Polar Ward Clustering Dark

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

np.random.seed(321)

n = 24
labels = [chr(65 + i) if i < 26 else f'A{i-26}' for i in range(n)]
data = np.random.rand(n, 6) * 80
Z = linkage(data, method='ward')

fig_temp, ax_temp = plt.subplots()
set_link_color_palette(['#27D3F5', '#F5276C', '#6CF527', '#F5B027', '#5314E6', '#F527B0'])
dn = dendrogram(Z, labels=labels, no_plot=False, color_threshold=0.55*max(Z[:,2]),
                above_threshold_color='#444444', ax=ax_temp)
plt.close(fig_temp)

icoord = np.array(dn['icoord'])
dcoord = np.array(dn['dcoord'])
colors = dn['color_list']

x_min, x_max = icoord.min(), icoord.max()
y_max = dcoord.max()

def to_polar(x, y):
    theta = (x - x_min) / (x_max - x_min) * 2 * np.pi * 0.95
    r = y / y_max * 0.55 + 0.4
    return theta, r

fig, ax = plt.subplots(figsize=(10, 10), subplot_kw={'projection': 'polar'}, facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

# Concentric rings
for r, alpha in [(0.5, 0.15), (0.7, 0.1), (0.9, 0.05)]:
    circle_theta = np.linspace(0, 2*np.pi, 100)
    ax.fill(circle_theta, [r]*100, color='#27D3F5', alpha=alpha)

for ic, dc, color in zip(icoord, dcoord, colors):
    thetas, rs = [], []
    for x, y in zip(ic, dc):
        t, r = to_polar(x, y)
        thetas.append(t)
        rs.append(r)
    
    ax.plot([thetas[0], thetas[1]], [rs[0], rs[1]], color=color, linewidth=2, alpha=0.95)
    ax.plot([thetas[2], thetas[3]], [rs[2], rs[3]], color=color, linewidth=2, alpha=0.95)
    if thetas[1] != thetas[2]:
        arc_thetas = np.linspace(min(thetas[1], thetas[2]), max(thetas[1], thetas[2]), 50)
        ax.plot(arc_thetas, [rs[1]]*len(arc_thetas), color=color, linewidth=2, alpha=0.95)

leaf_positions = np.linspace(x_min, x_max, n)
for i, (pos, label) in enumerate(zip(leaf_positions, dn['ivl'])):
    theta, _ = to_polar(pos, 0)
    rotation = np.degrees(theta) - 90 if np.pi/2 < theta < 3*np.pi/2 else np.degrees(theta) + 90
    ha = 'right' if np.pi/2 < theta < 3*np.pi/2 else 'left'
    ax.text(theta, 0.28, label, ha=ha, va='center', fontsize=7, color='white',
            rotation=rotation, rotation_mode='anchor', fontweight='bold')
    
    color = ['#27D3F5', '#F5276C', '#6CF527', '#F5B027', '#5314E6', '#F527B0'][i % 6]
    ax.scatter(theta, 0.4, c=color, s=35, zorder=5, edgecolor='white', linewidth=0.5)

ax.set_ylim(0, 1.02)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.spines['polar'].set_visible(False)
ax.grid(False)

ax.set_title('Ward Clustering - Polar View', fontsize=14, color='white', fontweight='bold', y=1.08)

plt.tight_layout()
plt.show()