univariate

poisson

Generator for a Poisson random variable

The numpy generator is used as default

class ALGORITHM(value)

Bases: Enum

Poisson generator algorithms

NUMPY = 1

KNUTH = 2

class Poisson(lam: Union[int, float], algorithm: ALGORITHM = ALGORITHM.NUMPY)

Bases: Sampling

Poisson random variate

__init__(lam: Union[int, float], algorithm: ALGORITHM = ALGORITHM.NUMPY)

Parameters

• lam – rate/intensity parameter

• algorithm –

  chosen algorithm (numpy by default)

sample(size: int = 1) → ndarray[Any, dtype[float]]

sample a random variable corresponding the distribution in scope

Parameters

size – size of the sampling vector

Returns

the array of simulated variables

cost()

Returns

the computing cost of the algorithm for generating the random variable the cost will usually correspond to the number of generated uniform random variables

reset_sampling_cost()

reset the simulation cost to 0

uniform

Generator for standard uniform random variables

Numpy is used here, the generator returns random floats in the half-open interval [0.0, 1.0) see https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.random_sample.html#numpy.random.random_sample

class Uniform(low: float = 0.0, high: float = 1.0)

Bases: Sampling

Uniform random variate generator

__init__(low: float = 0.0, high: float = 1.0) → None

sample(size: int = 1) → array

sample a random variable corresponding the distribution in scope

Parameters

size – size of the sampling vector

Returns

the array of simulated variables