org.nd4j.linalg.api.rng.distribution.impl

Class UniformDistribution

java.lang.Object

org.nd4j.linalg.api.rng.distribution.BaseDistribution

org.nd4j.linalg.api.rng.distribution.impl.UniformDistribution

All Implemented Interfaces:

Distribution

public class UniformDistribution
extends BaseDistribution

Base distribution derived from apache commons math http://commons.apache.org/proper/commons-math/

(specifically the org.apache.commons.math3.distribution.UniformIntegerDistribution

Author:

Adam Gibson

Field Summary

Fields inherited from class org.nd4j.linalg.api.rng.distribution.BaseDistribution

random, solverAbsoluteAccuracy

Constructor Summary

Constructors

Constructor and Description
UniformDistribution(double lower, double upper) Create a uniform real distribution using the given lower and upper bounds.
UniformDistribution(Random rng, double lower, double upper) Creates a uniform distribution.

Method Summary

Modifier and Type	Method and Description
double	cumulativeProbability(double x) For a random variable X whose values are distributed according to this distribution, this method returns P(X <= x).
double	cumulativeProbability(double x0, double x1) For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
double	density(double x) Returns the probability density function (PDF) of this distribution evaluated at the specified point x.
double	getNumericalMean() Use this method to get the numerical value of the mean of this distribution.
double	getNumericalVariance() Use this method to get the numerical value of the variance of this distribution.
double	getSupportLowerBound() Access the lower bound of the support.
double	getSupportUpperBound() Access the upper bound of the support.
double	inverseCumulativeProbability(double p) Computes the quantile function of this distribution.
boolean	isSupportConnected() Use this method to get information about whether the support is connected, i.e.
boolean	isSupportLowerBoundInclusive() Whether or not the lower bound of support is in the domain of the density function.
boolean	isSupportUpperBoundInclusive() Whether or not the upper bound of support is in the domain of the density function.
double	sample() Generate a random value sampled from this distribution.

Methods inherited from class org.nd4j.linalg.api.rng.distribution.BaseDistribution

getSolverAbsoluteAccuracy, probability, probability, reseedRandomGenerator, sample, sample

Methods inherited from class java.lang.Object

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

Constructor Detail

UniformDistribution

public UniformDistribution(double lower,
                           double upper)
                    throws org.apache.commons.math3.exception.NumberIsTooLargeException

Create a uniform real distribution using the given lower and upper bounds.

Parameters:

lower - Lower bound of this distribution (inclusive).

upper - Upper bound of this distribution (exclusive).

Throws:

org.apache.commons.math3.exception.NumberIsTooLargeException - if lower >= upper.

UniformDistribution

public UniformDistribution(Random rng,
                           double lower,
                           double upper)
                    throws org.apache.commons.math3.exception.NumberIsTooLargeException

Creates a uniform distribution.

Parameters:

rng - Random number generator.

lower - Lower bound of this distribution (inclusive).

upper - Upper bound of this distribution (exclusive).

Throws:

org.apache.commons.math3.exception.NumberIsTooLargeException - if lower >= upper.

Since:

3.1

Method Detail

density

public double density(double x)

Returns the probability density function (PDF) of this distribution evaluated at the specified point x. In general, the PDF is the derivative of the CDF. If the derivative does not exist at x, then an appropriate replacement should be returned, e.g. Double.POSITIVE_INFINITY, Double.NaN, or the limit inferior or limit superior of the difference quotient.

Parameters:

x - the point at which the PDF is evaluated

Returns:

the value of the probability density function at point x

cumulativeProbability

public double cumulativeProbability(double x)

For a random variable X whose values are distributed according to this distribution, this method returns P(X <= x). In other words, this method represents the (cumulative) distribution function (CDF) for this distribution.

Parameters:

x - the point at which the CDF is evaluated

Returns:

the probability that a random variable with this distribution takes a value less than or equal to x

cumulativeProbability

public double cumulativeProbability(double x0,
                                    double x1)
                             throws org.apache.commons.math3.exception.NumberIsTooLargeException

Description copied from interface: Distribution

For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).

Parameters:

x0 - the exclusive lower bound

x1 - the inclusive upper bound

Returns:

the probability that a random variable with this distribution takes a value between x0 and x1, excluding the lower and including the upper endpoint

Throws:

org.apache.commons.math3.exception.NumberIsTooLargeException - if x0 > x1

inverseCumulativeProbability

public double inverseCumulativeProbability(double p)
                                    throws org.apache.commons.math3.exception.OutOfRangeException

Description copied from class: BaseDistribution

Computes the quantile function of this distribution. For a random variable X distributed according to this distribution, the returned value is

• inf{x in R | P(X<=x) >= p} for 0 < p <= 1,
• inf{x in R | P(X<=x) > 0} for p = 0.

The default implementation returns

• Distribution.getSupportLowerBound() for p = 0,
• Distribution.getSupportUpperBound() for p = 1.

Specified by:

inverseCumulativeProbability in interface Distribution

Overrides:

inverseCumulativeProbability in class BaseDistribution

Parameters:

p - the cumulative probability

Returns:

the smallest p-quantile of this distribution (largest 0-quantile for p = 0)

Throws:

org.apache.commons.math3.exception.OutOfRangeException - if p < 0 or p > 1

getNumericalMean

public double getNumericalMean()

Use this method to get the numerical value of the mean of this distribution.

For lower bound lower and upper bound upper, the mean is 0.5 * (lower + upper).

Returns:

the mean or Double.NaN if it is not defined

getNumericalVariance

public double getNumericalVariance()

Use this method to get the numerical value of the variance of this distribution.

For lower bound lower and upper bound upper, the variance is (upper - lower)^2 / 12.

Returns:

the variance (possibly Double.POSITIVE_INFINITY as for certain cases in org.apache.commons.math3.distribution.TDistribution) or Double.NaN if it is not defined

getSupportLowerBound

public double getSupportLowerBound()

Access the lower bound of the support. This method must return the same value as inverseCumulativeProbability(0). In other words, this method must return

inf {x in R | P(X <= x) > 0}.

The lower bound of the support is equal to the lower bound parameter of the distribution.

Returns:

lower bound of the support

getSupportUpperBound

public double getSupportUpperBound()

Access the upper bound of the support. This method must return the same value as inverseCumulativeProbability(1). In other words, this method must return

inf {x in R | P(X <= x) = 1}.

The upper bound of the support is equal to the upper bound parameter of the distribution.

Returns:

upper bound of the support

isSupportLowerBoundInclusive

public boolean isSupportLowerBoundInclusive()

Whether or not the lower bound of support is in the domain of the density function. Returns true iff getSupporLowerBound() is finite and density(getSupportLowerBound()) returns a non-NaN, non-infinite value.

Returns:

true if the lower bound of support is finite and the density function returns a non-NaN, non-infinite value there

isSupportUpperBoundInclusive

public boolean isSupportUpperBoundInclusive()

Whether or not the upper bound of support is in the domain of the density function. Returns true iff getSupportUpperBound() is finite and density(getSupportUpperBound()) returns a non-NaN, non-infinite value.

Returns:

true if the upper bound of support is finite and the density function returns a non-NaN, non-infinite value there

isSupportConnected

public boolean isSupportConnected()

Use this method to get information about whether the support is connected, i.e. whether all values between the lower and upper bound of the support are included in the support.

The support of this distribution is connected.

Returns:

true

sample

public double sample()

Generate a random value sampled from this distribution.

The default implementation uses the inversion method.

Specified by:

sample in interface Distribution

Overrides:

sample in class BaseDistribution

Returns:

a random value.