xyz_coloring.py

"""Trying to recreate the 'repli_cube' mechanic"""
from itertools import product
import pandas as pd
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np

coordinates_range = range(-2,3)

combinations = list(product(coordinates_range, repeat=3))
cols = list(zip(*combinations))

df = pd.DataFrame({"x":(cols[0]),
                   "y":(cols[1]),
                   "z":(cols[2]),
                   "value":(0*len(cols))},
                   dtype=int)
print(df)

# Create 3D visualization
fig = plt.figure(figsize=(10, 8))
ax = fig.add_subplot(111, projection='3d')

# Color points by distance from origin
distances = np.sqrt(df['x']**2 + df['y']**2 + df['z']**2)

# Create scatter plot
scatter = ax.scatter(df['x'].values, df['y'].values, df['z'].values,
                     c=distances.values, cmap='viridis',
                     s=100, alpha=0.6, edgecolors='w', linewidth=0.5)

ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
ax.set_title('3D Data Visualization\n(Colored by Distance from Origin)')

# Add colorbar
colorbar = plt.colorbar(scatter, ax=ax, pad=0.1, shrink=0.8)
colorbar.set_label('Distance from Origin')

plt.tight_layout()
plt.show()