boost/accumulators/statistics/weighted_density.hpp
/////////////////////////////////////////////////////////////////////////////// // 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 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); } 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