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/*
* 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 2 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, write to the Free Software
* Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
*/
/*
* FastRfUtils.java
* Copyright (C) 1999-2004 University of Waikato, Hamilton, NZ (original
* code, Utils.java )
* Copyright (C) 2008 Fran Supek (adapted code)
*/
package hr.irb.fastRandomForest;
import weka.core.Instance;
import weka.core.Instances;
import java.util.Random;
/**
* Utility functions for sorting float (single-precision) arrays, and for
* normalizing double arrays. Adapted from weka.core.Utils, version 1.57.
*
* @author Eibe Frank - original code
* @author Yong Wang - original code
* @author Len Trigg - original code
* @author Julien Prados - original code
* @author Fran Supek (fran.supek[AT]irb.hr) - adapted code
*/
public class FastRfUtils {
/**
* Sorts a given array of floats in ascending order and returns an
* array of integers with the positions of the elements of the
* original array in the sorted array. NOTE THESE CHANGES: the sort
* is no longer stable and it doesn't use safe floating-point
* comparisons anymore. Occurrences of Double.NaN behave unpredictably in
* sorting.
*
* @param array this array is not changed by the method!
*
* @return an array of integers with the positions in the sorted
* array.
*/
public static /*@pure@*/ int[] sort(/*@non_null@*/ float[] array) {
int[] index = new int[array.length];
for (int i = 0; i < index.length; i++)
index[i] = i;
array = array.clone();
quickSort(array, index, 0, array.length - 1);
return index;
}
/**
* Partitions the instances around a pivot. Used by quicksort and
* kthSmallestValue.
*
* @param array the array of doubles to be sorted
* @param index the index into the array of doubles
* @param l the first index of the subset
* @param r the last index of the subset
*
* @return the index of the middle element
*/
private static int partition(float[] array, int[] index, int l, int r) {
double pivot = array[index[(l + r) / 2]];
int help;
while (l < r) {
while ((array[index[l]] < pivot) && (l < r)) {
l++;
}
while ((array[index[r]] > pivot) && (l < r)) {
r--;
}
if (l < r) {
help = index[l];
index[l] = index[r];
index[r] = help;
l++;
r--;
}
}
if ((l == r) && (array[index[r]] > pivot)) {
r--;
}
return r;
}
/**
* Implements quicksort according to Manber's "Introduction to
* Algorithms".
*
* @param array the array of doubles to be sorted
* @param index the index into the array of doubles
* @param left the first index of the subset to be sorted
* @param right the last index of the subset to be sorted
*/
//@ requires 0 <= first && first <= right && right < array.length;
//@ requires (\forall int i; 0 <= i && i < index.length; 0 <= index[i] && index[i] < array.length);
//@ requires array != index;
// assignable index;
private static void quickSort(/*@non_null@*/ float[] array, /*@non_null@*/ int[] index,
int left, int right) {
if (left < right) {
int middle = partition(array, index, left, right);
quickSort(array, index, left, middle);
quickSort(array, index, middle + 1, right);
}
}
/**
* Normalizes the doubles in the array by their sum.
*
* If supplied an array full of zeroes, does not modify the array.
*
* @param doubles the array of double
*
* @throws IllegalArgumentException if sum is NaN
*/
public static void normalize(double[] doubles) {
double sum = 0;
for (int i = 0; i < doubles.length; i++) {
sum += doubles[i];
}
normalize(doubles, sum);
}
/**
* Normalizes the doubles in the array using the given value.
*
* If supplied an array full of zeroes, does not modify the array.
*
* @param doubles the array of double
* @param sum the value by which the doubles are to be normalized
*
* @throws IllegalArgumentException if sum is zero or NaN
*/
private static void normalize(double[] doubles, double sum) {
if (Double.isNaN(sum)) {
throw new IllegalArgumentException("Can't normalize array. Sum is NaN.");
}
if (sum == 0) {
return;
}
for (int i = 0; i < doubles.length; i++) {
doubles[i] /= sum;
}
}
/**
* Produces a random permutation using Knuth shuffle.
*
* @param numElems the size of the permutation
* @param rng the random number generator
*
* @return a random permutation
*/
public static int[] randomPermutation(int numElems, Random rng) {
int[] permutation = new int[numElems];
for (int i = 0; i < numElems; i++)
permutation[i] = i;
for (int i = 0; i < numElems - 1; i++) {
int next = rng.nextInt(numElems);
int tmp = permutation[i];
permutation[i] = permutation[next];
permutation[next] = tmp;
}
return permutation;
}
/**
* Produces a random permutation of the values of an attribute in a dataset using Knuth shuffle.
*
* Copies back the current values of the previously scrambled attribute and uses the given permutation
* to scramble the values of the new attribute all by copying from the original dataset.
*
* @param src the source dataset
* @param dst the scrambled dataset
* @param attIndex the attribute index
* @param perm the random permutation
*
* @return fluent
*/
public static Instances scramble(Instances src, Instances dst, final int attIndex, int[] perm) {
for (int i = 0; i < src.numInstances(); i++) {
Instance scrambled = dst.instance(i);
if (attIndex > 0)
scrambled.setValue(attIndex - 1, src.instance(i).value(attIndex - 1));
scrambled.setValue(attIndex, src.instance(perm[i]).value(attIndex));
}
return dst;
}
/**
* Load a dataset into memory.
*
* @param location the location of the dataset
*
* @return the dataset
*/
public static Instances readInstances(String location) throws Exception {
Instances data = new weka.core.converters.ConverterUtils.DataSource(location).getDataSet();
if (data.classIndex() == -1)
data.setClassIndex(data.numAttributes() - 1);
return data;
}
}
