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Convenience fixes

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Attempting to fix issues pointed out by Vadim Pisarevsky during the pull
request review. In particular, the following things are done:
*) The mechanism of debug info printing is changed and made more
procedure-style than the previous macro-style
*) z in solveLP() is now returned as a column-vector
*) Func parameter of solveLP() is now allowed to be column-vector, in
which case it is understood to be the transpose of what we need
*) Func and Constr now can contain floats, not only doubles (in the
former case the conversion is done via convertTo())
*)different constructor to allocate space for z in solveLP() is used,
making the size of z more explicit (this is just a notation change, not
functional, both constructors are achieving the same goal)
*) (big) mat.hpp and iostream headers are moved to precomp-headers from
optim.hpp
This commit is contained in:
Alex Leontiev
2013-07-11 22:05:14 +03:00
parent e9b432b1d9
commit 6db2596ca9
6 changed files with 77 additions and 58 deletions
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18
modules/optim/test/test_lpsolver.cpp
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@@ -1,17 +1,17 @@
#include "test_precomp.hpp"
#include "opencv2/optim.hpp"
#include <iostream>
TEST(Optim_LpSolver, regression_basic){
cv::Mat A,B,z,etalon_z;
if(true){
//cormen's example #1
A=(cv::Mat_<double>(1,3)<<3,1,2);
A=(cv::Mat_<double>(3,1)<<3,1,2);
B=(cv::Mat_<double>(3,4)<<1,1,3,30,2,2,5,24,4,1,2,36);
std::cout<<"here A goes\n"<<A<<"\n";
cv::optim::solveLP(A,B,z);
std::cout<<"here z goes\n"<<z<<"\n";
etalon_z=(cv::Mat_<double>(1,3)<<8,4,0);
etalon_z=(cv::Mat_<double>(3,1)<<8,4,0);
ASSERT_EQ(cv::countNonZero(z!=etalon_z),0);
}
@@ -22,7 +22,7 @@ TEST(Optim_LpSolver, regression_basic){
std::cout<<"here A goes\n"<<A<<"\n";
cv::optim::solveLP(A,B,z);
std::cout<<"here z goes\n"<<z<<"\n";
etalon_z=(cv::Mat_<double>(1,2)<<20,0);
etalon_z=(cv::Mat_<double>(2,1)<<20,0);
ASSERT_EQ(cv::countNonZero(z!=etalon_z),0);
}
@@ -33,7 +33,7 @@ TEST(Optim_LpSolver, regression_basic){
std::cout<<"here A goes\n"<<A<<"\n";
cv::optim::solveLP(A,B,z);
std::cout<<"here z goes\n"<<z<<"\n";
etalon_z=(cv::Mat_<double>(1,2)<<1,0);
etalon_z=(cv::Mat_<double>(2,1)<<1,0);
ASSERT_EQ(cv::countNonZero(z!=etalon_z),0);
}
}
@@ -48,7 +48,7 @@ TEST(Optim_LpSolver, regression_init_unfeasible){
std::cout<<"here A goes\n"<<A<<"\n";
cv::optim::solveLP(A,B,z);
std::cout<<"here z goes\n"<<z<<"\n";
etalon_z=(cv::Mat_<double>(1,3)<<1250,1000,0);
etalon_z=(cv::Mat_<double>(3,1)<<1250,1000,0);
ASSERT_EQ(cv::countNonZero(z!=etalon_z),0);
}
}
@@ -71,7 +71,7 @@ TEST(Optim_LpSolver, regression_multiple_solutions){
if(true){
//trivial example with multiple solutions
A=(cv::Mat_<double>(1,2)<<1,1);
A=(cv::Mat_<double>(2,1)<<1,1);
B=(cv::Mat_<double>(1,3)<<1,1,1);
std::cout<<"here A goes\n"<<A<<"\n";
int res=cv::optim::solveLP(A,B,z);
@@ -85,7 +85,7 @@ TEST(Optim_LpSolver, regression_multiple_solutions){
if(false){
//cormen's example from chapter about initialize_simplex
//online solver told it has inf many solutions, but I'm not sure
A=(cv::Mat_<double>(1,2)<<2,-1);
A=(cv::Mat_<double>(2,1)<<2,-1);
B=(cv::Mat_<double>(2,3)<<2,-1,2,1,-5,-4);
std::cout<<"here A goes\n"<<A<<"\n";
int res=cv::optim::solveLP(A,B,z);
@@ -101,7 +101,7 @@ TEST(Optim_LpSolver, regression_cycling){
if(true){
//example with cycling from http://people.orie.cornell.edu/miketodd/or630/SimplexCyclingExample.pdf
A=(cv::Mat_<double>(1,4)<<10,-57,-9,-24);
A=(cv::Mat_<double>(4,1)<<10,-57,-9,-24);
B=(cv::Mat_<double>(3,5)<<0.5,-5.5,-2.5,9,0,0.5,-1.5,-0.5,1,0,1,0,0,0,1);
std::cout<<"here A goes\n"<<A<<"\n";
int res=cv::optim::solveLP(A,B,z);