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     41 #include "precomp.hpp"
     42 #include <climits>
     43 #include <algorithm>
     44 #include <cstdarg>
     45 
     46 #define dprintf(x)
     47 #define print_matrix(x)
     48 
     49 namespace cv
     50 {
     51 
     52 using std::vector;
     53 
     54 #ifdef ALEX_DEBUG
     55 static void print_simplex_state(const Mat& c,const Mat& b,double v,const std::vector<int> N,const std::vector<int> B){
     56     printf("\tprint simplex state\n");
     57 
     58     printf("v=%g\n",v);
     59 
     60     printf("here c goes\n");
     61     print_matrix(c);
     62 
     63     printf("non-basic: ");
     64     print(Mat(N));
     65     printf("\n");
     66 
     67     printf("here b goes\n");
     68     print_matrix(b);
     69     printf("basic: ");
     70 
     71     print(Mat(B));
     72     printf("\n");
     73 }
     74 #else
     75 #define print_simplex_state(c,b,v,N,B)
     76 #endif
     77 
     78 /**Due to technical considerations, the format of input b and c is somewhat special:
     79  *both b and c should be one column bigger than corresponding b and c of linear problem and the leftmost column will be used internally
     80  by this procedure - it should not be cleaned before the call to procedure and may contain mess after
     81  it also initializes N and B and does not make any assumptions about their init values
     82  * @return SOLVELP_UNFEASIBLE if problem is unfeasible, 0 if feasible.
     83 */
     84 static int initialize_simplex(Mat_<double>& c, Mat_<double>& b,double& v,vector<int>& N,vector<int>& B,vector<unsigned int>& indexToRow);
     85 static inline void pivot(Mat_<double>& c,Mat_<double>& b,double& v,vector<int>& N,vector<int>& B,int leaving_index,
     86         int entering_index,vector<unsigned int>& indexToRow);
     87 /**@return SOLVELP_UNBOUNDED means the problem is unbdd, SOLVELP_MULTI means multiple solutions, SOLVELP_SINGLE means one solution.
     88  */
     89 static int inner_simplex(Mat_<double>& c, Mat_<double>& b,double& v,vector<int>& N,vector<int>& B,vector<unsigned int>& indexToRow);
     90 static void swap_columns(Mat_<double>& A,int col1,int col2);
     91 #define SWAP(type,a,b) {type tmp=(a);(a)=(b);(b)=tmp;}
     92 
     93 //return codes:-2 (no_sol - unbdd),-1(no_sol - unfsbl), 0(single_sol), 1(multiple_sol=>least_l2_norm)
     94 int solveLP(const Mat& Func, const Mat& Constr, Mat& z){
     95     dprintf(("call to solveLP\n"));
     96 
     97     //sanity check (size, type, no. of channels)
     98     CV_Assert(Func.type()==CV_64FC1 || Func.type()==CV_32FC1);
     99     CV_Assert(Constr.type()==CV_64FC1 || Constr.type()==CV_32FC1);
    100     CV_Assert((Func.rows==1 && (Constr.cols-Func.cols==1))||
    101             (Func.cols==1 && (Constr.cols-Func.rows==1)));
    102 
    103     //copy arguments for we will shall modify them
    104     Mat_<double> bigC=Mat_<double>(1,(Func.rows==1?Func.cols:Func.rows)+1),
    105         bigB=Mat_<double>(Constr.rows,Constr.cols+1);
    106     if(Func.rows==1){
    107         Func.convertTo(bigC.colRange(1,bigC.cols),CV_64FC1);
    108     }else{
    109         Mat FuncT=Func.t();
    110         FuncT.convertTo(bigC.colRange(1,bigC.cols),CV_64FC1);
    111     }
    112     Constr.convertTo(bigB.colRange(1,bigB.cols),CV_64FC1);
    113     double v=0;
    114     vector<int> N,B;
    115     vector<unsigned int> indexToRow;
    116 
    117     if(initialize_simplex(bigC,bigB,v,N,B,indexToRow)==SOLVELP_UNFEASIBLE){
    118         return SOLVELP_UNFEASIBLE;
    119     }
    120     Mat_<double> c=bigC.colRange(1,bigC.cols),
    121         b=bigB.colRange(1,bigB.cols);
    122 
    123     int res=0;
    124     if((res=inner_simplex(c,b,v,N,B,indexToRow))==SOLVELP_UNBOUNDED){
    125         return SOLVELP_UNBOUNDED;
    126     }
    127 
    128     //return the optimal solution
    129     z.create(c.cols,1,CV_64FC1);
    130     MatIterator_<double> it=z.begin<double>();
    131     unsigned int nsize = (unsigned int)N.size();
    132     for(int i=1;i<=c.cols;i++,it++){
    133         if(indexToRow[i]<nsize){
    134             *it=0;
    135         }else{
    136             *it=b.at<double>(indexToRow[i]-nsize,b.cols-1);
    137         }
    138     }
    139 
    140     return res;
    141 }
    142 
    143 static int initialize_simplex(Mat_<double>& c, Mat_<double>& b,double& v,vector<int>& N,vector<int>& B,vector<unsigned int>& indexToRow){
    144     N.resize(c.cols);
    145     N[0]=0;
    146     for (std::vector<int>::iterator it = N.begin()+1 ; it != N.end(); ++it){
    147         *it=it[-1]+1;
    148     }
    149     B.resize(b.rows);
    150     B[0]=(int)N.size();
    151     for (std::vector<int>::iterator it = B.begin()+1 ; it != B.end(); ++it){
    152         *it=it[-1]+1;
    153     }
    154     indexToRow.resize(c.cols+b.rows);
    155     indexToRow[0]=0;
    156     for (std::vector<unsigned int>::iterator it = indexToRow.begin()+1 ; it != indexToRow.end(); ++it){
    157         *it=it[-1]+1;
    158     }
    159     v=0;
    160 
    161     int k=0;
    162     {
    163         double min=DBL_MAX;
    164         for(int i=0;i<b.rows;i++){
    165             if(b(i,b.cols-1)<min){
    166                 min=b(i,b.cols-1);
    167                 k=i;
    168             }
    169         }
    170     }
    171 
    172     if(b(k,b.cols-1)>=0){
    173         N.erase(N.begin());
    174         for (std::vector<unsigned int>::iterator it = indexToRow.begin()+1 ; it != indexToRow.end(); ++it){
    175             --(*it);
    176         }
    177         return 0;
    178     }
    179 
    180     Mat_<double> old_c=c.clone();
    181     c=0;
    182     c(0,0)=-1;
    183     for(int i=0;i<b.rows;i++){
    184         b(i,0)=-1;
    185     }
    186 
    187     print_simplex_state(c,b,v,N,B);
    188 
    189     dprintf(("\tWE MAKE PIVOT\n"));
    190     pivot(c,b,v,N,B,k,0,indexToRow);
    191 
    192     print_simplex_state(c,b,v,N,B);
    193 
    194     inner_simplex(c,b,v,N,B,indexToRow);
    195 
    196     dprintf(("\tAFTER INNER_SIMPLEX\n"));
    197     print_simplex_state(c,b,v,N,B);
    198 
    199     unsigned int nsize = (unsigned int)N.size();
    200     if(indexToRow[0]>=nsize){
    201         int iterator_offset=indexToRow[0]-nsize;
    202         if(b(iterator_offset,b.cols-1)>0){
    203             return SOLVELP_UNFEASIBLE;
    204         }
    205         pivot(c,b,v,N,B,iterator_offset,0,indexToRow);
    206     }
    207 
    208     vector<int>::iterator iterator;
    209     {
    210         int iterator_offset=indexToRow[0];
    211         iterator=N.begin()+iterator_offset;
    212         std::iter_swap(iterator,N.begin());
    213         SWAP(int,indexToRow[*iterator],indexToRow[0]);
    214         swap_columns(c,iterator_offset,0);
    215         swap_columns(b,iterator_offset,0);
    216     }
    217 
    218     dprintf(("after swaps\n"));
    219     print_simplex_state(c,b,v,N,B);
    220 
    221     //start from 1, because we ignore x_0
    222     c=0;
    223     v=0;
    224     for(int I=1;I<old_c.cols;I++){
    225         if(indexToRow[I]<nsize){
    226             dprintf(("I=%d from nonbasic\n",I));
    227             int iterator_offset=indexToRow[I];
    228             c(0,iterator_offset)+=old_c(0,I);
    229             print_matrix(c);
    230         }else{
    231             dprintf(("I=%d from basic\n",I));
    232             int iterator_offset=indexToRow[I]-nsize;
    233             c-=old_c(0,I)*b.row(iterator_offset).colRange(0,b.cols-1);
    234             v+=old_c(0,I)*b(iterator_offset,b.cols-1);
    235             print_matrix(c);
    236         }
    237     }
    238 
    239     dprintf(("after restore\n"));
    240     print_simplex_state(c,b,v,N,B);
    241 
    242     N.erase(N.begin());
    243     for (std::vector<unsigned int>::iterator it = indexToRow.begin()+1 ; it != indexToRow.end(); ++it){
    244         --(*it);
    245     }
    246     return 0;
    247 }
    248 
    249 static int inner_simplex(Mat_<double>& c, Mat_<double>& b,double& v,vector<int>& N,vector<int>& B,vector<unsigned int>& indexToRow){
    250     int count=0;
    251     for(;;){
    252         dprintf(("iteration #%d\n",count));
    253         count++;
    254 
    255         static MatIterator_<double> pos_ptr;
    256         int e=-1,pos_ctr=0,min_var=INT_MAX;
    257         bool all_nonzero=true;
    258         for(pos_ptr=c.begin();pos_ptr!=c.end();pos_ptr++,pos_ctr++){
    259             if(*pos_ptr==0){
    260                 all_nonzero=false;
    261             }
    262             if(*pos_ptr>0){
    263                 if(N[pos_ctr]<min_var){
    264                     e=pos_ctr;
    265                     min_var=N[pos_ctr];
    266                 }
    267             }
    268         }
    269         if(e==-1){
    270             dprintf(("hello from e==-1\n"));
    271             print_matrix(c);
    272             if(all_nonzero==true){
    273                 return SOLVELP_SINGLE;
    274             }else{
    275                 return SOLVELP_MULTI;
    276             }
    277         }
    278 
    279         int l=-1;
    280         min_var=INT_MAX;
    281         double min=DBL_MAX;
    282         int row_it=0;
    283         MatIterator_<double> min_row_ptr=b.begin();
    284         for(MatIterator_<double> it=b.begin();it!=b.end();it+=b.cols,row_it++){
    285             double myite=0;
    286             //check constraints, select the tightest one, reinforcing Bland's rule
    287             if((myite=it[e])>0){
    288                 double val=it[b.cols-1]/myite;
    289                 if(val<min || (val==min && B[row_it]<min_var)){
    290                     min_var=B[row_it];
    291                     min_row_ptr=it;
    292                     min=val;
    293                     l=row_it;
    294                 }
    295             }
    296         }
    297         if(l==-1){
    298             return SOLVELP_UNBOUNDED;
    299         }
    300         dprintf(("the tightest constraint is in row %d with %g\n",l,min));
    301 
    302         pivot(c,b,v,N,B,l,e,indexToRow);
    303 
    304         dprintf(("objective, v=%g\n",v));
    305         print_matrix(c);
    306         dprintf(("constraints\n"));
    307         print_matrix(b);
    308         dprintf(("non-basic: "));
    309         print_matrix(Mat(N));
    310         dprintf(("basic: "));
    311         print_matrix(Mat(B));
    312     }
    313 }
    314 
    315 static inline void pivot(Mat_<double>& c,Mat_<double>& b,double& v,vector<int>& N,vector<int>& B,
    316         int leaving_index,int entering_index,vector<unsigned int>& indexToRow){
    317     double Coef=b(leaving_index,entering_index);
    318     for(int i=0;i<b.cols;i++){
    319         if(i==entering_index){
    320             b(leaving_index,i)=1/Coef;
    321         }else{
    322             b(leaving_index,i)/=Coef;
    323         }
    324     }
    325 
    326     for(int i=0;i<b.rows;i++){
    327         if(i!=leaving_index){
    328             double coef=b(i,entering_index);
    329             for(int j=0;j<b.cols;j++){
    330                 if(j==entering_index){
    331                     b(i,j)=-coef*b(leaving_index,j);
    332                 }else{
    333                     b(i,j)-=(coef*b(leaving_index,j));
    334                 }
    335             }
    336         }
    337     }
    338 
    339     //objective function
    340     Coef=c(0,entering_index);
    341     for(int i=0;i<(b.cols-1);i++){
    342         if(i==entering_index){
    343             c(0,i)=-Coef*b(leaving_index,i);
    344         }else{
    345             c(0,i)-=Coef*b(leaving_index,i);
    346         }
    347     }
    348     dprintf(("v was %g\n",v));
    349     v+=Coef*b(leaving_index,b.cols-1);
    350 
    351     SWAP(int,N[entering_index],B[leaving_index]);
    352     SWAP(int,indexToRow[N[entering_index]],indexToRow[B[leaving_index]]);
    353 }
    354 
    355 static inline void swap_columns(Mat_<double>& A,int col1,int col2){
    356     for(int i=0;i<A.rows;i++){
    357         double tmp=A(i,col1);
    358         A(i,col1)=A(i,col2);
    359         A(i,col2)=tmp;
    360     }
    361 }
    362 }
    363