Not sure if this can help someone out, but this site here contains a lot
of 32- and 64-bit installers for several Python packages, including
Pysparse, Numpy and many others. A very useful repository indeed.
Fausto
On Tuesday, January 21, 2014 10:08:23 PM, Caleb Hattingh
<[email protected]> wrote:
On 22 January 2014 06:14, Daniel Wheeler <[email protected]> wrote:
>
>On Sat, Jan 18, 2014 at 5:03 PM, Phillip Feldman
>>
>>> TypeError: Cannot cast array data from dtype('int64') to dtype('int32')
>>> according to the rule 'safe'
>>
>>It seems like an inconsistency between PySparse and Numpy. You may be
>>using a 64 bit Numpy with FiPy, but a version of PySparse that was
>>built with a 32 bit Numpy. A gruesome hack to fix this requires
>>changing the line above from
>>
>> self.matrix.update_add_at(vector, id1, id2)
>>
>>to
>>
>> self.matrix.update_add_at(vector, id1.astype('int32'), id2.astype('int64'))
>>
>>You may have to do this in more than one place, which could get ugly.
>>
>
>
>There will be other problems. There were similar issues in FiPy itself,
>please see
>
>
>http://matforge.org/fipy/ticket/645
>
>
>
>I had a (very) quick look at the PySparse source. It is relatively easy to
>fix the numpy array dtypes, but you're going to find that "int" occurs an
>awful lot in the pysparse code, and as the ticket above indicates, "int" on
>Windows x86-64 is *still* 32 bit. This can lead to a lot of frustration.
>
>An alternative is to just use the Scipy solvers, so at the command
>>line use "python mesh2D.py --scipy" to stipulate the Scipy solvers.
>>
>
>
>I could not get pysparse working, so I use the scipy solvers. I really don't
>know C too well, otherwise I would have taken a better crack at fixing it. (I
>*think* changing all the "int" types to "size_t" could fix these issues, but
>I'm not sure and haven't tried it. "size_t" correctly reflects the change
>between a 32bit and 64bit binary on Windows.)
>
>
>
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