On Thu, Jan 7, 2010 at 11:10 PM, Bruce Southey wrote:
> On Thu, Jan 7, 2010 at 3:45 PM, Christopher Barker
> wrote:
>> Bruce Southey wrote:
wrote:
>>
>>> Using the numpy NaN or similar (noting R's approach to missing values
>>> which in turn allows it to have the above functionality) is jus
On Thu, Jan 7, 2010 at 3:45 PM, Christopher Barker
wrote:
> Bruce Southey wrote:
>>> wrote:
>
>> Using the numpy NaN or similar (noting R's approach to missing values
>> which in turn allows it to have the above functionality) is just a
>> very bad idea for missing values because you always have
Hi,
I don't know if many people are aware of it, but I have recently
discovered perf, a tool available from the kernel sources. It is
extremely simple to use, and very useful when looking at numpy/scipy
perf issues in compiled code. For example, I can get this kind of
results for looking at the nu
On Fri, Jan 8, 2010 at 11:24 AM, David Warde-Farley wrote:
> On 5-Jan-10, at 7:18 PM, Christopher Barker wrote:
>
>> If distutils/setuptools could identify the python version properly,
>> then
>> binary eggs and easy-install could be a solution -- but that's a
>> mess,
>> too.
>
>
> Long live toy
On 2010-01-07, David Warde-Farley wrote:
> On 5-Jan-10, at 7:02 PM, Christopher Barker wrote:
>>> I'm not really a fan of packages polluting /usr/local, I'd rather the
>>> tree appear /opt/packagename
>>
>> well, /opt has kind of been co-opted by macports.
>
> I'd forgotten about that.
It's not
On 5-Jan-10, at 7:02 PM, Christopher Barker wrote:
>> Pretty sure the python.org binaries are 32-bit only. I still think
>> it's sensible to prefer the
>
> waiting the rest of this sentence.. ;-)
I had meant to say 'sensible to prefer the Python.org version' though
in reality I'm a little miffe
On 5-Jan-10, at 7:18 PM, Christopher Barker wrote:
> If distutils/setuptools could identify the python version properly,
> then
> binary eggs and easy-install could be a solution -- but that's a
> mess,
> too.
Long live toydist! :)
David
___
NumP
On 7-Jan-10, at 8:13 PM, Xue (Sue) Yang wrote:
> This is what I had (when I built numpy, I chose gnu compilers
> instead of
> intel compilers),
>
numpy.show_config()
> lapack_opt_info:
>libraries = ['mkl_lapack', 'mkl', 'vml', 'guide', 'pthread']
>library_dirs = ['/usr/physics/intel
Christopher Barker wrote:
> David Cournapeau wrote:
>> On Thu, Jan 7, 2010 at 1:35 AM, Christopher Barker
>>> In the past, I think folks' have used the default
>>> name provided by bdist_mpkg, and those are not always clear. Something like:
>>>
>>>
>>> numpy1.4-osx10.4-python.org2.6-32bit.dmg
>> Th
OK,
I'm trying to dig into the code and figure out how to get it to stop
putting in zeros for missing data with fromfile()/fromstring() text reading.
It looks like the culprit is this, in arraytypes.c.src:
@fn...@_scan(FILE *fp, @type@ *ip, void *NPY_UNUSED(ignore),
PyArray_Descr *NPY_UNUSED(
This is what I had (when I built numpy, I chose gnu compilers instead of
intel compilers),
>>> numpy.show_config()
lapack_opt_info:
libraries = ['mkl_lapack', 'mkl', 'vml', 'guide', 'pthread']
library_dirs = ['/usr/physics/intel/mkl/lib/32']
define_macros = [('SCIPY_MKL_H', None)]
On 7-Jan-10, at 6:58 PM, Xue (Sue) Yang wrote:
> Do I need any specifications when I run numpy with intel MKL (MKL9.1)?
> numpy developers would be able to answer this question?
Are you sure you've compiled against MKL properly? What is printed by
numpy.show_config()?
David
___
I understand that intel mkl uses openMP parallel model. Therefore I set
environment variable
>>os.environ['OMP_NUM_THREADS'] = '4'
With same test example, however, still one cpu is used.
Do I need any specifications when I run numpy with intel MKL (MKL9.1)?
numpy developers would be able to a
josef.p...@gmail.com wrote:
>>> +1 (much preferrable to insert NaN or other user value than raise
>>> ValueError in my opinion)
>> But raise an error for integer types?
>>
>> I guess this is still up the air -- no consensus yet.
>
> raise an exception, I hate the silent cast of nan to integer z
On Thu, Jan 7, 2010 at 4:45 PM, Christopher Barker
wrote:
> Bruce Southey wrote:
>>> wrote:
>
>> Using the numpy NaN or similar (noting R's approach to missing values
>> which in turn allows it to have the above functionality) is just a
>> very bad idea for missing values because you always have
On Wed, Jan 6, 2010 at 11:35 AM, Christopher Barker
wrote:
>
> It's worse to have a binary you expect to work fail for you than to not
> have one available. IN the past, I think folks' have used the default
> name provided by bdist_mpkg, and those are not always clear. Something like:
>
>
> numpy1
On Thu, Jan 7, 2010 at 15:54, James Mazer wrote:
> Hi,
>
> I've got a some Numeric arrays that were created without
> an explicit byte size in the initial declaration and pickled.
> Something like this:
>
> >>> cPickle.write(array(ones((3,3,)), 'f'), open('foo.pic', 'w'))
>
> as opposed to:
>
>
Hi,
I've got a some Numeric arrays that were created without
an explicit byte size in the initial declaration and pickled.
Something like this:
>>> cPickle.write(array(ones((3,3,)), 'f'), open('foo.pic', 'w'))
as opposed to:
>>> cPickle.write(array(ones((3,3,)), Float32), open('foo.pic',
Bruce Southey wrote:
>> wrote:
> Using the numpy NaN or similar (noting R's approach to missing values
> which in turn allows it to have the above functionality) is just a
> very bad idea for missing values because you always have to check that
> which NaN is a missing value and which was due to
On Jan 7, 2010, at 2:32 PM, josef.p...@gmail.com wrote:
> On Thu, Jan 7, 2010 at 3:08 PM, Christopher Barker
> wrote:
>> Pauli Virtanen wrote:
>>> ma, 2010-01-04 kello 17:05 -0800, Christopher Barker kirjoitti:
>>> it also does odd things with spaces
embedded in the separator:
",
On Thu, Jan 7, 2010 at 2:32 PM, wrote:
> On Thu, Jan 7, 2010 at 3:08 PM, Christopher Barker
> wrote:
>> Pauli Virtanen wrote:
>>> ma, 2010-01-04 kello 17:05 -0800, Christopher Barker kirjoitti:
>>> it also does odd things with spaces
embedded in the separator:
", $ #" matches all
On Thu, Jan 7, 2010 at 3:08 PM, Christopher Barker
wrote:
> Pauli Virtanen wrote:
>> ma, 2010-01-04 kello 17:05 -0800, Christopher Barker kirjoitti:
>> it also does odd things with spaces
>>> embedded in the separator:
>>>
>>> ", $ #" matches all of: ",$#" ", $#" ",$ #"
>
>> That's a documente
Pauli Virtanen wrote:
> ma, 2010-01-04 kello 17:05 -0800, Christopher Barker kirjoitti:
> it also does odd things with spaces
>> embedded in the separator:
>>
>> ", $ #" matches all of: ",$#" ", $#" ",$ #"
> That's a documented feature:
Fair enough.
OK, I've written a patch that allows newl
David Cournapeau wrote:
> On Thu, Jan 7, 2010 at 1:35 AM, Christopher Barker
>> In the past, I think folks' have used the default
>> name provided by bdist_mpkg, and those are not always clear. Something like:
>>
>>
>> numpy1.4-osx10.4-python.org2.6-32bit.dmg
>
> The 32 bits is redundant - we supp
Hi,
I am new to this list, but I have been using scipy for a couple of
months now with great satisfaction.
Currently I have a problem:
I diagonalize a hermitian complex matrix using the eigh routine from
scipy.linalg (this is still a numpy question, see below)
This returns the eigenvectors as
> Sturla Molden wrote:
>> I would suggest using GotoBLAS instead of ATLAS.
>
>> http://www.tacc.utexas.edu/tacc-projects/
>
> That does look promising -- nay idea what the license is? They don't
> make it clear on the site
UT TACC Research License (Source Code)
The Texas Advanced Computing Ce
Sturla Molden wrote:
> I would suggest using GotoBLAS instead of ATLAS.
> http://www.tacc.utexas.edu/tacc-projects/
That does look promising -- nay idea what the license is? They don't
make it clear on the site (maybe it it is you set up a user account and
download, but I'd rather know up front
On 12/12/2009 22:55, T J wrote:
> Hi,
>
> Suppose I have an array of shape: (n, k, k). In this case, I have n
> k-by-k matrices. My goal is to compute the product of a (potentially
> large) user-specified selection (with replacement) of these matrices.
> For example,
>
> x = [0,1,2,1,3,3,2,1
> I also tried to Install numpy with intel mkl 9.1
> I still used gfortran for numpy installation as intel mkl 9.1 supports gnu
> compiler.
I would suggest using GotoBLAS instead of ATLAS. It is easier to build
then ATLAS (basically no configuration), and has even better performance
than MKL.
ht
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