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Changed method name to be consistent with Covariance, added double[][] compute method. 

git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@764312 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Phil Steitz 2009-04-12 18:48:29 +00:00
parent 53b912cb49
commit 3b26eea983
2 changed files with 27 additions and 2 deletions
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16
src/java/org/apache/commons/math/stat/correlation/PearsonsCorrelation.java
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@ -77,7 +77,7 @@ public class PearsonsCorrelation {
public PearsonsCorrelation(RealMatrix matrix) {
checkSufficientData(matrix);
nObs = matrix.getRowDimension();
correlationMatrix = computeCorrelation(matrix);
correlationMatrix = computeCorrelationMatrix(matrix);
}
/**
@ -183,7 +183,7 @@ public class PearsonsCorrelation {
* @param matrix matrix with columns representing variables to correlate
* @return correlation matrix
*/
public RealMatrix computeCorrelation(RealMatrix matrix) {
public RealMatrix computeCorrelationMatrix(RealMatrix matrix) {
int nVars = matrix.getColumnDimension();
RealMatrix outMatrix = new DenseRealMatrix(nVars, nVars);
for (int i = 0; i < nVars; i++) {
@ -197,6 +197,18 @@ public class PearsonsCorrelation {
return outMatrix;
}
/**
* Computes the correlation matrix for the columns of the
* input rectangular array. The colums of the array represent values
* of variables to be correlated.
*
* @param data matrix with columns representing variables to correlate
* @return correlation matrix
*/
public RealMatrix computeCorrelationMatrix(double[][] data) {
return computeCorrelationMatrix(new DenseRealMatrix(data));
}
/**
* Computes the Pearson's product-moment correlation coefficient between the two arrays.
*

13
src/test/org/apache/commons/math/stat/correlation/PearsonsCorrelationTest.java
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@ -240,6 +240,19 @@ public class PearsonsCorrelationTest extends TestCase {
corrFromCovInstance2.getCorrelationStandardErrors(), 10E-15);
}
public void testConsistency() {
RealMatrix matrix = createRealMatrix(longleyData, 16, 7);
PearsonsCorrelation corrInstance = new PearsonsCorrelation(matrix);
double[][] data = matrix.getData();
double[] x = matrix.getColumn(0);
double[] y = matrix.getColumn(1);
assertEquals(new PearsonsCorrelation().correlation(x, y),
corrInstance.getCorrelationMatrix().getEntry(0, 1), Double.MIN_VALUE);
TestUtils.assertEquals("Correlation matrix", corrInstance.getCorrelationMatrix(),
new PearsonsCorrelation().computeCorrelationMatrix(data), Double.MIN_VALUE);
}
protected RealMatrix createRealMatrix(double[] data, int nRows, int nCols) {
double[][] matrixData = new double[nRows][nCols];
int ptr = 0;