Package cern.jet.random

Class Empirical

  • All Implemented Interfaces:
    DoubleFunction, IntFunction, java.io.Serializable, java.lang.Cloneable
    public class Empirical
extends AbstractContinousDistribution
    Empirical distribution.

    The probability distribution function (pdf) must be provided by the user as an array of positive real numbers. The pdf does not need to be provided in the form of relative probabilities, absolute probabilities are also accepted.

    If interpolationType == LINEAR_INTERPOLATION a linear interpolation within the bin is computed, resulting in a constant density within each bin.

    If interpolationType == NO_INTERPOLATION no interpolation is performed and the result is a discrete distribution.

    Instance methods operate on a user supplied uniform random number generator; they are unsynchronized.

    Static methods operate on a default uniform random number generator; they are synchronized.

    Implementation: A uniform random number is generated using a user supplied generator. The uniform number is then transformed to the user's distribution using the cumulative probability distribution constructed from the pdf. The cumulative distribution is inverted using a binary search for the nearest bin boundary.

    This is a port of RandGeneral used in CLHEP 1.4.0 (C++).

    Version:
    1.0, 09/24/99
    See Also:
    Serialized Form

    • Field Detail

      • cdf

        protected double[] cdf

      • interpolationType

        protected int interpolationType

    • Constructor Detail

      • Empirical

        public Empirical​(double[] pdf,
                 int interpolationType,
                 RandomEngine randomGenerator)
        Constructs an Empirical distribution. The probability distribution function (pdf) is an array of positive real numbers. It need not be provided in the form of relative probabilities, absolute probabilities are also accepted. The pdf must satisfy both of the following conditions
        • 0.0 <= pdf[i] : 0<=i<=pdf.length-1
        • 0.0 < Sum(pdf[i]) : 0<=i<=pdf.length-1
        Parameters:
        pdf - the probability distribution function.
        interpolationType - can be either Empirical.NO_INTERPOLATION or Empirical.LINEAR_INTERPOLATION.
        randomGenerator - a uniform random number generator.
        Throws:
        java.lang.IllegalArgumentException - if at least one of the three conditions above is violated.

    • Method Detail

      • cdf

        public double cdf​(int k)
        Returns the cumulative distribution function.

      • clone

        public java.lang.Object clone()
        Returns a deep copy of the receiver; the copy will produce identical sequences. After this call has returned, the copy and the receiver have equal but separate state.
        Overrides:
        clone in class AbstractDistribution
        Returns:
        a copy of the receiver.

      • pdf

        public double pdf​(double x)
        Returns the probability distribution function.

      • pdf

        public double pdf​(int k)
        Returns the probability distribution function.

      • setState

        public void setState​(double[] pdf,
                     int interpolationType)
        Sets the distribution parameters. The pdf must satisfy both of the following conditions
        • 0.0 <= pdf[i] : 0 < =i <= pdf.length-1
        • 0.0 < Sum(pdf[i]) : 0 <=i <= pdf.length-1
        Parameters:
        pdf - probability distribution function.
        interpolationType - can be either Empirical.NO_INTERPOLATION or Empirical.LINEAR_INTERPOLATION.
        Throws:
        java.lang.IllegalArgumentException - if at least one of the three conditions above is violated.

      • toString

        public java.lang.String toString()
        Returns a String representation of the receiver.
        Overrides:
        toString in class java.lang.Object

      • xnBins

        private int xnBins()
        Not yet commented.
        Returns:
        int