[SciPy-user] scipy.sparse.lil_matrix and fancy indexing
Anne Archibald
peridot.faceted@gmail....
Sun Feb 3 16:29:23 CST 2008
Hi,
It looks to me like there's an inconsistency between how numpy
matrices handle fancy indexing and how scipy.sparse.lil_matrix handles
fancy indexing:
In [15]: A = N.zeros((3,3))
In [16]: A[[0,1,2],[0,1,2]] = 1
In [18]: A
Out[18]:
array([[ 1., 0., 0.],
[ 0., 1., 0.],
[ 0., 0., 1.]])
In [19]: B = scipy.sparse.lil_matrix((3,3))
In [21]: B[[0,1,2],[0,1,2]] = [1,1,1]
In [22]: print B
(0, 0) 1
(0, 1) 1
(0, 2) 1
(1, 0) 1
(1, 1) 1
(1, 2) 1
(2, 0) 1
(2, 1) 1
(2, 2) 1
In [23]: B-A
Out[23]:
matrix([[ 0., 1., 1.],
[ 1., 0., 1.],
[ 1., 1., 0.]])
(Fancy indexing also does not accept scalars, but that's presumably
just not been implemented yet.)
In light of the following, this seems like unintended behaviour:
In [24]: B[[0,1,2],[0,1,2]] = [1,2,3]
In [25]: p B
(0, 0) 1
(0, 1) 1
(0, 2) 1
(1, 0) 2
(1, 1) 2
(1, 2) 2
(2, 0) 3
(2, 1) 3
(2, 2) 3
At the least, I can't see why I would have expected this result.
Is this intended behaviour? Failure to raise an exception on bad
input? Just a bug?
Thanks,
Anne
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