gaussians.py

import numpy as np
from matplotlib import pyplot as plt 
# Uncomment if you're running in a jupyter notebook
# %matplotlib inline

axis = (0, 500)
sigma = 100
k = 3
ndim = 5

# k (uniform) random points in 2D space in the interval of (0, 500)
centers = np.random.uniform(*axis, (k, ndim))

# Show centers
plt.figure()
plt.scatter(centers[:, 0], centers[:, 1])

# Variance of the distribution
cov = np.eye(ndim) * sigma
points_to_generate = 5000

# For each center, generate points_to_generate points.
points = [
    np.random.multivariate_normal(centers[i], cov, points_to_generate)
    for i in range(k)
]

colours = ['red', 'green', 'blue']
plt.figure()
for i in range(k):
    plt.scatter(points[i][:, 0], points[i][:, 1], color=colours[i])