[Numpy-discussion] building inplace with numpy.distutils?

Hi (David)! I am evaluating numpy.distutils as a build/install system for my project - is it possible to build the extension modules in-place so that the project can be used without installing it? A pointer to documentation concerning this would be handy... Currently I use a regular Makefile

Re: [Numpy-discussion] copy and paste arrays from matlab

[crossposted to numpy-discussion and mlabwrap-user] Hi, Please find attached Python code for the opposite direction - ie format Python arrays for copy and pasting into an interactive Matlab session. It doesn't look as nice because newlines are row seperators in matlab so I put everything on one

Re: [Numpy-discussion] copy and paste arrays from matlab

On Wed, May 13, 2009 at 12:39 PM, Robin robi...@gmail.com wrote: [crossposted to numpy-discussion and mlabwrap-user] Hi, Please find attached Python code for the opposite direction - ie format Python arrays for copy and pasting into an interactive Matlab session. It doesn't look as nice

[Numpy-discussion] (no subject)

Hi, [You may want to edit the numpy homepage numpy.scipy.org to tell people they must subscribe to post, and adding a link to http://www.scipy.org/Mailing_Lists] Many of you probably know of the interpreter yorick by Dave Munro. As a Livermoron, I use it all the time. There are some

Re: [Numpy-discussion] Are masked arrays slower for processing than ndarrays?

All, I just committed (r6994) some modifications to numpy.ma.getdata (Eric Firing's patch) and to the ufunc wrappers that were too slow with large arrays. We're roughly 3 times faster than we used to, but still slower than the equivalent classic ufuncs (no surprise here). Here's the catch:

Re: [Numpy-discussion] Are masked arrays slower for processing than ndarrays?

Hi Pierre 2009/5/14 Pierre GM pgmdevl...@gmail.com: This playing around with the error status may (or may not, I don't know) cause some problems down the road. I see the buildbot is complaining on SPARC. Not sure if it is complaining about your commit, but might be worth checking out

Re: [Numpy-discussion] FAIL: Test bug in reduceat with structured arrays

On 11-May-09, at 10:55 AM, Pauli Virtanen wrote: Wonder why buildbot's 64-bit SPARC boxes don't see this if it's something connected to 64-bitness... Different endianness, maybe? That seems even weirder, honestly. David ___ Numpy-discussion

Re: [Numpy-discussion] Are masked arrays slower for process ing than ndarrays?

Hi Pierre, Here's the catch: it's basically cheating. I got rid of the pre- processing (where a mask was calculated depending on the domain and the input set to a filling value depending on this mask, before the actual computation). Instead, I force

Re: [Numpy-discussion] Are masked arrays slower for processing than ndarrays?

On May 13, 2009, at 7:36 PM, Matt Knox wrote: Here's the catch: it's basically cheating. I got rid of the pre- processing (where a mask was calculated depending on the domain and the input set to a filling value depending on this mask, before the actual computation). Instead, I force

Re: [Numpy-discussion] Are masked arrays slower for processing than ndarrays?

Hi, Whine. I was afraid of something like that... 2 options, then: * We revert to computing a mask beforehand. That looks like the part that takes the most time w/ domained operations (according to Robert K's profiler. Robert, you deserve a statue for this tool). And that doesn't solve the

Re: [Numpy-discussion] Are masked arrays slower for processing than ndarrays?

On Wed, May 13, 2009 at 18:36, Matt Knox mattknox...@gmail.com wrote: Hi Pierre, Here's the catch: it's basically cheating. I got rid of the pre- processing (where a mask was calculated depending on the domain and the input set to a filling value depending on this mask, before the actual

Re: [Numpy-discussion] Are masked arrays slower for process ing than ndarrays?

Robert Kern robert.kern at gmail.com writes: seterr() uses thread-local storage. Oh. I stand corrected. Ignore my earlier objections then. Pierre GM pgmdevlist at gmail.com writes: Also, importing numpy.ma currently calls numpy.seterr(all='ignore') anyway... hmm. While this doesn't

Re: [Numpy-discussion] Are masked arrays slower for processing than ndarrays?

On May 13, 2009, at 8:07 PM, Matt Knox wrote: hmm. While this doesn't affect me personally... I wonder if everyone is aware of this. Importing modules generally shouldn't have side effects either I would think. Has this always been the case for the masked array module? Well, can't

Re: [Numpy-discussion] FAIL: Test bug in reduceat with structured arrays

On Wed, May 13, 2009 at 5:18 PM, David Warde-Farley d...@cs.toronto.eduwrote: On 11-May-09, at 10:55 AM, Pauli Virtanen wrote: Wonder why buildbot's 64-bit SPARC boxes don't see this if it's something connected to 64-bitness... Different endianness, maybe? That seems even weirder,

Re: [Numpy-discussion] building inplace with numpy.distutils?

Robert Cimrman wrote: Hi (David)! I am evaluating numpy.distutils as a build/install system for my project - is it possible to build the extension modules in-place so that the project can be used without installing it? A pointer to documentation concerning this would be handy...

[Numpy-discussion] numpy slices limited to 32 bit values?

I'm using the latest version of Sage (3.4.2) which is python 2.5 and numpy something or other (I will do more digging presently) I'm able to map large files and access all the elements unless I'm using slices so, for example: fp = np.memmap(/mnt/hdd/data/mmap/numpy1e10.mmap, dtype='float64',

Re: [Numpy-discussion] building inplace with numpy.distutils?

David Cournapeau wrote: Robert Cimrman wrote: Hi (David)! I am evaluating numpy.distutils as a build/install system for my project - is it possible to build the extension modules in-place so that the project can be used without installing it? A pointer to documentation concerning this