// Copyright (C) 2011  Davis E. King (davis@dlib.net)
// License: Boost Software License   See LICENSE.txt for the full license.
#ifndef DLIB_MAX_COST_ASSIgNMENT_H__
#define DLIB_MAX_COST_ASSIgNMENT_H__

#include "max_cost_assignment_abstract.h"
#include "../matrix.h"
#include <vector>
#include <deque>

namespace dlib
{

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

    template <typename EXP>
    typename EXP::type assignment_cost (
        const matrix_exp<EXP>& cost,
        const std::vector<long>& assignment
    )
    {
        DLIB_ASSERT(cost.nr() == cost.nc(),
            "\t type assignment_cost(cost,assignment)"
            << "\n\t cost.nr(): " << cost.nr()
            << "\n\t cost.nc(): " << cost.nc()
            );
#ifdef ENABLE_ASSERTS
        // can't call max on an empty vector. So put an if here to guard against it.
        if (assignment.size() > 0)
        {
            DLIB_ASSERT(0 <= min(vector_to_matrix(assignment)) && max(vector_to_matrix(assignment)) < cost.nr(),
                "\t type assignment_cost(cost,assignment)"
                << "\n\t cost.nr(): " << cost.nr()
                << "\n\t cost.nc(): " << cost.nc()
                << "\n\t min(assignment): " << min(vector_to_matrix(assignment)) 
                << "\n\t max(assignment): " << max(vector_to_matrix(assignment)) 
                );
        }
#endif

        typename EXP::type temp = 0;
        for (unsigned long i = 0; i < assignment.size(); ++i)
        {
            temp += cost(i, assignment[i]);
        }
        return temp;
    }

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

    namespace impl
    {
        template <typename EXP>
        inline void compute_slack(
            const long x,
            std::vector<typename EXP::type>& slack,
            std::vector<long>& slackx,
            const matrix_exp<EXP>& cost,
            const std::vector<typename EXP::type>& lx,
            const std::vector<typename EXP::type>& ly
        )
        {
            for (long y = 0; y < cost.nc(); ++y)
            {
                if (lx[x] + ly[y] - cost(x,y) < slack[y])
                {
                    slack[y] = lx[x] + ly[y] - cost(x,y);
                    slackx[y] = x;
                }
            }
        }
    }

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

    template <typename EXP>
    std::vector<long> max_cost_assignment (
        const matrix_exp<EXP>& cost_
    )                         
    {
        const_temp_matrix<EXP> cost(cost_);
        typedef typename EXP::type type;
        // This algorithm only works if the elements of the cost matrix can be reliably 
        // compared using operator==. However, comparing for equality with floating point
        // numbers is not a stable operation. So you need to use an integer cost matrix.
        COMPILE_TIME_ASSERT(std::numeric_limits<type>::is_integer);
        DLIB_ASSERT(cost.nr() == cost.nc(),
            "\t std::vector<long> max_cost_assignment(cost)"
            << "\n\t cost.nr(): " << cost.nr()
            << "\n\t cost.nc(): " << cost.nc()
            );

        using namespace dlib::impl;
        /*
            I based the implementation of this algorithm on the description of the
            Hungarian algorithm on the following websites:
                http://www.math.uwo.ca/~mdawes/courses/344/kuhn-munkres.pdf
                http://www.topcoder.com/tc?module=Static&d1=tutorials&d2=hungarianAlgorithm

            Note that this is the fast O(n^3) version of the algorithm.
        */

        if (cost.size() == 0)
            return std::vector<long>();

        std::vector<type> lx, ly;
        std::vector<long> xy;
        std::vector<long> yx;
        std::vector<char> S, T;
        std::vector<type> slack;
        std::vector<long> slackx;
        std::vector<long> aug_path;




        // Initially, nothing is matched. 
        xy.assign(cost.nc(), -1);
        yx.assign(cost.nc(), -1);
        /*
            We maintain the following invariant:
                Vertex x is matched to vertex xy[x] and
                vertex y is matched to vertex yx[y].

                A value of -1 means a vertex isn't matched to anything.  Moreover,
                x corresponds to rows of the cost matrix and y corresponds to the
                columns of the cost matrix.  So we are matching X to Y.
        */


        // Create an initial feasible labeling.  Moreover, in the following
        // code we will always have: 
        //     for all valid x and y:  lx[x] + ly[y] >= cost(x,y)
        lx.resize(cost.nc());
        ly.assign(cost.nc(),0);
        for (long x = 0; x < cost.nr(); ++x)
            lx[x] = max(rowm(cost,x));

        // Now grow the match set by picking edges from the equality subgraph until
        // we have a complete matching.
        for (long match_size = 0; match_size < cost.nc(); ++match_size)
        {
            std::deque<long> q;

            // Empty out the S and T sets
            S.assign(cost.nc(), false);
            T.assign(cost.nc(), false);

            // clear out old slack values
            slack.assign(cost.nc(), std::numeric_limits<type>::max());
            slackx.resize(cost.nc());
            /*
                slack and slackx are maintained such that we always
                have the following (once they get initialized by compute_slack() below):
                    - for all y:
                        - let x == slackx[y]
                        - slack[y] == lx[x] + ly[y] - cost(x,y)
            */

            aug_path.assign(cost.nc(), -1);

            for (long x = 0; x < cost.nc(); ++x)
            {
                // If x is not matched to anything
                if (xy[x] == -1)
                {
                    q.push_back(x);
                    S[x] = true;

                    compute_slack(x, slack, slackx, cost, lx, ly);
                    break;
                }
            }


            long x_start = 0;
            long y_start = 0;

            // Find an augmenting path.  
            bool found_augmenting_path = false;
            while (!found_augmenting_path)
            {
                while (q.size() > 0 && !found_augmenting_path)
                {
                    const long x = q.front();
                    q.pop_front();
                    for (long y = 0; y < cost.nc(); ++y)
                    {
                        if (cost(x,y) == lx[x] + ly[y] && !T[y])
                        {
                            // if vertex y isn't matched with anything
                            if (yx[y] == -1) 
                            {
                                y_start = y;
                                x_start = x;
                                found_augmenting_path = true;
                                break;
                            }

                            T[y] = true;
                            q.push_back(yx[y]);

                            aug_path[yx[y]] = x;
                            S[yx[y]] = true;
                            compute_slack(yx[y], slack, slackx, cost, lx, ly);
                        }
                    }
                }

                if (found_augmenting_path)
                    break;


                // Since we didn't find an augmenting path we need to improve the 
                // feasible labeling stored in lx and ly.  We also need to keep the
                // slack updated accordingly.
                type delta = std::numeric_limits<type>::max();
                for (unsigned long i = 0; i < T.size(); ++i)
                {
                    if (!T[i])
                        delta = std::min(delta, slack[i]);
                }
                for (unsigned long i = 0; i < T.size(); ++i)
                {
                    if (S[i])
                        lx[i] -= delta;

                    if (T[i])
                        ly[i] += delta;
                    else
                        slack[i] -= delta;
                }



                q.clear();
                for (long y = 0; y < cost.nc(); ++y)
                {
                    if (!T[y] && slack[y] == 0)
                    {
                        // if vertex y isn't matched with anything
                        if (yx[y] == -1)
                        {
                            x_start = slackx[y];
                            y_start = y;
                            found_augmenting_path = true;
                            break;
                        }
                        else
                        {
                            T[y] = true;
                            if (!S[yx[y]])
                            {
                                q.push_back(yx[y]);

                                aug_path[yx[y]] = slackx[y];
                                S[yx[y]] = true;
                                compute_slack(yx[y], slack, slackx, cost, lx, ly);
                            }
                        }
                    }
                }
            } // end while (!found_augmenting_path)

            // Flip the edges along the augmenting path.  This means we will add one more
            // item to our matching.
            for (long cx = x_start, cy = y_start, ty; 
                 cx != -1; 
                 cx = aug_path[cx], cy = ty)
            {
                ty = xy[cx];
                yx[cy] = cx;
                xy[cx] = cy;
            }

        }


        return xy;
    }

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

}

#endif // DLIB_MAX_COST_ASSIgNMENT_H__


