/*
* 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.math;
import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.IOException;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.text.DecimalFormat;
import junit.framework.Assert;
import junit.framework.AssertionFailedError;
import org.apache.commons.math.complex.Complex;
import org.apache.commons.math.complex.ComplexFormat;
import org.apache.commons.math.distribution.ContinuousDistribution;
import org.apache.commons.math.linear.FieldMatrix;
import org.apache.commons.math.linear.RealMatrix;
import org.apache.commons.math.stat.inference.ChiSquareTest;
import org.apache.commons.math.stat.inference.ChiSquareTestImpl;
import org.apache.commons.math.util.FastMath;
/**
* @version $Revision: 1042376 $ $Date: 2010-12-05 16:54:55 +0100 (dim. 05 déc. 2010) $
*/
public class TestUtils {
/**
* Collection of static methods used in math unit tests.
*/
private TestUtils() {
super();
}
/**
* Verifies that expected and actual are within delta, or are both NaN or
* infinities of the same sign.
*/
public static void assertEquals(double expected, double actual, double delta) {
assertEquals(null, expected, actual, delta);
}
/**
* Verifies that expected and actual are within delta, or are both NaN or
* infinities of the same sign.
*/
public static void assertEquals(String msg, double expected, double actual, double delta) {
// check for NaN
if(Double.isNaN(expected)){
Assert.assertTrue("" + actual + " is not NaN.",
Double.isNaN(actual));
} else {
Assert.assertEquals(msg, expected, actual, delta);
}
}
/**
* Verifies that the two arguments are exactly the same, either
* both NaN or infinities of same sign, or identical floating point values.
*/
public static void assertSame(double expected, double actual) {
assertEquals(expected, actual, 0);
}
/**
* Verifies that real and imaginary parts of the two complex arguments
* are exactly the same. Also ensures that NaN / infinite components match.
*/
public static void assertSame(Complex expected, Complex actual) {
assertSame(expected.getReal(), actual.getReal());
assertSame(expected.getImaginary(), actual.getImaginary());
}
/**
* Verifies that real and imaginary parts of the two complex arguments
* differ by at most delta. Also ensures that NaN / infinite components match.
*/
public static void assertEquals(Complex expected, Complex actual, double delta) {
assertEquals(expected.getReal(), actual.getReal(), delta);
assertEquals(expected.getImaginary(), actual.getImaginary(), delta);
}
/**
* Verifies that two double arrays have equal entries, up to tolerance
*/
public static void assertEquals(double expected[], double observed[], double tolerance) {
assertEquals("Array comparison failure", expected, observed, tolerance);
}
/**
* Serializes an object to a bytes array and then recovers the object from the bytes array.
* Returns the deserialized object.
*
* @param o object to serialize and recover
* @return the recovered, deserialized object
*/
public static Object serializeAndRecover(Object o) {
try {
// serialize the Object
ByteArrayOutputStream bos = new ByteArrayOutputStream();
ObjectOutputStream so = new ObjectOutputStream(bos);
so.writeObject(o);
// deserialize the Object
ByteArrayInputStream bis = new ByteArrayInputStream(bos.toByteArray());
ObjectInputStream si = new ObjectInputStream(bis);
return si.readObject();
} catch (IOException ioe) {
return null;
} catch (ClassNotFoundException cnfe) {
return null;
}
}
/**
* Verifies that serialization preserves equals and hashCode.
* Serializes the object, then recovers it and checks equals and hash code.
*
* @param object the object to serialize and recover
*/
public static void checkSerializedEquality(Object object) {
Object object2 = serializeAndRecover(object);
Assert.assertEquals("Equals check", object, object2);
Assert.assertEquals("HashCode check", object.hashCode(), object2.hashCode());
}
/**
* Verifies that the relative error in actual vs. expected is less than or
* equal to relativeError. If expected is infinite or NaN, actual must be
* the same (NaN or infinity of the same sign).
*
* @param expected expected value
* @param actual observed value
* @param relativeError maximum allowable relative error
*/
public static void assertRelativelyEquals(double expected, double actual,
double relativeError) {
assertRelativelyEquals(null, expected, actual, relativeError);
}
/**
* Verifies that the relative error in actual vs. expected is less than or
* equal to relativeError. If expected is infinite or NaN, actual must be
* the same (NaN or infinity of the same sign).
*
* @param msg message to return with failure
* @param expected expected value
* @param actual observed value
* @param relativeError maximum allowable relative error
*/
public static void assertRelativelyEquals(String msg, double expected,
double actual, double relativeError) {
if (Double.isNaN(expected)) {
Assert.assertTrue(msg, Double.isNaN(actual));
} else if (Double.isNaN(actual)) {
Assert.assertTrue(msg, Double.isNaN(expected));
} else if (Double.isInfinite(actual) || Double.isInfinite(expected)) {
Assert.assertEquals(expected, actual, relativeError);
} else if (expected == 0.0) {
Assert.assertEquals(msg, actual, expected, relativeError);
} else {
double absError = FastMath.abs(expected) * relativeError;
Assert.assertEquals(msg, expected, actual, absError);
}
}
/**
* Fails iff values does not contain a number within epsilon of z.
*
* @param msg message to return with failure
* @param values complex array to search
* @param z value sought
* @param epsilon tolerance
*/
public static void assertContains(String msg, Complex[] values,
Complex z, double epsilon) {
int i = 0;
boolean found = false;
while (!found && i < values.length) {
try {
assertEquals(values[i], z, epsilon);
found = true;
} catch (AssertionFailedError er) {
// no match
}
i++;
}
if (!found) {
Assert.fail(msg +
" Unable to find " + ComplexFormat.formatComplex(z));
}
}
/**
* Fails iff values does not contain a number within epsilon of z.
*
* @param values complex array to search
* @param z value sought
* @param epsilon tolerance
*/
public static void assertContains(Complex[] values,
Complex z, double epsilon) {
assertContains(null, values, z, epsilon);
}
/**
* Fails iff values does not contain a number within epsilon of x.
*
* @param msg message to return with failure
* @param values double array to search
* @param x value sought
* @param epsilon tolerance
*/
public static void assertContains(String msg, double[] values,
double x, double epsilon) {
int i = 0;
boolean found = false;
while (!found && i < values.length) {
try {
assertEquals(values[i], x, epsilon);
found = true;
} catch (AssertionFailedError er) {
// no match
}
i++;
}
if (!found) {
Assert.fail(msg + " Unable to find" + x);
}
}
/**
* Fails iff values does not contain a number within epsilon of x.
*
* @param values double array to search
* @param x value sought
* @param epsilon tolerance
*/
public static void assertContains(double[] values, double x,
double epsilon) {
assertContains(null, values, x, epsilon);
}
/** verifies that two matrices are close (1-norm) */
public static void assertEquals(String msg, RealMatrix expected, RealMatrix observed,
double tolerance) {
Assert.assertNotNull(msg + "\nObserved should not be null",observed);
if (expected.getColumnDimension() != observed.getColumnDimension() ||
expected.getRowDimension() != observed.getRowDimension()) {
StringBuilder messageBuffer = new StringBuilder(msg);
messageBuffer.append("\nObserved has incorrect dimensions.");
messageBuffer.append("\nobserved is " + observed.getRowDimension() +
" x " + observed.getColumnDimension());
messageBuffer.append("\nexpected " + expected.getRowDimension() +
" x " + expected.getColumnDimension());
Assert.fail(messageBuffer.toString());
}
RealMatrix delta = expected.subtract(observed);
if (delta.getNorm() >= tolerance) {
StringBuilder messageBuffer = new StringBuilder(msg);
messageBuffer.append("\nExpected: " + expected);
messageBuffer.append("\nObserved: " + observed);
messageBuffer.append("\nexpected - observed: " + delta);
Assert.fail(messageBuffer.toString());
}
}
/** verifies that two matrices are equal */
public static void assertEquals(FieldMatrix<? extends FieldElement<?>> expected,
FieldMatrix<? extends FieldElement<?>> observed) {
Assert.assertNotNull("Observed should not be null",observed);
if (expected.getColumnDimension() != observed.getColumnDimension() ||
expected.getRowDimension() != observed.getRowDimension()) {
StringBuilder messageBuffer = new StringBuilder();
messageBuffer.append("Observed has incorrect dimensions.");
messageBuffer.append("\nobserved is " + observed.getRowDimension() +
" x " + observed.getColumnDimension());
messageBuffer.append("\nexpected " + expected.getRowDimension() +
" x " + expected.getColumnDimension());
Assert.fail(messageBuffer.toString());
}
for (int i = 0; i < expected.getRowDimension(); ++i) {
for (int j = 0; j < expected.getColumnDimension(); ++j) {
FieldElement<?> eij = expected.getEntry(i, j);
FieldElement<?> oij = observed.getEntry(i, j);
Assert.assertEquals(eij, oij);
}
}
}
/** verifies that two arrays are close (sup norm) */
public static void assertEquals(String msg, double[] expected, double[] observed,
double tolerance) {
StringBuilder out = new StringBuilder(msg);
if (expected.length != observed.length) {
out.append("\n Arrays not same length. \n");
out.append("expected has length ");
out.append(expected.length);
out.append(" observed length = ");
out.append(observed.length);
Assert.fail(out.toString());
}
boolean failure = false;
for (int i=0; i < expected.length; i++) {
try {
assertEquals(expected[i], observed[i], tolerance);
} catch (AssertionFailedError ex) {
failure = true;
out.append("\n Elements at index ");
out.append(i);
out.append(" differ. ");
out.append(" expected = ");
out.append(expected[i]);
out.append(" observed = ");
out.append(observed[i]);
}
}
if (failure) {
Assert.fail(out.toString());
}
}
/** verifies that two arrays are equal */
public static <T extends FieldElement<T>> void assertEquals(T[] m, T[] n) {
if (m.length != n.length) {
Assert.fail("vectors not same length");
}
for (int i = 0; i < m.length; i++) {
Assert.assertEquals(m[i],n[i]);
}
}
/**
* Computes the sum of squared deviations of <values> from <target>
* @param values array of deviates
* @param target value to compute deviations from
*
* @return sum of squared deviations
*/
public static double sumSquareDev(double[] values, double target) {
double sumsq = 0d;
for (int i = 0; i < values.length; i++) {
final double dev = values[i] - target;
sumsq += (dev * dev);
}
return sumsq;
}
/**
* Asserts the null hypothesis for a ChiSquare test. Fails and dumps arguments and test
* statistics if the null hypothesis can be rejected with confidence 100 * (1 - alpha)%
*
* @param valueLabels
* @param expected expected counts
* @param observed observed counts
* @param alpha significance level of the test
*/
public static void assertChiSquareAccept(String[] valueLabels, double[] expected, long[] observed, double alpha) throws Exception {
ChiSquareTest chiSquareTest = new ChiSquareTestImpl();
try {
// Fail if we can reject null hypothesis that distributions are the same
Assert.assertFalse(chiSquareTest.chiSquareTest(expected, observed, alpha));
} catch (AssertionFailedError ex) {
StringBuilder msgBuffer = new StringBuilder();
DecimalFormat df = new DecimalFormat("#.##");
msgBuffer.append("Chisquare test failed");
msgBuffer.append(" p-value = ");
msgBuffer.append(chiSquareTest.chiSquareTest(expected, observed));
msgBuffer.append(" chisquare statistic = ");
msgBuffer.append(chiSquareTest.chiSquare(expected, observed));
msgBuffer.append(". \n");
msgBuffer.append("value\texpected\tobserved\n");
for (int i = 0; i < expected.length; i++) {
msgBuffer.append(valueLabels[i]);
msgBuffer.append("\t");
msgBuffer.append(df.format(expected[i]));
msgBuffer.append("\t\t");
msgBuffer.append(observed[i]);
msgBuffer.append("\n");
}
msgBuffer.append("This test can fail randomly due to sampling error with probability ");
msgBuffer.append(alpha);
msgBuffer.append(".");
Assert.fail(msgBuffer.toString());
}
}
/**
* Asserts the null hypothesis for a ChiSquare test. Fails and dumps arguments and test
* statistics if the null hypothesis can be rejected with confidence 100 * (1 - alpha)%
*
* @param values
* @param expected expected counts
* @param observed observed counts
* @param alpha significance level of the test
*/
public static void assertChiSquareAccept(int[] values, double[] expected, long[] observed, double alpha) throws Exception {
String[] labels = new String[values.length];
for (int i = 0; i < values.length; i++) {
labels[i] = Integer.toString(values[i]);
}
assertChiSquareAccept(labels, expected, observed, alpha);
}
/**
* Asserts the null hypothesis for a ChiSquare test. Fails and dumps arguments and test
* statistics if the null hypothesis can be rejected with confidence 100 * (1 - alpha)%
*
* @param values
* @param expected expected counts
* @param observed observed counts
* @param alpha significance level of the test
*/
public static void assertChiSquareAccept(double[] values, double[] expected, long[] observed, double alpha) throws Exception {
String[] labels = new String[values.length];
for (int i = 0; i < values.length; i++) {
labels[i] = Double.toString(values[i]);
}
assertChiSquareAccept(labels, expected, observed, alpha);
}
/**
* Asserts the null hypothesis for a ChiSquare test. Fails and dumps arguments and test
* statistics if the null hypothesis can be rejected with confidence 100 * (1 - alpha)%
*
* @param expected expected counts
* @param observed observed counts
* @param alpha significance level of the test
*/
public static void assertChiSquareAccept(double[] expected, long[] observed, double alpha) throws Exception {
String[] labels = new String[expected.length];
for (int i = 0; i < labels.length; i++) {
labels[i] = Integer.toString(i + 1);
}
assertChiSquareAccept(labels, expected, observed, alpha);
}
/**
* Computes the 25th, 50th and 75th percentiles of the given distribution and returns
* these values in an array.
*/
public static double[] getDistributionQuartiles(ContinuousDistribution distribution) throws Exception {
double[] quantiles = new double[3];
quantiles[0] = distribution.inverseCumulativeProbability(0.25d);
quantiles[1] = distribution.inverseCumulativeProbability(0.5d);
quantiles[2] = distribution.inverseCumulativeProbability(0.75d);
return quantiles;
}
/**
* Updates observed counts of values in quartiles.
* counts[0] <-> 1st quartile ... counts[3] <-> top quartile
*/
public static void updateCounts(double value, long[] counts, double[] quartiles) {
if (value < quartiles[0]) {
counts[0]++;
} else if (value > quartiles[2]) {
counts[3]++;
} else if (value > quartiles[1]) {
counts[2]++;
} else {
counts[1]++;
}
}
/**
* Eliminates points with zero mass from densityPoints and densityValues parallel
* arrays. Returns the number of positive mass points and collapses the arrays so
* that the first <returned value> elements of the input arrays represent the positive
* mass points.
*/
public static int eliminateZeroMassPoints(int[] densityPoints, double[] densityValues) {
int positiveMassCount = 0;
for (int i = 0; i < densityValues.length; i++) {
if (densityValues[i] > 0) {
positiveMassCount++;
}
}
if (positiveMassCount < densityValues.length) {
int[] newPoints = new int[positiveMassCount];
double[] newValues = new double[positiveMassCount];
int j = 0;
for (int i = 0; i < densityValues.length; i++) {
if (densityValues[i] > 0) {
newPoints[j] = densityPoints[i];
newValues[j] = densityValues[i];
j++;
}
}
System.arraycopy(newPoints,0,densityPoints,0,positiveMassCount);
System.arraycopy(newValues,0,densityValues,0,positiveMassCount);
}
return positiveMassCount;
}
}