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/usr/include/boost/accumulators/statistics/

/usr/include/boost/accumulators/statistics

Name	Size	Mode	Actions
parameters/	-	0755	rm
variates/	-	0755	rm
count.hpp	2013	0644	edit dl rm
covariance.hpp	7137	0644	edit dl rm
density.hpp	10007	0644	edit dl rm
error_of.hpp	2588	0644	edit dl rm
error_of_mean.hpp	2193	0644	edit dl rm
extended_p_square.hpp	11633	0644	edit dl rm
extended_p_square_quantile.hpp	12522	0644	edit dl rm
kurtosis.hpp	3864	0644	edit dl rm
max.hpp	2294	0644	edit dl rm
mean.hpp	9334	0644	edit dl rm
median.hpp	10242	0644	edit dl rm
min.hpp	2294	0644	edit dl rm
moment.hpp	3436	0644	edit dl rm
peaks_over_threshold.hpp	17525	0644	edit dl rm
pot_quantile.hpp	7336	0644	edit dl rm
pot_tail_mean.hpp	7802	0644	edit dl rm
p_square_cumulative_distribution.hpp	955	0644	edit dl rm
p_square_cumul_dist.hpp	10365	0644	edit dl rm
p_square_quantile.hpp	10086	0644	edit dl rm
rolling_count.hpp	2574	0644	edit dl rm
rolling_mean.hpp	6753	0644	edit dl rm
rolling_moment.hpp	3741	0644	edit dl rm
rolling_sum.hpp	2871	0644	edit dl rm
rolling_variance.hpp	9486	0644	edit dl rm
rolling_window.hpp	7254	0644	edit dl rm
skewness.hpp	3691	0644	edit dl rm
stats.hpp	972	0644	edit dl rm
sum.hpp	3884	0644	edit dl rm
sum_kahan.hpp	5104	0644	edit dl rm
tail.hpp	11012	0644	edit dl rm
tail_mean.hpp	9158	0644	edit dl rm
tail_quantile.hpp	5535	0644	edit dl rm
tail_variate.hpp	4504	0644	edit dl rm
tail_variate_means.hpp	10463	0644	edit dl rm
times2_iterator.hpp	1965	0644	edit dl rm
variance.hpp	7522	0644	edit dl rm
weighted_covariance.hpp	5244	0644	edit dl rm
weighted_density.hpp	9518	0644	edit dl rm
weighted_extended_p_square.hpp	12842	0644	edit dl rm
weighted_kurtosis.hpp	4147	0644	edit dl rm
weighted_mean.hpp	6637	0644	edit dl rm
weighted_median.hpp	8667	0644	edit dl rm
weighted_moment.hpp	3384	0644	edit dl rm
weighted_peaks_over_threshold.hpp	12352	0644	edit dl rm
weighted_p_square_cumulative_distribution.hpp	1009	0644	edit dl rm
weighted_p_square_cumul_dist.hpp	11058	0644	edit dl rm
weighted_p_square_quantile.hpp	11110	0644	edit dl rm
weighted_skewness.hpp	3844	0644	edit dl rm
weighted_sum.hpp	3639	0644	edit dl rm
weighted_sum_kahan.hpp	4559	0644	edit dl rm
weighted_tail_mean.hpp	5788	0644	edit dl rm
weighted_tail_quantile.hpp	5135	0644	edit dl rm
weighted_tail_variate_means.hpp	10052	0644	edit dl rm
weighted_variance.hpp	6774	0644	edit dl rm
with_error.hpp	1277	0644	edit dl rm

Edit: /usr/include/boost/accumulators/statistics/weighted_density.hpp (9518B)

///////////////////////////////////////////////////////////////////////////////
// weighted_density.hpp
//
//  Copyright 2006 Daniel Egloff, Olivier Gygi. 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)

#ifndef BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_DENSITY_HPP_DE_01_01_2006
#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_DENSITY_HPP_DE_01_01_2006

#include <vector>
#include <limits>
#include <functional>
#include <boost/range.hpp>
#include <boost/parameter/keyword.hpp>
#include <boost/mpl/placeholders.hpp>
#include <boost/accumulators/framework/accumulator_base.hpp>
#include <boost/accumulators/framework/extractor.hpp>
#include <boost/accumulators/numeric/functional.hpp>
#include <boost/accumulators/framework/parameters/sample.hpp>
#include <boost/accumulators/statistics_fwd.hpp>
#include <boost/accumulators/statistics/sum.hpp>
#include <boost/accumulators/statistics/max.hpp>
#include <boost/accumulators/statistics/min.hpp>
#include <boost/accumulators/statistics/density.hpp> // for named parameters density_cache_size and density_num_bins
#include <boost/serialization/vector.hpp>
#include <boost/serialization/utility.hpp>

namespace boost { namespace accumulators
{

namespace impl
{
    ///////////////////////////////////////////////////////////////////////////////
    // weighted_density_impl
    //  density histogram for weighted samples
    /**
        @brief Histogram density estimator for weighted samples

The histogram density estimator returns a histogram of the sample distribution. The positions and sizes of the bins
        are determined using a specifiable number of cached samples (cache_size). The range between the minimum and the
        maximum of the cached samples is subdivided into a specifiable number of bins (num_bins) of same size. Additionally,
        an under- and an overflow bin is added to capture future under- and overflow samples. Once the bins are determined,
        the cached samples and all subsequent samples are added to the correct bins. At the end, a range of std::pair is
        returned, where each pair contains the position of the bin (lower bound) and the sum of the weights (normalized with the
        sum of all weights).

@param density_cache_size Number of first samples used to determine min and max.
        @param density_num_bins Number of bins (two additional bins collect under- and overflow samples).
    */
    template<typename Sample, typename Weight>
    struct weighted_density_impl
      : accumulator_base
    {
        typedef typename numeric::functional::fdiv<Weight, std::size_t>::result_type float_type;
        typedef std::vector<std::pair<float_type, float_type> > histogram_type;
        typedef std::vector<float_type> array_type;
        // for boost::result_of
        typedef iterator_range<typename histogram_type::iterator> result_type;

template<typename Args>
        weighted_density_impl(Args const &args)
            : cache_size(args[density_cache_size])
            , cache(cache_size)
            , num_bins(args[density_num_bins])
            , samples_in_bin(num_bins + 2, 0.)
            , bin_positions(num_bins + 2)
            , histogram(
                num_bins + 2
              , std::make_pair(
                    numeric::fdiv(args[sample | Sample()],(std::size_t)1)
                  , numeric::fdiv(args[sample | Sample()],(std::size_t)1)
                )
              )
            , is_dirty(true)
        {
        }

template<typename Args>
        void operator ()(Args const &args)
        {
            this->is_dirty = true;

std::size_t cnt = count(args);

// Fill up cache with cache_size first samples
            if (cnt <= this->cache_size)
            {
                this->cache[cnt - 1] = std::make_pair(args[sample], args[weight]);
            }

// Once cache_size samples have been accumulated, create num_bins bins of same size between
            // the minimum and maximum of the cached samples as well as an under- and an overflow bin.
            // Store their lower bounds (bin_positions) and fill the bins with the cached samples (samples_in_bin).
            if (cnt == this->cache_size)
            {
                float_type minimum = numeric::fdiv((min)(args),(std::size_t)1);
                float_type maximum = numeric::fdiv((max)(args),(std::size_t)1);
                float_type bin_size = numeric::fdiv(maximum - minimum, this->num_bins);

// determine bin positions (their lower bounds)
                for (std::size_t i = 0; i < this->num_bins + 2; ++i)
                {
                    this->bin_positions[i] = minimum + (i - 1.) * bin_size;
                }

for (typename histogram_type::const_iterator iter = this->cache.begin(); iter != this->cache.end(); ++iter)
                {
                    if (iter->first < this->bin_positions[1])
                    {
                        this->samples_in_bin[0] += iter->second;
                    }
                    else if (iter->first >= this->bin_positions[this->num_bins + 1])
                    {
                        this->samples_in_bin[this->num_bins + 1] += iter->second;
                    }
                    else
                    {
                        typename array_type::iterator it = std::upper_bound(
                            this->bin_positions.begin()
                          , this->bin_positions.end()
                          , iter->first
                        );

std::size_t d = std::distance(this->bin_positions.begin(), it);
                        this->samples_in_bin[d - 1] += iter->second;
                    }
                }
            }
            // Add each subsequent sample to the correct bin
            else if (cnt > this->cache_size)
            {
                if (args[sample] < this->bin_positions[1])
                {
                    this->samples_in_bin[0] += args[weight];
                }
                else if (args[sample] >= this->bin_positions[this->num_bins + 1])
                {
                    this->samples_in_bin[this->num_bins + 1] += args[weight];
                }
                else
                {
                    typename array_type::iterator it = std::upper_bound(
                        this->bin_positions.begin()
                      , this->bin_positions.end()
                      , args[sample]
                    );

std::size_t d = std::distance(this->bin_positions.begin(), it);
                    this->samples_in_bin[d - 1] += args[weight];
                }
            }
        }

template<typename Args>
        result_type result(Args const &args) const
        {
            if (this->is_dirty)
            {
                this->is_dirty = false;

// creates a vector of std::pair where each pair i holds
                // the values bin_positions[i] (x-axis of histogram) and
                // samples_in_bin[i] / cnt (y-axis of histogram).

for (std::size_t i = 0; i < this->num_bins + 2; ++i)
                {
                    this->histogram[i] = std::make_pair(this->bin_positions[i], numeric::fdiv(this->samples_in_bin[i], sum_of_weights(args)));
                }
            }

// returns a range of pairs
            return make_iterator_range(this->histogram);
        }

// make this accumulator serializeable
        // TODO split to save/load and check on parameters provided in ctor
        template<class Archive>
        void serialize(Archive & ar, const unsigned int file_version)
        {
            ar & cache_size;
            ar & cache;
            ar & num_bins;
            ar & samples_in_bin;
            ar & bin_positions;
            ar & histogram;
            ar & is_dirty; 
        }

private:
        std::size_t            cache_size;      // number of cached samples
        histogram_type         cache;           // cache to store the first cache_size samples with their weights as std::pair
        std::size_t            num_bins;        // number of bins
        array_type             samples_in_bin;  // number of samples in each bin
        array_type             bin_positions;   // lower bounds of bins
        mutable histogram_type histogram;       // histogram
        mutable bool is_dirty;
    };

} // namespace impl

///////////////////////////////////////////////////////////////////////////////
// tag::weighted_density
//
namespace tag
{
    struct weighted_density
      : depends_on<count, sum_of_weights, min, max>
      , density_cache_size
      , density_num_bins
    {
        /// INTERNAL ONLY
        ///
        typedef accumulators::impl::weighted_density_impl<mpl::_1, mpl::_2> impl;

#ifdef BOOST_ACCUMULATORS_DOXYGEN_INVOKED
        static boost::parameter::keyword<density_cache_size> const cache_size;
        static boost::parameter::keyword<density_num_bins> const num_bins;
        #endif
    };
}

///////////////////////////////////////////////////////////////////////////////
// extract::weighted_density
//
namespace extract
{
    extractor<tag::density> const weighted_density = {};

BOOST_ACCUMULATORS_IGNORE_GLOBAL(weighted_density)
}

using extract::weighted_density;

}} // namespace boost::accumulators

#endif

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