ENH: Add structural rank to sparse.csgraph
Greetings, I was recently looking for a quick way to find out if a given sparse matrix is singular. As it turns out the solution is to calculate the structural rank (an upper bound on the numerical rank) of the sparsity pattern associated with the matrix: http://www.mathworks.com/help/matlab/ref/sprank.html <http://www.mathworks.com/help/matlab/ref/sprank.html> http://www.cise.ufl.edu/research/sparse/matrices/legend.html <http://www.cise.ufl.edu/research/sparse/matrices/legend.html> Since this calculation is done via the maximum bipartite matching algorithm that I added to sparse.csgraph some time ago, I thought it would be a nice addition to include this straightforward structural rank calculation. The Pull for this feature is here: https://github.com/scipy/scipy/pull/6680 <https://github.com/scipy/scipy/pull/6680> Best regards, Paul
On Fri, Oct 14, 2016 at 6:56 AM, Paul Nation <nonhermitian@gmail.com> wrote:
Greetings,
I was recently looking for a quick way to find out if a given sparse matrix is singular. As it turns out the solution is to calculate the structural rank (an upper bound on the numerical rank) of the sparsity pattern associated with the matrix:
http://www.mathworks.com/help/matlab/ref/sprank.html
http://www.cise.ufl.edu/research/sparse/matrices/legend.html
Since this calculation is done via the maximum bipartite matching algorithm that I added to sparse.csgraph some time ago, I thought it would be a nice addition to include this straightforward structural rank calculation.
The Pull for this feature is here: https://github.com/ scipy/scipy/pull/6680
Thanks Paul. It looks like a nice addition. There's a reasonable amount of use in the literature, and the implementation is straightforward. So +1 from me. Cheers, Ralf
participants (2)
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Paul Nation
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Ralf Gommers