numpy.random.Generator.standard_exponential

method

random.Generator.standard_exponential(size=None, dtype=np.float64, 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

sizeint 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.

dtypedtype, optional

Desired dtype of the result, only float64 and float32 are supported. Byteorder must be native. The default value is np.float64.

methodstr, optional

Either ‘inv’ or ‘zig’. ‘inv’ uses the default inverse CDF method. ‘zig’ uses the much faster Ziggurat method of Marsaglia and Tsang.

outndarray, 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

outfloat or ndarray

Drawn samples.

Examples

Output a 3x8000 array:

>>> n = np.random.default_rng().standard_exponential((3, 8000))

numpy.random.Generator.standard_cauchy numpy.random.Generator.standard_gamma