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/* ---------------------------------------------------------------------
 * 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:
 * 
 * {
 *    "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
 *     }
 * 
* @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; } }




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