Java Entropy Calculate discretiseMaxEntropy(double data[], int numBins)

Here you can find the source of discretiseMaxEntropy(double data[], int numBins)

Description

Discretizes using a maximum entropy partitioning

License

Open Source License

Parameter

Parameter Description
data a parameter
numBins a parameter

Declaration

public static int[] discretiseMaxEntropy(double data[], int numBins) 

Method Source Code

//package com.java2s;
/*//from w  w w .j  av  a  2  s  .c o  m
 *  Java Information Dynamics Toolkit (JIDT)
 *  Copyright (C) 2012, Joseph T. Lizier
 *  
 *  This program is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU General Public License as published by
 *  the Free Software Foundation, either version 3 of the License, or
 *  (at your option) any later version.
 *  
 *  This program is distributed in the hope that it will be useful,
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *  GNU General Public License for more details.
 *  
 *  You should have received a copy of the GNU General Public License
 *  along with this program.  If not, see <http://www.gnu.org/licenses/>.
 */

import java.util.Arrays;

public class Main {
    /**
     * Discretizes using a maximum entropy partitioning
     * 
     * @param data
     * @param numBins
     * @return
     */
    public static int[] discretiseMaxEntropy(double data[], int numBins) {
        int[] newData = new int[data.length];

        double[] tempData = new double[data.length];
        System.arraycopy(data, 0, tempData, 0, data.length);
        Arrays.sort(tempData);
        int compartmentSize;
        double[] cutOffValues = new double[numBins];
        for (int i = 0; i < numBins; i++) {
            compartmentSize = (int) ((double) (i + 1) * (double) (data.length) / (double) numBins) - 1;
            // System.out.println(compartmentSize);
            cutOffValues[i] = tempData[compartmentSize];
        }

        for (int i = 0; i < data.length; i++) {
            for (int m = 0; m < numBins; m++) {
                if (data[i] <= cutOffValues[m]) {
                    newData[i] = m;
                    break;
                }
            }
        }
        return newData;
    }

    /**
     * Discretizes each column of the data independently,
     * using a maximum entropy partitioning
     * 
     * @param data
     * @param numBins
     * @return
     */
    public static int[][] discretiseMaxEntropy(double data[][], int numBins) {
        int lastCol = data[0].length;
        int lastRow = data.length;
        int[][] newData = new int[lastRow][lastCol];
        for (int j = 0; j < lastCol; j++) {
            double[] tempData = new double[lastRow];
            for (int i = 0; i < lastRow; i++) {
                tempData[i] = data[i][j];
            }

            Arrays.sort(tempData);

            int compartmentSize;
            double[] cutOffValues = new double[numBins];
            for (int i = 0; i < numBins; i++) {
                compartmentSize = (int) ((double) (i + 1) * (double) (lastRow) / (double) numBins) - 1;
                //            System.out.println(compartmentSize);
                cutOffValues[i] = tempData[compartmentSize];
            }

            for (int i = 0; i < lastRow; i++) {
                for (int m = 0; m < numBins; m++) {
                    if (data[i][j] <= cutOffValues[m]) {
                        newData[i][j] = m;
                        m = numBins;
                    }
                }
            }
        }
        return newData;
    }

    /**
     * Copies all rows and columns between two double arrays
     * 
     * @param src
     * @param dest
     */
    public static void arrayCopy(double[][] src, double[][] dest) {
        for (int r = 0; r < src.length; r++) {
            System.arraycopy(src[r], 0, dest[r], 0, src[r].length);
        }
    }

    /**
     * Copies all rows and columns between two double arrays
     * 
     * @param src
     * @param dest
     */
    public static double[][] arrayCopy(double[][] src) {
        double[][] dest = new double[src.length][];
        for (int r = 0; r < src.length; r++) {
            dest[r] = new double[src[r].length];
            System.arraycopy(src[r], 0, dest[r], 0, src[r].length);
        }
        return dest;
    }

    /**
     * Copies the required rows and columns between two 
     * double arrays
     * 
     * @param src
     * @param srcStartRow
     * @param srcStartCol
     * @param dest
     * @param destStartRow
     * @param destStartCol
     * @param rows
     * @param cols
     */
    public static void arrayCopy(double[][] src, int srcStartRow, int srcStartCol, double[][] dest,
            int destStartRow, int destStartCol, int rows, int cols) {

        for (int r = 0; r < rows; r++) {
            System.arraycopy(src[srcStartRow + r], srcStartCol, dest[destStartRow + r], destStartCol, cols);
        }
    }

    /**
     * Copies all rows and columns between two int arrays
     * 
     * @param src
     * @param dest
     */
    public static void arrayCopy(int[][] src, int[][] dest) {
        for (int r = 0; r < src.length; r++) {
            System.arraycopy(src[r], 0, dest[r], 0, src[r].length);
        }
    }

    /**
     * Copies the required rows and columns between two 
     * double arrays
     * 
     * @param src
     * @param srcStartRow
     * @param srcStartCol
     * @param dest
     * @param destStartRow
     * @param destStartCol
     * @param rows
     * @param cols
     */
    public static void arrayCopy(int[][] src, int srcStartRow, int srcStartCol, int[][] dest, int destStartRow,
            int destStartCol, int rows, int cols) {

        for (int r = 0; r < rows; r++) {
            System.arraycopy(src[srcStartRow + r], srcStartCol, dest[destStartRow + r], destStartCol, cols);
        }
    }
}

Related

  1. calcEntropyOfDiscreteProbDist(Double[] probDist)
  2. computeEntropy(int pos, int neg)
  3. discreteEntropy(int[] sequence, int numStates)
  4. entropy(byte[] f)
  5. entropy(double[] distribution)
  6. entropy(double[] p)
  7. entropy(double[] vals)