Hello,
I am going to the PyCon this week. I am presenting a poster about an
atmospheric sciences related project -- the most active development
from my coding site over at http://code.google.com/p/ccnworks/
Is there anybody in the community participating there as well? Any
plans for sprinting or
Mon, 07 Mar 2011 11:03:17 +0800, Ralf Gommers wrote:
[clip]
If anyone has new deprecations they want to put in for 1.6, discussing
them now would be good. I found one item in Trac, #1543. The proposal in
the ticket is to deprecate assert_almost_equal because it is quite badly
behaved. This
On Mon, Mar 7, 2011 at 4:10 AM, Pauli Virtanen p...@iki.fi wrote:
Mon, 07 Mar 2011 11:03:17 +0800, Ralf Gommers wrote:
[clip]
If anyone has new deprecations they want to put in for 1.6, discussing
them now would be good. I found one item in Trac, #1543. The proposal in
the ticket is to
Mon, 07 Mar 2011 06:39:20 -0500, josef.pktd wrote:
[clip]
Why does assert_allclose have atol=0, while np.allclose has rtol=1.e-5,
atol=1.e-8 ?
Probably no reason, it should be fixed.
What's the status on np.testing.assert_approx_equal, I would have liked
to use it more often, except it
A Monday 28 February 2011 16:31:59 Ralf Gommers escrigué:
Proposed schedule:
March 15: beta 1
March 28: rc 1
April 17: rc 2 (if needed)
April 24: final release
Let me know what you think. Bonus points for volunteering to fix
some of those tickets:)
While doing tests on the new
Hello all,
I am new to python and numpy.
My question is how to sum up N weighted matrices.
For example w=[1,2] (N=2 case)
m1=[1 2 3,
3 4 5]
m2=[3 4 5,
4 5 6]
I want to get a matrix Y=w[1]*m1+w[2]*m2 by using a loop.
My original problem is like this
X=[1 2 3,
3 4 5,
4 5
A Sunday 06 March 2011 06:47:34 Mark Wiebe escrigué:
I think it's ok to revert this behavior for backwards compatibility,
but believe it's an inconsistent and unintuitive choice. In
broadcasting, there are two operations, growing a dimension 1 - n,
and appending a new 1 dimension to the left.
On Mon, Mar 7, 2011 at 6:53 AM, Pauli Virtanen p...@iki.fi wrote:
Mon, 07 Mar 2011 06:39:20 -0500, josef.pktd wrote:
[clip]
Why does assert_allclose have atol=0, while np.allclose has rtol=1.e-5,
atol=1.e-8 ?
Probably no reason, it should be fixed.
What's the status on
Mon, 07 Mar 2011 08:30:11 -0500, josef.pktd wrote:
[clip]
assert_approx_equal checks for signigicant digits in decimal system,
which looks like it's easy to interpret.
Ditto for tolerance=1e-7, which has the advantage that it's what
print abs(desired-actual) prints.
I don't have much idea
On Mon, Mar 7, 2011 at 5:17 AM, Francesc Alted fal...@pytables.org wrote:
A Monday 28 February 2011 16:31:59 Ralf Gommers escrigué:
Proposed schedule:
March 15: beta 1
March 28: rc 1
April 17: rc 2 (if needed)
April 24: final release
Let me know what you think. Bonus points
Mon, 07 Mar 2011 13:17:55 +0100, Francesc Alted wrote:
[clip]
from tables.utilsExtension import getPyTablesVersion, getHDF5Version
File definitions.pxd, line 138, in init tables.utilsExtension
(tables/utilsExtension.c:9238)
ValueError: numpy.dtype has the wrong size, try recompiling
A Monday 07 March 2011 14:49:26 Pauli Virtanen escrigué:
Mon, 07 Mar 2011 13:17:55 +0100, Francesc Alted wrote:
[clip]
from tables.utilsExtension import getPyTablesVersion,
getHDF5Version
File definitions.pxd, line 138, in init tables.utilsExtension
On Mon, Mar 7, 2011 at 5:53 PM, Gökhan Sever gokhanse...@gmail.com wrote:
Hello,
I am going to the PyCon this week. I am presenting a poster about an
atmospheric sciences related project -- the most active development
from my coding site over at http://code.google.com/p/ccnworks/
Is there
Mon, 07 Mar 2011 14:57:39 +0100, Francesc Alted wrote:
[clip]
However, the size of PyArray_Descr does not seem to have changed
between 1.5.1 and the Git master. So I'm not sure why you see this
error...
Maybe a Cython problem?
That would be seriously weird. Maybe the binaries you have
A Monday 07 March 2011 15:17:17 Pauli Virtanen escrigué:
Mon, 07 Mar 2011 14:57:39 +0100, Francesc Alted wrote:
[clip]
However, the size of PyArray_Descr does not seem to have changed
between 1.5.1 and the Git master. So I'm not sure why you see
this error...
Maybe a Cython
Mon, 07 Mar 2011 15:23:10 +0100, Francesc Alted wrote:
[clip]
ValueError: numpy.dtype has the wrong size, try recompiling
I don't think I'm wrong here, but I'd appreciate if somebody else can
reproduce this (either with tables or with another Cython-dependent
package).
Ok, seems this needs
Thanks for your reply Ralf. I'm not sure if it's a warning or error, output
looks like:
...
building library npymath sources
customize GnuFCompiler
Found executable /usr/bin/g77
gnu: no Fortran 90 compiler found
gnu: no Fortran 90 compiler found
customize GnuFCompiler
gnu: no Fortran 90
reshape can view a 1d array as non-overlapping segments.
Is there a convenient way to view a 1d array as a 2d array of overlapping
segments?
nonoverlapping:
l: segment length
k: overlap
u is the 1d array
v is a 2d array
v[i] = u[l*i:(l+1)*i]
overlapping:
v[i] = u[l*i:(l+1)*i+k]
On Mon, Mar 7, 2011 at 8:37 AM, Pauli Virtanen p...@iki.fi wrote:
Mon, 07 Mar 2011 08:30:11 -0500, josef.pktd wrote:
[clip]
assert_approx_equal checks for signigicant digits in decimal system,
which looks like it's easy to interpret.
Ditto for tolerance=1e-7, which has the advantage that
Here is some *working* code i wrote once. It uses strides, look at the
docs for what it is.
from numpy.lib import stride_tricks
def overlap_array( y, len_blocks, overlap=0 ):
Make use of strides to return a two dimensional whose
rows come from a one dimensional array. Strides
On 03/07/2011 03:55 PM, John Cartwright wrote:
Thanks for your reply Ralf. I'm not sure if it's a warning or error, output
looks like:
...
building library npymath sources
customize GnuFCompiler
Found executable /usr/bin/g77
gnu: no Fortran 90 compiler found
gnu: no Fortran 90 compiler
On 03/07/2011 04:15 PM, Dag Sverre Seljebotn wrote:
On 03/07/2011 03:55 PM, John Cartwright wrote:
Thanks for your reply Ralf. I'm not sure if it's a warning or error, output
looks like:
...
building library npymath sources
customize GnuFCompiler
Found executable /usr/bin/g77
gnu: no
Hi,
On Mon, Mar 7, 2011 at 5:01 PM, Neal Becker ndbeck...@gmail.com wrote:
reshape can view a 1d array as non-overlapping segments.
Is there a convenient way to view a 1d array as a 2d array of overlapping
segments?
nonoverlapping:
l: segment length
k: overlap
u is the 1d array
v is a
On 3/6/11 5:54 AM, Charles R Harris wrote:
I suppose this might cause a problem with lazy/quick c extensions that
expected elements in a certain order, so some breakage could occur.
absolutely!
(I've gotten a bit confused about this thread, but if this is about the
question of whether
On Mon, Mar 7, 2011 at 11:08, Christopher Barker chris.bar...@noaa.gov wrote:
On 3/6/11 5:54 AM, Charles R Harris wrote:
I suppose this might cause a problem with lazy/quick c extensions that
expected elements in a certain order, so some breakage could occur.
absolutely!
(I've gotten a bit
Hi folks,
I'm setting out to write some code to access and work with ragged arrays
stored in netcdf files. It dawned on me that ragged arrays are not all
that uncommon, so I'm wondering if any of you have any code you've
developed that I could learn-from borrow from, etc.
note that when I say
A Monday 07 March 2011 15:39:38 Pauli Virtanen escrigué:
Mon, 07 Mar 2011 15:23:10 +0100, Francesc Alted wrote:
[clip]
ValueError: numpy.dtype has the wrong size, try recompiling
I don't think I'm wrong here, but I'd appreciate if somebody else
can reproduce this (either with tables
A Monday 07 March 2011 18:28:11 Christopher Barker escrigué:
Hi folks,
I'm setting out to write some code to access and work with ragged
arrays stored in netcdf files. It dawned on me that ragged arrays
are not all that uncommon, so I'm wondering if any of you have any
code you've developed
Mon, 07 Mar 2011 11:23:33 -0600, Robert Kern wrote:
[clip]
Can someone explain exactly what changed? Or point to the changeset that
made it? It's not clear to me what operations are different under Mark's
changes.
Mark mentioned three points here:
On 3/7/11 10:28 AM, Christopher Barker wrote:
Hi folks,
I'm setting out to write some code to access and work with ragged arrays
stored in netcdf files. It dawned on me that ragged arrays are not all
that uncommon, so I'm wondering if any of you have any code you've
developed that I could
@Jeff
I need to work with ragged arrays too. Are object arrays of 1d numpy arrays
slower than lists of 1d numpy arrays?
@ Christopher
I'd be interested in hearing if you come up with any better solutions.
On Mon, Mar 7, 2011 at 9:37 AM, Jeff Whitaker jsw...@fastmail.fm wrote:
On 3/7/11 10:28
On Mon, Mar 7, 2011 at 9:23 AM, Robert Kern robert.k...@gmail.com wrote:
On Mon, Mar 7, 2011 at 11:08, Christopher Barker chris.bar...@noaa.gov
wrote:
On 3/6/11 5:54 AM, Charles R Harris wrote:
I suppose this might cause a problem with lazy/quick c extensions that
expected elements in a
for your problem, you can do:
import numpy as np
weights = np.array([1,2])
matrix1 = np.ones((2,3))
matrix2 = 2*np.ones((2,3))
matrices = np.array([matrix1,matrix2])
weighted_sum = np.tensordot(weights, matrices, (0,0))
--
On Mon, Mar
Hi
I know Numeric 24.2 is really old and probably unsupported by now, but I
thought it might be of interest that Service Pack 1 for Windows 7 has
broken Numeric 24.2.
We have an old software product that uses Python 2.3 and Numeric 24.2,
frozen using py2exe, and we started receiving reports
On 3/7/11 9:33 AM, Francesc Alted wrote:
A Monday 07 March 2011 18:28:11 Christopher Barker escrigué:
I'm setting out to write some code to access and work with ragged
arrays stored in netcdf files. It dawned on me that ragged arrays
are not all that uncommon, so I'm wondering if any of you
On 3/7/11 11:42 AM, Christopher Barker wrote:
On 3/7/11 9:33 AM, Francesc Alted wrote:
A Monday 07 March 2011 18:28:11 Christopher Barker escrigué:
I'm setting out to write some code to access and work with ragged
arrays stored in netcdf files. It dawned on me that ragged arrays
are not all
A Monday 07 March 2011 19:42:00 Christopher Barker escrigué:
But now that you've entered the conversation, does HDF and/or
pytables have a standard way of dealing with this?
Well, I don't think there is such a 'standard' way for dealing with
ragged arrays, but yes, pytables has support for
On 3/7/11 11:18 AM, Francesc Alted wrote:
Well, I don't think there is such a 'standard' way for dealing with
ragged arrays, but yes, pytables has support for them. Creating them is
easy:
# Create a VLArray:
fileh = tables.openFile('vlarray1.h5', mode='w')
vlarray =
On 7 March 2011 15:29, Christopher Barker chris.bar...@noaa.gov wrote:
On 3/7/11 11:18 AM, Francesc Alted wrote:
but, instead of returning a numpy array of 'object' elements, plain
python lists are returned instead.
which gives you the append option -- I can see how that would be
usefull.
On 3/7/11 3:36 PM, Dan Halbert wrote:
We currently have some straightforward NumPy code that indirectly implements
a C API defined by a third party. We built a Cython layer that directly
provides the API in a .a library, and then calls Python. The layering looks
like this:
C main
On 3/7/2011 6:48 PM, Christopher Barker wrote:
On 3/7/11 3:36 PM, Dan Halbert wrote:
We currently have some straightforward NumPy code that indirectly implements
a C API defined by a third party. We built a Cython layer that directly
provides the API in a .a library, and then calls Python.
Den 07.03.2011 18:28, skrev Christopher Barker:
1, 2, 3, 4
5, 6
7, 8, 9, 10, 11, 12
13, 14, 15
...
In my case, these will only be 2-d, though I suppose one could have a
n-d version where the last dimension was ragged (or any dimension, I
suppose, though I'm having trouble wrapping my
Thanks very much. It works.
On Mon, Mar 7, 2011 at 11:53 AM, qu...@gmx.at wrote:
for your problem, you can do:
import numpy as np
weights = np.array([1,2])
matrix1 = np.ones((2,3))
matrix2 = 2*np.ones((2,3))
matrices = np.array([matrix1,matrix2])
Den 08.03.2011 00:36, skrev Dan Halbert:
Do you all have some recommendations about tools, libraries, or languages
that you have used to rewrite NumPy code easily into something that's more
self-contained and callable from C?
Fortran 95
It has the power of C, without the unsafe pointer
On Mon, Mar 7, 2011 at 3:36 PM, Dan Halbert halb...@halwitz.org wrote:
Or is there some higher-level compiled array language that looks something
like NumPy code?
You might want to try Eigen:
http://eigen.tuxfamily.org/
-- Nathaniel
___
On 3/7/2011 9:13 PM, Sturla Molden wrote:
Den 08.03.2011 00:36, skrev Dan Halbert:
Do you all have some recommendations about tools, libraries, or languages
that you have used to rewrite NumPy code easily into something that's more
self-contained and callable from C?
Fortran 95
It has
On 3/7/2011 9:25 PM, Nathaniel Smith wrote:
On Mon, Mar 7, 2011 at 3:36 PM, Dan Halberthalb...@halwitz.org wrote:
Or is there some higher-level compiled array language that looks something
like NumPy code?
You might want to try Eigen:
http://eigen.tuxfamily.org/
Thanks - didn't know
On Mon, Mar 7, 2011 at 4:22 PM, Dan Halbert halb...@halwitz.org wrote:
On 3/7/2011 6:48 PM, Christopher Barker wrote:
On 3/7/11 3:36 PM, Dan Halbert wrote:
We currently have some straightforward NumPy code that indirectly
implements a C API defined by a third party. We built a Cython layer
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