Hi all,
I have this piece of code:
Stats = [CatBase, round(stats.mean(Data.Ra), 5), round(stats.mean(Data.Dec),
5), len(Sep), round(stats.mean(Sep),4), round(stats.stdev(Sep),4)]
print Stats
if First:
StatsAll = np.array(np.asarray(Stats), dtype=('a11, f8, f8, i4, f8,
f8'))
On Aug 30, 2011, at 10:46 AM, Marquette Jean-Baptiste wrote:
Hi all,
I have this piece of code:
Stats = [CatBase, round(stats.mean(Data.Ra), 5), round(stats.mean(Data.Dec),
5), len(Sep), round(stats.mean(Sep),4), round(stats.stdev(Sep),4)]
print Stats
if First:
StatsAll =
Hello, All
As the subject say, I want to exercise *multiprocessing *module in NumPy in
order to take advantage of multi-cores. A project which processing large set
of data will be useful to compare single thread with multi-thread. I have
reviewed some projects using NumPy/SciPy list on SciPy
I've encountered something weird about numpy.void.
arr = np.empty ((len(results),), dtype=[('deltaf', float),
('quantize', [('int', int), ('frac',
int)])])
for i,r in enumerate (results):
arr[i] = (r[0]['deltaf'],
It looks like numpy.void does not properly implement __hash__:
In [35]: arr[0]['quantize'] == arr[1]['quantize']
Out[35]: True
In [34]: hash(arr[0]['quantize']) == hash(arr[1]['quantize'])
Out[34]: False
I'm not familiar enough with this kind of data type to tell you if you are
using it as it
Python 3.2, 64-bit Win 7
When I try to install numpy-1.6.1.win32-py3.2.exe (md5) I get Python
version 3.2 required, which was not found in the registry. What to
do?
Thanks,
Dick Moores
___
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
On Tue, Aug 30, 2011 at 7:47 AM, Richard D. Moores rdmoo...@gmail.comwrote:
Python 3.2, 64-bit Win 7
When I try to install numpy-1.6.1.win32-py3.2.exe (md5) I get Python
version 3.2 required, which was not found in the registry. What to
do?
Did you already install python from
On Tue, Aug 30, 2011 at 06:53, Charles R Harris
charlesr.har...@gmail.com wrote:
On Tue, Aug 30, 2011 at 7:47 AM, Richard D. Moores rdmoo...@gmail.com
wrote:
Python 3.2, 64-bit Win 7
When I try to install numpy-1.6.1.win32-py3.2.exe (md5) I get Python
version 3.2 required, which was not
On Tue, Aug 30, 2011 at 8:56 AM, Richard D. Moores rdmoo...@gmail.com wrote:
On Tue, Aug 30, 2011 at 06:53, Charles R Harris
charlesr.har...@gmail.com wrote:
On Tue, Aug 30, 2011 at 7:47 AM, Richard D. Moores rdmoo...@gmail.com
wrote:
Python 3.2, 64-bit Win 7
When I try to install
I have numpy version 1.6.1 and I see the following behavior :
In [380]: X
Out[380]: 1.0476157527896641
In [381]: X.__class__
Out[381]: numpy.float64
In [382]: (2,3)*X
Out[382]: (2, 3)
In [383]: (2,3)/X
Out[383]: array([ 1.90909691, 2.86364537])
In [384]: X=float(X)
In [385]: (2,3)/X
On Tue, Aug 30, 2011 at 8:33 AM, Johann Cohen-Tanugi
johann.cohentan...@gmail.com wrote:
I have numpy version 1.6.1 and I see the following behavior :
In [380]: X
Out[380]: 1.0476157527896641
In [381]: X.__class__
Out[381]: numpy.float64
In [382]: (2,3)*X
Out[382]: (2, 3)
In [383]:
2011/8/30 Charles R Harris charlesr.har...@gmail.com
On Tue, Aug 30, 2011 at 8:33 AM, Johann Cohen-Tanugi
johann.cohentan...@gmail.com wrote:
I have numpy version 1.6.1 and I see the following behavior :
In [380]: X
Out[380]: 1.0476157527896641
In [381]: X.__class__
Out[381]:
On Tue, Aug 30, 2011 at 07:19, Bruce Southey bsout...@gmail.com wrote:
On Tue, Aug 30, 2011 at 8:56 AM, Richard D. Moores rdmoo...@gmail.com wrote:
On Tue, Aug 30, 2011 at 06:53, Charles R Harris
charlesr.har...@gmail.com wrote:
On Tue, Aug 30, 2011 at 7:47 AM, Richard D. Moores
2011/8/30 Richard D. Moores rdmoo...@gmail.com
Is it possible to install 32-bit
Python 3.2 on 64-bit Win 7 (you seem to have done so), so I could use
numpy?
Yes you can insteall Python 32 bit on 64 bit Windows.
-=- Olivier
___
NumPy-Discussion
On Tue, Aug 30, 2011 at 08:51, Olivier Delalleau sh...@keba.be wrote:
2011/8/30 Richard D. Moores rdmoo...@gmail.com
Is it possible to install 32-bit
Python 3.2 on 64-bit Win 7 (you seem to have done so), so I could use
numpy?
Yes you can insteall Python 32 bit on 64 bit Windows.
Thanks.
On Tue, Aug 30, 2011 at 10:01 AM, Richard D. Moores rdmoo...@gmail.comwrote:
On Tue, Aug 30, 2011 at 08:51, Olivier Delalleau sh...@keba.be wrote:
2011/8/30 Richard D. Moores rdmoo...@gmail.com
Is it possible to install 32-bit
Python 3.2 on 64-bit Win 7 (you seem to have done so), so I
On 8/27/11 11:08 AM, Christopher Jordan-Squire wrote:
I've submitted a pull request for a new method for loading data from
text files into a record array/masked record array.
Click on the link for more info, but the general idea is to create a
regular expression for what entries should look
On Tue, Aug 30, 2011 at 09:09, Charles R Harris
charlesr.har...@gmail.com wrote:
On Tue, Aug 30, 2011 at 10:01 AM, Richard D. Moores rdmoo...@gmail.com
wrote:
On Tue, Aug 30, 2011 at 08:51, Olivier Delalleau sh...@keba.be wrote:
2011/8/30 Richard D. Moores rdmoo...@gmail.com
Is it
On Tue, Aug 30, 2011 at 10:27 AM, Richard D. Moores rdmoo...@gmail.comwrote:
On Tue, Aug 30, 2011 at 09:09, Charles R Harris
charlesr.har...@gmail.com wrote:
On Tue, Aug 30, 2011 at 10:01 AM, Richard D. Moores rdmoo...@gmail.com
wrote:
On Tue, Aug 30, 2011 at 08:51, Olivier
On Tue, Aug 30, 2011 at 09:43, Charles R Harris
charlesr.har...@gmail.com wrote:
You might want to download ipython and matplotlib also so that you have the
basic numpy stack.
Good idea. I got matplotlib, but ipython for Python 3x isn't on
http://www.lfd.uci.edu/~gohlke/pythonlibs/ .
Dick
On Tue, Aug 30, 2011 at 10:22, Charles R Harris
charlesr.har...@gmail.com wrote:
On Tue, Aug 30, 2011 at 11:02 AM, Richard D. Moores rdmoo...@gmail.com
wrote:
On Tue, Aug 30, 2011 at 09:43, Charles R Harris
charlesr.har...@gmail.com wrote:
You might want to download ipython and
On Tue, Aug 30, 2011 at 09:52, Charles R Harris
charlesr.har...@gmail.com wrote:
On Tue, Aug 30, 2011 at 8:33 AM, Johann Cohen-Tanugi
johann.cohentan...@gmail.com wrote:
I have numpy version 1.6.1 and I see the following behavior :
In [380]: X
Out[380]: 1.0476157527896641
In [381]:
I am not sure I follow : is the problem the coerce-sequences-to-ndarrays
behavior, or is it the fact that it applies to division and not
multiplication?
I thought the second situation is the more problematic.
Anyway, you seem to take it as a bug, should I file a ticket somewhere?
thanks,
johann
On Tue, Aug 30, 2011 at 13:58, Johann Cohen-Tanugi
johann.cohentan...@gmail.com wrote:
I am not sure I follow : is the problem the coerce-sequences-to-ndarrays
behavior, or is it the fact that it applies to division and not
multiplication?
I thought the second situation is the more
ok thanks a lot. Safe code is often better than over-smart code, so I
would line up with Charles here. There is too much potential for
ambiguity in expected behavior.
Johann
On 08/30/2011 09:06 PM, Robert Kern wrote:
On Tue, Aug 30, 2011 at 13:58, Johann Cohen-Tanugi
Hello all,
So i'm using numpy 1.6.0, and trying to convert a (4,4) numpy array of dtype
'f8' into a record array of this dtype:
dt = np.dtype([('mat','(4,4)f8')])
Here is the code snippet:
In [21]: a = np.random.randn(4,4)
In [22]: a.view(dt)
and the resulting error:
ValueError: new type
Hello All,
Last week I posted a question involving the identification of linear dependent
columns of a matrix... but now I am finding an interesting result based on the
linalg.inv() function... sometime I am able to invert a matrix that has linear
dependent columns and other times I get the
On Tue, Aug 30, 2011 at 17:48, Mark Janikas mjani...@esri.com wrote:
Hello All,
Last week I posted a question involving the identification of linear
dependent columns of a matrix… but now I am finding an interesting result
based on the linalg.inv() function… sometime I am able to invert a
Can you give an example matrix? I'm not a numerical linear algebra
expert, but I suspect that if your matrix is singular (or nearly so,
in floating point) then any inverse given will look pretty wonky. Huge
determinant, eigenvalues, operator norm, etc..
-Chris JS
On Tue, Aug 30, 2011 at 5:48 PM,
Working on it... Give me a few minutes to get you the data. TY!
MJ
-Original Message-
From: numpy-discussion-boun...@scipy.org
[mailto:numpy-discussion-boun...@scipy.org] On Behalf Of Christopher
Jordan-Squire
Sent: Tuesday, August 30, 2011 3:57 PM
To: Discussion of Numerical Python
When I export to ascii I am losing precision and it getting consistency... I
will try a flat dump. More to come. TY
MJ
-Original Message-
From: numpy-discussion-boun...@scipy.org
[mailto:numpy-discussion-boun...@scipy.org] On Behalf Of Mark Janikas
Sent: Tuesday, August 30, 2011 4:02
On Tue, Aug 30, 2011 at 18:34, Mark Janikas mjani...@esri.com wrote:
When I export to ascii I am losing precision and it getting consistency... I
will try a flat dump. More to come. TY
Might as well np.save() it to an .npy binary file and attach it.
--
Robert Kern
I have come to believe
On Tue, Aug 30, 2011 at 17:48, Mark Janikas mjani...@esri.com wrote:
Hello All,
Last week I posted a question involving the identification of linear
dependent columns of a matrix… but now I am finding an interesting result
based on the linalg.inv() function… sometime I am able to invert a
OK... so I have been using checksums to compare and it looks like I am getting
a different value when it fails as opposed to when it passes... I.e. the input
is NOT the same. When I save them to npy files and run LA.inv() I get
consistent results. Now I have to track down in my code why the
Hello,
Is the following behavior normal?
In [1]: import numpy as np
In [2]: np.dtype([('a','f4',2)])
Out[2]: dtype([('a', 'f4', (2,))])
In [3]: np.dtype([('a','f4',1)])
Out[3]: dtype([('a', 'f4')])
I.e. in the second case, the second dimension of the dtype (1) is
being ignored? Is there a way
Hi,
this is probably my lack of understanding...when i set up some masks for 2
arrays and try to divide one by the other I get a runtime warning. Seemingly
this is when I am asking python to divide one nan by the other, however I
thought by masking the array numpy would then know to ignore these
On Tue, Aug 30, 2011 at 10:34 PM, Thomas Robitaille
thomas.robitai...@gmail.com wrote:
Hello,
Is the following behavior normal?
In [1]: import numpy as np
In [2]: np.dtype([('a','f4',2)])
Out[2]: dtype([('a', 'f4', (2,))])
In [3]: np.dtype([('a','f4',1)])
Out[3]: dtype([('a', 'f4')])
On Tue, Aug 30, 2011 at 4:34 PM, Bryce Ready bryce.re...@gmail.com wrote:
Hello all,
So i'm using numpy 1.6.0, and trying to convert a (4,4) numpy array of dtype
'f8' into a record array of this dtype:
dt = np.dtype([('mat','(4,4)f8')])
Here is the code snippet:
In [21]: a =
Hi,
This is my second post on this problem I found in numpy 1.6.1, and recently it
cam up in the latest git version (2.0.0.dev-f3e70d9). The problem is numpy
treats the native byte order ('') as illegal while the wrong one ('') as the
right one. The output of the attached script (bult for
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