numpy.random.mtrand.RandomState.standard_normal method  
RandomState.standard_normal(size=None)  
Draw samples from a standard Normal distribution (mean=0, stdev=1).    
Parameters:

 
size : int or tuple of ints, optional  
Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn. Default is None, in which case a single value is returned.     
Returns:

 
out : float or ndarray  
A floating-point array of shape size of drawn samples, or a single sample if size was not specified.       See also  
normal
 Equivalent function with additional loc and scale arguments for setting the mean and standard deviation.   Notes For random samples from , use one of: mu + sigma * np.random.standard_normal(size=...)
np.random.normal(mu, sigma, size=...)
 Examples >>> np.random.standard_normal()
2.1923875335537315 #random
 >>> s = np.random.standard_normal(8000)
>>> s
array([ 0.6888893 ,  0.78096262, -0.89086505, ...,  0.49876311,  # random
       -0.38672696, -0.4685006 ])                                # random
>>> s.shape
(8000,)
>>> s = np.random.standard_normal(size=(3, 4, 2))
>>> s.shape
(3, 4, 2)
 Two-by-four array of samples from : >>> 3 + 2.5 * np.random.standard_normal(size=(2, 4))
array([[-4.49401501,  4.00950034, -1.81814867,  7.29718677],   # random
       [ 0.39924804,  4.68456316,  4.99394529,  4.84057254]])  # random
 


    
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