109 lines
4.3 KiB
Java
109 lines
4.3 KiB
Java
/*
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* Copyright (c) 2013, Oracle and/or its affiliates. All rights reserved.
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* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
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*
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* This code is free software; you can redistribute it and/or modify it
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* under the terms of the GNU General Public License version 2 only, as
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* published by the Free Software Foundation.
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*
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* This code is distributed in the hope that it will be useful, but WITHOUT
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* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
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* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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* version 2 for more details (a copy is included in the LICENSE file that
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* accompanied this code).
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*
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* You should have received a copy of the GNU General Public License version
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* 2 along with this work; if not, write to the Free Software Foundation,
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* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
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*
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* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
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* or visit www.oracle.com if you need additional information or have any
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* questions.
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*/
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import java.util.*;
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import java.util.function.*;
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import java.util.stream.*;
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/*
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* @test
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* @bug 8006572
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* @summary Test for use of non-naive summation in stream-related sum and average operations.
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*/
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public class TestDoubleSumAverage {
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public static void main(String... args) {
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int failures = 0;
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failures += testForCompenstation();
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failures += testZeroAverageOfNonEmptyStream();
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if (failures > 0) {
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throw new RuntimeException("Found " + failures + " numerical failure(s).");
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}
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}
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/**
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* Compute the sum and average of a sequence of double values in
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* various ways and report an error if naive summation is used.
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*/
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private static int testForCompenstation() {
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int failures = 0;
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/*
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* The exact sum of the test stream is 1 + 1e6*ulp(1.0) but a
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* naive summation algorithm will return 1.0 since (1.0 +
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* ulp(1.0)/2) will round to 1.0 again.
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*/
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double base = 1.0;
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double increment = Math.ulp(base)/2.0;
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int count = 1_000_001;
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double expectedSum = base + (increment * (count - 1));
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double expectedAvg = expectedSum / count;
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// Factory for double a stream of [base, increment, ..., increment] limited to a size of count
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Supplier<DoubleStream> ds = () -> DoubleStream.iterate(base, e -> increment).limit(count);
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DoubleSummaryStatistics stats = ds.get().collect(DoubleSummaryStatistics::new,
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DoubleSummaryStatistics::accept,
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DoubleSummaryStatistics::combine);
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failures += compareUlpDifference(expectedSum, stats.getSum(), 3);
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failures += compareUlpDifference(expectedAvg, stats.getAverage(), 3);
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failures += compareUlpDifference(expectedSum,
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ds.get().sum(), 3);
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failures += compareUlpDifference(expectedAvg,
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ds.get().average().getAsDouble(), 3);
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failures += compareUlpDifference(expectedSum,
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ds.get().boxed().collect(Collectors.summingDouble(d -> d)), 3);
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failures += compareUlpDifference(expectedAvg,
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ds.get().boxed().collect(Collectors.averagingDouble(d -> d)),3);
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return failures;
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}
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/**
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* Test to verify that a non-empty stream with a zero average is non-empty.
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*/
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private static int testZeroAverageOfNonEmptyStream() {
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Supplier<DoubleStream> ds = () -> DoubleStream.iterate(0.0, e -> 0.0).limit(10);
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return compareUlpDifference(0.0, ds.get().average().getAsDouble(), 0);
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}
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/**
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* Compute the ulp difference of two double values and compare against an error threshold.
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*/
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private static int compareUlpDifference(double expected, double computed, double threshold) {
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double ulpDifference = Math.abs(expected - computed) / Math.ulp(expected);
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if (ulpDifference > threshold) {
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System.err.printf("Numerical summation error too large, %g ulps rather than %g.%n",
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ulpDifference, threshold);
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return 1;
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} else
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return 0;
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}
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}
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