Dendrogram
Circular Cluster Heatmap Dark
Circular dendrogram with heatmap-style colored sectors
Output
Python
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 Wedge
from matplotlib.colors import LinearSegmentedColormap
np.random.seed(789)
n = 18
labels = [f'V{i}' for i in range(1, n+1)]
data = np.random.rand(n, 5) * 100
values = data.mean(axis=1)
Z = linkage(data, method='ward')
fig_temp, ax_temp = plt.subplots()
set_link_color_palette(['#F5276C', '#27D3F5', '#6CF527', '#F5B027'])
dn = dendrogram(Z, labels=labels, no_plot=False, color_threshold=0.5*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 * 0.9 + np.pi * 0.05
r = y / y_max * 0.5 + 0.45
return theta, r
fig, ax = plt.subplots(figsize=(10, 10), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')
ax.set_aspect('equal')
# Heatmap wedges
cmap = LinearSegmentedColormap.from_list('neon', ['#0a0a0f', '#4927F5', '#27D3F5', '#6CF527', '#F5B027'])
norm_values = (values - values.min()) / (values.max() - values.min())
leaf_positions = np.linspace(x_min, x_max, n)
for i, (pos, val) in enumerate(zip(leaf_positions, norm_values)):
theta, _ = to_polar(pos, 0)
theta_deg = np.degrees(theta)
wedge_width = 360 / n * 0.8
color = cmap(val)
wedge = Wedge((0, 0), 0.42, theta_deg - wedge_width/2, theta_deg + wedge_width/2,
width=0.12, facecolor=color, edgecolor='#0a0a0f', linewidth=0.5)
ax.add_patch(wedge)
# Convert to cartesian for ax.plot
def polar_to_cart(theta, r):
return r * np.cos(theta), r * np.sin(theta)
for ic, dc, color in zip(icoord, dcoord, colors):
coords = []
for x, y in zip(ic, dc):
t, r = to_polar(x, y)
coords.append((t, r))
# Vertical lines
x1, y1 = polar_to_cart(coords[0][0], coords[0][1])
x2, y2 = polar_to_cart(coords[1][0], coords[1][1])
ax.plot([x1, x2], [y1, y2], color=color, linewidth=2, alpha=0.9)
x1, y1 = polar_to_cart(coords[2][0], coords[2][1])
x2, y2 = polar_to_cart(coords[3][0], coords[3][1])
ax.plot([x1, x2], [y1, y2], color=color, linewidth=2, alpha=0.9)
# Arc
if coords[1][0] != coords[2][0]:
arc_thetas = np.linspace(min(coords[1][0], coords[2][0]), max(coords[1][0], coords[2][0]), 40)
arc_x = [coords[1][1] * np.cos(t) for t in arc_thetas]
arc_y = [coords[1][1] * np.sin(t) for t in arc_thetas]
ax.plot(arc_x, arc_y, color=color, linewidth=2, alpha=0.9)
# Labels
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'
x, y = 0.22 * np.cos(theta), 0.22 * np.sin(theta)
ax.text(x, y, label, ha=ha, va='center', fontsize=7, color='white',
rotation=rotation, rotation_mode='anchor')
ax.set_xlim(-1.1, 1.1)
ax.set_ylim(-1.1, 1.1)
ax.axis('off')
ax.set_title('Circular Cluster Heatmap', fontsize=14, color='white', fontweight='bold', y=1.02)
plt.tight_layout()
plt.show()
Library
Matplotlib
Category
Statistical
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