/*
* 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/>.
*/
/*
* PairedStats.java
* Copyright (C) 1999-2012 University of Waikato, Hamilton, New Zealand
*
*/
package weka.core;
import weka.core.RevisionHandler;
import weka.core.RevisionUtils;
import weka.core.Statistics;
import weka.core.Utils;
/**
* A class for storing stats on a paired comparison (t-test and correlation)
*
* @author Len Trigg (trigg@cs.waikato.ac.nz)
* @version $Revision: 8034 $
*/
public class PairedStats
implements RevisionHandler {
/** The stats associated with the data in column 1 */
public Stats xStats;
/** The stats associated with the data in column 2 */
public Stats yStats;
/** The stats associated with the paired differences */
public Stats differencesStats;
/** The probability of obtaining the observed differences */
public double differencesProbability;
/** The correlation coefficient */
public double correlation;
/** The sum of the products */
public double xySum;
/** The number of data points seen */
public double count;
/**
* A significance indicator:
* 0 if the differences are not significant
* > 0 if x significantly greater than y
* < 0 if x significantly less than y
*/
public int differencesSignificance;
/** The significance level for comparisons */
public double sigLevel;
/** The degrees of freedom (if set programmatically) */
protected int m_degreesOfFreedom = 0;
/**
* Creates a new PairedStats object with the supplied significance level.
*
* @param sig the significance level for comparisons
*/
public PairedStats(double sig) {
xStats = new Stats();
yStats = new Stats();
differencesStats = new Stats();
sigLevel = sig;
}
/**
* Sets the degrees of freedom (if calibration is required).
*/
public void setDegreesOfFreedom(int d) {
if (d <= 0) {
throw new IllegalArgumentException("PairedStats: degrees of freedom must be >= 1");
}
m_degreesOfFreedom = d;
}
/**
* Gets the degrees of freedom.
*/
public int getDegreesOfFreedom() {
return m_degreesOfFreedom;
}
/**
* Add an observed pair of values.
*
* @param value1 the value from column 1
* @param value2 the value from column 2
*/
public void add(double value1, double value2) {
xStats.add(value1);
yStats.add(value2);
differencesStats.add(value1 - value2);
xySum += value1 * value2;
count ++;
}
/**
* Removes an observed pair of values.
*
* @param value1 the value from column 1
* @param value2 the value from column 2
*/
public void subtract(double value1, double value2) {
xStats.subtract(value1);
yStats.subtract(value2);
differencesStats.subtract(value1 - value2);
xySum -= value1 * value2;
count --;
}
/**
* Adds an array of observed pair of values.
*
* @param value1 the array containing values from column 1
* @param value2 the array containing values from column 2
*/
public void add(double value1[], double value2[]) {
if ((value1 == null) || (value2 == null)) {
throw new NullPointerException();
}
if (value1.length != value2.length) {
throw new IllegalArgumentException("Arrays must be of the same length");
}
for (int i = 0; i < value1.length; i++) {
add(value1[i], value2[i]);
}
}
/**
* Removes an array of observed pair of values.
*
* @param value1 the array containing values from column 1
* @param value2 the array containing values from column 2
*/
public void subtract(double value1[], double value2[]) {
if ((value1 == null) || (value2 == null)) {
throw new NullPointerException();
}
if (value1.length != value2.length) {
throw new IllegalArgumentException("Arrays must be of the same length");
}
for (int i = 0; i < value1.length; i++) {
subtract(value1[i], value2[i]);
}
}
/**
* Calculates the derived statistics (significance etc).
*/
public void calculateDerived() {
xStats.calculateDerived();
yStats.calculateDerived();
differencesStats.calculateDerived();
correlation = Double.NaN;
if (!Double.isNaN(xStats.stdDev) && !Double.isNaN(yStats.stdDev)
&& !Utils.eq(xStats.stdDev, 0)) {
double slope = (xySum - xStats.sum * yStats.sum / count)
/ (xStats.sumSq - xStats.sum * xStats.mean);
if (!Utils.eq(yStats.stdDev, 0)) {
correlation = slope * xStats.stdDev / yStats.stdDev;
} else {
correlation = 1.0;
}
}
if (Utils.gr(differencesStats.stdDev, 0)) {
double tval = differencesStats.mean
* Math.sqrt(count)
/ differencesStats.stdDev;
if (m_degreesOfFreedom >= 1){
differencesProbability = Statistics.FProbability(tval * tval, 1,
m_degreesOfFreedom);
} else {
if (count > 1) {
differencesProbability = Statistics.FProbability(tval * tval, 1,
(int) count - 1);
} else {
differencesProbability = 1;
}
}
} else {
if (differencesStats.sumSq == 0) {
differencesProbability = 1.0;
} else {
differencesProbability = 0.0;
}
}
differencesSignificance = 0;
if (differencesProbability <= sigLevel) {
if (xStats.mean > yStats.mean) {
differencesSignificance = 1;
} else {
differencesSignificance = -1;
}
}
}
/**
* Returns statistics on the paired comparison.
*
* @return the t-test statistics as a string
*/
public String toString() {
return "Analysis for " + Utils.doubleToString(count, 0)
+ " points:\n"
+ " "
+ " Column 1"
+ " Column 2"
+ " Difference\n"
+ "Minimums "
+ Utils.doubleToString(xStats.min, 17, 4)
+ Utils.doubleToString(yStats.min, 17, 4)
+ Utils.doubleToString(differencesStats.min, 17, 4) + '\n'
+ "Maximums "
+ Utils.doubleToString(xStats.max, 17, 4)
+ Utils.doubleToString(yStats.max, 17, 4)
+ Utils.doubleToString(differencesStats.max, 17, 4) + '\n'
+ "Sums "
+ Utils.doubleToString(xStats.sum, 17, 4)
+ Utils.doubleToString(yStats.sum, 17, 4)
+ Utils.doubleToString(differencesStats.sum, 17, 4) + '\n'
+ "SumSquares "
+ Utils.doubleToString(xStats.sumSq, 17, 4)
+ Utils.doubleToString(yStats.sumSq, 17, 4)
+ Utils.doubleToString(differencesStats.sumSq, 17, 4) + '\n'
+ "Means "
+ Utils.doubleToString(xStats.mean, 17, 4)
+ Utils.doubleToString(yStats.mean, 17, 4)
+ Utils.doubleToString(differencesStats.mean, 17, 4) + '\n'
+ "SDs "
+ Utils.doubleToString(xStats.stdDev, 17, 4)
+ Utils.doubleToString(yStats.stdDev, 17, 4)
+ Utils.doubleToString(differencesStats.stdDev, 17, 4) + '\n'
+ "Prob(differences) "
+ Utils.doubleToString(differencesProbability, 4)
+ " (sigflag " + differencesSignificance + ")\n"
+ "Correlation "
+ Utils.doubleToString(correlation,4) + "\n";
}
/**
* Returns the revision string.
*
* @return the revision
*/
public String getRevision() {
return RevisionUtils.extract("$Revision: 8034 $");
}
/**
* Tests the paired stats object from the command line.
* reads line from stdin, expecting two values per line.
*
* @param args ignored.
*/
public static void main(String [] args) {
try {
PairedStats ps = new PairedStats(0.05);
java.io.LineNumberReader r = new java.io.LineNumberReader(
new java.io.InputStreamReader(System.in));
String line;
while ((line = r.readLine()) != null) {
line = line.trim();
if (line.equals("") || line.startsWith("@") || line.startsWith("%")) {
continue;
}
java.util.StringTokenizer s
= new java.util.StringTokenizer(line, " ,\t\n\r\f");
int count = 0;
double v1 = 0, v2 = 0;
while (s.hasMoreTokens()) {
double val = (new Double(s.nextToken())).doubleValue();
if (count == 0) {
v1 = val;
} else if (count == 1) {
v2 = val;
} else {
System.err.println("MSG: Too many values in line \""
+ line + "\", skipped.");
break;
}
count++;
}
if (count == 2) {
ps.add(v1, v2);
}
}
ps.calculateDerived();
System.err.println(ps);
} catch (Exception ex) {
ex.printStackTrace();
System.err.println(ex.getMessage());
}
}
} // PairedStats