/*
* 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.flink.api.java.summarize.aggregation;
import org.apache.flink.api.java.summarize.NumericColumnSummary;
import org.junit.Assert;
import org.junit.Test;
public class DoubleSummaryAggregatorTest {
/**
* Use some values from Anscombe's Quartet for testing.
*
* There was no particular reason to use these except they have known means and variance.
*
* https://en.wikipedia.org/wiki/Anscombe%27s_quartet
*/
@Test
public void testAnscomesQuartetXValues() throws Exception {
final Double[] q1x = { 10.0, 8.0, 13.0, 9.0, 11.0, 14.0, 6.0, 4.0, 12.0, 7.0, 5.0 };
final Double[] q4x = { 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 8.0, 19.0, 8.0, 8.0, 8.0 };
NumericColumnSummary<Double> q1 = summarize(q1x);
NumericColumnSummary<Double> q4 = summarize(q4x);
Assert.assertEquals(9.0, q1.getMean().doubleValue(), 0.0);
Assert.assertEquals(9.0, q4.getMean().doubleValue(), 0.0);
Assert.assertEquals(11.0, q1.getVariance().doubleValue(), 1e-10d);
Assert.assertEquals(11.0, q4.getVariance().doubleValue(), 1e-10d);
double stddev = Math.sqrt(11.0);
Assert.assertEquals(stddev, q1.getStandardDeviation().doubleValue(), 1e-10d);
Assert.assertEquals(stddev, q4.getStandardDeviation().doubleValue(), 1e-10d);
}
/**
* Use some values from Anscombe's Quartet for testing.
*
* There was no particular reason to use these except they have known means and variance.
*
* https://en.wikipedia.org/wiki/Anscombe%27s_quartet
*/
@Test
public void testAnscomesQuartetYValues() throws Exception {
final Double[] q1y = { 8.04, 6.95, 7.58, 8.81, 8.33, 9.96, 7.24, 4.26, 10.84, 4.82, 5.68 };
final Double[] q2y = { 9.14, 8.14, 8.74, 8.77, 9.26, 8.1, 6.13, 3.1, 9.13, 7.26, 4.74 };
final Double[] q3y = { 7.46, 6.77, 12.74, 7.11, 7.81, 8.84, 6.08, 5.39, 8.15, 6.42, 5.73 };
final Double[] q4y = { 6.58, 5.76, 7.71, 8.84, 8.47, 7.04, 5.25, 12.5, 5.56, 7.91, 6.89 };
NumericColumnSummary<Double> q1 = summarize(q1y);
NumericColumnSummary<Double> q2 = summarize(q2y);
NumericColumnSummary<Double> q3 = summarize(q3y);
NumericColumnSummary<Double> q4 = summarize(q4y);
// the y values are have less precisely matching means and variances
Assert.assertEquals(7.5, q1.getMean().doubleValue(), 0.001);
Assert.assertEquals(7.5, q2.getMean().doubleValue(), 0.001);
Assert.assertEquals(7.5, q3.getMean().doubleValue(), 0.001);
Assert.assertEquals(7.5, q4.getMean().doubleValue(), 0.001);
Assert.assertEquals(4.12, q1.getVariance().doubleValue(), 0.01);
Assert.assertEquals(4.12, q2.getVariance().doubleValue(), 0.01);
Assert.assertEquals(4.12, q3.getVariance().doubleValue(), 0.01);
Assert.assertEquals(4.12, q4.getVariance().doubleValue(), 0.01);
}
@Test
public void testIsNan() throws Exception {
DoubleSummaryAggregator ag = new DoubleSummaryAggregator();
Assert.assertFalse(ag.isNan(-1.0));
Assert.assertFalse(ag.isNan(0.0));
Assert.assertFalse(ag.isNan(23.0));
Assert.assertFalse(ag.isNan(Double.MAX_VALUE));
Assert.assertFalse(ag.isNan(Double.MIN_VALUE));
Assert.assertTrue(ag.isNan(Double.NaN));
}
@Test
public void testIsInfinite() throws Exception {
DoubleSummaryAggregator ag = new DoubleSummaryAggregator();
Assert.assertFalse(ag.isInfinite(-1.0));
Assert.assertFalse(ag.isInfinite(0.0));
Assert.assertFalse(ag.isInfinite(23.0));
Assert.assertFalse(ag.isInfinite(Double.MAX_VALUE));
Assert.assertFalse(ag.isInfinite(Double.MIN_VALUE));
Assert.assertTrue(ag.isInfinite(Double.POSITIVE_INFINITY));
Assert.assertTrue(ag.isInfinite(Double.NEGATIVE_INFINITY));
}
@Test
public void testMean() throws Exception {
Assert.assertEquals(50.0, summarize(0.0, 100.0).getMean(), 0.0);
Assert.assertEquals(33.333333, summarize(0.0, 0.0, 100.0).getMean(), 0.00001);
Assert.assertEquals(50.0, summarize(0.0, 0.0, 100.0, 100.0).getMean(), 0.0);
Assert.assertEquals(50.0, summarize(0.0, 100.0, null).getMean(), 0.0);
Assert.assertNull(summarize().getMean());
}
@Test
public void testSum() throws Exception {
Assert.assertEquals(100.0, summarize(0.0, 100.0).getSum().doubleValue(), 0.0);
Assert.assertEquals(15, summarize(1.0, 2.0, 3.0, 4.0, 5.0).getSum().doubleValue(), 0.0);
Assert.assertEquals(0, summarize(-100.0, 0.0, 100.0, null).getSum().doubleValue(), 0.0);
Assert.assertEquals(90, summarize(-10.0, 100.0, null).getSum().doubleValue(), 0.0);
Assert.assertNull(summarize().getSum());
}
@Test
public void testMax() throws Exception {
Assert.assertEquals(1001.0, summarize(-1000.0, 0.0, 1.0, 50.0, 999.0, 1001.0).getMax().doubleValue(), 0.0);
Assert.assertEquals(11.0, summarize(1.0, 8.0, 7.0, 6.0, 9.0, 10.0, 2.0, 3.0, 5.0, 0.0, 11.0, -2.0, 3.0).getMax().doubleValue(), 0.0);
Assert.assertEquals(11.0, summarize(1.0, 8.0, 7.0, 6.0, 9.0, null, 10.0, 2.0, 3.0, 5.0, null, 0.0, 11.0, -2.0, 3.0).getMax().doubleValue(), 0.0);
Assert.assertNull(summarize().getMax());
}
@Test
public void testMin() throws Exception {
Assert.assertEquals(-1000, summarize(-1000.0, 0.0, 1.0, 50.0, 999.0, 1001.0).getMin().doubleValue(), 0.0);
Assert.assertEquals(-2.0, summarize(1.0, 8.0, 7.0, 6.0, 9.0, 10.0, 2.0, 3.0, 5.0, 0.0, 11.0, -2.0, 3.0).getMin().doubleValue(), 0.0);
Assert.assertEquals(-2.0, summarize(1.0, 8.0, 7.0, 6.0, 9.0, null, 10.0, 2.0, 3.0, 5.0, null, 0.0, 11.0, -2.0, 3.0).getMin().doubleValue(), 0.0);
Assert.assertNull(summarize().getMin());
}
@Test
public void testCounts() throws Exception {
NumericColumnSummary<Double> summary = summarize(Double.NaN, 1.0, null, 123.0, -44.00001, Double.POSITIVE_INFINITY, 55.0, Double.NEGATIVE_INFINITY, Double.NEGATIVE_INFINITY, null, Double.NaN);
Assert.assertEquals(11, summary.getTotalCount());
Assert.assertEquals(2, summary.getNullCount());
Assert.assertEquals(9, summary.getNonNullCount());
Assert.assertEquals(7, summary.getMissingCount());
Assert.assertEquals(4, summary.getNonMissingCount());
Assert.assertEquals(2, summary.getNanCount());
Assert.assertEquals(3, summary.getInfinityCount());
}
/**
* Helper method for summarizing a list of values.
*
* This method breaks the rule of "testing only one thing" by aggregating and combining
* a bunch of different ways.
*/
protected NumericColumnSummary<Double> summarize(Double... values) {
return new AggregateCombineHarness<Double,NumericColumnSummary<Double>,DoubleSummaryAggregator>() {
@Override
protected void compareResults(NumericColumnSummary<Double> result1, NumericColumnSummary<Double> result2) {
Assert.assertEquals(result1.getMin(), result2.getMin(), 0.0);
Assert.assertEquals(result1.getMax(), result2.getMax(), 0.0);
Assert.assertEquals(result1.getMean(), result2.getMean(), 1e-12d);
Assert.assertEquals(result1.getVariance(), result2.getVariance(), 1e-9d);
Assert.assertEquals(result1.getStandardDeviation(), result2.getStandardDeviation(), 1e-12d);
}
}.summarize(values);
}
}