| ''' import os |
| import numpy as np |
| import matplotlib.pyplot as plt |
| import matplotlib.animation as animation |
| import matplotlib.ticker as mticker |
| import cartopy.crs as ccrs |
| import cartopy.feature as cfeature |
| import cartopy.io.shapereader as shpreader |
| from adjustText import adjust_text |
| from ash_animator.interpolation import interpolate_grid |
| from ash_animator.basemaps import draw_etopo_basemap |
| |
| class Plot_Horizontal_Data: |
| def __init__(self, animator, output_dir="plots", cmap="rainbow", fps=2, |
| include_metadata=True, threshold=0.1, |
| zoom_width_deg=6.0, zoom_height_deg=6.0, zoom_level=7, static_frame_export=False): |
| self.animator = animator |
| self.output_dir = os.path.abspath(os.path.join(os.getcwd(), output_dir)) |
| os.makedirs(self.output_dir, exist_ok=True) |
| self.cmap = cmap |
| self.fps = fps |
| self.include_metadata = include_metadata |
| self.threshold = threshold |
| self.zoom_width = zoom_width_deg |
| self.zoom_height = zoom_height_deg |
| shp = shpreader.natural_earth(resolution='110m', category='cultural', name='admin_0_countries') |
| self.country_geoms = list(shpreader.Reader(shp).records()) |
| self.interpolate_grid= interpolate_grid |
| self._draw_etopo_basemap=draw_etopo_basemap |
| self.zoom_level=zoom_level |
| self.static_frame_export=static_frame_export |
| |
| def _make_dirs(self, path): |
| os.makedirs(os.path.abspath(os.path.join(os.getcwd(), os.path.dirname(path))), exist_ok=True) |
| |
| def _get_max_concentration_location(self, field): |
| max_val = -np.inf |
| lat = lon = None |
| for ds in self.animator.datasets: |
| data = ds[field].values |
| if np.max(data) > max_val: |
| max_val = np.max(data) |
| idx = np.unravel_index(np.argmax(data), data.shape) |
| lat = self.animator.lat_grid[idx] |
| lon = self.animator.lon_grid[idx] |
| return lat, lon |
| |
| def _get_zoom_indices(self, center_lat, center_lon): |
| lon_min = center_lon - self.zoom_width / 2 |
| lon_max = center_lon + self.zoom_width / 2 |
| lat_min = center_lat - self.zoom_height / 2 |
| lat_max = center_lat + self.zoom_height / 2 |
| lat_idx = np.where((self.animator.lats >= lat_min) & (self.animator.lats <= lat_max))[0] |
| lon_idx = np.where((self.animator.lons >= lon_min) & (self.animator.lons <= lon_max))[0] |
| return lat_idx, lon_idx, lon_min, lon_max, lat_min, lat_max |
| |
| def _add_country_labels(self, ax, extent): |
| proj = ccrs.PlateCarree() |
| texts = [] |
| for country in self.country_geoms: |
| name = country.attributes['NAME_LONG'] |
| geom = country.geometry |
| try: |
| lon, lat = geom.centroid.x, geom.centroid.y |
| if extent[0] <= lon <= extent[1] and extent[2] <= lat <= extent[3]: |
| text = ax.text(lon, lat, name, fontsize=6, transform=proj, |
| ha='center', va='center', color='white', |
| bbox=dict(facecolor='black', alpha=0.5, linewidth=0)) |
| texts.append(text) |
| except: |
| continue |
| adjust_text(texts, ax=ax, only_move={'points': 'y', 'text': 'y'}, |
| arrowprops=dict(arrowstyle="->", color='white', lw=0.5)) |
| |
| def _draw_metadata_sidebar(self, fig, meta_dict): |
| lines = [ |
| f"Run name: {meta_dict.get('run_name', 'N/A')}", |
| f"Run time: {meta_dict.get('run_time', 'N/A')}", |
| f"Met data: {meta_dict.get('met_data', 'N/A')}", |
| f"Start release: {meta_dict.get('start_of_release', 'N/A')}", |
| f"End release: {meta_dict.get('end_of_release', 'N/A')}", |
| f"Source strength: {meta_dict.get('source_strength', 'N/A')} g/s", |
| f"Release loc: {meta_dict.get('release_location', 'N/A')}", |
| f"Release height: {meta_dict.get('release_height', 'N/A')} m asl", |
| f"Run duration: {meta_dict.get('run_duration', 'N/A')}" |
| ] |
| |
| # Split into two columns |
| mid = len(lines) // 2 + len(lines) % 2 |
| left_lines = lines[:mid] |
| right_lines = lines[mid:] |
| |
| left_text = "\n".join(left_lines) |
| right_text = "\n".join(right_lines) |
| |
| # right column |
| fig.text(0.05, 0.05, left_text, va='bottom', ha='left', |
| fontsize=9, family='monospace', color='black', |
| bbox=dict(facecolor='white', alpha=0.8, edgecolor='gray')) |
| |
| # left column |
| fig.text(0.3, 0.05, right_text, va='bottom', ha='left', |
| fontsize=9, family='monospace', color='black', |
| bbox=dict(facecolor='white', alpha=0.8, edgecolor='gray')) |
| |
| |
| |
| |
| |
| def _plot_frame(self, ax, data, lons, lats, title, levels, scale_label, proj): |
| self._draw_etopo_basemap(ax, mode='basemap', zoom=self.zoom_level) |
| c = ax.contourf(lons, lats, data, levels=levels, cmap=self.cmap, alpha=0.6, transform=proj) |
| ax.set_title(title) |
| ax.set_extent([lons.min(), lons.max(), lats.min(), lats.max()]) |
| ax.coastlines() |
| ax.add_feature(cfeature.BORDERS, linestyle=':') |
| ax.add_feature(cfeature.LAND) |
| ax.add_feature(cfeature.OCEAN) |
| return c |
| |
| def get_available_2d_fields(self): |
| ds = self.animator.datasets[0] |
| return [v for v in ds.data_vars if ds[v].ndim == 2] |
| |
| def plot_single_field_over_time(self, field, filename="field.gif"): |
| output_path = os.path.join(self.output_dir, "2d_fields", field, filename) |
| meta = self.animator.datasets[0].attrs |
| center_lat, center_lon = self._get_max_concentration_location(field) |
| lat_idx, lon_idx, lon_min, lon_max, lat_min, lat_max = self._get_zoom_indices(center_lat, center_lon) |
| lat_zoom = self.animator.lats[lat_idx] |
| lon_zoom = self.animator.lons[lon_idx] |
| |
| valid_frames = [] |
| for t in range(len(self.animator.datasets)): |
| data = self.animator.datasets[t][field].values |
| interp = self.interpolate_grid(data, self.animator.lon_grid, self.animator.lat_grid) |
| if np.isfinite(interp).sum() > 0: |
| valid_frames.append(t) |
| |
| if not valid_frames: |
| print(f"No valid frames to plot for field '{field}'.") |
| return |
| |
| fig = plt.figure(figsize=(16, 8)) |
| proj = ccrs.PlateCarree() |
| ax1 = fig.add_subplot(1, 2, 1, projection=proj) |
| ax2 = fig.add_subplot(1, 2, 2, projection=proj) |
| |
| def update(t): |
| ax1.clear() |
| ax2.clear() |
| data = self.animator.datasets[t][field].values |
| interp = self.interpolate_grid(data, self.animator.lon_grid, self.animator.lat_grid) |
| zoom = interp[np.ix_(lat_idx, lon_idx)] |
| valid = interp[np.isfinite(interp)] |
| if valid.size == 0: |
| return [] |
| |
| min_val, max_val = np.nanmin(valid), np.nanmax(valid) |
| log_cutoff = 1e-3 |
| use_log = min_val > log_cutoff and (max_val / (min_val + 1e-6)) > 100 |
| levels = np.logspace(np.log10(log_cutoff), np.log10(max_val), 20) if use_log else np.linspace(0, max_val, 20) |
| plot_data = np.where(interp > log_cutoff, interp, np.nan) if use_log else interp |
| scale_label = "Log" if use_log else "Linear" |
| |
| c = self._plot_frame(ax1, plot_data, self.animator.lons, self.animator.lats, |
| f"T{t+1} | {field} (Full - {scale_label})", levels, scale_label, proj) |
| self._plot_frame(ax2, zoom, lon_zoom, lat_zoom, |
| f"T{t+1} | {field} (Zoom - {scale_label})", levels, scale_label, proj) |
| |
| self._add_country_labels(ax1, [self.animator.lons.min(), self.animator.lons.max(), |
| self.animator.lats.min(), self.animator.lats.max()]) |
| self._add_country_labels(ax2, [lon_min, lon_max, lat_min, lat_max]) |
| |
| # Inside update() function: |
| if not hasattr(update, "colorbar"): |
| unit_label = f"{field}:({self.animator.datasets[0][field].attrs.get("units", field)})" #self.animator.datasets[0][field].attrs.get("units", field) |
| update.colorbar = fig.colorbar(c, ax=[ax1, ax2], orientation='vertical', label=unit_label) |
| formatter = mticker.FuncFormatter(lambda x, _: f'{x:.2g}') |
| update.colorbar.ax.yaxis.set_major_formatter(formatter) |
| |
| |
| if np.nanmax(valid) > self.threshold: |
| ax1.contour(self.animator.lons, self.animator.lats, interp, levels=[self.threshold], |
| colors='red', linewidths=2, transform=proj) |
| ax2.contour(lon_zoom, lat_zoom, zoom, levels=[self.threshold], |
| colors='red', linewidths=2, transform=proj) |
| ax2.text(0.99, 0.01, f"⚠ Max Thresold Exceed: {np.nanmax(valid):.2f} > {self.threshold}", |
| transform=ax2.transAxes, ha='right', va='bottom', |
| fontsize=9, color='red', |
| bbox=dict(facecolor='white', alpha=0.8, edgecolor='red')) |
| |
| if self.static_frame_export: |
| frame_folder = os.path.join(self.output_dir, "frames", field) |
| os.makedirs(frame_folder, exist_ok=True) |
| frame_path = os.path.join(frame_folder, f"frame_{t+1:04d}.jpg") |
| plt.savefig(frame_path, dpi=300, bbox_inches='tight') |
| print(f"🖼️ Saved static frame: {frame_path}") |
| |
| return [] |
| |
| if self.include_metadata: |
| self._draw_metadata_sidebar(fig, meta) |
| |
| self._make_dirs(output_path) |
| fig.tight_layout() |
| ani = animation.FuncAnimation(fig, update, frames=valid_frames, blit=False, cache_frame_data =False) |
| ani.save(output_path, writer='pillow', fps=self.fps) |
| plt.close() |
| print(f"✅ Saved enhanced 2D animation for {field} to {output_path}") |
| |
| # def export_frames_as_jpgs(self, fields=None, include_metadata=True): |
| # all_fields = self.get_available_2d_fields() |
| # if fields: |
| # fields = [f for f in fields if f in all_fields] |
| # else: |
| # fields = all_fields |
| |
| # meta = self.animator.datasets[0].attrs |
| |
| # for field in fields: |
| # print(f"📤 Exporting frames for field: {field}") |
| # output_folder = os.path.join(self.output_dir, "frames", field) |
| # os.makedirs(output_folder, exist_ok=True) |
| |
| # center_lat, center_lon = self._get_max_concentration_location(field) |
| # lat_idx, lon_idx, lon_min, lon_max, lat_min, lat_max = self._get_zoom_indices(center_lat, center_lon) |
| # lat_zoom = self.animator.lats[lat_idx] |
| # lon_zoom = self.animator.lons[lon_idx] |
| |
| # for t, ds in enumerate(self.animator.datasets): |
| # data = ds[field].values |
| # interp = self.interpolate_grid(data, self.animator.lon_grid, self.animator.lat_grid) |
| # if not np.isfinite(interp).any(): |
| # continue |
| |
| # fig = plt.figure(figsize=(16, 8)) |
| # proj = ccrs.PlateCarree() |
| # ax1 = fig.add_subplot(1, 2, 1, projection=proj) |
| # ax2 = fig.add_subplot(1, 2, 2, projection=proj) |
| # zoom = interp[np.ix_(lat_idx, lon_idx)] |
| # valid = interp[np.isfinite(interp)] |
| # min_val, max_val = np.nanmin(valid), np.nanmax(valid) |
| # log_cutoff = 1e-3 |
| # use_log = min_val > log_cutoff and (max_val / (min_val + 1e-6)) > 100 |
| # levels = np.logspace(np.log10(log_cutoff), np.log10(max_val), 20) if use_log else np.linspace(0, max_val, 20) |
| # plot_data = np.where(interp > log_cutoff, interp, np.nan) if use_log else interp |
| # scale_label = "Log" if use_log else "Linear" |
| |
| # c = self._plot_frame(ax1, plot_data, self.animator.lons, self.animator.lats, |
| # f"T{t+1} | {field} (Full - {scale_label})", levels, scale_label, proj) |
| # self._plot_frame(ax2, zoom, lon_zoom, lat_zoom, |
| # f"T{t+1} | {field} (Zoom - {scale_label})", levels, scale_label, proj) |
| |
| # self._add_country_labels(ax1, [self.animator.lons.min(), self.animator.lons.max(), |
| # self.animator.lats.min(), self.animator.lats.max()]) |
| # self._add_country_labels(ax2, [lon_min, lon_max, lat_min, lat_max]) |
| |
| # if include_metadata: |
| # self._draw_metadata_sidebar(fig, meta) |
| |
| # cbar = fig.colorbar(c, ax=[ax1, ax2], orientation='vertical', shrink=0.75, pad=0.03) |
| # unit_label = f"{field}:({self.animator.datasets[0][field].attrs.get('units', field)})" |
| # cbar.set_label(unit_label) |
| # formatter = mticker.FuncFormatter(lambda x, _: f'{x:.2g}') |
| # cbar.ax.yaxis.set_major_formatter(formatter) |
| |
| # if np.nanmax(valid) > self.threshold: |
| # ax1.contour(self.animator.lons, self.animator.lats, interp, levels=[self.threshold], |
| # colors='red', linewidths=2, transform=proj) |
| # ax2.contour(lon_zoom, lat_zoom, zoom, levels=[self.threshold], |
| # colors='red', linewidths=2, transform=proj) |
| # ax2.text(0.99, 0.01, f"⚠ Max: {np.nanmax(valid):.2f} > {self.threshold}", |
| # transform=ax2.transAxes, ha='right', va='bottom', |
| # fontsize=9, color='red', |
| # bbox=dict(facecolor='white', alpha=0.8, edgecolor='red')) |
| |
| # frame_path = os.path.join(output_folder, f"frame_{t+1:04d}.jpg") |
| # plt.savefig(frame_path, dpi=150, bbox_inches='tight') |
| # plt.close(fig) |
| # print(f"📸 Saved {frame_path}") |
| ''' |
| |
| import os |
| import numpy as np |
| import matplotlib.pyplot as plt |
| import matplotlib.animation as animation |
| import matplotlib.ticker as mticker |
| import cartopy.crs as ccrs |
| import cartopy.feature as cfeature |
| import cartopy.io.shapereader as shpreader |
| from adjustText import adjust_text |
| from ash_animator.interpolation import interpolate_grid |
| from ash_animator.basemaps import draw_etopo_basemap |
|
|
| class Plot_Horizontal_Data: |
| def __init__(self, animator, output_dir="plots", cmap="rainbow", fps=2, |
| include_metadata=True, threshold=0.1, |
| zoom_width_deg=6.0, zoom_height_deg=6.0, zoom_level=7, static_frame_export=False): |
| self.animator = animator |
| self.output_dir = os.path.abspath(os.path.join(os.getcwd(), output_dir)) |
| os.makedirs(self.output_dir, exist_ok=True) |
| self.cmap = cmap |
| self.fps = fps |
| self.include_metadata = include_metadata |
| self.threshold = threshold |
| self.zoom_width = zoom_width_deg |
| self.zoom_height = zoom_height_deg |
| shp = shpreader.natural_earth(resolution='110m', category='cultural', name='admin_0_countries') |
| self.country_geoms = list(shpreader.Reader(shp).records()) |
| self.interpolate_grid= interpolate_grid |
| self._draw_etopo_basemap=draw_etopo_basemap |
| self.zoom_level=zoom_level |
| self.static_frame_export=static_frame_export |
|
|
| def _make_dirs(self, path): |
| os.makedirs(os.path.abspath(os.path.join(os.getcwd(), os.path.dirname(path))), exist_ok=True) |
|
|
| def _get_max_concentration_location(self, field): |
| max_val = -np.inf |
| lat = lon = None |
| for ds in self.animator.datasets: |
| data = ds[field].values |
| if np.max(data) > max_val: |
| max_val = np.max(data) |
| idx = np.unravel_index(np.argmax(data), data.shape) |
| lat = self.animator.lat_grid[idx] |
| lon = self.animator.lon_grid[idx] |
| return lat, lon |
|
|
| def _get_zoom_indices(self, center_lat, center_lon): |
| lon_min = center_lon - self.zoom_width / 2 |
| lon_max = center_lon + self.zoom_width / 2 |
| lat_min = center_lat - self.zoom_height / 2 |
| lat_max = center_lat + self.zoom_height / 2 |
| lat_idx = np.where((self.animator.lats >= lat_min) & (self.animator.lats <= lat_max))[0] |
| lon_idx = np.where((self.animator.lons >= lon_min) & (self.animator.lons <= lon_max))[0] |
| return lat_idx, lon_idx, lon_min, lon_max, lat_min, lat_max |
|
|
| def _add_country_labels(self, ax, extent): |
| proj = ccrs.PlateCarree() |
| texts = [] |
| for country in self.country_geoms: |
| name = country.attributes['NAME_LONG'] |
| geom = country.geometry |
| try: |
| lon, lat = geom.centroid.x, geom.centroid.y |
| if extent[0] <= lon <= extent[1] and extent[2] <= lat <= extent[3]: |
| text = ax.text(lon, lat, name, fontsize=6, transform=proj, |
| ha='center', va='center', color='white', |
| bbox=dict(facecolor='black', alpha=0.5, linewidth=0)) |
| texts.append(text) |
| except: |
| continue |
| adjust_text(texts, ax=ax, only_move={'points': 'y', 'text': 'y'}, |
| arrowprops=dict(arrowstyle="->", color='white', lw=0.5)) |
|
|
| def _draw_metadata_sidebar(self, fig, meta_dict): |
| lines = [ |
| f"Run name: {meta_dict.get('run_name', 'N/A')}", |
| f"Run time: {meta_dict.get('run_time', 'N/A')}", |
| f"Met data: {meta_dict.get('met_data', 'N/A')}", |
| f"Start release: {meta_dict.get('start_of_release', 'N/A')}", |
| f"End release: {meta_dict.get('end_of_release', 'N/A')}", |
| f"Source strength: {meta_dict.get('source_strength', 'N/A')} g/s", |
| f"Release loc: {meta_dict.get('release_location', 'N/A')}", |
| f"Release height: {meta_dict.get('release_height', 'N/A')} m asl", |
| f"Run duration: {meta_dict.get('run_duration', 'N/A')}" |
| ] |
|
|
| |
| mid = len(lines) // 2 + len(lines) % 2 |
| left_lines = lines[:mid] |
| right_lines = lines[mid:] |
|
|
| left_text = "\n".join(left_lines) |
| right_text = "\n".join(right_lines) |
|
|
| |
| fig.text(0.05, 0.05, left_text, va='bottom', ha='left', |
| fontsize=9, family='monospace', color='black', |
| bbox=dict(facecolor='white', alpha=0.8, edgecolor='gray')) |
|
|
| |
| fig.text(0.3, 0.05, right_text, va='bottom', ha='left', |
| fontsize=9, family='monospace', color='black', |
| bbox=dict(facecolor='white', alpha=0.8, edgecolor='gray')) |
|
|
| |
| |
|
|
|
|
| def _plot_frame(self, ax, data, lons, lats, title, levels, scale_label, proj): |
| self._draw_etopo_basemap(ax, mode='basemap', zoom=self.zoom_level) |
| c = ax.contourf(lons, lats, data, levels=levels, cmap=self.cmap, alpha=0.6, transform=proj) |
| ax.set_title(title) |
| ax.set_extent([lons.min(), lons.max(), lats.min(), lats.max()]) |
| ax.coastlines() |
| ax.add_feature(cfeature.BORDERS, linestyle=':') |
| ax.add_feature(cfeature.LAND) |
| ax.add_feature(cfeature.OCEAN) |
| return c |
|
|
| def get_available_2d_fields(self): |
| ds = self.animator.datasets[0] |
| return [v for v in ds.data_vars if ds[v].ndim == 2] |
|
|
| def plot_single_field_over_time(self, field, filename="field.gif"): |
| output_path = os.path.join(self.output_dir, "2d_fields", field, filename) |
| meta = self.animator.datasets[0].attrs |
| center_lat, center_lon = self._get_max_concentration_location(field) |
| lat_idx, lon_idx, lon_min, lon_max, lat_min, lat_max = self._get_zoom_indices(center_lat, center_lon) |
| lat_zoom = self.animator.lats[lat_idx] |
| lon_zoom = self.animator.lons[lon_idx] |
|
|
| valid_frames = [] |
| for t in range(len(self.animator.datasets)): |
| data = self.animator.datasets[t][field].values |
| interp = self.interpolate_grid(data, self.animator.lon_grid, self.animator.lat_grid) |
| if np.isfinite(interp).sum() > 0: |
| valid_frames.append(t) |
|
|
| if not valid_frames: |
| print(f"No valid frames to plot for field '{field}'.") |
| return |
|
|
| fig = plt.figure(figsize=(16, 8)) |
| proj = ccrs.PlateCarree() |
| ax1 = fig.add_subplot(1, 2, 1, projection=proj) |
| ax2 = fig.add_subplot(1, 2, 2, projection=proj) |
|
|
| def update(t): |
| ax1.clear() |
| ax2.clear() |
| data = self.animator.datasets[t][field].values |
| interp = self.interpolate_grid(data, self.animator.lon_grid, self.animator.lat_grid) |
| zoom = interp[np.ix_(lat_idx, lon_idx)] |
| valid = interp[np.isfinite(interp)] |
| if valid.size == 0: |
| return [] |
|
|
| min_val, max_val = np.nanmin(valid), np.nanmax(valid) |
| log_cutoff = 1e-3 |
| use_log = min_val > log_cutoff and (max_val / (min_val + 1e-6)) > 100 |
| levels = np.logspace(np.log10(log_cutoff), np.log10(max_val), 20) if use_log else np.linspace(0, max_val, 20) |
| plot_data = np.where(interp > log_cutoff, interp, np.nan) if use_log else interp |
| scale_label = "Log" if use_log else "Linear" |
|
|
| c = self._plot_frame(ax1, plot_data, self.animator.lons, self.animator.lats, |
| f"T{t+1} | {field} (Full - {scale_label})", levels, scale_label, proj) |
| self._plot_frame(ax2, zoom, lon_zoom, lat_zoom, |
| f"T{t+1} | {field} (Zoom - {scale_label})", levels, scale_label, proj) |
|
|
| self._add_country_labels(ax1, [self.animator.lons.min(), self.animator.lons.max(), |
| self.animator.lats.min(), self.animator.lats.max()]) |
| self._add_country_labels(ax2, [lon_min, lon_max, lat_min, lat_max]) |
|
|
| |
| if not hasattr(update, "colorbar"): |
| unit_label = f"{field}:({self.animator.datasets[0][field].attrs.get('units', field)})" |
| update.colorbar = fig.colorbar(c, ax=[ax1, ax2], orientation='vertical', label=unit_label) |
| formatter = mticker.FuncFormatter(lambda x, _: f'{x:.2g}') |
| update.colorbar.ax.yaxis.set_major_formatter(formatter) |
|
|
| |
| if np.nanmax(valid) > self.threshold: |
| ax1.contour(self.animator.lons, self.animator.lats, interp, levels=[self.threshold], |
| colors='red', linewidths=2, transform=proj) |
| ax2.contour(lon_zoom, lat_zoom, zoom, levels=[self.threshold], |
| colors='red', linewidths=2, transform=proj) |
| ax2.text(0.99, 0.01, f"⚠ Max Thresold Exceed: {np.nanmax(valid):.2f} > {self.threshold}", |
| transform=ax2.transAxes, ha='right', va='bottom', |
| fontsize=9, color='red', |
| bbox=dict(facecolor='white', alpha=0.8, edgecolor='red')) |
|
|
| if self.static_frame_export: |
| frame_folder = os.path.join(self.output_dir, "frames", field) |
| os.makedirs(frame_folder, exist_ok=True) |
| frame_path = os.path.join(frame_folder, f"frame_{t+1:04d}.jpg") |
| plt.savefig(frame_path, dpi=300, bbox_inches='tight') |
| print(f"🖼️ Saved static frame: {frame_path}") |
| |
| return [] |
|
|
| if self.include_metadata: |
| self._draw_metadata_sidebar(fig, meta) |
|
|
| self._make_dirs(output_path) |
| fig.tight_layout() |
| ani = animation.FuncAnimation(fig, update, frames=valid_frames, blit=False, cache_frame_data =False) |
| ani.save(output_path, writer='pillow', fps=self.fps) |
| plt.close() |
| print(f"✅ Saved enhanced 2D animation for {field} to {output_path}") |
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