MNT Set up vulture and remove dead code it flagged

.vulture_whitelist.py

@@ -0,0 +1,12 @@
+"""Vulture whitelist: names that look unused but are intentionally kept.
+
+Referenced from ``[tool.vulture] paths`` in pyproject.toml so these
+references count as "used" and don't show up in dead-code reports.
+"""
+
+# pytest fixtures: looked up by name via dependency injection, never imported.
+from autoflatten.tests import conftest
+
+conftest.mock_freesurfer_env
+conftest.temp_subject_dir
+conftest.no_freesurfer_env

autoflatten/cli.py

@@ -589,11 +589,6 @@ def process_hemisphere(
 # =============================================================================
 
 
-def cmd_default(args):
-    """Default command: full pipeline (project + flatten)."""
-    return cmd_run_full_pipeline(args)
-
-
 def cmd_run_full_pipeline(args):
     """Run the full pipeline: projection + flattening."""
     print("Starting Autoflatten Pipeline...")

autoflatten/core.py

@@ -260,7 +260,6 @@ def ensure_continuous_cuts(vertex_dict, subject, hemi):
         while remaining and end_comp in remaining:
             # Find closest remaining component to any connected component
             min_dist = float("inf")
-            best_conn = None
             best_remain = None
             closest_v1 = None
             closest_v2 = None
@@ -280,7 +279,6 @@ def ensure_continuous_cuts(vertex_dict, subject, hemi):
 
                     if dist < min_dist:
                         min_dist = dist
-                        best_conn = conn_idx
                         best_remain = remain_idx
                         closest_v1 = conn_verts[min_idx[0]]
                         closest_v2 = remain_verts[min_idx[1]]

autoflatten/flatten/algorithm.py

@@ -1137,7 +1137,7 @@ def grad_J_a_fn(uv):
                     recovery_energy_fn, n_coarse_steps=n_coarse_steps
                 )
 
-                for r_iter in range(recovery_iterations):
+                for _ in range(recovery_iterations):
                     r_grad = recovery_grad_fn(uv)
                     if n_avg > 0:
                         r_grad = smooth_gradient(
@@ -2237,31 +2237,3 @@ def save_result(self, uv: np.ndarray, output_path: str) -> None:
 
         if self.config.verbose:
             print(f"Saved flattened patch to {output_path}")
-
-    def compute_distance_error(self, uv: np.ndarray) -> float:
-        """Compute average % distance error for UV coordinates.
-
-        Args:
-            uv: (V, 2) UV coordinates
-
-        Returns:
-            Percentage distance error
-        """
-        uv_jax = jnp.asarray(uv)
-        return float(
-            _compute_distance_error_jit(
-                uv_jax, self.neighbors_jax, self.targets_jax, self.mask_jax
-            )
-        )
-
-    def count_flipped(self, uv: np.ndarray) -> int:
-        """Count flipped triangles.
-
-        Args:
-            uv: (V, 2) UV coordinates
-
-        Returns:
-            Number of flipped triangles
-        """
-        uv_jax = jnp.asarray(uv)
-        return int(count_flipped_triangles(uv_jax, self.faces_jax))

autoflatten/flatten/distance.py

@@ -1,8 +1,7 @@
 """Distance computation functions for surface meshes.
 
-Provides two methods for computing geodesic distances:
-1. Heat method (igl): More accurate but slower, good for global distances
-2. Graph-based Dijkstra: Fast for local k-ring distances
+Provides graph-based Dijkstra for geodesic distances. Fast for local
+k-ring distances and accurate for small k (the surface is locally flat).
 
 Includes Numba-accelerated implementations for significant speedups:
 - K-ring computation: ~20x faster with parallel Numba
@@ -28,55 +27,6 @@
 GRAPH_DISTANCE_CORRECTION = (1 + np.sqrt(2)) / 2
 
 
-# =============================================================================
-# Heat method (accurate, slower)
-# =============================================================================
-
-
-def setup_heat_geodesic(vertices, faces):
-    """Precompute heat geodesic solver.
-
-    Parameters
-    ----------
-    vertices : ndarray of shape (N, 3)
-        Vertex positions
-    faces : ndarray of shape (F, 3)
-        Face indices
-
-    Returns
-    -------
-    HeatGeodesicsData
-        Object for use with compute_heat_distance
-    """
-    data = igl.HeatGeodesicsData()
-    igl.heat_geodesics_precompute(vertices, faces.astype(np.int64), data)
-    return data
-
-
-def compute_heat_distance(heat_data, source_idx):
-    """Compute geodesic distances from a source vertex using heat method.
-
-    Parameters
-    ----------
-    heat_data : HeatGeodesicsData
-        Precomputed data from setup_heat_geodesic
-    source_idx : int
-        Index of source vertex
-
-    Returns
-    -------
-    ndarray of shape (N,)
-        Distances from source to all vertices
-    """
-    gamma = np.array([source_idx], dtype=np.int32)
-    return igl.heat_geodesics_solve(heat_data, gamma)
-
-
-# =============================================================================
-# Graph-based Dijkstra (fast for local distances)
-# =============================================================================
-
-
 def build_mesh_graph(vertices, faces):
     """Build sparse adjacency matrix with edge lengths as weights.
 
@@ -482,30 +432,6 @@ def _limited_dijkstra(v, k_ring, graph, correction):
     return np.array([found.get(idx, np.inf) / correction for idx in k_ring])
 
 
-def compute_graph_distance(graph, source_idx, k_ring, correction=None):
-    """Compute graph-based distances from source to k-ring neighbors.
-
-    Parameters
-    ----------
-    graph : sparse.csr_matrix
-        Sparse CSR adjacency matrix from build_mesh_graph
-    source_idx : int
-        Index of source vertex
-    k_ring : ndarray
-        Array of target vertex indices
-    correction : float, optional
-        Correction factor (default: GRAPH_DISTANCE_CORRECTION)
-
-    Returns
-    -------
-    ndarray
-        Distances to k_ring vertices
-    """
-    if correction is None:
-        correction = GRAPH_DISTANCE_CORRECTION
-    return _limited_dijkstra(source_idx, k_ring, graph, correction)
-
-
 def compute_kring_geodesic_distances(
     vertices, faces, k, correction=None, use_numba=True, n_threads=None, tqdm_position=0
 ):

autoflatten/flatten/energy.py

@@ -144,41 +144,6 @@ def compute_metric_energy_edges(uv, src, dst, targets, n_vertices):
     return jnp.sum(errors)
 
 
-@jax.jit
-def compute_both_energies_edges(
-    uv, src, dst, edge_targets, n_vertices, faces, original_areas
-):
-    """Compute both energy components using edge list format.
-
-    Parameters
-    ----------
-    uv : ndarray of shape (V, 2)
-        Current 2D vertex positions
-    src : ndarray of shape (E,)
-        Source vertex indices
-    dst : ndarray of shape (E,)
-        Destination vertex indices
-    edge_targets : ndarray of shape (E,)
-        Target distances
-    n_vertices : int
-        Number of vertices
-    faces : ndarray of shape (T, 3)
-        Triangle indices
-    original_areas : ndarray of shape (T,)
-        Original 3D triangle areas
-
-    Returns
-    -------
-    J_d : float
-        Metric distortion energy
-    J_a : float
-        Area energy
-    """
-    J_d = compute_metric_energy_edges(uv, src, dst, edge_targets, n_vertices)
-    J_a = compute_area_energy(uv, faces, original_areas)
-    return J_d, J_a
-
-
 @jax.jit
 def compute_metric_energy(uv, neighbors, targets, mask):
     """Compute metric distortion energy J_d (vectorized, JIT-compiled).

autoflatten/tests/test_core.py

@@ -5,7 +5,7 @@
 import os
 import subprocess
 import tempfile
-from unittest.mock import MagicMock, call, patch
+from unittest.mock import MagicMock, patch
 
 import networkx as nx
 import numpy as np

autoflatten/tests/test_freesurfer.py

@@ -389,7 +389,7 @@ def test_input_patch_not_exists(self, tmp_path, monkeypatch):
         hemi = "lh"
         surf_dir = tmp_path / "subjects" / subject / "surf"
         surf_dir.mkdir(parents=True)
-        monkeypatch.setattr(fs, "_resolve_subject_dir", lambda subj: str(surf_dir))
+        monkeypatch.setattr(fs, "_resolve_subject_dir", lambda _subj: str(surf_dir))
 
         with pytest.raises(FileNotFoundError):
             run_mris_flatten(
@@ -409,7 +409,7 @@ def test_output_exists_no_overwrite(self, tmp_path, monkeypatch):
         existing_output = output_dir / output_name
         existing_output.write_text("old")
 
-        monkeypatch.setattr(fs, "_resolve_subject_dir", lambda subj: str(surf_dir))
+        monkeypatch.setattr(fs, "_resolve_subject_dir", lambda _subj: str(surf_dir))
         monkeypatch.setattr(
             fs,
             "_run_command",
@@ -446,7 +446,7 @@ def test_overwrite_true_creates_and_cleans(self, tmp_path, monkeypatch):
         existing_output = output_dir / output_name
         existing_output.write_text("old")
 
-        monkeypatch.setattr(fs, "_resolve_subject_dir", lambda subj: str(surf_dir))
+        monkeypatch.setattr(fs, "_resolve_subject_dir", lambda _subj: str(surf_dir))
 
         def fake_run_command(cmd, cwd, log_path, env=None):
             flat = cmd[-1]
@@ -487,7 +487,7 @@ def test_command_failure_raises(self, tmp_path, monkeypatch):
         output_dir = tmp_path / "outdir"
         output_dir.mkdir()
 
-        monkeypatch.setattr(fs, "_resolve_subject_dir", lambda subj: str(surf_dir))
+        monkeypatch.setattr(fs, "_resolve_subject_dir", lambda _subj: str(surf_dir))
 
         def fake_fail(cmd, cwd, log_path, env=None):
             with open(log_path, "w") as f:
@@ -514,7 +514,7 @@ def test_default_output_name(self, tmp_path, monkeypatch):
         output_dir = tmp_path / "outdir"
         output_dir.mkdir()
 
-        monkeypatch.setattr(fs, "_resolve_subject_dir", lambda subj: str(surf_dir))
+        monkeypatch.setattr(fs, "_resolve_subject_dir", lambda _subj: str(surf_dir))
 
         def fake_run(cmd, cwd, log_path, env=None):
             flat = cmd[-1]
@@ -614,7 +614,7 @@ def test_run_mris_flatten_preserves_original_surf_dir(self, tmp_path, monkeypatc
         output_dir.mkdir()
 
         # Mock _resolve_subject_dir to return our test surf_dir
-        monkeypatch.setattr(fs, "_resolve_subject_dir", lambda subj: str(surf_dir))
+        monkeypatch.setattr(fs, "_resolve_subject_dir", lambda _subj: str(surf_dir))
 
         # Mock _run_command to simulate successful mris_flatten
         def fake_run_command(cmd, cwd, log_path, env=None):
@@ -699,7 +699,7 @@ def test_debug_flag_preserves_temp_directory(self, tmp_path, monkeypatch):
         temp_dirs = []
 
         # Mock _resolve_subject_dir
-        monkeypatch.setattr(fs, "_resolve_subject_dir", lambda subj: str(surf_dir))
+        monkeypatch.setattr(fs, "_resolve_subject_dir", lambda _subj: str(surf_dir))
 
         # Mock _run_command and capture temp directory
         def fake_run_command(cmd, cwd, log_path, env=None):

pyproject.toml

@@ -66,6 +66,15 @@ autoflatten = ["default_templates/*.json"]
 skip = ".git*"
 check-hidden = true
 
+[tool.vulture]
+paths = ["autoflatten", "scripts", ".vulture_whitelist.py"]
+exclude = ["autoflatten/_version.py"]
+min_confidence = 80
+sort_by_size = true
+# kwargs: backend interface accepts/forwards opts even when this impl ignores them
+# trim: kept as no-op for backward compatibility in viz.plot_patch
+ignore_names = ["kwargs", "trim"]
+
 [tool.setuptools_scm]
 version_file = "autoflatten/_version.py"
 local_scheme = "no-local-version"
@@ -85,4 +94,5 @@ exclude_lines = [
 dev = [
     "build>=1.3.0",
     "twine>=6.2.0",
+    "vulture>=2.14",
 ]