randomstate.prng.mrg32k3a.standard_exponential

randomstate.prng.mrg32k3a.standard_exponential(size=None, dtype='d', method='inv', 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 – Drawn samples.

Return type:

float or ndarray

Examples

Output a 3x8000 array:

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