1 /*
2 * Copyright (c) 2013, Oracle and/or its affiliates. All rights reserved.
3 * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
4 *
5 * This code is free software; you can redistribute it and/or modify it
6 * under the terms of the GNU General Public License version 2 only, as
7 * published by the Free Software Foundation.
8 *
9 * This code is distributed in the hope that it will be useful, but WITHOUT
10 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
11 * FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
12 * version 2 for more details (a copy is included in the LICENSE file that
13 * accompanied this code).
14 *
15 * You should have received a copy of the GNU General Public License version
16 * 2 along with this work; if not, write to the Free Software Foundation,
17 * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
18 *
19 * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
20 * or visit www.oracle.com if you need additional information or have any
21 * questions.
22 */
23
24 import java.util.*;
25 import java.util.function.*;
26 import java.util.stream.*;
27
28 import static java.lang.Double.*;
29
30 /*
31 * @test
32 * @bug 8006572 8030212
33 * @summary Test for use of non-naive summation in stream-related sum and average operations.
34 */
35 public class TestDoubleSumAverage {
36 public static void main(String... args) {
37 int failures = 0;
38
39 failures += testZeroAverageOfNonEmptyStream();
40 failures += testForCompenstation();
41 failures += testNonfiniteSum();
42
43 if (failures > 0) {
44 throw new RuntimeException("Found " + failures + " numerical failure(s).");
45 }
46 }
47
48 /**
49 * Test to verify that a non-empty stream with a zero average is non-empty.
50 */
51 private static int testZeroAverageOfNonEmptyStream() {
52 Supplier<DoubleStream> ds = () -> DoubleStream.iterate(0.0, e -> 0.0).limit(10);
53
54 return compareUlpDifference(0.0, ds.get().average().getAsDouble(), 0);
55 }
56
57 /**
58 * Compute the sum and average of a sequence of double values in
59 * various ways and report an error if naive summation is used.
60 */
61 private static int testForCompenstation() {
62 int failures = 0;
63
64 /*
65 * The exact sum of the test stream is 1 + 1e6*ulp(1.0) but a
66 * naive summation algorithm will return 1.0 since (1.0 +
67 * ulp(1.0)/2) will round to 1.0 again.
68 */
69 double base = 1.0;
70 double increment = Math.ulp(base)/2.0;
71 int count = 1_000_001;
72
73 double expectedSum = base + (increment * (count - 1));
74 double expectedAvg = expectedSum / count;
75
76 // Factory for double a stream of [base, increment, ..., increment] limited to a size of count
77 Supplier<DoubleStream> ds = () -> DoubleStream.iterate(base, e -> increment).limit(count);
78
79 DoubleSummaryStatistics stats = ds.get().collect(DoubleSummaryStatistics::new,
80 DoubleSummaryStatistics::accept,
81 DoubleSummaryStatistics::combine);
82
83 failures += compareUlpDifference(expectedSum, stats.getSum(), 3);
84 failures += compareUlpDifference(expectedAvg, stats.getAverage(), 3);
85
86 failures += compareUlpDifference(expectedSum,
87 ds.get().sum(), 3);
88 failures += compareUlpDifference(expectedAvg,
89 ds.get().average().getAsDouble(), 3);
90
91 failures += compareUlpDifference(expectedSum,
92 ds.get().boxed().collect(Collectors.summingDouble(d -> d)), 3);
93 failures += compareUlpDifference(expectedAvg,
94 ds.get().boxed().collect(Collectors.averagingDouble(d -> d)),3);
95 return failures;
96 }
97
98 private static int testNonfiniteSum() {
99 int failures = 0;
100
101 Map<Supplier<DoubleStream>, Double> testCases = new LinkedHashMap<>();
102 testCases.put(() -> DoubleStream.of(MAX_VALUE, MAX_VALUE), POSITIVE_INFINITY);
103 testCases.put(() -> DoubleStream.of(-MAX_VALUE, -MAX_VALUE), NEGATIVE_INFINITY);
104
105 testCases.put(() -> DoubleStream.of(1.0d, POSITIVE_INFINITY, 1.0d), POSITIVE_INFINITY);
106 testCases.put(() -> DoubleStream.of(POSITIVE_INFINITY), POSITIVE_INFINITY);
107 testCases.put(() -> DoubleStream.of(POSITIVE_INFINITY, POSITIVE_INFINITY), POSITIVE_INFINITY);
108 testCases.put(() -> DoubleStream.of(POSITIVE_INFINITY, POSITIVE_INFINITY, 0.0), POSITIVE_INFINITY);
109
110 testCases.put(() -> DoubleStream.of(1.0d, NEGATIVE_INFINITY, 1.0d), NEGATIVE_INFINITY);
111 testCases.put(() -> DoubleStream.of(NEGATIVE_INFINITY), NEGATIVE_INFINITY);
112 testCases.put(() -> DoubleStream.of(NEGATIVE_INFINITY, NEGATIVE_INFINITY), NEGATIVE_INFINITY);
113 testCases.put(() -> DoubleStream.of(NEGATIVE_INFINITY, NEGATIVE_INFINITY, 0.0), NEGATIVE_INFINITY);
114
115 testCases.put(() -> DoubleStream.of(1.0d, NaN, 1.0d), NaN);
116 testCases.put(() -> DoubleStream.of(NaN), NaN);
117 testCases.put(() -> DoubleStream.of(1.0d, NEGATIVE_INFINITY, POSITIVE_INFINITY, 1.0d), NaN);
118 testCases.put(() -> DoubleStream.of(1.0d, POSITIVE_INFINITY, NEGATIVE_INFINITY, 1.0d), NaN);
119 testCases.put(() -> DoubleStream.of(POSITIVE_INFINITY, NaN), NaN);
120 testCases.put(() -> DoubleStream.of(NEGATIVE_INFINITY, NaN), NaN);
121 testCases.put(() -> DoubleStream.of(NaN, POSITIVE_INFINITY), NaN);
122 testCases.put(() -> DoubleStream.of(NaN, NEGATIVE_INFINITY), NaN);
123
124 for(Map.Entry<Supplier<DoubleStream>, Double> testCase : testCases.entrySet()) {
125 Supplier<DoubleStream> ds = testCase.getKey();
126 double expected = testCase.getValue();
127
128 DoubleSummaryStatistics stats = ds.get().collect(DoubleSummaryStatistics::new,
129 DoubleSummaryStatistics::accept,
130 DoubleSummaryStatistics::combine);
131
132 failures += compareUlpDifference(expected, stats.getSum(), 0);
133 failures += compareUlpDifference(expected, stats.getAverage(), 0);
134
135 failures += compareUlpDifference(expected, ds.get().sum(), 0);
136 failures += compareUlpDifference(expected, ds.get().average().getAsDouble(), 0);
137
138 failures += compareUlpDifference(expected, ds.get().boxed().collect(Collectors.summingDouble(d -> d)), 0);
139 failures += compareUlpDifference(expected, ds.get().boxed().collect(Collectors.averagingDouble(d -> d)), 0);
140 }
141
142 return failures;
143 }
144
145 /**
146 * Compute the ulp difference of two double values and compare against an error threshold.
147 */
148 private static int compareUlpDifference(double expected, double computed, double threshold) {
149 if (!Double.isFinite(expected)) {
150 // Handle NaN and infinity cases
151 if (Double.compare(expected, computed) == 0)
152 return 0;
153 else {
154 System.err.printf("Unexpected sum, %g rather than %g.%n",
155 computed, expected);
156 return 1;
157 }
158 }
159
160 double ulpDifference = Math.abs(expected - computed) / Math.ulp(expected);
161
162 if (ulpDifference > threshold) {
163 System.err.printf("Numerical summation error too large, %g ulps rather than %g.%n",
164 ulpDifference, threshold);
165 return 1;
166 } else
167 return 0;
168 }
169 }