/* * Copyright (c) 2003, 2022, 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.
*/
/* * @test * @library /test/lib * @build jdk.test.lib.RandomFactory * @run main Log1pTests * @bug 4851638 4939441 8078672 * @summary Tests for {Math, StrictMath}.log1p (use -Dseed=X to set PRNG seed) * @key randomness
*/
/** * Formulation taken from HP-15C Advanced Functions Handbook, part * number HP 0015-90011, p 181. This is accurate to a few ulps.
*/ staticdouble hp15cLogp(double x) { double u = 1.0 + x; return (u==1.0? x : StrictMath.log(u)*x/(u-1) );
}
/* * The Taylor expansion of ln(1 + x) for -1 < x <= 1 is: * * x - x^2/2 + x^3/3 - ... -(-x^j)/j * * Therefore, for small values of x, log1p(x) ~= x. For large * values of x, log1p(x) ~= log(x). * * Also x/(x+1) < ln(1+x) < x
*/
// Test special cases for(int i = 0; i < testCases.length; i++) {
failures += testLog1pCaseWithUlpDiff(testCases[i][0],
testCases[i][1], 0);
}
// For |x| < 2^-54 log1p(x) ~= x for(int i = DoubleConsts.MIN_SUB_EXPONENT; i <= -54; i++) { double d = Math.scalb(2, i);
failures += testLog1pCase(d, d);
failures += testLog1pCase(-d, -d);
}
// For x > 2^53 log1p(x) ~= log(x) for(int i = 53; i <= Double.MAX_EXPONENT; i++) { double d = Math.scalb(2, i);
failures += testLog1pCaseWithUlpDiff(d, StrictMath.log(d), 2.001);
}
// Construct random values with exponents ranging from -53 to // 52 and compare against HP-15C formula.
java.util.Random rand = RandomFactory.getRandom(); for(int i = 0; i < 1000; i++) { double d = rand.nextDouble();
// Test for monotonicity failures near values y-1 where y ~= // e^x. Test two numbers before and two numbers after each // chosen value; i.e. // // pcNeighbors[] = // {nextDown(nextDown(pc)), // nextDown(pc), // pc, // nextUp(pc), // nextUp(nextUp(pc))} // // and we test that log1p(pcNeighbors[i]) <= log1p(pcNeighbors[i+1])
{ double pcNeighbors[] = newdouble[5]; double pcNeighborsLog1p[] = newdouble[5]; double pcNeighborsStrictLog1p[] = newdouble[5];
for(int i = -36; i <= 36; i++) { double pc = StrictMath.pow(Math.E, i) - 1;
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