uvisbox.Modules.SquidGlyphs.squid_glyphs_stats

Module Contents

uvisbox.Modules.SquidGlyphs.squid_glyphs_stats.squid_glyphs_2d_summary_statistics(ensemble_vectors, percentile, workers=None)[source]

Compute vector depth statistics for 2D squid glyphs.

Parameters:

  • ensemble_vectors (numpy.ndarray) – Shape (n, m, 2) - Cartesian ensemble vectors

  • percentile (float) – Percentile of ensemble members to include based on depth ranking (0-100). Higher values include more vectors (larger glyphs showing more variation). For example, 50 includes the deepest 50%, 95 includes the deepest 95%, and 100 includes all vectors.

  • workers (int, optional) – Number of parallel workers for depth computation. Default is None (sequential)

Returns:

stats_2d – Contains ensemble_polar_vectors, depths, median_vectors, magnitudes_min, magnitudes_max, angles_min, and angles_max.

Return type:

dict

uvisbox.Modules.SquidGlyphs.squid_glyphs_stats.squid_glyphs_3d_summary_statistics(ensemble_vectors, percentile)[source]

Compute vector depth statistics for 3D squid glyphs.

Parameters:

  • ensemble_vectors (numpy.ndarray) – Shape (n, m, 3) - Cartesian ensemble vectors

  • percentile (float) – Percentile of ensemble members to include based on depth ranking (0-100). Higher values include more vectors (larger glyphs showing more variation). For example, 50 includes the deepest 50%, 95 includes the deepest 95%, and 100 includes all vectors.

Returns:

stats_3d – Contains ensemble_spherical_vectors, depths, median_vectors, spread_min_vectors, spread_max_vectors, glyph_types, pca_components, and num_glyphs.

Return type:

dict

uvisbox.Modules.SquidGlyphs.squid_glyphs_stats.getDirectionalVariations(vectors, depths, percentile, min_vectors, median_vectors, max_vectors)[source]

Compute the directional variation of the vectors.

Parameters:

  • vectors (numpy.ndarray) – Array of shape (num_points, num_ensemble_members, 3) where the last dimension contains the vector components.

  • depths (numpy.ndarray) – Array of shape (num_points, num_ensemble_members) containing depth values for each vector.

  • percentile (float) – Percentile of ensemble members to include (0-100). Higher values include more vectors.

  • min_vectors (numpy.ndarray) – Array of shape (num_points, 3) where the last dimension contains the min vector components.

  • median_vectors (numpy.ndarray) – Array of shape (num_points, 3) where the last dimension contains the median vector components.

  • max_vectors (numpy.ndarray) – Array of shape (num_points, 3) where the last dimension contains the max vector components.

Returns:

directional_variation – Array of shape (num_points, 3, 2) where the 3 represents the (pca first component, pca second component, pca mean) and the 2 represents the x and y components of the pca components.

Return type:

numpy.ndarray