Hi,
2) Is there a way to use another algorithm (at the cost of performance)
that uses less memory during calculation so that I can generate bigger
histograms?
You could work through your array block by block. Simply fix the range and
generate an histogram for each slice of 100k data
Hi,
While studying a bit nsis (an open source system to build windows
installers), I realized that it would be good if we could detect the
target CPU and install the right numpy accordingly. I have coded a
nsis plugin to detect SSE availability (no SSE vs SSE vs SSE2 vs SS3),
and including
Hi,
Can this be changed:
If I have a list L the usual N.asarray( L ) works well -- however I
just discovered that N.asarray( reversed( L ) ) breaks my code
Apparently reversed( L ) returns an iterator object, and N.asarray(
reversed( L ) ) (called arrY in my function)
results in:
(Pdb) p
On 2/1/08, Pearu Peterson [EMAIL PROTECTED] wrote:
Sorry, I haven't been around there long time.
Are you going to continue not reading the f2py list? If so, you should
point everyone there to this list and close the list.
Anyway, I have subscribed to the f2py list again I'll try to
On Mon, Feb 04, 2008 at 11:02:29AM -0500, Vince Fulco wrote:
Any trailheads for the simplest approach
I find ctypes very easy to understand. See
http://www.scipy.org/Cookbook/Ctypes for simple instructions.
HTH,
Gaël
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Dear Numpy Experts- I find myself working with Numpy arrays and
wanting to access *simple* C++ functions for time series returning the
results to Numpy. As I am a relatively new user of Python/Numpy, the
number of paths to use in incorporating C++ code into one's scripts is
daunting. I've
I have a variety of experiments that I put in this mercurial repo:
https://nbecker.dyndns.org/hg/
The primary aim of this is to reuse c++ code written to a generic container
interface, with numpy.
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round - works fine.
ceil - throws exception: 'complex' object has no attribute 'ceil'
floor - throws exception: 'complex' object has no attribute 'floor'
fix - throws exception: 'complex' object has no attribute 'floor'
My question: Is this a bug or a feature? It seems to me
On Mon, Feb 4, 2008 at 6:56 AM, Sebastian Haase [EMAIL PROTECTED] wrote:
Hi,
Can this be changed:
If I have a list L the usual N.asarray( L ) works well -- however I
just discovered that N.asarray( reversed( L ) ) breaks my code
Apparently reversed( L ) returns an iterator object,
--- Matthieu Brucher [EMAIL PROTECTED]
wrote:
Whatever solution you choose (Boost.Python, ...),
you will have to use the
Numpy C API at least a little bit. So Travis' book
is a good start. As Gaël
told you, you can use ctypes if you wrap manually
every method with a C
function and
On Mon, February 4, 2008 4:39 pm, Lisandro Dalcin wrote:
Pearu, now that f2py is part of numpy, I think it would be easier for
you and also for users to post to the numpy list for f2py-related
issues. What do you think?
Personaly, I don't have strong opinions on this.
On one hand, it would
On Mon, Feb 4, 2008 at 11:59 AM, Stuart Brorson [EMAIL PROTECTED] wrote:
round - works fine.
ceil - throws exception: 'complex' object has no attribute 'ceil'
floor - throws exception: 'complex' object has no attribute 'floor'
fix - throws exception: 'complex' object has no
On Mon, Feb 4, 2008 at 10:34 AM, Stuart Brorson [EMAIL PROTECTED] wrote:
Hi --
I'm fiddling with NumPy's chopping and truncating operators: round,
fix, ceil, and floor. In the case where they are passed real args,
they work just fine. However, I find that when they are passed
complex
Hi --
I'm fiddling with NumPy's chopping and truncating operators: round,
fix, ceil, and floor. In the case where they are passed real args,
they work just fine. However, I find that when they are passed
complex args, I get the following:
round - works fine.
ceil - throws exception:
Lou Pecora wrote:
I
would recommend using the C API
I would recommend against this -- there is a lot of code to write in
extensions to make sure you do reference counting, etc, and it is hard
to get right.
Much of it is also boiler-plate code, so it makes more sense to have
that code
Dear Mr. Fulco ,
This may not be exactly what you want to do, but I
would recommend using the C API and then calling your
C++ programs from there (where interface functions to
the C++ code is compiled in the extern C {, }
block. I will be doing this soon with my own project.
Why? Because
2008/2/4, Lou Pecora [EMAIL PROTECTED]:
Dear Mr. Fulco ,
This may not be exactly what you want to do, but I
would recommend using the C API and then calling your
C++ programs from there (where interface functions to
the C++ code is compiled in the extern C {, }
block. I will be doing
2008/2/4, Lars Friedrich [EMAIL PROTECTED]:
Hi,
2) Is there a way to use another algorithm (at the cost of performance)
that uses less memory during calculation so that I can generate
bigger
histograms?
You could work through your array block by block. Simply fix the range
and
Stuart Brorson wrote:
Anyway, since NumPy is committed to (Re, Im) as the base
representation of complex numbers, then it is not unreasonable to
implement round, fix, and so on, by operating independently on the Re
and Im parts.
Or am I wrong?
Sounds reasonable to me...
-Travis O.
Christopher Barker wrote:
Neal Becker wrote:
I have a variety of experiments that I put in this mercurial repo:
https://nbecker.dyndns.org/hg/
The primary aim of this is to reuse c++ code written to a generic
container interface, with numpy.
Neal,
I'd love to hear more about this. Do
On Feb 4, 2008 5:13 AM, David Cournapeau [EMAIL PROTECTED] wrote:
Hi,
While studying a bit nsis (an open source system to build windows
installers), I realized that it would be good if we could detect the
target CPU and install the right numpy accordingly. I have coded a
nsis plugin to
On Mon, Feb 04, 2008 at 12:05:45PM -0800, Christopher Barker wrote:
ctypes -- [...] Can it call C++ directly at all?
No, but you can use 'extern C' in you cpp file, if you have controle
over the file.
Gaël
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On Mon, Feb 04, 2008 at 12:49:58PM -0800, Lou Pecora wrote:
So, for those looking for speed up through some
external C or C++ code, I would say (trying to be fair
here), try what Chris recommends below, if you want,
but IMHO, none of it is trivial. If you get it to
work, great. If not, you
On Feb 4, 2008, at 1:05 PM, Christopher Barker wrote:
Boost::python -- best for writing custom extensions in C++ -- also can
be used for interfacing with legacy C++. There were boost array
classes
for numpy -- are these being maintained?
There are boost array classes for Numeric, and
Bill Spotz wrote:
On Feb 4, 2008, at 1:05 PM, Christopher Barker wrote:
Boost::python -- best for writing custom extensions in C++ -- also can
be used for interfacing with legacy C++. There were boost array
classes
for numpy -- are these being maintained?
There are boost array
For comparison of ctypes and SWIG wrappers of a simple C++ codebase,
feel free to take a look at the code for scikits.ann
(http://scipy.org/scipy/scikits/wiki/AnnWrapper). The original wrapper
was written using SWIG and the numpy typemaps. Rob Hetland has coded
an almost-the-same API wrapper using
Neal Becker wrote:
I have a variety of experiments that I put in this mercurial repo:
https://nbecker.dyndns.org/hg/
The primary aim of this is to reuse c++ code written to a generic container
interface, with numpy.
Neal,
I'd love to hear more about this. Do you have a two paragraph
--- Christopher Barker [EMAIL PROTECTED] wrote:
Lou Pecora wrote:
I
would recommend using the C API
I would recommend against this -- there is a lot of
code to write in
extensions to make sure you do reference counting,
etc, and it is hard
to get right.
Well, fair enough to some
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