# 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#

 UNURANError 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.