On Sun, Mar 1, 2009 at 12:26 PM, Bruce Southey wrote:
> Or just a Vista bug.
>
> A possible option could be using wine64
> (http://wiki.winehq.org/Wine64) . But is probably more work and if
> even if it did work it may not be informative.
Win64 is not yet usable AFAIK - it was only a few weeks /
Hi everyone,
I'm subclassing Numpy's MaskedArray to create a data class that handles
missing data, but adds some extra info I need to carrry around. However I've
been having problems keeping this extra info attached to the subclass
instances after performing operations on them.
The bare-bones scr
On Sun, Mar 1, 2009 at 10:37 AM, Kevin Dunn wrote:
> Hi everyone,
>
> I'm subclassing Numpy's MaskedArray to create a data class that handles
> missing data, but adds some extra info I need to carrry around. However I've
> been having problems keeping this extra info attached to the subclass
> ins
>> Well, the latest cython doesn't help -- both errors still appear as
>> below. (Also, the latest cython can't run the numpy tests either.)
>> I'm
>> befuddled.
>
> That's pretty weird. Did you remove the .so that was build as well as
> any source files, before doing build_ext with the latest C
1. "dimensions" is a field in the C struct, that describes the array object.
2. Is there a chance that the header file numpy/arrayobject.h belongs to a
different numpy version that you run?
I am not very experienced with cython (I suppose that Stefan has some
experience).
As you said, probabl
So I have some data sets of about 16 floating point numbers stored
in text files. I find that loadtxt is rather slow. Is this to be
expected? Would it be faster if it were loading binary data?
-gideon
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On Sun, Mar 1, 2009 at 15:12, Gideon Simpson wrote:
> So I have some data sets of about 16 floating point numbers stored
> in text files. I find that loadtxt is rather slow. Is this to be
> expected?
Probably. You don't say exactly what you mean by "slow", so it's
difficult to tell. But it
Hi guys,
Dag, the cython person who seems to deal with the numpy stuff, had
this to say:
> - cimport and import are different things; you need both.
> - The "dimensions" field is in Cython renamed "shape" to be closer
> to the Python interface. This is done in Cython/Includes/numpy.pxd
After
Zach,
I put the source my Cython generated here:
http://mentat.za.net/refer/bilateral_base.c
Can you try to compile that?
Cheers
Stéfan
2009/3/1 Zachary Pincus :
>>> Well, the latest cython doesn't help -- both errors still appear as
>>> below. (Also, the latest cython can't run the numpy test
Hey Zach,
2009/3/1 Zachary Pincus :
> Dag, the cython person who seems to deal with the numpy stuff, had
> this to say:
>> - cimport and import are different things; you need both.
>> - The "dimensions" field is in Cython renamed "shape" to be closer
>> to the Python interface. This is done in Cyt
> 2009/3/1 Zachary Pincus :
>> Dag, the cython person who seems to deal with the numpy stuff, had
>> this to say:
>>> - cimport and import are different things; you need both.
>>> - The "dimensions" field is in Cython renamed "shape" to be closer
>>> to the Python interface. This is done in Cython/
2009/3/2 Zachary Pincus :
>> http://github.com/stefanv/bilateral.git
>
> Cool! Does this, out of curiosity, break things for you? (Or Nadav?)
I wish I had some way to test. Do you maybe have a short example that
I can convert to a test?
> I'm all for it. I've got a few other bits lying around th
On Sun, 1 Mar 2009 16:12:14 -0500 Gideon Simpson wrote:
> So I have some data sets of about 16 floating point numbers stored
> in text files. I find that loadtxt is rather slow. Is this to be
> expected? Would it be faster if it were loading binary data?
i have run into this as well.
On Sun, 1 Mar 2009 14:29:54 -0500 Michael Gilbert wrote:
> i have rewritten loadtxt to be smarter about allocating memory, but
> it is slower overall and doesn't support all of the original
> arguments/options (yet).
i had meant to say that my version is slower for smaller data sets (when
you ar
On Sun, Mar 1, 2009 at 11:29 AM, Michael Gilbert
wrote:
> On Sun, 1 Mar 2009 16:12:14 -0500 Gideon Simpson wrote:
>
>> So I have some data sets of about 16 floating point numbers stored
>> in text files. I find that loadtxt is rather slow. Is this to be
>> expected? Would it be faster if it
Gideon Simpson wrote:
> So I have some data sets of about 16 floating point numbers stored
> in text files. I find that loadtxt is rather slow. Is this to be
> expected? Would it be faster if it were loading binary data?
Depending on the format you may be able to use numpy.fromfile, whi
Hi Stéfan,
>>> http://github.com/stefanv/bilateral.git
>>
>> Cool! Does this, out of curiosity, break things for you? (Or Nadav?)
>
> I wish I had some way to test. Do you maybe have a short example that
> I can convert to a test?
Here's my test case for basic working-ness (e.g. non exception-
Hi,
Can anyone help me out with a simple way to vectorize this loop?
# idx and vals are arrays with indexes and values used to update array data
# data = numpy.ndarray(shape=(100,100,100,100), dtype='f4')
flattened = data.ravel()
for i in range(len(vals)):
flattened[idx[i]]+=vals[i]
Many th
On Mon, Mar 2, 2009 at 00:50, Stephen Simmons wrote:
> Hi,
>
> Can anyone help me out with a simple way to vectorize this loop?
>
> # idx and vals are arrays with indexes and values used to update array data
> # data = numpy.ndarray(shape=(100,100,100,100), dtype='f4')
> flattened = data.ravel()
>
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