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The Waikato Environment for Knowledge Analysis (WEKA), a machine learning workbench. This version represents the developer version, the "bleeding edge" of development, you could say. New functionality gets added to this version.
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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 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 .
 */

/*
 *    Stats.java
 *    Copyright (C) 1999-2012 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.experiment;

import java.io.Serializable;

import weka.core.RevisionHandler;
import weka.core.RevisionUtils;
import weka.core.Utils;

/**
 * A class to store simple statistics
 *
 * @author Len Trigg ([email protected])
 * @version $Revision: 8034 $
 */
public class Stats
  implements Serializable, RevisionHandler {

  /** for serialization */
  private static final long serialVersionUID = -8610544539090024102L;
  
  /** The number of values seen */
  public double count = 0;

  /** The sum of values seen */
  public double sum = 0;

  /** The sum of values squared seen */
  public double sumSq = 0;

  /** The std deviation of values at the last calculateDerived() call */    
  public double stdDev = Double.NaN;

  /** The mean of values at the last calculateDerived() call */    
  public double mean = Double.NaN;

  /** The minimum value seen, or Double.NaN if no values seen */
  public double min = Double.NaN;

  /** The maximum value seen, or Double.NaN if no values seen */
  public double max = Double.NaN;
    
  /**
   * Adds a value to the observed values
   *
   * @param value the observed value
   */
  public void add(double value) {

    add(value, 1);
  }

  /**
   * Adds a value that has been seen n times to the observed values
   *
   * @param value the observed value
   * @param n the number of times to add value
   */
  public void add(double value, double n) {

    sum += value * n;
    sumSq += value * value * n;
    count += n;
    if (Double.isNaN(min)) {
      min = max = value;
    } else if (value < min) {
      min = value;
    } else if (value > max) {
      max = value;
    }
  }

  /**
   * Removes a value to the observed values (no checking is done
   * that the value being removed was actually added). 
   *
   * @param value the observed value
   */
  public void subtract(double value) {
    subtract(value, 1);
  }

  /**
   * Subtracts a value that has been seen n times from the observed values
   *
   * @param value the observed value
   * @param n the number of times to subtract value
   */
  public void subtract(double value, double n) {
    sum -= value * n;
    sumSq -= value * value * n;
    count -= n;
  }

  /**
   * Tells the object to calculate any statistics that don't have their
   * values automatically updated during add. Currently updates the mean
   * and standard deviation.
   */
  public void calculateDerived() {

    mean = Double.NaN;
    stdDev = Double.NaN;
    if (count > 0) {
      mean = sum / count;
      stdDev = Double.POSITIVE_INFINITY;
      if (count > 1) {
	stdDev = sumSq - (sum * sum) / count;
	stdDev /= (count - 1);
        if (stdDev < 0) {
	  //          System.err.println("Warning: stdDev value = " + stdDev 
	  //                             + " -- rounded to zero.");
          stdDev = 0;
        }
	stdDev = Math.sqrt(stdDev);
      }
    }
  }
    
  /**
   * Returns a string summarising the stats so far.
   *
   * @return the summary string
   */
  public String toString() {

    calculateDerived();
    return
      "Count   " + Utils.doubleToString(count, 8) + '\n'
      + "Min     " + Utils.doubleToString(min, 8) + '\n'
      + "Max     " + Utils.doubleToString(max, 8) + '\n'
      + "Sum     " + Utils.doubleToString(sum, 8) + '\n'
      + "SumSq   " + Utils.doubleToString(sumSq, 8) + '\n'
      + "Mean    " + Utils.doubleToString(mean, 8) + '\n'
      + "StdDev  " + Utils.doubleToString(stdDev, 8) + '\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 {
      Stats ps = new Stats();
      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;
	while (s.hasMoreTokens()) {
	  double val = (new Double(s.nextToken())).doubleValue();
	  if (count == 0) {
	    v1 = val;
	  } else {
            System.err.println("MSG: Too many values in line \"" 
                               + line + "\", skipped.");
	    break;
	  }
	  count++;
	}
        if (count == 1) {
          ps.add(v1);
        }
      }
      ps.calculateDerived();
      System.err.println(ps);
    } catch (Exception ex) {
      ex.printStackTrace();
      System.err.println(ex.getMessage());
    }
  }

} // Stats