Conditional generator p(x|z)

import numpy as np
import matplotlib.pyplot as plt


def generate_half_moon(num_points, radius, width):
    # Generate points on a circle
    theta = np.linspace(0, np.pi, num_points)
    x_circle = radius * np.cos(theta)
    y_circle = radius * np.sin(theta)

    # The function changes the mean of the standard normal distribution
    x_noisy = x_circle + np.random.normal(0, width, num_points)
    y_noisy = y_circle + np.random.normal(0, width, num_points)

    # Combine x and y coordinates
    half_moon_points = np.column_stack((x_noisy, y_noisy))

    return half_moon_points


# Example usage:
half_moon_data = generate_half_moon(num_points=1000, radius=1.0, width=0.1)

plt.scatter(half_moon_data[:, 0], half_moon_data[:, 1])
plt.xlabel("X-axis")
plt.ylabel("Y-axis")
plt.title("Generated Half-Moon")
plt.show()