/*
* 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 2.0f (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-2.0f
*
* 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 FloatSummaryAggregatorTest {
/**
* 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 Float[] q1x = { 10.0f, 8.0f, 13.0f, 9.0f, 11.0f, 14.0f, 6.0f, 4.0f, 12.0f, 7.0f, 5.0f };
final Float[] q4x = { 8.0f, 8.0f, 8.0f, 8.0f, 8.0f, 8.0f, 8.0f, 19.0f, 8.0f, 8.0f, 8.0f };
NumericColumnSummary<Float> q1 = summarize(q1x);
NumericColumnSummary<Float> q4 = summarize(q4x);
Assert.assertEquals(9.0, q1.getMean().doubleValue(), 0.0f);
Assert.assertEquals(9.0, q4.getMean().doubleValue(), 0.0f);
Assert.assertEquals(11.0, q1.getVariance().doubleValue(), 1e-10d);
Assert.assertEquals(11.0, q4.getVariance().doubleValue(), 1e-10d);
double stddev = Math.sqrt(11.0f);
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 Float[] q1y = { 8.04f, 6.95f, 7.58f, 8.81f, 8.33f, 9.96f, 7.24f, 4.26f, 10.84f, 4.82f, 5.68f };
final Float[] q2y = { 9.14f, 8.14f, 8.74f, 8.77f, 9.26f, 8.1f, 6.13f, 3.1f, 9.13f, 7.26f, 4.74f };
final Float[] q3y = { 7.46f, 6.77f, 12.74f, 7.11f, 7.81f, 8.84f, 6.08f, 5.39f, 8.15f, 6.42f, 5.73f };
final Float[] q4y = { 6.58f, 5.76f, 7.71f, 8.84f, 8.47f, 7.04f, 5.25f, 12.5f, 5.56f, 7.91f, 6.89f };
NumericColumnSummary<Float> q1 = summarize(q1y);
NumericColumnSummary<Float> q2 = summarize(q2y);
NumericColumnSummary<Float> q3 = summarize(q3y);
NumericColumnSummary<Float> 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 {
FloatSummaryAggregator ag = new FloatSummaryAggregator();
Assert.assertFalse(ag.isNan(-1.0f));
Assert.assertFalse(ag.isNan(0.0f));
Assert.assertFalse(ag.isNan(23.0f));
Assert.assertFalse(ag.isNan(Float.MAX_VALUE));
Assert.assertFalse(ag.isNan(Float.MIN_VALUE));
Assert.assertTrue(ag.isNan(Float.NaN));
}
@Test
public void testIsInfinite() throws Exception {
FloatSummaryAggregator ag = new FloatSummaryAggregator();
Assert.assertFalse(ag.isInfinite(-1.0f));
Assert.assertFalse(ag.isInfinite(0.0f));
Assert.assertFalse(ag.isInfinite(23.0f));
Assert.assertFalse(ag.isInfinite(Float.MAX_VALUE));
Assert.assertFalse(ag.isInfinite(Float.MIN_VALUE));
Assert.assertTrue(ag.isInfinite(Float.POSITIVE_INFINITY));
Assert.assertTrue(ag.isInfinite(Float.NEGATIVE_INFINITY));
}
@Test
public void testMean() throws Exception {
Assert.assertEquals(50.0, summarize(0.0f, 100.0f).getMean(), 0.0);
Assert.assertEquals(33.333333, summarize(0.0f, 0.0f, 100.0f).getMean(), 0.00001);
Assert.assertEquals(50.0, summarize(0.0f, 0.0f, 100.0f, 100.0f).getMean(), 0.0);
Assert.assertEquals(50.0, summarize(0.0f, 100.0f, null).getMean(), 0.0);
Assert.assertNull(summarize().getMean());
}
@Test
public void testSum() throws Exception {
Assert.assertEquals(100.0, summarize(0.0f, 100.0f).getSum().floatValue(), 0.0f);
Assert.assertEquals(15, summarize(1.0f, 2.0f, 3.0f, 4.0f, 5.0f).getSum().floatValue(), 0.0f);
Assert.assertEquals(0, summarize(-100.0f, 0.0f, 100.0f, null).getSum().floatValue(), 0.0f);
Assert.assertEquals(90, summarize(-10.0f, 100.0f, null).getSum().floatValue(), 0.0f);
Assert.assertNull(summarize().getSum());
}
@Test
public void testMax() throws Exception {
Assert.assertEquals(1001.0f, summarize(-1000.0f, 0.0f, 1.0f, 50.0f, 999.0f, 1001.0f).getMax().floatValue(), 0.0f);
Assert.assertEquals(11.0f, summarize(1.0f, 8.0f, 7.0f, 6.0f, 9.0f, 10.0f, 2.0f, 3.0f, 5.0f, 0.0f, 11.0f, -2.0f, 3.0f).getMax().floatValue(), 0.0f);
Assert.assertEquals(11.0f, summarize(1.0f, 8.0f, 7.0f, 6.0f, 9.0f, null, 10.0f, 2.0f, 3.0f, 5.0f, null, 0.0f, 11.0f, -2.0f, 3.0f).getMax().floatValue(), 0.0f);
Assert.assertNull(summarize().getMax());
}
@Test
public void testMin() throws Exception {
Assert.assertEquals(-1000, summarize(-1000.0f, 0.0f, 1.0f, 50.0f, 999.0f, 1001.0f).getMin().floatValue(), 0.0f);
Assert.assertEquals(-2.0f, summarize(1.0f, 8.0f, 7.0f, 6.0f, 9.0f, 10.0f, 2.0f, 3.0f, 5.0f, 0.0f, 11.0f, -2.0f, 3.0f).getMin().floatValue(), 0.0f);
Assert.assertEquals(-2.0f, summarize(1.0f, 8.0f, 7.0f, 6.0f, 9.0f, null, 10.0f, 2.0f, 3.0f, 5.0f, null, 0.0f, 11.0f, -2.0f, 3.0f).getMin().floatValue(), 0.0f);
Assert.assertNull(summarize().getMin());
}
/**
* 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<Float> summarize(Float... values) {
return new AggregateCombineHarness<Float,NumericColumnSummary<Float>,FloatSummaryAggregator>() {
@Override
protected void compareResults(NumericColumnSummary<Float> result1, NumericColumnSummary<Float> result2) {
Assert.assertEquals(result1.getMin(), result2.getMin(), 0.0f);
Assert.assertEquals(result1.getMax(), result2.getMax(), 0.0f);
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);
}
}