Cluster Highlight Dendrogram Dark

import matplotlib.pyplot as plt
import numpy as np
from scipy.cluster.hierarchy import dendrogram, linkage, fcluster, set_link_color_palette
from matplotlib.patches import Rectangle

np.random.seed(42)

labels = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L']
data = np.random.rand(len(labels), 5) * 100
Z = linkage(data, method='ward')

fig, ax = plt.subplots(figsize=(14, 8), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

set_link_color_palette(['#F5276C', '#27D3F5', '#6CF527', '#F5B027', '#4927F5'])

dn = dendrogram(Z, labels=labels, leaf_rotation=0, leaf_font_size=11,
                color_threshold=0.5*max(Z[:,2]), above_threshold_color='#444444', ax=ax)

# Add colored rectangles for clusters
clusters = fcluster(Z, t=3, criterion='maxclust')
colors = ['#F5276C33', '#27D3F533', '#6CF52733']
ivl = dn['ivl']
leaves = dn['leaves']

cluster_ranges = {}
for i, (leaf, label) in enumerate(zip(leaves, ivl)):
    c = clusters[leaf]
    if c not in cluster_ranges:
        cluster_ranges[c] = [i, i]
    else:
        cluster_ranges[c][1] = i

for c, (start, end) in cluster_ranges.items():
    rect = Rectangle((start*10 - 5, 0), (end - start + 1)*10, max(Z[:,2])*0.95,
                     facecolor=colors[(c-1) % len(colors)], edgecolor='none', zorder=0)
    ax.add_patch(rect)

ax.set_title('Hierarchical Clustering with Cluster Highlights', fontsize=15, 
             color='white', fontweight='bold', pad=20)
ax.set_xlabel('Samples', fontsize=11, color='#888888')
ax.set_ylabel('Distance', fontsize=11, color='#888888')
ax.tick_params(axis='both', colors='#888888', labelsize=10)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_color('#333333')
ax.spines['bottom'].set_color('#333333')

plt.tight_layout()
plt.show()