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* 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.stat.descriptive;
import org.apache.commons.math.TestUtils;
import org.apache.commons.math.stat.descriptive.moment.SecondMoment;
/**
* Test cases for {@link StorelessUnivariateStatistic} classes.
* @version $Revision: 811685 $ $Date: 2009-09-05 13:36:48 -0400 (Sat, 05 Sep 2009) $
*/
public abstract class StorelessUnivariateStatisticAbstractTest
extends UnivariateStatisticAbstractTest {
public StorelessUnivariateStatisticAbstractTest(String name) {
super(name);
}
/** Small sample arrays */
protected double[][] smallSamples = {{}, {1}, {1,2}, {1,2,3}, {1,2,3,4}};
/** Return a new instance of the statistic */
@Override
public abstract UnivariateStatistic getUnivariateStatistic();
/**Expected value for the testArray defined in UnivariateStatisticAbstractTest */
@Override
public abstract double expectedValue();
/**
* Verifies that increment() and incrementAll work properly.
*/
public void testIncrementation() throws Exception {
StorelessUnivariateStatistic statistic =
(StorelessUnivariateStatistic) getUnivariateStatistic();
// Add testArray one value at a time and check result
for (int i = 0; i < testArray.length; i++) {
statistic.increment(testArray[i]);
}
assertEquals(expectedValue(), statistic.getResult(), getTolerance());
assertEquals(testArray.length, statistic.getN());
statistic.clear();
// Add testArray all at once and check again
statistic.incrementAll(testArray);
assertEquals(expectedValue(), statistic.getResult(), getTolerance());
assertEquals(testArray.length, statistic.getN());
statistic.clear();
// Cleared
assertTrue(Double.isNaN(statistic.getResult()));
assertEquals(0, statistic.getN());
}
public void testSerialization() throws Exception {
StorelessUnivariateStatistic statistic =
(StorelessUnivariateStatistic) getUnivariateStatistic();
TestUtils.checkSerializedEquality(statistic);
statistic.clear();
for (int i = 0; i < testArray.length; i++) {
statistic.increment(testArray[i]);
if(i % 5 == 0)
statistic = (StorelessUnivariateStatistic)TestUtils.serializeAndRecover(statistic);
}
TestUtils.checkSerializedEquality(statistic);
assertEquals(expectedValue(), statistic.getResult(), getTolerance());
statistic.clear();
assertTrue(Double.isNaN(statistic.getResult()));
}
public void testEqualsAndHashCode() {
StorelessUnivariateStatistic statistic =
(StorelessUnivariateStatistic) getUnivariateStatistic();
StorelessUnivariateStatistic statistic2 = null;
assertTrue("non-null, compared to null", !statistic.equals(statistic2));
assertTrue("reflexive, non-null", statistic.equals(statistic));
int emptyHash = statistic.hashCode();
statistic2 = (StorelessUnivariateStatistic) getUnivariateStatistic();
assertTrue("empty stats should be equal", statistic.equals(statistic2));
assertEquals("empty stats should have the same hashcode",
emptyHash, statistic2.hashCode());
statistic.increment(1d);
assertTrue("reflexive, non-empty", statistic.equals(statistic));
assertTrue("non-empty, compared to empty", !statistic.equals(statistic2));
assertTrue("non-empty, compared to empty", !statistic2.equals(statistic));
assertTrue("non-empty stat should have different hashcode from empty stat",
statistic.hashCode() != emptyHash);
statistic2.increment(1d);
assertTrue("stats with same data should be equal", statistic.equals(statistic2));
assertEquals("stats with same data should have the same hashcode",
statistic.hashCode(), statistic2.hashCode());
statistic.increment(Double.POSITIVE_INFINITY);
assertTrue("stats with different n's should not be equal", !statistic2.equals(statistic));
assertTrue("stats with different n's should have different hashcodes",
statistic.hashCode() != statistic2.hashCode());
statistic2.increment(Double.POSITIVE_INFINITY);
assertTrue("stats with same data should be equal", statistic.equals(statistic2));
assertEquals("stats with same data should have the same hashcode",
statistic.hashCode(), statistic2.hashCode());
statistic.clear();
statistic2.clear();
assertTrue("cleared stats should be equal", statistic.equals(statistic2));
assertEquals("cleared stats should have thashcode of empty stat",
emptyHash, statistic2.hashCode());
assertEquals("cleared stats should have thashcode of empty stat",
emptyHash, statistic.hashCode());
}
public void testMomentSmallSamples() {
UnivariateStatistic stat = getUnivariateStatistic();
if (stat instanceof SecondMoment) {
SecondMoment moment = (SecondMoment) getUnivariateStatistic();
assertTrue(Double.isNaN(moment.getResult()));
moment.increment(1d);
assertEquals(0d, moment.getResult(), 0);
}
}
/**
* Make sure that evaluate(double[]) and inrementAll(double[]),
* getResult() give same results.
*/
public void testConsistency() {
StorelessUnivariateStatistic stat = (StorelessUnivariateStatistic) getUnivariateStatistic();
stat.incrementAll(testArray);
assertEquals(stat.getResult(), stat.evaluate(testArray), getTolerance());
for (int i = 0; i < smallSamples.length; i++) {
stat.clear();
for (int j =0; j < smallSamples[i].length; j++) {
stat.increment(smallSamples[i][j]);
}
TestUtils.assertEquals(stat.getResult(), stat.evaluate(smallSamples[i]), getTolerance());
}
}
/**
* Verifies that copied statistics remain equal to originals when
* incremented the same way.
*
*/
public void testCopyConsistency() {
StorelessUnivariateStatistic master =
(StorelessUnivariateStatistic) getUnivariateStatistic();
StorelessUnivariateStatistic replica = null;
// Randomly select a portion of testArray to load first
long index = Math.round((Math.random()) * testArray.length);
// Put first half in master and copy master to replica
master.incrementAll(testArray, 0, (int) index);
replica = master.copy();
// Check same
assertTrue(replica.equals(master));
assertTrue(master.equals(replica));
// Now add second part to both and check again
master.incrementAll(testArray,
(int) index, (int) (testArray.length - index));
replica.incrementAll(testArray,
(int) index, (int) (testArray.length - index));
assertTrue(replica.equals(master));
assertTrue(master.equals(replica));
}
public void testSerial() {
StorelessUnivariateStatistic s =
(StorelessUnivariateStatistic) getUnivariateStatistic();
assertEquals(s, TestUtils.serializeAndRecover(s));
}
}