Example usage for org.apache.commons.math.stat.correlation SpearmansCorrelation correlation

Introduction

In this page you can find the example usage for org.apache.commons.math.stat.correlation SpearmansCorrelation correlation.

Prototype

public double correlation(final double[] xArray, final double[] yArray) throws IllegalArgumentException 

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Document

Computes the Spearman's rank correlation coefficient between the two arrays.

Usage

From source file:cal.binBased.Calculate_BinSpectrum_Similarity.java

/**
 * This method calculates correlation coefficients between two MSnSpectrum
 * object while taking into account of intensities of the mutual peaks. A
 * perfect score is 1 (or -1). And value range is [-1:1]
 *
 *///from ww w . j  a  v  a  2s.  co m
public void calculateCorrelation() {
    // TODO: Make sure if any of binSpectra is empty, score i NaN!       
    if (sim_method.equals(SimilarityMethods.SPEARMANS_CORRELATION)) {
        SpearmansCorrelation sc = new SpearmansCorrelation();
        score = sc.correlation(bin_specA.getBin_spectrum(), bin_specB.getBin_spectrum());
    } else if (sim_method.equals(SimilarityMethods.PEARSONS_CORRELATION)) {
        PearsonsCorrelation pc = new PearsonsCorrelation();
        score = pc.correlation(bin_specA.getBin_spectrum(), bin_specB.getBin_spectrum());
    }
}

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From source file:org.dkpro.statistics.correlation.SpearmansRankCorrelation.java

/**
 * Computes the correlation between two datasets.
 * @param list1 The first dataset as a list.
 * @param list2 The second dataset as a list.
 * @return The correlation between the two datasets.
 *//*from ww w. j  a v  a  2  s .co  m*/
public static double computeCorrelation(List<Double> list1, List<Double> list2) {
    double[] l1 = new double[list1.size()];
    double[] l2 = new double[list2.size()];

    for (int i = 0; i < list1.size(); i++) {
        l1[i] = list1.get(i);
    }
    for (int i = 0; i < list2.size(); i++) {
        l2[i] = list2.get(i);
    }

    SpearmansCorrelation sc = new SpearmansCorrelation();
    return sc.correlation(l1, l2);
}

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