Opened 7 years ago
Last modified 5 years ago
#11295 new Bugs
Matrix Memory problem after using lu_factorize
Reported by: | Owned by: | Gunter | |
---|---|---|---|
Milestone: | To Be Determined | Component: | uBLAS |
Version: | Boost 1.55.0 | Severity: | Problem |
Keywords: | Cc: |
Description
Discovered that after using lu_factorize the values of the matrix have changed!
#include <iostream> #include <boost/date_time/posix_time/posix_time.hpp> #include <boost/numeric/ublas/matrix.hpp> #include <boost/numeric/ublas/matrix_proxy.hpp> #include <boost/numeric/ublas/vector.hpp> #include <boost/numeric/ublas/io.hpp> #include <boost/numeric/ublas/lu.hpp> using namespace std; using namespace boost::numeric; int main() { ublas::matrix<double> X(3,3); X.clear(); X(0,0) = 0.995182407377577; X(0,1) =-0.006473367705848; X(0,2) =-0.002032391957706; X(1,0) =-0.006473367705848; X(1,1) = 0.995182407377577; X(1,2) =-0.002032391957706; X(2,0) =-0.002032391957706; X(2,1) =-0.002032391957706; X(2,2) = 0.936175146339137; cout<<setprecision(16)<<X<<endl; cout<<ublas::lu_factorize(X)<<endl; cout<<setprecision(16)<<X<<endl; cout<<ublas::lu_factorize(X)<<endl; cout<<setprecision(16)<<X<<endl; }
Output:
[3,3]((0.995182407377577,-0.006473367705848,-0.002032391957706),(-0.006473367705848,0.995182407377577,-0.002032391957706),(-0.002032391957706,-0.002032391957706,0.936175146339137)) 0 [3,3]((0.995182407377577,-0.006473367705848,-0.002032391957706),(-0.006504704723334175,0.9951403000320849,-0.002045612067272957),(-0.002042230592742885,-0.002055601674665375,0.9361667907625133)) 0 [3,3]((0.995182407377577,-0.006473367705848,-0.002032391957706),(-0.006536193440632496,0.9950979888485471,-0.002058896174255709),(-0.002052116855767581,-0.002079077442455779,0.9361583394521271))
Is this fixed in newer versions?
Thanks
Michael Cortis
RA, Durham University
Change History (2)
follow-up: 2 comment:1 by , 6 years ago
comment:2 by , 5 years ago
Thanks for the explanation. Didn't realize that both L and U are combined into a single matrix.
Thanks again, Michael
Replying to 2015csb1032@…:
You interpreted the function in the wrong way, that's what the lu_factorize function does. The return value, 0 or non 0 value which you see, only specifies whether the matrix is singular or not. The return value is 0 if the matix is singular, and non 0 if the matrix is non-singular.
Now intuitively, you would think that lu_factorize should give two matrices L and U on decomposition. That's what is done in a way.
The matrix which you pass in lu_factorize(X), here X is passed by reference to lu_factorize function,which will decompose X and now, X will contain the information of the two factorized matrix L and U. Hence X is changed.
If you don't want X to be changed. Then, create another matrix Y, do Y=X and then pass Y in lu_factorize : lu_factorize(Y)It's a typical approach in LU decomposition, that the diagonal elements of L contains 1. So, the two matrices L and U are fitted into 1 matrix Y, putting L in the lower part omitting the diagonal elements, and putting U in the upper part. L and U can be extracted from Y easily (shown in code).
If, Y (after function ends) =
y1 y2 y3
y4 y5 y6
y7 y8 y9
Then, L=
1 0 0
y4 1 0
y7 y7 1
and u =
y1 y2 y3
0 y5 y6
0 0 y9
You can run the following code, it will show what I'm trying to say above.
ublas::matrix<double> X(3,3); X.clear(); X(0,0) = 0.995182407377577; X(0,1) =-0.006473367705848; X(0,2) =-0.002032391957706; X(1,0) =-0.006473367705848; X(1,1) = 0.995182407377577; X(1,2) =-0.002032391957706; X(2,0) =-0.002032391957706; X(2,1) =-0.002032391957706; X(2,2) = 0.936175146339137; ublas::matrix<double> Y(3,3); Y=X; ublas::lu_factorize(Y); ublas::matrix<double> L(3,3); L.clear(); ublas::matrix<double> U(3,3); U.clear(); for (int i=0; i<3; i++){ for (int j=0; j<3; j++){ if (i<j){ U(i,j) = Y(i,j); L(i,j) = 0; } else if (i>j){ L(i,j) = Y(i,j); U(i,j) = 0; } else if (i==j){ L(i,j) = 1; U(i,j) = Y(i,j); } } } cout << "The original matrix X :"<<endl; cout<<setprecision(16)<<X<<endl<<endl; cout << "LU_decomposed matrix in 1 matrix :"<<endl; cout<<setprecision(16)<<Y<<endl<<endl; cout << "LU_decomposed matrices in 2 diff matrix, L :"<<endl; cout<<setprecision(16)<<L<<endl<<endl; cout << "LU_decomposed matrices in 2 diff matrix, U :"<<endl; cout<<setprecision(16)<<U<<endl<<endl; ublas::matrix<double> Z(3,3); cout << "The product Z=L*U, which should be equal to X (Z=L*U=X), Z:"<<endl; axpy_prod(L, U, Z, true); cout<<setprecision(16)<<Z<<endl<<endl;Also, run the code with
X(0,0) = 1.0; X(0,1) = 2.0; X(0,2) = 3.0; X(1,0) = 4.0; X(1,1) = 5.0; X(1,2) = 6.0; X(2,0) = 7.0; X(2,1) = 8.0; X(2,2) = 9.0;instead of X(0,0) = 0.995182407377577;... for better understanding.
Replying to michael.cortis@…:
Discovered that after using lu_factorize the values of the matrix have changed!
#include <iostream> #include <boost/date_time/posix_time/posix_time.hpp> #include <boost/numeric/ublas/matrix.hpp> #include <boost/numeric/ublas/matrix_proxy.hpp> #include <boost/numeric/ublas/vector.hpp> #include <boost/numeric/ublas/io.hpp> #include <boost/numeric/ublas/lu.hpp> using namespace std; using namespace boost::numeric; int main() { ublas::matrix<double> X(3,3); X.clear(); X(0,0) = 0.995182407377577; X(0,1) =-0.006473367705848; X(0,2) =-0.002032391957706; X(1,0) =-0.006473367705848; X(1,1) = 0.995182407377577; X(1,2) =-0.002032391957706; X(2,0) =-0.002032391957706; X(2,1) =-0.002032391957706; X(2,2) = 0.936175146339137; cout<<setprecision(16)<<X<<endl; cout<<ublas::lu_factorize(X)<<endl; cout<<setprecision(16)<<X<<endl; cout<<ublas::lu_factorize(X)<<endl; cout<<setprecision(16)<<X<<endl; }Output:
[3,3]((0.995182407377577,-0.006473367705848,-0.002032391957706),(-0.006473367705848,0.995182407377577,-0.002032391957706),(-0.002032391957706,-0.002032391957706,0.936175146339137)) 0 [3,3]((0.995182407377577,-0.006473367705848,-0.002032391957706),(-0.006504704723334175,0.9951403000320849,-0.002045612067272957),(-0.002042230592742885,-0.002055601674665375,0.9361667907625133)) 0 [3,3]((0.995182407377577,-0.006473367705848,-0.002032391957706),(-0.006536193440632496,0.9950979888485471,-0.002058896174255709),(-0.002052116855767581,-0.002079077442455779,0.9361583394521271))Is this fixed in newer versions?
Thanks
Michael Cortis
RA, Durham University
You interpreted the function in the wrong way, that's what the lu_factorize function does. The return value, 0 or non 0 value which you see, only specifies whether the matrix is singular or not. The return value is 0 if the matix is singular, and non 0 if the matrix is non-singular.
Now intuitively, you would think that lu_factorize should give two matrices L and U on decomposition. That's what is done in a way.
The matrix which you pass in lu_factorize(X), here X is passed by reference to lu_factorize function,which will decompose X and now, X will contain the information of the two factorized matrix L and U. Hence X is changed.
If you don't want X to be changed. Then, create another matrix Y, do Y=X and then pass Y in lu_factorize : lu_factorize(Y)
It's a typical approach in LU decomposition, that the diagonal elements of L contains 1. So, the two matrices L and U are fitted into 1 matrix Y, putting L in the lower part omitting the diagonal elements, and putting U in the upper part. L and U can be extracted from Y easily (shown in code).
If, Y (after function ends) =
y1 y2 y3
y4 y5 y6
y7 y8 y9
Then, L=
1 0 0
y4 1 0
y7 y7 1
and u =
y1 y2 y3
0 y5 y6
0 0 y9
You can run the following code, it will show what I'm trying to say above.
Also, run the code with
Replying to michael.cortis@…: