Open Source Computer Vision Library
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347 lines
10 KiB
347 lines
10 KiB
#include "precomp.hpp" |
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#include <climits> |
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#include <algorithm> |
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#include <cstdarg> |
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#define ALEX_DEBUG |
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namespace cv{namespace optim{ |
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using std::vector; |
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using namespace std; |
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#ifdef ALEX_DEBUG |
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#define dprintf(x) printf x |
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static void print_matrix(const Mat& x){ |
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printf("\ttype:%d vs %d,\tsize: %d-on-%d\n",x.type(),CV_64FC1,x.rows,x.cols); |
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if(!true){ |
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//cout<<x; |
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} |
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else{ |
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for(int i=0;i<x.rows;i++){ |
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printf("\t["); |
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for(int j=0;j<x.cols;j++){ |
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printf("%g, ",x.at<double>(i,j)); |
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} |
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printf("]\n"); |
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} |
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} |
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} |
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static void print_simplex_state(const Mat& c,const Mat& b,double v,const std::vector<int> N,const std::vector<int> B){ |
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printf("\tprint simplex state\n"); |
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printf("v=%g\n",v); |
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printf("here c goes\n"); |
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print_matrix(c); |
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printf("non-basic: "); |
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for (std::vector<int>::const_iterator it = N.begin() ; it != N.end(); ++it){ |
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printf("%d, ",*it); |
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} |
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printf("\n"); |
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printf("here b goes\n"); |
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print_matrix(b); |
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printf("basic: "); |
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for (std::vector<int>::const_iterator it = B.begin() ; it != B.end(); ++it){ |
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printf("%d, ",*it); |
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} |
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printf("\n"); |
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} |
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#else |
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#define dprintf(x) |
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#define print_matrix(x) |
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#define print_simplex_state(c,b,v,N,B) |
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#endif |
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/**Due to technical considerations, the format of input b and c is somewhat special: |
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*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 |
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by this procedure - it should not be cleaned before the call to procedure and may contain mess after |
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it also initializes N and B and does not make any assumptions about their init values |
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* @return SOLVELP_UNFEASIBLE if problem is unfeasible, 0 if feasible. |
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*/ |
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static int initialize_simplex(Mat_<double>& c, Mat_<double>& b,double& v,vector<int>& N,vector<int>& B); |
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static inline void pivot(Mat_<double>& c,Mat_<double>& b,double& v,vector<int>& N,vector<int>& B, int leaving_index,int entering_index); |
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/**@return SOLVELP_UNBOUNDED means the problem is unbdd, SOLVELP_MULTI means multiple solutions, SOLVELP_SINGLE means one solution. |
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*/ |
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static int inner_simplex(Mat_<double>& c, Mat_<double>& b,double& v,vector<int>& N,vector<int>& B); |
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static void swap_columns(Mat_<double>& A,int col1,int col2); |
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//return codes:-2 (no_sol - unbdd),-1(no_sol - unfsbl), 0(single_sol), 1(multiple_sol=>least_l2_norm) |
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int solveLP(const Mat& Func, const Mat& Constr, Mat& z){ |
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dprintf(("call to solveLP\n")); |
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//sanity check (size, type, no. of channels) |
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CV_Assert(Func.type()==CV_64FC1 || Func.type()==CV_32FC1); |
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CV_Assert(Constr.type()==CV_64FC1 || Constr.type()==CV_32FC1); |
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CV_Assert((Func.rows==1 && (Constr.cols-Func.cols==1))|| |
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(Func.cols==1 && (Constr.cols-Func.rows==1))); |
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//copy arguments for we will shall modify them |
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Mat_<double> bigC=Mat_<double>(1,(Func.rows==1?Func.cols:Func.rows)+1), |
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bigB=Mat_<double>(Constr.rows,Constr.cols+1); |
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if(Func.rows==1){ |
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Func.convertTo(bigC.colRange(1,bigC.cols),CV_64FC1); |
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}else{ |
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dprintf(("hi from other branch\n")); |
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Mat_<double> slice=bigC.colRange(1,bigC.cols); |
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MatIterator_<double> slice_iterator=slice.begin(); |
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switch(Func.type()){ |
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case CV_64FC1: |
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for(MatConstIterator_<double> it=Func.begin<double>();it!=Func.end<double>();it++,slice_iterator++){ |
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* slice_iterator= *it; |
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} |
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break; |
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case CV_32FC1: |
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for(MatConstIterator_<float> it=Func.begin<float>();it!=Func.end<double>();it++,slice_iterator++){ |
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* slice_iterator= *it; |
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} |
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break; |
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} |
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print_matrix(Func); |
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print_matrix(bigC); |
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} |
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Constr.convertTo(bigB.colRange(1,bigB.cols),CV_64FC1); |
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double v=0; |
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vector<int> N,B; |
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if(initialize_simplex(bigC,bigB,v,N,B)==SOLVELP_UNFEASIBLE){ |
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return SOLVELP_UNFEASIBLE; |
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} |
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Mat_<double> c=bigC.colRange(1,bigC.cols), |
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b=bigB.colRange(1,bigB.cols); |
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int res=0; |
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if((res=inner_simplex(c,b,v,N,B))==SOLVELP_UNBOUNDED){ |
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return SOLVELP_UNBOUNDED; |
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} |
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//return the optimal solution |
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z.create(c.cols,1,CV_64FC1); |
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MatIterator_<double> it=z.begin<double>(); |
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for(int i=1;i<=c.cols;i++,it++){ |
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std::vector<int>::iterator pos=B.begin(); |
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if((pos=std::find(B.begin(),B.end(),i))==B.end()){ |
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*it=0; |
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}else{ |
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*it=b.at<double>(pos-B.begin(),b.cols-1); |
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} |
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} |
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return res; |
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} |
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static int initialize_simplex(Mat_<double>& c, Mat_<double>& b,double& v,vector<int>& N,vector<int>& B){ |
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N.resize(c.cols); |
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N[0]=0; |
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for (std::vector<int>::iterator it = N.begin()+1 ; it != N.end(); ++it){ |
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*it=it[-1]+1; |
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} |
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B.resize(b.rows); |
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B[0]=N.size(); |
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for (std::vector<int>::iterator it = B.begin()+1 ; it != B.end(); ++it){ |
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*it=it[-1]+1; |
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} |
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v=0; |
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int k=0; |
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{ |
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double min=DBL_MAX; |
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for(int i=0;i<b.rows;i++){ |
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if(b(i,b.cols-1)<min){ |
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min=b(i,b.cols-1); |
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k=i; |
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} |
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} |
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} |
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if(b(k,b.cols-1)>=0){ |
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N.erase(N.begin()); |
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return 0; |
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} |
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Mat_<double> old_c=c.clone(); |
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c=0; |
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c(0,0)=-1; |
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for(int i=0;i<b.rows;i++){ |
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b(i,0)=-1; |
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} |
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print_simplex_state(c,b,v,N,B); |
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dprintf(("\tWE MAKE PIVOT\n")); |
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pivot(c,b,v,N,B,k,0); |
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print_simplex_state(c,b,v,N,B); |
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inner_simplex(c,b,v,N,B); |
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dprintf(("\tAFTER INNER_SIMPLEX\n")); |
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print_simplex_state(c,b,v,N,B); |
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vector<int>::iterator iterator=std::find(B.begin(),B.end(),0); |
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if(iterator!=B.end()){ |
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int iterator_offset=iterator-B.begin(); |
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if(b(iterator_offset,b.cols-1)>0){ |
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return SOLVELP_UNFEASIBLE; |
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} |
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pivot(c,b,v,N,B,iterator_offset,0); |
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} |
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{ |
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iterator=std::find(N.begin(),N.end(),0); |
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int iterator_offset=iterator-N.begin(); |
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std::iter_swap(iterator,N.begin()); |
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swap_columns(c,iterator_offset,0); |
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swap_columns(b,iterator_offset,0); |
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} |
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dprintf(("after swaps\n")); |
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print_simplex_state(c,b,v,N,B); |
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//start from 1, because we ignore x_0 |
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c=0; |
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v=0; |
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for(int I=1;I<old_c.cols;I++){ |
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if((iterator=std::find(N.begin(),N.end(),I))!=N.end()){ |
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dprintf(("I=%d from nonbasic\n",I)); |
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int iterator_offset=iterator-N.begin(); |
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c(0,iterator_offset)+=old_c(0,I); |
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print_matrix(c); |
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}else{ |
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dprintf(("I=%d from basic\n",I)); |
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int iterator_offset=std::find(B.begin(),B.end(),I)-B.begin(); |
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c-=old_c(0,I)*b.row(iterator_offset).colRange(0,b.cols-1); |
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v+=old_c(0,I)*b(iterator_offset,b.cols-1); |
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print_matrix(c); |
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} |
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} |
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dprintf(("after restore\n")); |
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print_simplex_state(c,b,v,N,B); |
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N.erase(N.begin()); |
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return 0; |
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} |
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static int inner_simplex(Mat_<double>& c, Mat_<double>& b,double& v,vector<int>& N,vector<int>& B){ |
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int count=0; |
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while(1){ |
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dprintf(("iteration #%d\n",count)); |
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count++; |
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static MatIterator_<double> pos_ptr; |
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int e=-1,pos_ctr=0,min_var=INT_MAX; |
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bool all_nonzero=true; |
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for(pos_ptr=c.begin();pos_ptr!=c.end();pos_ptr++,pos_ctr++){ |
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if(*pos_ptr==0){ |
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all_nonzero=false; |
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} |
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if(*pos_ptr>0){ |
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if(N[pos_ctr]<min_var){ |
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e=pos_ctr; |
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min_var=N[pos_ctr]; |
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} |
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} |
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} |
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if(e==-1){ |
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dprintf(("hello from e==-1\n")); |
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print_matrix(c); |
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if(all_nonzero==true){ |
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return SOLVELP_SINGLE; |
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}else{ |
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return SOLVELP_MULTI; |
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} |
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} |
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int l=-1; |
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min_var=INT_MAX; |
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double min=DBL_MAX; |
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int row_it=0; |
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MatIterator_<double> min_row_ptr=b.begin(); |
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for(MatIterator_<double> it=b.begin();it!=b.end();it+=b.cols,row_it++){ |
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double myite=0; |
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//check constraints, select the tightest one, reinforcing Bland's rule |
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if((myite=it[e])>0){ |
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double val=it[b.cols-1]/myite; |
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if(val<min || (val==min && B[row_it]<min_var)){ |
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min_var=B[row_it]; |
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min_row_ptr=it; |
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min=val; |
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l=row_it; |
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} |
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} |
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} |
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if(l==-1){ |
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return SOLVELP_UNBOUNDED; |
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} |
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dprintf(("the tightest constraint is in row %d with %g\n",l,min)); |
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pivot(c,b,v,N,B,l,e); |
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dprintf(("objective, v=%g\n",v)); |
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print_matrix(c); |
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dprintf(("constraints\n")); |
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print_matrix(b); |
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dprintf(("non-basic: ")); |
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for (std::vector<int>::iterator it = N.begin() ; it != N.end(); ++it){ |
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dprintf(("%d, ",*it)); |
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} |
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dprintf(("\nbasic: ")); |
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for (std::vector<int>::iterator it = B.begin() ; it != B.end(); ++it){ |
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dprintf(("%d, ",*it)); |
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} |
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dprintf(("\n")); |
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} |
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} |
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static inline void pivot(Mat_<double>& c,Mat_<double>& b,double& v,vector<int>& N,vector<int>& B, int leaving_index,int entering_index){ |
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double Coef=b(leaving_index,entering_index); |
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for(int i=0;i<b.cols;i++){ |
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if(i==entering_index){ |
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b(leaving_index,i)=1/Coef; |
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}else{ |
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b(leaving_index,i)/=Coef; |
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} |
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} |
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for(int i=0;i<b.rows;i++){ |
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if(i!=leaving_index){ |
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double coef=b(i,entering_index); |
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for(int j=0;j<b.cols;j++){ |
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if(j==entering_index){ |
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b(i,j)=-coef*b(leaving_index,j); |
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}else{ |
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b(i,j)-=(coef*b(leaving_index,j)); |
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} |
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} |
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} |
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} |
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//objective function |
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Coef=c(0,entering_index); |
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for(int i=0;i<(b.cols-1);i++){ |
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if(i==entering_index){ |
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c(0,i)=-Coef*b(leaving_index,i); |
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}else{ |
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c(0,i)-=Coef*b(leaving_index,i); |
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} |
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} |
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dprintf(("v was %g\n",v)); |
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v+=Coef*b(leaving_index,b.cols-1); |
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int tmp=N[entering_index]; |
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N[entering_index]=B[leaving_index]; |
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B[leaving_index]=tmp; |
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} |
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static inline void swap_columns(Mat_<double>& A,int col1,int col2){ |
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for(int i=0;i<A.rows;i++){ |
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double tmp=A(i,col1); |
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A(i,col1)=A(i,col2); |
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A(i,col2)=tmp; |
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} |
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} |
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}}
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