> 2009/1/27 Nils Wagner :
> a make latex in numpy/doc failed with
>
> ...
>
> Intersphinx hit: PyObject
> http://docs.python.org/dev/c-api/structures.html
> writing... Sphinx error:
> too many nesting section levels for LaTeX, at heading:
> numpy.ma.MaskedArray.__lt__
> make: *** [latex] Fehler 1
>
Hi, Bob,
Thanks for your help.
I am sorry for my type error. qam array is the X array in my example.
cntl is a complex array contains the point (x,y) axises.
I will try to make a workable example. Also I will try to find out the
zeros_like function. However, I guess that zeros_like(X) wi
There are at least two options:
1. use convolve1d from numpy.numarray.nd_image (or scipy.ndimage)
2. use scipy.signal.convolve and adjust the dimensions of the convolution kenel
to align it along the desired axis.
Nadav
-הודעה מקורית-
מאת: numpy-discussion-boun...@scipy.org בשם Gideon
On Thu, Jan 29, 2009 at 00:09, frank wang wrote:
> Here is the for loop that I am think about. Also, I do not know whether the
> where commands can handle the complicated logic.
> The where command basically find the data in the square around the point
> cnstl[j].
cnstl is a 2D array from your pr
Here is the for loop that I am think about. Also, I do not know whether the
where commands can handle the complicated logic.
The where command basically find the data in the square around the point
cnstl[j].
Let the data array is qam with size N
Out = X
error = X
for i in arange(N):
for
On Wed, Jan 28, 2009 at 23:52, frank wang wrote:
>
> Hi,
>
> I have to buidl a grid with 256 point by the command:
> a = arange(-15,16,2)
> L = len(a)
> cnstl = a.reshape(L,1)+1j*a
>
> My problem is that I have a big data array that contains the data round the
> points in cnstl. I want to slice th
Hi,
I have to buidl a grid with 256 point by the command:
a = arange(-15,16,2)
L = len(a)
cnstl = a.reshape(L,1)+1j*a
My problem is that I have a big data array that contains the data round the
points in cnstl. I want to slice the point to the closest cnstl point and also
compute the error.
All,
Is there an objects.inv lying around for the numpy reference guide, or
should I start one from scratch ?
Thx a lot in advance
P.
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Is there an easy way to perform convolutions along a particular axis
of an array?
-gideon
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On Wed, Jan 28, 2009 at 6:11 PM, David Cournapeau
wrote:
> It is said in the email that this is reserved to the python project, and
> prominent python projects like Twisted and Django. Would it be ok to try
> to be qualified as a prominent python project as well ?
That would be great.
___
Sounds like a great idea!
On 1/28/09, David Cournapeau wrote:
> Hi,
>
> Just saw that on one ML:
>
> http://www.snakebite.org/
> http://mail.python.org/pipermail/python-committers/2009-January/000331.html
>
> Bottom line: it looks like there is a set of machines which were donated
> to the PS
On Wed, Jan 28, 2009 at 7:11 PM, David Cournapeau <
da...@ar.media.kyoto-u.ac.jp> wrote:
> Hi,
>
>Just saw that on one ML:
>
> http://www.snakebite.org/
> http://mail.python.org/pipermail/python-committers/2009-January/000331.html
>
> Bottom line: it looks like there is a set of machines which
Hi,
Just saw that on one ML:
http://www.snakebite.org/
http://mail.python.org/pipermail/python-committers/2009-January/000331.html
Bottom line: it looks like there is a set of machines which were donated
to the PSF for buildbot *with shell access* so that people can fix
problems appearing on
On Thu, Jan 29, 2009 at 1:18 AM, Michael Colonno wrote:
>I think this is doable; thankfully the Intel compilers on Windows and
> Linux are very similar in behavior.
The problem is that distutils does not abstract this kind of things:
you have a CCompiler class, and a subclass Unix C Compiler,
On Jan 28, 2009, at 5:43 PM, Timmie wrote:
>>
>> You could try:
>> np.fromiter((_.hour for _ in dates_li), dtype=np.int)
>> or
>> np.array([_.hour for _ in dates_li], dtype=np.int)
>
> I used dates_li only for the preparation of example data.
>
> So let's suppose I have the array "dates_array" ret
Thanks!
> > ### this is the loop I would like to optimize:
> > ### looping over arrays is considered inefficient.
> > ### what could be a better way?
> > hours_array = dates_array.copy()
> > for i in range(0, dates_array.size):
> > hours_array[i] = dates_array[i].hour
>
> You could try:
> np.
On Jan 28, 2009, at 3:56 PM, Timmie wrote:
> ### this is the loop I would like to optimize:
> ### looping over arrays is considered inefficient.
> ### what could be a better way?
> hours_array = dates_array.copy()
> for i in range(0, dates_array.size):
> hours_array[i] = dates_array[i].hour
Hello,
I have an array of datetime objects.
What is the most efficient way of creating a new array
with only the hours or minutes out of it?
Here is an example:
### imports
import numpy as np
import datetime as dt
### create some data
d = dt.datetime.now()
dates_li = []
count = 0
for i in ran
I think this is doable; thankfully the Intel compilers on Windows and
Linux are very similar in behavior. The exact same build scripts
*should*work fine provided the file extensions (.o --> .obj) and flags
(-L, etc.)
are modified. In terms of syntax this should be an easy thing to do (it was
wit
On Wed, Jan 28, 2009 at 1:06 AM, David Cournapeau <
da...@ar.media.kyoto-u.ac.jp> wrote:
> Michael Colonno wrote:
> >Thanks for your response. I manually edited one of the python files
> > (ccompiler.py I think) to change icc.exe to icl.exe. (This is a trick
> > I used to use to get F2PY to co
Michael Colonno wrote:
>Thanks for your response. I manually edited one of the python files
> (ccompiler.py I think) to change icc.exe to icl.exe. (This is a trick
> I used to use to get F2PY to compile on Windows platforms.) Since icl
> is a drop-in replacement for the visual studio compiler /
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