    // Copyright (C) 2013  Davis E. King (davis@dlib.net)
    // License: Boost Software License   See LICENSE.txt for the full license.
    #ifndef DLIB_SEQUENCE_SeGMENTER_H_h_
    #define DLIB_SEQUENCE_SeGMENTER_H_h_

    #include "sequence_segmenter_abstract.h"
    #include "../matrix.h"
    #include "sequence_labeler.h"
    #include <vector>

    namespace dlib
    {
        // This namespace contains implementation details for the sequence_segmenter.
        namespace impl_ss
        {

        // ------------------------------------------------------------------------------------

            // BIO/BILOU labels
            const unsigned int BEGIN   = 0;
            const unsigned int INSIDE  = 1;
            const unsigned int OUTSIDE = 2;
            const unsigned int LAST    = 3;
            const unsigned int UNIT    = 4;

        // ------------------------------------------------------------------------------------

            template <typename ss_feature_extractor>
            class feature_extractor
            {
                /*!
                    WHAT THIS OBJECT REPRESENTS
                        This is a feature extractor for a sequence_labeler.  It serves to map
                        the interface defined by a sequence_labeler into the kind of interface
                        defined for a sequence_segmenter.
                !*/

            public:
                typedef typename ss_feature_extractor::sequence_type sequence_type;

                ss_feature_extractor fe;

                feature_extractor() {}
                feature_extractor(const ss_feature_extractor& ss_fe_) : fe(ss_fe_) {}

                unsigned long num_nonnegative_weights (
                ) const
                {
                    const unsigned long NL = ss_feature_extractor::use_BIO_model ? 3 : 5;
                    if (ss_feature_extractor::allow_negative_weights)
                    {
                        return 0;
                    }
                    else
                    {
                        // We make everything non-negative except for the label transition
                        // and bias features.
                        return num_features() - NL*NL - NL;
                    }
                }

                friend void serialize(const feature_extractor& item, std::ostream& out)
                {
                    serialize(item.fe, out);
                }

                friend void deserialize(feature_extractor& item, std::istream& in)
                {
                    deserialize(item.fe, in);
                }

                unsigned long num_features() const
                {
                    const unsigned long NL = ss_feature_extractor::use_BIO_model ? 3 : 5;
                    if (ss_feature_extractor::use_high_order_features)
                        return NL + NL*NL + (NL*NL+NL)*fe.num_features()*fe.window_size();
                    else
                        return NL + NL*NL + NL*fe.num_features()*fe.window_size();
                }

                unsigned long order() const
                {
                    return 1;
                }

                unsigned long num_labels() const
                {
                    if (ss_feature_extractor::use_BIO_model)
                        return 3;
                    else
                        return 5;
                }

            private:

                template <typename feature_setter>
                struct dot_functor
                {
                    /*!
                        WHAT THIS OBJECT REPRESENTS
                            This class wraps the feature_setter used by a sequence_labeler
                            and turns it into the kind needed by a sequence_segmenter.
                    !*/

                    dot_functor(feature_setter& set_feature_, unsigned long offset_) :
                        set_feature(set_feature_), offset(offset_) {}

                    feature_setter& set_feature;
                    unsigned long offset;

                    inline void operator() (
                        unsigned long feat_index
                    )
                    {
                        set_feature(offset+feat_index);
                    }

                    inline void operator() (
                        unsigned long feat_index,
                        double feat_value
                    )
                    {
                        set_feature(offset+feat_index, feat_value);
                    }
                };

            public:

                template <typename EXP>
                bool reject_labeling (
                    const sequence_type& x,
                    const matrix_exp<EXP>& y,
                    unsigned long pos
                ) const
                {
                    if (ss_feature_extractor::use_BIO_model)
                    {
                        // Don't allow BIO label patterns that don't correspond to a sensical
                        // segmentation.
                        if (y.size() > 1 && y(0) == INSIDE && y(1) == OUTSIDE)
                            return true;
                        if (y.size() == 1 && y(0) == INSIDE)
                            return true;
                    }
                    else
                    {
                        // Don't allow BILOU label patterns that don't correspond to a sensical
                        // segmentation.
                        if (y.size() > 1)
                        {
                            if (y(1) == BEGIN && y(0) == OUTSIDE)
                                return true;
                            if (y(1) == BEGIN && y(0) == UNIT)
                                return true;
                            if (y(1) == BEGIN && y(0) == BEGIN)
                                return true;

                            if (y(1) == INSIDE && y(0) == BEGIN)
                                return true;
                            if (y(1) == INSIDE && y(0) == OUTSIDE)
                                return true;
                            if (y(1) == INSIDE && y(0) == UNIT)
                                return true;

                            if (y(1) == OUTSIDE && y(0) == INSIDE)
                                return true;
                            if (y(1) == OUTSIDE && y(0) == LAST)
                                return true;

                            if (y(1) == LAST && y(0) == INSIDE)
                                return true;
                            if (y(1) == LAST && y(0) == LAST)
                                return true;

                            if (y(1) == UNIT && y(0) == INSIDE)
                                return true;
                            if (y(1) == UNIT && y(0) == LAST)
                                return true;

                            // if at the end of the sequence
                            if (pos == x.size()-1)
                            {
                                if (y(0) == BEGIN)
                                    return true;
                                if (y(0) == INSIDE)
                                    return true;
                            }
                        }
                        else
                        {
                            if (y(0) == INSIDE)
                                return true;
                            if (y(0) == LAST)
                                return true;

                            // if at the end of the sequence
                            if (pos == x.size()-1)
                            {
                                if (y(0) == BEGIN)
                                    return true;
                            }
                        }
                    }
                    return false;
                }

                template <typename feature_setter, typename EXP>
                void get_features (
                    feature_setter& set_feature,
                    const sequence_type& x,
                    const matrix_exp<EXP>& y,
                    unsigned long position
                ) const
                {
                    unsigned long offset = 0;

                    const int window_size = fe.window_size();

                    const int base_dims = fe.num_features();
                    for (int i = 0; i < window_size; ++i)
                    {
                        const long pos = i-window_size/2 + static_cast<long>(position);
                        if (0 <= pos && pos < (long)x.size())
                        {
                            const unsigned long off1 = y(0)*base_dims;
                            dot_functor<feature_setter> fs1(set_feature, offset+off1);
                            fe.get_features(fs1, x, pos);

                            if (ss_feature_extractor::use_high_order_features && y.size() > 1)
                            {
                                const unsigned long off2 = num_labels()*base_dims + (y(0)*num_labels()+y(1))*base_dims;
                                dot_functor<feature_setter> fs2(set_feature, offset+off2);
                                fe.get_features(fs2, x, pos);
                            }
                        }

                        if (ss_feature_extractor::use_high_order_features)
                            offset += num_labels()*base_dims + num_labels()*num_labels()*base_dims;
                        else
                            offset += num_labels()*base_dims;
                    }

                    // Pull out an indicator feature for the type of transition between the
                    // previous label and the current label.
                    if (y.size() > 1)
                        set_feature(offset + y(1)*num_labels() + y(0));

                    offset += num_labels()*num_labels();
                    // pull out an indicator feature for the current label.  This is the per
                    // label bias.
                    set_feature(offset + y(0));
                }
            };

        } // end namespace impl_ss

    // ----------------------------------------------------------------------------------------

        template <
            typename feature_extractor
            >
        unsigned long total_feature_vector_size (
            const feature_extractor& fe
        )
        {
            const unsigned long NL = feature_extractor::use_BIO_model ? 3 : 5;
            if (feature_extractor::use_high_order_features)
                return NL + NL*NL + (NL*NL+NL)*fe.num_features()*fe.window_size();
            else
                return NL + NL*NL + NL*fe.num_features()*fe.window_size();
        }

    // ----------------------------------------------------------------------------------------

        template <
            typename feature_extractor
            >
        class sequence_segmenter
        {
        public:
            typedef typename feature_extractor::sequence_type sample_sequence_type;
            typedef std::vector<std::pair<unsigned long, unsigned long> > segmented_sequence_type;

            sequence_segmenter()
            {
    #ifdef ENABLE_ASSERTS
                const feature_extractor& fe = labeler.get_feature_extractor().fe;
                DLIB_ASSERT(fe.window_size() >= 1 && fe.num_features() >= 1,
                    "\t sequence_segmenter::sequence_segmenter()"
                    << "\n\t An invalid feature extractor was supplied."
                    << "\n\t fe.window_size():  " << fe.window_size()
                    << "\n\t fe.num_features(): " << fe.num_features()
                    << "\n\t this: " << this
                );
    #endif
            }

            explicit sequence_segmenter(
                const matrix<double,0,1>& weights
            ) :
                labeler(weights)
            {
    #ifdef ENABLE_ASSERTS
                const feature_extractor& fe = labeler.get_feature_extractor().fe;
                // make sure requires clause is not broken
                DLIB_ASSERT(total_feature_vector_size(fe) == (unsigned long)weights.size(),
                    "\t sequence_segmenter::sequence_segmenter(weights)"
                    << "\n\t These sizes should match"
                    << "\n\t total_feature_vector_size(fe):  " << total_feature_vector_size(fe)
                    << "\n\t weights.size(): " << weights.size()
                    << "\n\t this: " << this
                    );
                DLIB_ASSERT(fe.window_size() >= 1 && fe.num_features() >= 1,
                    "\t sequence_segmenter::sequence_segmenter()"
                    << "\n\t An invalid feature extractor was supplied."
                    << "\n\t fe.window_size():  " << fe.window_size()
                    << "\n\t fe.num_features(): " << fe.num_features()
                    << "\n\t this: " << this
                );
    #endif
            }

            sequence_segmenter(
                const matrix<double,0,1>& weights,
                const feature_extractor& fe
            ) :
                labeler(weights, impl_ss::feature_extractor<feature_extractor>(fe))
            {
                // make sure requires clause is not broken
                DLIB_ASSERT(total_feature_vector_size(fe) == (unsigned long)weights.size(),
                    "\t sequence_segmenter::sequence_segmenter(weights,fe)"
                    << "\n\t These sizes should match"
                    << "\n\t total_feature_vector_size(fe):  " << total_feature_vector_size(fe)
                    << "\n\t weights.size(): " << weights.size()
                    << "\n\t this: " << this
                    );
                DLIB_ASSERT(fe.window_size() >= 1 && fe.num_features() >= 1,
                    "\t sequence_segmenter::sequence_segmenter()"
                    << "\n\t An invalid feature extractor was supplied."
                    << "\n\t fe.window_size():  " << fe.window_size()
                    << "\n\t fe.num_features(): " << fe.num_features()
                    << "\n\t this: " << this
                );
            }

            const feature_extractor& get_feature_extractor (
            ) const { return labeler.get_feature_extractor().fe; }

            const matrix<double,0,1>& get_weights (
            ) const { return labeler.get_weights(); }

            segmented_sequence_type operator() (
                const sample_sequence_type& x
            ) const
            {
                segmented_sequence_type y;
                segment_sequence(x,y);
                return y;
            }

            void segment_sequence (
                const sample_sequence_type& x,
                segmented_sequence_type& y
            ) const
            {
                y.clear();
                std::vector<unsigned long> labels;
                labeler.label_sequence(x, labels);

                if (feature_extractor::use_BIO_model)
                {
                    // Convert from BIO tagging to the explicit segments representation.
                    for (unsigned long i = 0; i < labels.size(); ++i)
                    {
                        if (labels[i] == impl_ss::BEGIN)
                        {
                            const unsigned long begin = i;
                            ++i;
                            while (i < labels.size() && labels[i] == impl_ss::INSIDE)
                                ++i;

                            y.push_back(std::make_pair(begin, i));
                            --i;
                        }
                    }
                }
                else
                {
                    // Convert from BILOU tagging to the explicit segments representation.
                    for (unsigned long i = 0; i < labels.size(); ++i)
                    {
                        if (labels[i] == impl_ss::BEGIN)
                        {
                            const unsigned long begin = i;
                            ++i;
                            while (i < labels.size() && labels[i] == impl_ss::INSIDE)
                                ++i;

                            y.push_back(std::make_pair(begin, i+1));
                        }
                        else if (labels[i] == impl_ss::UNIT)
                        {
                            y.push_back(std::make_pair(i, i+1));
                        }
                    }
                }
            }

            friend void serialize(const sequence_segmenter& item, std::ostream& out)
            {
                int version = 1;
                serialize(version, out);

                // Save these just so we can compare them when we deserialize and make
                // sure the feature_extractor being used is compatible with the model being
                // loaded.
                serialize(feature_extractor::use_BIO_model, out);
                serialize(feature_extractor::use_high_order_features, out);
                serialize(total_feature_vector_size(item.get_feature_extractor()), out);

                serialize(item.labeler, out);
            }

            friend void deserialize(sequence_segmenter& item, std::istream& in)
            {
                int version = 0;
                deserialize(version, in);
                if (version != 1)
                    throw serialization_error("Unexpected version found while deserializing dlib::sequence_segmenter.");

                // Try to check if the saved model is compatible with the current feature
                // extractor.
                bool use_BIO_model, use_high_order_features;
                unsigned long dims;
                deserialize(use_BIO_model, in);
                deserialize(use_high_order_features, in);
                deserialize(dims, in);
                deserialize(item.labeler, in);
                if (use_BIO_model != feature_extractor::use_BIO_model)
                {
                    throw serialization_error("Incompatible feature extractor found while deserializing "
                        "dlib::sequence_segmenter. Wrong value of use_BIO_model.");
                }
                if (use_high_order_features != feature_extractor::use_high_order_features)
                {
                    throw serialization_error("Incompatible feature extractor found while deserializing "
                        "dlib::sequence_segmenter. Wrong value of use_high_order_features.");
                }
                if (dims != total_feature_vector_size(item.get_feature_extractor()))
                {
                    throw serialization_error("Incompatible feature extractor found while deserializing "
                        "dlib::sequence_segmenter. Wrong value of total_feature_vector_size().");
                }
            }

        private:
            sequence_labeler<impl_ss::feature_extractor<feature_extractor> > labeler;
        };

    // ----------------------------------------------------------------------------------------

    }

    #endif // DLIB_SEQUENCE_SeGMENTER_H_h_