Random Number Generators (scipy.stats.sampling)#
This module contains a collection of random number generators to sample from univariate continuous and discrete distributions. It uses the implementation of a C library called "UNU.RAN". The only exception is RatioUniforms, which is a pure Python implementation of the Ratio-of-Uniforms method.
Generators Wrapped#
For continuous distributions#
NumericalInverseHermite(dist, *[, domain, ...])
Hermite interpolation based INVersion of CDF (HINV).
NumericalInversePolynomial(dist, *[, mode, ...])
Polynomial interpolation based INVersion of CDF (PINV).
TransformedDensityRejection(dist, *[, mode, ...])
Transformed Density Rejection (TDR) Method.
SimpleRatioUniforms(dist, *[, mode, ...])
Simple Ratio-of-Uniforms (SROU) Method.
RatioUniforms(pdf, *, umax, vmin, vmax[, c, ...])
Generate random samples from a probability density function using the ratio-of-uniforms method.
For discrete distributions#
DiscreteAliasUrn(dist, *[, domain, ...])
Discrete Alias-Urn Method.
DiscreteGuideTable(dist, *[, domain, ...])
Discrete Guide Table method.
Warnings / Errors used in scipy.stats.sampling #
Raised when an error occurs in the UNU.RAN library.
Generators for pre-defined distributions#
To easily apply the above methods for some of the continuous distributions
in scipy.stats, the following functionality can be used:
FastGeneratorInversion(dist, *[, domain, ...])
Fast sampling by numerical inversion of the CDF for a large class of continuous distributions in scipy.stats.