Hi,
I'm looking for a Numpy equivalent of convmtx
(http://www.mathworks.in/access/helpdesk/help/toolbox/signal/convmtx.html).
Is there something inside Numpy directly? or perhaps Scipy?
Matthieu
--
Information System Engineer, Ph.D.
Blog: http://matt.eifelle.com
LinkedIn:
Lisandro Dalcin wrote:
On 1 September 2010 19:24, Neal Becker ndbeck...@gmail.com wrote:
It seems if I call kron with 2 C-contiguous arrays, it returns an F-
contiguous array. Any reason for this (it's not what I wanted)?
Try numpy.linalg.inv ...
I don't understand. What has
Wed, 01 Sep 2010 18:24:16 -0400, Neal Becker wrote:
It seems if I call kron with 2 C-contiguous arrays, it returns an F-
contiguous array. Any reason for this (it's not what I wanted)?
Implementation detail.
I don't think we have or want to have a policy of C-contiguous return
values -- if
On Thu, Sep 2, 2010 at 3:56 AM, Matthieu Brucher
matthieu.bruc...@gmail.com wrote:
Hi,
I'm looking for a Numpy equivalent of convmtx
(http://www.mathworks.in/access/helpdesk/help/toolbox/signal/convmtx.html).
Is there something inside Numpy directly? or perhaps Scipy?
I haven't seen it in
On Mon, Aug 30, 2010 at 3:08 PM, Pauli Virtanen p...@iki.fi wrote:
Mon, 23 Aug 2010 21:15:55 +, Pauli Virtanen wrote:
[clip]
in the history to have the wrong content -- so to be sure, we have to do
a brute-force comparison of the tree against SVN for each commit. The
particular bug
On Wed, Sep 1, 2010 at 10:46 AM, Charles R Harris charlesr.har...@gmail.com
wrote:
On Tue, Aug 31, 2010 at 2:56 PM, Jason McCampbell
jmccampb...@enthought.com wrote:
Hi Chuck (and anyone else interested),
I updated the refactoring page on the NumPy developer wiki (seems to be
down or
On Wed, Sep 1, 2010 at 9:07 PM, Charles R Harris
charlesr.har...@gmail.comwrote:
Hi Jason,
On Tue, Aug 31, 2010 at 2:56 PM, Jason McCampbell
jmccampb...@enthought.com wrote:
Hi Chuck (and anyone else interested),
I updated the refactoring page on the NumPy developer wiki (seems to be
On Thu, Sep 2, 2010 at 8:51 AM, Jason McCampbell
jmccampb...@enthought.comwrote:
On Wed, Sep 1, 2010 at 9:07 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi Jason,
On Tue, Aug 31, 2010 at 2:56 PM, Jason McCampbell
jmccampb...@enthought.com wrote:
Hi Chuck (and anyone else
Charles R Harris wrote:
So if you write float96(0.0001), the result is not the float96 number
closest to 0.0001, but the 96-bit representation of the 64-bit number
closest to 0.0001.
...
but wouldn't it be better to exactly handle strings since those can be
converted exactly, which is what
On Thu, Sep 2, 2010 at 10:25 AM, Charles R Harris charlesr.har...@gmail.com
wrote:
On Thu, Sep 2, 2010 at 8:51 AM, Jason McCampbell
jmccampb...@enthought.com wrote:
On Wed, Sep 1, 2010 at 9:07 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
Hi Jason,
On Tue, Aug 31, 2010 at
Thanks Joseph, I'll wrap this inside my code ;)
Matthieu
2010/9/2 josef.p...@gmail.com:
On Thu, Sep 2, 2010 at 3:56 AM, Matthieu Brucher
matthieu.bruc...@gmail.com wrote:
Hi,
I'm looking for a Numpy equivalent of convmtx
On 09/02/10 17:06, Christopher Barker wrote:
Does the clib for a compiler that provides a float64 also provide an
atof() function that supports it? Its seems that it should.
I think so, for example in C I can do:
fscanf(fp, %Lf %Lf %Lf, x, y, z);
where x,y,z are long doubles.
The equivalent
On Thu, Sep 2, 2010 at 10:55 AM, Jason McCampbell jmccampb...@enthought.com
wrote:
On Thu, Sep 2, 2010 at 10:25 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Thu, Sep 2, 2010 at 8:51 AM, Jason McCampbell
jmccampb...@enthought.com wrote:
On Wed, Sep 1, 2010 at 9:07 PM,
Thu, 02 Sep 2010 18:13:23 +0100, Colin Macdonald wrote:
On 09/02/10 17:06, Christopher Barker wrote:
Does the clib for a compiler that provides a float64 also provide an
atof() function that supports it? Its seems that it should.
I think so, for example in C I can do:
fscanf(fp, %Lf %Lf
Thu, 02 Sep 2010 08:27:18 -0600, Charles R Harris wrote:
[clip]
Hi Pauli, I gave it a quick spin and it looks good so far. The cloning
was really fast, I like that ;) Is there any way to test out commiting?
I didn't have permissions to push to the repository.
You should have push permissions
Pauli Virtanen wrote:
We'll just need to add long double versions of NumPyOS_ascii_strtod and
NumPyOS_ftolf that call sscanf with the correct format string in the end.
hmm -- if you're going to do that, maybe we could re-factor and use
sscanf everywhere instead of ato*() -- the ato* functions
On Thu, Sep 2, 2010 at 11:51 AM, Pauli Virtanen p...@iki.fi wrote:
Thu, 02 Sep 2010 08:27:18 -0600, Charles R Harris wrote:
[clip]
Hi Pauli, I gave it a quick spin and it looks good so far. The cloning
was really fast, I like that ;) Is there any way to test out commiting?
I didn't have
Thu, 02 Sep 2010 12:22:30 -0600, Charles R Harris wrote:
[clip]
I do have a question of how the maintenance branch shows up in the
github network tool, that is, I expected to see the different release
branches coming off the master branch whereas the all seem to be points
along mainteance.
Hi all,
I just wanted to check if this would be considered a bug.
numpy.histogram does not appear to preserve subclasses of ndarrays (e.g.
masked arrays). This leads to considerable problems when working with
masked arrays. (As per this Stack Overflow
On 09/02/2010 02:50 PM, Joe Kington wrote:
Hi all,
I just wanted to check if this would be considered a bug.
numpy.histogram does not appear to preserve subclasses of ndarrays
(e.g. masked arrays). This leads to considerable problems when
working with masked arrays. (As per this Stack
Ideally, I would like in1d to always be the right answer to this problem. It
should be easy to put in an if statement to switch to a kern_in()-type
function
in the case of large ar1 but small ar2. I will do some timing tests and make
a
patch.
I uploaded a timing test and a patch
On Thu, Sep 2, 2010 at 3:50 PM, Joe Kington jking...@wisc.edu wrote:
Hi all,
I just wanted to check if this would be considered a bug.
numpy.histogram does not appear to preserve subclasses of ndarrays (e.g.
masked arrays). This leads to considerable problems when working with
masked
On Thu, Sep 2, 2010 at 5:31 PM, josef.p...@gmail.com wrote:
On Thu, Sep 2, 2010 at 3:50 PM, Joe Kington jking...@wisc.edu wrote:
Hi all,
I just wanted to check if this would be considered a bug.
numpy.histogram does not appear to preserve subclasses of ndarrays (e.g.
masked arrays).
Hi, all,
I have a f2py wrapped fortran extension, compiled using gcc-mingw32
(v.4.5.0), numpy 1.5, Python 2.7, where I am experiencing the strangest
behaviour. It appears that loading pygtk breaks my fortran extension.
The fortran code has initialization code (it calculates reference state for
a
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