/*
* The MIT License
*
* Copyright (c) 2013 The Broad Institute
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
package htsjdk.tribble.util;
/**
* a collection of functions and classes for various common calculations
*/
public class MathUtils {
/**
* a class for calculating moving statistics - this class returns the
* mean, variance, and std dev after accumulating any number of records.
* taken from http://www.johndcook.com/standard_deviation.html
*/
public static class RunningStat {
private double oldMean, newMean, oldStdDev, newStdDev;
private long recordCount = 0;
/**
* @param x the value to add to the running mean and variance
*/
public void push(double x) {
recordCount++;
// See Knuth TAOCP vol 2, 3rd edition, page 232
if (recordCount == 1) {
oldMean = newMean = x;
oldStdDev = 0.0;
} else {
newMean = oldMean + (x - oldMean) / recordCount;
newStdDev = oldStdDev + (x - oldMean) * (x - newMean);
// set up for next iteration
oldMean = newMean;
oldStdDev = newStdDev;
}
}
public void clear() { recordCount = 0; }
public final long numDataValues() { return recordCount; }
public final double mean() { return (recordCount > 0) ? newMean : 0.0; }
public double variance() { return ((recordCount > 1) ? newStdDev / (recordCount - 1) : 0.0); }
public double standardDeviation() { return Math.sqrt(variance()); }
}
}