Brian Granger wrote:
>> I am curious: would you know what would be different in numpy's case
>> compared to matlab array model concerning locks ? Matlab, up to
>> recently, only spreads BLAS/LAPACK on multi-cores, but since matlab 7.3
>> (or 7.4), it also uses multicore for mathematical functions (
>> Good point. Is it possible to tell what array size it switches over
>> to using multiple threads?
>
> Yes.
>
> http://svn.scipy.org/svn/numpy/branches/multicore/numpy/core/threadapi.py
Sorry, I was curious about what Matlab does in this respect. But,
this is very useful and I will look at it.
On Thu, Feb 12, 2009 at 00:52, Brian Granger wrote:
>> I am curious: would you know what would be different in numpy's case
>> compared to matlab array model concerning locks ? Matlab, up to
>> recently, only spreads BLAS/LAPACK on multi-cores, but since matlab 7.3
>> (or 7.4), it also uses multic
> I am curious: would you know what would be different in numpy's case
> compared to matlab array model concerning locks ? Matlab, up to
> recently, only spreads BLAS/LAPACK on multi-cores, but since matlab 7.3
> (or 7.4), it also uses multicore for mathematical functions (cos,
> etc...). So at lea
On Thu, Feb 12, 2009 at 00:15, David Cournapeau
wrote:
> Gael Varoquaux wrote:
>> >From a programmer's perspective, because, IMHO, openmp is implemented
>> using pthreads.
>
> Since openmp also exists on windows, I doubt that it is required that
> openmp uses pthread :)
It is implemented using th
Gael Varoquaux wrote:
> >From a programmer's perspective, because, IMHO, openmp is implemented
> using pthreads.
Since openmp also exists on windows, I doubt that it is required that
openmp uses pthread :)
On linux, with gcc, using -fopenmp implies -pthread, so I guess it uses
pthread (can you b
Robert Kern wrote:
>
> Eric Jones tried to do this with pthreads in C some time ago. His work is
> here:
>
> http://svn.scipy.org/svn/numpy/branches/multicore/
>
> The lock overhead makes it usually not worthwhile.
>
I am curious: would you know what would be different in numpy's case
compar
On Wed, Feb 11, 2009 at 11:52:40PM -0600, Robert Kern wrote:
> > This seem like pretty heavy solutions though.
> >From a programmer's perspective, it seems to me like OpenMP is a muck
> >lighter weight solution than pthreads.
>From a programmer's perspective, because, IMHO, openmp is implemented
On Thu, Feb 12, 2009 at 00:03, Brian Granger wrote:
>> Eric Jones tried to do this with pthreads in C some time ago. His work is
>> here:
>>
>> http://svn.scipy.org/svn/numpy/branches/multicore/
>>
>> The lock overhead makes it usually not worthwhile.
>
> I was under the impression that Eric's i
On Wed, Feb 11, 2009 at 6:17 PM, David Cournapeau wrote:
> Unfortunately, it does require some work, because hardy uses g77
> instead of gfortran, so the source package has to be different (once
> hardy is done, all the one below would be easy, though). I am not sure
> how to do that with PPA (th
> Eric Jones tried to do this with pthreads in C some time ago. His work is
> here:
>
> http://svn.scipy.org/svn/numpy/branches/multicore/
>
> The lock overhead makes it usually not worthwhile.
I was under the impression that Eric's implementation didn't use a
thread pool. Thus I thought the bo
> 2009/2/12 A B :
> Actually, I was using two different machines and it appears that the
> version of numpy available on Ubuntu is seriously out of date (1.0.4).
> Wonder why ...
See the recent post here
http://projects.scipy.org/pipermail/numpy-discussion/2009-February/040252.html
Cheers,
Scott
On Wed, Feb 11, 2009 at 23:46, Brian Granger wrote:
> Hi,
>
> This is relevant for anyone who would like to speed up array based
> codes using threads.
>
> I have a simple loop that I have implemented using Cython:
>
> def backstep(np.ndarray opti, np.ndarray optf,
> int istart, int ie
Thanks much!
Brian
On Wed, Feb 11, 2009 at 9:44 PM, Stéfan van der Walt wrote:
> 2009/2/6 Brian Granger :
>> Great, what is the best way of rolling this into numpy?
>
> I've committed your patch.
>
> Cheers
> Stéfan
> ___
> Numpy-discussion mailing lis
Hi,
This is relevant for anyone who would like to speed up array based
codes using threads.
I have a simple loop that I have implemented using Cython:
def backstep(np.ndarray opti, np.ndarray optf,
int istart, int iend, double p, double q):
cdef int j
cdef double *pi
cde
2009/2/6 Brian Granger :
> Great, what is the best way of rolling this into numpy?
I've committed your patch.
Cheers
Stéfan
___
Numpy-discussion mailing list
Numpy-discussion@scipy.org
http://projects.scipy.org/mailman/listinfo/numpy-discussion
On Wed, Feb 11, 2009 at 23:24, A B wrote:
> Hi,
>
> I have the following data structure:
>
> col1 | col2 | col3
>
> 20080101|key1|4
> 20080201|key1|6
> 20080301|key1|5
> 20080301|key2|3.4
> 20080601|key2|5.6
>
> For each key in the second column, I would like to create an array
> where for all uni
Stéfan van der Walt wrote:
> Hi Travis
>
> 2009/2/12 Travis E. Oliphant :
>
>> ary['field1', 'field3'] raises an error
>> ary[['field1', 'field3']] is the correct spelling and returns a copy of
>> the data in those fields in a new array.
>>
>
> Is there absolutely no way of returning the r
Hi,
I have the following data structure:
col1 | col2 | col3
20080101|key1|4
20080201|key1|6
20080301|key1|5
20080301|key2|3.4
20080601|key2|5.6
For each key in the second column, I would like to create an array
where for all unique values in the first column, there will be either
a value or zer
Hi Travis
2009/2/12 Travis E. Oliphant :
> ary['field1', 'field3'] raises an error
> ary[['field1', 'field3']] is the correct spelling and returns a copy of
> the data in those fields in a new array.
Is there absolutely no way of returning the result as a view?
Regards
Stéfan
__
On Wed, Feb 11, 2009 at 6:27 PM, A B wrote:
> On Tue, Feb 10, 2009 at 9:52 PM, Brent Pedersen wrote:
>> On Tue, Feb 10, 2009 at 9:40 PM, A B wrote:
>>> Hi,
>>>
>>> How do I write a loadtxt command to read in the following file and
>>> store each data point as the appropriate data type:
>>>
>>> 1
Hi all,
As of r6358, I checked in the functionality to allow selection by
multiple fields along with a couple of tests.
ary['field1', 'field3'] raises an error
ary[['field1', 'field3']] is the correct spelling and returns a copy of
the data in those fields in a new array.
-Travis
_
On Feb 11, 2009, at 11:38 PM, Ryan May wrote:
> Pierre,
>
> I noticed that using dtype=None with a heterogeneous set of data,
> trying to use unpack=True to get the columns into separate arrays
> (instead of a structured array) doesn't work. I've attached a patch
> that, in the case of dty
Pierre,
I noticed that using dtype=None with a heterogeneous set of data, trying to
use unpack=True to get the columns into separate arrays (instead of a
structured array) doesn't work. I've attached a patch that, in the case of
dtype=None, unpacks the fields in the final array into a list of sep
On Tue, Feb 10, 2009 at 9:52 PM, Brent Pedersen wrote:
> On Tue, Feb 10, 2009 at 9:40 PM, A B wrote:
>> Hi,
>>
>> How do I write a loadtxt command to read in the following file and
>> store each data point as the appropriate data type:
>>
>> 12|h|34.5|44.5
>> 14552|bbb|34.5|42.5
>>
>> Do the stri
On Thu, Feb 12, 2009 at 8:11 AM, Fernando Perez wrote:
> On Wed, Feb 11, 2009 at 4:46 AM, David Cournapeau wrote:
>> Hi,
>>
>> I started to set up a PPA for scipy on launchpad, which enables to
>> build ubuntu packages for various distributions/architectures. The
>> link is there:
>>
>> https://e
On Wed, Feb 11, 2009 at 4:46 AM, David Cournapeau wrote:
> Hi,
>
> I started to set up a PPA for scipy on launchpad, which enables to
> build ubuntu packages for various distributions/architectures. The
> link is there:
>
> https://edge.launchpad.net/~scipy/+archive/ppa
Cool, thanks. Is it easy
Pauli Virtanen wrote:
> Wed, 11 Feb 2009 22:21:30 +, Andrew Jaffe wrote:
> [clip]
>> Maybe I misunderstand the proposal, but, actually, I think this is
>> completely the wrong semantics for "axis=" anyway. "axis=" in numpy
>> refers to what is also a dimension, not a column.
>
> I think the
Wed, 11 Feb 2009 22:21:30 +, Andrew Jaffe wrote:
[clip]
> Maybe I misunderstand the proposal, but, actually, I think this is
> completely the wrong semantics for "axis=" anyway. "axis=" in numpy
> refers to what is also a dimension, not a column.
I think the proposal was to add the ability
Robert Kern wrote:
> On Fri, Feb 6, 2009 at 03:22, Stéfan van der Walt wrote:
>> Hi Robert
>>
>> 2009/2/6 Robert Kern :
This could be implemented but would require adding information to the
NumPy array.
>>> More than that, though. Every function and method that takes an axis
>>> or reduc
I actually got it to work-- the function prototype in the pxi file was
wrong, needed to be:
int PyArray_SETITEM(object obj, void* itemptr, object item)
This still doesn't explain why the buffer interface was slow.
The general problem here is an indexed array (by dates or strings, for
example), t
Wes McKinney wrote:
> I am writing some Cython code and have noted that the buffer interface
> offers very little speedup for PyObject arrays. In trying to rewrite the
> same code using the C API in Cython, I find I can't get PyArray_SETITEM to
> work, in a call like:
>
> PyArray_SETITEM(result, i
Hi Wes,
I do not profess to be an expert, but I have been off loading a fair number
of loops to C from Python code and achieved significant improvements most
have been of the following form (which I have found to be the fastest):
size = *incomingArrayObj->dimensions;
r_dptr = PyArray_DATA(result
Hello,
I am writing some Cython code and have noted that the buffer interface
offers very little speedup for PyObject arrays. In trying to rewrite the
same code using the C API in Cython, I find I can't get PyArray_SETITEM to
work, in a call like:
PyArray_SETITEM(result, iterresult.dataptr, obj)
Announcing Numexpr 1.2
Numexpr is a fast numerical expression evaluator for NumPy. With it,
expressions that operate on arrays (like "3*a+4*b") are accelerated
and use less memory than doing the same calculation in Python.
The main feature added
On Wed, Feb 11, 2009 at 9:46 PM, David Cournapeau wrote:
> Hi,
>
> I started to set up a PPA for scipy on launchpad, which enables to
> build ubuntu packages for various distributions/architectures. The
> link is there:
>
> https://edge.launchpad.net/~scipy/+archive/ppa
>
> So you just need to add
Hi,
I started to set up a PPA for scipy on launchpad, which enables to
build ubuntu packages for various distributions/architectures. The
link is there:
https://edge.launchpad.net/~scipy/+archive/ppa
So you just need to add one line to your /etc/apt/sources.list, and
you will get uptodate numpy
Hello list,
I am not sure, if I understood everything of the discussion on the
named-axis-idea of numpy-arrays, since I am only a *user* of numpy. I
never subclassed the numpy-array-class ;-)
However, I have the need to store meta-information for my arrays. I do
this with a stand-alone class w
Stéfan van der Walt writes:
> 2009/2/10 Stéfan van der Walt :
>> x = np.arange(dim)
>> y = np.arange(dim)[:, None]
>> z = np.arange(dim)[:, None, None]
>
> Do not operate heavy machinery or attempt broadcasting while tired or
> under the influence. That order was incorrect:
>
>> z = np.arange(di
I'm pleased to announce SciPy 0.7.0. SciPy is a package of tools for
science and engineering for Python. It includes modules for
statistics, optimization, integration, linear algebra, Fourier
transforms, signal and image processing, ODE solvers,
and more.
This release comes sixteen months after
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