You should avoid meshgrid, as the follows:
...
#3D ARRAY
XArray = np.arange(0, NrHorPixels, 1./sqrt(NrCellsPerPixel))
YArray = np.arange(0, NrVerPixels, 1./sqrt(NrCellsPerPixel))
Z =
Amplitude*exp(-(((XArray-GaussianCenterX)**2/(2*SigmaX**2))+((YArray[:,None]-GaussianCenterY)**/(2*SigmaY**2
Hi,
in my Priithon project I the got from this
Minimum Distance between a Point and a Line
Written by Paul Bourke,October 1988
http://astronomy.swin.edu.au/~pbourke/geometry/pointline/
def geoPointLineDist(p, seg, testSegmentEnds=False)::
...
On Wed, Oct 6, 2010 at 8:12 AM, Charles R Harris
charlesr.har...@gmail.comwrote:
On Tue, Oct 5, 2010 at 5:49 PM, Pauli Virtanen p...@iki.fi wrote:
Hi,
Should we set a date for a bugfix 1.5.1 release? There are some bugs that
would be nice to sort out in the 1.5.x series:
Any Python
Thu, 07 Oct 2010 16:34:46 +0800, Ralf Gommers wrote:
[clip]
A 1.5.1 release soon would be good. All the issues above are already
committed, is there anything else that needs to go in? If not, I think
an RC by the end of next week (10/17) and release by the end of the
month should be possible.
On Oct 7, 2010, at 4:48 AM, Chris Fonnesbeck wrote:
The documentation for loadtxt and genfromtxt state that the unpack
argument functions as follows:
If True, the returned array is transposed, so that arguments may be
unpacked using x, y, z = loadtxt(...).
Provided that all the columns
On Sat, Oct 2, 2010 at 12:51 PM, John Mitchell worka...@gmail.com wrote:
After spending a lot of time building 'numpy' (1.5.0) and 'scipy' (0.8.0)
I ran the following tests -- per what I read somewhere:
numpy.test()
Out of several thousand small tests I found this one error -- perhaps its
I used your suggestion, but it keeps getting me those errors mentioned, but
on the definition of Z (line of the following code):
from pylab import *
import numpy as np
#VARIABLES
NrHorPixels=512
NrVerPixels=512
NrCellsPerPixel=16
GaussianCenterX=256
GaussianCenterY=256
SigmaX=1
SigmaY=1
On Wed, Oct 6, 2010 at 12:32 AM, Russell E. Owen ro...@uw.edu wrote:
There are two Python 2.7 installers available at python.org a 32 bit
version for MacOS X 10.3.9 and later and a 64 bit version for Mac OS X
10.5 and later.
There is one numpy 1.5.0 binary installer for Mac Python 2.7. Which
Just FYI:
The DEV_README.txt file needs a trivial update to talk about git not SVN
http://github.com/numpy/numpy/blob/master/DEV_README.txt
Regards,
Peter
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On Thu, Oct 7, 2010 at 2:34 AM, Ralf Gommers ralf.gomm...@googlemail.comwrote:
On Wed, Oct 6, 2010 at 8:12 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Tue, Oct 5, 2010 at 5:49 PM, Pauli Virtanen p...@iki.fi wrote:
Hi,
Should we set a date for a bugfix 1.5.1 release?
Thu, 07 Oct 2010 07:09:37 -0600, Charles R Harris wrote:
[clip]
No, I just wanted to include the Laguerre and Hermite polynomials and
add a domain keyword to the linspace method of the polynomial template.
But I don't think these are pressing needs.
It's a minor release, so I think we need to
On Thu, Oct 7, 2010 at 9:09 PM, Charles R Harris
charlesr.har...@gmail.comwrote:
On Thu, Oct 7, 2010 at 2:34 AM, Ralf Gommers
ralf.gomm...@googlemail.comwrote:
On Wed, Oct 6, 2010 at 8:12 AM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Tue, Oct 5, 2010 at 5:49 PM, Pauli
On 10/07/2010 08:45 AM, Ralf Gommers wrote:
On Thu, Oct 7, 2010 at 9:09 PM, Charles R Harris
charlesr.har...@gmail.com mailto:charlesr.har...@gmail.com wrote:
On Thu, Oct 7, 2010 at 2:34 AM, Ralf Gommers
ralf.gomm...@googlemail.com mailto:ralf.gomm...@googlemail.com
wrote:
On Thu, Oct 7, 2010 at 7:45 AM, Ralf Gommers ralf.gomm...@googlemail.comwrote:
On Thu, Oct 7, 2010 at 9:09 PM, Charles R Harris
charlesr.har...@gmail.com wrote:
On Thu, Oct 7, 2010 at 2:34 AM, Ralf Gommers ralf.gomm...@googlemail.com
wrote:
On Wed, Oct 6, 2010 at 8:12 AM, Charles R
On Oct 7, 2010, at 3:49 PM, Benjamin Root wrote:
I understand the technicalities of why this occurs, but from a user's
perspective, he is asking for distinct numpy arrays of specified types. The
transposing seems to be almost an unimportant implementation detail because
the user is
Just asking,
Should I backport some bugs that were corrected in 2.0 for numpy.ma ? I don't
have any particular in mind, but I'm sure there must be some...
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On Thu, Oct 7, 2010 at 4:00 AM, Pierre GM pgmdevl...@gmail.com wrote:
On Oct 7, 2010, at 4:48 AM, Chris Fonnesbeck wrote:
The documentation for loadtxt and genfromtxt state that the unpack
argument functions as follows:
If True, the returned array is transposed, so that arguments may be
On Thu, Oct 7, 2010 at 8:59 AM, Pierre GM pgmdevl...@gmail.com wrote:
Not needed. The unpack argument is used as the very end of the function
anyway.
Anyhow, could you open a ticket to that effect (else I'm quite likely to
forget about it).
I can open this one.
On Oct 7, 2010, at 4:01 PM, Chris Fonnesbeck wrote:
On Thu, Oct 7, 2010 at 4:00 AM, Pierre GM pgmdevl...@gmail.com wrote:
On Oct 7, 2010, at 4:48 AM, Chris Fonnesbeck wrote:
The documentation for loadtxt and genfromtxt state that the unpack
argument functions as follows:
If True, the
On Thu, Oct 7, 2010 at 8:59 AM, Pierre GM pgmdevl...@gmail.com wrote:
On Oct 7, 2010, at 3:49 PM, Benjamin Root wrote:
I understand the technicalities of why this occurs, but from a user's
perspective, he is asking for distinct numpy arrays of specified types. The
transposing seems to be
On Thu, Oct 7, 2010 at 10:00 PM, Pierre GM pgmdevl...@gmail.com wrote:
Just asking,
Should I backport some bugs that were corrected in 2.0 for numpy.ma ? I
don't have any particular in mind, but I'm sure there must be some...
That would be helpful. Please backport any bug fixes that you
On Thu, Oct 7, 2010 at 9:54 PM, Bruce Southey bsout...@gmail.com wrote:
I agree that this is a good idea to have this minor release with as few
changes as possible. This allows us to clearly state everything has moved to
git and localize any problems that users should not have related to the
Hello Robert,
I dare to bother you again with some questions.
this time I have a numpy array with fields
ar = array([(1.0, 2.0, 3, 4), (2.0, 3.0, 4, 5)], dtype={'names':
['q','wl','cssid','br'], 'formats':['f4', 'f4', 'i4', 'i4'],
'offsets': [0, 4, 8, 12]}, order='F')
on C API I want to
On 10/7/2010 1:31 AM, Charles R Harris wrote:
On Wed, Oct 6, 2010 at 11:07 PM, Andrew P. Mullhaupt
d...@zen-pharaohs.com mailto:d...@zen-pharaohs.com wrote:
I came across this gem yesterday
from numpy import *
R = ones((2))
R[0] = R[0] * 1j
On Thu, 7 Oct 2010 09:06:55 + (UTC)
Pauli Virtanen p...@iki.fi wrote:
Thu, 07 Oct 2010 16:34:46 +0800, Ralf Gommers wrote:
[clip]
A 1.5.1 release soon would be good. All the issues above
are already
committed, is there anything else that needs to go in?
If not, I think
an RC by the
to, 2010-10-07 kello 12:08 -0400, Andrew P. Mullhaupt kirjoitti:
[clip]
No. You can define the arrays as backed by mapped files with real and
imaginary parts separated. Then the imaginary part, being initially
zero, is a sparse part of the file, takes only a fraction of the
space (and, on
On Wed, Oct 6, 2010 at 6:17 PM, josef.p...@gmail.com wrote:
On Wed, Oct 6, 2010 at 7:08 PM, Jonathan March jma...@enthought.com wrote:
It appears that the numpy testing decorators for skipping and for
known failure should behave similarly to each other, at least from
their descriptions here:
Hi,
what about the normed=True bug in numpy.histogram? It was discussed here
a while ago, and fixed (although i did not find it on the tracker), but
the message
aanlktikwbsrxq0ynf3u3jo3ekrikszmwqy30pnsfg...@mail.gmail.com
suggests it just missed 1.5.0? I don't have 1.5 installed, so I can't
On 10/7/2010 1:01 PM, Pauli Virtanen wrote:
to, 2010-10-07 kello 12:08 -0400, Andrew P. Mullhaupt kirjoitti:
[clip]
But to implement this, you'd have to rewrite large parts of Numpy since
the separated storage of re/im conflicts with its memory model.
You wouldn't want to rewrite any of
On Thu, Oct 7, 2010 at 3:38 PM, Andrew P. Mullhaupt
d...@zen-pharaohs.com wrote:
On 10/7/2010 1:01 PM, Pauli Virtanen wrote:
to, 2010-10-07 kello 12:08 -0400, Andrew P. Mullhaupt kirjoitti:
[clip]
But to implement this, you'd have to rewrite large parts of Numpy since
the separated storage
On 7 October 2010 13:01, Pauli Virtanen p...@iki.fi wrote:
to, 2010-10-07 kello 12:08 -0400, Andrew P. Mullhaupt kirjoitti:
[clip]
No. You can define the arrays as backed by mapped files with real and
imaginary parts separated. Then the imaginary part, being initially
zero, is a sparse part
Thu, 07 Oct 2010 18:02:43 -0400, Andrew P. Mullhaupt wrote:
On 10/7/2010 3:45 PM, josef.p...@gmail.com wrote:
what's your namespace?from scipy import log
log(int(-2))
(0.69314718055994529+3.1415926535897931j)
This should explain:
R = ones(2)
R[0] = R[0] * 1j
R
array([ 0., 1.])
On 10/ 6/10 12:49 AM, Pauli Virtanen wrote:
Hi,
Should we set a date for a bugfix 1.5.1 release? There are some bugs that
would be nice to sort out in the 1.5.x series:
Any Python versions:
- #1605 (Cython vs. PEP-3118 issue: raising exceptions with active
cython buffers caused
Hi,
I'm not sure if this is a numpy.distutils or a regular distutils issue
so please excuse me if it doesn't belong here.
I 'm using numpy 1.4.1 and I have a C extension (using numpy arrays)
that I built with numpy.
When I'm debugging I frequently have to rebuild.
It use to rebuild only the C
On 10/7/2010 3:48 PM, Anne Archibald wrote:
Years ago MATLAB did just this - store real and complex parts of
arrays separately (maybe it still does, I haven't used it in a long
time). It caused us terrible performance headaches,
Years ago performance headaches from Matlab are not exactly
Hi,
On Thu, Oct 7, 2010 at 3:47 PM, Andrew P. Mullhaupt
d...@zen-pharaohs.com wrote:
On 10/7/2010 3:48 PM, Anne Archibald wrote:
Years ago MATLAB did just this - store real and complex parts of
arrays separately (maybe it still does, I haven't used it in a long
time). It caused us terrible
On 10/7/2010 5:14 PM, Pauli Virtanen wrote:
to, 2010-10-07 kello 15:38 -0400, Andrew P. Mullhaupt kirjoitti:
[clip]
On 10/7/2010 1:01 PM, Pauli Virtanen wrote:
to, 2010-10-07 kello 12:08 -0400, Andrew P. Mullhaupt kirjoitti:
[clip]
But to implement this, you'd have to rewrite large parts
On Thu, Oct 7, 2010 at 18:46, Andrew P. Mullhaupt d...@zen-pharaohs.com wrote:
On 10/7/2010 5:14 PM, Pauli Virtanen wrote:
to, 2010-10-07 kello 15:38 -0400, Andrew P. Mullhaupt kirjoitti:
[clip]
On 10/7/2010 1:01 PM, Pauli Virtanen wrote:
to, 2010-10-07 kello 12:08 -0400, Andrew P. Mullhaupt
On Thu, Oct 7, 2010 at 10:09, Ioan Ferencik ioan.feren...@tkk.fi wrote:
Hello Robert,
I dare to bother you again with some questions.
this time I have a numpy array with fields
ar = array([(1.0, 2.0, 3, 4), (2.0, 3.0, 4, 5)], dtype={'names':
['q','wl','cssid','br'], 'formats':['f4', 'f4',
On 7 October 2010 19:46, Andrew P. Mullhaupt d...@zen-pharaohs.com wrote:
It wouldn't be the first time I suggested rewriting the select and
choose operations. I spent months trying to get Guido to let anything
more than slice indexing in arrays. And now, in the technologically
advanced
On 10/7/2010 6:52 PM, Matthew Brett wrote:
Hi,
On Thu, Oct 7, 2010 at 3:47 PM, Andrew P. Mullhaupt
d...@zen-pharaohs.com wrote:
Most machines now
and in the future are not going to choke on these issues (for a variety
of reasons).
'Talk is cheap, show me the code' .
Yes, let's.
First
On 10/7/2010 8:21 PM, Robert Kern wrote:
On Thu, Oct 7, 2010 at 18:46, Andrew P. Mullhauptd...@zen-pharaohs.com
wrote:
It appears that your answer is YES, we COULD have that, BUT it would be
a lot of work.
You misread him. The answer is no. We will not change the memory
model so
On Fri, Oct 8, 2010 at 11:47 AM, Andrew P. Mullhaupt
d...@zen-pharaohs.com wrote:
On 10/7/2010 8:21 PM, Robert Kern wrote:
On Thu, Oct 7, 2010 at 18:46, Andrew P. Mullhauptd...@zen-pharaohs.com
wrote:
It appears that your answer is YES, we COULD have that, BUT it would be
a lot of work.
On Fri, Oct 8, 2010 at 7:40 AM, Charles Doutriaux doutria...@llnl.gov wrote:
Did anybody else noticed this? Anybody know what changed (the fact that
it's since Python 2.7 make me think it might be pure distutils related)
Could you check whether you still see the issue without using
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