/* * 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()); } } }