weighted_variance.hpp
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HPP
184 行
///////////////////////////////////////////////////////////////////////////////// weighted_variance.hpp//// Copyright 2005 Daniel Egloff, Eric Niebler. 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_VARIANCE_HPP_EAN_28_10_2005#define BOOST_ACCUMULATORS_STATISTICS_WEIGHTED_VARIANCE_HPP_EAN_28_10_2005#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/framework/depends_on.hpp>#include <boost/accumulators/statistics_fwd.hpp>#include <boost/accumulators/statistics/count.hpp>#include <boost/accumulators/statistics/variance.hpp>#include <boost/accumulators/statistics/weighted_sum.hpp>#include <boost/accumulators/statistics/weighted_mean.hpp>#include <boost/accumulators/statistics/weighted_moment.hpp>namespace boost { namespace accumulators{namespace impl{ //! Lazy calculation of variance of weighted samples. /*! The default implementation of the variance of weighted samples is based on the second moment \f$\widehat{m}_n^{(2)}\f$ (weighted_moment<2>) and the mean\f$ \hat{\mu}_n\f$ (weighted_mean): \f[ \hat{\sigma}_n^2 = \widehat{m}_n^{(2)}-\hat{\mu}_n^2, \f] where \f$n\f$ is the number of samples. */ template<typename Sample, typename Weight, typename MeanFeature> struct lazy_weighted_variance_impl : accumulator_base { typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample; // for boost::result_of typedef typename numeric::functional::average<weighted_sample, Weight>::result_type result_type; lazy_weighted_variance_impl(dont_care) {} template<typename Args> result_type result(Args const &args) const { extractor<MeanFeature> const some_mean = {}; result_type tmp = some_mean(args); return weighted_moment<2>(args) - tmp * tmp; } }; //! Iterative calculation of variance of weighted samples. /*! Iterative calculation of variance of weighted samples: \f[ \hat{\sigma}_n^2 = \frac{\bar{w}_n - w_n}{\bar{w}_n}\hat{\sigma}_{n - 1}^2 + \frac{w_n}{\bar{w}_n - w_n}\left(X_n - \hat{\mu}_n\right)^2 ,\quad n\ge2,\quad\hat{\sigma}_0^2 = 0. \f] where \f$\bar{w}_n\f$ is the sum of the \f$n\f$ weights \f$w_i\f$ and \f$\hat{\mu}_n\f$ the estimate of the mean of the weighted smaples. Note that the sample variance is not defined for \f$n <= 1\f$. */ template<typename Sample, typename Weight, typename MeanFeature, typename Tag> struct weighted_variance_impl : accumulator_base { typedef typename numeric::functional::multiplies<Sample, Weight>::result_type weighted_sample; // for boost::result_of typedef typename numeric::functional::average<weighted_sample, Weight>::result_type result_type; template<typename Args> weighted_variance_impl(Args const &args) : weighted_variance(numeric::average(args[sample | Sample()], numeric::one<Weight>::value)) { } template<typename Args> void operator ()(Args const &args) { std::size_t cnt = count(args); if(cnt > 1) { extractor<MeanFeature> const some_mean = {}; result_type tmp = args[parameter::keyword<Tag>::get()] - some_mean(args); this->weighted_variance = numeric::average(this->weighted_variance * (sum_of_weights(args) - args[weight]), sum_of_weights(args)) + numeric::average(tmp * tmp * args[weight], sum_of_weights(args) - args[weight] ); } } result_type result(dont_care) const { return this->weighted_variance; } private: result_type weighted_variance; };} // namespace impl///////////////////////////////////////////////////////////////////////////////// tag::weighted_variance// tag::immediate_weighted_variance//namespace tag{ struct lazy_weighted_variance : depends_on<weighted_moment<2>, weighted_mean> { /// INTERNAL ONLY /// typedef accumulators::impl::lazy_weighted_variance_impl<mpl::_1, mpl::_2, weighted_mean> impl; }; struct weighted_variance : depends_on<count, immediate_weighted_mean> { /// INTERNAL ONLY /// typedef accumulators::impl::weighted_variance_impl<mpl::_1, mpl::_2, immediate_weighted_mean, sample> impl; };}///////////////////////////////////////////////////////////////////////////////// extract::weighted_variance// extract::immediate_weighted_variance//namespace extract{ extractor<tag::lazy_weighted_variance> const lazy_weighted_variance = {}; extractor<tag::weighted_variance> const weighted_variance = {};}using extract::lazy_weighted_variance;using extract::weighted_variance;// weighted_variance(lazy) -> lazy_weighted_variancetemplate<>struct as_feature<tag::weighted_variance(lazy)>{ typedef tag::lazy_weighted_variance type;};// weighted_variance(immediate) -> weighted_variancetemplate<>struct as_feature<tag::weighted_variance(immediate)>{ typedef tag::weighted_variance type;};//////////////////////////////////////////////////////////////////////////////// droppable_accumulator<weighted_variance_impl>//// need to specialize droppable lazy weighted_variance to cache the result at the//// point the accumulator is dropped.///// INTERNAL ONLY///////template<typename Sample, typename Weight, typename MeanFeature>//struct droppable_accumulator<impl::weighted_variance_impl<Sample, Weight, MeanFeature> >// : droppable_accumulator_base<// with_cached_result<impl::weighted_variance_impl<Sample, Weight, MeanFeature> >// >//{// template<typename Args>// droppable_accumulator(Args const &args)// : droppable_accumulator::base(args)// {// }//};}} // namespace boost::accumulators#endif
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