Delete test.py

test.py

-import numpy as np
-import matplotlib.pyplot as plt
-import matplotlib.animation as animation
-from mpl_toolkits.mplot3d import Axes3D
-
-# Function to visualize
-def function_to_plot(x, y):
-    return (x**2 + y**2) * np.sin(np.sqrt(x**2 + y**2))  # Example function with minima
-
-# 3D Plot Function
-def plot_3D(populations, function_to_plot, save_path="animation.gif"):
-    fig = plt.figure(figsize=(10, 7))
-    ax = fig.add_subplot(111, projection='3d')
-
-    # Generate grid for the surface plot
-    x = np.linspace(-100, 100, 200)
-    y = np.linspace(-100, 100, 200)
-    X, Y = np.meshgrid(x, y)
-    Z = function_to_plot(X, Y)
-
-    # Plot surface
-    ax.plot_surface(X, Y, Z, cmap="viridis", alpha=0.6, edgecolor='none')
-
-    # Initialize scatter plot for moving points
-    scatter = ax.scatter([], [], [], color='red', s=1, alpha=0.8)
-
-    # Update function for animation
-    def update(frame):
-        ax.collections.clear()  # Clear previous points
-        points = populations[frame]  # Get current positions
-        Z_points = function_to_plot(points[:, 0], points[:, 1])  # Compute function values
-        scatter = ax.scatter(points[:, 0], points[:, 1], Z_points, color='red', s=1, alpha=0.8)
-        return scatter,
-
-    # Create animation
-    ani = animation.FuncAnimation(fig, update, frames=len(populations), interval=100, blit=False)
-
-    # Save animation as GIF
-    ani.save(save_path, writer='pillow', fps=20)
-
-    plt.show()
-
-# Example Usage:
-populations = [np.random.uniform(-100, 100, size=(20000, 2)) for _ in range(50)]  # Fake data
-plot_3D(populations, function_to_plot)
-