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[sorry for crossposting]
Hi all,
After the success of last years workshop, we decided to hold the
Pytroll workshop this year again at SMHI.
Pytroll is a collection of free and open source python modules for the
reading, interpretation, and writing
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[sorry for crossposting]
Hi all,
After the success of last years workshop, we decided to hold the
Pytroll workshop this year again at SMHI.
Pytroll is a collection of free and open source python modules for the
reading, interpretation, and writing
Raspaud
# Author(s):
# Martin Raspaud martin.rasp...@smhi.se
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any
On 16/05/13 10:26, Robert Kern wrote:
Can anyone give a reasonable explanation ?
memory_profiler only looks at the amount of memory that the OS has
allocated to the Python process. It cannot measure the amount of
memory actually given to living objects. Python does not always return
memory
Hi,
We noticed that comparing arrays of different shapes with allclose
doesn't work anymore in numpy 1.6.2.
Is this a feature or a bug ? :)
See the output in both 1.6.1 and 1.6.2 at the end of this mail.
Best regards,
Martin
1.6.1::
In [1]: import numpy as np
In [2]: np.__version__
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On 14/02/12 16:48, Bruce Southey wrote:
On 02/14/2012 09:40 AM, Olivier Delalleau wrote:
Really not an expert here, but it looks like it's trying various
compilation options, some work and some don't, and for some reason
it's really unhappy about
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Hi all,
I am trying to compile numpy 1.6.1 from source on a Redhat Linux
enterprise 6 machine, and I get a problem with Python.h : somehow it
can't be located by numpy's install script:
SystemError: Cannot compile 'Python.h'. Perhaps you need to
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On 11/10/11 07:49, Martin Raspaud wrote:
Hi all,
[...]
I'm looking for the operation needed to get the two (stacked) vectors
array([[0, 1, 2],
[6, 8, 10]]))
or its transpose.
Hi again,
Here is a solution I just found:
np.einsum(ik, jki
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David Goldsmith skrev:
Ahh, cell arrays, they bring back memories. Makes you pine for a
dictionary, no?
JDH
Not to mention writeline, readline, string concatenation using +,
English wording of loops, list comprehension,
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David Goldsmith skrev:
Interesting comment: it made me run down the fftpack tutorial
http://docs.scipy.org/scipy/docs/scipy-docs/tutorial/fftpack.rst/
josef has alluded to in the past to see if the suggested pointer
could point
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Hi,
Is it possible to read an array of 12bit encoded numbers from file (or string)
using numpy ?
Thanks,
Martin
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Nadav Horesh skrev:
You can. If each number occupies 2 bytes (16 bits) it is straight
forward. If it is a continues 12 bits stream you have to unpack by your
self:
data = np.fromstring(str12bits, dtype=np.uint8)
data1 = data.astype(no.uint16)
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Francesc Alted skrev:
Hi Martin,
[...]
and the output for my machine:
result_array1: [4 2 4 ..., 1 3 4] 1.819
result_array2: [4 2 4 ..., 1 3 4] 0.308
which is a 6x speed-up. I suppose this should be pretty close of what you
can
get
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Hello,
I work on a 64bit machine with 64bits enable fedora on it.
I just discovered that numpy.int on the python part are 64bits ints, while
npy_int in the C api are 32bits ints.
I can live with it, but it seems to be different on 32bit machines,
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Dag Sverre Seljebotn skrev:
Martin Raspaud wrote:
Hello,
I work on a 64bit machine with 64bits enable fedora on it.
I just discovered that numpy.int on the python part are 64bits ints, while
npy_int in the C api are 32bits ints
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Pierre GM skrev:
On Mar 1, 2010, at 10:04 AM, Martin Raspaud wrote:
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Hi all,
We are using at the moment a c extension which should manipulate masked
arrays.
What we do is to fill the masked array
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