dfce4e1943
Reviewed-by: bpb
197 lines
7.0 KiB
Java
197 lines
7.0 KiB
Java
/*
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* Copyright (c) 2003, 2023, 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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/*
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* @test
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* @library /test/lib
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* @build jdk.test.lib.RandomFactory
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* @build Tests
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* @build Log1pTests
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* @run main Log1pTests
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* @bug 4851638 4939441 8078672
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* @summary Tests for {Math, StrictMath}.log1p (use -Dseed=X to set PRNG seed)
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* @key randomness
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*/
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import jdk.test.lib.RandomFactory;
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public class Log1pTests {
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private Log1pTests(){}
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static final double infinityD = Double.POSITIVE_INFINITY;
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static final double NaNd = Double.NaN;
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/**
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* Formulation taken from HP-15C Advanced Functions Handbook, part
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* number HP 0015-90011, p 181. This is accurate to a few ulps.
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*/
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static double hp15cLogp(double x) {
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double u = 1.0 + x;
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return (u==1.0? x : StrictMath.log(u)*x/(u-1) );
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}
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/*
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* The Taylor expansion of ln(1 + x) for -1 < x <= 1 is:
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*
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* x - x^2/2 + x^3/3 - ... -(-x^j)/j
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*
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* Therefore, for small values of x, log1p(x) ~= x. For large
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* values of x, log1p(x) ~= log(x).
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*
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* Also x/(x+1) < ln(1+x) < x
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*/
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private static int testLog1p() {
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int failures = 0;
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for(double nan : Tests.NaNs) {
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failures += testLog1pCase(nan, NaNd);
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}
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double [][] testCases = {
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{Double.NEGATIVE_INFINITY, NaNd},
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{-8.0, NaNd},
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{-1.0, -infinityD},
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{-0.0, -0.0},
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{+0.0, +0.0},
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{infinityD, infinityD},
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};
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// Test special cases
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for(int i = 0; i < testCases.length; i++) {
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failures += testLog1pCaseWithUlpDiff(testCases[i][0],
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testCases[i][1], 0);
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}
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// For |x| < 2^-54 log1p(x) ~= x
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for(int i = DoubleConsts.MIN_SUB_EXPONENT; i <= -54; i++) {
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double d = Math.scalb(2, i);
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failures += testLog1pCase(d, d);
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failures += testLog1pCase(-d, -d);
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}
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// For x > 2^53 log1p(x) ~= log(x)
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for(int i = 53; i <= Double.MAX_EXPONENT; i++) {
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double d = Math.scalb(2, i);
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failures += testLog1pCaseWithUlpDiff(d, StrictMath.log(d), 2.001);
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}
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// Construct random values with exponents ranging from -53 to
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// 52 and compare against HP-15C formula.
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java.util.Random rand = RandomFactory.getRandom();
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for(int i = 0; i < 1000; i++) {
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double d = rand.nextDouble();
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d = Math.scalb(d, -53 - Tests.ilogb(d));
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for(int j = -53; j <= 52; j++) {
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failures += testLog1pCaseWithUlpDiff(d, hp15cLogp(d), 5);
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d *= 2.0; // increase exponent by 1
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}
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}
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// Test for monotonicity failures near values y-1 where y ~=
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// e^x. Test two numbers before and two numbers after each
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// chosen value; i.e.
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//
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// pcNeighbors[] =
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// {nextDown(nextDown(pc)),
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// nextDown(pc),
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// pc,
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// nextUp(pc),
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// nextUp(nextUp(pc))}
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//
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// and we test that log1p(pcNeighbors[i]) <= log1p(pcNeighbors[i+1])
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{
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double pcNeighbors[] = new double[5];
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double pcNeighborsLog1p[] = new double[5];
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double pcNeighborsStrictLog1p[] = new double[5];
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for(int i = -36; i <= 36; i++) {
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double pc = StrictMath.pow(Math.E, i) - 1;
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pcNeighbors[2] = pc;
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pcNeighbors[1] = Math.nextDown(pc);
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pcNeighbors[0] = Math.nextDown(pcNeighbors[1]);
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pcNeighbors[3] = Math.nextUp(pc);
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pcNeighbors[4] = Math.nextUp(pcNeighbors[3]);
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for(int j = 0; j < pcNeighbors.length; j++) {
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pcNeighborsLog1p[j] = Math.log1p(pcNeighbors[j]);
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pcNeighborsStrictLog1p[j] = StrictMath.log1p(pcNeighbors[j]);
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}
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for(int j = 0; j < pcNeighborsLog1p.length-1; j++) {
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if(pcNeighborsLog1p[j] > pcNeighborsLog1p[j+1] ) {
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failures++;
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System.err.println("Monotonicity failure for Math.log1p on " +
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pcNeighbors[j] + " and " +
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pcNeighbors[j+1] + "\n\treturned " +
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pcNeighborsLog1p[j] + " and " +
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pcNeighborsLog1p[j+1] );
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}
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if(pcNeighborsStrictLog1p[j] > pcNeighborsStrictLog1p[j+1] ) {
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failures++;
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System.err.println("Monotonicity failure for StrictMath.log1p on " +
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pcNeighbors[j] + " and " +
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pcNeighbors[j+1] + "\n\treturned " +
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pcNeighborsStrictLog1p[j] + " and " +
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pcNeighborsStrictLog1p[j+1] );
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}
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}
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}
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}
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return failures;
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}
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public static int testLog1pCase(double input,
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double expected) {
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return testLog1pCaseWithUlpDiff(input, expected, 1);
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}
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public static int testLog1pCaseWithUlpDiff(double input,
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double expected,
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double ulps) {
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int failures = 0;
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failures += Tests.testUlpDiff("Math.lop1p", input, Math::log1p, expected, ulps);
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failures += Tests.testUlpDiff("StrictMath.log1p", input, StrictMath::log1p, expected, ulps);
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return failures;
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}
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public static void main(String... argv) {
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int failures = 0;
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failures += testLog1p();
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if (failures > 0) {
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System.err.println("Testing log1p incurred "
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+ failures + " failures.");
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throw new RuntimeException();
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}
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}
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}
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