MannWhitneyRankSumTest.java

package org.baderlab.csplugins.enrichmentmap;

import static org.junit.Assert.*;

import java.io.InputStream;
import java.util.Scanner;

import org.apache.commons.math3.stat.inference.MannWhitneyUTest;
import org.apache.commons.math3.stat.ranking.NaNStrategy;
import org.apache.commons.math3.stat.ranking.TiesStrategy;
import org.junit.Test;

/**
 * Test cases for Mann Whitney U
 */
public class MannWhitneyRankSumTest {
	double[] x, y;
	double expected_pVal, pValue;


    @Test
    public void testMannWhitneyPvalue() throws Exception {
        String testDataFileName = "src/test/resources/org/baderlab/csplugins/enrichmentmap/MannWhitneyTest_pvalues.csv";
        InputStream reader = new StreamUtil().getInputStream(testDataFileName);
        
        try(Scanner scanner = new Scanner(reader,"UTF-8")) {
	        String fullText = scanner.useDelimiter("\\A").next();
	        String[] lines = fullText.split("\n");
	        String[] tokens, x_s, y_s;
	        int i, j, k;
	        
	        for (i=1; i < lines.length ; i++ ) {
	        	// Split
	        	tokens = lines[i].split(",");
	        	
	        	// Parse x contents
	        	x_s = tokens[0].split("\\s");
	        	x = new double[x_s.length];
	        	for (j = 0; j < x_s.length; j++)
	        		x[j] = Double.parseDouble(x_s[j]);
	        	
	        	// Parse y contents
	        	y_s = tokens[1].split("\\s");
	        	y = new double[y_s.length];
	        	for (k = 0; k < y_s.length; k++)
	        		y[k] = Double.parseDouble(y_s[k]);
	        	
	        	// Procure expected pval
	        	expected_pVal = Double.parseDouble(tokens[2]);
	        	
				MannWhitneyUTest test = new MannWhitneyUTest(NaNStrategy.FAILED, TiesStrategy.AVERAGE);
				pValue = test.mannWhitneyUTest(x, y);
				
				assertEquals(expected_pVal, pValue, 0.0);
	        }
        }
    }
}