org.briljantframework.statistics.FastStatistics.java Source code

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Here is the source code for org.briljantframework.statistics.FastStatistics.java

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/**
 * The MIT License (MIT)
 *
 * Copyright (c) 2016 Isak Karlsson
 *
 * 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 org.briljantframework.statistics;

import org.apache.commons.math3.stat.descriptive.StatisticalSummary;
import org.apache.commons.math3.stat.descriptive.StatisticalSummaryValues;

/**
 * A fast implementation of the {@link StatisticalSummary} interface.
 *
 * @author Isak Karlsson
 */
public class FastStatistics implements StatisticalSummary {

    private int n = 0;
    private double sum = 0;
    private double om, nm, os, ns;
    private double min = Double.NEGATIVE_INFINITY, max = Double.POSITIVE_INFINITY;

    public void addAll(double[] arr) {
        for (double v : arr) {
            addValue(v);
        }
    }

    public void addValue(double x) {
        n += 1;
        if (n == 1) {
            om = x;
            nm = x;
            os = 0;
            min = x;
            max = x;
            sum = x;
        } else {
            nm = om + (x - om) / n;
            ns = os + (x - om) * (x - nm);
            om = nm;
            os = ns;
            sum += x;
            if (x < min) {
                min = x;
            } else if (x > max) {
                max = x;
            }
        }
    }

    public StatisticalSummary getSummary() {
        return new StatisticalSummaryValues(getMean(), getVariance(), getN(), getMax(), getMin(), getSum());
    }

    @Override
    public double getMean() {
        return n > 0 ? nm : 0;
    }

    @Override
    public double getVariance() {
        return n > 1 ? ns / n : 0;
    }

    @Override
    public double getStandardDeviation() {
        return Math.sqrt(getVariance());
    }

    @Override
    public double getMax() {
        return max;
    }

    @Override
    public double getMin() {
        return min;
    }

    @Override
    public long getN() {
        return n;
    }

    @Override
    public double getSum() {
        return sum;
    }
}