method
random.RandomState.randn(d0, d1, ..., dn)
Return a sample (or samples) from the “standard normal” distribution.
Note
This is a convenience function for users porting code from Matlab, and wraps
. That function takes a tuple to specify the size of the output, which is consistent with other NumPy functions like
and
.
If positive int_like arguments are provided,
generates an array of shape (d0,d1,...,dn), filled with random floats sampled from a univariate “normal” (Gaussian) distribution of mean 0 and variance 1. A single float randomly sampled from the distribution is returned if no argument is provided.
Parameters:d0, d1, …, dnint, optionalThe dimensions of the returned array, must be non-negative. If no argument is given a single Python float is returned.
Returns:Zndarray or floatA (d0,d1,...,dn)-shaped array of floating-point samples from the standard normal distribution, or a single such float if no parameters were supplied.
Notes
For random samples from the normal distribution with mean mu and standard deviation sigma, use:
sigma*np.random.randn(...)+muExamples
>>> np.random.randn()2.1923875335537315 # randomTwo-by-four array of samples from the normal distribution with mean 3 and standard deviation 2.5:
>>> 3+2.5*np.random.randn(2,4)array([[-4.49401501, 4.00950034, -1.81814867, 7.29718677], # random [ 0.39924804, 4.68456316, 4.99394529, 4.84057254]]) # random