Added boost header
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Christophe Riccio
221
test/external/boost/accumulators/statistics/weighted_density.hpp
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221
test/external/boost/accumulators/statistics/weighted_density.hpp
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///////////////////////////////////////////////////////////////////////////////
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// weighted_density.hpp
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//
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// Copyright 2006 Daniel Egloff, Olivier Gygi. Distributed under the Boost
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// Software License, Version 1.0. (See accompanying file
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// LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
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#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_DENSITY_HPP_DE_01_01_2006
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#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_DENSITY_HPP_DE_01_01_2006
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#include <vector>
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#include <limits>
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#include <functional>
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#include <boost/range.hpp>
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#include <boost/parameter/keyword.hpp>
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#include <boost/mpl/placeholders.hpp>
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#include <boost/accumulators/framework/accumulator_base.hpp>
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#include <boost/accumulators/framework/extractor.hpp>
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#include <boost/accumulators/numeric/functional.hpp>
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#include <boost/accumulators/framework/parameters/sample.hpp>
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#include <boost/accumulators/statistics_fwd.hpp>
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#include <boost/accumulators/statistics/sum.hpp>
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#include <boost/accumulators/statistics/max.hpp>
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#include <boost/accumulators/statistics/min.hpp>
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#include <boost/accumulators/statistics/density.hpp> // for named parameters density_cache_size and density_num_bins
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namespace boost { namespace accumulators
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{
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namespace impl
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{
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///////////////////////////////////////////////////////////////////////////////
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// weighted_density_impl
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// density histogram for weighted samples
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/**
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@brief Histogram density estimator for weighted samples
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The histogram density estimator returns a histogram of the sample distribution. The positions and sizes of the bins
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are determined using a specifiable number of cached samples (cache_size). The range between the minimum and the
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maximum of the cached samples is subdivided into a specifiable number of bins (num_bins) of same size. Additionally,
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an under- and an overflow bin is added to capture future under- and overflow samples. Once the bins are determined,
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the cached samples and all subsequent samples are added to the correct bins. At the end, a range of std::pair is
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returned, where each pair contains the position of the bin (lower bound) and the sum of the weights (normalized with the
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sum of all weights).
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@param density_cache_size Number of first samples used to determine min and max.
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@param density_num_bins Number of bins (two additional bins collect under- and overflow samples).
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*/
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template<typename Sample, typename Weight>
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struct weighted_density_impl
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: accumulator_base
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{
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typedef typename numeric::functional::average<Weight, std::size_t>::result_type float_type;
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typedef std::vector<std::pair<float_type, float_type> > histogram_type;
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typedef std::vector<float_type> array_type;
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// for boost::result_of
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typedef iterator_range<typename histogram_type::iterator> result_type;
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template<typename Args>
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weighted_density_impl(Args const &args)
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: cache_size(args[density_cache_size])
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, cache(cache_size)
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, num_bins(args[density_num_bins])
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, samples_in_bin(num_bins + 2, 0.)
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, bin_positions(num_bins + 2)
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, histogram(
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num_bins + 2
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, std::make_pair(
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numeric::average(args[sample | Sample()],(std::size_t)1)
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, numeric::average(args[sample | Sample()],(std::size_t)1)
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)
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)
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, is_dirty(true)
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{
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}
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template<typename Args>
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void operator ()(Args const &args)
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{
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this->is_dirty = true;
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std::size_t cnt = count(args);
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// Fill up cache with cache_size first samples
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if (cnt <= this->cache_size)
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{
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this->cache[cnt - 1] = std::make_pair(args[sample], args[weight]);
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}
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// Once cache_size samples have been accumulated, create num_bins bins of same size between
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// the minimum and maximum of the cached samples as well as an under- and an overflow bin.
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// Store their lower bounds (bin_positions) and fill the bins with the cached samples (samples_in_bin).
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if (cnt == this->cache_size)
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{
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float_type minimum = numeric::average((min)(args),(std::size_t)1);
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float_type maximum = numeric::average((max)(args),(std::size_t)1);
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float_type bin_size = numeric::average(maximum - minimum, this->num_bins);
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// determine bin positions (their lower bounds)
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for (std::size_t i = 0; i < this->num_bins + 2; ++i)
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{
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this->bin_positions[i] = minimum + (i - 1.) * bin_size;
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}
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for (typename histogram_type::const_iterator iter = this->cache.begin(); iter != this->cache.end(); ++iter)
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{
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if (iter->first < this->bin_positions[1])
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{
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this->samples_in_bin[0] += iter->second;
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}
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else if (iter->first >= this->bin_positions[this->num_bins + 1])
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{
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this->samples_in_bin[this->num_bins + 1] += iter->second;
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}
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else
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{
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typename array_type::iterator it = std::upper_bound(
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this->bin_positions.begin()
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, this->bin_positions.end()
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, iter->first
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);
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std::size_t d = std::distance(this->bin_positions.begin(), it);
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this->samples_in_bin[d - 1] += iter->second;
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}
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}
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}
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// Add each subsequent sample to the correct bin
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else if (cnt > this->cache_size)
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{
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if (args[sample] < this->bin_positions[1])
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{
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this->samples_in_bin[0] += args[weight];
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}
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else if (args[sample] >= this->bin_positions[this->num_bins + 1])
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{
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this->samples_in_bin[this->num_bins + 1] += args[weight];
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}
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else
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{
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typename array_type::iterator it = std::upper_bound(
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this->bin_positions.begin()
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, this->bin_positions.end()
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, args[sample]
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);
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std::size_t d = std::distance(this->bin_positions.begin(), it);
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this->samples_in_bin[d - 1] += args[weight];
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}
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}
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}
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template<typename Args>
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result_type result(Args const &args) const
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{
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if (this->is_dirty)
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{
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this->is_dirty = false;
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// creates a vector of std::pair where each pair i holds
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// the values bin_positions[i] (x-axis of histogram) and
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// samples_in_bin[i] / cnt (y-axis of histogram).
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for (std::size_t i = 0; i < this->num_bins + 2; ++i)
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{
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this->histogram[i] = std::make_pair(this->bin_positions[i], numeric::average(this->samples_in_bin[i], sum_of_weights(args)));
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}
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}
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// returns a range of pairs
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return make_iterator_range(this->histogram);
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}
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private:
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std::size_t cache_size; // number of cached samples
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histogram_type cache; // cache to store the first cache_size samples with their weights as std::pair
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std::size_t num_bins; // number of bins
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array_type samples_in_bin; // number of samples in each bin
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array_type bin_positions; // lower bounds of bins
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mutable histogram_type histogram; // histogram
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mutable bool is_dirty;
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};
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} // namespace impl
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///////////////////////////////////////////////////////////////////////////////
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// tag::weighted_density
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//
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namespace tag
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{
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struct weighted_density
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: depends_on<count, sum_of_weights, min, max>
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, density_cache_size
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, density_num_bins
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{
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/// INTERNAL ONLY
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///
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typedef accumulators::impl::weighted_density_impl<mpl::_1, mpl::_2> impl;
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#ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED
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static boost::parameter::keyword<density_cache_size> const cache_size;
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static boost::parameter::keyword<density_num_bins> const num_bins;
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#endif
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};
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}
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///////////////////////////////////////////////////////////////////////////////
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// extract::weighted_density
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//
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namespace extract
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{
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extractor<tag::density> const weighted_density = {};
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BOOST_ACCUMULATORS_IGNORE_GLOBAL(weighted_density)
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}
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using extract::weighted_density;
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}} // namespace boost::accumulators
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#endif
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