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Add array heatmap logging to ViewerGL #2433
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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@@ -220,6 +220,12 @@ def __init__( | |
| self._scalar_arrays: dict[str, np.ndarray | None] = {} | ||
| self._scalar_accumulators: dict[str, list[float]] = {} | ||
| self._scalar_smoothing: dict[str, int] = {} | ||
| self._array_buffers: dict[str, np.ndarray] = {} | ||
| self._array_dirty: set[str] = set() | ||
| self._array_textures: dict[str, dict[str, Any]] = {} | ||
| self._heatmap_min_cell_pixels = 3.0 | ||
| self._heatmap_nan_rgba = np.array([51, 51, 51, 255], dtype=np.uint8) | ||
| self._heatmap_color_lut = self._build_heatmap_color_lut() | ||
| self._plot_history_size = plot_history_size | ||
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||
| super().__init__() | ||
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@@ -313,6 +319,30 @@ def _invalidate_pbo(self): | |
| gl.glDeleteBuffers(1, pbo_id) | ||
| self._pbo = None | ||
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| def _delete_array_texture(self, name: str): | ||
| texture_state = self._array_textures.pop(name, None) | ||
| if texture_state is None: | ||
| return | ||
| gl = getattr(RendererGL, "gl", None) | ||
| texture_id = texture_state.get("texture_id") | ||
| if gl is None or texture_id is None: | ||
| return | ||
| texture_ids = (gl.GLuint * 1)(texture_id) | ||
| gl.glDeleteTextures(1, texture_ids) | ||
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||
| def _clear_array_textures(self): | ||
| if not self._array_textures: | ||
| return | ||
| gl = getattr(RendererGL, "gl", None) | ||
| if gl is None: | ||
| self._array_textures.clear() | ||
| return | ||
| texture_ids = [state["texture_id"] for state in self._array_textures.values() if state.get("texture_id")] | ||
| if texture_ids: | ||
| gl_ids = (gl.GLuint * len(texture_ids))(*texture_ids) | ||
| gl.glDeleteTextures(len(texture_ids), gl_ids) | ||
| self._array_textures.clear() | ||
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||
| def register_ui_callback( | ||
| self, | ||
| callback: Callable[[Any], None], | ||
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@@ -445,6 +475,9 @@ def clear_model(self): | |
| self._scalar_arrays.clear() | ||
| self._scalar_accumulators.clear() | ||
| self._scalar_smoothing.clear() | ||
| self._array_buffers.clear() | ||
| self._array_dirty.clear() | ||
| self._clear_array_textures() | ||
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| super().clear_model() | ||
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@@ -1220,15 +1253,33 @@ def log_gaussian( | |
| cache["colors_uploaded"] = True | ||
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| @override | ||
| def log_array(self, name: str, array: wp.array[Any] | np.ndarray): | ||
| def log_array(self, name: str, array: wp.array[Any] | np.ndarray | None): | ||
| """ | ||
| Log a generic array for visualization (not implemented). | ||
| Log a numeric array for visualization. | ||
|
|
||
| Args: | ||
| name: Unique path/name for the array signal. | ||
| array: Array data to visualize. | ||
| array: Array data to visualize, or ``None`` to remove a previously | ||
| logged array. | ||
| """ | ||
| pass | ||
| if array is None: | ||
| self._array_buffers.pop(name, None) | ||
| self._array_dirty.discard(name) | ||
| self._delete_array_texture(name) | ||
| return | ||
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||
| array_np = array.numpy() if isinstance(array, wp.array) else np.asarray(array) | ||
| array_np = np.asarray(array_np, dtype=np.float32) | ||
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||
| if array_np.ndim == 0: | ||
| array_np = array_np.reshape(1, 1) | ||
| elif array_np.ndim == 1: | ||
| array_np = array_np.reshape(1, -1) | ||
| elif array_np.ndim != 2: | ||
| raise ValueError("ViewerGL.log_array only supports scalar, 1-D, or 2-D arrays.") | ||
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| self._array_buffers[name] = np.ascontiguousarray(array_np) | ||
| self._array_dirty.add(name) | ||
|
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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 🛠️ Refactor suggestion | 🟠 Major Abstract base and peer backends still don't accept The override now accepts 🤖 Prompt for AI Agents |
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| @override | ||
| def log_scalar( | ||
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@@ -1590,6 +1641,8 @@ def close(self): | |
| """ | ||
| Close the viewer and clean up resources. | ||
| """ | ||
| self._clear_array_textures() | ||
| self._invalidate_pbo() | ||
| self.renderer.close() | ||
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| @property | ||
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@@ -2325,18 +2378,192 @@ def _edit_color3( | |
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| imgui.end() | ||
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| @staticmethod | ||
| def _build_heatmap_color_lut() -> np.ndarray: | ||
| inferno_stops = ( | ||
| (0.0, (0.001, 0.000, 0.014)), | ||
| (0.2, (0.169, 0.042, 0.341)), | ||
| (0.4, (0.416, 0.090, 0.433)), | ||
| (0.6, (0.698, 0.165, 0.388)), | ||
| (0.8, (0.944, 0.403, 0.121)), | ||
| (1.0, (0.988, 0.998, 0.645)), | ||
| ) | ||
| lut = np.empty((256, 4), dtype=np.uint8) | ||
| for index, value in enumerate(np.linspace(0.0, 1.0, 256, dtype=np.float32)): | ||
| for stop_index in range(len(inferno_stops) - 1): | ||
| t0, c0 = inferno_stops[stop_index] | ||
| t1, c1 = inferno_stops[stop_index + 1] | ||
| if value <= t1: | ||
| alpha = 0.0 if t1 <= t0 else (float(value) - t0) / (t1 - t0) | ||
| rgb = [round(255.0 * ((1.0 - alpha) * c0[channel] + alpha * c1[channel])) for channel in range(3)] | ||
| lut[index, :3] = rgb | ||
| lut[index, 3] = 255 | ||
| break | ||
| else: | ||
| lut[index, :3] = [round(255.0 * channel) for channel in inferno_stops[-1][1]] | ||
| lut[index, 3] = 255 | ||
| return lut | ||
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||
| @staticmethod | ||
| def _downsample_heatmap(array: np.ndarray, target_rows: int, target_cols: int) -> np.ndarray: | ||
| rows, cols = array.shape | ||
| if rows <= target_rows and cols <= target_cols: | ||
| return array | ||
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||
| row_factor = max(1, (rows + target_rows - 1) // target_rows) | ||
| col_factor = max(1, (cols + target_cols - 1) // target_cols) | ||
| new_rows = max(1, rows // row_factor) | ||
| new_cols = max(1, cols // col_factor) | ||
| if new_rows == rows and new_cols == cols: | ||
| return array | ||
|
|
||
| trimmed = array[: new_rows * row_factor, : new_cols * col_factor] | ||
| finite_mask = np.isfinite(trimmed) | ||
| safe_values = np.where(finite_mask, trimmed, 0.0) | ||
| reshaped_shape = (new_rows, row_factor, new_cols, col_factor) | ||
| value_sum = safe_values.reshape(reshaped_shape).sum(axis=(1, 3), dtype=np.float64) | ||
| value_count = finite_mask.reshape(reshaped_shape).sum(axis=(1, 3)) | ||
| downsampled = np.full((new_rows, new_cols), np.nan, dtype=np.float32) | ||
| np.divide(value_sum, value_count, out=downsampled, where=value_count > 0) | ||
| return downsampled | ||
|
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||
| def _colorize_heatmap(self, array: np.ndarray) -> tuple[np.ndarray, float, float]: | ||
| finite_mask = np.isfinite(array) | ||
| if not np.any(finite_mask): | ||
| rgba = np.empty((*array.shape, 4), dtype=np.uint8) | ||
| rgba[...] = self._heatmap_nan_rgba | ||
| return np.ascontiguousarray(rgba), float("nan"), float("nan") | ||
|
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||
| finite_values = array[finite_mask] | ||
| value_min = float(np.min(finite_values)) | ||
| value_max = float(np.max(finite_values)) | ||
| denom = max(value_max - value_min, 1.0e-8) | ||
|
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||
| normalized = np.zeros(array.shape, dtype=np.float32) | ||
| np.subtract(array, value_min, out=normalized, where=finite_mask) | ||
| np.divide(normalized, denom, out=normalized, where=finite_mask) | ||
| np.clip(normalized, 0.0, 1.0, out=normalized) | ||
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| lut_indices = np.rint(normalized * 255.0).astype(np.uint8) | ||
| rgba = self._heatmap_color_lut[lut_indices].copy() | ||
| rgba[~finite_mask] = self._heatmap_nan_rgba | ||
| return np.ascontiguousarray(rgba), value_min, value_max | ||
|
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| def _ensure_array_texture(self, name: str, width: int, height: int) -> dict[str, Any]: | ||
| texture_state = self._array_textures.get(name) | ||
| if texture_state is not None and texture_state["size"] == (width, height): | ||
| return texture_state | ||
|
|
||
| if texture_state is not None: | ||
| self._delete_array_texture(name) | ||
|
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||
| gl = RendererGL.gl | ||
| texture_id = (gl.GLuint * 1)() | ||
| gl.glGenTextures(1, texture_id) | ||
| gl.glBindTexture(gl.GL_TEXTURE_2D, texture_id[0]) | ||
| gl.glTexParameteri(gl.GL_TEXTURE_2D, gl.GL_TEXTURE_MIN_FILTER, gl.GL_NEAREST) | ||
| gl.glTexParameteri(gl.GL_TEXTURE_2D, gl.GL_TEXTURE_MAG_FILTER, gl.GL_NEAREST) | ||
| gl.glTexParameteri(gl.GL_TEXTURE_2D, gl.GL_TEXTURE_WRAP_S, gl.GL_CLAMP_TO_EDGE) | ||
| gl.glTexParameteri(gl.GL_TEXTURE_2D, gl.GL_TEXTURE_WRAP_T, gl.GL_CLAMP_TO_EDGE) | ||
| gl.glPixelStorei(gl.GL_UNPACK_ALIGNMENT, 1) | ||
| gl.glTexImage2D( | ||
| gl.GL_TEXTURE_2D, | ||
| 0, | ||
| gl.GL_RGBA8, | ||
| width, | ||
| height, | ||
| 0, | ||
| gl.GL_RGBA, | ||
| gl.GL_UNSIGNED_BYTE, | ||
| None, | ||
| ) | ||
| gl.glBindTexture(gl.GL_TEXTURE_2D, 0) | ||
|
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||
| texture_state = { | ||
| "texture_id": texture_id[0], | ||
| "size": (width, height), | ||
| "source_shape": None, | ||
| "display_shape": None, | ||
| "value_min": 0.0, | ||
| "value_max": 0.0, | ||
| } | ||
| self._array_textures[name] = texture_state | ||
| return texture_state | ||
|
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| def _update_array_texture(self, texture_id: int, rgba: np.ndarray): | ||
| gl = RendererGL.gl | ||
| gl.glBindTexture(gl.GL_TEXTURE_2D, texture_id) | ||
| gl.glPixelStorei(gl.GL_UNPACK_ALIGNMENT, 1) | ||
| gl.glTexSubImage2D( | ||
| gl.GL_TEXTURE_2D, | ||
| 0, | ||
| 0, | ||
| 0, | ||
| rgba.shape[1], | ||
| rgba.shape[0], | ||
| gl.GL_RGBA, | ||
| gl.GL_UNSIGNED_BYTE, | ||
| rgba.ctypes.data_as(ctypes.POINTER(ctypes.c_ubyte)), | ||
| ) | ||
| gl.glBindTexture(gl.GL_TEXTURE_2D, 0) | ||
|
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| def _render_array_heatmap(self, name: str, array: np.ndarray, width: float): | ||
| imgui = self.ui.imgui | ||
|
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| rows, cols = array.shape | ||
| heatmap_width = max(120.0, width) | ||
| heatmap_height = np.clip(heatmap_width * rows / max(cols, 1), 80.0, 220.0) | ||
| target_cols = max(1, min(cols, int(heatmap_width / self._heatmap_min_cell_pixels))) | ||
| target_rows = max(1, min(rows, int(heatmap_height / self._heatmap_min_cell_pixels))) | ||
| display_array = self._downsample_heatmap(array, target_rows, target_cols) | ||
| display_rows, display_cols = display_array.shape | ||
| texture_state = self._ensure_array_texture(name, display_cols, display_rows) | ||
|
|
||
| if ( | ||
| name in self._array_dirty | ||
| or texture_state["source_shape"] != array.shape | ||
| or texture_state["display_shape"] != display_array.shape | ||
| ): | ||
| rgba, value_min, value_max = self._colorize_heatmap(display_array) | ||
| self._update_array_texture(texture_state["texture_id"], rgba) | ||
| texture_state["source_shape"] = array.shape | ||
| texture_state["display_shape"] = display_array.shape | ||
| texture_state["value_min"] = value_min | ||
| texture_state["value_max"] = value_max | ||
| self._array_dirty.discard(name) | ||
|
|
||
| draw_list = imgui.get_window_draw_list() | ||
| origin = imgui.get_cursor_screen_pos() | ||
| imgui.image(imgui.ImTextureRef(texture_state["texture_id"]), imgui.ImVec2(heatmap_width, heatmap_height)) | ||
|
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||
| border_color = imgui.color_convert_float4_to_u32(imgui.ImVec4(1.0, 1.0, 1.0, 0.25)) | ||
| draw_list.add_rect( | ||
| imgui.ImVec2(origin.x, origin.y), | ||
| imgui.ImVec2(origin.x + heatmap_width, origin.y + heatmap_height), | ||
| border_color, | ||
| ) | ||
| shape_text = f"shape {rows}x{cols}" | ||
| if (display_rows, display_cols) != (rows, cols): | ||
| shape_text += f" shown {display_rows}x{display_cols}" | ||
| if np.isfinite(texture_state["value_min"]) and np.isfinite(texture_state["value_max"]): | ||
| range_text = f"min {texture_state['value_min']:.4g} max {texture_state['value_max']:.4g}" | ||
| else: | ||
| range_text = "min -- max --" | ||
| imgui.text(f"{shape_text} {range_text}") | ||
|
|
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| def _render_scalar_plots(self): | ||
| """Render an ImGui window with live line plots for all logged scalars.""" | ||
| if not self._scalar_buffers: | ||
| """Render an ImGui window with live line plots and array heatmaps.""" | ||
| if not self._scalar_buffers and not self._array_buffers: | ||
| return | ||
|
|
||
| imgui = self.ui.imgui | ||
| io = self.ui.io | ||
|
|
||
| window_width = 400 | ||
| item_height = len(self._scalar_buffers) * 140 + len(self._array_buffers) * 260 | ||
| window_height = min( | ||
| io.display_size[1] - 20, | ||
| len(self._scalar_buffers) * 140 + 60, | ||
| item_height + 60, | ||
| ) | ||
| imgui.set_next_window_pos( | ||
| imgui.ImVec2(io.display_size[0] - window_width - 10, 10), | ||
|
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@@ -2365,6 +2592,13 @@ def _render_scalar_plots(self): | |
| imgui.TreeNodeFlags_.default_open.value, | ||
| ): | ||
| imgui.plot_lines(f"##{name}", arr, graph_size=graph_size, overlay_text=overlay) | ||
|
|
||
| for name, array in self._array_buffers.items(): | ||
| if imgui.collapsing_header( | ||
| name, | ||
| imgui.TreeNodeFlags_.default_open.value, | ||
| ): | ||
| self._render_array_heatmap(name, array, window_width - 40.0) | ||
| imgui.end() | ||
|
|
||
| def _render_stats_overlay(self): | ||
|
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||
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