1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
|
/*
* Copyright (C) 2014 The Guava Authors
*
* 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 com.google.common.math;
import static com.google.common.truth.Truth.assertThat;
import static com.google.common.truth.Truth.assertWithMessage;
import com.google.common.collect.ImmutableSet;
import com.google.common.collect.Sets;
import java.util.Map;
import java.util.Random;
import java.util.Set;
import junit.framework.TestCase;
/**
* Tests that the different algorithms benchmarked in {@link QuantilesBenchmark} are actually all
* returning more-or-less the same answers.
*/
public class QuantilesAlgorithmTest extends TestCase {
private static final Random RNG = new Random(82674067L);
private static final int DATASET_SIZE = 1000;
private static final double ALLOWED_ERROR = 1.0e-10;
private static final QuantilesAlgorithm REFERENCE_ALGORITHM = QuantilesAlgorithm.SORTING;
private static final Set<QuantilesAlgorithm> NON_REFERENCE_ALGORITHMS =
Sets.difference(
ImmutableSet.copyOf(QuantilesAlgorithm.values()), ImmutableSet.of(REFERENCE_ALGORITHM));
private double[] dataset;
@Override
protected void setUp() {
dataset = new double[DATASET_SIZE];
for (int i = 0; i < DATASET_SIZE; i++) {
dataset[i] = RNG.nextDouble();
}
}
public void testSingleQuantile_median() {
double referenceValue = REFERENCE_ALGORITHM.singleQuantile(1, 2, dataset.clone());
for (QuantilesAlgorithm algorithm : NON_REFERENCE_ALGORITHMS) {
assertWithMessage("Mismatch between %s and %s", algorithm, REFERENCE_ALGORITHM)
.that(algorithm.singleQuantile(1, 2, dataset.clone()))
.isWithin(ALLOWED_ERROR)
.of(referenceValue);
}
}
public void testSingleQuantile_percentile99() {
double referenceValue = REFERENCE_ALGORITHM.singleQuantile(99, 100, dataset.clone());
for (QuantilesAlgorithm algorithm : NON_REFERENCE_ALGORITHMS) {
assertWithMessage("Mismatch between %s and %s", algorithm, REFERENCE_ALGORITHM)
.that(algorithm.singleQuantile(99, 100, dataset.clone()))
.isWithin(ALLOWED_ERROR)
.of(referenceValue);
}
}
public void testMultipleQuantile() {
ImmutableSet<Integer> indexes = ImmutableSet.of(50, 90, 99);
Map<Integer, Double> referenceQuantiles =
REFERENCE_ALGORITHM.multipleQuantiles(indexes, 100, dataset.clone());
assertThat(referenceQuantiles.keySet()).isEqualTo(indexes);
for (QuantilesAlgorithm algorithm : NON_REFERENCE_ALGORITHMS) {
Map<Integer, Double> quantiles = algorithm.multipleQuantiles(indexes, 100, dataset.clone());
assertWithMessage("Wrong keys from " + algorithm).that(quantiles.keySet()).isEqualTo(indexes);
for (int i : indexes) {
assertWithMessage("Mismatch between %s and %s at %s", algorithm, REFERENCE_ALGORITHM, i)
.that(quantiles.get(i))
.isWithin(ALLOWED_ERROR)
.of(referenceQuantiles.get(i));
}
}
}
}
|
