Dendrogram

Radial Average Linkage Dark

Average linkage clustering displayed in radial format

Output
Radial Average Linkage Dark
Python
import matplotlib.pyplot as plt
import numpy as np
from scipy.cluster.hierarchy import dendrogram, linkage, set_link_color_palette

np.random.seed(654)

samples = ['Sample_' + str(i) for i in range(1, 17)]
n = len(samples)
data = np.random.rand(n, 7) * 90
Z = linkage(data, method='average')

fig_temp, ax_temp = plt.subplots()
set_link_color_palette(['#F5276C', '#27D3F5', '#6CF527', '#F5B027', '#4927F5'])
dn = dendrogram(Z, labels=samples, no_plot=False, color_threshold=0.6*max(Z[:,2]),
                above_threshold_color='#555555', 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 * 0.92 + np.pi * 0.04
    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')

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)
    
    # Draw with glow
    for lw, alpha in [(5, 0.12), (2.5, 0.85)]:
        ax.plot([thetas[0], thetas[1]], [rs[0], rs[1]], color=color, linewidth=lw, alpha=alpha)
        ax.plot([thetas[2], thetas[3]], [rs[2], rs[3]], color=color, linewidth=lw, alpha=alpha)
        if thetas[1] != thetas[2]:
            arc_thetas = np.linspace(min(thetas[1], thetas[2]), max(thetas[1], thetas[2]), 40)
            ax.plot(arc_thetas, [rs[1]]*len(arc_thetas), color=color, linewidth=lw, alpha=alpha)

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'
    short_label = label.replace('Sample_', 'S')
    ax.text(theta, 0.28, short_label, ha=ha, va='center', fontsize=8, color='#888888',
            rotation=rotation, rotation_mode='anchor')
    
    color = ['#F5276C', '#27D3F5', '#6CF527', '#F5B027', '#4927F5'][i % 5]
    ax.scatter(theta, 0.4, c=color, s=50, zorder=5, edgecolor='white', linewidth=0.8)

ax.set_ylim(0, 1.02)
ax.set_yticklabels([])
ax.set_xticklabels([])
ax.spines['polar'].set_visible(False)
ax.grid(True, color='#222222', alpha=0.4, linestyle=':')

ax.set_title('Average Linkage - Radial View', fontsize=14, color='white', fontweight='bold', y=1.08)

plt.tight_layout()
plt.show()
Library

Matplotlib

Category

Statistical

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