att.viz

Visualization utilities for ATT.

att.viz.plot_persistence_diagram(diagrams, ax=None, colormap='viridis')

Plot persistence diagrams for all homology dimensions.

Parameters:

• diagrams (list[ndarray])

• ax (Axes | None)

• colormap (str)

Return type:

Figure

att.viz.plot_persistence_image(images, ax=None, colormap='hot')

Plot persistence images for all homology dimensions.

Parameters:

• images (list[ndarray])

• ax (Axes | None)

• colormap (str)

Return type:

Figure

att.viz.plot_barcode(diagrams, ax=None)

Plot persistence barcodes.

Parameters:

• diagrams (list[ndarray])

• ax (Axes | None)

Return type:

Figure

att.viz.plot_betti_curve(betti_curves, ax=None)

Plot Betti curves.

Parameters:

• betti_curves (list[ndarray])

• ax (Axes | None)

Return type:

Figure

att.viz.plot_attractor_3d(cloud, color_by='time', backend='plotly')

3D scatter/line plot of an attractor point cloud.

Parameters:

• cloud ((n_points, 3+) array — uses first 3 columns)

• color_by ("time" (color by index))

• backend ("plotly" or "matplotlib")

att.viz.plot_surrogate_distribution(observed, surrogates, ax=None)

Histogram of surrogate scores with observed score marked.

Parameters:

• observed (float)

• surrogates (ndarray)

• ax (Axes | None)

Return type:

Figure

att.viz.plot_benchmark_sweep(results, ax=None)

Plot benchmark sweep with all methods overlaid.

Parameters:

results (pd.DataFrame with columns coupling, method, score, score_normalized)

Return type:

Figure

att.viz.plot_binding_comparison(detector)

3-panel comparison: marginal X | joint (excess highlighted) | marginal Y.

Parameters:

detector (BindingDetector with fitted state)

Return type:

matplotlib Figure

att.viz.plot_binding_image(images, colormap='RdBu_r')

Heatmap of residual persistence images.

Parameters:

• images (list of (resolution, resolution) residual images, one per dimension)

• colormap (diverging colormap (red=emergent, blue=deficit))

Return type:

matplotlib Figure

att.viz.plot_transition_timeline(detector, ground_truth=None, figsize=(12, 6))

Plot topology transition timeline from a fitted TransitionDetector.

Parameters:

• detector (TransitionDetector) – Must have been fit_transform()’d.

• ground_truth (list of int or None) – True transition sample indices (plotted as green dotted lines).

• figsize (tuple) – Figure size.

Return type:

matplotlib Figure

att.viz.export_to_json(results, path)

Export computed results as JSON.

Parameters:

• results (dict)

• path (str)

Return type:

None

att.viz.load_from_json(path)

Load results from JSON.

Parameters:

path (str)

Return type:

dict

Publication-quality plotting utilities.

att.viz.plotting.plot_persistence_diagram(diagrams, ax=None, colormap='viridis')

Plot persistence diagrams for all homology dimensions.

Parameters:

• diagrams (list[ndarray])

• ax (Axes | None)

• colormap (str)

Return type:

Figure

att.viz.plotting.plot_persistence_image(images, ax=None, colormap='hot')

Plot persistence images for all homology dimensions.

Parameters:

• images (list[ndarray])

• ax (Axes | None)

• colormap (str)

Return type:

Figure

att.viz.plotting.plot_barcode(diagrams, ax=None)

Plot persistence barcodes.

Parameters:

• diagrams (list[ndarray])

• ax (Axes | None)

Return type:

Figure

att.viz.plotting.plot_betti_curve(betti_curves, ax=None)

Plot Betti curves.

Parameters:

• betti_curves (list[ndarray])

• ax (Axes | None)

Return type:

Figure

att.viz.plotting.plot_attractor_3d(cloud, color_by='time', backend='plotly')

3D scatter/line plot of an attractor point cloud.

Parameters:

• cloud ((n_points, 3+) array — uses first 3 columns)

• color_by ("time" (color by index))

• backend ("plotly" or "matplotlib")

att.viz.plotting.plot_surrogate_distribution(observed, surrogates, ax=None)

Histogram of surrogate scores with observed score marked.

Parameters:

• observed (float)

• surrogates (ndarray)

• ax (Axes | None)

Return type:

Figure

att.viz.plotting.plot_benchmark_sweep(results, ax=None)

Plot benchmark sweep with all methods overlaid.

Parameters:

results (pd.DataFrame with columns coupling, method, score, score_normalized)

Return type:

Figure

att.viz.plotting.plot_binding_comparison(detector)

3-panel comparison: marginal X | joint (excess highlighted) | marginal Y.

Parameters:

detector (BindingDetector with fitted state)

Return type:

matplotlib Figure

att.viz.plotting.plot_binding_image(images, colormap='RdBu_r')

Heatmap of residual persistence images.

Parameters:

• images (list of (resolution, resolution) residual images, one per dimension)

• colormap (diverging colormap (red=emergent, blue=deficit))

Return type:

matplotlib Figure

att.viz.plotting.export_to_json(results, path)

Export computed results as JSON.

Parameters:

• results (dict)

• path (str)

Return type:

None

att.viz.plotting.load_from_json(path)

Load results from JSON.

Parameters:

path (str)

Return type:

dict

att.viz.plotting.plot_transition_timeline(detector, ground_truth=None, figsize=(12, 6))

Plot topology transition timeline from a fitted TransitionDetector.

Parameters:

• detector (TransitionDetector) – Must have been fit_transform()’d.

• ground_truth (list of int or None) – True transition sample indices (plotted as green dotted lines).

• figsize (tuple) – Figure size.

Return type:

matplotlib Figure