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123 lines
3.1 KiB
C++
123 lines
3.1 KiB
C++
// Copyright 2015-2016 Hans Dembinski
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//
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// Distributed under the Boost Software License, Version 1.0.
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// (See accompanying file LICENSE_1_0.txt
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// or copy at http://www.boost.org/LICENSE_1_0.txt)
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#include <boost/histogram/histogram.hpp>
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#include <boost/histogram/axis.hpp>
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#include <boost/random.hpp>
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#include <boost/array.hpp>
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#include <algorithm>
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#include <limits>
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#include <vector>
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#include <ctime>
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#include <cstdio>
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using namespace std;
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using namespace boost::histogram;
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template <typename D>
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struct rng {
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boost::random::mt19937 r;
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D d;
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rng(double a, double b) : d(a, b) {}
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double operator()() { return d(r); }
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};
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vector<double> random_array(unsigned n, int type) {
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using namespace boost::random;
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std::vector<double> result;
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switch (type) {
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case 0:
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std::generate_n(std::back_inserter(result), n, rng<uniform_real_distribution<> >(0.0, 1.0));
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break;
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case 1:
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std::generate_n(std::back_inserter(result), n, rng<normal_distribution<> >(0.0, 0.3));
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break;
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}
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return result;
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}
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void compare_1d(unsigned n, int distrib)
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{
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vector<double> r = random_array(n, distrib);
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double best_boost = std::numeric_limits<double>::max();
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for (unsigned k = 0; k < 10; ++k) {
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histogram h(regular_axis(100, 0, 1));
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t = clock();
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for (unsigned i = 0; i < n; ++i)
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h.fill(r[i]);
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t = clock() - t;
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best_boost = std::min(best_boost, double(t) / CLOCKS_PER_SEC);
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// printf("root %g this %g\n", hroot.GetSum(), h.sum());
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assert(hroot.GetSum() == h.sum());
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}
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printf("1D\n");
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printf("t[boost] = %.3f\n", best_boost);
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}
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void compare_3d(unsigned n, int distrib)
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{
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vector<double> r = random_array(3 * n, distrib);
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double best_boost = std::numeric_limits<double>::max();
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for (unsigned k = 0; k < 10; ++k) {
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histogram h(regular_axis(100, 0, 1),
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regular_axis(100, 0, 1),
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regular_axis(100, 0, 1));
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t = clock();
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for (unsigned i = 0; i < n; ++i)
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h.fill(r[3 * i], r[3 * i + 1], r[3 * i + 2]);
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t = clock() - t;
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best_boost = std::min(best_boost, double(t) / CLOCKS_PER_SEC);
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assert(hroot.GetSum() == h.sum());
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}
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printf("3D\n");
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printf("t[boost] = %.3f\n", best_boost);
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}
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void compare_6d(unsigned n, int distrib)
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{
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vector<double> r = random_array(6 * n, distrib);
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double best_boost = std::numeric_limits<double>::max();
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for (unsigned k = 0; k < 10; ++k) {
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double x[6];
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histogram h(regular_axis(10, 0, 1),
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regular_axis(10, 0, 1),
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regular_axis(10, 0, 1),
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regular_axis(10, 0, 1),
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regular_axis(10, 0, 1),
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regular_axis(10, 0, 1));
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t = clock();
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for (unsigned i = 0; i < n; ++i) {
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for (unsigned k = 0; k < 6; ++k)
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x[k] = r[6 * i + k];
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h.fill(x, x+6);
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}
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t = clock() - t;
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best_boost = std::min(best_boost, double(t) / CLOCKS_PER_SEC);
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}
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printf("6D\n");
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printf("t[boost] = %.3f\n", best_boost);
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}
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int main() {
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printf("uniform distribution\n");
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compare_1d(12000000, 0);
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compare_3d(4000000, 0);
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compare_6d(2000000, 0);
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printf("normal distribution\n");
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compare_1d(12000000, 1);
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compare_3d(4000000, 1);
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compare_6d(2000000, 1);
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}
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