Hi,
I want to wrap some code I've done in the past with a custom array and pass
numpy arrays to it.
So I need to transform numpy arrays to my arrays at the construction of an
instance of my class, as well as each call to a method (pass by value).
Then, some method return by value an array I have
Nick Fotopoulos wrote:
Devs, is there any possibility of moving/copying pylab.load to numpy?
I don't see anything in the source that requires the rest of
matplotlib. Among convenience functions, I think that this function
ranks pretty highly in convenience.
I'm supportive of this. But,
You should give ctypes a try, I find it much better than swig most
of the time for wrapping. You can find some doc here:
http://www.scipy.org/Cookbook/Ctypes2
Basically, once you get your dll/so with a function foo(double *a,
int n), you can call it directly in numpy by passing
A Dijous 19 Abril 2007 10:17, Travis Oliphant escrigué:
Nick Fotopoulos wrote:
Devs, is there any possibility of moving/copying pylab.load to numpy?
I don't see anything in the source that requires the rest of
matplotlib. Among convenience functions, I think that this function
ranks
Matthieu Brucher wrote:
You should give ctypes a try, I find it much better than swig most
of the time for wrapping. You can find some doc here:
http://www.scipy.org/Cookbook/Ctypes2
Basically, once you get your dll/so with a function foo(double *a,
int n), you
Does anyone know the right way to get numpy to build on windows using
Intel's MKL for LAPACK and BLAS libraries, under MSVC7.1?
I just did a whole lot of trial-and-error getting it to build. I
downloaded and installed MKL for windows from
An even simpler example generating the same error:
import numpy
x = numpy.array([0,0])
numpy.histogram2d(x,x)
HTH,
Emanuele
Emanuele Olivetti wrote:
While using histogram2d on simple examples I got these errors:
import numpy
x = numpy.array([0,0])
y = numpy.array([0,1])
dear all,
I've some problems with numpy.roots.
take a look at the following code:
import numpy
OK = numpy.roots([1, 1, 1])
OK = numpy.roots([1j, 1])
KO = numpy.roots([1, 1j, 1])
it fails with this error message,
Lisandro Dalcin wrote:
I am also +1 on this, but this functionality should be implemented in
C, I think.
well, maybe.
I've just tested numpy.fromfile('name.txt', sep=' ')
against pylab.load('name.txt') for a 35MB text file, the number are:
numpy.fromfile: 2.66 sec.
pylab.load: 16.64
I have found a way to build numpy on solaris x86 with
libsunperf. Basically, using the static library, and removing the
compiler flag for libf77compat (I think it's deprecated and has been
removed) and furthermore symlinking liblapack.a and libblas.a to the actual
libsunperf.a seems to result in a
updated.
now it works. many thanks.
L.
On 4/19/07, Nils Wagner [EMAIL PROTECTED] wrote:
lorenzo bolla wrote:
dear all,
I've some problems with numpy.roots.
take a look at the following code:
import numpy
OK = numpy.roots([1, 1, 1])
OK =
On 4/19/07, Matthieu Brucher [EMAIL PROTECTED] wrote:
I forgot you are using C++.
Yes, all my code is in C++, and in fact the code I use in Python should be
object-oriented as well, that's why it is not that easy to define how I'm
going to do this...
Doing the wrapping in an object
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Peter C. Norton wrote:
Hello all,
I'm trying to build numpy for some of my users, and I can't seem to
get the [blas_opt] or the [lapack_opt] settings to be honored in my
site.cfg:
$ CFLAGS=-L$STUDIODIR/lib/ -l=sunperf
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Christian Marquardt wrote:
Dear David,
the svn version of numpy does indeed build cleanly on AIX. Many thanks!
However, the wrapper problem still exists for the C++ compiler, and shows
up when compiling scipy. Now, I *assume* that SciPy is
This may be of no help at all but I see mentions of C++/Python/OO/SWIG
and it triggers me to mention something I heard about recently called
PyCXX:
http://cxx.sourceforge.net/
I /think/ the idea behind it is to basically make a C++ version of the
Python C API. You still do all the wrapping
David Huard wrote:
Hi Emanuele,
The bug is due to a part of the code that shifts the last bin's
position to make sure the array's maximum value is counted in the last
bin, and not as an outlier. To do so, the code computes an approximate
precision used the shift the bin edge by amount small
Matthieu Brucher wrote:
Doing the wrapping in an object oriented way is difficult, and maybe
not that useful. This does not prevent the API exposed to python
to be
OO, of course.
I have some difficulties to do this in an automated way...
I'm trying now to make a derived
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