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 } 170
