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Library/boost/libs/histogram/examples/guide_custom_storage.cpp
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19 дек 2024, 19:11
19 дек 2024, 19:11
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// Copyright 2015-2018 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) //[ guide_custom_storage #include <algorithm> // std::for_each #include <array> #include <boost/histogram.hpp> #include <boost/histogram/algorithm/sum.hpp> #include <functional> // std::ref #include <unordered_map> #include <vector> int main() { using namespace boost::histogram; const auto axis = axis::regular<>(10, 0.0, 1.0); auto data = {0.1, 0.3, 0.2, 0.7}; // Create static histogram with vector<int> as counter storage, you can use // other arithmetic types as counters, e.g. double. auto h1 = make_histogram_with(std::vector<int>(), axis); std::for_each(data.begin(), data.end(), std::ref(h1)); assert(algorithm::sum(h1) == 4); // Create static histogram with array<int, N> as counter storage which is // allocated completely on the stack (this is very fast). N may be larger than // the actual number of bins used; an exception is raised if N is too small to // hold all bins. auto h2 = make_histogram_with(std::array<int, 12>(), axis); std::for_each(data.begin(), data.end(), std::ref(h2)); assert(algorithm::sum(h2) == 4); // Create static histogram with unordered_map as counter storage; this // generates a sparse histogram where only memory is allocated for bins that // are non-zero. This sounds like a good idea for high-dimensional histograms, // but maps come with a memory and run-time overhead. The default_storage // usually performs better in high dimensions. auto h3 = make_histogram_with(std::unordered_map<std::size_t, int>(), axis); std::for_each(data.begin(), data.end(), std::ref(h3)); assert(algorithm::sum(h3) == 4); } //]