import matplotlib.pyplot as plt
[docs]
def visualize_probabilistic_marching_squares(summary_statistics, ax=None, colormap='viridis'):
"""
Visualize the probability map of isocontour presence using matplotlib.
Parameters:
-----------
summary_statistics : np.ndarray
2D array of shape (y_dim-1, x_dim-1) with probabilities of contour
presence in each cell.
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 probability map. Default is 'viridis'.
Returns:
--------
ax : matplotlib.axes.Axes
The axis with the visualized probabilistic isocontour.
"""
if ax is None:
fig, ax = plt.subplots(figsize=(8, 6))
im = ax.imshow(summary_statistics, origin='lower', cmap=colormap, vmin=0, vmax=1)
cbar = plt.colorbar(im, ax=ax, label='probability of contour')
ax.set_title('Probabilistic Marching Squares')
ax.set_xlabel('x')
ax.set_ylabel('y')
return ax