algorithm::sum gains coverage arg and improved documentation

This commit is contained in:
Hans Dembinski 2020-01-03 11:07:21 +01:00 committed by GitHub
parent 87e757f9e1
commit 270f6a1afb
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 83 additions and 35 deletions

View File

@ -9,6 +9,7 @@
#include <boost/histogram/accumulators/sum.hpp>
#include <boost/histogram/fwd.hpp>
#include <boost/histogram/indexed.hpp>
#include <boost/mp11/utility.hpp>
#include <numeric>
#include <type_traits>
@ -16,24 +17,50 @@
namespace boost {
namespace histogram {
namespace algorithm {
/** Compute the sum over all histogram cells, including underflow/overflow bins.
If the value type of the histogram is an integral or floating point type,
boost::accumulators::sum<double> is used to compute the sum, else the original value
type is used. Compilation fails, if the value type does not support operator+=.
/** Compute the sum over all histogram cells (underflow/overflow included by default).
Return type is double if the value type of the histogram is integral or floating point,
and the original value type otherwise.
*/
The implementation favors accuracy and protection against overflow over speed. If the
value type of the histogram is an integral or floating point type,
accumulators::sum<double> is used to compute the sum, else the original value type is
used. Compilation fails, if the value type does not support operator+=. The return type
is double if the value type of the histogram is integral or floating point, and the
original value type otherwise.
If you need a different trade-off, you can write your own loop or use `std::accumulate`:
```
// iterate over all bins
auto sum_all = std::accumulate(hist.begin(), hist.end(), 0.0);
// skip underflow/overflow bins
double sum = 0;
for (auto&& x : indexed(hist))
sum += *x; // dereference accessor
// or:
// auto ind = boost::histogram::indexed(hist);
// auto sum = std::accumulate(ind.begin(), ind.end(), 0.0);
```
@returns accumulator type or double
@param hist Const reference to the histogram.
@param cov Iterate over all or only inner bins (optional, default: all).
*/
template <class A, class S>
auto sum(const histogram<A, S>& h) {
auto sum(const histogram<A, S>& hist, const coverage cov = coverage::all) {
using T = typename histogram<A, S>::value_type;
using Sum = mp11::mp_if<std::is_arithmetic<T>, accumulators::sum<double>, T>;
Sum sum;
for (auto&& x : h) sum += x;
using sum_type = mp11::mp_if<std::is_arithmetic<T>, accumulators::sum<double>, T>;
sum_type sum;
if (cov == coverage::all)
for (auto&& x : hist) sum += x;
else
// sum += x also works if sum_type::operator+=(const sum_type&) exists
for (auto&& x : indexed(hist)) sum += *x;
using R = mp11::mp_if<std::is_arithmetic<T>, double, T>;
return static_cast<R>(sum);
}
} // namespace algorithm
} // namespace histogram
} // namespace boost

View File

@ -9,9 +9,9 @@
#include <boost/histogram/accumulators/weighted_sum.hpp>
#include <boost/histogram/algorithm/sum.hpp>
#include <boost/histogram/axis/integer.hpp>
#include "throw_exception.hpp"
#include <unordered_map>
#include <vector>
#include "throw_exception.hpp"
#include "utility_histogram.hpp"
using namespace boost::histogram;
@ -19,35 +19,56 @@ using boost::histogram::algorithm::sum;
template <typename Tag>
void run_tests() {
auto ax = axis::integer<>(0, 100);
auto ax = axis::integer<>(0, 10);
auto h1 = make(Tag(), ax);
for (unsigned i = 0; i < 100; ++i) h1(i);
BOOST_TEST_EQ(sum(h1), 100);
{
auto h = make(Tag(), ax);
std::fill(h.begin(), h.end(), 1);
BOOST_TEST_EQ(sum(h), 12);
BOOST_TEST_EQ(sum(h, coverage::inner), 10);
}
auto h2 = make_s(Tag(), std::vector<double>(), ax, ax);
for (unsigned i = 0; i < 100; ++i)
for (unsigned j = 0; j < 100; ++j) h2(i, j);
BOOST_TEST_EQ(sum(h2), 10000);
{
auto h = make_s(Tag(), std::array<int, 12>(), ax);
std::fill(h.begin(), h.end(), 1);
BOOST_TEST_EQ(sum(h), 12);
BOOST_TEST_EQ(sum(h, coverage::inner), 10);
}
auto h3 = make_s(Tag(), std::array<int, 102>(), ax);
for (unsigned i = 0; i < 100; ++i) h3(i);
BOOST_TEST_EQ(sum(h3), 100);
{
auto h = make_s(Tag(), std::unordered_map<std::size_t, int>(), ax);
std::fill(h.begin(), h.end(), 1);
BOOST_TEST_EQ(sum(h), 12);
BOOST_TEST_EQ(sum(h, coverage::inner), 10);
}
auto h4 = make_s(Tag(), std::unordered_map<std::size_t, int>(), ax);
for (unsigned i = 0; i < 100; ++i) h4(i);
BOOST_TEST_EQ(sum(h4), 100);
{
auto h = make_s(Tag(), std::vector<double>(), ax, ax);
std::fill(h.begin(), h.end(), 1);
BOOST_TEST_EQ(sum(h), 12 * 12);
BOOST_TEST_EQ(sum(h, coverage::inner), 10 * 10);
}
auto h5 =
make_s(Tag(), std::vector<accumulators::weighted_sum<>>(), axis::integer<>(0, 1),
axis::integer<int, axis::null_type, axis::option::none_t>(2, 4));
h5(weight(2), 0, 2);
h5(-1, 2);
h5(1, 3);
{
using W = accumulators::weighted_sum<>;
auto h = make_s(Tag(), std::vector<W>(), axis::integer<>(0, 2),
axis::integer<int, axis::null_type, axis::option::none_t>(2, 4));
W w(0, 2);
for (auto&& x : h) {
x = w;
w = W(w.value() + 1, 2);
}
const auto v = algorithm::sum(h5);
BOOST_TEST_EQ(v.value(), 4);
BOOST_TEST_EQ(v.variance(), 6);
// x-axis has 4 bins, y-axis has 2 = 8 bins total with 4 inner bins
const auto v1 = algorithm::sum(h);
BOOST_TEST_EQ(v1.value(), 0 + 1 + 2 + 3 + 4 + 5 + 6 + 7);
BOOST_TEST_EQ(v1.variance(), 8 * 2);
const auto v2 = algorithm::sum(h, coverage::inner);
BOOST_TEST_EQ(v2.value(), 1 + 2 + 5 + 6);
BOOST_TEST_EQ(v2.variance(), 4 * 2);
}
}
int main() {