numpy.matlib.randn(*args)
[source]
Return a random matrix with data from the “standard normal” distribution.
randn
generates a matrix filled with random floats sampled from a univariate “normal” (Gaussian) distribution of mean 0 and variance 1.
Parameters: |
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Returns: |
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See also
rand
, random.randn
For random samples from , use:
sigma * np.matlib.randn(...) + mu
>>> np.random.seed(123) >>> import numpy.matlib >>> np.matlib.randn(1) matrix([[-1.0856306]]) >>> np.matlib.randn(1, 2, 3) matrix([[ 0.99734545, 0.2829785 , -1.50629471], [-0.57860025, 1.65143654, -2.42667924]])
Two-by-four matrix of samples from :
>>> 2.5 * np.matlib.randn((2, 4)) + 3 matrix([[1.92771843, 6.16484065, 0.83314899, 1.30278462], [2.76322758, 6.72847407, 1.40274501, 1.8900451 ]])
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https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.matlib.randn.html