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 package test.java.util.stream; 25 26 import java.util.*; 27 import java.util.function.*; 28 import java.util.stream.*; 29 30 import static java.lang.Double.*; 31 32 /* 33 * @test 34 * @bug 8006572 8030212 35 * @summary Test for use of non-naive summation in stream-related sum and average operations. 36 */ 37 public class TestDoubleSumAverage { main(String... args)38 public static void main(String... args) { 39 int failures = 0; 40 41 failures += testZeroAverageOfNonEmptyStream(); 42 failures += testForCompenstation(); 43 failures += testNonfiniteSum(); 44 45 if (failures > 0) { 46 throw new RuntimeException("Found " + failures + " numerical failure(s)."); 47 } 48 } 49 50 /** 51 * Test to verify that a non-empty stream with a zero average is non-empty. 52 */ testZeroAverageOfNonEmptyStream()53 private static int testZeroAverageOfNonEmptyStream() { 54 Supplier<DoubleStream> ds = () -> DoubleStream.iterate(0.0, e -> 0.0).limit(10); 55 56 return compareUlpDifference(0.0, ds.get().average().getAsDouble(), 0); 57 } 58 59 /** 60 * Compute the sum and average of a sequence of double values in 61 * various ways and report an error if naive summation is used. 62 */ testForCompenstation()63 private static int testForCompenstation() { 64 int failures = 0; 65 66 /* 67 * The exact sum of the test stream is 1 + 1e6*ulp(1.0) but a 68 * naive summation algorithm will return 1.0 since (1.0 + 69 * ulp(1.0)/2) will round to 1.0 again. 70 */ 71 double base = 1.0; 72 double increment = Math.ulp(base)/2.0; 73 int count = 1_000_001; 74 75 double expectedSum = base + (increment * (count - 1)); 76 double expectedAvg = expectedSum / count; 77 78 // Factory for double a stream of [base, increment, ..., increment] limited to a size of count 79 Supplier<DoubleStream> ds = () -> DoubleStream.iterate(base, e -> increment).limit(count); 80 81 DoubleSummaryStatistics stats = ds.get().collect(DoubleSummaryStatistics::new, 82 DoubleSummaryStatistics::accept, 83 DoubleSummaryStatistics::combine); 84 85 failures += compareUlpDifference(expectedSum, stats.getSum(), 3); 86 failures += compareUlpDifference(expectedAvg, stats.getAverage(), 3); 87 88 failures += compareUlpDifference(expectedSum, 89 ds.get().sum(), 3); 90 failures += compareUlpDifference(expectedAvg, 91 ds.get().average().getAsDouble(), 3); 92 93 failures += compareUlpDifference(expectedSum, 94 ds.get().boxed().collect(Collectors.summingDouble(d -> d)), 3); 95 failures += compareUlpDifference(expectedAvg, 96 ds.get().boxed().collect(Collectors.averagingDouble(d -> d)),3); 97 return failures; 98 } 99 testNonfiniteSum()100 private static int testNonfiniteSum() { 101 int failures = 0; 102 103 Map<Supplier<DoubleStream>, Double> testCases = new LinkedHashMap<>(); 104 testCases.put(() -> DoubleStream.of(MAX_VALUE, MAX_VALUE), POSITIVE_INFINITY); 105 testCases.put(() -> DoubleStream.of(-MAX_VALUE, -MAX_VALUE), NEGATIVE_INFINITY); 106 107 testCases.put(() -> DoubleStream.of(1.0d, POSITIVE_INFINITY, 1.0d), POSITIVE_INFINITY); 108 testCases.put(() -> DoubleStream.of(POSITIVE_INFINITY), POSITIVE_INFINITY); 109 testCases.put(() -> DoubleStream.of(POSITIVE_INFINITY, POSITIVE_INFINITY), POSITIVE_INFINITY); 110 testCases.put(() -> DoubleStream.of(POSITIVE_INFINITY, POSITIVE_INFINITY, 0.0), POSITIVE_INFINITY); 111 112 testCases.put(() -> DoubleStream.of(1.0d, NEGATIVE_INFINITY, 1.0d), NEGATIVE_INFINITY); 113 testCases.put(() -> DoubleStream.of(NEGATIVE_INFINITY), NEGATIVE_INFINITY); 114 testCases.put(() -> DoubleStream.of(NEGATIVE_INFINITY, NEGATIVE_INFINITY), NEGATIVE_INFINITY); 115 testCases.put(() -> DoubleStream.of(NEGATIVE_INFINITY, NEGATIVE_INFINITY, 0.0), NEGATIVE_INFINITY); 116 117 testCases.put(() -> DoubleStream.of(1.0d, NaN, 1.0d), NaN); 118 testCases.put(() -> DoubleStream.of(NaN), NaN); 119 testCases.put(() -> DoubleStream.of(1.0d, NEGATIVE_INFINITY, POSITIVE_INFINITY, 1.0d), NaN); 120 testCases.put(() -> DoubleStream.of(1.0d, POSITIVE_INFINITY, NEGATIVE_INFINITY, 1.0d), NaN); 121 testCases.put(() -> DoubleStream.of(POSITIVE_INFINITY, NaN), NaN); 122 testCases.put(() -> DoubleStream.of(NEGATIVE_INFINITY, NaN), NaN); 123 testCases.put(() -> DoubleStream.of(NaN, POSITIVE_INFINITY), NaN); 124 testCases.put(() -> DoubleStream.of(NaN, NEGATIVE_INFINITY), NaN); 125 126 for(Map.Entry<Supplier<DoubleStream>, Double> testCase : testCases.entrySet()) { 127 Supplier<DoubleStream> ds = testCase.getKey(); 128 double expected = testCase.getValue(); 129 130 DoubleSummaryStatistics stats = ds.get().collect(DoubleSummaryStatistics::new, 131 DoubleSummaryStatistics::accept, 132 DoubleSummaryStatistics::combine); 133 134 failures += compareUlpDifference(expected, stats.getSum(), 0); 135 failures += compareUlpDifference(expected, stats.getAverage(), 0); 136 137 failures += compareUlpDifference(expected, ds.get().sum(), 0); 138 failures += compareUlpDifference(expected, ds.get().average().getAsDouble(), 0); 139 140 failures += compareUlpDifference(expected, ds.get().boxed().collect(Collectors.summingDouble(d -> d)), 0); 141 failures += compareUlpDifference(expected, ds.get().boxed().collect(Collectors.averagingDouble(d -> d)), 0); 142 } 143 144 return failures; 145 } 146 147 /** 148 * Compute the ulp difference of two double values and compare against an error threshold. 149 */ compareUlpDifference(double expected, double computed, double threshold)150 private static int compareUlpDifference(double expected, double computed, double threshold) { 151 if (!Double.isFinite(expected)) { 152 // Handle NaN and infinity cases 153 if (Double.compare(expected, computed) == 0) 154 return 0; 155 else { 156 System.err.printf("Unexpected sum, %g rather than %g.%n", 157 computed, expected); 158 return 1; 159 } 160 } 161 162 double ulpDifference = Math.abs(expected - computed) / Math.ulp(expected); 163 164 if (ulpDifference > threshold) { 165 System.err.printf("Numerical summation error too large, %g ulps rather than %g.%n", 166 ulpDifference, threshold); 167 return 1; 168 } else 169 return 0; 170 } 171 } 172