Hi All,
after the discussion on numpy.correlate some time ago, regarding
complex conjugation, etc. I today was pointed to yet another oddity,
which I hope somebody could explain to me, as to why that's a feature,
rather than a bug. I'm thoroughly confused by the following behaviour:
In [29]:
Ondrej Certik wrote:
Are we able to provide an actual patch to Python that implements this?
If so, then I am.
Imho the proposal should come with an actual patch, otherwise it's
difficult to judge it.
Your better off with writing a PEP first. In order to implement the
proposal you've to make
On Tuesday 19 August 2008, Alan G Isaac wrote:
Proposal 1: PEP 225, but *just* for multiplication.
Either ~* as in the PEP or @* (which I prefer).
(This looks simplest.)
Proposal 2: PEP 225
(but maybe using @ instead of ~).
Proposal 3: use of a unicode character,
perhaps × since it is in
Hi both trunk and 1.1.1 fail to build under cygwin vista (latest version)
I'm copy/pasting the end of the log
C.
copying numpy/doc/reference/__init__.py -
build/lib.cygwin-1.5.25-i686-2.5/numpy/doc/reference
running build_ext
customize UnixCCompiler
customize UnixCCompiler using build_ext
On Wed, Aug 20, 2008 at 8:04 AM, Charles Doutriaux [EMAIL PROTECTED] wrote:
Hi both trunk and 1.1.1 fail to build under cygwin vista (latest version)
I'm copy/pasting the end of the log
It is a cygwin bug:
http://www.mail-archive.com/numpy-discussion@scipy.org/msg10051.html
cheers,
David
Thx David,
Is there any plans on applying the suggested fix into numpy ?
C.
David Cournapeau wrote:
On Wed, Aug 20, 2008 at 8:04 AM, Charles Doutriaux [EMAIL PROTECTED] wrote:
Hi both trunk and 1.1.1 fail to build under cygwin vista (latest version)
I'm copy/pasting the end of the log
Cython just had a release, and amongst the new features are efficient
NumPy array indexing for integers, real floats and Python objects.
You can get it at http://cython.org
For those new to Cython, I've written a tutorial specifically targeted
for NumPy users here:
On Wed, Aug 20, 2008 at 9:37 AM, Charles Doutriaux [EMAIL PROTECTED] wrote:
Thx David,
Is there any plans on applying the suggested fix into numpy ?
Ha, I was not aware we used any asm in numpy, which is why I did not
think it could be a numpy problem. I commented on the ticket, and
there is
2008/8/20 Hanno Klemm [EMAIL PROTECTED]:
In [29]: x = array([0.,0.,1, 0, 0])
In [35]: y1 = array([1,0,0,0,0])
In [36]: correlate(x,y1,mode='full')
Out[36]: array([ 0., 0., 0., 0., 0., 0., 1., 0., 0.])
That doesn't look right. Under r5661:
In [60]: np.convolve([0, 0, 1, 0, 0], [1,
On Wed, Aug 20, 2008 at 1:21 PM, David Cournapeau [EMAIL PROTECTED] wrote:
On Wed, Aug 20, 2008 at 9:37 AM, Charles Doutriaux [EMAIL PROTECTED] wrote:
Thx David,
Is there any plans on applying the suggested fix into numpy ?
Ha, I was not aware we used any asm in numpy, which is why I did not
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