Dendrogram
Real Circular Dendrogram Light
True circular dendrogram with scipy transformation on light background
Output
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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