org.chocosolver.util.tools.StatisticUtils Maven / Gradle / Ivy

Go to download
Show more of this group Show more artifacts with this name
Show all versions of choco-solver Show documentation
Open-source constraint solver.
There is a newer version: 4.10.17
/*
 * This file is part of choco-solver, http://choco-solver.org/
 *
 * Copyright (c) 2020, IMT Atlantique. All rights reserved.
 *
 * Licensed under the BSD 4-clause license.
 *
 * See LICENSE file in the project root for full license information.
 */
package org.chocosolver.util.tools;

import java.util.Arrays;

/**
 * 

 * 
 * 
 *
 * @author Charles Prud'homme
 * @since 17 aug 2010
 */
public class StatisticUtils {

    protected StatisticUtils() {
    }

    public static int sum(int... values) {
        int sum = 0;
        for (int i = 0; i < values.length; i++) {
            sum += values[i];
        }
        return sum;
    }

    public static long sum(long... values) {
        long sum = 0L;
        for (int i = 0; i < values.length; i++) {
            sum += values[i];
        }
        return sum;
    }

    public static float sum(float... values) {
        float sum = 0.0f;
        for (int i = 0; i < values.length; i++) {
            sum += values[i];
        }
        return sum;
    }

    public static double sum(double... values) {
        double sum = 0.0;
        for (int i = 0; i < values.length; i++) {
            sum += values[i];
        }
        return sum;
    }

    public static double mean(int... values) {
        return sum(values)*1f / values.length;
    }

    public static float mean(long... values) {
        return sum(values)*1f / values.length;
    }

    public static double mean(float... values) {
        return sum(values) / values.length;
    }

    public static double mean(double... values) {
        return sum(values) / values.length;
    }


    public static double standarddeviation(int... values) {
        double mean = mean(values);
        double[] psd = new double[values.length];
        for (int i = 0; i < values.length; i++) {
            psd[i] = Math.pow(values[i] - mean, 2.0);
        }
        return Math.sqrt(mean(psd));
    }

    public static double standarddeviation(long... values) {
        double mean = mean(values);
        double[] psd = new double[values.length];
        for (int i = 0; i < values.length; i++) {
            psd[i] = Math.pow(values[i] - mean, 2.0);
        }
        return Math.sqrt(mean(psd));
    }

    public static float standarddeviation(float... values) {
        double mean = mean(values);
        double[] psd = new double[values.length];
        for (int i = 0; i < values.length; i++) {
            psd[i] = Math.pow(values[i] - mean, 2.0);
        }
        return (float) Math.sqrt(mean(psd));
    }

    public static int[] prepare(int... values) {
        Arrays.sort(values);
        int[] back = new int[values.length - 2];
        System.arraycopy(values, 1, back, 0, back.length);
        return back;
    }

    public static long[] prepare(long... values) {
        Arrays.sort(values);
        long[] back = new long[values.length - 2];
        System.arraycopy(values, 1, back, 0, back.length);
        return back;
    }

    public static float[] prepare(float... values) {
        Arrays.sort(values);
        float[] back = new float[values.length - 2];
        System.arraycopy(values, 1, back, 0, back.length);
        return back;
    }

    public static long binomialCoefficients(int n, int k) {

        long Ank = 1;

        if (k < 0 || k > n) {
            return 0;
        }

        long i = n - k + 1;
        while (i <= n && Ank >= 0) {
            Ank = Ank * i;
            i = i + 1;
        }
        if (Ank < 0) return Integer.MAX_VALUE;
        return Ank;
    }

}