545 lines
18 KiB
C++
545 lines
18 KiB
C++
/*
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* Copyright Nick Thompson, 2017
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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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#define BOOST_TEST_MODULE naive_monte_carlo_test
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#define BOOST_NAIVE_MONTE_CARLO_DEBUG_FAILURES
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#include <cmath>
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#include <ostream>
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#include <boost/lexical_cast.hpp>
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#include <boost/type_index.hpp>
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#include <boost/test/included/unit_test.hpp>
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#include <boost/test/tools/floating_point_comparison.hpp>
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#include <boost/math/constants/constants.hpp>
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#include <boost/math/quadrature/naive_monte_carlo.hpp>
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using std::abs;
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using std::vector;
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using std::pair;
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using boost::math::constants::pi;
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using boost::math::quadrature::naive_monte_carlo;
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template<class Real>
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void test_pi_multithreaded()
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{
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std::cout << "Testing pi is calculated correctly (multithreaded) using Monte-Carlo on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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auto g = [](std::vector<Real> const & x)->Real {
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Real r = x[0]*x[0]+x[1]*x[1];
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if (r <= 1) {
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return 4;
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}
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return 0;
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};
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std::vector<std::pair<Real, Real>> bounds{{Real(0), Real(1)}, {Real(0), Real(1)}};
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Real error_goal = 0.0002;
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naive_monte_carlo<Real, decltype(g)> mc(g, bounds, error_goal,
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/*singular =*/ false,/* threads = */ 2, /* seed = */ 18012);
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auto task = mc.integrate();
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Real pi_estimated = task.get();
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if (abs(pi_estimated - pi<Real>())/pi<Real>() > 0.005) {
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std::cout << "Error in estimation of pi too high, function calls: " << mc.calls() << "\n";
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std::cout << "Final error estimate : " << mc.current_error_estimate() << "\n";
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std::cout << "Error goal : " << error_goal << "\n";
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BOOST_CHECK_CLOSE_FRACTION(pi_estimated, pi<Real>(), 0.005);
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}
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}
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template<class Real>
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void test_pi()
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{
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std::cout << "Testing pi is calculated correctly using Monte-Carlo on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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auto g = [](std::vector<Real> const & x)->Real
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{
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Real r = x[0]*x[0]+x[1]*x[1];
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if (r <= 1)
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{
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return 4;
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}
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return 0;
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};
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std::vector<std::pair<Real, Real>> bounds{{Real(0), Real(1)}, {Real(0), Real(1)}};
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Real error_goal = (Real) 0.0002;
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naive_monte_carlo<Real, decltype(g)> mc(g, bounds, error_goal,
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/*singular =*/ false,/* threads = */ 1, /* seed = */ 128402);
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auto task = mc.integrate();
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Real pi_estimated = task.get();
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if (abs(pi_estimated - pi<Real>())/pi<Real>() > 0.005)
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{
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std::cout << "Error in estimation of pi too high, function calls: " << mc.calls() << "\n";
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std::cout << "Final error estimate : " << mc.current_error_estimate() << "\n";
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std::cout << "Error goal : " << error_goal << "\n";
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BOOST_CHECK_CLOSE_FRACTION(pi_estimated, pi<Real>(), 0.005);
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}
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}
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template<class Real>
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void test_constant()
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{
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std::cout << "Testing constants are integrated correctly using Monte-Carlo on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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auto g = [](std::vector<Real> const &)->Real
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{
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return 1;
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};
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std::vector<std::pair<Real, Real>> bounds{{Real(0), Real(1)}, { Real(0), Real(1)}};
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naive_monte_carlo<Real, decltype(g)> mc(g, bounds, (Real) 0.0001,
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/* singular = */ false, /* threads = */ 1, /* seed = */ 87);
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auto task = mc.integrate();
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Real one = task.get();
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BOOST_CHECK_CLOSE_FRACTION(one, 1, 0.001);
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BOOST_CHECK_SMALL(mc.current_error_estimate(), std::numeric_limits<Real>::epsilon());
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BOOST_CHECK(mc.calls() > 1000);
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}
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template<class Real>
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void test_exception_from_integrand()
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{
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std::cout << "Testing that a reasonable action is performed by the Monte-Carlo integrator when the integrand throws an exception on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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auto g = [](std::vector<Real> const & x)->Real
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{
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if (x[0] > 0.5 && x[0] < 0.5001)
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{
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throw std::domain_error("You have done something wrong.\n");
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}
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return (Real) 1;
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};
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std::vector<std::pair<Real, Real>> bounds{{ Real(0), Real(1)}, { Real(0), Real(1)}};
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naive_monte_carlo<Real, decltype(g)> mc(g, bounds, (Real) 0.0001);
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auto task = mc.integrate();
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bool caught_exception = false;
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try
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{
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Real result = task.get();
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// Get rid of unused variable warning:
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std::ostream cnull(0);
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cnull << result;
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}
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catch(std::exception const &)
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{
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caught_exception = true;
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}
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BOOST_CHECK(caught_exception);
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}
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template<class Real>
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void test_cancel_and_restart()
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{
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std::cout << "Testing that cancellation and restarting works on naive Monte-Carlo integration on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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Real exact = boost::lexical_cast<Real>("1.3932039296856768591842462603255");
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BOOST_CONSTEXPR const Real A = 1.0 / (pi<Real>() * pi<Real>() * pi<Real>());
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auto g = [&](std::vector<Real> const & x)->Real
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{
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return A / (1.0 - cos(x[0])*cos(x[1])*cos(x[2]));
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};
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vector<pair<Real, Real>> bounds{{ Real(0), pi<Real>()}, { Real(0), pi<Real>()}, { Real(0), pi<Real>()}};
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naive_monte_carlo<Real, decltype(g)> mc(g, bounds, (Real) 0.05, true, 1, 888889);
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auto task = mc.integrate();
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mc.cancel();
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double y = task.get();
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// Super low tolerance; because it got canceled so fast:
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BOOST_CHECK_CLOSE_FRACTION(y, exact, 1.0);
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mc.update_target_error((Real) 0.01);
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task = mc.integrate();
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y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, exact, 0.1);
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}
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template<class Real>
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void test_finite_singular_boundary()
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{
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std::cout << "Testing that finite singular boundaries work on naive Monte-Carlo integration on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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using std::pow;
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using std::log;
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auto g = [](std::vector<Real> const & x)->Real
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{
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// The first term is singular at x = 0.
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// The second at x = 1:
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return pow(log(1.0/x[0]), 2) + log1p(-x[0]);
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};
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vector<pair<Real, Real>> bounds{{Real(0), Real(1)}};
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naive_monte_carlo<Real, decltype(g)> mc(g, bounds, (Real) 0.01, true, 1, 1922);
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auto task = mc.integrate();
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double y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, 1.0, 0.1);
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}
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template<class Real>
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void test_multithreaded_variance()
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{
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std::cout << "Testing that variance computed by naive Monte-Carlo integration converges to integral formula on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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Real exact_variance = (Real) 1/(Real) 12;
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auto g = [&](std::vector<Real> const & x)->Real
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{
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return x[0];
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};
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vector<pair<Real, Real>> bounds{{ Real(0), Real(1)}};
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naive_monte_carlo<Real, decltype(g)> mc(g, bounds, (Real) 0.001, false, 2, 12341);
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auto task = mc.integrate();
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Real y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, 0.5, 0.01);
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BOOST_CHECK_CLOSE_FRACTION(mc.variance(), exact_variance, 0.05);
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}
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template<class Real>
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void test_variance()
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{
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std::cout << "Testing that variance computed by naive Monte-Carlo integration converges to integral formula on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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Real exact_variance = (Real) 1/(Real) 12;
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auto g = [&](std::vector<Real> const & x)->Real
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{
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return x[0];
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};
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vector<pair<Real, Real>> bounds{{ Real(0), Real(1)}};
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naive_monte_carlo<Real, decltype(g)> mc(g, bounds, (Real) 0.001, false, 1, 12341);
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auto task = mc.integrate();
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Real y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, 0.5, 0.01);
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BOOST_CHECK_CLOSE_FRACTION(mc.variance(), exact_variance, 0.05);
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}
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template<class Real, uint64_t dimension>
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void test_product()
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{
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std::cout << "Testing that product functions are integrated correctly by naive Monte-Carlo on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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auto g = [&](std::vector<Real> const & x)->Real
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{
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double y = 1;
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for (uint64_t i = 0; i < x.size(); ++i)
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{
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y *= 2*x[i];
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}
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return y;
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};
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vector<pair<Real, Real>> bounds(dimension);
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for (uint64_t i = 0; i < dimension; ++i)
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{
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bounds[i] = std::make_pair<Real, Real>(0, 1);
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}
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naive_monte_carlo<Real, decltype(g)> mc(g, bounds, (Real) 0.001, false, 1, 13999);
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auto task = mc.integrate();
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Real y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, 1, 0.01);
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using std::pow;
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Real exact_variance = pow(4.0/3.0, dimension) - 1;
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BOOST_CHECK_CLOSE_FRACTION(mc.variance(), exact_variance, 0.1);
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}
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template<class Real, uint64_t dimension>
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void test_alternative_rng_1()
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{
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std::cout << "Testing that alternative RNGs work correctly using naive Monte-Carlo on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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auto g = [&](std::vector<Real> const & x)->Real
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{
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double y = 1;
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for (uint64_t i = 0; i < x.size(); ++i)
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{
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y *= 2*x[i];
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}
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return y;
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};
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vector<pair<Real, Real>> bounds(dimension);
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for (uint64_t i = 0; i < dimension; ++i)
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{
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bounds[i] = std::make_pair<Real, Real>(0, 1);
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}
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std::cout << "Testing std::mt19937" << std::endl;
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naive_monte_carlo<Real, decltype(g), std::mt19937> mc1(g, bounds, (Real) 0.001, false, 1, 1882);
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auto task = mc1.integrate();
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Real y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, 1, 0.01);
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using std::pow;
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Real exact_variance = pow(4.0/3.0, dimension) - 1;
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BOOST_CHECK_CLOSE_FRACTION(mc1.variance(), exact_variance, 0.05);
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std::cout << "Testing std::knuth_b" << std::endl;
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naive_monte_carlo<Real, decltype(g), std::knuth_b> mc2(g, bounds, (Real) 0.001, false, 1, 1883);
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task = mc2.integrate();
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y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, 1, 0.01);
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std::cout << "Testing std::ranlux48" << std::endl;
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naive_monte_carlo<Real, decltype(g), std::ranlux48> mc3(g, bounds, (Real) 0.001, false, 1, 1884);
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task = mc3.integrate();
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y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, 1, 0.01);
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}
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template<class Real, uint64_t dimension>
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void test_alternative_rng_2()
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{
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std::cout << "Testing that alternative RNGs work correctly using naive Monte-Carlo on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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auto g = [&](std::vector<Real> const & x)->Real
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{
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double y = 1;
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for (uint64_t i = 0; i < x.size(); ++i)
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{
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y *= 2*x[i];
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}
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return y;
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};
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vector<pair<Real, Real>> bounds(dimension);
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for (uint64_t i = 0; i < dimension; ++i)
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{
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bounds[i] = std::make_pair<Real, Real>(0, 1);
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}
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std::cout << "Testing std::default_random_engine" << std::endl;
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naive_monte_carlo<Real, decltype(g), std::default_random_engine> mc4(g, bounds, (Real) 0.001, false, 1, 1884);
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auto task = mc4.integrate();
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Real y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, 1, 0.01);
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std::cout << "Testing std::minstd_rand" << std::endl;
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naive_monte_carlo<Real, decltype(g), std::minstd_rand> mc5(g, bounds, (Real) 0.001, false, 1, 1887);
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task = mc5.integrate();
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y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, 1, 0.01);
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std::cout << "Testing std::minstd_rand0" << std::endl;
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naive_monte_carlo<Real, decltype(g), std::minstd_rand0> mc6(g, bounds, (Real) 0.001, false, 1, 1889);
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task = mc6.integrate();
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y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, 1, 0.01);
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}
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template<class Real>
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void test_upper_bound_infinite()
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{
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std::cout << "Testing that infinite upper bounds are integrated correctly by naive Monte-Carlo on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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auto g = [](std::vector<Real> const & x)->Real
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{
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return 1.0/(x[0]*x[0] + 1.0);
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};
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vector<pair<Real, Real>> bounds(1);
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for (uint64_t i = 0; i < bounds.size(); ++i)
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{
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bounds[i] = std::make_pair<Real, Real>(0, std::numeric_limits<Real>::infinity());
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}
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naive_monte_carlo<Real, decltype(g)> mc(g, bounds, (Real) 0.001, true, 1, 8765);
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auto task = mc.integrate();
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Real y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, boost::math::constants::half_pi<Real>(), 0.01);
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}
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template<class Real>
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void test_lower_bound_infinite()
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{
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std::cout << "Testing that infinite lower bounds are integrated correctly by naive Monte-Carlo on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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auto g = [](std::vector<Real> const & x)->Real
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{
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return 1.0/(x[0]*x[0] + 1.0);
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};
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vector<pair<Real, Real>> bounds(1);
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for (uint64_t i = 0; i < bounds.size(); ++i)
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{
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bounds[i] = std::make_pair<Real, Real>(-std::numeric_limits<Real>::infinity(), 0);
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}
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naive_monte_carlo<Real, decltype(g)> mc(g, bounds, (Real) 0.001, true, 1, 1208);
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auto task = mc.integrate();
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Real y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, boost::math::constants::half_pi<Real>(), 0.01);
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}
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template<class Real>
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void test_lower_bound_infinite2()
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{
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std::cout << "Testing that infinite lower bounds (2) are integrated correctly by naive Monte-Carlo on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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auto g = [](std::vector<Real> const & x)->Real
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{
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// If x[0] = inf, this should blow up:
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return (x[0]*x[0])/(x[0]*x[0]*x[0]*x[0] + 1.0);
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};
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vector<pair<Real, Real>> bounds(1);
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for (uint64_t i = 0; i < bounds.size(); ++i)
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{
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bounds[i] = std::make_pair<Real, Real>(-std::numeric_limits<Real>::infinity(), 0);
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}
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naive_monte_carlo<Real, decltype(g)> mc(g, bounds, (Real) 0.001, true, 1, 1208);
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auto task = mc.integrate();
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Real y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, boost::math::constants::half_pi<Real>()/boost::math::constants::root_two<Real>(), 0.01);
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}
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template<class Real>
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void test_double_infinite()
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{
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std::cout << "Testing that double infinite bounds are integrated correctly by naive Monte-Carlo on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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auto g = [](std::vector<Real> const & x)->Real
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{
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return 1.0/(x[0]*x[0] + 1.0);
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};
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vector<pair<Real, Real>> bounds(1);
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for (uint64_t i = 0; i < bounds.size(); ++i)
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{
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bounds[i] = std::make_pair<Real, Real>(-std::numeric_limits<Real>::infinity(), std::numeric_limits<Real>::infinity());
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}
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naive_monte_carlo<Real, decltype(g)> mc(g, bounds, (Real) 0.001, true, 1, 1776);
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auto task = mc.integrate();
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Real y = task.get();
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BOOST_CHECK_CLOSE_FRACTION(y, boost::math::constants::pi<Real>(), 0.01);
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}
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template<class Real, uint64_t dimension>
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void test_radovic()
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{
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// See: Generalized Halton Sequences in 2008: A Comparative Study, function g1:
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std::cout << "Testing that the Radovic function is integrated correctly by naive Monte-Carlo on type " << boost::typeindex::type_id<Real>().pretty_name() << "\n";
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auto g = [](std::vector<Real> const & x)->Real
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{
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using std::abs;
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Real alpha = (Real)0.01;
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Real z = 1;
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for (uint64_t i = 0; i < dimension; ++i)
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{
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z *= (abs(4*x[i]-2) + alpha)/(1+alpha);
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}
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return z;
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};
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vector<pair<Real, Real>> bounds(dimension);
|
|
for (uint64_t i = 0; i < bounds.size(); ++i)
|
|
{
|
|
bounds[i] = std::make_pair<Real, Real>(0, 1);
|
|
}
|
|
Real error_goal = (Real) 0.001;
|
|
naive_monte_carlo<Real, decltype(g)> mc(g, bounds, error_goal, false, 1, 1982);
|
|
|
|
auto task = mc.integrate();
|
|
Real y = task.get();
|
|
if (abs(y - 1) > 0.01)
|
|
{
|
|
std::cout << "Error in estimation of Radovic integral too high, function calls: " << mc.calls() << "\n";
|
|
std::cout << "Final error estimate: " << mc.current_error_estimate() << std::endl;
|
|
std::cout << "Error goal : " << error_goal << std::endl;
|
|
std::cout << "Variance estimate : " << mc.variance() << std::endl;
|
|
BOOST_CHECK_CLOSE_FRACTION(y, 1, 0.01);
|
|
}
|
|
}
|
|
|
|
|
|
BOOST_AUTO_TEST_CASE(naive_monte_carlo_test)
|
|
{
|
|
std::cout << "Default hardware concurrency = " << std::thread::hardware_concurrency() << std::endl;
|
|
#if !defined(TEST) || TEST == 1
|
|
test_finite_singular_boundary<double>();
|
|
test_finite_singular_boundary<float>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 2
|
|
test_pi<float>();
|
|
test_pi<double>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 3
|
|
test_pi_multithreaded<float>();
|
|
test_constant<float>();
|
|
#endif
|
|
//test_pi<long double>();
|
|
#if !defined(TEST) || TEST == 4
|
|
test_constant<double>();
|
|
//test_constant<long double>();
|
|
test_cancel_and_restart<float>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 5
|
|
test_exception_from_integrand<float>();
|
|
test_variance<float>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 6
|
|
test_variance<double>();
|
|
test_multithreaded_variance<double>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 7
|
|
test_product<float, 1>();
|
|
test_product<float, 2>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 8
|
|
test_product<float, 3>();
|
|
test_product<float, 4>();
|
|
test_product<float, 5>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 9
|
|
test_product<float, 6>();
|
|
test_product<double, 1>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 10
|
|
test_product<double, 2>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 11
|
|
test_product<double, 3>();
|
|
test_product<double, 4>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 12
|
|
test_upper_bound_infinite<float>();
|
|
test_upper_bound_infinite<double>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 13
|
|
test_lower_bound_infinite<float>();
|
|
test_lower_bound_infinite<double>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 14
|
|
test_lower_bound_infinite2<float>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 15
|
|
test_double_infinite<float>();
|
|
test_double_infinite<double>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 16
|
|
test_radovic<float, 1>();
|
|
test_radovic<float, 2>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 17
|
|
test_radovic<float, 3>();
|
|
test_radovic<double, 1>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 18
|
|
test_radovic<double, 2>();
|
|
test_radovic<double, 3>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 19
|
|
test_radovic<double, 4>();
|
|
test_radovic<double, 5>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 20
|
|
test_alternative_rng_1<float, 3>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 21
|
|
test_alternative_rng_1<double, 3>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 22
|
|
test_alternative_rng_2<float, 3>();
|
|
#endif
|
|
#if !defined(TEST) || TEST == 23
|
|
test_alternative_rng_2<double, 3>();
|
|
#endif
|
|
|
|
}
|