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/*
* Copyright (c) 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
import java.util.*;
import java.util.function.*;
import java.util.stream.*;
import static java.lang.Double.*;
/*
* @test
* @bug 8006572 8030212
* @summary Test for use of non-naive summation in stream-related sum and average operations.
*/
public class TestDoubleSumAverage {
public static void main(String... args) {
int failures = 0;
failures += testZeroAverageOfNonEmptyStream();
failures += testForCompenstation();
failures += testNonfiniteSum();
if (failures > 0) {
throw new RuntimeException("Found " + failures + " numerical failure(s).");
}
}
/**
* Test to verify that a non-empty stream with a zero average is non-empty.
*/
private static int testZeroAverageOfNonEmptyStream() {
Supplier<DoubleStream> ds = () -> DoubleStream.iterate(0.0, e -> 0.0).limit(10);
return compareUlpDifference(0.0, ds.get().average().getAsDouble(), 0);
}
/**
* Compute the sum and average of a sequence of double values in
* various ways and report an error if naive summation is used.
*/
private static int testForCompenstation() {
int failures = 0;
/*
* The exact sum of the test stream is 1 + 1e6*ulp(1.0) but a
* naive summation algorithm will return 1.0 since (1.0 +
* ulp(1.0)/2) will round to 1.0 again.
*/
double base = 1.0;
double increment = Math.ulp(base)/2.0;
int count = 1_000_001;
double expectedSum = base + (increment * (count - 1));
double expectedAvg = expectedSum / count;
// Factory for double a stream of [base, increment, ..., increment] limited to a size of count
Supplier<DoubleStream> ds = () -> DoubleStream.iterate(base, e -> increment).limit(count);
DoubleSummaryStatistics stats = ds.get().collect(DoubleSummaryStatistics::new,
DoubleSummaryStatistics::accept,
DoubleSummaryStatistics::combine);
failures += compareUlpDifference(expectedSum, stats.getSum(), 3);
failures += compareUlpDifference(expectedAvg, stats.getAverage(), 3);
failures += compareUlpDifference(expectedSum,
ds.get().sum(), 3);
failures += compareUlpDifference(expectedAvg,
ds.get().average().getAsDouble(), 3);
failures += compareUlpDifference(expectedSum,
ds.get().boxed().collect(Collectors.summingDouble(d -> d)), 3);
failures += compareUlpDifference(expectedAvg,
ds.get().boxed().collect(Collectors.averagingDouble(d -> d)),3);
return failures;
}
private static int testNonfiniteSum() {
int failures = 0;
Map<Supplier<DoubleStream>, Double> testCases = new LinkedHashMap<>();
testCases.put(() -> DoubleStream.of(MAX_VALUE, MAX_VALUE), POSITIVE_INFINITY);
testCases.put(() -> DoubleStream.of(-MAX_VALUE, -MAX_VALUE), NEGATIVE_INFINITY);
testCases.put(() -> DoubleStream.of(1.0d, POSITIVE_INFINITY, 1.0d), POSITIVE_INFINITY);
testCases.put(() -> DoubleStream.of(POSITIVE_INFINITY), POSITIVE_INFINITY);
testCases.put(() -> DoubleStream.of(POSITIVE_INFINITY, POSITIVE_INFINITY), POSITIVE_INFINITY);
testCases.put(() -> DoubleStream.of(POSITIVE_INFINITY, POSITIVE_INFINITY, 0.0), POSITIVE_INFINITY);
testCases.put(() -> DoubleStream.of(1.0d, NEGATIVE_INFINITY, 1.0d), NEGATIVE_INFINITY);
testCases.put(() -> DoubleStream.of(NEGATIVE_INFINITY), NEGATIVE_INFINITY);
testCases.put(() -> DoubleStream.of(NEGATIVE_INFINITY, NEGATIVE_INFINITY), NEGATIVE_INFINITY);
testCases.put(() -> DoubleStream.of(NEGATIVE_INFINITY, NEGATIVE_INFINITY, 0.0), NEGATIVE_INFINITY);
testCases.put(() -> DoubleStream.of(1.0d, NaN, 1.0d), NaN);
testCases.put(() -> DoubleStream.of(NaN), NaN);
testCases.put(() -> DoubleStream.of(1.0d, NEGATIVE_INFINITY, POSITIVE_INFINITY, 1.0d), NaN);
testCases.put(() -> DoubleStream.of(1.0d, POSITIVE_INFINITY, NEGATIVE_INFINITY, 1.0d), NaN);
testCases.put(() -> DoubleStream.of(POSITIVE_INFINITY, NaN), NaN);
testCases.put(() -> DoubleStream.of(NEGATIVE_INFINITY, NaN), NaN);
testCases.put(() -> DoubleStream.of(NaN, POSITIVE_INFINITY), NaN);
testCases.put(() -> DoubleStream.of(NaN, NEGATIVE_INFINITY), NaN);
for(Map.Entry<Supplier<DoubleStream>, Double> testCase : testCases.entrySet()) {
Supplier<DoubleStream> ds = testCase.getKey();
double expected = testCase.getValue();
DoubleSummaryStatistics stats = ds.get().collect(DoubleSummaryStatistics::new,
DoubleSummaryStatistics::accept,
DoubleSummaryStatistics::combine);
failures += compareUlpDifference(expected, stats.getSum(), 0);
failures += compareUlpDifference(expected, stats.getAverage(), 0);
failures += compareUlpDifference(expected, ds.get().sum(), 0);
failures += compareUlpDifference(expected, ds.get().average().getAsDouble(), 0);
failures += compareUlpDifference(expected, ds.get().boxed().collect(Collectors.summingDouble(d -> d)), 0);
failures += compareUlpDifference(expected, ds.get().boxed().collect(Collectors.averagingDouble(d -> d)), 0);
}
return failures;
}
/**
* Compute the ulp difference of two double values and compare against an error threshold.
*/
private static int compareUlpDifference(double expected, double computed, double threshold) {
if (!Double.isFinite(expected)) {
// Handle NaN and infinity cases
if (Double.compare(expected, computed) == 0)
return 0;
else {
System.err.printf("Unexpected sum, %g rather than %g.%n",
computed, expected);
return 1;
}
}
double ulpDifference = Math.abs(expected - computed) / Math.ulp(expected);
if (ulpDifference > threshold) {
System.err.printf("Numerical summation error too large, %g ulps rather than %g.%n",
ulpDifference, threshold);
return 1;
} else
return 0;
}
}
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