Re: [Numpy-discussion] How to tell if I succeeded to build numpy with amd, umfpack and lapack

2011-02-19 Thread Samuel John
Thanks Robin,

that makes sense and explains why I could not find any reference.

Perhaps the scipy.org wiki and install instructions should be updated.
I mean how many people try to compile amd and umfpack, because they
think it's good for numpy to have them, because the site.cfg contains
those entries!

To conclude: numpy does *NOT* use umfpack or libamd at all. Those
sections in the site.cfg are outdated.
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Re: [Numpy-discussion] How to tell if I succeeded to build numpy with amd, umfpack and lapack

2011-02-18 Thread Robin
I think numpy doesn't use umfpack. scipy.sparse used to, but now the
umfpack stuff has been moved out to a scikit.
So you probably won't see anything about those libraries, but if you
install scikits.umfpack and it works then you must be linked
correctly.

Cheers

Robin

On Fri, Feb 18, 2011 at 11:32 AM, Samuel John  wrote:
> Ping.
>
> How to tell, if numpy successfully build against libamd.a and libumfpack.a?
> How do I know if they were successfully linked (statically)?
> Is it possible from within numpy, like show_config() ?
> I think show_config() has no information about these in it :-(
>
> Anybody?
>
> Thanks,
>  Samuel
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Re: [Numpy-discussion] How to tell if I succeeded to build numpy with amd, umfpack and lapack

2011-02-18 Thread Chris Colbert
It certainly does. Here is mine, showing that numpy is linked against mkl:

In [2]: np.show_config()
lapack_opt_info:
libraries = ['mkl_lapack95', 'mkl_intel', 'mkl_intel_thread',
'mkl_core', 'mkl_p4m', 'mkl_p4p', 'pthread']
library_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/lib']
define_macros = [('SCIPY_MKL_H', None)]
include_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/include']
blas_opt_info:
libraries = ['mkl_intel', 'mkl_intel_thread', 'mkl_core', 'mkl_p4m',
'mkl_p4p', 'pthread']
library_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/lib']
define_macros = [('SCIPY_MKL_H', None)]
include_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/include']
lapack_mkl_info:
libraries = ['mkl_lapack95', 'mkl_intel', 'mkl_intel_thread',
'mkl_core', 'mkl_p4m', 'mkl_p4p', 'pthread']
library_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/lib']
define_macros = [('SCIPY_MKL_H', None)]
include_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/include']
blas_mkl_info:
libraries = ['mkl_intel', 'mkl_intel_thread', 'mkl_core', 'mkl_p4m',
'mkl_p4p', 'pthread']
library_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/lib']
define_macros = [('SCIPY_MKL_H', None)]
include_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/include']
mkl_info:
libraries = ['mkl_intel', 'mkl_intel_thread', 'mkl_core', 'mkl_p4m',
'mkl_p4p', 'pthread']
library_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/lib']
define_macros = [('SCIPY_MKL_H', None)]
include_dirs =
['/Library/Frameworks/Python.framework/Versions/1.3.0/include']

If those lists are empty for you, then numpy is not linked properly (of
course yours will be ATLAS and not mkl)

On Fri, Feb 18, 2011 at 5:32 AM, Samuel John  wrote:

> Ping.
>
> How to tell, if numpy successfully build against libamd.a and libumfpack.a?
> How do I know if they were successfully linked (statically)?
> Is it possible from within numpy, like show_config() ?
> I think show_config() has no information about these in it :-(
>
> Anybody?
>
> Thanks,
>  Samuel
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>
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Re: [Numpy-discussion] How to tell if I succeeded to build numpy with amd, umfpack and lapack

2011-02-18 Thread Samuel John
Ping.

How to tell, if numpy successfully build against libamd.a and libumfpack.a?
How do I know if they were successfully linked (statically)?
Is it possible from within numpy, like show_config() ?
I think show_config() has no information about these in it :-(

Anybody?

Thanks,
 Samuel
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Re: [Numpy-discussion] How to tell if I succeeded to build numpy with amd, umfpack and lapack

2011-01-27 Thread Samuel John
Hi Paul,

thanks for your answer! I was not aware of numpy.show_config().

However, it does not say anything about libamd.a and libumfpack.a, right?
How do I know if they were successfully linked (statically)?
Does anybody have a clue?

greetings
 Samuel
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Re: [Numpy-discussion] How to tell if I succeeded to build numpy with amd, umfpack and lapack

2011-01-26 Thread Paul Ivanov
Samuel John, on 2011-01-26 15:08,  wrote:
> Hi there!
> 
> I have successfully built numpy 1.5 on ubuntu lucid (32 for now).
> I think I got ATLAS/lapack/BLAS support, and if I
> >  ldd linalg/lapack_lite.so
> I see that my libptf77blas.so etc. are successfully linked. :-)
> 
> However, how to I find out, if (and where) libamd.a and libumfpack.a
> have been found and (statically) linked.
> As far as I understand, I they are not present, a fallback in pure
> python is used, right?
> 
> Is there a recommended way, I can query against which libs numpy has
> been built?
> So I can be sure numpy uses my own compiled versions of libamd, lapack
> and so forth.

Hi Samuel,

take a look at numpy.show_config() and scipy.show_config() 

best,
-- 
Paul Ivanov
314 address only used for lists,  off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7 


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[Numpy-discussion] How to tell if I succeeded to build numpy with amd, umfpack and lapack

2011-01-26 Thread Samuel John
Hi there!

I have successfully built numpy 1.5 on ubuntu lucid (32 for now).
I think I got ATLAS/lapack/BLAS support, and if I
>  ldd linalg/lapack_lite.so
I see that my libptf77blas.so etc. are successfully linked. :-)

However, how to I find out, if (and where) libamd.a and libumfpack.a
have been found and (statically) linked.
As far as I understand, I they are not present, a fallback in pure
python is used, right?

Is there a recommended way, I can query against which libs numpy has
been built?
So I can be sure numpy uses my own compiled versions of libamd, lapack
and so forth.

And the fftw3 is no longer supported, I guess (even if it is still
mentioned in the site.cfg.example)

Bests,
 Samuel


-- 
Dipl.-Inform. Samuel John
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PhD student, CoR-Lab(.de) and
Neuroinformatics Group, Faculty
of Technology, D33594 Bielefeld
in cooperation with the HONDA
Research Institute Europe GmbH


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