uvisbox.Modules.ProbabilisticMarchingTriangles.probabilistic_marching_triangles

Module Contents

uvisbox.Modules.ProbabilisticMarchingTriangles.probabilistic_marching_triangles.probabilistic_marching_triangles(ensemble_data, triangle_mesh, points, isovalue, ax=None, colormap='viridis')[source]

Compute and visualize probabilistic marching triangles.

This function implements the complete stats->mesh->vis pipeline for probabilistic marching triangles visualization. It calculates the probability of isocontour presence in each triangle and creates a matplotlib visualization.

Parameters:

  • ensemble_data (np.ndarray) – 2D array of shape (n_points, n_ensemble) where each column is a realization and each row corresponds to a vertex in the triangular mesh.

  • triangle_mesh (np.ndarray) – 2D array of shape (n_triangles, 3) with triangle indices.

  • points (np.ndarray) – 2D array of shape (n_points, 2) with point coordinates.

  • isovalue (float) – The isovalue for which to compute the isocontour.

  • ax (matplotlib.axes.Axes, optional) – The axis to draw on. If None, a new figure and axis will be created.

  • colormap (str, optional) – Colormap for the visualization. Default is ‘viridis’.

Returns:

ax – The axis with the visualized probabilistic isocontour.

Return type:

matplotlib.axes.Axes