101 lines
4.0 KiB
C++
101 lines
4.0 KiB
C++
// (C) Copyright Eric Niebler 2005.
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// Use, modification and distribution are subject to the
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// Boost Software License, Version 1.0. (See accompanying file
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// LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
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// Test case for weighted_extended_p_square.hpp
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#include <iostream>
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#include <boost/random.hpp>
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#include <boost/test/unit_test.hpp>
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#include <boost/test/floating_point_comparison.hpp>
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#include <boost/accumulators/numeric/functional/vector.hpp>
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#include <boost/accumulators/numeric/functional/complex.hpp>
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#include <boost/accumulators/numeric/functional/valarray.hpp>
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#include <boost/accumulators/accumulators.hpp>
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#include <boost/accumulators/statistics/stats.hpp>
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#include <boost/accumulators/statistics/weighted_extended_p_square.hpp>
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using namespace boost;
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using namespace unit_test;
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using namespace boost::accumulators;
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///////////////////////////////////////////////////////////////////////////////
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// test_stat
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//
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void test_stat()
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{
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typedef accumulator_set<double, stats<tag::weighted_extended_p_square>, double> accumulator_t;
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// problem with small results: epsilon is relative (in percent), not absolute
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// tolerance in %
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double epsilon = 1;
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// some random number generators
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double mu1 = -1.0;
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double mu2 = 1.0;
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boost::lagged_fibonacci607 rng;
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boost::normal_distribution<> mean_sigma1(mu1, 1);
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boost::normal_distribution<> mean_sigma2(mu2, 1);
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boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal1(rng, mean_sigma1);
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boost::variate_generator<boost::lagged_fibonacci607&, boost::normal_distribution<> > normal2(rng, mean_sigma2);
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std::vector<double> probs_uniform, probs_normal1, probs_normal2, probs_normal_exact1, probs_normal_exact2;
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double p1[] = {/*0.001,*/ 0.01, 0.1, 0.5, 0.9, 0.99, 0.999};
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probs_uniform.assign(p1, p1 + sizeof(p1) / sizeof(double));
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double p2[] = {0.001, 0.025};
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double p3[] = {0.975, 0.999};
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probs_normal1.assign(p2, p2 + sizeof(p2) / sizeof(double));
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probs_normal2.assign(p3, p3 + sizeof(p3) / sizeof(double));
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double p4[] = {-3.090232, -1.959963};
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double p5[] = {1.959963, 3.090232};
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probs_normal_exact1.assign(p4, p4 + sizeof(p4) / sizeof(double));
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probs_normal_exact2.assign(p5, p5 + sizeof(p5) / sizeof(double));
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accumulator_t acc_uniform(extended_p_square_probabilities = probs_uniform);
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accumulator_t acc_normal1(extended_p_square_probabilities = probs_normal1);
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accumulator_t acc_normal2(extended_p_square_probabilities = probs_normal2);
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for (std::size_t i = 0; i < 100000; ++i)
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{
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acc_uniform(rng(), weight = 1.);
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double sample1 = normal1();
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double sample2 = normal2();
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acc_normal1(sample1, weight = std::exp(-mu1 * (sample1 - 0.5 * mu1)));
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acc_normal2(sample2, weight = std::exp(-mu2 * (sample2 - 0.5 * mu2)));
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}
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// check for uniform distribution
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BOOST_CHECK_CLOSE(weighted_extended_p_square(acc_uniform)[0], probs_uniform[0], 6*epsilon);
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BOOST_CHECK_CLOSE(weighted_extended_p_square(acc_uniform)[1], probs_uniform[1], 3*epsilon);
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BOOST_CHECK_CLOSE(weighted_extended_p_square(acc_uniform)[2], probs_uniform[2], epsilon);
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BOOST_CHECK_CLOSE(weighted_extended_p_square(acc_uniform)[3], probs_uniform[3], epsilon);
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BOOST_CHECK_CLOSE(weighted_extended_p_square(acc_uniform)[4], probs_uniform[4], epsilon);
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BOOST_CHECK_CLOSE(weighted_extended_p_square(acc_uniform)[5], probs_uniform[5], epsilon);
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// check for standard normal distribution
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for (std::size_t i = 0; i < probs_normal1.size(); ++i)
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{
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BOOST_CHECK_CLOSE(weighted_extended_p_square(acc_normal1)[i], probs_normal_exact1[i], epsilon);
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BOOST_CHECK_CLOSE(weighted_extended_p_square(acc_normal2)[i], probs_normal_exact2[i], epsilon);
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}
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}
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///////////////////////////////////////////////////////////////////////////////
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// init_unit_test_suite
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//
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test_suite* init_unit_test_suite( int argc, char* argv[] )
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{
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test_suite *test = BOOST_TEST_SUITE("weighted_extended_p_square test");
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test->add(BOOST_TEST_CASE(&test_stat));
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return test;
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}
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