/***********************************************************************
This file is part of KEEL-software, the Data Mining tool for regression,
classification, clustering, pattern mining and so on.
Copyright (C) 2004-2010
F. Herrera (herrera@decsai.ugr.es)
L. S�nchez (luciano@uniovi.es)
J. Alcal�-Fdez (jalcala@decsai.ugr.es)
S. Garc�a (sglopez@ujaen.es)
A. Fern�ndez (alberto.fernandez@ujaen.es)
J. Luengo (julianlm@decsai.ugr.es)
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/
**********************************************************************/
package keel.Algorithms.Discretizers.UCPD;
import org.core.Randomize;
/**
* <p>
* This class helps managing a sampling without replacement process
* </p>
*
* @author Written by Jose A. Saez (University of Granada), 21/12/2009
* @version 1.0
* @since JDK1.6
*/
public class Sampling {
int maxSize; // total number of elements
int num; // actual number of elements
int []sample; // actual elements
//******************************************************************************************************
/**
* <p>
* Class constructor
* </p>
* @param _maxSize number of elements
*/
public Sampling(int _maxSize){
maxSize = _maxSize;
sample = new int[maxSize];
initSampling();
}
//******************************************************************************************************
/**
* <p>
* It initializes the sampling
* </p>
*/
void initSampling(){
for(int i = 0; i < maxSize; i++)
sample[i] = i;
num = maxSize;
}
//******************************************************************************************************
/**
* <p>
* It returns one value of the sampling
* </p>
* @return the sampled value
*/
public int getSample(){
int pos = Randomize.Randint(0, num);
int value = sample[pos];
sample[pos] = sample[num-1];
num--;
if(num == 0)
initSampling();
return value;
}
}