25 lines
709 B
Python
25 lines
709 B
Python
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import numpy as np
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import matplotlib.pyplot as plt
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# Define the Gaussian distribution
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mu, sigma = 0, 5 # High variance
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gaussian = np.random.normal(mu, sigma, 1000000) # Generate a lot of samples
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# Rejection sampling
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gaussian = gaussian[(gaussian > -1) & (gaussian < 1)]
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# Generate uniform distribution
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uniform = np.random.uniform(-1, 1, len(gaussian)) # Same number of samples as the Gaussian
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# Plot the distributions
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plt.figure(figsize=(12,6))
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plt.subplot(1, 2, 1)
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plt.hist(gaussian, bins=30, density=True, alpha=0.6, color='g')
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plt.title('Gaussian Rejection Sampling')
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plt.subplot(1, 2, 2)
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plt.hist(uniform, bins=30, density=True, alpha=0.6, color='b')
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plt.title('Uniform Distribution')
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plt.show()
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