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From: Sonia Singhal <sonia.singhal@gm...>  20061216 02:53:29

Hi, I am doing development in Microsoft Visual Studio 2003. I have been using lapackpp2.5.0 for solving linear system of equations and doing SVD. Recently I started using an open source optimization package IPOpt to solve an optimization problem. This library uses certain routines in BLAS, LAPACK, HSL. The problem is that my code crashes in the lapackpp's call to LaSVD_IP(). It crashes giving a "floating point underflow" error. This doesnt happen if I remove ipopt's libs and code. I havnt really written any code for calling this optimization library, just instantiated its class just to see link the ipopt infrastructure into my existing code. I have used IPOpt earlier but then wasnt using lapackpp and ipopt worked fine. I have posted this question on the ipopt forum too. I am posting here too just in case anyone has any idea of what the problem could be. Thanks, ~ sonia 
From: Christian Stimming <stimming@tu...>  20061215 09:18:12

BEGIN PGP SIGNED MESSAGE Hash: SHA1 Good to hear. Feel free to ask more questions if something appears to be wrong. By the way you should be able to write std::cout<<U_; as well. Regarding the mailing list address: This is a "mailing list", not a "forum". You have been sending your emails to the address "lapackppdevelowner (at) lists.sourceforge.net" which is wrong; the correct email address to send your messages to is lapackppdevel@... (no owner)! Thanks. Christian Sonia Singhal schrieb: > hi, > > I think I caught my mistake. I didnt make a copy of the matrix before I > checked for the homogenous solution. :( > ~ sonia > > On 12/14/06, *Sonia Singhal * <sonia.singhal@... > <mailto:sonia.singhal@...>> wrote: > > Hi, > > Thanks for the reply. > As for posting it on the forum. I had sent the mail to the forum, I > have no clue how you have received the mail. I initially emailed it > without joining the list and got an error message, maybe thats the > reason you got it. > > As for the problem, even I am not familiar with the algorithms used > for svd and am not sure if the null spaces would be the same, but I > assumed that since MATLAB also uses LAPACK the answers would be the > same. > Even if the answers are not the same and I assume that the NULL > spaces are returned, then multiplying the original matrix A with a > row ( or column ) of VT ( or V ) beyond the rank should be zero. I > did this and I got a very high value when I used Norm_Inf(). Whereas > in MATLAB I get a very small value ( 10^14). > > Also right now I was making small examples ( 3x4, 3x5 ) and what I > found was for some examples I am getting right answers and for some > they are wrong. By right and wrong I mean comparing both with matlab > and checking if A*VT(r,:) is zero. > > For example : > This code / exmaple gives the correct answers > > // > // Trying SVD > LaGenMatDouble ForSVD(3,5); > ForSVD(0,0) = 1; > ForSVD(0,1) = 2; > ForSVD(0,2) = 3; > ForSVD(0,3) = 4; > ForSVD(0,4) = 2; > ForSVD(1,0) = 2; > ForSVD(1,1) = 3; > ForSVD(1,2) = 9; > ForSVD(1,3) = 2; > ForSVD(1,4) = 0; > ForSVD(2,0) = 4; > ForSVD(2,1) = 5; > ForSVD(2,2) = 8; > ForSVD(2,3) = 7; > ForSVD(2,4) = 4; > LaVectorDouble S_(3); > LaGenMatDouble U_(3,3), VT_(5,5); > LaSVD_IP(ForSVD, S_, U_, VT_); > LaVectorDouble x_(5); > > for(i=0; i<5; ++i){ > x_(i) = VT_(4,i); > } > std::cout << "\tNorm_Inf(A*x)" << Norm_Inf(ForSVD*x_) << > std::endl; > std::cout << "U:" << std::endl; > for(int i=0; i<3; ++i){ > for(int j=0; j<3; ++j){ > std::cout << U_(i,j) << " "; > } > std::cout << std::endl; > } > std::cout << "V:" << std::endl; > for(int i=0; i<5; ++i){ > for(int j=0; j<5; ++j){ > std::cout << VT_(i,j) << " "; > } > std::cout << std::endl; > } > > // >  > and this doesnt. > // >  > > // Trying SVD > LaGenMatDouble ForSVD(3,5); > ForSVD(0,0) = 1; > ForSVD(0,1) = 2; > ForSVD(0,2) = 3; > ForSVD(0,3) = 4; > ForSVD(1,0) = 2; > ForSVD(1,1) = 3; > ForSVD(1,2) = 9; > ForSVD(1,3) = 2; > ForSVD(2,0) = 4; > ForSVD(2,1) = 5; > ForSVD(2,2) = 8; > ForSVD(2,3) = 7; > LaVectorDouble S_(3); > LaGenMatDouble U_(3,3), VT_(4,4); > LaSVD_IP(ForSVD, S_, U_, VT_); > LaVectorDouble x_(5); > > for(i=0; i<5; ++i){ > x_(i) = VT_(4,i); > } > std::cout << "\tNorm_Inf(A*x)" << Norm_Inf(ForSVD*x_) << > std::endl; > std::cout << "U:" << std::endl; > for(int i=0; i<3; ++i){ > for(int j=0; j<3; ++j){ > std::cout << U_(i,j) << " "; > } > std::cout << std::endl; > } > std::cout << "V:" << std::endl; > for(int i=0; i<4; ++i){ > for(int j=0; j<4; ++j){ > std::cout << VT_(i,j) << " "; > } > std::cout << std::endl; > } > // >  > Thanks for your time, > ~ Sonia BEGIN PGP SIGNATURE Version: GnuPG v1.4.2.1 (MingW32) Comment: Using GnuPG with Mozilla  http://enigmail.mozdev.org iQCVAwUBRYJoP2XAi+BfhivFAQKzCQP7BvwUeKqGlbLSYrh2rVbWoy7yAFjYD5AT cBVEPecyYR1sX5ZN1Dj3CPRquGB1GcNexlnQfPJ9Tnawc4ZY4djjZa7BtOxXFzJq ZEfXlXbRiR1emMi/ikW5DLvvWPrkUGz9uCeA1MTIppL6xtcyd4Lui9PygAL+rrhq u19NPB9Le8k= =aaop END PGP SIGNATURE 
From: Christian Stimming <stimming@tu...>  20061215 09:14:12

BEGIN PGP SIGNED MESSAGE Hash: SHA1 (Please always write to the mailing list lapackppdevel, never to individual developers!) settingyin schrieb: > Stimming, >=20 > Hello! I=A1=AFm using LAPACK++,but something comfused me. > > I want to get A .* B=20 >=20 > A=3D 1 2 =20 > 3 4 =20 > B=3D3 2 > 4 4 > A .* B=3D 3 4 > 12 16 >=20 > But I can=A1=AFt get it direcly. I don't fully understand your question, but if you mean you want to have an "elementwise multiplication", then indeed this is *not* available in lapackpp. The reason is that lapackpp is merely a wrapper to the functionality that is offered by the numerical libraries LAPACK and BLAS, and those don't have this operation (probably because in numerics this operation is really never used). You will have to program it yoursel= f. Christian BEGIN PGP SIGNATURE Version: GnuPG v1.4.2.1 (MingW32) Comment: Using GnuPG with Mozilla  http://enigmail.mozdev.org iQCVAwUBRYJnWmXAi+BfhivFAQLFyAP/Qb/m7jragdiss7pyLUyd/NzDjt1Ib2XZ /MdjU0p1BQfML9ZLIN1GX2W0C7uL8PiDvoANeIUiNPp6zqaqfw3s/KJLjqJ/lDvc tUSM2LtLgmbuH8X1yWSkaW/7SpSoonQaYdXV4cyK+7u/Akk1eOzF05nE00ukfPc7 vWCWmowRJ+E=3D =3DAkCa END PGP SIGNATURE 
From: Christian Stimming <stimming@tu...>  20061214 20:47:58

(Please send your message to "lapackppdevel", not owner. Thanks.) Am Donnerstag, 14. Dezember 2006 21:18 schrieb Sonia Singhal: > Hi, > I am using the LAPACKPP on Windows with Visual Studio. I downloaded it a > couple of days back and am using the 2.5.0 version. > > I am using LaSVD_IP() to find the null space of a matrix. My matrix is with > m<n. I was getting wrong answers. > I dumped the U, S, VT matrices generated by the above call and checked it > with Matlab results. > Apparently, the U and V( orVT) matrix columns are fine upto the rank of the > matrix. Beyond that they are all messed up, hence my null space is > incorrect. I'm not so sure you are expecting the right thing here. As you said, the singular vectors for the nonnull singular values are as expected. However, the rest of the U and VT matrices, as I understand SVD, are quite ambiguous, given that they only have to span the null space. So as long as these vectors span that space, they can be totally different. As far as I understand it, you would have to check whether the spanned space of all these vectors from lapackpp is identical to the space spanned by the matlab vectors (I don't have a good check for that at hand, but surely one can think of something appropriate). > Has this been observed by someone else ? Am I doing something wrong here ? > the way I set up my matrices is > U  m*m > VT  n*n > S  min(m,n) . I have tried n also as in my case m<n. > A matrix is m*n I think everything is working fine here  you would have gotten clear error messages if any of these matrices were of wrong dimension. Christian 