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* Travis uses b2 and codecov now * replacing boost::multiprecision with custom implementation to avoid the dependency * improved axis implementation: `update` is now a normal method * introduced use_default tag type to set defaults * whitespace fixes and doc update
88 lines
3.3 KiB
C++
88 lines
3.3 KiB
C++
// Copyright 2018 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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//[ guide_custom_accumulators
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#include <array>
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#include <boost/format.hpp>
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#include <boost/histogram.hpp>
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#include <boost/histogram/accumulators/mean.hpp>
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#include <iostream>
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int main() {
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using namespace boost::histogram;
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const auto axis = axis::regular<>(3, 0.0, 1.0);
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// Create a 1D-profile, which computes the mean of samples in each bin. The
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// factory function `make_profile` is provided by the library as a shorthand.
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auto h1 = make_histogram_with(dense_storage<accumulators::mean<>>(), axis);
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// Argument of `sample` is passed to accumulator.
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h1(0.0, sample(2)); // sample 2 goes to first bin
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h1(0.1, sample(2)); // sample 2 goes to first bin
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h1(0.4, sample(3)); // sample 3 goes to second bin
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h1(0.5, sample(4)); // sample 4 goes to second bin
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std::ostringstream os1;
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for (auto x : indexed(h1)) {
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// Accumulators usually have methods to access their state. Use the arrow
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// operator to access them. Here, `count()` gives the number of samples,
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// `value()` the mean, and `variance()` the variance estimate of the mean.
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os1 << boost::format("%i count %i mean %.1f variance %.1f\n") % x.index() %
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x->count() % x->value() % x->variance();
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}
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std::cout << os1.str() << std::flush;
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assert(os1.str() == "0 count 2 mean 2.0 variance 0.0\n"
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"1 count 2 mean 3.5 variance 0.5\n"
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"2 count 0 mean 0.0 variance 0.0\n");
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// Let's make a custom accumulator. It must have a call operator that accepts
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// the argument of the `sample` function. Any return value of the call
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// operator is ignored.
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struct max {
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void operator()(double x) {
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if (x > value) value = x;
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}
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double value = 0;
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};
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// Create a histogram with the custom accumulator, initialize the accumulators
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// to 1.
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auto h2 = make_histogram_with(dense_storage<max>(), axis);
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h2(0.0, sample(2)); // sample 2 goes to first bin
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h2(0.1, sample(2.5)); // sample 2.5 goes to first bin
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h2(0.4, sample(3)); // sample 3 goes to second bin
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h2(0.5, sample(4)); // sample 4 goes to second bin
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std::ostringstream os2;
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for (auto x : indexed(h2)) {
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os2 << boost::format("%i value %.1f\n") % x.index() % x->value;
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}
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std::cout << os2.str() << std::flush;
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assert(os2.str() == "0 value 2.5\n"
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"1 value 4.0\n"
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"2 value 0.0\n");
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// // Let's go meta and use the histogram itself as an accumulator, just for
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// fun. auto h_nested = make_histogram(axis); auto h2 =
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// make_histogram_with(dense_storage<decltype(h_nested)>(h_nested), axis);
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// h2(0.0, sample(2)); // sample 2 goes to first bin
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// h2(0.1, sample(2.5)); // sample 2.5 goes to first bin
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// h2(0.4, sample(3)); // sample 3 goes to second bin
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// h2(0.5, sample(4)); // sample 4 goes to second bin
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//
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// std::ostringstream os2;
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// for (auto x : indexed(h2)) {
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// os2 << boost::format("%i value %.1f\n") % x.index() % x->value;
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// }
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// std::cout << os2.str() << std::flush;
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// assert(os2.str() == "0 value 2.5\n"
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// "1 value 4.0\n"
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// "2 value 0.0\n");
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}
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//]
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