google-nomulus/javatests/google/registry/monitoring/metrics/MutableDistributionTest.java
shikhman f76bc70f91 Preserve test logs and test summary output for Kokoro CI runs
-------------
Created by MOE: https://github.com/google/moe
MOE_MIGRATED_REVID=135494972
2016-10-14 16:57:43 -04:00

292 lines
9.7 KiB
Java

// Copyright 2016 The Nomulus Authors. All Rights Reserved.
//
// Licensed 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 google.registry.monitoring.metrics;
import static com.google.common.truth.Truth.assertThat;
import com.google.common.collect.ImmutableRangeMap;
import com.google.common.collect.ImmutableSet;
import com.google.common.collect.Range;
import org.junit.Before;
import org.junit.Rule;
import org.junit.Test;
import org.junit.rules.ExpectedException;
import org.junit.runner.RunWith;
import org.junit.runners.JUnit4;
/** Tests for {@link MutableDistribution} */
@RunWith(JUnit4.class)
public class MutableDistributionTest {
private MutableDistribution distribution;
@Rule public final ExpectedException thrown = ExpectedException.none();
@Before
public void setUp() throws Exception {
distribution = new MutableDistribution(CustomFitter.create(ImmutableSet.of(3.0, 5.0)));
}
@Test
public void testAdd_oneValue() {
distribution.add(5.0);
assertThat(distribution.count()).isEqualTo(1);
assertThat(distribution.mean()).isWithin(0.0).of(5.0);
assertThat(distribution.sumOfSquaredDeviation()).isWithin(0.0).of(0);
assertThat(distribution.intervalCounts())
.isEqualTo(
ImmutableRangeMap.<Double, Long>builder()
.put(Range.lessThan(3.0), 0L)
.put(Range.closedOpen(3.0, 5.0), 0L)
.put(Range.atLeast(5.0), 1L)
.build());
}
@Test
public void testAdd_zero() {
distribution.add(0.0);
assertThat(distribution.count()).isEqualTo(1);
assertThat(distribution.mean()).isWithin(0.0).of(0.0);
assertThat(distribution.sumOfSquaredDeviation()).isWithin(0.0).of(0);
assertThat(distribution.intervalCounts())
.isEqualTo(
ImmutableRangeMap.<Double, Long>builder()
.put(Range.lessThan(3.0), 1L)
.put(Range.closedOpen(3.0, 5.0), 0L)
.put(Range.atLeast(5.0), 0L)
.build());
}
@Test
public void testAdd_multipleOfOneValue() {
distribution.add(4.0, 2);
assertThat(distribution.count()).isEqualTo(2);
assertThat(distribution.mean()).isWithin(0.0).of(4.0);
assertThat(distribution.sumOfSquaredDeviation()).isWithin(0.0).of(0);
assertThat(distribution.intervalCounts())
.isEqualTo(
ImmutableRangeMap.<Double, Long>builder()
.put(Range.lessThan(3.0), 0L)
.put(Range.closedOpen(3.0, 5.0), 2L)
.put(Range.atLeast(5.0), 0L)
.build());
}
@Test
public void testAdd_positiveThenNegativeValue() {
distribution.add(2.0);
distribution.add(-2.0);
assertThat(distribution.count()).isEqualTo(2);
assertThat(distribution.mean()).isWithin(0.0).of(0.0);
assertThat(distribution.sumOfSquaredDeviation()).isWithin(0.0).of(8.0);
assertThat(distribution.intervalCounts())
.isEqualTo(
ImmutableRangeMap.<Double, Long>builder()
.put(Range.lessThan(3.0), 2L)
.put(Range.closedOpen(3.0, 5.0), 0L)
.put(Range.atLeast(5.0), 0L)
.build());
}
@Test
public void testAdd_wideRangeOfValues() {
distribution.add(2.0);
distribution.add(16.0);
distribution.add(128.0, 5);
assertThat(distribution.count()).isEqualTo(7);
assertThat(distribution.mean()).isWithin(0.0).of(94.0);
assertThat(distribution.sumOfSquaredDeviation()).isWithin(0.0).of(20328.0);
assertThat(distribution.intervalCounts())
.isEqualTo(
ImmutableRangeMap.<Double, Long>builder()
.put(Range.lessThan(3.0), 1L)
.put(Range.closedOpen(3.0, 5.0), 0L)
.put(Range.atLeast(5.0), 6L)
.build());
}
@Test
public void testAdd_negativeZero_throwsException() {
thrown.expect(IllegalArgumentException.class);
thrown.expectMessage("value must be finite, not NaN, and not -0.0");
distribution.add(Double.longBitsToDouble(0x80000000));
}
@Test
public void testAdd_NaN_throwsException() {
thrown.expect(IllegalArgumentException.class);
thrown.expectMessage("value must be finite, not NaN, and not -0.0");
distribution.add(Double.NaN);
}
@Test
public void testAdd_positiveInfinity_throwsException() {
thrown.expect(IllegalArgumentException.class);
thrown.expectMessage("value must be finite, not NaN, and not -0.0");
distribution.add(Double.POSITIVE_INFINITY);
}
@Test
public void testAdd_negativeInfinity_throwsException() {
thrown.expect(IllegalArgumentException.class);
thrown.expectMessage("value must be finite, not NaN, and not -0.0");
distribution.add(Double.NEGATIVE_INFINITY);
}
@Test
public void testAdd_iteratedFloatingPointValues_hasLowAccumulatedError() {
for (int i = 0; i < 500; i++) {
distribution.add(1 / 3.0);
distribution.add(1 / 7.0);
}
// Test for nine significant figures of accuracy.
assertThat(distribution.mean()).isWithin(0.000000001).of(5.0 / 21.0);
assertThat(distribution.sumOfSquaredDeviation())
.isWithin(0.000000001)
.of(1000 * 4.0 / (21.0 * 21.0));
}
@Test
public void testAdd_fitterWithNoFiniteIntervals_underflowValue_returnsUnderflowInterval()
throws Exception {
MutableDistribution distribution =
new MutableDistribution(CustomFitter.create(ImmutableSet.of(5.0)));
distribution.add(3.0);
assertThat(distribution.intervalCounts())
.isEqualTo(
ImmutableRangeMap.<Double, Long>builder()
.put(Range.lessThan(5.0), 1L)
.put(Range.atLeast(5.0), 0L)
.build());
}
@Test
public void testAdd_noFiniteIntervals_overflowValue_returnsOverflowInterval() throws Exception {
MutableDistribution distribution =
new MutableDistribution(CustomFitter.create(ImmutableSet.of(5.0)));
distribution.add(10.0);
assertThat(distribution.intervalCounts())
.isEqualTo(
ImmutableRangeMap.<Double, Long>builder()
.put(Range.lessThan(5.0), 0L)
.put(Range.atLeast(5.0), 1L)
.build());
}
@Test
public void testAdd_noFiniteIntervals_edgeValue_returnsOverflowInterval() throws Exception {
MutableDistribution distribution =
new MutableDistribution(CustomFitter.create(ImmutableSet.of(2.0)));
distribution.add(2.0);
assertThat(distribution.intervalCounts())
.isEqualTo(
ImmutableRangeMap.<Double, Long>builder()
.put(Range.lessThan(2.0), 0L)
.put(Range.atLeast(2.0), 1L)
.build());
}
@Test
public void testAdd_oneFiniteInterval_underflowValue_returnsUnderflowInterval() throws Exception {
MutableDistribution distribution =
new MutableDistribution(CustomFitter.create(ImmutableSet.of(1.0, 5.0)));
distribution.add(0.0);
assertThat(distribution.intervalCounts())
.isEqualTo(
ImmutableRangeMap.<Double, Long>builder()
.put(Range.lessThan(1.0), 1L)
.put(Range.closedOpen(1.0, 5.0), 0L)
.put(Range.atLeast(5.0), 0L)
.build());
}
@Test
public void testAdd_oneFiniteInterval_overflowValue_returnsOverflowInterval() throws Exception {
MutableDistribution distribution =
new MutableDistribution(CustomFitter.create(ImmutableSet.of(1.0, 5.0)));
distribution.add(10.0);
assertThat(distribution.intervalCounts())
.isEqualTo(
ImmutableRangeMap.<Double, Long>builder()
.put(Range.lessThan(1.0), 0L)
.put(Range.closedOpen(1.0, 5.0), 0L)
.put(Range.atLeast(5.0), 1L)
.build());
}
@Test
public void testAdd_oneFiniteInterval_inBoundsValue_returnsInBoundsInterval() throws Exception {
MutableDistribution distribution =
new MutableDistribution(CustomFitter.create(ImmutableSet.of(1.0, 5.0)));
distribution.add(3.0);
assertThat(distribution.intervalCounts())
.isEqualTo(
ImmutableRangeMap.<Double, Long>builder()
.put(Range.lessThan(1.0), 0L)
.put(Range.closedOpen(1.0, 5.0), 1L)
.put(Range.atLeast(5.0), 0L)
.build());
}
@Test
public void testAdd_oneFiniteInterval_firstEdgeValue_returnsFiniteInterval() throws Exception {
MutableDistribution distribution =
new MutableDistribution(CustomFitter.create(ImmutableSet.of(1.0, 5.0)));
distribution.add(1.0);
assertThat(distribution.intervalCounts())
.isEqualTo(
ImmutableRangeMap.<Double, Long>builder()
.put(Range.lessThan(1.0), 0L)
.put(Range.closedOpen(1.0, 5.0), 1L)
.put(Range.atLeast(5.0), 0L)
.build());
}
@Test
public void testAdd_oneFiniteInterval_secondEdgeValue_returnsOverflowInterval() throws Exception {
MutableDistribution distribution =
new MutableDistribution(CustomFitter.create(ImmutableSet.of(1.0, 5.0)));
distribution.add(5.0);
assertThat(distribution.intervalCounts())
.isEqualTo(
ImmutableRangeMap.<Double, Long>builder()
.put(Range.lessThan(1.0), 0L)
.put(Range.closedOpen(1.0, 5.0), 0L)
.put(Range.atLeast(5.0), 1L)
.build());
}
}