Julian Taylor googlemail.com> writes:
>
> On 16.05.2014 10:59, Dave Hirschfeld wrote:
> > Julian Taylor googlemail.com> writes:
> >
> > Yes, I'd heard about the improvements and am very excited to try them out
> > since indexing is one of the bottlenecks in our algorithm.
> >
>
> I made a
Please would anyone tell me the following is an undocumented bug
otherwise I will lose faith in everything:
==
import numpy as np
years = [2004,2005,2006,2007]
dates = [20040501,20050601,20060801,20071001]
for x in years:
print 'year ',x
xy = np.array([x*1.0e-4 for x in dates]).a
On Wed, May 21, 2014 at 3:29 PM, Siegfried Gonzi
wrote:
> Please would anyone tell me the following is an undocumented bug
> otherwise I will lose faith in everything:
>
> ==
> import numpy as np
>
>
> years = [2004,2005,2006,2007]
>
> dates = [20040501,20050601,20060801,20071001]
>
> for x in yea
On Wed, May 21, 2014 at 12:38 PM, alex wrote:
> > years = [2004,2005,2006,2007]
> >
> > dates = [20040501,20050601,20060801,20071001]
> >
> > for x in years:
> >
> > print 'year ',x
> >
> > xy = np.array([x*1.0e-4 for x in dates]).astype(np.int)
> >
> > print 'year ',x
>
did you
On 5/21/14, Siegfried Gonzi wrote:
> Please would anyone tell me the following is an undocumented bug
> otherwise I will lose faith in everything:
>
> ==
> import numpy as np
>
>
> years = [2004,2005,2006,2007]
>
> dates = [20040501,20050601,20060801,20071001]
>
> for x in years:
>
> print 'y
Hello,
I would like to expose an existing (C++) object as a NumPy array to
Python. Right now I'm using PyArray_New, passing the pointer to my
object's storage. It now happens that the storage point of my object may
change over its lifetime, so I'd like to change the pointer that is used
in the PyA
Hi Stefan,
Allocating a new PyArrayObject isn't terribly expensive (compared to
all the other allocations that Python programs are constantly doing),
but I'm afraid you have a more fundamental problem. The reason there
is no supported API to change the storage pointer of a PyArrayObject
is that th
Hi Nathaniel,
thanks for the prompt and thorough answer. You are entirely right, I
hadn't thought things through properly, so let me back up a bit.
I want to provide Python bindings to a C++ library I'm writing, which is
based on vector/matrix/tensor data types. In my naive view I would
expose th
Hi Stefan,
One possibility that comes to mind: you may want in any case some way
to temporarily "pin" an object's memory in place (e.g., to prevent one
thread trying to migrate it while some other thread is working on it).
If so then the Python wrapper could acquire a pin when the ndarray is
alloc
I have hourly 2D temperature data in a monthly netcdf and I would like to
find the daily maximum temperature. The shape of the netcdf is (744, 106,
193)
I would like to use the year-month-day as a new list name (i.e. 2009-03-01,
2009-03-022009-03-31) and then add each of the hours worth of
tem
Hello anonymous,
I recently wrote a package "xray" (http://xray.readthedocs.org/)
specifically to make it easier to work with high-dimensional labeled data,
as often found in NetCDF files. Xray has a groupby method for grouping over
subsets of your data, which would seem well suited to what you're
Thanks Stephan,
It doesn't look like CDAT has 'daily' option - it has yearly, seasonal and
monthly! I would need to look into IRIS more as it is new to me and I can't
quiet figure out all the steps required for xray, although it looks great.
Another way around was after converting to localtime_day
On 22/05/2014 00:37, numpy-discussion-requ...@scipy.org wrote:
> Message: 4 Date: Wed, 21 May 2014 18:32:30 -0400 From: Warren
> Weckesser Subject: Re: [Numpy-discussion]
> Easter Egg or what I am missing here? To: Discussion of Numerical
> Python Message-ID:
>
> Content-Type: text/plain; c
I agree; this 'wart' has also messed with my code a few times. I didn't
find it to be the case two years ago, but perhaps I should reevaluate if
the scientific python stack has sufficiently migrated to python 3.
On Thu, May 22, 2014 at 7:35 AM, Siegfried Gonzi
wrote:
> On 22/05/2014 00:37, numpy
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