEDubquLhDzxn/HEo3m0Eqliqvf9te+82pBifZpKCf4+Ke/jJx7eA32gx58HlrgwQlnzihCOc/hfXvkYmqyaruJiGnPu2+R+x/rJd36D3Fq9Buf/cjt9eTpEa+q0iBPULl0cbO92xENc0VvYkSonal4D8flthNJRRLGhLFzZN9u1cZ064Z/Zc2fS5Sonb1RP/1csOdMinLsm/Jin84qu2LCB/OkqGhrBleA/anVd3sCXLe4tlG6Yi/vThglv383X6Z9schiqrQ7wZj44lOd5a77uxi0EcyBsQkGd3Jigiz/+VvZsWmdEllEX3Y4vfE/Ou7YKwx5fcWr7SJddV0XNp54E7bajnZHurOzsw3GK6LK//zzj3Tq1EkOHjzoFUITjz/+uMTFxcmYMWPk7NmzykmwZMkSmwxuXwaRFVcol7s70l0YpucY7sMQ0owhRDRQl6cNNohAHLtSG2jOeHVGerk5NCEXR9uRwXNfo0y4VCwZJvvP5qsUF2V/5ffNDLVZzdqx78r3ZqNfqLNUvM2BiCMWk5+9+5YSjtLXA7kSU/ckJm4Y3IgWj3nuSbUwh4qqUgWW/Khtcclf6Gup0fc+2lPVLaPNyQu9H5H2Dz8u/V8YUyBKmetg+gbOeRg2AMrFyAZAhNtSajv2JVLLYZCMfq6vXFe7lrz/9lsyccQAaXjrZyqlFvXfzubdCSMlNDTMbJ9mU2rUuV7dnhz0ouE3vj1muLS57xGnlxgkXcqW0mXKyfAJbxvSyjWwqEfUFDXXxa4szC9cRMpklspQsQRaK+I4PNOlnYyeMsup24z6fNTCItLuDoo6FaCWX59iDm5t0UZFXdDmDNlacAQhegiQEYIUfUSa9u/arlpKtemYn8X23eezlDPj+TGTVe2yJXApocMEjtf1FaLU9x+LTy+Q6gxDAGUieD2i3PM+mCp3tLvXyOCuUy6igMGtjbM4P3CDKj8iuvq6flzfelX4y3mXlcGNtlSobUUbJ7TNcQY7/lunyoS0fegt6eWgWukS6lpBVMyZ4nHOinQbZa7VKC1bTiRZTInHfAeRsbCQQOWsg8Nfn4WCLAaMnbhh3McaTYtxzZ3xpjRu3somxW2UVxw8n6qCCxC7NAWRxJ2bN8iAl/Kj6kXFlet41HfXLR8pu055RrAYp0m1MuGSmJ5lUbsE6fXISsQaRp+K/szI1+TQ3p3yysDuynHSqWc/NbYj4AWHCoTeGtx8i2r/WqdBQ2XQupJFX34i2zeulSeeGVHo8URZS5UaooIC4MzJY2r7YLjj99S+vqG8POVDuzQ+cM5rmHMEIcvj+oaN7XaS+zt2hzHKli0r27dvN9wvXbq0LFu2TPbs2WP0uCdBKvmxY8eUKvn69esN6e/+DFJLIp0o3uHKCc1dYLCJiQhVUfrmtcoow9MUD3WlsRkI0NxQKUpqxDq2qNbPn1hwYjJxFXAwVIgurjzlEG9zJUjh7D1kpFK6RWQZi5gFH78rb48ZISN6d5JZb401pF/t3rbJ6enlmHAQ1QJIjcUi85Wps2xasGARNn3ezzJ07BTZtWWjitgV+C4HAwHxaVlqoQCBPNT6IloIdVhbFpkoQ3jiwXbyx2+/ydufLFB1YM7qF64H7eawWOjYpadd78O+xQ2RPKScj+7fVaWdo/7aGvb8BAgpIRUOomT66COcEoimYTyB+jhKXBANQknI7bVi5OaqJVVE3RwwKD/8bpnUrHeDjHr6MdUqyVlMGN5PCSK6i6IuyLHfzEUk8bnN294jg/83SYa/Ns2wYEV9KjIikH0BtWP04tVqVlEbitR/OLxef2Ggam1oDTijIOYEo/iQGWX/7Lw8Qz33mhW/q/Mf36dxY+VoqRZT+DiMWvJbqpeWRlVLqhR3c0A4DuPXrB9WSMmYWBWpRMcIZ4ASEWRU2KMh4WwsnSaYI5B1gjkZrUedhStSonGu3lgpuoDoK76q5XVlpHXdstK8dhn1W3C8W9aJlVbXxarfhxpm0yQhZGnASIPhvXfnFhndr6sSBbWFoxfSzRrcAJFLlBI01rUk9eb1HtYICACYQ3V8cGnLyvyuHE2qlVLGf4WSYeqGqC0eu7VGaXVcb61eWj2vBwbphPe/UCUw38z5QGVrAWRrwfGJGvV5H0xTY/Lyn/PLOk4cOWh4nTOB8xHt19CZwJFaeG18RSbbM6MmqlKz14b2LXQMNQcCW6ZaRnCS/jR/jiTGx9n9ef6OzWd3amp+S6R58+Ypw9u0lnrBggXy999/O38LiU3AixruonR4XzW69SAS3qhKyQKqnN6QnVEY2EakRyqhHzvRR/Ix2dxWs7QyHhCtgdgQJj/8j764MBqKMuFp3wVHQcNK0U5N9zMFqXSoF8K+2bVlg3z72YfKyDy4d4eq+9TSeBENe777fTK4a0dZvfw3Q5qqI+iNt4NxF1VUA8JfWCwPHPmaXa1aMNlBlAlq8fBCQ+QEabZaJAQtuhzp7alFuWE4vjP/V+n1XH50uLCsjHDdwhIqw0P6PC7LNuxSnmpEHuG11vqyFxWoAaPlFoyswsDCFedRg0pRKsqI/9Hv841ZX6lU8x/mfSxDut1ndXK3x3Hw0exZSqlaX3VVvUyJQq891ApisY3FGxZsWMjpwbmBbYYT5OcFc1XdclFByiAWdLe36SDuwhmZQRh3nAGMSpRNjHrrfdn0718yfmh+/bw1kDG05XiiWUcMIt2a0f3d57PlxltuM3R7QBmSvdsNBw3OBZRnmQNO4Bq1r5Opc79XkdBylZwj4BoQEKjqhz3bNcP683BY3VKtlNNEu1xUBZO/bjBxnuR3GQg0uy7SBGGR8YVjj9RwU3BcJr4/T1q2v185iz5/b3KRtrFJ89ZK+NRZnWvcsdyrfyUAgOOPMRNjJ/YZnBZ3Xhcrd9Quo4xec4ESZ/w2rIWqlC4hDSpGqxvSpPFdevFFXO/YhlplIwznaVTJ0jJ03BT5ddMRQ9QY2Wqj3nxPZsz/VX7acFC+/3e3oYRgwz8rZNBjHZSj1c5KXqt88+n7UrxECXnq+dFO6XIw9t05smPzennq/hYqe8oWtJ9zMrFgqv6GVX8qR1DztvlaCOQqNoe9WrZsqdK0K1e23NbhjjvusPXjiJO5/qbGUjMjX/DHn9PLiwK87BjYM3JyJeFKv1hXpZe7AkTbkCKpGVa2UMxKGqQ5MDGkZeUqoTrUxsOLaat6sD7agH2NKMGm48Z1k64A6UtQ4jYHhAXRR/z7z2fJ+OefUqnfWKRr7WDsQTPeUKqAmmnw1ewZqhcy+rqaA/u5aukSKg1Z0xvQz71azfTCT96Trz56R9X8QQ0ZQi+bjyWqCKqtbZAQfY/D96SlqXR2tDeyBJwrUWFBalEIh47pAh0LSjhnUEO4dtMBtWjYu32LvDH7qyKJ7CEV/68lP6m09cLE2mC41i0XadSmsFpMvl4CjKf+Q0dJi3b3ych+j6mab03AyhRblzoXM7JlwZxZUqf+jYb9gUV0jTK2/16txi26RLRamGt9fwF+7+BX31TOCxwfROiLUsuLGne8351pxM6YCmLCQ1SU014xI3PgOKHPd/lKVWXLulU2GZqW6kkx5qVcuqxSy5HyjtZPGigrcAQs7m+unK+IrQnI6fcDlNZ3n74sz73yhiFV+OjBfcrZ5Shob+d5Cj8OKAVD9hXaX3lzYADjL6LZe8+mqkwYZAXZAn4foqebjycV6OaAqCnmIQjtITqKNHNH1bsxrjizBMgdayKM6Y2rlVQ6COY64yC7AEYxbsfi01RmijPKEez9bfh+gHehRKUw8vtQlzbch2MdNdMoh0KG1/NjJxfZGYY1GspHOvca6LSyomat2sncX/+VMYN7qfHP1vUQ1qOm4xrYtOYvpVsD5X9ijM3+QYikIU0bgmR6tm7dKvfee6+tH0NcxMM9nnZZ/+RAV7mRPQS8rJrn0lVKna6iQcUou7y/9k4ymBCwqEAkok65SCXg0rBKtIQGF34OmJ4mMLxvrmI5xdJZWJvEsCBBvefUz36Qdxf8ptJRIWzmCNpS/aSufun1D7+UFya+U2AbECGBwQzDFccL+7Jh5ZIqDdFc5Aupprh+kS79zrgXVUQeKq//HU1U6bC2gDo1GDLoFz2g810WJ08IRt1RK0YaVS2l0qOt7T8sitve1kje/HihEjSDEjr6ajtK+sVUadryLunQqavV19WMDVcRCL3BrQFDGIshdAto3rSxfPTjSoPBbS6aYGuk+4+Vq+TUscNyb5cnDI/BYeLogh7RcUTJ9Gm02NdQOEYaX/+H2yixLkdZu3KpMri19lTuwBkLcowLZcKdmwWDemitR/mGVSuUqKG9oGYWrRsxZuCzNGcG5oqK0Y47RzQHpGn5Ac5jZF5BI0AD9aH/e6anEpNzBJSqFOX6dBa2niaIJiKS6O2GohrPq5RUkVhk3NgKxq+bLMyfGAt6PjNChox5S+o7WM+PLKSR/R5XNd3Owl2BCDglbWlFi5IOZA2UMEnzd+dvw7XryFsxNkPsFSKai7+dJ5/PLFpWg3bejJgw3dCq0FmgVO+dL39RaySsHeC8t8blK1Fuc9Pr1vWr5eamrm8B54vYbE3NnTtXevfuLS1atJDVq1fL/v375bHHHlNiaq5sL0Ns4+Sxww5P1NdKpFs/gSKdCYOoj9ncasC9qbJtRnD+64v+nRCmg8I7FCStYc6BoSI9VUq6pPcnjFdLnwtDH5FSKA1rRj+iRxM/+FLVOENZ9qOp4+1anGNywaIcUVZMSljgok7PtNUVnA8wtpBybArS1xA1qVchUh1DbZfhuD49/H8y/LW35bfvvpS5MyapxxHV/e9ogqF+3BqIcqOW+9dvvlAGg7lxGa2OYEibM2atZVjc366VvPXxQjl2aJ+8PKBboROytZRg9A611rcWRkjN2MIXtji3cB23aFhL7XP87jdeHFighMDWrL75X85Tx/KmpvniRjg+jkY49SnGKGsxNdwjo0tJg8ZNVW/V08eP2v25+I2IlqG9m70gy8HW8cMUZ42Xpun3llDHt04ZaVOvrLSuG6scLTDSUAJhDggEjXmul7z3xst2p3NC3A1vQfq//phg/HNUEFMD74fDNEbncMP5C/C4tl/RDhFpmbjGHKmv/OmrT6XXPc2cmsrqCPbsLQiGol4exiyOLRxuOO7Na8fInXVj5bZaMeo+yqAsjffuKoHDMdN3sLDVuITTxVzsAplOaEEF0TVHjjcEGjev+dupXSa8sZwQWQNYg+DcKAqOjl845pVLOe7cvOeR7ioDBVoORQHrlj8X/6jmeVPglMBY2fDKtYT1mr3lgtqa4dVne8rMiaOsvhZCc+aEeTH2DHr5DenYuXtBBfIKkcrRiGsZN6zhvPF8cyV2HZHx48fL8OHD5e6775YbbrhB1XmvXbtWfvnlF9dtIbGJEU8+LIvmf+qSvVXUBYc3AoMIg6gvpZdrwGAyFfmwhLN+HhYbaNnQ2EodnqXBE+l5jtSjFwaUY7EY029PyRLBapEG4TxESjGwm6utO3H4oKoH/mjqazZ/HyYTpJhhPYse0l3b3KwW+abgvCpMsA6vgfBOm7pljSLfmKiQagqhE23hjD97TqfI6gMXzKZyaeC5v37/SS3ezKVa41xwtN0TFsbtWt+hDG/0rLVH5VQDgnZr/vyjUIOgSiHOHXPCPE2qlpbYsuVUb1wI6hlTuAGSlpEpf/7+s0pV1haw1WPC7XJOWAJZI6hJ1wMnC45zyZgyMvV/Q21O6dPANqIHs+nCpjBgrN5eM0Za1C5jEICzJxPFWeMlxl/TjB1kBMAohWikVkuJCBMWvBhbcCyw+Ma5qAkdmdoauG6gZv7rwi+Usrm94HqeOXG0HNi9zfCYLdE4W8AxR7YL6sNByJVzC2OFFgUvU7a8qvE+dfyofDxtgt3fgbZrqEP3tFaJvd+PiDcimji2cLhhf2DewLyDzCvcx9iFWl/MQaZOI2/PWMMYcGOlkhZrz9FysvtdTVQKsj3s37lNAgIDVXTSWXjrcg/rUJwbmPMd9TEUZS1bp2yERX0GDaxFUFJmzjHz2FODDNmoG1f96ZC+DAQeJ730jJw5edzsb8P3lr1yLWG91qpOGeU0tzfogXahyMJCxNoSp5MuGam76699ZBcivVwDYzm2p3KpEqrEE9cybghAaNkjzhRW9GZsPnXPnTsnzz//vEycOFHq168vwcHBKvKNXtjE86SmJEtktGvUy/0t0q1RKzZcwl2c+uwqEH0pbAKw1rrFUUqHh8hNlUuaNeatTWhYuGqLTWcBAwCLdyzEkMYN1XSkb5vW3GHhhsf1iupo2zXwpfHyw7yPZNlP39j0fah114zeb+d8INXr1FW1pEbbFJCfkmzzbwgopiKhEOvSeLBbHyWshMlLb4xBWG37ySSzNf3oww5ht1++/kwJ65ir58bCFkaLo2DSbNasqVo8oCYZqY328N3cD2T+rLetLsjxlLkMAVuMyeFP95CeA4bI/A/fNlKM1XU2sUhq5mWZ9f0K1QYGYAFgKrpY1OsVYoV6UBuP0oSdm9fLj/M+tuvzoNhvr6EOB1STqqVUWrNKcw8NUvu6afXSRinO1nCmkxIZOygTwH7BQvrOOrGq5AEaA3gcBpg18BpzaadwRMB5MnvKeLNOMWtAbBEihE1btlP3lbiShai6I8B5gEgUIlDBQVf3JX6zZkjUqd9Qeg4cJkt/+kYunDtj82crVeztW6SehXpwOCmc+Vus4aoVA8ZyzEFwqmqOCpySvhAYgDFWp6x5p+d19RsqIbTp4160K/tq/65tqqWds0pMcA562mFTGDjucF45splF+WU4x7D2MedQx37TxiOsRRBxNtdaUMtKfeWZHmoutJfF38xTAo/Val1n0zodxxIBD6yR4My0NaqM8q8bGjeTGa+NtLtcBcE/jKN6g9vaWB4YUEw5CZrXilFBE3/HZqO7Ro0aqif3t99+K5s2bZLvv/9e+vfvL1OmTHHtFpIC7N69W/74+XvDfaSaZGdlSnik841ueMjMKXD6A4ic2GMgeRu1bBB4csVaBAtRc5F2a9EGDP41C1lEF0WJFAsaRBOsLnYrRRt5yRENvueRbjJ97AtKObwwDsflR7m3rFst2zaukZ4DRxRYoJSPKm53+mH+xBhZoC3cuxNGyXuvG6uT4vt3n0lWwmx6ziRnqPKSjIxLymg3BYt8Z2QbwEuNfQnj/rmuHW1W4UY6+vp/Vsid9zxo9XVIv9fSbu0F4jvvTn5dyleuolrHaZGE1Ixsgyq1JeJSM5TivdbzvWxkqNPT3rD/TRcVEFDq8/xoo6iALaDud+YE6+l/+usViy5EFswZJxgHYQjCGC8MZ+4SLWMHegdYSDtiOGlpp6b10s+OniARUVEyf9Z0uz4PvcIhjKilgboiQwcRXOiKaJFugDGjaumr1//9jz8p0z770dCFwRbQ4gxZLpZEtWCswigoaoquLbg6gwzXJsZynD++lJ4Kw8ycszwwKEipYh/Zv1t++36+zZ+3b+dWue6GfIV9W8Baztp17u0GtwachfUqRLn9vMS5htIxreUZPg6lMi1qx6pzUW+Q147NH++RlaE/R+EQ7zV4pHzx/lRZNP8Tu7pVbN3wr9z36BPmf5uV6wBzKhx7CEyYtsAz/1kBqhYdXUFsnWc0xx80ZXZv3WgY16rZuMYODQpUwoNwWmC/+ZmUlAGbf9acOXNky5Ytct9996n799xzj6xcuVKmT58ugwYNcuU2EhOWLl0qb4weZhTlBs7u040BBdEtW9WTfRFfmWTMgagFanQ9sfhBmpBp5K6wxQ8MY1sGfFcdO0xKWpqi9v4hr76l6p8P7dlZ6PsRScakghYvdW+4WaVQFTU1Wg8mRW0yx4SDlEGkyf79x89Gr4MtufNUsqqpAlqdOXrAQlTsttZ3G70euwl1o/Y6A8yBsQBeayg7Hz2wR9W/2sK6v5cp52CrDg8UWgNdFEpGhsvsjz6S6FKl5NKVFmfYX/vOplpMa4+Li5O7m90oOzetNzwWW8TtMAfON5Q8mF4n3foNsUuBHAuhw/t3yw1NmhX6WhxzRJQLu+7wOhhkhb3OG8dLrV5a3/sXCsKTP/1Whrz6ps2fg4jO7q3/SdOWbfM/o3iwUQshZ4Kx0LR0AeOplgaKaDtaEuGctbVV34kjByQ4JFSub3hVdd3cXIAUXWs9xJ2Bu04TGLGNqpQSXwIOF3OptJhT0GIJY6qtNfl9nh8l91swwkyNbTjWIIwKJxUcvOaOvy+V2yF7Tp8hZgvO8M9grESkHQYiSnQwpptzZGBc0vq3Q49CnznVvf/z0vnJAfLhW2NtFsGDEFtkVElpeXe+DWaKLSUWmpPSlnau0F8ZOnay3HxbC7scA/Hnz8pNTfM7WeE8s8eZWuxKdx3stzuvK2uz9odfGt1duxZUm23cuLGsWbNG/vzzT2dvF7FCeHi4ai2iRXKgCAxPaYQTI91Y9MPjZBpBIN6F1tLCEq6cQ00jd4VN2BhQTQ31ouDoBAqHARS8AWqTx7/3uXTtZ5sSaEZ6ukSVLCW9nnupgAGCyaIo6dvghorRypESEx4qT/Tpq3q5wtOclppSoO3Rf8cS5MiFNKVwnpiQIAf37FDbpBfVwSYiOu1IyrYlcAxvurmRSoH//P0pcu70iULfA8dBvRsbFUjHN6W0lWwFW+nYrq18+8MiiYy+GglB27oTCebF6D6b95VqZVa5Ri3DPnN2f1gNGLXmskSQCQBl+HV/LS30M7Zt+Ff9taXFEKKattalY9sgemhNfMdbg4pavbR+MYlzDcbr4X275fyZU4V+RlZGhhK1uqVFG3W/jA3lO84E0SjTNMyJI/rLtFevOtit0ezOu2XR+v1qfDKHPnIE59ZtNWKMSm58FXelzDsLGG2IgpoDWUpIF8c8Y2urp8LahSH6CiMGtb4ABiIcvNB2gCEOZ5U2lXl7bbwpyBCzpczOFU5DzBG2BqTwvfXKRxrKeDThVDjIvvvsQ5s+A/MnupxgTDOHrRkfWjtQRL31wo7mQCvWezp1E1vZtOZvCQoKVi1ZMZ9ULIL9EKicqdFO6W7gTRQ5gF+9enVleBP3Gt0AfV4BaoF+33pCqeE6C/SmdeZCnbgG1IpaE+1yZWQKn329zmtvy6CP1juOKic70yuP/s/afoORisjCVx/NkJ++mmP1fUg7hfr2rVeiYXqcUaqg1Y1BNRsLo2dHTVDX+awp48xG3g+dv6jETH7/fr4M6XafUQcDLLKhmguhMecf90jpO/RliYiMkjdefLbQOsRGzVrII08OsPoabK+zSlkQBTm1Y628/8YrhscOXbiosgJMmTfvC9XGrGTpMoY0XEdT3G0BEQ/U1+sJK1FCMi6ly/zZ7xQa5UJ5A6IQEN2yBs5v9IG2B7zn1uqlLB4Hb0/lhYNJP76g/OHVQU/IbDPXj7mWOYNefl2JsTkj68LRc0O/j2+5o43qQY92fYWB8wYq2LaOl1orM1fUUfqY7eYRZ7m5/d7othbyytRZNqlcb177jyrzscU5bu66xTgOQxzOKqjH47rx8svbLNeXzy95sgVP/j6thSocoZjroIsy7t058vLUWTa9/857HjJbOmb4fDsvOpTjQUMDTmBrb4V2yOTRg+WPH7+2yehGhg76h8MB6oz1Z40y4U4Ts/QGnLKyKFXKt9J7/MXoxiJNAye3tRMcA7ytCoaIdPhyrfO1hqW2Ru6oicEiXUvXtsVOwcRTpQitN4w+qwgDujJuq1xNC8O1kxR/QWa9NVaJ05gDrTr+XfG7xf3grOgoIpNY8CvV6zo1lCEA49aS2ikmRSy+Wnd8SKWY6x1nWnTD2WDbGtaqJKMnfyiVq9dUteTWQP18m3sftvqaqDDUcTlvVRSUc0mJuqCfNUAP863HkyQn9+p+XPffZtmxdbO0e6CL4TEtC8KVwGmhT+XG+YeUw73bN8sWK4qxAFHbRre1tGlccGTRg+gNImPmspycLczobOAs0Sv0Y2H7xKAXlOF6YPd2qwbrb9/Nl+TEeHUfBoirUssL2359mvzdDz4qseUrqf7d1kAmTOfm1ytVZEuYi2Jq0SRn67Z4YxmCtwEtA0ttoVb8+n2hLcTwmt9/+KpQ496WVGI475vWsF1Q0ZvAOGqrToGnz0usN1Deoek3wNELRxnGps3rVlmc3z+Y9KocP3zA6mc76hBVAnA1Slt0vqGNWL5DeHqhGi5t7u0knZ7or/6PcWK2WGQRMwi9CT8tVfdvypcvLw2bNDUswtGG59nH2ltUE8agBI8WFAJtoVLJMK+PaJCrIJpl1pPtpgUyvJAYuG01ghHNcYZDoKjzJ4wLtJ/R9h36aELQatyQp1T/Uz1JCRdU30rUJpujootqj64rHyH3PdpDBrw4zhCRNwVtss6dPikP9ehrtG9ctU16D/TtzZvLi6/PkPAIy63IlvzwlRzZX3ikzpoQniOgJKp9+w7y/uujDX3F07NyZdvJJBXxhhr8rDlfSrmKlaV523vU8zgvkdrvibZ/SGuu06ChfFWI+NekjxbIMyNfKzSFtSilQZpQ1fUV0dP96oXmC+I2yCLQp5ze/cCjKhts7ruW67vRsmn62BFy9OA+dd+TWV76qA6cBp169pU/f/1B4uPOWd3+1JQkKV/ZcvmGJYcW1geo57e3PtYaXD0UDpw65q5RlAtO+98wWbrIelcNOIeva3CzxefhOEKHFluBkBWueV8EQSJb0sy9ZVmL7dXX9UPwccrLQ+TiFX0mPauXL5Yfv/xYnRfWKEpyFhzeaN+FOQnnpGmNevcBw5RQ45+Lf7D6OW3v6yTN23bI/0wfdOC4Ax+YQokpzZo1k0+++11iYsup++fPnJSj+/eqCdq8GFq+wqctrb+wwNKrqBLvBwt4s1EpN04wGKxtjapiQIdnvag4IyqK9mKYbDABor573LtzJTwyUl4e0EMunDqqXnNwz04Z0auTBAQEqpRqc7gqFRULIS0zAO1CRvV73CjDBWndX7w/RZrd2U4J8WjgfMB73VFHi32Hnsg/fPFRgdfAUHj3tVGyxYIXX48zPePa9s2a9aEkJyXIZzPfMjyemJYtaw7Gq77nPQa9JDO+WmwYO2Fwu8vhCMNOL66D7e0xYJhSJLZUgwwxOgANDw3TKCUyldB/2xkp8jAAkRKpLcJ8RWgJwmpabTr2Va/nXlRRYEt9Z1ct/UVKxcSqNjlaiYGngPNJL3p4b5eeUq5SFTlhJdK1a8sGJR5XuXq+LoEphTlLMJaiPva2WjHS8rp8pXvTRTOuc1sU7n3pPPE0WqqxHkQ/W9x9n/z6zRcWS02g6XP80H7VaszSOg5js616Dr4Oxk6USpi2DzT3Om8A11ENXRAMZWQ4pq8801P91Ue5v3hvitzaoo3FVoDOuuZUFmLp/PaN6J2NjhdalkTt629QjmmUP1kqJUPwT8u0wXFwZYmWL8O94qPgYtT6tMI7FhEVXWBAwYUN5UTNILDlIkCUwNaJlXgP5soB3D3BmPbHtkb1MuFFdgoUc6IQjyZsU7ZCJflw3rfyZM9u8kDzG+TssQMyoncnCQoOkbe/WGSo+9WD68We324vUESHIVijbn3VimPskD6q16eWiggV9d6DRxktuFAP7rbUvjLhcuLoIflk+uty4shBo+d/+Hy2BIeGqr6f1sC54ArPOFpd/u/VsfLfvysNBivAYhaqsbhGNOclcLdwJNLM9b/79jYdZP7yTeo8NMcbLz4jE4bn9xIHWLAjSglxO+xDKBJDmdqZ5yOMQPRQxdzgK8YUHE5QidY2t2X7B+SJZ0dIzboNCrwW8yiyRVq0u1elUsK49KTRDfQp5uGRUTJ38b9WhfOgul7/5lssjvm2zgU4b7Dv0GMY6cboN4zzCbXyEN7CYhzZD8Q5INvK3FiNlnGnjh2WrevzRRNNObR3l8p0tNQuDLogniiP8CRY3yJzzZrGjbdEurU1W8QVh2nZipVl0kdfy+F9O+XNkYOUYx1aLp+9+6ZKK39y0IuFfp6zncWY2yG4pqXu93xmuBJN3btji9nXfzV7uiz7+Vv1P6PclqF15YMcPXpUbq9d1qBiq4xuXS2nRrOapY0MaFtqut1Rz0icDyYaUyVKb5pgzC3uTMWk7MWZBgDqX9ECBBH71o2vl6lTpijthOsrx8jDXR6XGV8ukmq1rjP7Xm3idBVYBMMYrH9TExnzzhzZvWWD9H2gpfz45SdKsASp5/BEaxMvfoMz2oPZCiLxzw5/SRmK014dbih7SYg7r6I1D3btrQyHwiZ4V0WYR744Qhb89reR6iv23bAnHlSK7xoYK13RKswaMIZg0GjRLpQQQH0aNbpxZ08bvRYRkP/+/Uuua3B1oR0YEKAiFKgPhYMVhhFSBZ0NImYQW3Jmyz9XgygNojY4r7BfsXDFvtWc1Rrr/16u9nXHLj0MYo+ejtKgT7zpeXLh3BllXJuC37Nn2yZpcPOtFj/PUVVqjCMxVzIytDEF2Q8Nq0Sr/YtxqbKZNonePPd4GzC+TLNVbmxymxJL/PWbz82+B+U8HTv3kGq16hZ4Dtoiruq+4O3gHEUbL9Qom4t6e5PTEOM2slA1rm/YWF6eMluJJqYkJapWgdCZQPZTYVFu4Kr5U2sxeFOjRrJgxRZp0KjgOAP9AZQ7NG7eSt2nCLNlaHT7gZAaarlMe3TDW2+aXhpcSI4ZJlFXLNiIZ9qHebvoEWqCizIHOnOOwaIWCxXsQ73B2uTG62X+3I/ljust10q6MsqtX5hhXyHN7NtVu+Sp50fLmhW/G6mV43m0gHG2Wrkti4dba5WXl16frtJcP53+uookQzE6JCxMHu3zTKGfERnqunEnKChIalUoJaePH1WR4nHPPyUfvvmqdOk9UGpff6PhdSqS6wFrAedP3fLGTomRTz8mM157ySi9FG3XEK2HYJ5GsG574TTwlvRJbwHHFOUjmsMZ2Q29O96mWsTpVctxLtS5kqpbThdl9pYUc/DR1NfkrdGDCwgqIjo/Z/G/ck9ny619nG1soDwIUTA4NeqVjyroQOVpaDO4ZrEv9X2z8RjaUt7Wur3Z90B7ZPhr01RJlCnudhx6I4jyN6xSskCnFG8bHnGdI+tPA1lrc35ZrRzYKHf5ctlG1SbMFlxZFgXHG8oVypQtq7SjTMuf1v+zQs1VTW6/U91H21NiHhrdPmx0a7UfaCOgTy8FoWY89dYi3XjOVgVI4p3Au6hPrfL2aAO2tSjpvO40MKz1LnaH0Y19pWWhhBUvIY/3fU6mzP3eSK0cQomeaHOktik4UPp07ijPjhovOzevl+ysTOnz/CgZO/1TVWtaGK5OhcRCNP1ikhw7tF/OnjwuTw19Wfq/MNboNe7uy6wH0UNEE3A9wDfatd8QFYH97dsv1fNQjf3m0/dVq7pyFasY3net1GwWtXwEWSy4hqrXrqvmzQnD+sn50ydVmQYiTMgWAYiOeUtabgUTIUR0ADh9/IhZfQS0jzNX+uKuuQA19HohK293+HobGD9vqVbaKOLdqsMDSr3eXGbDX78vMiu6hXWc6XlzrYJ5Gcr8emPUmyLd+pZuSIvXYmJ6bSZkstmKq7VIsD/h1H/9hQHy5qhBhsdhbP+68HNV/hJbvqJy/rpaT8aX4YztgxQvnt8KJiM9P9INASX0dyzMSLBmdCO91p9k+a9V6pTT1Yd53/xSANSzOTpZuNOpEGzl2inlZNVtS1SPCTdSPNWDKEn1GM+2+cP4MXX8K7Jk2Z9SOTZayleqKjc0yRemKgxXe8YRwb6rZXOZ/cMKmfX9cunWb4iR0wbGlqfreOEwQeSwUZVS0rrDfaqu84M3X1XphqeOH1HGYp8ho43eY2sbyGsdnJu31Swt11UtLxM+mCcnjx6SHnffIs89fo9BGAiL3vyetd6xT+GI0SenoWa75nX15Zu5Hxi9btJLz8rPC+Za/SxXZ3CoHsSVS0q9CpEqY4jdT+wn5IoAIiKfcL5hTMe1P2/mJKPr/NDenfL6CwPl6AHjDhtatqKnSyO8CYzpyHTRsgi85NI2u52VSto/f2M9gN+G9b47um5gjnq2Xx/Z8d86Wf/PcoPR3brjw2pOBc5uP+hv8Or0QbAoQLRLi3QjGrL9v7VGrwkxM/BaSy93l+FAXB/t1iKivuBthIe/QaUoh2pF3em1Nnc9AWy3u+pcsa80wTc9qOWHmJY3RD2xL6qUiVRKshBjsgWkALrD4YfSAUunTOVSeM47VmQwWtAn+6Vxb0jFqtVV73joCcz7Y4Ohdl/Dlo4UxLh+/qlO7WXeb6tk2LipMvh/kwxK8Ej19FSmiKXrXb8Qx/ZDzGjzmr8N8z1EltDGJzSsuMfHShjeuI6QVeBpB5avgjkbkU843zCmp8Sfky9mzZCACwcNYxcyHcKKF5e6NzYq8H53GF6+mumCdZE3Rro1ykeFWeyVbYnKJYurMj0Ezdzl6Or2WBe5u30HGf98X1VCBqdlp55PS+Pb8+u5vSVTyFuhS8JH+WrJKgkMy6/jRtP6dg88Kg1vud3wvDlvJyZFXJi5ecZtKDAO8ULxH66vEKUWPb5yTFEfWLJ4iKw7HC9ZOcb1itZw5wSKBS+iDTm5xteOqXidOwzHcykZkpSeraIa2Ka65SK9wuA23V9oO4Tz8HxKplzMzJGUS9lmX+uM9nG2GjFwSsWlZho9Dl+kt6VkIpWvZb1K8sGcr2Tdpny1WHMtIYN8oXG2l4E08w631pXbGtRU82FaZq5k5+W5VXzQVrCgPp10yTBn39HuXpUBgSwS8O3cD6R0bDlpc18nq5/jZcMDsQGs4Z7s8qDMGF9VPnxvpoye8qEaS/9d8bvc3Kyl2Xpue422a8mZgXWRtzsHEJXffSZFzqdmiIl0g1kqlCyu5oo8kzW9q+f2X37+SZ7oP1h+/2GB3HV/ZyNtlDImIpDEGBrdPkqlKtUkOT1bp15uLKQWEmTeIMEi3dToRtsKb1u0k6JRVGVwT6TWIQq181RyAcPWEsXcfMoi2p1jonzsicgCoiBYfNkaSfYkMHJxQwra+dRMtd1ZuXmSmJZleI07hasQETA1unEMvTUls2OLRnJbowbKaZGRnSsnE/MNMM15aq3sgVhfhJeNyjeyY9zTXc/hcRHK4ScS8kvJoML+/JjJ6v/N61apFj0QVQwJsX4NeUsWB7GP2Kji8tJLL8mQwYNl4LCRcuxcqlKqH/2WcYmBViLjjY4jYjsIjGF+j78YJttPJhvW6vCt4hrO1a2NoMGk6cm4WwA0NDRU/vf6ZOk/ckKBc5BizNbxzpUGKZRP350qP8z7WKV2oLVARKSJermFCIi5xaWvRESJfwPjDG2PbPWUujtVzLR/Pb6+lAciC1hY+YLBrQcLBjiC0HYKqX6aUwi/BWm97gLpw6bifTDEvRlNVR9twbD/4JxCv2SkobI1i/9jqY3nT/M/VbWUjzzRv9DPcLRlGPE8T/ftKxUrVpQP3n5LCVS2aHeftGh/X4HXuXMcJa6fp1rXjVXZbCjZurFSSaWZoDlVcDl7ur0vts2Usj4W7PEEjHT7KDu2bJRigcHS7oHO6n6EacswC5OsuRrAcF2rCkI8SeCV3pV7rrRKys69bDEt2d3lrDBy/juaaJSmygwRx7i+QqRk5eZ6RLwRkQT0Fo9Py5TQK32IfQW9ka1vNUP8F0SzoooHFxgHx8/8zOJ7MDbBSahllHhzLSuxTlhYmHzzzTdSvXp1OXopRGrP+NTs68pE0uj2x1ZySB3XItkQg/zvWKIUDw70uGYPWpMiK3Hf2VTDY0XpRnOt4BOR7qNHj0rfvn2lRo0aSrm7Vq1aMnbsWMnKyjJ6DU5S09u6devEH0GrIKSVo2dny/b3S4XK1Yyet1TqZy7SjfRyQrwFeHMbVS0lN1cpqVpUIPJ9S/VSSlkY1Cobocok3L2QzBdaurqwoViQ48BZ0aRaaalTNsJj9XM1YyOUQjQh3k71MiUsKtVDj0C/2MXcf1MV9M+OlBqx4coALxftO44lUpDmzZuraLelsjF3qVcT96NPHce8idaS6BLgDSADC3MpgIq6O9qn+jo+sYf27t2rjMvZs2dL7dq1ZefOndKvXz9JS0uTqVOnGr12+fLl0qBBA8P9mJgY8UciI6PkYOpe1ZtzzPRPbBbYMTdxow6DEK9U6Q8OVMa3ZvTiXEVk0lPnLBY28RfznX1M7S06rDUlpHAgNhhcOUC2nEhUCuGaUnHJ4sGGTA0kB0FksWrpcIMjHS0ZcSP+AbrMHJH8rjV64Dxkm7ZrA09HuE2pEB2m9KXKUkDNf4zue+65R900atasKfv27ZMPP/ywgNENI7t8+fLi7yCd/GJKkqSlpqjWYTFlyxstYG2NdGOgRqoKIb6AtsCExx/iXO5G8+oiddMT9dyEkGsT1Pa3qB1bQFtCA/X+5VJCmYHjx0B/B2s7U2VrqpYTT1ExurgkpmUrZyDxk/RycyQnJ0vp0qULPP7ggw9K2bJlpUWLFvLzzz8X+jmZmZmSkpJidPMFbr/zLunS+xlZ+fsi6dGuicoEcKSmG2II7lY+JMRXo6RRYajjLiYVS4YxSksIcSuWDG69kBF1JvwXBElMhW/Z8pV4EtgPcPhROd+Pje6DBw/KzJkzZcCAAYbHIiIiZNq0afLtt9/K4sWLldH98MMPF2p4T5o0SaKjow23KlWqiC/QqOnt8nCPvpJ4IU6iS8VIYKBxtNpSqpFppJspsoTYZ+jDo4taJkIIIcSdmK7ZkAHhrS0PCSHGePRKHTVqlFnxM/0N9dx6Tp06pVLNH330UVXXrVGmTBkZPny4NGvWTG699VZ58803pWfPnjJlyhSr2zB69GgVNdduJ06cEF8gJTlJVi39VU6fOCKlYmILPG8peh1q4ilnWhIh9quYe1tdFSGEEP/HtDUYamoJIb6BR2u6R4wYIb1797b6GtRva5w+fVratGmjlBw/+uijQj8fBviyZcsKbfKOm69x9tRJeW3Y0xJbvpJUqVm7wPOW0svR808D6SBMCSGEEEII8X5Q4hQYWExyc9FKitmKhPgSHjW6Y2Nj1c0WEOGGwd2kSROZO3euBFhSCtOxdetWqVChgvgj5StVVn/jzp6SJs1bFXjeUnq5XjQtqrhP6OgRQgghhFzzIAO0dIkQiUvNVL2SmVpOiO/gE1YXDO7WrVtLtWrVlFp5XFyc4TlNqfzzzz+XkJAQadSokbr/ww8/yJw5c+STTwq20/IHIqOipXiJcHli0AvyYNeC2QKWehhDZAViLIh4R4ZRfZkQQgghxFdA946LmTmq1IkQ4jv4hNGNFHGIp+FWuXJ+hFdD3zZowoQJcuzYMQkKCpJ69erJwoULpUuXLuKv3s7ylavKzk3r5dHezxR43lrPxpsql5Tcy5fZn5sQQgghxIcoHx2mMhUZ5SbEtyh22RPNbr0YtAyDijlE1aKiosRb2Xg0QRbO/0LmznhTPvttjYp662lXv5zHto0QQgghhBBC/J0UG21Hn4h0E/Pc06mbtL3vEQkJCbU5yk0IIYQQQgghxH2wuZ+PY2pwA6YcEUIIIYQQQoh3QKPbDwkOZKSbEEIIIYQQQrwBGt1+SHAQDyshhBBCCCGEeAO0zvyQkEAeVkIIIYQQQgjxBmid+SGs6SaEEEIIIYQQ74BGtx/Cmm5CCCGEEEII8Q5odPshjHQTQgghhBBCiHdAo9sPCaJ6OSGEEEIIIYR4BTS6/ZDAALYMI4QQQgghhBBvgEa3HxIUwMNKCCGEEEIIId4ArTM/hJFuQgghhBBCCPEOaHT7ITS6CSGEEEIIIcQ7oNHthwSxppsQQgghhBBCvAIa3X4II92EEEIIIYQQ4h3Q6PZDGOkmhBBCCCGEEO+ARrePYimDHFHuYsXYMowQQgghhBBCvAEa3T5KoIW2YAGs5yaEEEIIIYQQr4FGt5+lkDO1nBBCCCGEEEK8BxrdPkpQoHmjOySIh5QQQgghhBBCvAVaaD6KpYh2SCAPKSGEEEIIIYR4C7TQfJQgCzXdocE8pIQQQgghhBDiLfiMhVa9enWlyq2/vfnmm0av2b59u7Rs2VLCwsKkSpUqMnnyZLnWenGHBgW6fVsIIYQQQgghhJgnSHyI1157Tfr162e4HxkZafg/JSVF2rdvL+3atZNZs2bJjh075KmnnpKSJUtK//79xd9gTTchhBBCCCGEeD8+ZXTDyC5fvrzZ5+bPny9ZWVkyZ84cCQkJkQYNGsjWrVvl7bff9kuj23Kk22eSFwghhBBCCCHE7/EpCw3p5DExMdKoUSOZMmWK5OTkGJ5bu3attGrVShncGh06dJB9+/ZJYmKi+BvBZmq6I8KCpHgw08sJIYQQQgghxFvwmUj3kCFDpHHjxlK6dGlZs2aNjB49Ws6cOaMi2eDs2bNSo0YNo/eUK1fO8FypUqXMfm5mZqa66dPUfTG9HDZ4qRIhNLoJIYQQQgghxIvwaKR71KhRBcTRTG979+5Vrx0+fLi0bt1aGjZsKAMHDpRp06bJzJkzjQxmR5g0aZJER0cbbhBg8wWCTVqDhQUFSqkSwRJgIe2cEEIIIYQQQsg1FukeMWKE9O7d2+pratasafbxZs2aqfTyo0ePSt26dVWt97lz54xeo923VAcOEDGHQa+PdPuC4W3apzssJFBKhV9NrSeEEEIIIYQQco0b3bGxsermCBBJCwgIkLJly6r7t99+u7zyyiuSnZ0twcHB6rFly5Ypg9xSajkIDQ1VN18jKDBAihUTuXw5/35UWHCB6DchhBBCCCGEEM/iE1YaRNLeeecd2bZtmxw+fFgplQ8bNkx69uxpMKi7d++uRNT69u0ru3btkoULF8qMGTOMotj+Bgxvjcqlint0WwghhBBCCCGE+KiQGiLRX3/9tYwbN07VcEMwDUa33qBGPfbSpUtl0KBB0qRJEylTpoyMGTPGL9uFaQQHFJPsK/+zVRghhBBCCCGEeB/FLl/WEpSJVtMNAz45OVmioqK8eqdsPJogyenZSsm8dd38NHtCCCGEEEIIId5jO/pEejmxLqYWwlpuQgghhBBCCPFKaHT7MEFozo008yAeRkIIIYQQQgjxRmit+TCBVyLdVC0nhBBCCCGEEO+ERrcPg1puEHzlLyGEEEIIIYQQ74JGtx9EulnTTQghhBBCCCHeCY1uHyb4Sk23vl83IYQQQgghhBDvgdaaDxN4Ja08hEJqhBBCCCGEEOKV0Oj2YQKLsaabEEIIIYQQQrwZGt1+IKTGmm5CCCGEEEII8U5odPswQWwZRgghhBBCCCFeDY1uH4Z9ugkhhBBCCCHEu6HR7cMEBQQIyrrZp5sQQgghhBBCvBMa3T5e041od7ErgmqEEEIIIYQQQrwLGt0+XtNNETVCCCGEEEII8V5odPswiHCHBgd6ejMIIYQQQgghhFiARrePU5xGNyGEEEIIIYR4LTS6fZziIYx0E0IIIYQQQoi3QqPbxylBo5sQQgghhBBCvBYa3T5OGNPLCSGEEEIIIcRrodHt47CmmxBCCCGEEEK8FxrdPk5IEA8hIYQQQgghhHgrtNgIIYQQQgghhJBr2ej+66+/VE9qc7eNGzeq1xw9etTs8+vWrfP05hNCCCGEEEIIuUYJEh+gefPmcubMGaPHXn31VVmxYoXccsstRo8vX75cGjRoYLgfExPjtu0khBBCCCGEEEJ8zugOCQmR8uXLG+5nZ2fLTz/9JIMHD1bRbD0wsvWvJYQQQgghhBBCPIVPpJeb8vPPP0t8fLz06dOnwHMPPviglC1bVlq0aKFeRwghhBBCCCGEeAqfiHSb8umnn0qHDh2kcuXKhsciIiJk2rRpcscdd0hAQIB8//338vDDD8uiRYuUIW6JzMxMddNISUlx+fYTQgghhBBCCLk2KHb58uXLnvryUaNGyVtvvWX1NXv27JF69eoZ7p88eVKqVasm33zzjXTu3Nnqe5988kk5cuSIrFq1yuJrxo0bJ+PHjy/weHJyskRFRdn0OwghhBBCCCGEXFukpKRIdHR0obajR43uuLg4lSZujZo1a6qabo0JEybIzJkz5dSpUxIcHGz1ve+//75MnDixgAibtUg3dljVqlXlxIkTNLoJIYQQQgghhFg0uqtUqSJJSUnK+PbK9PLY2Fh1sxX4B+bOnasi2IUZ3GDr1q1SoUIFq68JDQ1VN9P0cuw8QgghhBBCCCHEGqmpqd5rdNvLn3/+qdLFn3766QLPff755yoi3qhRI3X/hx9+kDlz5sgnn3xi13dUrFhRRbkjIyMLKKN7m0eF0Xjfg8fON+Fx81147HwTHjffhcfON+Fx81147DwLgsIwuGFDWiPI1wTU0LNbX+OtB6nnx44dk6CgIPWahQsXSpcuXez6Doiw6QXavBnUDbDu3DfhsfNNeNx8Fx4734THzXfhsfNNeNx8Fx47z2Etwu2TRvdXX31l8blevXqpGyGEEEIIIYQQ4i34ZJ9uQgghhBBCCCHEF6DR7YNA+G3s2LFGAnDEN+Cx80143HwXHjvfhMfNd+Gx80143HwXHjvfwKMtwwghhBBCCCGEEH+GkW5CCCGEEEIIIcRF0OgmhBBCCCGEEEJcBI1uQgghhBBCCCHERdDoJoQQQgghhBBCXASNbkIIIYQQQgghxEXQ6CaEEEIIIYQQQlwEjW5CCCGEEEIIIcRF0OgmhBBCCCGEEEJcBI1uQgghhBBCCCHERdDoJoQQQgghhBBCXASNbkIIIYQQQgghxEUEueqDfZXLly9LamqqpzeDEEIIIYQQQogPEBkZKcWKFbP4PI1uE1JSUqRkyZKuPi6EEEIIIYQQQvyApKQkiY6Otvg8jW4LnDhxQqKiolx1XAghhBBCCCGE+HjAtkqVKoW+jka3CVpaAAxuGt2EEEIIIYQQQqxhLbUcUEiNEEIIIYQQQghxETS6CSGEEEIIIYQQF8H0ckIIIYQQQohXk5ubK9nZ2Z7eDHKNEhwcLIGBgQ6/n0Y3IYQQQgghxGu5ePGinDx5UrX2JcRTNduVK1eWiIgIh95Po5sQQgghhBDitRFuGNwlSpSQ2NjYQgWrCHE2cPbExcWp87BOnToORbxpdBNCCCGEEEK8EqSUw+iBwV28eHFPbw65RomNjZWjR4+q89ERo5tCan5CXGqmpzeBEEIIIYQQl8AIN/Hl849Gt59wOumSpzeBEEIIIYQQv2fJkiVyyy23SMOGDeW2226Tbdu2GZ5r3bq11KhRQ26++WZ1mz59uuG5AQMGyI033iht27aV5ORk9Rii+B07dpRDhw5Z/c6FCxeq76xbt640adJEHnjgAdmxY4d6rnr16rJ161az70tPT1fvS01NVffvvfde2bdvX6G/cdGiRbJu3TrxhHGblJRU6OvGjRsnGRkZhvtjxoyR+fPnF+m733vvPXnjjTfEFTC93A/Iyc2TjOxcT28GIYQQQgghLmf57nMu+dx29csV+prExETp0aOH/PPPP9KgQQNZtWqVur9z507Da2BoP/zww0bvw/MHDhxQhvJrr70m8+bNk+eee04++eQTadOmjdSqVcvid86dO1cmTZqkDOH69eurxzZt2iSnT59WRnxhhuRDDz0kkZGR6v5vv/0mtoDvgtMATgVH6vCLovRtC+PHj5ehQ4dKWFiYuo99WlT69+8v119/vQwaNEiio6PFmTDS7Qfk5F2WzJw8T28GIYQQQgghfg0i0jExMcrgBi1btpTjx4/L5s2bC205lZmZKXl5eZKWliYhISFy5swZWbBggQwfPtzqe8eOHSvvvPOOweAGiHZ36NCh0O2dPXu2dO/e3XBfHxVHVP6FF15QvwFG/8CBAw2G+c8//yxTpkxRhjccAwCOgmbNmknjxo2lVatWhgj/Z599phwHnTt3Vk6ADRs2qM8ePHiw3HrrrVK7dm0ZMWKEQX3+4MGD0q5dO5UpgM+HgW8ObBvej9fg+7QIvbad2G48d/78eendu7faR5ra/VNPPSU33HCDusFA17D0mwGOSfv27eWrr74SZ0Oj2w/Izbss2bl5bKNACCGEEEKIC4F6dXx8vKxZs0bdh3GK1G2IbGmMGjVKGZ+PP/64HD58WD2GtHAYpjBY8VjPnj1l2LBhyrANCrKcfAyD8sSJE3L77bfbva14H9LYrUXR4URYuXKlisT/8ccfsnbtWpWC/uCDD8qLL76oDPSnn35a/v33X+UgQIQfDobXX3/dyJhfv369Ss1GJF/b1t27d6v9tH37dvn777/V+wEyAx599FH1+Lfffit9+/aVY8eOFdi2kSNHysaNG9U2PPvss/L888+rx2fNmqX+IssAz5UtW9bofRMmTFAODnw+tgtGPdLzrf1mDWz7ihUrxNkwvdxPIt1wHCHaHRbs2lQOQgghhBBCrlWQdvzdd9/J6NGjVUQVRhoi0JrhjGhwlSpVVDDs/fffl/vvv18Zn2DixInqBn766Sf1OkSe+/TpIykpKfLYY48pQ91ZoMVVuXLWU+bxfdh23BA1hkFqzsDH9iKyjUi3RkJCgly6lK8r1bx5c+VY0PPkk0+qCH9wcLByMixfvlzVosNohxGvOTFatGihDOhq1aoZvX/ZsmUyc+ZM5dRAhgC+zxbwPdOmTZOAgAAJDw9X24HP0vattd9cvnx5td+cDY1uP4l0g8xsGt2EEEIIIYS4EkSscVPr78xMZahpqd8wpDVBMNRsI5UZkXGkpGvAwJ46daqKsqJW+84771RG6U033aQizPrWaIjiVq5c2RCBtgf0NteLjZlDq4kGqMPOyckx+zo4EXr16mVRaCwiIsJhBfBiZh5Hyj72HyLdiNQjao0Uc0cw/Xxrvxn7yxWt6Zhe7gfk5OXXc2fmUEyNEEIIIYQQV4JabH0qM9TIUbcM4+3cuasib99//72KNOsNbi39HGrbMIpR3w2jEDf0gM7KyjKr1I2677179xoe27JliyxdutTqdiLyjPR0LRptD1FRUQaFdQBnwJdffqmMYYDI83///Wf1M/B6/KZLly6pOmnUcUPQDSn2EIfT6rtXr15dwKDGdyNCXqFCBWXwQxBODz5Hv3168D2ffvqpeh/2L7IPUKttC3v27FHOD2fDSLcfkJObH+nOyKaYGiGEEEIIIa4EBjPSoWFkIy0ZBp4W9b7vvvvUX6Q2lylTRtV860FaNYzQu+++W92HUna3bt3krbfekieeeMKsajZqnhF9RS00UtqRFo3oL6Lk1kBEF8bmn3/+qbbLHrAtECdDPTS2EXXdkydPlk6dOqnfDecAPhPtyCwBJfA77rhDpYVDQb1r167qcbT2goAZDGk4GyDUVrVqVaP3oiYer4dgHZwWpmrwEGbDPoTjwtT58Oqrr8qQIUMMyu6oH0fqvq3t4OBIcTbFLmsycsSQ7oGTHZ4TeHh8gRMJ6bLvbKpUiykhdcrltwMghBBCCCHE10G675EjR1Tvay0t2JMtw3wNKImjndavv/7q1u+FSjhaepkay94Mau/RSx0OFVvOQ3tsR0a6/URIDbBtGCGEEEII8Xf80Th2FU2bNpVHHnlEiZFpvbqJZbV3tFhzBTS6/YCc3Py08oxs1nQTQgghhBBCroKe1e7mr7/+8rlD0MGGvueOQiE1P4CRbkIIIYQQQgjxTmh0+5GQGtXLCSGEEEIIIcS7oNHtRy3D8IeGNyGEEEIIIYR4DzS6/Si9HFBMjRBCCCGEEEK8BxrdfkD2FSE1kMle3YQQQgghhBDiNdDo9gNydZFuLdWcEEIIIYQQ4lxuvvlmdatfv74EBgYa7j/++ONu3dXjxo1TvaNt4bPPPpO9e/e6fJuIZdgyzI+E1EB2ztX/CSGEEEIIIc5j69at6u/Ro0eVsa3dN1qb5+RIUJBrzazx48fL0KFDJSwszCaju2TJklKvXj2XbhOxDCPdPs7ly5eNIt3ZFiLd8Rcz3bhVhBBCCCGEXDtUr15dRo4cKU2bNpVevXqpPtUwyjV27typXqPxxx9/SIsWLaRJkybqPStXrjT7uRMnTpTrr7/eEFE/duyYDBw4UD3XsmVL9dj58+flq6++kmbNmkmjRo3kpptukl9++UW95pNPPpH//vtPhg0bpl7722+/qcenTp2qvrdx48Zyzz33qM8lroORbj8SUTONeus5mXhJwkODJCw40E1bRgghhBBCiPM5c+aMuukpVaqU1KhRQ6Vc7969u8B7YFyCffv2SVpamtFzMIZLly5d5O2Kj4+X9evXS7FixZTRbYnDhw+r9HAY3lFRUXLw4EFlQCN6HhoaanhdYmKiMo7xW4sXLy7p6ekSEBAgs2bNktmzZ8uqVatUBBt06NBBunXrpr4bn3PbbbcpQ/rpp5+WL7/8UkXFH374YfVaGOjYD2vXrlUp8vPmzZNnn31WFi9eXOR9QMxDo9vHMTWyNVG15EvZEl082EjVPD0rl0Y3IYQQQgjxaWBwIr1aT48ePZRxefLkSRU9NpcdCnr37i3r1q0zeg5GZ8+ePYu8XfhsGL2FsWTJEmVot2rVyvAYjOnjx49LnTp1DI/BIMd9bFv79u3lvvvuk8qVK5v9zCNHjqh9gN+P1PaEhAT1mLmU8kWLFsnGjRsN+yk3N9fBX0xshUa3j2MqnKYZ3XGpGSZGd66kZ+VI6fAQt28jIYQQQgghzmLAgAHy4IMPFoh0AxilmzZtslrfbC7S7QwiIiIM/8Pw1RuzetEzOADuvvtuFXG2BqLQcBCsWbNGRc4RvV6wYIGKipvStWtXefPNN6VLly7qPiL3loTW8P2jR4+W/v37O/Q7if3Q6PZx9PXc+nTz86mZUrtspOHCyroS6SaEEEIIIcSXqVChgrqZA8JiWiq5OerWrSvuoGbNmiq9Oy4uTmJjY1U0XQOp4IjUb9++XRo2bKge27Bhg6qx1pOamqpuMLJx27Vrl2zZskX9HxkZKcnJyYb0cqSiI70eIOKP+/qIOV6rgTTzadOmKQMdxnl2draqOUc9OHENNLr9rKY7IztX3dIzc1V0OzQoUKWWI6PmYmaOx7aTEEIIIYSQa4WKFSvKSy+9pAzpcuXKSceOHQ3P1a5dW0W5EbFHnXZWVpYyeE0j3zCUYRgjMo+0daSaQ6QNjBgxQkXLS5QoIUuXLpUZM2ao18IIb9u2rVStWtXwOYho4/XTp0+XN954Q6Who/68TZs2BrX1p556ika3Cyl2WStwIIqUlBSJjo5WJzm8Qt7O2eQM2XnqqucKRIQFycWMHGlas7REhQVLSka2bDicICFBAdLquliPbSshhBBCCCH2gBRp1CYjimtLeyxC3Hke2mo7smWYn9V0AxjcIDM7/7nsnPy/SDHXar4JIYQQQgghhLgeGt1+VtOtJ+uKga1PQb+UzbpuQgghhBBCCHEXNLr9rKZbT+YVA1sf3c6gmBohhBBCCCGEuA0a3X4c6c7Q0st1vby1xwghhBBCCPEVKENFfPn8o9Ht4+ToDGpTNLXyHF2kOz2bCuaEEEIIIcQ3QK9qAIVvQjyFdv5p56O9sGWYj5NnxetyMTNb8vIuG2q7QRrbhhFCCCGEEB8hKChItcVCv+vg4GAJCGDMkLiXvLw8df7hPMT56Ag0uv3Y6IaweVpWjlE0PPWKsjkhhBBCCCHeDvpTV6hQQbVrOnbsmKc3h1yjBAQEqN7nOB8dgUa3H9d0g0yTNmEwwDOycyUs2LHUCEIIIYQQQtxJSEiI1KlThynmxKPnYFGyLGh0+ziF2NyqN7dpm7Ck9GwpH02jmxBCCCGE+AYweMLCwjy9GYQ4BIsi/Di9HCCqDcNbz/nUDKPoNyGEEEIIIYQQ10Cj28/Ty1MycsTULj+fkilnkzNcu2GEEEIIIYQQQmh0+zpQJ7dGyqVs849nmH+cEEIIIYQQQojzYKTbx8ktJL3cNLVcIzmdRjchhBBCCCGEuBoa3X4upGaJ9KxcVe9NCCGEEEIIIcR10Oj28/Rya5xMTJfMHBrehBBCCCGEEOIqaHT7uZCaNY5eSJdtJ5Il/mKmU7eJEEIIIYQQQkg+NLqv0Si3Xmht28kkVftdFAOeEEIIIYQQQkhBaHT7sYiareTliSRdypLTSZcsCq8RQgghhBBCCLEfGt0+jDMj04h4J6ZnSRxTzYmPkGyhHR4hhBBCCCHehE8Z3ePGjZNixYoZ3erVq2d4PiMjQwYNGiQxMTESEREhnTt3lnPnzom/kncl0p2dlSXDnnhI3hz1nMOfdSw+Xc6nZMr5lAwnbiEhrgOOogt0EhFCCCGEEC/Hp4xu0KBBAzlz5ozhtnr1asNzw4YNk19++UW+/fZb+fvvv+X06dPyyCOPiL+ScyXSDedDjTr1ZMUv30lKUoJDn6VlqiPanZPLFHPiG5kepxIveXozCCGEEEII8S+jOygoSMqXL2+4lSlTRj2enJwsn376qbz99tvStm1badKkicydO1fWrFkj69atE38WUgsKDpbHn86Pcu/YtL6InymSkJ7llO0jxNWaBvFpmZJNJxEhhBBCCPFifM7oPnDggFSsWFFq1qwpPXr0kOPHj6vHN23aJNnZ2dKuXTvDa5F6XrVqVVm7dq3Fz8vMzJSUlBSjm6+gRbqX//KdbFy9UkrFxMrBPTuK/LkJaTS6iW9EuuEkOpvMkghCCCGEEOK9+JTR3axZM/nss89kyZIl8uGHH8qRI0ekZcuWkpqaKmfPnpWQkBApWbKk0XvKlSunnrPEpEmTJDo62nCrUqWK+JqQ2po/l8iqZYulRt36kplR9HTbhIs0uonvnP/QI2C7O0IIIdcqzPgixPsJEh+iY8eOhv8bNmyojPBq1arJN998I8WLF3foM0ePHi3Dhw833Eek21cMby3SnXghTspXriIjJ73nlM9Nz8qVjOxcCQsOdMrnEeIKNEMb5+qx+DSpGRvBHU0IIeSamwvXHoqXpjVKc91GiBfjU5FuUxDVvu666+TgwYOqvjsrK0uSkpKMXgP1cjxnidDQUImKijK6+VpNd8KF81I6pqxTPzsuNdOpn0eIq9T7AVPMCSFFHlOc2IaTEHeRlJ4lWTl5subQBfWXEOKd+LTRffHiRTl06JBUqFBBCacFBwfLihUrDM/v27dP1Xzffvvt4o9cjXSfl5JlYmXz2n/kkebXO6xgrof9uom3o08pR3ZGcjr7dhNCHCMzJ1c2HU/k7iM+R0pGjvpLjRNCvBufMrpfeOEF1Qrs6NGjSpW8U6dOEhgYKN26dVP12H379lWp4itXrlTCan369FEG92233Sb+SG5enuTm5sq9XXrK9Tc2lqiSpSU1OVFOHjviFM8pa4SIr0S6wVkP9Zi/fPky2+wR4gdOPDjuEikkSnyMtMx8oxucSKTGiSXiL9qXwYnSNUKuWaP75MmTysCuW7euPPbYYxITE6PagcXGxqrnp0+fLvfff7907txZWrVqpdLKf/jhB/FX0CkJToeBI8fLDU2aSaWqNdTjp44dLvJnw2O672wqjQkfx597rpv+tHMpGcoAdjdJ6dmy9YRxWQuxzkXdIpH4P+lZOXLwvHfPJ1rm2KmkoouREuuGjCfG6WtlPL2UlStH49M8uj3evJ9sNbwxZm0+nshzlVy7Qmpff/211efDwsLk/fffV7drgZy8PElLTZETRw5Kzbr1pXh4uJQuU9YpRrdWJ1uyRLBULlXCKZ9H3M/uMykSERrklyJjOP/1oJYNBnCp8BC3bkfSpWz1vTAqapeNdOt3+ypH4tLkxsrRnt4M4gbQgnLzsfy07TPJGVI9JlxiIkKkREiQV9Zzn0/NkMycCAkNopCos8EYvf5IgoSHBErjqqUkIKCY07/jWgMODBjaes4kZUgtP5zznZHNcjopQ2IiQgt97d6zqZKematK18JDvWus8nYwlmJdVNrNazFfwKci3eQqSP3GQLt3xxYZ3O1eJaYGKlatIWdOHHParqKgmm+TnXtZtdTyx1IBE5tbcd4DAoApl/JryU8leSbS7ovAsGHqnnPw9nZ5p3WR48zsPJVBte5wvIoowyDHeeANAmZapBvjyrlk3xESRSmYpXMB+x5ZOJjHUzLcq3lxJvmS7DqdLEcupMmFi5lqG/acSZHsK87RDUcTvP7c9QYKyw5Jy8otsB9xTVHjpCDYT3EXMwpdDyVfyja0zsUYRWwH1/qesymy5Xgi53gz0H3jwyc2Ji5EukFEZH7UaOjYyRIe6TwF9sQrtd3BgfTP+CI4dvne3UtSLSZcfJWdO3fK6jVrpU3HhyQxO1BKhARKthmrGynm15WLkGLFirm9ng6LSUzQtnjRr/VzEr4JZNJUL+O756S37EsYMxVLOtYy0y2LXDOOMFy6e07nz12BgcWU0V0uKkwaVIxy67WrR2+4wCFQNcb7M7x2n05RY3v56DA1Dl3KzpUyEaESGxmqxkg4OPC7LqRmqt8TFRbslu2C0QcD25xjVONiRo4cT0iXGhwDrBJ/xejD9WHN6WsKNE6iS7jnePsKuZcvG8TmqpS2fH0fPH/R8D+cRpVKFveqrAyMqUh/19Z0WHcEBxaTSDdd39bAvsO1DQ7FXZQGFZnRpoeWlI+SeuWkvpiaohYpJSLy01qr1a4rZcpVcNr3YICCcU98E82jezQ+3avrKa0B4cSmTZvKMwP6S7fHukhKepacT8mU3NzLZtMXtUWKO4CxgIWuxrkU34mQeYqcK8cNDhJTYDgwAm472FeeEhC01TlcWDQT17HmhNl1OsVjLY+0SLd2HuojyN7I+ZQMQxYB9h3WBLi28P+Ok8my0SSSDMPbXeRnLxT+Ohjd3pDl4M3geoDzBNFXc1jKYMC5wfZhxuTaoNsAIxtiil9/MlNe6vuobNv8n0cy6Kyt6XaeTlbGLY79zlPIJrlosAncBdaTWtbS3rP5DlQ4AjSDG2As4nxuDI1uH0W7wNJSk6V4eIQEBOQfyqMH98pbo58zRMCd1UqF+LaBgygsapl8kddff13CIyJl/MzP5NaWbeVyIau5EwnpbkvzRt2S/qvOpWb4rHPDXWgZChjD9GMLJucNRxJkx6lkt28TFv6IzK05eEFFD30l7RUOHywQvbV8xDTKff70Sfnl688kIS6/HMoULNLMOWPcgakTD45Kb8ZcW090M8nOyncWmA6TqE1NdVOKOcqabHpdTp5yzBBr+zJPGc8oEzA1ohcsWCBPd+8iq5b+WuB9GMM8dS15K9q4DsPQXPo9nj8WnybbNq6RT6e/Lnu2bZIxg56Qg6cviLecC9tPJhkcldtOJKkxMzEt27DWcxfHEtLVWgv78mTCJSVQB4eFHmzjyUQKU+qh0e3j7ZJgXJStUMnweOalS7L85+/k9ImjTvsuekt9ExgSeuPhZKJ3LyLNkXopS5b++bfc+9iT0rztPfJo72ckMMh6VUz8xSy3DPSY7LaeMO7ri8kQYlGewFciRvrFAY6VBlLRtLZN7l6IH4lPk1OJl5RhggiR5rn3dlAjrUWJvRF9PeTJY4elX6c28teSnyQyuqRdxqS7Uk/1IDLszXWxphloOzetly4t6sv9TarLp++84VGNFnucVqe98NzVdAa0KJ0n10CaAwMOCr0qOTr39OzZU/bv2SUThveTjav+NJtJ4CsORE+UkJiCeQfz03efzZKadRvI/OX/yVuffCsZl4PtbjfmTGDc7j+XKhuPJCgDWz/+WxKWdTWmRv6W40lKwM8UtLBjIOIqNLp9nMeeGiQfL/rLcL9Clerq7+njRe/VrZHl5igK0ub0fSe9FW83ckyPGwwKXxIFwYJn28kU+ejHlfJon2fVY1mZGfLe6y/LlnWrrb7X1UY3JkGkdZmb57DQ8cS5CGEipMQi8mmqZutN6CdgzbiGB18fldHX1LkaOC71Yl8ARqw3tzWDSNXqAxfkYNxFr21zhTFcb6x8PvMtiSpZSsbNmCvBISGSkmTssNLAOeyJyH2umYv5WIJ3tl5S9du6azwvL0+mj3tBtQ3FmiA7E+U3BccAd5W/2HP8YMx4OlMD0U2k5GPtgeghrq2V+86rv//sj5N/D14wXGPuFsvU7xs4zjVHQHBwsDzRq7d8sWS93NKijcz7cFqBbcM54s3lJ54KVlnKStOcUvUaNpbHnxokUSVLq85AuJY2HDqnzg9PgGN4PD5dreFsKY9xB9au2XOnT0huTo4hEMFz8CoUUvMzsKiJiIqW005UMHe3lxf1M+dOJUu1mBJe2YIJBoFWqxIWHCi1y0YoIRtvw5zAChbrvtDGAeccUo3TL2VKUHCwIbodHBIqOzdvkAvnzkij21pYXZQiSuUKIRksvg6cT7X4PBY6MBxKlnDffj6dfEmlef13NN+QCQkKkGY1S3tl26NM3XiCSDcmb1zzepsHvwWLcXeI0iFiqI8YAKzNjl5IkxsqRXvl+LN26275/L0pUqVGbena9zm5mJHfgxbtAb0FiHBqpCYnyb8rlkifISNVlHvfzq3yQu9O8t7XS5QOiR6cB4fj0qRuefeO/eYWrViEYyzxtpZBphHrHZvWyfHDB2Ta5z9Kw1tut/g+/BakmLtacMkeAwDXGq5/iFV5AhhSB87lO6/0jj/NPtPWP7jusP/wuDvPTb3zHNcGnLrXlYuUBg1vlmf+N1mV6YycNFOKlwg3K0KItYqn9q0557AnBcn00VnNGNS3xNXGrB4Dhl59T3a2DHikrXTs3EPCn35WzeuYX925z2wpC3F3erm1DIrRA7pLbna2zPz6N+W4QGkjWw/nw0i3jzN59GB5d8Ioo8cqVKnm3Ei3m41uLMoxsaHVFYQZvAmImWAxrnmb8RcRT9SCuqtezpbBEPVf20/m18ZmZV1doEGAzFTYwtNRBnNg8YPzDkImn7w90fA4FhVt7+skG1evlEvp1qNQSGtyFOwjc5FOtLrad9a6Ki8wrW1yJYhu4FrRg32H4+9txxbOCL3DAucqIktInTPFXbVglkRysFj1ZEqhpesa409yQrzs2rJBvnh/irzz2ktXzoE0r01/XrvyD8nNzZG77u+i7te8rr6EFS8hv3033+x7TyVdjei5A4zdaBGUnBgvCz5+VzavW6X2KeYh1Pp7WytA08jRjU1ukxnzf1V/NUPhq49mqNpUU04kXPJI1oA1PFl7fFg3Vq9atlgSL8SZfR3SuxFtdPeYampMIdq9fOVf8tHnCwzaPtGlYiQkNEzizp6WzIxLBcZcT6THJyQly88r18v6Q3Hy39EE1T7u30MXZOXe86qd1KZjCWo+9WQJif5agLMcztdNa/6WYwf3GR6H079O/Yby89dz5VJmtluzsK6KDRb+Orenl5sY3ci2Obhnh/p/+PhpkpqSLNNeHa7GTgSAvDlzzJ3Q6PZxzp46IelpxoPAw937yu1tOjjtO5DS4s5BW/sujI9I+YLhjYkOizBP15cjrdjSPtp2ItmjAwvSitceilepcJpSLQa80f27yqzJYw0Ld0SRACLBcBggfQ5/van2C3WdSOk6sHubRJcqbfTcHXfdq9LM//v3almFpYWcIwt3pQ56Kl/9V/9+RDkspZSbggiuu0okUENuLp0cxxdGmjccVzirsFiBI8B0/8E4M6dEr7VFcTVaijuuFdOU3J2nUzxej4bzEenvWKhe0KU/Iq30hYnvyJLvv5I/F/9gcFR5Y6bN3Q89pspESseWVfeRXo7Hlv38rZFTUAPniGnKvysN7k3HEtUY/sn01+WzmW/JyL6Pypcfvm04Pz2l02AOU4VgACHV+jffYoh0IjNo9bLF8tXsd8xmO7n6urJVSE0/d3nCwQ715zPnLihnC9JhP572mrzw//bOAsqq8oviB2boYYAZurulQxRQBAlBBEVFQNJAukNakJROCQEBCf8KiiIoaQAirXRKSDPE0DH/tb/hjve9ue+9+/q9cf/WYukEw51b33fO2WefVq9K1BXjwNuXMl5UOOEObZ3Mx7MxYsw4mTHF8trimN+uVUE2rf7WwMzqts9HfObMkUNeeeFpaVrvBdm990/V74ugFusR1kf0Jvvacdt67cEarbXcaS7w2CstXzjb4vvqN2kt507/LTs3b1LvJV/JzPHu1/fx2/9e367z1uvi1o0/yQeNXpTjh/ZL8TIVpPvQcbJ5/Wq1NoHz1wOvBcofMOgOchBwp0xpOeu2ZoM3lemUp8BGDhs+Vzd0+t5nvLBQPbI3jkXvaIyX8uajV2TToUuqv2r735ZjUHwJfn99ZhaV1lvR/1boEKAho2trhIe3QbVQ66OEqcqQzm3k7u3b8vRzL8pX8z+V1csXx226cD0RVKKapxkxwRUzEMD9goDxzMljcvfOHclfpITF17PlyiO5CxSW39b9YPfn4PdyttcV5w4bcC0QRHYe5wsgaHQmmaz9PW9jr4c8NvCO8mvgjWcGzwUqtDejb6n2ALN4u9qNjT4SFqu//kLerlleXq1UyKL6iuqWv91XUWmFozruSbRVDO7USs6d+VsFWC/Wf10qVK0uG1etUPemr+45M5tFff8hjjVXvoIW31P71SZy83qU/LbW+Dn2hf8E1iIYAGnVxDZdPpTF63ZJ0/e7ysLpY2X/7u3q87h3A1Va/vexw9L17VfUPaE/3/DB2LnlZzl64K9470UEc76szu7Z9pv8/vNam9+PY/KlOkgD73R4hPR+501JlDixDJ/xhdy4HiXTRvS3+Xd8kYTDv7HzVNSTSRyWX0NyYOvPG6Ri1RoWn08XmUFKln/GUD2CwM1XypEbt+5Io8ZNJCJjZjVxJFPW7JIokXGo4et1ybrSDbSEBJKE2E+jyl24RGmL7ylSoozkyFtA1q78n/oYow29bbKIJDAmeZiVjfv8XFr9e8sXzpKipcqrHnjwbPU68myNl2TJrEnqdzl77W7A+yD5AgbdQc6dW9FqZJjl527JhlUrbMqkXAHBL6pmrjw0u05HqQUVjsDYPGKTg95TBInWFTr8fO0lg6B2/ffLZd+uP+K+fvveI+Vy7A+wodUHXTjHr1cprjbsGjj2vad9XzVGtU7LGuMFN/OTIXLj+lVJnjKl2nyhH2ny0L4qC4l1R+8arYHPBYJbL5IWqiJ/aL/6OF/h2Je4ng4ffixvtmnv8GdBDnj04k3TCgRsRvVVJGTj9529oaRwzjr/+sK0COdKO17IuzRpIe4BSEy13wGBmz/M1bB53HPykmxc/a06pq2bfpJuzV+J27w4AhVGby7UCOwQyE4d3l9tGCq/WFfGD+ouX38+M+57EHT7S16MhAVaQjQ2/LBCtv2yXsLTpIv7HKrdgyfNDai5x/pnCEFfhzdrK3MdPTnzFpAS5SvJySMH/WLgiWdnz5nYMUx7t29Rypm0EelVNf7tdt2lcImysmvrL+p7kUAIlITGFatkBALrQ3/uUkGXnqo166mA56vPZ8T/GdH3vSbtRdL8llXV+sb1a9L/g2YyuHNr9bwZgfvcl9Jt/Fun/rkoP69ZKTVfeUOpBbLnzietOvaRjT98I8cO7vObsezpqDvx3Ok10LuP4LB42YrxvvZSo6aq7QSjY/Vg36L1rXsTrNsb9xyT8HTppe+oqar4g8AbCTejd6gvr7dqDTAoHGFdR0IC4z8P/7VbHWehpyyDbi3BefzwfrXO4vdEQt6b79pjl26plhcNqPsmDOklzV4sp9rrrPF128MD3e8Ozw68Q1985XWL72nba7Byf8f5w7k/T1M/Bt3Bzu3b0ZLSKui+e+e2DO/ZVpmreBJkAjcduaReNmazvahsY9N//FK0muVn/RLccvyy+h4toMHsP41FM8bLiF4fSJdmL6s+O036ieyvP6rJqAZjziwqTZcvnpfylatJ9XqvyvjBPdW4Fg2tz9uX882P6fqMsAE7efSQNG3bLU5u2KHfx5I1Ry6ZMKSnWjRsEQguyFFPNhvYjEdkyKSMOKwpWeFZyVOgiMOfhcXx5OXbKujE/WZ93+I+0qRikOfa6i3Uj+lAMgszPMcO6KpGi1y5dMGuoZo30ZIn2ChMGNxTBnZooa4vZKXDe30Qt9GJHW+Gip5vF2YEgV8t+ExG9mqvgq4qL9aTGvVfl3EDu8vhfXvMzfG95b3kBTa26TNlkTnf/ix9R0+Tnh9PlPd7DpYyz1S1eJ4vGySpvA2u3VGrjTKqwuWefV5SpQ6P+xyCLciJz589JXcx8swqOMQ193XSQC8bPbB3hxw9+JcKaK0ZNWuZtOps6UniC7kk2h12/h0Vl0SFlHzp7MlxX8f5HPPZl9K0bde4z8UqXWICQgWkZ/fvv0qRUmVVj7we/A4Nm72rksNG7ygkGD39PsD7dPOxKyrpgvW69ztvKNVV5RovSb9PZsiB3dulf7u34xKC/pwrjXfnr+t+UF4DVWvXt1AKZs2RW1YsspQY+8KwCu8a7G/s+TMc2b9Xrev5izwV72vPvFBH0kZEyqov41e7cW69rR7B+z5l2gwy/NPFqg9aA73m7V6vGe+d7wvzLzzrUPUZ+YYAvBqhbsNzdXDvLmVIlzOvpSoHvNbifdUig+SMlojT71etA2B3/EDwnOtbGbGmf9yjrfy4YqkUL/u05Myb33C/4ct9sd63YefWn+Xxo0dSoUp1i+/JnC2nSmIiJjGaEvJfhJXuIGfg+NnyQt1XLT6XLn0GtRHTKoVmwJzHTk3qqqyvPdQc4mt35aAJeRpePEeeBIO29nx4blH9hpnS5mOXVfCo9fg1fPtd1beIjc9nE4arPrsH9++rn4Xqoy+ryVgMsZGcNnKAHPxzl0p0ZMicVboMGiNFS5aTod3fk7N//2tehyQCXuS+2OwisNNvcjet+VbSRqZXUjMNmKx0HjRGXmnS2tDhVOP8jTs+NTAyQgtUG7/bUcbOi+0HMmLVlwtlwbSxpn4mFlQsunvOXJcjF24qWTHuu23Hr6o+YwSk+885ns2MCkPHt+rI98sWqErI3EkjpWPjOkpdYoS3pcnaJmrN8sXyw1eLpHq919SmIGe+gvLLj9/JikVz4r4XrQd7z173WQCG5xObMChBKr/4klqAcWxdBo+R3AUKKRNIZO8dgfnZ3mLduvUSfeO6ZFQSyNjnolHLtpI7f2EVGOB9owVcvg5cURXQS7SvXb0s+3f/Ic+8EN+vA5vZ5rUqqkQrKiRa1QP3+qbDl2T9wYtK8eEr9MoSHBvOZ7Lk8R2UYVIEuSyqd9Z4K0GEDe0+nWwTCVQEri/Ue83i+/DOxLGtXDJP9u/ZofpRz/m5UhN9/6HFuqckqNu3SqkKzxp+f51GTVUAFJE+tpdeD36fwy5UP3H+8EcbrwUFABLM+PPXmetx/gyb1/2gqvDh6SLUs/V8nQYydNoCOXHkgHwxM36vOfBlKwfW6I2rvpGnyj0t6TNmtrgnh01fKB0HjPS5YRWSw7HJENvvmnTpM0q9N1tIqrD4DurwSsDXHj82XsPxs72VOMJ9uWrtRmVGZ/2uxP13797dePPjvW3+hX54tNI5UvBpKrAUqVLJc3VekZCQ+FM/kiZNpu5j9HZrvx9k+0bFFZznk1bmpq6o/TSgvEJ/9IBxs6TPyCmSKWsOOXH4gHzUpY3FGmpd2PIWse+Afz/GWln2meclY5Zs8b734rmz0rRGOdn2yzqV5A4Uw2F/waA7yIFbKdzKrclbqJgcO2Qsj9KARAVZU1DtpYaSMlVqFXxjM2xtzmYNKmexplIxhl/DYoyg00jOYwtIx5ERbVH7abV5jMyQSf1uLTv2lhEzl6hAEhkzLYCwlbn01gJ95u/jqo8YfX+augDVBLwIkR39/svP4/0+tpyRPYn+5Y7FAMdYpUbdeAsHzC0QlGHhsBVA4EXqj946DRwXZF4A5xRyP1tcPH9W/jd/hqnATW/YA6dv+ATos64wqDIy87IG173L4E/k0+XrZdqXP8qCNdvkna791WJtBKoL3jJUU1WvO/fVMzF34kh1bVGlAVVerCuvvv2ezBwzRA7u3Rn3dyBX0xJh3gbn969dO1TPac0GjS02L6go/3PqpKxd+ZWpxII3EkHnLl6Wvh+8rdQKehB7YxPR/o1a8v2XC9TncA3/8aGZFp4DzfBQA9J8UPG5F+N9P6pKGL21ZPZk9c7FPY73I/6LRz12BFqs4sMXyQO9vPjwn7ulUPFSNr933pTR0r1Fg3iuyzhMbwTemGqgT2YgORUamkQ9M9agz/e7pZ/L51PGqI+hlvEn1gZqCABu3rgmhZ8qY/N9VebpKuqdb6RwwjOqGQk6SoSi9xUV2I2HL6pEDpKVWBeRAP/l8GXluaKdV9xjy+ZOU+0D+mtfsFhJebfbAMlTsKjN3w/7B19w8cZtiZEYeeEly6IFwCg+vKeQ6LIGp9EbCX8EhkZtX9ZAYdfJRkIAtOjQSzr0swxuNfAeO+GlKQdIEi79bLrq4bVO7GOf1LpzX2VEhskAvlCzILHuTE80QFGi+0exBopGwOOhee2KcuDJmoo9w46TUar/Xnuv4t/Fuu/Ou8taWYVpRA2avSOVqtWM+xwS2DAv0xcejGaPezqZiveFdYECe4+Rs5YY/h0Up7LmzC1LZsUqiXwxPSGQYdAdxGCzDZmrUZUAC93BvTtsbrDWffeVfPj+W7Lo0wnqeyD/GjFzsfQaPkl+XbtKSYH0JmFGqOD6zDWLfwMPJIJxLMbWGwQzYAN8784dNVJGDySV/cfOVDNe9RsGX5jtALxE137zpZJ1Vq31ssXXIJ+ZsPBbebf7wHh/Dxtfb7qyIhjRy5iw2E364ntpopszqQfXaky/zjJ/ymi7lUUzGzFvcEPJEmPUvY37E1J5W9R4uZHcjr4pWzb+6JNjQ2sBzh/uRSwk2rV/od6r6vO/b/op3sYWj4a3glzMFMU/t/67r5VzbfP2PS2+/k63/lKgWAklM9eSVQCyNV+YwKgq9/Il6lyVqfSvXBugNWDykh+kzmtNTPws71TAZsz+TFWysdHSSJYksZTLFSHl8mVQ1fivPv9UVTs1My1fVbuNHOkrVqkhAyfMide7qz33jd/pqKS86KHGsRoFiHi2D5y76bNKN+67k8cOqWDLFrUbviU3rkXJj98si/c1T2/KkaiyrkD98et6Ve0MC/93JntoSCLJkja5pEgWKm+910l2bN6ovEUQtPhzvJW1NwVUbR/PWKScy20BmTdGL37zxWeGXz947qbdflCsMQgq8H3oC7YVdOofDQQlSPa90apdvO+DkgQJDqNpAQCtaN6W8aPaFiOJZdSspVL3jbcNvwfXu3G1UoaKQW9MKTEz4hLnC6oMR+MykcBCZdSIE5duqT2ap5MbR/65op6lKjXrGX4dxlqYujBn3LC496i31Iq4f5AUQuHDLFBYouhj7x2PXu+sOfPIss+mxn0OiSYks/Fehd/QX2eR2HTvd7N+x3QaOEra9Rlq8TkkWaECRXJLK54pJaoXklb4XVC933rsiuw+dc3i3sE73pZPg7Y2vfVuJ/lr5++qDTMQ1JT+hEF3EIONCiobF85aGtSAMpWqKCMYo4o1Krbo/0R2CvJ0LSupzCJeeUOm/2+tvNdjoKF8yRpkZpH1/uXIJTWqCplFV4FEF1LUeo1bWPQs6sEMxV46mfnBcze8vkBDPoQKKWTbz9WqbyiTRL8izh8cWrEoxv3dB4+VaZy3TKzwcrZeI3As6FM1AseIr8PN3N5YFOsqm6+l5aiOGpmF6EEVHIv42m/NmXK5AxJQHZvUlQXTPjH8OhY99Cp+t3R+vK+hiu6NIFdTUSRPmUrqv9VKZZOtpYa9RkyWss88Z7G5VbOHz3v3uYHZE+55uMAiAWQk18tXuJi6H20ZFll7DXg6g7/ki4VS8fkXVeCiUShTakmTMomkD0sm/fr0lvNnTsn6VcvV1/D7+MrzwCjJgONEctQWz9d+RTJnyyFL50yx+7ORrLQ1+tATYEOlqUZQQUZg87SuQmMNphFgo46NrJbg0HjgYfkpqnHW6quylZ5TBlR6imdLI8WyppEqBTJIvQavquQVXK5xfHg3+stYzzrYgxoIfZS21kuAZw+Jmq8XzDQMcnG9UKW25dCOe8XZy7Bl/Wq1BpW36vHUwPkb0audzJsUv2J728CXwNPAowP7IOv7zbpwAbUdghprPO1mj6SHGaPO0yeOSM/WjZThlz12bP5ZBnVsadM3Q1MqQnrtib0JTPl+3bhBTRuxNTkH7/p3uvZTARr8J7xp/gXZt7NFHyhymlQvY9PYUXuWkIT7be2qeMkYvFeR0NBGJeqNxpx9xrVrgj0xxiriPjVqC3yzTQeVwEYhRVMKQd3kybUdATfuE1trxq6tv8pbL5RWRQlbPP18TckNJdacyepdYnYMWkKEQXeQO5cDa/dyzWhq6NTP4wXOyObBZA0GVcieaaYQ1psgvDixMO75Y7PD44B8B8ElXhRmJLq22LBqucqa1XvdOPMMEDDCJRGzVLUF2t7IJE8AqQ9eeBMXrVSuttaEJQ+VtCmTqPOF3puRfTrIjWtX474Od1woAryxwOgdslFlbfdGTeX4bg+4ficOCZHFMyfZ/B4sHP5wMtd607Hw4ZyjN9kecJ1Fr5C9F74n+Gr+DLl184aqyhmBSt7Lb7aQqSP6GyYLjni4nxb3mhZ0v1C3oU05YfZceaXzwNHqPaAPFLAh2XX6mteSQVofNs5XvTea2/w+ZL7bvlZdSXztgUAJjr6eYusfO+Twvj+l5iuxcnyQLlUSyRiePO7jFypXlOp16ik/Ca2ypO+X9mYVTj/jWqscwrnWlneAJuF8670uEhYe7jAoREXGW0aP+nYK9MeWqlhZBS/2QJUeCQ7rGcOeNloySprAIOm52q/EfZw0NLFKumgUzpJGOvUfKccO/iU///id+v385cJr/bzCbHTLBsdKH1SXcX4RLNjaWMO3wNroCIkuV9oqWnbqI+MXfGO4vwDq3Z63gHw5b7qSyFsDlYY3Exvnrt2STm/VlS9mTrT5Pbh3G7X8QO1L9H4tAAGyJ9dHvMvNVEaP7IutaBqZqOmpWLW6UhihNcJR0WTriStuK9uQJNy8fo1KhOO62gL70gU/bpMs2XPFPd+eXoPw/nSlRQ7O5EgS2mtpAzXqNZLM2XPKok/HmzYacwZ98uXHb5bKJ/27yJWL523eo1CnYt+sJa+RRPOU9wTuSW2Eqi3+3LFF3WsZDPq5NfAeeKMN9sVRKjmA/cF/tdrNoDuIuf1kI4hstxHoS4Tk1UL+ff6c3I6OVk6i1q7nRlXlHi1flU2rvxFfAIMyZO1haqSRImmI5IpMKdrajeoYeoNQFdHmfqJHyZsPMOTbCGjhom1UQUZ1rGyudJIvY5j0Gj5R7t+7p5QEehDkwLjLk0C2rt+cI/uNRTkyQ3zTHD34PbDJ/XbJXDWT0hberoYaoblvYuQJFmZb97YGlBlILtl74bsLFgmYKdVq2Nji3rSm/YcfqwBj3MBuypxLDxYtT8r50FaBQBRupqjY2EJ7bmCQ2L9dMwv5O9QbmB7g6VaCWLfve0q1cvTAn3a/txh8Buq8LBMG95ArF/+x+71Irnkq4MX1gNKnQpUX4j6XL0P89+GMyRMlZcqUcYGBCv69nOQz6nnb/ut6dQ2TpYivstGDii2SLPbMErXN7p9nzE+hcIZbOknn1wtmqUqNESGJE6l3phZE1HuzuSRN/m/SA1z1oHM93i3WgRLGhGnSTA19wA3Spkwqz1V+RsYv+Faee+JyfcIP1W68i/XrHJ5lVGHtvcP1Pf8w1oQHhj3Q868fJYZ5xM74sgCcF1QEYZxoBKT7hbOklvc7dpY06SJl8sd9453L2Gq390aa7di5U82IL1XR2IBO/zwh0W9k/HbUg6NLza4Nh/fvlWy58tpVNmgJuJcaNZMNq75WyWJ7oFACyTCSLq5IorEPwVpStHQ5eb3lBw6/HwaFkHGjeAKOX4726DOCfZYrj+bxwwdUwgAKMXsg0G3erodEZshsdxKMK73/SBhoVWA8E5i5Xun5mnb3HZiLPW/VFosWEygx3N274TlBscg6AWwNjBzhLeVozcF6O3HRd0opiuvjr9G//oZBdwKodNsKntFDAcnrridyZzzEkKBiPI69HjsNyFKfr/OKjBvUwzAb7Wm6fTRW+o/7dz4ueCp7GimQKbWS+mkg+wwzkYlPKj9YNMy4qbsCztm5K9elRZ2nDSsK6VIlVX/wwsmbIUyeLVlQOg8cqRw8rat3Kjvu4AXmzhxoVHzRl1i8TPz5nUbVHVRBMc7HFkgU+NJNFgGAlvU+cfig5C5Q2OHfwZgcJGpw/jXXe08D+fr1qKvKTd8oqC2SNVwyhidTGx2YsKCl49sl8wyr3Z4KGnHtce+j+gmXYCNyp08pzxXMKNnSpVAmhNt+XhdnDKbfGEBm6MkAAgE3ZIZTPu6n3Ivtges2d85sSR2WSqYO6WH3OLD5h0eCJ441c97C0mfUVLWBAulTJ1PBlTX58+WVAwcOSIEixbwS/BttdNDzZs1fO7dJsdLlbVYO9eA5gGs9XGMdJR6c6e/GBtJMkK43UUOyypYvQ6pkoZI7MqWkTBbbeoBkgbV8HufaU5UwI0nwp6MHxet1zhRuGXSD/BnD5KmysedfzUn2gcLKmjsPHlkEEzBXgqdFweKO13Kt2o1jR8BjC/z8vaevKyNUBGFmJM/WQBkypHMbw69hX44EdfZ0KaVs3szSe9hY5UMAHxmj3m5v9Pzid9q5+ReV0C1Soqzd70WAgH5UvHOs3zsINPHHXaCEMztaEkl1/Sgue8C5/tHDRw4rsvrnA1VNV5KEODVQNb30ejNTf+ezicNlZO/2ygQVLXIee8av3LKY5OIMJw7vlzyFjA3+jJL97foOdfg+dmadwDnYdepanFoUrQHHD+1T19EROI6rly7KD199Efez3Hk/4Rn5/fhViznhhsd865ZKBBnNjDc6xkSJEimTZChHMAXJ2wnsQIRBdxCDDCwe/vC06Qy/XqL8M6rnFbOuB7RvrkaCIeuJ4MAMeEDg1JwmXYQM6/5e3Pgcb4CHEIuavl8awWx48thNcabw5KrirT28GOcRmTGzXLl8Ia5vVpu37EkQJP+ydrWS5uUwmI2YM8JyNio2E/UbvqZMQ5YvnB1vofaklMp6Q4TNCwyrzFxfOLOid7/2q00cLmK+mu0MEzXtdDV8+x15panxxs2I0R92Uou4N0DmG2Y7SFJYky1tSsmWNoUUz5pGtRhgZAZM9dBrZQ1aMDyR3cU9dSn6nmz/bYM8uH9Pnq0ev88XgUze9GGqmlgkS7jUrF5Nar/WRBkvWs/sRdXz7gPPXWNIFndu+UUpBNDLZY8MqZNJjiwZ5bPPPpNfNq6XzT+usPv9WKjdDXb2798v365YbtHPmVknK7cmZbIkkvRelHw+dYw69zhf9ubougN+P+viCY4TrrmYPmCGRw8eKkdbR73dABteM+PQ1Giqs9flnomqp+ZgDbXHmZPHbDqXhyULjZ03nDFMBWMA348WHQ2ci0MemFKBZIb1+xLB58mjh5QxokaS0MQSkSp+8gWKq8zhKVS7VZuXq8iebb8pUzFfmqrpkxng8F+x/bpmg7AKVWvIF+t2xplA2gPnypW+ZVT+YNKq90nQkysylaR+sqZDxt+2+RtqrTQyYvLU+9Lw/bT1Z+WsriXd7NGgaRsl4TWq5Hmi2n3l1j3TldkkSZJIsdK2TfP0oKUD+6TiZZ52KrHjDEiKYGQcEv54R5ml6ftd1Tr03bIF6hn3xCQaqEDQz+zymnr+nOQxkejXQMIAxr+nTxy1+T3OJI1QVUYCRuOH/y1Sz2q5Z6uZ+vu/rv1eqew0TyEoQF1pIYKKbq/VsdjizN/HVNGvRLlKpn72wwcP1D5tzoSP1ce47v5oY/QnDLqDGMhKsBjYkhohOP1o8nwpXrqiynDDMRTSHmdAL2i/Tz5VphHWI7E8BTZn77/6QryKQ970ltJiyD9TJ48NKCE9hku3PhBCtdvTfYowhII8EtId66ALG7H0YfE3aIWyhEu3oWNl+KdfxFuoPeVkjt9TL/tBD/mhv3ZLeZ1c1oiUSUOUtA8JWgSTCIy+W/a5ocEOwIvXnXmTzqBXAVSsWkONujELVBlQFiDx4GkwhgtVOCNyRMQmiRInTiQlsqdVwS6MTSCvhPstepj0oJfJXcf9qNsPVNV3zYolSrECDwajlgcck0bBTKmlfa9BatM2Y1R8l31P3ZeQtF29fV82r/9Bjd2x198HtERazZo1ZfHixdKyyRsO/w0YWbmTvJo241OZOLSvGgcF8B+j51hP1OmjKpDVKgkI/D1R5bLGyEAKox/Rs2dGwQIwvg5KFmza7LnKaiC4ig2obZ9TKF6Q2HxsIjrQrg0qIMCWqkp7l2dM/W9CFb3r00cNVA7sGvh3sbF3BwSR1ocOaTnWSL2zfoaw2Fm8RuRJn0pKln9aipYqL5OG9lEbSIzO8VVvol62r1XCsubIbTHRwx74XbFBvh51xW5LijugioVkBqSk8f/9f593DSTVFy/7Uho2e8fw56G3291rb/1+uhx9V+05yjxd1Ym/91hJffXjrgACBoxScwdn1ARj5n4lDZoanysjMB3imRdqqeM3oxDCuuKMLDl2NFaMzBo7VO0jzIK+afixLJ41USnDcA7cXRdRIHBVGYFnftHa7WrMphN/SU230I/scrXSjfYCa+M3BLLNO/Q0NCE1AvPZ0UKCHnCcU1TMkVB1BvhVxE4kMvf9SPj979f9Fut8SEgipWIyIjRJEnm7fQ+1V8P7C/8O1h5v+6QEEgy6gxjMkERlwB7IOA+aOEfm/7BF3mjd3mG/ihGoVHwy72t5+c2W4g3WrvxSHj58YDFqImdkSlXp1oMgAq6ymqIHL0pUyNF3joVeGZadvm4qQ2eWA8dOqc1Zjfqvx/ta1rQpDDdo2EgUyZ1NSZ9xfbSZjq5kks0u1KnTpJM5K3+RygZVTz04r6jGl86RTr0c4RIOmf5aG32XAFU9M/I3dzef6GcCOGdIwOjHXDnihbqvSumnq8ikYX3izft1B/RM22qtgPFWyqT/Li6o3DydJ1JyRKRUsiuoS6aN6G/xd7DI7PvnulsjZ7DRQZUACQYj6Rmk0pFWfak4tvKFc0rb3h/JhX/OxBs5o59b7O4Ys/v3H8qWDWtsuthq4DnWlCygcePGkitThDy+9a8JoRHYWO0/55okHn9nxfLlqrqmSQMR9IWG2F8K69WrK02at5TpI/urBCaqM7vPXPPoOED0HBuNuIlIn1FNk4CDthmw4cEYNBhszh4fW1FwxMUb92Tr8auGlVsE41pFz5E3EK6N9h6AGzCCvOx54iuEtEq3vgKKKnO1Og1Usgayb/31xbgaV98v2NAZVcCgFClYvJTyuLAnLdcnWXNGhqkZyahu4d2AjS2OzRfoDepA6acrGypqHDG4U2sZP6i7V3rSMb4QDvpGI8wiUiWTJAbPWY6IVBKZMkTmThxpOJ4LigJPqa2Q2I2JSSTTvvxRzT02C9Z57FNmffJRvPOGJKCrx4fnxcxsboD10F4Psc1/4+FD5eeBiSVmuO/E74KEyIV/Tivj04rP1XDquN7+oLvcvX1L5j5xsD/ohocMEn3WJoDOgmvszP4YakGM6YTRntafbg2SctbPrTVINuB3twajSG0ZtxqB9az7sPFy9fKluGsN5ZTZlkasPxgN6IwZMtSvSApo++BCmVNLtUIZpVK+SKmYN0Iyp4lf5Hvx5dclR94C8tmEEepjvNcReHtrfFygwaA7iFn99WLlwOkL0E8I2TKqd/Z6wpwFCxgcNrFB1xxuIYm1rnLrN5T5M/zryJ46TRqVtYe8GAsSqr8Yb+CJBxgvQ0heQxKHqFFh1tiTpEIyiUBn6vD+MrJXuzjX4dhFP8Yjjup68NLDZlU/a9YavBch0wdIaJTMnlYKFS+pFBCQztqa/YnD3YOZlzYCDGw4YF7ibsb/xp3Yn79r6y+q2hUSYq4NQvv9sRm+cuG8mj3vCS5fPC9jB3aT7Zs3Gn49S5r4plZIDGHhyZctvXzQ5yMltbTuV4RsEvMuscA5myDSXMtjHj+WV5q0iXdf4hrj3jMC175JkyYyYeHKeAZ1UHR4Asje79+9K3UaNZPn6zSw+70IuPXVeHDo0CF5pWoZ+W2dscuyfuSPmfnnWND153jnzp1y9sxpqfziv+9NtAeYYea0KZI5a3b5uPv7KrGDzQlmwXpqs2Br0wjzxtdbtVObPEfg2mPDUyx3Jnm3xwBZt/J/dmfdW1e5YK6mJYVQyYeJJD6nbcQcVbr17wgYK8HF2lalBlMfNBCMFcmcWlVCPuj9keze9pusWb7Y0vjt7HWnN+UIuG2NbER1BtU2Daw7RtJy62p30aeeUoZqC2eMj53te/OeT3oTrXtVKz73oukeWuvpFXv/2OJwYoCzYP3F5IZqdV81TEZHGHgmaOSNTCFbN65Rk1Wsk614fg9fiPaY3wQq/cCMP4IGfp9WnfooY0gkW6yPz1WZOZ4vs+8PBCntXrffrmME9m158heWWeOGKoNSR5hpIfnXQA1mvWvVv1HumX/bNMwAc7BewyerqR/q5917JMddHMWGKrc70wXRioNRtM4Cc1UkmFC4MGq/xO/0x8mrNtUMSFpgv2o9pWHh9HGGCShHQAFav3FL1dqoFR8gFbenDNPM5/44cVXtTcyC5/TVZwqrUboASVP9Woo2EhTJoLLTExIaqp6lHZs3xpkho3cc+yG9iaP1MSYUGHQHMQjkICX0FbH9GO1kSOfWqsruCWD2hmorpDEa2PjYqzzpq+CoUmAWMfpYMNZJ25x4ovqAIPLF+q/Lgp/+iNc3j1m+qHzYAptIyLhhtoF52KP6dlCbEryEXRlnoQeLtF7aikx2t+YNHM61Rs+xvtKA8wy5X+uu/ZRRGPp97W3IsXm1drrGCJ5fj15WAYPZxdoIbFy0StaJIwclR+58TqsyIFlD5jm1ncSDMyz/fKZSK7zwUsN4X8MCkzG17SCoSJbU8sZbkPbVlokf9TJ8XrDQbD1+RUnL9IsKNjO2FklNWo5ADPeWtbQUVXZ9BdGawlnCJVnSUKW+mDcpduyepyS8KiFw4556J7Xp8qHkL1Lc7veHp4jfT1mwYEF56aWX5JMPOztU8UB6ak+aiXMKYxq9SmPZ/76S1OFppUTZ2D7H5ElC4ilqbJEqVSpZsnSJXDx/VrVyAEgC3X2etWM1cjDGOwMbMDNGllDe5H6SrMyfMbU0b95Chk1fqKq5zoDqCJJCMFWKPX//VkoeOQy6H1nII23JhnHeraueGNeGdztaZOA/MPOToRYj0iDldTa4QaBuq9LUokMveblxSwtXbUcOvDjmolnC5e12PaRqzXoq+QWw3iA5YRYE6c4ka5DY1Cc0YJK38YcVLql6EKxXrlFXJn7UWyUWPQWC2Dkrf7bpYI010xZpUqeSeQsWybkzp2TGqEHxvo71xRMyc/i+tH2thl1JsC3g0AzZ/MxPPooL3DXOXHWtbciZ0XMI+LPnju8rYgYkvzJnzaFk4I4w26KHCj/YuukndW4cOaobAXUjkl/wGrp5/ZpS1WkTTJxJrLk7GQTvc+1ZdvaeR+vZ2VMnZKONKT8IqBH4Ipmp71/GMRs5rZ84ckDmTxntcP2zBeaIY7yt5o+EQHr731flyIX47ZfYz20+dkU9X87Wgg7s2akC75x5CsS15lgn0QHe6XkzWMYplWu8JB37j1ByeA2cG5g47j59TXk5YH0/evGm7Pj7qkcnBQRl0B0VFSVXr8ZKAC9duiRff/217NsXOyOO+I7bt6Mdjv3yJKhC9B83S8mJIFHzhFs0gr1SFZ5VfzTSGGzGrcHGB/JogN7f11t9oDLB2ogivERsZc302OolwYv/zKVYCavRjFlscB0B2WqF0sXlwzHT5bd1P8iPK5aoz2OT7o6LuXV2/K9d21QvnaNgM0NY/Mo8zLYKFiwgbbr2U5Jue9lVBMYYLYKXIjZA+O+Bf27EZWndCbr15wNSNTPO5UY0frejqgq6CzYAK5fOV1ljo81E1jT2JcnYvBfNkka6DR6jpAKzxw2zeU7hHo7EBf7729HLsvnoFZvGMpD/Qt6MUUzWG27I3fMbjL2yDhoKZgqTU8cOK1dbuOxrIHBwRy6NKve9B4/UfWRGDaOXluvP2/z58yVLlswyuk97h+aNf569ZlEhVmP07j5QG2At4NLfl+my5pE32rSPM1CKdNDLbU3FsmVk296DFsYxp67CMdc9MxioF4xmUmM2NDZgCPQdYd0vWzRrGqlWo1ZcG44ncFTp1gJcOOmiIojeQkdVbmvfDvhOtO87TCYvXhUvqYyNmNGsbSPwjrLlvovq/7kzlokMVLrNgNaN8qWekra9hzwZfxMT92zinehIBo9kLp61h05s8mMVUv9+DOOqEb3buyQ3jjVIHa2SmqM8aD6JpDwUNEY95igqp7aTDARVKpSWfsNGqwkLRv3BCFDcGW+IZ/TPvXuUzwFGFbrC+z0Hx7aoLJoT72sHz91wOpFi9vfBdcbexqxpnjW41ljjMcHCUXL+5OXbDuXyCN60/VWREmWkjgNDVnvgfGLKDhzNcY9jHXTmPMJvwl210YnDByR3wSIueytNXbpGarzcyOb34PdCMhNV781Y44/FrvdGr9Pvly2QtBGRUqlaLaeOA+8vPGcYwwfVI4zetEoyAm+02Gw7cVXtP7G/+P34FbWfc7VtZ+/2zaqtMVf+QupjTHCxBSb7aCpL7R1U/61WqqhhrWxBAQAjGXGMuBehpjDjJZJgg+7Zs2dL2bJlpVy5cjJ9+nRp2LChrFu3TvXj4WvEtyPD0LfnS9DfPWTK52om9OShfVxa9K0zXjAH0Uu9zGx+UGUukjncIpOLsQVRly/FfQ6VB2T3bAXWCF4PGozMQdVp39kbMnvcx6qCbPRvZ7EjLdcDac0LNeuonuPPp45Vm1Al1zaxOTM7KmzL+jXKyd1RRQtO0dYgM1ksSxpp2Ky1jJq9TC0gjsBLEecH/9Vz3wNBNxZgFXTndy3o1lgw7RObga4ZMPIL5nK2jFUcyVC1++TZEvll5MzF8l6P+NUb63OHzLdW4UYFF1lefQUc9wu+54evFskXn46XxIlDLKpI6NM3yjQbyeJbt24pz9Z4Sc2TR4AEEPTFZt5dW+BQvcPmZcrHHypXaEfYSq6FhYUpU7WjB/fJstkT7f4MvH5wzNhMxG5orsi241dl599RcVVwLbuPYLx8jfpqRr2Gs0E3KJIrs6QKfSQzPxmiZiTjGBDgu9N3aqs1AxtkbEyKlrTvWIzfw9q8BkmhEjnSqpFybepXUcY17uLoda95FUB5NKZfZ+Wub4QtNQbe/RgTGRaWShkEouVl8/rVFt+DRB/e7bYq2HiWEJxj5rQtJg7tHU/ZE+Kgyq2nQKYwVRlHYqHPe43j1kG8E3EfGiWvEBhgw6upsJxZOqFw0bNv1zbJX7h4vDYRs2BjPmTSXOXx4AluRd+UN58vKZvXrzH8eliy+K0kRvTt2l5ebdYmTkmiR1s3YQ7livES1k2M/UwZllqeMmlKaOSRg+kUzT7obqjywHvA7PsTiTaz98DZv4+rZ8HVoFurKpd95nllumoPtOjtPHXN7jk+fD467tih+kD/sStA8YLiCVrcVn25UK0fUAPae3bjO5a7pzTCecX5zVvQ3LgwI/IVLqYCSbSSOVKP4D4x8u4AF/85o84DWsecVfolC00s5XJHxI1gXLN8iQxo97ZK0FlMBLgYW0V2dbSaxq6tv6oJANi7o5Uy0sGeCMrPFFbqUIzCfKPqU7J/j+3RtQkNp4PuSZMmqar29u3bpWfPnrJ8+XKZOnWq/PrrrzJliuMRJcRzPHr0UMJckPS4S9GSZaXL4DGq99YZsytr/trxu3rJWGNmcQYwadCyZ+h3HD3nSwv3bqx9yO5h3qDWSw2pKTa4kPugKmFkaIVRC5ejrsuP3yxVvezWFM5s6QztqLKIjW+PoWNl6tLVccoEbAxhsuEsWAgvRf9bwcfvtHnDaqlUrabdHjVUj2zJ4RGw5c8YHufiC4dWVwIv94Lu2IoUsrNPV6tpau6jPVCBWvbZVJsGJ46A42vngaMMR99gb24009nWPdrgxSqqPQH3OrLYZkGWF/JzVHJxn+J+vX//gTIrqvZSQ4tFuWBG8/ckKJQpXAaMGK/6bT/p3znuekNK7MrMe0jDkJHe8MMKpQwoWeFf2ZgRyZIkttuegcTuggULpGenD+IULY42irZGj2AcGpIXn36+VA49GbME8LhEpnLcJ21EsaxpZevGH2Vot3eVQz02Ua70HAO8k/QSbj3ol4Qzv70NGH4PW338CG5bvfWq2lCO7ttRPV/u4KjioPkyHNi7Q7LlyquCOyPCbVS6tV5AKJkAgtrBnVrFjcHRQFV5y7ErShmCiggSKkiu4FnZcjxWKWIroDl/9pSad2w9ag9BtDPBAvoVM2XLITs3b1LVWQ0l5zwZpZJBR59scPEHiSFseLVT6Eyl21q6vH/XdilqsDY5Q6GnSqtgAUEHWrzcYf33X0v0jWtSoOhTNlubzK6Xs6ZPka6DYltf0JqlB+cObvu/HrmsKnVogUACxlFPPd5vSFj+vuknNSLOFUNZDcih8d5EoGCt5EDSxez70xlp+fHDsQq0/EWMz69+nbcFgsKPZywydJY3ep9CdgxJtCb3xvoO9Qh6bzXDxQ2rVqjnyVUQiEERVv+tlpI1Zx7l5aJdK0eScSSx4KlhpBByhmMH96l/052EBsBzhIQzPHxsTYNxxBczJ0qq1KnltebvO/13sf5DPVY+d4REhGHMaXOpULW6jOjVzmNKJw3s+4/s3xs3bhHPt5nWnIJW/d1FSpZVz9PY/l0sWokSMk4H3aGhoZIiRQqJiIiQ/PnzS4YMsZvSNGnSODzpxLP0HjFFPp4RO8LG12CM0swVG1UQifEbzla8IU0f3qudzJv8b1+pKxWHolnD4xZ03H+Q3GKm+E/fLLPIhm4/eVU2Hr6kNkOobqP3FAv4nQeYDf3vSxsveizqG3/4Rm5H31Tzma0lvNbO0I7AxrdknkwqgINs+ct509W/CemjkWulM9lxSM7Q72k0q9nyuJM6lKbiPOJF2rvN6xazcp1JCLgSeCNQ0SrdCJYxBk/f6+MKr7VoK0+Ve1pleteu/J9TfxcLJsZ+4R43IgWy804EuEgMoa8JhiPo73ZmrBmy4ti8o8cW/cM///idXL180eLYINW11y9pa4F+9qm80vPjCXLs0H65eO6MxVgzsxJejWOXMaLkkXLBr/ZSA4emX+lMJC3efPNNKVown2RL8chCweIsmBjw55koGTOotzKf1LspO3Md9YSHpZRvvv1Wrl29olzqsQmBC/Gu09eclprb6glHRerg3h2qB9cesaMUbV//HOnDZdKMWapfdtxA91yr7ck4EfRq6p0De3ZIkZJlbH6vvePV+ruRsNLG4EBKbR2AAShDVEB7/Kr8cviyelbgeWCPX39aJUmSJovntpzYyf1L+rBkUrdWdXmpUTOZPXaoarvSwHsQCQCsJUgA4I91Zd6sJBY/S39P4Vn45/RJKWbgEO4KUAR9+P5bDiugtsD9tHLJPKn0Qm2bM8DNPO8aEWHJpWj2CNXb2rxWRdlk0CuLc4dKHbxNEABCPQDlmj3j0ajrN1Tby9PPO29GZg32PH3eeUPNHLZugcH7Eyole+A5cWbkIAwzl236M563jB6sAeXzRCiZr62EJpIFuF4zRg9SLUr2wHMESTSerXUHLsgvRy4phZvWsoH7BYk8qAdcQSWvUyRRz3nhbBHSttdgVcjRrjf2RrbULPgdIM/Wj011FSSKxn/+jeR+IpN2FahO+o6eplr9Pp8yxqWf0axddzWi1xWvJu39heC2dI60ki9Tauk7aqpKfMKg0NVEgBFQXy37+U+pXvc1m61ittSWeXT93bgfe348UXlUaGbICR2ng26cpLt3YzNQmzZtivt8dHTCaXQPJvyZ6EDADROvnq0bqQyfM5u5L2ZMkCuXzsubOqmnhhOmomrTXDJH2rgML+aQ44UwYUgvOagb1YVDMxqFgGccztx4gUMWiP8iCMQmAlVzuEHq0felOAN6wLOkTa4qrzPHDJElsyfHGbA4Y8R0zioYyluomIydv9yiJ96VTQ/uI1RuSpQqrfrjsSj/b16sMZ1ZYmcuXnN6U3/tzoO4RALMQ8zMFjbznho6dYHqixrVp4Ma+2YGzAd+p35Vu3Nsbc2gtEeBjGHyTruO6p5C5tmMMZY1WJAWzRgn5StXs8jKu3pPIhnUsnFDNU4wU9YcysxGu3YIEsy2P2Czi40YqpG4djUbNHb4d8z4NgAcT6u3Gsm4D9urnlFXQAV8zdr1asP9os6t2qjdwhlKFy8qi79aLscP/SUfdX1HJRKxkYY002xvPM6drZFBDx88lFebv6eqFfYw475eu0oF+Xj8NOWmr3cFdxZ7j7aWOEPi8+jBv2xK4mFCaE/loE8m4DnuPWqq+oc95SPy848rVYXG2g8l1JmF5wnwUOjYd4jqYx7Vt6NaD83y0GTQjSq3/rzfir6hEgbFSrvWl2wNxo7dvXNHRvRq79LGfN/ObUoWDP8Ld593DYy1rFy+tBrtN6pPx3hKB8Pj+Mf2zHT4LiAoWrxhtxpL5y6YEtJ/3EzZ/usG+dggoIFKyValFu80VMOdzX0Zqa705IpIGausy55WKuWNVO83KIqM1vqYxzEqUYQqrxlwrNbHu+67ryVGYuT52q+IK2Ad1XxRYADZuFEDadC0jeoTBqhgo6pubf6lVbidmW9uDyT6oazTfD7cAQnCVp36yhczJ6ikhjN7Iagm0mfMLKUqVnbp39bnj3GN8f6sWjy39BkxSRVTMCLRU+D3ShWWOi45YGSKaot8GcIkW7p/1yz0hPcZNVV+Xfu9UicmdEyvMjdvxmbu1q5dK8mSJYurbmvcvn1bZs50vjpGXAeyO1RN/Qns/2GIgCAVFWZHxkdg55af1UsJ7rG58hWM/zOdTCRgoUHgjc0cXjYd+g1Xzsk9W79mSl4MSRgWSE2eikoCKlgNmr4TL8CHOZqrFM4cLtVr15Pm7XvIZxOGx2WIj1+Ktpul18D3WMtQsSmFqZOjBcOMvA+SybK50kn73oPUTPdPxwy2MNoyAyTGx564mppFvzmBM+yY/l3EE2BT3XvkFOn20TiHSQmADT1c5lGlzZglm0eDbtyXpXJGyJBxM9QGfXDn1jZNpuz9jHd7DJTWXfrFfQ7Sa7Mjr2z1dxfOkT7OzGbh9FhXXySo0P5gZtOgje6Cozp64As/Vdrh3zG7SON3Hj58uGz/fbNMGdbL5SrtT98sVe72+mNL70I/tzV1qlWRT+cvkczZckpoaJK4ChEMahz1naIH/ICBp4RGRIaMyrjJyMhRj6MZ4xpd328po2d8rvwlXMWee7kmLY++eUO59ttqEUltR1quB4E5VBzYiA6ePE+peiC3dwesT+gVx6gfa1xRPeDcP1M0h/QZOVmNlrzrhJu42Up3lM59H+A+HjZtoc2qsrPgXQezz51bNsmYDzs5lTgA+3b/oebu2goWsC6j59NZimRNI2MmTZcS5Z+RQR1bqoSoI0UAvByslSZQHGBdglICLViuBlf4HdAvi/sEa2WFKtVl4ITZsmX9ajVyyhpIsyF71weNeH8hOWDth2IPJBvff7W6TYUU1iOMqYQ6RK9kwp6ocv70hrOS23T9UJltoT0GM+ddUjcsna88eRwlA8wWAhCMjRk3XrXT4B5E8g6tGjtORiklA/x50BaIlhJPBdxg0tA+qlXIU7z5TgdVuMBcd7PPEvaCLWpXtFDLOItRexkUjo1friFzVm6SilWdm6NuL/n/XoPn5advv3T6na5v0dSrL5Fc6zFsgl0zuoSC6TdhlSpV5Pz58zZl5BkzZpTy5d3rMSLOgU1I9HXzY0q8RZ3XmsiAcbNk87rVMm5QN7t9g3gJjR/cQ0o/XcXC0MjdzQ8WHgSMWOBR6YYpWKHipdWi4qw0FZvdud//Gtevop/R6srmwSJoD0+mTFhUBr9vB9VLh30sFmJ71TEs3nvOXLP43J4/NkvXt1+JN77E6Nxgk2AGtZnIk17a9hygzE30Mn2zQFJpxjle23he0H2vcmh10LfmDHhX4f7ERgsz5pEYMnLWxj07flB3OXPimArU7cmjnV1g9MmhKsVzy7Cp89QxnD5+xPTf1UaOYeHUj+LKE+nePaltdjKEJ1f3++dTP1GjiACq147m40KGDtk7QAINs8nNqG+SmgwUwXPPPSdz586V7/+3WGZ/MsTpahxUBeg9fKlR07hjQzCXLNTcM+GI5q/Xl+GfTFAbetxj6E1DW4C9Gd7YtCKpYasyh/ckHJIdvbuceVfiezu3aSrhYanUyDiYwHmyp1vzZUCSYOD42apFw9l+bqPNGRJLcEie+/1v6p3kDujlRVsW3r/WuNxqkDyJvP5yLRn92f9U9QeKEU9Wuq0nXezfvd2lij/G9mB9NAKBDgJvjD1ytiKGSvn0L3+06SmSyoSqwRalcqeX8bPmS7bceWXsgK4Ok2547uDhgjFDWDMRpKHlAPOpGz9fUvnIuAraCVBBrpg3QsrlTqeSQpCqN36nk6z/7qt4ShwcKoJFBIlYD7WA29nxVjCVO35on01pOVrsMCrSCLzvimUNjxd4QxHYb+yn8vjxI6VUdHaPBBk41i9txrYrGBUCMOoQVe/hvT5QijC863FNcS3hz4O2QHe8Y6xBW9D3yz6PMxP1BDjnME4dO3e52ndATWBkDKg3IZw8rI8UKFZSMmbJ7vK/a6s9RrXBVC2v5PxQL2KNcgeYKMMoVStMGI1/dEQipawMt1A8IRGKxD32OnjHJVRMn6nSpUtLxYoV5eDBgxaf3717t5qrSnzP7ehoSRnmvns5JEia46GrVK31surN2LjqG5WRxgJj5OKIyvjQqZ+rjY+tRdoZQyhruWypJxVvBN6Qf731bmdJG5neqewtjEEgOdIHD6jMaTNw3QFSYPx+OFeZsmSPk8BjIUG/uX6msD6wweJt3e6yYuEc1VeFWeX2sDfKwQi8CCFRGzB+pupR0kxCnAGbCzNzS2Emo8n+UYlAMOpovrOrQJYJx82WLz2jnKchWdRk5FCN/LzmO+k+bLxDB3dXg24tAfLai8/IsvU7lJERgitHEj+cl+4tGsqnowdbfD596mTxxkS5Au7zp7KlkQ7deymTnZF9OiivBWzssdmJHW0Sf7OLgBFGUVpfqDaexAzOKnmbNWsmkydPluWL5siJQ/YrXtbgHQnlhn4mMzYinqQI5p/LfRncuZVKpuF8QWq+61RUvE2iFnBjA2kLBD5Th/dTLTj2cPZdiQRNqRxpZOaYwUoS76zawpZRnN6XQSUe7LwvzPb/ARgWoj8R94u2ycPG0Zl7TQPJSTgD22pTcDXoBlCb5IhMqYKX1i9XUeuII4zaneJ9z+MYi75W/PwuzV6WDd8vd+r4kLjA2J4yOdPaTNI9V/sVmf3tz3EeAo5M9/B+QLsCKl/aTGBnxsOZfTdVLJhdxs5eoqrK+NhM3ycq21gztWds8cxJkjYivXrnugqUMfj3UyaNTWKjkozz+na77jJ+wbc2K+g4XPRCw0jPlXnSu7f9phzXjUzU0MftSLqvBd4w19IDAyscd+1X37LbK24E2u5g9gUVgitga2VrAghMId9u3ly2bFgjM54Yq3kLvKtwPxUt7Rl/BD2a9BoqiC5NX1az4ZEA1v8+2L9BXQKvHxi3utMuau/1BYVm3vQplenuoI4t5J9TJ13+dzD+Nk26CCn+ZAKAq893stAQtV+3fu/Omzxa+r7X2CPTNgIR01sfVBpatmwplStXVk7lhw8fljfeeEO5zELiSnwLHtxbt26ql7G7oIL7TL70UrlAeimVM63LG3mMjVjw0x9StFS52FmgTespg5ZFM8arjXyXZvXVCw7joFBNtoWz8nI9WIBQ8UYiAYvsq2+/q45l9ddfyLxJo+xmNBfPmiSTPuptOMcS8i1PgOPDogKH5ylLV6vsHrK56InTAm9NloYAXBnxGLihwo1y8/ofpEGzdxy+qLMYyMscAbO4YtnSqT44BKYtaj+tnF/Ngg3l7tNRds1icA//retn16oQRUt5RzEDOeDna35X0q/vln6uMvxnnkjrEJRNXbbaobwJCwSM1NwBQcezRbMrt2TMtO7YuI6sWDTbsHqFxFX3lq8q4x69qR+SN1iwPOXpgN8LI8eGT5gmTd/vIktnT5F9O2Mz4tgook8ZM2URXEEWDfMquEdDSr1n229qY3Hl4gXz/54Lx92hQwc5duyYvF77OUmUKMZURRFyYhjJtO7cVyXiNDJ4OOjG+StfIKt0/+gTtSkZN6i7SqigHQQmjjiHaA/Bc/3HyShlUGSPH79ZJnkKFpF8hYt7/DyGJU8iMz+dKVcunlfJJmeqpraKswi4EVwgiMdzZc+l35GJmlHgrbneYv34a+fvMrBDC6cMCcGyOVOVVwWSb54OukGhTKmlQO5syvQK68issUPtqjLsSfVtzef+/efYd7C1CZwjNHUBzn2lfJFSJGu4OqfWAXj2XHnVf3H92r9Ry+b4I9zbSAJiLNw/p+w7IzuTZDECx1itdAHJmTuPqkxijCfmeJsNxuAyDnd1jBV11bUcj5m1GSmS/BXzREhEeErVMgQzKDxPRsozzfjNFZAcRgsZChaujK6MPf5EUiJbmnhtPVCltOzYW/1stP2Zqfji2mfJkUvNqXd1/cFx2KuOvtOkkQwcMVapfYyk+55ix+aNatxqrnzumajZAwUWeHN88ekEaV67ojStUTbO8R1tZjiGD8fMUL4q7uDICDJPhtQyY+5iCQtPK/3bv60CfWfB+/fnNSuVV44W9znr12BdhIBSQ8/7PQapPm/EDqecUAMGC07VG4YMGSLdunWTF198UYoXL676vLds2SIrV6703hESQ9Dv8vjRI0mVyvVgUHtGtRc3sreoABXIlNrmCBpHoP9OezE3avmB6nGbP2W0nDp2WIqWKquO2xHubn6wGGJsgj4DhxcMXt5vPl9CuQ2fO/OvkRUCmukjB8rciSNUn7m1ZAoBjjsvFmtyRaZSVXNtA4A5um0b1VBBP15q2JAjS48AHJVEI4nqrHFDJTJjFnmx/usOJVzIzLtq/oaZuTly5VaJlKHd3nNKmhRrUnctnjxS40zUHSUd07gWdUUZhNnrp3YXyD+xyfjqtwMy/X8/xfUh4r9mZoOHpwj1SKCLzS+SQ6+93UqZe00bMUCaVi+jNrHaQgNpf9dmL8vd27dl7OcrVA8eQLDuqSSQddW0XJ4M0q13P5WcKP10ZbWxxQb33OVrqk950+FL6g+M1nBfoko/qFMr1S5Sy4bbu+G/5eI5zJEjh0oIrZo3WVrVfdYwQaaBEW0t6lSKZ8IEJYezbu9mwPuz2ztNZeCYqWrU1bDu76uAFvc41AK7Tl1Tz7Ujx12MINuyfo16th3day54fykqlSspC5d9rZ5nOBCbDWBsyeX/uR77XoexFGZzG8m3tXvXjImakbEW5NFQR6GVqULlF1TrEM6zmb5JtPF8s3iu8hywNcYs1M11RwU22dNK/2EjVS/+/+ZNlwHtmtnc3D4yUbG1Vj5t3fiTFClZTiWUnUEf+CLYQWUeExWezhv5RH1l+f2YvwvZa7fmrygTJuv7s98HzeTbxXPlg94fqR5ze3hi7cSajip98mRJJE/BwjJxSC+ZMWqQw/tWOXWPGqiSV7amUZh9XxsFiVhby+VKp1RHGOGK+emDOrZyezSfBhQjeEZL2+iXdzQb2dp/AMeaL2NY3N5PA+oPnNPOzerZ7SvGONHW9Sq7VSk1e9yDenWRdl1i/W+s70FPAY8ItFVp71mYz0HB8HS+SKUQRPEGbtuQ72PPZtQf7wjs897tPkC+/OUvpfKEkZ+WAG7XZ6jM/+F3NfLVXcysqU8XzSWT5i6Ra1cuy5DOzhtTQlqOyQm1X23iUruQEXj/IAmoHT4UAvCsSBeZQfq821glsxISppfsCxcuSOfOnWXYsGFStGhRSZIkiap8V6jgGQdN4hwhIaEyeNJcl+cZQxaFynbVghkMgzK8YFDxdnVTh8wpnCjHzV8hq3adkmlf/qj6XFA59daG3HoDjAUGI77A663aycK125Wp1rGDf0nLOpXiFo4P2zaRVf9bIO/1HCRN23a1/D0SJ5J8Gd2XlVuDpIaW2IDpUOM2HdXi0v+DpnH9u/YW4gO7t8s73fpbVO+McGWRsH4hVi6YUUZNnS0Fi5dU5woSbbPAgRT9ddayOlT1NWmyBpIdU5etEV+AhRByPUfnzxpPJl+wkatcKIsMGTNRyTqrv9xIjVrCplZTM+QpWFTGfb48rgIF8qYPc7uP217gDan5U4Vi/72/jx1SCQEY+SDDffLYEXlwPzZohMle56b1JGuO3DJo4meGlRgj8Hi72kKi0bNrRylZqqTKhqO6hDYNfVURFZu+77+l/h3rarGrbu9mwLt0QNe2Mn7mAtVHql1LZ/jmizmSOCREajhIqLmrCmpQp4ZM/vQz2fvHFouRcc72dKONRHu+UeXHTHBUwjzdmgF5NAJv3GcffjJDJXqQpEI1zB5Ivgzp0kayZM+pTI5s4WxfohG430rlSCdtO3aWETOXyIkjB20GMRdu3LOZkNTQG0bh52zd9JNUrVnP6eOyZVyI9wgSqxXzRFqsFUjwjV/wjaQKC5eOb72kvDCQMMcGGMmuA3u2q9/vlSatHe4zXDGetPW+rJA/k3QfMkY69h8hXy+YqZ59e6POcMzwmkASxB1Fpr1JB7jmqCKXLFpQhkz5XAWIn/R33H9uBqxPk774Tqq91NDw3Dq7HuFYoWyESko/lx7S+NGffakKOa3rVVEqDb3KAUkETFzBmDS062XK6nrvMYhMZU5pNHnsKJk8Z6HD+eSuoCZjdO4b13aEIkOJ7GnUtUaSBwm0KgUyKM8TJLmxX8OEFwSIrjrewwMAZqha0gy/lz3VpzOY2avj+terUlZGTJsrj2MeS5Ikzik/CpcoIwt+3KaKMADLjyf2RNnUuY9t1wBod8D7JSQ0xGsJF3+RKMbkmyFlypRSqFAhFXTXrVtXVq9ereao9u/fX3r27CkJhRs3biizuOvXr0t4uGsPly/AeCvNbdsVsMDiBeII9G0ev3RLOYD6imqFM7pd7daAHPbA+RsWck4YHf3y03eqwogMJ4KJQk+VMpT3IOvp7mghe5y7fkcZveApRNVuVJ/2KqGCIAySNT14VG9ej1I93NiAwXTDUSUMi4je1dRV8G/vOHpW3m/RVPVdz1n5i9MV3wKZwlSVH9Wyk1duyQmdyzkWdVT5nQmCsYG//eCRqd5IT1E6Z1qn57Q7c4/iPOM82NogIpkEeainng97QEJ+7FK0/H38qIwd0E3JegHMrAZOmKMkcisXz5MmbbsqBYFZsLBWK+T+RgPnaeykqTJ+XGyvHIy2UHWDEdzkYR+qxMonc7+KV4mDEZKzEmdX2Hfmqpy78UAdG1QccE4388zA5Ozo/r0WPej2lCzlctv3dHDEsbOX5e+bj+Tu3XtqE2bvGBG8QUaNUUFIMNx/9Fj1rcNlGIqhxtVKSZP3u0iT9zob/n1UVzWpuKvEelzciO2V3fWHFChWQhkfYlwdqiPWyR8EEJAXj57zZZxaxGjDig22JwJv/fOz/+xlCQ1FFfSR3Lp5PZ7/BgIfBLxG1X/0cqOFQ39fzBr7kXw8fZGp5LWeZ/OnN6UwQAvJntMY+/hvewaULkgGwmgN7yco1+o3bmUqWFCzo928P43OC0ZJbVizSgW33YeOM1RWXLl0waHzv1nwznWUPMB7HF4Ny5Z9qVQYjd/tJG26fCjeQqvKugoSPvvOXrdQm0HdAIUGfBOeq11fOUpDLv9ewxfk6qULyjQPSjF3xmuheoxnzRkws3v+5wuVqsUdxYItUNVG0GcWKFCwb9OfO3+DIhlUqmbAZI3dp6Lk+p2Hqv0C0z1QvS5UvJTNv4OEG54n/fsValKoZTzF7fsPlR+QFtugwIR3XfaIFGr6T0KIHU0H3UuWLJHGjS3HbOzcuVPq1asnDRs2lKlTE8Z8tWAJur/b8qes+HKpcma2JZezBwJus1VQZNv/+ue6ZE8bay6GRU/LwKPPCVkqZMzRr+iJUQ41inpmobTeAB256NxsTF896Oj1/OufG6o/FhvHhTPGK1MNsGn1N5K7QGFVlUdFBxK2sfOW+y1IPHz6oqz59Q8lcUTyImny5E5VEDBP/d7Dx/FkqmuWL5GJH/WWpRv3xEs22AKSr8iwpPKnHZdoT4Jg8bkCGdyu0triTNRtJdu2pTqFQSAk6cjC+wpszHB+b997oNxqYeqWLEVK5SbtKvg9nivo2pgZI05fvi5f/bBBipV5Wr2fIH9EoN1p4Ki4dhdPBqnOgOvZu3tX9exibF3XIWMla87cht+LpRibDOv50faAOVKZnM6ZIBlxLfqOPPd8NSlW9mlp1amPqeSAVlnR7le0RYwf1EO5Ilufd1fWHXvcuIuA4UacydjxQ/ulQ+M6aoOGfmf8Fz3x9d5ors7r7eibykfDFpAHo/rnabCJ3HP6ugzr00V+W7dKVWhhWKYHwTCea+sJE2hFwJrqLliboWgzC5y2McoO65G7YB4vTAY9DYoBCLwvXrqqKogAKiy4cqdNF6kksH/t3CaTvvjebWNOJHcrOhFY/H3lloz6ZLxEZsyk+vtdBYnoPu81ltad+hoqGotlC1cjH90BzwaSWP9cu2vR9gL1AAJwGKZtWvOtbP9tozRq0dZwxKuzYN12tj0KCdYmLdrI0oXzVDKjRfuebs/VnjtxpGqhQmvZM/kjXWrDu3jjrvypjEbF70Cd6kxbKJJEf1+9LdNnzlajWq9HXZU6rzWV93sNjpdEh4Fjp6Z15amyT0uv4ZPcupaOwF4Oe/UzV/8t9P0ng25bnDx5UurUqSMHDhyQhECwBN3Tvlgh7Zs2lPk/bLW5ibOFK1l9mCfp58FCUnj11j0lddUHIXiQHzx+rIJvjHhAJSTRkwcJBlQIAJFNv6PLEKo5niGJ1QYKFTxUur0BspMY42Nm5AQ2hkWzhHstwDLaRKDvUz+HG4F2y5cqxcnUsOC16drfqf4fjDaBEZGnjxWzxVs1flUSJw5RJiCaU6erDGj3tprvC0mjs4sM7puLN++poBUVN1sBc/LQELnz4KHNoNYRSDBhc+xN8FzsP3ddue9aV8RKZk8bz8zHF+B6o4KDEWKeAMEFWls8nRzAeCBcf3uO/pDSelNebsSR89dl4ZJlMmX4AFU1QgUbZnX6vlyYwn06ZogcPfinTFr0vekNpbvVLj2jRo+RPr17qaAVwaG7xj5GuLq5tVWtOfDEBR49qRihiFFGCBC0ntrJS34wpcLwRABjC6x9G3cfkSF9u8svP34nlWvUlTfatLdIXOH5hgIAEleANQqjprRkIqrNxUqVV4kEZ3HlHsEzj2DCHTUdwIbc1jgrT1x/HCPeS1gjPx0zWMn5b0RdVTPMK1StLi81amZzSoo3fwfsf1Cdxfto7MBukjNPfuUnYLYFB2AOMvwW5q7abNFeBJATwx7Ok21G2jqKfRL2d94KJF1VGuEa9x08TMZ8PEQKFi0ho+Z86VSCUs+JIwfkvQbVpP/YT6VO/Vflmfyur0c4V1h70ErnT9Crj9YBZ1FFtTNR8u3SheoZQtHj4xmLlMcNikBQuUDdcvPGdZmw8FuViPHFenrhxl2lJsA7kEG3FVFRUZIunXc3o74iWILuMTMXSK/3mytzBmdNVbyV1Xf0wtSqJwjMT0fdlht3HkqKpIklZ0TsrGFUBe4+eGzakdMV8G/s/Puazfm4WjCXL0MqjzlDu1ORh0TuyL49ys0xc7acTh+TN6W0/1uxUlo0ayJZcuRW0kOMIHEFZNRfr1xM3uk+QLnNmwUBt36MG17OV27dkwdPFj9cY5xHGCQhiYJgD8mjE5dvqfvP2eDbE9JYM+D52HX6WpzzOyS9MBHSJ738gStqESMwnhDTEryxCT947qZarI3AO6Zy/vQ+S6Tpwb148PRlmThhnKxc+rnM/maTqrzCvAhBwaY1K5Uzc4d+w5V6ydNtQmb59tuV8s5778m1qChp/E4Had7eXOsYJhukTpMurtfPExVXV5RCruCL+wLP9PHL0TJ/4WKZMXqwkurOXLHRonKIVzveZ6mShqq2Di0xDfln17fry7vdBkijlm2d/re1th5Xq6BHLhibeZqhfJ4Ij/pg2Kos4xi9AZIhuDdcefcicbL3TJSMHNRPli+cJfmKFJeewyYq5ZqjdRwy6vcaVlO908M/XRzv61gTKuSJ8Or7CiqLm/ewJ3skt+95RkbticT1up9/k/ov1ZZaDd+Sdn2HuvQzJg3tI7+tXSULf9oueTOndbtaG3utr1kUTXyNq8+5dvxQsx44fEzmT4n1TIBaCP4NZ04ek4LFSkrvkVPi7fGQPLdW6Hh6v/7X2RvKwJaV7gRKsATdg8dOkyE92sv3u/5W/WzO4M2sfjBga3MOqTLkcJhp6E+wiUQG3xOZU7O9fK7yx87d8sorr8iFc2eV87utXk57YJwbeoYXrd3hlHN54Syplauxq/fAlej7arHBC/3Krfuqp9peMgYGKmil8AVIDBx7YjSHMX6enivtzr158PxNC6WKs3i6D8waPNeQ5lorWlytBHi6In/4/HW5fif2/A3v+YEydoRbdNP3u0r6TFmc+nmojFqPXHGX6OhoGfjRcEmdNY9UqVlf9fXaG7WENpOWdZ9RY436fTLD5vehIoLKiDfAc7v79DWJdmEsk3XyzpugqrT31BU5cvCAkj0juEIlyZYhKqZsYEQW3oufzP3apZFXFfJGuDW2697DR3LsovO+LigwP18wo0+SXBsOXfSKt4e79wYSF8cv35I1G36RYT0+UP4OSLTAMNTebHMoG5CQgwEtJnpY4w1Zrz2QrL4cfV8pS9xp5UJ/vycmR/z2228Sljm3XHkQqq67M8UIKAjfbfC8Siq+3a6HqX59Z1ozYBDrqSSFr1UlSLRg76GtnTAoRXLYyAsDrYLuKATMgvsNrQ/+UPl5I3b0XXMg8SioDiZJmszpgBsZUn8Hlf4Gsnps/iKuJVUvyOzpUkj6VMm8MkbIFSDBR7AMeT4k0+4E324q6xxSvkwpOXH0sHw0bLg8TJIqnqrBDGdPnVSSVmdHhYW68cvhHtD3lkKCnycylUTff6gWTCw6l2/dU/JKtDzg43Q+vD9SJQ1RlS84iQdKwK3dmxXzJFFyc8h6XcHbJnAI7qCWgSHL5SceE6iu5/SSzNUZUPUrnye92twcvRStFCLu4I1zGRYWJuNGD4/r5x/WvYMUK11BTaOwfq7Razl30kg1Fuudbv3s/lxvGlKi2oIKGjaMCA7NvjNR5faW/NnWOahSKLNkiwxTPYsbflgho/p0kOJlKsozL9SSSi/UjpMSw+diyscfSkT6jGpMmisBNyq1qd0MKJKFhqjETqbwZOqZMtOeBcKSJfGZqgS/o6erjEjCu/vOwPMC9+vmr7wo5ctsldVrflKOzAi4oWJb/fVi9VyhBUJbN/HfdSu/kloNGxsG3ACJYl8S+mS9xPsLFd07Dx6phHey0MRKXm3GywdJT0/tsZ599ln1330HD0vd+nWldKXnlBO5Gbn5vMmjJCJ9BjXSFqZungq4AfbW+INzArNYT7VkmcETzxrehbjOUI6cv3FHuZXbwtNti/bWuEAPuJ3B7Z7uhEawVLrHzf5Cfli5XHqPmGL67+ROn1ItAP6QTQcqyKL5wgnak73e/nKCdwQCCVQYZ4wepCSzLTv1MZ0U0lwqncHbzvKaLBSgEu7tf0sPKsnX7twPaEWKq1l9X/TG66ve2ECUyJHGrWqft55tJNbOXnO+1UH/Ts+f0XsVr0ePHssHXXrIrCnjVWLs+ToNpECRpyRH3gJy9u/jatYrZmC37TVEXmvxvs2f4w13cHvPLDa8mLrhCE8Zu7kC5t3ff/BINqxaIRtWLZedW35Wvej13mwunQeOlj93bJWtG36Ut97rHGcW5ixZ0iaXYlk9py5AwL3nzDVTvd6+asfRJOZ4Fzm7m0UyDu1I+tYE3Kt478Kl39NJg5t3H8jhC9GqdWjpnCmyYNpYNaYrPF2EGhXa/aNxaqoKRg0igLTl7YA50r401DQjA4YZG9q2rBUH2G4WyJha3Q+e5tKlSzJ+/HiZOHGSpImIlJ7DJymzL0cFq0vnz6qeZSRWSnvAiNII9MZvP+n8yEhX8bSCFccPxaUtnxxv+jUEIz4zUktoJOSRYYEkUyXOEX3voZy8fEsFOmY36FjsqhfxvBO8PenxrlPXZNlnU+WziSOUIQd6QjFiytp3AK8dfA+qOsjouwICt4SUAQ1WYMCDyrfZ95GvPSWcVV74Y8N6+uodNT7QWVWLrzY+sz6bL+MnTlJjq7LmzCPzVm1WI8LQG/nKW61syqM1vLm5tYU2Pxzn9+bdhxayWNwOkA672gPpCTAOTHNfB+jpR+CNABtSfU9QJlc6j3uk4DwiyD1/467dhJuvTQuRxELFFX3ouObY2WJaASqPaCeCMurmvQcqoYnrj0qtdnyQ0OPzCMBRzfWkQZkt932s5/uPHJe1K7+W27eiVbU7c7Yc8dztrUFSACMXA/GdhnsDwdql6HsqWEOSDSZY3k54Hjt2TJq3aCFbNm9WEyKsfTEwc3zJrElS9/W3LcwInXX8dvZ+/PXIZfEV3njekGSD2hIu59bJFG+MTw1mGHR7+cT5mx93HFYbCWfGhXm7v5d4H2wezkbdURllWxlIT89DNgs2LXDcBah+LZoxXlVwIBuHYQkchqeN7C95ChRRX/928VyHFTJv9ioSz1YXj1yMNlW1dXYm6n/p2UaQCMWImfmvkEVWzBPhMwkv+jpXbtknFy9eknyFizn1d/1ZUdYSLw8xWePRY3VuUSX0pgGQGTDyypvyU28ZFlo/96eu3lbGb9blG5jmeTt4tXevYjSlJ6XD3jp/cAzHem42aeltT4xg5dGjRzJt2jQpWa6ipMySXxbOmyPrv/9ajbq8dvWKUg50HzpeqtZ62SfvJVzb9Qcvii9AIqZSXu/t75FAQDILLWVaopDxhCXs6U7gTBjWX86cOS3j5q8w9f2QGDPgDn6QOUZ2Fn3oZ6LuqA2PrR47uHb7kuRJEku6VEnUuCuYxaBftXWXvrJr668qK4+exKMH/pIfvvpCQkJC3Qq4/fH7Edsg8EPVNVdkShU4nrhyy6axUeIArNAEyrONqjXM0aAaUdJ9G8E3KnjYMPrSiR19nVmzZpXUEc4l8hDcoh/Yn6j3Twj+JPbYyDJ3QT+sN8ntgyo+7j+sR5hljeomqslo6cDv5q+AW7tX/T3twez5Q9CHP6gQo5AChQbGqtrSoAaSrDyQCAkJkY4dO8Z9/HNESsmVPZuUq1RFsucpqMwqrRV33twT49riGTDrgeDus+7N3wXvcLSm5k2fSiWJoCjBfo84D+XlQVrpfu7FOqofbOi0Baa+PyIsqZTxsbyP+KaCE3X7gTIPirp936L67St3SWuwaYAkyZbRFvoWEyVK7JIxEEDMBllTsazhPukRJa7dlzDiwljA+48eSdKQEGXqBG8CmOn4ygU+mNFG4F2+eT+2rSQG0tekkjF1MpV084e8dMffV+PNkPfmKJuEDJIqkBh7AyQ/y+by3kgpRxW+B48fKwM24rpqDKohJNatW07cmdrxXwT3I84jJP1ICOmTGc8XyuDV5Mz2k1c9YvCnecYaqciQ6C7gI+8EYhtWuhM4t6KjJU2k+YpDBvZeJEiw8UbPnta3B/kkNuvYoPsL7Xgglzt3444axaXvp0yazHU5F+SCMAyhrDzw70u4m1o7nKKKS8S0Oklzwy0qgZEAdnZiACrygeAaH4jAmFH1IUff8+i4K1SlPGme5kqFL1liBtzugKolDBLzpg+TrSeuWPTOp/ORa3RCAfejZuKmL0yg/cLbaggUuiDLRgIaRRBc17sPHiv/Dv01xeehXIJCBFs3mKgiuYl9HNqxIlMlU4ls+CgggYDRiHBeR4WbZmbBBXUqQQocGLM8GS3iCEiX+GD+N0Dl18+tinGgook/WBiw8MCxFaNGtEUP+3eMlbl1/6HDTScCEATb//Vxd4T4E2cmIUBdhZF3gWj4FAjAsCtNtjRqM33z3kOdMghJU7gHP5Doew9MG2diE44KKFQQVAAlDJREOSSx3JZHcf3cgd6nHizvL1/sJXD9sPfOYfX53JEp5f6jx3L3/mO5/eChKlLolSEpkqYwcCJP9OT5ThnwU3eIbfj0BnHQnTJValMbH/RaEuIvtH4gyfCvE/u/s6gTKdMbZHBv3XskWEf+uX5XsqRJLlhS8HX0sGFR8mePICEkdu6zIxBjo9LqT+O0YALvOCh3jNQ7cNVGMI7efshjYWKE96FmCpdIEqngXY1lyhRGSXcCRF+NRUKFuE5sMuqRClj9eS7xzCPIxp804rwZLAPu4IVBd5CybO1Wibp51+73IMPGgJsEGtZGMNhU6HvU2J9ESGBiJC9HwIfNI3r30U6AnnMG3J4B55Uqtf82mmEonjO0JBD3zyWS+P6eXkD+mzDoDmKnRntGVEWyhtOsiBBCiMewnhgAuSvmtdI0ixDvoFU1w1Mk4XPmJlrbhadn1xNilgSp15w6darkzp1bkidPLhUrVpRt27ZJQiIqKkpaN6wp+3b9YfMlnSWc0j5CCCGel5drwTbmhDPgJsR7YNQdYKDouQRGehoLEz+R4ILupUuXSrdu3WTQoEGyc+dOKVmypNSqVUsuXvTNkHpfcOHCBflr9w559Ci2N9aa8BShPp3fSgghJOEDUydU3EpkT6PG9tEkjRDvEpI4sTId5ZhFzyQwYO7qzZnWhPyngu5x48bJu+++K61atZKiRYvKjBkzJGXKlPLZZ59JQkFLIKSNsJzBjB4VOFtynBIhhBBPkzE8uVTIEyEpk7IzjRBftXRkCEvOHmSPnMvEkoMzzokfSVBB9/3792XHjh1So0aNuM8lTpxYfbxlyxZJKFy6dEn9N21EpMXn06dOKpXyRcY6RRNCCCGEkKBu6aCBmmdImzKJZAqnGR3xHwkqXX358mV59OiRZMqUyeLz+PjgwYOGf+fevXvqj8aNGzckGCrdMFILC09r8flUT6oPlJYTQgghhAQ3UJWk5mxuj4DpCoT4kwRV6XaFESNGSJo0aeL+5MhhPcY+8KhevboMGjtNVfH1QFpOCCGEEEKCH8xhZyGFkIRBggq606dPryrAMBrTg48zZ85s+Hf69u0r169fj/tz+vRpCXQKFiwotV9pFO/zSUMT1OUkhBBCCCGEkKAnQUVpSZMmlbJly8q6deviPvf48WP1caVKlQz/TrJkySQ8PNziT0KZoUoIIYQQQgghxL8kOD0yxoW1aNFCypUrJxUqVJAJEybIrVu3lJv5f2UGISGEEEIIIYSQwCDBBd1vvvmmcvceOHCgnD9/XkqVKiWrV6+OZ66WEAlJxKCbEEIIIYQQQgKJRDExMTH+PohAAu7lMFRDf3cgS83/OHlVrt9+EPcxPNVeKJzwEwuEEEIIIYQQEkyxY4Lq6f4vE2LlZE4IIYQQQgghxP8wUksgUFpOCCGEEEIIIYEHg+4EAk3UCCGEEEIIISTwYNCdQAgNoYkaIYQQQgghhAQaDLoTCKx0E0IIIYQQQkjgwaA7gcCebkIIIYQQQggJPBh0JxBY6SaEEEIIIYSQwINBdwIhaSgvJSGEEEIIIYQEGozUEghJQngpCSGEEEIIISTQYKSWQEhC93JCCCGEEEIICTgYdCcQWOkmhBBCCCGEkMCDQXcCgUE3IYQQQgghhAQeDLoTCJSXE0IIIYQQQkjgwaA7gcBKNyGEEEIIIYQEHgy6EwgMugkhhBBCCCEk8GDQnQBInFgkJHEifx8GIYQQQgghhBArGHQnAEIQdRNCCCGEEEIICTgYrSUAkrDKTQghhBBCCCEBCYPuBEBoCC8jIYQQQgghhAQijNYSAKEh7OcmhBBCCCGEkECEQXcCIJTyckIIIYQQQggJSBh0JwBCaaRGCCGEEEIIIQEJg+4EQBLKywkhhBBCCCEkIGHQnQBIGsrLSAghhBBCCCGBCKO1BACDbkIIIYQQQggJTBh0JwCShYb4+xAIIYQQQgghhBjAoDsBwEo3IYQQQgghhAQmDLoTAMnY000IIYQQQgghAQmD7gRQ5U4SwstICCGEEEIIIYEIo7UgJ3u6FP4+BEIIIYQQQgghNmDQHeQkS0ITNUIIIYQQQggJVBh0BzkhiRL5+xAIIYQQQgghhNiAQXeQE5KYQTchhBBCCCGEBCoMuoMcBt2EEEIIIYQQErgw6A5yKC8nhBBCCCGEkMCFQXeQk5hXkBBCCCGEEEICFoZsQQ7l5YQQQgghhBASuDDoDnIYdBNCCCGEEEJI4MKgO8hhTzchhBBCCCGEBC4MuoMcVroJIYQQQgghJHBh0B3kJmqJEnFONyGEEEIIIYQEKgy6g5SkIYklMQNuQgghhBBCCAloQv19AMQ1UicPlRRJQ3j6CCGEEEIIISSAYdAdxL3ceTOE+fswCCGEEEIIIYTYgfLyIIUGaoQQQgghhBAS+DDoDlJC4aJGCCGEEEIIISSgYeQWpDDmJoQQQgghhJDAh0F3kMJKNyGEEEIIIYQEPgy6g5QQjgsjhBBCCCGEkICHQXeQEhKSyN+HQAghhBBCCCHEAQy6g5TQxAy6CSGEEEIIISTQCZqgO3fu3JIoUSKLPyNHjrT4nr1790qVKlUkefLkkiNHDhk9erQkVBJTXk4IIYQQQgghAU+oBBEfffSRvPvuu3Efp06dOu7/b9y4ITVr1pQaNWrIjBkz5M8//5TWrVtL2rRp5b333pOEBivdhBBCCCGEEBL4BFXQjSA7c+bMhl9btGiR3L9/Xz777DNJmjSpFCtWTHbv3i3jxo1LkEF3YsrLCSGEEEIIISTgCRp5OYCcPDIyUkqXLi1jxoyRhw8fxn1ty5YtUrVqVRVwa9SqVUsOHTokUVFRfjpiQgghhBBCCCH/ZYKm0t2pUycpU6aMREREyObNm6Vv375y7tw5VckG58+flzx58lj8nUyZMsV9LV26dIY/9969e+qPXqZOCCGEEEIIIYQEfaW7T58+8czRrP8cPHhQfW+3bt3k+eeflxIlSkjbtm1l7NixMnnyZIuA2RVGjBghadKkifsDAzZCCCGEEEIIIcQTJIqJiYkRP3Hp0iW5cuWK3e/JmzevhWRcY9++fVK8eHEVlBcqVEiaN2+uqtQrVqyI+54NGzbICy+8IFevXnWq0o3A+/r16xIeHu7W70cIIYQQQgghJGGC2BGFW0exo1/l5RkyZFB/XAEmaYkTJ5aMGTOqjytVqiT9+vWTBw8eSJIkSdTnfvrpJxWQ2wq4QbJkydQfQgghhBBCCCHkP2mkBpO0CRMmyJ49e+T48ePKqbxr167SrFmzuIC6SZMmqiLepk0bVQVfunSpTJw4UcnSCSGEEEIIIYQQfxAURmqoRC9ZskQGDx6spOAwTEPQrQ+oUdb/8ccfpX379lK2bFlJnz69DBw4MEGOCyOEEEIIIYQQEhz4tac7EIEeP23atHL69Gn2dBNCCCGEEEIIMUTzA7t27ZoqAgd1pduX3Lx5U/2XLuaEEEIIIYQQQszEkPaCbla6rXj8+LH8888/kjp1ajWyLJAzKqzGBx+8dsEJr1vwwmsXnPC6BS+8dsEJr1vwwmvnXyAaR8CdNWtWZfJtC1a6rcDJyp49uwQDsKXnWLPghNcuOOF1C1547YITXrfghdcuOOF1C1547fyHvQp3ULmXE0IIIYQQQgghwQiDbkIIIYQQQgghxEsw6A5CMEJt0KBB6r8kuOC1C0543YIXXrvghNcteOG1C0543YIXXrvggEZqhBBCCCGEEEKIl2ClmxBCCCGEEEII8RIMugkhhBBCCCGEEC/BoJsQQgghhBBCCPESDLqDkKlTp0ru3LklefLkUrFiRdm2bZu/D4nYYcSIEVK+fHlJnTq1ZMyYURo0aCCHDh3iOQtCRo4cKYkSJZIuXbr4+1CIA86ePSvNmjWTyMhISZEihTz11FOyfft2nrcA59GjRzJgwADJkyePum758uWToUOHSkxMjL8PjVjx888/y8svvyxZs2ZV78UVK1ZYfB3XbODAgZIlSxZ1LWvUqCFHjhzheQzg6/bgwQPp3bu3el+mSpVKfU/z5s3ln3/+8esxE3PPnJ62bduq75kwYQJPX4DAoDvIWLp0qXTr1k25l+/cuVNKliwptWrVkosXL/r70IgNNm3aJO3bt5etW7fKTz/9pBa1mjVryq1bt3jOgog//vhDPv30UylRooS/D4U4ICoqSp599llJkiSJ/PDDD7J//34ZO3aspEuXjucuwBk1apRMnz5dpkyZIgcOHFAfjx49WiZPnuzvQyNWYA3DHgSFACNw3SZNmiQzZsyQ33//XQVx2K/cvXuX5zJAr9vt27fV3hKJL/z366+/VkWC+vXr++VYiXPPnMby5cvVnhPBOQkc6F4eZKCyjaopNiTg8ePHkiNHDunYsaP06dPH34dHTHDp0iVV8UYwXrVqVZ6zICA6OlrKlCkj06ZNk2HDhkmpUqWYPQ5g8C787bff5JdffvH3oRAnqVevnmTKlEnmzJkT97nXXntNVUoXLlzI8xmgoKKGjT6UXFqVGxv+7t27S48ePdTnrl+/rq7tvHnzpHHjxn4+YmJ03WwlnCtUqCB///235MyZkycuwK8dVF6IFdasWSN169ZVyjyq8wIDVrqDiPv378uOHTuUREsjceLE6uMtW7b49diIebDxABERETxtQQKUCli89M8eCVy+/fZbKVeunLz++usqwVW6dGmZNWuWvw+LmOCZZ56RdevWyeHDh9XHe/bskV9//VXq1KnD8xdEnDhxQs6fP2/xzkyTJo0KBrhfCb49CwK8tGnT+vtQiANQiHv77belZ8+eUqxYMZ6vACPU3wdAzHP58mXV74ZMsR58fPDgQZ7KIHkhIuMI6Wvx4sX9fTjEBEuWLFEyO2T7SXBw/PhxJVFGK86HH36orl2nTp0kadKk0qJFC38fHnGgUrhx44YULlxYQkJC1Jr38ccfS9OmTXnegggE3MBov6J9jQQ+aAVAj/dbb70l4eHh/j4c4gC044SGhqr1jgQeDLoJ8XHF9K+//lKVGxL4nD59Wjp37qx68WFcSIInuYVK9/Dhw9XHqHTjuUNvKYPuwGbZsmWyaNEi+eKLL1SlZvfu3SpRCakyrx0hvgP+M2+88YZqFUASkwQ2UMJOnDhRFQmgTCCBB+XlQUT69OlV5v/ChQsWn8fHmTNn9ttxEXN06NBBvvvuO9mwYYNkz56dpy1IFjGYFKKfG9lj/EEvPsyB8P+owpHAA27JRYsWtfhckSJF5NSpU347JmIOyCJR7UbPLxyUIZXs2rWrmgJBggdtT8L9SnAH3OjjRtKZVe7ABx4m2K+g717br+D6wVcBE4+I/2HQHURAGlm2bFnV76av6ODjSpUq+fXYiG2QJUbADcOL9evXq1E4JDioXr26/Pnnn6rapv1BBRVSV/w/kmAk8ED7hvVYPvQI58qVy2/HRMwB92R4lejBc4a1jgQPWOcQeOv3K2gbgIs59yvBEXBjvNvatWvV2EUS+CBBuXfvXov9ChRCSGTCVI34H8rLgwz0KEJih40/3CQxfw8jBFq1auXvQyN2JOWQSn7zzTdqVrfWzwZTGTjyksAF18u69x5jb7AJYU9+4ILKKAy5IC/H5nHbtm0yc+ZM9YcENphBix5uVGsgL9+1a5eMGzdOWrdu7e9DIwZTHY4ePWphnoaNPkxCcf3QFoBpDwUKFFBBOMZQIQiw55RN/HvdoBJq1KiRkihDmQc1l7ZnwddR/CGB+8xZJ0gwNhPJr0KFCvnhaEk8YkjQMXny5JicOXPGJE2aNKZChQoxW7du9fchETvgMTP6M3fuXJ63IOS5556L6dy5s78Pgzhg5cqVMcWLF49JlixZTOHChWNmzpzJcxYE3LhxQz1fWOOSJ08ekzdv3ph+/frF3Lt3z9+HRqzYsGGD4drWokUL9fXHjx/HDBgwICZTpkzqOaxevXrMoUOHeB4D+LqdOHHC5p4Ff48E7rUzIleuXDHjx4/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" + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Next:** [Part 6b — ODEs](../06b_odes/)" ] - }, - "metadata": {}, - "output_type": "display_data" } - ], - "source": [ - "# Generate a NEW dataset for back-testing (different trajectory)\n", - "key_backtest = jr.PRNGKey(123)\n", - "times_backtest = jnp.arange(0.0, 15.0, 0.01) # shorter window for demo\n", - "with SDESimulator(source=\"em_scan\"):\n", - " synthetic_backtest = Predictive(\n", - " l63_model,\n", - " params={\"rho\": jnp.array(rho_true)},\n", - " num_samples=1,\n", - " exclude_deterministic=False,\n", - " )(key_backtest, predict_times=times_backtest)\n", - "print(\n", - " \"backtest synthetic shapes:\",\n", - " synthetic_backtest[\"f_times\"].shape,\n", - " synthetic_backtest[\"f_states\"].shape,\n", - " synthetic_backtest[\"f_observations\"].shape,\n", - ")\n", - "states_backtest = synthetic_backtest[\"f_states\"][0, 0, :, :]\n", - "observations_backtest = synthetic_backtest[\"f_observations\"][0, 0, :, :]\n", - "times_backtest = synthetic_backtest[\"f_times\"][0, 0, :]\n", - "\n", - "# Sparse observations: every 50th timepoint (as would arrive in real time)\n", - "downsample = 50\n", - "obs_times_sparse = times_backtest[::downsample]\n", - "obs_values_sparse = observations_backtest[::downsample]\n", - "\n", - "# Dense predict_times: full grid (interpolation between sparse obs)\n", - "predict_times_dense = times_backtest\n", - "\n", - "# Apply learned model: posterior-predictive with Filter + SDESimulator\n", - "predictive_interp = Predictive(\n", - " l63_model,\n", - " params={\"rho\": jnp.array(rho_post_mean)},\n", - " num_samples=3,\n", - " exclude_deterministic=False,\n", - ")\n", - "with SDESimulator(n_simulations=50, source=\"em_scan\"):\n", - " with Filter(\n", - " filter_config=ContinuousTimeEnKFConfig(\n", - " n_particles=50,\n", - " record_filtered_states_mean=True,\n", - " record_filtered_states_cov_diag=True,\n", - " )\n", - " ):\n", - " samples_interp = predictive_interp(\n", - " jr.PRNGKey(42),\n", - " obs_times=obs_times_sparse,\n", - " obs_values=obs_values_sparse,\n", - " predict_times=predict_times_dense,\n", - " )\n", - "\n", - "pred_states_interp = jnp.asarray(samples_interp[\"f_predicted_states\"]) # (num_samples, n_sim, T_dense, 3)\n", - "pred_times_interp = jnp.asarray(samples_interp[\"f_predicted_times\"]) # (num_samples, n_sim, T_dense)\n", - "\n", - "print(\"interp shapes:\", pred_states_interp.shape, pred_times_interp.shape)\n", - "interp_draws = flatten_draws(pred_states_interp)\n", - "pred_times_interp_1d = flatten_draws(pred_times_interp)[0]\n", - "\n", - "# Plot: sparse observations (scatter) vs dense posterior-predictive interpolation (bands)\n", - "fig, axes = plt.subplots(3, 1, figsize=(10, 7), sharex=True)\n", - "lo = jnp.percentile(interp_draws, 2.5, axis=0)\n", - "hi = jnp.percentile(interp_draws, 97.5, axis=0)\n", - "state_labels = [r\"$x_1$\", r\"$x_2$\", r\"$x_3$\"]\n", - "for i, ax in enumerate(axes):\n", - " ax.fill_between(\n", - " pred_times_interp_1d,\n", - " lo[:, i],\n", - " hi[:, i],\n", - " alpha=0.3,\n", - " label=\"95% CI (interpolation)\",\n", - " )\n", - " ax.plot(\n", - " times_backtest,\n", - " states_backtest[:, i],\n", - " \"k--\",\n", - " label=\"True state\",\n", - " lw=1,\n", - " )\n", - " if i == 0:\n", - " ax.scatter(\n", - " obs_times_sparse,\n", - " obs_values_sparse[:, 0],\n", - " color=\"C3\",\n", - " marker=\"x\",\n", - " s=40,\n", - " zorder=5,\n", - " label=f\"Observed (every {downsample}th)\",\n", - " )\n", - " ax.set_ylabel(state_labels[i])\n", - " ax.legend(loc=\"upper right\", fontsize=8)\n", - "axes[0].set_title(\n", - " \"Back-tested real-time forecasting: sparse obs, dense predict_times\"\n", - ")\n", - "axes[-1].set_xlabel(\"time\")\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6.5 Full observations and high-frequency, low-noise data\n", - "\n", - "A common special case is **full observations** with **high-frequency, low-noise** measurements. Under that assumption we can **accelerate inference** dramatically at the expense of some bias (depending on how valid the assumption is). See the [deep dive on this topic](../../../deep_dives/l63_speedup_dirac_vs_enkf/) for details." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "**Next:** [Part 6b — ODEs](../06b_odes/)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python (dynestyx2)", - "language": "python", - "name": "dynestyx2" + ], + "metadata": { + "kernelspec": { + "display_name": "Python (dynestyx2)", + "language": "python", + "name": "dynestyx2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "nbformat": 4, + "nbformat_minor": 4 } From 90a281356e54332784490d870819840a1ad1bdb1 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Thu, 14 May 2026 15:05:25 -0400 Subject: [PATCH 17/28] simplify notebook changes for PR --- docs/deep_dives/fhn_sparse_id.ipynb | 1515 +++++++++-------- docs/deep_dives/gp_drift.ipynb | 3 +- .../l63_speedup_dirac_vs_enkf.ipynb | 769 ++++----- docs/tutorials/quickstart.ipynb | 744 ++++---- 4 files changed, 1517 insertions(+), 1514 deletions(-) diff --git a/docs/deep_dives/fhn_sparse_id.ipynb b/docs/deep_dives/fhn_sparse_id.ipynb index ad314a9f..5cd59767 100644 --- a/docs/deep_dives/fhn_sparse_id.ipynb +++ b/docs/deep_dives/fhn_sparse_id.ipynb @@ -1,784 +1,785 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Sparse identification of FitzHugh–Nagumo dynamics\n", - "\n", - "This **deep-dive tutorial** walks through sparse drift inference for a FitzHugh–Nagumo (FHN) SDE.\n", - "\n", - "**Goal.** Given noisy observations of the state, recover the sparse structure of the drift $f(x)$ by expressing it as with the elements of a polynomial library $\\Theta\\,\\phi(x)$ and placing a **Laplace prior** on the coefficient matrix $\\Theta$. This is a Bayesian SINDy-style approach. We fit via **SVI with AutoDelta** (MAP estimation) and then compare the recovered coefficients and filtered trajectories against ground truth.\n", - "\n", - "**What is known.**\n", - "- Initial state distribution: $x_0 \\sim \\mathcal{N}(0, I)$.\n", - "- Observation operator $H$ (identity here, observing both states).\n", - "- Polynomial library $\\phi(x)$ (monomials up to degree 3).\n", - "\n", - "**What is inferred.**\n", - "- Drift coefficient matrix $\\Theta \\in \\mathbb{R}^{2 \\times 10}$ via MAP (Laplace prior promotes sparsity).\n", - "- Diffusion coefficient $\\sigma_x > 0$ (HalfNormal prior).\n", - "- Observation noise standard deviation $\\sigma_y > 0$ (HalfNormal prior)." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## FitzHugh–Nagumo Model\n", - "\n", - "### State SDE\n", - "\n", - "The state $x_t = (v_t, w_t)^\\top \\in \\mathbb{R}^2$ evolves as an Itô SDE:\n", - "\n", - "$$\n", - "dx_t = f(x_t)\\,dt + \\sigma_x\\,dW_t,\n", - "$$\n", - "\n", - "where $W_t$ is a standard 2-dimensional Brownian motion and the true drift is\n", - "\n", - "$$\n", - "f(x) = \\begin{pmatrix} v - \\tfrac{1}{3}v^3 - w + I \\\\ a\\,(v + b - c\\,w) \\end{pmatrix}.\n", - "$$\n", - "\n", - "Parameters are fixed at $a = 0.08$, $b = 0.7$, $c = 0.8$, $I = 0.5$. The true noise values used to generate data are $\\sigma_x = 0.01$ and $\\sigma_y = 0.1$, but **both are treated as unknown during inference**.\n", - "\n", - "### Observation process\n", - "\n", - "Observations are collected at discrete times $t_1 < t_2 < \\cdots < t_n$:\n", - "\n", - "$$\n", - "y_k = H\\,x_{t_k} + \\varepsilon_k, \\qquad \\varepsilon_k \\sim \\mathcal{N}(0,\\,\\sigma_y^2 I),\n", - "$$\n", - "\n", - "where $H = I_2$ (both states observed).\n", - "\n", - "### Initial condition\n", - "\n", - "$$\n", - "x_0 \\sim \\mathcal{N}(0, I_2).\n", - "$$\n", - "\n", - "### Inferred quantities\n", - "\n", - "We do **not** know $f$, $\\sigma_x$, or $\\sigma_y$. We parameterise the drift as\n", - "\n", - "$$\n", - "f(x) \\approx \\Theta\\,\\phi(x),\n", - "$$\n", - "\n", - "where $\\phi(x) \\in \\mathbb{R}^{10}$ is a polynomial library (all monomials in $v, w$ up to degree 3). The full set of inferred quantities and their priors is:\n", - "\n", - "$$\n", - "\\Theta \\sim \\mathrm{Laplace}(0,\\; 0.1) \\quad \\text{(promotes sparsity)},\n", - "$$\n", - "$$\n", - "\\sigma_x \\sim \\mathrm{HalfNormal}(0.1), \\qquad \\sigma_y \\sim \\mathrm{HalfNormal}(0.5).\n", - "$$\n", - "\n", - "All three are inferred jointly via MAP (SVI with AutoDelta)." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import jax.numpy as jnp\n", - "import jax.random as jr\n", - "import numpyro\n", - "import numpyro.distributions as dist\n", - "from numpyro.infer import SVI, Trace_ELBO, Predictive\n", - "from numpyro.infer.autoguide import AutoDelta\n", - "\n", - "import dynestyx as dsx\n", - "from dynestyx import (\n", - " ContinuousTimeStateEvolution,\n", - " DynamicalModel,\n", - " Filter,\n", - " LinearGaussianObservation,\n", - " SDESimulator,\n", - ")\n", - "\n", - "import matplotlib.pyplot as plt\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## True system\n", - "\n", - "Define the true FitzHugh–Nagumo drift. We will later build the full DynamicalModel by piping in this drift and spreading shared arguments from a dict." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "# FitzHugh–Nagumo parameters\n", - "_a, _b, _c, _I = 0.08, 0.7, 0.8, 0.5\n", - "\n", - "def fitzhugh_nagumo_drift(x):\n", - " v, w = x[0], x[1]\n", - " dv = v - (1/3) * v**3 - w + _I\n", - " dw = _a * (v + _b - _c * w)\n", - " return jnp.array([dv, dw])\n", - "\n", - "state_dim = 2" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Model configuration\n", - "\n", - "Constants used for data generation and inference setup.\n", - "\n", - "| Symbol | Role | Value | Status |\n", - "|---|---|---|---|\n", - "| $\\sigma_x^{\\mathrm{true}}$ | true diffusion coefficient (data generation only) | `0.01` | **inferred** |\n", - "| $\\sigma_y^{\\mathrm{true}}$ | true observation noise std (data generation only) | `0.1` | **inferred** |\n", - "| $x_0 \\sim \\mathcal{N}(0, I_2)$ | initial state prior | covariance = `I` | known |\n", - "| $\\Delta t$ | observation spacing | `0.1` | known |\n", - "| $T$ | total time span | `[0, 50)` | known |" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "# True values used ONLY for data generation — both are inferred during model discovery\n", - "sigma_x_true = 0.01 # true diffusion coefficient\n", - "sigma_y_true = 0.1 # true observation noise std\n", - "\n", - "# observation times t_1, ..., t_n (spacing Delta_t = 0.1, span [0, 50))\n", - "obs_times = jnp.arange(0.0, 50.0, 0.1)\n", - "\n", - "observation_dim = 2 # observation_dim=1 also works (observe only v)\n", - "\n", - "key = jr.PRNGKey(0)\n", - "key, k_data, k_svi, k_nuts, k_filter = jr.split(key, 5)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## DynamicalModel construction helpers\n", - "\n", - "The Dynestyx `DynamicalModel` needs three pieces:\n", - "\n", - "- **Initial condition** — $x_0 \\sim \\mathcal{N}(0, I_2)$. Fixed; collected in `initial_condition_kwargs`.\n", - "- **Observation model** — $y_k = H\\,x_{t_k} + \\varepsilon_k$ with $\\varepsilon_k \\sim \\mathcal{N}(0, \\sigma_y^2 I_2)$. Constructed inside each model function because $\\sigma_y$ is inferred.\n", - "- **State evolution** — wraps the drift $f$ and the diffusion $\\sigma_x I_2$. Constructed inside each model function because $\\sigma_x$ is inferred.\n", - "\n", - "`make_state_evolution(drift_fn, diffusion_coeff)` is a helper that accepts whichever diffusion coefficient (true or inferred) is provided." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "# H in y_k = H x_{t_k} + eps_k (identity: observe all states)\n", - "H_obs = jnp.eye(observation_dim, state_dim)\n", - "\n", - "# Only the initial condition is shared and fixed; observation model and state\n", - "# evolution are constructed inside each model function because sigma_x and sigma_y\n", - "# are inferred.\n", - "initial_condition_kwargs = dict(\n", - " # x_0 ~ N(0, I_2)\n", - " initial_condition=dist.MultivariateNormal(\n", - " loc=jnp.zeros(state_dim),\n", - " covariance_matrix=jnp.eye(state_dim),\n", - " ),\n", - ")\n", - "\n", - "\n", - "from cd_dynamax import adjust_rhs\n", - "\n", - "def make_state_evolution(drift_fn, diffusion_coeff):\n", - " \"\"\"Wrap a drift f(x,u,t) into a ContinuousTimeStateEvolution.\n", - "\n", - " diffusion_coeff: scalar sigma_x in dx = f(x) dt + sigma_x dW_t.\n", - " adjust_rhs clips state and derivatives to [-100,100] / [-1000,1000]\n", - " to prevent SDE solver blow-up.\n", - " \"\"\"\n", - " return ContinuousTimeStateEvolution(\n", - " drift=lambda x, u, t: adjust_rhs(x, drift_fn(x, u, t)),\n", - " # sigma_x I_2 (isotropic, constant diffusion)\n", - " diffusion=dsx.FullDiffusion(diffusion_coeff * jnp.eye(state_dim)),\n", - " )\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Data generation\n", - "\n", - "We simulate from the **true** FHN drift using an SDE simulator. The model observes the state at `obs_times` with Gaussian noise." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "# Data generation: simulate dx_t = f_true(x_t) dt + sigma_x_true dW_t\n", - "# y_k = H x_{t_k} + N(0, sigma_y_true^2 I)\n", - "# Uses the true (known) noise values — these are NOT passed to the inference model.\n", - "def model_with_true_drift(obs_times=None, obs_values=None, predict_times=None):\n", - " return dsx.sample(\"f\", DynamicalModel(\n", - " state_evolution=make_state_evolution(\n", - " lambda x, u, t: fitzhugh_nagumo_drift(x),\n", - " diffusion_coeff=sigma_x_true,\n", - " ),\n", - " # y_k = H x_{t_k} + N(0, sigma_y_true^2 I)\n", - " observation_model=LinearGaussianObservation(\n", - " H=H_obs,\n", - " R=sigma_y_true**2 * jnp.eye(observation_dim),\n", - " ),\n", - " **initial_condition_kwargs,\n", - " ), obs_times=obs_times, obs_values=obs_values, predict_times=predict_times)\n", - "\n", - "predictive = Predictive(model_with_true_drift, num_samples=1, exclude_deterministic=False)\n", - "with SDESimulator():\n", - " synthetic = predictive(k_data, predict_times=obs_times)\n", - "\n", - "# (num_samples, n_sim, n_times, dim)\n", - "obs_values = synthetic[\"f_observations\"][0, 0] # y_k shape (n_obs, observation_dim)\n", - "states = synthetic[\"f_states\"][0, 0] # x_{t_k} shape (n_obs, state_dim)\n", - "times_1d = jnp.asarray(obs_times).squeeze()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Data visualization\n", - "\n", - "Time series of the latent state and noisy observations, and the phase-space trajectory." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ + "cells": [ { - "data": { - "image/png": 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Nlw1z/835ToRuEHRZWLFiRZ14B27DdhDrCEeDPX4Hfn/7xAscrJjv22J/rgjTZNOdwryx03WDN126kVCQnXTSSeLGQ1HUmu2EAwq6e7CdcADM9s9BAN1CbMUnXdKYGYvi3F4cNPXc22KeE0fXmeeNgz/7JAAN/Xbsv29D+3R0/pszaLI/DrYZDjLtXbK43DaeijiKd2oOPCdsC+yP6J5Sn5sd22lL63sw/TEHvRTRdIulexPbBt3z2uM3xrZNtzP7gbGJ+dvn4J6/GboSso/lcXLiiC5SjUF3L7rvUbyWlpZalzs6Z/bX22x7Zr/KmEO6MNbXrhwJ76b+FihWeJ1tYT9D10n7/oOYcUNNOTdNPc8mFMf2sM3T1Yz7YgwboXBhf0MhY0IXQLq1MekD3YltY91MF6zmwvNG9zHz3t1Yv9vYdSR0q+NkBmNgODFHt2b2u/bnW1FagooV5bDhDZSDZvtAZ2LGsNgHN5tBiPRNr28GjTd7W8wYgPoGweY2GY9gDkxt4U3AFtsZKxPeCDhbzME9Bx684XHQRysPZ7Ltg1QdwXUoVOh774j6bnBtCW+29KmmTzL9kzlQ43HyBtyU78QAc95YeT7+85//yA2JFgwOJujf3Ng2eFOtz9LR2tAydfLJJ4ufNwfuFMP0ZadYYMxMa7QTQiHE2BAONjggZXwBB162s6K04HBmnIKAPuWcneTgnIN7tq+mnPvWoLHfTnvh6DiaemyMM2lqf2Q7+084c84BIAeYbBMMFK4PtlNHg+emwMEeA6Q5oGc8BGPvOMjk5Edjac4P9zdGuA77r/qsRubAnP0TxQbPBWfR+WBcBQeXDSW3YPIRxjowlojfi/0+LaH8rJlEwBnbXXNoyrlp6nk2sW+PJsygyXgb7o/9MvsStgFb8f7YY49JH8aEKBQ1tKayP2I/50z9B+8xtDYxbpLxbYzH48QRY10o/BTlcFCxorQKNLszaJfB6JxVbAxztoU3usOdMTUxzdS82bR0mwz2ZAAsb0q8OZk4cgmob/aVx8HZVc6m1neTIsxoZc7S2c4+cbaxKQN7M000Z/RtZ4nt8+lzW1yPgyUOmkxMC0NTvhMH4pxFpRXBdpbNkcuUIzgAo3iznx3md+AAkjddW0FgukeZ56ihY+b1sg8o5zWgdYUPfoYDAWaY+vDDD1ulndjeoDnrSYsJZ0V5HKZ7nek+RAsBb9i2weKcIbWnqbP55jlxVDeB540DndZOrWzbVu1pr/oNjrIMOoIDS04smLBt8bfM3wAHgxSP9cFAa2Ym44C8pfDcU7DyYYqkRx99VIKvKVRb4zfWUN/D/qAp7ZpCiKKeD54jWhRoCefA2H6iyITii9+BA3nbJAY85y2BEzfsI1varmx/C/aWUi6z7z/4Pem6ZCsm2H8Q2z6ksXPTnPPcEHR/oyXWdAXjsbCd2MKgdWaJfPvtt2st50SIrahpjjWQ54X3KFoZba0r9fW7zfmN8lzxQesSA+vZ9lWsKIeLxqworQJnmJglibM/dPlqbCaNA0XGs/AGQH94exylJG4MWmg4g82ZKNb1aMk2zRkk2+Pla0cpPc0BoX2qYA5gaaExTfv2gyFzfd7oKNaYxcl2f02tYk4zO7dnm9qU++X2GvtO9e2nvu/kaBsUHk0dpEydOlU+u27dujrfgTPmtn7b/E78DhRg9gNLWktsY5kojuknbd4M6TrDmBxbOLDgDdl0WWmNdmLCASm3S3HLmXRe+8bOGwewnJV2dO6b4hbGAQHFF/dpe51o2eSMJs9pa2O7T9tjpIinj3170NKYFcZwsX3xnNu61ziC34Xtxz6LUlNTF9u7rnHQy5geXn+zrbXGb4zbcJSinO2PLmQUE/Zwff62HB0nJwoYh0BsXbvs4TFyUGzrikSrOX+XLYHb4/Xi53mOTZhBytF3sIcxT7yXvPbaa7WOm9YQbsM+OxkxUwKb55p/sx+mRaOp56ap57kxGOfB708RTRddthcKGPtzZN93M2bGPqazvnblCPYRvIa254LQgsfr21xxwW3Z9128LnQ1a6g9KUpTUcuK0irQbYJuAAxapv8w01qyXgY7Wc4i8z12+ra+/wy2ZyAy88dfccUVYl2g0OFNgEGqtnnkmwIHoBy4s9I3Z3RoYufMHW+CDLSkpcO+c3ZkAeDglu5pvBlwm5xNdGTpoF8uYZAibzi8qXCfHGBztoyuRzTv0+eZN0POHvImQ+HD1KY8Nu6H69GXnjcQBvDzRusorao9nPXjd2LaZw4YOCjiDL79TYPfgbP69CnmgIl+2BzUOprdN78TU6Lyu/C4uR9+B3O2kd+Ns4pM08obkiOxaQ+vM13BOJtnOwPKpAkUrJwJp5Dh7CZnEum7TzFl71PNWU1uiwHvvAlyHW7XdMfgzCQHHRxM8HzQpYtuCWxX/D6t1U5M+HkeE88Xj8fWBYxw0Evfbvpys51wIED3M0duMDz3HFQzxTHTsFKs8Xw7gi4WHFBQBDI43UxdTKuVbX2T1oTtlIM/nn9OStBV0qwp4iherbVpySw22wdFCs8TJ1NoWbOF6YltrVAUO1yPLj62NDV1MX8ndC1kG2LMFAfMbEs8b2Zbbo3fGLfBNszYEbY/rsPfFd08aZlhf8LfFNdjrA4txvxdsZ9g38JEB7x+/Az7ZMYo8FpSkJpxC47g96CLGt1H6frI2XP24zwGWkhbAi2+FPp0IeKMvDlZwXbV2DZ57uhqRFcq9ru8/5ipi9mXsD6WLbQKcV/8PdJFmX0tf/N333231T23Keemqee5KbDPYDwn2ynvI7aplgn3QRdSfkf2J9wHrdT2sSC8b/GzFG5sa2zX/I6O4mXYxmitYRvksfJezXsCa0LRvcw2mL4p0ELDc8X7GrfFvot9PRNNtFbNJKWb0yY5xpRuC9MbXnPNNZYBAwZIOkqmIB0yZIjl6quvtmzYsKHO+nv37pVUq1FRURYPDw9JB3vSSSdZvvzyyzqpi5ma0ZaFCxfKcj7bL2e6T6ZS5DH079/fcskll1jWrl1bK5UjU086gmkzmSaZqXPDw8Mlla2ZqtE2LSRTWzINZkREhKR7tP85vfHGG5bx48fLOQgICJA0zXfccYclKSnJug5TUj744IOSEpbrzZw507JlyxZJM9lY6mLC1LUXXnihpMbk9+Xrv//+u86xMt0v09UyZS/XO+uss+Q47FPMmmk5eR2YBtc2xer3339vGTVqlJzTuLg4y5NPPml555136k3Das8NN9wg7cKe1NRUyz//+U8510yRyfNkn37TTAHKtK/PPvusJTY2VlJ3Mk0zr41JRkaGpM9km+P15XedPHmypBS253Dbick999wjx+bou5Fly5ZZpkyZItc3Ojpa2sCvv/5ap+0WFBRYzj//fLlGtumAHaUuJn/88Ydl+vTpsl1e/5NPPlnari1mymAzLav9b6op182Wr776yjJ06FA590yx+vXXX9dJi9pQ6mL746jv/DItb2MpgJuCma62vof992dbYZptR8fTlNsl09EeeeSRkhaa54ht6vbbb5f07q35G2OababcZb/C92zTGDM191133SXtkb8n/q6YDv6ZZ56RVL+E/eucOXMk7S/X6d27t6TTTk5ObvQ7vv3225Jant+PvzO2JfP62sK/HaWyddS3LV68WPpKHgvTNL/22msOt1kfn332mWXs2LFyTKGhoZZ//OMftVKc27Y13nP43Zk6vEePHrIf29TATT03TTnPtv1WfTA9O3/D9incbVMX33rrrdZ7BH/zK1askGtun776u+++k9+lu7t7rT7D0W+Ux8+U7+yTeO/lNeVx2qbRb+p1LC0tlXY+evRoaZM8z3z9yiuv1Pu9FaU5uPC/jhZMiqJ0fegrTssVZzNNlwtFcRZoBaWljMkPOIuuKIqiOAcqVhRFaTfovsW01S2p76AobQldshhMbabBVhRFUZwDFSuKoijdGMY4MealIRyleFYURVGU9kDFiqIoSjeGAcIN1dYg6i2sKIqidBQqVhRFUboxTNeblJTU4DqtVQtJURRFUZqLihVFURRFURRFUZwSLQqpKIqiKIqiKIpTomJFURRFURRFURSnRMWKoiiKoiiKoihOiYoVRVEURVEURVGcEhUriqIoiqIoiqI4Je4dfQDODisaM61nQEAAXFxcOvpwFEVRFEVRFKXTwxpe+fn5iI6Ohqtr/fYTFSuNQKESGxvb2tdHURRFURRFUbo9hw4dQkxMTL3nQcVKI9CiYp7IwMDADrPupKenIyIiokHlqXQftE0o2h4U7SMUvW8onXkskZeXJwYBc6xdHypWGsF0/aJQ6UixUlJSIvtXsaJom1C0j1D0vqHoWELpKuPLxsIsdJpeURRFURRFURSnRMWKoiiKoiiKoihOiYoVRVEURVEURVGcEo1ZURRFURRFUToNlZWVKC8v7+jD6BIxK+Xl5RK30hYxKx4eHnBzczvs7XRpsfL444/j66+/xo4dO+Dj44Np06bhySefxODBgzv60BRFURRFUZRm1uVISUlBTk6OnrdWOp8ULKx10la1BIODgxEVFXVY2+/SYmXx4sW49tprMXHiRFRUVODuu+/GnDlzsG3bNvj5+XX04SmKoiiKonQoBaUVeGnBbhw1KALTBoQ79dUwhUpkZCR8fX21WHcriBWOj93d3Vv9XHLbRUVFSEtLk7979uzZ4m11abEyf/78Wn+/99570sDXrVuHI488ssOOS1EURVEUxRn4cOUBLN+bKY8frj8Czuz6ZQqVsLCwjj6cLoGlDcUKoVcToWDhdWupS1iXFiv25ObmynNoaGi965SWlsrDtmANoZmMj46A+zVNdYqibULRPkLR+4bSWmOJfekFsMAir0vKKuDp7py5lzg24/FzAMxnpXUwz2VbnVPzevH6eXt713qvqePabiNWeEJuuukmTJ8+HSNGjGgwzuXBBx+ss5wVPhmA1FHHTqHFi61FIRVtE4r2EYreN5TWGkskZOShorxCXm/Yk4C40NoDSmeBgeD8DrSw0BqgHD5sCzyfpK1iVrh9XrfMzEwJuLeFsTJNoduIFcaubNmyBX/99VeD691111245ZZballWYmNjERER0aEV7NmIeAwdKVZ2pOTjq/UJ+Oe0OEQHG6Y9Bd26TSjOgbYHRduE0pJ+Ij2/FHnlgLuHOx6bNwKDowLg4da295Tk3GK8vjgep42LxuiY4CZ/jhPGHNzSZYkPpfWwFxGtCa8V2xtd9+wtK/Z/17sNdAOuu+46/Pjjj1iyZAliYmIaXNfLy0se9vBEd+SgkB1MRx/Dsj2ZWB2fjUBvT9x4zMAOOw7FedqE4jxoe1C0TSjN7SfKKi2Y3DcMZRVVGBUb0i4ncHdaIban5MF1gwvG9q7fLd8eHjOP33worWNZMc9lW51T83o5Gq80dfzi3tUvwvXXX49vvvkGixYtQt++fTv6kJyWisoqlFVWwdez/iYRGWiIuKIyNb8qiqIoSkdDy8j8LcmYN7YXArwbnh2nIHlrZRJmDnfD1P7hcHN1QWyoL+47aRjakwBvd5SUVyGzsKxd96t0Xly7uuvXhx9+iI8//hgBAQGS8o6P4uLijj40p+O+77biknfXILe4/iJLMSGG61dCjp4/RVEUReloHvpxGz5fm4DXF++zLssoKMXl76/Bu8via627KTEXf+3LxcsL92LN/ix8tuag9b3Sikr8vDkZry3e22igdUPvJ+YU48dNSaiqqn+dHoGG609qbokGyjcC4zwiIyOxf/9+OCPnnnsunn322TbfT5e2rLz66qvyPHPmzFrL3333XVxyySUddFTOB2dbtiQamdLWH8jGrCGR8jdnbPialJRXyt8kOadYOiJXV5cOOdbFu9Ixtncwwv3ruuspiqIoSnfBuzpz18KdaZjaPxSJ2SX4c0cq1uzPxtr92dibVoCoIG+E+nlh+d50lFRUYUhUAB79abt8blRMMIb2DISbiwteX7wX1BhnjY9BWPX9tbLKIvd+boN8vT4BX6xNwPVHD7DWZKE4+mVzMo4aFIlrP15ffVxuOGZYD4fHvCvVCKouLq9EXnEFgnzbLl6is/Poo4/i1FNPRVxcXJPW53h3zJgxeP7555u1n1mzZrXoc/fee6+UArn88ssRFBSEtqJLixVNbdc0UnJrspyVVlSJILjr683yd58wX/SL8MeBzCKZjSHllRbpnCKrZ0eayvcbk/DhigN47PSRGBDpj5bw5boEfLL6IHoEeuGtiye2aBuKoiiK0hW4YfZAnP7KMnGp+sdbq+u8/+GqGuuJybvL98Pd1QXeHm649L01Il6uPqq/uJHRuyK7qMwqVl76czcWbE/Dw/NGYExsMH7alCxFJB//ZQfuPXEoQv08cc83W0R4/L7dKP5H9mUU0IZS733cJCWvRMVKPbCg4ttvv41ff/0Vzgqz6/bv31+8mOjN1FZ0aTcwpWkkZBdZXw+I9MPmxBzr379sScFbS/fhh41JtT/TAlewN5fskw7tHTvTdHNYuS9TnlPzamrhKIqiKEp3Y2tSLs5+fQXSC8rEIuLv5Y4ZA8MR4uuBHgFeiAr0xrDoQJw9IQbjegfDx8NNRAqpqLKI6EjOLcHCnek4542VWL43Q0TGU/N3YsH2VOxJyxehQn7bmiLPjG01ySupwIt/7pH7OskuLMPQngHyurDUWOaI7MLyWmLlsKukl1V0yKO5E+J053rrrbdqLVuzZo1kxIqPrzsu+vnnnyXh05QpU2ot//LLLzFy5EipX8IMW8cccwwKCwvFY2jx4sV44YUXrEHtdB9jgfQjjjgCwcHBsv5JJ52EvXuNyWdy2WWXOfwcs8exnAfjvbmv0aNHy77tOfnkk/Hpp5+iLenSlhWlYfhD256cL5YK+pn6errh6g/Xi8tXTlG5dGrv/BUvQXh8zWfjtSs2J+RiWM9AeLkb2TkaIy2/pkMqKau/E2uMtk6pqCiKoijOziM/bsP/VuyXbF4UJr5ebiJWvNzd8MmVU7B4Zzp+3JSMiAAvPDJvJB77ebsIjTkDA3HhjCFYeyAb936zRdzCegX5IKe4DEm5JSIyftuWKg8PVxf4ebtLjEnfcD/xuuDYgHxw2SQRGvszCuHh5oIp/cKQVViGuHA/GVekVouQj1cdlFiYp84cJSUPmMyHIsmEcSuMn+GyUb2CxNrD7TDwvylQKA27v2MsD9semttgUiJ7KDC2bdtWa9m///1vXHXVVQ4TQC1duhTjx4+vtSw5ORnnnXcennrqKZx22mmSypnrcTxHsbFr1y6xdjz00EOyPtNUr1u3TkpyjBo1CgUFBbj//vvlsxs2bJDx23/+8x/s2bOnzucoVGgxee211zBw4EDJqHvBBRfIe0cddZT1mCZNmiTuaiz66CibbmugYqULw8ZLk26wr6d1GTubT1YfwLcbkpBfUo49aYXW97JqXjbKA99vlcA+do5nTYjBuRN7iwr/c2c6zp0Yi/lbUpBVVIbLj+gn1XA3HjJiYshD8xwX5TQ7MdvjtYedou330/SFiqIoSlf3fli6O0Pcsqf1D8cHKw7grb+MmXgO8F+5YBye+3039mcWSizJkKhAeQzs4S/rUzisO5At6x/ZLwRBPh44ZmgPLNmVIffcJ88YJfdW3tf/3JEmyXQ4IVlYZkxc8nHn15sl+J5CggP0vekFIojIEQMjcMPRA+Du5irxKHQVo8WGcDKUcOLz3pOGIccmiQ8FkJ+XO77fkIQNh3Lwr5n9sXRPBrYm5uKhU0dgdGzTa7B0BigGbMUK3bvWrl2Lzz//3OH6Bw4cQHR0dB2xwoKYp59+Ovr06WMVQSaenp7w9fVFVFSUddkZZ5xRaxvvvPOOCA4ey/DhwyXWxP5zFB6PPfYY/vjjD0ydOlWW9evXT2oVvv7667XECo+xrKxMEliZx9TaqFjpwmxJzMNDP27FxdPiQGsl/VIj/L3w0p97kFFgpAz09nDF1H5hGB4dKCKBsxqRAV5YfzAb3/6dJMF1lVVVYjLma/qnMmYls7BUnimG3loaL4+IAE/Zz/I9mcgqLBUhwY6Sfq5/HzQ6yrMnxorAccR7y/dLXAs7Tgb8OeK0sb3En/bIQRGyL021riiKonRldqcWiIViVEyQ3D8f/GGrLO8f4Y8vr5kKT3c3PHv26DoTeEcPMWJGGBxPYRDk446oQGMykOsxDsWWQT0C8PfBHLi6uKBfhB+Kyirl9e60Arn/7003ZjSzi8pxxqsrJLjf14tpiCuxJ70AgyIDrIH4FDVcbpJeUIqcojIkZBsu5MG+HnjxvLGSrOf9FUamKx9PNxFJ5M2l+/DSeWMbnZCkaxstHB0B990cKCpYSoPwWrEI+e23347wcCNRgT3MXGtfNHH06NGYPXu2bGvu3LmYM2cOzjzzTISE1F8jZ/fu3WJNWbVqFTIyMmRimRw8eFDEiiNoaWHMzLHHHltrOUXJ2LFjay2jixjh+m2FipUuToivJz5bc0hmT0rLq6TzoFDhz394r0BcMi1OZljo3nX+m6vkM+z8JsSFoneon3VWxOS5c0ZjQGSANPbbvtiEFfsypUMrKq1Aer4hgJbsTpft0W92W1KezNhEV3dgY21mSvZxZmYXLTG9pZP6boMRF/PBygN47LSamQJbJvcLk4eiKIqidAfMTJycLLz9i40yeRjg5Y6HTh0mQsWkvoE93afvPH4I/DxdUZxnTBw6gts3B+HHj4iSgHvWb+GkZFZBqVh3aAE5kFUoAooxKyUVZXhjyT55hPl5Ykq/UPQO85UYmdyimjoq8RmFuObD9VYXMI5NCMVLcbVr+LO/7bKuf87E2CadG37n5rhidbRlJSEhQVyxfvjhB7GS0D2rPihisrNrXy83Nzf8/vvvWL58OX777Te89NJLuOeee0SI1FdLkDEltHi8+eabYgXh+I3HQuFRHzxG8tNPP6FXr1613rN39crKypJnWmvais5xhZUWMSjKXzoZiglaR9gpsHMJ9fVAqL8XXOCC95cfEJetp84cLYKBnca1H63H/ScNx6S+oSJWaDK+cGofpOWVyEyOWXX06bNG4/w3V8r2H543HJkFZXj85+2IzyySWRiKoru/MbKKebq7yIzQe8vjEebnhfF9QsT8uykhF+6uh3Dh1DicPLonftiY3OzZCkVRFEXpqtAqYSa82ZNWIJOB9D6Y1LfpE3eMF+EgtTiv/nXoZTGoh7+UBbB1x2ZJA2YF4yTmf84ZI8t4j+dkJIPyl+3NxJr4LMlI9tNmIxCfrmDv/LUfk/uGSkwK7/cWS02sCi0rZPGumgxiJnefMBRT+3e9SUkKBLJp0ybcd999Yu3w8/Ord31aMBgz4kigTZ8+XR7cBoUILTYUPnTnqqysrFWnZefOnSJUZsyYIcvoymWP/eeGDRsmooTWF1uXL0ds2bIFMTEx9VqIWgMVK10UmhgZaHfU4AgJbmPqYfqfMuXvZ1dOxaM/b5eUxZyIoaChKGGwPMUKM235eblhT4KRC52zJHOH1/g/mrDDpIvX8r2ZMiPyziUTpUNk2uPYEB8JkNuYkINNh3KRX1qBrIpyfLku0VrB9ogB4eL3SnPx+ZP7YESvIBErzChSH6z/Qv9d/lgZ4N/UIDxFURRF6YxwIpDigNYJwvv40UMjWz3hTIifpzzsYQwL3b43HMyRuFfGofL+PzImSB5XHdVfltPqsmxPBlbszcTfh7Ilcc/Xfxv3fMIxBicje4X4oHeoL5buSpeCloRZzChqAr09MDGufpemzoy/v78Ii1tvvVUmfK+44ooG16ebF13FsrOzrW5etKAsWLBA3L+YXYx/p6enY+jQofI+67FwGbN5cX+hoaGSAeyNN95Az549RXzceeeddfbF47L/3G233Yabb75ZRC6zieXm5mLZsmUIDAzExRdfbP0sA/x5PG2JipUuyk+bk/HjxmQM6RmArIIyESq+Hq7436WTJVvHI/NGSNAdg/D+2J4qdU9oYTFhjnWr6bmBgHcWZ6RYYQAeO1PO9nx4+WTpkNiZEfqkMh3ihkO5+GlTkqRJzC+pkFkikpRTgud+34kZAyNggUU6OEfB81x2/3dbpNMkl8/oq2JFURRF6ZJ8vuaQDOB3pORLbTPeY8P8PXHNUf1x6tjarjmtBfexOTFXBArdungfpkcF90vRxFgSelpQVNhCAUNvDD6uPqoSu9PyJbXy/owiLNubga1JeVLHjQ8G2fNvU8DQ6uLu5oI7jxuKvuG+RpxMar54gxw1KKJVC1AzbobHwCxp3E97w1gTuoAxqN7d3b3RdceNGyfrMmMYoVBgVi4Wb8zLyxORwQryxx9/vLxPgUEhQcsIY16YEplphW+44Qax7AwePBgvvvhinWLp/BxTH9t+7uGHH7ZmBdu3b5+kPubx3H333dbPlZSU4Ntvv5X0yG2Ji0UrJzYIGwMzJVBRspF0BFS1aWlpoqKpxpvCE7/skBmO40ZE4YUFu1BWYcGjp43APybXn6mB1hUG8TG710VT47A6PksyeNx4zMB6A96ZwYufGxMbIjMsTeFfH67DlqQ8cU1LzKmdY51dBzstmqHZWd567CAM7BEgvrTsYM56bYV13TPG9cIl0x37aHZ1WtImlK6LtgdF20TX49nfdmLRznQREDtS8qSWyn/PH4uTRtXOENVa/QSHg68s2muduPzu2ulWofDqor3ipUEeP32keELUB2u0PP/HbnlND4izJ8aI4Pnm70S8vniffB9/bzfEZ9QNyKZ7GBMJ7E0rFA+M/102CZEBRsxrYZExiKb1wN+v+V4VVRYL9qYZsRg9grzrCC5nhDEjt99+u7hatcW9ntec2cUonFqSXfXVV18VFzTGz9QHBQ2vG2Nq7BMGNHWMrZaVLggtGXSXopWClgwKlekDwnD+pN4Nfu6McTHSSQyNMhqMOUvSEExVyHiT5kDXtEPVGUG4z6/WJyCrsFyC/2kzoeWEaQ/5OPfNVVLjhR0jC1uxszFnQ7Kq870riqIoSleDGbwoVugqTaEyMMIfJ4zo2Wb742DVFCoUKbYWjcn9Qq1ihVaJhmASHA+3PXIv35acJ2MQxsBcPDUOX69PtAoeZg5buz8Lq+OzsfZAFrYn54mXBlMqm1zx/locP7InxsQG4fOV+3Bqfw945BSjr5dXreQCjuB4wVI9ZuB3s81ORpf3ziBWTjzxRMnmlZiYiNjYpiUdaE88PDwkyL+tUbHSBdmZmi9xKAUlFdifWQQ/Tzc8cfqoRlUzzbjDo5tmHTkcmM74w5VGlrEzx8fi6KE9cN+3W2T/t80ZJFnBmGUsr7hcvgczn9AXlg9+BW93N3h5uOKv3ekY1jMAfcP9ERfuKzE6jVFaUYlV+7LEfY2ZThoTfaQ1TdCKoiiK0hi83727bL9MOrJmGblkely73Y84brBlZK8gqfPCuyI9HxqCyXQYk0qXb9KzOhsoj/2kUT2xYHuaxMZwO8eN6CkP8/68MyVf7tFvLd2H1PxSbEzIlQfpG+KBk/sZZQtyiysQEVD/PZ9eHweyiuQ+ztie2FAfa9YxwtedpVbbTTfdBGfl8ssvb5f9qFjpgqzalykzCmYGkVvnDHaq2A4eC13NGJDHDoQB/M9VZxjpH+GHT9cckhmPSXGh0nGN6xMiIuXbvxMlvzsr1vKx/mAOrv5wvXyO1hfWimERKVpraOoND/CSeiy20M2NMzu0GN130rAGj/OpX3eKz+0r/xjXqLBRFEVRlNYiozpmlBXlea+keGAa4fbCXpBwwP/CuWNBrdSUAf6sIZFWsWLWXiEMxr/0iL4OkwNwwnFUTLA8fL3c8P7y/YgO8hEPjkU70+Q8cPKyrLIKmQWlRsC+p5tsy154cIxgTjiWV1bJeWTmUuLv7Y4egd6dQqgoBipWuiCr92eJKZU/TmYNOX9yw+5fHQFjYmxhgL/Jc2ePkeC7Eb0CxYxMi8tLC3ZLBhGan+nvSqsRBRmzj+1LL5RsY+YMzP9WHJDaLky5fM8JQ3HCqJ5Wq4tp4mY8ji0HaYHycpPEAoRB/oz5YSHN1s64oiiKoigNQdcv2+dZgyMlEL2tufqo/vho1QHcMHtgnffMpDlNgZlC6brNiT4Wm7alKffU2BDDW4L3fJZJ+GNbCr5aEy9iicKEgmV/ppEdzc3FBSxzyPs+67cwxpVChkkBzOQ/hWUVMpag2KEQ64jgeqXlqFjpYjDD18GsIqtV5coj+9fpKJwdmorNYH3WZzFnZlgXhp0Xq+zuSjXSKr9ywXi8uGC3pHRkkUlmGWMnRpHDOi83f74R93y7BdMHhEtnzw6YyQdsO93lezLwxPwd4gJHP1ry5/ZUeebNobOdP0VRFKVzw3s4B9l0hya0NLQHJ47qiRNGRh221YGfb248qy1xYUb9Ed7rf9+WimOHReGIfsHYu28fAnw9Ue7iLq5eTLxTSb8wVlevsMgYKC2vFL6ebhKsT8HCv2lV6RdubNP8bhQ9/Ki6ejs/Kla6GLQ2cDC/JTFPKtyeN8n5ArJaAi0oJqeOiUZeSbl0ZsxWxsJU5MkzRkmMDjsgzkbRLzYtvxTZRWXS2fFBvN1d4evlLm5lLIBFdy92WMwuRmg6XrDDKFR1zNAe8swgQAogiij649KfmIyIDhQTtaIoiqK0FryH8T7HYTgtAjMHt111cHucwT2K7uHMZkpvCN7DTWgRiQz0tmaVoqBLyS0WTxK6hFGUMPaFlhQ+zM+4VJdJoIDhBCTdxOhqxwnJxhIGKB2PipUuRs8gHxSVGn6Zp4/rBV/PrnGJzQC9QB93axwKM3swB70JO53LjqhJZXzHcUNEeNCl7IMV+/HrthQJyiupqEJJRRlu+myDmJQl+C7E1zqTxc6R+eS9PVyx7kA2npy/w7pNdoY3HzMIj/28Xf5mJ/fCuWM0pkVRFEVpNVhXhS5M5KIpfXB8G2YBc1b+NbO/xJdO6FN/kUh6STA0hfoqxNdDXN+ZEpn3crqCUbxwEpdkFpbKg/C+z+WMg2E9mfqsK6zLQo8NupUH+mjsakfRNUayihWaQH+vdmFiVfiuJMJIXnEFCksrRJgcyqIVpWYdxq5M6RdW63Ou1YH3zCrSO9QwAecUl4mgY0fFgH2akfekF+CaD9cjyNtdfFrpZ3vLnEH4YWOSdVssdMn0z+sPZluXsXDm9uR8a4pnWnUodj5efRCT+4biuqPr+v0qiqIoSmP38oJSwzJwwZQ+TmHtaG/4nSfGOS6fwKB5xq5SY/A1oZcDRQiXubpRxLBQdYBYUShKeD4pXri++ZnKqkpJr+zp5iqB9xQltMTQmkMRU1JeJROjFD72YoWToRkUPxZj4rI7XqP2QsVKF+OdpfEyo8CZiMFRAegq0KJhsietQL7b+yv211qHxSnpImYfhEjBMjEuBL9uNURcsI8nJvbxlxz2P25KgpurK6b0C8Vnaw4ht8S4ORSWVeLfX25CgI+HZGGh6fjNiydLR3bDJ3/LOkzBSP9eZiuxZVW8keCA+ztjfIxVaCmKoihKY3AQbAaAD4xkan5jok2pgQKC1icKFI55CIWKvWDg+wHVrtpmAh0KFX6ebuLmxGVJRSVKCoxt0mmMFhu64TF439hfVZ1rlJBdLC5nMq7w9Wi07ovSctTZvgvBH+x71QP4OcONWIuuCAtHsXPZeCjX2kmYsHNxhG0K4/Mm9cazZ4+W2RZ2LhQc9588HEv/PQuPnDpCYleYQpndH4MbWZySKZRv/XwDvlh7CPsyCmTm5txJvRET4lvLfMyO0jaLipl9TFEURVGaAu8p5qTbCSO7n/tXU2AAPWGQPaG4MBPncFJRnm3GBrZQ1NB7IoqxLx6uUruNf/Pz3AJr21RUVYk1RqwylcYzvTlocZFCk64u4nJmwphWkl9Sbk2KoLQealnpQszfmiwuTfzBnTk+Bl0NBtAv35uBU8f0qmVpYaav5XszJaEAOx9HjLApdskUyDxPu9MK5G8WryKhfl64YGofeZCU3BLM35KML9YdwtakfPyxPU0edAeLC/O1dogku5AxLm5yXEybeO+JQ/HIT9slqP8fk/tIgKSiKIqiNEZRWQWW7DJqlMwdHqUnzAH0iOB9lYKCeNlk7WSNNYoZJtJpCN6vKTpoJaHooSsY3CDZxaqqjIRFfHAimO5iFC2MX6G1hS5j3Cef6Y7G91zLKmXcQLh/Tb7TeqhY6ULQjYlwwM6Bd1djWHSgPEzuOXGodOgXT40Tn152IPX5jLJDYlrizYm5mDEgXP6++4ShWH8gWwpJOoLpki+Z3lceu1Pz8eX6BLy3bL/MsGxPycdZry1H/wh/6ZSCfDyxaFcaLp3eFyePjsaEuFCx+NAdjP6wS3elY0zvYMwY2H4ZXRRFUZTOx8IdaTKh1ivYR2IuFMdw4pBihbVVKFBM6ELn34RCzlyPbtx05eJ9PLOwTIQHxxIe7oalxixEWVlVJRaVCotF6rvws7R+GXVfmDa5CvnFhhs5BUxrCZXMzEwMHToUq1evRlxc01JBz5w5E2PGjMHzzz/fon2ee+65mDhxIm699VY4CypWutBMzMq9WdZ0ut0BBtPbB9Q3xIheQfIwYcwKH01hYI8A3HX8UFwxox/+89tOfL42AWv2Z8uDsKCkn6c7Nifm4KjBEQj09pAU0iw++d8/90iw5G/bUlWsKIqiKA5hADgHy/9duEf+ZlFiDdquH3oz5BaXywRiS6F1xfTUEMtKNe5uLhLbwvnPvuG+KCitlMxgtKAwRIYWF7p8mZTmVclnaO2xT4VMywwFEcVVc6/no48+ilNPPbXJQqU1uPfee3HkkUfi8ssvR1BQzZipI1HflE7KT5uS8cB3W6w/lj93pMmPiD82s6Ci0vqw8u1jp4/CkjtmSWyKGS/DHO8M1ntjSTymPLYA1328XmZa6CpGoUJOHq2+x4qiKIpjHvlxG67431opckym9m/6ZFx3xCzYTCuUmZ74cGAsiwnv3+YmuR8KEFpSOMZirTbGuciy6vIQjHOhuGHAfkJWsYzNaIkhfM3ClMxk2hyKiorw9ttv47LLLkN7MmLECPTv3x8ffvghnAUVK52U1xbvxfqDOZIByxQvhIPj2FDfDj66rg+LVN5y7CCxtDAzGQPtJsWFSJFJpkb8cVMyPlh5QDKXcbaMHd+QqO5h8VIURVGaD6u1093IzDzFjJNK/Xi41VSiZ1A7M3w5ephxLSb1rUcLCNelaOlRHf9aXlElYojvM66FFhI+aCDpEeAt3hkDIvxFxNBqQtHCRD8UnDtS8iW7GK8nhUzf2F546623ah3LmjVrpMBlfHx8ne/3888/w8vLC1OmTKm1vLS0FDfccAMiIyPls0cccYRsx5aKigpcd911YhkJDw/HfffdZxVP5Msvv8TIkSPh6+uLqKgoHHvssSgsNEQyOfnkk/Hpp586TfNTN7BODius84ezaGe6VazQz1VpH04ba1S9nzEwHKNigqUzYHV7ikfGuKRUW1VcqmOKVu/PlAC98yf1aXJqaZq5n/l1J44eEolZQyLb9PsoiqIoHcPbF0/EqS8vk9dMmR+lae8bhOIgpjphzoVvr6q+09ZlfJ8Q/N8pw61/X/DWKvmMPbx/U3zce9IwBHgzHsUbV/xvnbXeDTOEVVRn/XrjognWTKB8ZnwLRQ4nMpNzi8WKQoGSlFNsPdaBQ4Zhy5attfb573//G1dddRX69q0paG2ydOlSjB8/vs7yO+64A1999RXef/999OnTB0899RTmzp2LPXv2IDTUqEvD92iRYazL2rVrceWVV6J379644oorkJycjPPOO08+N2/ePGRnZ2PFihW1xMykSZPEBY3CiIKpo1Gx0olnFJgqz9/LHav2ZYnPJn9cJ4yMQu8wtay0F+yYrp01wPo3O6SxvUPkcdvcwfh41UE8+9tOqdvy02bD+kW+Xp+IC6b0xpUz+iPEz7PBfXz7d6IIID5mDo6oVQhTURRF6RrwXsDB8sGsImuhYaVhfDzd4SO30MMvyMj7N4PjTasKg/RdbfyPzMTGxLPaqkNocaFYMeNf6B5GKw23JzVcyisNITRoCNZu2IyErCKp+bJk4R8iJD7//HOHx3PgwAFER0fXWkbrx6uvvor33nsPxx9/vCx788038fvvv4vL2O233y7LYmNj8dxzz8kxDB48GJs3b5a/TbFCy8vpp58uAiYmJgZjx46tFU/D/ZaVlSElJUUEUUejYqUTQjOlmdObPpQLqivWnzCiJ26ZM7iDj04xoZ8rY4n6RfiJNYXuYXymsOTzq4v24c0l8eKXfPKoaMwdEVUrHbKJbRAfrTOfrDmEx+YNR5jWn1IURekSMHibJFfPxJ81IbaDj6hz8cXVU+t9zyywafLh5ZPrXdc+/p3WLhOxlGQXo7yqqlY5AooajsXMuBn3aoXj7uoimVkZt0rxMmjIcPw5/0dkFZUhs7AUN992By79142wePmLmLEPvi8uLhY3L1v27t2L8vJyTJ8+3brMw8NDLCHbt2+3LqPrmO32pk6dimeffRaVlZUYPXo0Zs+eLW5gtMjw9dlnn221yhAfHx9r3IwzoDErnTTzl8nLC/fgq/WJ8lpdhJwPWk84H8MaMbMGR2Jcn2C8ceF4iXFhMSqmRFy6OwN3fLUJEx/5Q4Irf9iYhOKymuwmtjFIH606KDnhX/zTyBajKIqidH6++TsR5725Eruq6381J9OlYkwO1vewr3PW0LpedlXobd9j4cgAHw9ZxzZzGKEwYO0XwqxgptuY6W5Gy8uw4cOQmpwES3kJ5n/3FdLTUnHupVcjJa9UBI1Z4NKEsSZ00Wpt3NzcxBLzyy+/SFrkl19+GUOGDKkVN5OVZWSXjYhwjnILalnphJj+k4Qz9/ybvxuaj9nYtRCR88CCXhSR7NwmxoVKxjYvd1exoMSF+6GgpBw/b07B9xuTpEgli0jywZzv50yMxU2zB0kRzJX7MrElMc+63cwCo4quPQzq6xnEqrxqdlEURekssJigeW9nymIWF1acEwoTjwYKPdOiIsH2FkutyWXGrJAdW7fglWcfw7W3/Bt+foZVhdlEMwrKZGwQ4mtYauiaZWbkqqpOItA7ri88PT2xbNkyq3sWLS0MsL/pppus+1q1ijE8NaxcuRIDBw4UoWJ+B1pnpk2bhrvvvhsDBgzAN998g1tuuUXe37Jli7iHUTA5AypWOiFsZOzMvDxcsSM5X5Yxjd5tX2yUyvUXT2u/fNxK49fKnKlhEJ63q/F6cvWs2c6UfPx9KAcvnz9WhMxT83di7YFscRl7d9l+cftiYD1jlNhZmebsf0zuLbnebaGJ+ubPNsh671wyUdIsK4qiKM5PUm6JpMAnmrLYueNUHU0U2t/3KVjorm9mIuMkMoVJTGxvPPXgPXB3c8NdN1+HkgoLsovKUVJhZC3LLiqTBy03E6bPxF133SXWFS+/ACla6e3hjmuuuUZiU+i2xZgTBsrTXcs2xfHBgwdFeDB4f/369XjppZfEDcwUMgsWLMCcOXPEcrJ8+XKkp6eLlcU2uJ/vOwsqVjohzPb19Fmj5fVJLy6VZ5onzfeUzgHduZ7+dae8fn1JPPy93KTT6h/hh7gwP+xKLcDO1HxJg0xMi8zp43rh1DHRSEtLq7W9hOxi8Yslv21NxfmT6YKmKIqiODMc/KbkFlstK1PVBcypaUphR7qe0c3biEUBIqsLRY4eNRI//vijBNV7eXrAyxMI8vWstsJUilDJLSqXycvQ2AEYOnI03vvwY1x91VUyZigpq8Tjjz8usScXXHghCvLzMWHCBPz6668ICQmx7v+iiy4SATNx0iSxptx4442SEYwEBgZiyZIlUuE+Ly9PBM8zzzxjDdgvKSnBt99+i/nz58NZULHSiWGGid1phmWFmcD4g2DVdMX5Ye715//YZf2bwXa7Uo0AS8a48Kb10w1HiPvXbV9sQk5xmeRqp6n4raXxyC4swxnDgxBpk8l4f3UhMbI5MQeAihVFURRnJ6eoXJKumLPwk/tqvEpXsMDwPs97ta+nu7h1kR9++KFeAUSBw89FB/kgt7qQ5JU33o7nHn0Ax595gTX6393TCw89+SxuuPcx+UzvUN9aAmrRokXyzPTJtz74tLweEOlvXYcWFFOIUCQxM5i7e40cePfddyVg376+S0eiYqUTs2Z/FkorLIgM8BQ3IpoZNW1x54AB9BsP5crraf3DEBPqi8/XHMLkvqE4fmRPjIoJkusZGegtaRBZk+WsCTF4c2k8Nh7KwWdrE/DFugRcMLkANx4zUNIg7s+sESt0L2PhUMYxMW5GURRFcU6SxQXMsKqM7BWEIN+6WSGVzoUZY0ICHWT5tIfFQBOziyVelff8EF9PBHl7IHDeKTi4fx8OHjqEqOgYSZ/MjHGmIxoFLkURa7zQsYLxLqYooWXH9njcmmARMrOL0W3MmejyYoWmrqeffhrr1q2T3NIMIGIRnM4Ms0V9uS4BZRWGf+tRgyIxSKujdyps3fVOHh2Nl/7cLa9nDIqQAlYmnFkhNCGfNCoaJ47sib/2ZOCaD9eL9eV/Kw/g678Tcc3M/tbiU4S+sixMaYoVmo/NAlaKoiiK85CSZ+MC1l+tKl0B3m2jgrxRUFIhBT4bw6xyn1/CuixV8PNyQ7Cvp2QRu/zq6yRelQXA6eqdU1wu25cgfwvEfdz27m4mZzCzizFutimuayaXX345nI0un7qYBXSYU5qp2bpSPvaswjLsTjVSHB412DlSyylNh8Lh0dNG4Pa5g0VQ0DLCVMaT4mrynHPGZP1BI21hZKDh78oOZ8bACEzqG4LYYC/0Z0ax0gqJffl87SGZYTFzvZuugvd/twULdxrxLd9tSMRVH6yVNImKoihKx9Mr2NcatK3xKl0D3qvp/kXviKYIBVpU6NLF+zdFSW5xuUwy0jrjIm3EG7EhvrIO67hYqscIjG3hfZ6fo3WFyXgI2xPfI4E+7q1QMrNj6fKWFQYMmUFDXQVWQ6cCzygsAyfLjxjgHKnllOYxKibY+vqx00ZKikNWvzVTED/y4zaJUSGRAbULQzEAPymrENfMGiB+rI/+xHXLxJ0gPb8Uwb4ekg2Mf/PRP8JfPsd4F7J8bwZOGxujl0xRFKWD4Sx6TjFLELhgolau75ZQ0DBRUmaBcc9nMp380gpQw/p4uMHH0x3ulVXSRqhHooJ8xbvGLDTNei58FJYZ7SjC38saA0URk15QKlYeWl1oselsdHmx0lxKS0vlYcJMCaSqqkoeHQH3S5Vs7r+whMF4hi/kmNhgBHq7d9ixKa2HN2dVqq9jpL+nzJTwH+kX7lvrGvcO9cFyAAcyC3Hd0QMxd1gkHvxhG37blibpDZmvPbuwXCww7PASs4uQVVBi3d7sIZHaZroQ9n2Eomib6Dws35Mhz6N6BcHXo+Y+0Np09jZhe/yNpQ/ujDBREr1mTIFhekAE+LjL92U6ZLqE5xdXSGwK4IEegYYHBV3BmEmMbmJ8JOYUi8jhWeJEKD/DMQUtLPbnzvy7rc6p7XWzb3tNbYsqVuxgSrgHH3ywzoliDmqmc+sIeDFzc3PlYru6uiI9J98auDU+2qdOClula3Dv7F5IzCmVBCD9AyprXedgtzJUVlZgfXwG0tKCZNmN03vg2imRuOOHPViXUCCzLCv2ZSHU1x17kl2xaschVJRXoFeQF4pys1DUgd9Nads+QlG0TXQevv/7oDyP7OHVpvfzzt4mePxM2VtQUCBB4F2RqAAPa4ZQUzx4u0EydhFfdxf4BnhY/ybuLkCEnzvCfN2QXlAuVjoKE1pcGJBPbwsKHeKCqlqf5T54TuW9ZsS1NAdeL+4jJyenTrvLzzcy2jaGihU7WIDHrOBpWlZiY2OlcA5zU3fUD5SNiMfAC13hmiKuYOT4sXGIjKxxJ1K6Fn3r8dQa4+YHt+XJyCiugndASK1sI8+fH4x/vrdWKiLTypJVVIHl+/MQ1yMI7h7uGNUnHEEhYZIpxEynqHRu7PsIRdE20TkoKCnHqgOGB8eMYb0QaZuPvpXpKm0iMzNTjt/Xt3bK3q6AGYrv72lBcUm5WFWqKivRVFuYv7sFBZYKmeSk1CllPAuD7eEi7mFJWeXoE+Zb6zPl5cbkd2sjtWOKiuR6hYWFISqqbmZSb+/aLu71oSMVO7y8vORhD38YHfnj5g/SPIbE7BJJUUf3rzGxIZrlqRvSK8QX4f4eyCm1YGtyPqbbxC3llVRI5pBh0YE4b1IsbvhkA0oqqvDOsgMI9/fEmv3ZWLgzXYpGnj0htkO/h9I2fYSiaJvoHPx9KFeyN3LIfcSAyDb//Xb2fqJnz57yHejt0tWhO1dungvymqHHaFHJqI51ZeKe4tIKScJjenhxU7lpRt0XihfTPYvtoa2EX3BwsAgVR9tvajtUsdIJYQAVYU0OTUfbPWEn8+DcvggICUVkYE0aZDIgMgAfXTFZilH1CfPD1+sTsfZAthQeYywL/WCZUWRXStPMr4qiKErbsHiXEa8S5u9pTbCi1A8HvBQstEC1lUWgs/PMh+vk2QVFuHZWf3z45x7kFpUjszqmxUxn/M/pcZg3Jho52Vli+WgLAUt3PTe3w2/XXV6s0Fduz5491r/j4+OxYcMGhIaGonfv3p22oCA5ZUyvjj4UpYMzyDDjlyMCWUzK28OaOSw1rxSB3uU4lFWE3WkFkvedaRAVRVGUjmNddXr6fuFGxkalaXAA3BqD4K7I0JgwLNubiZuOGYjwYD9kMtza1QOBfu6SEpmTlXvTC3Hfj7uwaE8OHj0uVtyxnNna1uXFytq1azFr1izr32Y8ysUXX4z33nsPnQ1zsMmZ9SMHan0VpXFuOGYgfD3c4O7mij+2p4hbGGOeFu1Mw/bkXAztaQToK4qiKO0HXXBMC/e4Php7qrQOt80ZjKtKKyT9McWJrVWKaYt7hfhI4UnWZaNlpTPgvDKqlZg5c6Z0CPaPzihUyILtqfI8vncIgiR1naI0DC0sFCrkmKFR+OjyyVI4inEsp/53mRSTVBRFUdqXPWkF1RmbgNlDe+jpV1oFV1cXESokoDo2hbAANUnMLpZ6K/89fyxOGFk36N0Z6fJipSuxKSEXz/6+S14XlKqvptIyxvYOwYS4UPh7uaOs0oI7vtyEx3/e3iXz1iuKojgrC3akWl16h0d3TLZRpesLl/tOGopnzhqNOJssYO5uLjhqUGSnyaamYqUTsTo+S7I6kFGxajJWWk5MsA/iwn1x+lgj7un1Jftw2xebUF7ZOYuFKYqidDbWxhvxKpP7hsHXs8t75SsdxPg+oRgcFYD+kTVxUf0j/CV2pbPQeY5UwdakPEk/F+TjjsdPG6lnRGkx4/qE4KhBEbj0iL54+sxRYib+an0CrvlwnQoWRVGUNqaqyoK11cH1/5rVX8+30uacOqYXThjZU14PiQroVGdcpXwnYkeKUThqVExwpzHdKc7JeZNqMuGN6BUkaTP/9dF6/LE9Dfd/txWPzhuOHzYlSzAeRY2iKIrSemxLzpN08nTH5T1dUdpzHDkkqnO5HapY6SQwnuBAVpG8PmJAWEcfjtLFOHpID7x47lhc9eE6fLL6oFhXdkqn5oJp/cPgUR2gryiKohw+f+0x6qsM7xkoAfaK0taUlFdif0ahvB7Ss3NZVnQE0knYnV4sqeZoUJmhKYuVViC/pBwvL9wjj5yiMswaEoljhkTKe1+uS0BKHqvgWsT9sKyiCok5xdiSmIsKjWtRFEVp8YBx4c40/FkdXH8wuwgV1YX6FKUtqayywN/bHcG+HvXWaHNW1LLSSfgrPleeB0T4o5cW81MOE+ZXv+z9teI3TbYl5WFQjwARKIN6+GNXagHS80tlxu++b7dIRhFz3bcvmYDIAG+9BoqiKM3ko1UH8fX6BHEDI71DfeHtocUNlbbHz8sd/zl7DHw9O197U8tKJ2Hpvhx5vnxGX2v+bEVpKWF+nlIMatqAMIlXOZhVhD+qa/hcdWR/uYGStPxSsbqYQoXQz1pRFEVpWa20orJKSZbj7uoiWZoUpb3oEeiNAO/ON4ZUy0onIDWvBNtTi8QFjLEFinK4MEHDP6f3ldcpuSX4eNUB5BSXY0R0EM4YH4OTRvfErZ9vxI+bkpGQXSwzf7ypHsgsQlZhmV4ARVGUFtAr2Ae70wrkNYPrY9VTQlEaRcVKJ+DPHWnyPCTKH94eagxTWpeoIG/cMmdwrWVe7m544dyxSMopxvqDOTiUVYRJfUPlPVpaFEVRlOZDF5yCEqNeGuMHYkN99DQqSiPoyLcTwHSyJKuwHE/O39HRh6N0E1h7hVYWFo4qqagS0VxlsUg7VBRFUZpPVlEZissrrZaVGLWsKEqjqFhxcorKKrB8b6a8pp9hiK9nRx+S0o34dPUhxIX5wsvdFcm5JWJhySpkljBFURSlubBaPeEkEFPCx4SoZUVRGkPFipOzJTFP0hoGernB291VivQpSntCl7AbZw+UYNC8khrxrCiKojSPnSn58nz04EhcfVR/TZijKE1AxYqTwziBBTfPQKifB+vzIVgzgSntyAvnjpEMdLypXnVkP1m2Jj4Lu1ONG66iKIrS9OLOZgzq2RNjcOKonpLsRFGUhlGx0gn4ZE2CWFVICEWLorQT/SL8ceqYXlJn5ba5g3HUoAiUV1lww6cbUFph+F0riqIojbMxIUeK63q4uWBqP8MdTFGUxlGx0gm47Ig46+tewUb9C0VpbzgD+PRZoxDo7Y7tyXk45aW/pKK9oiiK0jjzt6TIs6+nO3w8NRmrojQVFSudgHB/Lzx76gDce8JQLSCldChlFVUI8TPipnamFkgtFrWwKIqiNM7iXeny3CPQS0+XojQDFSudhDA/D2udC0XpKK75cD0CvT0QWi1YEnOKkK1FIhVFURoks6AU25ONWL8+oX56thSlGahYURSl2ZwyOho9A71QUFqJX6pdGxRFURTHgfWP/rRdXrOwc3iAZvVUlOagYkVRlCZz65xBmDEwXJ6vnz1Ilv33zz1IzS3Rs6goiuKApNwS/LEjVV7TMs2aaYqiNB0VK4qiNJmZgyNxx3FD5GZ75vgYKWiWWViGea8sw5/VN2NFURSlhl82J6OgpEJeB3i7S+V6RVGajooVRVFaBCsw33D0QHmdll+Klfuy9EwqiqLYseFQDqoskMK6Pp5uKlYUpZmoWFEUpcWcNq4XIgO8UFllwZr9KlYURVHs2ZxgpHgP8vGAC1xw7LAeepIUpRmoWFEUpcV4uLni7Akx8npbUp6kNlYURVEMSsorkZBdJK+DfD0Q5u+J2FCtl6YozUHFiqIoh8Upo3uJe0NpRRW+35ikZ1NRFHT37F/v/BWPb/5OwB/bUlFp4cSOC3w93ZBZUIaiMiN+RVGUpqFRXoqiHBaRgV5SuDQlrwRvLtmLM8b1kmr3iqIo3ZG96QX45u9EeZ1bXC7PIb6e4gJGknKKMSAyoEOPUVE6E2pZURTlsGAqTro2uLoYVe2X7s7QM6ooSrclPsNw+2Is36Es43VcmC+uOqofJsSFqBuYojQTFSuKohwWrq4uuHBKH6m/Qt5cuk/PqKIo3ZYDmYXyXFhWAQuAHgFeuGR6HE4aFY0HTh4OL3e3jj5ERelUqFhRFOWwOXdSbzwyb6RYV2hZ2ZGSp2dVUZRuyf5qseJXXU/l/Ml9cMLI6A4+KkXpvKhYURSlVWCGmznDouT1p6sP6VlVFKVbciCzCGUVlZIhkcwbq0JFUQ4HFSuKohw2OUVl2J6ch2OGRcrf325IlJSdiqIo3S0T2KPzRqJfhJ/8fdSgCPQJM14ritIyVKwoinLYfLkuAXd8uQk5ReXoGeQtz79tS9UzqyhKt4KZECMCvLB8r1Ek96KpfTr6kBSl06NiRVGUwybY11Oes4vKcOZ4o0jkd9WpOxVFUboTP2xMkpTFMSE+mDnYsDYritJyuoVYefnllxEXFwdvb29MnjwZq1ev7uhDUpQuRbCPhzwv2ZWBAG/zdTpS80o6+MgURVHajz+3p+KFBbvkNbMkujHriKIoh0WXFyufffYZbrnlFjzwwANYv349Ro8ejblz5yItLa2jD01RugwhfoZAMX22IwO8UF5lwfN/GDdtRVGU7sAnaw4hMacE7q4uOHtCbEcfjqJ0Cbp8Bfv//Oc/uOKKK/DPf/5T/n7ttdfw008/4Z133sGdd95ZZ/3S0lJ5mOTlGdk8qqqq5NERcL8cAHbU/hXnw9naRKCXOyxSUQA4cWQUNifm4MdNKfh1SyruPaEcPp5aV6A7tQel49E20TFsPJQjz7MGRyDIx92pfpPaJhRnaxNN3W+XFitlZWVYt24d7rrrLusyV1dXHHPMMVixYoXDzzz++ON48MEH6yxPT09HSUlJh13M3NxcaVA8fkVxtjbhZ7FgWm9/RAV4wr0sH2cNDxaxwhiW95Zsxxmj1G+7O7UHpePRNtH+JOaUIi3fmOw8Y3iw03lwaJtQnK1N5OfnO49YOXDgAPr0af+MGBkZGaisrESPHj1qLeffO3bscPgZChu6jdlaVmJjYxEREYHAwEB0VGOSDCMREToQUZy2Tdx5cs3vLCKCrmDxcuP+dks2LjlyqFpXull7UDoWbRPtz2urtspzgLc75ozrD2dD24TibG2CseROI1aGDBmCa665Bvfeey9CQ0PhzHh5ecnDHl7EjhwEsDF19DEozoWzt4nTx/XCa4v3SZD9uoM5OHJQREcfUpfG2duD0v5om2g/issq8fXfSfJ6eHSg0/4OtU0oztQmmrrPdjmyJUuWYOPGjejXrx8ee+wxFBcXt8duER4eDjc3N6Sm1q73wL+jooxK24qitA0njTKqNueXVmD53gw9zYqidFn+t2I/8koq4OHmgqn9wjv6cBSlS9EuYmXixIlYsGCBZOb66quvMGDAALzxxhttHtDj6emJ8ePHy75NuE/+PXXq1Dbdt6J0dzi72CPQCxYLsHBHGqqqjAB8RVGUrgRrqry2eK+87hHojbhw344+JEXpUrSrzYcpgxnw/swzz+Dpp5/GsGHD8PXXX7fpPhl/8uabb+L999/H9u3bxR2tsLDQmh1MUZS2My0fP6KnvB7QIwCuWm9AUZQuyHO/70J2UTn6RfjhnYsn4IgBallRlNakQ7KBnXrqqVKk8dZbb8VZZ50lQfBtxTnnnCOZvO6//36kpKRgzJgxmD9/fp2ge0VRWp85w3vgveX7sWJvJiqrLFogTVGULsWmhBy8v3y/vH7olBEYFNUxiXgUpSvTLmKFNU22bdtmfSQkJMjy3r1746STTmrz/V933XXyUBSlfZkYF4pAb3dkFZbh74PZmBDn3Ak2FEVRmgrTvd706QapMMVCuJP6av+mKJ3WDYzpgDds2IBBgwbhvvvuw7JlyySv8759+/Ddd9+1xyEoitIBeLi54qjBRhawR3/ejrIK5ymQpiiK0lTYd5VW1PYC+X5jEvZlFMLFBQjx88RZr69AXkm5nlRF6YyWFftsXIqidB9mDorADxuTsSM5H3vTCzC0p7pJKIrSeSgpr8TVH64TS/G1swbIsj1p+Xjguy3ymlYVTzdXBHi5w8fDrYOPVlG6Hl26gr2iKB3P9AGGZaW4vBLrDmSrWFEUpVNxKKsI2YVl2JVqVNvOLizF6a8sl1TF3h6uGBDhj3tPGibFIGlNVhSlddFflaIobUpUkDciAjzl9eJd6Xq2FUXpVCTlloCZ102ryf3fbRWh4ubCmiphGNM7WCZhYkI0ZbGitAVqWVEUpc2ZFBeKnzanYGtirgSlMq2xoihKZyA5xyhk3TPIB79tTcEPm5Ll73ljo/Hs2WO0hpSitDFqWVEUpc2ZMzxKnjMLyyQzmKIoSmeyrJB9GQX410fr5XWonycunhYnr7WGlKK0LSpWFEVpc8wiaaUVVdiUkKtnXFGUTmVZscCC7cl5qKiywNvdFT2DvDX+TlHaCRUriqK0OWH+Xgj28ZDXaw9k6RlXFKXTkJxbgvS8UuxKLYC7qwt6h/liTGywBtMrSjuhMSuKorQLMwZG4IdNSXCBxqsoitK+/LQpWawjJ42KbtbnCksrcDCrCKn5pfL3I/NGwM3VBUcNMrIcKorS9qhYURSlXZg2IEzECtMXK4qitBdFZRV4bfFeq0tqsK+RnbApLNubgaTqAPsLpvTGuZN6t9lxKoriGHUDUxSlXRjfJ0SeNxzKQXmlVrJXFKV9KCmvquXS1VQ+XnUQ13y4XuJU5gzrgQdPGdFGR6goSkOoWFEUpV1g4TQGprI45K9bUvSsK4rSLjBz1+jYIHltWknIpoQcvL54b536T1VVFjzxyw7c/c1mVFZZcMa4GPz3/HHi/qUoSvujYkVRlPbpbFxdEOxnuF+sjM/Us64oSrsRHexTR6zsTMnHj5uSsdqmPyopr8SNn22wuo3NGhyB8yfFQnWKonQcKlYURWk3+oQaFZ63JObpWVcUpd3oVS1WEqrFCmPnEqtf788okueC0gpc+t4a/LAxCe6uwM3HDERGQRke+2WHuIIpitIxqFhRFKXdGBQVIM970wv0rCuK0i58vT4Bby2Nl9fJOUbMyjd/J2DB9jSrgEnNK8HpryzD8r2ZYkWJDfXDH9XvM02xt4ebXi1F6SBUrCiK0m6M6mX4jeeXVNRyx1AURWkr0qvTDpPZQyNRVlGFrUk11t3Ckgqc8epyax2VfuF+iPD3sr4/tV+YXhxF6UA0dbGiKO3qN+7j4SZB9msPZOOUatcMRVGU1sBiscDFpXYgfE5xuTxfPqMvTh3TC4eyilBRaYG3h6u4d+2ptvSyKv1/zx+LmBBfRAZ4iasYs4cdPSRSL46idCBqWVEUpd0I8/eEr6fhTrFe660oitKK/LgpCRe+vbqOm2lOkSFWQqrrq9CqW1ZRiYTsYvx9MEeWDYz0x883zMD4PqHoEegtgmdCXChOHh0tyUEURek4VKwoitJuhPt7wc/LMOhuOKTFIRVFaT1eX7wPucXl+GDFgVrL86otK/7e7vj7YDae+W2nuHzRakIZEhXojXtPHIqQ6myFiqI4F+oGpihKuxHm54l3/zkRs59djG3J+VIc0sNN50wURTl896/6yCkuQ2VVFe7/bgu2JubBXLNfhJ+4faXllaJfhL9eAkVxUnSUoChKu0HXCgavBnq7S5Ar6xwoiqK0Rt9y3dED6iwvLqvEvvRC7EwpkJTpFCo+nm6IC/PFHXMHY1jPIMwcHInY6rTqiqI4HypWFEVp90HF4OoUxs/+vlPPvqIorQKD4s3sX5wMYXriuc8vFnevSotFJkooUgZE+OGx00ZiXO8QPfOK0glQNzBFUdqVz9YcxP5MowjbhoM5yCgolVgWRVGUllJaUYmIAC9x99qYkIPpTyxAekGZvMf+5dY5g3DmuBic/9ZKlJRXGRm/Ar31hCtKJ0DFiqIo7Qr9w5m+2HTRYBG2U0ZH61VQFKXZVFVZsGBHGt5cuk9SEqfklcAMX6Gl5eJpcfLwr07sERfmhx0p+YjPLETvMHX9UpTOgLqBKYrSrrDOwczBEfK6pKIKi3YaVaIVRXG+oHUKAAoCZ4SZv574ZTtu/PRvrI7PEncvCpXh0YF47pzR+OvfR2NkryC42dRdca9O6PHVuoQOPHJFUZqDWlYURWlXOJv50Kkj8MvmZHHTKCip0KxgiuKEfL8xCW8tjccZ43rhkul94QyUlFfg0zUJWLgjVayy5ZWGkKIcGds7GLfPHYIp/ULF1evbvxPxwcoD6BPmi2fOGg1vDzcRMlsSc62FIhVFcX5UrCiK0iGM6R2C37elYlLfUE1frChOCIUK+Wp9YruIlZLySikWyz7BtICQyioLlu3JwEerDmDRznSUVlRZ3wvwcpfaTXefMASnjOlldS+96bO/kZRTIn+P7R0iQoWcPSEWfl5umNQ3rM2/j6IorYOKFUVROoQxscEiVjYm5OoVUBQnZGRMEDYn5OKf0+PaZX8vLtiNpbszcPmMvjh2WA+sP5CDJbvT8c36BGuwPHF3dZFg+pfPH4sHf9gGeqlN7R8u79Fi+8qivfKaRR4vnNIHs4dEWj/r6e6K08bGtMv3URSldVCxoihKhzAqJkieNx7K0SugKE5IebUFo0czs2Yt3JEm1eInxoXWiYF5+tedcHN1QWyIL44aHFFr271CfFBUVoEX/tiNu7/ejMKySut7Hm4uEiRPEZOYXYy8kgqs2Z8tQiXc31PEC8kvqbB+5vqjB9Q5BkVROh8qVhRF6RBG9QqW54NZRXh54R5cO6tuQTdFUTqO7CLDmhHi69nkz9Bla8W+TJmEYDIN1jWZWO3qyd86LScmgT4eOG5EFFJyS/D9xkS8t2w/knIN1y1ToPh6uuOBk4dh+oBwxGcUYkq/MLy1dB++25AkAfUsBGmbAGBcn2CJU+H6KlQUpWugYkVRlA4hyNdDUoum5ZdiU4JaVxTFmaAVJKvQECv/W7Ef9588TIRDYzDQnUKlqKwSn6w+KMtePG8s+ob7YdmeTGPbsKCi0oKv1ifgveXxWLkvq+bzLkbK4Stm9MN3GxLRJ8wPp48z3LZMKwyFCONWZgwMx6gYY9LDZEBkAD64bBICvT1a8WwoitKRqFhRFKXDGNjDX8QKZ1wVRXEe6IJlZtrampSHzIIy+IY2PGRgGvIAbw/MGR4lmbhI/wg/ESqEkxK0ouSVlIvYYL0T20B5WkXS88vETcyw6rhIbJs9Q3sGyqM+gpthCVIUxfnp0nVWHn30UUybNg2+vr4IDq7b4SmK0rGMrp4VTc2rcf1QFOXwKSitwJ6M4hZ/3tfDDe/+c6L1b9PKUh90xXphwW783/dbMSkuVNKRF5SWY3tyPi56exUue28NPltzCOkFpdZsXt4eDHaPxuCoAIzoFYSrjxqAYF/DIrJkl+EuxnTEiqJ0b7q0WCkrK8NZZ52Fa665pqMPRVEUB0zqGyLPecUVKK+oCaZVFOXweOjHbXjkt/1Ys7/Gxao5uLq6INzfy5oIozGxklFQirziciTnFuPOrzcaVeIzirAzNR9LdmdIlXnaaXw93fDMWaNw1KAIDIwMkAB5TzdXCbaf2j8M0cE+tTJ3DY829q8oSvelS7uBPfjgg/L83nvvdfShKIrigIl9jFoHFVUWGdyMtPM/VxSlZZguVgxon9zPSOtrsj+jED6ebk3K8hXq51lHrDCeha6bIkjSC/D134lIyilGQakx4ZBRnWZ4YKQ/MgvLJOie8SU7U/IlnfAZ42IkWJ7Wk33phbLugAh/eWbFea5HJvcNtdZHURSl+9KlxUpLKC0tlYdJXl6ePFdVVcmjI+B+eXPoqP0rzkdXaRM+nq7w93KTQc6KvZlSXVrpvu1BaT3OnRCDD1fsl5oktu2CaX+v+2Q9wvy88PZF48WCsjo+CwHe7rXiQGiR2ZyYi71pBRIQT4vJmvhMrNyXic/XJuBQdrHD4Pq+EX64efZATIwLQWSgNx76YRvWHsxGdLC3ZO+KDfGRtjo0KgCLd6VbP9s/wleO88IpvdEj0As/bUrGEQPCtE23ItpPKM7WJpq6XxUrdjz++ONWi4wt6enpKCkp6bCLmZubKw3K1bVLe+4p3bBNRPp7iFjZeCAdaYONQFyl+7aH7sjaQ3koq7BgWt/muzzxmr+2PAle7q64dHJP63J/l1JUVlZgT3IW0tLSrMs/X5eCivIKpOZUYNv+ROQUVeCxPw7A090FT58yAEHe7qiyWPDVqkNYuCdH4kuKK6qwJdGYuDNxcwEGRvjKc3phOXw8XOUYZg0MwsQoN6AkD2kleQhwr5D9+blU4KV5fVFcViXHMyDQgvNGh+ODtSmyb8/yAqSlGVaWMeEuGHN0NCyWilrHrhwe2k8oztYm8vNrkmx0KbFy55134sknn2xwne3bt2PIkCEt2v5dd92FW265pZZlJTY2FhEREQgMDOywxuTi4iLHoAMRpau1icuPLMXd32xBVgkQGVlTaVrpnu2hq7LhUA6+WJeAG44eUMv9qqyiCq99sVteHzG8t8SJNIeE7CKsSzKy6V1zTAiCfDxQUl6JnoVucHNLRqbd72r6EHcs3GcMEPIsPvh1bwosLq4oKrfgtVXpcHVxwV97MpCaV+NhYBLm5yHve3m4ITrIG4+dNgK/bUvFz1tSrOv07xlWa38De1XK/vIr3RHVo4d1OddIKU2Hu0cGBkUFoGdUzXtK26D9hOJsbcLb27tripVbb70Vl1xySYPr9OvXr8Xb9/Lykoc9vIgdOQhgY+roY1Cci67SJsbEGkH2WxJzxZGEbilK920PXZUHvt8mz68vicf/nTLcujyzqBQu4kAFhPh51Xv9mG2rqLxSqrjbkpRb8/nEnBK4ubliW1IeHvl5hyzLL63AtuR8qfLOYHZaMQO9PLAlKRfXfLS+VsX3PdXxI4TuY35e7pg9NBJHD47EyJggPPbzdiTlGB4GxeVVuO+7bQjx87Dun0QF+dT6DqxKz/dXxWdhS1JerbooRw2OxNDoIBSWVmi7bSe0n1CcqU00dZ+dTqxQ/fGhKErXYFAPf0lhykHVvoxCDIg0Am0VpatQXFaT6Y6xH7ak5xsWjNhQH6nyXh8r4zPx6qK9uH3u4FoD/iFRAdbXP2xMwvK9mQj0dkdpeRWKSitRVlSJc99YKdYWJrJwBOcHQnw9EBvqJxm5xsYG440l+8QF7PIj+mFYdCByi8vRM8gHJeVVePKMUXjox604lMWgekPsXDOzv7iB2dc/YTav8X1CsCMlD0OiAusMkpoS5K8oSvem04mV5nDw4EFkZWXJc2VlJTZs2CDLBwwYAH9/HRApijPAbEGs6cBB0MZD2SpWlC7H1iRaDQ0ePnVErffSqmsMRQbUDNozC0olza+tSxgrvnOdL9cl1BIrrNR+9JBIfLshEd9tSEJxeSXyS8rFimIP7R/9IvzQO9RX6p8wIxgnCp4+cxRG9KrZ5pPzd4hQ4bqmGKJ72QMnD5NMXxEBXpg9pAfeW77f+hkeg6PMXVxGS1JRWYWkIlYURWkuXVqs3H///Xj//fetf48dO1aeFy5ciJkzZ3bgkSmKYsJBkOn6tWZ/Ns4YH6snR+lSbEwwxMqxw3pIhixb0qotK+sOZOO7DYk4fkRPXPr+Wni5ueKDyyfBy90QABQNT6bkiYigOxbdJllZnlabssq6GXX4k4rw98BRg3uI9YPpgCkcIgO88Mo/xkumL2bd2pteUKuWCYXVX7uNgoyXTIur5ZYpvu0BhoCa0j8Mf+5IkxTGceF+jaYY9vXs0sMNRVHakC7de7C+itZYURTnhoMcFoLjjC0HbIrSGVm4Mw1vLN6H+04aJm5Ttmw8lCPPo2Pr1hEyxQr55u9EzBwcKfEpxVWV8ntgquFFu9Kwfn82kquD3vekFdTaBjNyMb6EYoKuWExD7OPhhksnRmLe5IFIzS/Flf9bJ+sO6RkoFpVJfUPl7z5htTPw9Qv3l6rx/E2O7W3EkzmiV7APXv7HuBacKUVRlObRpcWKoiidg2E9A7EpIVdiVpgdSd1FlI5k/pYUzN+SLK6JNx4zsE4chhlr8vu2VJw0uqe4Yv3nt12y/D+/78RbF0+0rseUoBP7hqJnkLdYET9fcwjhAZ44eoiR/So9v0SKJtJ9i1Xgn/99J7KLypCWV4rz31xVZ79uri4SX3Lx1DixqDAbFwXKDUcPxAsLdkshxsKyCiTmFCPU17jFM9aEcSPrD2bj5FHRDX53CpmH7FzVFEVROhIVK4qidDiccf587SEZtO1KzceIXs2vN6EorcX7y/dbA8cXbE91KFYY7M7CiYeyi3D7nMHW5cyuRUtKXkk5ZgyMEGvHhVP6yHu/bU3B28vi4e/pht2pBdiVWiDboCuVybvLD1hf0wHL29MN/p7uCPX3xBsXjsd1H/8t7+1OK5Aq8J5urhKkzmKMp46Jltc8fkJRY/Lv44aIGIoN9dWGoihKp0LFiqIoHU7fcD/xaecAcWNCjooVpUNgYDoxhQqJz6gRErZB8WsPZMlrxndM6FPjLnXTMQNx+5cbxSpz5vgYiR2hxZCuW3tS81FUbsSXrDtouIaZ+Hm6idWEqX7pisXYEV8vd7i5uGBCXAiuPLKfWEhYCZ7pgylUTFgNvn+EvzwqKqtElGTklyLEx72WxUSFiqIonREVK4qidDj9wv3Ex56DxL8P5OAfk42ZaEVpL77fmIQ3l+zD5TP6Ylr/MOxMzUdmQRkOZBZKDIltoPmv21JhsTDgnG5ewPN/7La6L976+UYk5RoZvv7zu+EaZguzE7u7ukqs1uwhkeJGxuxefx/MwYsLjOKQtLQEeNdYRY4Z2kOEChncI8Ba64SuZZdMj6sl7t3dXPHP6X2l2JtWf1cUpSugYkVRlA6HGYb6R/ohvaBULCuKcrgczCxCVJB3k+KfKJLfXrpPXKhG9grCqWN6iUA587XlcHdzQVZRWa00wot3pkksypGDIiSVcE5RuWTpMqGsYdavkb0CJUA+q7AMx4+MwgVT4tAnzBdvLt2HXzaniCvXDxuTEeHvLZnCknKKZXsxIT5IyK6pxzLYppbKvLG9EOjjIe5jU/qFYVr/cG0siqJ0aVSsKIrS4dCv//lzxmLK4wvEZYbpWOm2oigtgULige+3iAh57LSRGNijZrDviO83JEldEgaqx1Vnx6Il5Z1LJkpQPNunWdBx0c50sabQrYsV2U1oeGGiiOyicvnMnccPETFz06d/Y296IY4b0dNaQ+iqI/sju7AMK/dlyXaYBYwV4i+a2keKMjK98NO/7pSkE6F+nrWEUr8If3lcPqOfCCpFUZSujooVRVGcAs6Cs+5Dal4pNiXkYHK/sI4+JKUTiBJiigkTCgCmwmbBQ1Zef/SnbRjXOwTHj+wpldRDfT1r1Tv5Y3uqPJ8zMVYsJPwct0nRwQxaf2xPw8IdadiRkl9rPxQRswZHYNaQSEwfEI4v1h6SwowkxNcT7y2LF6Fipvo1YWzKXccPxfaUPLG8mCmCuc9B1cKKYuSnTUmSkrg+bF3TFEVRuioqVhRFcRrG9w7Bz1tSxMVFxYrSEBsO5eC+b7fg2ln9xWphy8p9mfI8rk+IxI/QgpFVWC7FD2//YpNYUL64eirySirg4eYiaYgJg9ZZvZ1B6jMGhmPJ7gzJ2GVCTTQ2NhizBkeKQKElxVYwTIgLFbES7Osh6Ye/Wp9ofY/xJbbwczwe24KM9kknrjt6oDYCRVG6PSpWFEVxCpjBiBW5yar4LFzX0QekOB05RWVWtywzGP2T1YdqiRUGutNVi0ztF4bRMcESj8KU2L9sSZbltJ78ujUVLy/cgyMGhEtMCl2qXlm0Ryx7ZGe1SHF3dUGYvydGRAdJXROmJmZwPC2B9paNMbHBeOjU4ZJ1K8zPE/9bcQCpeSXWwHdFURSl+ahYURTFKaBrDgOHyZr4LJnd1gGeYrJ8bwYe/3mHZOq6be5ghPt7ikWE2bCYSjghp1hcvX7dmiJV4UP8PCUAncJiSFQgtiXnYsGONElPzLTCd3+zGYWlFdicmFvnJNOCMiDCH+dNihV3sqW7M2pVmmfmMKYldoRt1ffHTx+J5//YJfVWFEVRlJahYkVRFKeAs9TMmMT6EiUVVWJlYbFIpW1dqZh5yjaAuz0pKa+Uoob2Fgou356cJ4kWKFj7R/jhz+1p8t7yvZmSEnh/plH/hAHxj/y0XeJUZg+NlIrutMCE+Hng/77fKhaVA5lFkrGrsjrGxR6mzR4VEySZuljQ0dPdDd9fN10sOLS48PwwnTAtK5sTcqXWCcVQU7LcPXrayFY5V4qiKN0VFSuKojgN50/qjdcX75Og6P+t2I9nY8d09CF1WTZWx3wEeLvj4yumtPv+KUb+/dUmnDuxN6KCvCSI/Y65gxHs6yliZMVeI+6E0PWrqKymUCMLMVZZLGIZufvrTVh3IEeExLbkmuxcpjuXPYxXmRQXKvEsP2xKkr9fOm+cJHeglLnhk7+lyKMZtE8hdekRfeU1rX2/bEmplUpYURRFaVtUrCiK4jRwoDp9QBh+3pyC37elYsmudEn/qrQ+TGJAGIPBrFr2GbUa+hwtHg1dFw7qKTjDGrDYvPNXvKQA/mT1Qeuyj1YdxGVH9MXa6mNjZiyKkCMGhOGVRXtRUcnjNOKbSsurRFyYFhbSL8JPxBczcY3qFSTfictoOXnq150iTFxdXPD6ReNlWVp+CbYk5mFfeoE1rfC7l0ys91zQynPy6OgmnSdFURSldVCxoiiKU8Hq2xQrhWWV+HDlARUrbQTT55pQWFAoNgZdoh76YZu8pvsY63044p1l8VLskDEbZnX1vJJy/L41VbJkMS1vpYMaIfszCiVtNeujeLi5ws/TFVv35+KHjUY6YHuYyYtWl0BvD9w4eyBOHdur3mP/Yl2CuJwNiw7EOa+vrPUeUxLPGR4lr5sq2hRFUZT2QcWKoihOBbM3ebm7oLTCgmAfDxkgaz2J1odFCU1oXWmKWOF1GNc7GOsP5mDt/myHYoVWFQoVQqsJYza4r4oqC95bvl8sI/+Y3AdJuUaFdrpzUZwUlVXiUHaRpP6lNYWY2eEILSST4kIwqEegxKTQosIK8d9X72vuCENs1MfrF4yX46f72fwtKbXeoxXvhtmaJlhRFMUZUbGiKIpT4enuinG9Q7FiXyZG9w5WodJGpBcYMR23zx0sqXabytT+4SJWWMvk7Imxdd7fnlxTOJHWEfLgD1uriyNaxH3rxT93YXdqAQrLKqzuXLZQ0PQO9ZV6JpP6hmJiXKgEqztiVEwwgnw9JOtXQ5iC17beyenjeiElt0RjUBRFUZwYFSuKojgdE/saYmV1fJbMwiutzyPzRiKzoBT+3s27DUzpF4pXFgG70wok5iMyoHaxw1XxRmD8oB7+OG54D6nivnhXenVsDCQjl1nDxCQ6yFvSDA/sEYBJfUMQ7uclFeZ9PBsWIKS5xUPpNmYS6ucpboeKoiiK86JiRVEUp2Ny31B5XrYnA8VlFfDx1K7qcKGr1eM/bxcrxbyxvSRmhYKgKTATF1P2lldasHR3uogOsm5/No4f2VNcv1iv5Letqfhg5QGxmPBv2wruJrRvsKDi8SN6YlyfYKlLQrHSXrEi3M+Jo3qKG9vRQyLbZZ+KoihKy9ERgKIoTseEuBB4u7tKQb77vtuKZ84a3dGH1On5en0CNiXkyoNihexOzcdLf+6Br6cbnjhjVL2fZTFG1mShpYOZwBgcz4D5J+bvwDO/7cSh7GKpHG9Pr2Af9A33FSsMrRgXTY2TpAnMyHX/ycPQUVx9VH9Yjmx6BjRFURSl41CxoiiK0+Hl7oYxvYOxcl+W1ANRmgctIYt3pmPm4EirK9U+iRkx2JKYK0HmfC8+o1DS+NaXvrisolJc8rjN4uxKCYQvdSBMmDKY6Yyn9w9DhL8Xgnw98cf2VEkznFtcIdnDjhgQjo9XGamKWcTRTBfcEahQURRF6RyoWFEUxSmZOzxKxEpCdlGz6oAowMM/bpP6IQnZxbjiyH5ySs6f3BvrDmRb3esYRzI8OlCC2YvLK5FdVI6knGKrS9fq/dlStX17Ui7KKuumGQ7398RJI3ti7oieErTOgHjbrG0s6mhb2JEB8rS0sFI866WENaECvKIoiqKoWFEUxSk5ZXQ0HvxhG4rLq2SQPSHOiGPpitDSMbRnYK3aJy2FLloUKuTPHWlWscICiyN6Bcp7TFxANy4WQ8wpKpfaJ8c8uwhZReUOt+lP64yLi1hifD3c8H+nDMOsIT0krfRjP2/HztR8TOgTigun9hF3L2N/ta0m4f5eImaYylhRFEVRmoqKFUVRnBJWP48M8EJafqnEOXQ1scIYD3dXF/x9KBuP/rQd95w4DOP7hLSK8DEJ9vVAUWmFWFFoZdl4KBd70wvEckIO2FR/N6FeYpHFM8b3EksIH3QnO+eNldZCjv0jAuSZ6YtXxRvV5unylVNchgdOHm69fmH+nsgsKBPLy8jq4pCKoiiK0hxUrCiK4rRM7hcqBQYX7kjHhoPZiA7xqZMqt7NBNytm1fp9eyre/iterBOELlgUKwcziyS9LmuHNJWUvGK8sSwRUWEFEghP963yyiopgDjsgV/rrWdz9OBIBPq446/dGegZ5IN/Hz8ET/yyXY5vdTxdxrIxd3gPKf5It6/UPKM2C0VIYk4xHv9lhzVehamJTxoVXWsftOasKMjE8SOjMEszbymKoigtQMWKoihOCwe/P21KRm5JOW7+fCMm9AnB0508M9h/F+7Bkl3pGBMbYhUqhMUJc4vLpYAil9574lC4u7qid5hRsNE2bicppwgfrTyE8spK/H0oR9zkjE3VrsxuQgsOq73PHtpDRMrX6xMlbfEr/xgnwfLnvrFCqsb3CfPFu5dMwhPzt4u7mL+Xu1SKX7o7Q1INswI9YfawbzfUpCXmdnhstjVMyMBIf4lb2WVXV0VRFEVRmoqKFUVRnJYxscHoF+GHPWmFUsBwR0pNdfT2JqeoTNyjbIPImwvFyYLtafJ6zX7DfYqB6bSEJOUW4+lfd4jbG923bvx0g7z/8RWTRTS8umgvvlqfgMLSCqRUWzhs8XJjTIk7ThrVE30j/MX1KreoXOqeMBPXGxdNkPW4HVaWZy0bfhfGobAgo5e7KyqqLGLReXTeSLGc0AXM9vuy4jvrtVCYzBkWJRaZY4f1QLCv42B5Fnm0d01TFEVRlOagYkVRFKelR6A3XjpvHI5/YSnySipQWlHZIZnBONi+6+vNOHVMNC6fYQSst4SUvJI6y0bHBuFAViGW78mEBRYREiePjhZRUVBSgRs/2YC9GQV14ktYh2Zsn2DEhfmJZcXVUgV3D3eM6BWEcyf1lnXeWLJXgvZHxwbXipVhqmJaqUzuOmForW1ToMSGGhYdW3jeA7w9rNm9Xr1gfIPfl5YVwiB+XjumpFYURVGU5qBiRVEUp4ZZsmYOjsCinenIyC+VmX1zwNxacCD92ZpDmNovzGoNsMV0f/puQ1KDYoXWCE83VxnIm9t9d9l+cfua3DcM187qjzPG9cKnaw7Je8VlVfh9Wyq2J+dbg9fJHV9usr7+c6dhiaGBgxaWQB8PsfDQFeutiybi3DdWimvXmCg/bEgpruVytWpfltVCZUIry7QBYa0SzN8Yfl7ueOpMo9ikChVFURSlJahYURTF6bl21gARK0ytuzUpT9yWWgrFjoebS63B8wcrDogQ+fbvRHz9r+l1PsP1bV257F3BaO35YVMy3l66D14ebnjpvLEyUGdBy49WHUBJeZVYRpg9a1tynsSm2FtbuEVul+5YDGBnYUV+htaJsybE4p1l8VL53YRig/u4fEZf7EnNx1nDA5EHX4lFIT9uShKXMjIypiYT1xnjY9DeYlNRFEVRWoqKFUVRnJ6JcaHWNLhPz9+JWUMicOb4WEQFNS8z2HcbEvHRqoO4cEofcbUy4bYJs2AVl1VKHEdJeaVUWaeVxGJTEzG9oFTc02yzez37+y78tjUFJRVVKC2vxAkvLEVmYZlDy4sJrSF05brqqP74+2AOUnKLxc3qyTNGYVh0IFbty8QjP22XFMAMsqdQiQ72RlJOifWckFPH9EJVVRXS0tIwLDIQrq6uspx1T952i8eQqACxxCiKoihKZ0TFiqIonYJX/zEOZ7++EusOZiOzkO5glbjz+CHN2gZdtChGvvk7EcePiIK7mzGwP21sDH7cmCyWiB0peRjbO0SC3hmnQiFjWjQePGW4WEtohXFzc4Gbiws2HMxBfGahw/3xfXc3F7GA8DUD5+kGNqhHIFbFZ4oVhlaj1LwSXP7+WrHgDKiO8xgcFSDV5XkcC3cYrmBDogJx6fS+2JNegKMbSQVMIffmRRPg56ndvKIoitJ50buYoiidgkl9w3DJtDiJH2GBw2E968aWNAQtIEzd+/Hqg0jPL8XKfVk4YmC49f3h0YFI25mOLUmGWGF8DONI6IrFgobMRnbRO6tEJDkixNdDLCIVlRZx7aKooHXFFBom87em4tIj+uHooTVig5YaZv06lFUsFhfCDFs8JqYQZupgwgxek/uFyaMpsGq8oiiKonRmVKwoitJpoCXli7WHUFhWiUd/3o7BUYFigbDHUcaw//y+S+JdTJeu3Wn5mNIvFD9uSsYxw3qIMPh5Swo+XX0QP29KxpakXCl0SOIzaiwn3Kyvhxt8Pd0xKiYQp42LwfT+4QjxM1zJ8kvKJQMX37/ti42ybFr/MCzfmwk/Lzf8Y3IfqyCxhUkDhkXXdtc6cWS0xHzQfSwxuxgT+xquX4qiKIrSXeiyYmX//v14+OGH8eeffyIlJQXR0dG44IILcM8998DT03FNAEVRnBfWJflzRxpiQnxFPLCa+gkvLMEZ42IkNe/CnWk4alCEBJi/81c87j95GIZH1wSW00JC97GxsSGS6pcZuB78YRt+3pwswoeVGBmPYg9ds2j5OHtCLL7fmCRxJkcNjsAl0/oizM+zTrC9baayfelGZq5zJsbivEm9ZTuMh2kqtPyY1p+OSNmsKIqiKB1NlxUrO3bskKDT119/HQMGDMCWLVtwxRVXoLCwEM8880xHH56iKM3kUFaRFCGkVWJozwAJgN+ZWoDP1yXgi3UJCPB2lwrqkYFe4ub18p97cOrYXlJEcXdqAZbuSUdhaaW4VRFm5XJU6Z3xJUwR7O3hKhnDaCUhzMrF+iRk1uBIa3ri+mA9E6YZZlKA6GAfeFd/tqWoUFEURVG6I11WrBx33HHyMOnXrx927tyJV199VcWKonRCKERMaF05c0IMHvphmxROpEWERSO/Wp9oXWdfRqG4dTUExQcFxRUz+koxRdYjScsrxbUfr6+zLtMO9wnzFfFiW7ekPmiR6R/hj8l9vQ5bqCiKoihKd6XLihVH5ObmIjS0YZ/v0tJSeZjk5Rmzr7TS8NERcL90Aemo/SvOR3dsE7ScsMI7iQjwxJiYILGAMA4kLsxXxAljTJjgq7LKSA3M5QeyiuDh6gJPdzeM7xOMJ88YiTeWxGN1fBYKyiowvncILp0eZ91PZIDhJmruy4RFGO8/abTEvNDY0pRzf88JRraytr5O3bE9KA2jbULRNqE4ez/R1P12G7GyZ88evPTSS41aVR5//HE8+OCDdZanp6ejpMSob9ARF5NCiw3KrKGgdG+6Y5uoLCpGRbkR8H7K4ACU5mejh58rEnJKkV9egQg/d3n0DvHCwWxjwuGMkaH4YkMFeod448RhYRgS6YuCnCycPyoISZm52JJcgr5BLlKjxJZATyCzsAJDe/hicKQvlu7Lxdz+ftIPOCPdsT0oDaNtQtE2oTh7P5Gfn981xcqdd96JJ598ssF1tm/fjiFDauovJCYmikvYWWedJXErDXHXXXfhlltuqWVZiY2NRUREBAIDAzusMdFfncegAxGl27YJ7xK4eyRIrZTRA2Lk+4+Oy0fK1tquXkkFlXD3MLq2ob174MXhvcWyEhvqWyueJD57r6x35PDeiAzzq7WNuMh05Cbk4IQxvSXd8ZWz4dR0y/agNIi2CUXbhOLs/YS3t3fXFCu33norLrnkkgbXYXyKSVJSEmbNmoVp06bhjTfeaHT7Xl5e8rCHF7EjBwFsTB19DIpz0d3aRLCfF1zgIlXmyyoBH09XDI0KxG9bU+v9zMGsYkzpX1NLxSS9oETqmNBtrG+4f53gdcbEbErIRXJeaac5v92tPSiNo21C0TahOHM/0dR9djqxQvXHR1OgRYVCZfz48Xj33Xf1Jq4onRjbIPWsojL08vTBkAYKQzKuJCm32OF7Xu6u0kEzpbCjLFuRAV5SeZ4ZxxRFURRF6Tg6nVhpKhQqM2fORJ8+fSROxdbXPCoqqkOPTVGUlnHpEXE4mFmMnoGG6bhXsA9OHNUT/cL9UFBagXeX7Zfl/SP8EJ9ZhDg79y4T1mJ56+IJ9e5nxsBw/LUnAwMj6xdDiqIoiqK0PV1WrPz+++8SVM9HTExMrfcYSKQoSufjtLG1f8u0ilx9VH95vXxvhnX5hLhQPHDycPh7t6yLo5h57pwxh3m0iqIoiqIcLl3WuZlxLRQljh6KonQ9bK0g4f6eCPHzhAfzGCuKoiiK0mnRO7miKF0CVpTvG264fTVWXV5RFEVRlM5Bl3UDUxSl+3HPiUOlAn1ceE2aYkVRFEVROi8qVhRF6TL0CPSWh6IoiqIoXQN1A1MURVEURVEUxSlRsaIoiqIoiqIoilOiYkVRFEVRFEVRFKdExYqiKIqiKIqiKE6JihVFURRFURRFUZwSFSuKoiiKoiiKojglKlYURVEURVEURXFKtM5KI1gsFnnOy8tDR1FVVYX8/Hx4e3vD1VX1paJtQtE+QtH7hqJjCaVzjy/NsbU51q4PFSuNwItIYmNjW+vaKIqiKIqiKIoCY6wdFBRU77lwsTQmZ7o5VJ1JSUkICAiAi4tLhxwDlSfF0qFDhxAYGNghx6A4F9omFG0PivYRit43lM48lqAEoVCJjo5u0LKjlpVG4MmLiYmBM8CGpGJF0TahaB+h6H1D0bGE0hXGlw1ZVEw0AEJRFEVRFEVRFKdExYqiKIqiKIqiKE6JipVOgJeXFx544AF5VhRtE4r2EYreNxQdSyjdZXypAfaKoiiKoiiKojglallRFEVRFEVRFMUpUbGiKIqiKIqiKIpTomJFURRFURRFURSnRMWKoiiKoiiKoihOiYoVRVEURVEURVGcEq1g3whVVVVISkpCQEAAXFxc2ueqKIqiKIqiKEoXxmKxID8/H9HR0XB1rd9+omKlEShUYmNjW/v6KIqiKIqiKEq359ChQ4iJian3PKhYaQRaVMwTGRgY2GHWnfT0dERERDSoPJXug7YJRduDon2EovcNpTOPJfLy8sQgYI6160PFSiOYrl8UKh0pVkpKSmT/KlYUbROK9hGK3jcUHUsoXWV82ViYhU7TK4qiKIqiKIrilKhYURRFURRFURTFKVGxoiiKoiiKoiiKU6IxK4qiKIqiKIpTU1lZifLy8o4+jC4Xs1JeXi5xK20Rs+Lh4QE3N7fD3o6KFUVRFEVRFMVpa3GkpKQgJyenow+lS57bqqoqqXXSVrUEg4ODERUVdVjbV7GiKErDVFUBaVuB8EGAu5eeLUVRFKXdMIVKZGQkfH19tUB3K4uViooKuLu7t/p55baLioqQlpYmf/fs2bPF21KxoihKw2z5EljxMtD3SGDOw47XqSgDvr3GEDQz/61nVFEURWkV1y9TqISFhekZ7URihfj4+MgzBQuvYUtdwjTAXlGUhtn0ufEcv6T+dQ6tBDL3ADt/1rOpKIqitApmjAotKkrnxLx2hxNvpGJFUZSGaYrrV6VNJ2Sx6BlVFEVRWo22iqdQOse1U7GiKErD+PcwnnsMb1zQ+Ibq2VQURVEUpdVQsaIoSsN4GD6nGHRc/etUlBjPIXGcRtEzqiiKoihK9xMrS5Yswcknn4zo6GgxK3377bcNrr9o0SJZz/7BzBKKojSRiCFAn2lAUK/61ykrMp491K9YURRFUZRuKlYKCwsxevRovPzyy8363M6dO5GcnGx9MCOBoihNZNyFwKQrgIpSoCjL8ToB1SkJ9/8FFKTrqVUURVEUpfuJleOPPx6PPPIITjvttGZ9juKEBWnMR1tU6VSUVoGB6hm7jdomzsTip4D5dwGpWx2/HzuxRrAU2ogVDbZXFEVRlBaRmZkpY9j9+/c75Rk899xz8eyzz7b5frpFnZUxY8agtLQUI0aMwP/93/9h+vTp9a7L9fgwycvLk2dW+OSjI+B+zSqjStfGZdGTwJ7fYZl+EzDsVOdoE1UVcPEx8ttbCjPqFVIu7t7GOmWFQEk+XL66VOquWI6tpzaL0nqXSPsIRduE0gX7CfOYzUd3gxP0p5xyCvr06dOk7z9r1izxQHr++eebvA9utyWfI/fccw+OOuooXHbZZQgKCqp3+2a7s297TW2LXVqssFrma6+9hgkTJogAeeuttzBz5kysWrUK48aNc/iZxx9/HA8++GCd5enp6SgpqQ4ibmd4MXNzc+Viq1WoaxO2w6hTUrXqbWSHT+34NmGxIPTrs+ACo0MpSo1HcbhRjbYWlWUIqqiCe0U58tJTgIw0BOYkAjmJyBqyGxYvx52Y0jpoH6Fom1C6Yj/B2hw8bhYu5KM7werv77zzDn766acmf3dTGDRnfRbebO7nTIYMGYJ+/frhf//7H6655hqH63CbvIa0Enl4eNR6Lz8/v0n76dJiZfDgwfIwmTZtGvbu3YvnnnsOH3zwgcPP3HXXXbjllltqWVZiY2MRERGBwMBAdAS8yEwMwGPoLB2M0jJc3Kt/yJ6eDcZWtUub2LMAcPOAizsrzhpVZwPcyhHg4Lhc/ngAyD8AuHsgxN8L6DcLLhteBsoKEVGRDMQObJtjVATtIxR7tE0oXaFNcJKYA1pWWOdDoIWhvDqpS3vDJDLNyHg5depUnHfeebjhhhvkb77+7LPPRIh4e3vj0KFDGDBgADZv3oxBgwbV+uxvv/0GLy+vOt5AX375JR566CHs2bMHvr4+GDtyOL794Wdcd/31koiKj5deeknW3bdvH3bs2IFHH30UW7ZskQryPCZaUPr37y/rXH755Q4/17t3bzz55JN48803JTEVj+/ee+/FmWeeWet4mPjqiy++wPXXX+/wHPC6sb2FhYXJd7bF/u9uKVYcMWnSJPz111/1vs+GwYc9PNEd+eNmB9PRx6C0I31nwKWRa92mbSIvGVj4SN19FmXyx1B3/fLimnUqS0W0YNBcYMvXcEneAPSf2fR9M0B/x4/AiDMA746ZIOiMaB+haJtQulo/weO0zeYqUKg83kB2yrbk7iTA06/JqwcHB6OgoECOncKEAsTPz08sXD4+PnjjjTdw7LHH1ppYN+FYdfz48bWKKjJJ1Pnnn4+nnnoKp82bh/xDW7F0xWopH/DCCy9g165dGDF0EB6682bALxwRPaKwfv16mYQfNWqUHMv999+P008/HRs2bJBt/+c//xHhw1AJiiBCQfvEE0/gww8/FA+lgQMHipi58MILZSKVrl8mkydPxmOPPYaysjKH42fz2jlqd01th91OrPDi0D1MUZwSrwCgNB8YNq91trf1W2DT58DxTwLBsU3/XFFGPcszHS+3neUqr3aX7DlGxAooVprDyleAvX8aj3McW0AVRVEUxdmhWDFdnf773//iggsuwPfff4/s7GyEhoaK1aI+T58DBw5IqQ5bKFboVkWxwTgWhHpg5NABgLc74BMETw93+LpbEBXsBfh6AW5uOOOMM2ptg65lFCPbtm3D8OHDJdbE09MTvr6+koSKMHSCAuSPP/4QSwyhuxcF1Ouvv15LrPAYKVRofZFjagM6lVihIqT6M4mPjxfxwQtOcxVduBITE8V3jtDM1bdvX7kYNCUyZuXPP/8UZasoTgkLL5bktF4l+L+eM57ppnXmO03/XImRWKIOfuGOlzOo3la4bP4SyNxr/J0VDxRnAz4hTdt36hbjOeegsd1mzGIpiqIoXRy6YtHC0VH7boFYYemNt99+GytXrsTixYtFrNCdi65RtKw4ori4uI6b1OjRozF79myMHDkSc+ccizkzJuHME2YihHGhrN9cxZiT6kB8ue+GYvfevWJNYbx2RkaGNaj94MGDMj52BMfadFWzPzaKkrFjx9ZaRgsR4fptRacSK2vXrpWMBSZmbMnFF1+M9957TxQnT77tSb311ltFwFAx0gRGlWi7DUVxKqZeC5QVAKUFgHcrBqWbwqGp2FtQWJmenWBw79rLKUr2LwWYJYzMugfoPQWYf2ftNMep24C4+rPw1dlXQVpN3MywU5p37IqiKErXhW5RnWQSi2IlKSkJ77//vsRNMz6F8c8UK6wZyFgWWzcvW8LDw2U9Wxhz8vvvv2P58uX47afv8NLr7+CeR57Cqt++Qd+xPQE3T8DDD3D1AKrKgdJciSmhxYNWHFpBqkqLMGLsBJTZZL51ZBwgDO7v1au2y529q1dWllF/jdaatqJTiRVm8moodRsFiy133HGHPBSl05CfAnxyrtHhXPZb44F8aduA3b8Ck640XMhMKsoAd0/AxRWwVKcGpKCozzJiT3F18UcPHyMehZ2efxSw+3dgPS2XFiCwF3BotbEe9+PuBaRsNERWQaqxfPwlQM/RQMSQpp+DvkfWbHf3bypWFEVRlE4Jxcr27dslnuSVV16RZXS7WrhwoSy/6KKL6v0sLRiMGbGH4oZB99PHDMb9N1yMPuNm45sffsYto6eLO1elizvgHQwUpSMzNVEKo1OozJgxQz7/10+fGhuqqMlwK5+rrLT+PWzYMBElNADYunw5goH7MTExIq7aik4lVhSlS8NYD0t1Z1FZZogEz4ZNzi4/32asV5ILHGsExiFtB/D9dcCY84FR5wAbPzGWZ+5xLFZYlZ5xJUkbjGeKGv8eQGEaUJxrHIujuJP0nbX/5iTNn9VB+a7uhuDa9h2QsQuYcg3gaWeVqY+hJwORw4AlTwMBhv+soiiKonRGscLwA4Yk0H2L0LLCoPV//etf4vVTH3PnzpXwhuzsbISEGG7UdOVasGAB5syZg0hfF6xasRTpmVkYOqifiI+4uDhZZ39CIvwthQiNjBZXMwbyM16b4uPO+58wdlBVI05oeZHP7d8Pf39/Ca+47bbbcPPNN4vb2BFHHCFJAZYtWybHT48mk6VLl8rxtCUqVhTFWUhcB/x6d83fpXmNihX0nmoEoh9YUbOMg/zKcmDd+8BVi4EhJwK+YTXbStlixLIkbwTykoBym3iT+qA/LLcTPQZY8V9j2dBTgO0/GK9pvaEViP68OQeqrTEVwL6FxmPNW8D4fwJH3gb426Q+5np82MfohPUHTnut8eNSFEVRFCfFzAZ24403WpfRssI46muvvbbBzzIuhTUBP//8c1x11VWyjEKBWbkYk83SGn1ieuLZB/+N42cfKTEqt119IS6+ZgOGjZ0iMS/x2zfi008/FXczZvti1rEXn3wQM48/rTq+xYDC5JJLLhGLinwuPh4PP/ywuHax/iBTGfO78HjuvrtmnMLv8e2332L+/PloS1ws3bEkaDNgY2DDoqLsyDoraWlpki6us6QbVFoAC0IufrLm79PfACLqpjOs1SaCvOH6wWmGWDj3YyCoF/DeSUZGMUKxYsI4mEWPAytfrbHgmIT0NYQIM3jRmpF9QGqsYNNnQHAf4LxPAFej1go+uwDIOQSc8Ixhcfn7QyDuCCBuhrF9r0AgP9lwIZtwqSFUzKB5dx9g3IWAixtwsFpgDTsVmFFd24jdEcUOt8GA/Gbks+/OaB+haJtQumI/wcEwB860TDS1JkdXgjEjt99+u7ha1blmvA9zstEvotrtK9Nw4ea9k94RjuA9lp4YBSkS22IJipHsYqyFUl/sTEO8+uqr+OabbxpMXNXQNWzqGFstK4riLNCSYgs7lMbgoD56rGGVYaD76HNr3mO6YtYsiV8KLH4CyNjN21WNVYTxJAxmp6XDNt6FUNBQsLh7G36tplAhYQONTjJzNxA1CgiMNjpHD28bi5CfEacy4Z9G3ElFsRHwl74DWP2GsR7dxNih7lsETGMxKRdjvc+rzcuM2WEcjKIoiqK0JXR3lkQxLkBgB5a3KCuq9lIwMmydeOKJ2L17tySKYoHyWpiTjm5exj3adOuiG3Z9UMwUptd858OEFenNQpJtiYoVRXEWSponVtyy9wLFe4AewwyxwsD3gJ6GVYWWluUvA3t+BSpsMn7QTeus94yCjXS/ooWDgfj2My9bv6n5HI9j0xfAqLOMvylC6Hq2+QvgtNeBcz4yliesqb0dMz4mbIDhbsYkALwJrH4T2PmL0VHmHjL2881VQG6Csa58OU/gi38awufMdwH/tssyoiiKonRz6GPE+w3viR12DBbjGJj+n9aS6knEm266yfH6VnFSfcyWarcuBtgTuoNzHTPZDhEX7UpjjMD3md7Yw26yshlcfvnlaA9UrCiKs1Ca2yyx4r1/AVwOLgBGnmlk3GIMyg83GAHzrE+Ssql6TRfDckG3K3ZOFCzpuwAG5zOj17xXartbsaO0FTi22cHMAHgGzuclGm5fYy4Afqp24yIUTKe8VOMPy2OLX2J8hkUe2SFTmLCzpHsYA/mZZYzuZma6Y1auZ6dN4cVUzlCxoiiKorQRZtZMWit4j+oIF2TukxN1rLWWlwyEeNWeTLRYjMycFFQUKIxF5d9mJlGz3pkpXrL3G9+H93x+lvd1+xhV3mcPQ6y0F53DaVFRugOmOAkfaAgCxpE0gFtudU2h8EFAzCSjs2LnxM5HOigfw81rytXAnIeNzGDkt3trxAXdtOw7ZYod++JXtq8ZqH/Sf4CgGMMNzaxez06W0GJCS4hpSud3oasZ0xnTGpOy2ZjlGXkWMO81wz2Mx8w0zOa+OaPk6W+8NrevKIqiKG2BTRpf2yxZ7Q5dqhnbSZdte2FRWQZk7TMesm6wYYHh/ZQCx4RuYBQmnJxkGQMzlsXcHteXeiy+NfdZJ0ctK4ribG5go88DBhgpDuvFYoFbHsWKBdjwMbDtW2M5a5xMvNyIT2EFeNPSQUacAWz63OjwaLFgeuAew+svCMkMXeNvAfYuBEacXnsdBuGf86EhdN48urb/q22nTxh3QhcwpjXe+GlN59hrnFFThUkEvr8BSN1suIUxsJ9ixTTHm7NFiqIoitKWlhV5Xdm6w2MmtzELJ/uF1Y0RNWFlec4dcqKR8ZsUG7Xer6x+4WJsk8fJe759jAon/5jkxvY78TNmDCjv24w9pQVGLC41WcGcFbWsKEpHw07sk/ONgfrAOXWrxDsi5yBcOVOSFW8IFc6UsHr8TVuA2fcb1hYTWj9M8UHRQIvIpCuAk56rWwVYsnEdrFl/4LHAcY85rhZsWmTsZ6EoLla9YdSNMek/25gxokhiJ8rjZWIAU7QwaxndySi+aB2yrTHjSKwwccCGT4AtXzd+rhRFURSlQSxtZ1mhmKAAqSwxYkTqoyTbqEtmul3zflmQVpPd0wyoZ2xKXoJxL6XlxHT74nHTokIXbQoVei3wwQB8JsDhPZsPWd6BsTktQMWKonQ0zOLFzoVuUUffA4T2N6ws5kyMPfFL4PLhPHhk74YLZ1DYEZ3xFnDUHUasB7Et/siZFxMGyZ/7ETCWwgDA4qeAT/9RIyyYqWvps8Zr+sM2BVsXMQolsvnzGrcwwpSL/WfVzAAxKYDt7BI7zhOfNeJW2CEzwD8/tX6xUpQBrHrNsNQoiqIoyuFgW8XDPrX/4UKhYFo1GhJCZpwns3DK3wyAzzLco+nmbbpEe/gZ2orbSt8OpG037uH0bhBrigsQEG2MA9zcjftvreMxMo11JtQNTFHaAwbLUTQ4KvKYus14NoPamVXrlzuMzFhnvl3z3o6fgL8/kExctGlI19pjOFzO/sAoomiLrdCwFSu2sPM8tNpIY8h99p1hWF76zTKEAMVTUzjhaWDhY8DUaw0XLsLAffsOcur1wPTqwlicDbJn58+G2KKI4UzS7l+NDtdWrNCiwhmlA8ur/64WNIqiKIrSKm5gtu5TrYRVgDQkVqrfEzcwG8+EChZPLjIEFQUJPQ9ssa7rYtzv6fpNgeRowpPu1RQ7nQwVK4rS1tCt6rMLgZ6jgOOeBA6tMgoocsaDMLCcmPEjpsWB5mIKlH2LDUuFjfnY4t8DFV4hcDvjXbjYCxViWxG+PrcymoMHHANs/ARY+zbQZ7ohMCIGGQH0TSVqBHDex8brzV/Wv09b8WKfLtnsqNmRstI9O+M1bwL5ScCmTw3hxM/P/zeQubfpx6YoiqIoTbWs+ITVP8F3OMlzTCHSULYxq2XFB/BgbGmescxSn3iiS5c7EBxrjA8oWjh+MGueOXL1opDx6hxB9baoWFGUtoY1SUjyJuDn2410vQyCZyX34hwjja9Zv0R+lT6GmxOzZu1dULMdWivGnC8Pi5sXCrYvQpAjoWJrWWEnxuxi9cHt7fjRiH3ZNR8YcsLhfdcVLxvPjmJcGoMZwwgtPae9ZliWfr3LOH/c7vTrjXNgL1YYlNhJqjEriqIozki1WDHrkbQm4tJsCg5LtfhwNQSMmXqYwsRMUmMWeLQv2uhSnbKYGcBofaHHBjNvUlyxmCTFiq1FxrTmyDY9jH21QiHIjkDFiqK0NvaDZ1uXJwoVQosJxYpZC4WWCM60cFC+/L+GRYEwHoUDfwanX7fGJpCuCqVxs+vvWE2xUtRAMB+h2xWzjzFWhY/9fwGRQ41jawnmDFBDFXTrw8xaRv9bdtRMuUzr00+3An88YLiJOZopYufsyL1OURRFUZoCLRKSzreV4znknmhnGeH9rSCxblp+iUOpMFITm1YWigz/yJqge+9gY0zAR7h/jYXGjFNlOmMTfhdm/ZIUxsWGO7kZO9PJ0OlIRWlNdv0GvDkL2L+sZhmzfNUnJpY8U+OD+sIY4Ne7DaHCwT6tCBQOFDLsSO1TAjcEP/uPL4CLqlMaN4SZlYtm5APLgMS1aDGm4Bg0twWf7VHzmsdBJlwGDD7RMJ0zrsZR0H9zzouiKIqi2MPBPy0RvA/Wl9zGFrpycV3GVNoG5zuavBRcAL9I48FJRttsmRKLQkFRYlg/KFRoRXHzQmZeISL7Dcf+g4mAm7dRNsD0XLB1JWO8KGubefhg5syZNVXvOcFHtzBOeNp+tgHOPfdcPPtsdaIdJ0HFiqK0JgsfNZ5/r86KRZh6kIT2s1mWalSRz9xjxKzs+d1w/WImsJNfMAQETb2mheLYB2s6Gabr3fgJXAtSGvhluxmzMWbAe0PwuGwtNAxqbyl03zrtdSBqZPM/a6ZYFlyMIPpPzjVSLTPjGDvxxHV1/Xftgw0VRVEUpblQJNAdqymFiCWtcGrjSV7MzGK8xzKWlA9ZVlVd46SsWqTQksJYFlcjKyaFhasrHn3uNZx68smI692rxmWsjbn33nvx6KOPIje3ulC1E6BuYIrSWtjOrpgmXDLvVaPQIsUG3b7obsXUxK9OB6rKjBmUnqONIHLWP6HA2P6DMbtjboedl8m2b+GSfQBuU+5unePmrMuwU4Ct39a1cDQXmqBtzdDNgbNE4y4CUrcCvacYmcqYrpGCLSQOyNhpWKl4MwnpWyOOKOoURVEUpaVI6t/yptdZMQUN70+OguVNzMk1s8gxoTiprKgtPqSqvBcQ0sdw36qqRFFxCd7++Gv8+stP1duqrLG6NLTPw2TEiBHo378/PvzwQ1x77bVwBtSyoiiHQ+J64MtLjWB4dh5nv1/T8ax7D1jwkNEhMQiOnRo7qZxDhiWFQoX+pIxFuXIhMPVfNZaQ/kcDQ06q2Y+ZnYQmZQbVsWC8f1TrXbsjbgZ6ja/tytURTLzMyETG82BakpiAgL7EvSYArp5GZhUG4dMljG5yjjKLKYqiKF0bWtXre9inx29w3VLDQlKUXr1uoeP1bDFT6vvYZN50wJQjjsSLb35gxLGWl+Dc00+Gi08wSooK5P1DSWnwjJuMXRmVQMTgmpgZVzf8vHg1vLy8MGXq9BqPh8w9KC0pxg033IDIyEh4e3vjiCOOwJo1a2rtt6KiAtdddx2CgoIQHh6O++67DxabCdUvv/wSI0eOhK+vL6KionDssceisLCmTMDJJ5+MTz91njpmallRlMOBLlzMTrXtO8P1Kai30dmwY1v7bk2WL8aQfPcvozo74eCbouCof9etkUJYs4SzO6zuzsH5ho8MKwMtL4xxcXFDlY9N4cfWgNVwCc3PzoC9b230OMP69PNtxo3lmAc76sgURVGUjuad4+p/j9b545+s+ft/8+qPb6RnAyfsTH64qcbKYstVi41n3oPFKuJitYKIWxhdme0yUwYHBSE/v1AE0aENi/DbwiXw8/VBTl4+ogJC8frH3+DYmUdg0MhxdXa3dOlSjB8/3pgItQb+u+COf9+Jr776Cu+//z769OmDp556CnPnzsWePXsQGmqIJ7532WWXYfXq1Vi7di2uvPJK9O7dG1dccQWSk5Nx3nnnyefmzZuH7OxsrFixopaYmTRpkriClZaWimDqaFSsKMrhwMwchG5dhB0VXZTM2il0/6JIMTs+WgNY24SWGAoW2zgWR3EnA2Ybr98/2diHGQzPQDpHmbFailhskjrestKQWAnta6R83vmLkdJ5/p2GhWXIiYbpXFEURVFaRANB8vaUVVtZGJDP+zCzd8kkoquRYdO6SQuCAwOQX5AvbmP/fe9TXHD6ifj+t8XILixDqGcw3vzgS3zw6tMOd3PgwAFER1dbVKpd0wqLS/Hqa6/hvffew/HHHy/L3nzzTfz+++94++23cfvtt8uy2NhYPPfcc3BxccHgwYOxefNm+dsUK7S8nH766SJgYmJiMHbsWFnXhPstKytDSkqKCKKORsWKohwO5sCeVolFTxod18BjgfTthhXFLOTITow1TeY+Bvz9IZC+01he3yCb4qGswNgeB+20zFCsMI6DBB5GELwjKKpMfFvZYtNSGFRvwiD72EnGDNPpbxgzapm7gQX/B/j3ULGiKIrS3bh0fv3v2caIkIYyY/L+bNY7Iyc+AwT0qr94YkV1vIqZMp8V4SlWxHITaLiVFWVJfGWwjxvy8/NRWFKOtz/9Hit//gSLV65Hdm4+vvzhV4SFheHYE+Y5LBRZXFwsbl4CxwMs27YvHuXl5Zg+fbqxnLv38BBLyPbt263LpkyZUkt8TJ06VTJ8VVZWYvTo0Zg9e7a4gdEiw9dnn3221SpDfHwMS05RUROSDbQDGrOiKC2FgmLPHzVV6vmagfG0rDC2gkKFnSDdw65cDJz6shF7YpvNylEqXrLiJcOa8s3VhrAxxQnT93LC5nAydjmCMTWMFWHAurMUWLS1rDBJQc8xNfnkL/zGeJ83hYWPaEYwRVGU7gZdo+p72McyNriuV819mZNk3iHG/cV+PRMGxxN6RxCzdokpUtJ3AMzWWV6E4KBA5Jda8P4vqzFt6hQM6NcHgYGByK7yw8uvvoYbbroZLr4hDgPmGWtCFy2B7uCthJubm1hifvnlFwwdOhQvv/wyhgwZgvj4eOs6WVlGXZeICOdIYOMkoxJF6YTQGsFChSbmzMpHZwIJqwz/VQ6qr/4L6DmqZr3B1VXiGY9SX0YPT/8aEbTmrRqxYnaoQb1a//swwJ4B684Cg+zpJseYH8mAYnOugmOBkWcbs2c0wf/y7448UkVRFKUzY8ZrMGaTHg+0mnCZoxoqtPSzzIB5nxaxYwFKcoCcA8Z9WkRPMIIjeyG3oAgvvPgibrz+OuPjAf5YuGixWEIuuuiieg+JrlnbtlW7lFdbcfr37QNPT08sW1ZTy42WFgbYDxs2zLps1apVtba1cuVKDBw4UIQKodWF1pkHH3xQPsttfvPNN9b1t2zZIu5hFEzOgLqBKUpDrHzViDcZfpoxQHYUkG6mFGQAPGMoSOQw4Mx3gcghdbfJgPrzPqnfqkJYBNL6OtBwAzMFzvhLAL8egHNYZ9uWs6qTFDiC54QpjbP2AuvfB/pMA0af255HpyiKojg7Dlys6rxvrTJfPYfPrJt0vZI6X3ZV7bktM3MnUx4z3tM2eJ/u4XThLsoUN7A/Fy5C375xmD37GCB7HwID/PDaa6/hX//6l2Tjqg+6aN11111iXQkJipSMon4hgbjmmmskNoVuW4w5YaA83bUYUG9y8OBB3HLLLbjqqquwfv16vPTSS9ZCjxQyCxYswJw5c8Rysnz5cqSnp4uVxTa4n+87CypWFKUhNlan7qMr1pRrjIHx0FOMzooZqTiDQgsLX5s1URgEPueRuh2cLY3FnJgzNoSuY+b67ECZuYQuaEXVxSa7K6wPQ1E34FgjFfSPNxuuYo4EoqIoitL94CRiWZFhLWkoKQ3rdVG0mG7QnIDkg5k97e/lXMb7PicyaU0xoaWf92q6KrNEgWQDC0BBYRFuvPYa6/6DAvxQUlLSaA0TxpSMGzcOn3/+uYgOs6bYE088gaqqKlx44YUSDzNhwgT8+uuvCAkJsX6WFhvGvDCWhdaUG2+8UTKCEbqhLVmyBM8//zzy8vJE8DzzzDPWgH0e27fffov58xuICWpnVKwoSn0U23RCqVuA76o7Fs7msz4K0wkz65cpUljQadp1wGyb6vUtxTawz9vGskK/VckK0nYFoToNzMRC4lhcsxzYtwj4/CKjZo19JjFFURSl+2GKCaYWrq9gMScf7T0d3H0My4p9umPGpNA92zZ7mFcQ4OZuFIpknKpUpi+Vt8497UR5IDDGECveIXj1pefx6rufNKmw4/333y9WFGbxcq0WUgy6f/HFF+XhiEWLFllfv/rqq3XepwXFFCJMV8zMYO7uNXLg3XffFZHDIH1nQcWK0jXZ+6fRgcRUFzpsCWZNFHuSNwMfnwvkJ9UUhWLVdwbb0V2sNbC1rNANjB3pBV8Zz+zgaFnp7phihcW/Tn8LeO0Io8r9j7cYiQLasMKvoiiK4uTYxpvYJrZpquWemGKFk4QFaUbgPGGRZ1pQPAOMyUVab2iJ4X2J8asWTmK6GpYaTmiaVh2OFZrBiSeeiN27dyMxMVHSEbcHzC5GtzFnQsWK0vWgq9Qf1QUDr1zU8kGrI7HCjuuP+w0TMAWFTwhwzP8Bm780OjEG3bUGFCi2bmD8DuwYlRpYg4axQbSiUMSd+Y6RQW3Tp0b8yviL9WwpiqJ0V2oJFIsRZyqB70F116MlhFYRM7MXPSUIl9Oli9k9KUZMdy/WWLOtSWamMTatL7INd0O4yGdans/qpptuQnty+eWXw9nQbGBK16Moo7ZvaUuxFSucGWEedqYkpFAJH2QMiDlIZsD8+Z8Cl/xcu8M6HHxD6xaeVGpD32Bazpa/BLx9rDFzNfs+472fbweSN9Wsyxo1S58FfrrVcXYXRVEUpWshRRqDaty66UZtJsahCMncW13QsdzI4lUdZ2L9LFMUc4KSYwoKFQoY3vOZFplCxBEcK9AdzL5WmH3dF6VZqGVF6XrQLag1iF9szLgUZxnZPsxZmj4zgDPeNDokdoAULqS1hIopVo573MguxhgZpX7yEo0bBJMcTLsROLAC2P0r8MXFRn0bxvzQNL/jpxpTfjNN8YqiKEongx4JFAycoGLfz9hGM55R3KnLjTl7895uemHQzTo7vvr96hotrG3GhC68z/DeTzcwR5QWGu/T80IC4pn+uKrh4H6lUdSyonTdgDpmzTocAdFvlmFdoUWFnQ07not/BP75IxDY07CocGa/rYK5abkZdirg10CK4+5MQTqw5WvDPE9oYaF/MONVgmKNGbPvrzduVAeWVScmAJC5p+62eI0/OgvY9EX7fgdFURSlUZj9qkWY2TTNjF6uHnZeF1W13cUKM4H07VJ9XhLZUKAwOJ6TXiJwKmpvxx5PHyC4t5HymAKFrmJMkNONYyirWiHGVi0rSueitADY8LERr0Cx4HCdvJosWi2FA1sOarktdkoswhgzCeg7o+XbVFqX3IPAshdq/uZNJHG9cRM66z3gneOAbd8Cq9+s8RsmmbuNDGK2rHrdsLis+C8w6iy9UoqiKE4AixUyC1ZSUpLUBOHfLGjYJFgDpSzPcN+qLAXKqwA3Fm+ka1eR8TcpLgJKK4CqYqCwulK8i7tx3+dkJD2H+RlSUgpUVgHllYCLXaYwW+yziDkpFptsYE0+r83YdllZmdRw4TXktWspKlaUzsWqV4HtPxppg69a7HgdxieQomwj0M02/qMpcEaeNTuYCpec9JwhjjhDk5tozJDQrWjnL0bQ+6C5h/mllBbB1JK20ILC60bO+xSY8zAw/07g17uNQpomGbvrbitqFBC/RC+EoiiKE8FBbt8+fZB8YBeSEqvvv43BeBSmHaarFievpMJ8lRGbglQjMQ4nsMoKjfU9coGSfMNli5OTFCheXsYEliOLPuNXfCtqCkN2YiwWi1g+eJ5bW6yYsPAla7mYqZdbgooVpXORuq3xdZg+mEKDtVF2/w6MPqfp22dWr2+uMmbpORtzyks1n9/1G7DwUaDXeGDCpcDqNwwTr4qVjsFMLekIuu9NvhrYu9CIX9nxI+BfHafCoEp76DJI7HPtNwfeCNe+Y+Tzn3aDEYSpKIqiHBae275A7zVvo2LoPFROurrhldN3AX8+2vA6Yy8ECpOAPQuMhDmFTMpT7ep9wbeAR3UmMJOyasHDwXZlrBGoT8+NLiBWqqqqkJmZibCwsMMSE/XBgpStYbXpVGKFFTeffvpprFu3DsnJyfjmm28wb968Bj/D4ji33HILtm7dKjmq7733Xlxyic0sq9K54KCSlo+GYCcSPdZYj51KQzBWYf8yI086Z2G+vtKYNWHu9ElX1hY6ZqFGzthYXc3sUiAqHWdZsYVFu1j3ZuQZwP6lNRlgKFj4mu6EvJ5MxsDrTb9kQqHRUpjtZeMnhoWHYta9mRY9RVEUpS7r3oMLLPDY/g08jqwnjS8zdzFD1+oXgRIHFhFbilOAggQgaaXNvTwYiJ0DBNjd0zkmSN8JnPJizaSWn00dtC4gVjw8PKTQZFuIldaiU4mVwsJCjB49GpdeeilOP/30RtePj4+XgjpXX301PvroIyxYsEDyR/fs2RNz56rrTqek/yxg6zdG8FpDmJVqGxMrK14GDiw3zMG5h4yBa8RQYxalxzDHhRo50DUHteYgV2l/zHz4RKoG2wTxsY3YChRmdpEc+z5GdjW2C2aJ+fxCw2Xg6OqUx3QN4N+2224qnKEz0yJT0DbX/VBRFEWpCy0YZmC7I/YtBhY9bvTjnIAkHCOYr+2h18WWr4x+mkH0Y84HoscBwQ6KLjJYnmKF7ue8d+gEZYfQqcTK8ccfL4+m8tprr6Fv37549tln5e+hQ4fir7/+wnPPPadipbPiUZ15y8xjbsvGTw23H3ZqpkhhZjBmoqAJ0pEZMmWzMbNCtyEOdgcdZ7gCpW6t6xJkCpOy/Jq4mMMJ4lcODzO7Cxl7AbD+fzWixRQqhK56FJfMlc+Coed8ZAROMp4pv7oa8Z8P16zPdVsiVpL+rr0NRVEU5fBhf9xQzbSDKw3PCE5Kmeud/gaw6InasYhDTwY2f2FYwDkxRVfvuY8BkxoogthnuuFOvvs3YP9fwJG3GTGsSrvSqcRKc1mxYgWOOeaYWstoUWmoGmhpaak8TPLy8qymstZIv9YSuF8zCKrbU1HKeRAJgrPYn4+CdLiwaKMt7FzeOhqWqdcbsSy2WCxw4cxLdrxs09J7GixnvAOXry413qZYsd2Hh6+x79ICWIqzjc/QXawDrou2CaMNmPLTwlo3FCxuXnDZ+ZNVhFiO+rcIUJcP5gGJ6+BSVgDLJ+fCcvkCublZ5Wt1+mPLsHmGxaUl17Qkt+Z4KGbbsV1oe1C0TShdtp+YeQ9cfrldrBx17vu0jdDttzQfFndvuPQYIRYTi5s3XOwmjSypW+GSsQsulipYfMIkpbElcljDfXWvCXChEKou9mhhGuPOdv6cuE00db9dWqykpKSgR4/axd/4NwVIcXExfHzq+rw//vjjePDBB+ssZ+q1EjN1XQdczNzcXGlQzuxT2B4ELnkJHhXlyB90FsrSavxSXYsyEHBgDdwrqos42VG57kPkRNSkq3UtSkfgkvvhzZkYvu8dgoxZz8KSlYfQ3BS4VJUju8iCKpt9UCiFVW+/NC0eXhXlKCp3QbHtOu2EtgkDj4m3SmxKuWcfoPdAWeYSPhWhPzIuzYIs736w8Poc/QJcC5IQ+vOVcM85gPKPzkfWSW8jMLAfPLJ2Ws9rTthEVGZxgqLactYMfDIS4VvdPvLTElDm1RfthbYHRduE0lX7CReXMLjOeBQWr4Da9+RqQtL3wbWiHDnuPVE5pdqlNz0dwZkH4VbdJ7sWpsMteYO8rvLwQ/rZP8FC124XV7gc2AHX8iJUeQcby+wICB4Mz7QNKI2egoKqIKAD7vldtU3k5zfNC6FLi5WWcNddd0lAvgmFDQPzmd87MDCwwxoTMynwGDpTB9MWuLhXAe4eCA7vCURG1ryxZxNc8g/Ie45wm3ETIs31D66AyxcXwKU4CxbOhQf1gqtvOCICfQAfb/Ek4qx9eO/BRpC2rSWGBZ+qKuBemSv7CgiPRoDtcbQT2iaqiTyp7smJ3wEXd3fxL47oPcjmjT7A/7d3HmBOldkbfwMzDGXovRdp0gWpFlBRBEVBVGRRBLur/i27a1vLqruirmvXVbEXFFHRRakiYgGpIoJ0kN6R3mfyf9578k3uZDLDgAOTTN7f89xJcnOTuUlubr73O+e8Z/dfERz1NxRZNw2VZz4JlKsO7AgbNpSvVgcodZSf5+IgAqHjr0yxpMzH5zFGx4PQMSEK9nkim8mf/TsRSN/j/R5XWDwMwfOf8VYHRv4fsH8Lgq0vR+D7pxDYs8lbHyxbF4Ga7VCxWi1g6QQE2AbBReJb9jNjnUi63ObVQRZvMxDFva70BYf0fD4mWNiPRBcrVapUwYYNGzKt422KjmhRFZKSkuItkfBDzM8vNw+m/N6HmCBUqxLw3Lt878WOKIV0rD9ZNMa2Z7F8+kFg+uvAVw9avmrlZl4ExblKBfYxFSgUkixaGoFo1rjN+lhuLLvLMyWNtQ/59JnomMgG9r5hTnHpmggsmwgsGgvUbAc0v9iKI1lEuXUZArPeBupkbvIZWD0NqN7aCimPFOcqw+c5uPu4Hxc6HoSOCVEgzxNs7LtjLdDiUqDSiZnv89cnrp/juYZ5neNTSnnn5MBX/7CGkOS0vyJwlkVevJRdpna5ukWuY3+VaO9LxYZAl7tQUAnk4zGR2/9ZoMVKx44dMWrUqEzrxo8f760XcYornht9F9BniDl1EOasRtL4PBMrrD2Z+Sbw/TMAB5HefecD3Z8APvxTeHvWLbA5YN/3ws2iIun45zx/SSKPqdLMFjL7A2DVVFv4+bK2JSVkbc2CeNoalzshbJ7ww7NAx5uPUqyEwtlsQNn08G6FQgghcsHqGQDrUbetAC54AShSPHyf3/GLboyvnQW0Hghsmh9uc8BJqR5PApUah3tijX/AnED9HM5lVOQbcSStgV27dmH27Nne4qyJeX3lypUZKVwDBgzI2J6WxcuWLcOdd96JBQsW4KWXXsJHH32E228PdbkW8ceBkAvYoX0ZRdEe21Zl3ZZ2g5xlYRNANnN0QqVyc+CSty3S4uj9CpCeBvzwjFnOupOaiG/8jm6MsDDqQlIrARVDn/GONXY8+SMkc4YDI28FFn915JEVPq//x1QIIcTR4yIj/C2PbEfAlgN+KFh+ehdY+nX4N+DyTzP/pnMyMlKokHLHr85QHBlxFVmZMWMGzjjjjIzbrrbkyiuvxFtvveU1inTChdC2+Msvv/TEybPPPosaNWrgtddek21xvELXCL9lsYt+cH3kCYtw1nzr8tAgMgA0udBCyUwBG3O3pXT1H27PU6Y2MPpOs73tkEP0hD1WeLJcOMr6dzQ4O7OFrogtipUNX2eIv3hIrOzeAlRpbiKXIpapAIzSsWCJERJaWa+dDdQ+Nff/i25kOzcA5erl/esQQohEhc17HV5vFB+Vm5rTJ3trcXKSWRbeRCbrUWuYWEny1Z7O/dQi6JEwvZtOXyImiSux0qVLF8+xIDsoWKI95qeffP0PRPxyaG/0KMvuTdbIjyebAZ8DuzcCa38GvrjVhAq91C95C2jcA/j1f8B3/wFWTwc2zgeuHGmz7Ovnhmds/EX1kfCxbsaG1OsisRLL+Bsz0uXF3WauMn/UKCwoTrb9Bmzc7VlZere3LLHtSlXN/f+qe7qJ418/sx9I1sgIIYT4Y2SKfEe4R7EekQsnLNk/xZvELASccTewIHMZgAczKKLBWsbCcTUkTijiKg1MCDS5IOsMi6tX4UCThfcUIZ9eY+KjWDlg4JcmVNzj+7xmgoRFeHu3Ws7rF6HeOyecmfMJi8/vYJPJKDaHIkYjKzRMYCfkYmXstidwC1tEhREXpgUyJ5rpAYzAkbF/z/7HLRos9pw91JqICSGE+OMwG8Ix/TXg85sy15XyXL5kgq1jdPzcx4DT7wQ63QL0jIiicHLSwZ5ajrJKAYtlJCNF/MA0ntP+YiFhFs67lDDmovb4txXNzfsM+OQamzlnt9qez2WeXScVGlj61+ZFwJyPLA2IjyW1DmO+wGJsB6N88eSokogUDQkTwmOClKgEsGkjU/4Io29MF6DLDFMHV062tEAndCh6I4+hSA7us4J9VzsVmaoghBDiyFgzy87D/sjKhnl2yahJrfZWfD/lBeteT6FSvj7QqJtNJkaLbpesklm4MOWX1An3YROxh8SKiE/RQtzMCp2carQFJj8PjA81hGIO60WMoGRziHN2fd3PwJxhQMVG4fUMJ+cEBRDDzb98HHacErGLX0y6FNKLXrVCzU+uth9CZ9TAtEKmb+3ZYhEWZ3+5b9vhxcqu9VYHlV2qghBCiNzDiZ8vcjBDYuru2HssDZwUKQWUrGTREn9EPRLWmvozJa6fpE8lDtC0sIgfGFHhLHdSCpBU1AafXDizMuKGsFBpdz3Q5/XD55+6GhUKFNYbtL4inCKUHRzAMrR86TtAt8F59MLEMaVpL7us1MQuOePGH6lW/YETfU0lWZ9CW0xXhM8Zt0jXuexgpIbw2HSRlRzq64QQQvjSuJiO7bch5nnacfV4653lTwv74bmQUAkA1VoDV422zAim9RYJWdFHg722HNm1KBAxhyIrIj7Ys9VSdL57ymvmiKvHAmtmAu/2ApZ9E96OAqLDjZlPdNGga9P8kXadszBtrzmy/Slb+yhehMgX2t8ItLrc6lX8qQDtQ52KZ71rl0z9Ym0T08U+u9EEByMwtMCu3ibn/+EiKSWrmshhnQt7AsnCWAghcv4tHnqpXa/aArjg+ay28zwnn3wV0PwSYPl3wLi/m2CheQ7Tui//xKLfF75w+HeaYwP+fv++4sh/90W+IbEiYh/WAwy73DcLEgTeOt/Ei0fAahN6/xdo1D13z5lpEHkYYSPiGxbWc8mOsx8GfvnIImbOhIFNId++ANj3OzDuPqDOqeEGpDlF6ZhiwDRBihUerxIrQgiRPSunZG4N4GD2BDMZ3LmUdYXse/XNYyGhUsTqUyhWDpemG0mFRmaO4y+wFzGNxIqIfWgj64QKi+rnfmLpOTxZ1T/bCuvY7C+3QoW4juVEJ6zEpl5nW/xwhu/kgcCUl6yGheJ40KjsOxy7vGnOBvLY2rsNOMBoS8Vjv/9CCBGvZEw6RtT6sZDeOTGyHpDnZEbB926xNgUUKoyWHy7qHY0z/54HOy6OJxIrInah2weFSa0OdpsChWk5wbRQH4tLrSnjhIeB0jnMeuc0o756mtkVCxFJjXZAq+3WbIwF92/2AK4aYxbZkTj7bHr1t3jaZgVLSKgIIUS2bFpkNacOv4vi8m/D17csBpZ8ZWYnzIRgfyzXD+1oxIqIO1RgL2IL5vu/f4l1mZ30uEVVfnrPZqk3Lw4LlVLVbYC4ddnR15BwNv30v2XubiuEg/UrPZ82ccIfRgoWRljY7T5bsVLLfkgpVvgjzLoqIYQQWZn1tl3WbG+XrPNLC1nMe8Ik5OLIZrtOqDBFt8eTdh+tiqu21DubAEisiGPDN48Do+4E0kO9LLJj1ybgs5uARePs9sTBwK6NwA++Rk5Mw9myzIRKcgmgWR87SbE/ius0zpCwEHkNj0+mGvD4Klkd2LoUeLunFYX6YaFm+xssF5qw5wpTF2aGfoyFEEKEocvib9/b9Q43hNd76bOhOkAvm2Kx9cLyIip1zc2remug9ytA5zvDrQxEgUZiReQ9FCgLRwGrptpsdE7MeAPYMBeY+C+7zUaNjr7vWSdxFiyzqL7iiTZodIXOrGNx21doqE9S5D2rfrTLqq2Aq0YBpWrYMffOBcCOdeHt2JysVT8gtWJmJ5u9W/WpCCFENIdPwnYBjEY70eGK7Jk1QSdG1ql6EZQW1veKsC6QzaCPpE5VxDWqWRF5j7/bbLT8/mguSt51X1dxMuERYPdGu07r2fpdgQ2/mKf6/C/s//CERytCnuyEyEtobfntk+FePEw/GDgSePM8YNMCYMiZJqhrRMmZdu407gdZCCFEZmMbNm92lvK87ta7VgWcpCxb19ZVO8nsi4sdofOXKBBIrIi8h3mnhCLCFcFlh7/3BcVHy8uAnz80EfPLsHD/i+RiQLPetriZ7GWTrFFUw3NlESvyHr9j3I41wKQnLN2LzceG9jXB8sY59gPasDtQ6URrLEncDyqjf7Tezsk6WQghEg2eK0+9LXy73bWWlfHuhVbrx3EExw+tBwC/fm51gKpPSViUBibynkMhsZJU7PDNGRniJZ3vAlIrWd5/4/Os0J4wmkJb4irNMz+ubshqlmHiGm3z/CUI4TULZX+V2p2ADb8CC760Qk9GWK4eZzOBbFY27VVgWH9LaXQwpcEJdeZmM7Vh9gfRi/M3LgB++fjw9V1CCFFQYTTl/YvNBYyTPDx/MmOCQoUcbuJTFGgkVkTew5lk73IPsHB0ztu6/hS0eaWn+he3h+pXgpb3T1Fy1VibXfFTq6PNfHPg6CI5QuQlFNrd/gWcOxgoH0ozdO5zLPK8+E2g26NAIMmOdZpCMD3RPdbVrdAgYvprwNSXgc9vzvp/RlwPTH4eWPq1Pj8hRGLACRxO5ND9iy0JXjsLWDrBCuk5HqjY2NJvSY2TzblTJCxKAxPHLrJCWCCfEz2fA/ZsBratAl7pbDUpPFnV62InspJVM6eKOdgZ/IoR0e8TIq9h3vTy78wNzEGRvHg8ULGhOdjxOP7kGou6sBiUdSs711mRPW+zX0tOs4NMK2vQVZ+dEKLg88twYOZbdm6cP9J+7wvRebFeOCvjhLOAdXOAQGGgaKi4XiQkiqyIvMcf6fAX0EeDJ6DFXwHvXGhCha4fnMnmiYuUrJL9YyVUxPHCpSGyTopGEITpCjxOWVN1ywxLWaRQZ0oYUxpa/Qk48z6bIWQEkNCCk30DokFrbiGESAR4LuRk5qx37DxKp8WKjUyoEJ4n3TjA3yxSJCQSKyLvYQ1JhxtzJ1Y4qPvuP5b2VSTVHlfntPD9jKwIEQvHdPkTLN1r7ie2jvbchDVWrG/p85pFYNggcvhAoEY7oMHZVovFJqacKdy/M9zsjPjrVPxOeEIIUVA5dMBq+Jzb50lXWLF9oYhkH3atJxvmASumHP/9FDGDxIrIe7x8/Qp23WvmlA2MqDzfGti13sK/HOjVPjWz3XHJyvqERGwc0/xBJSyGZ1H8up9tfYNzbD0Fy2VDrXHp8knAG93M/pgwzcFFVLavDj9voULAKf8HVG5mx78QQhRkaJ7zZndg03xL+e7wZ+DCF8J2737850p/DzaRcEisiGODyy/NLrLCDt/Dr7QwLz3UOWtdqLCl2/Ck1fEmoOPNme1jhchPaPbA5qPsnsxoCW2Mq7fJLKgrNwH6vgsULQOsnQW82gWYMxxYGWouSVif5adZH6DXi0DTXsfvtQghxPGEUeSvHgJeaAusmRF2+2L0mRTx/dbThdHfe4XQulgkLCqwF3kPC5Fp50pcfr+fTewA3svyUClU2gy0zvR0Aytdw7Zpcak+GRFbMArS85lwp+XWVwAHLsq6HXv/3PA98NZ5wLYVwOc3AQ1D0ZfI2UIhhCjoMKo8+k5g+hC7Xfd0++2nlbu/Kz1h3crZj1i6LAUNjUmIalQTGokVkfdsWWx5+yQlNbz+9W4mULavsRNR6ZqWOlOmFtD2an0SIvZxQiW7244yNYHerwDv9rai+yUTTIizCzMjMw6mkv3wnP1Ad77z2O67EELkR9rXF3eEbYkvfNHMR9hYl7BW1T9WoKUxJ4ZcWljN9sCqqdYYWiQsEisiZ3ZuAH7+wArfOkXpERE5e8IcfucG1rIf0OGGcAiYxcnsU8FL5ufTnpjpYK6+RYiCRLm6lt64ebEd88y5LneCCXTH7s3AliW28LvQ74P83GMhhMhbofLGuWbhzihJj38DJ/W3+0440+zeXT+q1CpAkwutx4qfQ6G+bWoKmdBIrIic4SCLYViGaHMSK2P/biek3q+GxUqyL8eUtSlMieHz0TOd/VW+etDuq9ZKn4IoeLBuhSK/QgNgxxr7DiwaDfz2PXDFp9bwzG/JyV4tTvALIUQ8s2o68PEgGxeUbwjU62xREoebyHSkVgROuyPr86QdsEulgSU0KrAXOZOUYpccVPltViNtCDkAYxdazhC7mRC/X/r4+0PF9gGbcf71M7NqrX2KDeaEKGhQrPP7Q8HCXiwszq96EnBgp7nhTH4hswFF+iHgwO783GMhhDh6nOPhT0PNDXH7qlAWRWdg9XRgRIRAyQ0b54fGGfv1ySQwiqyInJn9fvgkRMESrYssO3Q7/GlgP74ELB5rAmXux7aO9SnMUWWRMcO6ba7UJyAKLkVLW8SEsKC0/3DgxbYWZRn3d3PD4XrXX4DixV/nJYQQscLcT+0c1fySrOepA3uAL24H0vYDC760Jrc8t101FhhxfebJTTZ/5qQNHcAKH2YYyhqX9XOsm71IWCRWRM74Z3rZ0C6aWGHeves2z0Jhfwd7NnLaudaus0Oty9enSKl3BlCkuD4BUfDFSpd7zJa7RAWg1eWWWrl7k9VwUbRz9pEFpBwIlK6e33sthBBZmfGGjQNOOCOrWJn6X6u7Y3YFhQrNR1ijx8aP/nHEpgV2zqOAYX3K5aGJzOyo0swWkdBIrIjDd5h38CTlYPfZHauB0/4K7Nli61yhvEsDY66pEypNL7KBmYOOYBIqoqDTeoDNJFZtaTnZTtRTtLS4xH78KVBYfE/77mh9iaa/bm44XR8CSlU97i9BCCGwe0t4DEDHLj90NZw7AtgaEiqcfGGdKyMoP39oKa6u7mTsveHnURRZHKualSVLlhzpQ0Q8Q4thh78b/dSXgflfAOt/8YmVkNXg+U8Dfd8JR1woYuj8VbGxNdNjaJiF9kIUdNhPoEHXsFAhzu2GP+RtBoWijUET8/w+RZJa2RpJjrnLIjKsDRNCiOMJTUKiTVzSMXT8g1afwl5plZsB138LnHGv3V+yKjDwC6D7E8DAUcApt4Yf62yLhchrsdK0aVP07NkTEybQM1skVmQlJFY4U+woWztsPbj8W+snQbevcfdb+JfCxJsNDgIXvWLWhZxlKVvnOL8QIfKJrcuB75+2TvaEURVCMX/2Q8Ad860AnzOS3wwO9yhy1Ghred2/rwC+fwb46h/R/48//VIIIfIS/wSjX6xMeR74fXloYrOQ1ZgwXZzOX/ydb3+DpYTVag8kFbF0WAdt3YU4VpGVli1bon///mjWrBmGDBmCfftCaT+iYJF2KHxSuvRtqzEhzm6VxfQskKPTR7M+tm7jr8AHfYFfPzfRcuZ9dvnT+zYjzJMXC+7opy5EQYf1KnM+AuZ9BiybmDmywpoVwlqV674BKp5oZhVvdAeWTQo/R8nKwNkPhzs8s+tzJAtHofz/+gNLvjrmL0kIkYD4605YHO8mLnmuchMsjCJPfh749X+WadHrpawF9EyDrd/Vrjc+73jtvUg0sVKzZk3885//xKpVq3Dvvffi7bffRo0aNXDPPfd460QBwuXPM12ldC2gUOHMJ63kEtZp1uWeph+0ExUHTHQ36v0y0OHPQK0ONtBaOcW25WPUS0IkAisme0LCg1FGv1ihI5iz+uQP++WfmDsYa8HeuRCYPdQez3RLNkz707BwLViEjWfg23/bJSM4QghxrM12yIZfQwX16UCtTkCd0+z2d/8BPr7K0sKiccbfgXP+CbQZqM9JHBuxcuDAAWzcuBHLli1DvXr1PMEyaNAgvPDCC6hfv/6RPp2IaYJAg7OBuqeFRYk/ssLLpV/b7AqjMAzp7tpgQoWDLj6WoqTzXRYGXjUt+14tQhRUNzAHIyiuBqX/x8DAL4FPrwNG3grs22EuYNdNAlqxw3MQ+Pwm+9GnEKHQ9yyOQxMG3N7hBI8/xUwIIY5ZGtguSzv98nZbT6fPS97K3H2eNXj83Y8GxxMcV0RzFxUiL9zAihYtitTUVFSoUAGlSpXyltKlS+OCCy7wLkUBggMfpnGtm2M593T4aNor8wzLbz8AEwcD62bbjC9PTsy/pzWhawrJWeOLXrV+K37RI0QiiRVXTMrvAAvu+T2iC5hLF/v0WpuJZC8WuubMfMuilEydZONUCn/ORHrfrVCzVu+xGzKuBlv157dMCCGOjViha2GLS22SZe0soFg5YMBnlq7q6ldJSqnw5IoQf5AjHjleeumlSE5O9sTJp59+im+//RYjR47E+++/j5deegnHmhdffBF16tTxRFP79u0xbdq0bLd96623EAgEMi18nDhC6PLBnHvap0bOsNC9aM0MEyocRFU/2S45sPIPqDirzI7eQiQSxcqEr0dadTvzCgoTuuSxFoV1LEzxOu9poOnFdv/vv1kqGSMotEJueVnmGclQh+dDZU4AGpxz7F+TECLxYNNHwsL5X4YDc5iWWsjqWTmZ4ncEJa6nmhD5IVY+/PBD/PzzzxlioVevXvjmm29wPBg2bBjuuOMOPPjgg5g1a5ZX6N+tWzcvLS07GPlZt25dxrJixYrjsq8FgoP7LL3LFfa61BPasfZ40kQLZ36Zr8qISoWG4agLoyqqSxGJTlGfWEnyifWFo4Fhl9t1NlKl+MgooF9r0Zc2A8IzlRMfDQ0OosC+RsXL41C50ICBdS40tPCnhwkhxB+h+cVAz2ctkjL2vtC5qyFQs0N0gSKxIvKQo8rJYUH9Y4895g38KRZuuOEGtGrVyotkHEueeuopXHvttV6NTJMmTfDyyy+jePHieOONN7J9DKMpVapUyVgqV658TPexQME0lNfOAn4ODZL2+xrW0ZaY7l5ep9pU61TLWhXX/ElRFCEsFcJBUe9Y5pvgaXOVXZaqFm6Y6hqtla4J1Dndbo++E1g/F9i4ANgVchIjjboj2O9D7K1/vrnyjLkHmPYqsGaWPgEhxNERWV9KFy+eXz6/kXeaGGl8vtkROzKlgYUmX4TIj5oVFtLv3Lkz09K4cWN8/fXXuPrqqzFw4LFxd2Bh/8yZMz3XMUehQoXQtWtXTJkScpmKwq5du1C7dm2kp6ejdevWePTRR71eMdmxf/9+b3Hs2GHRBD6eS37A/xsMBo///9+3w/LfXdHuvp0Ich/W/4LAiBsRCKYhSEewcnWBSk0QZDPIzYsRGPl/XmTF21YUrGNCHBmBQhk1JEHOQLrPq2orBFb+6NW0BKud5K0PlKwGbFqI4PbVdnvtT/a4Tv+HwIFdCKydheCb3b1BQ7DTrUCrP2X8m/TfV6LM2JuB1HIIMq0s7SCCTNvQ8ZGw6BwhjvqY+H0FAp//GcHml4Qdu9b9jMAn1yCQdgBBtiwoXRPB8idkPscUSQ3XzBVK0hggDkjP57FEbv/vEYsV1qaUKVMmY6latSpOPPFEdO/e3bt9rNi8eTPS0tKyREZ4e8GCBVEf06hRIy/q0qJFC2zfvh1PPvkkOnXqhHnz5nnRoWgMHjwYDz30UJb1mzZtyrd+Mvwwuf88oCjQjhep27cg5dBB7A0WQ7FDBxHctQXbF0xG+RGXIHBwD9KTiiGtVC0gLR17SzXEnq07kLxpHUodOohDaQFszyE9T8TnMSGOnJSW13sC4uChEgi670SFjijadC/21zw1Y12xQEkUP3QQ+9Ytxp7yy1F242IEkI6tRWqiUOfHUfbLa5C0YwWC+3di3/wx2FEt1KuA7N6L0mlpwO7tOFTxRCRvmoudW9bjQHF9BxMVnSPE0R4TqT++iJS924Fpr2FLzR4otHMtyn/cG4XS9iM9ORVppWoCaWnYkZ6KgxG/80UbX4aiKyZiX0o17NMYIOZJz+exBAMex0Ss5BTFiDU6duzoLQ4KFQqrV155BY888kjUxzByw7oYf2SFvWUqVqzo1b/k18HEdDbuw/E8mAIphYGkZKRWqYfAcputrTDmWk+oBJOLI1DuBCSF3D5Sm3RFaqVKQIUzgfptUTg9DZVko1rgjglxFFS6LPr6ahFR6OqNEFiajNS0bShRvS5w1ZeeW1jF6g3t/hsmIfhWDwQ2/orii0eiWLnqCHZ9GIHPb0Tw4D4cKlwYyUkBJJcsC/yejDJFCwH8ToqEROcIcdTHRPnqCGxI9q5WSt+AwOf9ENi/DcGkFATK1c343S9buxlQNuIcU+l64LTrweQwGRPHPun5PJbIrenVEYuV/IJWyYULF8aGDWGbTsLbrEXJDXQxO+mkk7BkyZJst0lJSfGWSPgh5uegkAfTH96HvdusIJ79T/yWqtnBwl3+bxYJ8+S0aSFwaK/32ABz6U8837bbsRaBKs2Ayc+Zm1Gn/zMbQxH7x4SIHZhOWbmZZ1QR4GdarDRQs234/uJlrWcRa1d2bUBg6ssILJ3oOYIz7dL8LAKWXsZr+3fIKjzB0TlCHNUx0fEmYP7nXg1q4P2LrUaVKV5sS+CzIw6UrqFzTAEgkI9jidz+z7gZ5RQpUgRt2rTBhAkTMilC3vZHT3KCaWS//PKLl7qWkEx6wjrMT3g4d9u7LtksnA8kmVBh06f6XW1djbZAl7uBC56zExgb1/32PbBnyzF9GUIUSCo3BXq9CHS4IfttOMlQsqr1PAoUBjYvtEmEnesR5G0/+3yGGEIIkVtYNM/fehbUU6iwHQEnU1gPF7mdEMeBuBErhOlZQ4YMwdtvv4358+fjxhtvxO7duz13MDJgwIBMBfgPP/wwxo0bh2XLlnlWx5dffrnnYHbNNdcgIVnxg12unmGXyyYBH/Y316EcIiv48SVg9VSAxfR/+sgrGs7U5C7S7Ygdt1XYK8TRwe/O6LuAH18O9zZwuP4qFC2VGgMsyufM2K71KLybUedgVrHCiOoftTHW91mIxIEtC7YsCZ9D2Jg2cjKkbYKOo0S+EDdpYKRv375eofsDDzyA9evXe3bJY8aMySi6X7lyZaaQ0u+//+5ZHXPbsmXLepGZyZMne7bHCc+OdcD4B+xt+PVzoGrLrG8J121dBiwZbycqNn+q3hrYv8vuZ28VP+zCTfgYpSYJcXRsXQowlWvtbKDdtZnvS/GlbxZKtu/juiQEt6/0xErw4G4bWHAi4aTLvTozvNsbSC4OXPZ+5iaVfg4dAOg+xmhp5Hd31N8svfOi14DCcfWTIYQ4Uji58WI7L9XUo2xtO384ytQEtq2yvmpCHCfi7pfn5ptv9pZoRDanfPrpp71F+GZl2diR4d0fnvG9LRlmg5lh6HdtqFfD2Y8AG+ZZ74YD2YgVIcQfgzUoX/3Drpevnyk/3CO1on1/KR4IZz7ZNTolFembF6MQv5vsaM/+B+XqAdtWWMSTS051at88av/71NuApr3D6zkxsWqaXd+x2oSQEKJgwgjsiOtCQiUAnDwoa7+mzndbBFfnAnEcias0MPEHSQ0ZEXS5B0g7EF6/P4p13JQXgTF3hbdv3geYNwJYPC68fWQamPNjP/N+fVRCHA00rnBUCHWk90PB0bBb1u9uqWrYcvFnCJaoZI1aWRz7xe1ev4SM2VCrwI8+QFn+nV2f81Hm+1JSw83d0tP0mQpR0Niz1Yx3GF2d8QawaKytr3Nq1t94QjOdKs3V9FEcV+IusiL+AH2GWNE8U7pqtLEByrj7ALoG+Zk/Ehh7r10//U5zIHKRlAO7gT6vA6mVoouVxufZzK8Q4shhEasjO+tvFr36Sa3sdY5OK1cfYBM3TirsXAvMfBNYM9O2YRH+hEeAs6JMJFDE9H4Z+OQaSwGhKPFHdFJKmSg6GFE/4z9fHNwHtLjkyF+vECJ/4Pec55Jl3wA/vQc0XRA23ylVDajSwiKzfhr1yJddFUKRlUQjKcVSQihaONtKcVG3c/h+pnp9er1dp+hYPskGKhzQuIHU78stpSwyt53bUMRkN4MrhMgZioRW/S3Fgqlc0fBHOPgd7f8Rghe+aIYYWxbbd5BuYUzjWD/H69XipW5uit4816PcCTZTSkGyeXHm+5KL2eXBvVkfx9nYb58EprwA7N6sT1eIeIDf87fOB4YPtN9zZlowNTxtP1DxRIARWta3ucisq2mliBEiH5BYSTS+/hfw+tkW6uWAqPOdQKt+dt/uLcAHlwEs0q19qp2YKGqSQk17eBIj8z6TO5AQx4r215mZRXbF8HQBc/dxcBGi+IKPzeSiYmNLF2PNC61GPRGzBFg9HVj8FbBoXPi5GElh1IWpY5xJJetmh++f/II9lkSLrPhTSKOlkwohYg9OWDob4u2rge2rrA6uVHWgXhdbz/EBsyVa9jMjD7Jjbf7ts0holAaWSHmptBReMdluf/cf69fgbzr3xW0WFuZJquezwCdXm02xO6m16Av8MhzYMNdETf+I/HYhxLGn9QCg1eVewzZ/34NgUsixh99f5+RTobGlhLH3EdcNvdQatt42zyKjPB9Mehyo3gao1dHszVlQ2/Iye/xvoVqW7CIr+329XCJ7MAghYpOfPwzbEtNAY+/vFollivf0IbaeDR9rdwpPZLK/GlNOhcgHFFlJJLHihIo/vYN9HGhjPP9LYP7/QhbF74ZTPxhVcWlddCJyTkGu6FYIcfyh0GBDtuXfWtrm9NeQ7uxFmfLl+rFUbAQ0uxjwOk8nWQSFs6Nf3GrR0U3zbTvakLKOjXAQw/soTnaut3UctHByIxK6CxKmlHJwI4SIfVh7SlivyqgKoW15rQ5AsbJ2/vC7fZUob99vTUiIfEKRlUTBPwPqoLXp+5fYrAq71LpZWw5qXENI1rj46XSL1a5UanocdloIkSNM3di0AAEKiRL1bN1v35tbD2GvlRPOADb+aoMQ1pXQgnjWO9bkdc/mcGoZ61z6vmfCg2wJFfIz5ezcwdH/vzPn8Pd/EULENAFOaLBO5fffbEWxckCF+jYxed5/bN0fbSQrRB6iyEqi4GZA/eKjSHFb2MSRg57Stcw96LsnfWIlVK/iLwBucqGd2IQQ+cfER4HJz3tXg0lFEfDVr2T0VHFious/bKaUDmNlatm6qf8FFowCDuy0ejQOVJxQITvW2GVOERM6AtY42cQOG1AKIWIf1pcx5Zu1K3T55PfejREcMsoRMYTESqLgil8Z6u3+hM2g0lVo/Vzg0F6gaBngnEesRmXr8lAOa5TIihAiNmAKmCMpBWmpvjQtJxzc7CgFBYv2KzezWdT2N1oElWYaW5Za3Ypz/vGnjpLiFcyamCmjkbDwtkIjYO6nwMy38v41CiHylACzLGg3zuhK4RTgoletXoUTG4qmiBhFaWCJQka6RimgVnu7Pu5+K77lieqUW4Hvn7b1nG3Ztgqo2d5sUIUQsQcnElzRe1JRHKzSBsH2NyBQ6URbT0tSf5NJ4lzEeA5grvrKKVZ8P+N168ty1oPmDkQHMNaxEPZh4NKoO9CF3asjYB47zxmuYFcIEZsc2o+yo65HwP3un3EPUP8cgD2aWKfCSYu1s4F211hBvRAxgsRKokVWXGE8m0BNfs6uMy2EzkJ+WIjb44njvJNCiFyTRBOMbaHrKZa2Qcc+1/+o9vCsj3FiZcUUK7Sv1ARofz0wbYj1VPrqQaBkNUsNockGn5O9XGiJ7Ipy/XAmNjLlTAiRf9AUg65dkWlcwSACo/+GIht+QrBQEgLsrdToPDPqYBonYVbFznVAITn7idhCYiVRcAMNihW6go28zW7TU93rtRDRMG7Dr8d/H4UQucefohlZW5YdDbsD1Zi61cDSQFmXUudU4MSewJSXgLH3hqKtjL50tHTRhaOs8aOrY/Mz/n5gecjeODLnXQhxfGGT1mFXAMlFgYvfMhcvx7QhCPz0LoKMqJx4IVC2NlC8XOaJB9axEN4nRAwhsZIonP5Xc/Ki+8eb3YH0g0CTXkC9Myz9g3nrhLOkTOdg0b0QInbxCxQaZeSGKs0AcAlBZz9Hxz+bc9gn11gvpZ/esXq2Ey+w+6PVrPhTv9QUUoj8gWmf4x+0aChdvrhMfRk48+/h+rYxlsKZXqIyAu2vR8ClgxPWsKybY41faaJTSjbkIrZQgX0iwW70H11pOepVWwG9/gswv73xeeFUjqot7ZKh4DfOBX54Nl93WQiRDZw9JWc9EBYUfxSeD9rfEO6pwiawn91o5wwKmHH3AXN86WX+aIoTLizGF0Ic38wJth9gbZmD9WiEE5QfXu6ldgfL1kN6sfKW1uln3mfA4nF23eunonlsEVtIrMQrmxYC80Zkde/g4IG56AwH+2HKBzvSswlcahWg3wc2G8vZlc53hvsyVGlhOeylqtlsDQtnhRCxG1nhJERuYfSD9SmvdDYHr2gw350LC+xZr0LXIBbjs+h+8VfAlBeiR1Zof87nfaNbVhvjxeOBhWOsE7YQIm+hJTlrzSK/6zs3Ah/2tz5rjLqkpHp19d53mWMCh2siS9hAVogYQ2IlHuFJ5tPrgO+fAdbMynzf0gnAB/2A188G9u+ydRw4/LeTzZzQqpBChWLEj+tYz2L7Vn8C6px2ZLnwQojjC527rhoLNDw394/hjCrNNcjqGdkPfEhycXMTO+U2szSnaGFtG/PaF421iRKX+hXZi4UTJn7YhPKbwcC2UBM6IUTewknGSEZcZxFRmnGUrQcUtxqWwK+fAUP7hrdzxjtE9SoiBpFYiUdWTQtf37Uh833sUO1wvVLYOM4V0DP1i70RohXeUpiw8JZk1xRSCBEbMDL63X+AUX8BNi/O3WPYxT5avYqfklXC1zm4oa35SVeY7TmCwN6twNBLbcbWRXV4XqGgcdD+2EFRw6gLKSErdCHyHE488Lff1aZWbGTfwWUTgUASUL6eZzEebHBO+DGMsmRc90VWyofGAELEEBIr8QhzULMravWLlX3bgHU/W6drUr0N0LxP9OcsfwJw2VBzB+GsqMt9lVgRInbZ+KtFV6M5dUXD1ab5IyiRMOraLXTO4PmAywXPAXVPt4EMm0Qyl2Thl8DmhVaEv2Nd5pRRpo05GJFx/WDmDMuaoiqE+GP8+BLw5R2Wttn8YhMqe0Jjga4PmhUxoyfsneYokpr1vNCsD1Cvsz4NEXNIrMQjrfoBDc7OHD1xuBlMwsaOLKyj8xdPVG2vyf452X/B2RzOHhrORVcHeyFiEzr8uAhGbicV6PTj4ORFdjB6QkJpIxkd7dl/hSlfjMAWLmKuQ6yfe+eCzILJH1nxF/PSdWhryHlQCJE37AxlWLDW7JePgRU/2O1GPUzAuHpUf9TUL1ZcGpgc/USMIsuHeKVcPbukS09UsRIEvv4nsH2lDWTK1rGTVW5wJzeiyIoQsQmLZB2cVMhtwOKy9623EuvTssOdV1wfBkZGaGvqYD0LC/D5HOzbtGu9nXsYlaHA8UdW/NFewpRUuo4JIXKGaZZ0+vL3Q4mEAoPRS/L7CnPvc8KFrp+MgJJqJ3lR0UOlaiFpz7rMduf8PkcaZggRQyiyEq/wJMRISf2umde7gQHTMjbOCxXW1bFLDi6OVKz4rwshYgf/RMKRTCowMuL1W8mBGW/a5eqZdkkb80gKJQE9/g3cMgsoUtKzRvVECiMnHDRlV1e3aVHu91WIRObTa4F3e1tU83BRFUY9uT2jnYyo3D7P0rrowEe3r8Y9vLqVA9XaZa1TqdzUJjwqNznGL0iIo0NiJd5Y+SMw4gZLAWl9hVkPE9oYf3GHzX4yNYye66RGWxvI1D0NSCqSu//hBApFTs22x+iFCCH+EMxDd+R1uiaL6pnm1flvdtulj1RrBdTrkvlcwfTRq8fZAImTIpzpZS3Nhl8zR3vd7G2keDkS0mWlLhIEung60b/2p+jbcHLy9+Xh3mj83a/QCOjzuidMUKG+uX+e/YiJGZ42GKkhodsZNauXfwK0vvLYviYhjhKJlXiDJ6SN84EdqzP/gE9/HVjDWdBgOAWDxXQUNEzLYKO33OIKbyNTzIQQsUOADROOUbpms4uAQaPCdS3u+U8aALS5Mpzn7kQSZ2Q5KBr4pZ1vKEheOd3sUZkbzwgMLdH/SF48O2y/fT4w/4s//PKEiIvfeke0rAi2MHivj6V7U4BsXWbrez6TOcWL9aicZHAP46QBv7t+Z0DCdf5zihAxhGpW4g33Q8+0iy1LLYpStIytT9sPbFlmrjyc/ez/iXWibdIr91EVv1jhc7IbteuULYSIHfxWwYyC5DWcmXW4WVhGbneHmsmlRrEhrtEGuOF7YORtwOKxwKIxttQ+BTjrgfB5hWktmxcBNdoBhXI5ZzbhYRuUfftv4MTzw7PPX/7Famdo2ypEQYEGOaR8faBMzaz3uwiJN0G50q62HgDU7pTj0x6o0QnBlEIInHBmXu+xEMcMRVbiDXaod4OHj6+yH+oV31sh3uYlJlgqngj0fc+ECjkSoRLpEuIv4hVCxA4soCUVGx/7GdEN8+ySjWVZRH/aX4CTr4q+Le+/9B3goiFAx1uA5BLmTjT6LiD9kImVkbfabQqZ7P7ftCGZbY6Zix/J6ulmz06XMfZzESKWxQeNLXKLc9SLJlT8YmX7Gvv9L1YOOPvhwz5tWpm6luaZU9G+EDGGIivxhnPrYKoFi+YoXpgWwX4HjKiwaK7HE9apftV0sxhlGPhI4MDnlP+zKE0lFdwJEZO4iGdue6zkBayV41K1pfVeiQbTUodeYucm5s6z+dwPzwLrZlsUmEW/7KDNXi1LxlvhbySf/TmcmtLyMrvO9JVItyK/dTsdkfyduIWIFXauB4Zdbtevn5S7x7h0btamMRJJcfHdU5YexsaPFCi87vqpnP901tQuIQoIEivxmgZGocIICGcVOQgg1doA/T+ylBDaFzIqwpPXFSOOfOaVAwohROxSubl9t4+HvThnYqe+DLTsB8x8C9gfivBGg2ldjO6umgr89h2wcDRQOjQ7zEmVCQ8BgcIWHW7VPzyLzJqUht2sF4zr4bI1VDxMytW1wdnpoaJ/4n/tFDISKyIW2TD3yB/DCKWLZrJpY6ebrdB+20oTL3xOZ1bR40mgaa+83WchYgilgcUbbpCweTGwdKL9QDN3/cz7gWvGW70Jf+xd+hZzuVU0J0TBg+mdnG31F9MeK7yC+9FAnVPtNkVETnaqzLMnyyeF+0KxlqXbo0CJSmZzzHPZ6L8Bw64Axv4dmPQ4MOMN296lmLGhrYPnOYoYvyCpfxZQsqpddyk2SgcTscbRZCjSkMI1co508OLv/qR/h79b7a7Nox0VIjaRWIl1mLO9aipSln8V7m3A2ZSvHgQO7TU3njPuteJS153aWYT689qFEOKPwPOLXyjkVM9G23PiIiNla5u44uRJhxvM3YiprEwFm/8/4NfPzX3wp/fMjtXl6bsiY9LtXzYhU/f0zIKEs84u6jzvM+CjKyyPX4hYwX1vmJZ9NI87QDvwBeYESn75CNj2m0Uo65yWxzsrROyhNLBYJ5iGwJi7kXrwAFCqlJ2snKUh00AYNWHNyql/Cbvq+CMp2RXnCSHEkeJvJOe/HgnFSTTxwn5QdDHkhErp4sApt9nAa/0vlqPPyMmqaRZ5celhFCY8p9GZ8IO+wP5dwMAvwilgtEV29Syz3zeBM/cTq7uLBi1f3cSOEMcDV1eW235Irp8Q670Ij3mmUBKmR875yK43PNec9oQo4EisxDrJxbyLpN+XIDD8ivBMYu9Xze1rwiNAi0uz2n+edLk1kGzaOx92WghRYM9HTLvaty0sQKLBCEqm27WzOg2SeZ8Cjc6zLttsaLd1KfBhPyvE9yIvocZ3qRVtoMeifRqJcPDGAuMPLgNK1wB6vwKMvRfYtMAes/TrrGKFfSjG3W/Ch26JQhwveKyS3NaXrZ5mxzOFtTOP2LXRbvM4pmCpfSpw2ftK8xYJgcRKrLN4vFdAz1hJsEhJBJpfbMWuLDbljCOjK9H6HTCHVXmsQoi8hAP9S9+2QVNO/ZecqHFRYCdsaAxCeA778SXrk0L7Yp7DGCFhSticYSaGuDDS8vlNVpuyeoYJFTd4Yx7/wb0WUWGkZPem8P/nOheRcfzycdgO9sAeq/XhDPbPH1iNTa32OlbEsaFmWzO72bTQhHmJkBDPDrrc8TvGGhUe5xTnTG2kmGeUhulhFz4voSISBtWsxDrMRy1WFukppRE89TY7UbkiVP4Ql6ysE5YQ4vjBCEduivr9lsQuLYzNbAkHYMVDzWdpEkARU78rcO5jQIVGdh9TuziDzOaSo+8E5n5ss8usVqZYcdauXPfVQ1bz4qCooZDxwwiNw3X7XvglMO1Ve34hjhUUKq7HEI/d7JjyIjDiBmDHWrvtXPT4mAUjrSkr61TaXGVGFUyNlKGESAAUWYl1kosi2OEmpM0dgSRaFrJmJTUHFx4hhIgFWl1uAoTRDOdi5AqG9261aAojLx1vBup1sejIT+9aVIapXT2fNYGxdhbw84c2q7xzLbB7A/D9s9YA16WWMe3LOYZRzHAAR0HkF1UHd2c2B6jSzCLXDkZ5Cicf+/dFJK7Ip1hxKWGRMNrnalGc0x6dvirUB9b9YjbghBHItldbSiN7Hp16u2yLRYEn7iIrL774IurUqYOiRYuiffv2mDZtWo7bDx8+HI0bN/a2b968OUaNGoW4w+V/b15kl+olIISIdVhHx14RNduF17lz19xPrUcUYfqWK3iv0jy8LVPHGnQFOt9pzSU5y0w3RKbHzB1u/ScYXe54U/gxrHNxdTGMvKycCqydHR4MOjjIo5hhYX+0yEtuoVnA8EHAZ759ECISHoPu+HIiO6deLK5/Cn/7a3UCFnxht/l9OrFn6HjeFb0OTIgCSFyJlWHDhuGOO+7Agw8+iFmzZqFly5bo1q0bNm5kakBWJk+ejH79+uHqq6/GTz/9hF69ennL3LlH0aApP3F9BFxag7PqFEKIeCLaRIuX2hWiWmurH6nexlK5xt0HfHKt9WShEKnc1FLKKG6YEssmedOHWIoN4TY8X3JZMdnSu2iHTJhC41gzE/jf/4VrYFhwH63273BQPDGl7PffjvyxInFwURHXjiAa0dK5eHx+NMDc8ZhKllolbDzheq84xzAhCjBxlQb21FNP4dprr8WgQYO82y+//DK+/PJLvPHGG7j77ruzbP/ss8/i3HPPxd/+Zh2PH3nkEYwfPx4vvPCC99ho7N+/31scO3ZYE8b09HRvyQ/SKzTCzpP/D2V2LASWfe3NpATzaV9EbMBjMRgM5tsxKWKLuDkeap+KwLQhNivsCvAXj0OQqWBu8H/RELuedgCB3yZ7A7XglqWeyYjXl4UuSIzK7FzvpcsEln6NINdTCJWoiOCl75jr0urpCPwy3Ivc8HwZcIM7UqYWgiechcCWJQh2+j+gVHVbf6TvX0op268DuxA8uD+m0sji5phIBA7uDR2/QJCiOdpnUqMt0PpKBGa9HdowHfjhaQT2bEawYmME//SR1ww6MOFhBIuVRYApZdwsqViuj1sdEyLWjonc/t+4ESsHDhzAzJkzcc8992SsK1SoELp27YopU6ZEfQzXMxLjh5GYzz77LNv/M3jwYDz00ENZ1m/atAn79oW80vPhw9xesgWKLh2N5EMHsbdQKezJJpokEgPvmNi+3TvJ8HsgEpt4Oh5KJ5dB0p7fsbNRXyT9vhT7a3VGWjbns9LFqyBp+284uHSyd+7jtrta/xnJG39G4V3rcah0bZT+9n4kb55v0Zcl45H+3MnYddI1KLpsHAodOghsWowtGzag3O5tCCAd27s8irSSNRAskorAOa0QLFoWOMrzaeq0p5HC/8Ga/dVLESxWDrFCPB0TBZ3U7VszjpOdmzfgQLHox1vKoSIoESyEwKH9CBzc7R37wULJOJSWju2rl3jF9aUXjUdaajUEDuzyju9tuw5k+/2JRMeEiLVjYudOE90FRqxs3rwZaWlpqFw5c0d23l6wIOStH8H69eujbs/12UEx5Bc4jKzUrFkTFStWRCk2Zcyngyll9Q8otnM5ULQkUjtciVQXChYJCY+JQCDgHZcaiIh4Oh4C2AckJaNMjUbASRcipySWQLVmwO41SNr1G5BSAoXLVkHxqtUBLo6mZyL4ymnAns1ebX3hXWtQ+ruHeNUaV5asgkpliiFQsoKXOlOu/snmNOZRyexkV0626EqDc47stRzc4r0WUjE1GSh/FKlkiX5MHNiFwOi7EKzXGWh+KQoEjBz6akkCKYUzjpMypUoClSKOEwrtQslAxcuAdv2Ab59AoUmPIUjDiDqnImnv7yiXWsRLAwskJSMpwLTHg95zlq9ay4soFqhjQhw30vP5mGA9eYESK8eLlJQUb4mEH2J+frnTS9UAqrZCoHprBNggTSQ8PMHk93EpYoe4OB5Y5B4qNA7Qsvhw+1qxoVkX12wPdPsXAkwZiPaYklUsBeuC54HvnwaWT0KAVsYcBO7fgcCn15pjEmes2b/Fn+e/ZTEw6x2gVkeg0bm5ex2bl5ijma/eJnCAA87Yeu/j4piY+wmw8VcENv4KtLwMcc/SicBX/wDa3wC06mfrnAPYGfci0LBb1scwXXH2UKD1FWZNPOkxb3Wg+xPAhnle35XAt08APZ8L92EJEWD64xF8vnFxTIjjSiAfj4nc/s+4ESsVKlRA4cKFsWFDyCUjBG9XqVIl6mO4/ki2j2XSytRF8LynM/U4E0KIuCLdUmE82KX+cLDYnnDAxu716+cAY/9u6/p/bJ3tySVvAsklgMJJQNWWVvTOPhS71tvAjs5hXAgHkmc9YINJnlBTQ9H33YdJpWHB/uTngS73AP+7Jev9e7fl5h0QkfiNDwoCEx+1y6kv+8TKvpw72PP49noD7bPjk3S+2xo7v3ex3ebxzyJ7R4OzzXSHVt9CFHDiRloXKVIEbdq0wYQJEzKFr3i7Y8eOUR/D9f7tCQvss9s+5uEPq7P4FEKIeINOhqf9Behyt9dD6rBUbGQDNAqObx4L9VEJwf4r/uelUCEuasK+FmVqW5PJhj2AE84Eqp1kg+MxdwOfXA2wd5VzAfO7kkVjzD3WrG/8A1nv8xzK4mbuL7Zw5gZ1T0OBwD+jyEigv7dKNLGycYG52lHIsykkrY0ZLVk1NfQcIae7SJtiGkN0+5eaQouEIK7OrqwlufLKK3HyySejXbt2eOaZZ7B79+4Md7ABAwagevXqXpE8ufXWW9G5c2f85z//wXnnnYcPP/wQM2bMwKuvvprPr0QIIRKUJhfkflvOGp//FDBxsPVT8XepZ+PIaET2nTj7YRNG7O1StzPQsp8JD6YfzfsMOPU2287rLr4ncyPJaPhdxZxQoQOZ+GORlXjtF8LjZtkkoHYngKmNGb5fnB29H/jte4vk0b6Y6YZMH6zaypzwKH6//bcJEjYqpagpXMREtkv16nwX8N1/7JKCnCKc2/E4LJo/dbRCHG/iSqz07dvXc+V64IEHvCL5Vq1aYcyYMRlF9CtXrsyU/9apUycMHToU9913H+699140aNDAcwJr1qxZPr4KIYQQuYZdvC961WaQ923PhVgpEb7OGWrWoSz/zuyO2VCy14s2WPzmUWDZNzYQZME9IzJbl2ZuTBmViH4YLo1M5Mysd4FNC0w8+jMEnPjLMD2II5huyIagFFwU4YwaMhrIY63tNcDSUGYHjzv2SGE9S+UmJnAYRfGiSUHr00MBwsanXg2Kb2hWuyNQ++Pwbb5P3JaNI0uFerAJUcCJmzQwx80334wVK1Z4vVCmTp3qdbF3fPPNN3jrrbcybX/JJZdg4cKF3vZsBtmjR4982GshhBB/OLWGHb3dgC275rh+scImkplm70MD4lrtgQGfAxe+CBROsfuZBvbOhQD7wHAgOepvVkMQSYu+4evlT7BZ8ILCrk0m3rYuz/vnnv6aRRlW/JB5PU0QCCNd+0Nd2TPdv9PS9WKRyS+Ejy3WTJEOfwa6/gOofxZQslq4ZoUREe/6fouqEN7PY5nuYUwR6z/cIis5cdlQE0Yjb7VIjRAJQFxFVoQQQiQwjH5cMSLnAZ1LJ2Jx/pn3ASt/DBfXR87en3S52RWPuB747QdLMxv1V3NkYi0L08ZOPN+2PeVWr8Gkl+6z4Eub/b74DWD1TGD4QBNSjBocjvVzzf2J+9L5ThNiG+dbClqVZuFBrRvY+m8fa358CVj6NbBwDHDN+Nw9Ju0gMOEhoEpLoMUlh98+1MzQ69jO5ZTbgV//Z+tYMO53avv6X/bZMb2Kn/uxEGd0Iat7+tHVfjjRccFzZuxAKjW2hThB/dO7mcUK3wOKnJlvApsX2fF2ydtApROBbo8C3wz2nMOiQsG9ebFdLxUSQ0IUcCRWhBBCxA9eXUAOMI2GC+tUfl8BjL4retTFQVHS81kbRC4eb7PlO9fYQHTEdcDU1sCJPS2tx6UvDfA3Fg7mPhJBUUInMVotn/1IeID8xR02eL3kLWD1DKBmOxMNHOTSjtlFiHJi9gfAvE/ttRztIJbpSCTtgAmJ3AzgmdrENDsu2YkVPlckdL3iQJ2Cj5+XG8D7WRISTHu2miiiPfUfYdE4YO7HQNeHLIWKNSX8TPw2w0eCE15+Z7tDB4DZ71ua1sLRWc0bDuy09DC+dsKICmuenKVxnVOAK0dm/97zfWB9C6kYEkVCFHAkVoQQQhQcODs98IvodsLZ1UW49LIKDUx80HaWVrHsycLCaC7TXjMRULuDRQOcm5kbqObGunjJBLOoLVEhLLpYSO0G6RQoTO1ZdAKwZWnYCvey9w//3NxnF7k5WrFSsqrVYZCd63NXE+E3PcgODrwZvVj+rQkhwnohsna2Ddg916yItDum6Ll1TAVj2t2RwHoYCklGrMjEf9nlzx8Ap91hQiXSUju3sA7FiRWKLTp/8bNd8hUwM3M6ugfv274amPJzuO6p8fnAuYPDx58jJ5HIPkIULH4nNSEKOHFXsyKEEELkyIw3rf7k189tAJ5TZCWSdXOAYuWAXi8Dp99lA39aJm9ZBCz/xiyU/9MQ+PKvFrlxqT4UHax3YWpRdqz60S6bXRwWK1tC4sDDRSB8g1WmnuUGDphJhVBvmsOx+CuLblCUOei45lj/S+6exy8wGFXIdv9CzlVugM9CdCey3GtkGpiD9UL+53bi7UhglOzzm0wkEueexdQ/4jq/12iXu+PCpV/5XweZ9irw5rkmVOjulYmgHRs0F6ATGG87x68+r2cVKoeDKYgONV4TCYIiK0IIIQoWjIgw0hFMs/oBV1uQnVhhmtGvn9ljXHpO1ebA909Zc0n2euEsPQfT3JauZNOHWM1B7VMs5YfP/dN7wIa5wPnPWLSEg1KXukSb2m2rLJWsehtLm2LBuSswJ64Wx+965np05ATrXdzgObfuZF8/Er7OgnBSuroZCMwZBmxbkbvn8QsML0IRpZ7Ia15YFKjeGqjQMHNEyqWeRT4XP0M/LuKTHXw/2aOkftfwuoWj7JKfn9fzZFf4PWJqmnufo5k1cFt+VrTPZkSEBe2sU+ozxIQU3ytaEvO42LLYPideMoLi3gsKV0aeeBySQskm0vg83Kfc9BqKxEWoCkpfGiFygcSKEEKIggX7p5C0Q0DFE62ugoO75tnUVHCQPPNtu16ro82A//JxOGWJg0wOrrkwUsO6Aw5OOYhdPilzmhlFypAzbdDa8xlrRMmB8aKxtk3lZmGb5EVjInYkFFGhgGHDv7F/t9uH6/9CseSgIHIF3tnhd93ie8MGgy7SQ7HS8rLD1wY5GvewAThTkrITg0zh4vvJSEatDpbG5G/w6TjkEyuRaXWuTsMPP18KUf7vcfeF31/WBPkjRkzv80RDugmQ4uUtauM+303zTbw16QU0PMfe7w8uMxHT9z1gwSh7LLcfPsiu8z3qcKM9fs7wcINHCibWqFDUukgZxQkjdNcx9S0ArJh8dKlnhPbINdqa25gQCYLEihBCiAJKMDxw50Ayu7QZlw5Eutxtg1TOXrMQ2j/odRQpCTTpbQ0mF422+gs2BqRQcZEZChfWuXS62QTO/JG2npEYwlSzSFytA4UQB6RePUPt6J3PsxMrTKuiSMoJCiU/rqCeheFM13LF3rmhbB1bcsJFTBilIKwVWTkl63YuKhEZXSKuSaKfyc9Zql/3x62ehalifP8pVvyOWUyRY8qeqzX56AqzGHZ89VBov34Fapxsz8NIldcodJfVEhEeP24f/REsCh+KKT7eCSBC8UZzBH6ejNBRJBHnMHc0FCtzZI1VhSgASKwIIYQomHBGm2lHnMVnXcTuzVbcHklSEUvL4YCY23FAWK+zLRwMf/dU1sdw4M36kAq3AJ1uAbavAV7raoPsg0wZ2wPMfs8WQnta/o8fngPm/88EESMofB7ex4EwO5k7KJJok+y/zQExU6lyEivRBvWRuCgFB/G01OVCQcGaG39NR17hxEpaKDXKX+/hGDQ6c/TIpYFRbNBCmq5tfpjWxc/GNZykMxZFxqaFlirFlCxnZe0skB2MiK2ZadcZQaLT2+yhtp5W165RpYvwXPSK1b0wgrNqKtDiUnst0183BzkvQuZzPKPgo5ihWCldy97vo0n5EkJ4SKwIIYQoWDTtDSybaJcUA+y3wkJmioXsoHjgQJ8Df88VLESTC4FV06y+xI+LEjhYw8DHUaxQdPCSBd2c4fciF2nAns22bJwbfR+SitkAl889/gGbgW98nt3HYngOsBn5adQ98+N2+sUK048OA6M27BvDiJKrfdgRquuhcGFUiQPwE84w2+acmP8FMPl5iziccQ9wwplZt3FuZ0zZ+vIO62/jh2Iy8v2sfjLQ/Qnbn2qtsj6nv9aH7zPFCovPncOXi3CVqRkWKl5kJCQqmIbFpqC8ZKoeRSqNGdi00u8ax8+Rz9HsIhNdO9ZYeh6PL78TGlMEKagokP19gPj89bpYhOXrf5pxAT9D9gFypghCiByRWBFCCFGwOPU2q8MoFKqLyE1+vyv05kD0el8dSna2xJGDa8LBPwe3HLAy5YdRkNPvtFQuzuCzaJ0pQRxIr/gRWDIuwk1rb7hu4+ehtlBgUWixQJ+DeqaKlasXdtMiFDRMfWL3eUZgWMsRrSbEwefzu1BNfdVSwJxoo6igMOI+5yRWWGjud7+K1oGetRv+18ioikutY/TBmRNEpuiVKG9LdjD6xfQv9tFhDQgXwveWURcnVuqfDayYYoLpoiFmlTyFvXTWhy2NSe1TTaywz40TtWzQyG24vzNeB6a8GOHOFjARQtFDi2kX4eJxcM4/zVzh85stBY3pf4zCkJG32b6zfkcIcVgkVoQQQhQ8nFA5Upcl/wDWsX1lWPSwIJ1RBEZBIuHMur8QfM0sWzjgP/2vQNnatr7B2UCbQcCbjJAEgXbXAZWaARMfAdb+BKSUthl8Fmsz2uNP7WLEg0ulJva8HPByIMyeHezBwX1jClW0mpjs2L4qfJ1ixQkhDq45uGfdDaMDh+uxEpneNecjG+D7a1oYEaFBgRMcHODzcWyMSXODyMaSjIRQWFBslK2b+XON1meEz8XXk1rFUsD4Wli3xM+BUZeKDcNGBK6GhVEzvlYKEUZPXMRjwsM+t6+Q4CpVw4QVoycUWa0HWOSnZltgM9P02thtVytFUUjb4siGl7l1bRNCSKwIIYQQnssSG0pGiyRw4M9BLKM1HKSy4DpaZKVm+/AMvx9XWO2H9RksnOcguFpri4RwYFy6pqVm0YqX+7N6ug10vWhJwNzNmKrEYm4uhANzRnEYHeLzfvkXBIqURImksghsmROyyi1j9Tss9qdA4GC5chOLAvj3j2LF2QsTDuAZzYkUK4wgsfcIxREH/N66iAiU69zutyfmtm4909HOe8qiFnM/tZQvCgCmn/F105Wraktz5iJXhmp9vAaMaRZN4vvmL8wnjKowusZ0PO4/G0NSRI76G1CysqXmUYC80NaiJrvWZ368S6Xz2zfzcznj70Dzi4GPB4XFjrNgPv1vWT9j9z6RNTMyr+e+CyFyhSIrQgghBAfzrf4U/X246FUTDNyG9QZcXO2DHw7oGd1wwoXF2NmJFcLO9CzGZo8XRiAcbvDP9DGaArjUI6Z/MZVp7xZr6rh4rBV+c7DteopwoL19tWeCfEQVESzypxBjjcUXt1k0gIN91m+wRoZpTkxFY/0Noy1emlXEe0D74FnvWP0LRQH3n5EOXm/YA5j7sW3HqBFhXxrXmZ7Pu3C0mQ+Uqw/8vswiSmzYuHuj2UczRYuigaJo9J0mvBiVogMaRQEFJNPOPhqQNZJB6OzlFyYuVYyCg6l03F+KF0ZGKOh++85qTCig+r4fjsrQ2cuJlWh1J+wJQ4tj3ueiTRSfDr7P0cSuECIqEitCCCFETjjHLM7IMyrA4mgOwCNh5KP1FTZAPfV24NPrzJ0qO7HC9YzSsJGkHxed4WCXaUROrHAQzNQxFsef1N8G0YxacPCenGopbOznEgggGCiM9PR0FCqchAAHx+2utf1nxIJpbYWLWr8XDsqdAQDrZTbMs8WftvXN4OwFjmt4SBjhoMjxHrc9LAZolczXFEiy/+nej9+Xm1jh6/CnotGVy0H7aMd7F4WvM1rE/aRIo5CJ7FvC+xl1oWsX0/f4ObCG5MwHTCRtZbpeEGjaB+h8V1a3rnkjLP3M2Vr7XeT81/1ihfvDz8PrsRIlLc5B0SuEyDUSK0IIIURumP6aWdtycMtmiJEwRYk2uJE1HdmJFaZ9sS7CwXoH9vmY+kr4+Vjn4mx2CYUFB8V0CvPqYwJAi8tMwHDQz+Jt1r0wQHPoIAolJdvj2l9vs/lM6WIhOSMJne+0CNH6OSasWPzPHiuMMNDZjIXmFDdcKHjoisXUNdbLsMkj/z/FCiMNfK2s0+Dgn3bDTLOigxmjLIwUBQ/ZQmHlFyD+tCvuH4UH3y8KHy5s1MhoCwUb64T4HCzk99s8e0IlALS/wWpHKJezesIAABTlSURBVIqmvWIRm3Mfs/fFNXbk+9asN/D5TcD6uWZPHc1W2F/zQ+Hj0r0i+/LwMyKbFgGfhXq3VGkevr/rP8z4gOLVfdZHUk8khJBYEUIIIXKFs7Sd9LgNSDl4zw7WVTCFKyexsuCLzLdZv8K0MP+sPSMRpFxdEyWMciz5CmhzpUUmCFOlOCD36kh+tnVJKUgrWhFJ+1xUZrnVqLDPiX/AzWgQa1QoQrjQ5tkfLaB4+q058MOz1h2exfaEhf3s3M7Uqqot7DpFDDvAE0Z5vn8mPMjv87qJPRa5Fy5sqV58/RQy7HPDYnhu60/fokDq+qBFfxiloZVxrfb2PD/+F6jZwXqwfP2wPb77Yya+WDBPIUjxxfeFRIpLV0viFyF+/DbXjKT4C/v9kRVaVhM6pzkYhXNw/5geyPc5Q6zkYKEthMiCIitCCCFEbvDXGfg7lUez9H3D1wXeP5D1Q4cqPxxgs2eIo2Y7S0UijCQw6rFotNWMTHs13JXduW2xMSXrWgoVRrDXy9i2cSMq//y8pSW5NCnWf0S6UfF1UbxwkM2ajcg6DIoGpr8xwsH0Mw62ubS/LrxN/a6ZHxNZ0/PJ1RaRoqDw6ktKhGt6/OlR3E+mbhHWiDB1y73vFEbea9hs4oSCidtQDNLNbf5Ia+DpCu5zqgtxdtQuMhKJX1AUj2gk6oQee7u47fzREtbSOPwip+cz1riSjxNC5BqJFSGEECI3+Ae//saBWX5ZfTPrHf7siYeoML3ID+sdxt1v10vXsHQqDoIvectuc3a+483AJ9dYYT1hXYbrmULrZA6eW/TNeMrg2Y8g4B8wOyeuSOvc/sOz9jpx0LWLFsCs+2DX+NZXZr8tRQpFQzS3K6Zb8f73+pggoeUync0anGONG1nA74eRHOKiI3RkI07A8TWwGL7fByYgnK10xv8LPS4Spqa5epLsxIpfYLr/72CRPx3L/JbM/veYkao+r2WOkhE2n+QihDgiJFaEEEKIXP1i+mobotU5ODiQ52CXEQ1aCmcHLYo5WI+GS1Pi/2EKmIO1JEy7om0woaBhGpVLTzrvSbue5it8d1AoZIiViln3OafX0+JSYMIjVpxOVy7WvNAlLFq0iDUa0aDAY22Li5yw4z1rUcrUsUE80+v8MK2M1DnNBJl7H1zzRWdywPeA0LbZT6TIcDASQ5HH/ckuDYz3OVvklmHx58E6ItaiRMImkiunAA3PDX8mQog/jMSKEEIIcaTkFFkhnFWnWHHd2qPRoJulM3GwzbQuFu8zCsM6Ds78M5IQLZWp3hkmVjgYZ5F8JNtWITDscpQ/dBBocgFwxt32fIw0nHV/uM/KkVC3C1DiZRMXtPOtc2rmtLfhAy1Nq1X/zI9jtIeRJlr9uqiKg6/dpZw5S+ETzgQ63WKuYi6yEllvQmHDSErJkEjJTpxklwZGITHg85ybh1Kgcd8p7rKL0ERS5xRbhBB5isSKEEIIcaSwjiMnXEPBtbOAGm2ib8OBMqMrpOVlJlbY4NH1IYnWy4WwYJtRHgoGf41LlEF74OBu6w5Ph7DerwC1O+GoKJxkfWhYaM/Gmb5UM0+MUAAxCuHqSvyizUWJGNFwEafIaI5L7aKDF7fJaT+jCTQSKSqyi6yQaO9bJOxpQ0GVnaARQhwXJFaEEEKI3MC6jdykTfmFBms82OPkcLh6DEYa+r5r0ZXItCYHB/PRrJOjFYczlYligkKCwsk1NjwamvY2EcGojP/18zqFAaM37JtCeJuGAewN4y94b9TDUski3yv2h8muySIjN7Q8plMYozpNLoy+f35xwiJ2f6H70ZAbQSOEOOZIrAghhBC5oVR1i6jkZhBLa+GZbwOn/SV37y2L110EwxXMHy0+IRFMLoEA06nYlJE9VuhsxeiFvw7mSJ43WuG8K1SnWKE4ccKm8fnA+AfCzSEpVtoMNGezKi2i7m9UsUKL48nPh2+zMN9vH+zwi7te/1VERIgCgsSKEEIIkRs4yL9mvEU9DkebQdbQMDvb4kgoJAgbHuYBwbbXIG32cBQ+6fJw7xJGb75+xJonHo1YyQlGMdh5nmKDNsIsji9V1SI5TqwwpYpWxB1uzPp4ChC6odXqdPj6oOXfAs0uirJdCWusSdFCa+lCOZggCCHiBokVIYQQ4kjIzoo4miPYkZJTo8kjoVV/bKt2NiqVrJR5PcVE84uR57iIC5tIUjCww/2GeWG3LUZacnJQ6/YvSweLVh8SmQ6XncMaC+fPf+qoX4IQIjZR1ZgQQgiR37CPCvEXrucVFABtr7b/ccHzFt04FilyrlCeDmjsIj/7/bDN8P4cXNGcuMuukN0fWWENjvtf2fH5zcDQvsD6uUf0EoQQsYkiK0IIIUSs9HBxhfZ5TesBthwr2HuEPWD4OvyF7a6vy9blR//cfrFCm+fDiS3+T4qk3ETAhBAxj8SKEEIIkd8kH2OxcqyhSxgduN7tbR3sHc622BXeHw3+NLAytXPeduRt4WhOdn1WhBBxhdLAhBBCiPzGpSzN+Qhxi+uf4rdOZud7WifXPytvIiuHrenx9abJbTNHIURMo8iKEEIIkd9UawWsnQ007Ia4Zc8WuyxWxnrLbJwPNOwO1O96+CaaOcHGkhRAe38HqrbKedtCyblrCimEiBskVoQQQoj85tzHgC1LzfI3Xhl9Z7g+pfF5tpBCKX/seZkGNuCzo68DEkLENRIrQgghRH7D+ooqzfJ7L+Iff4PJ7NzFhBBxhb7JQgghhPjjNOpul0175d+7GdlAUggR98SNWNm6dSv69++PUqVKoUyZMrj66quxa1fOnX67dOmCQCCQabnhhhuO2z4LIYQQCcMptwHdHgXaR+lQf7ygIxlpeG7+7YMQIjHTwChU1q1bh/Hjx+PgwYMYNGgQrrvuOgwdOjTHx1177bV4+OGHM24XL65ZFyGEEOKY2C/XOSV/31j2YWGHe/Z9EUIUCOJCrMyfPx9jxozB9OnTcfLJJ3vrnn/+efTo0QNPPvkkqlWrlu1jKU6qVKlyHPdWCCGEEPlCvc62CCEKDHEhVqZMmeKlfjmhQrp27YpChQph6tSp6N27d7aPff/99/Hee+95gqVnz564//77c4yu7N+/31scO3bs8C7T09O9JT/g/w0Gg/n2/0XsoWNC6HgQOkcI/W6IeB5L5Pb/xoVYWb9+PSpVqpRpXVJSEsqVK+fdlx1/+tOfULt2bS/yMmfOHNx1111YuHAhPv3002wfM3jwYDz00ENZ1m/atAn79u1Dfn2Y27dv9w4oCjQhdEwInSOEfjeExhIinscSO3fujH2xcvfdd+Pxxx8/bArY0cKaFkfz5s1RtWpVnHXWWVi6dClOOOGEqI+55557cMcdd2SKrNSsWRMVK1b0ivvz62CiOQD3QWJF6JgQOkcI/W4IjSVEvI8vixYtGvti5S9/+QsGDhyY4zb16tXzUrg2btyYaf2hQ4c8h7AjqUdp3769d7lkyZJsxUpKSoq3RMIPMT+FAg+m/N4HEVvomBA6HoTOEUK/GyJexxK5/Z/5Klao5Lgcjo4dO2Lbtm2YOXMm2rRp4637+uuvPUXoBEhumD17tnfJCIsQQgghhBAitomLafoTTzwR5557rmdDPG3aNPzwww+4+eabcdlll2U4ga1ZswaNGzf27idM9XrkkUc8gfPbb7/hf//7HwYMGIDTTz8dLVq0yOdXJIQQQgghhCgQYsW5elGMsOaElsWnnnoqXn311Yz72XuFxfN79uzxbhcpUgRfffUVzjnnHO9xTDnr06cPRo4cmY+vQgghhBBCCJFb4sINjND5K6cGkHXq1PHcDBwsip80adJx2jshhBBCCCFEwoqV/MIJINdvJT9gbQ7t3eiaoAJ7oWNC6Bwh9LshNJYQ8T6+dGNrf7AhGhIrufSAZqRGCCGEEEIIkbdj7dKlS2d7fyB4ODmT4FB1rl27FiVLlvTs3fID1+tl1apV+dbrRcQWOiaEjgehc4TQ74aI57EEJQiFCs2ycorsKLJyGPjm1ahRA7EADySJFaFjQugcIfS7ITSWEAVhfJlTRCXu3MCEEEIIIYQQiYXEihBCCCGEECImkViJA1JSUvDggw96l0LomBA6Rwj9bgiNJUSijC9VYC+EEEIIIYSISRRZEUIIIYQQQsQkEitCCCGEEEKImERiRQghhBBCCBGTSKwIIYQQQgghYhKJlRjnxRdfRJ06dVC0aFG0b98e06ZNy+9dEseJb7/9Fj179vQ6uwYCAXz22WdZOr8+8MADqFq1KooVK4auXbti8eLF+nwKMIMHD0bbtm1RsmRJVKpUCb169cLChQszbbNv3z7cdNNNKF++PFJTU9GnTx9s2LAh3/ZZHFv++9//okWLFhlN3Tp27IjRo0dn3K/jIbF57LHHvN+P2267LWOdjonE4h//+Id3DPiXxo0bx9XxILESwwwbNgx33HGHZys3a9YstGzZEt26dcPGjRvze9fEcWD37t3eZ07BGo0nnngCzz33HF5++WVMnToVJUqU8I4PnnhEwWTSpEnej8qPP/6I8ePH4+DBgzjnnHO8Y8Vx++23Y+TIkRg+fLi3/dq1a3HRRRfl636LY0eNGjW8AenMmTMxY8YMnHnmmbjwwgsxb948734dD4nL9OnT8corr3hi1o+OicSjadOmWLduXcby/fffx9fxEBQxS7t27YI33XRTxu20tLRgtWrVgoMHD87X/RLHH35VR4wYkXE7PT09WKVKleC///3vjHXbtm0LpqSkBD/44AN9RAnCxo0bvWNj0qRJGcdAcnJycPjw4RnbzJ8/39tmypQp+bin4nhStmzZ4GuvvabjIYHZuXNnsEGDBsHx48cHO3fuHLz11lu99TpHJB4PPvhgsGXLllHvi5fjQZGVGOXAgQPeTBlTexyFChXybk+ZMiVf903kP8uXL8f69eszHR+lS5f2UgV1fCQO27dv9y7LlSvnXfKcwWiL/7hguL9WrVo6LhKAtLQ0fPjhh16kjelgOh4SF0ZgzzvvvEznAqJjIjFZvHixl1Jer1499O/fHytXroyr4yEpv3dARGfz5s3eD0/lypUzreftBQsW6G1LcChUSLTjw90nCjbp6eleHvopp5yCZs2aeev42RcpUgRlypTJtK2Oi4LNL7/84okTpoAy53zEiBFo0qQJZs+ereMhAaFgZeo408Ai0Tki8Wjfvj3eeustNGrUyEsBe+ihh3Daaadh7ty5cXM8SKwIIUSczpzyx8afeywSEw5CKEwYafv4449x5ZVXernnIvFYtWoVbr31Vq+mjcY8QnTv3j3jTWD9EsVL7dq18dFHH3nmPPGA0sBilAoVKqBw4cJZHBl4u0qVKvm2XyI2cMeAjo/E5Oabb8YXX3yBiRMnegXW/uOCKaTbtm3LtL3OGwUbzozWr18fbdq08RzjaMzx7LPP6nhIQJjWQxOe1q1bIykpyVsoXGnGwuucMdc5IrEpU6YMGjZsiCVLlsTNOUJiJYZ/fPjDM2HChExpH7zNcL9IbOrWreudSPzHx44dOzxXMB0fBRd6LVCoMM3n66+/9o4DPzxnJCcnZzouaG3M/GQdF4kDfyv279+v4yEBOeuss7y0QEba3HLyySd7dQruus4Ric2uXbuwdOlSr+1BvPxmKA0shqFtMcP5PLm0a9cOzzzzjFc4OWjQoPzeNXGcTiic+fAX1fPHhsXULH5jvcI///lPNGjQwBu03n///V4BHXtviIKb+jV06FB8/vnnXq8Vl1NMcwWG83l59dVXe+cOHifsu3HLLbd4PzodOnTI790Xx4B77rnHS/PgOWHnzp3e8fHNN99g7NixOh4SEJ4XXA2bg7b27KHh1usckVj89a9/9Xq2MfWLtsRsh8HMnX79+sXPOSK/7chEzjz//PPBWrVqBYsUKeJZGf/44496yxKEiRMnevaBkcuVV16ZYV98//33BytXruxZFp911lnBhQsX5vdui2NItOOBy5tvvpmxzd69e4N//vOfPfva4sWLB3v37h1ct26dPpcCylVXXRWsXbu29xtRsWJF7zwwbty4jPt1PAi/dbGOicSjb9++wapVq3rniOrVq3u3lyxZElfniAD/5LdgEkIIIYQQQohIVLMihBBCCCGEiEkkVoQQQgghhBAxicSKEEIIIYQQIiaRWBFCCCGEEELEJBIrQgghhBBCiJhEYkUIIYQQQggRk0isCCGEEEIIIWISiRUhhBBCCCFETCKxIoQQIm4YOHAgevXqld+7IYQQ4jiRdLz+kRBCCJETgUAgx/sffPBBPPvsswgGg3ojhRAiQZBYEUIIEROsW7cu4/qwYcPwwAMPYOHChRnrUlNTvUUIIUTioDQwIYQQMUGVKlUyltKlS3uRFv86CpXINLAuXbrglltuwW233YayZcuicuXKGDJkCHbv3o1BgwahZMmSqF+/PkaPHp3pf82dOxfdu3f3npOPueKKK7B58+Z8eNVCCCFyQmJFCCFEXPP222+jQoUKmDZtmidcbrzxRlxyySXo1KkTZs2ahXPOOccTI3v27PG237ZtG84880ycdNJJmDFjBsaMGYMNGzbg0ksvze+XIoQQIgKJFSGEEHFNy5Ytcd9996FBgwa45557ULRoUU+8XHvttd46ppNt2bIFc+bM8bZ/4YUXPKHy6KOPonHjxt71N954AxMnTsSiRYvy++UIIYTwoZoVIYQQcU2LFi0yrhcuXBjly5dH8+bNM9YxzYts3LjRu/z55589YRKt/mXp0qVo2LDhcdlvIYQQh0diRQghRFyTnJyc6TZrXfzrnMtYenq6d7lr1y707NkTjz/+eJbnqlq16jHfXyGEELlHYkUIIURC0bp1a3zyySeoU6cOkpL0MyiEELGMalaEEEIkFDfddBO2bt2Kfv36Yfr06V7q19ixYz33sLS0tPzePSGEED4kVoQQQiQU1apVww8//OAJEzqFsb6F1sdlypRBoUL6WRRCiFgiEFQrYCGEEEIIIUQMoikkIYQQQgghREwisSKEEEIIIYSISSRWhBBCCCGEEDGJxIoQQgghhBAiJpFYEUIIIYQQQsQkEitCCCGEEEKImERiRQghhBBCCBGTSKwIIYQQQgghYhKJFSGEEEIIIURMIrEihBBCCCGEiEkkVoQQQgghhBCIRf4fb929LmCBm6wAAAAASUVORK5CYII=", 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" + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Sparse identification of FitzHugh–Nagumo dynamics\n", + "\n", + "This **deep-dive tutorial** walks through sparse drift inference for a FitzHugh–Nagumo (FHN) SDE.\n", + "\n", + "**Goal.** Given noisy observations of the state, recover the sparse structure of the drift $f(x)$ by expressing it as with the elements of a polynomial library $\\Theta\\,\\phi(x)$ and placing a **Laplace prior** on the coefficient matrix $\\Theta$. This is a Bayesian SINDy-style approach. We fit via **SVI with AutoDelta** (MAP estimation) and then compare the recovered coefficients and filtered trajectories against ground truth.\n", + "\n", + "**What is known.**\n", + "- Initial state distribution: $x_0 \\sim \\mathcal{N}(0, I)$.\n", + "- Observation operator $H$ (identity here, observing both states).\n", + "- Polynomial library $\\phi(x)$ (monomials up to degree 3).\n", + "\n", + "**What is inferred.**\n", + "- Drift coefficient matrix $\\Theta \\in \\mathbb{R}^{2 \\times 10}$ via MAP (Laplace prior promotes sparsity).\n", + "- Diffusion coefficient $\\sigma_x > 0$ (HalfNormal prior).\n", + "- Observation noise standard deviation $\\sigma_y > 0$ (HalfNormal prior)." ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "image/png": 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", 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" + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## FitzHugh–Nagumo Model\n", + "\n", + "### State SDE\n", + "\n", + "The state $x_t = (v_t, w_t)^\\top \\in \\mathbb{R}^2$ evolves as an Itô SDE:\n", + "\n", + "$$\n", + "dx_t = f(x_t)\\,dt + \\sigma_x\\,dW_t,\n", + "$$\n", + "\n", + "where $W_t$ is a standard 2-dimensional Brownian motion and the true drift is\n", + "\n", + "$$\n", + "f(x) = \\begin{pmatrix} v - \\tfrac{1}{3}v^3 - w + I \\\\ a\\,(v + b - c\\,w) \\end{pmatrix}.\n", + "$$\n", + "\n", + "Parameters are fixed at $a = 0.08$, $b = 0.7$, $c = 0.8$, $I = 0.5$. The true noise values used to generate data are $\\sigma_x = 0.01$ and $\\sigma_y = 0.1$, but **both are treated as unknown during inference**.\n", + "\n", + "### Observation process\n", + "\n", + "Observations are collected at discrete times $t_1 < t_2 < \\cdots < t_n$:\n", + "\n", + "$$\n", + "y_k = H\\,x_{t_k} + \\varepsilon_k, \\qquad \\varepsilon_k \\sim \\mathcal{N}(0,\\,\\sigma_y^2 I),\n", + "$$\n", + "\n", + "where $H = I_2$ (both states observed).\n", + "\n", + "### Initial condition\n", + "\n", + "$$\n", + "x_0 \\sim \\mathcal{N}(0, I_2).\n", + "$$\n", + "\n", + "### Inferred quantities\n", + "\n", + "We do **not** know $f$, $\\sigma_x$, or $\\sigma_y$. We parameterise the drift as\n", + "\n", + "$$\n", + "f(x) \\approx \\Theta\\,\\phi(x),\n", + "$$\n", + "\n", + "where $\\phi(x) \\in \\mathbb{R}^{10}$ is a polynomial library (all monomials in $v, w$ up to degree 3). The full set of inferred quantities and their priors is:\n", + "\n", + "$$\n", + "\\Theta \\sim \\mathrm{Laplace}(0,\\; 0.1) \\quad \\text{(promotes sparsity)},\n", + "$$\n", + "$$\n", + "\\sigma_x \\sim \\mathrm{HalfNormal}(0.1), \\qquad \\sigma_y \\sim \\mathrm{HalfNormal}(0.5).\n", + "$$\n", + "\n", + "All three are inferred jointly via MAP (SVI with AutoDelta)." ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, axes = plt.subplots(2, 1, figsize=(8, 5), sharex=True, constrained_layout=True)\n", - "axes[0].plot(times_1d, states[:, 0], label=\"$v$ (state)\", color=\"C0\")\n", - "axes[0].plot(times_1d, obs_values[:, 0], linestyle=\"--\", alpha=0.8, label=\"$v$ (obs)\", color=\"C0\")\n", - "axes[0].set_ylabel(\"$v$\")\n", - "axes[0].legend(loc=\"upper right\")\n", - "axes[0].grid(True, alpha=0.3)\n", - "axes[1].plot(times_1d, states[:, 1], label=\"$w$ (state)\", color=\"C1\")\n", - "if observation_dim >= 2:\n", - " axes[1].plot(times_1d, obs_values[:, 1], linestyle=\"--\", alpha=0.8, label=\"$w$ (obs)\", color=\"C1\")\n", - "axes[1].set_ylabel(\"$w$\")\n", - "axes[1].set_xlabel(\"Time\")\n", - "axes[1].legend(loc=\"upper right\")\n", - "axes[1].grid(True, alpha=0.3)\n", - "fig.suptitle(f\"Generated data (observation_dim={observation_dim}): states and observations\")\n", - "plt.show()\n", - "\n", - "fig, ax = plt.subplots(figsize=(5, 5), constrained_layout=True)\n", - "ax.plot(states[:, 0], states[:, 1], color=\"C0\", label=\"Latent state\", linewidth=1.5)\n", - "if observation_dim == 1:\n", - " ax.scatter(obs_values[:, 0], jnp.zeros_like(obs_values[:, 0]), s=8, alpha=0.6, color=\"C1\", label=\"Observations (v)\")\n", - "else:\n", - " ax.scatter(obs_values[:, 0], obs_values[:, 1], s=8, alpha=0.6, color=\"C1\", label=\"Observations\")\n", - "ax.set_xlabel(\"$v$\")\n", - "ax.set_ylabel(\"$w$\")\n", - "ax.set_title(f\"Phase space (observation_dim={observation_dim})\")\n", - "ax.legend()\n", - "ax.grid(True, alpha=0.3)\n", - "ax.set_aspect(\"equal\")\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Polynomial library and true coefficients\n", - "\n", - "Library terms (monomials in $v$, $w$): $1$, $v$, $w$, $v^2$, $vw$, $w^2$, $v^3$, $v^2w$, $vw^2$, $w^3$. The true FHN drift uses only a subset. We build the coefficient matrix $\\Theta \\in \\mathbb{R}^{2 \\times 10}$ so that $f(x) = \\Theta\\,\\phi(x)$." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "True coefficient matrix (rows: dv, dw; cols: library terms):\n", - "[[ 0.5 1. -1. 0. 0. 0. -0.3333 0. 0.\n", - " 0. ]\n", - " [ 0.056 0.08 -0.064 0. 0. 0. 0. 0. 0.\n", - " 0. ]]\n" - ] - } - ], - "source": [ - "TERM_NAMES = [\"1\", \"v\", \"w\", \"v²\", \"vw\", \"w²\", \"v³\", \"v²w\", \"vw²\", \"w³\"]\n", - "N_TERMS = len(TERM_NAMES)\n", - "\n", - "\n", - "def monomials(x):\n", - " \"\"\"Evaluate polynomial basis at state x = (v, w). Returns (N_TERMS,).\"\"\"\n", - " v, w = x[0], x[1]\n", - " return jnp.array([\n", - " 1.0, v, w, v**2, v * w, w**2, v**3, v**2 * w, v * w**2, w**3,\n", - " ])\n", - "\n", - "\n", - "# True coefficient matrix (state_dim x N_TERMS) for FHN: dv = v - v³/3 - w + I, dw = _a*(v + _b - _c*w)\n", - "true_Theta = jnp.zeros((state_dim, N_TERMS))\n", - "true_Theta = true_Theta.at[0, 0].set(_I) # 1\n", - "true_Theta = true_Theta.at[0, 1].set(1.0) # v\n", - "true_Theta = true_Theta.at[0, 2].set(-1.0) # w\n", - "true_Theta = true_Theta.at[0, 6].set(-1.0 / 3) # v³\n", - "true_Theta = true_Theta.at[1, 0].set(_a * _b) # 1\n", - "true_Theta = true_Theta.at[1, 1].set(_a) # v\n", - "true_Theta = true_Theta.at[1, 2].set(-_a * _c) # w\n", - "\n", - "print(\"True coefficient matrix (rows: dv, dw; cols: library terms):\")\n", - "print(jnp.round(true_Theta, 4))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Model discovery" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Build a Dynestyx SDE model that jointly infers:\n", - "- $\\Theta$ — drift coefficients with a sparsifying Laplace prior,\n", - "- $\\sigma_x$ — diffusion coefficient with a HalfNormal prior,\n", - "- $\\sigma_y$ — observation noise std with a HalfNormal prior.\n", - "\n", - "The observation model and state evolution are constructed inside the model function so that the sampled $\\sigma_x$ and $\\sigma_y$ flow through to the likelihood." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "def model_with_polynomial_drift(obs_times=None, obs_values=None):\n", - " # Theta ~ Laplace(0, 0.1) iid for each entry in R^{2 x 10}\n", - " # Laplace prior promotes sparsity: entries not supported by data shrink toward 0\n", - " Theta = numpyro.sample(\n", - " \"Theta\",\n", - " dist.Laplace(0.0, 0.1).expand([state_dim, N_TERMS]).to_event(2),\n", - " )\n", - "\n", - " # sigma_x ~ HalfNormal(0.1) — diffusion coefficient in dx = f(x) dt + sigma_x dW_t\n", - " sigma_x = numpyro.sample(\"sigma_x\", dist.HalfNormal(0.1))\n", - "\n", - " # sigma_y ~ HalfNormal(0.5) — per-component std in y_k = H x_{t_k} + N(0, sigma_y^2 I)\n", - " sigma_y = numpyro.sample(\"sigma_y\", dist.HalfNormal(0.5))\n", - "\n", - " # f(x) = Theta phi(x) approximates the unknown drift\n", - " def drift(x, u, t):\n", - " phi = monomials(x) # phi(x) in R^{N_TERMS}\n", - " return Theta @ phi # R^{state_dim}\n", - "\n", - " # Full model: dx = Theta phi(x) dt + sigma_x dW_t, y_k = H x_{t_k} + N(0, sigma_y^2 I)\n", - " return dsx.sample(\"f\", DynamicalModel(\n", - " state_evolution=make_state_evolution(drift, diffusion_coeff=sigma_x),\n", - " observation_model=LinearGaussianObservation(\n", - " H=H_obs,\n", - " R=sigma_y**2 * jnp.eye(observation_dim),\n", - " ),\n", - " **initial_condition_kwargs,\n", - " ), obs_times=obs_times, obs_values=obs_values)\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Build the conditioned model via filtering + data conditioning" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [], - "source": [ - "def data_conditioned_model(obs_times=None, obs_values=None):\n", - " with Filter():\n", - " return model_with_polynomial_drift(obs_times=obs_times, obs_values=obs_values)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Run SVI for MAP estimation..." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import jax.numpy as jnp\n", + "import jax.random as jr\n", + "import numpyro\n", + "import numpyro.distributions as dist\n", + "from numpyro.infer import SVI, Trace_ELBO, Predictive\n", + "from numpyro.infer.autoguide import AutoDelta\n", + "\n", + "import dynestyx as dsx\n", + "from dynestyx import (\n", + " ContinuousTimeStateEvolution,\n", + " DynamicalModel,\n", + " Filter,\n", + " LinearGaussianObservation,\n", + " ScalarDiffusion,\n", + " SDESimulator,\n", + ")\n", + "\n", + "import matplotlib.pyplot as plt\n" + ] + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 4000/4000 [27:25<00:00, 2.43it/s, init loss: 766.3178, avg. loss [3801-4000]: -911.7092]" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## True system\n", + "\n", + "Define the true FitzHugh–Nagumo drift. We will later build the full DynamicalModel by piping in this drift and spreading shared arguments from a dict." + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Inferred sigma_x = 0.0094 (true = 0.0100)\n", - "Inferred sigma_y = 0.0955 (true = 0.1000)\n" - ] + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# FitzHugh–Nagumo parameters\n", + "_a, _b, _c, _I = 0.08, 0.7, 0.8, 0.5\n", + "\n", + "def fitzhugh_nagumo_drift(x):\n", + " v, w = x[0], x[1]\n", + " dv = v - (1/3) * v**3 - w + _I\n", + " dw = _a * (v + _b - _c * w)\n", + " return jnp.array([dv, dw])\n", + "\n", + "state_dim = 2" + ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "# Note that we get \"close\" to a good model within 1000 steps, but the last 3000 steps are needed to get a high-fidelity final MAP estimate here.\n", - "num_steps = 4000\n", - "optimizer = numpyro.optim.Adam(step_size=1e-2)\n", - "guide = AutoDelta(data_conditioned_model)\n", - "svi = SVI(data_conditioned_model, guide, optimizer, loss=Trace_ELBO())\n", - "svi_result = svi.run(k_svi, num_steps=num_steps, obs_times=obs_times, obs_values=obs_values)\n", - "\n", - "median = guide.median(svi_result.params)\n", - "Theta_inferred = median[\"Theta\"] # (state_dim, N_TERMS)\n", - "sigma_x_inferred = float(median[\"sigma_x\"]) # scalar\n", - "sigma_y_inferred = float(median[\"sigma_y\"]) # scalar\n", - "\n", - "print(f\"Inferred sigma_x = {sigma_x_inferred:.4f} (true = {sigma_x_true:.4f})\")\n", - "print(f\"Inferred sigma_y = {sigma_y_inferred:.4f} (true = {sigma_y_true:.4f})\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### SVI loss curve\n", - "\n", - "The negative ELBO decreases as the MAP estimate is refined." - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Model configuration\n", + "\n", + "Constants used for data generation and inference setup.\n", + "\n", + "| Symbol | Role | Value | Status |\n", + "|---|---|---|---|\n", + "| $\\sigma_x^{\\mathrm{true}}$ | true diffusion coefficient (data generation only) | `0.01` | **inferred** |\n", + "| $\\sigma_y^{\\mathrm{true}}$ | true observation noise std (data generation only) | `0.1` | **inferred** |\n", + "| $x_0 \\sim \\mathcal{N}(0, I_2)$ | initial state prior | covariance = `I` | known |\n", + "| $\\Delta t$ | observation spacing | `0.1` | known |\n", + "| $T$ | total time span | `[0, 50)` | known |" + ] + }, { - "data": { - "image/png": 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", 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" + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# True values used ONLY for data generation — both are inferred during model discovery\n", + "sigma_x_true = 0.01 # true diffusion coefficient\n", + "sigma_y_true = 0.1 # true observation noise std\n", + "\n", + "# observation times t_1, ..., t_n (spacing Delta_t = 0.1, span [0, 50))\n", + "obs_times = jnp.arange(0.0, 50.0, 0.1)\n", + "\n", + "observation_dim = 2 # observation_dim=1 also works (observe only v)\n", + "\n", + "key = jr.PRNGKey(0)\n", + "key, k_data, k_svi, k_nuts, k_filter = jr.split(key, 5)" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(6, 3), constrained_layout=True)\n", - "ax.plot(svi_result.losses, color=\"C0\", label=\"SVI (AutoDelta MAP)\")\n", - "ax.set_yscale(\"symlog\")\n", - "ax.set_xscale(\"log\")\n", - "ax.set_xlabel(\"Step\")\n", - "ax.set_ylabel(\"Loss (negative ELBO)\")\n", - "ax.set_title(f\"SVI loss (observation_dim={observation_dim})\")\n", - "ax.legend()\n", - "ax.grid(True, alpha=0.3)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Parameter recovery\n", - "\n", - "Compare true vs inferred values for all inferred quantities:\n", - "- **Drift coefficients** $\\Theta$: side-by-side heatmaps (red = positive, blue = negative). The Laplace prior shrinks unused terms toward zero, recovering the sparse structure.\n", - "- **Noise scales** $\\sigma_x$, $\\sigma_y$: bar chart comparing inferred MAP values against the ground truth used for data generation." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ + }, { - "data": { - "image/png": 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", - "text/plain": [ - "
" + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## DynamicalModel construction helpers\n", + "\n", + "The Dynestyx `DynamicalModel` needs three pieces:\n", + "\n", + "- **Initial condition** — $x_0 \\sim \\mathcal{N}(0, I_2)$. Fixed; collected in `initial_condition_kwargs`.\n", + "- **Observation model** — $y_k = H\\,x_{t_k} + \\varepsilon_k$ with $\\varepsilon_k \\sim \\mathcal{N}(0, \\sigma_y^2 I_2)$. Constructed inside each model function because $\\sigma_y$ is inferred.\n", + "- **State evolution** — wraps the drift $f$ and the diffusion $\\sigma_x I_2$. Constructed inside each model function because $\\sigma_x$ is inferred.\n", + "\n", + "`make_state_evolution(drift_fn, diffusion_coeff)` is a helper that accepts whichever diffusion coefficient (true or inferred) is provided." ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "vmax = max(float(jnp.abs(true_Theta).max()), float(jnp.abs(Theta_inferred).max())) * 1.1\n", - "\n", - "fig, axes = plt.subplots(1, 2, figsize=(10, 4), sharey=True, constrained_layout=True)\n", - "\n", - "im0 = axes[0].imshow(\n", - " jnp.asarray(true_Theta),\n", - " cmap=\"RdBu_r\",\n", - " aspect=\"auto\",\n", - " vmin=-vmax,\n", - " vmax=vmax,\n", - ")\n", - "axes[0].set_xticks(range(N_TERMS))\n", - "axes[0].set_xticklabels(TERM_NAMES, rotation=45, ha=\"right\", fontsize=11)\n", - "axes[0].set_yticks([0, 1])\n", - "axes[0].set_yticklabels([r\"$\\dot{v}$\", r\"$\\dot{w}$\"], fontsize=12)\n", - "axes[0].set_title(\"True coefficients\")\n", - "axes[0].set_xlabel(\"Polynomial term\")\n", - "\n", - "im1 = axes[1].imshow(\n", - " jnp.asarray(Theta_inferred),\n", - " cmap=\"RdBu_r\",\n", - " aspect=\"auto\",\n", - " vmin=-vmax,\n", - " vmax=vmax,\n", - ")\n", - "axes[1].set_xticks(range(N_TERMS))\n", - "axes[1].set_xticklabels(TERM_NAMES, rotation=45, ha=\"right\", fontsize=11)\n", - "axes[1].set_yticks([0, 1])\n", - "axes[1].set_yticklabels([r\"$\\dot{v}$\", r\"$\\dot{w}$\"], fontsize=12)\n", - "axes[1].set_title(\"Inferred (MAP)\")\n", - "axes[1].set_xlabel(\"Polynomial term\")\n", - "\n", - "cbar = fig.colorbar(im1, ax=axes, shrink=0.6, aspect=20)\n", - "cbar.set_label(\"Coefficient value\", fontsize=11)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ + }, { - "data": { - "image/png": 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", - "text/plain": [ - "
" + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "# H in y_k = H x_{t_k} + eps_k (identity: observe all states)\n", + "H_obs = jnp.eye(observation_dim, state_dim)\n", + "\n", + "# Only the initial condition is shared and fixed; observation model and state\n", + "# evolution are constructed inside each model function because sigma_x and sigma_y\n", + "# are inferred.\n", + "initial_condition_kwargs = dict(\n", + " # x_0 ~ N(0, I_2)\n", + " initial_condition=dist.MultivariateNormal(\n", + " loc=jnp.zeros(state_dim),\n", + " covariance_matrix=jnp.eye(state_dim),\n", + " ),\n", + ")\n", + "\n", + "\n", + "from cd_dynamax import adjust_rhs\n", + "\n", + "def make_state_evolution(drift_fn, diffusion_coeff):\n", + " \"\"\"Wrap a drift f(x,u,t) into a ContinuousTimeStateEvolution.\n", + "\n", + " diffusion_coeff: scalar sigma_x in dx = f(x) dt + sigma_x dW_t.\n", + " adjust_rhs clips state and derivatives to [-100,100] / [-1000,1000]\n", + " to prevent SDE solver blow-up.\n", + " \"\"\"\n", + " return ContinuousTimeStateEvolution(\n", + " drift=lambda x, u, t: adjust_rhs(x, drift_fn(x, u, t)),\n", + " # sigma_x I_2 (isotropic, constant diffusion)\n", + " diffusion=ScalarDiffusion(diffusion_coeff, bm_dim=state_dim),\n", + " )\n" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "name": "stdout", - "output_type": "stream", - "text": [ - " sigma_x: true=0.0100, inferred=0.0094, relative error=5.8%\n", - " sigma_y: true=0.1000, inferred=0.0955, relative error=4.5%\n" - ] - } - ], - "source": [ - "labels = [r\"$\\sigma_x$ (diffusion)\", r\"$\\sigma_y$ (obs noise)\"]\n", - "truths = [sigma_x_true, sigma_y_true]\n", - "inferred = [sigma_x_inferred, sigma_y_inferred]\n", - "\n", - "x = range(len(labels))\n", - "width = 0.35\n", - "\n", - "fig, ax = plt.subplots(figsize=(5, 3.5), constrained_layout=True)\n", - "bars_true = ax.bar([v - width/2 for v in x], truths, width, label=\"True\", color=\"C2\", alpha=0.8)\n", - "bars_inf = ax.bar([v + width/2 for v in x], inferred, width, label=\"Inferred (MAP)\", color=\"C0\", alpha=0.8)\n", - "\n", - "# Annotate bar tops with values\n", - "for bar in bars_true:\n", - " ax.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.001,\n", - " f\"{bar.get_height():.4f}\", ha=\"center\", va=\"bottom\", fontsize=9)\n", - "for bar in bars_inf:\n", - " ax.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.001,\n", - " f\"{bar.get_height():.4f}\", ha=\"center\", va=\"bottom\", fontsize=9)\n", - "\n", - "ax.set_xticks(list(x))\n", - "ax.set_xticklabels(labels, fontsize=11)\n", - "ax.set_ylabel(\"Value\")\n", - "ax.set_title(\"Noise scale recovery: true vs inferred (MAP)\")\n", - "ax.legend()\n", - "ax.grid(True, axis=\"y\", alpha=0.3)\n", - "plt.show()\n", - "\n", - "# Relative errors\n", - "for name, t, i in zip([\"sigma_x\", \"sigma_y\"], truths, inferred):\n", - " rel_err = abs(i - t) / t * 100\n", - " print(f\" {name}: true={t:.4f}, inferred={i:.4f}, relative error={rel_err:.1f}%\")" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data generation\n", + "\n", + "We simulate from the **true** FHN drift using an SDE simulator. The model observes the state at `obs_times` with Gaussian noise." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "# Data generation: simulate dx_t = f_true(x_t) dt + sigma_x_true dW_t\n", + "# y_k = H x_{t_k} + N(0, sigma_y_true^2 I)\n", + "# Uses the true (known) noise values — these are NOT passed to the inference model.\n", + "def model_with_true_drift(obs_times=None, obs_values=None, predict_times=None):\n", + " return dsx.sample(\"f\", DynamicalModel(\n", + " state_evolution=make_state_evolution(\n", + " lambda x, u, t: fitzhugh_nagumo_drift(x),\n", + " diffusion_coeff=sigma_x_true,\n", + " ),\n", + " # y_k = H x_{t_k} + N(0, sigma_y_true^2 I)\n", + " observation_model=LinearGaussianObservation(\n", + " H=H_obs,\n", + " R=sigma_y_true**2 * jnp.eye(observation_dim),\n", + " ),\n", + " **initial_condition_kwargs,\n", + " ), obs_times=obs_times, obs_values=obs_values, predict_times=predict_times)\n", + "\n", + "predictive = Predictive(model_with_true_drift, num_samples=1, exclude_deterministic=False)\n", + "with SDESimulator():\n", + " synthetic = predictive(k_data, predict_times=obs_times)\n", + "\n", + "# (num_samples, n_sim, n_times, dim)\n", + "obs_values = synthetic[\"f_observations\"][0, 0] # y_k shape (n_obs, observation_dim)\n", + "states = synthetic[\"f_states\"][0, 0] # x_{t_k} shape (n_obs, state_dim)\n", + "times_1d = jnp.asarray(obs_times).squeeze()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Data visualization\n", + "\n", + "Time series of the latent state and noisy observations, and the phase-space trajectory." + ] + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/28/rfdjbzgj0bz_x56whkjmhl600000gn/T/ipykernel_65249/2550543806.py:38: UserWarning: Legend does not support handles for PatchCollection instances.\n", - "A proxy artist may be used instead.\n", - "See: https://matplotlib.org/stable/users/explain/axes/legend_guide.html#controlling-the-legend-entries\n", - " ax.legend(\n" - ] + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(2, 1, figsize=(8, 5), sharex=True, constrained_layout=True)\n", + "axes[0].plot(times_1d, states[:, 0], label=\"$v$ (state)\", color=\"C0\")\n", + "axes[0].plot(times_1d, obs_values[:, 0], linestyle=\"--\", alpha=0.8, label=\"$v$ (obs)\", color=\"C0\")\n", + "axes[0].set_ylabel(\"$v$\")\n", + "axes[0].legend(loc=\"upper right\")\n", + "axes[0].grid(True, alpha=0.3)\n", + "axes[1].plot(times_1d, states[:, 1], label=\"$w$ (state)\", color=\"C1\")\n", + "if observation_dim >= 2:\n", + " axes[1].plot(times_1d, obs_values[:, 1], linestyle=\"--\", alpha=0.8, label=\"$w$ (obs)\", color=\"C1\")\n", + "axes[1].set_ylabel(\"$w$\")\n", + "axes[1].set_xlabel(\"Time\")\n", + "axes[1].legend(loc=\"upper right\")\n", + "axes[1].grid(True, alpha=0.3)\n", + "fig.suptitle(f\"Generated data (observation_dim={observation_dim}): states and observations\")\n", + "plt.show()\n", + "\n", + "fig, ax = plt.subplots(figsize=(5, 5), constrained_layout=True)\n", + "ax.plot(states[:, 0], states[:, 1], color=\"C0\", label=\"Latent state\", linewidth=1.5)\n", + "if observation_dim == 1:\n", + " ax.scatter(obs_values[:, 0], jnp.zeros_like(obs_values[:, 0]), s=8, alpha=0.6, color=\"C1\", label=\"Observations (v)\")\n", + "else:\n", + " ax.scatter(obs_values[:, 0], obs_values[:, 1], s=8, alpha=0.6, color=\"C1\", label=\"Observations\")\n", + "ax.set_xlabel(\"$v$\")\n", + "ax.set_ylabel(\"$w$\")\n", + "ax.set_title(f\"Phase space (observation_dim={observation_dim})\")\n", + "ax.legend()\n", + "ax.grid(True, alpha=0.3)\n", + "ax.set_aspect(\"equal\")\n", + "plt.show()" + ] }, { - "data": { - "image/png": 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", - "text/plain": [ - "
" + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Polynomial library and true coefficients\n", + "\n", + "Library terms (monomials in $v$, $w$): $1$, $v$, $w$, $v^2$, $vw$, $w^2$, $v^3$, $v^2w$, $vw^2$, $w^3$. The true FHN drift uses only a subset. We build the coefficient matrix $\\Theta \\in \\mathbb{R}^{2 \\times 10}$ so that $f(x) = \\Theta\\,\\phi(x)$." ] - }, - "metadata": {}, - "output_type": "display_data" + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "True coefficient matrix (rows: dv, dw; cols: library terms):\n", + "[[ 0.5 1. -1. 0. 0. 0. -0.3333 0. 0.\n", + " 0. ]\n", + " [ 0.056 0.08 -0.064 0. 0. 0. 0. 0. 0.\n", + " 0. ]]\n" + ] + } + ], + "source": [ + "TERM_NAMES = [\"1\", \"v\", \"w\", \"v²\", \"vw\", \"w²\", \"v³\", \"v²w\", \"vw²\", \"w³\"]\n", + "N_TERMS = len(TERM_NAMES)\n", + "\n", + "\n", + "def monomials(x):\n", + " \"\"\"Evaluate polynomial basis at state x = (v, w). Returns (N_TERMS,).\"\"\"\n", + " v, w = x[0], x[1]\n", + " return jnp.array([\n", + " 1.0, v, w, v**2, v * w, w**2, v**3, v**2 * w, v * w**2, w**3,\n", + " ])\n", + "\n", + "\n", + "# True coefficient matrix (state_dim x N_TERMS) for FHN: dv = v - v³/3 - w + I, dw = _a*(v + _b - _c*w)\n", + "true_Theta = jnp.zeros((state_dim, N_TERMS))\n", + "true_Theta = true_Theta.at[0, 0].set(_I) # 1\n", + "true_Theta = true_Theta.at[0, 1].set(1.0) # v\n", + "true_Theta = true_Theta.at[0, 2].set(-1.0) # w\n", + "true_Theta = true_Theta.at[0, 6].set(-1.0 / 3) # v³\n", + "true_Theta = true_Theta.at[1, 0].set(_a * _b) # 1\n", + "true_Theta = true_Theta.at[1, 1].set(_a) # v\n", + "true_Theta = true_Theta.at[1, 2].set(-_a * _c) # w\n", + "\n", + "print(\"True coefficient matrix (rows: dv, dw; cols: library terms):\")\n", + "print(jnp.round(true_Theta, 4))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Model discovery" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Build a Dynestyx SDE model that jointly infers:\n", + "- $\\Theta$ — drift coefficients with a sparsifying Laplace prior,\n", + "- $\\sigma_x$ — diffusion coefficient with a HalfNormal prior,\n", + "- $\\sigma_y$ — observation noise std with a HalfNormal prior.\n", + "\n", + "The observation model and state evolution are constructed inside the model function so that the sampled $\\sigma_x$ and $\\sigma_y$ flow through to the likelihood." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "def model_with_polynomial_drift(obs_times=None, obs_values=None):\n", + " # Theta ~ Laplace(0, 0.1) iid for each entry in R^{2 x 10}\n", + " # Laplace prior promotes sparsity: entries not supported by data shrink toward 0\n", + " Theta = numpyro.sample(\n", + " \"Theta\",\n", + " dist.Laplace(0.0, 0.1).expand([state_dim, N_TERMS]).to_event(2),\n", + " )\n", + "\n", + " # sigma_x ~ HalfNormal(0.1) — diffusion coefficient in dx = f(x) dt + sigma_x dW_t\n", + " sigma_x = numpyro.sample(\"sigma_x\", dist.HalfNormal(0.1))\n", + "\n", + " # sigma_y ~ HalfNormal(0.5) — per-component std in y_k = H x_{t_k} + N(0, sigma_y^2 I)\n", + " sigma_y = numpyro.sample(\"sigma_y\", dist.HalfNormal(0.5))\n", + "\n", + " # f(x) = Theta phi(x) approximates the unknown drift\n", + " def drift(x, u, t):\n", + " phi = monomials(x) # phi(x) in R^{N_TERMS}\n", + " return Theta @ phi # R^{state_dim}\n", + "\n", + " # Full model: dx = Theta phi(x) dt + sigma_x dW_t, y_k = H x_{t_k} + N(0, sigma_y^2 I)\n", + " return dsx.sample(\"f\", DynamicalModel(\n", + " state_evolution=make_state_evolution(drift, diffusion_coeff=sigma_x),\n", + " observation_model=LinearGaussianObservation(\n", + " H=H_obs,\n", + " R=sigma_y**2 * jnp.eye(observation_dim),\n", + " ),\n", + " **initial_condition_kwargs,\n", + " ), obs_times=obs_times, obs_values=obs_values)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Build the conditioned model via filtering + data conditioning" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "def data_conditioned_model(obs_times=None, obs_values=None):\n", + " with Filter():\n", + " return model_with_polynomial_drift(obs_times=obs_times, obs_values=obs_values)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Run SVI for MAP estimation..." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 4000/4000 [27:25<00:00, 2.43it/s, init loss: 766.3178, avg. loss [3801-4000]: -911.7092]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Inferred sigma_x = 0.0094 (true = 0.0100)\n", + "Inferred sigma_y = 0.0955 (true = 0.1000)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "# Note that we get \"close\" to a good model within 1000 steps, but the last 3000 steps are needed to get a high-fidelity final MAP estimate here.\n", + "num_steps = 4000\n", + "optimizer = numpyro.optim.Adam(step_size=1e-2)\n", + "guide = AutoDelta(data_conditioned_model)\n", + "svi = SVI(data_conditioned_model, guide, optimizer, loss=Trace_ELBO())\n", + "svi_result = svi.run(k_svi, num_steps=num_steps, obs_times=obs_times, obs_values=obs_values)\n", + "\n", + "median = guide.median(svi_result.params)\n", + "Theta_inferred = median[\"Theta\"] # (state_dim, N_TERMS)\n", + "sigma_x_inferred = float(median[\"sigma_x\"]) # scalar\n", + "sigma_y_inferred = float(median[\"sigma_y\"]) # scalar\n", + "\n", + "print(f\"Inferred sigma_x = {sigma_x_inferred:.4f} (true = {sigma_x_true:.4f})\")\n", + "print(f\"Inferred sigma_y = {sigma_y_inferred:.4f} (true = {sigma_y_true:.4f})\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### SVI loss curve\n", + "\n", + "The negative ELBO decreases as the MAP estimate is refined." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(6, 3), constrained_layout=True)\n", + "ax.plot(svi_result.losses, color=\"C0\", label=\"SVI (AutoDelta MAP)\")\n", + "ax.set_yscale(\"symlog\")\n", + "ax.set_xscale(\"log\")\n", + "ax.set_xlabel(\"Step\")\n", + "ax.set_ylabel(\"Loss (negative ELBO)\")\n", + "ax.set_title(f\"SVI loss (observation_dim={observation_dim})\")\n", + "ax.legend()\n", + "ax.grid(True, alpha=0.3)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parameter recovery\n", + "\n", + "Compare true vs inferred values for all inferred quantities:\n", + "- **Drift coefficients** $\\Theta$: side-by-side heatmaps (red = positive, blue = negative). The Laplace prior shrinks unused terms toward zero, recovering the sparse structure.\n", + "- **Noise scales** $\\sigma_x$, $\\sigma_y$: bar chart comparing inferred MAP values against the ground truth used for data generation." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "vmax = max(float(jnp.abs(true_Theta).max()), float(jnp.abs(Theta_inferred).max())) * 1.1\n", + "\n", + "fig, axes = plt.subplots(1, 2, figsize=(10, 4), sharey=True, constrained_layout=True)\n", + "\n", + "im0 = axes[0].imshow(\n", + " jnp.asarray(true_Theta),\n", + " cmap=\"RdBu_r\",\n", + " aspect=\"auto\",\n", + " vmin=-vmax,\n", + " vmax=vmax,\n", + ")\n", + "axes[0].set_xticks(range(N_TERMS))\n", + "axes[0].set_xticklabels(TERM_NAMES, rotation=45, ha=\"right\", fontsize=11)\n", + "axes[0].set_yticks([0, 1])\n", + "axes[0].set_yticklabels([r\"$\\dot{v}$\", r\"$\\dot{w}$\"], fontsize=12)\n", + "axes[0].set_title(\"True coefficients\")\n", + "axes[0].set_xlabel(\"Polynomial term\")\n", + "\n", + "im1 = axes[1].imshow(\n", + " jnp.asarray(Theta_inferred),\n", + " cmap=\"RdBu_r\",\n", + " aspect=\"auto\",\n", + " vmin=-vmax,\n", + " vmax=vmax,\n", + ")\n", + "axes[1].set_xticks(range(N_TERMS))\n", + "axes[1].set_xticklabels(TERM_NAMES, rotation=45, ha=\"right\", fontsize=11)\n", + "axes[1].set_yticks([0, 1])\n", + "axes[1].set_yticklabels([r\"$\\dot{v}$\", r\"$\\dot{w}$\"], fontsize=12)\n", + "axes[1].set_title(\"Inferred (MAP)\")\n", + "axes[1].set_xlabel(\"Polynomial term\")\n", + "\n", + "cbar = fig.colorbar(im1, ax=axes, shrink=0.6, aspect=20)\n", + "cbar.set_label(\"Coefficient value\", fontsize=11)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " sigma_x: true=0.0100, inferred=0.0094, relative error=5.8%\n", + " sigma_y: true=0.1000, inferred=0.0955, relative error=4.5%\n" + ] + } + ], + "source": [ + "labels = [r\"$\\sigma_x$ (diffusion)\", r\"$\\sigma_y$ (obs noise)\"]\n", + "truths = [sigma_x_true, sigma_y_true]\n", + "inferred = [sigma_x_inferred, sigma_y_inferred]\n", + "\n", + "x = range(len(labels))\n", + "width = 0.35\n", + "\n", + "fig, ax = plt.subplots(figsize=(5, 3.5), constrained_layout=True)\n", + "bars_true = ax.bar([v - width/2 for v in x], truths, width, label=\"True\", color=\"C2\", alpha=0.8)\n", + "bars_inf = ax.bar([v + width/2 for v in x], inferred, width, label=\"Inferred (MAP)\", color=\"C0\", alpha=0.8)\n", + "\n", + "# Annotate bar tops with values\n", + "for bar in bars_true:\n", + " ax.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.001,\n", + " f\"{bar.get_height():.4f}\", ha=\"center\", va=\"bottom\", fontsize=9)\n", + "for bar in bars_inf:\n", + " ax.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.001,\n", + " f\"{bar.get_height():.4f}\", ha=\"center\", va=\"bottom\", fontsize=9)\n", + "\n", + "ax.set_xticks(list(x))\n", + "ax.set_xticklabels(labels, fontsize=11)\n", + "ax.set_ylabel(\"Value\")\n", + "ax.set_title(\"Noise scale recovery: true vs inferred (MAP)\")\n", + "ax.legend()\n", + "ax.grid(True, axis=\"y\", alpha=0.3)\n", + "plt.show()\n", + "\n", + "# Relative errors\n", + "for name, t, i in zip([\"sigma_x\", \"sigma_y\"], truths, inferred):\n", + " rel_err = abs(i - t) / t * 100\n", + " print(f\" {name}: true={t:.4f}, inferred={i:.4f}, relative error={rel_err:.1f}%\")" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/28/rfdjbzgj0bz_x56whkjmhl600000gn/T/ipykernel_65249/2550543806.py:38: UserWarning: Legend does not support handles for PatchCollection instances.\n", + "A proxy artist may be used instead.\n", + "See: https://matplotlib.org/stable/users/explain/axes/legend_guide.html#controlling-the-legend-entries\n", + " ax.legend(\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "result = Predictive(\n", + " data_conditioned_model,\n", + " params={\"Theta\": Theta_inferred},\n", + " num_samples=1,\n", + " exclude_deterministic=False,\n", + ")(k_filter, obs_times=obs_times, obs_values=obs_values)\n", + "\n", + "filtered_mean = jnp.squeeze(result[\"f_filtered_states_mean\"], axis=0) # (T+1, 2)\n", + "filtered_cov_diag = jnp.squeeze(result[\"f_filtered_states_cov_diag\"], axis=0) # (T+1, 2)\n", + "filtered_std = jnp.sqrt(jnp.maximum(filtered_cov_diag, 1e-10))\n", + "\n", + "# Align lengths: filter may return T+1 (includes prior at t0)\n", + "n = min(len(times_1d), filtered_mean.shape[0])\n", + "t_plot = times_1d[:n]\n", + "fm = filtered_mean[:n]\n", + "fs = filtered_std[:n]\n", + "st = states[:n]\n", + "obs = obs_values[:n]\n", + "\n", + "from matplotlib.patches import Ellipse, Rectangle\n", + "from matplotlib.collections import PatchCollection\n", + "\n", + "fig, ax = plt.subplots(figsize=(7, 6), constrained_layout=True)\n", + "\n", + "# 1-sigma uncertainty ellipses at each timepoint.\n", + "# Covariance is diagonal, so ellipses are axis-aligned:\n", + "# semi-axis along v = fs[i, 0], semi-axis along w = fs[i, 1].\n", + "ellipses = [\n", + " Ellipse(xy=(fm[i, 0], fm[i, 1]), width=2 * fs[i, 0], height=2 * fs[i, 1])\n", + " for i in range(len(fm))\n", + "]\n", + "ec = PatchCollection(ellipses, facecolor=\"C0\", edgecolor=\"none\", alpha=0.07)\n", + "ax.add_collection(ec)\n", + "\n", + "ax.plot(st[:, 0], st[:, 1], \"k-\", label=\"True state\", linewidth=1.5, alpha=0.9)\n", + "ax.scatter(obs[:, 0], obs[:, 1], s=4, c=\"C1\", alpha=0.6, label=\"Noisy observations\")\n", + "ax.plot(fm[:, 0], fm[:, 1], \"C0-\", label=\"Filtered mean\", linewidth=1.2)\n", + "ax.legend(\n", + " handles=[\n", + " ax.lines[-1], # filtered mean line\n", + " ax.collections[-2], # noisy obs scatter\n", + " ax.lines[0], # true state line\n", + " Rectangle((0, 0), 1, 1, facecolor=\"C0\", alpha=0.35), # proxy for ellipses\n", + " ],\n", + " labels=[\"Filtered mean\", \"Noisy observations\", \"True state\", \"Filtered 1σ ellipses\"],\n", + " loc=\"upper right\", fontsize=9,\n", + ")\n", + "\n", + "ax.set_xlabel(\"$v$\")\n", + "ax.set_ylabel(\"$w$\")\n", + "ax.set_title(\"Phase space: true state, noisy data, filtering distribution (mean ± 1σ)\")\n", + "ax.grid(True, alpha=0.3)\n", + "ax.set_aspect(\"equal\")\n", + "ax.autoscale_view()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv (3.12.11)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" } - ], - "source": [ - "result = Predictive(\n", - " data_conditioned_model,\n", - " params={\"Theta\": Theta_inferred},\n", - " num_samples=1,\n", - " exclude_deterministic=False,\n", - ")(k_filter, obs_times=obs_times, obs_values=obs_values)\n", - "\n", - "filtered_mean = jnp.squeeze(result[\"f_filtered_states_mean\"], axis=0) # (T+1, 2)\n", - "filtered_cov_diag = jnp.squeeze(result[\"f_filtered_states_cov_diag\"], axis=0) # (T+1, 2)\n", - "filtered_std = jnp.sqrt(jnp.maximum(filtered_cov_diag, 1e-10))\n", - "\n", - "# Align lengths: filter may return T+1 (includes prior at t0)\n", - "n = min(len(times_1d), filtered_mean.shape[0])\n", - "t_plot = times_1d[:n]\n", - "fm = filtered_mean[:n]\n", - "fs = filtered_std[:n]\n", - "st = states[:n]\n", - "obs = obs_values[:n]\n", - "\n", - "from matplotlib.patches import Ellipse, Rectangle\n", - "from matplotlib.collections import PatchCollection\n", - "\n", - "fig, ax = plt.subplots(figsize=(7, 6), constrained_layout=True)\n", - "\n", - "# 1-sigma uncertainty ellipses at each timepoint.\n", - "# Covariance is diagonal, so ellipses are axis-aligned:\n", - "# semi-axis along v = fs[i, 0], semi-axis along w = fs[i, 1].\n", - "ellipses = [\n", - " Ellipse(xy=(fm[i, 0], fm[i, 1]), width=2 * fs[i, 0], height=2 * fs[i, 1])\n", - " for i in range(len(fm))\n", - "]\n", - "ec = PatchCollection(ellipses, facecolor=\"C0\", edgecolor=\"none\", alpha=0.07)\n", - "ax.add_collection(ec)\n", - "\n", - "ax.plot(st[:, 0], st[:, 1], \"k-\", label=\"True state\", linewidth=1.5, alpha=0.9)\n", - "ax.scatter(obs[:, 0], obs[:, 1], s=4, c=\"C1\", alpha=0.6, label=\"Noisy observations\")\n", - "ax.plot(fm[:, 0], fm[:, 1], \"C0-\", label=\"Filtered mean\", linewidth=1.2)\n", - "ax.legend(\n", - " handles=[\n", - " ax.lines[-1], # filtered mean line\n", - " ax.collections[-2], # noisy obs scatter\n", - " ax.lines[0], # true state line\n", - " Rectangle((0, 0), 1, 1, facecolor=\"C0\", alpha=0.35), # proxy for ellipses\n", - " ],\n", - " labels=[\"Filtered mean\", \"Noisy observations\", \"True state\", \"Filtered 1σ ellipses\"],\n", - " loc=\"upper right\", fontsize=9,\n", - ")\n", - "\n", - "ax.set_xlabel(\"$v$\")\n", - "ax.set_ylabel(\"$w$\")\n", - "ax.set_title(\"Phase space: true state, noisy data, filtering distribution (mean ± 1σ)\")\n", - "ax.grid(True, alpha=0.3)\n", - "ax.set_aspect(\"equal\")\n", - "ax.autoscale_view()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv (3.12.11)", - "language": "python", - "name": "python3" }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/docs/deep_dives/gp_drift.ipynb b/docs/deep_dives/gp_drift.ipynb index 65502fbd..9967f137 100644 --- a/docs/deep_dives/gp_drift.ipynb +++ b/docs/deep_dives/gp_drift.ipynb @@ -94,6 +94,7 @@ " ContinuousTimeStateEvolution,\n", " LinearGaussianObservation,\n", " Filter,\n", + " ScalarDiffusion,\n", " SDESimulator,\n", ")\n", "from dynestyx.diagnostics.plotting_utils import plot_drift_field\n", @@ -194,7 +195,7 @@ "def make_state_evolution(drift_fn):\n", " return ContinuousTimeStateEvolution(\n", " drift=drift_fn,\n", - " diffusion=dsx.FullDiffusion(diffusion_coeff * jnp.eye(state_dim)),\n", + " diffusion=ScalarDiffusion(diffusion_coeff, bm_dim=state_dim),\n", " )" ] }, diff --git a/docs/deep_dives/l63_speedup_dirac_vs_enkf.ipynb b/docs/deep_dives/l63_speedup_dirac_vs_enkf.ipynb index 052da46a..dae9208f 100644 --- a/docs/deep_dives/l63_speedup_dirac_vs_enkf.ipynb +++ b/docs/deep_dives/l63_speedup_dirac_vs_enkf.ipynb @@ -1,401 +1,402 @@ { - "cells": [ - { - "cell_type": "markdown", - "id": "intro", - "metadata": {}, - "source": [ - "# Speedups with full observations: \"Gradient-matching\" vs pseudo-marginal MCMC\n", - "\n", - "This tutorial compares two approaches for learning SDEs when we have **fully observed** states with **low observation noise** and **high-frequency measurements** (so observations approach exact state measurements, i.e. Dirac):\n", - "\n", - "1. **EnKF + NUTS** (filtering-based continuous-time): Uses `Filter` with EnKF to approximate the marginal likelihood, then NUTS for MCMC.\n", - "\n", - "1. **Gradient-matching**: Discretizes the SDE (Euler-Maruyama), treats observations as exact states (`DiracIdentityObservation`), and runs NUTS directly on all states and parameters. This avoids filtering entirely and is typically much faster. This approach loses accuracy when the following assumptions fail to hold:\n", - " - **Fully observed**: $y_t = x_t$ (or $y_t \\approx x_t$ with low noise)\n", - " - **Low noise**: $R = 0.01^2 I_3$ (approaches Dirac)\n", - " - **High-frequency**: $\\Delta t = 0.01$ over $[0, 20]$\n", - "\n", - "The speedup comes from data-conditioned independendence of the Euler-Maruyama increments induced by these assumptions---this independence allows us to vectorize (stack) all time-steps together and form a more traditional regression problem.\n", - "\n", - "\n", - "\n", - "We report timing and posteriors for both approaches." - ] - }, - { - "cell_type": "markdown", - "id": "setup", - "metadata": {}, - "source": [ - "## Setup and Model\n", - "\n", - "We use the Lorenz 63 system with:\n", - "- **Learn**: $\\rho \\sim \\mathcal{U}(10, 40)$" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "imports", - "metadata": {}, - "outputs": [], - "source": [ - "import time\n", - "\n", - "import jax.numpy as jnp\n", - "import jax.random as jr\n", - "import matplotlib.pyplot as plt\n", - "import numpyro\n", - "import numpyro.distributions as dist\n", - "from numpyro.infer import MCMC, NUTS, Predictive\n", - "\n", - "import dynestyx as dsx\n", - "from dynestyx import (\n", - " DynamicalModel,\n", - " ContinuousTimeStateEvolution,\n", - " DiracIdentityObservation,\n", - " LinearGaussianObservation,\n", - " DiscreteTimeSimulator,\n", - " Filter,\n", - " SDESimulator,\n", - " Discretizer,\n", - ")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "8b98a625", - "metadata": {}, - "outputs": [], - "source": [ - "def l63_fully_observed_model(dirac_observation: bool = False, obs_times=None, obs_values=None, predict_times=None):\n", - " \"\"\"Model that samples drift parameter rho and uses it in dynamics.\n", - " \n", - " Default is noisy Gaussian, full-state observations.\n", - " If `dirac_observation=True`, uses Dirac observations (y_t = x_t)\n", - " \n", - " \"\"\"\n", - " rho = numpyro.sample(\"rho\", dist.Uniform(10.0, 40.0))\n", - "\n", - " state_dim = 3\n", - " observation_dim = state_dim\n", - " observation_model = DiracIdentityObservation() if dirac_observation else LinearGaussianObservation(\n", - " H=jnp.eye(observation_dim, state_dim), R=jnp.eye(state_dim)\n", - " )\n", - " # Create the dynamical model with sampled rho\n", - " dynamics = DynamicalModel(\n", - " initial_condition=dist.MultivariateNormal(\n", - " loc=jnp.zeros(state_dim), covariance_matrix=20.0**2 * jnp.eye(state_dim)\n", - " ),\n", - " state_evolution=ContinuousTimeStateEvolution(\n", - " drift=lambda x, u, t: jnp.array(\n", - " [\n", - " 10.0 * (x[1] - x[0]),\n", - " x[0] * (rho - x[2]) - x[1],\n", - " x[0] * x[1] - (8.0 / 3.0) * x[2],\n", - " ]\n", - " ),\n", - " diffusion=dsx.FullDiffusion(jnp.eye(state_dim)),\n", - " ),\n", - " observation_model=observation_model,\n", - " )\n", - "\n", - " # Return a sampled dynamical model, named \"f\".\n", - " return dsx.sample(\n", - " \"f\",\n", - " dynamics,\n", - " obs_times=obs_times,\n", - " obs_values=obs_values,\n", - " predict_times=predict_times,\n", - " )\n" - ] - }, - { - "cell_type": "markdown", - "id": "data_gen", - "metadata": {}, - "source": [ - "## Generate Synthetic Data\n", - "\n", - "We simulate the L63 SDE and add small Gaussian noise to get observations. With low noise, these approach the true states." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "gen_data", - "metadata": {}, - "outputs": [ + "cells": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Observations shape: (2000, 3)\n", - "True rho: 28.0\n" - ] + "cell_type": "markdown", + "id": "intro", + "metadata": {}, + "source": [ + "# Speedups with full observations: \"Gradient-matching\" vs pseudo-marginal MCMC\n", + "\n", + "This tutorial compares two approaches for learning SDEs when we have **fully observed** states with **low observation noise** and **high-frequency measurements** (so observations approach exact state measurements, i.e. Dirac):\n", + "\n", + "1. **EnKF + NUTS** (filtering-based continuous-time): Uses `Filter` with EnKF to approximate the marginal likelihood, then NUTS for MCMC.\n", + "\n", + "1. **Gradient-matching**: Discretizes the SDE (Euler-Maruyama), treats observations as exact states (`DiracIdentityObservation`), and runs NUTS directly on all states and parameters. This avoids filtering entirely and is typically much faster. This approach loses accuracy when the following assumptions fail to hold:\n", + " - **Fully observed**: $y_t = x_t$ (or $y_t \\approx x_t$ with low noise)\n", + " - **Low noise**: $R = 0.01^2 I_3$ (approaches Dirac)\n", + " - **High-frequency**: $\\Delta t = 0.01$ over $[0, 20]$\n", + "\n", + "The speedup comes from data-conditioned independendence of the Euler-Maruyama increments induced by these assumptions---this independence allows us to vectorize (stack) all time-steps together and form a more traditional regression problem.\n", + "\n", + "\n", + "\n", + "We report timing and posteriors for both approaches." + ] }, { - "data": { - "image/png": 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", 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" + "cell_type": "markdown", + "id": "setup", + "metadata": {}, + "source": [ + "## Setup and Model\n", + "\n", + "We use the Lorenz 63 system with:\n", + "- **Learn**: $\\rho \\sim \\mathcal{U}(10, 40)$" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "true_rho = 28.0\n", - "obs_times = jnp.arange(start=0.0, stop=20.0, step=0.01) # high-frequency\n", - "rng_key = jr.PRNGKey(0)\n", - "data_init_key, data_solver_key, mcmc_key = jr.split(rng_key, 3)\n", - "\n", - "true_params = {\"rho\": jnp.array(true_rho)}\n", - "predictive = Predictive(\n", - " l63_fully_observed_model,\n", - " params=true_params,\n", - " num_samples=1,\n", - " exclude_deterministic=False,\n", - ")\n", - "\n", - "with SDESimulator():\n", - " synthetic = predictive(data_init_key, predict_times=obs_times)\n", - "\n", - "# f_observations / f_states: (num_samples, n_sim, T, ...)\n", - "obs_values = synthetic[\"f_observations\"][0, 0] # (T, 3)\n", - "states = synthetic[\"f_states\"][0, 0] # (T, 3)\n", - "\n", - "print(f\"Observations shape: {obs_values.shape}\")\n", - "print(f\"True rho: {true_rho}\")\n", - "\n", - "# plot the data\n", - "obs_t = jnp.asarray(obs_times).squeeze()\n", - "for i, label in enumerate([\"x\", \"y\", \"z\"]):\n", - " plt.plot(obs_t, jnp.asarray(obs_values)[:, i], label=label)\n", - "plt.xlabel(\"Time\")\n", - "plt.ylabel(\"State\")\n", - "plt.legend()\n", - "plt.title(\"L63 synthetic data (fully observed, low noise)\")\n", - "plt.tight_layout()\n", - "plt.show()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "956a8401", - "metadata": {}, - "outputs": [], - "source": [ - "num_samples = 100\n", - "num_warmup = 100\n" - ] - }, - { - "cell_type": "markdown", - "id": "dirac_section", - "metadata": {}, - "source": [ - "## Approach 2: **Gradient-matching**\n", - "\n", - "Discretizes the SDE via Euler-Maruyama, uses `DiracIdentityObservation` (y_t = x_t), and runs NUTS. No filter needed." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "dirac_run", - "metadata": {}, - "outputs": [ + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "sample: 100%|██████████| 200/200 [00:00<00:00, 337.80it/s, 1 steps of size 3.44e-01. acc. prob=0.95]\n" - ] + "cell_type": "code", + "execution_count": 1, + "id": "imports", + "metadata": {}, + "outputs": [], + "source": [ + "import time\n", + "\n", + "import jax.numpy as jnp\n", + "import jax.random as jr\n", + "import matplotlib.pyplot as plt\n", + "import numpyro\n", + "import numpyro.distributions as dist\n", + "from numpyro.infer import MCMC, NUTS, Predictive\n", + "\n", + "import dynestyx as dsx\n", + "from dynestyx import (\n", + " DynamicalModel,\n", + " ContinuousTimeStateEvolution,\n", + " DiracIdentityObservation,\n", + " LinearGaussianObservation,\n", + " DiscreteTimeSimulator,\n", + " Filter,\n", + " ScalarDiffusion,\n", + " SDESimulator,\n", + " Discretizer,\n", + ")\n" + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Discretizer + Dirac + NUTS: 2.20 seconds\n", - "Posterior summary (rho):\n", - "Dirac:\n", - " mean = 27.70, std = 0.03\n", - "\n", - "True rho: 28.0\n" - ] - } - ], - "source": [ - "# For Dirac, we condition on the states (or low-noise obs as proxy for states)\n", - "# With low noise, obs_values ≈ states; Dirac treats them as exact.\n", - "with DiscreteTimeSimulator():\n", - " with Discretizer():\n", - " mcmc_dirac = MCMC(\n", - " NUTS(l63_fully_observed_model),\n", - " num_samples=num_samples,\n", - " num_warmup=num_warmup,\n", - " )\n", - "\n", - " mcmc_key_dirac = jr.PRNGKey(1)\n", - " t0 = time.perf_counter()\n", - " mcmc_dirac.run(mcmc_key_dirac, obs_times=obs_times, obs_values=obs_values, dirac_observation=True)\n", - " t_dirac = time.perf_counter() - t0\n", - "\n", - "posterior_dirac = mcmc_dirac.get_samples()\n", - "print(f\"Discretizer + Dirac + NUTS: {t_dirac:.2f} seconds\")\n", - "\n", - "# print true vs posterior\n", - "print(\"Posterior summary (rho):\")\n", - "print(\"Dirac:\")\n", - "print(f\" mean = {float(posterior_dirac['rho'].mean()):.2f}, std = {float(posterior_dirac['rho'].std()):.2f}\")\n", - "print(f\"\\nTrue rho: {true_rho}\")" - ] - }, - { - "cell_type": "markdown", - "id": "8b64f820", - "metadata": {}, - "source": [ - "## Approach 1: **EnKF + NUTS** (pseudo-marginal MCMC)\n", - "\n", - "Uses the continuous-discrete filter (EnKF) to approximate the marginal likelihood, then NUTS MCMC." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "a2dfeb74", - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 2, + "id": "8b98a625", + "metadata": {}, + "outputs": [], + "source": [ + "def l63_fully_observed_model(dirac_observation: bool = False, obs_times=None, obs_values=None, predict_times=None):\n", + " \"\"\"Model that samples drift parameter rho and uses it in dynamics.\n", + " \n", + " Default is noisy Gaussian, full-state observations.\n", + " If `dirac_observation=True`, uses Dirac observations (y_t = x_t)\n", + " \n", + " \"\"\"\n", + " rho = numpyro.sample(\"rho\", dist.Uniform(10.0, 40.0))\n", + "\n", + " state_dim = 3\n", + " observation_dim = state_dim\n", + " observation_model = DiracIdentityObservation() if dirac_observation else LinearGaussianObservation(\n", + " H=jnp.eye(observation_dim, state_dim), R=jnp.eye(state_dim)\n", + " )\n", + " # Create the dynamical model with sampled rho\n", + " dynamics = DynamicalModel(\n", + " initial_condition=dist.MultivariateNormal(\n", + " loc=jnp.zeros(state_dim), covariance_matrix=20.0**2 * jnp.eye(state_dim)\n", + " ),\n", + " state_evolution=ContinuousTimeStateEvolution(\n", + " drift=lambda x, u, t: jnp.array(\n", + " [\n", + " 10.0 * (x[1] - x[0]),\n", + " x[0] * (rho - x[2]) - x[1],\n", + " x[0] * x[1] - (8.0 / 3.0) * x[2],\n", + " ]\n", + " ),\n", + " diffusion=ScalarDiffusion(1.0, bm_dim=state_dim),\n", + " ),\n", + " observation_model=observation_model,\n", + " )\n", + "\n", + " # Return a sampled dynamical model, named \"f\".\n", + " return dsx.sample(\n", + " \"f\",\n", + " dynamics,\n", + " obs_times=obs_times,\n", + " obs_values=obs_values,\n", + " predict_times=predict_times,\n", + " )\n" + ] + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "sample: 100%|██████████| 200/200 [01:41<00:00, 1.96it/s, 3 steps of size 5.12e-01. acc. prob=0.94] " - ] + "cell_type": "markdown", + "id": "data_gen", + "metadata": {}, + "source": [ + "## Generate Synthetic Data\n", + "\n", + "We simulate the L63 SDE and add small Gaussian noise to get observations. With low noise, these approach the true states." + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "EnKF + NUTS: 108.71 seconds\n" - ] + "cell_type": "code", + "execution_count": 3, + "id": "gen_data", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Observations shape: (2000, 3)\n", + "True rho: 28.0\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "true_rho = 28.0\n", + "obs_times = jnp.arange(start=0.0, stop=20.0, step=0.01) # high-frequency\n", + "rng_key = jr.PRNGKey(0)\n", + "data_init_key, data_solver_key, mcmc_key = jr.split(rng_key, 3)\n", + "\n", + "true_params = {\"rho\": jnp.array(true_rho)}\n", + "predictive = Predictive(\n", + " l63_fully_observed_model,\n", + " params=true_params,\n", + " num_samples=1,\n", + " exclude_deterministic=False,\n", + ")\n", + "\n", + "with SDESimulator():\n", + " synthetic = predictive(data_init_key, predict_times=obs_times)\n", + "\n", + "# f_observations / f_states: (num_samples, n_sim, T, ...)\n", + "obs_values = synthetic[\"f_observations\"][0, 0] # (T, 3)\n", + "states = synthetic[\"f_states\"][0, 0] # (T, 3)\n", + "\n", + "print(f\"Observations shape: {obs_values.shape}\")\n", + "print(f\"True rho: {true_rho}\")\n", + "\n", + "# plot the data\n", + "obs_t = jnp.asarray(obs_times).squeeze()\n", + "for i, label in enumerate([\"x\", \"y\", \"z\"]):\n", + " plt.plot(obs_t, jnp.asarray(obs_values)[:, i], label=label)\n", + "plt.xlabel(\"Time\")\n", + "plt.ylabel(\"State\")\n", + "plt.legend()\n", + "plt.title(\"L63 synthetic data (fully observed, low noise)\")\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "from dynestyx.inference.filters import ContinuousTimeEnKFConfig\n", - "\n", - "with Filter(filter_config=ContinuousTimeEnKFConfig(n_particles=25)):\n", - " mcmc_enkf = MCMC(\n", - " NUTS(l63_fully_observed_model), num_samples=num_samples, num_warmup=num_warmup\n", - " )\n", - "\n", - " t0 = time.perf_counter()\n", - " mcmc_enkf.run(mcmc_key, obs_times=obs_times, obs_values=obs_values, dirac_observation=False)\n", - " t_enkf = time.perf_counter() - t0\n", - "\n", - "posterior_enkf = mcmc_enkf.get_samples()\n", - "print(f\"EnKF + NUTS: {t_enkf:.2f} seconds\")" - ] - }, - { - "cell_type": "markdown", - "id": "compare", - "metadata": {}, - "source": [ - "## Comparison" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "timing", - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 4, + "id": "956a8401", + "metadata": {}, + "outputs": [], + "source": [ + "num_samples = 100\n", + "num_warmup = 100\n" + ] + }, + { + "cell_type": "markdown", + "id": "dirac_section", + "metadata": {}, + "source": [ + "## Approach 2: **Gradient-matching**\n", + "\n", + "Discretizes the SDE via Euler-Maruyama, uses `DiracIdentityObservation` (y_t = x_t), and runs NUTS. No filter needed." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "dirac_run", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "sample: 100%|██████████| 200/200 [00:00<00:00, 337.80it/s, 1 steps of size 3.44e-01. acc. prob=0.95]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Discretizer + Dirac + NUTS: 2.20 seconds\n", + "Posterior summary (rho):\n", + "Dirac:\n", + " mean = 27.70, std = 0.03\n", + "\n", + "True rho: 28.0\n" + ] + } + ], + "source": [ + "# For Dirac, we condition on the states (or low-noise obs as proxy for states)\n", + "# With low noise, obs_values ≈ states; Dirac treats them as exact.\n", + "with DiscreteTimeSimulator():\n", + " with Discretizer():\n", + " mcmc_dirac = MCMC(\n", + " NUTS(l63_fully_observed_model),\n", + " num_samples=num_samples,\n", + " num_warmup=num_warmup,\n", + " )\n", + "\n", + " mcmc_key_dirac = jr.PRNGKey(1)\n", + " t0 = time.perf_counter()\n", + " mcmc_dirac.run(mcmc_key_dirac, obs_times=obs_times, obs_values=obs_values, dirac_observation=True)\n", + " t_dirac = time.perf_counter() - t0\n", + "\n", + "posterior_dirac = mcmc_dirac.get_samples()\n", + "print(f\"Discretizer + Dirac + NUTS: {t_dirac:.2f} seconds\")\n", + "\n", + "# print true vs posterior\n", + "print(\"Posterior summary (rho):\")\n", + "print(\"Dirac:\")\n", + "print(f\" mean = {float(posterior_dirac['rho'].mean()):.2f}, std = {float(posterior_dirac['rho'].std()):.2f}\")\n", + "print(f\"\\nTrue rho: {true_rho}\")" + ] + }, + { + "cell_type": "markdown", + "id": "8b64f820", + "metadata": {}, + "source": [ + "## Approach 1: **EnKF + NUTS** (pseudo-marginal MCMC)\n", + "\n", + "Uses the continuous-discrete filter (EnKF) to approximate the marginal likelihood, then NUTS MCMC." + ] + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "==================================================\n", - "TIMING\n", - "==================================================\n", - "EnKF + NUTS: 108.71 s\n", - "Discretizer + Dirac + NUTS: 2.20 s\n", - "Speedup: 49.5x\n", - "==================================================\n", - "==================================================\n", - "POSTERIOR SUMMARY\n", - "==================================================\n", - "EnKF:\n", - " mean = 28.01, std = 0.04\n", - "Dirac:\n", - " mean = 27.70, std = 0.03\n", - "\n", - "True rho: 28.0\n" - ] + "cell_type": "code", + "execution_count": 6, + "id": "a2dfeb74", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "sample: 100%|██████████| 200/200 [01:41<00:00, 1.96it/s, 3 steps of size 5.12e-01. acc. prob=0.94] " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "EnKF + NUTS: 108.71 seconds\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "from dynestyx.inference.filters import ContinuousTimeEnKFConfig\n", + "\n", + "with Filter(filter_config=ContinuousTimeEnKFConfig(n_particles=25)):\n", + " mcmc_enkf = MCMC(\n", + " NUTS(l63_fully_observed_model), num_samples=num_samples, num_warmup=num_warmup\n", + " )\n", + "\n", + " t0 = time.perf_counter()\n", + " mcmc_enkf.run(mcmc_key, obs_times=obs_times, obs_values=obs_values, dirac_observation=False)\n", + " t_enkf = time.perf_counter() - t0\n", + "\n", + "posterior_enkf = mcmc_enkf.get_samples()\n", + "print(f\"EnKF + NUTS: {t_enkf:.2f} seconds\")" + ] + }, + { + "cell_type": "markdown", + "id": "compare", + "metadata": {}, + "source": [ + "## Comparison" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "timing", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "==================================================\n", + "TIMING\n", + "==================================================\n", + "EnKF + NUTS: 108.71 s\n", + "Discretizer + Dirac + NUTS: 2.20 s\n", + "Speedup: 49.5x\n", + "==================================================\n", + "==================================================\n", + "POSTERIOR SUMMARY\n", + "==================================================\n", + "EnKF:\n", + " mean = 28.01, std = 0.04\n", + "Dirac:\n", + " mean = 27.70, std = 0.03\n", + "\n", + "True rho: 28.0\n" + ] + } + ], + "source": [ + "print(\"=\" * 50)\n", + "print(\"TIMING\")\n", + "print(\"=\" * 50)\n", + "print(f\"EnKF + NUTS: {t_enkf:.2f} s\")\n", + "print(f\"Discretizer + Dirac + NUTS: {t_dirac:.2f} s\")\n", + "print(f\"Speedup: {t_enkf / t_dirac:.1f}x\")\n", + "print(\"=\" * 50)\n", + "\n", + "# print mean and std of rho from both posteriors\n", + "print(\"=\" * 50)\n", + "print(\"POSTERIOR SUMMARY\")\n", + "print(\"=\" * 50)\n", + "print(\"EnKF:\")\n", + "print(f\" mean = {float(posterior_enkf['rho'].mean()):.2f}, std = {float(posterior_enkf['rho'].std()):.2f}\")\n", + "print(\"Dirac:\")\n", + "print(f\" mean = {float(posterior_dirac['rho'].mean()):.2f}, std = {float(posterior_dirac['rho'].std()):.2f}\")\n", + "print(f\"\\nTrue rho: {true_rho}\")\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "4dc69f9b", + "metadata": {}, + "source": [ + "Note that the speedup scales with T (number of observations), so a 10x longer timeseries would experience ~10x further speedup using Discretizer + Dirac. Feel free to experiment" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv (3.12.11)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" } - ], - "source": [ - "print(\"=\" * 50)\n", - "print(\"TIMING\")\n", - "print(\"=\" * 50)\n", - "print(f\"EnKF + NUTS: {t_enkf:.2f} s\")\n", - "print(f\"Discretizer + Dirac + NUTS: {t_dirac:.2f} s\")\n", - "print(f\"Speedup: {t_enkf / t_dirac:.1f}x\")\n", - "print(\"=\" * 50)\n", - "\n", - "# print mean and std of rho from both posteriors\n", - "print(\"=\" * 50)\n", - "print(\"POSTERIOR SUMMARY\")\n", - "print(\"=\" * 50)\n", - "print(\"EnKF:\")\n", - "print(f\" mean = {float(posterior_enkf['rho'].mean()):.2f}, std = {float(posterior_enkf['rho'].std()):.2f}\")\n", - "print(\"Dirac:\")\n", - "print(f\" mean = {float(posterior_dirac['rho'].mean()):.2f}, std = {float(posterior_dirac['rho'].std()):.2f}\")\n", - "print(f\"\\nTrue rho: {true_rho}\")\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "id": "4dc69f9b", - "metadata": {}, - "source": [ - "Note that the speedup scales with T (number of observations), so a 10x longer timeseries would experience ~10x further speedup using Discretizer + Dirac. Feel free to experiment" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv (3.12.11)", - "language": "python", - "name": "python3" }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" - } - }, - "nbformat": 4, - "nbformat_minor": 5 + "nbformat": 4, + "nbformat_minor": 5 } diff --git a/docs/tutorials/quickstart.ipynb b/docs/tutorials/quickstart.ipynb index bc6c3e86..7cc4184e 100644 --- a/docs/tutorials/quickstart.ipynb +++ b/docs/tutorials/quickstart.ipynb @@ -1,386 +1,386 @@ { - "cells": [ - { - "cell_type": "markdown", - "id": "752beec6", - "metadata": {}, - "source": [ - "# Quickstart: Writing dynestyx models\n", - "\n", - "This quickstart gives a fast and direct introduction to `dynestyx` for those who already know about Bayesian inference for dynamical systems. If you would like a more conceptual introduction, please see the [Mathematical Introduction](../../math_intro/). If you would like a step-by-step introduction to `NumPyro` and `dynestyx`, please see the [Gentle Introduction](../../tutorials/gentle_intro/00_index/). The tl;dr is that `dynestyx` is an extension of `numpyro` designed to make the specification and inference of dynamical systems simple, fast, and reproducible. In this notebook, we show how models are built in `dynestyx`, building upon an example of a simple linear, Gaussian dynamical system." - ] - }, - { - "cell_type": "markdown", - "id": "2b986e62", - "metadata": {}, - "source": [ - "## In math\n", - "\n", - "For this tutorial, the simple dynamical system we use a simple linear time-invariant (LTI) dynamical system, with linear, Gaussian observations. In particular, we have a two-dimensional state $x_t \\in \\mathbb{R}^2$ that evolves through a simple SDE that couples the two states via a parameter $\\rho$.\n", - "\n", - "We will place a uniform prior on $\\rho$,\n", - "$$\\rho \\sim U(0.0, 5.0),$$\n", - "and specify the SDE as\n", - "$$dx_t = \\underbrace{\\begin{bmatrix} -1.0 & 0.0 \\\\ \\rho & -1.0 \\end{bmatrix}}_{A} x_t \\, \\mathrm{d}t + d\\beta_t,$$\n", - "with unit covariance in the diffusion. Observations $y_t$ will be Gaussian-corrupted versions of $x_2$,\n", - "\n", - "$$y_{t_k} = \\underbrace{\\begin{bmatrix} 0.0 \\\\ 1.0 \\end{bmatrix}}_{H} x_{t_k} + \\varepsilon_{t_k}; \\qquad \\varepsilon_{t} \\sim \\mathcal{N}(0.0, 1.0).$$\n", - "\n", - "We will specify an initial condition $p(x_0) = \\mathcal{N}(0.0, I)$." - ] - }, - { - "cell_type": "markdown", - "id": "0b7a48fa", - "metadata": {}, - "source": [ - "## In code\n", - "\n", - "To specify this system in `dynestyx`, we write it down as a `dynestyx.models.DynamicalModel` in part of a `numpyro` program, and then use `dsx.sample`. We'll also use the convenience class `dynestyx.models.LinearGaussianObservation` here, but this is not necessary, in principle." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "bb6e5186", - "metadata": {}, - "outputs": [], - "source": [ - "import numpyro\n", - "import numpyro.distributions as dist\n", - "import jax.numpy as jnp\n", - "from dynestyx import DynamicalModel, ContinuousTimeStateEvolution, LinearGaussianObservation\n", - "import dynestyx as dsx\n", - "\n", - "def continuous_time_lti_gaussian_model(rho=None, predict_times=None, obs_times=None, obs_values=None):\n", - " # Sample rho using normal numpyro sampling\n", - " rho = numpyro.sample(\"rho\", dist.Uniform(0.0, 5.0), obs=rho)\n", - "\n", - " # Create the dynamical model with sampled rho\n", - " A = jnp.array([[-1.0, 0.0], [rho, -1.0]])\n", - "\n", - " dynamics = DynamicalModel(\n", - " initial_condition=dist.MultivariateNormal(\n", - " loc=jnp.zeros(2), covariance_matrix=1.0**2 * jnp.eye(2)\n", - " ),\n", - " state_evolution=ContinuousTimeStateEvolution(\n", - " drift=lambda x, u, t: A @ x,\n", - " diffusion=dsx.FullDiffusion(jnp.eye(2)),\n", - " ),\n", - " observation_model=LinearGaussianObservation(\n", - " H=jnp.array([[0.0, 1.0]]), R=jnp.array([[0.15**2]])\n", - " ),\n", - " )\n", - "\n", - " # Use dsx.sample to sample from the dynamical model\n", - " return dsx.sample(\"f\", dynamics, predict_times=predict_times, obs_times=obs_times, obs_values=obs_values)" - ] - }, - { - "cell_type": "markdown", - "id": "72c025ae", - "metadata": {}, - "source": [ - "## Simulating from the model\n", - "\n", - "To generate from the generative model, we have to tell `dynestyx` *how* to simulate from the model. Pass `obs_times` (and optionally `ctrl_times`, `ctrl_values`) as kwargs to the model. We simulate with a `dsx.simulators.SDESimulator`:" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "d23cf87f", - "metadata": {}, - "outputs": [], - "source": [ - "from dynestyx import SDESimulator\n", - "import jax.random as jr\n", - "from numpyro.infer import Predictive\n", - "\n", - "obs_times = jnp.arange(start=0.0, stop=100.0, step=0.01)\n", - "\n", - "prng_key = jr.PRNGKey(0)\n", - "sde_solver_key, predictive_key = jr.split(prng_key, 2)\n", - "\n", - "predictive_model = Predictive(continuous_time_lti_gaussian_model, num_samples=1)\n", - "\n", - "with SDESimulator():\n", - " synthetic_samples = predictive_model(predictive_key, rho=2.0, predict_times=obs_times)" - ] - }, - { - "cell_type": "markdown", - "id": "6b493b1f", - "metadata": {}, - "source": [ - "The `samples` object now comprises a dictionary that contains all the outputs of the `numpyro` program:" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "6513da83", - "metadata": {}, - "outputs": [ + "cells": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "f_observations (1, 1, 10000, 1)\n", - "f_states (1, 1, 10000, 2)\n", - "f_times (1, 1, 10000)\n", - "f_x_0 (1, 1, 2)\n", - "rho (1,)\n" - ] - } - ], - "source": [ - "synthetic_samples.keys()\n", - "\n", - "# print the shapes of the variables\n", - "for k, v in synthetic_samples.items():\n", - " print(k, v.shape)\n" - ] - }, - { - "cell_type": "markdown", - "id": "9604e5cc", - "metadata": {}, - "source": [ - "In particular, `observations`, `states`, and `times` all correspond to our dynamical system." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "42650716", - "metadata": {}, - "outputs": [ + "cell_type": "markdown", + "id": "752beec6", + "metadata": {}, + "source": [ + "# Quickstart: Writing dynestyx models\n", + "\n", + "This quickstart gives a fast and direct introduction to `dynestyx` for those who already know about Bayesian inference for dynamical systems. If you would like a more conceptual introduction, please see the [Mathematical Introduction](../../math_intro/). If you would like a step-by-step introduction to `NumPyro` and `dynestyx`, please see the [Gentle Introduction](../../tutorials/gentle_intro/00_index/). The tl;dr is that `dynestyx` is an extension of `numpyro` designed to make the specification and inference of dynamical systems simple, fast, and reproducible. In this notebook, we show how models are built in `dynestyx`, building upon an example of a simple linear, Gaussian dynamical system." + ] + }, { - "data": { - "image/png": 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", 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" + "cell_type": "markdown", + "id": "2b986e62", + "metadata": {}, + "source": [ + "## In math\n", + "\n", + "For this tutorial, the simple dynamical system we use a simple linear time-invariant (LTI) dynamical system, with linear, Gaussian observations. In particular, we have a two-dimensional state $x_t \\in \\mathbb{R}^2$ that evolves through a simple SDE that couples the two states via a parameter $\\rho$.\n", + "\n", + "We will place a uniform prior on $\\rho$,\n", + "$$\\rho \\sim U(0.0, 5.0),$$\n", + "and specify the SDE as\n", + "$$dx_t = \\underbrace{\\begin{bmatrix} -1.0 & 0.0 \\\\ \\rho & -1.0 \\end{bmatrix}}_{A} x_t \\, \\mathrm{d}t + d\\beta_t,$$\n", + "with unit covariance in the diffusion. Observations $y_t$ will be Gaussian-corrupted versions of $x_2$,\n", + "\n", + "$$y_{t_k} = \\underbrace{\\begin{bmatrix} 0.0 \\\\ 1.0 \\end{bmatrix}}_{H} x_{t_k} + \\varepsilon_{t_k}; \\qquad \\varepsilon_{t} \\sim \\mathcal{N}(0.0, 1.0).$$\n", + "\n", + "We will specify an initial condition $p(x_0) = \\mathcal{N}(0.0, I)$." ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "\n", - "plt.figure(figsize=(10, 5))\n", - "\n", - "times = jnp.squeeze(synthetic_samples[\"f_times\"])\n", - "states = jnp.squeeze(synthetic_samples[\"f_states\"])\n", - "observations = jnp.squeeze(synthetic_samples[\"f_observations\"])\n", - "\n", - "plt.plot(times, states, label=\"states\")\n", - "plt.scatter(\n", - " times,\n", - " observations,\n", - " label=\"observations\",\n", - " marker=\"x\",\n", - " color=\"black\",\n", - " alpha=0.5,\n", - ")\n", - "plt.title(\"Synthetic Data: States and Observations\")\n", - "plt.xlabel(\"Time\")\n", - "plt.ylabel(\"State / Observation\")\n", - "sns.despine()\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "1c8c8a86", - "metadata": {}, - "source": [ - "## Bayesian system identification\n", - "\n", - "Performing Bayesian inference for system identification (in this case, obtaining posteriors of $\\rho$) also becomes simple. Recall that to obtain posteriors of $\\theta$, we must compute posteriors with respect to \n", - "\n", - "$$ p(\\theta \\mid y_{1:T}) \\propto p(\\theta) \\underbrace{p(y_{1:T} \\mid \\theta)}_{\\text{marginal likelihod}}. $$\n", - "\n", - "We can accomplish this by appropriately **interpreting** the `dsx.sample(..)` statement. We will proceed with the normal numpyro tools, but wrap it in a `Filter` context for marginal likelihood computation. Inference over $\\theta$ is then a standard Bayesian inference problem." - ] - }, - { - "cell_type": "markdown", - "id": "69e749ec", - "metadata": {}, - "source": [ - "The `Filter` object gives us some control over the way we solve for the marginal likelihood, including the method and its hyperparameters. By default, we use an ensemble Kalman filter (EnKF); the EnKF is biased for nonlinear state space models, but still generally accurate for high-quality inference. To change the filtering method, pass a config, e.g. `Filter(filter_config=ContinuousTimeDPFConfig(n_particles=2500))`.\n", - "\n", - "After specifying the marginal likelihood computation, inference can proceed in the standard way for `numpyro` (although, MCMC quality may vary based on what approximation to the marginal likelihood we take). The EnKF provides a very smooth marginal likelkhood, so we can often use NUTS in state space models that are not overly complex. " - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "14756201", - "metadata": {}, - "outputs": [ + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "sample: 100%|██████████| 200/200 [07:39<00:00, 2.30s/it, 3 steps of size 1.02e+00. acc. prob=0.94]\n" - ] - } - ], - "source": [ - "from numpyro.infer import MCMC, NUTS\n", - "from dynestyx.inference.filters import Filter\n", - "\n", - "obs_values = synthetic_samples[\"f_observations\"][0,0] # shape (T, obs_dim)\n", - "\n", - "mcmc_key = jr.PRNGKey(0)\n", - "\n", - "with Filter():\n", - " nuts_kernel = NUTS(continuous_time_lti_gaussian_model)\n", - " mcmc = MCMC(nuts_kernel, num_samples=100, num_warmup=100)\n", - " mcmc.run(mcmc_key, obs_times=times, obs_values=obs_values)\n", - "\n", - "posterior_samples = mcmc.get_samples()" - ] - }, - { - "cell_type": "markdown", - "id": "c0a63174", - "metadata": {}, - "source": [ - "Plotting the posterior values of $\\rho$ shows a posterior centered at the true value of $2.0$." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "5745525c", - "metadata": {}, - "outputs": [ + "cell_type": "markdown", + "id": "0b7a48fa", + "metadata": {}, + "source": [ + "## In code\n", + "\n", + "To specify this system in `dynestyx`, we write it down as a `dynestyx.models.DynamicalModel` in part of a `numpyro` program, and then use `dsx.sample`. We'll also use the convenience class `dynestyx.models.LinearGaussianObservation` here, but this is not necessary, in principle." + ] + }, { - "data": { - "image/png": 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", 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" + "cell_type": "code", + "execution_count": 2, + "id": "bb6e5186", + "metadata": {}, + "outputs": [], + "source": [ + "import numpyro\n", + "import numpyro.distributions as dist\n", + "import jax.numpy as jnp\n", + "from dynestyx import DynamicalModel, ContinuousTimeStateEvolution, LinearGaussianObservation, ScalarDiffusion\n", + "import dynestyx as dsx\n", + "\n", + "def continuous_time_lti_gaussian_model(rho=None, predict_times=None, obs_times=None, obs_values=None):\n", + " # Sample rho using normal numpyro sampling\n", + " rho = numpyro.sample(\"rho\", dist.Uniform(0.0, 5.0), obs=rho)\n", + "\n", + " # Create the dynamical model with sampled rho\n", + " A = jnp.array([[-1.0, 0.0], [rho, -1.0]])\n", + "\n", + " dynamics = DynamicalModel(\n", + " initial_condition=dist.MultivariateNormal(\n", + " loc=jnp.zeros(2), covariance_matrix=1.0**2 * jnp.eye(2)\n", + " ),\n", + " state_evolution=ContinuousTimeStateEvolution(\n", + " drift=lambda x, u, t: A @ x,\n", + " diffusion=ScalarDiffusion(1.0, bm_dim=2),\n", + " ),\n", + " observation_model=LinearGaussianObservation(\n", + " H=jnp.array([[0.0, 1.0]]), R=jnp.array([[0.15**2]])\n", + " ),\n", + " )\n", + "\n", + " # Use dsx.sample to sample from the dynamical model\n", + " return dsx.sample(\"f\", dynamics, predict_times=predict_times, obs_times=obs_times, obs_values=obs_values)" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import arviz as az\n", - "az.style.use(\"arviz-white\")\n", - "\n", - "az.plot_posterior(\n", - " posterior_samples[\"rho\"], \n", - " hdi_prob=0.95,\n", - " ref_val=2.0\n", - ")\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "d5016e81", - "metadata": {}, - "source": [ - "## Likelihood sweep\n", - "\n", - "As a quick diagnostic, we can sweep over fixed values of $\\rho$ and evaluate the marginal log-likelihood $\\log p(y_{1:T}\\mid\\rho)$ using the same `Filter`-based model. This is useful for checking identifiability and seeing whether the inferred posterior mode aligns with the likelihood peak." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "27699b7e", - "metadata": {}, - "outputs": [ + }, + { + "cell_type": "markdown", + "id": "72c025ae", + "metadata": {}, + "source": [ + "## Simulating from the model\n", + "\n", + "To generate from the generative model, we have to tell `dynestyx` *how* to simulate from the model. Pass `obs_times` (and optionally `ctrl_times`, `ctrl_values`) as kwargs to the model. We simulate with a `dsx.simulators.SDESimulator`:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "d23cf87f", + "metadata": {}, + "outputs": [], + "source": [ + "from dynestyx import SDESimulator\n", + "import jax.random as jr\n", + "from numpyro.infer import Predictive\n", + "\n", + "obs_times = jnp.arange(start=0.0, stop=100.0, step=0.01)\n", + "\n", + "prng_key = jr.PRNGKey(0)\n", + "sde_solver_key, predictive_key = jr.split(prng_key, 2)\n", + "\n", + "predictive_model = Predictive(continuous_time_lti_gaussian_model, num_samples=1)\n", + "\n", + "with SDESimulator():\n", + " synthetic_samples = predictive_model(predictive_key, rho=2.0, predict_times=obs_times)" + ] + }, + { + "cell_type": "markdown", + "id": "6b493b1f", + "metadata": {}, + "source": [ + "The `samples` object now comprises a dictionary that contains all the outputs of the `numpyro` program:" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "6513da83", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "f_observations (1, 1, 10000, 1)\n", + "f_states (1, 1, 10000, 2)\n", + "f_times (1, 1, 10000)\n", + "f_x_0 (1, 1, 2)\n", + "rho (1,)\n" + ] + } + ], + "source": [ + "synthetic_samples.keys()\n", + "\n", + "# print the shapes of the variables\n", + "for k, v in synthetic_samples.items():\n", + " print(k, v.shape)\n" + ] + }, + { + "cell_type": "markdown", + "id": "9604e5cc", + "metadata": {}, + "source": [ + "In particular, `observations`, `states`, and `times` all correspond to our dynamical system." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "42650716", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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ISjKDqa7HDrIMFamBJEGBuTRv3jwxdOjQpJ/HaGE9QW7gRfzw+OOPy+gnhA463NIRIWRhvhG50SOHkIrwIEIH2QPtBfhtRWhCFCidMU8G0vL4DaKTRJo4j912283WMJvzIwqpX6tbg+d01y/Xye/wm078+uuv0hhORbzhhS222EI+GCvWMWQfzzzzTErHgYGBQcPBpOQZGBjUC1DM3bzjRDiAM7WF9DtSVWCuQil19hvKBKruCeW0NiBiAfMVDFi6Aq+g0pAy/S3Sb6iluOuuu+oskoCxBHsZbGT8VWlJytjUv5dUJFJ+nOAa3M6f73CeF5FBt/otvPwojqmAwUhNiROkbFLbos8Lzsstfcrt2vheauZ0oOAC57Vlcn85Jx14/Yk+pUqbymTs0nU0oLQT2aqsrIwdx8mQztxDmcfgI93Vrc8S30td19FHHy0bJOtgXPW6K1LPiLjB8MZ1Mged94kxJhqkxokaKIymm266KZY+6jXm6awjfpe6R8YU9jy91tFtfvB/GmY7ke765Tu5Xq4bJjsFUocxcnBU6CmB6QB555wjKvpm0vIMDBoXTITJwMCgXgCxATn/0DOTEoOS99lnn0mPMA1WUd50DB8+XFIUowCRPqSoiGsDVaCOAUHKFcoONN6ZgEaeKEHUrRDtIiqBcoTyCDUxxAVKweH7iYyhNFKvQgQAhdEJvN148WkgioFAahHGA0osHnO9aN0NfD/paICxpRaHKAspY1wfqV8KKHek4OF5V0bogw8+KM/LaSQwXijR//nPf6QxwHu4BhRRani4VxTM47knZc6tZiZdWnEiHHwH84Lf5Rwx9h555BFZj6RqrNR5MV8YL9I5MVa4Hs6L6+Y7SOUjwoLCTyqZroyT0sUxvoO0PyJFzDEe6d5fPo9xxbnwecgXFH12MmQydumAaBj3h3vJvSHKwnVjAKf7naQSYtQy16AOV5EkUsEwBKipIR3MCcaLdaTTigNqb1TtE0YWtYlEurhPzGlaA6jvIwJDOiPRJqjuGRcIYDAgca5gbBAVTQfMT6J3pJry24yFDuQNxhkpl3w/3w3hiludYyaygvEnSsW8YQyJxmF0Y9xQw5UpiIAxlsxjzpdrYY1yvjvvvHPG32dgYFCPyDZNn4GBQfPE22+/LSmeoY4uKiqSdLw0/zz11FMj//77r+tnbrjhBkmze8011yS8pjedTUX/C+00vwN9NTTCbo1rU30HgD74sMMOk81laYpJU9Fdd9018sILL9je9+CDD0qqbiiDUzWuhe74oosuklTKfCffTYNNnao4nUaujCk0zYcccohnE9XXXntNNgVWDTGvv/76GLU5Y6FTfUOdDT2yTlENNTbNVzt37iybjNKwlSadbteVLq34jz/+GDnnnHNk81OawNIole+fPHmypLXWAaX8QQcdJBuX6o1roWpmjvAcmu7hw4dH3njjDdmI1ElD/tlnn0kaauaf8x6nc39pJrvZZpvJc2AMmM9XX311Aj2+E+mOnaIVh55eh5qrUFTroPEwc4frpuFyuo1rFaAkv/XWW+WYQNtPQ1XuxW233eZ6TXrjWtVsmfHWafT5Tu4pFOyqoSv/dzZJBtCa77333pLan+/ifu23336RqVOnJtCKQwvvBdYc7+H3aAbtxM8//yxpvVknNI499thjIz/88EPCmHrJimSNa6FG53sZO5r9Msd0KFpxJ124utdq7PguqNN79OghxwLaeOafTuFuYGDQOODjn/o0yAwMDAzSBSkzZ5xxhkx5cTJMGRgYGBgYGBhkA8ZgMjAwaBTAd0M6DxTRbsQEBgYGBgYGBgbZgKlhMjAwyCqo4YHJDSOJOg9qKQwMDAwMDAwMGgtMhMnAwCCrIP2OBpU0VqWQGmpdAwMDAwMDA4PGAmMwGRgYGBgYGBgYGBgYeMD0YTIwMDAwMDAwMDAwMPCAMZgMDAwMDAwMDAwMDAw84N/QWLjWrFmTsrGigYGBgYGBgYGBgYHBBmcw0UW7ZcuW8q+BgYGBgYGBgYGBgUEqbFAGk4GBgYGBgYGBgYGBQSYwBpOBgYGBgYGBgYGBgYEHjMFkYGBgYGBgYGBgYGDgAWMwGRgYGBgYGBgYGBgYeMAYTAYGBgYGBgYGBgYGBh4Ier1gYGBgYGBgYGBg0FhBm5jq6mpRU1OT7VMxaKQIBAIiGAwKn8+3Xt9jDCYDAwMDAwMDA4MmhcrKSvH333+L0tLSbJ+KQSNHQUGB6Ny5s8jJyan1dxiDycDAwMDAwMDAoMkgHA6LefPmyehBly5dpCK8vhEEg+YZgaysrBRLly6V86Vfv37C769dNZIxmAwMDAwMDAwMDJoMUIIxmrp37y6jBwYGXsjPzxehUEjMnz9fzpu8vDxRGxjSBwMDAwMDAwMDgyaH2kYLDDYs+OtgnpiZZmBgYGBgYGBgYGBg4AFjMBkYGBgYGBgkRXl5uVizZo3raxzndQMDA4PmCmMwGWQdZiM2MDAwaNwy+r///a949NFHxerVq22v8ZzjvG6MJgMDg+YKYzAZZBVmIzYwMDBo3KBQuqSkRKxcuVL83//9X8xo4i/POc7rvM/AwKD2OOKII8See+6Z8ecuv/xyMWzYMDP09QhjMBlkFWYjNjAwMGjcgLJ5l112kWxTymhasGCB/PvPP//IppAHHHCAaNGiRbZP1cDAwKBeYAwmg6yCDRaPSuvWrRM2Yp5znNfNRmxgYGCQnSyABx54QJx33nmirKxMUvIimx9++GHZNPT7778X33zzjXjppZdMSp5B1nvulFZWZ+XBb2eCF154QQwePFg6Idq2bSsmTZokzjnnHPHYY4+JV199VfaU4vHhhx/K97P+Nt54Y0mh3rt3b3HJJZeIqqoq+Rr60hVXXCF++OGH2Oc4BlatWiWOOeYY0b59e6lHbbvttvJ9Cvx/woQJori4WL4+cuRIuZ4NEmH6MBlkHS1btpRGkTKS2IiBMpZ43cDAwMCg4QGhw0cffSR++uknsXz5cnHI2K6ijW+N+KpmoPjiiy/FwoULZY+ToUOHrlePEwOD9UVZVY0YeOk7WRnIn6/cQRTkpKdS42g48MADxQ033CD22msvsXbtWvHJJ5+Iww47TPz1119yzVEXCNq0aSP/YtCgI9Gkd+bMmeLYY4+Vx84991yx//77y/X5v//9T7z//vvy/Upvmjx5sjTK3n77bXns/vvvFxMnThS//fab/O6DDz5YDB8+XNx7772yCTAOENazQSKMwWTQKMBC3nvvvWPGEuC5MZYMDAwMsgcMIGojfv75ZzFr1ixxzDbfyeOjKr8QD/0Ukc1DO3bsKAoLC2XqnoGBQWqDqbq6Wuo4PXv2lMeINgGMm4qKCtGpUyfbZy6++OLY/3v16iXOPvts8cwzz0iDic8UFRXJ1Fj9c9OnTxdfffWVWLJkicjNzZXHbrrpJvHKK6/ICNdxxx0nDTQiW/3795ev9+vXz9w+DxiDyaBRgOJhUjp08NxEmAwMDAyyB9J08IJPnTpVKl4KPQorRTgckOk/eKoxnEyEySCbyA8FZKQnW7+dLojGEuXBSNphhx3E9ttvL/bdd1+ZVeOFZ599Vtxxxx1izpw5Yt26ddLgSlWqQLod7yXlTweptXwPOPPMM2XK3hNPPCHTAolI9enTJ+1r2ZBgapgMsg6daQmBcfTRR9tqmpw0tgYGBgYGDQNqIK6++mpJ7kAKkA6iSuDPP/809UsGWQfGO2lx2Xjw2+mC1Lf33ntPpskNHDhQ3HnnnWKTTTYR8+bNc33/559/LlPndt55Z/HGG2+I7777Tlx00UUpWSkxljp37izT7PTH7NmzZVRJsesROYbUZdq0afJ8Xn755QxHfsOAMZgMsgpydZ0ED927d08ggvBqmGhgYGBgUH9A6cJoKi0tFWvX2J1X1DTh6Sbdh3Q8k5JnYJAeMLDGjRsnyRowgFg7GCr8rampsb33s88+k6l7GEmjRo2SaXPz58+3vcftcyNGjIixWPbt29f2aNeuXex9kEmcccYZ4t1335Vpgqp+ysAOYzAZZBUscryUToIHRQTBcZMbb2BgYJAdoGxhFKF4laxba3sNDzeGFEYVKXkGBgap8eWXX4prrrlGstFRQ0T5wdKlS8WAAQNkfdKPP/4oo0DLli2TTHgYSLyPmiVS6UjNc0aB+BwRKiJIfI46KFLsxowZI/s6YQwRCcb4wvDit0nNO+WUUyQTHwbYp59+Kr7++mt5HgaJMDVMBlkvKD7kkEPkxuvMx8VoOvLII6VRZZiXDAwMDBqeUvyee+6RKUEykhSwUycrjzaZAB988IF0cnXr1s3cJgODJEDX+fjjj8Vtt90ms2eIHt18881ip512khEkDBj+4ohgXe2+++4yAoRxgyFE+hy04qTTKeyzzz7S8IIinIgwUSLW41tvvSUNJHQpjDJIIcaPHy+JWkgNJEoMO9+///4ro05EmIh6GSTCF8mUPL4Jg4mJEk5NjOnrY2BgYGBgkHzPvPLKK6XRhDe6Ra5PrD4/Xsfkv3Kt7D+D4jVlyhTpNTfOLYOGMuaJqGy00UZmzhk0yHwxKXkGBgYGBgYGCVDRfZVuF/DZ/avK38p76N2SqgjdwMDAoKnCGEwGjc4L4EXwwHFeNzAwMDCofygDCFpiitSD/kQmML/fL9N7SOcxpA8GBgbNFU3GYKIL8ZAhQ2QqHQ8K2aBkNGg+wBj673//K3NvnVTi5NcyB3jdaTQZQ8rAwMCg7qGY76hfwjAKumgMHO/QoYOkPDbpeAYGBs0VTcZgopD0uuuuEzNmzJDsHttuu63YY489JH+8QfPxZlKsCBuT3n8JY+m0006TfQvokK2nffAeDCw3Q8rAwMDAYP1kMql2MJVC8OA0mFTvGdi36A9jZLCBgUFzRZMxmHbbbTfpwYJeEc54GukVFRWJL774ItunZlBHwJOJt/Knn36ShtGDDz4ofv75Z2k8LV68WNJpYjBTfExUCUOK16DDhP3F5M8bGBgY1B3I5sA5qZxXToMJeQ3hA4bS1KlTJZ2xgYGBQXNEk6QVx9P1/PPPi5KSEpma5wXoF3komOanjRdsuAsXLhRfffWVNIjoQ0BB8fvvvy+6dOkifv/9d7F27VppQNEVm94gv/76q2jfvr346KOPxKBBg0wfEAMDA4M6BHsmtMQqkpQTSKxhIl0PmU06Hk5MAwMDg+aIJmUwzZw5UxpIKNcIZhp3DRw40PP91157reGTb0K1S6Ti0SOAvxwjqlRcXCyNKAxfPJn0+6BHAUYz3k3mBM1teZ2eBa1atcr25RgYGBg0WSB7VV88VcMEkL8D2ycmpeDYooZpxIgRUiYbGBgYNEc0KYNpk002kV2MSQ944YUXxOGHHy6jC15G0wUXXCDOPPNMm7ese/fuDXjGBpnULk2fPl0aQLm5uTJaRJodUSfAczZjvJmqbg2jiTnBZk0DONMw0cDAwGD9nVdkbxxwwAHSCYUMxiiilqksErC9n0g/r1VVVYk999zT9Dc0MDBotmhSBhOerr59+8r/jxw5Unz99dfi9ttvF/fff7/r+1G8eRg0buDJ3H///cU777wjjWGiRfn5+dKQwlDiQUoIfzGS2JwxnjimSB969OiR7cswMDAwaNJA5mIs4aw65ZRTZEQfJxbHCgoKRN/eXYQQC2LvV7J42LBholevXlk9dwMDA4P6RJOOn6NA6zVKBk3Xq9myZUvxn//8RxpKeCypV5rUS4geLazGiBxTefT85YHxRMQJdiYnDbmBgYGBQebOqyOOOEKmQkO88/nnn0vjCVmLDM7Ps9LzYoiEpcweMGBATD4bGBgYNEc0GYOJ9LqPP/5Y0pfi8eI5tSwHH3xwtk/NoA5SQO6++265IeOpZOPddqOAePvgAjHvtGKbgcx71F8e1DnNnj1bsuUZUg8DAwOD9QPOK4wm6oSRsQDHVGlpqZg/b47tvaGAX0aeIH2A1dTIYAOD9QNrj/TWTHH55ZdL/cmg/tBkUvKWLFkiDjvsMOn1QqDTxJYUru222y7bp2awnikgeDCfeuop8cADD8hjeCy37BHvtaRDbeB4PClChiUPanlSNU2XeQMDA4P1BzJ4iy22kPstzKQYTJ3zq8QuvahhCsXeN3TwIBEJ5knnJXWoOLMMDAwMmiOaTITp4YcfltElUvAwnqCbNsZS80gB2XHHHWX/jr/++ks+MKKqarw/IxsoBoOSUa9nz55yTkAzv2jRooY8dQMDA4NmCRXJRxbDQgr+PL1YHDY0biyBNq1byj54y5cvl2nRkEQYGGQNOFQrS7LziDpz0wXEZYMHD5bOibZt24pJkyaJc845Rzz22GPi1VdfjZUe4IwA5513nuxBSkS3d+/e4pJLLpE1hIAMmyuuuEL88MMPsc9xDODIOOaYY6RzWfVV430K/H/ChAkyDZfX4Qf45ptv6vS2NBc0mQiTQfMFC5kIEY1o2agxgKrC8Vz5/u384tdlcc+lypUnwkQKCMYTDE48DAwMDAxqDwwf0usgVSKylKwh+PfffisqIqFYRKpdu3Zm6A2yh6pSIa6BmCQLuHCxEDmFab2VyO2BBx4obrjhBrHXXnvJmu1PPvlEZlHhNEavgcwKtGnTRv7FoMEIoi8lZSnHHnusPHbuuedK0qyffvpJ/O9//5PBBEAmFpg8ebJcn2+//bY8BknaxIkTxW+//Sa/m7KW4cOHi3vvvVfqVDBRG13KHcZgMsg62GSJFtKsFkFRnCPEXv3jU7Nlrk/sNygont23QEx4rETs1DcoX5/w34WixNdd7LHHHuK0004zTHkGBgYG6wHkL0oZESMVYSJqhEx2Q2VFmQgVFohHHnlEeqlpXmtgYJDaYMIZsffee8ssGUC0CWDc4DQmg0bHxRdfHPs/jJRnn322eOaZZ6TBxGeoOVSZNwq0aqGPJVlZijH6pptuEq+88oqMcB133HHSQCOy1b9/f/l6v379zO3zgDGYDLIONlk8JE888YTYo1eZeHyvfNvrFTUR8ey+lufmg8PjHpwpo/xido9txBlnnCGjVAYGBgYGtQd1oIWFhfJBug9pzqRAn7Glu8Xk9wnpjf7uu++kwWRgkFWECqxIT7Z+O00MHTpURnkwknbYYQex/fbbi3333TeW/uqGZ599Vtxxxx1izpw50omBwUUKXTKQbsd7SfnTAUkL3wPoVUrKHvoXaYFEpPr06ZP2tWxIaDI1TAbNOwUEjweL2mksgWqPOuK8UEAy5OHdhGkPxj0DAwMDg9o7r1DcdtllF2ko8QBFOe6U4QGfJb9JJ8KLbWCQVZCuT1pcNh4Z0OqT+vbee+/JNLmBAweKO++8U2yyySZi3rx5ru+H3p/UuZ133lm2UcFBcdFFFyVNlwUYS507d5ZpdvoDvYmokmLXmzVrllzz06ZNk+fz8ssvZzjwGwZMhMkg6ykg5MtTOOxF2hDyMOspsSRvl1AyHlGEh0kJMTAwMKgdcDo9/fTT0vihtxLpPByr8XBaEWHy+/ySkIn0oClTphgZbGCQBqjFHjdunHxceumlMjUPQ4Uor3JUKHz22WfydYwkBXQmHW6fGzFihPjnn39kql6yxtKQSfAgW4faKuqnqK0ysMMYTAZZBXny0IKTa+vV+DDoYTDxfooev/zyS5l3a2jFDQwMDNbPgYWXmRqLFStWiBO3KBaH9w+KoR3dhXAw4BNV5VWSuQs5ftBBB4lu3bqZW2BgkAToLFOnTpWpeB06dJDPaa+CkwIHBS1ziAKRdQNRA/oNtUY4JUaPHi3efPPNhCgQBhERKiJIrEF0I1LsxowZI/s6QTCBUUTvSj6PQTRo0CAZaSKqvNFGG4mFCxdKspd99tnH3D8XmJQ8g6zC7/fLRYzhBP2lG0LkfXiAqJIymqAmNzAwMDCoPZCpKGtz//hd3LJ1haexBIJ+n6yjwMCiaaZhyTMwSA3WzMcffyxT7NB/IHS4+eabxU477STZ70jPGzVqlKzN/vTTT8Xuu+8uoz+nnHKKXGdEnKAV14GRQ4sWagn5HJFinMpvvfWWGD9+vDjyyCPlbx1wwAEyOtWxY0eZGgjBC+x8vLbffvvJc4Ci3CARvojqBLqBeM+w1sm5TlUsZ9BwYHOG6Y4ixKqLEgsnt/m/EvHhEYl0nbd/WSUu/Ngn6Wz5PIwvJiXPwMDAoHYgFe/GG2+UBea+NQvF/NOLk76//z3lYoVoKWUwjcedzF4GBvUFIjFEVIiMmH3foCHmi4kwGWR9Er/77rsxb4cbQu6HZc8mPgPLizGWDAwMDNZPFr/44ovi999/l/UShQWpe8qEa6olpfGpp55qlFYDA4NmDWMwGWQ9/YN0PKx+Z8GiQojKYhcEggHZeA3SCJreGhgYGBjUXhaTnvPrr79KEgev2lGbDPZbUamTTjpJnHjiiZ5p1QYGBgZNHcZgMsgqSI0kp5YNmr4CbmiZJ0R5dWLmqN9v5d/S8JYok6G1NTAwMKi9LKY4fOXKlZKxtKK8NOVnKC/F0OL91DGZOlIDA4PmCmMwGTSK2jI2Wq+UvKf3KZD0tU5gYNE0EeKIbJbikcrCNbiB46Y/lIGBQVMAzHjU+CJP04kw5QQDUv5SXI7D6rXXXjPyzsDAoFnCGEwGWQUGxUsvvSSLhZMxLLlm5UUikj6zR48est9ANgo/MYZomkvB84IFC2yvoXjQz4CUQZOqYmBg0NiBE4qeLSAdg0lEaqSxBP0xhhMGl5fzyMDAwKApwxhMBlkFvZNIBaGGia7Uyehr3fDbb7/JjZo+INRCNTRIR8EYgiL0tNNOk70SlLH0f//3fzJN5YMPPhBPPPGE8bwaGBg0WuD8oYcLfWFSGUwryyKxGiZIH7p27Sp22WUXUVRUZKJMBgYGzRLGYDLIOkjleOWVV0RZWVlGn4tEwtJgKSkpkV7NF154ocGNEoy9/fffP5aScvrpp4tZs2bFjCUMOhinKioq5LkaGBgYNEYoWYos4+HlpAKt863XOhdZ6XikU//000/SecR3GFlnYGDQ3GAMJoOsgtolmrBVVVXVKkLERk2RMpt0tjZqmsSNHTtWGm0YTWeddZYksVDGEk3icnNzZTTNwMDAoLECplIeyNV0UvKe3Dtfyt0ZM2bI5uE4iyDxMX0ODQwMmhuMwWSQVZDCQTPhZHhqZpXnaxQnK3a8I444IisbNUYa9VNbbrmlZO0jtfC7776TdVkYS3TQxhg0XlcDA4PGChw6pNdhLCGv0jGYinN9su6JCDoOIyJMpCMbGBgYNDcYg8kguxPQ75cGBRu1VwJIXtDrswFpMBGdmj17tty0swGMtJ133lmSPmD8/fPPPzI1kNoljKbWrVsbr6uBgUGjBzIUoweDqVer9NUD1UScfniXXXaZIbkxMFgPfPjhhzLVtTmRRR1xxBGybUFThjGYDBpFHyYiTSEPl6anwSTCorCwMMbQlC1grFG7RGrg2rVrJdsfqYbUZL3//vsyPQ8mQEMvbrAhgk1/4cKFrq9xvDkpBU0ZRMCXLl0aY7l7bM/8tD63/6CQZNYjlQ8ZR4Q9GYGPgUFjgWkJUvf4888/pbEHgYyO22+/XdZ2N2UYg8kg6wLrnXfekekgLYsLXd+zc7+Q6/F2BT6rX0gwKAYMGJCVGiFY8fbbbz/x0UcfiV9//VUUFxdL42/77beXQoPXoRanP4mh2zXY0IAxdOKJJ4pjjz02xiCpwHOO87oxmhoPYynyNBMH1DP75oscOthGacmvuOIK2e7BwKAxQ7UEYX92ppGqliC8vqE4Ouu7ZKBly5aiVatWoinDGEwGWQVGBOHnxYsXi8ryzFjyDtg0JAuOYaNDuN1zzz2ynqkhBRwRJbyypLLgVf3jjz+k0qDoxvmr2KdMDZPBhuaxXbRokfjkk08kIcBRRx0lfv/995ixdNxxx8njvM77DLILouIw3eF88jJ4jn6tTIx8IDF6FAz4pLMIRxH30ziHDBo71L5MZgiRD2U0qZYgikyqvvZtdIYpU6ZIGn9VA/3111/b3vPpp5+KIUOGyNe32GILuT4VqI/ebbfdZMo/mTaDBg0Sb731Vux13rvTTjtJB27Hjh3FoYceKte4wjbbbCNOOeUUmR1DVswOO+wgDjroIMn6q4OSB15//PHH5fP//e9/8lwxfsju2XXXXcWcOXNi76dFDBg+fLh0GvM7bil5qa5fpSVOnTpVjBo1SraOgVyLjB6FH374QUyYMEHKHpw9I0eOFN98842oLxiDySCrQBjFGPLC1Rl/nghTaWmp3KDfe+89ce+999aLV0hXBPX/d+/eXey9997SO8t17NCtVPxn45lixkdvS2GrekQh1BBcBgbN3WP7yCN2jy1rG2cCbJhsmPQsw1j66quv5PFs9E8zSATyCVmFE4j0Ojc88l2V+PbvxPtVXVUlZfm3334rlRzDCGrQ2IGCjRLP3qyMJuqQlbHE8fokkjr33HPFiy++KB577DG5bvr27SuNFpo/K5xzzjni5ptvloYEbLwYSOgZ4OSTT5ZGB/J05syZ4vrrr4/pGDhrt912W2m0YEBg5FBfSDaMDn6btYphdt9994mDDz5YvP7667aUWjKA0LH22msv+Ry95swzz5TfizGDjsNrSo4j1wHlCDizKUeo7fWDiy66SI4Bv0f0G8ebAueLc4fxganz/PPPF6GQe0ZSXcCjOsTAoGGA5wLPApNdVK+f/a7qhpRXCK9FXSqCfC/1VggADKYTTjhBvo53gwdKxpN7slirxf/2XCt63umPNeUFCKGmHpI2MPBaIz/OXSSun9NRVEX84q/7nxWXHb+/TMPo16+fVEDY3OfNmydOPfVUqZiwHvCM4kFNxZRpUP9A8SG69Pnnn8uIvxDFaX/WJyLyfnJfhw0bVmey18CgPoHcwShSRtLDDz8sjytjqb7kEroEzl1+lygQePDBB6XTl3MYPXq0PAaBynbbbSf/j2GBcfDyyy9Lw4co/T777CMGDx4sX+/du3fs+++66y5pLF1zzTWxY4888oh08NLuBKItgGy+4YYbYu/p06ePlMn8BhEp8NRTT4ndd99d6jiA39TB92LM/fzzz2LTTTeV/wdEnyC9qs31YygqXH311WLrrbeW/8cgokE2+w0yhjHgvf37949dT33CRJgMsgoMG7wXsOTlhvy13ug32WQT0blz56ReodoWeOqhexY1nhMY8G699Va56GGHQjjpSkLHQp98jtcEoTFp0iRpHBoYNDcoh8LJT/0gjSXw0oqusTQX1rYkdQmF5FoifYMoBsc333xz8cADD5ial0YAZCYeXu4nUaJMoAh7uK/PP//8BlP3YdD0gVFElogOntenEwcZSKRo3LhxsWPIx80220z88ssvsWNjxoyJ/b9NmzZSz1Gvk872n//8R34HhtWPP/5oS1VDR0HuqocyKvT0OVLYdBDBwRh78skn5XP0nldffVVGchRIqz7wwAOlgYbM6NWrlzzurFGti+sHONQU0PGAaiVDpOuYY46R+tV1111nu7b6gDGYDLIKwrh4PAghh6KFw5U1EeG/cq147Afv/ks6MFj4/IgRI2TUx03QrU+Bpx66V9ErjDw8LxhPCBkWMtEtHbyPqBdeDzw0xutq0ByhHApLq3Ntx0nHoIkza2rgwIHSQAI8J5WWDRKPoVfUNZkTo6GxITD9Md7UH6EAZZomWVxYKOUghtYLL7wgCXAMDJoC2P+daWM8b+z9xDAU5s6dKyNBpORR53PnnXfK14j2kr4HU53+wNgZP3587DuIJjmBcUSqHUbJK6+8IuX2jjvuGHud7yVtDucxNag8QH3VeukpdsqRo+TT5ZdfLptlE3WaNm2a3GeIjtUXjMFkkFUQHSIMTLg3Erby5mvClqcjmKaTE5IFhBvFgChi9VHgqUL3RIvw8kD0gNDAq4JnB2NL5RYrcC4YTHho8IQor4iBQXNsDSCEfe2xQWPwsD5ZG6wHlnRubq7c+DhG0fEtt9zSqFmqMIY4T9j83Jj+OM7rTd1oopYBRYSxT1W30fO2tbbn1VWVUmZzb5GReMMNDBo79P0fh+jRRx9tq2mqL6MJnUfVDikgD6nFQelX+OKLL2L/55xwLpM2q0CKHU5iDDycUxgxAOcxhgTOD7Jc9IebkaQDYgW+99lnn5WRpsmTJ8eMluXLl0s96+KLLxYTJ06U58J56VD1i151kJlcfzogvfCMM84Q7777rowMsm/UF4zBZJD92ocff5TKRl7IKqmrjljd4/cdmLzE7t05FkkEihipIIRyESheUSKUOrwlbgWeHOf1ZIqCCt0jPLp27SoFD0bWm2++mWAsAQQC54VShceV/xsYNDew3igUdvo38HKyjsltpxC4fbBUVF1cKPv7kCJClBYPKbn5N954Y4OzVKULnB5cA/KFQmtlNPGX5xzndZ2BqimCcUbJIS1GRQO9sKQkkmAwIYdJn3niiSdEjx496vlsDQzWP6LqJHjAUHASQdQH4yO6A44W6m8gZEB+0GIBmYjRpnDllVfKaA+Md5wXaf2KaQ52OwgZqAuFNIEUPGVMIZdw6JI6hxFCqhrvPfLII5MaMgqw5UECQU2Rno7XunVrWZtEGjWMwER1cAbrgPUO+aGIJtyMznSvPxnI6MFRBZsejIEYX1yrblDWNYzB1AzRlJqxYURAKUykKT/X8mJUhyNy871wWkXSz0Yz+CTwjKKEXXXVVXIxO69RKXV8L6lxqsCTvzznOK8nGxsVuseLyqJUqYBeCh0eV84LpRFKUIwsA4PmBhW9dYKIKtEG1g2b9JXbWA6QfftViW02GyI3TTY9UtpIBcM72pAsVekCBYCUWhwlymgiDUUZSxzndd7XlIGs+u6776Rx61WsrVDl0Ln8PstxRVqQ6cFk0BSAQxMZ5CR4UNkkiq67vhgfqbmBQIGUOiJCGCAYNfyu/p7TTjtN1hr9888/UkfRIzjIIHQRUuaItNBaBXTp0kUaELwHqn+IITCwSH9Op8caRhJGDDqLXmfk9/vFM888I0m6IHggsoOzy6n33HHHHeL++++X57HHHnvU+vqTAf2LiNdhhx0mr53aKwgk6ANXX/BFvHKYmiEwFlgM6aQcNFXojG5OlhfluUUIHHLIIY2ipobzJSWHc+7fJiJemrRYLC2NiA43WtGYyGXe9+mDedVi28dL5f+5lp49e0qlhWuGkIHws37vCdWq8LFiWVF/AQsVD4zb3NC93ixUFDyEBpElFTkqzhFizQXxz+ZdVyGVSd6PN4UCzeY67ww2bLA+hl473X7wuSmipkUXsWjm5zLd9vnJBbGo8Zxt7hPbHXVRrCs8mzIPnBENwVJVm+tDppCmovqSEFHCWKJvCYpDYznX2gIvNAoMXmFSjqsvtqfuLFwTFt1vjdMN67K56y1rxdLyoLxveH3xHDeG/cWg+YK9m+gKLLS1nWt8B3u0276MzoBxYuZx80B5HcwXE2FqZsh2M7ZMwcQlpItHYtXK5fJYTTg9Gz6gzV5CwISK6SOCkCOUrEeLFHEDv0deMPUVjAl/ec5xL2+2Hrrnd3hOkSXgNxWN5vlb2oveiSxRm7XVVltJ4gfTm8RgQ0Jg9AEisOP5ouP+/5FG0S79ArHX3nvnbbk+8FgSGYb8QRlLDcFSlSk4F4wiPJicN95e/vK8ORhLAFlFZAn5FnEhfdjvee/G4nk5ITke7C2NaX8xMEgG9n0vJybHjbFkoMMYTM0M2W7GVhvgzSTKlBO0FKrqNAmaSANxNrClBwghajbsutq09dA9ihxMM+o5iiCKHp202xfGT2jOirAMTdN9mz4C5Oca4WvQHEHq3d333pdwvGajsfJvbo/Bci3kh+LrY9rU96XRwfohnUI1O1Qg9RW51VjSh0m9pQ6RNJWQH4eO5dThOcebOuEDIDp/++23yzScgC/RabW43Nsrm5MTknKS+4nhZGBgYNDcYAymZgg9B1ev1WlsaS4Ab+ZDDz0kc+fLS9dlZDDpNUwYS6THsGET8XEahSpKhAJGPRGGFePAX55z3KvAE0Nn3333lekqfDdRJmjEyc+NlK0Su3ReLopDNTFadAmfxQaGcUWjTtJcDAyaG1g3dGv/5Ne/k77PSYpC7rkqPsbgoFs9kSbFUgUlObn71DVl22jCsCOnnzqlFitnit8PWyX+PGKVmNjLJw0maHZJ5W0ORhNjD+1wYUGicRROoPXQPteyhbx/GF0UYGf7nhkYGKRfu+hFBMHxTFsMNGcYg6mZIhvN2GoDvJI8SM1p3TLaWd4XT91587e4onXHl3YSiIAWYkIhg22PugJYZJzXqaJEGD/qAfTnXgWebP70FkEx5Pth/4KND8XgrX1rxH07h8RDE0tFjr6aIpaRRtpffbLt1DeaEoGIQcNDRXLbtk8kPIhE7BvtzH/jm7JPhOVGjIODGj8cCqS3wVK11157yfUFyxPMT9lkn1M1ljBVcT5Xbx5nunxw65XyvDH+FJNVczB+kVdDNx2U8PrqtfH6JWe0vLKiXDqsiCRC/NCYMhgMDAzcgQxGfiFjnZFhnnOc143RZMEYTM0QbHyks7g1Y2tMaS5A5stHIrLxWHFhgTwW8fllYR4o19bwP+vsaSKbdQ1IhUtvZkYjWeohnN5erhmmGd7L//WeC6QUcQxPsVvanF4XhkJBx2y+B2NoQFvrPVv3CopJveOGni50VFSqqQmd9Wn2a7BhAMUYR8yiRYsTXvP57NvL4I7x9VFZHZGGEgo2TgrW5qdvPi1WvH+bePWl52WaHr18iP4SucgWWPs4czAGWMvhSNxJ4/dFYoxTXAPX05TBtbKuMQxXrlia8LpeWppAOx6pifWmgz3LyASDhsIGxFtWL2OHXGPtYxgpo4m/POc4/28OYxypg2swBlMzAxsVeejHHXecTGvRDQOec5zX12dDq6uog/Joko7HuW0+epQ87guEYgaPbjDp/9cXAcoKESUUKzZ8Ik18nwLfdfzxx0tmQNJr9J4LNF+DyhJjEgPA7br0ujBokFEWevfuLSNNOlrlxZUptTRRqGCf4neJUjUlRaKpEYgYZI8sIOiIzNasWJj8Q/6gNEJwUEDUQtPBI9fdJdpMv0wMWDVVprzSIoD1k811w9qH4ZK+QpxvFV21NRCVJjWX9FtJXNPE0/IYZ9o8lKxNlIP6pTubVYarq2X6DgYT9MXNoZGvQeOGaqZKOr5B5lCGEjoNeo8ymvirnMgc5/XmYDCVRueJmje1QfLOoAZNDijnd955p5wcTPJzJnUWbT+7QOy926Xi2JOmyOJqGN523XVXSUiQTdpylc5DNIkUnLatWwpRJYQvGBJr1liMeTma07aiJnHRDmzvF3PWWN2eSY/huukirXeaJ6xMd2o8oChmUANz3jSevOCCC+RnSOkjAuTFZKfqwqipeOutt2TdhYpsKZRWxc+XVzgHZVQgdJRx0VTIH5ShqIwj/hJNwLhsrAQiBg0P5nRFhd1oDleVC5bCNcGHRHvfarG94zOk5OXk5MvNi02a9WWRKQixkVggOk+aJKPFOCV4TzbXDfOcXiY4PWoi9uvs1auXNBKQtZwrD3qdNEUg25FrENisDZN6aFdEk5GXqvRLxgE5yz11joWhaTaoSxDRZX6h3AMcL8492cAdiulT1ZYybjg4VENxWqXwHhxBvIdjOfXUj6q+oQjBmCfMl/XJBDAGUzNDRUVFjNoVI6Ht9M/l8d9/WS6fs4kxgXhfXUQdlNGkRx3U+1IpOCjaBxxwgPRGskDLSouECAmxZm1JrAhx8qC4N6DCJcI066Qi8cn8anHMBwtEXl4LSd+N8URzNdVTiUJk6pqefvppabhgJF188cWyLxKNJzlPzuOYY45Jes5cJxEpVYjuTLH7ZWmNGNM9GKM8Z5xUITTMU03RuFCGorq3EIiAxkggYpAdsNHS3yLQM34MGTPe/4M4KDhNPh/U3p7MAD+KMjDijRStv9VV1eKSSy6R65hIU7bXDYoCzViJMlWHf7e9phrXEmW65pprmnTTVsZ47NixUrGoXkFK9Ku213PzC0R1WYVrgbhfWA3BUbz4y/3Tx6Ix9gA0aPpQDZaV0WSQHjCG2M9Zy3pJA05nZLeqL8VgwvFL1LmpA2MpVUPuVDAGUzMDyjlFt998801UiFi3eOGv34olS9bJDYvXa9uVXhk5XlEH0tV4PV0Fh0XJ4mRBfvHZXHHk1kKUV7rT0lZ5lABt1TMojt54tXjy3/ZSEGAYEmVSHhGVVoOR+Morr0glBwYu1XgSY4o0Eq8xQSFEsSP1iAgV76MWTDeYwpGIeHJmVcxgCvot45X3oDjQzbqpGReqqZ8iEFHGEthuu+1sfXMMNlywPmrCYRlRUmjRqrV4POey2HMcCAtWh0X3lpZRVJCfJ8IyimFt1NZcsrydOBqI2hB1Pumkk7K+bpCjb7zxhmTE6z7J7mXFAYMHFrlD7zccNk3dGEBpmjH1bXHdYfbjffr2E7/9/oeUa84C8Q4FEfF3uI2UFziJaPKLDCZaVRtnmoE3TLNVu/6AU4U92cnE2VBgPfDbbrWWKkLeGPfKxYsXi2uvvVauT5xWPEfWKWMJJ+9tt90mZVpTuJ5k4JzrosbU1DA1M6Cc33PPPZIuW8/VRAlRxdU33HCD7FRfW2H9+uuvSy8Em55OW85zjvN6ujUHfGbw4MFykZZG8+YjHtOyOklOyM59fTKdZO7cudL4IhKkNmV1zoTst9xyS1vjyW233VYqZM8995xrzj3HMK6o/UK48ByjU0/5A8tKIzY6dAwmnb2PMVJ5wU2N8IHURZ1AhNeI0D3wwANN5noM6gekWX3++edisy3Gyeeb+34R03OniN0KExnj3vw9rmSHq+3KjU4qguLB2qUp9L333ivnX7bA/EZpoLk1azmkN3+LRtI4ThoaMqUp1/NxLz/88EOZClkWbfFge33tWhlZduuzdNn4kFSm2GPIFmA8mkIPwKYGQ8TjDpRhnfG2oR7g+eefF08++aQ0nPTXeM5xXgfZOL9kD6LiOIpx+uBgx0H1559/Sv0JXYVoDCyl6roqGvn1JHvUFSFPkzGYUFZHjx4tvfwqxYpIgkGiQGXDc04SIiBsWBgn119/vVSEa6PsqpQ8Pqse6nfVIxMiADZP+htxvsFoH6Owz++ai5ysP9OmHQLyN9mouU6MI/2cMXTo9fLaa6/FNnyMtGnTpkmFDMHwxBNPJIwJSgDfiUBhzHg+vNVacfCAGi2VyMrvx4uuG0yKwY/fp3YMA6OpsMqpMUOAIlQVgcjkyZOlYEWgQqXM2BhsuFB0/X8WDZDPn829SnTzLRM3hh5IeK++PsI1doPJpoT7hCRVefnll6XBhMMCYyRbNaFPPfWUXLMyVSXibWwgb5tqnr9a8+T6k6ZTmJ/oQS4vr5DGkBu26BaQrylHFHOC5425B2BThCHiaVxoqvdDGd5EziG/4jnrtSg/R+zQv1j4RVi8+eabYtasWQmOj+XLlzfJFikblMH00UcfiZNPPll6+kh9wKtHIS6T0SAOFubChQulMekcG9JcXn31VZlyoVhRapuShyHAvfj++++lcOAvzzmeSUoe53L11VdL6u1JAy2O7i06WyFhHnrvJQdBVQJUzq2TBYVzwdgm0sN1t4ysFluMHCo9JmzwMPURccOAco4JETtqnVCEmHNzv3hTXNv/J3H9uFIxsrPDYNKMvKDfJxUszofcWQQOIW+MkMYmPN3A9Sqads4bI2lStBC/Z8+echxRrvA4bajC08DyMkIgsyqcPMWKlaEHZ1gfUIq7gfWCjGdeIcPYtN2cGQ0B1q+u5P9b4i6EcJ7gTGkKa9sL3A/2CMY5R7duo0BZ0tf6lLcT7wcyD4MLGaHXOjXGHoBNETpjq1LSTRTP3I/aGnroiqqcgvV/5/Z+8dJuZeKqLS1diBIGdDSIslZqWUQ4npuC43eDNZj+97//SUEBs9vQoUOloCAyMGPGjGyfWqMCk/jbb7+1MaAo4EFAuPIaUZ3apEbw/SweIi5ujc44zuvpLCY2XwgUVKFhbjCuUREh4tgfKyJpRZjWVESkokUEDeNHzyf+448/xJQpU6QAGNE5IGYd6xfX9f5CsvMxRpwH3hQ63LuNycCBA8UjjzwiI5sv7Wix94Gu0T67IC/oE+0KdIPJ+sv3q5A26S6cQ2PxQiejh6e+i9dReogyEZ4nFE+kiYa9pDZiSDHXmlp/KYO6hU7h7wVWcTSALPHGQQWuqV1gzpy5cm4p1krWnZszoyHQt29fudcotrd1le6OGpQNaiObsvOA+0E9CLULNY4IoDIedXrhu752rxlB5hG514mFUMqoATNU43VHxKOMJhPFyy6a4v1Arm6++eYxxxTyFZKdAwdY6/ukkX6pg7GWIdBC187TShwaY9SsIdBkDCYnVOjTWUuiA4HNZNAfzR0oGvQ1YvPT09rY0BX7iaJ8rQ1QpFH8Mb74zgEDBkiBwF+ec5zXeV8qcC54jzHgOO9fF1v357O1XWJKuF63BKv4yW+VuX7X2oqITNfEYNpss81sRcXMAzynjMfZ21jzpVehZdBRJ4F3mN/j3J2GHs/vvvtu2buK783VU2G1xpxt8n3i0q3jaSy6coiigcBBiGJQNoZ5mCoXnqibugfcV8gu8EYRScR4olaM+64a3G2I3iYDC+k4Xogu6WsiGZBNGOqsYUgDUDwyiVrXJZjXGGw46ZAfNMvWwTGUD9YIxoBX1KwpgGg6LSn426qFvYC9siYix4J7wDWqOjMdar+hJkIpjKoHIE4X7iHkO8ZoWn8oIh4dJoqXPTSl+8E6pmccddmsY+QXuhNptDrUubO/k52zbt06+dm6qkUsr0pk22zsaJIGE4ocdRXjxo2TXcWT1T1x09WDXM3mDtLRMADIp9dpXVkUTHBeZ8NLt3mXMwpB9GbChAlygfEaBg8KNt5VvBEc5/V0SCXwULCxUg9DLUyXPMsjGfYFYsp6v7baFPUFxAPfRUTOVYkGx6u/R6SRRhNaPN76OeMxheyCMdmrR9w4WLV8qdzkOVc8yLfccktCbRfnhmGBEUgDTR1VSUJeKsIkySxKS6VywRxE8WoMDFF67jVRPiKPeu419wPjiHsq79E/i0Wr318QhWWLpfeYFD2opDFGeX9ta+IMmj5wdqQCxlLAQZjgiWgUA3nNmkUBJ5W4oeeXciqw7mF8cyscVnWMrO1tttnGVjvZFMF1kMURqbGif/NXh0WfO9aJjjdZ7FikTlPHiKPJ2cxSjQ8yFYMXinLVHJx6RwwlegD+/vvvRlasJ5DTOhEP4LnT+WXQMHKCOU2to/N+sK82NrIn9n5FJ87/IQnr379/wjkiyzCO0Om4ji+++ELqLnURNbv/ozmi/yX/Ex/Mblp08E3SYKKW6aeffpKhwmSg3w4CRD2UUticwUYG+wmeWQyFOHxy8uNFwEBwehPSjUKwYHbffXdJNUkqHcqSylVnQ8WA5fV0jQI2WdXA9qjBlgGykT+eTrh977jH1hcIyoiGG714IBCU54GxNH36dFtaIEoN6XfO/iH3b7NK1JStlhs510Ldl+p0rcBnoUpHaeOhw6WPbgyhqDsdpUJ1y1b05Y2BJUrlwuNhggyDwnpV4ImBhJBkzPg/9+L4oTXipgkR8eKE+TIiyHgROSMqR30hRlRjiJwZNCxYO0QlFD6uGez6PmqW0o0wsaxY56TSYrgj67Mxv5RTgegILJpuKYTIFNYHzhrWT2NSjDIF4wvJBo6Srp07xhhL56/xiaqAlZ6D3EDm817neCgnl6pjIg0aQ+nSSy+Vyhfvx/DkWFMhv2mM0J1a7E0qiqcTD3B/zPjWPxhjsk/23Xdfmd6G3qPuB7rIscceKyM5jcmhyBo+6qijpD5Caj26EnoYDlAdZJKgS3JNONwrKyvr7BqufftX+ffcF34UTQlNzmCiySnMHrCapWoSiELH5NAfzR0o+KSQED6d/esvseOFRUUxzx8eD8X8lCkDDJ8988wzxdtvvy2NMwwzjC9ozHmQDnjeeeel1UiOhchn8FrqdT1dC6pim6/ulS6r8M6ZDfgsel+uibQ36myU4YNS58ypB1t3rRbnjq6RSj8bDNdy+OGHJ8wTzs3Nu1yThOYc3LJDrjhls5BUINjYGkNkybk+dt5551ix91lnnRVjw8NbTs0B9wFF58bt8hIYwZhjvIdoU7Z6YBhkF8wBfV1FJL2De8TVGWDK8WB65W3IKeYdMgdHzPDhwxt8/SAHSKuhXQFRYvD67MR5zhpRUf2mDGQnxhL3dNnSf+WxqpqINHa4Ru4DRqyKLDuzFFRqIsdVbejxxx8vDSzGb6eddoql8G6oNRDrC8ZUGUs4+HDEOYkgMHrpg9WYlPTmCii40aX4S9q9Slvda6+95FpCF/nyyy/lGmgs8121WUEfJIjAeiwuWyAmDrL3oWTNMp+G92oj+vXoJNc3USbm14bqHG0yBhNKJ8YSVLMov3i/DRKB8s9ElxGRkjgFbMDvj0ULeHzyyScp64zcGHkQDGrD5NiQIUNiTczwsHoVcruBTZhQNgvX2fRNpXvoSlbrNu09v6u0vFJ+hu9iwybKpQwfxgQFzC0NcZPWVtQJZYdUFGeomfOiEBrj3NmsTTXh9MIZW+SKO3fKl0oEih9GHOlvjUHYqOghXrFzzz1XKqNKYWIcrrnmGulZRxEk2qSDcWaOofQwz5TB3NgMQoP6B+uCuaIQ9jCYcguLbbTi4Ojh7mnB2/UJ2r6FubbjjjtmxeHFWkXmqfocr6gyygQEEU15DTC+1ICiQBXkWg6sQChHykAyClj3vEexZZFNsKwingFAujGyUqV/q/YTGFkQ5+BEY99ASctWTVpzofFn/Nk/lQIL2Ks5TguLTz/9VEb+G8Ne05yhMjGU3kB2C8YqaW7U+bJmyOhxc8RmCxhurHHmjqISf23HpeKp8fZ+dzhC+7UNiue3nC1eGfeTZMkF6AjObJsNBf6mlIaHgoc1zyQlLYjHhnrj3MDmRHE+AhWvYEFuXCFZu9aiEWfjJ6JDBCGdOiMnAwxkAKNGjZIRE45hBOA5ZHHxOkbFVVddJaNcqYDBhpeMz3kZb9P+ik9RNm9VM/DED3ZvTVm1pcmQhki4mfNRfaForMn1Irx+W27P55N04IGANPzwrDoZ36htohaO153X1F5jxUsGjDUUhbfeektuZo2BVU71rGKcaGQMaQebLWNw6qmnyvvKZturVy95n92uibFlfA488EBxxhlnNJoNwaBhoTsZCn3uHu2Ww3ZISMnbvo83QcJGra11jrxi/pFR0NDKH/MbdlbVGgBlNRRMJH1AJvEe0lQbw9quLZDByCf2j5pqS74GgjlS5pNKB4sWDjHWOdfMeNwxp1fs8xhW0ImTecC9QkZgNPEZ1bONz1Ev4dZnzyA1kNGHHHKI3JNplQGor1Vef/YZZDjjbJxY9Q/WwpgxY+Q+SfoazhVkBnWPzHvWAul6qbKhGhLKEc46R2ZduMlc1/ehLw1taclcf7hSErZQn45jiHKYDdEYbzIGEwIBLz2KL14s9SD/0iCuBKt6GZSMTh2svkaq6SCbOko/46YU3kwYYBAA0LgTndpiiy3kd7GJkp6nevOgMFCgnc5i4vPbbbddrIbJCYT+//0cN/pWr7UKjzFwZi+3u3pb5lobMAKKiI5K+VDeFKJfXMd3VqZJDDv2DcrvQ1mgQFlvRqvA61yP06hLkZGXIHxUM9jaMhTWJbhPpAsQsSVdAAPppJNOkmOF14nIH+9ByUnWnFbVdhnHxYYL3UhYGHGPAufk5SdEmPbsHxLHjvAgn/H55Lpjc0cRYd03NB0/ax5PPXITJx2yJeS4CF7DAYXygQx0kx9NBRg8GIZcT4d21t7RoVNnqRDedtttokePHjEGUrIUUA4LAvG6UPYUjsl07EhY/HfXsLhmeys6jSIP4QMyEPm8ofZxqQsw/ijgKLDoQ8pogrQI5yBzkOO8nsqJ9fPiNeKWd2cnEHgYpC8jKENQrQVYQzjylT6DjtNY2w3gJO3VrbMY326l6+swULPmdVl3wgknSFmILK6tPC6rjMuMpWvtZRKNHU1GurOg3R5YygaJKXSyb0mZlXcPfNHXMQoQuISO6S2UzqalGHlUXQHf/fXXX0sFe7e8r8Tx4cfFvNk/yQJCIk8srHQXk0qhc2Nckn0//HGFqqhFK6mYyKaqjql7wqgc+X4iVhhwu+yyS6xujfQPDBUMgZLqRM+mKtrmr/M8EHSE16HVdBp1oTRLFvJzrTQK5Y1uDH2YqFXCKFLFngh6rpO/3G+EP9fL/73mCNeDYfr444/LdFlDF7xhAqWgRcRqkt1axNOAnWvFjSTvgd3yRb82fte5hZxRTJykF2WDJW/OnDlS4aHGj7XQwp6VG3M8sQ6odWrKRgDGEgXsKN7bjN9SHluzrlReN4oTDbxHjBgh38c+gGzsVxy/XuQnrQdwnmzVpUrs1s8vThywOsYUymfo24ZzxtQwrT9wAGIU4bxk3qG485fnHE+HyWznOz4Rd0z7Q5zy1Hd1cEYbHtClSGFnbiMrSMPj/+ga7IcYT0RnG1OqLg4NSJ5wmA4dOsTzfegCyF6FZVGHMXNsfWqWn5/RdMnXmozBZJAeIC647rrrpFe2vDSuvJBJwiJWhYkow6RfpPJ8ELK97777ZNocrCl4GkmpIOWPRTdOzBCd/cvFuBaLZW466Xgww+gCwouxB4FCCiECpk0re50Mv4UBxIatMHLUaJlLLyNH1Ykc/nyPiigpRV+xOeHhZCNfuta98JLPYURyrfqYIFzwhrLhO9NIaFabDjp3tGjLFblCY0jbIe96v/32izUExSDGiGJ+8Jqq11LF7k5gaKmoGfMK8od0GpgaNC+wxrj3a9ZasmZC4AfX943M/0cEPNKwih1GCGhZZDWuZt2ylnHQUFPXkFBKPWsEmXDVlhGxRRf7e9rk1sg1ggLhZOFsikBO4XneZftt5fPyGiFrV5Ht1Dtyv5GnKFM45masiLOtclzVsBYX5seO8xm1H+AcIwpFUbxJ4c0u/loel+1vzjSyuzbA+cleSZYGuoKeaYHsUlT6jS0DA1mF3Jr5o7u8BjifdcMoFArJTC8yjHjUNmq2oqRxkF/UBsZgamZg0T755JPWJqWFQI4eYi0SDCCiJSwWinaTeT74LjxVRGwU/z7eEqIJKP6LFi20CQcUZzZXfkMBZQe2HjcaWRYjRgib9CXj7MoU30fot027eIqPLxCKeZ7diq+5PqXEX3LJJTJiwm+rFEUvrwjfSQQIAeBM/UExICqEIuDssbL7xuk1qQwFg3JM+A7qxjIhxqgvcD+hO912221jxdlEnLh+xnH77beX46UYwHRs0iHXdoz3UDtGypLBhgPVAPHggw8WNTXJnQCnt/0sISVPgaCukzGvuCAvxjqnyAacxDD1DRwHRKdVdPjMMYnpg8W5AbkWkFdOFs6mjMLopUaCBdJZ9vDDD8ea0UKos8cee8hahj9K4gYT9ZDcMyk//fEbStYBcoXPqjYS0LQ3xjSlpgT2VhRY1R9HMUkqIohUPZnG3/hBg51rcwVRF0jIcNIipzCecPYir2SGTCQiI89OR2w2wbkRFWO/nzfXvX4JsP/3bBGX6/fee6+szyKKvD7OobIm2LBWwRhMzQiK+YzNCK+v6gWkoCiiMWwIHasu9V7AO0KYn5QU/q8UpCOPPNJiPNJS/rr27i+jE/fff7/k9+f/ql8EYWk+70xpQ8nebbfdpKJx5KZxC+jCT6x+Sxh1XbrFc2g//PgTeS4IoU30hrZRcFx5gwmP85f6G2jO2cxRbNzSglSq3Pjx42Wtlm5EYiRBakE+LxEiHUM7pZeTt+CvP+XYcT0Ym9kuAFWRNwzJ0j+/EYcPtbQjlBqMJ/5+9tlnMQPUaeAdOMgfM6RU7na6jZANmg9UA0Q5T9J4/yStp5qzFrBrsX1hlq1bHZNPGC4QuTT0ukEOEEVHUUDpd0NBgWUMUBe6vs0cGxXCllLTsbM9pIZ8xMGFR51IFE4shdKSkphcqNSaerdpaRm6ONmQJ8iLTNK2DRKB/GYvfv/99+VzapZo96FqmjjO641FSW+ukEQwoZCc86o5fefCiAgE/PL/GCfMd9XLqDGRu2AQrVq5Iul7z948rmdNmzZNpuixhjNt86B0DvDpH/Fa8BE9WjWpnmHGYGpGUH2TVC1OYZ59gWKYsKGxgPGaepEt6MYCmyLvhciBdDy8C3gaZS8eX1xN+u7Hn2QUhd/GmCJPHWOJNC1Cu25FgixcSCT4HT1i9FdOP3mOnOvcP+fHjufn5UnlnYVKzZITetQDTybsNESpOF+MRBB0REvWVUZiRBIYY5dddpmtFgeBR3+igw46SArA75dm3mvFJ6x6O84P7182hYMyqlEC77rrLvHixMXiwV2C4swxuWJSL4vEQaXXeRlBl2wVFN1a+GxzafPNNzcpNhsYVANE6lt8WkQhU7D0nQaXP1It1wzyBycM/Xwasg6AdYIco86T6ArRFDdgLBJ132STTSS9ejrsoE0CEctgWvyPvZ8eJEsQYSAnkJertZRpEbYi0nIfKovvKxUlVp875dCCHIMIVWOq62hqYI9647VXRe+aOWLCFkNlJgj1yaqmibRHUsmbQ12prmw7kW1lW+k1OHd4HLRxhXh9wh/iglFlloPW75d7pNPZmk2Q5YJhTflGm1beTh6nk2hWtG0MegGOk3RTapXOQbYPTvSfFsXvZb92+Z4ZSI0RxmBqZmAyU78k06PC7p3YVRNCDIBkXg88uoSSCd9iCL3yyitSkVbfk0M3Ss34QXkgbQbCBWhkeS+RHZj0VKqc83z4HAszkBNfnP0HDrK8lz6fKNU23gkTtpFphESmnPhyUU0sHQQFHvAcQ4exIEIkhZpDNSur9snX8Hhi5OEF1VnsWMSkOP70009yzEork6ce0cy2IkpxrqACfZwbtRip+l/VJxRTH1G/d955J3b8holB8eJeQmzZzapF4Lq5n2osdfh9PvHx4Zayw7zA4CV1yShAGx5wwrBmxHqwwxFhcpJ0fX50oWhfYKV5XXHFFZJYhHnbEIqT2uDx0D/wwAPSyUEvITfURNcKMo62AU3Zo68rpmUllgysrKqWqXTUOyLbVV0XMoJ7M+uX2bHPD+9sOVikUVSssedVlsSi0DxoPM/9bAoKUmME44YD8OihQjyw9QpxvO/p2GuqZpeIJ1TXTV0mO5VtHcnS/RsK6AqqzyM6ziWbWQ6EYweWyXWAzMK5wPsaS+Na5sSUKVOkI6gg33t+OOuuSqN13KQcEm1Kd8yVI1/18izKjTvXfv71V3m8qZDAGIOpGQGFHCMI5Z/JrtcwgZM2y5MLGyVX0UWnmqR4j++++27pYWXRoxQgCCTjXtd4ukYgYHlRULDZSBFmNDjDm4jwpv7J6ZHAG4ungjqaiD9uuIVycuVvcS377Ld/7HhRUbEsPsawCTs0rOqaiLwuFDjGAYOL3yXCBFGEKlb2aVExwPfgSca44zfPP/98W+oPGxBUraQY8v1Br0KMKO6bUSVyHWQQGBh4mhSNejr9r+q7SJVCVNJqnDhoU3+MKZDr9aJA76E17SXqeNNNNxkFaAODYofDgRGIpmbNXpk60jR7mT2HnTTZopzEXNm3D8qXcoz00Oeff15GmhpCcVIbPPIRogm+36v+sbKqSpLgIJNSpTg3BcUUA5EI8xeffyaPB0O5kqABwgfkPjKZvYA1j8xcUxIf7x4t4/fw+klxJo+CnECMipwsBOQt/RSJghhkfp/ue/j/xJVXXSW262IxU7aKWKnvRABgrsWxyV6LTG7qEU/dwcc1qrWfKt2/ocB6V3T8OGjztUCS2jtxCFPn2ZhITtCTILkaNsybJc9ZpxSJ6gVKPqY75jp7M8bRuor493arXiyPu+mHjRHGYGpGYFMiuoPHX0YGwvZN/vbt/LFCalW3kw7YJDFAAJsmDwyRYUM2jf92fr40jlgQGDWk2iHcUSTYcN3y+3mdiAveikotJ6+4RSt5DXzX2/97N3a8b98+sYaITo+0bsewAIlEsaBRslAE+C6ZFudg6iIixEauarvYZPQ0BsaUprWA7wjXJKfTdOvNxLlxPzDEqNnKptePMeE62EjdyCeOGhYSHVtYyi/jouZLMjCXUGh/+MGbccegeUBFIZSC/cYbb4q2O5wkREEr+brf4ZBww+M/2tfQEcNC4pYdEtfEsE7Woma9K2pxjBg3xakuvZRqg2fuqzXiTaMbkXWeeF1TpTg3BcX0448/FhdccIGojjau7dKtm+zVhnFEpE2lGVHkLveQUNxA/Lcsri3e8VV8HHL8kVjkA/A5xtbUPWaO93/+R9y2oLv4stehokV1vD/exGWPiqX37CJ++eVnuV6oMXFrON7UoFLeSOtnDirGxlTp/g0FZAXtVHr37i0G9t/Y9ho6Evss6afZdJI6oVql4Pz+7NNPPd/nbLGSn5cbS8XNtJck30WNuDPNr3/bkHQiJ2tf0phgDKZmBjwdGAssCp8jJU9BNWIkEgT5Q7I8ZybytddeK/Oh2eQQwkx+Kay+fM9W8EvaCoYBG+HgwYOlYYARxYbrxtiD95ZNGC+RTl+95Vbj5XehAP32R5zF5YUfl4uBAwfK33/CoXQFNTYHIieqlgrPqK7EOEkfdJmAIcjvogzoApEomGLCSkUk7ox8qd9UBhkEFHhnswXGmZQYUia9DLfLt4obSZx3MqMJAcjYcN/dWMwac/65Qe2jEEpuvPXZD+LDhfE0VTdSFSecvQr3GRAS2/dJzPG/52tr3TL/mGOsfSW3SJdTipNib6tLLyUOnpNPPjkl82Mw2tSaxqHIj6YaYWLc9t9/f5klgKyeP8+SuwsXLk5IreZeMC5WkXsrUV5j3fSS8qqYE27x2rgc9Iv4/OD7cUDxW+xVBpnhlOfifXHa5sT3wE0D88Q27VeK1rkRqaBTW5jpXHST0xxjH82WnFZOCPQI5iBzkVQyNSc5nk1HBb+LXoDO07ZFfkJ2zrhx4yQr8RNPPNFo9jrkFA5tygwqy9OnOw/6LecVc0I5xNMB+wRkV5CF4UBvK6x51tG3RtY+oxPhVCeTqbGMkReMwdTMwIaGscBC1jcqBUWmgFFAR3dIDmCCcjOaZO+Rq66S3ggEFJ8l8sOmyML54qi4wl1ZYfV2QrgOHTpUfvewYcPkAlGeIadApnaIjVf279B6E117/Q0xAegPBMR7VUPEJzWbilfLNxX5xVYn+sd+qEqI4nB+eC9ZdBQnk17HeKBoKW+mL0lEiHGZOHGi/H59DDAwKJBEQUiRkSfc2JWpYeKcaBDL2DU0PbIOlEu8RIyLTv+uo3NRfJQYU5RUNyi6dYqNMaipdcP7hAHcFPLPDWoXhfjggw/kJocX+99Vdk+jV68lHWsr7U4FFx+DxKpy6wXVrBoFm4L2F198UUaOabKqG0t1zVLHfKaGM5kRtsnG/aRMRGagOCm51RSdAaxjiH2Qy0qRWltSGjOWVGo10TTuh2LJXF1lGbvhsNXU3Gk4hzSZibznew4//PAmkYLTmOGWzbBRt05SZkNWgnxNNgf1e9Si7B+5z+tymv9zjHqXVN9VX1DRI/QI5h1p/irdn+ccz2aESaXkgZJ1VoqkDtL5cVI2phodokOck2whEo0kp4PystKYczTd7CT1e1YbmkXScCz7d5483rbqX3H00UfL8gCcyGQQNPYaUGMwNSMw2TBMmKCSttWlsSqbumrwiuJBiguRD7cQKx5cpdCyuPgcyrakjnV8tYrwQKqQP3+a2HHLEXJjZKNVlN5OoYYCRDExBpZP05pm/zFXepVJYUNpOXXVoeLQqgtFRPjF/J47S2PNH7B7pNsX5yVQi/M+/o9SpULBg9r7PTcd3o8hqUe7OGc+i5Bgg9fPU+HR7yqTbmL5UbZCxpFc5mym5EHRvOuuu0oB7oU9+oekNwkwj7wa7UaiHnWKizEo8VgRjaNPC0aTs9izPtOoDOofzH+81zhAMIxvuOEG0XL4Trb3pJOSt7YikrZHEyCbkD9EcWDLQwYxh5TMYs7VB6U3ythDDz2UlOFq1YplckwYG6LTGJQ4IpqqMwCvOE6ynJB1zctWrLTVoSILWbfsBThSMBYDwVBClF/vaKGX0rLWyYDwcsIYpI8aF/Wtf8sKua8//fTTMrsimQI6tHs8wrcmv5NcX6p/k+rxxDFFtpINOc1vsqczB6m5Yc2TAstfnnPcjVCqocBezn7HOfw5b47tNeQA+xuGQmOqbyQ9cMSIEXIdO0mwFOatTNzzAz7LSUrNJo7ldB0e6HGXXnppLMV55SprTv72y88yGwidizrzsWPHNnqSEmMwNSMohjgm6M477yxyHH2YFJRRgYGAdxavoluPE96jmssqwwPhKfNRezrTtCzmvZM3yxX/t2OlGP3NFLnBstFCuat7X/XvR9lBgc/LiSsly1eulueDIMIjWROIC5pI+74WdW2VPd2wW2GV8EWpcBVN+AknnCBD4pw/ij+eoK172ZUf3cBhsVKLQzqDirgpRiKUNK7BLcKkk+K5GUxDo+mJnAceuwcffDBrihQMfXh0UimYY7tb95f777XpEkxgQ8CwpsZk8uTJUsnEQKYpnrPYU88/r480KoP6B4Yx65L19eOaPPF3jp2xskextdGeWnmKmBfuKJ6qnpDwHVD56/jxX/dGhkrRZr3jxKBGDmONtcN5KKX7pZdeStmkM1Og7Jx66qkyZZjf9vKoVldWyIgbhgYRGtIVidjjiGqKzgCum4h6p45WlJ3SUozjSZMmSfmFXMQw5Fqpax0zZkxMFrPd0B8vclkLcfDgeEsCfR9iTCDxyGaKUnNJEw6LxFTpU3rNkTKea+CRbP6FHZsV+gD9m2699Vb5wFgCUFDDNpsNhZ+9gXQt9hWMc5RrSEf4y3NVI52tPYT5wn4uyxEcjHPIKOY7D2oDs8mO61brLh3AHu9xSxRo1bJYfpZSCiL96Ro3jNGXX34p9w35m1EHCxErDCh0PGQ5bWAauy5gDKZmBCYwk44N/t133xW5DpY8BQweHqRe4CVms3cDCi1pN3gVVSd7FbVpk+9LSMWRfQhGWF6rQPlKqZSjEBNJUmk1zrzWs88+2yKUiMQ9GuWVNVLppqs0BleLNfZu1HzWzTBpl28ZjSw+hBWeqMMOO0xsv/32MrL09G6Jipn6HtWBnmtDIPDgd1CAYHSiZgOjya1GQ0/D0/tJKRTk58qxRuli3N2Mx4YC3nLuIUZgOkXXyc5TjQVNgtlQ2by4PtKTVG0av6MbTeSfS8+WzycbHDerZp8bANjQzjjjDOmQyd36ONtrfXxx1rM/Il3FhMpbxS+RngnfUeYorXzjd/daSx0oG0qZpZAamUFOvG6M15XRpCL1zF3mqTfhA7TiVdIRwxpgzsNQRvoJMqipOQMwljD22DtWRus4/f6gHHPSm2+55Rbx5ptvSk/whAkTZP2B7CtXVRNrM/HrKVZ60rgeccfUtRNzRe/Wvpg8oWnm66+/LlOUG9o4aU5pwm4RJl8kLA0JlSqWLP272rGJMleJhmA0OY0lnBLZGBfW4nPPPSfT79BrUK4xTvjLc47zerZSudAXWPucS26ufT9tHbJabjCv9NS9bIN7SKoghqcXrbibr713r57yGtAf0Bspv0gHKmWSe7TjjjtK5k1A2i9kGZwHOmZT6BtmDKZmBkLVbGIyjSXJ3UVZZvKi3HoVdRLlIT2DyYzioAocQY7DFgsF/VJ4VFelZwjgISKFi3M95JBDbPVWa0rKpHFClALB3bW9vfA6UNDS1WDCK8JiHjlypHxOTiyF2y+88IL47w4lYteNQ54kDXwObwcGBdeNlxUvKN4hrgvlSbLGuVhMupHkdl7z/5wnBQFGE0rGsccemxVFintMbrssvGzbNqkimEbtvjSYmGPt8iMxFkIEKuPH9aJYk//OhkEkETB/uPcIbML0jV1AGrjPIzdDd5z/pwRlLuyyxeBgCFy5RrzyqzX/PALhsTm4ZY+AmNQ7IOcrv0ttJAXC1CYqYxzjHE9vXShObO6sj1GjRklHimJ1c0MkXC3nPrIKxi7OEYOC6HZTcgYoTznjSJqMqm3YfMxYafwRQX7mmWfkXkHPNdYzDKeMS1W1Jbt9LjWzYJteQTFnSjwFDxmATKC/XUPXxjTlNGHnOIVdpDQZENxLVcec7DpgiNUBURNzljnAXohTAlZXSJuyNS7svRjY7OWjR4+W+wtOXP7ynOO87pU2Xt/ACUrZAWsk7GCdDa/8S46ZIsrK9pxSkVUejBtO4fIy99R8t0ya+fPmyr1bEb9k4sjfZ599pF6AE7xKeZhrqmXtEudFawpSLBsTOYYbjMHUzMBmjzKOF7YgWjvjBJOdnFE8NXgNjznmGFeGEp5/8803MmcVpeHB3XLFc/vmuxZ349mStVEV5TaPJZsQxo9TeGOokS6nQta6wVQT8cWiYCzQQNCurBQN2ErkFyQ2VA0F/DL1jt8hasb5Y3DhNevawn2q92sbEFoftVjTVmUoYczhAWHR85p7hCm+8fRrk/g7a1attGrKcnKkx4n/ZwMISqJuXBtGk9Z3OCkm9HJXFhmLGccVin/PLhZ9W1s52gg+7plq1kdk4LjjjpORJeXZwoBFwWR+NJY0BYPMohDKA62jUoSSer9jr0Usx0JlNOB7zy52dimF07fIlSrhJ0cWivcOLRRt8izF9sADD4z1l2EtkS6GsUKqqa441Ta9irXOuscoQNmRMrXQ/RypaVTzHOOf+U+dYlMylgDjhlFEKiHRedVvLpSbJ+tIkRk4jWQ6dGVlbA2jdPn8gaSGr8LmXQOxe0ZqLgpSQxd6N+U0Yec4Vbuk5HEPuE9EPFQrkEwYXVlf7HMYTd9++62MLJIGm61xYS8h24T5h3OVa1JtTngumXR/+83GbNuQYDzQn0hRLV231vZaWamlQ+BUYA1lsz7HyXD666+/Wn3QPBh30A18uXYdq7ysRDo7uCYc0Zn0+OL3YdZjbkZ8lmzJyw1JPYF59vbbb0vZqeRLY4UxmJoZ2NyJsLCAc100YpRcFjDClwaFeBXJKcfb5wyx8h4EKMLSX1Mhjh6eIyYPConXD8wXx420R2uUIaE3hlWN5fAGOYUt/4chRSkW+qkS/WJT5TwRMsOGDU8oWqxyyX3r1L6NNEiIFkEkAX2ts5eAG147sCDhGB5mzplx5HtIs8nzVYkB7fxJm7juNygxipWTE5IpiaQmwu6TrfQBxpLrUfc5WQRSxwv7JY6PuueDO1qb9p79rdQdlA9V4Mo9YNwwuhHWbHB4lFRdHKAXRGP2KBkkpqphHLhR408OfBT7fyTq/Y6EvdNg3ZwLTuhZxV1aWCmtGOD0CsJAQX5dcsklsvgbD7nyfK5vehWfwYmEDKIGs9CjfIM1wHgo1qn6qqmqbzBuyDnGEW/5Pt2sHj9rZr0vZRYKKusZ2UsUHq8+kShkSlllNFKY4nb2aeMTfbq0kbIdGcBvEi1saEVSpYqzL7E/qTRhnW2xsdUycS6kLOlF+lVuBhOKrs8ns0Iw5CGA8LoOZ0oe8rlLly7SQUo0AFmOjoAh7dVLsb7BXMT5iWLNAyfvTjvtJP+qY7yeTRIR5jNz2Bl04V4peYQzJ5vZFHqftYsvvjiWKeT36AMRDIZEj9OftR3LywnG+rDh6Ej3etgryKqBXl1+d47lMG7dsoUcN84NBy4kJaq2qrHCGEzNCAhG2HHwCImls8Xd2yWGqVGS8SCx2bFJsLGz2asaGwWUalIw8CQTRi3MiS8sUtvG97STJ6h1p68/vp+0O77XGVVR0R8iTR0HjRGhvLhSTkSHzQsBzSZdUGjP/UUJr3CQPoCq8pJYjygKxPkOImmpoPeA4TzZLFV9jYqMYQCcupl7zc+e/ZPXAlVVlMlzYvPRGfgaGsq7qmrJ0o0wefXW0Y/TvFulu7B5oVRxrarmjetnkwPcU+6xmgMmytQ0oCKkyth1YqT/98SDLgaTishGM7mSQp+jHdq1lfOJOXbXXXdJwwTCBeQBGy6Mm8zxukivQtnEG8o87lj2u5h/ovv7YAW0GmlH5G9jWDCfMeSaktHEuZ900kli2223lSx2+cJSqLr6LQIBalmgckfxYWz++usvKdelxziqRugseW54cu8C8cex1WJC51I5h7baaitx4oknZkVBUuyfRNyVQaHYFhtjLZOSrZ19lpLaTqwW7X2Jjre5K62IBtdAbc8777zj6aCr0YpvfTVW83aaiN58880y7Y25z/0levP4449nxdGHQk3qHeuKe9YmslK88sxj0lDiOcd5PdvsarIRs8NjUFiQL/dCZAPyiahstuaT6rOmygsYO44FHGzDCm71zQGfdT+4VpygpM+pco5kDgbmEZkJvEfuIYWWcZsTtJiQkQXIUOasMuQaK4zB1IzA5KVgk03g8i3cG5JRe6TCnii0LGYWx5VXXhljylMbBt9F2gXvHdIx+VRRsiKgGV14rFBa8GpQGKkWlGqGx++T/pG7y4ViYaS9zSNBV2hqCEi3CWrd5AHn367AJX87mtanjD+8OnjJMsm35Rz5XRVuVsWaLGrdaMwE4ZoaKRBUAXk2hQJjgyeec5nU25suWYfXVdtScKJhdq4Nw5DrZLOActwSzAE5thixeDBRyjgXiscbUxd0A2+wWaI4s3bTXVP0UXMip6cVMU6HXFw3mKpIiY3+LjLgk08+kfUDzCMiIyiIdZVexZzE2w5D3Nv7e18rPctYS6rhKx59oqZ4S6Flbux9RXRgLGAQOSMJ3HcejKP6i9xGfksmNo0lLx28vL+lSOJNzlZ6MqmHigER5Y/rwADHEFTzB0Ohsdw/5exScvb5nMtd3/fabxb7LUox85E2El7GRKyWRNZDWYCxFkIO5j17IL8LOQc6RTbqhNh/WYvsE0fvubV4bNRMcW3LJ6VxB52/2j+ySdnN+ErHrEZcBSoqyqV+hXxgHJlr2Uw3Y82x3pjjGN/llVUip9BdNgZ8XIuDRbG6KuaAwuHJ/2FYph8eqX5eDgZkNvsGckXW1lVbTrSKslKp6ymHOs7zxt5uwBhMzQRM1FdffVV6XhAmXnvXwUNCYoc+lhKDYMVY4oGQ5DuUd5bvQRlBAWbBt85LYTBFfzBf08ExWBC85MtedNFF0gjD08DiIo2GTUnm0cLJH7GMtWcrxshNiqgWhAF4PSPRHHkdLfITBWReyC+vBQWKPgOq+LVLBuQ0jN20adOkgQc4fyJtpNTpxmAyLFgdTjAmVdEnQpP0x2xtxBh/jBHn89L+7ql2IFe7j16pNttuFH/TGVvkxArjmUMUhHOtbLrMH8aV+UYKDJ420jww0lHQsu0dNEgPyAeMAeZOukauW9ChYJtjRU6nfikjnNPmVduiFkPaVEjDBOWINU6KK3Pn3HPPlR5cHDNEQeqimS00uCgAyYhRwBN75ctz4H2kqKj+UCiZ5OZzrLFEKdKF83yhEOaYIklgTVPbopQblR6NnFBEHqnAvUMOZKMhKteAcQRDF/cK2YQ8oh7r9NNPl9Fw7inznDS4xnL/UCo7deos/7+R373peMBntQxB5pKqRq2Jt8MgvrZ4P3OW68dRCrbcckvpROV32Q+znQkw0G81PFXX2ViAroSekOAwCNfIMVPpcIq9MFtgrqPPITtxBrTZ/1rRafJlru/F+ezs0eT3WY4qjHH0OIwd1jCpy+hxbtF8lUrKeoekB92jKpphsHzZEvldrD/WG72deF9jhjGYmgkUgx0bN6lPVVEr3ol7d8kX/zuk0NaPiYnOZkheOp3t8b6hcNCNnb8owm502Tr80TSd4Z3iU0rlGOORJm2Gv/wOi5UFx6aFAg1CwvJSzvRbBBNcC8KbAsXSCnv6XevWbURRqzYJ5zC8Zyu54Ihe8LuS7ammRjyye2qFXGfB4jxhcGMThSUQYcf3bNQrkSLZDf+WJAoa/btJF8yGtw7hRYGsaqSXDO8cUihOGh2SPVWKPCJrfbUalF4tLSIPFFqlQHJ/Eajcb5kCUFwk7wvngTKJ4dhYlBGD1GDuIiNQwJA3e/qniwdDN4sC4X0PW4pEFqZ2vjUi1LZbSoOJVZSrFdrtvbEls5hjyCX+Mn+guIVemHNina5vM1vW+3XXXSfnairkh3yxZt7ynKNtA1gLnA+pTI0ptSsZcOIQFSPy4hZhUiQJzAOiyNQ8oQCpvYH7qYg8UoFUbYylZClj9VmHx7Vwj+gNI9O+ChaJ7cteE2tWLpNyX/UxyhZjnrNXlCraV/ulF1guKuJJvWqy6Kqthsnnl/MeuYzhqAgj2EOVkk30VLGaNRQYewxcosl/z5kZO07LFBzEHOf1bEVuuEd33nmndA5XVdozRxRxCvcMYyVVhKm++4PhLCWaQxQe5Hbq69m4NihqYhk7sWN+6y/zC+ZE0o7Z21k/6F1u0XyVSsoDHZDf9/ktR+va1auk3oURyXfiqE6XqjxbMAZTM4HKUUUxpeCzKoU+ria/ShFjMeM1pAcHBhd9Vp599lm50C2ml/RS8nQobwoLHUGrGsCi3Jx55pnSaOL7dYOpSgRjZA0s7KsefU08ND3uWQKDhwwVbTt0Sfi97fqEpKBn4bLpsUA5943bpp7mKFpsMixgxc5Hji7eD8aW9JzIKkvQOLE6Yo/UOHkmdC85tOKQcmSSJlgX4B6oAvl0UwLv3jmRGWzg3db9cmtAylwiVYfNlbA/nlplNE/eNE/8dMhasevGwRgTIRTnsDQ2BWVyQ4eKYLNeSdPFo3pbzj1iu8AMcWzgTc/P7RP4JOHY3DBecl9KgwkmzjyN9YFVxNxhfeL5puccDgCUOjZbVeegEy8gdzIttuYakQX0gMsEioIcWSKdTNF6q8ZKU+0E6xSCByfU+kQxItIOFFsWckxldqWbkqdkBfcHw6Uhx0Y1d2ee0J8PRkPqdS4dMEfs1GmZ2KvrUnm9yH/mABTqDV1j5dYrijFC8f47hcFETR1gjcAcifMzLZY8n19eb9eiiOgSWCkZDFlD3GNqTkmRR68g26KhHQDoDRhxC9bEz5cmscwh9hnVqDcbQG8iOwcZFHKw+e41MF++znmii1Af5jWXGqI/GOfIOHIfqyvLxZ95B4k3cy9yfS8RPKfBFIiub+Yi14QsJspMny6c224OKpVKymvKmSWiGUPh6spo1LST1Bl4nfnVWNJg3WAMpmYEJi+sQywIZ92PE3nB+O6GcGVTJ/JBRAdFAeYgxXIn01JcirdTpd4M7xCJFdcS1aDpIZsuC4h0CFIGVGQnJKzvr44E5LnAUsfm9rl/04TvXbHgN1nP4MQHf0WkMcKCRvgzHmnXWkTTxhgLzlEpWzfddJP0VjMO+w10p9f+KjxAvFtj9X464pUyccFUu1BjaGSebo/BYnZNR2nYNvQmzJiwsXCP8eKQHlAbrCqPiFlLovfKYZRzv1A2MYT1jZoxfWBiqSjOiYj/275Mvg/Br+oHGrOANLCgmjrjtVZpvwpnhF5MGmVyYrUolE3TUhtMEdG/jT7JLIIFjBLOBUWFjZhoB3OaqAXED4oy+vLLL5eUv9CgZ2I0kW5Iuij1d6kisSvL4koc56bGCRkClTDKQH3QMde1N5rP4CDi/lIXohAuaC/HU9FNE5EhJW+zzTaTdS0YTkoOsKekazMhD5H9yqnVUOC+UKfDuR966KEyJZj/K7QPlkijkXo4ZTQ0tDLu1iuK+QNJRirjMhSwDHb27FQtLJx9mHr36StmHhUWHx9YLa4e8KtMmcIxQQQFRlvmCOuoIR0A7LuqD9SisnimyKABm8i6RWQRRFfZSO0ErAl0FSKtlRX2iPQR/S0SKoBBkMwBU9/9wbh31FWSXss5/2fb1LWDyomtO8UvGZ8jrt42V8pFroc+XTrbsRuYg2QrQSiDvMj3V4t3cs4VN2++ImZ4Mc+oaUReZjNtMRWMwdRMoDz2qhap3JHG5kSnYmvDUkDIqoaC9MpRbHtKMUpBgBTzPixaE9/8PjjI8tYqClm+i0XD4qJoEKYrjJqKhbNEIGowQZWKYOB82JxlN1oHFi5cJBb/vTj2fFWNtfhrqiqlp1nVNLAIMZzSQdBvCTY2b4QcQhByAjYdVQCcDMdVnSm637pWPPZDlZg6r0a0vG6N+G15TWwTQ6C23vtysaTHBDFracN7m9lwJ0+eLO+DSjWpDUi/UQrSRK2GCfC96n5zryW1vcuGzT1hXBkTDGljMDV+KE8ha4L6QGcj1/ODT9ueK8rjaTVDE75LNrOVBlPi2r52ejz62SLXJ946KNGwj9RUiz1a/SoKl8+UNVUoEaqOALnBeSLHHnroIfHpp5/aItmpgEJ4zz33iMsuu0zOTa/N+7HvrTX8zhxHs8pwWM555BsKxfrUUXmhPrzRnDdpRdSq0OdKdB0lj/t3uk5SShOtILLIeLBecX4BZGXPVtZ9/L8982XbiVT4epElFy0q5oZXQZBNjBPRSerefvopnuq1do1FloABTmoic6eho4NuvaJwCtx4443CXxwnR3KD3ipC1Yl5yVcnrXhhUbzYd/vefrFDj0rpNHzqqafEY489JuuKqU2F1rshHH7MX1Jaqa3iGkLaXl5dWSaNbXQU9mbuVzaiuDhXcFIjdzzZZKN7LueabK8jmllf/cFYt5wjDkr25b6tU6+7QwJWLZtCcY5PXDkhT1y4Va7oVGS1eKA+ndR6L0ZQJaso9WD+cI/2KPhRbOJfKI7vv0Z+B/eOrCacuUR9G3NNszGYmgmYiISuebAwa1J47c4bG4qHSKNQha4IZxar7vnLSZFv4UYrrjYnVYRKESkpf2xCLBLy5aUAKF8rQj7rXMiclV6I/HyZVuf+Y37x+7q4IvVdqcVoV1leKj+jIlR4p9JNP8Oosb7aL8cST8ypp54qx4g86WTF3zdVT5ZxpIVaysCairhhgWKoe6r/5cUsgIgeaUzrw0xF+o2qWaD3UsLr0TmFp0j27yJn2WH0Yixxf9hs+vTp06j7LhjEwbwhOgqLZE6+vanhDoGvbc8XRDrKv9f/NShhCK2mtj7XPmBfLKwRuz9tUe8P7WQ3ymYusRbUEYMj4oxhZeKCjh9K+cIaV+v8wgsvlFT1OHxko2m/X5xzzjkxBtBkYHMnygJVOUoYEVmvPm4q5dlNSULB4TsoYq6P3jX14Y1mnGDPpOcUHn2lTJdUhsUtT78jwhtDN271uWKcUHAU6cPGbd0j716Yv9piclNtBxoazAWUfmQ69/ea0Stir9XUVMdkPeNJKnY25JPqFaUUaIwW9vZAS2tdeQEWXLVWmcMYOF6GszPCtHzFSttzGkWTxoUjljlBJA4D87zzzmuQnkIYFxitrGMef/31Z+y1N197VSrYqm0FyEZkgnMkKwd9xe9SD6QcAjgHr7jiCnHttde6OjluvfVWWQKhG01u/cFqC3Q79n4iXeh2OXqDOw+cH3rG9nz6UXGZH/SFpQ5HNHbq1Kky3Z/vdc41lUqKg2VRZZ5ou+8Vold+3Fl73845sbYj3OtsE4ukgjGYmgkQ6oRHVaFy3zbxnfyqjyvEQi3yA44ZYRcusnan2uo5hDeWjUSlTaDw/ndv9073CrttbCnPXl4WvBp4LxH8xx9/vDTKeM5392wVFFv4f4l1L0fwEYVAwXdDx06dRbBjf7FnxZVifMWtoiqqGFRXWeeOQs5vIGyAV9NJHUGNdYdN8rDDDpOLH6MOA4/zfPsP96jd7Ej0PKOUrwoD21tC6cjhlndHobjIrmw25ByBrRBSjNqiJhKJGYLOujUVjVRMZtSUIKCdUb6atUul8IcWlo0ik47hBtmB8hTCQvfKK6+IsnK70d8x2h/GiaVaJFgB/qVgi3aiu9bw2c0gd2L6X9b8GhBdV+q89LRiokKkiHCc+Y4CQiQhnWiLSqfDiCellM90L3R3lPzwb02sUfXmXe3KB58jwo2iWR+9mNR1oaS5eaM5nmntDe8lPQ1HB9+xbIlVKzN12ofilZVdxPdiIzF0+8nyfTxIqUYhT5Wy6IYV0TRGnaioIYEC9/zzz8eeHzY0vkGEa+wynnuYrYajyEjSwdeEc8Ur1cNFWTTql47BhNxlHpA66TUPnAbTzz9be7ACTacVs6nqV8X9Zo9NN2K7vmAv5zpAe62VyPKl/8acGTjf0CWy1ScK9jevCBPjhR7FmsK4IOLHnqc7OXhOlIZoGuuBe65jfQhsdGBwE4Xnb6iote21vyOJJFrJEIlGpVnDyB6igKQ+YzjpshY9AL0AB0ung28QeT2HilOCr8ZeL6u05lg2I86ZoHGfnUHaQFjAOKRqUz5bYPfcaS0XXFEUrBFLzswTL+xleUV4IKiUwZQK43okN5gozoSBB0WE1A+iN6QMoEyf3/Lt2PtyRZVYvnqdXERdh8dz6XUg51esWi2+j/QVf0U6SkMPhKI/jueS+gWFdgXu0/zGz+JKn0oPQggj3Gjed9RRR0mPGgJGFnOnGENfIOTa+O2QwYFYsTRYtzZ7NTsIOK+Q99nvplYqMZbURutkxGITZd5wT/lLDQAbgNPzN6ZLjaw3mTFjhkypMqQPjR/MGxRkUl5J09HnelK4Rrp9otWWB7u/PWI93KCC3HrURykkPJh/f/z+u9ygkVvU4rCR05U+HWXq92Xl4r3wYPHj4hKpJOf6qsQfUxL7ggSvXGOb+18cUyiu2CZXbNVDI6jw+cRnn30mrr76aulwqUvWKz5H6rWqt9S90SpLQKVmZwKiEihneLQjNZYRs6Yk3mj777WWMcFvkKbH/pDKq3/Qi4mNupeVxu+fivI0FFSaF+lcbo4a/UyQ4aQi8sgGFP35F9U9xTqRJ5b02DblZ0Z2Dsi1gOFLaiWOQy95byN9kLLdvlZhUFON27lHPLp27SpTVtOJ2K4vOG/Sf5mPrKdH94g7bR/e3fo/80+REGQDGKM0uWeuuOk+FmGWdU84T+YdTmOMJAwN/vKc4+p17rkORWBTF1D3MdChr+34PxkaTIB9HlmLrGSNqGi/HtkmYgSzqpecKK+ymn4zRsxXUr4bM4zB1EygBAdKAxufsyDf+dyJPfuHZGPWnfoGYyxPsilh1OuaCr9H63W8bCv1PRhJCF0pYPx+eWyjYLw+aPvAN6LFLmeLkp5biTfL+rp/V4cBomrbs+LPqy3Bn5dr9WdRKX/J0j32XXaCOPe9ipjyryLULF4EACk9pPZg3DG2HE9Fre7TumbLRnYa2gzaMvb/aVPfz4o3DKFL2J/rcUvLe/i7SnH/jORpPBiNai69PtvujVU09UoRQcHG2HTWS1XXhOUGh8eNdIamwCC2oQPFAJYnHB9yPbj0RlMorYqIcPk6UbV8gYg4mjmmE8F0er6drQv02ifmm9qMOxXUiDkn+sTFY6xjpIHACgX5Qqq8eGTdIQ99KX76t0zM7b2ndOyQp+9+jokOqEu3zhUfH2k5RXCOoDzglaeeCKVVp8tFUUrW6DHdlDxFfa2+Q3+eaUqeiiCinNEs3B9lyCIaqPD5F1/GyCYwBiHYIIKRDE/PCnunb/v9MiOiIdNwOHfkEoqp2+/qSi97INkG2WisradXhgPpp1ATfWVciXDiOEzmsXeus9yQPRMg4LAAWFPU5dUmqlhbmXPiiSfKjAjnfrVdH8sppxy6qtdRNsB6h7LbWbXw2mzLGcD5kb6qorPKaCJFj7/MQ/Qi6ndgIlVpeETKVXoeNUBujpdMQJSKaBjn+354hGvNaboI+CxnB/eFe0DPTpgUiVLrEU3WDqUYKstkqO+PhO/iPsKui7O/sesCxmBqRmBSsnCd3hZfVBFJF1MPKxAFgXhucDpQES2l1OjYuV9QfH5Uvhi7cTvJUAQbCl4q5aFwfiKv5zBRsMX+nr+1uqXdkFL59njEMBhZfDBcJatfChd3in7Weq4zdilPCQaXGk8Wcyqj0xe0FDcEJBuWjvyNx8X+/90Mq6lrQwJFgXA5KUv8ts5yplBVkzoSKZXFiDeVPNfOBqAinVCHnjLKLoxVVADhSGqmiTA1bqi2AESXSMUCbdp5p1F+tahGLLjzELH44ZMTOPZ3qrg29v9Xa8ZmlJKn5ttJo+PeStYo54esoncYaTtnb+6TBo/q4ZKMzldBEkeE/Uk98LbzTCJOMQKUZx7DRU8XwuCkGTc1Tih4tVEQFCkARiB5/zgeuE7+8lwxkWaSkqfOlVoCWg8oVtSyirjTqSJ6TYogAmeHk/zDiQ77Xiou+aDc9T7yPTxoLdAQyi7zhF5CeLy5HwXBsLh+kl0RP35kfG4xjshMUjQbEnqvKPYflOZMoOrMqPHxkq3SueWYw6VnOb7Hl6hwMz8uuOCCBuuXw16O0eTm/GTucJy9jIyFiy++uMGNJuQiLVJYf87xmr/aGmBF+MDeq/Y/5BMkCIyjysIgSgPhllq/lDGodY68IOVtfcadccIwg6Qi4bVIhgaTX8SujTlK+QTGkjN1UNVOqeOv5l5qe32HvkGpBzLnIZDIRn/KTGAMpmYCJhyMUOQbW/VHPpvBkjKdTFvs224UFCeMys0oVSI3SlPuRhX85kEFYrOuAXH7Vmvlgj3hhBOkQYNwK4sEhS83TuDwZM1EkSkiviivf43FlsUY6GQDOnOfwhLR2la87VaArrpas+hRDPYZkEhy8FHNkNj/fSFr82XcnAZRqCQu6AoLClKy7tU1uBZS4F5d0losHHCgq2DSjaF0Iky5DhmrvE0IZupGwHEjQuK2He3e/dxcK5WHKCMRgMZe6LkhQ0Ue6I/B/d16660lIUpBkbcyPm9lGEuZIogEg+mXSLz58wVVx4jlkeK0U/LcUl50g2Ng+/giZu3j6OB10uJQbJLBzbhIJv6SyVN9bTHH6b1GtAtCmpNPPln+xYgaO3ZsoyE84Tzovaf619VUWYr2/AXxcRs4aKB8H7KVLIEff/xRfPnll0m/N7/3KOEkbFWeeL4HOYDMboiaGJVWisxhXp+xRY44d5x39EY1327obADVKwpFlDWnanHTBXMfQyPZ/Pp+gd2w6OZb6lkPpYCyjsHfkM4+5iMGk1fKHfdUpbeiT2CY1FfjVzeg7DMuOBucPAq6ToFM4BpU2mzr3LAoWbtGfo7vIBJTn5E7xgbmT/4SZXJShlM7ngmCfp/Ucxh/rgkjzItMSqVIu6EgGK99JnppapgM6h2q0Z7qj4LXJTcnXmPQq5XfNTrSt42mYDhea52XmaWvhCtUwDp27Bs3MlrkhMW4ceOkR4WFQY1B/qRTRET79QWR5LSproimwuWGQlJBwZtB7YJC1xaJ1tDC6O+ocRnZJSA27RB/n8o7Vo1sexa6R6tmRjaK/b/l5nuLvE5W9MtpbK5Z9rctFeKGG25oUG8Y19Kld38R7j5SBDv2FXkbWX2jdJRXJ6ZpJKMVV0ayAoK/ffv2sT4gYLPuibnL/oBfKgPK64SnzUSZGidU5EEVeiNfkDM5+d59vHx6GlCSlLxSkSderomnqnqluylk0hhVGS04PJiLzLdM4bYUTnjDItVJN2LP7xOZw3uMhxgFEG807GNTpkyRzp3aRiBYMxivKCusJf7ynOO8nomij9JHZIl7S/pQXjQ9q2v3uIH75htvyvehhNPyQTU9TwVnraMyfLlHnONZZ53VIDUxnDf9YEizAwPaJVcSmffUBTd0NgAK9SGHHCKJO2QUxSUbwAt/rLB6gG200UZixx139HzfgpX2nkG5IjHSef2kPNGx0JcgD3bYYYcGIephrtFHLZWzg72W9Y0zBxbe+mr86gT7N+m1OIHROyb0sjtUnQaUSkFtVb1UzD1BiPcOsOqJpDzNyRHXXHON1InU+lVELjzn+O23317rcUd2E9UiCk25QTDaxsXW6iEDBKNvZ69nz7/77rtlmrE+vqxt7iH9n2gO7fU9agwogchWWmW6MBGmZuIBxoNJDimLV3aZ14QsG5Rb5IAGZApO5wbpWQpt81NrKrke2kyvaI8OgA5zyimnyDDzHXfcIVMGRPt+MpVOoYbQsIOpKBWqVQNpX0TWDiHU6YPilnam93IBrfKs83t+coGYeWKR9Aoxfi023lwUdOodUwp8eMyjWBfJEztWXCduqpos7qreM3a8aNjOouPht4niTROLc9eti9fxLFm6VAqGhmIaAgjkvMK40pjT0T3NJFWESb4nqknmOQJuW/TvKuejIn2gnqxSn0hRlJdXSA8q72OsVfqSQeOD3hMG7zKptEQV5s6LU/w6YW9pkHxCOT2bmUaYvKBy5iEmgAYZuZgpnOdBj6gHZlS59iDzAsoAEQ2YBYkqEb1RtSUoCZlGD/QIBIqxegD9Oa9nQrPMukXWMW7UfPl9qoYpriLoji281BhN6WQhVDkGcuue8bFD4ULJbSiHCWlOKIwYTc4+RG7AYEm2jzTE2gsG0/f+o4CivLNWzz//fKnIuo1tt9ZxAgVF8OGGf84uFsePtBO8kPoGgVN9A2eDSmNLBda3iuDUR+NXJ9i/cYAQtZFN6XNzxcXj7RGWQ4eEYitGRU44x/0GWMdGdbYcsjzQhdDjDjroIFdacbJyiBrWFjgk6E/JGHDuToPJavWQucHk8/lijeoxeFTDemWkkgLLfSTVMNn3sM4wEJm3jRnGYGpGHmBAHw0Wpx4piHh4bbu1sJbzgHb+GOuM2yY3eVBq5cCtngX4HMX+RH5YWNBo4u1wopopqZEnpIPCFlakoriwQHqjqJ9RFKheqF7rngaWHxLC36a7aLH7haLFATfGqG8rNUviyupDxa+RHuKumr1EuUgMQ7fZ5cyEe1ChpRTk5RdKbxIbYkMpCvI6tN+CMtYNqVI3QTwlzz6+JSsWy7mI8IPqlVQ7N6WksqpaKo6que3BBx/caFKTDLzpjckxj9FAJ2HJU7dcsq2lIH1wbtTp1DClY0ShyBMpwSObLkueE07x8f7c6pj5t0U3dyX2kCEh13NRRDSsD+Y9Rg09n6DezxR8lhYSyDfkh14gruQer6fbAJLPYLQQocITjFwOV1mK5UyNahoDSfdw4xBJ5zecEabhnQO2saH+pCHT3hQdeqqaVJCNJpp6Y2L+jyy1w9vQQwHl+tgHaVIKI6Bb3UtOdDFFKkpEhD6JSb7zvl0TW4o0hLMPhwLKdjpA0UY2EWmqj8avbtfPuTFvqefjt+/+xm5Y07vyoMEhW72ek0wDxwPnzGtvv/223Kfri1YcJ4rF1usToTqKMOXn50t9i7Ho2bOnTGHVx525CNMw+73X9yjmPow6HN2NGcZgakYeYOWRQaEpHrqD7X1um8PY7pZh8vPJiekq+vudOehucDLq6PVTehE1yoKi7lbCUP8kjWszRWEnKy2ua+dO0tNEHjNCLJln0OfB8rV9n6C4Y7uAmJpzligQcaMrrCn+JZHkPalA58NvFWd9283VEDnplFOkcKiPNAEvIJChXFYYXfRvxhGm1eUR23sKnSGmaN8OlAyMJbxMTu+khYjcaHh9yJAh9dLc06DuwPxU0RDWg3wkMZjWVVrMUKzvwoLCjCNMXmmhznTfZGl6KPNQK5MuQq1NqjW2YIWj5rBt9wRj7OP5qZusPrFXvtjfxcGk0k5Yh0RxMJQ4t9qAtUNNGd+nFEFVIM5zjvN6ukaIcrrxwHjpEFwn2uRYDp7F/8SVbd0BRZSMyFk6Xm+XILMNKI0NZZhgPNCLTjpsPGQdaWg4vFAueX999NJK537grSeKobz2CoEog6EbyJBgrqk1ixx2M24UoUm+/IDOhZgcyGrSBVVvs/qqDQLs3yjjikDIifygg7SlrEzW4blFaDA61qdhuxPs37fddpvUv1Rj3ZLqRJ3i2BFxOamiSVv2yLGdN6QIGMVEBrmGl198XvQT80SeKK9TWnFkBOQM+cUtRNBRw5RphCkQnTA4ULgGnFOkHWM4wsRLqjGGIGmlyDuv1N3l0Z5sXDvNpL3udWOBMZiaAVRXcKx9FhabMulpCjOX1GTEkufc5NLIXBDBgE90j0asdOy6cVxgRLT+RAgGlc6xqf9Pe4QpQyxaY53suDFbyGJkVfCdDColb9YS+25Oat4J/ZaKPv6/xZ6BT2O1D7q3OZ3tJdihj/hi0/Pl/yvYmbW6jnfefU8yQykPTEN4V/mdeVHmvl6+v8X7W/7g2oMpWYSp081rbcZ0kcNgys3NkYqPSu/xgiqGZZ6yiWWjQ7tB5t5uNkaUD+5XQReLLc8N10637j3Gc2VFcmVKpuDanieyd+k1FU64kcwAFE42cZR6vM+p2JeWrbQrJC1btRLzTiv2dCLdH03Nc8N4LeVMZ4UEyDxFjoJiUZu1r1LylLGkHA5qH+B4Jil5vA8mwdm//SZWrysTNw+O9x3KK4yPwQ8//hBTkFFGYZtTjdLdcGTlOSkbh3NfxowZ02ARZgwgIi+y3tdjSpB5ofrJUYyfGOFpGCco85f0qWVl9hN1plO5rQe1t+JAdDMUlFMCR6cPkqgkRpjTEYFSqwy6+nT6EfF87bXXpOODNTQn3Nn2ut74GtlEWpuixdfBc+i7VcSuroDxceONN0qyAtYQjLBO6Ocoa8tzc8X4aJ97wD0mGghz8OTJk2U97yarPhAHi1fEmW0/ihl/epphbcF9Y523btNOBH3OlLzMCCeCUW8SspW5RkNcWDNZXxjpGE+MCYYlLIJ6X0od102Pj9nEiRMbfaaJMZgaCZ74Yr54/qs/PTfQVJ4cBApWvGpmGNBC7ExKt81BdVx3g2KPU9+djsfh1M2Tb9Abtw3EGpth3CmhrgvC2kSY2oQs5eXdd6yQNgWvCLOkiNYkLVyTJL1BWAQa8je0Oq50w9fKawM5wq/bfRVjpvnok+ni/vvvjzVtZFOo7ygT3uzNNt9c/n+Az54nvPGd68TNn1emjDBBCqEb0zl++5vz8/Ji3rZkYFNnTrHp4glv7HnLGzJYT0Rsv/76azmH2OA37dNNzN3hK9f3b/1/JWJtTU7M0RD2SP1UyPPZlQwM9mS1Sq3z0ksFBkRLVO+YVHPSuf7OGpJcOfnoT+/v61RkvwCLtdRqrsv/mfcYcvy/Ns4CRQpw5JFHJkRnec5xXk8naqMMYhpIrx64txg6ZnPRPjd+T1atiddeBgJBeb4oRNCXAxSkN35LNB53rfiP+CBsFXrnO8hhgBoPDEdqYuhZ5Ya6jGCoyJwyIJKRiDBfUFDrsu4lE3AfqVvZfPMtRE1OcdoRJtLAFIj+oYS7RTJVhCkg93Z2tPQcqkSriNhutdVW0jip69ogJ0aOHCn7Fcm14oiKjO0eiNUq8jossOyl55xzTmzOcA95DvFAbVNzk4F6P9LrOQ8nyQNoqUXFVeRPB5FaDE/GlFYkpO4OC1iZIDnLf445wjGqoLhfn/PH+Jbpg5VVopVYVycpeeFwWMoA1hT/xxFBSi/peYpFD33MLRK95aOl4v++t2QHsorebtnoT5kJjMHUCLB4VZm45JWfxDkvzRKPPPJorVheFBsJQEDqHoSy6ojoWpx4qwujRn+Vi5asH0snTIqnKt2ibJRlFogyRvRi4krhneoT8tjhCootpaG6skIuOAoxaaSGcud9EpZ0SxZ5Y2NSaYPXaAQZ6SYw6MZf1/xKsX/gA/n/tjufISojVtF3bZpM1hZzQlZUwLk5BroNFp0Ou1WmIXmlQ308vzqhvi0YsStKq1auiPWsSob+7SzFkftPCmlDpSUqqFQSN9RniklTBGPBBsh9Ug6OcS0Wi1Y+ezNihVlLwjESD7yFoRR9erby/2h7ztTySu91S8vzUnpVBJvzQCFPxcJW7ejzcv6Q5GxNqyu85UaXYl+CvCPig1zG08q8l4rRsGG1TkXjc17eWI6n+70q/Qtlam51a3Fnzl2211tr/bZU1Jioy+jRo2MOuoNfSowyVYugrS7UCcYE44sH+xsNO+ub3QyFjjo8RbRxnNZzSYd+Z/XU8YYE9wMmxXWRxHNMFmEqiI41huhee+0lzjjjDNd5snStlSK1JpIrArTgSNNgwlgmkvCf//xHKvp1XRvk5vSAIAqEfHaD6YZJuTFHCPOQ6Bc10kQQMUBGjBghWQ55jsHRv3//Ok39ZE5CgAO7JEaNW2uSXEd2rpMkhaaunDPsmS+//LI835atWifIsqlTp1q1hbXsU8T1n3766fL+VVRXi8ODlq6osLEvORNhqsh+SUmJZOiE2IZxwfhj/jEv0AdadYmzCSt8uzQkgqGQlAFK/2ns2SbGYGoEOOG/M2L/X/zPv64sL+SEejU65D2wMCG8eBBd0UPsbN/tHfSgOi20sygX3LVzvE6nxCvZ2xGi1b1bycCix1PF3x6+f0Vf/+LYa1XaRuvE5hu5p0asXGN5S/JyQzKs+8knn0jhyEL14v9X1MfJ0g31MdyotRZazzDC5OYZzB2+hxT29b3hKDDWc/1d5f+dm2Ornc4UuZ37iXa7neMaYZr4eImY8Fi8xkPNFz2HHFA8rAu9jTSGRB1HD48LRSIRpFI0VC8mPcWsoehnmzpQ8kmLUd7E6iQslhjTvA85hVLcpqM157zQ2rcuI5ZG53pVqSFOWMXNQqZTEWFKhUXlmW3UC6JNKd2wRbdEGQYrGw1QMdxQrjCaqE8hlSWbRr9K//KKwAVy4grm3Lnz5DpF6aQ2gXFlbqypEOLGz+w1CrpTad8BiRYTc0NF3nBu8fv33XefNCTri92M3+IepGL2G9Tevmc0NK24YmCDbv2LP1dlZDDhbFBGk1fdyN+ry8TFr8yKPa+qqkyZkqeWmYqQMsdwSOopoXUN6qT22WefGCOfs3eQLiuYkxi27PnMLWrUSAVDXnHO1NrUtbF08803i8MOO0zqMqO75YgDNk2UIUU5dvnkNHggSOD8MD45Z8Z12fI4QcK9994ro7msU+ZubfsUsc+yVq191i+qHKnQm/jjBtOqSPK6U6fBxDlxfpwnkSUMV/4+99xzch0/8MXfYvm4M4QTXDdzh+gcqaPc58bek9EYTI0APy6MK26//jFXLPl7oZj24EVi4dzZctMgfePnn392rfdQPTkwqBRtrbTuA5/G3rNobcS1YBq0yCXH3NvQ8ecWitYTT/B8/Ydw71hqzOcLkqe9PPNTlU3oojS8nWPV+YBHq+1EFTruOmi42KJ3G9fXIj5LQemzUa9YugULcf/995cCtNIhHEoiuTQDSlmzE9Q2EQrZM48w2ZdXqcaoF8mzPC/1ueHo0AuHnQaTqhvz5xe5jsdPS8I2RVUZTGpj1uvY2JSKalaJX04uFG8d7B5peuLHqpigRTkgrQGvdUNAedQbin62qQNF4/rrr7co4qOF1ZE00jZZ40QkyjoMFOdVHSuPHV95esL7u/nsG2SqeknnyyolL6GPXOvWck6lW+j9/V/uLE5eSId+XwGZzfmwNrbddlvp+WbNo2RwPNtGP/eKyIsb1pbEv4O0GrVOccpRpK1SopxyQ5d9136amLKHgaRSklW0+YMPPpCGwu+//14v7GZ8B4Yexr86bzc8skeeVLpRMmk6TLF8QwIFnH0cg2FRl60TXg8kMZiUks6YUiN33XXX2QzrJz7/U4y5dppYti5uTEVqamx7XSoFmXpYxgQK7Prau5i7sEgSfWFuYLC19dkjfXNWxM9ZySbWO32i/vjjD6l8Mw4wBzNvOde6imCwXmixgMHTI7RKvL7ratHBxSkNhnSKzzWnf4fID+OpnEzs0/r9glFYkngVF8trqO35I3twTDC3AqEc8WbYSs93w//VeOthbtk+m266qVwrOKe5HtYwOijseIzRo1+6NxPGgGONIws4L66tNv3yGhLGYGpk8PUcJcase0vste4Jse7xA6WxRDg2Rm/tUORUATCTT3r71qxJ6Hb923JvYXj1tsm9LqH2vTxfe6Z6G3FP9R4xT69e95RuGkuhryKtPNrxG7eXqQNuKGhpRZ5WLFsiw9YqzY1Ik1yI0fTEXSquEQ9V7yR2r/xPzGBKpqBt7o97fxdptU6UyNbGYDoz+ELs//ndByXdtOsaRcVxhcMp1mPjjuLiMh5OZUil5DlTp2gcjOD/8phC0b9dQD7coFO0Q9KRbr1FXbNKNgT9bHMAYzJ48GApV2Qalsf7PphXHTOmMYaRR/R4ebZmgti4/DHxTnizlL/FXEtWW+kMYqvnbrVMyEqiIOnMrUEd6o5By4k2Rbli+qSZ4vkxs8S3X38pz4d0FWoSUN6zbfSzx5D65IbZc+KEPLN+nhVrLMk1UEyv0qqdclSX5c/NshtMpVUWi6J6KMUW8P2PPPKIbS3WlVLOvoAXnGhfsrpc9jJ+kx5GpEy98cYbDRpxRvZQu+OVHZHKuGFNcF+IuJDqqJxlX8xdLi55NR5ZiiFSk9II09edWtt1xd7mBuauTkU9bnBiTfLrv8UdtGr+oAux76OEM34YGuyzQ4cOldGqutpncCDxYJyPGJS4zhasjt+jbsXxOnBnKhvrTkWdMPY4v8qK+PepFHecisqoqg34HPeMe1dRBTdp7VL7FMgeGd/Tmp+kEyrGTtbJTTfdFCPq8CJ/OrHiVHk9yrHGPcKgq20EraHQuM9uA8SC0oDYua0VHu0v5kjWFBVZImLiVORUAfCJJ54oi+uYhL5cR0jV762YTx6YXGn36tfz8PzO4vzq48Q6YQmgYR0ikmEOlFVlxsinUJWE8MGXpMC7tNJa/KXrVktBiVL3wgsvyEJinZhgaaSl+E/1oWJOpGuMVjyZp3jbQLxP1Ft/VK9XDRPo7ItvAOFArmzqRn52QxQ6ltnSM+wXra4m2LKjqwHp7KXklsIJaqorpcDs7FIv55ZGhceMsD20wg0JnU3MST+broK2IdVBsRmivHj10lA47JWyhD5I+YHktYnO6C9TLZmDx6lw8BwZOKZ3i4RzVqlv6dyLwhz7eaysSjzfnPY9a+XhfWhn62/rQKno2yFPGuh4YKdPn16reVKXRj+/j0POKyVvXWn8npaWlstMBsDvwfQpCYYCgYT6Ut1Z5DRO1FtRjvg8v819ogaCui4VFayr/jO60si4kwbJOSWbZyhx9DDCgGvoiDNzjGge46HjxMBrYkrgJRFwMJwlfD4UlMox90WXRQc8YBF1OAFLXjoRJu4XqVMY+xi5zIW6YG9zA3P3+OOPj6XWDp24W+y1qTUWmYgiWUDZ5n7yGeqrSOvkee/eveU5U3+J4zSdJsvpgggrDZAxbN3qfv/7e1wHY/qrul6n/MqJ1mVxz4k8M+cDGqMc64LeRMiyPffcs9aOPD5HbzbgDwSS1qzNdbARuuGunfPFR0cUii17BOQ5Um9H6qqKGkGwQcsQdNaE7B4MRdFbRpPUPWGu8rxZ1jAxQCgZhGTxMpFmoD/qC4T4uOnKQ0TdTnMDC0NffwhrNicmn1ffDjYdBAOLEo+qP89OdtBq/KGev9exKMUUCNOsMdFAyMvN82S1+3KRu0DP7z2a4iHvn0oyHbnfXhGmuQusGqhwldVUc8aMb0ROlaXM9h05NkE4SaQRYVLEGHhT9GBKbVPy9DzsmnXLpAIKs08yat66QpVGk+gUlhWaMuuWkuc0Kr36qqRDP69vdGzkCNdsGBeqGauOdBW0DakOihoAUiygkGZTY0Pzeaxhfe6wEfL+dgXJ5csjNTvZnvvbJCdnyHMwroWCfqnMjuuik5L4RL9+/eRxUnNOPfVUmSqSDM9+b+91EwkmRpw6H3V3LKICRj2wTpRoqbo6JvUOiJa5Qkw9rEDsrDGwFxUWSAOB9GkUu9oq4rrR33flh+Lvhw8WK1euyDgqg0JN2o+X8b+uNO5oGTJ0iFRCee9jjz0m2S1RVpkTzn5ryWQ5DhO1Z/Fd7GuKqEKPANR1BMOauz6pPDPuXyz0TiFn38WgJSJFb59sRJyVsdBFLBOHBN4T54WeEWeGXhAdhBXlWxNxT3keNLC/VOj5PE6ppORH0drTVEYYzkqcsYpSnMgb9YHKYK8Pp1+vXr2kI5hmyne2eCJ2fKDfao9x1QRrDql6ONaTapzONWN48xpGL+l9GGBuTXxrCwyZu+66S/jzEudGjeakPnRwSJ4X5+I0mDbtYG2Gah0RHdOjMsgtHL/MxUsvvTQW4a0NyObAwKOHnluEad+KS8V1VQeI18NjbMfnhb17rR0UbczL+FM2wnxAr+F60c9JqdShfjcc8cv3MSYYWZzXsccem5VG0fVuMLGB8mDzIH+RcKf+qC9wE/h+QuXNBU6vB4teP4IyzYR68803k276FBMzLngpWreML+C54U6ieJhdKTn17QwUdJ9fbOZPzG+vjC7qmojfs47BiUBxO5HXa1j6v62fRpIC7/Ia63jAFxF///Gj+HjbH8WcE4TYe0BIFG1zTOx9erM2pfQlq2H6MtxfzDutSMw9rVhsNaBjrWnFdTwcujGW1ofygWKXSZPJ2qKgMJ4b7BzFtSK+8bqxBjJGei8ZPaXODSuTpFQBxSbENVNTcMMNNzS4cYEihkKmI10FbUOrg+Ja8NyihB8wvKW4Z2f39DV9WijFtCYFnXcCyUswsSn01Z9YSvsP/9SII4fbFfOC6MfLtXxgxcJJc1jViT5VbvyXjuJ6p5OoOirndINpxt9h8e4c9+t779BCcd6WuWLbjezXVxSoiaVLMf/Xh1BAGf27iGliM/GD6Cv+zDgqoxgN9fHzkmEjR46ShgOKHcoyGQ0o5Bxz1siGI/HnztQylO+ObVtZ/QL9fml4KccJBt/RRx9dJ/1nnFFgrlMZ8vI8PNLyqLVVbTpImXr++ecbVD5xnijGKk3ys7wp4j+hRxMcf149C0vXrZOOa6J1NEWlDjEZ/Dl5SYkkRHTvlU7LQEAqukS/UHBZX4rtsK7B/CB7ZtSoUZ6ZGtRrqVo49RnV5wyZRX0QOhTvQXmvq32W+YBjjAyJla2G2F67r3pXUROOz639N40bFU4dhvT1vfoHpRMFNj+idlXVNba5QEsHjCZSK92aEKcL5gGsiRGf39Vg+ibSX9xXs3tCycH/1ezo+Z0njrLu+7juAXHjdjlizfJ/paGOfGPsMfR0KHIR5Ar3inkD46ZK42vsqJXBhILHRKGokG7Ht956q+1RX6DIFDpLQsLNBc5wLgtEV+JlTmtlpdz0UynWeJWmTJliE+7lIlf4c+2eqK8XpZ+/ijfioOA0lxd8nkaBFzW19X26ApF+szR+zotuOBK0vBK+cLW4Yau4knrFNjm281saaZUQYXJSAOv4I9xVtC+0Pr9n9/imjXckzbNOODI+MNN6JZQjmfxQNjJpMllbvPPTIu2sIp73qrfGBhh7T8QS9mpT8qpVU96zP1cln19nj40r3NLT+8UXDcqOoxs2tVHQNrQ6KFUTyLU9tqM78xbQ5RbzmchBKo/hzLCdbjbskj4sGz9HZcA2jqawp21u1c3N1ewd5jRKODKTOiGYpkglygTOKHK6tMs6WuUlrv87Bs+MsQ6yhyKva+s1xrlGQ06F3mJBzOhPNy0Ug4fshUB3u9KnUKkpfjO+/U5+N/eUXk+MKwX2buevy123OoZXdy+R34NRwtyCBprnrBsIBZzrK1NF1ysKzO8po9eRhRnDAZuGxITeltKNfOK3Gzolj9/06k0l1vyTtGdhuKZK0l2T6pxKBvm+fU74C1snMNA5QRqlcjpQJ4yji7+pGsSvL1Mg0WGcxV4I+ux7DUYd94r9hJpLxpHoDTVAMNqlai+QLvhezgtSg48+iRNsgS/CA0ROIOLawsWt0fa54yxabeQYDhTdiY5xKh0a5eUxfWF9gGFWOGznBFbEKZWneH7mpZqtUn7v9KMKxWmjA+KETcukocq1sM7stZGRWD05TmfuFamnRBBJC27sPZhqbTCxoAlHNnYgHLkJ+qOxwVkfsu7vOTZPLYsFQwgBwKaSjIcfWka49lsXx5WUG6r3S3ifKtpPB3YDJw5/cQdPg2n7PknqovR0HkeKXTKlxCdIyfMwbqIG08GDg2LP/vHf5jL1nkMlIl/4Itb4yRqmQFBs3cv7XPv640aGjl8iKZripgFfIEcqN2xsu+66a72GohG2j3w4O/7b2pg4x/QEl94kUhH2B0Vur+HCF8r1rGFK1kTUDSocz6OhCDAUq6Ru2NRGQcOLiTffrQ6K4+myszV2oLiouhUU22RQ0UnuJdfPxk/6dDK8Gx4lZobjxDJhlwiTMtCZqhWO6GbPltHIjxbJYn6jyEFmQBp3qrXF+hjTwm4kt/fZ77+XW0UvPHfC6zMoRTDBMe/xftfGa0wtzkknnSSZ5RTGihlyDuLEpDYynbRQxubggw/2ZuvT5PXanDZi2zu+FM99s0B+DiOUCJHbXNej8G7kBUPaW9EAqJKZL3oNFWuP71RrsjYOJbcoML9H2pAyfvKSiJyDh1j9YVBQjzrqqAZ1fhAJef31172JKf61Mj4o3XdDMBCQ44lBQ4pXMlm2buWyBEIiN1w0PjfWZBVFmHlLQ1lSdesjms6aoPbo888/F8v/jbcdcUIvnVP7CBkMxw2uFIPaW/3+OLbNNttIx1hd7bNcL3OK9VXmWGPM/XOG2hn9Vp9vpUW69WpSUSdVd6lLDq6JeYgcxbhYH8eq7Hf26UxRMGjbhF6Mf0a80+7IQBnyuzdTso5eheVynjA+ssn5ppvGXuvnW2QbIxxa3Odp06bJOdXY65dqbTDRH+D222+v0yK6+sC1114r0xPUo6HpQdOB08MfKVsb68INOGe8pQiq2bNnyzCnG1C8qe/C092/ML75z3J4cIGXwqtjVXn0HBwG06xV1ub4St7unulpXg1mfdKrob3mqIUo/zNOsuAGrxSKdRXuF8Qw+n3WdZRHQrEolPwbCIrupz6Z9Pc2d0lFBGtE6j4FKeHzS4OezTGVIrq+sLxXkbTiem71Weiorbc+THTc70rRfs8LPFPylOBPVyqgbCEoUWrwlDdE2otilXTWeug1IakUNOW9xuClhlMHzzneHGqYOH8aKRKFYONWUVkvYFjzPmh8+YuxtShF7RCz8fSqk2PPikZZcsWtZo7Z9dRMu0dbiQTVU04Z7ihGbNiffvppyugl66N0jbtcVVByBEVeKWbMXzrV7/FaZsYxnm8UWmoKrrnmmoy93qqubObMma5kDU8++aRcTxi66SiyjFPbtu4tG3Sl/a+aVmJ5SZU49wWr2TDfT7qam0KuO9JCOe7jo8geiFaxbrguiCTIUiEyxFjzWm1YNN2iwBSm64qZXg83bZ59HDsXWo1QmcvI54Zcy9Qh08fG6zdb9bNS1Kqra8SZlSe4RpiQZ+gMqRqddhhoEUsMitYFeeHUzXJiBCrsWyqSwzpwI6NaX/B9OIr5Pa8Gw2qtqzomzo+1ecpIn7h5+zzx00lFct6gQxHpWJ90NicYV+Y9zgAnsxs6kTOSpByTbhEm3YhibPW9h/tIdIzfQMerrdNfOQpnllr7nTMlzytaqbBi3s9p/U5RoFrOCxVU2X33uDzPEXHZjTTlfiEDWPfIxKaQwl4rg4m8RIQy3iGUdDyq+qOx4IILLpBWtXpgTDQ2OGtGyC/V87/xJCo6cTZYtwJOhMpbb70lFwVCoSg3flvdcpO9ivZ1qMCDz5Eis807G4lN7lonvov0S9oh+sx3EoV9QEREoCjuyYSVzfabld4CLT8nICo9Co4qHExbtjS+6HUowy4YVXzk7znZBBsQ1WuXSSHI/VSd5+sLbD4dOsbH2u9IY9DxwfLEfkicZ9Ewi+orv/coz/mjxjodPwobHJsOAhPFC09iQ0SAFaskipiz1oPn6ShoynuNkKfLu1Js+MtzjjeHGiaVJoLSmLvlkaLnOa8mfT+8ItxXZBbpO6Tk5WiMT56f0zZrX8sunhGmQR0CCc2xeSZ75hTE7xdvwQBQjSxT1S+xPvr23Tjpe+6rthimNtpsO1m/gbeXdcFUf2t+Zp5RxpQHHnQMpkxT8phn1LOicDgjs6S34lTj2tNh1eK7MK7++tNDYU5C0oPc8lqztswDD7Ie1j73BsMIg4k9DEMJhi0efLcig6gLNkwK/4k88n2yzk0buqnzqsVjJfFi9536+GV9KXsvMoHUq4YymojcnX/++aJDJ/fobK6w5EpVVbV4KTxePL+kp+31ZUuXyPmB4UV9SLLx83tkkKQC947vpUdbfTiiWR+ko8mmpnmpUwVR0PkMcneEVgqj0j6RYXWZxcD3YtCxfxcW5CfM/cu/TpQ5pIC6GkyhoDS81J5YrjHa8hynKuOdjAo/FRgf5MXqNZYzvYPPLnNKF8UzUNywrsZ77Hq3jp/XxN5BGUhhDo8ZM0aOkYIe1fJVrJX3Q/WYIhugKTgYa2UwKWrJrbfeOtYQTH80FiCIZUGq9mhsqHF463PyCmwRJgwgFgubNDnjbgWcWOgonLzv+km54vkd4puYW8pcqqJ9m8HkEKg1oXwxr6wopfI924WylbzZttufFHue23WAjeknVW8AL3lRHW1c6wQFoWqRqnGoqqjbRdkhVCHaqgTlDFD59+8yBE+eOoW5CIz6hD8YP8dczdPjRIVWsxD7rFR4IikjlG6bgef5+P0xZkellDcUQw6/4yUL0lHQeA/yj8aSqsEk9ZX6c15vjPKmNo0+yUnP33SSGOb7I+n7iU4ig9j48PTCINVvY8uxkupzCqu/ezvhddjmFG7ZwX5vFGVv2zy77Fi5Yrncm6jjSNXbY/HyNeJFrW2AE7dV7y1ujKY2/7vOeh8pMioVzYs1MBlQ4jAsWf+Z1u8xP3GeKWINha9XtpBzj+tNt96B38Y4qXCRi1d/38pb6EYjIRiOnMfrs6s8STP8AXf5CHEEij31C6SSU5OF8cgcgrCgLuSBzoYZI3sIBOQjL+SzGftVufY6NxRMGpSyvzZkHRPrh8hoWZTMyImOPsvBpmb86XM3Fzv8t0SsjmaFkJLKfVURumTzYO3qzOvnGDuc5ZAx0PZkfZjbvKDP4YBDB1kTybdFmFTUCwP4kCEh0SY/Pm4cRzF/+eWX16te0An0MIgKqL9p4XBiM/en/5sYVZ08MORKXEWZAPKE9cCcq9Ecw6qxK9dw4YUXpiTwSAbZSLysTGzj/14M8P9le61idXIZFPEFRI9b17oSOr1xYEHCveN3YN8kNVjBlkJaXSnnEXs/c7Uu6rMarcGEFyjZw6D2NUzFLVravHpsRmz8m222mQiHCuVEVF698iorl5jmdAhzJuo5Y+3eziWitQhX2TfDZPbShVPL7b0y8u3CwNeuj4hoqTkfRHsiOOGWlbdT4Cvb84J+m9uKD70Yp2K/7ZFMVu3R4wUCA/X9agP3R9IIr2WAwT07iGHdPfL/PUBo2hfdvFWag2ouWF+o1ti9CkVmRqMlpOOTxov0QdUwpZOSp9In2BDwhuNlago5zID1xwZMoz3Sdvj79ttv257zemOsmazNJqsMjq38ViqWF9jnlacUefTuu+9KyuJMoJSF7/+pSUqeoPDe3BqpFN0yyR5lbt+2Tdp9mM5/2aWZp4Zvw/1iKSvhQI50blCDFGO48zCYUjmE8cRCz5ypEoQhAVss94XzUPhtiVWzi1eXtcW+kOraWXMqyuPEv53GJb0Ifh/FmRTW8963k4HojrpgyH1ds/ZRmKgzI90IOYDSOG7cuJiij0G1PkquzobJPCEtjz0TBTQ/aDeYnM5F0ri4xxhdRJ0bSqFDgUTZ9HVzJ+K4MPS0/Nu3wErlLo/kiql/ClES7X+YE7RS1FC0U5EylJXYa21S4eyxOaLqogLRpvpf8dlnn0k5R3lGXRtNjDVjjjwNR+uO3SIV6BnKkL12Yq54Yq98GzMlY0DdGs4JjNC6ckyyriB9kL/tOD+Yg9dUJTpxJ25EhDzxu3IDEZn9pMhJItr1tWvbWq5NghSXX365bJOwPtkCfNcpwcR2PM6536/8cXFx1ZFiXPnt1gGfXyxYExGzlyfqTz8tsV8/ewBOBuaHTiteqTGiVua1lZFfxb673XbbNXpK8fVuXIuSR3oej/pW+ADeNAoZeQBuBv+nxqepQo8mgU1o4qltwBhLTKp3lxaJCXd8KQ6+5VUZaZr/9zLR/5L/iQFXTBMzVuWLJQMmi9wij+hejd0QScb5sDho5dPjCGHTbTPxeNvrxZvtLULB+KpfLtx7PKxUNVAainz2zbug3xaxlMHbFg0Tn82vFKumPpB5hClK+uCGGO9/1GAK16yfl/CTmngRI1i0aIFnc18vQC3ui/Z5QbjQ2Z7UifoCwn3J0rgHaWN/kroSl7khvdg6EYnD4v4jbKWOhKIpD+mWNnJebOikUZBG1FRS2FQdFB72q666Kibo+ctzjjcE82FDAPkzduxYdwpwB4hGo4hiAGCo0GsonSQSPRrRYuyB8u92T8Tptp+b5e1I+XWZRdPtxJpVqyStOBECGkQnMxw+n2dPiW0h7KnBn4bja77VxONifXxi8AfEdhU3iK/Cm9g+d+yI5JFnlBeZtpjhPOH9qmGsnmbEOfGdGBnK6+61phTlNorp4MGDhT8vMT15XZsBSaNnzA3SbsCvyyOeCpje/FYHyizGgd68cuLEidJAgfQAY5A+PKecckqtFHInGyZ9I9VYy9Q8bTpjMDnrcdWcQdFsSNmk1lywuG16H/BbFM1qHSGHmQc4DLiGZHOf3oWZ4MbtLFn3zh6rpUGJoXvffffJaHJdplTxXfTxsdJOczxZ23TSon0GJK63vq0stjaUcqKWqUho0gVrjOAAEeK1a+2OMXSNsC/RMjpyeI44b1yiY0Ix07IOWNfje8Q/u8/wdpIUCmcCKbwY/7VZCyolr7KiPFbPrcMXsutQyPr/1mwnFon2cZIs4V7OobV4lJBzMWIR7+Rojhiliy2LtJDXw/lQvwnVOQGBpoBaGUwoODDHoBiMHz9ePpiIsJCsT1+JVICnnhAoD3DmmWfK/9PQq7lEmP7+Z4ktJKsoRpe2sbxN364tlsxIlzzwYuw9H5Z0FqUte4niI+53/Q0nOUcyg6lozIG2RnW+YEh8XDNYHruiymqAG9TSu5yc/QrT/0rPiFARoGc+nSeFRWitNyOOl/IVDnnXKChGOLWBt3DkG2eKaWF7RI3NKZiEHm6OS9fsrQI/icKBW8v/08ukvhknpXepKr7h7xP4xPO9K6sShakVKYlPmmpH2l4Xn1Uwv8cmllB1m16HvFQm9nvekg3zHbTjpPUcd9xxTSIkD5inpFHiFXv//fdtr/Gc47zeFDxm6cwdvPLpgA1Q9WlBbpEOF0iLOtFnUzZwEK3R9DgnM57zk27kQ4UFeTLChfKdqp7MKQ+PCLybtCC6Ret2khac78Zg8RHpiXQT+1VeZnufP0WIifFya+6YCqxHGFOJyurKE0ohRgKGEgRBRK/c1pTqIYPjjffjrCjY5riE930QHiZajrP2Azcwv+n3w9+EPUbbF5Sy5cSOfQJiyuZxZRgHHefNNaGQkkL1yy+/yAiBF9lRJmyYGNDbb7+9HHfON1czmB77vjKB8Ib9j3PCQMaAa6gaC+Yqa6Bt28R6Ujcw/4A6//w8q0EvxijKKNT6fy/3qDUrt5wDb9dYDrvPV3n/pnM2M3eI1rHecZrXZUQdRwfzk+92ytFbq/dxzWRxSxXfZ4BFyoB+CqHI+qS0Oe8RQQKp+FdXJcz9skjQk33RDdwvomk8dOSHfLF6tM0331zWKFKLl+lcJKjw0EMPiZKSUleCh2C/LZN/QdRxUuWSMODMMlQZCchGfe9QBhO6GOuPtQUpxAknnNBk9spaGUwYKuQ9I0QQbjwI/3MMBr36AtSQqh+M/kAwNlXo7GXgnyVLEwQ3QsmJGf8khto9vYGOzSzGgOd2Pip1zWdt6CUz34sZHSsjxbFiUx1eHcc9Tsa+qKKLqLrGKtjMr/IWul76R02Ou8H05I9VCREm6ZFaD3ZHpxeyS+dOIidU+2JSlCXWDAKtPjfkXqH4uJZFvD3aV/8Wp3i2QRsz1RdHocBnabcHDrIEcbHL1z85s0r8scK6Fz1bxccQTyhepqZEw819YtO6+OKLJcGD3suJ5xyvzabWGMG8JO0G5KTo1cIGqRjFGAe85AV5qaMnzuWIsZWbH494JDM7lEz4ealdW1ryj0W8QbqXopROl6k0xxeXrTsuOTXh/cGNRslCdwwmWYtXy8J5lCSIBVCGMgHKBZ/BkMgVWoF4daWM2iiWqhtvvFGmxjiBYstejeMNpZT3KqNmUaStbW8qGmxngdTBfWZ8pWPNIZztpA/u4/PWwQXi9h3zYpE4nK1ELKAZ5vwU9TpKFZG49WXDxICgHg+lmfPNjxZdjniwXKyuEGKA7y/Xmg9F/95QUSbG4YcffhClZWnKD19A6kHsoYAMEM6d8SOFi/m/aKU7E2vpzPdFyU/TxJqItd7e/P4fsabCfX90ppOpNcU4U89Ul0ov38nawvjnoWOlaCFWRKw9X/fH9GmTqP+w3ePEQRawFupKJhMFJDKLzHPWJaFrLMjpI/WPdMH3YIA5HQPMOYxH7iMpbjS7r03EE12OiKOcJy4GE2mENixzOHGi+lpVTWqDibWFQwmmR73+LBDNJkI2BANB+R5qLtkrm0r6eq0MJlIc6DtCobMiU9h5552lJ+OFF5Lz+RskjzDhTNUjFm59LjAcS1om0oV7wlG3U1olYgWiXgaB8o7WlK0ToWizMbXQnJ90GnhKoX55fmK6no0phV+LstbBgIdgXL5saVo1TGO757vmxuqYv5qridhZ8uhYnoJcIhmc1xrwQyGaJM8/xW+h4OClwuNbX1TUKoVH9xx7YXlljpgcjQR5oUdL7+sd2N4vBrR39yjrofubt7dSRpjfeJFJ62gqQhPFC2VTJ3hAgdaJIHhdL+afuXC1+Gt5/UXf6wPcD2ijVfQg15d8k2YT572qISFe5/YFyelqwToRX8vIGJnXrvXuWZfkZ9VM/O4f+zrr1LG9VD64B6+99ppMe1Vra8macrFgRXr3orIiUekZsOlguZ5QolHs8vLTdxgtL42fJ/U6MLlm2lSX6yAdivFukxexKbQoRihUyBQvpYpzJz0JTP/0U/HNX/F1NyeaXks2Qc26FSmdPcgsN7pmXU4GUjAlPrCbdf+ZO2du5hO3D/lFzPruK/l8n332kVGSTKPPKgrM5xURFUouRFVEPiWpRPS0SiqtMdw2YG9roVg8UWS5xoZIseXesubkb6aZraMcpSoxJTcUlNePfEV3gLilTUv31HkiGJGVC0TQZzlDyiurPf2JO/S177OsU8k2mJcnm8LWZYYA94zMC+ZAWXncYDqk8gKbQa4iTCM6ezAxhn3yO3DKQVBRV3usTJ0bP15mOLVqZS+F4NzaTDxWHPKyeyqqE78vD0sDV6Wx/b42vlevWblcpuIRZUIeE1WuTVN0HCzUG1JT6kYEVu04VvXFE65zrNIl2t8i164PqNo5onp6yUkswhQJiIqSNTKajAxljjaV9HV/bT0gbIhO4Lmpz5S85ogah+czf8gOok1OtW1MZQ8UDeR1ZwK3wuuWjkLq6X9Vi38jrWSBswJ2gKxLiHoGiNfoKQDyu6sTN+WtHrW8WYd82s3VgJDeyGCOjRWvVZt2ku0qV6uPSoB2yiePKBCrXrhY/r86Ca24MliUwVSybm3SFLpM6i0A37VJJ2/h5WwQp3+TPK9wWHpaEJb1RUWNcN94k03SOCdrzF7+JTGSoH9iZGfvezTrpCTpkdrQnTkmV25cCFc8oCpa3RSA4oXTQid4oGhXJ4Lgdd4HFq0qE7vdNV2MvzHeZLQpgE2Ma1ApoyGXFgVOsLbZnGE9YhyOHtdL7D+quzh1W++009WiSJxReaKYUnmyqBBWOhE48/2wuOKjCvF7NDLp/nvWbzoZGv/9e7E8zoaMXMGIReFgnW12zVSx1Q0fiLXlaXiAHbn9YOmy5dIw4fr4jUCrzgn1fF5oWxA/UdY7zT9RhjIB1wEVv9UDJr4WC3Ks72ZN4XyiaaSbYsUxSBVgXl3ZamOxcON4itP4wEz5dzP/r2Ltd28lPQ+MRdX/xunU01O1C4taiPtmVIsZi1PPn+sm5Ykx3fzisEFhOffY/2oTfUa24LzFuauK6QFGBAaTbI4bPcV1Fd6RU6mwl5VJ6nWiU/UNVZyPHLFkbhrZEColL/rWknXrZCSC65w8ebIcR2etdOyjIiKp/1WmhzPlatN74sbwqwcUJIyNYh6sa70Pgx/WROayjTU4ypCn9nOU9SEd/eLTo9xbhKDg8x1E7J599tk66/eDbMSoY27oTbOTlSl4oTRK1qEQ1PS9c4atk/MBxyL3VO8dmAlwHpEtIMlAXCJMzsyZqnKHsRc1mModS4VsJachrYh2rPqu+PyJZftEIqL8k4djcoq9slmn5FHoedlll9ksddX5WRWBGqQHZ2uhoTmLEyZ6pikbiUgtdLd6tFSMrbhTlIscu8EURJhaq0QttJxu8SLo8rnfJHzX3JXR33MpfERAQ1HZ/YwXbAZTXn6hVMw6drDnUI/p3VY8fLjVqE83VfJzc0RkxYKkHc/xPjlpxck3rtJqcCpcCiAzMZiKi4rE/qO9+1DMiLj3d9nUFw954wFng4D+tr48LS1btXGNej00O9HziBPp1i/saRD6Vb82p3YGZ8+W9s8pjxp/MRqbitDkPKm5gh2KtUmdBBF3/vKc47yurmf2P00jcuYE509TSmUwzU/SDV4BBRdFndqWQw89VLQsLhTX7ztETBqQ/LMvh7cSr4XHyf+rFKjbPy8Vl3+YvCh9WKeAfD+RXh3VVZVyM+Z88MqSvobyvGxFnODh79WpPc1hF0KZyqDlFEARhWGuaGLcgXV81Rny76oK7yhs12KLGYqoBaxdqZqLejX15P7olOl7bewTQzoFpVKEkeGVusO+jYOCzwd7uRdbd/MtFb4UjKLSEbPxxjL1JlkxfQsYvr4uFqMeTL9BN333iA5i6NZGwVW90lTTWowmjuGtR96uWL5UhKLbRmV0P7ivelfP72MONUTaMPeWfYB5QQ/EAi3l0hP+gHVuUeO5U4d2ch8hooB8xXAsKbXmetvCHNGnfaHN6F23do283yrjRdcW5q5MPjf5fmrl6opMQR9v5rhMF9U8bcppq/bz6UcVih9OKLI1Idah6pq494wpRlhd7LHMfYgKkFNhB6mWWwQnGXT/rXQgrlmb0OMIpw/387333qtVhIz5oe6R0zgClQ6m4V49HM7uqJypcLbB8fCdqubGP/0cb3ir9D16MA3ZqJOMsJNuyD4BQVBTQK00HxQCKBoJc8Jqw4OUFHIsec0gfTjz5ycGvrU9R9A7JxOd0MHBgffFJP+M1D8SDotdnioV5dURcfBL3p4gigH1VIoWRYUilJsf8yxXR1PfCvrGGd0qVyyO1TgpBDv0toS3S/+Tvr5Fsea1usG0+J8lcoN0Ri6fPm4LMTGqbOmCE4GVlxNlZfOocpBdwB0pcRUOz4kK8dc2JY/oHTSuXri86jDX407GQBpAw4BTX2l5JVodnH6/nPVIKv0qgRhEq4/7bnFmCszMf635M+PvRAVMRgeCQVnL0VQMJqA6yLcfNlG8XjFQrApb546yw3H9WlaRA9tEgdKNsQFKI8kVRgwXFDA8oSjy+npFAU7zB6WHUqX7pMJFW1mGQY4jMl1ZURYzKPB+Y5zgfHr8v0/F3uOVSavLk3AgcU6u6DRaRirwrjvT6VR6cLKeZF1a5cZqNFDeMlXgUKpJBeL3nWQL10wISuWKsSPlhdQupzxBeSSai/K4RLR07XFzV/VeSZvWqvPYcccdYympi0vcBxQdC4dQMvxycqFoq/XPCQRDcu+jyL02kWfOTW9ai9HEPgrJBvPAH44ruZFArrzWn8Pu9ZvMo7vvvlsqrA0B6rVGjhwpszfODj6X8v1kfLD2VD30lluOk3OLunJ0MsavrNKSQaGAX5y5XTzbAIOUZTbSb9HTj+4SED8tqUnZc89JdFPXjX25f5AcMJf11ATlHO3iS54uqlClKfiMCXOgLlK/qYeiRhCD0ZeTn1RHSAWnrBjWIXH+sX6eeeYZWcvE+n1k+jzx6veL0v4NnDs4sZgnzvQ7oDvKwZjNRrum5IWd9aYeYl05Q3XikmC0tCMc8YkhQ4ZIA07RijuzqJqVwYQHkYLCa6+9VuYC87juuuvksUGDBtX9WW5ABlNetIu3ggpL6yA9oK9vobg69Ih4KOfm1D8SCYu3/6gR3e4NiNfmJVdKde9Dbg6Bep8Y5J9vT8nTFRkXSu0OB1wj2u54imuE6a3cC2N0qSrVD3Tq3EUunGTpKboYwrPbpnXrpAJK9qUKPms7RvqBjrmRzKJ3Tu/M77/NFjWV3l7ANaJI0mg6URll0UEYomRT7MzGXh9peWwQM779TksYiM+52VVaW3T5cpSUw6ks6V6+NBof63j4O2uzXrzW4Z3KyYlRI5NilKmnPdtAobvw7flipO9nsU3kYxmJxehVKUCMO0rE7VPjvXLcGN0aM5A9NEkFAY8m1TpU/RaefJRUpZxs3LFYHDG2lyhIZTixebbtJj3MMEiKdHt6OdJseY6hhBOGujLWGbUcVZq8xZM7b1nyqEckSv/vBIoc34mjQ0d1dF2HkuysZRWVsVRBzp11nwkYUxhjmVtOUg3qKWWaUI3Vn+r+++8XDzzwgE2ZZd3xGr3DIo6msv9ErEj0GlGQksyC64d1jnoq5PZNP7jXYq1YuTplylb/dgFx7rj4teQXFEpjFAXx5JNPzjhtEZC6pIwmUrGgvmY+oMh1bh8/1/KqiOw36FQklSLLXkMEvC4BQcNBD34hrnjdvQcYkdF2gVIx0W93oLrDmuuqHnrjvn2koYxsRa5Sa56bZyn1wYBPtCuKj7N0TmgyaYtuAXHgi2Xi/76vFMPvX5e0Z6MC8/fJJ5+s1T3yAvfp22+/tYx/G4tmZiqrMvhQyDHqIaKpC8ccBgxyZW1FWBRvfZRrhCmnYx/x0Z/u6Z622p7o5Xk5iZiv7JHIYtb9T/OXiCvf+Fmc9oy95i4Z0Ckw8viOfE3H/PDPanHB1Aqx9k8rFVdh/8nxNF0QzHGXg8ibzxbYr1H14mPdnH/BhbHjynnNPFWsk9QYPv300zKa2BRQ62IOJvKxxx4rbr75Zvk45phjpNfNIDPUJKFjjR1zKJIoJe198bxsL7xbM1L+jUQbq3Xu0i1lsaAeTq4oLxe7tJyX4HnV0wjVdyu8WLOVWCMKRdHg7aTn65dw4kJot/t58q8e/dlqmwlSoCXzJuqyhAVGz5tkQjS3RTuxZcDakLr5rAJ8vYeUbgSmC6dxhsCscYTknXi5JpGyUxa3h/Kk4vLVV19JBRNhtueee9Y5vTbz51/VhykixAS/JWi/X1kgPhIjEt6PcNY99tIDrg1+pikHXkBeoBgTVcTRoqcX1TdUHxo3KEMnGTCKILkBD+TcKvYMfCq2yf815s0mX1wReeQEam9sZhtkEZBe6IwIe4H5jJL21ltvxdjaFC7ffZA4JUktk0L+2EOkkaaTZiSDZH5y9JMJ11TJeU9kCQUJRiuU0H0m7x97zyVPfiSOefSL5N+d407oQCbFhAkTbH2Q9AgTzSi9gPxkrfPYZZdd0jYM9fmJcopiUumImOf4rXvEdaMgEVFhDupsecia5557TjrjnMD/LK8jEkzafsLJ7sXa7TZ2H1uUSsGXn54802m+hw4fKceGews1cW2cKaxhFDcyYDAOYd9jzJmT2/eIy+wS2OgikQS51q7AJ8eYz2AQ1CUpzfQ/lonP5iwXj36a2EiVdTNjcZkoH3moZ/aEDRAPBeP36/777pWyFYORaycCtDpaS4IjYbON2oid+7cWeb++ZdXgaYyU1KgsXBMRR75aLr53EKmkMiCcbHbrA5WKhyGo1/RkGr1R4lY5fuqqfQUGGGMeaN8rIcNG3bPOR9wutnmsNMGgAGVa0oEijVKszzqWloTl73CcvZLfffmN/3myLHuB+jsMk5z+W4vFGhPm2e9Xixs+qxLlf9kNpvfffcf2PFk/trHdgwn3jvnHfLj0sstjx9X+UVJWIWUQPVRh2XznnXeaDKNs2hoKeb+qazT/T/YwqH2EyU0ZdRqirXoNTFikbpgTieYVRxcb0QvlwZjjKKRWYWVdQKOE7No6bjDxm/RtsC1qh8F0VpVGSOHzi10rrxYnVU6xvSfYwqKIVYWmACYc1Ysg75c35bG79h/iaTChMFA3kgyDuiYWglL75IwA3fVLG3H9p+kJe+cG9mt5sWjdMrkAvqV634Rj+wQ+Fvl9rLA3yjUeF5Sbiy66qM7JD1BmWreJCklC4FFmwlYDJ4pKB3WtP2CxMs6o6i2f/x7uItMy/Vrxe05uZo6RpRozmA4EKoqQ6t/TUEw5CGeUSAwavSAc8DwVYyHK55133pnQn2joRh3kWiXt49RTT5WGA2tun6HxNNPqJhZFY25ef/318v+b+X9JeF311rrq4wqZSoQnXnkzqW1wenN1b7EXSFebP3++HP90jWgnj0teTkgyyL26f54Y12aFmDlzpqV0h+Jz95eyYjFnuf0eV3z5jO056SNuwMinf4hTSaxw1AK4FXarwnqcjrUp4MZzy5pBgQ9E17JCy1yf3Kd5UOiO0UmExTmOKgLlRE6ULY3Glbld7I14vVgUMURJV9v3qNOEOGOWGFNxl+19rccfFiMHSAa9b1V5RYWMXDEHevXqlbGSq9Y4qWIYO8xJlGaOs3/5Kx0pgn5/Qn8azke21igpEbNmzarTCHh1EscJa+7T4DBbGlMyQAnPNQVDOTFnASQ0OBQZO0nOEaV2p60G++x1e28qJnXzSZm79WZaTXJNZgaJYslTtYJ1BdXUnHPXI39LIlZWSbp4dI84AyPGV10ZvVwzjg6cvE4SJacON0/VdHvIA112OdOEH/iuRkaMlQFJujM95hRgF04HRGuV7gexjkJ52G+l9mrv7SpWiE8/mmr7fJsogZEvxe/QY5HzVbJbGep7+qeLG0IPyP9X1YRjhE/skTyaStP6tA0mPN8qdYD/ez3IZzaoO4OJyexMZxg7abe0DCa83orJjRxWhD/RKXDGO05l0Jfw+7KHgbZCoIOsXDxblP8R98oSzvdiz/JFN6F3wvZ82IQQbYR8a8vQpqv1U5cdI369fKLYdbidTGG7gZ1Em8Icsd3AjtLrgpcCrNVoiXVs3SKx4ebSJYle1bM+Dorz30/PYHJToFLVWpSJxBSAw4PvCX+0g7nyypM2Qn69G03v+gBhq6cixc5r2XyRO3gH2zEUE1Js+25zoBhfcavYtfIaMWiLbWzvKcmwJOfZn9wjcAhMrpVrJ5XNrWdMfcCtIBzwVzW79EqNRNCTS45xq2p7FGbP/lVeC+QCGE0qJeirBeuaZIRJKZ1//GHVUO4TmJ7wnud/rhatr18jbvwmRypnbOgYTvxfpfJlinA0BdnN4+qEooQOONZgKOgXN2yXL3bpFxBP7xmQ9Tysrwc/mevp/OgSWSZa/mtPgfKKpjJXVGpcpKbKs3haYdGauGLDUsQpgXOI68tUWWB+yrqtnJyE+gfdgFIsZqQhKcZGwH2BPU1XcFWPFNVri+tQDh0vyH5ZuVZ7gKFDh0qWyNWiWJQ45HGoVUd5rRh6783xjsa30xgEv/jyK+mB5rtpOJtp9JkxxVj88MMPJVvXIXtMEg/vFhJbdAvKaEjPFpEEo8N5r9XYorgTjatruewG5hRrzhnxSwqf30rvjMr4UCAgC+pp10C69yGHHCJrwvRoBgYVMoy9J1cjTKis8WVUTyKju9XVcn7VVQ2q6nPHfWM8WnexnHdfhzcWa0UmPR8TafDPP//89dpnVGYC++S4ceOEPxhKMJj0KBjz1tk6BuhlrcwzNb91fQv4IhZDHr+LcSZbcWivu323G3DCqoBHjU75n5MfTQWMf+t2eXPE4E3jRjSAqAvAWoqxd4OHg1mdDb+FjCoothwdt+XcIzr5LPuhKtpfhN+llum0005rMk3r05ZCXLzqksz/vR4o5Qa1N5jCjgZiCCPnmBYU2oWGV18hVaTti05gFo1klAoExLoqn6vSb1vsPp+YVRnP3WahBQtbiXC0s3XuusVi00EDxalVp0glIMEIU4WCHn4JVcPERoVXgmtFCSXdxc27X5QbFF9dOFE8cOjImJAGf0Y6i0er7Yq/F0pLXGoWPDrRu2FgtJ6rThAIxfrWcD2srzvuuEOmQdUlUB5WR0kJdJSUV4hVQbvHrlvXrtJoPe7448VfkY7SG0XvEtv3VVWLi6bHw/AXVx2Z9Pe9bATmofJ0c/8xUhoCKHooEnpBOAoEfzF4UOy8el0wlmyYKE/UbOpYuGCBLLTGwcF9pQ8MRtO0X+MbNN61pgLllS8ocqeKX1Bj1busrvDJsbIKyH2SOY16IbVf6HDzLbTMD4nb9o/3BguFAjJSRVGwl8E0bZ6lSN78eaWrZ7Zrp06iU3FclrKmUCr/WePtGClbMEt0aNfW5oxyY+CEsIW+YdQH4bQJL4yms8x8Q1Qk2f5UQ1DGgLlPuhRp7ZkqC3i2DzroIGnw5CmqtygGdQiIE0ZZCi+/AcMhRo3TKKMZLLXI4OLgE+LH3GMkU5pS0NNJVUZB5vx1tkjW0IAOdoNpUNdWYtTozeTes8/z3r1pBnfw2eq8AIZ3bfrOOHFi/uti+w7LxfsHRET3c14TBw93KN6+RIOpVYsiOZ+Zg7B5NYRDBx1KrwXS63y9ALU899gXrUcbN3YLGfFjv8cRhXxVqf96FE8276WZ6Zp/Ysf+DXSMNfZNF8hwKMzrymBCvn7yyScWWUVZmdizpxUNLBbp9TXyAvOT9NG6yEzge3j8tWCR8DtqO3UdTurELiJsRVn8INToKrvCKccwpvgOxhaDj9TSdevi0VHVrDgVWHtuhnBeQbGVwaTdb6LxOL0unhDX/VZHcwjnrIyIFteuFed5OJiVkwEjj/0cg9KJMd2DVto/Dh9HSnNjR62KBh5//HHXcD5CmdcM0oezP4Jzg7YEl30VydQ67bme2qbj9KqTrf+07CwXO4tAeRmcRoIq8NW9rkz++dVa53d8KaT3DRwvn1cUdRFrVq8UU8MjRe/vDhO3f2kPPQSiKQJeedhK0Kg8XFIw2JjwDHp584iWMSYYS3h4FJ6smSjSggtVbqriZh2KTShTvBetJ7MhKqQQHHiPaIRHmlddp+Tx/X+HExWO5SsSf2e//faXHsmiqGcIoPzqwNCYtThu3CyIJCrGXliwOj5XFRsaih1GWqa1HLUB64AND+IUouHKaCK9kwgEc9CtWbQCihtU27zuTOdbs2a1PMbnqbFzU/KSpeJkC4wJyqAzXUVGJquqREVUeXVi3IrLYv/HSETRYmMfMWKE/OsWOXGTBKGAT3Qpir+SEwyKrbbaKikZwsqowjFl8xzXlLzS5QttLG8YNmeeeaYIVHpHCZb++498ny5P3QyHjjnVcqMnakVqXotWltNh3dJFovzP770bhEZvPUoRystHH30kDYxM8/cZ28MPP1zO3X7xbgEx3LtLtFdNOCxlqWLjA/wWtXekaynWt2OCb4tCX4W4J3SbaOUrSZpa6HYuyC6dkW7VsrgCDuasrBI/Dz5RBPttKUqjEUE36N51vz8o55OMSr33nozYIhfTqS/Ue4jR40X2TIvY55Lev0plQ3wZHmA7Rr0P9ykT4yFdeH0la0bPKEkrwhSVVyqK1LNHD1kTCikBMo05tnZdSYz0QekCRx99tIxE+TTipttbniXnC7Irk0gTSne6KdVe8gZwjAggxrwiRekbsOZTf/8CsfozO4lTJuC61kdB1zMT6OmEDlxeWZmQ7WOrqQ6EXA2m/u3i7ynKse6JmxxTBoj6XRx7m2rEaulGmFjrpIkDfeqRHkz0t1VUhqlxwtl3zA4jxcljo6RY2nqpSfKTnC9plMgC5kS5S+NvwLxjfmGcQcbSVJrW18pgoumdU1kATHReM0gNjITK6nDChHcSGOChpo+Fjr/+WmBbpE7qbIWZESuUDfLzC2RqhvKYqXQwhUBMkPhifSlgetKb1HJu1Drlbhw3VBZFvWGVoWJb2ofdEHHfHRQRQ37AyhNXQgGFy/ldbsJL3zjT9T7l90vsE9ahY6e0Bek/jhzq3TZNz1iYUnWyOKzSIrtQCFeUSI8fmxMbBEIYRiPWUF0aTV4pP+XhgAgttKcg/frLLzKlbOWq+PouLCxK+L43ZleJh76tFBdVHeVKU+qFc98vj/XqYh6y0WNcuDXCrg8gmCn+puv7I488IiZNmiSPM5dIr2L+UYiazJvMucKO5qw/qY6OM55/1pmbU6mxRZiUATllyhRZ76HLdTzdkAMs/seuACsoR4dq7sn1EtEg2uAVFXBTFDEkcjVlq1XLFjJ6x4bqpYTtM9BS5lpFG3A7U1k+OqJAFATszhHky8x37DVKtnMTEbFyxXJxQvB1W42jE/16dZfXvMkmm0ha7QEDB1rn4PeJiEZXraNbC3+sKD8YJRJgjZN6hOc4U6A4kSY2opN3JAhlE8cT90XJAP7ynL0aNkMdQ/zx86iKsv25wY2OnbVA1NYtbbk0SlVWMOH4pMqWriwyvihdOFFQ/GHKo2E7czSd1gsYcjh+TjrpJHHwwQcn/pa2Z6oeRkTT76ne3Za5IRkYQyExatSoOo/8K+hRVM6bNCWFdJpFc+6kwm7UxyJU2XbC1nINEull7FCAlYFICj3jB3Mic4P0TJ2ghPnOWuZ+ovgm/VmN3Q3Z6SRpcTNuk8kb/s8x0uYwkNEBJK24hlWfea9fz/P0++W4qih4Kor7dKjqcWxiyBcVt0rQbvRIZUGf0Qm9NpUDxfVcHYdD2gGVhqv3NnJmKHmB6yf1DayOxO/rinKf3H8H9I/XK0I/zrzgfvzy/dfyWG5uvmi9xb6iaGjyTB4MJpxsNMXGYApFW8g4QekB72MseTRU/XJWDCaVRuQEG2xtilg3ROx653Qx+ur3RVmls+mZfVwRnsNH2KMTFQ4a63TYq0Sb7nJhkOLARC7UIgigo0abWh01mMh3HlPwV+w4qXWhNva6BNW0LS8vXwptHcGu9jxYJ04Pvhj7v+prwvwhdz0VQxYLDC+Zwl9pRjl8DkMRFLVomXbt3X3Vdhrh1fN+lBvDFbtbXp8Ttu7jWcf0cXio7dgJPeaLkguLxIiWKyXpAwKKDaWu65i80llKCruIgIM1cM4aIdPSHn0i3q/mmS/mJox9UXGxOPb1cvFkzaSEYulk2KJrMNaQj/uNIKcgdfr06XVKS5sMKI1EMlEczjrrLDnubPgwCRE1QFmn2aOXUsb1YzS5UaHKotzCQrkZUGzudCyl6xFsKKgUQ5R36j3uvfdeec4o40TdZPGuSwS2JJIrIppnGsUSbyEP1pLXPuBG+rC8pFIU5MUjeqtWLJdKLI4DiCPSScfaulfiOQ7tGN/eMFBQlOb9mchKprBm1Uoxun38nv+32j1qHczJkXMW+QPxQ06Mcjfi2mZBIaL1bkPescaZSygMmQBjHmYpxuW7f5Ir1MgSjCug5jNOGSJpvOYFSB+8wBR2snMxZ0j/Av+6tFFIB2u1bW1taZlMz6YPE9HgGTNmiB9//FFee7qtF5At6CrqvLz2TOZujDBBm5+V5VZqLUo7TUrrsk+crujqQ8k9JfKTToTp0I+tPTsYyhWjR48WwWiEqTA/Tyr2GE0wOdIY1B91CKJ/s9anTp0q5R/rYnLbuKFcGiyW18taSUW6snFb6zXe4yTt8SLP8ZI3PPg/x3BaYdRjoCY4TqMkU39H6e/TAfeQ70GXOvDAA6UxkG6k0glVl0q6MN9ZXo15ZNe/9IwaXyg3LWp2BafjZ2LvgJg8MErYEQhIWVFVFV/zfyxJX09Q81fVXD1fvrl0FNPTbYs25aKVr1SMyvtXOj4Yfyv6HXVEdx4gWmx9hGi7I1Eq74grOiOykb2UhtbFE493fR9rDgOQTAIcGk2lB2NG8UkGVnHFk3+te+UZADxleNwMUuPnv60Q5A8LV6csMh45arSw+yD9tghTOnnOFPOStw6gGa2qtCunKEWxgr2oh7DL3ueLw4vvSlrQjHAGodw8KUR0X3RBv82TnlN7EY+ikIaAx5a/6TRzZIFBEXrPdRaxxXJHA0YvVPz1o8jtYWff6z9kpJjx2sNCWI7ipChxEDgQmeNcDx/bSz7+n72zALOrut7+vj4ucfeEhCABAsHdLaXFC7RFCi0UK1BooTiUAm2hpR9a/qVYcQnurgkQCIEYEeLJJOMzV7/nt8/Z5+xjVyaDhGblmSczV8/ZsvaSd70LOXPP0WLsRTb1p5/Myg4U128LaUVIXLpLQjw3RzmeZeLKK68sKpoZFLhwi54t0evdsrEKj2E0O1krquktlbMd45emzWI2rb9xCHAYKMpFMq66u3yyzSDbuZK1dC0tYn58uAhVDpQRO+77m1SeimIa44soIYezck4xEtBjHKREIjnc/a5FNf6EyU1oSzwUysmDn0OAhpHsM0NH2lCfDu2w+z6Iippy7xinGCyMB+OD88j199CaDyrZJ/lnEcol5fOqRoa1yNhBX4sj4ec0BS3XsCO0mpMwKjIKjDOfJcTbgffwx138dYXKPiFAk5jvyEhvhllJNpMRca0eQd8bqZXzRay3sb+nfLpc/Omio2WwiPHLmOxpMnjk6pmnSw+zMSsNt9vWtsk9hPPijqLnE8aXDDCtCFi70QJxIowSsoQYJQQCFNwZ3ZGP9U3RowdeRzojKszG4TpZinT+lga/L5++atHgeiSl+Fz600n6ZhO2ixFWbE2Tui65T10v1/Ug499u/qmfqxBocL04xtSMdVdhOjrgl/+Z6nCeyE4q0QOB0Ty9zx6cExf9thEikiiXBmp2jPkZuazcewQcOJvQYZmFhuEbi0XFfrvtJ/76179KHQcxxAF72muW5vSMG+ewQqMEyT/2KxN7/qdNOkyqxgsYpb4eEF2PMobsZz4XXcOPclyeWBgR2UG7iSNH5aTRfu5553l6UNLYWjWcfylxblHjzXex7lk7ZAu5Poh7OMfIQpZ63jC2+++/vwxa9Oo7IC9LXqK8QoRrgbU5gxPuObderxFwIBv3jogHDqsQo25sFguajbVI77NHHzcC2b+860Mx47LibO5VDWucazwckWPCGti2tlYcWTtXzgVzh5BpbIiPpautU8IUVmUCM0zMO5A7/IGqPUymZs9HGKUVnJHYjWedddZ6QfxQUoYJFrzJkyfLBbjPPvvI39UPdQ4UweoMLxvEX/yUkIp4uSF5RHrf/+AD5/tDYUeD2yBIXvust0QuaSjKVDojNzqRTSKO0bhTSXRuZKdaM2HDACnvO9Txmi9yTtY6eb0mIQUK4LzzzitpyvXDicObyCEONzCpYjZPV1LrHQu8NQZTY+OlMaUzWQWJe34mTtzao3Ddhdi6/PNTIxr9VtbOvo3vY38mCrEQHBGZtnCN2PLyF8RDU/NnZTA49T2pR1bTkTKR6edtNA2UY/lq25FfmHQadBizzJW671L6Mq1otb9fMjaV14qqnX8uVg7bS6xctfobpxfFgGD/KScJwwCDiuyWgqAQfVSUxn7C+zE23Bkx9gKFwBgBHDY4HDhgFdp6uPvdbiQN6QbhHoGC4iBhmJIZ4/qJ7nMPZBvX+MBDv871FtmsAVfCYeLghSmN8WQM9Ka1xYjOcjegXz/pLKGviFYC89NlabNzn166a2GDR1Hd5g325jIOOJnuMI1YMEX0jdqw3wc+Wm7pqPcWNFn1aZHawpnuIyZUS4OimMCQWxhTaKeBWhEFDlI1B4w2a1Khm45GJQSV9crc4swTZR84ZtMuZZiQdhNmx/XoztLhRx9rvWZg3AuTzlcXo2cJVaSd62cPAVkeO3asdJaKQbHo16U7IErWCJshkM9XGRgdrhQ3a5jQSZdccol4+N1ZYv8b3hALV+dvwltI3vvKYKoNqmNW7K/Fnp9kqCRhjqrZM50K1qeCrqt2BuhcBU9jbP32KJ+lCLx4zenP+OvB6oTBqCf7gSWT0glR5DlqPfg5t8wf+5tzhO/AaH7ltddFQ58txdpem4iDjvqFmNuQFJ+OOFo09XavUeOe5+YGis48sFHHOIVC8vq+bg2Ju5f3F1fc9uA6NYnH4aLPHJ/b3NbhU8Nk65C2VYtFNurVT40pVw25mckrC7ilAdVhOVbYgw+/aASJkVbVmbeA4Mxef/1fHAF2HO299tpLOqXA0LGnsA+ZL36YPzdqSEqenkwKkocDj44LEgKj6CXJ0phI/DAheRdffLH8IdVK0aj6m58LLrhApjvXlxv/LkWnFla6Mps0lJI75jCgXx8x80si/M6+NqdHH/U1glfkjHqnv6Z+IqJl1RZspryiQhoyRJFRckAedIlvZBA56A6TFz/tjYiMGmVsqF69+8hDuRTRrxsnQXV2J3tZKOqDooepqlTRu5pbEja6aO92V+GD0O0cbNzf23sin6HY0Jr2OLnqkihwBisPlKKQnHrPNLGmLSXOefCTgvSseq1CbondWT6IjIPvH1wTrBrmLF4lX0OtWakO0+Wv20WgZ21fJqJltoGy9TaTvvEoEwfHU089JQ1oFbhgvmSx+tq1csxUf6h8647It1tgKMMRw6Dle5hPap305tSfLfl+FbdyP5APkH1Q9S7UFLIfGQPGI7DsytQtGLMYS2Swwb9zWOpEA8WIzt41bORoaVRxbVdffbXMkOhy0Stda5ApMxU+kFwltTU1MiKsRNcUO249Qfxs57HW35dNcVLKI2VjdxFlgwqnqacvS0vnnPocDJRi+/swF/Q5RH+zTzA0Ei5IrZLtBxuPqzow3ivnMpORTjBBgqaxk7ucYVJ1SXy2KvLGOP6/D+22DZuO9AbYUqkiSAxc9Ux8/qRJk2SWp1jIv3JGmXOyCG75d3pvKzuOo19mzvt/MntZr6muMiiXyU5gXP/2sdkSGbLztc7ar1JFZSTtv73wRiXPZSYGfo6iCA/X9jPYdLNO2JoOi1PELWQ1cCAJeDOufnB+HCDWpcoGtmo9g3RRCRJ0BdlSdAcwXt1ZCpovHv/JT4xGx6zHdNq2NdraO8SZ900V2XilqNmD7LJTlv7nt8ZtFtnEFqIoSX++3fGiIVQjnmwZHujMFRKVPcNxYcyj9Ch0jaEeVO17xBUiNsRmAFXSnnaemZLlkJ5WrgyTW8iUv9jq3Vf5RGWN7rn3Pvl3PGTSi4fL5J5ij5BlImNGFpfMpPpJuPpWKgr+INHbHAT15ZqyuF7qPMaeM/KbIFX5XtUwwdCzvmAOv4+iN6/MqWM5k/SlCO9RGRUZFwg2M3YvsUnYxuIrpddLNIo+ISMa/GR2OxEbspnlMNXW1kvcMtFaFGVlZbCiUMxQ0SIYek4wST7CsbhoLzLiY123BjdAgROdRtlS9FmonoXDsJhmiJ7v7OEPdcOwaE30E39LG4XLQeJ2Dsb38bKp5TMUk+0mW5HPQYXyILtTjLijkr7flUxKxQTUUUl0xhTr96lZ73cNri+TNSir8tCvttSNkLCzYh2mshFbiT6HXSoi1b3EMo05fMd+SYehPHBwaQdBVwRDHspqDgkOvN9OComfjMnJQ4UIG+PF85deeqkvLbaaW9Yp86Uflv0qDQiLYv874IADZCRNn6reVd+vgBJ6nPoHooHAajbLzRAv7Pa52Kt6jgywcPgPON7ZiNSSrHGfHPaqngfGNNabTjSgi9/huN2InhLloeTZmUb9IoXfhrHndJD+b7pz7xTT24rvdTRw9pEB/fuJbbff3vc54CV+e04PjoQT+aF1U5cYurilrUOMHj1arhOyPZCPFEPyoqCgRHCpTWHOgtAFypjlO9D3sk4nGpXfy/uoX4oMcLLC6ZIrsKfbTWipIlfAuMIInqvVVGTM3i26JIZvIUqt5cCRnzZtmsyE+pFNBQnnCdBFagmDMmgvr+kvyrf6kajd6Rir1nRu2shIxaNGQ1h0AkGQ7hI3U6YeUJFBgkfsYMyanEE6csFLHWK1uwG49r55S1aJmV9+aT6e8fSUW7DaULzoW8aFvS7XRpk346ecJXW+BpVdssZUvx0yFTqzKJC6IGcJXUsminnhnJcNTJfbjvYXX86Sjezdcn96V4N9c/lcX7RHkPSsMMpIwgmbwKXYTKVf1hK9ON+shUxV9vG4be42Kn7X+VGD035WDZWDMkxMgSTrGux1vopl9yszob+q11oqF5H1gXw3ZxlnFXqcMVZZSFq5lJZhCkk9w3jjhPlJQ3O7dPz4UYGcH1zjWl3YaNddd50shMS4gJZQ/9kg+YVUvzUBpgFRVW4oGzceNt3ZIXIuIyO0yMlsphymc6L/9dLhms5ZLJGQTgGRRfrqJPLg5tM55TAVjnyWm5gQInVT08WxCKlDfrnGOIcS4rpQSiheNnA+YUOfeOKJItbuhDcUkspN/Au5gahwQPwtfajYquP/ieacfzNceiykVi0oeG0X7ufv+Kizcv+IfSiqGSfSdvvttwf2oSpUPB9UnxKtsSEpsU7b4HgpaxsvoaSRXdtxRL1sQEnGMEiaB+8g54cCf6RXKH/WpO9hl4ryEVuJnvucJlqT9pqqTIRFRsNC987znd0lqjEvc71Jr5y4YteY+NcBIevgV4Wo+ZquchhwKBB8qNLYGd/62ihkxTAHl40RKWtcNMNm/00LZw+/TeH6MG4wxDGk/rmXMT+X75CSY1I+dDMRqXSydCohGKP6xuDYcKCz3jgTyBYXm2HaeUxvD54fPUDGGmOf77jsk77ScPvplIicO915oXluIeHauB9ogJFa0SL+G79MHBGxswWdHe3inXf1fWlfE/f04VS77kSJfo/lifw0zKp5dI+6apmhBFYH9JHaPTLBhfa8ahTLe3AgyGK6G9fa1y4c186Y8R6MGKLjxWa1CkHyEGVcuY1r6OLdEk7kZ15TUm/We6m5U2QsqmdaobFi/eCM8h4gX25RZ2ZnVog5FRuLUD/beVT3UFVRJvcy3+921Na0dt3Aczvep937kQWtnre8UXyQHuKpYaLX567/diIgMibhEhKqGyBGlhnX2Dz7bQcs7tjjfiZuet04szpTaXH99dfLsfGrmTE+NyOdJgVlDMowq+nF+Qaipgc2INrwc24VrT3shRD9kJlCjw4eOFDsGZ4qg75X/+lPIh6zDfVpWQOS+1J2S6lXEiZ8Mqi/o1ugh6dOTQ9Gd4WcTGUtsaOgbWec4iMnebJ07gBi/5CXXOXi6TbJFqLQDvkyTNG6fqLXIX/o0nVzv4MGD3FA8lqTabk3KEcgUIvd4Q4SHr+jt9VHqEATac4Fvi+oJyvOm3qONUOmcX2oX+qyw0T09S9/+YvsR8KmoL8Fhy7KBazvBimcIu5lRppVOr5Xjzpfh2nh/Hmiw9UHZeSIEQ78rsrU0HjQTQubM9PzsXhccutD94hhPm4TJ/GBXy+oYjJMb732svE9kZjoM9gH7+ojivnn6cw28v+OXEwasUQ4qF+CzaaYzu5s7qC0b6mi00BDIBGUNVl85+kiOdM2svyyEMiInv4Z2J9uahhV9SE7Equfn9TGFEM1XGwWG8W1/R772d9lNh1WBb7W43HDgZ4x8wsZ+VmxKtgRTSQM9qlSa8iidX1FJmQbmJXRrKigaZ4p30aLIhwDWBgxGHtW2vfPIagIDIDswdjkZ5QRCWNtMu+LW3IOh+m9RWm5jvgsMi1AHPg+3UD6npHkScMSkgY/ggvmmHrJoObYoUhUjiPO8zvvvCPXrWK3Cyqm9lu25fQvCGDBPPzww2U25YP0RuKMFUeIhz9rkxHpw58sLVOnMgUdHYYu/Xvs72JS+AtxTew26zXz582VUE331Sbf/690anTo1IBa4970e8y05c8SKb6PbNpoCKxY8jC+uLZCUVaVMaaugD3KZwTVMCkjl7lhPcoMWTYrdRzvzVfMX4zoQQBdljZ2eGB7xcJ5dLlmzzJx9nZmM8+wUb8xZcoU6SxCj4zRnc9pUplTAhd+NUHKyB05eqz33kzdXx6PSQNdZiZdTIaH3fKO6Kq4HZDXZ620oNXuehfa6SqHaU5TPHA3jd9hb1EbM87V6hn/ccDiEhV28PHTr9da+13CktP2mludM85S9DowRUXqFbRS9Cwm30dwA4Y/vSG422kia0xAbsaMGdLxxVCGCfP07SvE7fHrxVOJC8SKFStFWjunVIAVu8Ropp2yGkgXI9SWyj5Vmk2hros1FAShD2LSY23JxtGmka/myPo+l+0wOeIlrInscZbvdwZmmHJCRKu9tc17bVy4HQf3gX6mjl2/3o40LWoWSr2AjpANbF1S43NB0VgiL7qHQANrAqgmZDl+kFTFiAxKJciG+sE4TKRSUVhQ8rKpqF0iMv7HP/5R1shskCIG3rR4VUfzqjLzcHCpp4bVq0Ssj9MRSedC4qb0j6y/1QbYMTLDW7RrHmxbbrmVVP4sZCKOukE8JbOtr8MUC9mKYE2nd4PAKNXRaiibipp6SS1eisOk1P3bq+tklAFID8XjGErFRKdRXPV1dqTo8pTRb+Pc1C/zvq9ilTdVrOCAQQ2ElYSzKdHx2YtCzHpVjFr8XGC/nrK4f7QZ1hu36DOO8uJa/JSX4zpKwP0OHmBnNdrbbCfHzykkqk7ku2+eOioi6WCdcbyRBvOgLST0AmHt6kXDuuJdutS/3093CYcftTY4TIyxluwSp09KyDHncZxW6mb8DC0OeMhvuO5wVU9RFbIN7Bv3jYtN+hgwHsaQqOtdd/3H4RC76xe+a1G01rQb8GW1M6mK9XrGy1JGYX+870hpkGN4AcNTRj9jFATZ1pftcdsNFcN6VoifbDXIU8ehoF7nnnuu+Pe//y1Zvep69bUc23e+srGdQ+rsQ/25Jfkz04x+b7FG7BwxsqO6pFJJBxRMXVHHzFdkVqapyd47h070wkeb375fdHxt62DP55tTn0l2SONSUZPzo+opWDvH/et98fM73/c4NSpjTFQeI4Nx8MviyPvMGbUoID5AghAoGzdunNRxjKHVwLwE+e1eYyyITpDDpdce4Qh4pXi9df3eZdZ3sS/JEoCQwFEMgnzqYwWxAFAxnCbPdZpGeHW9F6KZNlk/62ur5XmpehrpUgqdc7HOJhIz6c2VqGyAL0RScz6nR0Z7nlawOL2VAfVIjA3zL3tMhe3nZmUHi46Fxr4AylgIJqr2MvuetUZA1t3EWCd/4fOuuOIKmS1kPnkNcwm6ZGiLQcbUN7TWyGCU21lthXThvFLOczGSNCNwkDJI8hPtrMF+ZU+TGafOy+3Y+dGis9744b5wOk/9zemO61NSDFQwqP4qyGHivus0W6dUYb4V7FFdb6q5waprDBI/Jr/DjzzSd08p6dOrhwx643RDVe4WPpK9TJCcvls/eIcJQwlqXoQDUy02jCiisxukiIE3tc1nMwzjffWKpb6R3FAuI3pMvsDx2IJQX9GhUXz7FW5akDwzw7TV1ttI4wg2LIq82zSM8I1pZw8ilXngc7/IGobB2dO8EKWdK5eK+moDYtGZyYnlTcVFfNQhsHfkQ/n/xlWNsm6JdZQvOu0nEe2EviNzgNis4zbxYGbXwNdn2ptEw7vevhwoQYgxlKw1seNuqe/RSx6k7W/dJcrXBmeBdLiELis1ljgl+vnJwYPxuS4dyT3fucw2/DNt9sHgB2noTKbk91fX+MOw5DWGDTY/jIjWT18U03MjxXWpwwpeRzaXdRhqI+pCDmV9+ZVX5m0Yu66iDjyUtWRlJMRmyrW7hyx2KLJEQPL8spccMGQbOMCaW1ocGSbksSPKpDEHzAEIlI7NL7be5tsWxRToF2ntY0JA9NYF92Z2t37HICcDpAylUqAVl03eRLxyzq6iuizm2ANuqJdiyjvuuOPMmrCcaDEzRcisxLi8TVXdGY7Nws6+YpZkM45AhzJqIukOeS30HvNr2qukY+1K0fD8//P96IPva7MyTIlYRNYREbgiCqvXU6xqSUpH49UvV4oGH9gXa5PMFMYe1xRE+kBgQkIXzZ5PEHIwx3wPDpNiq5sY+kIUK7/ZY7ToU53Imyn9bLG9hvxe42YUK0bKo8Z7WGPoHBqwn3TSSQXXGlkF6NS3284ZENRRGU2t3loZFdTpaG+1avIuuugi0V2SL2jS4arXU2c7/Rk9FNsFsnXUp7BO3M2yr7rqKgvBEXd9BM3U1RpTDmmAT249zjqTBBKmQ6J6FeEQ8T0K/sln8sPa414Uxf1T780UHVVagI6stjZGKiCMw6Ta2hQjav1Ri8Za0ccP/YzTBJzQnQ1z13+pcVDBsueff15m09986x1fJE4xUMGg1yhInvecCInWZq9+LrZxrYQkk6bUdHnLHKPZMHo/KPjgN9bpXqPzZpg621pk1ny77bYTdfXeEp2YycYKlLsUJtX11mHi0CKtj4wcOVIuIOSDDz5wFP5tEFHQc1eNa9euWumbYfLz8D2va/PCp+wMk7FJbr7lVonnRhlIfv21wZmGtPn3oZHXxPCQEfVvavc6AFeceLA44ic/suAXMwIYwJrftxvU6tHqbcJGkWq/sqRkxyNqo/pGFCvuSGmTMBy4PTqv9X190zsPiESzN3NAFFEvCL8mfaTv+xubDaWvGu0GSVlAhuz4J7xOpZpJPg8DCrhroT5MOmLxs8XBhdCM67XXXW98T2eL6N3TUGAZaRR411ZTuEoacltP8hoZOiacOSJyHTLX3j8zwYxbuugGJogdXVEni2TQ6qpw4EFYgzPE4ek+lGRRrYzk1clofFAPJn4IFPG/uwfa0FrjQOeziKgudzmAt7xuFCx/HwTnj+JvMmHAY3CcgkS/Tz37ijFEhLDYImp3ZlQdyIPq/TOqOmSGPUezYJx1vZ1VrNL+3miogAERjgT2raOhbNjn/cw1jiFrQokyQpMZp2GXy3rX8GlPt4snZ6WtGqaayjKphwk8QpWtj5s+PH62EEYcUE/W1+ZDasWPxhp6/kOTUMJ6XdJgOsPgYwyVY0tkGDpnlV19KHGZKEXsrEJhQ03BzoP7bRWWP+2ZEK2/rxF7jymX+w1oIQGPQnYG90x2QDKamZlwXZQR/unnXocxY56d9TVVMvgB6gFW4O6SQNZJ6TA5Ddf9I+/L/3tVehELoWjwGKC7YEfFsfxy9hzHcziBavw+P7XK0UeuYvS2QsTKHYGsoCnjcZwf1i/rWK9f5zHVAFU1AedMu+mmmyTxCHoj1bhcZrKyO50i0QfWtZeXi9TqhT5Oo7M5biFRzsdf9q8yggdaEBNbCN0HwRH7RDlNOi06j9MuR3fMOfsJ6mH/3n3ff317ZRXDGgvs//WMTZnep8pJK96W8u4bv6xusY3QZZAJ6nnGM2d8eCqdlo9jDwLN83NeKtwetRDiy6WNeanv21qbJZLj5ZdfFvMXLPQkAeoSRq0wxBlArrFRftAOE4sMxjXkN7/5jYy+sAmIAB5//PHdfY0/SFEG78jRRqq/vaXJ12EKKurVX9f08B/For8fk9dhalizRioxKLsxCOu0ZpTuFLIyiH4UeVskTArKzk6voY9h3btHracI2C3JRZ85/t4k/JXYOOTEthJxfeutt0piIyJCEQTjok+Dn6SbVkrIlTvSiTLXoyGKnt0tLa3t8hCQfS/ySHmZ/2E2pyH4tMRY/9Of/iQbRBcSnfThwL+/6fsaFDt0/18vWSL/ToBTNq8rSKkvSxo1KNF48GGMkXvTG4vEV9meUukWX4DrjA6ii2mYrGTU6DHfePEnhwKHnWRNcl0yRgSHJFFHcPasE7dwfRyiRG65H53pUR1g6mDjOzgwdFnU4O1N810IBgyQE3S36heVT4IcJsZz5513LrqIOig4zFjtt0k/X6NXQWaU40Lmr6rW3p86XDCqQYz8vycsDo28ERgxJxqtJJxsEeEP7pbGFkZzROsh1JnOirZkWtzxpp1lbm9tcUTGlfz7E0OHVsdNgp9QpzTIWF8Ux1PXYV2f9j63gcRYY4hw/4zXaz9eK8aZMZ42F/VzJGzUe6h5honv2GOPFaeddppsON331HvzjlPDi7fkdXiLsdOuPXRzz2PlPjTF+eR3Oxh66PKdhIyGQ8XOuBRT7yWN2rvvFo88ZNPSt+YS4qjIS+K06OPy7+Z27+ckTUheVUVC1kFBTuCsbfvmMkw0QveT7QcamW/H5ywzWfEChLmnduWUX5/meBzdxhmGDxbX0kfqTKzd9lD5XWSN0HexgCwm+hMbgCwe8CvWpp6lYW3jYOhZGoIrkDvtMliIBaeGxb8PDIvyqBDbRWya/rWNjQ59ZDlMubAMdJXKjjt5ZEaINNAz2wthPgkQMRaMEw4me1LRovM3j3MPeh0Teo42Cjhua6uHB9R6FxcUOCll0KMjCVNvKSevVmu6bcFDfTZdMYELFeRTL1W6HMddsZzyPKU2bqeJ4Khb2tsMJEbdNf41zCwpgoVfL1kqYiO28SCgDhtn6CY+A8eLcp71JdPUJYcJo+73v/+9/B3ihzfeeEPihYkk8NwGKULM1TuvwUjBV5abNUwuA+xH4/yzLTqdLAx7WVfBsTJqVEPI3n0M3Pupp54q6Vk32WzzPBkmr0JKJf0x76oppx5pdYsinlCySegr8XTCWD9K2DBEfC688MKiKHYRyeGvGdyFpHnaFNEx5z2DySzpdHg23nhj0ar1pspqRae6JNMGPa/KrgZlw4JqjPyKnnuYjFB8LgYsTVMLidvYD6wpiEQs9jnYawb061sQZy3hC3kUMU/d8sZ88V54Y42cw/9+/5SyM3W8guiwLtU1tqE996v536ji5OAj0MMBwbxVuJza0f2q5WuYB64zyEjiGjHeQuGQtweHNmxAUrbbzp+m+rsWDizuA6NdZpboU+KG/GhiwWJcmUneg+6niLsYyWdK/HJno1azR2XcQYeror8Uo7NPmZvVDWstA6IslPYYHoESjoi9Il62O6R3r16OQErb56+Kpk9ekHBAIuM12lolw7TxH58Tf37WNlprKmHiyomzkr+yHntjQVq0JJ2NWa/YNSI/k+g8aww4MpFtd32Lew9ipOHQY8hSx6SLOyJNpgujGIMVfYoBi3FC9roQw5x8v0YGgAw3SWyUXiuGNGLXjbwNY7vqeNAkmXVKhomAbTGBFdbNylhf0eO4G+3HMuXi6tgd1t9Ayd2SCRnzNKBPb4maYb0xZj7B9m7PMKksgFv+7zPDWVCCg5zIcz2rli+RGUwcj7Va7R2iCEP8GPKQcFmV1OugLqST5jq/lTR0GBlmdCk6UzWszte8VpFNnDvJGPcjNomJLytPcnxuEltDo64uCyUtO4WsVVf69kw7qkncWPVv629FsU/DVuxX9kj/znmiRjTLuSbYSOkCWRL9TCKwShCS94dN9tCgjLW7Js4tncIOHqhlGFTD1Nne5oSVmPLmnFWiQ0+3+wioFYg1EmZdtEX6kDLIMMjYAzvFPiwmg1fVtlQGuFvTEfHADK+dBOSY+W7ZaH/z+/zXD2uH7y72e9dbh8mtcCkohSmPJo0bpLCwOVetMqA6M5cam7F6kMHW4858XL17tGCGKWf2cHJKyFFLM3zECKkEUW4oiu223zk4w2TSiuviR0PLOigv4hQhSnHR6/bfn+W8VJVQVJMxgvaWCH8xIjNlPbzMMUHS8MLNMsOCozVs4TOO5zhcdtl1N/uap97t+xkoNpQl3w0OOoiet0NrxKeLH7TRek9HhzxkiIoWchzch4ZfbQyK6JprrhHjNh4v/waSEDdTlt4Mk/3+1S2dYmFDMDxro942fKpioN3jyS0YjjdnDrb+jvt09E6GbYdz/CabWg5oEEPRugiHNYYetOFkKjIup3hofK18HicTXUY02y1cFwEHWTAdi4s64TRwlI3L/ABTOfa44xzPD6wrjhjlmxZFIMDBxx6eemJcPHqYE/Zz9yHGtZaJTlFjFu861s2MZ+V4YZgTQFNGf17JY+yoaKYiMlDXqArIqcngO3DOJMGEucXKwvaeum9+/kwXBeX3pe19rkvdkLEiqkXcuTf2OecbkeXNB9UFUkOjj7fccgvRv19fMT1nk/QElaxBcgPTFs6PyqSxtnR14u7XoyLFOqRKSbsrwwS0kDHiHshIAcNjjtCvOrlNkKj+fUiPOU+L2w4d7YTkFZFh8jNs6w88V3RFcNQgJqE2gqxAoX5MjCmQn5oDf+dgiXOvvx69vSxjQL+QVSuXyzXIecS4pVz1RV0Vgm5+IokJTJIVt7QmnQNO+aWqQ1PyyGx7b37+9rNyDCSj59aG4Yrc8OMxgf1xLDHrhNDVOKl+MFXk3a/T0rF45plnpHNBoA+nSWVpFKRNzz5j+5D1ausMPgfD8XKHwzRQo+VGb3eFErwmERKHlNmBEhrEKxIRMrwzXv6vODnxuDhb3C6Jy6hRwiZxn0EgC/7xj3/I66jZfG+xQ/hT0TtkrMVnMluL7Tts51xJUqs39zyXcQZAbznQ/3wA1hYJWBt6ltv3O8zs3mCTVrxCGOs4G4rKsw47gQwhOqmYcojNN91ETJ48WQZtHpzpXcv9+vSSbMfxcUata1BzZNYvmXvIQtaXvq5dcpgYYGoBKH5e134O/0ui8PhE/aC61GVpu9m1u8iiWB0KVBaLSAU3vclbpK5qoPbee18rysNh8877H1ivIdVdMMPkExZjIyai4YKF1kSv/9/nlaLBJFL4sQ8khlokPo+IQylU4UdsY/esKEb4nj//+c/i0D0miSPq7OLvTXfc22Egb7eRP6QvFI5KI4foG9HuIPrzoGLMxc3+j4+sNzDKKA4OmkIRl1AR86MICoSJdc8kakQHkSofh6kiaWf1zvzvx+Le94KhkXofhsoewbSm7cJp1HFvZOV0Kd/Thov89Jhj5RplfULrDZSoO50mPnu//faTWSajBtNrZHTLhFUAAQAASURBVCr6achr5s3zkgMwLxy01ILw+03xG/0Ljc1avFVtTsNgwuBgMo1vShrbUmKRjwPMOgNeMnmLPpLd78AxzgP5p5vFxACxSnxR9gvxUuJcD1tXRVW1hI9Cc8244UgWcvT9aGrdukpfynoBORkSjGV15mTCxh6piNm7YWl7rGCGqTbkH8XnU+uqbeP6/ZUVst6NNUjEfNM+MTG2X7Xv/i6PRyU8fW1Dg0N/+mUTGjNl0iHHGUOPYIQpJ/CN2TaznDtrr/rA0MNptQsu6onDmA4P+mnvvfeWRiD6lffjJBcU3WESLaJXfY0LkvftkpcAC4NVy499zU/UPkX0LLA7M6YTv7jZ1YYNHSxfTxaWrAhZru6QtoCMAEuqrFzPwNvXOrDcCPYoYV7dWbY5mh/c1mpA4VhjbXVGHyNkSKxFZul4f+C5HQrLrIQKXMYCIHDRkEHaA5EUmTicIcWay55hXaMTlA7nf/Q6EEdFQOAndbv+wtfZbhYV4sEHHywIhy9GCHoCTeWacPLGlduDx17ERmPO9ayealzLfbKH3qy/TNwTv1r8OGJA4mfnBoolwhvApdI1SKwAG5mbPEe+XMMBDWPnr8o/HspJXd1g3GO1GfxKRSqlLcNZWAyqRUk4GpM98nB65rZ4HTx6h75l9vnyy8CRDUev4rTiS6wvzlKXHSZoXok84GVy42eeeab48EOD8WyD+IuOx8ezrqwo943o+XVu3zls9GjQxdGErapcRhwbGg2q0z+mfib/X3P78VbGStFEo8Ruvvlm8WZjfWmQPB8lj8JGseGw5ROMS5TPvJxBRXlQxEs9ryKhMCCVsoFO3W2UOGtP/yaxuux5l6FUMEqIHhEBOfzQQ63n/71isNjvgAOtv999zyi2dUtHMiUPUCJr+aABOra4X3XhdHOfyrBUQKT8YVcD8pVXXF9NEzq3KEjTJ0kDGkNTwP6RBt+sYnnLYkeaP/93hwvSozqYGjVx924Kl9uHfmNzs+UsUbBM1LI7IXp8FrUcjC3rwF0fSHJBZUwwFh577DFfh001ufVbp3qGic+54kFnD4580NVvSja/7Hmx059fEUsbnXAodDiNC1vXBmd03y4zqHOV6LVqkC0Aj4IaljqmYprVHrBpf3HQ5gPEpQcbWU93l3i/Gg9VQC6p3MNhUbXVQaL3DoeJqoiRIdwhbB/2yWxI/PezYMrsHetXWYX0bmlYsVRkTdIG7LmpDRXSmICGnu9Fx06eYARS3NNILQhOCT329Az9Fv3t3698w4jsTu0YLGF4rHEyZkSryUbyHVc9bUf/065xYL2RHZXjrBFdIC6/XBrDrEF0KgYhUXTm6JZbbvHNnOpyyaudWEXW33+88PfyO+XnmnsmyGHaephxrozpm5/evVRhvwGPQm/jNGHo5VtrjCXZKC/ts1NftfjUMBmwUyEmpj+U7QHQoexlBW9fV5m3MsBhp0Fus01XrgdPP1uR8dTuuM+f325t3+fatUaGhwh+osJuFszckzFlPqsr/ZvXlw0YI/pttIXUfayf+jp/+GNFWdzo1ZbLyTGqbZkrrqv9t9gp+bJ0ijhnsXcU8ymOGg4U+jPfUCb6jXKcMe05Y57HNE+X+zGo3vLv7xffTBhECRlL5TzFtSw15yZjyzrjOZWhYb1h8/AYpBGDw07a/LTWG1OXzjwZJqVP2a/NF+SBmQKLDGBFDCIG01tp4ByubTTO0oiZMazv1VvOG2OBfig2OBkKh+Xawqmcu8aHiCLVKeJ9bSfd3adKfT+kUSBgfvC04hySePoY31BU0kyOTQjl52WXlca6878ibjy+DnlAciZ0zi/DND5kdOnWRX8dhBEoIXUwrDQJC1oa14q0ySLXsGatVFw0/eOgXpOrCDR6/RymfPSVhXoCcdiQUQsiGlBECLBQnXzyySUV/gPj2X1s4Q338nyjaJZDh6jR448/bhloSn78n9nW780t/oca44DDqyALQYe27kSWaY05A52skJG5xYjFMAM2mE/cY/7Mp17yC0WD2iKMuf6w7Ffixh3W+JI0HL6x/X2Fgsf6WgiqIcPoeDU7wfEYTjOGzvI2/3Vwzz33iWuvvVa8+uqr8m8iyt0ZfWJsITjgMzHCMW51UX/yPGuRuXUXl5PlgM2RiFx4F7tWxT12HD5Tp04Vy5e5acW/XYepqcN2Hj5e6KwN5KAk+tjZXnxPGX3dkF365S9/Ketx+L+YdgCM+d+P2kL8bHvDWPFjUHPrGlVAjoTKqkXtrieIih2NoJB+ACPvj/ilmN3o1V9qq+/fK7jX15IPnhUtTQa8prX3lnINYKiTaWSsWAuRAIdhTXtazjfkOBbhjlafiKiY07IliyXcB2gUsJZ9991XZqdkHybtM1Np53cwV2THcbIWLXJmgFv1pmIaWRDXDDQNw5nsKtHzfBl86qYufa1TRGvsSPkQjbHTrmHyf3/U9KhO293bF2jdJCfv4+KLLxYHHHBAwbXG3lWNyHWDrX/ECeVL13vXoWI9G1beIqojRmaHjEJXKNH95KGpX/s+zppapcHRdSjT56ud2TF1lokFdqBap//OpNMy6EM/nGN2tGHTOEr0NCPYndNIEJAm0yaI9R4u1mx7qthi4tYyA73J+I0dr2vuNK5DDzhxPb/b0tAje8Q/kUEG9i0ODj8Eq1TQoRihjsr6bHPcl86fJe85qIfYspbidSsZEvaC6lVWXRZxnBOSxS+VEpMmTZLZNoT1BlU2zoVf03bFLuyW/6T3CrwONaWFUDqMdSYA3/vyF8GtONj/2H2Mv+r5qZhEI9G4wRabSskgYrGN6AePNxpCY8/ynlH/aBeHPpwSq9pMsqNcVvTqbeuPiGvf3PVpVl4TKA49A/mDdZiUoHhh1IJWnLQsxtCll17afVf3AxIdj88ia3dR+OZSHWLRjUeL5MyXPe/1U9S6MqWMyIiY5xwOD+9TdRruA17/y+3I+GUG8pEAFNrs244dJDd8NqD48aJXOqTCDWqeWUj0ugNdmnN2Fo/Dhu/AcJD9Syj8D2JsymVFTHOE7k3v7hhDrpFoLQdAEFvTZoNqxdGThojz9xsrNupv31NQsXQ4ZNAAA9HhkCtkeIaKmB8MLBp/Nn09y/Oce84PN+nhixF9LfXsZTurd6b3sX4/IXWOVQughMOJOrVrPzIinp+1O+F8L778sjSMWcvUXEAm0F2seShlgjx89j777CNqR0wQdds7qePXtOdEYuA4UbPjMdJY8Ov1gs6D2jpb5r9O9VmQ9P1rnNApd13KNy0XPGw3aNWXCGsDvS17pQQU5fqJnpkkUKYygPma1RYrdobJvlC9JwpG60ZmPZ6fXJ06SkR7jxD3VDoZQ5EdhxhrcaNewdlwglaKRbK2vockelBOE3UaZGryQdJwgqgTdOtPRRKj9mg2nZTRWc5L9jwYfqX39HtPuTJMGMCffPKJdNplYbwm7angbCnXXxPLiOeefVaOpyKM2MUHuaCcupxW3/fV/K88AZ+gDFPO3AElsocXlJCpvxm3hx9+uCBLHgYgrKvus9JNAZ2NeSFFelluKNMpnQwMy+5wmPKRZTDddfU28kPfl8RZ9N588XhMFuqHV/v3FIPQgXmfMmWKaG0ygmRkdtGDd911l3jyySc9wdl7M3s4/ob5luBgz3obRvxRdpS4db6BFMlmUhYknfvafoB2vbLGMyZhkVdeeaW4/vrrZVaV1xNgqXexwLkl1tN20tUrCVqouqymDx4T96ed/RaLZNiW0tDYLBEMBP2zbQ3id5Ps51RjZNaau9UCjjiOgt88us87JXdk9gu8jlzEsDN6VuQfD+ynSLl/EHVFs39tnVETafRhk7VKx/5FBg82N/vQtbZ3yHtlXeE0Fqu/b5+6Ruog1bNwcWtEvLECFj9h1aDqgUI9YHHe1P7i4rfpu5eTNeAgHAqiaX4oDhOL94EHHpBR7C233FJClTDQNoi/KDw+RldHuc0gdEzkBfFa/AwxNNEsuy8XI7ry7tu7h1GsLpwOE4dWvPdQ+XtDS4fMYNxwww2yH0coj/Hst/EzeSLjTT44cCWjEs2icdVysecee4jOBoPe2i2qPyMQKFL5pUYcygMggXrzWZQBY0S02K4jC7juXE5UaXCFq9NHi/ErrhT117YbyrqpSSpbDoWgDBOK5KpDNhWn7DJSHL/DcEGSKfW+0bfBT7LmgUAR6hNPPFGwgas7UXX5FJuWVQkRWQIZHbPf8fk+55w/9uijjr97mw0qdRnas8LjnLVozIJ3Z/YM/HzjmkPyAFWB86GDnd3CgaMw91tttZWkqu3Onm6KxhRnh7kL7X2uqBi6ieM1zUkh+h1zrSjbcrKYMrtdKnS3sIcuvurPYthI/wi6+9B2M89925C8F2baB5cychnjW2+9VcJlgMkkgjpT+oiejU4VMFpLFeWMKKY4VTOg2LZgZC3Pc6irCG9THy8t/2s/N5z03RNfBLYbiIuM+MXPjjUeCEXkWlF9YzBOcdgU/OXlmd79iV6vZH371CxIw9KEuW3cIy2GDhkso7QIfbCUzmvWdKm7zsNy1mm6rO07f1px439eO6psrfid+H9iz9ZHLEcZ+Xf8Gs91frrC+E69n9SZZ5xptXtQjlBLZ1rc/NpcMW9li+/6L4Q6KFX4OIw6gkk454Wgn2ToMRT9nKRCZ50OpybAIRnU+vfvFicw3/5nf+rzqjt61DbpJA+xeEKSD/RP2HvwkyY7uNO/Ty+pb9Fh9zxgZGery6LS0GX+uSd3z7BXss59s8TstamHgQ5JXiaaa0dbjqWCybq5n5gfYKZkZ1g7OCbAG3FAuIbxfUoxPY3vz2Vz1jm+5uXbPUHDYsrq+gkjg9eZDcnMCgGECyb6OxzcG1A2AiGKuZc1yPkE8Yqf/gk94WT/dbPhIQ9ndrJ+z5rQw1E9vOMxbantaJQnEqLnAWcH3pebBEVB24Ggc+ZuOXFr+fipEYNOH/l68RI5PwSROW8prylWmpqa5FwQTGBMOOeUHVmeiInGtWs8NUydmZB4r6mvhBMrAjJ+1heGvC47TDTOg/SBSBVRYP5nE2LsbaAVL+w0wY6kyxWxO8WIqqSYd0a12NWkntXFL7KlF9KRYkU5Kr9BOUyyxihmGBj/ef0LuciZq1NOOcXxmW7j1u/73Hj6YqXqy6dkRo3oqGLscwtBd9VADdrzYqlvEV6X6vRndNNT5BjfKEDGiYgGUZXAniC5nKN2hmLTxkxCxCpq5efgKAEzKMTUpKRndo0of/oi0TL18cAeEjRtJapFFJt5CyKTKFZUDw5gspU+8L6ewlkbRJGwXy2CkmO2HSLGD6jxZEn0SLPeD6dMeI1p4Hso5779jejhogXO6Ch2CqQfrAXqYjDquytdz5juv//+kkJWsYRtEbIhmIhiEJTXWj9IGuluefDDReInd88Va7d39jbR78FBA63VD3xbkLz7318onvjEcPZ0I0/NFc4ja5hDjjV82jYFiBI00TVDz5713erUqkyxyrIwfmRhFDUxujMeixY2fgNokINk0Q1HieV3nCLGjRsrvjJ7IqklzncCNweKw+H+7GcGpK/Zh+ULo+PgyZM9GSZ0Do6LWhtb9hXiuCFLpDELRNRNXZyP+VLSGYfDDvpxvzoGvd7m1M0MI3yryJeSaXB0RaN4M+GsTVPyq6eM14Y0uFa4fY2V0VGO0A0vzRZ/euYLsfv1rzneryLv+ZyLH3deIl5oGSHOeb74vc3HEdkHDhUEydKFMcLRlb/nyaD6wsS1sVPBIZprVpgO2LpIvibj7M/zn5rv6zABhVX3Iy8xXimN1S2H2dCnQz+2m40PHdRfOoysu86hxuOt7UkJg1I1nIqNMkgOOPBgmel3s4muTRl7sOfAoVYgChY6XZgrIG9Al9k3OEm77767vKZ87Qv8RNkjdfVGjaTKhES1dgJyjIpwmOpMwhd9+wyvd66B2oSxZ7lOzp9LLrlEljIQ0CRBwBm27z57ez6b8odMi5eBUrevHs9sL85P2TTqNSFjv+081KvX9GssL8vvVOAc6T2wVB0wjYEhfdlsi63kc2fHHrLe07cqIlE92Oz0Tw3KMI3o5TzDkFAkJseH+TQIUbLWXpFQz742DFS1ysmIkKwr5D3odAUr/cE7TNQwqdQui4hCUiBKG6SwsJgZryCZOMBrUJ8SfdLzWJWwI1EtjWuMhWc2mFMOkzT4zIMvHs6JJz9bJQ80jACnw+RUdgND3hSpnzIqpiAfw4zoEk5T1iymdYuescCIAEpRzGcrIo1HHrjf93k9soMCx9hA2YF/B25VUREQrc5hTLpqzLJZeU3SaIvHZWSGA6GYdDKO0NoG43WBTffMQ5ooIl3lIX8otnGtnygKYhwmoyGvcwLdUdepH9qsiX7RuqE9Ki04ju486zVMcWEfrAntd+uxRJlU3ieebNT+dLQ4MdMbjR0nDWT6udHMTi8Y7g5h7oiiKYPrVLN5pRIdolLfs5enZxRy7kPTjV9C/vPIJ8imuOGwqBuxuUgNNiJ735bDtKKpQ5z/yKfi9Ps+kpFyfR6VI4LzyDzgnMu+KNHiYbD64R+NRAqylZUiysi3+iuVlcm9CuybuSO7d9GFFwW+X+m9WE9v9DefZDuaRW11lewD9+Ybr1nzpOCAqrCdsfpwgT8l90Gb9pPQuuWLvnLUgLZl41aj2Q6NmOWMCR3y7OSHyLuvw+RD+rDppptK/UMDXl2On+B0evX6Er3GC0jsi0fkxCAfHY+sNusQdPbbO26/TcKodEcomLhA/Rasn6blxoiToleIWauL3wuyHRCkCI2NcqwKQfIYI2rDCvXJ8XOY9LNROSmcNavNViDrItMWBPcYdMN1dUePM5Kz8fyPh4ilyUqxYre/yrWpw/RS0Soxv73CIoJS6y6UMAJmj09fJoNFnEecM24jPD3HSVDz02OOkbV1q6udNUytPQxjuGetbUhrZbrWuc/3YFTjbILoIEO7xx57SN3ozojmE7WSWltb5HWr2rTewul8JoqAlFlNZlUNmI9sNzgmr5E5x+FjzLBfSAhwLjHuLz7nbEsi7zkXlo5hPnkju6mjxlHJryY65+KTZRlncKoHZ3iwUPeLk0R9I/+rOmDOfxy++/77oOc9bR2dcm4IoJ9++umB/S//ffw2nsdSWWOOOZ/J5jK36mxA31SMt1s3RLNJi2EYHQ6xl5pDBX38wTpMbACYLYB2UTjo7gWwQYIFZX/bbbeVzChYbUYhdFF9URRDE4eJakSnWJrIJlWuMepX5nZWiz88MVO88uUKeR06YsJN+tCi1f4EseRNrG4qKjKwyaaby80Eq0wQHEF/GCVGFKIYPK0i0mhZ6w9jPDv1K7EqVyPOWbybEQWrqRE33nijVA5E51SBskckXt79UFZ+BsqTqAxwA5S/KgjNJ1BpH3fccdLoC8ocYQAB+yBjS91EwXsvYHhzrzCLGU7d6oLN9WbPctY5uWsUFq2hH4cxKMoxR4b381fkfpA8Gudh/FZW1/k6bUcedbRcx2TvmFcOrO6gkFWCsj7vvPMsY5Bon+P6tOzFytVruuSscf31u50geu1/piiffLHn+W+6hqlNNfYw10inBuvS62NwBlXdzHuZ4F5abnEGV0IF2cpKEZUl4TJVpgI9oNeR1ecxHPI1Yy4kZMBlvY8ZTW9r75C62t18M4j8JhaLyP1bV1srcikb4vOfeSZcGrIZn4AR5ylBF5hn3U5TW6dzz/L9hx9+uJUp18Wtry7cOeGr3ws1nLWWi5alo32C/T3ee3jh8+UlZZiQti+dxnkhCUeiEo7IXKigVZCgN5g76ma6kmHSr31wr2or651zsbPphCrFijszmC+YEmm1WdjCEcNRuOOtZeKq5p+Iu16cLtemnuGNxhMiQg8jiDoG9pORfP35M/YYLfsisea4n15abRLiZu6tq+8px3qz/X4hfj1tIzGx4//JxztDZZ6gmJtxVAnfxQ9BU3X2ybqZvAsk5+vA1tbUyrIPxZJX5bKL0pmsRUgRJCNCNulLENse38+4sdaBELLv/va3v0k7RtU3rVjmdYzSZhAtPOVisXV/5/o8O3mKeDSzg3jCdeYEybGPtjuCXZ09g5mA1frGSQKdo5wlsoOgKow2BN5AT0dnUjp4BG2AHgb1v/TrHTh81Ghp++Ows9+gCE+aNiKkD1FtDqOLP5b/J9MG2QMoD8YRPUZD3WJsqO+LlHzCMEC/+93vLA9xgxQnHIYocaJExXRJb8vZim5KRqtINKVa2A6TSq2zUPVDgIhpp6to8Y7X54o77/w/0ZmLBR4afgeMm1Rgp81HF+XUDO3fUzZFkxjXgHNLh+qjnE488cSiiv2t5psuxa/k89wwMbHz/4m7VoyRhh3ZJaBe0J2yyQNpYnNeymj0u4rmEYkhckPtXjFjwNzjJKPsA+c+l5GRFq6L6wuK9pQCkeRAQCG2treJmIqsBQjRcV2WrHXCZVa3Ji1DgoPJFq0HTs42Zv2a1ZFhpD7r8SlPy78TcdtB2TH8qXjzwZskkYCCYhHdLapnTAnCuDIu5aJDjAwrjL4heoPGeKJM1tSVmj2BHr566x+J8vEGUUgpbJPdITo0y22A3fq6DYHEuFfF/27GzmIdpkGDBxfFjNeVaw8apyaNdvmB9C6BENxPlxd/T+pb2ZsV5ca9TP/sc/H666/L6KmCA+a9dlOXkInRMxTRWMxoI1FZKXKurBAGLZ+PE8D/bifg1HuniQsesUk7EPQDgaKYy0LNZ38W66Tf+F6n3SdO01P6/Pp9z0l3fSiNoVJqmDJNy0uiUIhU1kldRu2IbFqcJ8PEc4rsQr43j8Pk52SHzb51yIE958sxJzOtCEGUXP20fz1cPlGwZj9JudZ88sW/Wb+PHrORBaOlJAIHhHXDWakk1m+UaGo19PastSFR23+Y1J+VrQY8d3TfKnmGEezDCWxrsXXbvo9Vi9Zmp66D+IjgKjV2CzK9xSphEpOYjoFezB/kMLGnyM4QoGEfAN/iPoJeL8dBy3RViA4rsOae86tTR3scAH0EZ2e9NTk3xv9hBSjLo0Icu1lM9NSYLJFee/9KtHUkrRqdq6++WjrrBNxIErCX3VTZSNuSOUafs/KQ6LPW2dfokezO4qzUqXmb2OqytEXRpxgSHhRMdjO2T4WYMMGggVe9pYARAxHG4ZOEJT6BWh1qmQ8m2dLSLM7oN8fxWP+Bg2UQmP2I48OaVLXJNK7VdUYoY8wbaoiaahwz5pL1e/DBB//w+zDBn87EbJDiBeUN1SZODIWrQLzyybKcXT+xJuelgS0L2cojETW7hJsseXrKF0YmXd6at0bMbkiKlaJO/DX1E/Gn1JGeokQ3DaRfb5Rjtnc2IA2Snx97jDjssMOkcZAJBVFQm98bicjsih8UKkgwZH7xi5/neUVItH30lIRhkVLnIOVHUgQHYLgjsimg0wmjyzYKE2WJkgDaAh682BobRUUeRCuOgcHBQvSFekDl1AWJ3/JZ3mS/nvcStSZ6xDmcz2E6rv9yGQRRUlcRE5+6sPaXT97EMoJ0Q7xVu8aVwp/hyUGbu2qVmPqxYQRWlhmHx4jQEnF3/Grx8OZvynnBwT722GNlz5XuYslDgB+c//d7RN8TbhaXRO8Sk8JOg0ePetb17NWt2ZNi2Ca7Q3TGSHcNzOwVLWJZozFfHFpA8pBQCQ6T3rhWNtrsxsPO4TD5BBZwXo+/22Z2Wy2cayOj9T/63YvFB/R0461nD2Pfp9IZuRaJ0BbF3JnLypo7WB71TMS4oX2lPmNvK6dCCY9jkBHN1qFVutz3vk0fjs754x//aPS+izsNL4bu8Aft4Ng7i3PW2i12yZ3xrD1mncucBpL9Pf76a65J/qACQoU4H4DnJkrYW1DOM/8EVKAVz6cXeA7DdtHXiws6TH4tNHSHtyqalUXtZNmqtabGyJfLSoeiVrjZETRxk3xsNKi31aIBeB2OjuwZZLazAEGgQ7fbe4yx+kp19B4rlo0/WqIhqs2xgmqcuhbuhbV97rbGJLWlQ+KDRe2eWqXlK1dK+BmBPDIB1nWay1u2MTEh2fnqocgsgTAhSMP3y3HI4zckym2o38PxS6zf5301T57j3DsBhg9yY8Wkjn9o15VzrPULU8cHfgcBmb/uWybuOqRcbOUqg2ivGSoSAzaSzt0555wj2yeodQV8jTHXW4Uo6bFiqsyWcM58vI72Mc2TdRXo125GyecrOsQTawc4nB7O/zvuuENcd911hqPp0/RW17f5kGKMd3WVs46pZcx+krRmhx12kGeJJNEyM+iDB/Z39Ixq+uhpB6wUHYEtRRACG6o7ey1+Lx2mX//61+K3v/2tZGmhsByvUf/ZIF5h0eLtszhgXQnlVN8lf2XeN7TGF1KRbmnwbCBFIasOfpUxAu/ul33pZWKPb8j8RNycOdjzfCTkNaDcmHl3+l6XHpXGQQitNhF9IjTce6jaZgbURZ0TGBDgbQvV77jFbdC0PmdH5pBY8xIZ1WLsUSrAWmQDuoCwbDQaEVXuXiW5rFQcOEs4If369bPqhAoJyoHCSt4TlGHqN/k80XPyBdKhBmrBeOX7bL8M07/etOl/uVdqwWTtWDYnGcD8ZNmtJ4p3ptxnGc/y/l3RKOhomdOQT/ZpzVp/ZedHHKLsd9UYUvWDGBlystERpWd+uhPuy3jghLZP/JmI1PYVkyMG5bBDchlH5FkvLucA6o56qq6SpyBXTPlc/Oxf7xedpfL7rjazjkY24jQx/LF6J717sRmmRV9/3a2HXaEME/tvbSaeh93T/vu5ef7j/GG7k5nR7TCtWW3W9oQjsg/YCy+8IOsCCgVGUslO2biWdZvVHNCh9RGryN7tMGFooB9Vf75CugSdgH6QDUUrnfr3+ebh4sHP0+I3zxgwpa8b09bnFbNcfveifX84wakV88TKR68UiZeukbBeJQtW+xPsKAiv+qpCGaYItSglsCyWhYz74f7p3VIoAy/rFYeN7CIkzx6wTXvnpIPGWeomE1H3yB4oNnCWby6gedZlxx22s87/ESNGSKOUwCNONk4zzjlOtBIyxRjaiAyQVfaQY7YsYzh6TY2NkjkVinw+65CNjP1fEc3JtZVJOefjoYcfsSCpZJKVpM2AAFmWcNwIbubLGLH2OffOPvtsycppvD54fegwwnFhO2DQ3mqsPZwS1ZS4Rdj7ADTyoQ+0iWQuIs5PnRjYF0lKSIgjxvufL+2iTMR6DJDXTfmJSg4wx9gPJAz8mHk3Hz3YcC6qq8Wypf6MwMUKTqmeY8rn9CNtdSPk+YQzjFNNC4177rnH0j2hcESEXJ+hpgCHFvRNEJpD1ZLqMi9ZLZ0fECOqxlOpN2DNSa23XzRp1ConU1m5bxkfWEdxwvnOHzzpAzhYFj61IHiYHCx44er/DeIvKDkOSdLcP488K86P3it+GZni+9rKUKev8amK/R0OU9hwmFTQI5nOiNSy2XKjbL+tt2Bvm933zztFfvUusbgzkqyTHbjPxtfP203ceuxW4nd7jpBRVxxENkmqI4DNzjxFiOhAeADcoBTR2eo63/+vaP3SaQyjXFEijAdZJsgEOOSCOmSnU0nx5oKk+CQ7wqpzYXw5qICFcNhATV1KBkT2fTL7P/lJvKanKB+9rVRe7C2K8vN99tCeXuYad521ZNPKUDwaCswwsY4UfbOSgfX2ITSyd6W48UijAe2jHxsR28Vrbex4p0uP353eQ8zJDhDPZLfxzVIyB+M22dT8bhPzrK/lSET2CCESybzqRuQzny4VR976jiOTVqwoog4lfjOvH+JQnJPtU8YQ65jmrMXI8JAT6tddNUy3v/mVeG3WSvHuPH+sOaL7437fhQ7iniDWUM5OtKKmazVMZvPm7hLdyPZzmNwORT6HiXX2yExvjUlL1nu9ev/ikOk0bz5hSxkRp56OACFQXtbBabvZHezdGRNqBgiOVGjQrf+8u8JqFOvyl6wgGoIhXGgsceAVLCuj1Ukhr/c81Bn912tUi6D4vmOaPVZkVIj+VjTMFpk1S8Tvf/97yzDX977fulOOU6Gv5N5LoR6HgVP1lcKJhS65kJMyZNjwwpA8n96Am4Vs6OqQyqR0GAkEN2SdyAcuHx3FeQL5UDFOk05Z7pYVq5z7umHVSmvdwKTIuYPBqSBuBLl0ZABZBKuOxNSpsDAquff1GfL9OEHuwJ1kznRlmGpr6636PT0womjzR4SXWRPdpzJ4Lgl88cP4FFOOoJAyfsgPRfyh6o/0PU/J30tfZcTYjn+J+zO7+2YPbQkFBp5wsOt2Ps5ogZFOiwsuuEBMmzZNngHoAuBnwkXJjnz+5SxpFzGWQwYPEesikCo4M0zFBdpksCOVkkFddBc6BbscQox9ws7aeQVbJlMEEUM+Zl4/JMErr7wi1yRzwVgpRMPSJV+L3FfvWa+rMMlFsPN4HT8gidB5Bx100A8fkodB5/6hv436f4N4hUWx9dZbS+wwDsQlZfeLU6JTxPkxf4a3udn+/tF6Uy/p0QJYSVjs5TEz4vXE1WL1f38vi/3eeM0oANTltP/aEUM/8a0/0X4fNu8xx+Hu1oFViajYe3w/0dy4RsIQwf8iQT2mFMIL5UQ05+9//3vRkWvFZKWkJtdmFEU/f40YlFkq9hCfyEgGfcJQDCqyzvUH1zDlxIhRY8Tk5BXijJRBH42jw2GDEwMcAIOCSF0x18lrqIfBmMLpEj4464iJ00aJsEb8KK11SfiE9PT7kXUOsZjMakWiURFzUbAqqagol80wiVbuMtK4tuFmvyWkusyAEprD4pGsC2Z5YfoEsWfyWtEhvI5hWzIr/v3q52JBazRwnUUjRjNg2IlQ+rr86p5p4t15Db49p4rZf/TxUZIIeY3pMyfZEcfOVMbKMDF/GCzsJ2Tj0HxxdOQlT3GyknrR/I1C8nRiB7d0aOQsz5gU2LqsbUvKtY/xoqL0+eAe+Wo+Lv7p7t162MU0z0Unq1Didijcxq7bQPrJAz7GvdkLSRd9K6mxWLpipYTjYSzPnDlTGsQESzbq54VHI7NWtkqHGjKkhJYZnbnaCEjIgI0P6YNimmJt8Tqd2t4t7EPWZLi6t6gZ76zfUnsJQwvRA+B+9ORusR2dkDTEyfICP8KwQWeh8/KJMj5VUjMIeqzXCELk4JbxHXeIC1O/8Dweot9PolKuWzJ++ZhUec39998v3nzrnYIO004RGxGz5oE/yP8rtGClcjreff9D37lTfcLIEqK3CmWb8pE+PPGCk6L9yccfs3QGjrU6f3Dkf/KTn0hH3DEGML+Z2bEhoRUeYoNVHUIGSjBy3XsJR8Tdl3D/Aw6wGCodr9XQJiq29srPfAJ4prBmqamRdWBFULPHA7ZAKp2SxjZnOGeWWx9ZjaFDxv7z64emJFbfX2ak/IT1EjIDrQpiR4aFrM1LL70k9YBCRzivL2vt9Y02CiZpKEZQf44apiIcJuwsaMTpe6WCs6wZ5joai4tRISdRxUfLslagGghrqfD3ykqDOZfvksFZ0ziFVrypyQhid8x5z7p2qMh5LVklxpR9wz79wUPySN/l+9kgXmExwoA2adKkPOwstszM2eM4KmykdzsWUUjok2GiNgZHJW48B74W5YfBnHWl2ZFCx6dfhqm9rU2UL54qIl9/JPpFvArXT1A2RF0pLifz6GMDSVGPs/lQ3DiUxUTr9MaWx/RaKC7ae5g46YDtZLRkZI+4SEy7Tyz++HX5uThNsNUBrVCKAVy8n5QlEtJp26jcTiujqMGDQ0Rw8803S4Y8DIlixoHXoFBUenz6cuOGb23e0YrYK6XSu08fIzr+yCP5D14fw1uP2DL2ZKkwfFCWQRmmxjUN8kDjEBheabxGt6+CmgIracv6HUrBxlLnlkeJd6Obyd97JjJibGihA3I6oleZdBZV2wIUq+ea20tnp0IKzdWuw5z3igHEdaDkdebGpxO/F1fF7hAHhe2GwLO0AmM/Z0yJkzCja/LfDxb5Pn798186+uI8P8PrMB3yz7flfdB8UWHei41eIjnN6N+kv7/z0FUh49urypgjvyyi2zlzZ5j8YKBuCZkQoqDMooJjATWlBhBDFT06fPhwaaDuv6kdyPLbexiX1dWVYnLnZeKCeRPFzLUJu5bIBWsmcKPgLNSncH9j+gY7JuxpyGYGnnKHqNt8L+f3K4fJVN16TUkxKFClTrgW9AFrn9YLUBTjBLoDPcEMh8Wx5BHEibvqsJBWUS7uzuwlPs867QjOu5ptD5W6EV1K1DzIWefaZSsLswlsPodJtdBIrV0mWhZ8KrJJp5PdkTOCC6pWR5elS5Y6WBQZu0LZpgc/tCF0bnm0wQkXHVRl7M+qmEFpz/eoGh7WAg4tCB9LQiGxq5nYOCv2sPFezdHdd1xPaRz7UTlLB9dVyxiJUStk7HEFgUPKwvZ4VvrU8iBbDwg71jlQyr322kvWpxbqMRjTPl+XeDQmbSfVC9EbJHEuunyQvB77/ka0B5T1spdyHc3S8eB60QFcM2OuvtevFE05w7x2553s5rT5RA+Mu6XYGiYl2CcEGVmHQDiBvfE7QWsaIpdrgQAF3URwqoBL6vDOYqR///6y1phAMPesHNZQNm3pE3SyYtWlNg3/AJQVWVKCUbLp8Q8dkodQD8BmJWoPzAmBevHxx529TTaILRymsJFVlBdu9tipRUe2Dc+U/694wKYp1g8BgpLVWuM4WEnILIC1HTG89NSwn8OUTHaKZVP+KnaJzxMTt9qqqMaqHGgwqbCRYZwKCnSqx2UdVjQqm0QWE+3QG1uee9LR4oTdx4vjjjtWvh8BY4ujQ1M2deCj8ArVB7XmYnJj77CFTafbKCplhhDHjywY2YpiGcJ4DWwwKFwikfvdlxTHPNohLpnez4qQqaav8xcslPeujJZSMhW6kcJ3oswYe5rixgMcJhxrDkuc2p496j2wkaCI+rqIfsg9mzjf8dx52+SkTuH6g6KRpUB5dCmm3kwJaxEnkogsRhp7F6NZl/HhBaIlZ8z/CalzxMzs4IKGe3dkmFSBvVv+/rLTuWzV+v64hcCBymKWkmGKa84gASB3FnBdpcJkTuxQqZI84u4f584M+B3E7vcgZVGv4b9g4SLx8MMPy3VANB9IHoZBEIyX+hYMZWh9ly9dKj7JjRJvto+Qhr3MZkcikkhCF8leFQrJmk2yU+z7fJBNvv+yyy6Tv0dddaZqDhXTWlk0LHW0bJpbBAxKX5Y4iDiH7EGurZCzpCjsCeIsMSF7hfZoeVlFfv3mY5rEK41eXAStFM27n+CsYKAnysp9x0oXpXdjdf0MXe7KsrywvN7Y92YvI13WNjbK93AtiDvb5CePfpS/T48uU46IO4xT5kQnRUInUY8bVGeMYJjm2o1o/7Zj+stzSGaT/LxoV40Wvdx2ve5V0Z7MWLWPSLmWAhpRFxIj671z/f5JVeLITYyNpSBioI9YW+yFdxYF66YAH0y29mAtcu2q/lLfz+77zwfJk/MdQMDxSOIScWSfeSK7+Y8kLHufffaR44aTqchZ/Ho+kbFivwEzGzPGbjLslvBqG4X1y9TZga9b0Ji/hmn3MrvJ8SaheeKi2ofFngMNiC9oLwK0BOhZi7Dk6Z9RdZWNgmA8CTD4rok8cs0110jHDBuDNbXjIGMuJvQNyZop1apj5Ihh8vcevXpLp5nzne9jrMhs/eAheUSd8EiBLCiaXoTFjNP0TcpNN90kJ4hBZjGQglxfBPgYDGjVeQgT/BifkCrRJrbpmxYv1V8pKZh1Iwd4ln4kRnqPlsV/GPdlWm+ZYqU+5DXI6G+g0s1EHvXDqm9NsAPIoU2Ui/+DG9c6I65kg4p1RPTGluoxfrhOIABA8azO4NFoUY6edV0uAwf8MnA5DkUyQMVS6zNuGF8oCK6zoTMs7p+RER2ZkFXUenXsNvl/1c6/kIruwAMPlIZWULo6lfIeOG4YDJk6OpPzeFCGKZdJSyOEZtRlibinx9MpuxTHhphPJlQ4C7RVnzDruvUmyp3N0lHBoGduwY67o7WBRmse4TMoUC1WKNwHOsBhr5op5wsusF8Vg1w+B6Q7+jAN7lEci+SsZS2BY4HOVuQqxWRmlPQN2XM5derUompJShGV7SmG2MJNCe1eV57Pjid8aaTnn2Ebw7WmKkt2dshDHWODmp5CTHlcNRFaCAk62g2j5YSTfilJYiRDaCYjdhjs1MVyX8ZiEkqj6pzy3TdnrYIi6ft5Sa6HeDk7wZFhqqmqMBqXipw4dnPb8K4PUKv619JThXoN9EKxMndFi5hw6fOiqcO4rnmr8vdPa+/syNto1D1P3Eeool7qcs4HNV5Bgp7v29/I2Pws8nzg65pyFa4sS9rRxqOlMyPP7ZotvHW/OKKsfR3poPfs6k4Bhgi7LnWzZPzU3BTqYUNGSbUbmfrhVBlEC2KhVa9TwhwubGgTL32xXNzxuh2M+SJrB2FfOSItPvylf1b0vp9UiIS5JdGjBAgIRGKYL2oKXuf0lfQT0Bd8hqLjN6/aer7W5dgX6stWbp53fnJt7FZRscVBoqK6xiopYH8zr5zLo3cwmiLrsqY9J5/HDk5rhEGe+2i1HZ1WM+DmJ2c9Z+tVNwqg79ynxNw5s62/b43/RQytzoqbd2u1+kfhpPK7DDyGwuLT7Ajr9bmwbQthd0nmvwI2163HbuX4m1pCdBLv0/XjudtFRSyesGZnywmbWzBcgmw4Tdhmqq57fZIuOUzAlegp9Ic//MHRLRlFi5H2TQmHEY7axRdfLA0p0qV4/93BXvVNC0oVRxOHqbXZSdnsJ+5I6LjQQjHl6HIxJrxYUjDrRg7rvlwLy6CciESxwasKZLO2j37l2Yx9NKPoua+E2OHukAhFE3KuITtwp27z2TYoEDJdSmH6iTIS+Hyc4E022UQUK+7GlgquABSQw4XvhF6Tg43H+OH5Qmlg5qtzrl24iGD8cBhyKHI4ckgWg7/lu7hGflC+yjGMaDUbA0JGfVfZJnvJqCAMN+wzIB46qYU6PJf4RPZ1R4Lrspy6UNjjMN2b3s1iVuLwIRNYaR6keiPKSnXidVF+3nuBGF3jXF9JF7ZcRXnl76GMjNAyZih7Fa3Vi4Vf/mKFePKT0liIJFtUKdmQbE6u26OOOkr2IcHwoJbFKTkrakc00w2v7G6WPCW7jvFnmyy2uTGZEH6ARrAW/Ry85+bk79uFcEhSDN+dGPRwCQ6TG5LnZyDNWmM/9ufjtvJ1DfV9c+a2hr48YUJY7h2c9zfffLPgPfIRjKWsnzTnnwwHhgv7mcc37esKgpm9l4i8A/PlO4LuW/VnU7TMat3RmHvHzhsls1colrBqtKhlQef+ZGOnnhtS63/kq28lY7/TTjsVrKF0y1VPzxTNnfaa+Wiht1GmQ0buKCor/Q3t9vkfe7IDzFDrnPdlfRWIlvvuuy/QUUfPEixsiBh94faNfBB4GeekTrF+lzWL2bQ4P3WS9Ri9iQxKeO9+wOCEGZEgru4sFUVDX6JwbVAwcxbon1/I4NRJhhpWr5LMxlxnfUXECxuP+p+JZAvfmm3bWCu09hFIXVlwAOuXWxmfiZNGAOzFF1+UwYM8LOSib4yAg3cfLFy0yDrrJUPtQicjc9jcf9bfPnr49YxBONS5ZJYI+cAs3dJz6DgJvydjCQqDOecsunnUG57XRqJGJhkb7+577g38TFh4legtYNyyojUn7vzIyFQ6dPTCqWKnoRWi1yDbAaoU9l5Aj+Ak4VQTYGH9YgOo8XhrjUGTr9YGDixQ30JO/t7j+zn+5jwFVoeOc5N5qAxTLpeRNU3GgxG5dpXTtPvuu3d7YOF7S/rgx4bHBGDgfFMC3IHsBhkFJpxDho1IlPP7Lih3smE4Gx3ZiPjChO8EyY3pHzv+3jHymagwSR3cyqA+IcTSs+ys1WczPhdTpkyRUIKJW24Z+B3QPfZtneuBIehyzNNxsaCjSo4zCoPNiKOsO6n5mG/om3HuuefK11TlgljyjP9xlJjjYiAghbJOZINo3KYLf/N4MVA6GUWq9zoLbHjlNBXbp4fvAtZDtgs4icqAuYtslaBEUEQYajDd4Jgppwlc9RlnnOFo4Oln+LHeMMS4Rg6SuIv04Z7MXpYCINrDd+psYX6F+F2Ro484TOy+m+GcKXEbQ7ozV5mISkMS+MOsWbNkrxGuzd0X6jf3ldbngs/AECxa4uVSl2GY4VgoeJMukLbg4CljvSiHqRsyTMVArPJJS4vhhDLOHKx+1zt9ReE6S4xXcPLd2ovJHOOgexyiZdcKRZAxBC56zV5bZw38zFEv5yeLm0yjYrFhGKHvMAgKZZOjkYiETQHV7W3S8z7/wkvyM4jeojdu/8ypKwjcoAdUndyHi1p8MzNAZBWjnjR+tCCD4aibmc2yapE191a606hV6eeqxc/DcyNFMV6VWlewps0ZUf/xFoVbQ0QT/pmObNtaX7rvXLpT6kFqG8kWBzmxjFVrW4dIbf6TgtegG//MAT3JWkSF+PN0wynp7GiTZ128h/d+qO9h7qgR4X90VT5n6anpTvbMfjXB+6b5mesdfzMv3BeB6g8+sB1AAjn5hOtRe4kMFc4meu3tX5R7HLLKCf7suSyZz5b5n92FpIfZFJbAJQFjxa6bj4b83qq/io8TXkbSznRO2p6SyCgSER2v/NPxfCadcWQe/TLnO0c+lX3/sp3+2Xe3LN/yRPG7Wx6TmTE+GxuIsapywX9Vf0LOLdbDa687HaqhYZvwimO6z6xH5e8dzfnp8dUd6HC6tlduluOQ6TtOu1ftPbmctKUo/0DHYJdXbbqHdc6GUh3yOnlcBXnok1Vq4Ktnz56yFpY6Y501eVlrWNZNI+lkUixeZFLDm8Ec5TRhx/9PZJgwxFkUbnn22WdlZuObEJQFEBCyBkowYvibXlB+woHBItB/vmsBgoGxTWQwnywRvcSPO+2mbWdEHxGtSS2rpCmDgzdyRinQj7JB6NSpgUa5lGzG6DGQdR52m3bcLt7PbiT2vDdtKQgOUQ4FFId7kf94S/swefp02yhlvKlpY554TzwgBY4NybiQ3r333nvXeZ74LpQGGRZdZFPJXK4kuJ+SH2850NUs9xdF1zApg533Ae9C8Uq67wDyDzIb1D6wl3AalNOEE3XmmWeKhoYGGa1xi9sYklSxdFWv6uHJMM3N9begZxyiGL9+zlG+fhnFSF0ttRDOeXezF+l1MVGRlvOPYQT0Bggk0mJCfboqrC0CLMUKvZqe+mCWjKLhwIPVlvDjjpbAmgvbYQp2aHIFqIWLkXX0l8TGu/1IOksYWxycfjOsJQt8pXPJl/L9qolmd4ly+oNqvYbVB/dh0qPS7EscprUtToMyyGFSEe9X5xt78um5ORlsAI6H3iuYTQ6FpD4gmDFwgBGJzZrXQfNIHMuVaaf3ArSctSXrDJNJcfK93jNVjQX6A5iuClSxT7zBh5xo7Uha1MzsfTcrW77IPsJ16AQnPrdZlOiObeB3jXIGUnSYsLuptPHlEesaCQYFzQfz/smM0pk0+bxc3Jgj1WQ9nMuKykmHi8gQA/KoS6swGg7jyGIPcXa50QC6MX3qvdMcj005fUdx42F2nawu6flTHX+zTji7OEvp6UfgVfWWyydGfz1j0mBiJNDMeT62l713yGrKXj0BDiyBIqCJXRHKhHg/1w3EVdUA5XOYkLpQq6hodaII2tMGKdTcuXMlodEWGzuZ6FLptCNjsSLnH3h9OXGOiNUPkN9RjKzoOUFmagiIgO4Iko6k0SsM57BNy37iXA2rssevX5/eommpUfefFPl7DapgiKOZcnmZnPvVKzUkiLD13I37GDTujPuJJ54onaeaiZOt4B7loWqdYouAnOlKVvTII4+UZ6LcNxCefGHsnfmVm4te5rmN/bl82RIPQynztL45S112mIDFnXrqqRIix0CRObnyyislX/15553X/Vdp9v3hAMCA14W/g6A2NExlIagfFsZ3JSwQqDUxADE08mFclSzLGZACJXodtB4VrnTtuS232koqJuCRr71qQDiCDj8yhWGtYSfSLCrE4cmLxZsLMzKSAUwOJcBcE50iw6Tj23+79xiJb/3k4r3FxgOc8DgUPcYCxX1BdqLKMKHIVbRuXURRjSuYxAknnOCA0QUdam7RN/SgOmdErtQNjyJVyoUfgxHQPxPx6KOPSqiHZM0aM0Y6TTQcpFk0zpKMdPXrn5dWXFKJmr2nKrc4wOMw6YYjThyfDQ285zM1h+nSg22mJLf8YgejsNMtNMF121gpV4ZJJ6RIRIxeK6wF4JNqjIMYDYsVHAOdGWpa1r+fji6dGx8kpn78qYyiUfwrGc1cLFpKMnqkv0BNUKoLsDw9i7uuGab/fLhMjq10vAMyYtl6W1fen97V8dyiv/9ULL/nPLm2CpGTlCoW25qPssCwm76kpSiWvO0O+qmjmWJBh8n8KFUH3tqRkroLp539QW+wfM1SmRMVqFm+woi2sh5Yy9dee60MesAMpwvBPrJPGJIEt4Kyj9w3OhHUANlOeb0KCqrXbYXCFh27Qmi7UZk6e54uKh6BXkK/gwzwk15VhQmL5PWZ37P5oGBD7J2yHcSjmR08TGEWhMddwxQ2iCwUlDGIupyxnjvPbuJdjKx+7ibDsC83MhThngZLXzQSErU7HOX7nrZcTGZoVS0G2b+g88VvbhnLnUf6Qx/d8HW+h8wK9813qTEI6uunRLEKIm+88bpcQ26WXklhjW4LCK52kWPH0SOS+0HfEITABiqmDjXc5IT+c4aTDcEZwB6kJEMXzkR55jUYTk2TqBKvZJyvsW+qeNMXHQf0mHNZZXj9ZEmzufdiMTFxkkE8hexdv0psN8muiysvK7PqHDMmBXqQKH21jRZA4B4Zi6Hltt5VdPLIMRt1iHiuU9ZNk8lRe1nZAG2dRh2YWhesoUsuuaSkmkWE9Yddwpzyk0sYe2fMiGFWDRMB2b69zIa4JkxvfZYuOUx4rTBkXHjhhTK6cvTRR1v0o3id3xfBgUN5qZ980YFvQ1BeRHwwmFMdhaMbbuhSEM2k6r+kZNK220onxYjqBNdtpBJ10pFMx/2zXSgnNicF70RXSO/ioFLToUf3EtGIxLfWljs3P4qdLukYDdQ+BTmJFMvzXdQLkBoula1FF78C3K7WHulSqK9IIcHgIUOEMmXMVdQtn4LmGjHayOqRCeQzmA8iwE1m13Nd9EOIz5b06iNHeuqEkE4tsqUO52qfYmD9vnVnuNiIMtfkHjs3blt3mKavMBQ4Rjj6RdXLdYXoQRcMU8UwhnyVc+Kx/STWZ7hYMPE08adrrpUGiszW1fTOk2FSDlP+9VtMfY5b9L2fr5eLLmrITt3NSdwxbcEa6ZBzaMo+GsLr8MQ2sp2k17JOoyPb1ihr3xiPfffdt1tx6PlqmEb+/mmxVuMCzgfJm7eqzdBtrqnYNWyQJiDtKfs7lIORMJcmRgVnG3qLfaiYG4OEy1WBmiUpI7gyv3KsHBvOHTJDPXs7g32cm+g9lakLWuM42OwH9IIykGvN6LhOYU9fIxVUG1Bt3JB7GMt9SiaOfKjNOk3QvTiIwN78dGRQ496g4M2/j99G3GA2vvZr9ntW6lRxY/oQx+OcbU9mtvVxmCJyPIECEUjifz/hrBpYZOPQBX8+WCy4drJo+fgZR5S9s8UwjBO9vW1S9g+/K26LXSdqRKs0Mjm3misHiYWhPlJfAZtzj53fnkWfw8LpJ5wTulD7CrIHPSTrd5JJuR4pUdDlH+nJ8v/2nJGJlTWK5jkTi0blWexpAJ0zGlD7OarrwkpqvNf4n7WrgiucN0HEDg5x2QHcO2cfNgh2FGekLulEncw8ZZvscoHpuQDSoqLuyezrlMkYQW4zaMxqdK9P5O1FGalPgT4O72OvpYtPPkJUVdrn40477iBiZootFc6fnVdtKHaJTJctONqmPSFtGNbCgROCEwBfL1oo4fu8VtlT6pyFUhzdzePMO3tJITlKkZqaGskhQGYdtsZcxLiXuV9Mt5iP+/TqJY4+6oj/bYdJ1YNg3BK1JcODoiCS/00Jxjqbn2icLvxN5MVPOFxUsb36+a4EBfr222/LKCWGSrIhf9H6igcv8RgEA2vsv/MZZR988KFUphgzwwv0xQqas+zKr+RGYswxHMhyQCNPVJSDqlgYDhEZ0tlE/YIyKq3JrFTkKBsiR+vi2OpU43oBbldqj3RZR39Jrr1ddtlF7LzzzjKrR91Q5eb7Bt7D5hO2EK/HtxHPru1jEamgsPkhC5fULMHhvSo9mQe+D4dJHdy9Qu6op3FDjDkGBjBApcSDJN/BGdRw0y+i7c4MxIV9UFMvd9hhh1kkC6y9oO/mMDn2jvfEfe+bGOk8gnGiCuYN8b8X2Ch1odneiuZOCQGqmeA/X8Y92aQPftj5S/YfVVIjUbfo7yg2waSMZW+D5pzcl+yDp39aIY6KerPQA8JrChYms2fJvHQnS55aLsXQr/vVuVjX1m9TGWjQm8jqDsY1byfFIrNeCfnnAYYzpAw5KILRWRjDGEkE3/JFYGGtVIEaJYvWJuValkQQoZB45wunzqf2Fl3HOYUBFBQTyGQMSB7GMY4bckPsH/L//iZZDEJUV62t2rKQqEmEPK0cKs1efbq0mPazgk5jnPM9fjrymG2L67OonL+6iriYPGGg2Gtjp7NofKFZGO6ex2iZqNIgRpaEQnLNcm1ca1BmU8JMI/kj95ZwJmWN3j6yb83XhhGeSRufXTHA6yD+M36j2CsyTcLkaV7OdcwdvJ94PTVSPP/2NKmf3UE/vwCAQh34ifve2GsEy5gbxiDodR+bmfMvc4YxDRxLnQsgE7CV3IE69pqEygVkmNYlVqXey7nFPaB3jL5G9ofu2fln8VLGWxMPAYcunFPcL3uBfSYdL5ERpydPEzekDxFPDvmN+KC1p1U/I7/X1dy6lAxTnTCy2ZG6ftJ+YNxwZGu2+ZHv6cEo0/eQ65v/6fvimgOGigdO2EK+Vw+G1NXWiGEm8x5BAJWZ8hN9/04KzxS5pTOls0PA67lnnwl835KVa0Vk+DYiFI1LcgUdxstjrDv2CWvpiiuuKDm7hKArYNcly0Rz5569DTt86/hc29bLZcSUJx4LbBr+P+EwYcwoQ4baFv6GThx2kG9KUN5AY+i0rASlxN+q7873WVhcGLAoZa477dNQVpf2eR/mBfaoBot+ApsMULoPP/xQxArQigfBFAfNMRqngq9XCpZasd12262k2h3VjJb/jfa6tsxpyIoZKzKiNWVEj6gXAAIDMUJXxY9qPF/t0f2/9EaKujvKpq6L78booTZJRv7K/R14srQnXHC1WCWqxXzRVyokycgWiYhla1rF14P3Em05Y16fOn1HsdVQA9bRmUxZDhJBDOqdFFz1itidgdemopX5aFYL1TPFtfonGicr4aDwQsicn6PDBSOhrFTijBF1Q8AguCe/6Pufn/tSvDF7lbjgkcLMnDjiL7/8svaIfU2dOdu4uiF2k+e91dVV0tio2v3kvMa7gk+4IXlD5z0uVr735DplmHR2vVJroNxwxmQqJXUDxtO+I/2jfj+LvpDXYVJOAFAyveB3XQUIJ9LckRIfzm/Ie69tLkpeoMTW9dX1M/ZNzt8InLUq46jTOm7zuHSaFCSPKKyCEqE3CtE3K2PezS6HIUKWHZ2/bNly8cpyuygdSDtGJDBnCqeDYKcKwknmR/U8rAl5HYraA84R4Wo7UkydihuSV+0TNFRDjNFMrznqYugL5afji830unXFfpv0C2wi/E7WqHtemzMcgcpNdhe7RT5xvpY9FTICpjixA8ZsJq5/9WuxqMGbaWeutplUnF5HMII55zgz02nDoQ6Z0fJ8gcm+oQZ5NuoOSGXPAbIJsdsp8VvH+SB1biIlDFIFfwLdowxct1OrgggqaNOj70Ahyow5z5n9i9zZqxe/ysnrCLcZcE+3rMvRN7zOOQ6sMdZ8eQ9jPZycPFPMyQ0SJ6TOFZ91OI328n4jPO8l2EwgAzuK4O0fDhgrnshuL/6aPky0hirFqgHbSeimPR7++i1a7Z+d1OW30Qctp0Y5psxL/W4niAMj7zrWLMIUs4b44fp226iPGGs2otb3DbXCo0aa9xaOWNlgP9min/1cfahZVFdWyDlkLcz/yu7n5Jb6/c4QvSf/TvTY61cSTq6jTFrbDdZZdBKZ71IQNxcdaNTcqQbjQIQhIYG1+us5n1mvK8sZQbSVK1aIubNnGQ/61F3/TzhM1KOQskfwVIlOX3/99fJxoHnflFA7RbqbDuxEn8FncthgiH7fhagDFMVsehzMAMZfh6Q6g5lp8vVOSSZTcl4ku1NHaew2FV88LQ5qfVbUlMdlJgnFDMMbjhWRjauuusosJC1OOLxgh8Mh0jkFiGqNu6lFbHZzq5XGJloNBfi6sOT5UY3nqz3adkRPsXF/52v3GOuNtqxjgsm6LoSMWz7YIYbR2kYbKz24Jiwe2+lLccKo1aJjv0tES8+xVvYx2d5mZRCmTvvIoiHHsEJxB0VhW2e8Kta8cqdVE8DerSzP7wTnM5b0DJPeuwkDWM+G+b5XY/BLdbTLmkgcc6hHVTbTmyXxsk7lE/bdvK/sugaddWhK1saX7xHxYd/bfLLBUrXYTSvuNFSyZjTT7TBFm5aIhobV1p5VMItS5K05tlMS9SHnyOdYMHY6XDbd2SlpclU9jFt0qJofDby8hmhU7u2uMKrlE2XrnPvQdHHoze+Ie/JkDweFnO0kXjF7ESFtH02R+i8I+YM96s6+/GpiXNSbFMnUuLM3uD+3geknw3tVWYEat76BOQ8YEUbpxwtsw4TrIyhFthnHLOgwPurWd6VBA610PpREvPcw0Wt3o4kqwr2773Hw3t6zctZqG66LroYYYF0Lst3On5/uaDczkytFvbgqdrbYtvMfwZ/H3gmH5Tixbp9pHS7+O22pOO5f3j6MUueZ0WxF8R4kiiVM9dyKmZTP5dW1gU3crfeKrJw/XcdW1dTIgJfHkfFJC/O+oHPADWNG/3CmA2vTqbPd86SCNkq/tY8x2FCReNyo/XGfCX/8oMZgJn3Nn214zoriGOX85MfjjL3DNbMHFMw/VlnjcWjcQeQoNPmakJ3C3sM+YF/+7Gc/E3XVLhpIjdJafmYeE/eDrJM0wi3HRl+0flcEOVx7QoMwJzR0BFPM+mQtqd6L6jzWAwhMbdxcZ7pzp4tyuHcYbN/LmdFHRDablk4z6J+JWzn7IulSOcRwbMrH727V7qpzFrgxuoggIOuUfkrFtuaZaAZnVYCUYBLBBsbn6xU2iqXNZP9LJztF3949/7czTHiTiqIXDC6RSgw0nKgbb7xRfFPCwQPj0B//+EfJIkbqG2Y+NxHE91FQrGwgI4qVLsphap8XTJ3s1/lZCYufCAIbYvfdjHRssTJ+/MYyesE1okQZZyL9++23n4SN8LlERouNSKDQOYANWmb78cYOs9hUhCxyAgyHdXWWukMUxE2XdSUdUMKYKjrnaLO3vizd8LUce5358dT9x4i6SLs4brAXqlhelrAO45nNcatGi7mnL1q4zL/Xyaop14mm941mutJQiMVEPBrqcpatPKb1ltAWN4aSKkQPEh2SR/Eq90Bn9eOPP97KBvp9tX7W5KO2Rzg02npt7Lt/mrQooZ8sjg4wCA7WOuHASozbCwXSil9z5WUGFMZ6fekZJuoErWv30dr5PpO1+/xZO2t/h6Wx3tjohAO9kdlEfJ4dKnb7tzPIkvJpCKvgKayx7oQ6uw3rhz4MhueOCTuLwnVoF0Q2GAVBK5bh8huyLfob91odNxo+Mu/oJx0GNbafs2nqoVsNEhceaDgZ7rFA7wOfQXcyXrd8nHOsSR4jC4yjQlbLT+aubJWv69Gjp6if5Kz3cUtCi5wTwzh2M6ezV6H1a1HydZtBEMP9gtggg7Ou4s4w+ekOvY7yqONPFR0imMBAAl5NGJXsi1RmGG5f+dCwYwS2ms5YtIDDpNjE0B/y7Blg9Olp6z0+IMNkzxFnF/Ork04NHz5CnvP0OdOhqn4BDdYKMHE/cWeeuEZ0uh+cfESPMk+GSQVtVnXYewKaaZVZ0OXr1S0yCNrR4B+AuuppH8bCEkU5fAoSaPevs69vQrVTH4E2UHLP5yHpKKtehkDbg8gjajRkSVCGCSnUYkAX9gf3IOuINSe6PGQ7T2r7kkFj/oFxq/O4s8POCL/y0kuitbUlMOvy9BwjE+hX49zW2mr1q/zpT48OvF41/0DjYr2HOZAcwI1Z64wftjMQ18cee6womy6iakzN85a1BJkHNkuHds6fM8Bg/MymU6Kttfl/u4aJw1bx3QPDo/8AkwsLnIIMfFNy2mmnye9gUUKTycJZHwSjlIWVj2XFLS3Z4MhmPiYuGa0Mh43GYNX+BnOQhEzljIKASQs2RAwBMnooaupv2GzFRpUV7ABF49RtOevAQokT8XbXp31X0l3Okf9nh2U2DehL+wfegt9wZ4ukTZ09Z05Rxe1VFWXioamG4bg8VWYRWxA1IqNZv/epvk0AlXAIyAwOUI116LkEm9TJO48Qe47rK8a5MnaD6p0Mg27Rm+6VxaMSjnf66afLnlzK6PDzh/SsUyEnRDalHLmD9fcOYRs+8O/M3nnfa3w/EC1/4yudM5ndAmqY+vbpLTMPCRMe2xVIXo9KjU7b5zLyfSaHXF+t50soarQ2qK10RqffyY4X+yevFu8tho465AvJe+SLjNV4mbWjGgt3l0TcRkIeJz3fvgCxzHW9/rX/axiufEGrnhUhec5xj0TldaOYta7LdYdt7pgfXbiGT5d3ivkdZVIvN7XZ/VsYO/Yq+48C9nxreNI1r4v3wmPFsgH5e4npDJR7joiKvUc6o7rlwts/Bn2P4aNg9sVk1AqJ25AtBGmur83vdEcwUkNhEe05SNTtmh9Rwny99/kCR91GPlHZHMkaaRp1yvFwByY3CTnZ95jDzs6kwwhXmRB9XwQRtRCh33O0l0lQN5aXtoaNOphIROpG3SnHyN0mazMa2jrIuO5yzdF/8MEHfY3w1lajz1gque61iDv+K5jMSmXUQKsopyPfHm7/9Dnr9xumV8lMDXYIuocsHnaJ37oas9HYgnWOjE++7KFbZFNpk10wH7oHUeyh1Peo8/jxl+0A6OpVK8V7ZkDU3Tz3uMc6xJEPtsj3M1d/fs95fxVlCakvsJfaOoJ7ww1W2fdcTvTY/nCHw1RWWS2DIzhL1HlS6lKsTRc2x3t5k/HdOLHcHzpDnYPyPvrOsXRla5ORedLPFMazO2tfvy3pkoVEYRseKQWrzz33nGQmUZmN9a1z77clqo+GioQfNr7woeQX2VXSJxRMcYtiJWX92WefiWZXFLmQLJj/lUyv4vwCedTnE4XHJib6Xyxkg8MLiJWM5AVADnDOyLpAbQmzy3ctfrj4da1hUqKcEzJIyXbv4QL1MAf3wkV29Hxi+MvAzyOCo4sitsDAI+NbOXZHMTbkjdLr4w+DHE6tqh9RcqyrwHvx2uAmiYzPBfuPE7f/bKLHudlyiD91rpJjonZdYiiXkUEYCFLIVlMbiWL1o9Kev9qep3kr87NOytqSPkZt3EahhaJHyIjwXZj6hVibKy6oELQCVGFxUA0TEGKdalll4Eo5NPT79xuLfMx5bjgjX48B5g7e6BHXpnTM12F6bn5U7lcOdPQ9lLXrwmrpvdbiX5vPbKkctqm8RtWXqNgMk5IHZ6SkruYziIpzzqkIrL5PBtQWaIBdXime7hgtktufLNrTOQccM2X2SUOnbrqpkdkIkqaOtHhtfmF49fSMTe9/0BgvBKYy5L/e1LkEsU8pWf6BrnYLwRmm/J8z68tgHYfEQxkRCofEwBNvFrWT8jekxTFd2mPzojJMSg+ypvWaV2Vou9/vgGCpX7T18PH06bIeDYNePzuDAhoECUesfFvsknRCCzFolcTKymUWgHMBXcLn6+fJ8J72a7MuR68pZGdDP5o2Te55N9yP/SsDIMlgA3zrwcXpyKAsqfoeyMEIeNsZpmAbJ5xJWboOR1DB+RR8EvFTe8mU7SQHfT7zmg+lk0+2DM8OfI6x5SwFmUMmTJ3Hq9vt74Ixb+gQ/8bO93yaFs1KZUUT4sstzvYEIsgyUtP20H//G3gdW4TtNdLRauot00FsaGyW9iE/kIKQ/CjWpotoG/mKKZ/LzDkEcHxWOuvd5DAM6n3pEPyGW2+91ZOF/cE6TEDizjnnHIldpH5JkS5g6JCB2CBewbi49NJLv5UFgmLC6QH+d5dprBUriXhMKiY2j6Lo5pqZYwgZgM2V4hRzLRRpcj36oRlyOWFsPJQ5RAWKSvrbkp9s5VReXyzzZgFH9M4P2ypWFHsh40Hfi98mT3HgqdH/RuTeNo5GhIOp4d29M1DYZHyV0+xuavf2orQ44F5Yigwqd4wjalFkXw8XJO/MPZ3kG9Vl0aIUaT76cSU3pw/0fyKTkpFEZYRL+E0yKTpS+aOBJ931Yd7n1Vgg40ILnbVHAWqwTHRakBx5PbJfmfeEVu+vMameqzqc8wUlvIzCmRk8jCfuEXx7sYfGba/bBb7XP/+lL5NakLh9/UTbcunobFrndIBVdBrp0II1eg1TKBKWUA5FiKCTwnSHNLY7AwCfLForWgK66D6b2Sb4g4ZvKw2OIMEQ41/w88b/qt2BysS6nYH7CpDGzFpgM+NFYgmH4UykWjGlufvuFJJPskbR+J3pfRyP69BUBS/U5dToE57HshoZAMZMKWeUL/udT4apUFuG839n92/MBjSH7tc7f+BFiWww3dJgZ6YC5PQXslIfUyeJU6w3gVWGdj7SB+uOtHsj0EVAWXd45D1l/W0CGh2/9MJzYuUXH4iqpXZjW72mBB8bllrVn+7++++3nHeu//BDbQfSXUfp2MdmWw83fFnp2pzJDOgn+TJBuvipIX0pqMy0goZm8gSFoyJlBSo7OlPSsMdxpL6Vej7GwC94RANb63oCrpszsbgMk/fz74pfY/3emHO201DwXXpEqWb1nMe67LfvPuK0U0F+eEWH4vU48FxHkO7lzASxdk2DtOv43I7G4FpyoNXG5eesoKrKMNFgl2A6n4PzXQqDdEQbztvf/Er8/o6npL5gHXZqjqqSTKpTtJkU/eFITAbEWfOvv/663KfdiU74NqRLJx1YWG4cpiUib0r22GMP8de//rU7r+8HIxh+HLxsBrcy7W7hYOcARrlSJFiKDBk8WGaX2AQQMGDosRmImrBJmftSCoKJioGPll3KdYcpZByiCj8O1ACFKNnIqkqDEa6r/Hz7YeLOn2/t+9xDp2wnmWH2DjAMShWU/BNPPCEVazrZIZpFueOAS6eNng/FRu0HuIwI9t8999wjPx/DNt2w2JHxOHlKh3hmTkaOuSrY54A3asycRo2bXGCbYc5GykEG0sjeVeKRX28v3j4/uH5O0d+6RZVCcT1E6U455RSpzC9/yr+RppKFPllB1rAfLlt3DDhQ/Q7VGtEivij7hXg+bhhyiv7XDwqroAgTwoZTc2qFXSysjJ/f/OY3BoWxEGJNo90rDEhDMdjxxz62DW+/YLXOouc3N4xF/5hhpCTnfSB1Q//KbOC4zGjrEciSR9CEfcq86LU93SHTFnoz4je9Mke0A7x3ycxcforr6h7BvUUKZZhY+qxB9hH/U8Op9F65otKDAbGn9/51COrNb9gQdYO22zaw4rGo3HNdgTU25IzMwYycs2E0/bFKFdYC9wlUitrkUgJiQcyZbl1SKMOUTHaK0FojUJaa9754NuPVx+9OsJkm80lNzz6itqoib4Zp/3vbxc0fdEodyBoGvqzD+5Xjkc+o5rl9R0XFfYckpL5AyCDi2LjltVn+RfXMOwFC9Etdm4EEyHa2OvR/YzOwv055ndDUE6TQ4VM6CURQHSWikptB9Z7Uw+7S9qbvc1MXOXXUx1n//kZ+e8rdcYK1MSRsGPuVPmyPSmIaE3BLa7t06CECIsCnarl870SrCwqqU4INtZgM0ykR55qrGOuExD6WsWHeiKrH5ownE0Zg7JFHHnG85qUXXxTPP/u07/cZtYqG7i0fOdExj9RjJTs75bmBw6OvAXfzZ5tFOWfpBHW/tB7gGrFHWXeMabE2Xdi1r59eWSfbI0BU5edU03uzca3RaqFhbZMMiGMTMk5wEqxviLQuhwaJyJBNYtBV3xyyTVBqbhCvYGSQuqSXQHdgxPOJZMczex4M6F+4QacuKzPGYa+ijPyvfvSu4cUKm58InpvOFKWplB6bhgwT8CuaH3/bxA8YlDuM8qcNnjishzhhx+Hr3LhWCffLIS2LerNpD1aeA0c6ukU222lXxaOmEH188cUXpREOnWi4qoejeDZeZvZsymatonOiTHKOXVkcTx1CHqvHDfsChjcgAK6DvJz1z0RzuLJWMN44GLkXru2zxaU1GuY9ZG8US5FugOiH6PjQfF/Yxr/i18n/R4UNR4VrymbSvodsVBtfpH/Uea1Qb9P8ubnRODgee+JJeeixR/mfIvF1zTwXqmFiPSRXGZm11rZ2aTS5jV2MrXTTSrnWL1+5q2/hNAycRIjR/9Thode6kyXPT5Y3dohxf3zW83jG3WNlpQ1DQfLVbxaqYWrsyEldB5wGx537VHLpweNF/9oy+b+fbDbIhnY9/aXNHBWJxhyQvMqKcgd8uhRRhnzaHaEPqLMLkpkrjeAJuvimm26S0d9SAmIKZlpI5qzMz7SG/ug9436RfP120XPBK+KGtDMqj9SZGdxCcukLX4uWupGeDNM9y4dbv3eIMnnP6FqVMUVPeMkTgseT5575aYU4cnxEXBC9z+qFBeTMHfCa/rW7D56RHQKKyX6ip6VY+rkYOPN+kXvyj45zVpHmUBMDfNoNn3JA/1ykDw4JFbYbFky3a23yyadZeyx18Tu23MeGvi/Rv0FS0cduPtzU0iIDqdQwMTYqcOvn/KXNWiPkgLBB/+0WGsEWk2E6P3a/o+1F/W7HB0I09X5TBMU5X1VgLB63s90d7a1izhefQ1fq+T7Y7/Rebnq9VM5kneOe+WwdidMpnDrYsW7NtWjbGCF57qN3Su1PGvGzAfpuJK/p8S98gj5Zo+EG8tHHn0hnCZsQWy+opc0PzmFiUVx00UUWpSA//H7hhRcaxdUbxCNsbmq9GDsW++NffHPjpIoOWcTLlhZPvayKEGF1goGQA4T/+ZvrB4/blYgABhX05GUJ3WEymIBQLBglHAYjR478zljydEWQL1q/rqL6REHVPnL4cOuAGxVyMlOFtKhhPgELrAvzThCDqDXKKRwvdyjPEaNGS+NPx+4T+GBeR/VxGph+VN5BUmx/FiVJjSFLl1g4JA9E8N+sh66SCiioE7VcHFqq+S+ySdgu3B4YWuXbZ2hieJajQJjrQO+X+7CM5bRiVj9R1MMps0ZgbVOzfIweU9Qk6PUxXZXT7/8ob1TQgB71sAwKSQzjumxZ6xYyMo0toSpfxyQSicpxhVAGpirW8bpSUOvSt8YLowsKHugZsVfbxohhcx8VmWX2vPXZaCsx9HdTxBsNXijXkNp8tDlC1hGwDpkn9JfuFI7oXSXeuWAP8bPtndmdQgIkKqoFjYj8SrbMaNQBGS1GYiHTYXI7+0XyiTyW2V5c+3an2OfuNum0cTa9+eabJRPvLF4TnCHQ5QktQ6pEn4EtJmwmKqNCdH75uvjy80/F208/Jv4vXZiMxU9em2VDlXSjeGmHvbZyoYi0WUA24DAxz+gJJUGkD/Vm7aPx2fZzI83ASqKsTOoKd33gMBfzKk61Wlecs/zgNC/99C0RyyYdgefOdE6iALhe1ku+MziXL8PUbLQRGFHvr69Y79TGFCPvmb2z/OTIh9rEk1/a9o1bz1RG7Wu7L7NH4OdsPMAeMwhRqIfm+mDpJaMRJNQBF1XrXSTpw8lJo4UOEit3zmODcM6FsrtoUk+JCs4P9s2Ru9sU4HV19bJPU9gH/YMTxByr81nfI2Rw0Bk4O/Sq1NeImz7fWrc59IzxPSpwSuBGD2KXEvAK+9gEQ3c9XFSM3FpkR3vnku+urTHOklQmI8+Kyy+/XJ7v66N0yWECXoKh9uc//1ni8/nhdyBcsFttEK9gEEGUgbOEQzNtmb1Zv1iVcSgYJc1Ti4MguIXNhvIjgkZUvJBce+hm9nu/gcnjeohehTTDBzYsIkZEY2T0+zvGsupKPZUuncWsFOHAI8oC403vkBF5rAp1GNE2k645UR0Mf9MFLLAuGADgvInEye7tLqU7fpNNZXQOdhyyBDDl0HiOw0inrpbvC3/7zIJA8jh06FWFk+M2VgvJlI8WiZP//Z5IZsPSIeeApYbu8ccft15zcvQp63eojL1QAlcfJZGVUeBcJiWqtXowJZWRtGWEIvemd/O8BiMqYwaTVqxYJWEaGKfoAz8ITymyuqVTvDvPqNkIcmYZwzJzHImCGxBZ531uFp4nAyaSal6jiNUdk7LycnnYgioAm9+VDvH55MDNBngea+7w12H6vL21MCWNqIjmkKze5Ej5/5kVV3ne27syJLT+yg55+Svj+3Aq0VtqDRUr7gbdShJl5dIh1dkT2evoQQziUmomlSOgs+KVkmGanR0kznuhU3zdLOQ5ATEPNTwKbl+sTCmyF1pCaztgXar5//Ziphg+bJj405/+JJ0C2XYjnRKNwhnAcdeLKMnX503PrqMTlJRXVUv9yM9vf/tb6TSxrj0Okyt7/JfYP30NbtUUNDpsotTB7G89CDJaC0ZtOrBW3HeSUfvG/geCzT3jNDH2QNipL1EChIq/cWghC8qXjVZ7FcjbSZEpjuf23Mn4zrO386/tQ1+SNS5G3sxu4v/9OSH+OyMtDnvQ1pN6EpLxLsu1Ww3DVwkvQ6CS38futX6vqKiS8GXGiPOBdjJBZECfL7MzkX7BMOtaiiR9OKTMri3bOeJskn5z+iBx18K+Ys//tFl2Fw4PWUb2Ns4SgeaDJ9oZuQMP2N9wes29euvXRjb00uW7yHtTmUe/DBMpPM53+p3Sh0qJW+Mohwlm13TTKocTXVFVLZ0l9r3qL7UugdFoLCF6H3qx6LH/mZ7nyhNxkezssDJb7A1QI6XWSq7XDtO9994rozEnn3yypEjmh99xmHhugwTTa7NQ+V2H5BOkm/xf7+JJLgtmY8knbFyVyRox3I6CumtKVMPWXlW2As1k0rKGCRgKhxf/q5qmUjpCK0GBAK0yGKeSHiMS5YCCAZa0rlH2dREdcrfVsOKKi7sq3CcQrSVLFotBITsa+kj8Ypl6Y52U7eRM/QeJ29H85z//KQ89jEdVX6JHWWvre8h5JUpHZgPlS1bPr27ML8OkN0At9FpdLjtgtBgQLczypfDuRGghJuA+inWmWaOn/Xe6eG7mKvHX5w32NnqIzZgxwwFz0GV5zjvXx0Wed/yNYTTgxP8naiYeLGJak137mo1DbUHOgL+mRVQcHXlJ3Bu7QlSJNpOSPCe2q18rJoTmiDe/XCoPDO6Lg5FoZKEszS5jgutxMKjyCXPDd6koZDxhfJcbTSXXiVlTuDJdLokFpmeHi5XCzvrW1dbIueEHlEF3twLwq4l56Qv/+g/dkWtYs0bOd7nPOK72Mcp457kv+DuqOjJVsdh1R61WnGaRNfa17D+hv9SvZJdoJaDLS2fvIob2DM46Kbpsd4aJCPTFbxS+lnaz5xH3hsOOQ0hGWmZCvwGUyIk7Dg/MhvSsr5NGJYXyZCwN2vqsJ1kW1C9N7/vmFl33fdpuB6G2235H6aTSc5BWJWRLyfy7YajuDFONVnOjP2fNx8AJBoGOGehRTJhJ7Rr/e/K2ojIRlc+hm/SAEOuNc1s3Yonf4birIBLBrSDR6zH/oDkcyKuvvirKo0IcOs7fieC7yeoXI0Hsc7MbbGi5En1LY5fUm1t0tXD2M3NLr5BtD7S0tRvkPx0dcn0yHvydLqD78rHwRcwsrZIXM/4w8YymZ3ILbecJaRKV4oRHm8WrC3LS6VYU3ZxbkDvRTkJSwrsKuA170Jj3/wy5VOzQcYO4s/Zk6VDCVLmqpdMT7OT3Pr16yj179tlnO1r4uDOK9t8yxWTcr/nYkmUr5H4naEptJvbZujhMjXVOcihdOtrbTLIk+mPVy2tmzwH9JemyvjlNXXKYMOiA4bmFOpRvGs++vgoGETVMHJAcvmkt2hWPRQLT7Ic9WNjIdAuGAz84JGmNucTdP+T/HbOl/H9tu22QRk2GPGXAqd/58WuaV0jYjMogjGkws49WGpFVItSklvn/u147/zh6C0lscNEBdoPTb0IYCyItrS3NjhqERAhDJVRSxIcIVt+5dsaEQxgYZS7dKfpVRzyNYVVUnkglaXGou4PqxvzS70F1SYUgecftNEbcfrR/zYcuKuqP0Y5SJ1KrCBcKie5YfTRzrjwMgDgQmaQIV4neD6J5gbd25LKYk1mS6HGsp4G3zod7V+N8XPQFcVXsDrF95HNxUtQo7u1TGRIPJC4XjyX+KMomHS4NByKQBAsoOC8Edc1Xo1QIQkr2j8/faMwYB+2uu+0WWP1QOGLUKkbj4kfJy8Tk5OWOTE5HW4s0AHCUMNy6EkQpdK3Fim4cVldVSwM4YTqDxchbizLigRle5yCVzVmENMwRhkV3FCePGDFKDNHOza2G10uShR/96EcS4liVsHWB/P48n6UyGjjnTsmJ9s7CDo9qGouRzA97B/17yy23FG0099N6exWSwT2Cnb8999hdrin04nHHHWfUi+Wy4oWMDWNCPswZ69ct+Uxmfb8uard118p5n0odzPxy77CuOfomWbTiwft9rZYB07MV1CwSudeZMNvaDQN4p9G9REXcmDOVSYBABZuqMiZE/yrvrOO8qTOduXI7tLrRqTdvdgvvu36fMtG3yv816CT07uTNCtc9+2VuDnxjjFDJYN2PgTxID0gqh6mxQMNwXfg8RdmNzlS07Xqw109eyxr08sVkmLx7yRBd/4VzzoDZ4ltOFOm1y+S8EERiTgnSQddNMFLpDT2gGDMhcao9weIlS8RiYQTE0GFktMu2PdqTYcIJamszbAPWKm1D7Oecu0A5R+FYmQgpqEjLSuu8YK6pITr88MNLglSHS63lhoHTfAs9wdClQBWByuPA53P+fzAOExEZcIg6lITfr7zySvncBgmG5KEg+aG3gpLhtQY7ysOLjAjYP6caUU0kAI1SlKBg3vlgqvV3TZkzO6AYnpY1dnoUMIb4CSecIP/nbz7roIMOKrlegY1NxJAeVD3r7APmT7NGSBwvhgJd7ru7FqKrcKAHTtlO9CvQW6U7hEhSLBoRH+Y2cj1TmkIivd2yzCichaoVSCwUtE8e1CzeP6xBjAwtdtQLHf7zX1vN9DB2OayD6sb8jNeg3rbFKNJi2A/1T2EPsC+KjXjrDndTe1LWCEGyQkF1UMPojqVzRGpNfliRDr2J52mE6dcUNLHWmJthdfbA5ZbMtNjRgELdfPPNBSNt7Xlo1QvxgzBnfP6sL7+QfydN2t05Da5DFviRCRkje4Px5TbAWpsbpbMElBPDRTEtdpcEsa4VMmQwyjBUGotsDK5QXG0pH1rijOGws0f5n4hoKQd7EF15TV2d2GqiTYX+1YpmaVizB9F/g+oNp+KYbQvj+23GKyE2WaMxm5GNSBY+NBSUT7GUMocgRRjDYqUUFO6EwXXi17uOFEN8HKfqKuMcYo3ed999MtPF6puRGy5277xOXJ08wrfAvphggnJ4lqerROVSu87v0y9mSx2I4c0P8GRHpqcI0oclORvC1ydkZ7AxRtnbquCf39uTJrVzxKiLwx4gEERwS9XJLTunWiz5bbXYfnBEnLN93AERJ1iJ8b3xxhtLnaYLNavu6/YT5vlXE5179QmtFABnhJ/f7zOiSw5TaJvjrN/dGSZFzhCp6iHqhxuBszbhPGfb8yxb5phr4zyYPHmyJL9Adt2ot/jppOD98kB6l4J6vSlXIe5P7xo41zrpTdxEE1jPNS73tHNBb5x//vmOc1UPKMbicZnNpN4NyWkBr96DRxrQ0PrBHoeJPd9u1sdBsKbX5bqb6er38ouhS8Vj8QtF70irpfvY96BcgPaVEvCKlAi9z6STIm6WBvQfMEgSTJEdBHo6ceLEkrJb65XDBF5d/bDJp0yZIhftnnvuKX/4/cknn5Rp4w3iFRSiUnoskukZO4rXo5zo4whx/5rNxY1tk8WfP7EhUvmobwsJhvHQfvaCLPPBkbuNFArCFe6WCIRqvIYi0Ps/FCsoEbpSky14P2pgqF9dUSdackaWBWgSBsl3nV36NoUDEmW1ds0aMTPrUvam4wGka5/wB3k/p23m69IhBUaJdCZTEuvOHG3c01g4+4ffs2KwK3P1orZHL2tOldNUypwGOUbFKNJi6l3Ux3PokAGjrqLYiLceIV7VGZHZJeorbRr/nIclTz2ST/RIZFDEecE1B4k3Xn7F83jbgunGN2heTby8XDqBqkaGLJred4XXZl0b349WW0khRkXmDKNqhjpgTWIH97suTx0rM0zyJRF/6GVFIi4zAAQ36M127LHHdmugo5QIpg7JYwgefPBBkfLpBeInajj9lm1Ks5tUlqkU/TRxqH/94ajRo0W//naNVn3/4TK4odiq1Dzuv4nTIPYTxdyVTnWKz6bZeoL70a8/SFI5o1ZNOYYY4kCISsmklVq3eN6+Y8Xr5+0mxplQcPuajc9BD02fPt3YK6YROS83QDRkDCdr/4izuasS917xcyzZw1V9bVjgB8vCMljBPf/yl7+UBqy+joNIH3Q5MfqM9XvPkO2ok1lgbDkz1VlKDy4klM2I2267zWrciY5ShB9VcWMc3jq+Uly7l30tc9dkZXDx17/+tWQydAe4cLitsSgx4Db5fmdNpmwfUlkuelfnz9z4UUgH9WoapiFi+//8RtFrm4M9TteKhy8Tez9WJWZm/ZnT0EsE5RXDrNL1jPOVh2wqXjvXZvXUxc0ep4vS5WTSz0//MnjktH5uWhJYCtcja44TCZkdZe453+lVqrPY6ecj9hbPNaw2gjCJMvvz9/rFOXI/dnQmfSF54WSLvHdqcvnusgVvG+MQkGFCbthsjmx5sV2VERgEHcp3sN9wukppPB4SJUoWQKO5l+cvkHuCfQbRlHvP/aAcJlLm+g8RMbIGGNX88DvOlN4te4PYwsKADpSDl/FKxZzjBAyr38DBYk3lSHHxpZdbCmFdaunZuJeceaK4+KCNJdysmIMvFjfY8NQ88r8ysLsCySNLQJqZqMhfpswQR76/uXgicYjcsBRu8rjqA/S/IswLUfp0OuU5ZEKhsBjdQ0hI1y1xv55mtmJc/dxN0ugeN9bIUmUyWakEdaOHrIGC76xMxuR3r8ucrovDVIxyPGazuNmvxmCVfOGFFxzORD7R7xto6UMPPSRrQ9paW8Tbx5eLB+KXeZwjbLNQnganeiTy4ui/xROJiwJelROrG7zUwRkzm6PbdOX1fTyNnXVSgdPu+0js8ZfXHDTv+Rr3wiCly57j+vjPjSIECBn9harKnff9bHYb+RwZ4cRg/6Lu8p4DJU6fdUQfvu4mayklw6RH09c2NcpIflCPmf07r/LA7hC/r0uaeCJgNtQlcLaVwt557Hb+/aFgx+KMzPY0oGW9evaQhjCGIBks9q+8NtVgNM93KGMvF46JNabhhYSiMUcNVpBgrDJWqkk581lKPxYkHgmLYXnqrILEPeZKp8g6u1BIjrWuT9oz9u9bhmwWxKD17zdOHam0GDJmU/HT9zYWB70ySjquZEmpwwM2hxD17vHW34p2mIIE+C8tHQh6qrNUEVMsWvCVhCQRwGD/UB/MPOQLWl3+elJCmNCHZMLyBaK8GabiIq6MO+cABi3z8Mo5u3pYUwuJ/t36ef7az40MYlVciEhlreXsJ3O2w9Q+533x5owlYr/kNZJIwS1KzwCv9sv2Bp1LSS07tNYFAVRzq+qcemtZQvd9hctrNNi8IfOy/cQBBxwgy1PI+FCSctVVV0lCJ3c/SX3NE7g2zlxjbqq0+kiCeyCQbJY8e/3xO/Btzgz2KxTkvRa9Zj7nnOeakFHKMSTkrTFVAUMFxf0mCbdikbCoLDd0yspVq6W9AgT59ttvXy+Z8oIpRFyilMoG6bpg0GGowGzWo4ez2Bzj9eWXX5bpdqIPLGbkoDHBUzRjRUaM7xNc1IjSIhN43nnn5Y0cVmiNGDcfP9bj9PI3xYuSaasLEQHuBQcBQ6A1UiuOOPIoMXvOFfJvHlf3+r8ijCGH9ayvV3iLUulHUuFU/m25hKgIGXCvbcMzxbvZjcWye8+XDQ4j1dXi3XfeEYnJ+8r3Ug+WGIAD9ZDxcSJnHVBlFUaz0XWZ01ik6w6T6temZPIDKfH44d5MxoS+ITGvPSqx3IpmdZthW4n35+ehiA0b0XIlqXRKri/qCIb3jIst+/Dcl5Llzp1hilbb0Jp8RtcvonaTbj/xI+ui07n6HiV6Xw/5mkzGOiC5h6dM5rE3Z68Se5oNk+etspmfPP2TNIOR5247bqIYfsHTjseAeaBzOD7BtJ+8hRB/38+rO2DJ63/qfzyP//6jgWLLPmkxtW2ASM+YIYuacVC6u2i3tBqmiMMxZZ2EI/768nNXg9d8hpZyONDVqklvqUaCnyQjFZJs5eftjYK8/047bi8Wv7dUzj3Z+4Y1ZFLj4qUXnxeThhswtCCJmgXrGHOQSSjJxauKyzCZR7/a+wROLr74YtkfpVhDZuthPcROY3qJ0+51Utrng0j56Qr1N8gLarrY901aA97OiG1Q9oJVNFd8hlUFO9rak+LJp5+USJhorFIMHlwjnRay7BjgGKLSUW01qLezPg5TQhRnWCpSgv333986SxUxRcPqlaKquVmymIKwoN6J66jNE7NZ3ZoWmbbFkhUNciTFoOYn7vMECHFQCwfdTiAwwHpH32KQ1ySi0hmes8JZTxvuaBLZMn9bIq05THrWojwWEvuMjIhnj6kUi7Jnir9nfiQfTwaYnx7mR1Nw7jG4CYSdeOKJsk7Ies5Hb2zaOk3MrrTrZs9L/VLcagYhl+fqRK1odbRNUI3H/fRMxehtRctnL4varJ1JjHSslRlR1izrCAcJNAR1wfyuB1nY48dtN1Ssbk2KMX2rRChULfr36ycWNzrXFGd5f+jjWyolAJUMq+4wkcEiYIXuffvtt6WDy9W74YR/it0u7s/sLv4Uvc03wEAmHiedgHUpDlO4xBqmutpaUV/HemkQybRBKy57UK6n0uWwPguFhcuPjqXcIMHCwmSBE4GIRp1KjA3Gc0TEiTiqLvODa4MdosXNwQcFG5RMlmpKmk90h+nc/fwL8zG0u+Is8d1A8jA8OCDGjx8vnnnmGfk/f/M4z69vbCndQfpA3YUnIhgKiR7lwUpps5DBppVaOd9aU230CJIfXCPHdeEIA/KgDnyF/e/T24Znoiy74gAHGYOFWPL4PoxFXUIJ/6LfsqjBoEjtEQYFgYTyAm2pwLjf/Z5Nh1wXSVn07TqJVpVoF29plLjFQF7d1MJBorIWuuT8qHVdsD6ixqq7++uz7ehpxjQEWzrTngNPzzjpEXamwd1kmYgmkdmUSe9KFunv+wU3FY6Y0VQlbdOfEw/NTIv4QddJaMy8eYZhQcS7u/umFXK8x/atEqMTTR6Da/MenbI3CT1GSpEgSB76F+eVcSuV2j5IHlrdX6xY1SBaWoz9+vabb0g4O3sYo72tvd3RtyufKIKRVC4sxo20M1q5TLIgayLSbupbzhzWC84mtUNnnnmmA0rkJy+evbM4Y4/R4sIDx4kyVysC5JKAhr5BRpf6E11EPRERe3SjEv13L5C0QIbJ3Ls4LNwXPxidOPzQdyu2NX4wdpWOUka0RcUsOsRbieJapnB+M5ZkmlQzXOUw9ayrlRlzzmVKG/gfJ+Cm/cvzBmIIqgBdP+KIIzyMikFBBDfhj1/zdWVncP84k5wfKjt0+h5e9jN3v59iIHkIzhIyOLzSqgNVTnvjizfL/1VGxq8Oi2tkD6q6SerB9aycn95oW/aVA/YHo92xnxq06UtzPa25zcekp2pTe+53uhh67mOierh9dry/NCzPKeD1hx12mPxhDTOOfnrxssmbiJuO3tKah4TZAkHvG9XR1iqd1zrzPPg4N0o8kzGuuTJsjBvwWXQwP2QeEXeLiHzNnlVgj3GEHbKUOqLaipjYamgwi/DbDc5gezaTFE1rjcxdr959JekZfT1hyetuhtXvpcME7pcIBxhEGDb4YRAoGKWfywYJFjY8kV4iErvu6sTcojQlLW55uXwO5Y0z8fLXwRmmfJ3qOeyJejBXhXDpu4/tI6oTUcngU1/ZvbVEfDcsecA96LOhs+/xN4/zfHewUK0vgkHEobnp+PE+kDwhTt8meA4qzUyTqvSXWRUNUvbEMy+ILUI2HT2pegUjmPbJDImdR1FR7EnWuFRHNchhKoSoZO27D5HmZq8yR9I5o4cSBg37gqxZexG9sS56zGa862hcaTAzxmKOtbVReKGYmrUNgUWNxueekzo58HOL6Qgvr9tnPypbTj/Qd44YdU0I1wa8WR1a87VMkqLM9eszs7Chzbfo3Y9bLZzLSANj1aqVDlrxYiS37EvR+sb/SYOeXnsYCIwpWYhSMy/dAck7Ypsh4s8/39P8y37tfz9LSuNT1Hn7OOUTv68bUB2WuhgjEoepGNr3YqWuzwARM8d/xfJlEhJGhoFapqjplB2k+rQESJnoFL1NyuV0NiQuOPUX9pM5uz4rn8x54R75P/fJfF5yySW+UCI/GdWnWpy11xhR7SIRonfU9iN7BuqIoDHXgy3cN9kuHWLUW2s+6ke6omdY17QmfTNMqA8yPzhMsHMxr8yvMnDV/OJ07z+23qoFUkb1VuFZDpprt3Rq8DK1dtDxELqgbxXMc+yYUXK8IXxgzrkOZP/Rwed8zoTJIoqmPEjQnbro4+WGq941PWU1MMVxhPIZ+Klae5sNqivJKSrkeLgz7MqZaZv1tnTSFNKE+jo/h4nnFaOgm2zGz2HCUNedL5zt9ozKHGas2lTlZM7PGtl8t4wN28gIPeP4ceXO0jlm3I4//nhZC1cso6u8npA3QPVWerhY239rOR9KnjD7+40bUCPnniwjY6Eybure/GTjsE09rp8XjPe1114r6clL1W3XHRbMPHjDFwY8dFHGQG00rFpl9QLle6HR55oZp+5mWP3eOUz0Rdljjz2kUU/B4rRp0+QPhdksYp7jNRskv7DQYZzThWgBxgiGE3AtorcohC8bgxdzPigCGwIjh59C0UoOvqkX7SXuOt5mcOouYTMC/Tr66KMlo5su/M3jPL++Ff91hxO5xx67e6Jpp/X+SDZvtQWeMltJDwytEpuE5lmHH8onmrCjk+nK3o7CX96roowtHSlZK4Oz9Morr4jXXnutZIUVmGEqYOgyv3qfk1yyXXQGsN91pg1KfBWJKyuvEO8v8NYH5ZPGXptaNLnk8ZSsyNU7Mkb/+sjYG59mvX1ilBRbx5DPYVL9pZBrY7eKavOs5+Bnr5Kp5zDUx1Ht76C6HF+WMJ9pwDAgeKIyTEAjipXN+iXE1lsZ7QfQ7dR5UChPZgRd1d1kLV9pDmNQdmLtGrtJ77inNxf7PFwmXl9gMJOVKle87mU2PNCEQTPufCbMbd11sB955BEiGjPGbPGihTITATyLeoSICSdUjmjQtO8RtiFw5cs/lUQASsLxMg8kryFXJX70lpONc+2yJfJ/5o/7pCcbLLdBLQaCJKF1/33hrF3EPSdOKvget67QYZhkfkAc0E9KyYzssLx7UWWYZi1vFltc/oLjufgyA/0SCscsxk0cGAxS1i8964DO6VH22poqyzFQjlthZ8CdNTNo6dGzRNNvfMkIYs1clRKHHHKIPANk1tfUgcqh8hPmCCcWx46z0k2Cg2PWa/mHBTNMbhlSG5Z6QfXewnnyq5Fy3Fcm2JbI50zlc5gSsagv4YYu6EnsTsaCDCQNlvX3+CEc5s+n+a/9eEuu3NpTm4bnW1kZBSVsEcFZPr/1N+crozmt7AeVTksHuKQG16p2r83J7HnntDUSGu0e19amRkmshpOGvU2QQxGGuB2mj7MjA+denVNkeqAmLzVoGsmDJgknKhxkG2xt1c6mYW2jhAAyj9Tusd7WN7KvkhwmJoiMwHvvvScxv2SW+MHoJfOEw8RrNoi/sLHwrMGeElnUhQOZTYDyg2lQsQXR8VzJ5yudhk6QjsUA49AlUgdrmt+GoN+QLvGos1dCdwobHCYwlLNOV87fPK7T0/8vCIqe/UPdhZvVaM/INIupTB3Yeobj0MjrYkriQrF1f0PhSipTvQ9HqtNxcA0OrRA/MxuxjqnLyNejKBH2rttRzZduR+LRgBqmItYO3/WPn4wRsbaVYvl/Lwxkt0L5y7WfyciDqKOLJW7sNSAxa7WieA485YDetmiotYfyOUXFZpj8oJTqgHaXflWajFgYbxirKuKt14g98OGiomCDDkiez/P1tdVSR5eZ2HGIRYqVbbaZJA83ZURDTkO0l55y3wTLEc5yPmlqXCuuuupK6++a/iNEY+VwWfjeFf316YqsKL/S3xni81iDQM67CzJcXV0j6noYxvnAAf0N0pZx44xed+UVlpHBeRDk2Oq1InWhdk8RfEwLoCCvZzcTLy53OkEd6Zz8Tgx3IGoYyhStlwqx3GFkL7HP+L7i9N1HSUeomDlwv0ZnySN6Lh/Tnp+WszPCfo2jVcDgiFve8TzXr9EI4FZUVVtrlTlFDwJZv/7662VmQF/HzU1NHoepWEmtWSLPNvYJkDuVAVAya0WrDJYyBjgpKhiSD0XJ9bLncJSAa7mFrNncx28wvt/tMJnjRb2r51ozOXl9fD5GLIFa9/W6pbzFpjAvlN0KEkVCpEgf6muqpPGsxsKvhon5wlGij8+kSZM869Sv9rE8ERPp1QvFJanjxO3p/cSnueFi+zKcKKe4ncx8ol/bs+/OlPYaThPXD2Moe6hYUXTiq9Lemp62jP09ykZY8NVc6XAwTqxX6g3VOKh1eu+nhr04NzdA9BD+eo21xjwDPwVxUiypkpJIQB0z0qOXkaULmc1qK8oSktwGqa/vKWv6gH2y3iBBW98C5SU5TERLfv/73/sqRR7jOV6zQfxFRfNwYojU6kKkAAMPTDnRLw5ojL0vm+zN9MAMpzLLZ0ixIdi8quu4W7Yd4U99293CIaj6UfjRlXeF2vqHIMBw7vo3DVKde4lmjYke/R3GusLh67LfCCMCzr6LdtgwgKzLwO8bWitGho2o1+CqtAx2IFBCE610Q3+OmOhP61oYklecsbrN0Foxctb9IrxmYeD6VfoYx5+1u/dee4muSGbYtgZEIqs1b5bxS+OLO7XIXj6HCfjGRiHnfn11fkb0ub5VPPx5Shx4rwGfGN/bOzYTB5gQENdTI+qNB5hDoGQ4JcyFDql7w6xnCurrY92nNpB+DgdOmMxc9zKc4ZAZBSxGOr54TRp+tD0AO8/nENC55557vpFAR6FltEnfcrFSO+Aj4bA0GsgSYPgXK/PX2uPk1+uOgBNGELqKwFN3SXNzk1i12siQff7ZdFmDQHAMfd/aZtQw0W4AuOyyJv/x1QMip595tjR0dUlrjZkRVnyv/c9wPMY9M3+gHeiFR+1QV4wX9v0tx04UZ+/t7icXLO7gippzxgDIjnTehml1Wdr9zs96MyAqE7umzRtRr6ow7qmhsdlyenE+0C1ks6Ci19cx5/Lbb71lGakhMwsRBHnySCgsP491w+dzrl9zzTWOlwDf4txTMLtC8HocK8ZEUZW7ESMYof3MNeA2/lX96srHr/F+rumlcR3F1LP0r4qINa/+n2ifZ2Sz3JKvB5QucRMirjJMuUxKzo1q/+DXQJbnmRuCfO6eWfIefBTHmJEjJMT3/zL7iivSx8pZrIxm8gYginX2bl4yxmLlRD8QAD3ppJOK3kM4KWu0TLlb9ECq1RMsZDiOwKF5P4ES7Kb0miXWmabmlPV6WvQx389Wa421xJiWkhUrBJvuP2iIwx7YdtI2MoOIrFi1WvbcxCblrFsfyzBKcpjwbt3KWRcWclCDyA1iOA/0hUEBkr51KwSUuMQ7m/hnnJ6lq2wokltJFKph4vOo/9ApPp84bQcZDfz1bqO+1f5TylnqLrry9X0dQKupQ4uUrBY1YptKo5AzX7NG1RGecTts/92tx0PhqGgQdm3Jolxv8UbGKFT958x6uaY4dMhmkt53R863HFr3jZA+KEFJ7rjjjrJWIIhK/rwdElaPGA7yV14zqFORSo2gBNl0YHAbg/KtDzWv2X6sNtQiOucYGbZkg31QfJ7zp4JWkLbbY9d7sjorWzLi0AfbxVOzDYv7wyXew3j/0Uadx3GbOes9btjXPljZ72SZJOV7RcxzMPlBs/TH/Bp3nrLLSIdTIQumzeygDuEsJFNfNyBOQPCIRmIYMG/UgZTa9LA7ZIsRfcWggbZjFImEZc3nBRdcIGE6meVzAt/7+9QJ1u/3fWrMmaRX96nZ4ZwDioeOAlXRXYc7DFo9UgYc7vTNWmR0mgg/FNOqh9RVV14p6/eCRDdM+/YfIO898rUN02tsce5pd/NhlWFif/E9GPjfpvESxJJnQ5X3ENtvZ/TsU7Io2zvQKFe1fn7SQzJ0CdGZyshzl/EmG8kPa/fee+8Vf/3rX+XvZGogvUglO7tMKz44skakO1olxB6HG9ZbiR4xMbkjQsvlGY/hi6PP+Vco+IkuJKjCe1iP7rmi1hmqZjkWrvGxyEFWe4k8iK3Ivku1tQa7aiKRNwjSpzouquMhseJBfxRRsZkaVVcFaUvnwuly/bMH+W6gmH5zzGt4nuCNX02h3/lz8YW/txrAKnl9RdU6ZZismris4Wjyw/hR/1ess6TqkDra7TqlfGJlO80GwNiOKliKvb3mtX9bZBxqK4Ci2CTszabpr1FkL6Wy1oXznPVLlq9w7JuZcxeIffsagb+46JR6rivQ6fXSYSIdCvQuSIhe85oN4i9sKNWTyJ2l4+BGIfAaoo5sCLUprMnSIlL5lKx6DxEE0sS6gqWQk2hgUBPb7hZVu0I2I4iufH1sYLYuwsEHdS4Hq1vclNOxRm/RJnLylhHrIPnss89EtN0oHk5mnCC/adnRFq3srEWr5PeitMi8oLjc0UoKunGq37nAdsJ06RPQ0LDYDBMRLWoeqduwql5dcvj4mLX+MegefeRR67mTdra70A+oLRNP/mbH4C8zP1+vH/q/+LViYMYwWHU7i0PztORvAg/JHq6Cb79gxQdLgo2rn01wBgRUDZP8vbpaOjSyD43PmPo5THr9op/DpGeQcbyACKkDumJYcNGuLomUcc84JL/61a9khun000+3CGswXr5tdkuctdGj7WDPxuPGyWtDx2GAllcGZ8/uy+wmLk/9VJwydYyo79FD6h+MBfSkWzCA3nzzTZl56c4aS9Z+ecRYJyOrOsXuk4+QQQz2ZLtprM6dO0ca9sVIx5oVkoyjttNmnOp0LcOsK+MkX6P1NiJbyPd/W+Le9soAU/WuOAVJxego4WRtFiOimz5ZPp+nxm/WF59bDhNjypxTH4yDwHqhhuzRRx+VAUqMdvZieSJutR7g+9rnfig6nruu4H3BYPpu78vFO7+Iy+/iPMfpBno0cZCRpcwunyO/RzU7RTBa8zlM6EE+C9sLdIpbFHlFvgyT1YNNE4JrOGzsHQJT6Ag32kOH7tdUVsi+Q9gq65Jh0muYlj94qXQgQdPwucvvPke0LJjhu+9VRgRnwx2o8Yu9vf3m657HpjWUd5mswgEnzBiZP85fCZ9NJosO+ipWxkSRr1cner8+veX7sB9YD4q6HWhfD2EkKhTAgIxTWUCwVZ1djDdQbfZCd2WYIj0N+1/Vh7W3t1kZ5KOHrJBzCDmcgqD/oB0mDg9YNTDQ3ALO+5xzzpG0lxvEX1BMp5xyimQUdHdXJr2K8gJWQhQXvDLKXRX1IamUc4G5A2svzUvLImYVOdhnn32sCNZ3KQor35105euzyFoV8/Au5DBNbgC2FyysIwxXVdAPHEc3KoCgqWhPW2dSwj2JVgJ9UcXHbsGp7l/rn4UgMwmr4rn7bFRyHyaMawxG4IiS8ShWOHorC5I1XL0eSSxEX6zgbb12ONzx+JHjI76R96CDU5ImaFk7xM/AKYbOWUmF2cwPQ4DmpQoeqTs/6ncFydPH2PE6H4NRf4SiW1nwbhrk50YfKOoaOdB322036ZDomWH+5vFvgt2yUCCH7zvmpz+1/m6PVlmwX9ZXTW2wvmO+78gcIHptvo88pzCOCRr49YGDuvnf//63PNO6M4umWLqUPCW2FjPnLpQGY6TCGOOhQ4bIc6JXlX9wol3Yj59/yVXS6I+bsBcknXV+h7tOUr5GRBxZXL356Tctbl2hO1CK2fLLL2Zaj7W8e7/mwHjX+qJVwaiW6gpDj+VCEQlRh5GS8WL9Ys/gGPN9isUT0os999jdUcOUXrNYXDjR61TrAhPpwZG35e+b9IlIBww0CfoW41AhbwYNGij3PGMOLI/nMX4LqQ7lND3wwAOe9ciegN0uXw2T0Eg0lMAcSOCMoBTwQQxoN9oD6nglVWUxcfLJJwfW6bhJHy551T9bdWL0Gfk/fZByuYzldMhMb8NCsfYzG1GA/OGVtBwzHExex+s9kDyf4NvihfO91+gXfDLXlv7U8/OyeTNMvEcFNdAhkPa4+wwGCfNFUCCm7dl8ohzRNQ2rZR2XunfOfq68LJwSEdNBUcER1u30rB1c1GWL/gbrIkiP3/3udyXbX5E8NUxLwkYmWNkcHVowanrGQD1w/kMWtz62kinJYSL1D1MLkJ799ttPOk9nnXWWZE2CZhxjnzqmDeIvLBB6M7DRyDQpuemDlDy8UJ44OURx+R/PnwI5JVlXWNu9+ff8T5u4+DWjkBTlT3O39REn+kMXFBQ1RHrjvSCH6eJxztoZP0Fx7hj5XFwS/T+RSMRkc1sd/mDDCHJS2bL+iPQARynVGKxKRMW/fr61OLULkE6cH2UscM39TFihn8jarGhUHpLDhtkH9MB625GriOc/cI6u/VgsO6+H2HYjf2NQ9UbJZ1gikRAUtG7CFe/JW0zDUCWVFYbRy8HFmEiIRkeHg8BBOUU6NXn/2jIfSJ73iwfW2ePU0dpq0hsbEMRTok8WdY011dUOZ0mJcpq+CXbLfNkCJT172nUW7amsuOOOO6wayUR1YdICjD4M5XzwcaLtRLMhSMkHjytVqrZ0sqMirZEqEdJaA+x36E/l+r/7mHFi1zHBNSWNqahYvrpR3st+++xjPZ5yZZR2jXzieS8NftlfnA+QTuiBuW9a3JAe/W/0EU18hwwaaD0WyyatvenXE+2KZ74M/K6aKuO+KqtrZF0YCBiCkew71gHkJccdd5zlMHJu1tbW2HUjIisL17fsXzgLUR+y1xNGvfohM7tmrQGtj5n9hBj7c3eqFHNPjYsRdcWtexVkczsLOD2qTsodBFK6P5fLeohnOpIGzA29ww91gG60h25j7DKiVjz77LMyUOInwAET9f1F1RYHiLKhm4vn1thz6CdHR1+2FBnjBAxWUmW7pviGD7JW/TdBDjI77uyEX8Duxee9jcYzPtlWVUesNzT/y9v+DrKiIo+VVcoSFNXDigAL66lQDzMlzGNvTY/lE7uJckZCPRWEGHT6F6dVijf2tR3DqjJjnQLRez/nnznqVxW2GCJV3Vh3ZZjasmZvKXOcKisqxGyjDZN4p32E/D78hPW1BKMkh4mNBKkD9KMUinEI33LLLRJCdsUVV8jn/teyBaUIWSSotIk+EdFR0pGLWswnPM/YshFxQjGqp680FugDn6fFtW/bikLf4Eo4aDHAlBLcIN8/wUjB4KTI1i2DQ6UZZzgerJ17et8pfh59Xpy5caMYHrJrc6pDbZbyIvqEQUCwg/W1rpCqF8/eJbC2KOi+ceKJkrFOX5gbzMikGJOIeC5abB9CkyfkP4S1TxDXxG4TfcvT4vLY//m+QvlL6eZVeTNMwDDckW0/SJ7WS9Yho3t41Wy5SFpOIX08yGZwGPrB61pMVgL6MSnjUnfY8tVwIGVlCaPXSktp9aVfNxnNf7/NzHC+ukzf7JmWTf3xj38scr4GkddYccOddbnzU8O5lwyUPkX26yJlZmZRyTGRF0RdPOO4q9tvv0Marr8/+zdiUuc0sdc4JzOa2s+rOg06ZqLEmYXT7OfjTiOoX8i0WDTBQSIgh5HKT6HeS90pK5qdOkdvzKxqXnv3Mvq4IFUV5ZYD40e+sDyAHAMZMcwoQq+p6ynr7phPMgHyO3r3lgFfN0se2Qq7D1NOdHbkzy4p2T/sLVfgfjjvGxqMOYAZFacNo/HiSR1iYHVIfHRyZcF1z1rlGqmnc+877AV0uZ9YNVjZjPirVjcpryVrwJ4VxIuG8u61ruujr99/Wn4X4xea9474VfIMj2Hf57i/ip57/0r0PfJK0WP/s/LflHyT0XuSHxw/DHl3piqZSsvr4jnGDt3jNrj99nJdbY0QGScsLYiZ1bh++zNenOdU5tmUSRhiOqDxsgqrD5Ky3QjYlLKPokVmmLIm++CouqzobGuxWO12GxYRY3pGxPg6zSY0ex6xbkeH/J23sMZIqer3uquGKaMFGuT1LJ9l9YWbNXeeTBQAiSWT+21mtb+zxrUsVBQ0G5SMCD/8fv7555dcPPa/JmwmIin0mdAN1c5sRG44YBk8TnqXHjnQj1MMPvnJKjHwb+1iFhwBGiXwEBeiS6Wt+R5YrZ566imr0/gG+X4JCp4otltwekr5DESHFG1UmxSvZidYf58QecaKyirIGIodVrZ1hVSN6lMl5v/pAPlTLKUz61NFtfQGm2+mvNEwDkmCDI2NTVYUUY8kVpUFHzgnR6YUvBZ3lmjLsN3wVxcie25DLe4DSwjyW2b9xnuIloeMQ04Z7vxP9La902uc/+HRT+1rMe9fN2T8otP6YzCFURQuDYjvuRTqOeV+zYiIUbuH0KLAnTUMOsOIDhP5J2rvJh9RGX/WKoiK7mzQm004P+uK2J3igx+vEBGtLmTJ1wvFW2+9JWHuwLmuP2SsrxFMtJzs0AsvvCBqTDY4KVq2KkhwmDB+FZtqEAHLNyGfLXYaaBv3r/HUvE4+2M7E7bLj9lbmxA+S55ftRaKdTaKy3MzkxuLSYSJjiKMINE9Bxd0OCNB3vYYpHdAvLmhP64JRTSaz03REolEDGogNoKQqHhLTlvqv29fmGwawsq3IJLlpoFnPboi/EstwzWbFb1wN0Rk1FbRRxAtuR0Tfa7FwSEK5ca6iHz8onslOEremD7CeJ+AULrN1XSFK9o+zI2SdJucRjhBrmf+zrrYH6UxGXiewQ2BkxWZF2OP7jrMdb3lN0XyZDQ3ynBPimEc0R9kc32jIOLRWr2mUiQKuiyAkZRQ4H6XQ8ud8oMC+r3v+Kuv3MXUaPD1fLZHIipOjT/k+t7zVcJIVS2SpGfRonu91k6VEI2Ers7l8xSpZDsBY5SOP+z7Lt6clN4g0/ijaZLHiGN08PS4Wt8fFKy2jDDxqKCQLINUhhlLlPbBaDRwzQR5qFK8q2WlI1NfI5IBXNOX/i5Td64OgOGj+vPal28RJq+2Grm5Z2pEoybg8asgqRw0Th7hSXuGoUYgMfIm1BgTju8gIq27tKc3of6zDaI6qiyJ+GDrMaFyp1PSlB48XJ+w4XGw+KJgh74LYfQWvwx1s9IvE21FF54v3Gx31ZHWRTgoDihTVR6sxExeVu58iGnNlojPpNM7G//FZ8eGCNZ5DUp97HcZn3ZtmP6WTSfH888+LHiX22PkupL6yMFRDh9L1rK919HXLdhTOorHmIcOhhsWvJgNoJWuUaCi9SnT49LpKdMgWnscGV2VFbSInEsIwqlvnfyINWIKRFNm7jVi1v8vKK6UewRF46603redpUF1IqONhHDlvMIKDDO5vQyoTUc/8DBpgt1Y49Mc/siF5PqQPQT529eoZ1liprAVnq2oWGyTxaMSmFaeCMJsWf3mnM+9+CxKVselhwq9aWpplYMTNFLa20/8zV7fnHJlRP8IFsmVBwWprvPxIH7TgAUiWww47zHMejO5TLcpjEVFXEROH/Giy5ZypxsL6WeMmfSjEMHhZ6jgrw4WAPJB9obQssQoMEdgggKCIiorJ+sJI+ewsp+3jdsaQpg8fl//fk9lD/v/OaiOoMbvBuK6vc71EKBJzZJjaOjrlOmLsGTvqUEvJmBDIXrmyuP5H46rb/Ov98iSo8tHgt6RtuDu2YantISJ5HCYVaGDu+4g1smZvrOmzckXoHIhQ1tdA/gaH6VsU1f1bkTJcN71WXNl8qEhFK2W6mWgUCouNyP+qIJX0PcoEo0w3Mt2iihCJSqr+AP9rlN3rg+AsUz/EPDV++Lj4v5tvFde+7a+0CvXgQdyMWu7Injq4iNKSaWBNEMEmU1xq07p1FdY1PUqk4ZIJrsPR98mECVs4oAA/236YuOjAjde50bINlTM+55a0UTjtFqPZbfA8sNegEEaOerg4+A6igiTVB10glpYNFU+0jBQxl+HTqqfhtAPTjxzC8dmaFdne2izne5V5QCuaeV3+Ob04VrZvWn6160ixx9g+4uKDNvZ9ngP+hccftP4+/uc/c/R12zE8S/SNBcNMbzjSyL4SCaZvCg3EaV7qkFBUGj///Oc/u+wsbT3Mn3wivdZuGaDLqjNj4q3E6cbXm0bwVlttJSmj3cahMtrImuBUUWu1jF4qplGcdDUfbch5M5ycNcrwZEz9st3fpVRoWQSyuTYkr3jHDmhdp8kMyblJVh1DkYwcdVJBcORE3ADhys8QWVEpOsXBG3np/vNJuMwwunF8+2+5h1gRNtjmspmM1b/H8fqAj2xLmcQvOaPJ7KabbupBBfA49OW+12HqLeXguHWEZOYMhRzNqXWhzcEr5+wqXjt3N7kndthhB2mHqKCFi77D9d355wryEu4L5x14JAFiWFxz4agj08P5xvqEXe3zzz+XgY5ikBFkh93SaVL3K3ljUU6seek28fX/O148mNlFHNB5pTjkzY2MHllmA3npPkdVbY5ZD5wznA6un6BDISdcF0VSAzyzGHEwp4aMn20HRURPn0bpyslj3u9OGw6gWx74zKglJqNHxq6U/nVIvnNX7ZuaUJt4v+xUcdZYW99NGl4r752M1voayN/gMH2LwuFHZJPGY6r/xrRpH8lCQZwaivC233576RyhnIANQPuo8MUyspNnyogYqGZ4iv1pfeym/EMXsobQ+KrIGvPksostGVBWOJLmjg67I3sWLCMUlvBZ4J7g0P3Ywb5poTgWGl83SQKGhFsps5ZZ03PnzTMf9P9M+op1RbboZxAuKFmeq/N1OvxqmNwiG+TCZNRRfPQZ4cCN1BrwhDXtaV/nR5d5K43I9Jo2e13o71GNh3WHqbKiXJLHBPX9mJYdJc54+dtpM1BIaspi4o6fbx1YqybZzKorxEl9vhKvnDHJMvJUX7cRPcvFSUPtjNyEwfacXn/Y5p7P5eB2ExVhVAFPuvbaa2Xvqa7U+f3nhEm+j6ebguEvvUJNhkOQy8ozAFIlzgHH96eTYoAwYIi48ewT9jHZNZVqCbvOiBvSP/HVGYylag79fQuq6U7J009NcUSu/eSlmTatupJMslPCG5FUOmeQqqTTcs3kq00DJqZDAG/d9GMxyqcOMZ/U7/YL6/emLWiaKixoHOex2+gMIh47/0UjkMa1AgGjdYvb0CTYSl2qaFzivRethsktLBf0D9H+fAQo/WrLRG15TF43TXch+VIOWr5MRiGHSdWMSgbPVEpmkLi39g57Xqi7VWucOeP5IOfktCKIiLKuOtW1nSbEuYlgUkjMyA0XmZhBFJIy2Sf0NXdgxGj8HorE5dlEwAJoG/uv2FpHVadXLEue7kxvPzgqzt8xLt45oVLcepAXmrigUemArKcWDOl7XbNY0pyT1w6JG730SoERFhJ3lnFyP9th6jNmomySDcs2e/H7pnOKkQ0O07coKBwOdRwhUrh6p2+8fPqbXHfddZK1ByWi0qYoeQUlyEddjGJhI+KYoUQ5bDew5H3/BGOF7JIy1iVlbAlQLre4HR/3QRXJJC0YAXSeOE0cktQdfpuFlxx2jz1mdB9nfVdU1QQ6TKx9lW1V0digKCx9xYbUOpXvGp+oult6VhiQOCXtwhlYaDfP5VDD/LyGAfBXdYi/Oj8j7vokWZBi/KGMQfiRr8g6n7zw+QpfiNCVhxjZI/1jcCbIpgw2mcdqQy44UK5K5EqAGX0bohp9ukXVuPzmxOPE8P69Avu6fXLx3uI/J2zjaOALvboukGxAtgHNrS5AV4GpsU/IRhDgKFW62ucOVksizxiPBMtoUqk7TLFkoxCzX7MySewTzhHD+DDm8OvWiK8R89eU4TjNz/aVa5Z6EdYFWefv2zmhUxd/8sknWjG5/zo94d/ePlItTWtF81qjOfiyFSvF448/Ls9RyHagbQ+65xdmLHPQM+/fp3SWxLEjDbIJt6xetVKuYTeELuaz3Efd2CwWN9sZJvm5Y8d6AqD8TWC03KfvTj5IHp8oyWDa2iT0tBhabIxr9tjkyZPl3/n04rTcmLyflTOvHZtFOYGSaEWLHuIoq/NNBpeste6Vc1ytLvykc7Vzry9p8mZ5EmXl8nxSKtHP8dumZpVFDKOyf8WK0mH9+/Ur+Nrmp/4s7vw46Wh4fuXuwQFw+5pzIupi3EVWtxkEFcAIKQ/pfpbTcOBzOx11tgxEoXepnfq20S3fusO00047SYMeJb5BShdFmcrmYuGAHWbBqv85GCFqIP2MQUvjRKLx/K5oNfPhp4GmEEnGYeJ/Vdi6Qb5fwpxAbcs8qYMzKMPUFdEjYp25qAglzaZ2GQOCwfqjRsOvD9Q3KaxhvhP4Go4aMIwgpy9S3VOER2wnjdfFi5c4+ir5yVZDnfcyN1cYZuCufaCRoh8cJp5pFR9lg6OXOL56bcHPHusQF73iD7H8ODsyb/S1kN9SX2FAQ8b1r/Y4WXuO6yOLbFUhPdTiWw2tt3TDiccbUW/3vdCpqxSo07dV13LPiZPEX4/YvEt93YiI7zS6t8PxctNXQxLBfnA3ro3GjQwABzrPdWsk1MdwdTcahQIaB5zvBy6oZyPopbV4kdHMurGpRZ4ZIBYgcAmpjGjCX+ffmDlEHJX8g5icvFyeKXvuuaeEJH4T9PDdmWGCAl1nrbMezzodBOpsdKmuLJf1SEhji9HvCDgQ85mPoOqjRY1dggDqclStP2tdxtS97qi+8q/1wJmbAhsnl3o999oHoSKZEk2GtGLriFgu6F10F/D/YslN+H70SSEhw/H3j/IHDljnQGk5C1jH6FI91lQeNepYFQlLUNPcYqT1g0dErM0Z/Pjbu1493bJiodH+wgzo+Y3hT/otlXuP17F3qCUsJRMt+40VcS9tc94X89cWH8xSyAIc2aOjr3hfEI5YrWpAmqyr03L5jzYRNYlIUc2LV69ZI6ZOnepIAPygHSaiUe+8847EVoN/ZJOCjS+G2WiDGAYjG4zoJYsFpwnqcP7nbx5XEAk2H5FPlDwYXxWJzte7Bmp3Cvl5P9CnDfL9FJwF6PiJMimnoSsOU9BKsLq7y4aKaYt6GVpqdfCS4fy2o8oK0kFxMY4TsCMl0TonBn/gz/4q6vc7Q0TG7SlZkpB8pQP9ejjvxd03qSvOSaf6iOblolV44Q9EO4lEqoNTlyCYd6cwjDpV4O+WQrp0x9G9PcZ/2mSGi2vOAb+/du6u4qFTtrMchDdeNzITHop0oF25bx+eWUh2GNVLHLLFILHNcKP+oyuiFyjrRjg6UvW+g7HpHzPs9bPvfgdIgxa9jEHRnVj7zuVzC2aYrGuPRGSGiz5TSpLJTpExDY3W9g5ZP0FdCwaviva7s5Q7hQ2WRWBm72THi0ZRJdctwTiivd83ZwlRTZaRo448UmskaxuvVWudY7m2zWmAsQeGDTXqWOKJcrlHcQpgyiuUNcxHMlGMnBp9wrcoH7gfNWdu47osanzfnR/b9+DOUuMs+GUyWKeS6Kl1qff7irh+1jrQUxyWUjIkhTJM8vny/GcMDhtrkL2o+vSFzNohJWSg+E5VL+QOcOSTM/YYbf0eWf2VCGmoHqTVVMOyP+Gb/0/0WfyGKG9cIM/I/gMGBq6Ba+cYZxfXy/hts802JZ+nxRBTlvqZVs++gHlnvGfPni1tS8aRrOu6tp+JaPfhBwNU8ocL/yihi9QlYwMQMP5BO0xAxeBuR9kQ+QK3z42TIcEQAm5TymL+XxMUAmPGGHFgAcEDp87/qpkoz3NAUwDJgoL6dsyYMTL1ywF63GbB0U7qYoBx0MV8XSmjN8g3Kxhp0KQqtqTOQq3eCygqXSpCTgWo+rvyFQrWgJH1XRhKHDAc8PRioNBYiV7oiyh8d2LYBJHtPbpgsam70/vAIvpZ4V9Iw9kVqVaiSCmuHfu5ODDyrud5CSusqJA/GKwEP8ieYdhorWV85YCI0bPFTZHb1p7/8FJGv24UJ821E3MtCLJNasww/N99521H4bJuHBZbgPxdyP6b9PM04y1WdBjerOU2sQFrn6alBP/Qsbv94o/Wcz17GwEN5pNoLPDm7pKQD0uXLnEz2KECZ+iHl19+2X5BLit79yDpdEYayjAgEshU2SudohzpFzJgaboow5seRBTSf99Ez5bccOONFtTH6ezn15npznax9GsDZtbS1iHPUGp1Jk2aVHBOVQ1TJNT1YPCFO3uzWAsXLJBjj+Gvy+7DjTlrNbPaiH4koGvQMTDsuR14DHbsr+YPHhEdb9/teA7DObniK9/rU7TijAm2W7GBAQxsFcAt5DD9eGSeXnuqYWwuJ+bPny/vQzY196lnZS9wbvHd//nPfwpe65ZD6jyZ+CFDBonWtg7PNfC5/GSXzhR7D41KFNDhhx8uGltaHfpS15s3fz3Ceh8tXNwNf4sRFcDMJ6VmYSyHyafBsxLGjjUIyoU9sS595gbJRvIaq2Eel2L23Hkys83Zjw3Qnf3tvtc1TKRGyWRwqFDw9sQTT8giQNL7GAwYgmSeNohT2OxkkTCocJJoXkpqm//5m8d5HuWAw0OTOgqPYaZRRBH5iMHYXEQNcZq+jzCLDWILePHLLrvMgqJ1JcOkAuZDa52Lwt2otcJsKksigsOHQ0n1/vm2RRbt19VZjoWSFlEu5mRtGJ3CX0fDEZGacJjxmjxeSNZV1Nw75D1Qm3JOg/uJWRnpsDQ/d4Msxl/5xJ8dz+djpESU80nDVPYwuH5+uMdbp/ofBpPCdv8VxB0xzhehQ/wa16reQ9GAkCUHJEaG6vsBiYUuHHJ+tSFQt38f5Njthok7f761ePI3O5b8Xn1MPpjf4NDFEOmwBkFLfPzxR9ZzbR1Jcfvtt0t9O3HixC7r0adP30let7s+Ip/EQykroEIgkjojMhJKgN1dsauxn3cbkpN1CBi8GJzK0ATC5q5Rcwv3jDPGmcH5/V0xVh21jX9Wo17rGdbW3q5B8rIOAoV80jL7fUIB8veySqOVARl97rkQlTKd14LkkZkp8fuvtvJA5tyy3SAvHG3lihUWi60uNQlnxsOdUcew5axQjrQuBENoBNrW3CTSn78gDpliz3fnJ0+K5feeL07Ywp8FU2XGcZqLyTTwGtph3HnnnfLvQnyBA2LBZBKtM1616q5x/M855xwZ5HWPDeuU+WJPYOSDTigEk+1fa+wzvS3b2FEjPKiCSNTow6Y3soZYgz1X36OXI1sT07K/2UiFVWfLuupKD9IP5tvkNL/f39uHECnlc69rO9C633IRvL65V/YAtnuxjINuufXYrcTv9h0rdh3TW0S0QF0+h2nlqtUyAIVe6+r3/iBIH4jYXHnllbJQlZ899thDNsXbIE5hgeAIkQHCwFI1JPzP3yozBGQLhwfH58UXX5QHN8qCzaMrqCvedBo+YIFh0qGAc3303v9XBOOEYnNqAVWGaV0cptk+jVF1KTPhX9S/oSw59KBove222751Q4kDhggTByDOwu0LhoqHZ4XFq9nNxY+Tl1iviytDp7q4OqtErnAvCRXRVHL+K0Y/tOYFM8SyW08UHV/avWwQnfbcT1TBL7ruoIMOkr9DFECmuDUgMKiTUWw/OOLB5DdaOEB/UWeTnmFSbE5xE9bjFrLW1EYqljzVfFHJW9lNZN2MW36+vQ2Z/C4FWN1uY/uIHkX0aPJ7r5KYlm1SdNr8ELWf+qFNGjBj5hdi5syZ0gnBGemqLt14QI28bl0GDPRSHevyo8hbck0QJAOySkRWJybJpp3rnD3E9dGvSUX7Y3GnkbUg520SSe8pkAsYi/kK6b9pOXEnf6dczyZDD+1xmFpWiuYCuqtvzzrRw3S8+g0YKNnduE9qg2+++WZf3afYLgsFLv788Mfi8K+Pyvua2sFjRLzXEN/MmZvTRGWON+trP6H8BjVHZJjQm37rkfvCuUZemtUsnp5jwrCXzRXZzlZx+8FeRx0VwtoieMV6K8aA5bs5syQrYxEZpnxSMXqS1Jk4S4cccog8kwx6exdkOJORP6yJCRMmiCOOOCIwiHH6HqNFdVnUIoCgllHJ0s/e9qAUqJFVKAHsK8aaYD/7Xu0jteZ0JySVMMaK84OxWFea7IM296+5xbkuVj7LDLEcwiphI73ezY5zvI61xDpHBxTbBNgte4/vJ1tAGL0EtSbqefYN5xR1U9QRPvnkk+sMBfxBsOQRATjrrLPEoYce2t0fvd4LmxxHSHeWlCinSWWGUIwUJbMZ+ZtDFGU1f619eL65JCJmm0GKT5rqZJaKPgY4rd9lI8INkl9U/QRKWUX4FKyqFFG2oG4I+kltyDCU+Qq+l0OJyDSH1bdtKKEkgX9Mnz5dHoKPrxoqrp41UkJgmkSVSOYijgxTqrZwcTGyfRGNw7/K9fOQPGBwquitzlpZjBPLYcN7KLoGqsyBj5GdL3P35/QR1u9vHV9ZUtPAnpVxETHXi+4wTZluBKda8zhb0kFoXOubYXoqs63I+kDy8jUoXF9E3xs6Yx7GIQEp5pBoq17TAmyHIBWQ6O7O0s9fmJ+J7MzoI3JNskcokMZg0tdlttMJeec5HCujPtaE6rkgTe7VuHvNCpndBt2w2WabyVYX3xUawQ2l9ZOhw4ZbhtgN8X+KE5dcIUIvXi/SKX9HtqZtsei74kNRU1UpBvU1+x+JsCzMxyjGQGf+3boPI/KMM84QsVSrJ7iiC89kWteI1++/RbTlgjMAiXBW1O1xkvNBMzBhJv098qOxMXHVG52SjGBpi8kOGg7LgCkGOQEZt6FJgJUMEz11lEOjWjb4se8pueJ1Q/cQ8S+WIIpxUz3P1tVhWhEbYEG0qQF64IEH5JkYdelhWddkkrAoBE6QnL3XGPHxH/cWw3tVyr93GNVTHDtpkNgpsVB89umnnvcqWCL2F7Yr0DoC/jinAwcPdWSYxocNshWkc/k8Cx1CjTn6Yl3O0iB0gPrc26YVDtqw/S2HKWToifZcXCzJmZ1jNSGr97Of/axbsjxZ7bzLl2GKxePyvCOjzZm5Pgb1N9CKf8tSDMOTamyGs4RiAvJDpJHnfveqvTg7kmlxyKNh8ddPKsRfFm4iXnnlFVnMT32Kuwh9g3x/RDWM5KDA4GGuCtW8+ME/SrVnocrVKVCJSn/bhhJr++2335b/c+9AnvSmmVBU+GVBCkmPuhoR+9To2O4nGDZuFjwOo3z7RO8T5ZZ5a7Ly/RirGBxkJBRsVmaCAwzBVhcs0O1c5UNJEj31yzB9udyAvTzxibcPCwIEkj4tFeUJX0IMDjk/n1snllhfRXf6+tY41zrwLLKdwNN697ZrWkKRmIxiwyJHrUt3BhUoaF/cVDiYxR5F/+PMDejXR2yR+kQGETLzP3C8DiMPg+2jjz6yjHE37KhRGMYjUrNmlujbPEu89NJLkiSIPiys3+9KilljC7+YbmWYkAtHfC4ybY2istLol+OWLSJfi5pFb4ojxgkxKTpTPrZiVYM0xhnP3/72t76QdfQQrylf9I7j+5pS/oQuq9pyYqvXthUvZLYMvHb69fht8N2GBTOk/eHlTnHWc4YzY0Tws3It4MAH1SbjUFGTx5omuNrSaWZFAvpR9762WfbsQQcTLLjnnnuKzpConmfy+kTX5L3sWLFmdYPM7KADqdNTgYG1Hd794ehZWMDQ1vc843fy1j3F6g+elHPv1sudnSnpgHLvwMXQ4dTqn3nmmWKR2W7AqGPLibvjV9vXM/9Dee2sITKgJAjW5Sz1C06NWPW2vCY+t4hyJxGNJ0Q2ZIxh35ARHCsPJR0wVgXJ54cgX3cgTOImE2Uhh6mmrl6et8wfwaANjWs3SLeIamymnCWYTNTiqupnUwJHY3GxuFmIS19pF+9Mny2jkRx+sBmuj/jQ/6X5ZZ4233xzaazJwssC/oGfIirZYRIhK2JFZB2H7dsWlD+wCg5HSEow9hQMxtHMsAiWO10wJo7ZZqDoePUWserxazzPf5obLrYOO9shMO6qQS4/7nqifL2U9r67TR7A7EucPgwZnCcilESw+Ty/rOEK4aQTdh/gr80KJqvYbaM+VkRej+oVEub7xBNPFPvuvXcg6UN1dZUQGSeO8IcQc9Ejt26jhLWIrrzmmmvEyOE2NGyjceMkffOvf/3rLhVz55VwROx0p7MPlluUg6aK3U8a8pV4tPoaceGyc0Xb5696jHyMSIzeRNywjt0r49b0gdbv/XtWSwgWBjiwmO86yhvkL2HEHlA1X5R98qBY+uVHHv0HrKfRhIW5Zfobz8kM+jEVr1uP1ffsLfcle/xvf/ubr7GG4ctz/RpnOr7vnVXBevKL154UK3JGtsW3z9Bgg8J5x/Cn4qjIS9bsFGrTJWmtKyqsgA66ih5M1H74rUfG64033rAgvu0mecT1e5f5OjUY4KwvtcawNUoJDOA0/eXg4V3OMM3NDhCZ9ibJUsm1cxbts88+0u75dIXzM5XTyPVtueWWJe9HyYBnBsfcAapevXvLz+cayN5BxvGvf/1LOkxr1tprxF3jyfXwmaq5+rrqCPR6/1rnZ9x50S+lA8x17zeqMAU5c5EY4m3DoDPmcc38EIAHwdQdvZD+dOAI6/f8UFbOmWqpc74r+2Nd5QdwJP7wRNF2EgVjw7CZqZPg/4amFgdUgRQnUTFIBFAGOFhdKUDcIN8+NPO8886TqeliIHmKtWldHKZQJCodCzKQRKa/CxgOjrwiOVEFtnqX+aSZBdILbIsR7gU4zVHbjRQTI7M9zydz3gOHw5oDD8IaIrQcTE98mS4qwzS3ISuNLg5YWMqoj+C+zj33XJnl5UB1sRxLWZFzOkxuatWvVgUb09hOCpKXrx+bLugMKINpUhyN+jujEGZgRIen/FHEv576g8ow6Sx5bhZBREFEln4933ps5swvZMQdfdrdeyQSi4mvCvRVUfTKQObYqz8fZ2Qbfj5suQfCqaLmMkttQrV00oe3MxuLFmFnYlatWCEJm7gvslJEmb+PtQTQHr/54K1ixXtPSKfQrf+MfnLeDda3KiZ61dd4IOmJ8koZrWfP52PyJcPwp6uvEukGuwY77mIc+2CJvX8kHXZb4Sj9zbG/iqtjd4gdhxtzMXt1/pSB7iSo/nVcW1AglPFYsGCBJCvg9+O3sNfAgWO8uk/Vs/LZOCpkVUpZ6xjciz54QdSHDbh3qZISEdE+9wN5nzi/0OdDwuIHE8fA53Gghl3JSjBm1NnzvztAdfCPD5OOMvdOKxZq23Ai+C5Y3ZS4abpZQ9hmfB5Oaley0NQAKUGtQxKj2P0QnFgYPNmfw+oKm+rcWS7mnUPdqSW4wniqWriHHnponTM9lR0rRXL2W3kzTKw3gjSct6NGjZKB4vURBbVOV8yAUzNTSpfjDVIadI//wdqrRnHLV9pFgDCioFQVDhjsLVEDWGy+j4fgBrGFeWXe1OFdoNZffJYb1iX8vy6KQYcoD3j37yoLqer1oG0mMk5UUYmqHSjVYUJwvD755BOxz1CvIaUyV7pweKh6MgwA5uOiN7QmoT5z8sSXKdHjGvuAYf4wwvgsxpOMGcEN9qXehFLJPFdD3VLgUGRIlM2vF9oq8atl4zAE7sK4fPqJ0UzT3QEe2xIdPmJgH7HLuAFdXl/fR9HvQXeeEOYcSNqrr74qZjQb9MOrzQwgj/Ecr1lX6VttB7Ai0eIMK9aPyiq4H9dlwIAB0tmlDUVnh6FL8vnS1Iew31jzGC4KHvxtikFFbEjQEkNHceZxbXI/ufIkGF5+LHnptiZZ56JICZS0tnfKOaV2kuxTvhpf6YxpbQ7KXLC26942xgu4Jno8iC1Pr4OqMls9vLDzZ+LRI4IL7Ve32dAz9R0EdCjQxzkOmiv0EPemaKj1YMeA6pB4bX7a9yxA5wEn1mHRhYQ9oUoG3PVGyDtnblXwM9oWfi6GtM02xi+TkU4TaxI95A74qgyO6i9Zqm2j+v/hfOAs6BIvq5DQW/YQ+4LxVg18aWCtZEJojuN9qnaVeSHr1RXjv1OLyKHb6yvj4rrDnBkiPrfYz8apA3bvFj07pmqnuU/2F/e8rpDj/v37i8oKIxDg3qdK0EmsTZzL7bffXn73d0U08607TBgIQBZIGRO1UbSnv/nNb8Sf/vSn7r7G/3khAkK/KxamrpxnfDFLbgCcpdGjR4t//vOf8nAhOvJdQy02SGFBSTOnSCFI3lWpo8U/0pPFvp1/WgdIXtjq51Vske83KQoGpxulvUPG7ydHp5T0WTgGFD5DeOJXD6Zqo3QhaomhwGGNMqfWB8iUkqCs3xrtvMZJomieg1NFBVXWqG9VYfVK08ZSjH8VIb37XbsAWcktx/obKhgkGDczPp0u/4656sNUPRQO7DbbbP2DyjDpojeuZb0QTcaIRrbZaU/ReOrnInr6VCv7yXNBbGqlyD0n2f3Gql1kP0GCkQTEGpbUfLLJJpvIzIKEYplwo7JyO6OkSIGUTJiwmdUvkQg5tSjfduDkQbOZMtLPVVemExlcfvnlVkBB9adyGNE+SIqWpkaZIXA7uh9M/UjWTXDfjBc/fkIAmGxLZzIl0mbvp7KsveGfn5uWulpB2QwIXH6HqZdo9BA77DrMH5N38pQOSzcCWwLmi3HJdWNv+RmZquYZ8WsGCvxvVoPTQeQeZFays7Mk8h93fTW1o2654/bbrd+X5PybTicbFov21mZpt6A7WYc33XSTdFbcWSCuj7UKhL1U6KDb8WAM93nCzuK8/uZbUgdzDsMySCDx/fffl/ZTwxp73u6JX+mxgRk7HDjOjq5c07vzVnt07YjeVeKJ03YQ716whzyrga3zXUXdIw6TyO8wcZ3sLf7n/KcNxrraAUOGDBHRIRPMv/z3Ag46a1jNIayy37X98a05TBdccIGMWHKg6DeNpw6l9QbpXmFxozgxzMZvakcgkumMdJYwfom6cEhAVQ1F54Yapu+/KIIA/i8EyWsWFeK69BHii9wQOzpYoj1bXVsnHQQikfTR+K6KLlVk/91335WGgZ5hUnJw5J2SPpOD64477jDS/rG4LwTET1TjPvYRCj0aSxQFyUOYO6AFiuaWPXjXXXfJoAUHs5+sdNVXlZKdx5B47UujxqlV87ATJkfxmL52k0ZdONi5traWJl/SB+qhWAs0P6Vpo5L1EDHhEb1fVZlWOIJORUfiJKueeLW9B4raHr0syCjP+bGplSqj+lSJKw42qH0xxJnHv3xt1LYECeuS9aj3YEJ2GuJcx5A3qJpI5UBQ23rE8uPF7en9xB2Nkxyv/+C992SAAKMFI9XN1vptCD1yvrxiXzHriv1kc+UgYW9xluGU9Fw7w/GcEaDwbtCqCqMvjrtWZcXqBrnXMJoJDPg5FtRSnnzyyWL27Nkye5UURjaiPGp/z3kvGA4N+x04LtH6IM2tiu3/GLvL89w/9i8PJJPhGnEQWHu0CWG9YNiSJfEzMpl/RQ3OfblbFfxqYlyctGXcQ6et+geVsr71+mrWz1sDTxTLc3Xiz6nDrdfoWRw3BFlJR2dSogvQvZxF1FjCMooDpTtMyYxRd8u5hV79/+2dB5hU1fmHz2zfpTfpRbBgQ8WCBXuPsSvRqLFXkqjJ35rYEktMjF1jiRqj2AuKIhZU7GAXVJAgKtJBYGH7zsz/ec/Mmblzd2Z3dtkys/t7n2cYpu6dc8895+vfsGHDmubNqaqKVUKdV5pnnlvQ0/zn+37mu+/m2+qJjBmN1J3HyHqxPMazgiRFiFCUUGbIfWrKXurNWSrwXAejBnU3/boVWVnOFnMxxlwYnXf1UW4Kk+YQLQ/Hr3Gud8YQJYfz2BxKS2lpqakI1i+MFOdHDAycc66bdJoPZyJN2hKxUN1xxx1WG/dObrxNCC4tAX2ecOUhiFhLcAfMacKrN2zEJrHny2sDdvJjldl7772tm5XeGjSvzcbJ2NFgHlOli4WroSp53vAOF3LTWIVp7bqyWIM+Fxvf2jAvXRiU66uBILC+sHm5MBvCb+q8nsTD5BKB2SzZIDkP3nCmPYamTrTlsyhZXJush/wuNgN+F56BVB7e4NrEog4u9CYdCNtYW1k33NB5iLwFDlzlJxe+wnkPR3vAuKIPjy7sb06pvtAECjvH8iRdn5j24mHqXJiXVChxeYS33XabLe7gVRz4P8/xWnM1AK8oi4Q81dQG7bnYY0B6EQD+ebT9gESFCYGa9Z8m8i7kcPCQIbYnyzW1J5reA+MJ2RAK1to5R65rWyhLjsK8XFPgb0bkg/lLqCFC7oDixHGg6abL5/MLZuR9+fvLuCpjKBR4Moja8DNr1izz6aefRh6Ew7F8ypE9Ih8+eWKF+WJpPGTOXbuprpK8qMLUP5B+Lx2MNK5dAQozc4V8LgTnVGuKkw+IQkHpYx08aELcK7F5n8Q589jMmlh4FIoZRWvSNbB686uZP6sLB5gxVXeau4KHx97Da44Lasabj0KbmJOrL0r8nsIC+xvZA52X11Vv887LH2p7WrmSvSJdT0uyeUSqAt9DGGpOTq65cFquufOrrvY1xoyxoMog48D4k+PbUJoon3GhrU1ZI4o9teVdSwDvMVOUxRnUVlfWfzCTgzuat0LbJM11vrF2nHl2Ttgc/kSlVfCHDx9udtttN1vsBm/T+lJQUGC261Z/IRvYbrvt7A2DRLa2vmmSwoSFKtlAEwqWqpzu+sJiwYKA9a8jgoUEC/qUqdPMfV/mmkdmF5jKgl42HpvFlIuXEAYbT9oMcami5eEc0e8hnZA8r6WuqQpTRVWN3aT+8Y9/WIGwLVzirhoRkHNHGCk5eo0NqfKDoQDFi822OkkN1mQ5TIyFs+TyOaymQ4bFc8V6FNf9ezd/WJ3gAWBdcsqnC3Pge1JVAAqWrTHfhIYk5KA0JSTPYcvEO4UpKjAzxuQxUuwBj5ETjFwKjyv6MKXPb8yboW3t/zluhBW81e2pDxOlxP925Fbm9uO2rSOU8JvZx5IJizzHa811jbgKdiaQawqKO5vtcuoWJkmG31PiP/8I7TvvvLPNdeoSnXOdu3SNeT1Cvl5F/fv3s14FBMjmyM9q6T2P8Drmc++SRFEFwa+8vK6QVr52jTVmkK/ihSXBVQf157E4sLqjSNlE/q596hhZvPpdKuXl7eBWsf87w0RBI/IxyZtEMUARZg5yPMwBPI3e4jh+XO9Gcihhyv+S/80r3qw0v362IlYZjnXB5eyki8snQqgPRzoZJbzuHZv54f7myOXnWmH+xWA8NLUwN2AFd2RJIg0AL1o8zDHCp8siTXtdRVm8QY3NYXJeMZQzvEhuzeV7nZfZhTvymzgejEeBejxZjB/XHuNHwaCmyFv1ra+usp/DRZWk4tya802QLKYk8vca09kc/Uy1eX52tf2d/D6UxMmTJzdLrntRUZHZdESiYSYZzF/2JeZ3hyr6gEWCzvH+Rfzf//63Xbxbgquvvto2xMV61NHgIr755pttuCMX6XOVO5muv77fXuwIbljGuAhefPFFazls9lK4okVgY2EjZPFqKCSPRc/h1k7W2zEDG6hP66GyOpKnQ2Wcxx57rE0KgzBnKcG91157WeMHlk6qBdIIsiFSlbDld/CbUFRuuukmk5ukUlBNtCGuFwQRhEaUVsJd8ZqvWhUvcZ6Mj6MVspyFmeqUCHWcS34boVxUnWIjTUbt6sXmztrDYhXMsB6nS6RKXuKG6K2Wl++aIFdX2zmFFZ51AaEL5Q7vwp45n8UaMHoFQkK6CKkmYb49eZjg2B2HmEO2Tq6YOk9cMrweuvWlS7RnUCeE0zTG1XkvvY1HOdfe/lsfLIz0VCOigP2xa1RhGjpsmMkviITnLfwpsVHuLjvtZK8TQlfJRclUpYmxv/HGG23eUTJLNHM8WFNXKVizerX1EpGL5FeY3HpLyehk5ZRRmJBh8ETkdupuqqIheV6crONVXEPl8TXj/Jrxsf9vkrPQhuX586/qoyZavY7vRxDHA49wyZ6eLIzQwe+56qqrrDBan+X+vDEFCTlS5HKhZDUm59kZZAilW7KqrtLqDeuF6h8iYWXnecbm6JGREEiUPM6J86YhRHMebqr6lZlcOdo8unhDu87SYJkIo1R9qOqD6+jQQw+NKYk8tiGsRUVWeSJKB+WN4yY6gDFkTErXpvaacKyMIQrftGnTmhTRU9/66o7ZlRVPpw8T+EPy/q/mrMjxRsMROc9c848++qitStgckUh8xyeffNzg+/AqMa7smeyR2Zg20iSF6brrrjOXXXaZFXhYsEm2JrSIC4jQuUyBi5GT6b1lI1yUlL5FuGTx/Pvf/249S4w5HiU2VywvCF9YDv2lZ0VmwvkiByFZvkyqykt+D9OHp9fN/0kFViosZ2yuXAttURjEhULZnJFu3ezcTZbDlAzWGm/PJge/g2uETvGsP0OHx8u1OtYtTOzBNPl/wVjVKYRHFDgMD9vvsGPsPTOXJrr9ZiwMmnWeIWMj4zuw1DkBjGP8/vvvrWL60aLku5zzduUGQqZkl+PT+u32/TmBOl62xavjAn1u1IWEdRIvAsfBhssc43wX5obNfwr+EXt/MJrUXv2/D63SyDF7E+nbgYMpbcHPrzjwmOebq+JocVFEUK2uCZqaNPLWyNng775yQknC9es1GUyp3cl6Bzi39913n/lpQSTfqXuPnmbjTUcmNTKUFBfZ3BOv0pSJ+yK/HQHL72Hzt0nwE6ytscK3v+qbMywgDKeqtMbaQmijC/n3tyJw8i3XFsKn8wBUL/w69p5STwl3OC/vGTM8EC9R3hCuMqcrK45gjxc+nYgA5mx9XijoWhiIrV0oIsyfxrYhYc0kmoj58/LXdfvGMfb7lcSLaoQDkXUGD4ijd3HYjjcKCsdMmPYf/vAH+7077LCDqe423Mwo2sNsNmo763GaMmWKzZtvarN1hHO8KxiEWLPZd8hl4545hoLNmCBP4c3iN6TKL33yq4gCzOt81uXBNpaG7CZ4jSlAglLnzcWsj6DvmGNevVDQKsj8RsbdGfyaQwaorKy0+29jQufpGZaNlZybpDCRu0RYDRMGjw99SAhfIGmYGMVM4frrr7dCmbu50tzZBgmdhBigLFGFEAGIxQrLCF4nzgHWFy6sTN4ERSJsuii3bLwVwcRLcdeq2xpUmOrJl04ZksdixSbZFtWx/CXzAeEEA0C+L1E5GYFoVTs/fBfznzKvWEy/+PyLOu8pWzI/4fGKiohQwobHxkHDShSMZSvi+QY3RcPvYOm6kBnz70jIsYtzRzEhSZhrk/xBNh/Gl00BA8bPFck3OderguILJaMPNY2xSHYpio8Tx/6re+PFMZwy5Y4Dq+n7779v1wSe83w0QXGrramyggvheLvuOrZdheSlK/h5vS3essnNVXF0tbNW9xlhizKky14bxk9aYR7z1SSUKEcIdMJ1WTRPasxOO5vlK1YkhgJG4TpjL3RKU6aGb3ON4fF0VUT9jOgRMF13PKLO8xSRSKZkeS30LvHcD2sLwjvhcOCKPji4HNx6AawBCPPhUNyw4u9Dc17ec6Yw0IiQvOhxsoag2DEGyC0NKQm8jhfGX/DBjxsZ5jT7DgoIY9yYOcC5oYEuv79PIL4e98qrMvvlz7HP//6I3UxOOJSgMHn5ek1JrHQ+4+56ibmIGYR65ieef76P8cDA2NRr0XndUab53UQCoKBxb/ffigr7OsfCe1MV7YGTJlbE80LDYVskgvW/sTTkwed4kLMZl4CnzH191FZXpfA4hWPFf9hzkdd33333Jh23n4iBLj0llvHCuMj1l42VnJscREhSHFYtSjB+/fXX1hLX2HA5mim6btOpbiR9NhWq+bH5uRuuwGyECU64EFYYxt1bpYaysjxPvgJW+0zeBEXdTc7FT5f0iPfjeSa4m1liejVYAKKxfXJcyVEX8pEJoNg/9dRTJnfe2w2+Fw9KsgWeTYAGuMx9jDjbbpCkopHvqQWVne24u/h9NmOqEnm/v9LTRwlBxq1JLPScN5oh4l3n2nQV1caNGxeLzfYnDf+wOpSgqKSbx+Kt8rbXyHjuaE0wbBavqazTmNUJNPw2bgj9yYRIb0gemxjGl4qq+CaWKXOkpWCc/N4W9ghv2eTmMixM/TaSWwIbbbxxve+tT0+N5IxEeH3qm1bwYB7jISSRHj748ENTHQ1XO/7Xvzaji+LhZ3nRJqwoTXh6MzV82/UfTOV9nvPb5DmCFSkKA/Ttkh+bz6wRyRQLQlfJo8HYAZsEIk3F/efFeRYQtP2CdbKk+8bg1imOD+8HYfbphE2y3+MZQcGob+93axJjwVqHB6Oxc4D1loIEjMGhXSOepME5q8wheV+aEZ2q7Zp+0kknGbM4Et5bMryuEX3Z6oiihZEXjxKyCwZuxhOllbUYZZGy+oRIYiymsBWpIE0xBnPMeJcYV1cVE0XUVcTkeV7HA0koc6r8mre+rzWVHv2XuUDp76YcU337t2s4jsGLtXmzXg00u14WMQjm9kgM2/Qq8K48OwY+QuJciN76kmPLtafuLeaFecd1w7nsMCF5DHSyGGCslLyWLn/84x9t07T6blhJmwquZk6K95atIJC5jtTeKjXA87ye6ZugSMQtVv4KQJ8vCZvlz12XcrhceMm+w9O/1lxID9cnfSfYFDIB18V+QGk8rCUVfZd8GNuYvPkljCMWQn4bG9+529fNPdh/RF6djeSggw6yGzYWVry11lPUP+6FXl6e2MTWCVlYmBFmWPQJm3AhPBwT+SSUxsWC5w91GXN/xDI5JuebBn/ryH7JE7FPG7uh55hCSQU6xoXQXMbEW2LZv0HHCmEEIv2wsGi++c77piPh9bagJLnS9M1ddpsWEI4ffkwUxP3Up6Z6lfCyyiprkecco6hvElXEqIa5OBQ57oED+ptrT/1F7DNffBS/hlxj9EyFOZkqLArv5+p3J9R5vrAgz/4mv7JfmJ9vr3POK3nWrm+aFzzUt99+e+xxTiBRSPX2PeZvUGiGNac5zQqs7a63It4frt10cs04nqOPPtoqKs4ItHhtKOn84fuZM3gcMCrzu5vimWWdCVaVm2PNO2afgkgxBm4oPMiHoZJIQaNASd2qxt8sD9o1l0JejLkruEGaAco/Y4shjWuR80Zlw/VptOrPnXXXtWuizvO8zlqOUsHvS4bf8ObyWBsKhUxGffYo5+VijBjTwV3rn2UFG0Tmc9EmuyYeX3SNR6lh7MiLwyPGPb+1OQzrXbt2NaO3jRQPAqoi1gfzk1zBZOH17VJhShVXzAXYmBPAxETgqO8mT0n9IU1+Mn0TFHUtmv45XvHNW6Zibuo+RKGo1HTiqPqvta9CQxMehwOREEAEJmLCMyGGmLnKpknuTOk7Dye8dmjOewmPe6yclTS/xHlU+K5UBptRfROff3l2ue1HRSgf54AwYyyuhx19nPn1m/3Nrg+HTZWntwTJ2N5kagQv1kGvhY7ziDBCoQWOyVsK/sq3Q2bpushuWx5u+Poc2L04ZTlmR62vUIgTEjm/WGaff/55+39nLfWHcJaZyHGUjBxrowP4/c5L0ZFAaKJYjpfmLrt9wph4ZcT6qm95Fd9Ne9V9nzeHzhlOCFkijKwgP6LQ/5DTP0Gx6ObZK0qK2qadQFNwgnkqalbWFfR79ewZC7VNIBhp0IogzrWbDK5vBPR0QqgQ+pBPbENUnyz7z5qjTVNxIXkoTOQpY6RJJ8yedZDeNhR+wFDCGPzq6YiBxgtThnmNEsL7CH975plnGrUXOM8s6y1rHWFjrMnc8xi5zlYz7l63SMVuD1WZ22fUmOtn5Nvj4Jy4am183xlnnGGuueaaBBmGaxGFan2MwXzmuOOOs6XD/dc1j3me122hlfz8lKGN7AMOW00xL88a3uoryJGK+jz4jPEvfvELe+5tGxCvtl4P3sa1M0Kbxv7PPCW1g3nLeUIOaM7msZ08nuDHa/eu970oSsw78qnbtcJEXwpunEA0RPeYG1Xcxo8fbxeRloBKKpxo7tHq+T+3ZDkNQmQDbIAsHC7EMl3cmr3z4Po9TA/UHlTHys0GRTw4rv5MyXNjUyAMZvWMZxOev63gzlhpXsBzw0Lvzy+xyfGvvGI3alemvSHmrMqxn3/vvffsBonQyfdQPeiDH6vMjB8rbMiboyYUsMqYi1tHmPGvPWw+lErHW0ivCRcWBX99K95y4ZXQ9g0eX5GnRwd0ij7O92ycNSmqYTmPG78PL73ru+X9LCwMx8MPURgRcq494zCz3dAe5o/71W8lbE8g7OGR89LcZbc33CCitFAxrWev3mZtOHUIixPA3zu1pF4PU1FeJDwUQR+F1ylMpXndE4R8by7avnvtkTUGNZQGfz+lBKI5Ml5++P77pMI/BU8Q0CgcQCRMMrkBrzCeulQtAbwGB64n1hzWUr+rwGsogapw8jLmqTwYrEdUE2ON+eUvf5lWmD3zAKWZ9AjkI2vMCdUVsnFKIzTjWcdAgiJCODN5Xc0Fx08j2mR8sjTHXPtpV1MWzLORDlxnr732Wmwv4poj3K+5r0VXSRXlMFmBF57ndcaQvlAoGMmuE6+HiblJGCR7TlNC2xrKQeaY8dRxLv35p2n1a/SI9yh27F94l4B6A83ZvL6iIq6cJ6suGTumaI4vyloyL2+mk+ZpiIBSBJzAu+++O8Gay8WM+5DnW4IrrrjCPPTQQ7HHVDiBN99808agCpGNuDh4qiEZsyKtZqYNNdSD94JbxBovOlxFH1cdJ1OSLlGCUDIoffpxaBOzfU68ol2uCcXCCgjJYA1ggyOkwOWXEFJCIRQKPrDxf7Y4z2zbP1Hh+OcHVeaPO8dD5BBAEEoQnNgojzjiCDs+KBiuB0YwXJtg+WXcXB4TVkk2Sr8Q48LwrDJXw8YROQdei3fp/C+NGWnMmnDqxOLi/MTjn3zebvY+EBWAKS/t9zA5EPg4Ljum4bCpqqw0Obm5JtcXYuStWoW3jfmA0PjMObuYjoK3wAOCKdZsBDRn1W+usDznneC8FRYVmfdDW5gDcpOX4t2gU8AsKA2bXr7eQ/DwEXEFgtPPHsx5Rrhyf8MrNDFXvPJ8p+LGVURrSyh64KpvlVaFYxXeHOEkClNuz8FJczTf/iEYW2vwBqSK0OD6TaVQOr2T15kTKDQIijmB+JguvPdMk3POgYnfGWhMWXGr/VilBq85BmjSElyPt/rgdVc1EYG/wl96Nbp3MLe5IezjdSAcrTHJ/3w/1wZzjr5GzjtECXTueRwpLb5Rnc+yZjL+5CgRFs5axfxl7SEf77zzzrMeCGQ6vD7uWiRPGzjOpniZ/AVe3HXtvf6BcUOZpABQRAlIXN/dkDK/DjzwQPudGD1dpENzFn3gtyJTM88mzCw3h49MrYhUL/3OFPQdbqpWLzGmb+S5ysX/M6RCV83/xD5mnNnnOAcohTgcmnLcyQh7jHczQvU7TRg7jiNbDDdN9jBx4rgR64mlxj3mRllGLC4kQrcETGpn3fXepCyJbAXhlIIBhx9+eIJVlJ5M9ZXTDaVRYpQcnWTNWvlehILGbpItCcoiizgVrm6pjTdOBfqYOP7yl79YqxgWSTY2p5wgTFAMhQ0XgejTJRHh6OsV8XH6ZFHQ3PNJREGctrjEWty4kSMxdOhQG/vvQoSxuqLEej1MlOBmc0eR4m+7ClPeRR9BAksl38N7C1M4AEu/jJSSz0nRV8qvMG3ev6sZ2qtTnWp4/hwmB0ojGz6/YYt+hWblRV3MpbuiMKX8c2bHHXfMmPnQWjjBz5uzhFLeEmW3nZcHxXX0dtvXqabm5W/7pidIfLEsYIU75hq5cwt+jCTge3s1MVe8glmBt/tqhoMFGoGe6/TQx5IUc0jmYY2GO7LOra2KjMPvXq407y0IRpPTS+x5TeaFQo5BQG9IYcLo5PJ+/CHAtasWpewX1xhY2/BWu/D7hoRL10qAe3JTbKnrJHa3z5YErZEI4Zn18k9/+pMNg2uM8OoawfIZdwPv41TFOlifOa/O44EigwDtIge8eS3e0D8EfG54B5ti6Eu3wMtGG21kc+ud5zaVh4n5RY8wilE0pTdUOgoT+xBN5tlrnpsTNm/OT11tsTwawl+1PB6mOrCk1iy++UizbvI/7NxnnyOiAkXU5Ww1V15/ftS7DctMD7O8LHXjKAyPKNSZEuHSGJq0euLVaUwIkRAiNWwebEK3f5ZvZq3MMRO+qr+KXaieHk0OBDJ/EzsWTTYphAZKimaKhYfNyRlAysOJFnA8TA4WWMJqrDIT7aGEhfC///2vtfKh/PAbi6PdPsurwwllhc97udIc8VS1OW1KwH4X70cgw9KK8uo2VCyLCBReB04oEFGY7P9DIWv5JmfAu+hzDvk+YtrZlA7cKL6JeM9n5ZLv6vw2P0WejqX5PiHXVcPzNq31wiaIVZqN9spdw6ZHccD8da+iOj2cvDS1l0g24wQ/f4GHlii77YSj3Nw8s2Llz/WK1H1K0stXQPBw3gTOXV40v82rMOX4FKbCLFKYsK4T+o8iP+2HoLn5Q19/wSSGo+LiSJn1fp0DpkvUI/XCnBq7xm666abWI8Lal0xQJK8HgwljufKBs8wPlYmhef/+NHJ9sG4w9oRk8T2dok2JHYFw/RECDcHxI8SfeeaZ1suWDqzlVLyjai5z1hZ18FT5dFz7TlVCDi05XY3dB3g/IVWuESzXyWmnnWbveczzCOPJYMyoKse5xThBpIDz6LN2YgDnxvf4jRUogutTtTLdAi/8nVS5sN4cJhROHAf77bdfk/bShoqQEl55wQUXxKoyHvRE8nn1wGfVsWuB1gOOfp0i58rVFmCvZK1wOWbkhDWHDFBaWmq+/iZeyKh87nSzyR2JIa93zEisvpqtlZybvHpiYaGhGqXBqWfvvQkhGob4ZEIQSJTFwv/1gGPMuV9sZbr26ldvM8FUwtbEYGIold+KbROUc3KssE+D10ypUkNoHMfCpuD3inm9MAj1riQwoVOughShHaxHrox2t06RTaCsJlFhIqZ/0pwa89PSn61SxMbr8nz4bpf8z3ewqXibB/cqivSAct4lNnc+7130XQVLmkyyAfthE7aV/KKfqU9hwtuW+rVoeeQUHiaUvxtuuMGGvlR6zMy+tKgYwdJlZuLEiRkzH1qLZBVHHc1dcRTFBWpqg6Z07bp6y09vNyC96pfMf9dbhlyXQdHE81qPZZzKiF49Oa+BghOZBIIYhUtcfs2Vb/oVpuQhZ5yv/xxWnHDtc93a8sybbZbynCIoI89wTa9bvtCc9mS8VxM92FyPaLcOMUcozzywV9eUXvHGwjGw/nC8rHOuOW66nnpSF7jnc1VJ5OsKm3IVqcKHt6YpuUucFzwEzLtknlnm5MUXX5z0s4wtY4eiguJKZAC/l7XUrZ2uPYpTalCe8IjQwgEFqyULvPDbiGBAcU429hROcucGox2GOooPNcVbss3gutUD/XPf5aOh7KcqdT51PgpVZM55i0N0KQjb/caGZ1ZUWIMAlRTT9VqmS0FBgdm2R9z7RcEqTz91y2VTI0+434BSnCkG28bQpNWTfAFOIHGl//znP63HiVCZBx54wMZFCiHShw2EHhDOMsjixiL04tzIIrg0mLghp8pd+V9oYIKi4X8XGyWLPBanzz77LGNKi7M5YbG0+VV1FKZE4QPvEsdN2ATlaNlUCUvCo0PjRiymOVELb7lPYQJX9MI1DWa8CcVBcMACR8Um+n4gABQUxYWugZ0ijf8YQ5pz40Vyln0vbAIIDIS6eOF8sskiCLhiEPUJVj1K4pt1n86JyrMTegkZ3HezSF+mvx25VZ3QQOvV8jQ8fOOk5DlTtYtmWyUaxbWj0VoVR11Jd7w/P69aXW9IXirFNhmcY84dSv978yPJ7JWe3BWmite76ZTtbABBmeIpLjy5jkM1iYkehZT1c3T/nIRrP9LYt8yGLiZrWutgLF3LlKnzg2azuyrM0H8FzKxVidcgYWVOqP++YNMEj29jPEyfLg4meIJYmzhfKBGEaxOWlS6sX5TiJj/I5i8maXYa9vTCIQw6WRGE9fXMumpsycCrRWgYf//dd9+166erNuiuxWRKDT251ldZSqfAi6t0yvi5dhFeWHP57ewfeMvYE5hbTfGWHLr1ALtuTzk/kp/qhe/DaEflPrx3rspdslLxYQx70Wuky5DNEl5zzYE5H6TLJPtN60tRUZG56KwTzB+3CpqKqXeadTNfT1rdk72WcWPeUA+hseXss1Zhonb///3f/5mZM2faweKiIx4UNywlgoUQDYMn4K9//atdeOnjQB4gFlCsf2ycf3k3aF6an2dOXnN2WkUfvMne4Yq6m2BM8AiF7N/MlMakKCtUyWNBrfUtSZvnRPIygONlwed3EK5ATDvPseagjLCpsNEU5IaThuS5ohf8dvd/2+NicKT3Et4qqiQhpGH5zC/0WKnD8b/PcbKpJ+tjwSZw9tlnWwHWC1Zf/iZWXSdY1edh8oZR+Z1NzoOwYl1VLPzKeTCA34ThCqGkU7d46PQGnZIv9+GcHCuMRAqPiJYgZhxmDvXomVD+18/8Vel7KFwoayrjR66vSp4L58wGmMf8NrdWNaQwXZL3mLmj1xP2/308cx1HLEYphHMEYbxIqYQ1jC+uMh/ryQ/r8kyliShLLi+HY+E9u+66qxW0r3j8Y3Pxe8VmzGOdIkVZGuFh4jd5w6jwKLieOa+++mranguXj+fyODEsVSVJeWELYN3DY0PRApTLxubpNeSZJZQQb1AyENzxgqFwck6Yt/58spaqWukv8OLCCF1Ok/t+Z1SzFRB9YItgHrFPo/zRiw+vWNNC8gLm2B2HmJH9utY7xsxJvHHMub0fqTF/ezfR0xrmOojuCWtNolEMIwFzgSJpnJeW6kW6cOFCc/d1l5pVX7we88AlHGM0f43fgHzjbtlGk1ZPhAHiZYGB4aLjx5OUTSiIEKJh2KScRwNrH15bhHWbh1NcbOatKzbnvdfDzK2NeBG8RSGS8ZOnTHTtiu9N6ccvxB7fMr0mVj2KxZi/hcUqE2DtcFZJf0je3jmfJTxGsUS4JwYehYBNbcKECTYsAssqC3dBdFWr8pTV9eb7ML5slFi72OCxcGL0YeNkQ+F78cDtuNMuCcm+vMY5c8LWoYceWmejRCAjTAPF6G8fxxUuGjIiqHAOXJgcjTEDKYQrr8IU8AnXq8sjG/lvHpgRy7PyNqXlOHfYYYfIphVKnSgc+1u5+TZPJFWTULH+xM5nIMesKyszN9cebdaGisyN08Pm/OpzzZJwXLFtbMkAFHgKx7jcPS94lLwFREoa475qQ1wZaATqVNb7nPxEr8/ZeZPMESWfm637Jo6DG0+uP6fspBLWMGIhXPIerh8UF0Jx+T+vYUjheDAQY5TAwMLl/PyC7mbU2APt9zYmJM+fhsXfYR1kDWI9S1Z4oD6vD94bwrut0J+krDj5jKx7HD8NfJuap9eQZxZj0t+PGlXnNfa6d955x0YDUGABKBbmwoHTVWpaqsAL0QZETOFpTJbTWVUTWcOZlxTlwFPSUoYm/j6KIvMPpYl5+e2KGnPp1Crz2My4MrefbWAfmSffhBN7L3KumUuMNd7Vliq0UBltWMy88DZLh9WV4YTfxG+5/vrrW8TblZEKExeYm0zERXoTE5uznr8Q7Rm3yXEN4WmycedVkQaLWLBYIOk91DWakwPLnrvWVKSQayeF4gI+YWmVP3wRe3zxa5Wx0AFCyoi9bylrU2Nhkd18882tsOFXmM7Imxz7vy0KUV5uFR5C77DGkkBMKBkKCsIL688uAyMLdKWn8axTLBCYXM8IEqTJ82H9YuzZOLHqMT4ocO+862mcm5Nrx48NiL/H9yQbP5QOJ4A8NLeLmWAONwtPeC+hapQ3KT+VNRqnQEHUG7D7Jn0abGLs9SI4S7rNuapsOC+J42GudbQqea2JV6HtO3hD82O4r9m6+t/mmg9yzMTQWLNT1Z2x19/6vnGKKwIKFRvP37du7yzXh+nOX482fz1sCzOoR+pS9pmEq1LmqgCiSPirvhUM8JYvjl9TE45M7N20JmqQ55plPSV/M5mwhjBJIReXlM64IqA7BYbjwIPD86w9CNUI3dtvv71N/MdYw/saUyVvh4GJ6x3fi/DJd6JUpMpbSeWRoI+UM+Ksq6gr8BORyd/49NNPzYknnmh22223ZsvT81PiKxO6gUlciyhDTsghxi/+fktWrUy3wAt7Mfk1nONkyiqhtIwf30cfKXpGtVQDeHfMzDv+xhtvvBFTRLwzbFi3JI2ao+BdQvmfNm1arPhDSzBixAjrROFY2V+9rVHYM7mGuIb5HfSAnD17tslGmqQwUWmG+FOgGzH5BCxCp556qn1NCJH+Jke89uuvv24XFlceloWHTRPhvYsn97TifzNMhSc3x4u3Kp6/IJp7DY8M1rF99903Y5Iu2QApfIEw4s9hghIT35A4fqyjLLjeDY1xs96bysqY8rCRRyZyid8INN5kXtcHixh5wh/YoA877DBbja+8Iv53C/LzrVLHueHGou83DvG32ZjYPBD0Bg4eahYUbWYr/+F1ciGQ3nCsVArTktIqM+2iPc1dx482v9ohEjKYjFQhefRVYtMKBpJ7FKrD8efzCottz5dMmQ/tEe/5CW26T+Q+Knw5pgUjFvnvGll7A+X4uuuuMzXVvqIIHkX64FH9zYk7DzPZAsYIyl3jmSV8zAqwPk9rzc/xMMR8T4PrLTbwKSGhiGcd4ZNebXiTkwm5bu11nhpX8Q0jCNczIdP8HwEUBRWjDcI1pZ9ZrzFQ2BykBto+zPs58Zr3Vv/j76Mssh80VsDl+iXvhXA3m8OU5D1vRpVxjtP27krRoLU58FflzJv/vvXKoYRyzw2FjVwtvHctWbUy3QIvKNLsBTSCTlZ4KZAbaSvB/sD6zzlqqeqi7pgJx3vhhRfs8bBfoXh4w1N/KvW3So5D5AoKDPPW9btqKTaIemCRY/zh/s5AwfOMH+XNW0rRzDiF6aabbor1W7r66quta/KJJ56wlgKqmggh0oMF1zXnY1FhAyE22uWhsBFvtskIzwUbNpVpGKD9ClOPnj3tYoWAhsKRKQUfAO8Qx8RCWuMR5B2/yX019n+UJBQslCvWIAQWQgFcwQKvRfar5cEEhckt1m4TIQeTfkWsWyhNzmPEpmTLinuq0BE+R8w/SbicM8JlvN3NwTUDxnJKiNTYsWPteWRN5Hk2Zjb8Xr3jIZZ9AslDTO6eNs/071ZsfrFV/wTvkZ9gVDjzejCc4IfHaODOyXNKaz1NjQeHllhBS7Qc3lNY1C0eCovwE1y10P5/tYmGiaXRZ80L5/vHH38069aWNrrXSybD9YLSRMgs3mC/AJtQzMLUvyhiTGGsYz2KkgiOCKi/+tWvbNgYawpWcf4mXmi8R/w9V6GTCAC8ShSbQbnhOkeh4nMFDTSqnefLUfOGLLn8GdYYQqj4u42F35GqLHZlbXzM8O6gCLYUuT7vWCBJVUOvZ6Slq1amW+CFe1dZzk9J564RQ1QwaI1SrPUtGanBPH377bftHHShpLZxelH8PN70QZUJh5IXGkHxZ89hTrHftZSSUh1tDUIdA39TWpe76wo+4AVlb8rGNhZNUpjo8YG7GDgZd999t508WG44QUKIhvGHILBZsyGzwKAQxHJKPPKTzRlM0l/Dj1/GJsSMzZ+NgO/HI5wpVWpc/xP48d+/rfP6JfmPm8NWPhh77Cpe8VuOOuooGxqBwuOvzPTBgmCd3lXO0obSBHyPP5yBxwhNgzbaIvZckamylfzYtAjrIYTNv6m75ogoHy7p1VlT2WDxUPEdW2wZr2j3YP7fk45JMh2Jzc4fjuJC8qoqK2KbIePC8SMQzfg0HpaZ8Bs9/x/VLaK0Z2MjwWzBq/T2L/8+9n9rLV4e6cvlKuc1ti4D85Wy4n16181JzKaqeMlwvX4QthCyXvw2rhiFaiqSephSgayCsvO73/2uXiEXIwqeZgwyRNBwDfNZbqxTGGcoz8x3vfTSS3b9Rvhz18+r1XVzd7ys9RSjgdunV5s5K4LmL9OqYvlSrE+u5HZjcGW7U+UjepueU2inKQpZuvjn3rDhI6yCwbrJPTciC2it4SoTtlbVyoY8JWeddVaC99ex/OfV9vw4ZX3KlCktum66RsQ4JehJxrH5e7VhQA2nyHUjl5U9Dm9YS3p0ukb3PsaGaApvfjTH5sLy2DsxKnDtZEpKQKsoTGiMfkjc4zUhRMP4QxC88doUNkA4R/id//382GewFNFLIxmVC76K/b8wN7FUAJs+YQaEa2ClIm9nfasONRdsCBdddFHE6lS+Nul7bh34mr1nPLC+kj9AUvi9995rBUY2X6zQ3uo83rLiVLzjs2yCKEwIQ2wmCECMhdtMWMNQJhE4CksSE8MJPcYohOWRpFW3eXlx4SNs7AgDFI9wAh8JxShP/QYMir1/45yFafVh4jsobEH7hmQeprfefMO+zvtspcCCAvv3KsvLkn5/LIhj+Tzz4QcfxOLyRcvg9fRUV0UE/T7hVTZhPC/qDXBhs43VcZjzzK9QEgHP63nMRrjWCL91+YvnTI6Hr1V8Pc2U/2+G/f/4vIkNfhfKiGsNkAqEOKzkeI/oKUljUmDtQLbhGFhHEf7oReSMXRhCnAfsnRpvblUiny8Jmht8Vc5Ka3LNZneVmyvfqrLXIcdIlAEFtJKtMfWBYIz3u6FCBBwr3qXGKmSNwW+Imr84MYSZVhqZWGiGfREHAIY8P2UV1faYMdB5G++2FM7rRsg0+wnGOJSRX0+MCwEFFHVJ4r1zY+wq0lEMpKWVlNxor0FXadKBQYE5zfETFZKtEQ1NUpiwwCTTvrnQW9JiIUR7IlkIAvdUL2Ijo7IN1iuuK4f1EKX4vqWPXZoymdj1ACKpmbwocg1x82cKVO3DI0Kfi/rAu+QEEwQgwlaca5/7gKcq3DqPJbeyujYmKDEWbBz0kCPMDgHJbSR8JxZklA3CnLy4AhMs9t4iDslAceHGOcYbxZgT6kfs+2NPPFXn/WsevzDhMQUfvB4lfhuWQgQ0L66nU9m6tfZ1Z+lmc42ELi6uV2Gqin4vQkI2hkhko4dpdUFECN5w6FDrGaqtjQg/wXBOXABqAG/VR84fikV+fvK+O9kKcxKlhGvThbut83RjPXlUwCx/5i8m9MUL5qy8lxr8PpQdmpLW16CZ65X1mDUBhYlxRfgj55N1mHV5xowZ9ju8xi7WEfpSWsLGXFJzep3vfv27WrPtPWVmeXniWXF5ObapdV6eXd9cYZnGgmDMMXKPMO+dJ15YwwgnRIhtKT76PnGtCi//zipz9LDjnvPJ2FJdubGKYUtHfXBsjKHX6AYbdIrsQRguCeWmcEZLe734foyJ7B/MCxS2YEE8uqFLZ7yfyYu58DswJOIJpZlwSx1raXTc0Au4FlwEhyUQ8RRzzpmTRNJka75s3RW2Hkg8c1AK0huSwkDR0JZJJIRIDxYO7+KB0MrGibJE+X48J2E2vahpA8sWGSh+fq4I17EyLfI0uUPRQgDnuqWYBNazTFq0UFCIsXYNZuuzWiK4YGXjHgWH8WIhxlPUpaQwoVmeo7yKqluBWENAhBJyD7AMY2l1Y4FwhnJDuIq/DwcbJRsBymYqSx0bB4ITCgvfyfnj3n0Xr0cEoUTvVfnSH4w3wA8HEx4jhGGsiwgWCGZsSsajAy1autwYU2y6dO5sTj55nD0uzjPHSl5YxcBy7Ml1jvOTUKSiGh3iOTaEA3mYWsfDtDTQI3oNh6wHMlwYCf0MRpVYf7J8MtZ48l4QuDG8zKlpPx5CJ4ARNkwOBwoKMkbIY+K9/9BiM3lurckLpNcoFkETmaWhdY8QX3rWcAxcT3ixp0+fbhURZByia+jl9Pe//90K+m4toPIoa+sS8kzDqc+Ff41zrR64xhGKuQ7xEE2cOLHRvXNY54ki+Oijj+x1nSodDsHbhRK21D7g7/nVvWtns8mwDczLL79sC2YgQHPPY35vJoRoOe88nhnGaNN7wubIjarMrQdGxmiDTvFrk9AzjGqt0b+OvY7jcb2Maqrj4XVdO3dKmqu4rDLSnPiWW25pVAPk9YmWWbVqlY2iYP905Obkmk6dCqzxAR0C5e+yyy7LiPPdoh4mEpm5cYGfdNJJscfc2NSx3mC1FUI0DRYRkiap5uQKPwyuioTkhRd9FXN5+5n2Q10laubKPHPh1KA5fWona7lEgH700UftZsrilSkeBQSThx56yFqAG1KYNu+TYwLBaqsoIQAhIHCPcoly0anIE5JXG1/eaoNh+16EHkJqEHTw9vz5z382//3vf2MheSz8WF3JjfIbf1joUWRRWlP1R2FcOWdA6MH48eOtFRpLH78vVTJ2n94ei5wx5vRdBtvfQ+ghMf6EACI0Mje8rApFQh/22muPmAELAYhwQzbLZCWO75o3wPyxJtoMORzxqhEjn0kKdHvDqwM5L+qypUttSGheNDneheSFgrUJBo/xkxOTz5eVhcxBE1CEIzCvmMvZXOAhlQDGnPYWJvA7TLoWMsPT+922+W0olOCxT7YWPf/887G2AayXGEgwVrAecJ3wHldUxSv0ueuOa2pWuK7huCzq8fbUkrFwPHwPRgtvBU8nvDcGV3wC5ZK1yDtcQ26Jh+fy+osvvtiiEUFjN0psU3DBeb9PKKxAKw0Md02tfNcScFys/RjN+P+iVeVm9orE4kHOcIdiijLf0rmfznjAPscxMV+GDNsw9npxUZHJ9zWKhVU1edarRMh7S1ekKyoqssZH9iyUTe/+yPKGV4kQRn4DhkBvK6J2qzAxCNzQVknSc4/dIsSFSoiBEKLpYSiEmWF5Q+ClGtPSr6cb89zFZsWzf7Gbam5ufHH8fo0xf3m72pz+Qt0FkcVpwryuZm7OxlbQR2HASoUQzqaQKRYeFAGaGWI5C0aLMyTjyM3yzFfndjavn1hsracUmEH5wbuEcICQs+lGkY0EmbTGV6IcIYHPINSwuGPhZDzeeuutWIlwFn4Suhkbb3z9muocu7ZxPiiJSmijfxNiYyOEiLGmFPI555wTy0tjzeScuvAKP/4KYIdvN8waoRCg6C/1wAMP2Ea53CejxKPscOyUxkUpzE+ioF06c6hZGfVnIWMz7lKWWhZveFVVVOqqramxAuO+IyLexmDFOntfEE1iyovuzp8uTpSwt7irzHy0KBT7XuYIpZlXr04MgWpCwb2MC1f+/e9/bz22KCusX36FCUU03b5HfCfeIYwzqYRc54Hm2uNaJpzJm5vIcXBcNCz193LCuo635Oep95j/heuGuv1+SmS98BuFWMswqLBWUOjBebmoZNpYoxbXPuGD3PxGnUWR6WXhmue9GHNaih2GJX73h++/lxii+PrrNvm/pfpANRWOBYUIQxL3OwyIr6E10SHlumPvYE62tLLnjAfgytr36RMPYdx1n4NMMBrWCydVX2w+L+tt/vr1MHPNNdfYqtYuv7WlKI3ufS7ag5sDeYVrCscKzyPXEOmSjUWGcpoaPqMmh0K0XNU818yWjRordNnPS01NdbWtntenS1xhmrsyaK58szISkucL2cGr5Ep2k7CMssBihWUsU5Qlt0FxbCganetJQj5zdGRj2nVInhUkvJuV+/+Y7ba1j2lyWZIfSBCs2PzIv2Sjw7rqlFKUG+96xkZJk0BCLhxUMPv666+tJwullm7w/j5MbmNjczj77LMT8tIoj4zHaeutt7ZWOD+dfTlR8+bOMU8++aRVBFGYEKqwBiNkJMNbKIB5xGcRvrp3r3ue186O9NCDrl26WKFUxXpaD5dXEsgrsGXqB5UETe5LV5nihZECBn/ePaI8b9Apsj1X+apiOg8VwgkKPII2c6ykuK7QGc7iLCZXMY21gVwRfmeOx1gEA7sErNJfHwi3GCQInWKNIZw3lZDrFDU8w1S1TFbamuvFH4bFNUcvLNaX8tnvmgW3/brOd/+4JnIu/HlFGHJYzxCEKfTAMbJGcK3Xl2+V6vjpXcWaz9rmVZjZR1zIHwZuwoUjId4tgz8Ha23pGqugnXbaabFGtFTnrM/j1xYwPuwnTllN+B2B3FhUA/vIrrvu2io5TBjxmB/MC9d8vuzgfxnzy1vM2ENOMHl5caVuWmhr8/6uD5o1eX3sfkXLH0JbWzKipCC69yG38PfoyRp7LT+SP828fuyxx6wxj/02U7yKLaYwffDBB1bQ8EI4CwIY1kzibTNt8guRjVXzCL1ywjFeJYRfF1Kya7/4wreqInloGAso4Wd8Bkul6x6PZ4lY+0xSmDgWLLmuyMKvn4mHG3k5YKNEYQkrLLHSKIaxxOloeWEUpqUevWT2ykhIHuFLJMCi7LC433rrrVaZ8W56LsTJC2E//C3+Ju9F+fEbjerrI+JKuvN3/WNf9vqd9nu9/G78Oeapp56ylQA5d5xLrNtsfGXP/6XO2Lzw/MRY1UPmCInpzB//Ak84V7gqPjAck5rWtg0LqkusYkuz41UL55k9B8ev5TGD4nPdU+cg5qFgPmGtxQiAlR6PR05+XcGtZ6fsE0r8IOhxbaPo1Pri2Z4/tqReIebVebV2jJjnNJsln4Prsz4htymlramqhoXdEapIbT33e5hYvxCGUWBYUygSQxEc5KqmCOOME98XaV4bF/b5buaKW4vIy3LlvFuD7t261qkGi9KEkTCTvA2MOfsvay7z7ttIi79Y+Bvjx/Mony1ZZdAL5wuPJucP4xZ7wr/fX26+Kt7RXHnllaaiPHHP7NmrV6zQEMa2Tz75pEXHuMiz9zF3Kd3voF6v66HFHD/33HMzzqvYIgoT1UyIT3SQpI21APcvSZCTJk2ysfZCiKYvOiyKhOW5krUsMLizCT/zNmYFr/zgjX+nVPFhhx1mF3Ysjdz4frfoZtJi5ayr/FYsaI/NarjU7OTjCs3QTpEqcigIWINZqOd8PSsmZJaGisyhzwTML1/oZEPinICJ1RbDDuPA5u0dCxQS1jIUHhRMR05eZIN0YS70Z0k2hqmELbzyKEAIKHiwvJT9NLuONXZdaaldX1Hc+I14mlDYeFy+vG7/rFemTDa33XabfS9KGes03kisul78nkiO5b777ssogaUjwXyndLUNKfU8f+TIuMXY72FyAjceJj7/6aefWov3T6sShaY/7reJ2aBL5lznTYU1DGu+LQrjU5g6FQRMl7zUjWLf/TGyljA+fA9KQ0usfeQ9sn65wg1+xj5QllRhCobC1svDesM6SJNrCoGg9Nx4441Nqh7HGo8CTesE78xBEeNvsJew7rFetmak0FFHH5PgdXdKUyblMDlQSogGQJl9ZUE8XHplRciOGUZMFJKWbPybrM8RSjRKB+HkeDNpdcEaXugbv6deecfekzuEF5rj9bbcaAmKPHtfwjVWU5ZgaGitflptrjCRzEzSowOLChclGy4lONmwsZgJIZoGGxphCk5ZchY58mFQgPyhIGyILIRssN4FMRQKWuGcBZPPUjiA70Mw47rNlB5MbgFFUSSUzfXuqGygOe/+I/LM00fmxyrz7L777jYUpVtBxBy/QUkklGLmuh6msufmVsHBGohA4/rWMM7+cWBjcQIM1bEcgZwcWy4VLw8bZmMFDbxZbMJY+/ybBQm7fs987x6RjYf3u94s5DnYxzV1vfhrVq22grfLJ0UpjChmiQJmTTAilq9++2ETrq02q9/4txW4WzopWCTHNSoFT1SNqfDYDFzehKM2HLDnmOsb5Zg+RXgTanzKxF4jM6NU8/qC95VCDMlymOCAHqkLF3i9c++++665++67W8Q4wLpAuBFKSbIwN295am/nBDzhtjhLIGDznzhGIM9yffKLWN9Q3LyFQDhGwpCZc3vvvbcZPXp0HQNcS7LxoA2ShjhmoreBqAwKL6F89u8fV4q6dutu9xzCRFlr/cavlsQpmewl/H3X448964yzokV8orjmIzg0CPNE+SM6TOv8+tGoqwXBxJvMRSgBNfUdXOTEzgohmqeZrbPIEQaARQuh+cb3qxL6u7Dhsmjy3rNfiZTTPuft7naDJNSNmPtMD4NwYSLOg+P3hCRjSLdIwjuKFgLCb37zG3P+NvGxYRyxopL4Sh4QSiXrFxU+6UHlxsGrNLFx0+DP610CQls4Rv4enr7GbvD8NjYtLMaM+xNrt7bPTw+NNCac2DS2uGyx+XnFcru5oSxxzvk/yiS3kCfB1zFs2BB7zPwdjo05we/3Ny5F+EY4K/3wSfPTLeNMzfL5ZosttsioEM2OBNclc4L5W+hRmDp5nBR+JaFT50gYEEoTBhYUcQS7HF858qra9MptZzL2WnniCXsNMPcDOXWLmCyrSWyS6aWyNnLtcS3gPYaW8magLGGYwSiD0vTLR5OHFns9TFyPrENc35xP7qnKh5GrqdekGzOrDHmufydsozThqW5tz463F5kjE70NrlIiaz17KoZKR2FhUazIkOt31ZpwPER0kZvkwIP04jeJuW6uCMSECRNsKW/mlevT15JUenoH+uH5bFfYGqUwMVEILQEGHsskF7eDRS2ZO1oIkR7J8mBYZCjXz4bHorPW05AVsDKzAVLg4eEva822T/YyCws2skUCiMXOhjAIhCGOx4Wmpei3mAD7rxMWCT+75557zAYmXoiB72MzmTJlin0fgileIhQnPG/JlEfWNY6FDfH888+PfVdxl542DILnif2n0mBjcDHvLmn33bLB9nn6tQwdMiRhIwsvn2e9DiiCjAfHY5vyBkhwDyT1MNHzxFX3Qxlk/iDAFRYkhmHQ64fxQrnq2aN7LIwoU0rMdzQQfhBsuTa9c361p89SgU9H4NrlM8wFzh05DMztE3camvC+rQYmVnHLRrhWGBuEU4wpGBD8fF+VOo/kma/pRRQJe8N4RJGNlhLQ3dpNcjue4Jfmxt2EXruFN6/oPzPD1jvIGu4aXa/v8TFmXON43fMLCpN6KCh00xpNV7cenH1z0FVKRFGiMql3jIYOHWYfk1N81VVX1amU2NKQ53v55ZcnNEXHE1bma7BbHC2xSQVYbryXc9+ShrHKykpbje/BBx+sE7nBY55v6Wp9GaUwYT0hvp8SwJdeeqldhHbbbbeExEdXFlMI0TT8eTBspq+++qpViBAacjxWVkrq8hwCL8IEysDhRxxlN0u8K+RCeRevTAyD8JbjxmJnlYIG+jE5IQRvEJsb+UEsyJ+vjCuBhC2Q7EqYMPk/hCbgdWOT4zPJlEfGneRw17jwkcWR9WxSeG9rmUVwQ/kinK8xHjq3YSG0IcDVRkue55tas2TRTwlFIkqKi80xxxxj8668FkzOcyoPU21NtZk8eXJsIyXvjSqLnX0d4GtCATsufC/FP4iHZywySXnuSLiGwSji3jn/3ar4g1U+byvhlsxZvIhUcyMsHgb1KGnQop9tuLlMvzQXrltfhUg/C9dGPoNhhOunJdc81gPWIMK5UGi94W6LoscB3t/xyaqu9n0oWJxXDDxcw37Pd1MUN4pw+QU8t/5T6KY1hP2ahhrrZSCMH4oS+xBeP29o5Oidd7fKJvtIY/eA9YXoLYx47Etc+xhROQ7W89pvpia8d0huxGvpxZ8n29xUV1fHegcS+urFVf9FhsmkyJYWVZjYgLF87rHHHjZviZt3o6VHCHkEQojmL3MKES9DTkJujYNrkxBZhCm8GWyIycLvMi0MwnmWyMnAqocQefLzDVuhEJTYRJ555hm7SNueSt9HrLrB/M42RJjQBSxweIcYQ6+ymEx5ZJOhATfHhHI0q8f+5hrzO/PVum52PAmLJLSnKU0lCelj8yUELhxdenMDIVNTnegxGjt2V2t8oq9dsga5eYGQ6W0ShamvZs60VfE4zwhe/G76b1CK3p//gpWSfFRKp+Npag1Ls0gOc4p8EvB6mDbplRsrIb7Kdykwb11VWhpTpjp32a8uxQUx1gZCWpORG0jtjmZN5Mb6QlguUTAthWs0jqLDdcsavMfDteawZ4xZXpFc1AqHgjYc0+WxuZDa9Q2bjhndQnWNK625/lPUIhvh/LEPsKbavP39rzVmyC6meLffWoMaXhuKnOEdbA1cmCXFS1CWqPbIPoIRjoiC/nmJrSryTdCeYwxiRIG1Rhnvrl272oIi7D203fh3wemmYsie5v5uf7TzmWsQw4ALEWz3ChODTmdjfjw3f9d5rLyEBwghmnchomkqfTTwIJV4evZQDY+wHBZDvL2XXXaZFcq5VjM1/C6ZQMQNj5irNoXiUxVuOLwX75GzHmMNvHyHyAaWW7POCi9O4XAKp19Y8D92x4Kl1zWtrDV5doF3izxhEJRnb4zQ4bxoWAPx6HTqEvEgjsmZbT0BbHqObtGmud5QPMchm+SZmsu7mo+LzjEbBX5KELzw7nOMZ511lhk3bpwNmQ7WJCpM5ZU1drxIVsar8dFHH7Vq4nJH5oht4+fYC+eauRvyeB426hk559N+qBuCxjlmDhHhUZ/VuIUNyq0GaxfXMZ72ZEUK6lOYXHU8FEyuWe911tywlrA2cIyusMwPwT7mm6q+tsCCvzk1rF2z2h4f6x5RAa5MNWtLs6zbu/w+cr/VMaYtGNa75fo8tSTMG64xzukVV1xhfhx0qDGnvmx+XPqzfczzvO5tbt6SeMMsaYVB9IG3x99OY3aMvbc4J2jD1d08Qj6gUXtLK8mVlZXWeImXiXF5+u2vzNXfbmYWrAnF2hJxw6CXrSHgTSqRwkliMfCD5pvJgpkQ2QgLHaE3VFHCyuQNpaDCGlYkmsGRD8FrzmtCzmGmhd/VtxmwCWENcwJ8TTRsrT7qs1QRhoeCufPOO9tGeukIS658K14uqhA5izH3H374oR1HmtI2ttyv8xLOnTvXfjanMu4h2nT4EJuD5QgGa22fJ44dK/UvNso1R2+eZ4sCvHBcXAA5KffV2P+rKitsY13CgSi/zD1et9zcxCWeqlyuL40rDKE1u3XoXFi3rC8eUkJ7ELCrohUMoSaqJyWrFsn8QenFyv2vf/0rZehWS4fgtBYIVyhL3JJ5XH/RI9K/LRUIcI1tALs+/aJoccB6hkcMjzRrMy0MyJvkeW810/z8PGvcwsCB1wAhnDWNc+fPn2kSe/3JmFNfMeawO01b8JfDtjQ7De9p7jp+tMkmUGD/8Y9/WOMdkQuEwpG76kLieJ7XeV9r4A2zpFCMXx4/dty42OOKUG5Cg+DWqoxbWlpqFSK3J7OPs2/iHab6I1Ee5FXjhcrWIkOtV1NSCNFkXAgZDUlDnjAHyoejMOGdcbHvCMTZ1POA48ODRr7RhRdeGIvxD9Wmb4VCwMCI86ZPdkJQIa+APIi2HAf+NnlJgOKb79EFRwzomaDMzfnmGxsGQgn5fp0D5sVfl5injikxv9g4UeA+IjdSghhqa6psWXFy1rwlzwsLEr10hHgxTswlclJRsrN188o2kuUUoRCjnKPA/uSJFjtl24jhcasNIhPlq2URDerpBb1sZAfzBeGDkKGWKpWdKaCEuCqasLwsUWk6t1+kN+TCcK+U34HwhsLVkpZtVyyA3EAEW+7vuusu23Ll+OOPt0oba/WoUaNin6ntsZFd+4DKbKxXCLkYS5rluszNM2bITsbk1fVutQZ9uxaZx8/c2fxiq/4mm2AvJZoKhRevH0oS4a/c85jneb01Q8vqa6jst420VYPgYDBojXUUh0NRYs5TdAnjI+GwHFM27zdSmITIArAOUbTg6aefNitWrkywUBIvjDeF+OBMLBmeDrjwOX4UH0KNEI6+WZq6IaUfrLaE0M1cFSkx/J9vCmNNKhujNDJujB8CFuE1CDgoFy4WnA0SAZXNoLFwbjhP/DZvLvSF5/8uoQ8TibGUSEeBHNYp/vyzv0oMb+kcqDRdTCQEMS8QsGGErsoWQjj3Bd7mPrZKXo4dDwpYIJRlWhPj9oxfqOlWnGcVXIQw5tWpL9X1ngztHtmit/xXmdng5ipz1fQS66nYb7/9bNNMPovS1Z69hCg5XIMYEbh2ylMsCytXl5mDk5Ty5jPMeW9hlZb0AqAcuTXHrT8I2axrCJSsMXs+18OcMX1D87PpbnM+ECjxDPO+bIgKaO+4Agaw8cYbx0LvuOcxtEaZ7nQpKky8/tuiMm5RUVHMGIC8wn7O+PB/vFyu2W82z2spTEJkOGywKEt33nmnLQaQn1+QkO+CcP/www9bQZ8FPRvDrAhtuP32223VH34PoTdHPJF+Qi2/l8+5ilnFxSVWmMQKWF/YUrLv4YYQM2vWrNjz3nK/CDfEajfWuug2LX5bcUk8D+2j998xY8eOjT2msh0bDAnFycooe9kgsMred+pUYkNETj/9dBuzjiXPVt+q9lVKyiu0myjheoSYMG+yTbnOVvw9sfJzAtbrwbxFYf5qUWLithcMCetqcuy8IGkaoZwCSwjWhJtmsxCSbg4TRVBQPlJFGvYvKDeTPaW811ZFPNWudxqhjK2xLuIpIgTJ2+eNaxEDDnmFWOCX1ZSYY//vn1ZBwohCc153zWZDVEB7x4Vmu4gACoaw3nPPY2jpMt2Nobie+dKalXGLiopsfhXzmn0FwyJ7GM+3h5ZDUpiEyHDY5FGEsNawoVZ5rFobjRgRq8qE4EXhh2y1TrLQXn/99bGFdfG69CssuXKmeVGNacCgwXahJq+HkuwoTekoBowb1nvGmhAC4q4JpUPZIbwArw/KnSsO0RiwMJN8S5WldTnx3jErVyyxG3Hfqp9smfjf/mK0VRx5vy8FqQ5VpiDWqBAljtAlPGN4qRiTQDhR4QqGAzEBnWp5zJtsU67bS0hefl6uDd0ivC5ZTnDsc7m5VgBBEcZKy1zkPCMEEWra2r1gWhuuSXJ8uLehtynKpffplHixXPNOVWz8aAXQlGu2sfD9XFN4cFk76I+H0vTxxx/bolisSazhhOvxHizurHd8hpBaGS8yB/ZV1ns8JZwjIhi45zHPt3ROUGPwN6320xpKeEFBgTUKUHmVcWKuY/RjzeJ5POKzZ8+2Rp9sRQqTEBkOCx3V7377299Gk4bjwtWsWTPtYkgC/+9+9ztb8j8blSUHQiFemHQ5ZZt8UxI1XKEgDB++of1/bl5ECGHRJrGeanDpeIQQWCZOnGh7QjGmCDXkiZDrgwCE1ZjCDYSyNda66Jpwosx4mTf7a5vsKQCNAAA9EUlEQVSv1HvuJLPt//5r3n5lkrVCszEXeZOdkhAwkTCudaVrrPWakucUEeDzKEX5vhV+TVnEc4XQRr5FawiRInqufK6RnEDAehWoakgVtVQg8LumxTQdpQz5Y489ZgvAZGt53saC8YDfbhUOk54hZd7qgA3V5bMYB5jzrVFa2TWHdUrT999/b6655hr7Otc/XmDu77//fvscIZaE07LeePuuNRXmRCrFi+c7ypxZH1hHKfCA0Yy9gIbnGMq45zHP8zrvy0TvdVtQVFRkixVR6IE9hWsPQwXP493lnjGkAEW2GgakMAmRBaAo0QcNYb6wMJKnA8FoXwbCQGjumM3KklN6UErS5YHDis2N+0d+MwrS8mi1ue++m28tgFi6KLeNIpmOgsN3kEtA76a//OUvVvDheLAOUxKchR4BzJX/bQxOOUE58op81ZXlNnRwzerVZu6cb6yCh1KFoPxzdf1hDHlRhcmEQ7bwB16wefPmxZSgfF9Xz6qaoBWYOAYUJvKY5GFqHfzewoK8SM8dwuuI/U8VsoJ32ZWBR2FgDcBzQe4iIZUdQQBmnLj+GIeG+vEe+EiZueqtKjP1p0KrgHBNUyADA0Rr4PJGWDs4ZkJ4OQaq5z366KO2CIQXqpnhAadc9Pp6C5kLjzzyiC104/eA8Jjneb0jzJn1gXnDGs+N3FVvThCP3WvNoeA2B0mq7bc6paWl1pDD3slaRZ8oIl64BtjPmHOE1baG4aKlyIBhFkKkC5vu/gcemPAc1kuez3awAqP0NbYk8uGb5pnOBcYM6WrMmtU/2+cWL11mhSs2NRQfQp/SUSZZzMl3QPmYOnWq9SwBiz15TWwAhNEk6wfTEGwSfA+CbtjTVrR87WorLJPLgJJECCEhV4Qx1NdjBnJNJOSuWzQXgo3J2xvEFQ1wlNVEPBaEl1x11VU2rCvblexswW8Fvu3Yba2QgRDrzZfzg7DNjTmBEMK8xnOBB4PnvR7CSw4aaQZ2LzbvXRJphtteYJzw7HLdNaQwvTIvaK55t5au3tGcp4AV4MgrImesNUCwZu1gzXBQZpwqpxMmTEh4Lx5h1qnmCK10xQq8+VPAPY95PpOKFWQqnAv2DcLLwFumG3ie1zMlHBZvdVtTGW3czJpEz8iDDjrIGgdcgRpaZ3At0pw+W/ccKUxCZAHOcnjdddeZlydHkk4dl156qX0+my2HLgTCKTmEKiVr9JiMYNiYny7oYr4/v4sZ1iWiLNQEI54XFmrygdJdoBGwaASIBwYr/uWXXx7rw8TY8hz5FE1J9uU30mjX9lyqiZ+n7l062e/Fe0BRD5QekmW5FYTjVfKS4cKT1q4ttaE/eKqcp4LNac+hiSF9VciRgYBV3uiZIVoPvxFgq0HdrCD/3nvvxZTlZHA+eQ0hl1yYr776yipLeDD8iedn7zHCKksoTe0JLPkIp6wJ6cqGzHGufT6Ld4l+bN6S+y1t/GHtYM1g7SGvkHNMeC/9s3jOCeB+5aY5QgK934vH2ilLPJ9JxQoyFReaTYsLN2beMt08z+uZElqWCSF5gEGDcUJZOuecc+z/uUdpIleT6zdblSWQwiREFoCwxIaLNdq7SJM4jrDN87yerZZDFwJBrDNhRjRtRNipqVtpuQ7oRt2KIhvGXkMj98FQ2MZQNyVkAuswvW6w4lNpDyuxyzFAUKUUdFOEG1ftCwtvTnWkOS9UrFtjhWln/eb/xTk15ro9jNl7w7rNTr1QJMJ9N/HhjCE5YNyK8+p6p2jhhfBNThfzJlvnSzbil2m4jilRj+fEFXRI/rlArNADxUG4Lpyy1NKlsjMFlKUrr7zSGjLSEQ4xPqCsoCgxtjvuuGOrVRNEQXENTlkz/vnPf9rjRjkmNNB5gL0ln5uzHYT/e8mV8ipLHWXOrA+sp6yh/jFrzTLdTS368Pej4n2+WpOuXbva/EqUI5Qk75g5pYnXs1lZl8IkRBbARjtp0iQrADwxN75Iz+z1y1jlHl7nfdkqEBHDf8UVV5h77rnHCpFYqf46eyPz6fL8Bj1Msf+H4ooBgiY9MxorJCG0oBQRe81nXS8mcshcTlNThBusb1QCxMpdGY57EwYVVVhlic2XzQSl8e/7FZs/7FxoLtutMC0PE7lI5FYdd9xxtoAAitlvtq47boQC8j7+HpWestUjmY188kNibh7nG8GL88HN9Xfxw7XNXHPJ01wbhHt1NMEXRR9FaN6qNKwohLqWl1tjB+NEGC1j3NJwnijGgVKEsnTLLbfYMEqEbK57rOyusI0rAtMSAjjfS2EaLzzuaHNmfXtqEbLsH7PWLNOdLt4w1a7F9RvZWoqioiI7Ll5lyeGUpmwPAZfCJEQWwIbqPDBH/PpUc7U5z1xjfmdWFg62ixDP87qLsc5WpYkQOtfc8bXXXjMTZ9eYHe9ZXe/nUI4cnQoiO0coHLbCR1N6P/A5lBuSV1GW3AJPOA2ep6YKNwhMFJ/gd06p3jb2fLi6zHrDOFYUHwS9nQeltzQ7DxPHi1DI2FEdj8d7Dq27cQbD4VhODJX0pDC1HstKE8MrmVfk1t17773Wa0QvHj8/rAnb8B/OKYo6pfOZH4R7EfbVUWA9oGw+8/ZXT5eb17+L5+mlUq64plA28ehSia41LNusCVzfu+++uzUAYSCBvn372sdY2emfdeKJJ8bWlZYQwPGAkxvlhceZVAo703FNh5ORab2yvKX2G5P/KxqHFCYhsgA2YfoBYSVksw2bHFNrIgIxj3me1zMlCbWpsBGRUEs4C94ykuEbat5K+J2fUDhgBSWafBLG1BgQTrlR+AGPkjfXAM8TY90U4YbwNwQ5lKZQTr55IbizfT6Qk2sVHIQq8pxya9aaUX3rLyfuV5gQohHEXnrpJWtVx8L9qy3zk44VeWJUyKMnVLbPl2xiztK1SZ8nl8zNOT/eXmScU5RulHWuD8K+CP/qCLiEcpi/2pj9Hq6/qTXXE4VwuH4Zs9ZSFpxnAkWY/A0vXN9Y2cmR9F93zSmAews8eIsVNGeulMgsvEUf2iqfqbIDVGiUwiREFuD6GmBhdcnEwD2PeZ7Xsz0nhePHKoxwiFUZ63pDJNGXrGLAd6CANGaR5m8iVKBUkHfgT/ZF6ED4aso4O8+Vq/ZVGS6IlZfGO4hHi2PebXD6G55TmMhvwUPFcaFgcvupNJR0rHgNK2RTekmJlml0SgW1ZCFjFC+xOW3FxVbwP/zww81tt91mw72YK4R/ZUrieUvCPB0zZoxVKljnGgLDBHmHRx11lFVU6JvTXDlCmeyZcOuXN2fJv3611jiINlKYGioj2UJUd4AKjVKYhMgC2Gi9hQi4J8fH+5jXs10A5vgR5BH+0w2n6xwNw/MrBihbTnlId5FuyWRfhBRKitOXBW9CbXT57bdBHyvQcZwIz43B5TCR00JDRbyNHCu/fVlZXU0S/ZNxpaLe1Vdfbfs2ibad78cee6z1hFDopLQ6cS7P+zlslWmKFhCSdt5559lcJ8K7CPvCU5EpiectiQtfPPjgg2O/99yXKlK+n9BWBDQKaZB7iEc1k5L0W4psK1YgmgevkuQtANGadO0AFRrbJjtMCNGkQgSuezz3L7/8csJjXicWPpsXJKA7OELk7bffbhWdhrxMg7vlpPQ64clBEE13TFxIDX/X/xmXa4Cw0RQrMUoRlQw5lwU1FSYUVZhGbDjUFBautGF16VBREzbF+YEEDxOlqfGmMVZ8T6o49pAJxLwahO5RKU9heW0Hnk+KtVBBjRymy8J9zB27LIu9fuV7uVbBpVgA5agpIMDcw2uAAtHUuZiNcC2jAOFdw1L9r49rzF0H1y2f7saEa4H3TZ482RphUJra+1i15PolMhevjtSWJca7RRVzpyRRoRHaS4VGeZiEyCLLIZZoLKZuw+PeVW9rL5ZDvC/8ln322SftXkypKudRDKOxvVdaKqQGT8GGG25oz9GaV243tdWRMMGACdnfmy4og99FK4XF+zCtteFZ3KMsbdonz4zuH8mDemluMCFU0QmSVAFk3ojWYdSgbinDWPD0kaPzzqx4IYefK8JmeVnQhqiSi/fUU08lKNWZlnjeWnlMhMtyDTHPJ82pqfM+56kdNWqUNQasTxhtNpJNxQpE8+A1kDWhp3qz0q0dV2jMCoWJ8BESFxE2iOUeMWKE7cnQURZAIZzlkIWHam1eeNzUQgSZhovBp+w1sc9NXWRRKlgrjj/+eGudzwQQVgid22GHHUzfYmMqv400jv3pxx9szoXb9AoaqPcQ9njQnIcJr9zXX39tren87p0GxYMHymriHjqqB2KpJw+EnCma5IrW4YzdhqcMyfviiy/snK+sjld/qw0HrMCPQuV6+HSkynjJxsqVzGcOozTlJpFgMAjQk4zrXmFooiPnM7UFa9pxhcasUJhmz55tF0n6s9Dl/Oabb7YN/y677LK2PjQhWtXzwsKTrPoRzyerspVtuMIIWJK57snP4vGqioaLP3gJBHJs0QbyujJFieQ4zj33XPPf//7XjBs3znQviSg1Jw1fYT0MKE3wh50a9qq5MEWnMO25555WEXPheHnR74LqhCKDkbAmlzifTlEN0Tz8clRybx5KK8oQ5y2h4mMg1xoQmP+AF/LVV1/tsAn7XD80n2We838MpvlJ8jW4jrbddlubz0fBh0zrmSNES9KlqO0ybda08wqNWaEwHXjggbYkIWVzsaSSk/B///d/dbRYPwiQbC7emxDZSEepfoQQxKKK4I9lnfwNQtmG3brOTPu+/t4rXghYYyzwRGdS6WWENpRCwoaO3STuIe8SKLdVz2DMoPpdTOg4fg8TYVt4IehdhXGpf/9+sfdX14YSGtciUOK5oIpYY8MVRdNBIdqwd2LoJXMUryDXsm1i26mL57wF7blivlD0gZ5gFDNoD2G3TYV5iwzA2hDxlCaKMDzHbcqUKTY/DxSGJjoCV/xyc3Pm7sPNFgPaJvSttAPIKFmhMCUDoYrkz/q4/vrrbUiPu/n7IgiRLXSU6kccP+WVyVOgGhiWYn5jeTDX7PlQekURIBiK5DzguZkwYULGLNJLly61VreHHnoo4flOeaF6+0p5sa9Gwy5cDhNhmYwZipgNV8qPWxmrPB4m/goKFZ4lBE/nvRBte10z5yncMnyjTWKvoeeiMG255ZY2n++GG26w3pKO7CnhesYAwhiQ3zhjRVwBfeZ/BVY5cjl6zmMrREfg1LEbmst+sVmb/f2CDiCjZGWVPCpNUUHrxhtvrPd9l156qfnDH/4Qe4zQJKVJZCMdpfqRC7vBY0JDTzxNKD54mhoTPobOwWcIdfroo48aXa67JWD9Yd3ieFBujImXTa9Fw4uyaG3YDO6WOg7dDkMgoui4d6H8nHXWWfY3v/HGG2b5svnGRPfOGlcBg3ClvHzr6cDgRJXF008/PeurKmYT/jnMfKc8+B133GGWLVtmavvEezExJZi39O1i7iBwENLZkZWlp59+2o4Z3jZy8P71ea1ZF+pmBg8dbp5ZbEzPngvsNTBs2DBbhn38+PGa30K0AkUdQEZpU/PiJZdcYjfv+m7kMXhBACJE75hjjrEds+sDCxQnznsTIlvpKNWPCLthcSVkbN68eZFchfz8Rik9+QWFNiQXjw5l1zPBw8RmgVecsCp+zw3vBxNC5RwPfl638peXbkUBE4p6oXICkTFB4Ca8jt/KmK1btzb2/ppQ/LsrKqpiuW4u3Eu0HuEU7QIwCqBEL4yGkdn3BnKswYBQFpSDRYsWddhCR4zPww8/bN59911bHpxwO/IbV64uNd923tnc/OZSM3/BIpubR8EHSrR/8sknGWEoEaKjUNTOZZQ2VZj++Mc/2l4g9d2wnDrYMPbaay+zyy67mHvvvbctD10I0YJQDhw3PgIiwhKCo9c6//p3teb2GfUIj7n5sZwgDC+ZIGiyWRx99NG2lDehczOXexP840txTQMhecnC9qiMh8Dt8r9M2BPiF05c5hlHV7FPPZhal0NGDbD3m/aN5CqhsHLj3Nm57qmSF/aET+JxpRBKJij+bYHrHUbYIlVzuX4YF/Ib6U9FCB5zn8esF/Sr2n777RVyKoRoHyF5WIq4pQOeJZSl7bbbzhaAUOy9EO0bQpBoJeCSt73eEHwmR45MvXwtXRPxSqGcUHIdBSwTQGlCqCOWOy8fJS6i2PQqCpnvou/ZtFcadqxYDlMoNjYoQQiK77//fqwYBCwrw5MVGat+3YtMt27FtoLg/PnzrXApz3vr8ft9NjZbDuxqxmzYKzYfKGZEBVg8SaGwp2dWMGiVfeYx55fqhtw6IsxRDCiEtFJa3eU40qwZZRJlijA8XsMIsOuuu5pzzjlHc1sI0WxkRcYvyhJlc4cMGWLzlpYvX26WLFlib0KI9gnllrnWXQlsBCQH1YS9xQz8VFbXWCUJj04mCU4c06233mqOOuooGzbomHFGZ0M12EvGFpgTRtUNk5v+UzCphyngscCjWE6bNs0K4d7QB29IXn5+ntl7772tpwJhXCF5rUtBXo45cMv+pken+DlG0KfJKop0YVE8h4mwSwyDKEkoALfcckuH9giSB0HPKrypFMnAo0T4HesDucmsF8x7jBHkUrSHRplCiMwhKxQmSuVS6GHq1Kl2gcRq7G5CiPYJ1/emm24aq5zHGuDoVBAw3yxPrTFR6MCF4tF+AE9KJsBxPP7447afzuo1ieFVr59YYq7fJ3mM980fJvbYctGJzsN03XXXmQsvvNBa3hG8+3o8ap6aDyY/L8989tln9j3kMkWKT4i2hDlKeBmKUUV1Yv6ay8HhdUVVGLPRRhvZPowoSYwbFfPwluJZIgSXvOVrr73WyglCCNHhFCZc8WwYyW5CiPYJCs/WW29tNt98cxuW5KWqNmze/jF1QnfQBKwHeuLEibbkdqbkfuAtv//++21S+vK1iXlVuw5JHWL41vfJPUzhqjJT9eGjNgzPCYwomGVlXkUo7mEKh0ORMu3l5TYXVH2Y2h4Ef3Jw8KZWVtUt+MG5+uKLL2wPk0xR/NsKFKObbrrJhiviYUJxoiAGcx4DAHP74osvtl7cjj5WQogOqDAJIToWrgkewiTeEG6E4pw6Jc98uTRoznqx0tzq87p4ycnNtwIUOQ7khmRC0QcvGHum/VBPTKGPGp9u6ExFFa/fYYbXfG/69u1rxowZY6vwRQplVMTeG/Qs8127dLV5o/T1oUpepo1LRwRhn/mAwlvjKS/ftTBgn8fLxGvTp083K1asMB0VvEnnn3++rXzJtT106FCraLI2oEARtohBwvVewyghhBDNhRQmIUTG4Zrg4VmiPw2CEfkbL83PM1vfXWa+WRGyOUxfLEmudATDgVgIE0KUK6Xd1lBSfMSIEdYT1Bi8vZTAFckbPGiALRpAk26S32nDwHgVe3KY8grjhQJWr15le/mQN8N4KocpM8BTwlynT5ZjUNdIjhmKLa91ZI8gBpQnnnjCKo4YB8hloqw4HiWUpQEDBpgPP/zQXls8N3DgQDN58uSM8SwLIbIfKUxCiIyD5O1DDz3UKgGEJKE8IRT5Q/NqU0TldS3Jt+8nLwRlKVP6sZCYTlnkxoYT1/EwheM5SRSQILfjiCOOsAKlLUPt8RytKY+HJoVCQdvLhsqBJMZne1+M9gBCPeGjKEMI+l7wqnLDc3j44Yd32POF4oiCT5Nf8vXwklIRknH55S9/acPvyHPkPffdd5/1oMogIIRoTqQwCSEyFgo9YH3HI4PnpKKiIkFoTKUwVVdVW0ULgWqbbbbJmIpZrgEvimBjqPE50kJRjemnBT+aP/3pT3acECoRIvGsYXV3rKuI/62uXbrECmFkiteto4OiRH8hFCPCzLwQbkZ5/S233LKOMtWR4JpHwcezRE4ic/eAAw6wyhEV8mhmT89GDAeELvI+GQSEEM2JFCYhREZCKfCdd97Zho9hUcYSj8cIJYgwJahN0eS1rLLKhvFROOKKK67ImD5MLhGd42oMvog8E44WckApJOl9/Pjx5sQTTzRz586N5HTUxD1Mw3pExgq6du1ix5C8LnLEFLLU9qDgjhw50lZ7c/PagbGAucI10NGr5KE0oVzibUaJHDdunA3DAwwio0ePttcC48X7Oqo3TgjRMnTsFVgIkfFW5Z122skK+QiNKAhe70kqDxPP83lKk1PCOxMUA1dSnLC89Q0RdHoi/ahIhne96RC4SXqn35KjS25ceRoyaLA5++yzrcCJ4KkcJpMR8+Lbb7+1546wMi+bbbaZvcergoe1o+PWBEJKn3vuOav4M5dPO+20WBsCPKjyngohmhspTEKIjPYyEYqE0kTBBLwnlBN2OUD+3J7457pZTxSKxCeffJIRJYYR5PASEHq1vjiFqUvnztYzwdjgpWBsELwD4bhS+cb8+P9RpPj7p5xyikKWMmiO77jjjlZZIqTSy5133mmVJpQBSuRnguLf1riQUqcs0XaEsDzuuRboLSbvqRCiuZHCJITIaIvyIYccYoV8rMcIRPyfsBtuqTxMObl5MU/Utttua4XStoZjOOOMM6ynbH244b0qE44WFu/cqcRWyUOoxkuB5wrlcHS/eMjfnJXxQfphwUL7Ho5FIUuZAefh1FNPtecxoRl7535myJAh5q677jJ77bWXihj4Kmg6ZcnlJ3LPY3lPhRAtQepOiUII0cZgUSeMDWsy+Qk0sqXAAcoSnpSQpymrvygC+R8oJ1SRyxTlAGVvq622srkXVLRriPGTK8z0nyKK3/+9Wmn23jDXXPFmtXn1N51iVe9mzpxpNt5445iyVJgbNr/aIr60l5u4R2vGkhyzz7p11tOF4Jkp49LRoaIbOWh4R8y/r4g8OfJge4f3hCIGhKXqfMXD8vA0+Q0hKE14TzW3hRDNjTxMQoiMBcEH4R7vCRXE5s+fb5UOlCFu/v5EjunfrbH3a9euNX/+858zJv8DhYZmui536JNF9TevveujGvPJ4oiH6J8fVJuDH62wYYihaEze2tI15rPPPouND6GKI3snLuvkfY28c5059PFy89ynS23jzwcffNA88sgjGRGqKCLz4umnnzbPPPNMfDhyIkovYZY8z+s6X3GlKZXXWN5TIURLIA+TECJjcQnceIroX0SeDsUNUIS4Vdcm9mVyrCqvNdUrV9rmllTLyyRBEwEYJQaumlZlJh2XmOhfH+Rw2YIRgYhSRLE9fhu/0XonkoASNWdF2MwvzTPduwdtA1C8c+Q9Mb7yWrQ9nAfOIZ7UGLn5dq6Qj+Oe1/kSQoi2QR4mIUTGN6ykCS15HBtuuKG59dZbrbCP0F+bov8r4W4oFninyAvJFKVg4cKF1hvkyopP+V/DYXkOfi99nGjUGYgqTCYcsiWUUcBQKFOVK3fPk+vEuMyZM8eOrarkZQacByq/kX/jKF1XZpUlDASE45Gfkwm5eEII0RGRh0kIkRX5CgiV3FM2m3A8ijoEw4l9axwoBSgRKEvNUZWuufKxpkyZYr1EhAji+aFoxc8VYdOzOHVfJpQ+Kqi5HKUPPvjAnLMfv7vWFOTn23GgtDj3jFFebt1KGPwthG4apH733Xf2nufksWh7OKeER+JhOuKII4x5IJLD9MXMWWZxZZFVsPfcc0/bvFkIIUTbIA+TECIr8hXcPQImoXZ4kYpzU7iYol4mhFC8KpngYUKZoQEvVf/69u0be55eSsm48LV4GCEKIgIzvwmPg/vVPXt0t2OB8kNzXv4GBS8cT35Vk6B0uVwnFEl5LDIDZwTgvNJbKPZ8bch8/vnn9lzxHm5CCCHaBilMQoisgnwO15jyqM2T5zAB4WuUIc8UxcB5y8aNG2e9TA0pTHie7Os5OdY7VVNTY71MhOb1iOp/PXPLY+8hh4n3hD1NcfOiKzyfoycVlQapMognw5VjFplR2GTWrFk2rPLj0l72+f/ODNlz+tZbb9n5rvBJIYRoO6QwCSGyChrZUl4cr0t9EIp34IEHWq9OJjF9+nSrMI0ePdqGyaUKxnOKFL+TJryu/wy/Z+vekdynS8cE7e/Ee1RRUWEVo9pw/BuXlEXKh5PD5HK6KKCBJ4OCAqLtQRmeMWOGvX/11VfN+TP6m8Nn7Gg6DdzcGgcILaVKHtUVhRBCtA1SmIQQWQXeolGjRtVRmL5bFfesoBhwo9/R7bffboXRTICwKsLn9t13X7PjjjtaL1iuZxUe8M+1CQoTv5GiDvRZ2mKLLayy5Pc0oHStWLHChiry/c6rBMXFRbFx4u+S54SHafHixbagQKaMS0cGzyPVH8lrw6O0bNlyM2DYxjZ8koInvI7CjNKk8yWEEG2DFCYhRFZBvsfbb79tFaKE5yvjuTvutdmzZ1tBk89kirJHiCBC8EsvvZRYRtoYs3id5zcETCxviePfYYcdbD4Ln3ng60hM3utLusU8S7HPxTKcKKIXtAoTf48QPG4I5wjjrnmtaPs5QbNVKkCi9BJW+emnn9rwPPLT8JJS9IHKkDpfQgjRNqhKnhAiq3C5PP4S2tWeJrZ4UlA2CDvDck/PpkyB4+aYqGwH0R60dcgNGFu0gjA8FCUUnLlz59rf9uPqiIK0trzSfh9jEvucNykqHLJCNh4qPFGUZuf7UKDIi1GVvLYHJen555+3/0dpwlvoQEnCI8j5P/roozOieIkQQnRE5GESQmQV5P+Qs+OavzoqfS2NVq5caZUFwpkyqSQzAjKlvZ0XzFPULsFrlhNVCPkdCNJffvmlVXK45eZFPEPBmuoEARvy0bSiUDGPqnx4ofBMMQ6/+tWvbDEMwr3ksWh7OH8UdiDcDgWfEEwUI+4595w3QktTNSYWQgjR8khhEkJkFfPnzzdfffWVzcnxctEbIetluvH9Kvsa1eQotX3ssceaQYMGmUwKwRo7dqxV5FCQvB4mr9dsQWnEi8TveOedd6yXyIXelVVESo6HQ5EGvQ4UoML8eODAWwsLrXJGQ1SKPRx//PFm8ODBNgSMin3yWLQ9KEZjxoyxihHKNErTRhttZO95zPO8zvuEEEK0DVKYhBBZBR4WV/Ftnac1TbjvlmaDm6vNha9FSo5vvvnm5vTTTzfjx4/PKMXAlUQfMWKEPS6vwkS43UETKswVb1Wb5+cErQJFDhIeNcqRb7/99tZLVF4Z+Y5AVGnsUmDM/hsXmZKS4oSQvCc/X2MVTBQmil+gLIHrayXaHtdjiYIenJMBAwZYLyr3POZ59WESQoi2RTlMQoisggp5+++/v5k5c6ZZF1pjOptI/o4toJBXZIi+I19n9913NyeddJINPcsUCLuiOh2FHKiUZ6ueBRYmvGfK/2rM1B8iniU8RpRQP+yww2xVvRtuuMEcc8wxpja4yL43NxBRmEovjfSZemNBjulekNibivwtPBbqu5SZ4EXCY4pyxHkG/k+RD6B5La/zvkzoJyaEEB0ReZiEEFkFCtCtt95qPS5hzxJGJTm8MVtttZUtwf3NN9+YBx98MKP6DbleSnh8LrzwQvPwww8Th1fnfXjQ8CqhLKEcUlkP5erqq6+2iqGrb9GtKPGzew8OmtF9449RHPFWTJkyxdxyyy0qS52BoATtscceZqeddoqVEQfueczzvC5lSQgh2g4pTEKIrALFYeLEiTY0bXl+PDcJgXKbbbax+UH8Hy8OyfT/+te/MkZRQAgmd4gcIpg0aZK5/IMS+//r3qmK5TChMFH5jj5NeBYef/xxM2fOHPPxxx/bkL4RPXLt+/besP4gAZQtFC9yumbNmmWLP4jMgjlx5JFH2gbEnGuU6dNOO83e85jneV0hlEII0XZIYRJCZBXOS4MA+UJoT/PQt53NwS/2MMOHD7fKUt++fc1+++1ne9e4kCYEz0zBCb54fB599FEz4YsKM/C2GvOX96JFGwoL7T1KDqFYTkl6/fXXrfKDMvWLjdNbuqkkSA4M+V6MC4pXpiiPIgLng/OCMouShDeRXDPueczzOm9CCNG2KIdJCJFVoHBQKptcoMpAiXmxZhczar9Ijg6KEV4aSmfzPjw0eJsyLZwJhYjjQ6HheMvDhaa4OFJWHI8Cz+NhIsQQTxn9mHgfpaVRmL5dGTZb9ol815YbpFaeaFBLWBdFA6i0h1KpUuKZaQAAlCSXa8Y9j5nnvK7zJoQQbUcg7K/N284teWxC5DRkmgAlhEj/Or733nttjxr6CVE2HCWDpQzhcsmSJbbh55lnnpmgnGTab7jzzjvN7NmzbY8d8q9Ymw4++GCbe8Xz/B76L/FbKBCx5ZZbmqOOOsrmMI3ql28+OS1S3OGyN2vMdXslFnpwjHi4ty0ewXeNHDnS/s0hQ4a08q8VDYGij1KbbF9irmTiHBZCiI6EPExCiKwCDwsV8qj+ds4559hQM8cRRxxhzj//fFvogPdlUoU8LxwbjWi5cfyUkCax/4ILLjALFiywHjKUKNhss82sosRn+vfvb71Nq2vjS3e3gngfJj9Lly613gkUJgpI0JdKZB4oQ6kUIhn3hBCi7VEOkxAiqyBsjUp4m266qXnuuediVfC45zHP8zrvy1Q4Nsqj01CXMDunLMHUqVNtsQYUHLxLAwcOtEIzn8E7ZPvyhOK/bWCXulX2HOS/LFu2zIb4oZwpf0kIIYRoPPIwCSGyCpSHM844w4bfEZ7GPVXEnn32WfuYMD1yPzLZMs+xnXvuuTbHCi8QIYUoM+43DBs2zPzhD3+wBSBck9kVK1bYz5LXZArJeVlrH+ckKUvuwCtF7hPfQ6l1hXUJIYQQjSdzTbBCCJEClxBPFTEUjPvvv9/euypj2dCklWNE8cPLhCfI/xuolEYInVNyevfubav/kdcU8izdBZEK4ykhh4mQvksuuSSjlUghhBAiU5HCJITISlA48Cx54XE2KEtN+Q0oTocddpj1SpHH5MhvYBXHezV9+nSzfPny5jtwIYQQogMhhUkIkZWQs0QImxceu5ym9vYbCNm77777bG8mr8KUl2PMvJ/rFn64bXqkES7lydXLRwghhGg6UpiEEFkHCoXLYSKE7bTTTouF5/F8NihNjf0N5CN99tlnZtGiRbYEtWOvDfNMTpI0pq+Wh2x1PD4XDAZtaWr18hFCCCEajxQmIURWgafFq2i4fB9vThOvZ3JFuKb8BqrpUUod8Bw5SvIDJjfJSl4bdTrhYaKwBDevoiWEEEKI9JDCJITIKvCS0FvIX+DBWwiC1zPZm9KU34CnCKWJ5zt37pzwfck8TOFw5Em8TChKs2bNsg1ShRBCCNE4VFZcCJFVUPzg6KOPtsqDvzgCj6kIh0KRySW0ObYTTjjBKjL+ynX8hlNOOcUqS97fwP/xQsVD8oKx13KTKUyBHOuJQmHis7vttpuq5AkhhBBNQB4mIURWgZfk6aefNs8880ydPB8e8zyvZ7o3BSUmVZlv13vJCyXGL730UvtabW1tgx6m2nAkdK9Lly5mm222Mccee2xGK5FCCCFEppI1CtOhhx5qu9yz4ffv39+ceOKJ1tIqhOhY4F2hSpy/OIK3iAKvt7d8HRTAjz76yDbm9SuDyRSmqupa2+SWUD7C+NSDSQghhGjnCtNee+1lnnzySTNnzhxrQZ43b54NyxFCdCwQ/P3FERYsWFCniEJ7UxBQAFevXm0WLlxow+y85CbRmILhyGe6d+9eJ+dJCCGEEO0wh+mCCy6I/X/o0KG2a/3hhx9uK0DRyFEI0XFwxRGcknT//ffb5/1FFNob5eXl1pPmrZIH3ZNE2gWjVfKorDd+/Hgb0ieEEEKIduxh8vLzzz+bCRMmmF122aVeZamqqsqW5fXehBDtA5SiI488MuE5HrdXZYkiEPw2wpKLi4vNU1/XxF7L8SlQ3rLieKOmTp2q9U8IIYToCArTxRdfbGPxe/XqZX788Ufz/PPP1/v+66+/3goY7kaFKSFE+wBPy7PPPpvwHI+zoWltUyC8jpykAw44wK6BN8yoP0Dg7R9qY4YjPFOZXGZdCCGEyGTaVGEirI7Qkvpus2fPjr3/wgsvtJ3uX331VZObm2t+85vf1Inl90JFKYQndyPPQQiR/XgLPBCGd9pppyXkNLVHpQmFhwIOH374ob3PS9at1sPaaM0L1sqvvvrKrFixonUOVAghhGhnBML1aRwtzPLly83KlSvrfc/w4cOTWkZ/+ukn6zF6//33zc4775zW3yMkD08TwlR7SwgXoqPAdfzggw8mFHhw17VXiaKXUXu7zil6Q3lwu27WVJgfz0pdCTBwdan1SBG2vMcee5jHHnvMFoAQQgghRBYVfejTp4+9NQUsrC7cRAjRccCAQmgueAs8eAtB8Hp7C0FDUZw0aZJVeqiUl5dH/mb9pdOxhxUWFprFixfbz0thEkIIIdpplbzp06fb/iNjx461lmNKil9++eVmxIgRaXuXhBDtA4oenHDCCTanx+9BQmnCs4Sy1N6atPKbUH64J1yZEuPG5KdlXEJxoqKoEEIIIdpp0YeSkhKbzL3PPvuYTTfd1OYrjBo1ykybNs0KEEKIjgXKUKpwO55vb8oS8JvOOOMMc/PNN5stttii3vxNRzAYtE18r776amtgEkIIIUQ79TBttdVW5o033mjrwxBCiDZXmsjrvOqqq8y4ceOMMRUNfoYS5P3792+V4xNCCCHaI1mhMAkhhDCmsrLSPPLII7ZgztFHH22MeTjlsBC217lzZ3P66adbz7wQQggh2nFInhBCiEgvJnKXXn/9dfPoo4+mHJLTXqiwIXs5OTnm888/Nw8//LBVtoQQQgjReKQwCSFElkDBh2222cZ88cUXtnx6KlZVRPKbaFg7a9Yss3TpUqtsCSGEEKLxSGESQogsAA/RXXfdZc4///y0lB+8S5RXJywPBYuy4kIIIYRoPMphEkKILAAlCY8Rvedqa2vr9JkKEYIXCMTyl1CWevfubYYMGWJ69uxpFSchhBBCNB55mIQQIgugXDplxTfeeGPrPeLm5eEv4n2WQgWdzQYbbGB69epl8vPzzUUXXaSmtUIIIUQTkcIkhBBZAiXC6cEE/ka0wbAxv51cYe75pMZ8trqL2WOPPaxHimbfAwcObKMjFkIIIbIfheQJIUQWQahd9+7dzcKFCxOerw0Zc+dHNSYQqDWDBoVt6fE999zTDBgwwIboCSGEEKJpyMMkhBBZgstbSlYhLxQpjGfLiS9ZssQWeSAkj2IR//nPf1T0QQghhGgiUpiEECJLoODDggUL7L2fYDjuRaIoBIrT8ccfb0Py8Er5i0QIIYQQIj0UkieEEFkAHqObbrrJTJ48Ofbc1dOqzJV7FNr/1wRDCQUiuBGKd9xxx9n/FxUVtclxCyGEENmOPExCCJEF4CEqLIwoR3l5eVYZ6tvJ41WK6ktUxaOMOO956qmnzAsvvNBWhyyEEEK0C6QwCSFEFoCH6PTTTzdHH310zFu0tjqcUCXP0aVLF9u3ac2aNaasrCytRrdCCCGESI4UJiGEyBIIrevbt69VmPAk3f2xp/dSOGC9TsFg0Hz77bemX79+9nbyySfbzwkhhBCiaUhhEkKILAKlKBQK2duqyrhbKS83J/Ya95QdP/LII023bt3a9HiFEEKIbEdFH4QQIksgtG7dunW2Ch63Kk9/pUA4okTl5EQUpy233NL06dOnTY9XCCGEaA/IwySEEFkCoXWHHHKIVZZQiqpDHoUpEPE2oTARiodniea19GESQgghRNORwiSEEFnCTz/9ZK655hqbv0TFvJJOnWOv5eUEbGW83Nxc64Xiveedd5657777pDQJIYQQ64EUJiGEyBI6d+5sbyhLhNvRnNZRVFAQa1DLe9555x2zbNky8+abb5oVK1a06XELIYQQ2YxymIQQIkvo3r27uffee820adPMWWedZWpqqJJXYF8LmKAJBPLN5ptvbsuK421Cedpzzz1N79692/rQhRBCiKxFCpMQQmQRa9euNf/+97+tlwlPkjGRHksF+Xm2KMSSJUts2fE99tjDnHTSSdYT5fo2CSGEEKLxKCRPCCGyhNLSUvPQQw+Z+fPnm5KSEnPCCSfEXuvdo7vp1auXzV9aunSpOfjgg83gwYOlLAkhhBDriTxMQgiRJRBih1K02WabmREjRtgQPRMtgpefl2OKigpMcXGxGTZsmJk6daoZPny4+jAJIYQQ64k8TEIIkSUQWnfKKaeYq666yipG3pLhVMkbMmSIOeCAA8yOO+5oPU3/+c9/zJo1a9r0mIUQQohsRwqTEEJkWVjeX//6V/PBBx8kPN+v7wZm7Nix5ttvvzUzZ860RR9WrVpllSY+I4QQQoimIYVJCCGyFHouOYYNjecrEbp37LHHmh49esRKjQshhBCiaQTC3kYe7RysrN26dbMhKl27dm3rwxFCiCZBUQc8RxUVFeYqc7N9bmbB9uaZ6t1sqN7JJ59s+vbta9c8lCVVyRNCCCGajhQmIYTIQjD8oDQNXPWhGW1mmqfNL0xhj4FWWcIwJIQQQojmQSF5QgiRhaAUHXnkkWaW2dT81xxtyk2JfSxlSQghhGhepDAJIUSWepieffbZhOd4rKp4QgghRPMihUkIIbI0HI8qeBR2OO200+y9q4onpUkIIYRoPqQwCSFEFkEhB6+yRM7S4MGD7b1XaVIpcSGEEKJ5kMIkhBBZBFXvKBXulCWXs8S9U5pUSlwIIYRoPlQlTwghsozKykpTXV2dtD2CSokLIYQQzUteM3+fEEKIFoa+Sql6K6nHnBBCCNG8KCRPCCGEEEIIIVIghUkIIYQQQgghUiCFSQghhBBCCCFSIIVJCCGEEEIIIdqLwlRVVWW22WYbEwgEzOeff97WhyOEEEIIIYRox2SdwnTRRReZAQMGtPVhCCGEEEIIIToAWaUwvfzyy+bVV181N954Y1sfihBCCCGEEKIDkDV9mJYuXWrOOOMMM3HiRFNSUpJ2+B43b0NHIYQQQgghhGhXHqZwOGxOPvlkc/bZZ5vtt98+7c9df/31plu3brHb4MGDW/Q4hRBCCCGEEO2LNlWYLrnkElu8ob7b7Nmzze23327Wrl1rLr300kZ9P+9fs2ZN7LZgwYIW+y1CCCGEEEKI9kcgjPumjVi+fLlZuXJlve8ZPny4GTdunJk0aZJVoBzBYNDk5uaa448/3jz00ENp/T2Upu7du1vFqWvXrut9/EIIIYQQQojspkuXLgl6RkYpTOny448/JuQfLVq0yBxwwAHm6aefNmPGjDGDBg1K63t++uknheUJIYQQQgghEpwq9TlTsqLow5AhQxIed+7c2d6PGDEibWUJKEeOd6khLbI1QAEkp0reLqE5I7TOiExBe5PQnBEdcZ3p0qVLva9nhcLUXOTk5DRKwWoNmCiZMllEdqA5IzRnhNYZkWlobxLtec5kpcI0bNgwWzlPCCGEEEIIIUxHLysuhBBCCCGEEG2BFKY2orCw0Fx55ZX2XgjNGaF1RmQC2puE5ozQOpOlVfKEEEIIIYQQoi2Qh0kIIYQQQgghUiCFSQghhBBCCCFSIIVJCCGEEEIIIVIghUkIIYQQQgghUiCFqY248847bT+poqIiM2bMGDNjxoy2OhSRQVx//fVmhx12sB2nN9hgA3P44YebOXPmJLynsrLSjB8/3vTq1ct07tzZHHXUUWbp0qVtdswis/jb3/5mAoGAOf/882PPac4IPwsXLjQnnHCCXUeKi4vNVlttZT7++OPY69SDuuKKK0z//v3t6/vuu6+ZO3euBrKDEgwGzeWXX2423HBDOx9GjBhh/vrXvyb0xNSc6di8/fbb5pBDDjEDBgywe9DEiRMTXk9nfvz888/m+OOPt81su3fvbk477TSzbt06kwlIYWoDnnjiCfOHP/zBlhX/9NNPzdZbb20OOOAAs2zZsrY4HJFBTJs2zSpDH374oXnttddMTU2N2X///U1ZWVnsPRdccIGZNGmSeeqpp+z7Fy1aZI488sg2PW6RGXz00UfmnnvuMaNGjUp4XnNGeFm1apXZddddTX5+vnn55ZfN119/bf75z3+aHj16xN7z97//3dx2223m7rvvNtOnTzedOnWy+xTKt+h43HDDDeZf//qXueOOO8w333xjHzNHbr/99th7NGc6NmVlZVaexSGQjHTmB8rSV199ZeWfF1980SphZ555pskIKCsuWpcdd9wxPH78+NjjYDAYHjBgQPj666/XqRAJLFu2DPNdeNq0afbx6tWrw/n5+eGnnnoq9p5vvvnGvueDDz7Q6HVg1q5dG954443Dr732WniPPfYIn3feefZ5zRnh5+KLLw6PHTs25cCEQqFwv379wv/4xz9izzGPCgsLw4899pgGtANy8MEHh0899dSE54488sjw8ccfb/+vOSO8IJM899xzscfpzI+vv/7afu6jjz6Kvefll18OBwKB8MKFC8NtjTxMrUx1dbX55JNPrCvSkZOTYx9/8MEHrX04IsNZs2aNve/Zs6e9Z+7gdfLOn5EjR5ohQ4Zo/nRw8EwefPDBCXMDNGeEnxdeeMFsv/325phjjrGhv9tuu6257777Yq/Pnz/fLFmyJGEudevWzYaPa5/qmOyyyy5m6tSp5ttvv7WPv/jiC/Puu++agw46yD7WnBH1kc784J4wPNYmB+9HRsYj1dbktfUBdDRWrFhhY4H79u2b8DyPZ8+e3WbHJTKPUChk81AIndlyyy3tcyw4BQUFdlHxzx9eEx2Txx9/3Ib3EpLnR3NG+Pnuu+9seBWh4ZdddpmdN7///e/t2nLSSSfF1pJk+5TWmY7JJZdcYkpLS62BLjc318ox1157rQ2hAs0ZUR/pzA/uMeB4ycvLswbjTFh3pDAJkcEeg1mzZlkrnhCpWLBggTnvvPNszDdFZIRIxxiDFfe6666zj/EwsdaQW4DCJISfJ5980kyYMME8+uijZosttjCff/65NeiR4K85IzoCCslrZXr37m2tM/6qZjzu169fax+OyFB++9vf2oTHN9980wwaNCj2PHOEsM7Vq1cnvF/zp+NCyB0FY0aPHm2tcdwoBkJyLf/Hgqc5I7xQpWrzzTdPeG6zzTYzP/74o/2/24u0TwnHhRdeaL1Mxx57rK2oeOKJJ9piMlR21ZwRDZHOmsK9v/hZbW2trZyXCfKxFKZWhpCH7bbbzsYCe619PN55551b+3BEhkGuJMrSc889Z9544w1bwtULc4fKVt75Q9lxBB3Nn47JPvvsY2bOnGktvu6G94BQGfd/zRnhhTBff7sCclOGDh1q/8+6g4DiXWcIxyKPQOtMx6S8vNzmknjB+Iv8Apozoj7SmR/cYwzGCOhADmKOkevU5rR11YmOyOOPP24rg/znP/+xVUHOPPPMcPfu3cNLlixp60MTbcw555wT7tatW/itt94KL168OHYrLy+Pvefss88ODxkyJPzGG2+EP/744/DOO+9sb0I4vFXyNGeEnxkzZoTz8vLC1157bXju3LnhCRMmhEtKSsKPPPJI7D1/+9vf7L70/PPPh7/88svwYYcdFt5www3DFRUVGtAOyEknnRQeOHBg+MUXXwzPnz8//Oyzz4Z79+4dvuiii2Lv0Zzp2Kxduzb82Wef2RvqxU033WT//8MPP6Q9Pw488MDwtttuG54+fXr43XfftZVfjzvuuHAmIIWpjbj99tut0FtQUGDLjH/44YdtdSgig2CRSXZ78MEHY+9hcTn33HPDPXr0sELOEUccYZUqIVIpTJozws+kSZPCW265pTXejRw5MnzvvfcmvE4Z4Msvvzzct29f+5599tknPGfOHA1kB6W0tNSuKcgtRUVF4eHDh4f/9Kc/hauqqmLv0Zzp2Lz55ptJ5ReU7XTnx8qVK62C1Llz53DXrl3Dp5xyilXEMoEA/7S1l0sIIYQQQgghMhHlMAkhhBBCCCFECqQwCSGEEEIIIUQKpDAJIYQQQgghRAqkMAkhhBBCCCFECqQwCSGEEEIIIUQKpDAJIYQQQgghRAqkMAkhhBBCCCFECqQwCSGEEEIIIUQKpDAJIYRod5x88snm8MMPb+vDEEII0Q7Ia+sDEEIIIRpDIBCo9/Urr7zS3HrrrSYcDmtghRBCrDdSmIQQQmQVixcvjv3/iSeeMFdccYWZM2dO7LnOnTvbmxBCCNEcKCRPCCFEVtGvX7/YrVu3btbj5H0OZckfkrfnnnua3/3ud+b88883PXr0MH379jX33XefKSsrM6eccorp0qWL2WijjczLL7+c8LdmzZplDjroIPudfObEE080K1asaINfLYQQoq2QwiSEEKJD8NBDD5nevXubGTNmWOXpnHPOMcccc4zZZZddzKeffmr2339/qxCVl5fb969evdrsvffeZttttzUff/yxmTJlilm6dKkZN25cW/8UIYQQrYgUJiGEEB2Crbfe2vz5z382G2+8sbn00ktNUVGRVaDOOOMM+xyhfStXrjRffvmlff8dd9xhlaXrrrvOjBw50v7/gQceMG+++ab59ttv2/rnCCGEaCWUwySEEKJDMGrUqNj/c3NzTa9evcxWW20Ve46QO1i2bJm9/+KLL6xylCwfat68eWaTTTZpleMWQgjRtkhhEkII0SHIz89PeEzuk/c5V30vFArZ+3Xr1plDDjnE3HDDDXW+q3///i1+vEIIITIDKUxCCCFEEkaPHm2eeeYZM2zYMJOXp+1SCCE6KsphEkIIIZIwfvx48/PPP5vjjjvOfPTRRzYM75VXXrFV9YLBoMZMCCE6CFKYhBBCiCQMGDDAvPfee1Y5ooIe+U6UJe/evbvJydH2KYQQHYVAWK3QhRBCCCGEECIpMpEJIYQQQgghRAqkMAkhhBBCCCFECqQwCSGEEEIIIUQKpDAJIYQQQgghRAqkMAkhhBBCCCFECqQwCSGEEEIIIUQKpDAJIYQQQgghRAqkMAkhhBBCCCFECqQwCSGEEEIIIUQKpDAJIYQQQgghRAqkMAkhhBBCCCGESc7/A6D3Pb2ghgDBAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "\n", + "plt.figure(figsize=(10, 5))\n", + "\n", + "times = jnp.squeeze(synthetic_samples[\"f_times\"])\n", + "states = jnp.squeeze(synthetic_samples[\"f_states\"])\n", + "observations = jnp.squeeze(synthetic_samples[\"f_observations\"])\n", + "\n", + "plt.plot(times, states, label=\"states\")\n", + "plt.scatter(\n", + " times,\n", + " observations,\n", + " label=\"observations\",\n", + " marker=\"x\",\n", + " color=\"black\",\n", + " alpha=0.5,\n", + ")\n", + "plt.title(\"Synthetic Data: States and Observations\")\n", + "plt.xlabel(\"Time\")\n", + "plt.ylabel(\"State / Observation\")\n", + "sns.despine()\n", + "plt.legend()\n", + "plt.show()" + ] + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "/var/folders/28/rfdjbzgj0bz_x56whkjmhl600000gn/T/ipykernel_8806/2187872338.py:35: UserWarning: The figure layout has changed to tight\n", - " plt.tight_layout()\n" - ] + "cell_type": "markdown", + "id": "1c8c8a86", + "metadata": {}, + "source": [ + "## Bayesian system identification\n", + "\n", + "Performing Bayesian inference for system identification (in this case, obtaining posteriors of $\\rho$) also becomes simple. Recall that to obtain posteriors of $\\theta$, we must compute posteriors with respect to \n", + "\n", + "$$ p(\\theta \\mid y_{1:T}) \\propto p(\\theta) \\underbrace{p(y_{1:T} \\mid \\theta)}_{\\text{marginal likelihod}}. $$\n", + "\n", + "We can accomplish this by appropriately **interpreting** the `dsx.sample(..)` statement. We will proceed with the normal numpyro tools, but wrap it in a `Filter` context for marginal likelihood computation. Inference over $\\theta$ is then a standard Bayesian inference problem." + ] }, { - "data": { - "image/png": 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", - "text/plain": [ - "
" + "cell_type": "markdown", + "id": "69e749ec", + "metadata": {}, + "source": [ + "The `Filter` object gives us some control over the way we solve for the marginal likelihood, including the method and its hyperparameters. By default, we use an ensemble Kalman filter (EnKF); the EnKF is biased for nonlinear state space models, but still generally accurate for high-quality inference. To change the filtering method, pass a config, e.g. `Filter(filter_config=ContinuousTimeDPFConfig(n_particles=2500))`.\n", + "\n", + "After specifying the marginal likelihood computation, inference can proceed in the standard way for `numpyro` (although, MCMC quality may vary based on what approximation to the marginal likelihood we take). The EnKF provides a very smooth marginal likelkhood, so we can often use NUTS in state space models that are not overly complex. " ] - }, - "metadata": {}, - "output_type": "display_data" + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "14756201", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "sample: 100%|██████████| 200/200 [07:39<00:00, 2.30s/it, 3 steps of size 1.02e+00. acc. prob=0.94]\n" + ] + } + ], + "source": [ + "from numpyro.infer import MCMC, NUTS\n", + "from dynestyx.inference.filters import Filter\n", + "\n", + "obs_values = synthetic_samples[\"f_observations\"][0,0] # shape (T, obs_dim)\n", + "\n", + "mcmc_key = jr.PRNGKey(0)\n", + "\n", + "with Filter():\n", + " nuts_kernel = NUTS(continuous_time_lti_gaussian_model)\n", + " mcmc = MCMC(nuts_kernel, num_samples=100, num_warmup=100)\n", + " mcmc.run(mcmc_key, obs_times=times, obs_values=obs_values)\n", + "\n", + "posterior_samples = mcmc.get_samples()" + ] + }, + { + "cell_type": "markdown", + "id": "c0a63174", + "metadata": {}, + "source": [ + "Plotting the posterior values of $\\rho$ shows a posterior centered at the true value of $2.0$." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "5745525c", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import arviz as az\n", + "az.style.use(\"arviz-white\")\n", + "\n", + "az.plot_posterior(\n", + " posterior_samples[\"rho\"], \n", + " hdi_prob=0.95,\n", + " ref_val=2.0\n", + ")\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "d5016e81", + "metadata": {}, + "source": [ + "## Likelihood sweep\n", + "\n", + "As a quick diagnostic, we can sweep over fixed values of $\\rho$ and evaluate the marginal log-likelihood $\\log p(y_{1:T}\\mid\\rho)$ using the same `Filter`-based model. This is useful for checking identifiability and seeing whether the inferred posterior mode aligns with the likelihood peak." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "27699b7e", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/28/rfdjbzgj0bz_x56whkjmhl600000gn/T/ipykernel_8806/2187872338.py:35: UserWarning: The figure layout has changed to tight\n", + " plt.tight_layout()\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from numpyro.infer import Predictive\n", + "\n", + "from dynestyx.inference.filters import (\n", + " Filter, ContinuousTimeEKFConfig\n", + ")\n", + "\n", + "def marginal_loglik_at_rho(rho_value, *, obs_times, obs_values):\n", + " with Filter():\n", + " predictive = Predictive(\n", + " continuous_time_lti_gaussian_model,\n", + " params={\"rho\": jnp.array(rho_value)},\n", + " num_samples=1,\n", + " exclude_deterministic=False,\n", + " )\n", + " out = predictive(jr.PRNGKey(123), obs_times=obs_times, obs_values=obs_values)\n", + " # Keep this robust to scalar vs singleton-shaped return.\n", + " return jnp.ravel(out[\"f_marginal_loglik\"])[0]\n", + "\n", + "\n", + "rho_grid = jnp.linspace(0.1, 4.5, 20)\n", + "loglik_grid = jnp.array(\n", + " [marginal_loglik_at_rho(r, obs_times=times, obs_values=obs_values) for r in rho_grid]\n", + ")\n", + "\n", + "rho_hat = rho_grid[jnp.argmax(loglik_grid)]\n", + "\n", + "plt.figure(figsize=(8, 4))\n", + "plt.plot(rho_grid, loglik_grid, lw=2, label=\"marginal log-likelihood\")\n", + "plt.axvline(2.0, ls=\"--\", color=\"black\", alpha=0.8, label=\"true rho\")\n", + "plt.axvline(rho_hat, ls=\":\", color=\"C3\", alpha=0.9, label=f\"argmax ~ {float(rho_hat):.2f}\")\n", + "plt.xlabel(r\"$\\rho$\")\n", + "plt.ylabel(r\"$\\log p(y_{1:T}\\mid\\rho)$\")\n", + "plt.title(\"Likelihood sweep\")\n", + "plt.legend()\n", + "plt.tight_layout()\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv (3.12.11)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" } - ], - "source": [ - "from numpyro.infer import Predictive\n", - "\n", - "from dynestyx.inference.filters import (\n", - " Filter, ContinuousTimeEKFConfig\n", - ")\n", - "\n", - "def marginal_loglik_at_rho(rho_value, *, obs_times, obs_values):\n", - " with Filter():\n", - " predictive = Predictive(\n", - " continuous_time_lti_gaussian_model,\n", - " params={\"rho\": jnp.array(rho_value)},\n", - " num_samples=1,\n", - " exclude_deterministic=False,\n", - " )\n", - " out = predictive(jr.PRNGKey(123), obs_times=obs_times, obs_values=obs_values)\n", - " # Keep this robust to scalar vs singleton-shaped return.\n", - " return jnp.ravel(out[\"f_marginal_loglik\"])[0]\n", - "\n", - "\n", - "rho_grid = jnp.linspace(0.1, 4.5, 20)\n", - "loglik_grid = jnp.array(\n", - " [marginal_loglik_at_rho(r, obs_times=times, obs_values=obs_values) for r in rho_grid]\n", - ")\n", - "\n", - "rho_hat = rho_grid[jnp.argmax(loglik_grid)]\n", - "\n", - "plt.figure(figsize=(8, 4))\n", - "plt.plot(rho_grid, loglik_grid, lw=2, label=\"marginal log-likelihood\")\n", - "plt.axvline(2.0, ls=\"--\", color=\"black\", alpha=0.8, label=\"true rho\")\n", - "plt.axvline(rho_hat, ls=\":\", color=\"C3\", alpha=0.9, label=f\"argmax ~ {float(rho_hat):.2f}\")\n", - "plt.xlabel(r\"$\\rho$\")\n", - "plt.ylabel(r\"$\\log p(y_{1:T}\\mid\\rho)$\")\n", - "plt.title(\"Likelihood sweep\")\n", - "plt.legend()\n", - "plt.tight_layout()\n", - "plt.show()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv (3.12.11)", - "language": "python", - "name": "python3" }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" - } - }, - "nbformat": 4, - "nbformat_minor": 5 + "nbformat": 4, + "nbformat_minor": 5 } From c8c5cd8a88f0f6c3467802608e0e377e1f78eb4c Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Thu, 14 May 2026 15:08:27 -0400 Subject: [PATCH 18/28] simplify notebook changes for PR --- .../sde_non_gaussian_observations.ipynb | 868 +++++++++--------- 1 file changed, 434 insertions(+), 434 deletions(-) diff --git a/docs/tutorials/sde_non_gaussian_observations.ipynb b/docs/tutorials/sde_non_gaussian_observations.ipynb index 50814299..9469aeb8 100644 --- a/docs/tutorials/sde_non_gaussian_observations.ipynb +++ b/docs/tutorials/sde_non_gaussian_observations.ipynb @@ -1,451 +1,451 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Inference in SDE-Driven State Space Models with Non-Gaussian Observations\n", - "\n", - "One challenging but common problem in practice is state space models with non-Gaussian observations. In this tutorial, we show how to write these and use them in `dynestyx` for a state-space model with a Poisson observation process. We'll use a differentiable particle filter (DPF) combined with stochastic variational inference (SVI) to infer model parameters." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## The System\n", - "\n", - "We'll model a system with continuous-time stochastic dynamics and discrete-time count observations. The latent state follows a one-dimensional Ornstein-Uhlenbeck (OU) process:\n", - "\n", - "$$\\mathrm{d}x_t = \\kappa(\\mu - x_t) \\, \\mathrm{d}t + \\sigma \\, \\mathrm{d}W_t,$$\n", - "\n", - "where $\\kappa$ is the mean-reversion rate, $\\mu$ is the long-term mean, and $\\sigma$ controls the diffusion strength.\n", - "\n", - "At discrete observation times $t_k$, we observe Poisson counts that depend on the latent state via an exponential link function:\n", - "\n", - "$$y_{t_k} \\mid x_{t_k} \\sim \\text{Poisson}(\\Delta t \\cdot \\exp(x_{t_k} + b)),$$\n", - "\n", - "where $b$ is a bias parameter and $\\Delta t$ is the observation time step. We will place a uniform prior on $b$ and infer it from data using stochastic variational inference with a differentiable particle filter." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Specifying the Full Model in `dynestyx`\n", - "\n", - "Now we'll write the complete model as a `numpyro` program. We'll place a uniform prior on the bias parameter $b$ and use fixed values for the dynamics parameters. To specify the Poisson-process observation model, we can simply pass in the correct distribution as a callable -- dynestyx will turn it into the appropriate equinox module under the hood." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import jax.numpy as jnp\n", - "import jax.random as jr\n", - "import numpyro\n", - "import numpyro.distributions as dist\n", - "from dynestyx import DynamicalModel, ContinuousTimeStateEvolution, ObservationModel\n", - "import dynestyx as dsx\n", - "import equinox as eqx\n", - "\n", - "# Fixed dynamics parameters\n", - "kappa = 0.8 # mean-reversion rate\n", - "mu = 0.0 # long-term mean\n", - "sigma = 0.4 # diffusion strength\n", - "\n", - "# Observation parameters\n", - "dt = 0.1 # observation time step\n", - "\n", - "def ou_poisson_model(bias=None, obs_times=None, obs_values=None, predict_times=None):\n", - " \"\"\"\n", - " Ornstein-Uhlenbeck process with Poisson observations.\n", - " \n", - " The bias parameter controls the mean count level and will be inferred.\n", - " \"\"\"\n", - " # Sample bias from uniform prior\n", - " bias = numpyro.sample(\"bias\", dist.Uniform(2.0, 10.0), obs=bias)\n", - " \n", - " # Define OU drift function\n", - " def drift(x, u, t):\n", - " return kappa * (mu - x)\n", - " \n", - " # Create the dynamical model\n", - " dynamics = DynamicalModel(\n", - " initial_condition=dist.MultivariateNormal(\n", - " loc=jnp.zeros(1), \n", - " covariance_matrix=0.5**2 * jnp.eye(1)\n", - " ),\n", - " state_evolution=ContinuousTimeStateEvolution(\n", - " drift=drift,\n", - " diffusion=dsx.FullDiffusion(sigma * jnp.eye(1)),\n", - " ),\n", - " observation_model=lambda x, u, t: dist.Poisson(rate=dt * jnp.exp(x[0] + bias)),\n", - " )\n", - " \n", - " dsx.sample(\n", - " \"f\",\n", - " dynamics,\n", - " obs_times=obs_times,\n", - " obs_values=obs_values,\n", - " predict_times=predict_times,\n", - " )" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Generating Synthetic Data\n", - "\n", - "We'll generate synthetic data using the `SDESimulator`. We'll set the true bias to $b = \\log(50) \\approx 3.91$, which corresponds to a mean count rate of about 5 when the state is near zero." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "from dynestyx import SDESimulator\n", - "from numpyro.infer import Predictive\n", - "\n", - "# Generate observations at regular intervals\n", - "T = 1000\n", - "obs_times = jnp.arange(start=0.0, stop=T * dt, step=dt)\n", - "\n", - "# Set random seed and true bias parameter\n", - "prng_key = jr.PRNGKey(0)\n", - "sde_solver_key, predictive_key = jr.split(prng_key, 2)\n", - "\n", - "true_bias = jnp.log(50.0) # approximately 3.91\n", - "\n", - "# Generate synthetic data\n", - "predictive_model = Predictive(ou_poisson_model, num_samples=1)\n", - "\n", - "with SDESimulator():\n", - " synthetic_samples = predictive_model(\n", - " predictive_key,\n", - " bias=true_bias,\n", - " predict_times=obs_times\n", - " )" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can visualize the latent state and the Poisson count observations:" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ + "cells": [ { - "data": { - "image/png": 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", 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" + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Inference in SDE-Driven State Space Models with Non-Gaussian Observations\n", + "\n", + "One challenging but common problem in practice is state space models with non-Gaussian observations. In this tutorial, we show how to write these and use them in `dynestyx` for a state-space model with a Poisson observation process. We'll use a differentiable particle filter (DPF) combined with stochastic variational inference (SVI) to infer model parameters." ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "\n", - "# f_* : (num_samples, n_sim, T, ...) under Predictive + SDESimulator\n", - "t = synthetic_samples[\"f_times\"][0, 0]\n", - "states = synthetic_samples[\"f_states\"][0, 0]\n", - "observations = synthetic_samples[\"f_observations\"][0, 0]\n", - "\n", - "# Compute expected count rate\n", - "expected_rate = dt * jnp.exp(states[:, 0] + true_bias)\n", - "\n", - "fig, axs = plt.subplots(2, 1, figsize=(10, 6), sharex=True)\n", - "\n", - "# Plot latent state\n", - "axs[0].plot(t, states[:, 0], color=\"C0\", label=\"Latent state $x(t)$\")\n", - "axs[0].set_ylabel(\"State\")\n", - "axs[0].legend(loc=\"upper right\")\n", - "sns.despine(ax=axs[0])\n", - "\n", - "# Plot observations and expected rate\n", - "axs[1].scatter(t, observations, s=5, color=\"C1\", alpha=0.6, label=\"Observed counts $y_k$\")\n", - "axs[1].plot(t, expected_rate, color=\"C2\", alpha=0.8, label=\"Expected rate $E[y_k | x_k]$\")\n", - "axs[1].set_ylabel(\"Count\")\n", - "axs[1].set_xlabel(\"Time\")\n", - "axs[1].legend(loc=\"upper right\")\n", - "sns.despine(ax=axs[1])\n", - "\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Bayesian Inference with Differentiable Particle Filters\n", - "\n", - "For non-Gaussian observations, the standard ensemble Kalman filter (EnKF) may not be appropriate since it assumes Gaussian observation distributions. Instead, we can use a **differentiable particle filter (DPF)** to compute the marginal likelihood. \n", - "\n", - "The DPF provides unbiased gradient estimates with respect to parameters, making it compatible with gradient-based inference methods like stochastic variational inference (SVI). While the DPF is more computationally expensive than the EnKF, it can handle arbitrary observation distributions.\n", - "\n", - "To perform inference, we'll:\n", - "1. Wrap all our inference code in a `Filter` context with the DPF\n", - "2. Use SVI with an automatic guide to infer the posterior distribution of the bias parameter" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 50/50 [21:51<00:00, 26.24s/it, init loss: 84395.2344, avg. loss [49-50]: 3331.3447] " - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## The System\n", + "\n", + "We'll model a system with continuous-time stochastic dynamics and discrete-time count observations. The latent state follows a one-dimensional Ornstein-Uhlenbeck (OU) process:\n", + "\n", + "$$\\mathrm{d}x_t = \\kappa(\\mu - x_t) \\, \\mathrm{d}t + \\sigma \\, \\mathrm{d}W_t,$$\n", + "\n", + "where $\\kappa$ is the mean-reversion rate, $\\mu$ is the long-term mean, and $\\sigma$ controls the diffusion strength.\n", + "\n", + "At discrete observation times $t_k$, we observe Poisson counts that depend on the latent state via an exponential link function:\n", + "\n", + "$$y_{t_k} \\mid x_{t_k} \\sim \\text{Poisson}(\\Delta t \\cdot \\exp(x_{t_k} + b)),$$\n", + "\n", + "where $b$ is a bias parameter and $\\Delta t$ is the observation time step. We will place a uniform prior on $b$ and infer it from data using stochastic variational inference with a differentiable particle filter." + ] }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "True bias: 3.9120\n", - "Inferred bias: 4.3293\n" - ] + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Specifying the Full Model in `dynestyx`\n", + "\n", + "Now we'll write the complete model as a `numpyro` program. We'll place a uniform prior on the bias parameter $b$ and use fixed values for the dynamics parameters. To specify the Poisson-process observation model, we can simply pass in the correct distribution as a callable -- dynestyx will turn it into the appropriate equinox module under the hood." + ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "from numpyro.infer import SVI, Trace_ELBO\n", - "from numpyro.infer.autoguide import AutoDelta\n", - "from jax import random as jr\n", - "import optax\n", - "from dynestyx.inference.filters import Filter, ContinuousTimeDPFConfig\n", - "\n", - "# Extract observations from synthetic data\n", - "obs_values = synthetic_samples[\"f_observations\"][0, 0]\n", - "\n", - "# Use an AutoDelta guide (point estimate - similar to maximum likelihood)\n", - "# For a full posterior, you could use AutoNormal or AutoDiagonalNormal\n", - "guide = AutoDelta(ou_poisson_model)\n", - "\n", - "# Set up SVI with Adam optimizer\n", - "optimizer = optax.adam(learning_rate=0.05)\n", - "\n", - "with Filter(ContinuousTimeDPFConfig(n_particles=2_500)):\n", - " svi = SVI(ou_poisson_model, guide, optimizer, loss=Trace_ELBO(), obs_times=obs_times, obs_values=obs_values)\n", - "\n", - " # Run SVI optimization\n", - " svi_key = jr.PRNGKey(1)\n", - " num_steps = 50\n", - "\n", - " svi_result = svi.run(svi_key, num_steps)\n", - "params = svi_result.params\n", - "\n", - "print(f\"True bias: {true_bias:.4f}\")\n", - "print(f\"Inferred bias: {params['bias_auto_loc']:.4f}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can visualize the ELBO (evidence lower bound) during optimization to ensure convergence:" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import jax.numpy as jnp\n", + "import jax.random as jr\n", + "import numpyro\n", + "import numpyro.distributions as dist\n", + "from dynestyx import DynamicalModel, ContinuousTimeStateEvolution, ObservationModel, ScalarDiffusion\n", + "import dynestyx as dsx\n", + "import equinox as eqx\n", + "\n", + "# Fixed dynamics parameters\n", + "kappa = 0.8 # mean-reversion rate\n", + "mu = 0.0 # long-term mean\n", + "sigma = 0.4 # diffusion strength\n", + "\n", + "# Observation parameters\n", + "dt = 0.1 # observation time step\n", + "\n", + "def ou_poisson_model(bias=None, obs_times=None, obs_values=None, predict_times=None):\n", + " \"\"\"\n", + " Ornstein-Uhlenbeck process with Poisson observations.\n", + " \n", + " The bias parameter controls the mean count level and will be inferred.\n", + " \"\"\"\n", + " # Sample bias from uniform prior\n", + " bias = numpyro.sample(\"bias\", dist.Uniform(2.0, 10.0), obs=bias)\n", + " \n", + " # Define OU drift function\n", + " def drift(x, u, t):\n", + " return kappa * (mu - x)\n", + " \n", + " # Create the dynamical model\n", + " dynamics = DynamicalModel(\n", + " initial_condition=dist.MultivariateNormal(\n", + " loc=jnp.zeros(1), \n", + " covariance_matrix=0.5**2 * jnp.eye(1)\n", + " ),\n", + " state_evolution=ContinuousTimeStateEvolution(\n", + " drift=drift,\n", + " diffusion=ScalarDiffusion(sigma, bm_dim=1),\n", + " ),\n", + " observation_model=lambda x, u, t: dist.Poisson(rate=dt * jnp.exp(x[0] + bias)),\n", + " )\n", + " \n", + " dsx.sample(\n", + " \"f\",\n", + " dynamics,\n", + " obs_times=obs_times,\n", + " obs_values=obs_values,\n", + " predict_times=predict_times,\n", + " )" + ] + }, { - "data": { - "image/png": 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", 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" + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Generating Synthetic Data\n", + "\n", + "We'll generate synthetic data using the `SDESimulator`. We'll set the true bias to $b = \\log(50) \\approx 3.91$, which corresponds to a mean count rate of about 5 when the state is near zero." ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10, 4))\n", - "plt.plot(svi_result.losses)\n", - "plt.xlabel(\"Iteration\")\n", - "plt.ylabel(\"ELBO Loss\")\n", - "plt.title(\"SVI Optimization Progress\")\n", - "sns.despine()\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Full Posterior Inference\n", - "\n", - "The `AutoDelta` guide gives us a point estimate (similar to maximum likelihood). To get a full posterior distribution with uncertainty quantification, we can use `AutoNormal` or `AutoDiagonalNormal` instead:" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ + }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 50/50 [21:46<00:00, 26.13s/it, init loss: 4887.0552, avg. loss [49-50]: 2773.0498]\n" - ] - } - ], - "source": [ - "from numpyro.infer.autoguide import AutoDiagonalNormal\n", - "\n", - "# Use AutoDiagonalNormal for full posterior approximation\n", - "guide_normal = AutoDiagonalNormal(ou_poisson_model)\n", - "\n", - "# Set up SVI\n", - "optimizer_normal = optax.adam(learning_rate=0.05)\n", - "\n", - "with Filter(ContinuousTimeDPFConfig(n_particles=2_500)):\n", - " svi_normal = SVI(ou_poisson_model, guide_normal, optimizer_normal, loss=Trace_ELBO(), obs_times=obs_times, obs_values=obs_values)\n", - "\n", - " # Run SVI\n", - " svi_key_normal = jr.PRNGKey(2)\n", - " svi_result_normal = svi_normal.run(svi_key_normal, num_steps)\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Draw posterior samples from the guide using its learned parameters `svi_result_normal.params`." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "from dynestyx import SDESimulator\n", + "from numpyro.infer import Predictive\n", + "\n", + "# Generate observations at regular intervals\n", + "T = 1000\n", + "obs_times = jnp.arange(start=0.0, stop=T * dt, step=dt)\n", + "\n", + "# Set random seed and true bias parameter\n", + "prng_key = jr.PRNGKey(0)\n", + "sde_solver_key, predictive_key = jr.split(prng_key, 2)\n", + "\n", + "true_bias = jnp.log(50.0) # approximately 3.91\n", + "\n", + "# Generate synthetic data\n", + "predictive_model = Predictive(ou_poisson_model, num_samples=1)\n", + "\n", + "with SDESimulator():\n", + " synthetic_samples = predictive_model(\n", + " predictive_key,\n", + " bias=true_bias,\n", + " predict_times=obs_times\n", + " )" + ] + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "True bias: 3.9120\n", - "Posterior mean: 3.9546\n", - "Posterior std: 0.0833\n" - ] - } - ], - "source": [ - "# Get posterior samples\n", - "posterior_samples = guide_normal.sample_posterior(\n", - " jr.PRNGKey(3), \n", - " svi_result_normal.params, \n", - " sample_shape=(20,),\n", - " exclude_deterministic=True\n", - ")\n", - "\n", - "print(f\"True bias: {true_bias:.4f}\")\n", - "print(f\"Posterior mean: {posterior_samples['bias'].mean():.4f}\")\n", - "print(f\"Posterior std: {posterior_samples['bias'].std():.4f}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Let's visualize the posterior distribution:" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can visualize the latent state and the Poisson count observations:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "\n", + "# f_* : (num_samples, n_sim, T, ...) under Predictive + SDESimulator\n", + "t = synthetic_samples[\"f_times\"][0, 0]\n", + "states = synthetic_samples[\"f_states\"][0, 0]\n", + "observations = synthetic_samples[\"f_observations\"][0, 0]\n", + "\n", + "# Compute expected count rate\n", + "expected_rate = dt * jnp.exp(states[:, 0] + true_bias)\n", + "\n", + "fig, axs = plt.subplots(2, 1, figsize=(10, 6), sharex=True)\n", + "\n", + "# Plot latent state\n", + "axs[0].plot(t, states[:, 0], color=\"C0\", label=\"Latent state $x(t)$\")\n", + "axs[0].set_ylabel(\"State\")\n", + "axs[0].legend(loc=\"upper right\")\n", + "sns.despine(ax=axs[0])\n", + "\n", + "# Plot observations and expected rate\n", + "axs[1].scatter(t, observations, s=5, color=\"C1\", alpha=0.6, label=\"Observed counts $y_k$\")\n", + "axs[1].plot(t, expected_rate, color=\"C2\", alpha=0.8, label=\"Expected rate $E[y_k | x_k]$\")\n", + "axs[1].set_ylabel(\"Count\")\n", + "axs[1].set_xlabel(\"Time\")\n", + "axs[1].legend(loc=\"upper right\")\n", + "sns.despine(ax=axs[1])\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Bayesian Inference with Differentiable Particle Filters\n", + "\n", + "For non-Gaussian observations, the standard ensemble Kalman filter (EnKF) may not be appropriate since it assumes Gaussian observation distributions. Instead, we can use a **differentiable particle filter (DPF)** to compute the marginal likelihood. \n", + "\n", + "The DPF provides unbiased gradient estimates with respect to parameters, making it compatible with gradient-based inference methods like stochastic variational inference (SVI). While the DPF is more computationally expensive than the EnKF, it can handle arbitrary observation distributions.\n", + "\n", + "To perform inference, we'll:\n", + "1. Wrap all our inference code in a `Filter` context with the DPF\n", + "2. Use SVI with an automatic guide to infer the posterior distribution of the bias parameter" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 50/50 [21:51<00:00, 26.24s/it, init loss: 84395.2344, avg. loss [49-50]: 3331.3447] " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "True bias: 3.9120\n", + "Inferred bias: 4.3293\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "from numpyro.infer import SVI, Trace_ELBO\n", + "from numpyro.infer.autoguide import AutoDelta\n", + "from jax import random as jr\n", + "import optax\n", + "from dynestyx.inference.filters import Filter, ContinuousTimeDPFConfig\n", + "\n", + "# Extract observations from synthetic data\n", + "obs_values = synthetic_samples[\"f_observations\"][0, 0]\n", + "\n", + "# Use an AutoDelta guide (point estimate - similar to maximum likelihood)\n", + "# For a full posterior, you could use AutoNormal or AutoDiagonalNormal\n", + "guide = AutoDelta(ou_poisson_model)\n", + "\n", + "# Set up SVI with Adam optimizer\n", + "optimizer = optax.adam(learning_rate=0.05)\n", + "\n", + "with Filter(ContinuousTimeDPFConfig(n_particles=2_500)):\n", + " svi = SVI(ou_poisson_model, guide, optimizer, loss=Trace_ELBO(), obs_times=obs_times, obs_values=obs_values)\n", + "\n", + " # Run SVI optimization\n", + " svi_key = jr.PRNGKey(1)\n", + " num_steps = 50\n", + "\n", + " svi_result = svi.run(svi_key, num_steps)\n", + "params = svi_result.params\n", + "\n", + "print(f\"True bias: {true_bias:.4f}\")\n", + "print(f\"Inferred bias: {params['bias_auto_loc']:.4f}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can visualize the ELBO (evidence lower bound) during optimization to ensure convergence:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10, 4))\n", + "plt.plot(svi_result.losses)\n", + "plt.xlabel(\"Iteration\")\n", + "plt.ylabel(\"ELBO Loss\")\n", + "plt.title(\"SVI Optimization Progress\")\n", + "sns.despine()\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Full Posterior Inference\n", + "\n", + "The `AutoDelta` guide gives us a point estimate (similar to maximum likelihood). To get a full posterior distribution with uncertainty quantification, we can use `AutoNormal` or `AutoDiagonalNormal` instead:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 50/50 [21:46<00:00, 26.13s/it, init loss: 4887.0552, avg. loss [49-50]: 2773.0498]\n" + ] + } + ], + "source": [ + "from numpyro.infer.autoguide import AutoDiagonalNormal\n", + "\n", + "# Use AutoDiagonalNormal for full posterior approximation\n", + "guide_normal = AutoDiagonalNormal(ou_poisson_model)\n", + "\n", + "# Set up SVI\n", + "optimizer_normal = optax.adam(learning_rate=0.05)\n", + "\n", + "with Filter(ContinuousTimeDPFConfig(n_particles=2_500)):\n", + " svi_normal = SVI(ou_poisson_model, guide_normal, optimizer_normal, loss=Trace_ELBO(), obs_times=obs_times, obs_values=obs_values)\n", + "\n", + " # Run SVI\n", + " svi_key_normal = jr.PRNGKey(2)\n", + " svi_result_normal = svi_normal.run(svi_key_normal, num_steps)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Draw posterior samples from the guide using its learned parameters `svi_result_normal.params`." + ] + }, { - "data": { - "image/png": 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", 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" + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "True bias: 3.9120\n", + "Posterior mean: 3.9546\n", + "Posterior std: 0.0833\n" + ] + } + ], + "source": [ + "# Get posterior samples\n", + "posterior_samples = guide_normal.sample_posterior(\n", + " jr.PRNGKey(3), \n", + " svi_result_normal.params, \n", + " sample_shape=(20,),\n", + " exclude_deterministic=True\n", + ")\n", + "\n", + "print(f\"True bias: {true_bias:.4f}\")\n", + "print(f\"Posterior mean: {posterior_samples['bias'].mean():.4f}\")\n", + "print(f\"Posterior std: {posterior_samples['bias'].std():.4f}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's visualize the posterior distribution:" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import arviz as az\n", + "\n", + "az.style.use(\"arviz-white\")\n", + "\n", + "az.plot_posterior(\n", + " posterior_samples[\"bias\"], \n", + " hdi_prob=0.95, \n", + " ref_val=float(true_bias)\n", + ")\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Summary\n", + "\n", + "In this tutorial, we demonstrated:\n", + "\n", + "1. **Writing custom observation models**: We created a `PoissonObservation` class that can be used with `dynestyx` by subclassing `ObservationModel` and returning a `numpyro` distribution.\n", + "\n", + "2. **Using differentiable particle filters**: For non-Gaussian observations, we used `Filter` with `filter_type=\"dpf\"` to compute the marginal likelihood needed for parameter inference.\n", + "\n", + "3. **Stochastic variational inference**: We used SVI with automatic guides (`AutoDelta` for point estimates and `AutoDiagonalNormal` for full posteriors) to efficiently infer the observation bias parameter.\n", + "\n", + "This workflow generalizes to other non-Gaussian observation models (e.g., binomial, negative binomial, von Mises) simply by changing the observation model class. The DPF enables gradient-based inference for these challenging problems where traditional methods like the EnKF may fail." ] - }, - "metadata": {}, - "output_type": "display_data" } - ], - "source": [ - "import arviz as az\n", - "\n", - "az.style.use(\"arviz-white\")\n", - "\n", - "az.plot_posterior(\n", - " posterior_samples[\"bias\"], \n", - " hdi_prob=0.95, \n", - " ref_val=float(true_bias)\n", - ")\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Summary\n", - "\n", - "In this tutorial, we demonstrated:\n", - "\n", - "1. **Writing custom observation models**: We created a `PoissonObservation` class that can be used with `dynestyx` by subclassing `ObservationModel` and returning a `numpyro` distribution.\n", - "\n", - "2. **Using differentiable particle filters**: For non-Gaussian observations, we used `Filter` with `filter_type=\"dpf\"` to compute the marginal likelihood needed for parameter inference.\n", - "\n", - "3. **Stochastic variational inference**: We used SVI with automatic guides (`AutoDelta` for point estimates and `AutoDiagonalNormal` for full posteriors) to efficiently infer the observation bias parameter.\n", - "\n", - "This workflow generalizes to other non-Gaussian observation models (e.g., binomial, negative binomial, von Mises) simply by changing the observation model class. The DPF enables gradient-based inference for these challenging problems where traditional methods like the EnKF may fail." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": ".venv (3.12.11)", - "language": "python", - "name": "python3" + ], + "metadata": { + "kernelspec": { + "display_name": ".venv (3.12.11)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.11" - } - }, - "nbformat": 4, - "nbformat_minor": 2 + "nbformat": 4, + "nbformat_minor": 2 } From 2e02f2f321fd9e5f91be71a3f8853ef60c373879 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Thu, 14 May 2026 15:35:07 -0400 Subject: [PATCH 19/28] improve API documentation for diffusions --- .../developer/models/diffusions.md | 59 ++++++++ .../public/models/core/diffusion.md | 133 +++++++++++++----- dynestyx/models/diffusions.py | 92 +++++++++++- mkdocs.yml | 1 + 4 files changed, 243 insertions(+), 42 deletions(-) create mode 100644 docs/api_reference/developer/models/diffusions.md diff --git a/docs/api_reference/developer/models/diffusions.md b/docs/api_reference/developer/models/diffusions.md new file mode 100644 index 00000000..76501d53 --- /dev/null +++ b/docs/api_reference/developer/models/diffusions.md @@ -0,0 +1,59 @@ +# Diffusions + +This page documents the diffusion internals used by continuous-time solvers, +discretizers, and backend integrations. + +## Overview + +Public model code should usually work with `FullDiffusion`, +`DiagonalDiffusion`, and `ScalarDiffusion` through +`ContinuousTimeStateEvolution(diffusion=...)`. + +Developer-facing code sometimes needs the lower-level evaluation layer: + +- `Diffusion.evaluate(...)` evaluates a structured diffusion object at a + concrete `(x, u, t)`. +- `EvaluatedDiffusion.as_matrix(...)` returns the corresponding matrix `L`. +- `EvaluatedDiffusion.apply(...)` applies that matrix to a Brownian increment. +- `resolve_metadata(...)` canonicalizes `bm_dim` and validates the coefficient + shape against `state_dim`. + +In other words, the public classes describe the structure of the diffusion, +while `EvaluatedDiffusion` is the solver-facing object used after a concrete +state, control, and time have been chosen. + +## API + +### `EvaluatedDiffusion` + +::: dynestyx.models.diffusions.EvaluatedDiffusion + options: + show_root_heading: false + +### `Diffusion` + +::: dynestyx.models.diffusions.Diffusion + options: + show_root_heading: false + filters: [] + +### `FullDiffusion` + +::: dynestyx.models.diffusions.FullDiffusion + options: + show_root_heading: false + filters: [] + +### `DiagonalDiffusion` + +::: dynestyx.models.diffusions.DiagonalDiffusion + options: + show_root_heading: false + filters: [] + +### `ScalarDiffusion` + +::: dynestyx.models.diffusions.ScalarDiffusion + options: + show_root_heading: false + filters: [] diff --git a/docs/api_reference/public/models/core/diffusion.md b/docs/api_reference/public/models/core/diffusion.md index 669925be..fd9bde84 100644 --- a/docs/api_reference/public/models/core/diffusion.md +++ b/docs/api_reference/public/models/core/diffusion.md @@ -25,6 +25,59 @@ pass the matrix/vector/scalar value directly. Reserve callable diffusion coefficients for cases where the coefficient genuinely depends on state, control, or time. +## Choosing a Diffusion Class + +- Use `ScalarDiffusion` when one scalar scale is enough. This is the most common + choice for isotropic diffusion. +- Use `DiagonalDiffusion` when each state coordinate should have its own scale + but the loading remains axis-aligned. +- Use `FullDiffusion` when you need to specify a genuinely matrix-valued loading. + +For `DiagonalDiffusion` and `ScalarDiffusion`, `bm_dim` determines whether the +state coordinates have independent Brownian drivers (`bm_dim = state_dim`) or +share a single Brownian driver (`bm_dim = 1`). + +## Construction + +Each diffusion class accepts either: + +- a constant coefficient, or +- a callable `(x, u, t) -> value`. + +### Constructor Arguments + +All three constructors take a first positional argument `coefficient`. + +- `FullDiffusion(coefficient, bm_dim=None)` + - `coefficient` may be: + - a constant array with trailing shape `(state_dim, bm_dim)`, or + - a callable `(x, u, t) -> array` with trailing shape `(state_dim, bm_dim)`. + - `bm_dim` is optional and is inferred automatically from the matrix shape when omitted. + +- `DiagonalDiffusion(coefficient, bm_dim)` + - `coefficient` may be: + - a constant vector with trailing shape `(state_dim,)`, or + - a callable `(x, u, t) -> array` with trailing shape `(state_dim,)`. + - `bm_dim` is required and must be either `1` or `state_dim`. + +- `ScalarDiffusion(coefficient, bm_dim)` + - `coefficient` may be: + - a scalar, + - a constant array with trailing shape `(1,)`, or + - a callable `(x, u, t) -> scalar_or_length_1_array`. + - `bm_dim` is required and must be either `1` or `state_dim`. + +Typical constant constructions look like: + +```python +import jax.numpy as jnp +from dynestyx import DiagonalDiffusion, FullDiffusion, ScalarDiffusion + +FullDiffusion(jnp.eye(2)) +DiagonalDiffusion(jnp.array([0.1, 0.2]), bm_dim=2) +ScalarDiffusion(0.1, bm_dim=2) +``` + ## Mathematical Interpretation ### `FullDiffusion` @@ -41,13 +94,7 @@ The SDE is dx_t = f(x_t, u_t, t)\,dt + L(x_t, u_t, t)\,dW_t. \] -This is the most general case. The process noise covariance is - -\[ -L(x_t, u_t, t)\,L(x_t, u_t, t)^\top, -\] - -which may be dense. +This is the most general case. ### `DiagonalDiffusion` @@ -62,14 +109,10 @@ Its interpretation depends on `bm_dim`. If `bm_dim = d_x`, the vector is interpreted as a diagonal matrix: \[ -L(x_t, u_t, t) = \mathrm{diag}(v(x_t, u_t, t)), +L = \mathrm{diag}(v(x_t, u_t, t)), \] -so each state coordinate receives its own independent Brownian driver and - -\[ -L L^\top = \mathrm{diag}(v_1^2, \ldots, v_{d_x}^2). -\] +so each state coordinate receives its own independent Brownian driver. If `bm_dim = 1`, the same vector is interpreted as a column loading vector: @@ -77,13 +120,7 @@ If `bm_dim = 1`, the same vector is interpreted as a column loading vector: L(x_t, u_t, t) = v(x_t, u_t, t) \in \mathbb{R}^{d_x \times 1}, \] -so all state coordinates share a single Brownian path. In that case, - -\[ -L L^\top = v v^\top, -\] - -which is rank 1. +so all state coordinates share a single Brownian path. ### `ScalarDiffusion` @@ -98,30 +135,19 @@ Its interpretation also depends on `bm_dim`. If `bm_dim = d_x`, it is interpreted as isotropic independent noise: \[ -L(x_t, u_t, t) = \sigma(x_t, u_t, t)\,I_{d_x}, +L = \sigma(x_t, u_t, t)\,I_{d_w} \] -so the process noise covariance is - -\[ -L L^\top = \sigma^2 I_{d_x}. -\] +with \(d_w = d_x\). If `bm_dim = 1`, it is interpreted as a shared scalar driver applied equally to every state coordinate: \[ -L(x_t, u_t, t) = \sigma(x_t, u_t, t)\,\mathbf{1}_{d_x}, +L = \sigma(x_t, u_t, t)\,\mathbf{1}_{d_x}, \] -viewed as a column vector in \(\mathbb{R}^{d_x \times 1}\). The resulting -covariance is - -\[ -L L^\top = \sigma^2 \mathbf{1}_{d_x}\mathbf{1}_{d_x}^\top, -\] - -which is again rank 1. +viewed as a column vector in \(\mathbb{R}^{d_x \times 1}\). ## Typical Usage @@ -153,26 +179,63 @@ state_evolution = ContinuousTimeStateEvolution( ) ``` +```python +import jax.numpy as jnp + +state_evolution = ContinuousTimeStateEvolution( + drift=lambda x, u, t: -x, + diffusion=ScalarDiffusion(lambda x, u, t: 0.1 + 0.05 * jnp.tanh(x[0]), bm_dim=2), +) +``` + ## API ::: dynestyx.models.diffusions.Diffusion options: show_root_heading: false + filters: + - "!^evaluate_value$" + - "!^resolve_metadata$" + - "!^evaluate$" + - "!^as_matrix$" + - "!^gram_matrix$" + - "!^apply$" ### `FullDiffusion` ::: dynestyx.models.diffusions.FullDiffusion options: show_root_heading: false + filters: + - "!^evaluate_value$" + - "!^resolve_metadata$" + - "!^evaluate$" + - "!^as_matrix$" + - "!^gram_matrix$" + - "!^apply$" ### `DiagonalDiffusion` ::: dynestyx.models.diffusions.DiagonalDiffusion options: show_root_heading: false + filters: + - "!^evaluate_value$" + - "!^resolve_metadata$" + - "!^evaluate$" + - "!^as_matrix$" + - "!^gram_matrix$" + - "!^apply$" ### `ScalarDiffusion` ::: dynestyx.models.diffusions.ScalarDiffusion options: show_root_heading: false + filters: + - "!^evaluate_value$" + - "!^resolve_metadata$" + - "!^evaluate$" + - "!^as_matrix$" + - "!^gram_matrix$" + - "!^apply$" diff --git a/dynestyx/models/diffusions.py b/dynestyx/models/diffusions.py index 7fb752c1..a959d622 100644 --- a/dynestyx/models/diffusions.py +++ b/dynestyx/models/diffusions.py @@ -18,29 +18,52 @@ class EvaluatedDiffusion(NamedTuple): - """A diffusion object evaluated at a specific `(x, u, t)`.""" + """A diffusion coefficient evaluated at a specific ``(x, u, t)``. + + This is primarily a developer-facing helper used by solvers and backend + integrations. It pairs a structured ``Diffusion`` object with the concrete + value of its coefficient at one state, control, and time. + """ diffusion: Diffusion value: Array def as_matrix(self, *, state_dim: int) -> Array: + """Return the evaluated diffusion coefficient as a matrix ``L``.""" return self.diffusion._value_as_matrix(self.value, state_dim=state_dim) def gram_matrix(self, *, state_dim: int) -> Array: - """Return the diffusion Gram matrix ``L L^T`` at the evaluated point.""" + """L L^T.""" return self.diffusion._value_gram_matrix(self.value, state_dim=state_dim) def apply(self, dw: Array, *, state_dim: int) -> Array: + """Return ``L @ dw`` using the structured diffusion representation.""" return self.diffusion._apply_value(self.value, dw, state_dim=state_dim) class Diffusion(eqx.Module): """Base class for diffusion coefficients in SDEs. - A diffusion encapsulates both the numeric coefficient `L(x, u, t)` and the + A diffusion encapsulates both the numeric coefficient ``L(x, u, t)`` and the structural interpretation of that coefficient inside the SDE - `dx_t = f(x_t, u_t, t) dt + L(x_t, u_t, t) dW_t`. + ``dx_t = f(x_t, u_t, t) dt + L(x_t, u_t, t) dW_t``. + + Most users should instantiate one of the concrete subclasses: + + - ``FullDiffusion`` for an arbitrary matrix-valued coefficient. + - ``DiagonalDiffusion`` for axis-aligned loadings. + - ``ScalarDiffusion`` for isotropic or shared-driver noise. + + The ``coefficient`` may be either: + + - a constant array or scalar, for time-homogeneous diffusion, or + - a callable ``(x, u, t) -> value`` for state-, control-, or time-dependent diffusion. + + ``bm_dim`` is the Brownian dimension ``d_w``. For ``FullDiffusion`` it can be + inferred from the matrix shape. For ``DiagonalDiffusion`` and + ``ScalarDiffusion`` it must be specified explicitly and must be either ``1`` or + ``state_dim``. """ coefficient: DiffusionSpec @@ -66,6 +89,7 @@ def evaluate_value( u: Control | None, t: Time, ) -> Array: + """Return the raw coefficient value at ``(x, u, t)``.""" if callable(self.coefficient): return jnp.asarray(self.coefficient(x, u, t)) return cast(Array, self.coefficient) @@ -78,6 +102,7 @@ def resolve_metadata( u_probe: Control | None, t_probe: Time, ) -> Diffusion: + """Validate coefficient shape information and resolve diffusion metadata.""" raise NotImplementedError def evaluate( @@ -87,6 +112,7 @@ def evaluate( u: Control | None, t: Time, ) -> EvaluatedDiffusion: + """Evaluate the diffusion at ``(x, u, t)``.""" return EvaluatedDiffusion(self, self.evaluate_value(x=x, u=u, t=t)) def as_matrix( @@ -97,6 +123,7 @@ def as_matrix( t: Time, state_dim: int, ) -> Array: + """Return the matrix-valued diffusion coefficient ``L(x, u, t)``.""" return self.evaluate(x=x, u=u, t=t).as_matrix(state_dim=state_dim) def gram_matrix( @@ -119,6 +146,7 @@ def apply( t: Time, state_dim: int, ) -> Array: + """Apply the diffusion coefficient to a Brownian increment ``dw``.""" return self.evaluate(x=x, u=u, t=t).apply(dw, state_dim=state_dim) def _with_bm_dim(self, bm_dim: int) -> Diffusion: @@ -146,7 +174,21 @@ def _apply_value(self, value: Array, dw: Array, *, state_dim: int) -> Array: class FullDiffusion(Diffusion): - """General matrix-valued diffusion coefficient `L(x, u, t)`.""" + """General matrix-valued diffusion coefficient. + + Use ``FullDiffusion`` when you want to specify the diffusion matrix + ``L(x, u, t)`` directly. + + Args: + coefficient: Either a constant array with trailing shape + ``(..., state_dim, bm_dim)`` or a callable ``(x, u, t) -> array`` + with that trailing shape. + bm_dim: Optional Brownian dimension. If omitted for a constant + coefficient, it is inferred from the trailing matrix dimension. + + This is the most general public diffusion class. Prefer it when your model + genuinely needs a dense or otherwise unstructured loading matrix. + """ def _validate_init(self) -> None: super()._validate_init() @@ -199,7 +241,25 @@ def _apply_value(self, value: Array, dw: Array, *, state_dim: int) -> Array: class DiagonalDiffusion(Diffusion): - """Vector-valued diffusion with diagonal or shared-driver interpretation.""" + """Vector-valued diffusion with diagonal or shared-driver interpretation. + + Use ``DiagonalDiffusion(v, bm_dim=...)`` when the diffusion is naturally + parameterized by a vector ``v`` of length ``state_dim``. + + Args: + coefficient: Either a constant vector with trailing shape + ``(..., state_dim)`` or a callable ``(x, u, t) -> array`` with that + trailing shape. + bm_dim: Brownian dimension. Must be either ``1`` or ``state_dim``. + + - If ``bm_dim = state_dim``, the vector is interpreted as the diagonal of + ``L = diag(v)``. + - If ``bm_dim = 1``, the vector is interpreted as a column loading vector, + so all state coordinates share one Brownian driver. + + This is often the right public API choice when each state coordinate has its + own scale but you do not want to write out a full matrix. + """ def _validate_init(self) -> None: super()._validate_init() @@ -261,7 +321,25 @@ def _apply_value(self, value: Array, dw: Array, *, state_dim: int) -> Array: class ScalarDiffusion(Diffusion): - """Scalar-valued diffusion with isotropic or shared-driver interpretation.""" + """Scalar-valued diffusion with isotropic or shared-driver interpretation. + + Use ``ScalarDiffusion(sigma, bm_dim=...)`` when the diffusion is controlled + by a single scalar scale ``sigma``. + + Args: + coefficient: Either a scalar, a constant array with trailing shape + ``(..., 1)``, or a callable ``(x, u, t) -> scalar_or_length_1_array``. + bm_dim: Brownian dimension. Must be either ``1`` or ``state_dim``. + + - If ``bm_dim = state_dim``, this represents isotropic diffusion + ``L = sigma I``. + - If ``bm_dim = 1``, this represents a shared scalar driver applied equally + to every state coordinate. + + This is typically the simplest public API choice for constant isotropic + diffusion, and is usually preferable to writing ``sigma * eye(state_dim)`` + by hand. + """ def _validate_init(self) -> None: super()._validate_init() diff --git a/mkdocs.yml b/mkdocs.yml index edaa341d..184b12bd 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -89,6 +89,7 @@ nav: - Overview: api_reference/developer/index.md - Models: - Core Models: api_reference/developer/models/core_models.md + - Diffusions: api_reference/developer/models/diffusions.md - Specialized Models: api_reference/developer/models/specialized_models.md - Checkers: api_reference/developer/models/checkers.md - Inference: From 740750e35241d1d77788e46ebfdc7999f85e8452 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Thu, 14 May 2026 16:12:13 -0400 Subject: [PATCH 20/28] improve API documentation for diffusions --- .../public/models/core/diffusion.md | 158 +++++++++--------- 1 file changed, 75 insertions(+), 83 deletions(-) diff --git a/docs/api_reference/public/models/core/diffusion.md b/docs/api_reference/public/models/core/diffusion.md index fd9bde84..586612a7 100644 --- a/docs/api_reference/public/models/core/diffusion.md +++ b/docs/api_reference/public/models/core/diffusion.md @@ -25,113 +25,112 @@ pass the matrix/vector/scalar value directly. Reserve callable diffusion coefficients for cases where the coefficient genuinely depends on state, control, or time. -## Choosing a Diffusion Class +## `Diffusion` -- Use `ScalarDiffusion` when one scalar scale is enough. This is the most common - choice for isotropic diffusion. -- Use `DiagonalDiffusion` when each state coordinate should have its own scale - but the loading remains axis-aligned. -- Use `FullDiffusion` when you need to specify a genuinely matrix-valued loading. - -For `DiagonalDiffusion` and `ScalarDiffusion`, `bm_dim` determines whether the -state coordinates have independent Brownian drivers (`bm_dim = state_dim`) or -share a single Brownian driver (`bm_dim = 1`). +`Diffusion` is the common base class for structured diffusion coefficients. +Most users should instantiate one of its public subclasses instead of using +`Diffusion` directly: -## Construction +- Use `ScalarDiffusion` when one scalar scale is enough. This is the most common choice for isotropic diffusion. +- Use `DiagonalDiffusion` when each state coordinate should have its own scale but the loading remains axis-aligned. +- Use `FullDiffusion` when you need to specify a genuinely matrix-valued loading. -Each diffusion class accepts either: +Each class accepts either: - a constant coefficient, or - a callable `(x, u, t) -> value`. -### Constructor Arguments +### `FullDiffusion` + +Use `FullDiffusion(coefficient, bm_dim=None)` when you want to specify the +matrix-valued diffusion coefficient directly. + +Accepted `coefficient` forms: -All three constructors take a first positional argument `coefficient`. +- a constant array with trailing shape `(state_dim, bm_dim)`, or +- a callable `(x, u, t) -> array` with trailing shape `(state_dim, bm_dim)`. -- `FullDiffusion(coefficient, bm_dim=None)` - - `coefficient` may be: - - a constant array with trailing shape `(state_dim, bm_dim)`, or - - a callable `(x, u, t) -> array` with trailing shape `(state_dim, bm_dim)`. - - `bm_dim` is optional and is inferred automatically from the matrix shape when omitted. +If `coefficient` is constant, `bm_dim` is inferred automatically when omitted. -- `DiagonalDiffusion(coefficient, bm_dim)` - - `coefficient` may be: - - a constant vector with trailing shape `(state_dim,)`, or - - a callable `(x, u, t) -> array` with trailing shape `(state_dim,)`. - - `bm_dim` is required and must be either `1` or `state_dim`. +Mathematically, `FullDiffusion` represents -- `ScalarDiffusion(coefficient, bm_dim)` - - `coefficient` may be: - - a scalar, - - a constant array with trailing shape `(1,)`, or - - a callable `(x, u, t) -> scalar_or_length_1_array`. - - `bm_dim` is required and must be either `1` or `state_dim`. +\[ +L(x_t, u_t, t) \in \mathbb{R}^{d_x \times d_w}. +\] -Typical constant constructions look like: +Example: ```python import jax.numpy as jnp -from dynestyx import DiagonalDiffusion, FullDiffusion, ScalarDiffusion +from dynestyx import ContinuousTimeStateEvolution, FullDiffusion -FullDiffusion(jnp.eye(2)) -DiagonalDiffusion(jnp.array([0.1, 0.2]), bm_dim=2) -ScalarDiffusion(0.1, bm_dim=2) +state_evolution = ContinuousTimeStateEvolution( + drift=lambda x, u, t: -x, + diffusion=FullDiffusion(jnp.eye(2)), +) ``` -## Mathematical Interpretation - -### `FullDiffusion` - -`FullDiffusion` represents an arbitrary matrix-valued diffusion coefficient: +### `DiagonalDiffusion` -\[ -L(x_t, u_t, t) \in \mathbb{R}^{d_x \times d_w}. -\] +Use `DiagonalDiffusion(coefficient, bm_dim)` when the diffusion is naturally +parameterized by a vector of state-wise loadings. -The SDE is +Accepted `coefficient` forms: -\[ -dx_t = f(x_t, u_t, t)\,dt + L(x_t, u_t, t)\,dW_t. -\] +- a constant vector with trailing shape `(state_dim,)`, or +- a callable `(x, u, t) -> array` with trailing shape `(state_dim,)`. -This is the most general case. +`bm_dim` is required and must be either `1` or `state_dim`. -### `DiagonalDiffusion` - -`DiagonalDiffusion` represents a vector-valued coefficient +Mathematically, `DiagonalDiffusion` represents a vector-valued coefficient \[ v(x_t, u_t, t) \in \mathbb{R}^{d_x}. \] -Its interpretation depends on `bm_dim`. - If `bm_dim = d_x`, the vector is interpreted as a diagonal matrix: \[ -L = \mathrm{diag}(v(x_t, u_t, t)), +L = \mathrm{diag}(v(x_t, u_t, t)). \] -so each state coordinate receives its own independent Brownian driver. - If `bm_dim = 1`, the same vector is interpreted as a column loading vector: \[ -L(x_t, u_t, t) = v(x_t, u_t, t) \in \mathbb{R}^{d_x \times 1}, +L = v(x_t, u_t, t) \in \mathbb{R}^{d_x \times 1}. \] -so all state coordinates share a single Brownian path. +Example: + +```python +import jax.numpy as jnp +from dynestyx import ContinuousTimeStateEvolution, DiagonalDiffusion + +state_evolution = ContinuousTimeStateEvolution( + drift=lambda x, u, t: -x, + diffusion=DiagonalDiffusion(jnp.array([0.1, 0.2]), bm_dim=2), +) +``` ### `ScalarDiffusion` -`ScalarDiffusion` represents a scalar-valued coefficient +Use `ScalarDiffusion(coefficient, bm_dim)` when one scalar scale is enough. +This is usually the simplest choice for isotropic diffusion. + +Accepted `coefficient` forms: + +- a scalar, +- a constant array with trailing shape `(1,)`, or +- a callable `(x, u, t) -> scalar_or_length_1_array`. + +`bm_dim` is required and must be either `1` or `state_dim`. + +Mathematically, `ScalarDiffusion` represents a scalar-valued coefficient \[ \sigma(x_t, u_t, t) \in \mathbb{R}. \] -Its interpretation also depends on `bm_dim`. - If `bm_dim = d_x`, it is interpreted as isotropic independent noise: \[ @@ -149,29 +148,10 @@ L = \sigma(x_t, u_t, t)\,\mathbf{1}_{d_x}, viewed as a column vector in \(\mathbb{R}^{d_x \times 1}\). -## Typical Usage - -```python -import jax.numpy as jnp -from dynestyx import ContinuousTimeStateEvolution, FullDiffusion - -state_evolution = ContinuousTimeStateEvolution( - drift=lambda x, u, t: -x, - diffusion=FullDiffusion(jnp.eye(2)), -) -``` +Constant example: ```python -from dynestyx import DiagonalDiffusion - -state_evolution = ContinuousTimeStateEvolution( - drift=lambda x, u, t: -x, - diffusion=DiagonalDiffusion(jnp.array([0.1, 0.2]), bm_dim=2), -) -``` - -```python -from dynestyx import ScalarDiffusion +from dynestyx import ContinuousTimeStateEvolution, ScalarDiffusion state_evolution = ContinuousTimeStateEvolution( drift=lambda x, u, t: -x, @@ -179,20 +159,29 @@ state_evolution = ContinuousTimeStateEvolution( ) ``` +Callable example: + ```python import jax.numpy as jnp +from dynestyx import ContinuousTimeStateEvolution, ScalarDiffusion state_evolution = ContinuousTimeStateEvolution( drift=lambda x, u, t: -x, - diffusion=ScalarDiffusion(lambda x, u, t: 0.1 + 0.05 * jnp.tanh(x[0]), bm_dim=2), + diffusion=ScalarDiffusion( + lambda x, u, t: 0.1 + 0.05 * jnp.tanh(x[0]), + bm_dim=2, + ), ) ``` ## API +### `Diffusion` + ::: dynestyx.models.diffusions.Diffusion options: show_root_heading: false + show_root_toc_entry: false filters: - "!^evaluate_value$" - "!^resolve_metadata$" @@ -206,6 +195,7 @@ state_evolution = ContinuousTimeStateEvolution( ::: dynestyx.models.diffusions.FullDiffusion options: show_root_heading: false + show_root_toc_entry: false filters: - "!^evaluate_value$" - "!^resolve_metadata$" @@ -219,6 +209,7 @@ state_evolution = ContinuousTimeStateEvolution( ::: dynestyx.models.diffusions.DiagonalDiffusion options: show_root_heading: false + show_root_toc_entry: false filters: - "!^evaluate_value$" - "!^resolve_metadata$" @@ -232,6 +223,7 @@ state_evolution = ContinuousTimeStateEvolution( ::: dynestyx.models.diffusions.ScalarDiffusion options: show_root_heading: false + show_root_toc_entry: false filters: - "!^evaluate_value$" - "!^resolve_metadata$" From 2ebb45c5f5bdf7ee97a2813ca57401f338245d88 Mon Sep 17 00:00:00 2001 From: Matt Levine Date: Thu, 14 May 2026 20:00:11 -0400 Subject: [PATCH 21/28] Update dynestyx/models/diffusions.py Co-authored-by: Dan Waxman --- dynestyx/models/diffusions.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dynestyx/models/diffusions.py b/dynestyx/models/diffusions.py index a959d622..ac9075ae 100644 --- a/dynestyx/models/diffusions.py +++ b/dynestyx/models/diffusions.py @@ -164,7 +164,7 @@ def _validate_init(self) -> None: raise ValueError(f"bm_dim must be positive. Got bm_dim={self.bm_dim}.") def _value_as_matrix(self, value: Array, *, state_dim: int) -> Array: - raise NotImplementedError + raise NotImplementedError("Please don't construct `Diffusion` directly; instead instantiate one of its subclasses (e.g., `FullDiffusion`, `DiagonalDiffusion`, or `ScalarDiffusion`)") def _value_gram_matrix(self, value: Array, *, state_dim: int) -> Array: raise NotImplementedError From 3612c92a0430d64d5b2153659f0b10078eb32a37 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Thu, 14 May 2026 21:01:38 -0400 Subject: [PATCH 22/28] simplify code and improve docs --- .../developer/models/core_models.md | 2 +- .../developer/models/diffusions.md | 2 +- .../core/continuous_time_state_evolution.md | 2 +- .../public/models/core/diffusion.md | 76 ++++++---------- .../cd_dynamax/continuous_filter.py | 18 ---- .../cd_dynamax/discrete_filter.py | 14 --- .../integrations/cd_dynamax/utils.py | 21 ++--- dynestyx/models/core.py | 88 ++++++++++--------- dynestyx/models/diffusions.py | 15 ++-- dynestyx/solvers/sde.py | 5 +- 10 files changed, 86 insertions(+), 157 deletions(-) diff --git a/docs/api_reference/developer/models/core_models.md b/docs/api_reference/developer/models/core_models.md index 1f86d15e..f7626794 100644 --- a/docs/api_reference/developer/models/core_models.md +++ b/docs/api_reference/developer/models/core_models.md @@ -7,7 +7,7 @@ classes: - `StochasticContinuousTimeStateEvolution` Most users should continue to construct `ContinuousTimeStateEvolution` directly and let -`DynamicalModel` canonicalize it internally. +`DynamicalModel` refine it internally. ::: dynestyx.models.core options: diff --git a/docs/api_reference/developer/models/diffusions.md b/docs/api_reference/developer/models/diffusions.md index 76501d53..0c02900c 100644 --- a/docs/api_reference/developer/models/diffusions.md +++ b/docs/api_reference/developer/models/diffusions.md @@ -15,7 +15,7 @@ Developer-facing code sometimes needs the lower-level evaluation layer: concrete `(x, u, t)`. - `EvaluatedDiffusion.as_matrix(...)` returns the corresponding matrix `L`. - `EvaluatedDiffusion.apply(...)` applies that matrix to a Brownian increment. -- `resolve_metadata(...)` canonicalizes `bm_dim` and validates the coefficient +- `resolve_metadata(...)` resolves `bm_dim` and validates the coefficient shape against `state_dim`. In other words, the public classes describe the structure of the diffusion, diff --git a/docs/api_reference/public/models/core/continuous_time_state_evolution.md b/docs/api_reference/public/models/core/continuous_time_state_evolution.md index 4e25266a..1d15e0b3 100644 --- a/docs/api_reference/public/models/core/continuous_time_state_evolution.md +++ b/docs/api_reference/public/models/core/continuous_time_state_evolution.md @@ -5,7 +5,7 @@ state evolution. Most users should instantiate this class directly and pass an o `diffusion=` built from [`FullDiffusion`](./diffusion.md), [`DiagonalDiffusion`](./diffusion.md), or [`ScalarDiffusion`](./diffusion.md). -Internally, `DynamicalModel` canonicalizes continuous-time dynamics to refined +Internally, `DynamicalModel` refines continuous-time dynamics to deterministic and stochastic subclasses. Those specialized classes are intended for developer-facing integrations and are documented in the developer API rather than the public tutorials. diff --git a/docs/api_reference/public/models/core/diffusion.md b/docs/api_reference/public/models/core/diffusion.md index 586612a7..d1ee5918 100644 --- a/docs/api_reference/public/models/core/diffusion.md +++ b/docs/api_reference/public/models/core/diffusion.md @@ -16,9 +16,16 @@ where: Dynestyx exposes three structured diffusion classes: -- `FullDiffusion`: general matrix-valued diffusion \(L \in \mathbb{R}^{d_x \times d_w}\) -- `DiagonalDiffusion`: vector-valued diffusion \(v \in \mathbb{R}^{d_x}\) -- `ScalarDiffusion`: scalar-valued diffusion \(\sigma \in \mathbb{R}\) +- If your diffusion has the form \(L = \sigma I_{d_w}\) with \(d_w = d_x\), use `ScalarDiffusion(sigma, bm_dim=state_dim)`. +- If your diffusion has the form \(L = \sigma \mathbf{1}_{d_x}\), use `ScalarDiffusion(sigma, bm_dim=1)`. +- If your diffusion has the form \(L = \mathrm{diag}(v)\), use `DiagonalDiffusion(v, bm_dim=state_dim)`. +- If your diffusion has the form \(L = v \in \mathbb{R}^{d_x \times 1}\), use `DiagonalDiffusion(v, bm_dim=1)`. +- If your diffusion is a general matrix \(L \in \mathbb{R}^{d_x \times d_w}\), use `FullDiffusion(L)`. + +The same constructors also accept callables `(x, u, t) -> value` instead of +constants. For example, if \(L(x_t, u_t, t) = \sigma(x_t) I_{d_w}\), use +`ScalarDiffusion(lambda x, u, t: sigma(x), bm_dim=state_dim)`. The same pattern +applies across `ScalarDiffusion`, `DiagonalDiffusion`, and `FullDiffusion`. In practice, many models use a constant diffusion coefficient. In those cases, pass the matrix/vector/scalar value directly. Reserve callable diffusion @@ -42,7 +49,10 @@ Each class accepts either: ### `FullDiffusion` -Use `FullDiffusion(coefficient, bm_dim=None)` when you want to specify the +Mathematically, `FullDiffusion` represents +\(L(x_t, u_t, t) \in \mathbb{R}^{d_x \times d_w}\). + +Use `FullDiffusion(coefficient, bm_dim=None)` when you want to specify this matrix-valued diffusion coefficient directly. Accepted `coefficient` forms: @@ -52,12 +62,6 @@ Accepted `coefficient` forms: If `coefficient` is constant, `bm_dim` is inferred automatically when omitted. -Mathematically, `FullDiffusion` represents - -\[ -L(x_t, u_t, t) \in \mathbb{R}^{d_x \times d_w}. -\] - Example: ```python @@ -72,6 +76,11 @@ state_evolution = ContinuousTimeStateEvolution( ### `DiagonalDiffusion` +Mathematically, `DiagonalDiffusion` represents a vector-valued coefficient +\(v(x_t, u_t, t) \in \mathbb{R}^{d_x}\). If `bm_dim = d_x`, this means +\(L = \mathrm{diag}(v(x_t, u_t, t))\). If `bm_dim = 1`, this means +\(L = v(x_t, u_t, t) \in \mathbb{R}^{d_x \times 1}\). + Use `DiagonalDiffusion(coefficient, bm_dim)` when the diffusion is naturally parameterized by a vector of state-wise loadings. @@ -82,24 +91,6 @@ Accepted `coefficient` forms: `bm_dim` is required and must be either `1` or `state_dim`. -Mathematically, `DiagonalDiffusion` represents a vector-valued coefficient - -\[ -v(x_t, u_t, t) \in \mathbb{R}^{d_x}. -\] - -If `bm_dim = d_x`, the vector is interpreted as a diagonal matrix: - -\[ -L = \mathrm{diag}(v(x_t, u_t, t)). -\] - -If `bm_dim = 1`, the same vector is interpreted as a column loading vector: - -\[ -L = v(x_t, u_t, t) \in \mathbb{R}^{d_x \times 1}. -\] - Example: ```python @@ -114,6 +105,12 @@ state_evolution = ContinuousTimeStateEvolution( ### `ScalarDiffusion` +Mathematically, `ScalarDiffusion` represents a scalar-valued coefficient +\(\sigma(x_t, u_t, t) \in \mathbb{R}\). If `bm_dim = d_x`, this means +\(L = \sigma(x_t, u_t, t)\,I_{d_w}\) with \(d_w = d_x\). If `bm_dim = 1`, this +means \(L = \sigma(x_t, u_t, t)\,\mathbf{1}_{d_x}\), viewed as a column vector +in \(\mathbb{R}^{d_x \times 1}\). + Use `ScalarDiffusion(coefficient, bm_dim)` when one scalar scale is enough. This is usually the simplest choice for isotropic diffusion. @@ -125,29 +122,6 @@ Accepted `coefficient` forms: `bm_dim` is required and must be either `1` or `state_dim`. -Mathematically, `ScalarDiffusion` represents a scalar-valued coefficient - -\[ -\sigma(x_t, u_t, t) \in \mathbb{R}. -\] - -If `bm_dim = d_x`, it is interpreted as isotropic independent noise: - -\[ -L = \sigma(x_t, u_t, t)\,I_{d_w} -\] - -with \(d_w = d_x\). - -If `bm_dim = 1`, it is interpreted as a shared scalar driver applied equally to -every state coordinate: - -\[ -L = \sigma(x_t, u_t, t)\,\mathbf{1}_{d_x}, -\] - -viewed as a column vector in \(\mathbb{R}^{d_x \times 1}\). - Constant example: ```python diff --git a/dynestyx/inference/integrations/cd_dynamax/continuous_filter.py b/dynestyx/inference/integrations/cd_dynamax/continuous_filter.py index cd15a416..6fc63b8b 100644 --- a/dynestyx/inference/integrations/cd_dynamax/continuous_filter.py +++ b/dynestyx/inference/integrations/cd_dynamax/continuous_filter.py @@ -39,18 +39,6 @@ ) -def _coerce_to_param_dtype(params, *arrays): - """Cast arrays to the first inexact dtype found in a parameter pytree.""" - dtype = None - for leaf in jax.tree.leaves(params): - if isinstance(leaf, jax.Array) and jnp.issubdtype(leaf.dtype, jnp.inexact): - dtype = leaf.dtype - break - if dtype is None: - return arrays - return tuple(jnp.asarray(arr, dtype=dtype) for arr in arrays) - - def _config_to_cd_dynamax_filter_kwargs( config: ContinuousTimeFilterConfig, params, @@ -167,9 +155,6 @@ def _run_linear_kf( ) -> PosteriorGSSMFiltered: """Run exact continuous-discrete KF (AffineLinearDrift + constant diffusion + LinearGaussianObservation).""" params = dsx_to_cdlgssm_params(dynamics) - obs_times, obs_values, ctrl_values = _coerce_to_param_dtype( - params, obs_times, obs_values, ctrl_values - ) cd_model = ContDiscreteLinearGaussianSSM( state_dim=dynamics.state_dim, emission_dim=dynamics.observation_dim, @@ -235,9 +220,6 @@ def compute_continuous_filter( ) params, _ = dsx_to_cd_dynamax(dynamics, cd_model=cd_dynamax_model) - obs_values, obs_times_arr, ctrl_vals = _coerce_to_param_dtype( - params, obs_values, obs_times_arr, ctrl_vals - ) filter_kwargs = _config_to_cd_dynamax_filter_kwargs( filter_config, params, obs_values, obs_times_arr, ctrl_vals, key ) diff --git a/dynestyx/inference/integrations/cd_dynamax/discrete_filter.py b/dynestyx/inference/integrations/cd_dynamax/discrete_filter.py index c7e74638..61398247 100644 --- a/dynestyx/inference/integrations/cd_dynamax/discrete_filter.py +++ b/dynestyx/inference/integrations/cd_dynamax/discrete_filter.py @@ -35,18 +35,6 @@ from dynestyx.utils import _should_record_field -def _coerce_to_param_dtype(params, *arrays): - """Cast arrays to the first inexact dtype found in a parameter pytree.""" - dtype = None - for leaf in jax.tree.leaves(params): - if isinstance(leaf, jax.Array) and jnp.issubdtype(leaf.dtype, jnp.inexact): - dtype = leaf.dtype - break - if dtype is None: - return arrays - return tuple(jnp.asarray(arr, dtype=dtype) for arr in arrays) - - def _lti_to_lgssm_params(dynamics: DynamicalModel): """Build dynamax ParamsLGSSM from LinearGaussianSSM.initialize for an LTI model.""" state_dim = dynamics.state_dim @@ -117,12 +105,10 @@ def compute_cd_dynamax_discrete_filter( if isinstance(filter_config, KFConfig): params = _lti_to_lgssm_params(dynamics) - emissions, inputs = _coerce_to_param_dtype(params, emissions, inputs) return lgssm_filter(params, emissions, inputs=inputs) # EKF and UKF share the same nonlinear params representation. params_nl = gaussian_to_nlgssm_params(dynamics) - emissions, inputs = _coerce_to_param_dtype(params_nl, emissions, inputs) if isinstance(filter_config, EKFConfig): return extended_kalman_filter(params_nl, emissions, inputs=inputs) diff --git a/dynestyx/inference/integrations/cd_dynamax/utils.py b/dynestyx/inference/integrations/cd_dynamax/utils.py index fa141ee4..4b01241f 100644 --- a/dynestyx/inference/integrations/cd_dynamax/utils.py +++ b/dynestyx/inference/integrations/cd_dynamax/utils.py @@ -39,6 +39,11 @@ def _normalize_cd_dynamax_diffusion( pad trailing Brownian columns with zeros to match `(state_dim, state_dim)`. Diffusion with `bm_dim > state_dim` is rejected. """ + if state_evolution.bm_dim > state_dim: + raise ValueError( + "Continuous cd-dynamax filters require bm_dim <= state_dim. " + f"Got state_dim={state_dim}, bm_dim={state_evolution.bm_dim}." + ) def _wrapped(x, u, t): L = state_evolution.diffusion.as_matrix(x=x, u=u, t=t, state_dim=state_dim) @@ -56,18 +61,6 @@ def _wrapped(x, u, t): return _wrapped -def _validate_cd_dynamax_continuous_diffusion( - state_evolution: StochasticContinuousTimeStateEvolution, - state_dim: int, -) -> None: - """Validate continuous cd-dynamax diffusion compatibility from resolved metadata.""" - if state_evolution.bm_dim > state_dim: - raise ValueError( - "Continuous cd-dynamax filters require bm_dim <= state_dim. " - f"Got state_dim={state_dim}, bm_dim={state_evolution.bm_dim}." - ) - - class _ConstantFunction(eqx.Module): value: Any @@ -287,10 +280,6 @@ def dsx_to_cd_dynamax( } ) if isinstance(state_evo, StochasticContinuousTimeStateEvolution): - _validate_cd_dynamax_continuous_diffusion( - state_evo, - dsx_model.state_dim, - ) diffusion_coeff = _normalize_cd_dynamax_diffusion( state_evo, dsx_model.state_dim, diff --git a/dynestyx/models/core.py b/dynestyx/models/core.py index b0c1c6b3..7df6216f 100644 --- a/dynestyx/models/core.py +++ b/dynestyx/models/core.py @@ -1,5 +1,7 @@ """Core interfaces and base classes for dynamical models.""" +from __future__ import annotations + from collections.abc import Callable from typing import Any, Protocol @@ -92,7 +94,9 @@ class DynamicalModel(eqx.Module): initial_condition: Distribution state_evolution: ( - Callable[[State, Control, Time], State] + ContinuousTimeStateEvolution + | DiscreteTimeStateEvolution + | Callable[[State, Control, Time], State] | Callable[[State, Control, Time, Time], State] ) observation_model: Callable[[State, Control, Time], Distribution] @@ -160,29 +164,26 @@ def __init__( # Skip shape validation when inside a numpyro plate context, since # batched parameters produce shapes that don't match unbatched expectations. - def _canonicalize_continuous_state_evolution( + def _refine_continuous_state_evolution( + current_state_evolution: ContinuousTimeStateEvolution, *, x_probe: State, u_probe: Control | None, t_probe: Time, - ) -> None: + ) -> ContinuousTimeStateEvolution: if not inferred_continuous_time: - return - diffusion = state_evolution.diffusion + return current_state_evolution + diffusion = current_state_evolution.diffusion if diffusion is None: - if not isinstance( - state_evolution, DeterministicContinuousTimeStateEvolution + if isinstance( + current_state_evolution, DeterministicContinuousTimeStateEvolution ): - object.__setattr__( - self, - "state_evolution", - DeterministicContinuousTimeStateEvolution( - drift=state_evolution.drift, - potential=state_evolution.potential, - use_negative_gradient=state_evolution.use_negative_gradient, - ), - ) - return + return current_state_evolution + return DeterministicContinuousTimeStateEvolution( + drift=current_state_evolution.drift, + potential=current_state_evolution.potential, + use_negative_gradient=current_state_evolution.use_negative_gradient, + ) resolved_diffusion = diffusion.resolve_metadata( state_dim=inferred_state_dim, @@ -191,21 +192,21 @@ def _canonicalize_continuous_state_evolution( t_probe=t_probe, ) if ( - isinstance(state_evolution, StochasticContinuousTimeStateEvolution) - and state_evolution.diffusion is resolved_diffusion + isinstance( + current_state_evolution, StochasticContinuousTimeStateEvolution + ) + and current_state_evolution.diffusion is resolved_diffusion ): - return - object.__setattr__( - self, - "state_evolution", - StochasticContinuousTimeStateEvolution( - drift=state_evolution.drift, - potential=state_evolution.potential, - use_negative_gradient=state_evolution.use_negative_gradient, - diffusion=resolved_diffusion, - ), + return current_state_evolution + return StochasticContinuousTimeStateEvolution( + drift=current_state_evolution.drift, + potential=current_state_evolution.potential, + use_negative_gradient=current_state_evolution.use_negative_gradient, + diffusion=resolved_diffusion, ) + resolved_state_evolution = state_evolution + if _inside_plate: # Cannot validate shapes with batched parameters; trust the user. # Infer observation_dim from observation model if not explicitly provided. @@ -222,13 +223,15 @@ def _canonicalize_continuous_state_evolution( self.control_dim = int(control_dim) self.categorical_state = bool(inferred_categorical_state) - # Plate-batched parameters prevent reliable unbatched shape probes, so - # we resolve continuous-time diffusion metadata from synthetic vectors. - _canonicalize_continuous_state_evolution( + # In a plate, parameter callables often expect batched parameters, so + # we resolve diffusion metadata using synthetic per-trajectory probes. + resolved_state_evolution = _refine_continuous_state_evolution( + resolved_state_evolution, x_probe=jnp.zeros((inferred_state_dim,)), u_probe=None if control_dim == 0 else jnp.zeros((control_dim,)), t_probe=jnp.array(0.0) if self.t0 is None else self.t0, ) + self.state_evolution = resolved_state_evolution return x_probe = _make_probe_state( @@ -245,7 +248,8 @@ def _canonicalize_continuous_state_evolution( u_probe=u_probe, t_probe=t_probe, ) - _canonicalize_continuous_state_evolution( + resolved_state_evolution = _refine_continuous_state_evolution( + resolved_state_evolution, x_probe=x_probe, u_probe=u_probe, t_probe=t_probe, @@ -259,6 +263,8 @@ def _canonicalize_continuous_state_evolution( t_probe=t_probe, ) + self.state_evolution = resolved_state_evolution + obs_dist = observation_model(x_probe, u_probe, t_probe) inferred_observation_dim = _infer_vector_dim_from_distribution( obs_dist, "observation_model(x, u, t)" @@ -419,10 +425,10 @@ def __init__( raise ValueError( "DeterministicContinuousTimeStateEvolution does not accept diffusion." ) - object.__setattr__(self, "drift", drift) - object.__setattr__(self, "potential", potential) - object.__setattr__(self, "use_negative_gradient", use_negative_gradient) - object.__setattr__(self, "diffusion", None) + self.drift = drift + self.potential = potential + self.use_negative_gradient = use_negative_gradient + self.diffusion = None class StochasticContinuousTimeStateEvolution(ContinuousTimeStateEvolution): @@ -443,10 +449,10 @@ def __init__( "StochasticContinuousTimeStateEvolution requires diffusion with " "resolved bm_dim." ) - object.__setattr__(self, "drift", drift) - object.__setattr__(self, "potential", potential) - object.__setattr__(self, "use_negative_gradient", use_negative_gradient) - object.__setattr__(self, "diffusion", diffusion) + self.drift = drift + self.potential = potential + self.use_negative_gradient = use_negative_gradient + self.diffusion = diffusion @property def bm_dim(self) -> int: diff --git a/dynestyx/models/diffusions.py b/dynestyx/models/diffusions.py index ac9075ae..c247563e 100644 --- a/dynestyx/models/diffusions.py +++ b/dynestyx/models/diffusions.py @@ -2,7 +2,6 @@ from __future__ import annotations -import copy from collections.abc import Callable from typing import NamedTuple, cast @@ -74,12 +73,10 @@ def __init__( coefficient: DiffusionSpec, bm_dim: int | None = None, ): - object.__setattr__( - self, - "coefficient", - coefficient if callable(coefficient) else jnp.asarray(coefficient), + self.coefficient = ( + coefficient if callable(coefficient) else jnp.asarray(coefficient) ) - object.__setattr__(self, "bm_dim", None if bm_dim is None else int(bm_dim)) + self.bm_dim = None if bm_dim is None else int(bm_dim) self._validate_init() def evaluate_value( @@ -150,9 +147,7 @@ def apply( return self.evaluate(x=x, u=u, t=t).apply(dw, state_dim=state_dim) def _with_bm_dim(self, bm_dim: int) -> Diffusion: - new_self = copy.copy(self) - object.__setattr__(new_self, "bm_dim", int(bm_dim)) - return new_self + return type(self)(self.coefficient, bm_dim=int(bm_dim)) def _constant_shape(self) -> tuple[int, ...] | None: if callable(self.coefficient): @@ -200,7 +195,7 @@ def _validate_init(self) -> None: f"Got shape {shape}." ) if shape is not None and self.bm_dim is None: - object.__setattr__(self, "bm_dim", int(shape[-1])) + self.bm_dim = int(shape[-1]) def resolve_metadata( self, diff --git a/dynestyx/solvers/sde.py b/dynestyx/solvers/sde.py index ddd04c5d..7f4986be 100644 --- a/dynestyx/solvers/sde.py +++ b/dynestyx/solvers/sde.py @@ -372,11 +372,8 @@ def _diffusion(t, y, args): shape=(state_evolution.bm_dim,), key=k_bm, ) - terms = dfx.MultiTerm( # type: ignore[arg-type] - dfx.ODETerm(_drift), dfx.ControlTerm(_diffusion, bm) - ) sol = dfx.diffeqsolve( - terms, + dfx.MultiTerm(dfx.ODETerm(_drift), dfx.ControlTerm(_diffusion, bm)), t0=t0, t1=saveat_times[-1], y0=x0, From a4cee35ac9a825189375636786f90637f30f8651 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Thu, 14 May 2026 21:19:32 -0400 Subject: [PATCH 23/28] clarify resolve metadata docstring --- dynestyx/models/diffusions.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/dynestyx/models/diffusions.py b/dynestyx/models/diffusions.py index c247563e..81b580fe 100644 --- a/dynestyx/models/diffusions.py +++ b/dynestyx/models/diffusions.py @@ -99,7 +99,7 @@ def resolve_metadata( u_probe: Control | None, t_probe: Time, ) -> Diffusion: - """Validate coefficient shape information and resolve diffusion metadata.""" + """Check coefficient shape and resolve ``bm_dim`` if needed.""" raise NotImplementedError def evaluate( @@ -159,7 +159,9 @@ def _validate_init(self) -> None: raise ValueError(f"bm_dim must be positive. Got bm_dim={self.bm_dim}.") def _value_as_matrix(self, value: Array, *, state_dim: int) -> Array: - raise NotImplementedError("Please don't construct `Diffusion` directly; instead instantiate one of its subclasses (e.g., `FullDiffusion`, `DiagonalDiffusion`, or `ScalarDiffusion`)") + raise NotImplementedError( + "Please don't construct `Diffusion` directly; instead instantiate one of its subclasses (e.g., `FullDiffusion`, `DiagonalDiffusion`, or `ScalarDiffusion`)" + ) def _value_gram_matrix(self, value: Array, *, state_dim: int) -> Array: raise NotImplementedError @@ -205,6 +207,7 @@ def resolve_metadata( u_probe: Control | None, t_probe: Time, ) -> FullDiffusion: + """Check matrix shape and infer ``bm_dim`` from the trailing dimension if needed.""" shape = jax.eval_shape( lambda: self.evaluate_value(x=x_probe, u=u_probe, t=t_probe) ).shape @@ -279,6 +282,7 @@ def resolve_metadata( u_probe: Control | None, t_probe: Time, ) -> DiagonalDiffusion: + """Check vector shape and verify that ``bm_dim`` is either 1 or ``state_dim``.""" shape = jax.eval_shape( lambda: self.evaluate_value(x=x_probe, u=u_probe, t=t_probe) ).shape @@ -359,6 +363,7 @@ def resolve_metadata( u_probe: Control | None, t_probe: Time, ) -> ScalarDiffusion: + """Check scalar shape and verify that ``bm_dim`` is either 1 or ``state_dim``.""" shape = jax.eval_shape( lambda: self.evaluate_value(x=x_probe, u=u_probe, t=t_probe) ).shape From 19a344b8a58f8567ed6f229092d2ceabbc6bffb5 Mon Sep 17 00:00:00 2001 From: Matt Levine Date: Fri, 15 May 2026 11:39:18 -0400 Subject: [PATCH 24/28] Update dynestyx/inference/integrations/cd_dynamax/utils.py Co-authored-by: Dan Waxman --- dynestyx/inference/integrations/cd_dynamax/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dynestyx/inference/integrations/cd_dynamax/utils.py b/dynestyx/inference/integrations/cd_dynamax/utils.py index 4b01241f..87659ef9 100644 --- a/dynestyx/inference/integrations/cd_dynamax/utils.py +++ b/dynestyx/inference/integrations/cd_dynamax/utils.py @@ -193,7 +193,7 @@ def dsx_to_cdlgssm_params(dsx_model: DynamicalModel) -> ParamsCDLGSSM: state_evo = dsx_model.state_evolution if not isinstance(state_evo, StochasticContinuousTimeStateEvolution): raise TypeError( - "dsx_to_cdlgssm_params requires StochasticContinuousTimeStateEvolution." + "dsx_to_cdlgssm_params requires StochasticContinuousTimeStateEvolution. You probably tried to call a continuous-time CD-Dynamax filter with a DeterministicContinuousTimeStateEvolution or DiscreteTimeStateEvolution." ) drift = state_evo.drift if not isinstance(drift, AffineDrift): From 6d390043cd9bf6a597e934f9f7e190e65b0c0a63 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Fri, 15 May 2026 14:20:08 -0400 Subject: [PATCH 25/28] probing and errors for cd-dynamax diffusion plumbing --- .../integrations/cd_dynamax/utils.py | 42 ++++++++++++------- dynestyx/models/core.py | 11 +++-- tests/test_models_core.py | 4 +- 3 files changed, 37 insertions(+), 20 deletions(-) diff --git a/dynestyx/inference/integrations/cd_dynamax/utils.py b/dynestyx/inference/integrations/cd_dynamax/utils.py index 87659ef9..99ae3f5d 100644 --- a/dynestyx/inference/integrations/cd_dynamax/utils.py +++ b/dynestyx/inference/integrations/cd_dynamax/utils.py @@ -28,16 +28,18 @@ type SSMType = ContDiscreteNonlinearGaussianSSM | ContDiscreteNonlinearSSM -def _normalize_cd_dynamax_diffusion( +def _as_cd_dynamax_diffusion_coefficient( state_evolution: StochasticContinuousTimeStateEvolution, state_dim: int, ): - """Return a diffusion coeff compatible with cd-dynamax's EnKF SDE solve. - - cd-dynamax's internal diffrax wrapper builds Brownian controls with shape - equal to `y0.shape` (state_dim). For diffusion with `bm_dim < state_dim`, - pad trailing Brownian columns with zeros to match `(state_dim, state_dim)`. - Diffusion with `bm_dim > state_dim` is rejected. + """Return a full-matrix diffusion coefficient for cd-dynamax. + + This adapts any Dynestyx diffusion shorthand (scalar/diagonal/full, constant + or callable) into a function ``(x, u, t) -> L(x, u, t)`` returning a full + matrix. cd-dynamax's continuous solver paths assume Brownian controls have + dimension ``state_dim``, so rectangular diffusions with ``bm_dim < + state_dim`` are padded with trailing zero columns. ``bm_dim > state_dim`` is + rejected. """ if state_evolution.bm_dim > state_dim: raise ValueError( @@ -185,8 +187,7 @@ def dsx_to_cdlgssm_params(dsx_model: DynamicalModel) -> ParamsCDLGSSM: Requires: - drift is AffineDrift (A, B, b) - - diffusion_coefficient is constant (callable returning same value for any x, u, t) - returning same value for any x, u, t) + - diffusion_coefficient is constant (array/scalar-valued Dynestyx diffusion) - observation_model is LinearGaussianObservation - initial_condition is MultivariateNormal """ @@ -201,15 +202,26 @@ def dsx_to_cdlgssm_params(dsx_model: DynamicalModel) -> ParamsCDLGSSM: f"dsx_to_cdlgssm_params requires AffineDrift, got {type(drift).__name__}." ) + if callable(state_evo.diffusion.coefficient): + raise TypeError( + "Callable diffusion is not supported by the continuous-time exact " + "Kalman filter path. If you need callable diffusion, use a " + "continuous-time nonlinear filter config such as " + "ContinuousTimeEKFConfig instead of ContinuousTimeKFConfig. " + "When the goal is exact filtering, CT-EKF is the appropriate " + "fallback here because in the linear-Gaussian case it emulates " + "the KF via auto-diff and cd_dynamax supports callable diffusion " + "in the nonlinear case (not directly in the linear-Gaussian case)." + ) + # Extract constant L and use resolved Brownian dimension. - x0 = jnp.zeros(dsx_model.state_dim) L = state_evo.diffusion.as_matrix( - x=x0, - u=None, + x=jnp.zeros(dsx_model.state_dim), + u=None if dsx_model.control_dim == 0 else jnp.zeros((dsx_model.control_dim,)), t=jnp.array(0.0), - state_dim=dsx_model.state_dim, + state_dim=dsx_model.state_dim ) - Q = jnp.eye(state_evo.bm_dim) + Q = jnp.eye(dsx_model.state_dim, state_evo.diffusion.bm_dim) ic = dsx_model.initial_condition if not isinstance(ic, dist.MultivariateNormal): @@ -280,7 +292,7 @@ def dsx_to_cd_dynamax( } ) if isinstance(state_evo, StochasticContinuousTimeStateEvolution): - diffusion_coeff = _normalize_cd_dynamax_diffusion( + diffusion_coeff = _as_cd_dynamax_diffusion_coefficient( state_evo, dsx_model.state_dim, ) diff --git a/dynestyx/models/core.py b/dynestyx/models/core.py index 7df6216f..2be12f26 100644 --- a/dynestyx/models/core.py +++ b/dynestyx/models/core.py @@ -225,11 +225,16 @@ def _refine_continuous_state_evolution( # In a plate, parameter callables often expect batched parameters, so # we resolve diffusion metadata using synthetic per-trajectory probes. + x_probe = _make_probe_state( + initial_condition=initial_condition, state_dim=inferred_state_dim + ) + u_probe = None if control_dim == 0 else jnp.zeros((control_dim,)) + t_probe = jnp.array(0.0) if self.t0 is None else self.t0 resolved_state_evolution = _refine_continuous_state_evolution( resolved_state_evolution, - x_probe=jnp.zeros((inferred_state_dim,)), - u_probe=None if control_dim == 0 else jnp.zeros((control_dim,)), - t_probe=jnp.array(0.0) if self.t0 is None else self.t0, + x_probe=x_probe, + u_probe=u_probe, + t_probe=t_probe, ) self.state_evolution = resolved_state_evolution return diff --git a/tests/test_models_core.py b/tests/test_models_core.py index 1da23b26..7080bb7d 100644 --- a/tests/test_models_core.py +++ b/tests/test_models_core.py @@ -7,7 +7,7 @@ import dynestyx as dsx from dynestyx.inference.integrations.cd_dynamax.utils import ( - _normalize_cd_dynamax_diffusion, + _as_cd_dynamax_diffusion_coefficient, dsx_to_cd_dynamax, gaussian_to_nlgssm_params, ) @@ -452,7 +452,7 @@ def test_cd_dynamax_rejects_diffusion_with_bm_dim_exceeds_state_dim() -> None: diffusion=FullDiffusion(jnp.ones((1, 2)), bm_dim=2), ) with pytest.raises(ValueError, match="bm_dim <= state_dim"): - _normalize_cd_dynamax_diffusion(state_evolution, state_dim=1)( + _as_cd_dynamax_diffusion_coefficient(state_evolution, state_dim=1)( jnp.zeros(1), None, jnp.array(0.0), From d2f8564948967c384a14d9498d13bd48047f64f9 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Fri, 15 May 2026 14:24:51 -0400 Subject: [PATCH 26/28] fix lint --- dynestyx/inference/integrations/cd_dynamax/utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dynestyx/inference/integrations/cd_dynamax/utils.py b/dynestyx/inference/integrations/cd_dynamax/utils.py index 99ae3f5d..fb41e80b 100644 --- a/dynestyx/inference/integrations/cd_dynamax/utils.py +++ b/dynestyx/inference/integrations/cd_dynamax/utils.py @@ -219,7 +219,7 @@ def dsx_to_cdlgssm_params(dsx_model: DynamicalModel) -> ParamsCDLGSSM: x=jnp.zeros(dsx_model.state_dim), u=None if dsx_model.control_dim == 0 else jnp.zeros((dsx_model.control_dim,)), t=jnp.array(0.0), - state_dim=dsx_model.state_dim + state_dim=dsx_model.state_dim, ) Q = jnp.eye(dsx_model.state_dim, state_evo.diffusion.bm_dim) From 83641cb07933520a3d08458af7dc615b3619ae8c Mon Sep 17 00:00:00 2001 From: Matt Levine Date: Fri, 15 May 2026 16:46:48 -0400 Subject: [PATCH 27/28] Update dynestyx/models/core.py Co-authored-by: Dan Waxman --- dynestyx/models/core.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/dynestyx/models/core.py b/dynestyx/models/core.py index 2be12f26..1cb5558c 100644 --- a/dynestyx/models/core.py +++ b/dynestyx/models/core.py @@ -415,7 +415,7 @@ def total_drift(self, x: State, u: Control | None, t: Time) -> dState: class DeterministicContinuousTimeStateEvolution(ContinuousTimeStateEvolution): - """Refined continuous-time state evolution with no diffusion.""" + """Refined continuous-time state evolution with no diffusion, i.e., describing an ODE.""" diffusion: None = eqx.field(static=True, default=None) From 8501a17dc088157d7d84f8a4cb02ba2935fb3065 Mon Sep 17 00:00:00 2001 From: Matthew Levine Date: Fri, 15 May 2026 17:38:43 -0400 Subject: [PATCH 28/28] streamline DynamicalModel init --- dynestyx/models/checkers.py | 13 +--- dynestyx/models/core.py | 138 ++++++++++++++++-------------------- 2 files changed, 66 insertions(+), 85 deletions(-) diff --git a/dynestyx/models/checkers.py b/dynestyx/models/checkers.py index 5cb6bbac..669f456c 100644 --- a/dynestyx/models/checkers.py +++ b/dynestyx/models/checkers.py @@ -190,23 +190,16 @@ def _inside_numpyro_plate_context() -> bool: def _infer_observation_dim_in_plate_context( *, - initial_condition: Any, observation_model: Callable[[State, Control | None, Time], Any], - inferred_state_dim: int, - control_dim: int, - t_probe: Time | None, + x_probe: State, + u_probe: Control | None, + t_probe: Time, observation_dim: int | None, ) -> int: """Infer observation dimension in plate context, falling back to explicit value.""" if observation_dim is not None: return int(observation_dim) - x_probe = _make_probe_state( - initial_condition=initial_condition, - state_dim=inferred_state_dim, - ) - u_probe = None if control_dim == 0 else jnp.zeros((control_dim,)) - t_probe = jnp.array(0.0) if t_probe is None else t_probe try: obs_dist = observation_model(x_probe, u_probe, t_probe) return int( diff --git a/dynestyx/models/core.py b/dynestyx/models/core.py index 1cb5558c..37b475a0 100644 --- a/dynestyx/models/core.py +++ b/dynestyx/models/core.py @@ -164,15 +164,27 @@ def __init__( # Skip shape validation when inside a numpyro plate context, since # batched parameters produce shapes that don't match unbatched expectations. - def _refine_continuous_state_evolution( + def _make_probes() -> tuple[State, Control | None, Time]: + """Build synthetic inputs for validation/metadata resolution.""" + x_probe = _make_probe_state( + initial_condition=initial_condition, + state_dim=inferred_state_dim, + ) + u_probe = None if control_dim == 0 else jnp.zeros((control_dim,)) + t_probe = jnp.array(0.0) if self.t0 is None else self.t0 + return x_probe, u_probe, t_probe + + x_probe, u_probe, t_probe = _make_probes() + + def _resolve_continuous_state_evolution( current_state_evolution: ContinuousTimeStateEvolution, - *, - x_probe: State, - u_probe: Control | None, - t_probe: Time, - ) -> ContinuousTimeStateEvolution: - if not inferred_continuous_time: - return current_state_evolution + ) -> ( + DeterministicContinuousTimeStateEvolution + | StochasticContinuousTimeStateEvolution + ): + """Return either a DeterministicContinuousTimeStateEvolution or a StochasticContinuousTimeStateEvolution. + If diffusion is present, lazily build probes to resolve its metadata (e.g., bm_dim). + """ diffusion = current_state_evolution.diffusion if diffusion is None: if isinstance( @@ -191,13 +203,6 @@ def _refine_continuous_state_evolution( u_probe=u_probe, t_probe=t_probe, ) - if ( - isinstance( - current_state_evolution, StochasticContinuousTimeStateEvolution - ) - and current_state_evolution.diffusion is resolved_diffusion - ): - return current_state_evolution return StochasticContinuousTimeStateEvolution( drift=current_state_evolution.drift, potential=current_state_evolution.potential, @@ -205,79 +210,47 @@ def _refine_continuous_state_evolution( diffusion=resolved_diffusion, ) - resolved_state_evolution = state_evolution - if _inside_plate: # Cannot validate shapes with batched parameters; trust the user. # Infer observation_dim from observation model if not explicitly provided. inferred_obs_dim = _infer_observation_dim_in_plate_context( - initial_condition=initial_condition, observation_model=observation_model, - inferred_state_dim=inferred_state_dim, - control_dim=control_dim, - t_probe=self.t0, - observation_dim=observation_dim, - ) - self.state_dim = int(inferred_state_dim) - self.observation_dim = inferred_obs_dim - self.control_dim = int(control_dim) - self.categorical_state = bool(inferred_categorical_state) - - # In a plate, parameter callables often expect batched parameters, so - # we resolve diffusion metadata using synthetic per-trajectory probes. - x_probe = _make_probe_state( - initial_condition=initial_condition, state_dim=inferred_state_dim - ) - u_probe = None if control_dim == 0 else jnp.zeros((control_dim,)) - t_probe = jnp.array(0.0) if self.t0 is None else self.t0 - resolved_state_evolution = _refine_continuous_state_evolution( - resolved_state_evolution, x_probe=x_probe, u_probe=u_probe, t_probe=t_probe, + observation_dim=observation_dim, ) - self.state_evolution = resolved_state_evolution - return + else: + if self.continuous_time: + _validate_continuous_state_evolution( + state_evolution=state_evolution, + state_dim=inferred_state_dim, + x_probe=x_probe, + u_probe=u_probe, + t_probe=t_probe, + ) + else: + _validate_discrete_state_evolution_output_shape( + state_evolution=state_evolution, + state_dim=inferred_state_dim, + x_probe=x_probe, + u_probe=u_probe, + t_probe=t_probe, + ) - x_probe = _make_probe_state( - initial_condition=initial_condition, state_dim=inferred_state_dim - ) - u_probe = None if control_dim == 0 else jnp.zeros((control_dim,)) - t_probe = jnp.array(0.0) if self.t0 is None else self.t0 + obs_dist = observation_model(x_probe, u_probe, t_probe) + inferred_obs_dim = _infer_vector_dim_from_distribution( + obs_dist, "observation_model(x, u, t)" + ) + _validate_observation_dim(observation_dim, inferred_obs_dim) if self.continuous_time: - _validate_continuous_state_evolution( - state_evolution=state_evolution, - state_dim=inferred_state_dim, - x_probe=x_probe, - u_probe=u_probe, - t_probe=t_probe, - ) - resolved_state_evolution = _refine_continuous_state_evolution( - resolved_state_evolution, - x_probe=x_probe, - u_probe=u_probe, - t_probe=t_probe, - ) - else: - _validate_discrete_state_evolution_output_shape( - state_evolution=state_evolution, - state_dim=inferred_state_dim, - x_probe=x_probe, - u_probe=u_probe, - t_probe=t_probe, + self.state_evolution = _resolve_continuous_state_evolution( + state_evolution, ) - self.state_evolution = resolved_state_evolution - - obs_dist = observation_model(x_probe, u_probe, t_probe) - inferred_observation_dim = _infer_vector_dim_from_distribution( - obs_dist, "observation_model(x, u, t)" - ) - _validate_observation_dim(observation_dim, inferred_observation_dim) - self.state_dim = int(inferred_state_dim) - self.observation_dim = int(inferred_observation_dim) + self.observation_dim = int(inferred_obs_dim) self.control_dim = int(control_dim) self.categorical_state = bool(inferred_categorical_state) @@ -415,7 +388,15 @@ def total_drift(self, x: State, u: Control | None, t: Time) -> dState: class DeterministicContinuousTimeStateEvolution(ContinuousTimeStateEvolution): - """Refined continuous-time state evolution with no diffusion, i.e., describing an ODE.""" + """Continuous-time state evolution with no diffusion term, i.e., describing an ODE. + + This is a refined form of :class:`ContinuousTimeStateEvolution` used when a + model has deterministic continuous-time dynamics, i.e. an ODE rather than an + SDE. In most user code you should construct + :class:`ContinuousTimeStateEvolution` directly and let + :class:`DynamicalModel` refine it into this subclass when ``diffusion=None``. + Its main semantic guarantee is that ``diffusion`` is always ``None``. + """ diffusion: None = eqx.field(static=True, default=None) @@ -437,7 +418,14 @@ def __init__( class StochasticContinuousTimeStateEvolution(ContinuousTimeStateEvolution): - """Refined continuous-time state evolution with resolved diffusion.""" + """Continuous-time state evolution with resolved stochastic diffusion. + + This is a refined form of :class:`ContinuousTimeStateEvolution` used for SDE + models after the diffusion metadata has been resolved. In practice that means + the attached :class:`~dynestyx.models.diffusions.Diffusion` has a known + ``bm_dim`` and can therefore be used safely by downstream SDE solvers, + discretizers, and inference backends. + """ diffusion: Diffusion = eqx.field(static=True, kw_only=True)