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algorithm::sum gains coverage arg and improved documentation
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@ -9,6 +9,7 @@
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#include <boost/histogram/accumulators/sum.hpp>
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#include <boost/histogram/fwd.hpp>
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#include <boost/histogram/indexed.hpp>
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#include <boost/mp11/utility.hpp>
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#include <numeric>
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#include <type_traits>
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@ -16,24 +17,50 @@
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namespace boost {
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namespace histogram {
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namespace algorithm {
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/** Compute the sum over all histogram cells, including underflow/overflow bins.
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If the value type of the histogram is an integral or floating point type,
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boost::accumulators::sum<double> is used to compute the sum, else the original value
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type is used. Compilation fails, if the value type does not support operator+=.
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/** Compute the sum over all histogram cells (underflow/overflow included by default).
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Return type is double if the value type of the histogram is integral or floating point,
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and the original value type otherwise.
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*/
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The implementation favors accuracy and protection against overflow over speed. If the
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value type of the histogram is an integral or floating point type,
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accumulators::sum<double> is used to compute the sum, else the original value type is
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used. Compilation fails, if the value type does not support operator+=. The return type
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is double if the value type of the histogram is integral or floating point, and the
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original value type otherwise.
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If you need a different trade-off, you can write your own loop or use `std::accumulate`:
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```
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// iterate over all bins
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auto sum_all = std::accumulate(hist.begin(), hist.end(), 0.0);
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// skip underflow/overflow bins
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double sum = 0;
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for (auto&& x : indexed(hist))
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sum += *x; // dereference accessor
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// or:
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// auto ind = boost::histogram::indexed(hist);
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// auto sum = std::accumulate(ind.begin(), ind.end(), 0.0);
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```
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@returns accumulator type or double
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@param hist Const reference to the histogram.
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@param cov Iterate over all or only inner bins (optional, default: all).
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*/
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template <class A, class S>
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auto sum(const histogram<A, S>& h) {
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auto sum(const histogram<A, S>& hist, const coverage cov = coverage::all) {
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using T = typename histogram<A, S>::value_type;
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using Sum = mp11::mp_if<std::is_arithmetic<T>, accumulators::sum<double>, T>;
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Sum sum;
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for (auto&& x : h) sum += x;
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using sum_type = mp11::mp_if<std::is_arithmetic<T>, accumulators::sum<double>, T>;
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sum_type sum;
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if (cov == coverage::all)
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for (auto&& x : hist) sum += x;
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else
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// sum += x also works if sum_type::operator+=(const sum_type&) exists
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for (auto&& x : indexed(hist)) sum += *x;
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using R = mp11::mp_if<std::is_arithmetic<T>, double, T>;
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return static_cast<R>(sum);
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}
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} // namespace algorithm
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} // namespace histogram
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} // namespace boost
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@ -9,9 +9,9 @@
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#include <boost/histogram/accumulators/weighted_sum.hpp>
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#include <boost/histogram/algorithm/sum.hpp>
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#include <boost/histogram/axis/integer.hpp>
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#include "throw_exception.hpp"
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#include <unordered_map>
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#include <vector>
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#include "throw_exception.hpp"
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#include "utility_histogram.hpp"
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using namespace boost::histogram;
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@ -19,35 +19,56 @@ using boost::histogram::algorithm::sum;
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template <typename Tag>
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void run_tests() {
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auto ax = axis::integer<>(0, 100);
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auto ax = axis::integer<>(0, 10);
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auto h1 = make(Tag(), ax);
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for (unsigned i = 0; i < 100; ++i) h1(i);
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BOOST_TEST_EQ(sum(h1), 100);
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{
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auto h = make(Tag(), ax);
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std::fill(h.begin(), h.end(), 1);
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BOOST_TEST_EQ(sum(h), 12);
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BOOST_TEST_EQ(sum(h, coverage::inner), 10);
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}
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auto h2 = make_s(Tag(), std::vector<double>(), ax, ax);
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for (unsigned i = 0; i < 100; ++i)
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for (unsigned j = 0; j < 100; ++j) h2(i, j);
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BOOST_TEST_EQ(sum(h2), 10000);
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{
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auto h = make_s(Tag(), std::array<int, 12>(), ax);
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std::fill(h.begin(), h.end(), 1);
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BOOST_TEST_EQ(sum(h), 12);
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BOOST_TEST_EQ(sum(h, coverage::inner), 10);
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}
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auto h3 = make_s(Tag(), std::array<int, 102>(), ax);
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for (unsigned i = 0; i < 100; ++i) h3(i);
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BOOST_TEST_EQ(sum(h3), 100);
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{
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auto h = make_s(Tag(), std::unordered_map<std::size_t, int>(), ax);
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std::fill(h.begin(), h.end(), 1);
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BOOST_TEST_EQ(sum(h), 12);
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BOOST_TEST_EQ(sum(h, coverage::inner), 10);
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}
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auto h4 = make_s(Tag(), std::unordered_map<std::size_t, int>(), ax);
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for (unsigned i = 0; i < 100; ++i) h4(i);
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BOOST_TEST_EQ(sum(h4), 100);
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{
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auto h = make_s(Tag(), std::vector<double>(), ax, ax);
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std::fill(h.begin(), h.end(), 1);
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BOOST_TEST_EQ(sum(h), 12 * 12);
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BOOST_TEST_EQ(sum(h, coverage::inner), 10 * 10);
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}
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auto h5 =
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make_s(Tag(), std::vector<accumulators::weighted_sum<>>(), axis::integer<>(0, 1),
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axis::integer<int, axis::null_type, axis::option::none_t>(2, 4));
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h5(weight(2), 0, 2);
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h5(-1, 2);
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h5(1, 3);
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{
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using W = accumulators::weighted_sum<>;
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auto h = make_s(Tag(), std::vector<W>(), axis::integer<>(0, 2),
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axis::integer<int, axis::null_type, axis::option::none_t>(2, 4));
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W w(0, 2);
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for (auto&& x : h) {
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x = w;
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w = W(w.value() + 1, 2);
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}
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const auto v = algorithm::sum(h5);
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BOOST_TEST_EQ(v.value(), 4);
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BOOST_TEST_EQ(v.variance(), 6);
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// x-axis has 4 bins, y-axis has 2 = 8 bins total with 4 inner bins
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const auto v1 = algorithm::sum(h);
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BOOST_TEST_EQ(v1.value(), 0 + 1 + 2 + 3 + 4 + 5 + 6 + 7);
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BOOST_TEST_EQ(v1.variance(), 8 * 2);
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const auto v2 = algorithm::sum(h, coverage::inner);
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BOOST_TEST_EQ(v2.value(), 1 + 2 + 5 + 6);
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BOOST_TEST_EQ(v2.variance(), 4 * 2);
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}
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}
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int main() {
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