org.nd4j.linalg.sampling

Class Sampling

java.lang.Object

org.nd4j.linalg.sampling.Sampling

public class Sampling
extends Object

Static methods for sampling from an ndarray

Author:

Adam Gibson

Constructor Summary

Constructors

Constructor and Description
Sampling()

Method Summary

Methods

Modifier and Type	Method and Description
static INDArray	binomial(INDArray p, int n, org.apache.commons.math3.random.RandomGenerator rng) Generate a binomial distribution based on the given rng, a matrix of p values, and a max number.
static INDArray	normal(org.apache.commons.math3.random.RandomGenerator rng, INDArray mean, double sigma) A uniform sample ranging from 0 to sigma.
static INDArray	normal(org.apache.commons.math3.random.RandomGenerator rng, INDArray mean, INDArray sigma) A uniform sample ranging from 0 to sigma.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Sampling

public Sampling()

Method Detail

normal

public static INDArray normal(org.apache.commons.math3.random.RandomGenerator rng,
              INDArray mean,
              INDArray sigma)

A uniform sample ranging from 0 to sigma.

Parameters:

rng - the rng to use

mean, - the matrix mean from which to generate values from

sigma - the standard deviation to use to generate the gaussian noise

Returns:

a uniform sample of the given shape and size

with numbers between 0 and 1

normal

public static INDArray normal(org.apache.commons.math3.random.RandomGenerator rng,
              INDArray mean,
              double sigma)

A uniform sample ranging from 0 to sigma.

Parameters:

rng - the rng to use

mean, - the matrix mean from which to generate values from

sigma - the standard deviation to use to generate the gaussian noise

Returns:

a uniform sample of the given shape and size

with numbers between 0 and 1

binomial

public static INDArray binomial(INDArray p,
                int n,
                org.apache.commons.math3.random.RandomGenerator rng)

Generate a binomial distribution based on the given rng, a matrix of p values, and a max number.

Parameters:

p - the p matrix to use

n - the n to use

rng - the rng to use

Returns:

a binomial distribution based on the one n, the passed in p values, and rng