It's hard to say whether it's a linear algebra bug, or matrix creation bug.
Could you check that the result of A = matrix(QQ,A) actually makes sense?
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On Sun, Jan 8, 2012 at 9:12 AM, Dima Pasechnik dimp...@gmail.com wrote:
It's hard to say whether it's a linear algebra bug, or matrix creation bug.
Could you check that the result of A = matrix(QQ,A) actually makes sense?
It looks ok to me:
sage: A = matrix(QQ,A)
sage: A
10 x 76 dense matrix
Sorry for replying to myself but after a bit of further digging
it appears that numpy didn't have anything to do with this.
It was just the route by which I came across the following problem:
sage: C = random_matrix(ZZ, 10, 80, distribution='uniform')
sage: C.ncols() -
I looked into it a bit and it seems to be an IML bug. Presumably 75 is some
cutoff inside IML, though I haven't verified this. You get the right answer
if you use a different backend to compute the kernel:
sage: matrix(QQ,A).right_kernel(algorithm='generic').dimension()+A.rank()
76
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This looks like a very serious bug to me. I can confirm that the bug
occurs with 4.8.alpha6 and 5.0.prealpha.
John
On 8 January 2012 13:31, Vegard Lima vegard.l...@gmail.com wrote:
Sorry for replying to myself but after a bit of further digging
it appears that numpy didn't have anything to do
On Jan 8, 8:31 am, Vegard Lima vegard.l...@gmail.com wrote:
sage: C = random_matrix(ZZ, 10, 80, distribution='uniform')
sage: C.ncols() - (C.right_kernel().dimension() + C.rank())
More specifically:
sage: C.right_kernel()
Free module of degree 80 and rank 80 over Integer Ring
Echelon basis
Just noticed the following:
sage: import numpy as np
sage: r=10
sage: c=76
sage: A = 2*np.random.randint(2, size=(r,c))-np.ones((r,c),dtype=np.int)
sage: A = matrix(QQ,A)
sage: A
10 x 76 dense matrix over Integer Ring (type 'print A.str()' to see all of
the entries)
So matrix(QQ,numpy) actually
I made a ticket here: http://trac.sagemath.org/sage_trac/ticket/12280
Hopefully we can fix this at the bug days 35.5 ;-)
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