/* --------------------------------------------------------------------- * Numenta Platform for Intelligent Computing (NuPIC) * Copyright (C) 2014, Numenta, Inc. Unless you have an agreement * with Numenta, Inc., for a separate license for this software code, the * following terms and conditions apply: * * This program is free software: you can redistribute it and/or modify * it under the terms of the GNU Affero Public License version 3 as * published by the Free Software Foundation. * * 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 Affero Public License for more details. * * You should have received a copy of the GNU Affero Public License * along with this program. If not, see http://www.gnu.org/licenses. * * http://numenta.org/licenses/ * --------------------------------------------------------------------- */ package org.numenta.nupic.algorithms; import org.numenta.nupic.model.Persistable; import org.numenta.nupic.util.NamedTuple; /** * Container to hold a specific calculation for a statistical data point. * * Follows the form: * <pre> * { * "distribution": # describes the distribution * { * "name": STRING, # name of the distribution, such as 'normal' * "mean": SCALAR, # mean of the distribution * "variance": SCALAR, # variance of the distribution * * # There may also be some keys that are specific to the distribution * } * </pre> * @author David Ray */ public class Statistic implements Persistable { private static final long serialVersionUID = 1L; public final double mean; public final double variance; public final double stdev; public final NamedTuple entries; public Statistic(double mean, double variance, double stdev) { this.mean = mean; this.variance = variance; this.stdev = stdev; this.entries = new NamedTuple(new String[] { "mean", "variance", "stdev" }, mean, variance, stdev); } @Override public int hashCode() { final int prime = 31; int result = 1; long temp = Double.doubleToLongBits(mean); result = prime * result + (int)(temp ^ (temp >>> 32)); temp = Double.doubleToLongBits(stdev); result = prime * result + (int)(temp ^ (temp >>> 32)); temp = Double.doubleToLongBits(variance); result = prime * result + (int)(temp ^ (temp >>> 32)); return result; } @Override public boolean equals(Object obj) { if(this == obj) return true; if(obj == null) return false; if(getClass() != obj.getClass()) return false; Statistic other = (Statistic)obj; if(Double.doubleToLongBits(mean) != Double.doubleToLongBits(other.mean)) return false; if(Double.doubleToLongBits(stdev) != Double.doubleToLongBits(other.stdev)) return false; if(Double.doubleToLongBits(variance) != Double.doubleToLongBits(other.variance)) return false; return true; } }