/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.commons.math3.stat.correlation;
import org.apache.commons.math3.TestUtils;
import org.apache.commons.math3.linear.BlockRealMatrix;
import org.apache.commons.math3.linear.MatrixUtils;
import org.apache.commons.math3.linear.RealMatrix;
import org.apache.commons.math3.stat.ranking.NaNStrategy;
import org.apache.commons.math3.stat.ranking.NaturalRanking;
import org.junit.Assert;
import org.junit.Test;
/**
* Test cases for Spearman's rank correlation
*
* @since 2.0
*/
public class SpearmansRankCorrelationTest extends PearsonsCorrelationTest {
/**
* Test Longley dataset against R.
*/
@Override
@Test
public void testLongly() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
RealMatrix correlationMatrix = corrInstance.getCorrelationMatrix();
double[] rData = new double[] {
1, 0.982352941176471, 0.985294117647059, 0.564705882352941, 0.2264705882352941, 0.976470588235294,
0.976470588235294, 0.982352941176471, 1, 0.997058823529412, 0.664705882352941, 0.2205882352941176,
0.997058823529412, 0.997058823529412, 0.985294117647059, 0.997058823529412, 1, 0.638235294117647,
0.2235294117647059, 0.9941176470588236, 0.9941176470588236, 0.564705882352941, 0.664705882352941,
0.638235294117647, 1, -0.3411764705882353, 0.685294117647059, 0.685294117647059, 0.2264705882352941,
0.2205882352941176, 0.2235294117647059, -0.3411764705882353, 1, 0.2264705882352941, 0.2264705882352941,
0.976470588235294, 0.997058823529412, 0.9941176470588236, 0.685294117647059, 0.2264705882352941, 1, 1,
0.976470588235294, 0.997058823529412, 0.9941176470588236, 0.685294117647059, 0.2264705882352941, 1, 1
};
TestUtils.assertEquals("Spearman's correlation matrix", createRealMatrix(rData, 7, 7), correlationMatrix, 10E-15);
}
/**
* Test R swiss fertility dataset.
*/
@Test
public void testSwiss() {
RealMatrix matrix = createRealMatrix(swissData, 47, 5);
SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
RealMatrix correlationMatrix = corrInstance.getCorrelationMatrix();
double[] rData = new double[] {
1, 0.2426642769364176, -0.660902996352354, -0.443257690360988, 0.4136455623012432,
0.2426642769364176, 1, -0.598859938748963, -0.650463814145816, 0.2886878090882852,
-0.660902996352354, -0.598859938748963, 1, 0.674603831406147, -0.4750575257171745,
-0.443257690360988, -0.650463814145816, 0.674603831406147, 1, -0.1444163088302244,
0.4136455623012432, 0.2886878090882852, -0.4750575257171745, -0.1444163088302244, 1
};
TestUtils.assertEquals("Spearman's correlation matrix", createRealMatrix(rData, 5, 5), correlationMatrix, 10E-15);
}
/**
* Constant column
*/
@Override
@Test
public void testConstant() {
double[] noVariance = new double[] {1, 1, 1, 1};
double[] values = new double[] {1, 2, 3, 4};
Assert.assertTrue(Double.isNaN(new SpearmansCorrelation().correlation(noVariance, values)));
}
/**
* Insufficient data
*/
@Override
@Test
public void testInsufficientData() {
double[] one = new double[] {1};
double[] two = new double[] {2};
try {
new SpearmansCorrelation().correlation(one, two);
Assert.fail("Expecting IllegalArgumentException");
} catch (IllegalArgumentException ex) {
// Expected
}
RealMatrix matrix = new BlockRealMatrix(new double[][] {{0},{1}});
try {
new SpearmansCorrelation(matrix);
Assert.fail("Expecting IllegalArgumentException");
} catch (IllegalArgumentException ex) {
// Expected
}
}
@Override
@Test
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
SpearmansCorrelation corrInstance = new SpearmansCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
Assert.assertEquals(new SpearmansCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new SpearmansCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
@Test
public void testMath891Array() {
final double[] xArray = new double[] { Double.NaN, 1.9, 2, 100, 3 };
final double[] yArray = new double[] { 10, 2, 10, Double.NaN, 4 };
NaturalRanking ranking = new NaturalRanking(NaNStrategy.REMOVED);
SpearmansCorrelation spearman = new SpearmansCorrelation(ranking);
Assert.assertEquals(0.5, spearman.correlation(xArray, yArray), Double.MIN_VALUE);
}
@Test
public void testMath891Matrix() {
final double[] xArray = new double[] { Double.NaN, 1.9, 2, 100, 3 };
final double[] yArray = new double[] { 10, 2, 10, Double.NaN, 4 };
RealMatrix matrix = MatrixUtils.createRealMatrix(xArray.length, 2);
for (int i = 0; i < xArray.length; i++) {
matrix.addToEntry(i, 0, xArray[i]);
matrix.addToEntry(i, 1, yArray[i]);
}
// compute correlation
NaturalRanking ranking = new NaturalRanking(NaNStrategy.REMOVED);
SpearmansCorrelation spearman = new SpearmansCorrelation(matrix, ranking);
Assert.assertEquals(0.5, spearman.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
}
// Not relevant here
@Override
@Test
public void testStdErrorConsistency() {}
@Override
@Test
public void testCovarianceConsistency() {}
}