numpy.random.Generator.standard_exponential method  
Generator.standard_exponential(size=None, dtype='d', method='zig', out=None)  
Draw samples from the standard exponential distribution. standard_exponential is identical to the exponential distribution with a scale parameter of 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.  
dtype : dtype, optional  
Desired dtype of the result, either ‘d’ (or ‘float64’) or ‘f’ (or ‘float32’). All dtypes are determined by their name. The default value is ‘d’.  
method : str, optional  
Either ‘inv’ or ‘zig’. ‘inv’ uses the default inverse CDF method. ‘zig’ uses the much faster Ziggurat method of Marsaglia and Tsang.  
out : ndarray, optional  
Alternative output array in which to place the result. If size is not None, it must have the same shape as the provided size and must match the type of the output values.     
Returns:

 
out : float or ndarray  
Drawn samples.      Examples Output a 3x8000 array: >>> n = np.random.default_rng().standard_exponential((3, 8000))
 


    
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