import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D import numpy as np def read_xyz(filename): """ Reads an XYZ file and returns coordinates and atom types. """ coords = [] atoms = [] with open(filename, 'r') as f: lines = f.readlines() # Skip header lines (first 2) for line in lines[2:]: parts = line.split() atoms.append(parts[0]) coords.append([float(parts[1]), float(parts[2]), float(parts[3])]) return np.array(coords), atoms def plot_crystal(ax, coords, atoms, title): """ Plots a single crystal in a 3D subplot. """ # Define colors for atoms (Titanium=Silver, Oxygen=Red, Ca=Green) colors = {'Ti': 'gray', 'O': 'red', 'Ca': 'green', 'Pb': 'black', 'I': 'purple'} # Scatter plot # s=size of atom, alpha=transparency for i, atom in enumerate(atoms): color = colors.get(atom, 'blue') # Default to blue if unknown ax.scatter(coords[i,0], coords[i,1], coords[i,2], c=color, s=200, edgecolors='k', alpha=0.8) # Draw "bonds" (lines between atoms close to each other) # This helps visualize the structure num_atoms = len(coords) for i in range(num_atoms): for j in range(i + 1, num_atoms): dist = np.linalg.norm(coords[i] - coords[j]) # If atoms are closer than 2.8 Angstroms, draw a line if dist < 2.8: ax.plot([coords[i,0], coords[j,0]], [coords[i,1], coords[j,1]], [coords[i,2], coords[j,2]], c='black', linewidth=1, alpha=0.5) ax.set_title(title) ax.set_xlabel('X') ax.set_ylabel('Y') ax.set_zlabel('Z') # Set consistent limits so we can compare ax.set_xlim(-2, 5) ax.set_ylim(-2, 5) ax.set_zlim(-2, 5) def create_comparison_figure(): # 1. Read Data # Make sure you ran generate.py first to get these files! noise_pos, atoms = read_xyz("gen_step_00.xyz") final_pos, _ = read_xyz("gen_final.xyz") # 2. Setup Plot fig = plt.figure(figsize=(12, 6)) # Plot 1: The Noise ax1 = fig.add_subplot(121, projection='3d') plot_crystal(ax1, noise_pos, atoms, "Step 0: Random Noise") # Plot 2: The Generated Crystal ax2 = fig.add_subplot(122, projection='3d') plot_crystal(ax2, final_pos, atoms, "Step 50: Generated Crystal") plt.tight_layout() plt.savefig("result_plot.png", dpi=300) print("Saved comparison figure to 'result_plot.png'") plt.show() if __name__ == "__main__": create_comparison_figure()