Tree Diagram

# === IMPORTS ===
import numpy as np
import matplotlib.pyplot as plt
from scipy.cluster.hierarchy import dendrogram, linkage
import matplotlib.patheffects as pe
from matplotlib.patches import Rectangle

# === USER-EDITABLE PARAMETERS ===
title = "Phylogenetic Tree — Mammalian Species Clustering"
figsize = (14, 10)

# === EXAMPLE DATASET ===
np.random.seed(42)

# Species grouped by evolutionary proximity
species = [
    # Felines
    'Lion', 'Tiger', 'Leopard', 'Domestic Cat',
    # Canines  
    'Wolf', 'Dog', 'Fox',
    # Ursids
    'Brown Bear', 'Polar Bear', 'Black Bear',
    # Large Herbivores
    'Elephant', 'Rhino', 'Hippo'
]

# Create feature matrix simulating genetic distances
n_species = len(species)
features = np.zeros((n_species, 8))

# Felines (0-3) - close genetic features
features[0:4, 0:2] = np.random.normal(10, 0.5, (4, 2))
features[0:4, 2] = np.random.normal(5, 0.3, 4)

# Canines (4-6)
features[4:7, 2:4] = np.random.normal(8, 0.5, (3, 2))
features[4:7, 4] = np.random.normal(6, 0.3, 3)

# Ursids (7-9)
features[7:10, 4:6] = np.random.normal(7, 0.5, (3, 2))
features[7:10, 6] = np.random.normal(4, 0.3, 3)

# Large Herbivores (10-12)
features[10:13, 6:8] = np.random.normal(9, 0.5, (3, 2))

# Add noise
features += np.random.normal(0, 0.2, features.shape)

# Calculate linkage
Z = linkage(features, method='ward')

# Print summary
print("=== Phylogenetic Analysis ===")
print(f"\nSpecies: {n_species}")
print(f"\nExpected clusters:")
print(f"  Felines: Lion, Tiger, Leopard, Domestic Cat")
print(f"  Canines: Wolf, Dog, Fox")  
print(f"  Ursids: Brown Bear, Polar Bear, Black Bear")
print(f"  Large Herbivores: Elephant, Rhino, Hippo")

# === CREATE DENDROGRAM ===
fig, ax = plt.subplots(figsize=figsize, facecolor='#0d1117')
ax.set_facecolor('#0d1117')

# Custom colors for clusters
cluster_colors = ['#FF6B6B', '#4ECDC4', '#45B7D1', '#96CEB4']
color_threshold = 6

# Create dendrogram with custom styling
dendro = dendrogram(
    Z,
    labels=species,
    leaf_rotation=45,
    leaf_font_size=12,
    color_threshold=color_threshold,
    above_threshold_color='#636e72',
    ax=ax
)

# Color the dendrogram lines
for i, d in zip(dendro['icoord'], dendro['dcoord']):
    x = 0.5 * sum(i[1:3])
    y = d[1]
    
# Style leaf labels
for label in ax.get_xticklabels():
    label.set_color('white')
    label.set_fontweight('bold')
    label.set_fontsize(11)

# Add horizontal threshold line
ax.axhline(y=color_threshold, color='#FFD93D', linestyle='--', linewidth=2, 
           alpha=0.8, label=f'Cluster threshold (d={color_threshold})')

# Add cluster annotations with boxes
cluster_info = [
    (1.5, -1.5, 'Felines', '#FF6B6B'),
    (5.5, -1.5, 'Canines', '#4ECDC4'),
    (8.5, -1.5, 'Ursids', '#45B7D1'),
    (11.5, -1.5, 'Large Herbivores', '#96CEB4')
]

for x, y, label, color in cluster_info:
    ax.annotate(label, xy=(x * 10, y), fontsize=11, fontweight='bold',
                color=color, ha='center', va='top',
                bbox=dict(boxstyle='round,pad=0.3', facecolor='#161b22', 
                         edgecolor=color, linewidth=2))

# Styling
ax.set_xlabel('Species', fontsize=14, color='#e6edf3', fontweight='bold', labelpad=50)
ax.set_ylabel('Genetic Distance', fontsize=14, color='#e6edf3', fontweight='bold')
ax.set_title(title, fontsize=22, fontweight='bold', color='white', pad=20,
             path_effects=[pe.withStroke(linewidth=3, foreground='#238636')])

# Style axes
ax.tick_params(colors='#e6edf3', labelsize=10)
ax.spines['bottom'].set_color('#30363d')
ax.spines['left'].set_color('#30363d')
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)

# Grid
ax.grid(True, alpha=0.1, color='white', axis='y')
ax.set_axisbelow(True)

# Legend
legend = ax.legend(loc='upper right', facecolor='#161b22', edgecolor='#30363d',
                   labelcolor='white', fontsize=11)

# Info box
info_text = f'Clustering: Ward\'s method | Species: {n_species}'
ax.text(0.02, 0.98, info_text, transform=ax.transAxes, fontsize=10,
        color='#888', ha='left', va='top',
        bbox=dict(boxstyle='round', facecolor='#161b22', alpha=0.8, edgecolor='#30363d'))

plt.tight_layout()
plt.savefig('chart.png', dpi=150, bbox_inches='tight', facecolor='#0d1117')
print("Saved: chart.png")
plt.show()
# END-OF-CODE

=== Phylogenetic Analysis ===

Species: 13

Expected clusters:
  Felines: Lion, Tiger, Leopard, Domestic Cat
  Canines: Wolf, Dog, Fox
  Ursids: Brown Bear, Polar Bear, Black Bear
  Large Herbivores: Elephant, Rhino, Hippo
Saved: chart.png