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/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
/*
Copyright (C) 2004 StatPro Italia srl
Copyright (C) 2004 Walter Penschke
This file is part of QuantLib, a free-software/open-source library
for financial quantitative analysts and developers - http://quantlib.org/
QuantLib is free software: you can redistribute it and/or modify it
under the terms of the QuantLib license. You should have received a
copy of the license along with this program; if not, please email
<quantlib-dev@lists.sf.net>. The license is also available online at
<http://quantlib.org/license.shtml>.
This program 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 license for more details.
*/
#include "toplevelfixture.hpp"
#include "utilities.hpp"
#include <ql/math/randomnumbers/rngtraits.hpp>
#include <ql/math/randomnumbers/ranluxuniformrng.hpp>
#include <ql/math/comparison.hpp>
using namespace QuantLib;
using namespace boost::unit_test_framework;
BOOST_FIXTURE_TEST_SUITE(QuantLibTests, TopLevelFixture)
BOOST_AUTO_TEST_SUITE(RngTraitsTests)
BOOST_AUTO_TEST_CASE(testGaussian) {
BOOST_TEST_MESSAGE("Testing Gaussian pseudo-random number generation...");
PseudoRandom::rsg_type rsg =
PseudoRandom::make_sequence_generator(100, 1234);
const std::vector<Real>& values = rsg.nextSequence().value;
Real sum = 0.0;
for (Real value : values)
sum += value;
Real stored = 4.09916;
Real tolerance = 1.0e-5;
if (std::fabs(sum - stored) > tolerance)
BOOST_FAIL("the sum of the samples does not match the stored value\n"
<< " calculated: " << sum << "\n"
<< " expected: " << stored);
}
BOOST_AUTO_TEST_CASE(testDefaultPoisson) {
BOOST_TEST_MESSAGE("Testing Poisson pseudo-random number generation...");
PoissonPseudoRandom::icInstance =
ext::shared_ptr<InverseCumulativePoisson>();
PoissonPseudoRandom::rsg_type rsg =
PoissonPseudoRandom::make_sequence_generator(100, 1234);
const std::vector<Real>& values = rsg.nextSequence().value;
Real sum = 0.0;
for (Real value : values)
sum += value;
Real stored = 108.0;
if (!close(sum, stored))
BOOST_FAIL("the sum of the samples does not match the stored value\n"
<< " calculated: " << sum << "\n"
<< " expected: " << stored);
}
BOOST_AUTO_TEST_CASE(testCustomPoisson) {
BOOST_TEST_MESSAGE("Testing custom Poisson pseudo-random number generation...");
PoissonPseudoRandom::icInstance =
ext::make_shared<InverseCumulativePoisson>(
4.0);
PoissonPseudoRandom::rsg_type rsg =
PoissonPseudoRandom::make_sequence_generator(100, 1234);
const std::vector<Real>& values = rsg.nextSequence().value;
Real sum = 0.0;
for (Real value : values)
sum += value;
Real stored = 409.0;
if (!close(sum, stored))
BOOST_FAIL("the sum of the samples does not match the stored value\n"
<< " calculated: " << sum << "\n"
<< " expected: " << stored);
}
BOOST_AUTO_TEST_CASE(testRanLux) {
BOOST_TEST_MESSAGE("Testing known RanLux sequence...");
Ranlux3UniformRng ranlux3(2938723U);
Ranlux4UniformRng ranlux4(4390109U);
const Real ranlux3_expected[] = {
0.307448851544538826, 0.666313657894363587, 0.698528013702823358,
0.0217381272445322793,0.862964516238161394, 0.909193419106014034,
0.674484308686746914, 0.849607570377191479, 0.054626078713596371,
0.416474163715683687
};
const Real ranlux4_expected[] = {
0.222209169374078641, 0.420181950405986271, 0.0302156663005135329,
0.0836259809475237148,0.480549766594993599, 0.723472021829124401,
0.905819507194266293, 0.54072519936540786, 0.445908421479817463,
0.651084788437518824
};
for (Size i=0; i < 10010; ++i) {
ranlux3.next();
ranlux4.next();
}
for (Size i =0; i < 10; ++i) {
if (!close_enough(ranlux3.next().value, ranlux3_expected[i]))
BOOST_FAIL("failed to reproduce ranlux3 numbers...");
if (!close_enough(ranlux4.next().value, ranlux4_expected[i]))
BOOST_FAIL("failed to reproduce ranlux4 numbers...");
}
}
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()
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