/*
* 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.
*/
/**
* UniformDataGenerator.java
* Copyright (C) 2008 K.Hempstalk, University of Waikato, Hamilton, New Zealand.
*/
package weka.classifiers.meta.generators;
/**
<!-- globalinfo-start -->
* A uniform artificial data generator.<br/>
* <br/>
* This generator uses a uniform data model - all values have the same probability, and generated values must fall within the range given to the generator.
* <p/>
<!-- globalinfo-end -->
*
<!-- options-start -->
* Valid options are: <p/>
*
* <pre> -D
* If set, generator is run in debug mode and
* may output additional info to the console</pre>
*
* <pre> -S <seed>
* Sets the seed of the random number generator of the generator (default: 1)</pre>
*
* <pre> -L <num>
* Sets the lower range of the generator
* (default: 0)</pre>
*
* <pre> -U <num>
* Sets the upper range of the generator
* (default: 1)</pre>
*
<!-- options-end -->
*
* @author Kathryn Hempstalk (kah18 at cs.waikato.ac.nz)
* @version $Revision$
*/
public class UniformDataGenerator
extends RandomizableRangedGenerator
implements NumericAttributeGenerator {
/** for serialization. */
private static final long serialVersionUID = -6390354660638644832L;
/**
* Returns a string describing this class' ability.
*
* @return A description of the class.
*/
public String globalInfo() {
return
"A uniform artificial data generator.\n"
+ "\n"
+ "This generator uses a uniform data model - all values have "
+ "the same probability, and generated values must fall within "
+ "the range given to the generator.";
}
/**
* Generates a value that falls under this distribution.
*
* @return A generated value.
*/
public double generate() {
double range = (m_UpperRange - m_LowerRange);
return (m_Random.nextDouble() * range) + m_LowerRange;
}
/**
* Gets the probability that a value falls under
* this distribution.
*
*
* @param somedata The value to get the probability of.
* @return The probability of the given value.
*/
public double getProbabilityOf(double somedata) {
double range = (m_UpperRange - m_LowerRange);
if (range <= 0 || somedata > m_UpperRange || somedata < m_LowerRange) {
return Double.MIN_VALUE;
}
return 1 / (range);
}
/**
* Gets the (natural) log of the probability of a given value.
*
* @param somedata The value to get the log probability of.
* @return The (natural) log of the probability.
*/
public double getLogProbabilityOf(double somedata) {
double range = (m_UpperRange - m_LowerRange);
if ((range <= 0) || (((somedata < m_LowerRange) || (somedata > m_UpperRange)))) {
return Math.log(Double.MIN_VALUE);
}
return -Math.log(range);
}
}