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Change covariance to be positive-semidefinite.
Minimal changes to the plot but fixes a warning and more realistic data
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examples/api/power_norm_demo.py

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import numpy as np
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from numpy.random import multivariate_normal
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data = np.vstack([multivariate_normal([10, 10], [[3, 5], [4, 2]], size=100000),
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data = np.vstack([multivariate_normal([10, 10], [[2, 2], [2, 2]], size=100000),
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multivariate_normal([30, 20], [[2, 3], [1, 3]], size=1000)
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])
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