KarlI have the following reduction that I can do in Eigen. Is there something
similar that I can do in ViennaCL? RMMatrix_Float v =
(prod.block(0,0,rows,cols).rowwise() -
aVector.transpose());RMSparseMatrix_Float v1 =
v.unaryExpr(std::ptr_fun(clip_lower)).sparseView();
Essentially, I am subtracting a row vector from every rows of a matrix. Then, I
am applying a unary operation (soft threshold for example) on every pixel and
making the matrix sparse.
RMMatrix_Float is a typedef for a row-major Eigen Dense matrix; SparseMatrix
being its sparse equivalenth
Thanks and Regards
Sumit
From: Karl Rupp <r...@iue.tuwien.ac.at>
To: Charles Determan <cdeterma...@gmail.com>
Cc: viennacl-devel@lists.sourceforge.net
Sent: Wednesday, July 15, 2015 1:53 AM
Subject: Re: [ViennaCL-devel] ViennaCL eigenvectors?
Hi Charles,
> Everything appears to be working correctly with the power method. A
> followup though, is it possible to return 'all' eigenvalues and
> eigenvectors with the power algorithm?
No, it only provides the largest eigenvalue in modulus.
> The Lanczos example (in the
> feature-improve-lanczos branch) code looks like it would iterate through
> all eigenvalues and eigenvectors. For example, with a trivial matrix of
> size 4x4 I would expect to get 4 eigenvalues and 4 eigenvectors (of
> length 4, i.e. a matrix of 16 elements).
Lanczos is typically used for obtaining estimates on the largest
eigenvalues of a huge matrix (say, the largest 10). There is actually an
implementation of the QR method for finding all eigenvalues of a
symmetric matrix available, too, cf.
https://github.com/viennacl/viennacl-dev/blob/master/examples/tutorial/qr_method.cpp
(I need to check why it does not show up in the manual)
> This leads me to another question, I didn't see a merge between the
> Lanczos algorithm. Is that still under development or is it now
> implemented in the master branch?
Some parts currently experience a final polishing (for example,
yesterday I eliminated the Boost dependency), so it will migrate to
master soon. :-)
Best regards,
Karli
> On Fri, Jul 10, 2015 at 4:20 AM, Karl Rupp <r...@iue.tuwien.ac.at
> <mailto:r...@iue.tuwien.ac.at>> wrote:
>
> Hi Charles,
>
> the interface for the power iteration has been updated to also
> return eigenvectors:
>
https://github.com/viennacl/viennacl-dev/commit/e80cc2141f266eb9b279dd45b7c4075b557bf558
>
> Please let me know if you run into issues.
>
> Best regards,
> Karli
>
>
>
> On 07/08/2015 06:58 PM, Charles Determan wrote:
>
> Greetings,
>
> I have seen that I can get all the eigenvalues with the lanczos
> algorithm in the lanczos.cpp example file but I don't see any
> documentation on eigenvectors. The only thing I have found is
> on the
> feature-improve-lanczos branch
>
https://github.com/viennacl/viennacl-dev/blob/karlrupp/feature-improve-lanczos/examples/tutorial/lanczos.cpp.
> Is this intended to be implemented or is there existing
support for
> determining eigen vectors?
>
> A secondary question, is the same possible with the power method?
>
> Thanks,
> Charles
>
>
>
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