// Copyright 2015-2016 Hans Dembinski // // Distributed under the Boost Software License, Version 1.0. // (See accompanying file LICENSE_1_0.txt // or copy at http://www.boost.org/LICENSE_1_0.txt) #include #include #include #include #include #include #include #include #include #include #include using namespace boost::histogram; namespace mpl = boost::mpl; std::vector random_array(unsigned n, int type) { std::vector result(n); std::default_random_engine gen(1); if (type) { // type == 1 std::normal_distribution<> d(0.5, 0.3); for (auto& x : result) x = d(gen); } else { // type == 0 std::uniform_real_distribution<> d(0.0, 1.0); for (auto& x: result) x = d(gen); } return result; } template double compare_1d(unsigned n, int distrib) { auto r = random_array(n, distrib); auto best = std::numeric_limits::max(); for (unsigned k = 0; k < 10; ++k) { auto h = Histogram(regular_axis(100, 0, 1)); auto t = clock(); for (unsigned i = 0; i < n; ++i) h.increment(r[i]); t = clock() - t; best = std::min(best, double(t) / CLOCKS_PER_SEC); } return best; } template double compare_3d(unsigned n, int distrib) { auto r = random_array(3 * n, distrib); auto best = std::numeric_limits::max(); for (unsigned k = 0; k < 10; ++k) { auto h = Histogram(regular_axis(100, 0, 1), regular_axis(100, 0, 1), regular_axis(100, 0, 1)); auto t = clock(); for (unsigned i = 0; i < n; ++i) h.increment(r[3 * i], r[3 * i + 1], r[3 * i + 2]); t = clock() - t; best = std::min(best, double(t) / CLOCKS_PER_SEC); } return best; } template double compare_6d(unsigned n, int distrib) { auto r = random_array(6 * n, distrib); auto best = std::numeric_limits::max(); for (unsigned k = 0; k < 10; ++k) { double x[6]; auto h = Histogram(regular_axis(10, 0, 1), regular_axis(10, 0, 1), regular_axis(10, 0, 1), regular_axis(10, 0, 1), regular_axis(10, 0, 1), regular_axis(10, 0, 1)); auto t = clock(); for (unsigned i = 0; i < n; ++i) { for (unsigned k = 0; k < 6; ++k) x[k] = r[6 * i + k]; h.increment(x[0], x[1], x[2], x[3], x[4], x[5]); } t = clock() - t; best = std::min(best, double(t) / CLOCKS_PER_SEC); } return best; } int main() { for (int itype = 0; itype < 2; ++itype) { if (itype == 0) printf("uniform distribution\n"); else printf("normal distribution\n"); printf("1D\n"); printf("t[boost] = %.3f\n", #if HISTOGRAM_TYPE == 1 compare_1d< static_histogram< mpl::vector, container_storage> > >(12000000, itype) #elif HISTOGRAM_TYPE == 2 compare_1d< static_histogram< mpl::vector, adaptive_storage > >(12000000, itype) #elif HISTOGRAM_TYPE == 3 compare_1d< dynamic_histogram< default_axes, container_storage> > >(12000000, itype) #elif HISTOGRAM_TYPE == 4 compare_1d< dynamic_histogram< default_axes, adaptive_storage > >(12000000, itype) #endif ); printf("3D\n"); printf("t[boost] = %.3f\n", #if HISTOGRAM_TYPE == 1 compare_3d< static_histogram< mpl::vector, container_storage> > >(4000000, itype) #elif HISTOGRAM_TYPE == 2 compare_3d< static_histogram< mpl::vector, adaptive_storage > >(4000000, itype) #elif HISTOGRAM_TYPE == 3 compare_3d< dynamic_histogram< default_axes, container_storage> > >(4000000, itype) #elif HISTOGRAM_TYPE == 4 compare_3d< dynamic_histogram< default_axes, adaptive_storage > >(4000000, itype) #endif ); printf("6D\n"); printf("t[boost] = %.3f\n", #if HISTOGRAM_TYPE == 1 compare_6d< static_histogram< mpl::vector, container_storage> > >(2000000, itype) #elif HISTOGRAM_TYPE == 2 compare_6d< static_histogram< mpl::vector, adaptive_storage > >(2000000, itype) #elif HISTOGRAM_TYPE == 3 compare_6d< dynamic_histogram< default_axes, container_storage> > >(2000000, itype) #elif HISTOGRAM_TYPE == 4 compare_6d< dynamic_histogram< default_axes, adaptive_storage > >(2000000, itype) #endif ); } }