Hello,
Are you running a 64-bit machine?
I looked at the code, and the problem seems to come from the fact that
it is doing a naive check on the type of the numpy array; it is
currently assuming that your float32 array is a float64 array which is
why you are getting the strange results you are. See below:
sage: a = numpy.array([[1,2,3],[4,5,6],[7,8,9]],float)
sage: a.dtype
dtype('float64')
sage: matrix(a)
[1.0 2.0 3.0]
[4.0 5.0 6.0]
[7.0 8.0 9.0]
sage: a = numpy.array([[1,2,3],[4,5,6],[7,8,9]],'float64')
sage: a.dtype
dtype('float64')
sage: matrix(a)
[1.0 2.0 3.0]
[4.0 5.0 6.0]
[7.0 8.0 9.0]
sage: a = numpy.array([[1,2,3],[4,5,6],[7,8,9]],'float32')
sage: a.dtype
dtype('float32')
sage: matrix(a)
[ 2.00000047311 512.000122547 8192.0019722]
[ 131072.031677 2.34082748762e-310 0.0]
[3.16202013338e-322 4.74797085653e-321 4.94065645841e-324]
I will submit a trac ticket, and post a patch for you later tonight.
Thanks for the report!
--Mike
On 10/11/07, adrianmatematico <[EMAIL PROTECTED]> wrote:
>
> When I call matrix(a) and a is a numpy array, things do not work:
>
> sage: import numpy
> sage: a=numpy.array([[1,2,3],[4,5,6],[7,8,9]],'f')
> sage: a
>
> array([[ 1., 2., 3.],
> [ 4., 5., 6.],
> [ 7., 8., 9.]], dtype=float32)
> sage: matrix(a)
>
> [ 2.00000047311 512.000122547 8192.0019722]
> [ 131072.031677 6.64723988631e-312 9.63032207325e-270]
> [ nan 6.01334411715e-154 1.20061630269e+195]
> sage: b=matrix(a)
> sage: b
>
> [ 2.00000047311 512.000122547 8192.0019722]
> [ 131072.031677 6.64723988631e-312 9.63032207325e-270]
> [ nan 6.01334411715e-154 1.20061630269e+195]
> sage:
>
>
> >
>
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