Dendrogram

Real Circular Dendrogram Light

True circular dendrogram with scipy transformation on light background

Output
Real Circular Dendrogram Light
Python
import matplotlib.pyplot as plt
import numpy as np
from scipy.cluster.hierarchy import dendrogram, linkage, set_link_color_palette

np.random.seed(42)

n_samples = 20
labels = [f'S{i}' for i in range(1, n_samples + 1)]
data = np.random.rand(n_samples, 5) * 100
Z = linkage(data, method='ward')

fig_temp, ax_temp = plt.subplots()
set_link_color_palette(['#F5276C', '#27D3F5', '#6CF527', '#F5B027', '#4927F5'])
dn = dendrogram(Z, no_plot=False, color_threshold=0.7*max(Z[:,2]), 
                above_threshold_color='#9ca3af', 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 + np.pi * 0.025
    r = y / y_max * 0.7 + 0.25
    return theta, r

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

for i, (ic, dc, color) in enumerate(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=2.5, alpha=0.9)
    ax.plot([thetas[2], thetas[3]], [rs[2], rs[3]], color=color, linewidth=2.5, alpha=0.9)
    
    if thetas[1] != thetas[2]:
        arc_thetas = np.linspace(min(thetas[1], thetas[2]), max(thetas[1], thetas[2]), 30)
        ax.plot(arc_thetas, [rs[1]]*len(arc_thetas), color=color, linewidth=2.5, alpha=0.9)

leaf_positions = np.linspace(x_min, x_max, n_samples)
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, 0.18, label, ha=ha, va='center', fontsize=8, color='#374151',
            rotation=rotation, rotation_mode='anchor')
    
    color = ['#F5276C', '#27D3F5', '#6CF527', '#F5B027', '#4927F5'][i % 5]
    ax.scatter(theta, 0.25, c=color, s=40, zorder=5, edgecolor='#ffffff', linewidth=1)

ax.set_ylim(0, 1.05)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.spines['polar'].set_visible(False)
ax.grid(True, color='#e5e7eb', alpha=0.6, linestyle='-')

ax.set_title('Circular Hierarchical Clustering', fontsize=14, color='#1f2937', fontweight='bold', y=1.08)

plt.tight_layout()
plt.show()
Library

Matplotlib

Category

Statistical

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