Created
November 12, 2019 18:41
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Contour plot of 2D gaussian
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| import matplotlib.pyplot as plt | |
| import numpy as np | |
| from scipy.stats import multivariate_normal | |
| N = 200 | |
| X = np.linspace(-4, 4, N) | |
| Y = np.linspace(-4, 4, N) | |
| X, Y = np.meshgrid(X, Y) | |
| pos = np.dstack((X, Y)) | |
| rv = multivariate_normal([0, 1], [[1, 0.8], [0.8, 1]]) | |
| Z = rv.pdf(pos) | |
| plt.contour(X, Y, Z) | |
| plt.show() |
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This is one solution, but if you want to define the contour levels to be a certain amount of probability you can use my repo: herzphi/2DGaussianContourLevels