[SciPy-dev] conversion among sparse formats
Nathan Bell
wnbell@gmail....
Fri Dec 7 21:24:01 CST 2007
I've added a small benchmark to the scipy.sparse unittests (enabled with
level 5) that compares the cost of converting among the various sparse
formats. The matrix is 900x900 with approximately 5 nonzeros per row
(5-point finite difference stencil). Using the latest SVN, you can produce
the table below with the following command:
python -c 'from scipy.sparse import test; test(5)'
Sparse Matrix Conversion
====================================================================
format | tocsr() | tocsc() | tocoo() | tolil() | todok()
--------------------------------------------------------------------
csr | 0.000002 | 0.000292 | 0.000356 | 3.460000 | n/a
csc | 0.000312 | 0.000002 | 0.000358 | 3.450000 | n/a
coo | 0.000389 | 0.000361 | 0.000002 | 3.460000 | n/a
lil | 0.024000 | 0.024000 | 0.022000 | 3.540000 | n/a
dok | 0.027500 | 0.060000 | 0.025000 | 3.510000 | n/a
The numbers are the time (in seconds) to convert a matrix in format on the
left to each of the formats using the to___() methods.
Some observations:
1) None of the formats supports todok(). Does anyone want/need this?
2) Something is definitely wrong with tolil() since the reverse conversions
(e.g. lil_matrix.tocsr()) are 100x faster.
3) Conversion among CSR/CSC/COO is relatively cheap, so it should be
leveraged when going between the 'slow' but flexible formats (lil and dok)
and the 'fast' but inflexible formats (csr/csc/coo). Specifically, when
converting any 'fast' format to a 'slow' format, you should first convert to
the most convenient 'fast' format. Conversely, when converting from a
'slow' to a 'fast' format, using another 'fast' format as an intermediate
incurs no noticable overhead.
4) lil_matrix and dok_matrix are the only construction-oriented formats we
have, so it's important that they be reasonably quick.
--
Nathan Bell wnbell@gmail.com
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