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61 lines
2.4 KiB
C++
61 lines
2.4 KiB
C++
// Copyright John Maddock 2024.
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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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//
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// The purpose of this test case is to probe the skew normal quantiles
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// for extreme values of skewness and ensure that our root finders don't
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// blow up, see https://github.com/boostorg/math/issues/1120 for original
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// test case. We test both the maximum number of iterations taken, and the
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// overall total (ie average). Any changes to the skew normal should
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// ideally NOT cause this test to fail, as this indicates that our root
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// finding has been made worse by the change!!
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//
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// Note that defining BOOST_MATH_INSTRUMENT_SKEW_NORMAL_ITERATIONS
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// causes the skew normal quantile to save the number of iterations
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// to a global variable "global_iter_count".
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//
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#define BOOST_MATH_INSTRUMENT_SKEW_NORMAL_ITERATIONS
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#include <random>
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#include <boost/math/distributions/skew_normal.hpp>
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#include "math_unit_test.hpp"
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std::uintmax_t global_iter_count;
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std::uintmax_t total_iter_count = 0;
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int main()
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{
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using scipy_policy = boost::math::policies::policy<boost::math::policies::promote_double<false>>;
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std::mt19937 gen;
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std::uniform_real_distribution<double> location(-3, 3);
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std::uniform_real_distribution<double> scale(0.001, 3);
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for (unsigned skew = 50; skew < 2000; skew += 43)
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{
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constexpr double pn[] = { 0.0001, 0.001, 0.01, 0.1, 0.2, 0.3, 0.4 };
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boost::math::skew_normal_distribution<double, scipy_policy> dist(location(gen), scale(gen), skew);
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for (unsigned i = 0; i < 7; ++i)
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{
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global_iter_count = 0;
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double x = quantile(dist, pn[i]);
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total_iter_count += global_iter_count;
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CHECK_LE(global_iter_count, static_cast<std::uintmax_t>(60));
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double p = cdf(dist, x);
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CHECK_ABSOLUTE_ERROR(p, pn[i], 45 * std::numeric_limits<double>::epsilon());
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global_iter_count = 0;
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x = quantile(complement(dist, pn[i]));
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total_iter_count += global_iter_count;
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CHECK_LE(global_iter_count, static_cast<std::uintmax_t>(60));
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p = cdf(complement(dist, x));
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CHECK_ABSOLUTE_ERROR(p, pn[i], 45 * std::numeric_limits<double>::epsilon());
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}
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}
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CHECK_LE(total_iter_count, static_cast<std::uintmax_t>(10000));
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return boost::math::test::report_errors();
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}
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