white regions in voronoi diagram

Question

help pls How i can color the unfilled (white) regions in the corresponding color points, just like all the others? the code accepts several clusters as input, gives each a light and builds a corresponding Voronoi diagram, marking in bold the boundaries between different clusters

the code accepts several clusters as input, gives each a light and builds a corresponding Voronoi diagram, marking in bold the boundaries between different clusters

from scipy.spatial import Voronoi, voronoi_plot_2d
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap

np.random.seed(10001100)
n = 5  # Number of series
num_points_per_series = 10

cluster_distance = 1.0

all_points = []
points_clustering = []
for i in range(n):
    cluster_center = np.random.randn(2) * cluster_distance
    points = cluster_center + np.random.randn(num_points_per_series, 2) * 0.5  # Adding randomness within each cluster
    all_points.extend(points)
    points_clustering.extend([i] * num_points_per_series)  # Track the cluster of each point

# Compute Voronoi diagram for all points
vor = Voronoi(np.array(all_points))

# Function to get point color by cluster
def get_point_color(cluster_index, n_clusters):
    # Generate a colormap for n_clusters discrete colors:
    cmap = plt.get_cmap('viridis')
    colors = cmap(np.linspace(0, 1, n_clusters))
    discrete_cmap = ListedColormap(colors)

    # Now, use the cluster_index to get the color from the discrete colormap
    return discrete_cmap.colors[cluster_index]

def plot_filled_voronoi_with_boundaries2(vor, points_clustering, n_clusters):
    fig, ax = plt.subplots()

    # Generate colormap for n_clusters discrete colors
    cmap = ListedColormap(plt.cm.viridis(np.linspace(0, 1, n_clusters)))

    # Plot Voronoi diagram boundaries and filled regions
    voronoi_plot_2d(vor, ax=ax, show_vertices=False, line_colors='black', line_width=0.5)

    # Fill Voronoi regions and thicken boundary lines between different clusters
    for point_idx, region in enumerate(vor.point_region):
        polygons = vor.regions[region]
        if all(v >= 0 for v in polygons):  # Check the region vertices are valid (not -1, which indicates an open region)
            polygon = [vor.vertices[i] for i in polygons]
            region_color = get_point_color(points_clustering[point_idx], n_clusters)
            plt.fill(*zip(*polygon), alpha=0.5, color=region_color)

    for ridge_points, ridge_vertices in zip(vor.ridge_points, vor.ridge_vertices):
        if all(v != -1 for v in ridge_vertices):
            v1, v2 = ridge_vertices
            p1, p2 = ridge_points
            if points_clustering[p1] != points_clustering[p2]:
                plt.plot(vor.vertices[[v1, v2], 0], vor.vertices[[v1, v2], 1], 'k-', linewidth=2)

    # Mark the original points
    for point_idx, point in enumerate(vor.points):
        plt.scatter(point[0], point[1], color=get_point_color(points_clustering[point_idx], n_clusters), edgecolor='black', zorder=2)

    plt.show()

# Call function with vor, points_clustering and n
plot_filled_voronoi_with_boundaries2(vor, points_clustering, n)

im looking into code... try replace all(v>=0) to any or True