creating a normally distributed matrix in numpy with specified mean and variance per element

Question

Assume 3 matrices Mean, Variance, Sample all with the same dimensionality. Is there a 1 line solution to generate the Sample matrix in numpy such that:

 Sample[i,j] is drawn from NormalDistribution(Mean[i,j], Variance[i,j])

P. Camilleri · Accepted Answer · 2018-05-04 15:09:58Z

2

Using linearity of mean and Var(aX +b) = a**2 Var(X):

Generate a centered and reduced 2D array with np.random.randn(). Multiply pointwise by std (np.sqrt(variance)) and add (still pointwise) mean.

answered May 4, 2018 at 15:09

P. Camilleri

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1 Comment

user3639557 Over a year ago

Completely forgot about the transformation between a standard normal and a normal distribution. Great!

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