Hi Carlos,On 8/27/06, Carlos Pita [EMAIL PROTECTED] wrote:
Hi all!Is there a more efficient way of creating a constant K-valued array of size N than:zeros(N) + K?Maybe something like this:I
n [12]: a = empty((3,3), dtype=int)In [13]: a.fill(11)
In [14]: aOut[14]:
array([[11, 11, 11],
[11, 11,
Matthew Auger wrote:
I recently installed python2.5c1, numpy-1.0b3, and matplotlib-0.87.4. I
was getting an error when importing pylab that led me to this curious
behavior:
matplotlib-0.87.4 is *not* compatible with 1.0b2 and above. A new
version needs to be released to work with
Tom Denniston wrote:
I was thinking about this in the context of Giudo's comments at scipy
2006 that much of the language is moving away from lists toward
iterators. He gave the keys of a dict as an example.
Numpy treats iterators, generators, etc as 0x0 PyObjects rather than
lazy
Tim Hochberg wrote:
I'm actually surprised that the take version is faster than my original
version since it makes a big ol' copy. I guess this is an indication
that indexing is more expensive than I realize. That's why nothing beats
measuring!
Actually, your original version is just as
Martin Spacek wrote:
Actually, your original version is just as fast as the take() version.
Both are about 9X faster than numpy.mean() on my system. I prefer the
take() version because you only have to pass a single argument to
mean_accum()
I forgot to mention that all my indices are,
Charles R Harris schrieb:
+1. I too suspect that what you have here is a reference/copy problem.
The only thing that is local to the class is the reference (pointer),
the data is global.
Chuck
Ok, so you guys were right, turns out that my problem was caused by the
fact that a local
Nope, that's the way python works in general for any type other than
basic scalar types.
a = [1,2,3,4]
b = a
b[1] = 99
print a
[1, 99, 3, 4]
print b
[1, 99, 3, 4]
Also the issue never comes up for types like tuples or strings because
they aren't mutable.
--bb
On 8/28/06, Sven Schreiber
Matt Knox wrote: Hi there. I'm in the unfortunate situation of trying to track down a memory error in someone elses code, and to make matters worse I don't really know jack squat about C programming. The problem seems to arise when several numpy arrays are created from C arrays in the C api
Numpy builds, but fails to run with the error message:
python
Python 2.4.2 (#1, Apr 24 2006, 18:13:30)
[GCC 4.1.0 (SUSE 10.1 Linux)] on linux2
import numpy
Traceback (most recent call last):
File stdin, line 1, in ?
File /usr/lib/python2.4/site-packages/numpy/__init__.py, line 35, in ?
Travis Oliphant wrote:
Instead, I like better the idea of adding abs, round, max, and min to
the non-import-* namespace of numpy.
Another I'd like is the built-in data types. I always use:
import numpy as N
so then I do:
a = zeros(shape, float)
or
a = zeros(shape, N.float_)
but for
rex wrote:
Numpy builds, but fails to run with the error message:
python
Python 2.4.2 (#1, Apr 24 2006, 18:13:30)
[GCC 4.1.0 (SUSE 10.1 Linux)] on linux2
import numpy
Traceback (most recent call last):
File stdin, line 1, in ?
File
Christopher Barker wrote:
Travis Oliphant wrote:
Instead, I like better the idea of adding abs, round, max, and min to
the non-import-* namespace of numpy.
Another I'd like is the built-in data types. I always use:
import numpy as N
so then I do:
a = zeros(shape, float)
or
The following code indicates there is a problem adding a numpy scalar
type to a Numeric array. Is this expected behavior or is there a bug
somewhere?
This bit me in the context of updating some of my code to numpy, while
part of it still uses Numeric.
import Numeric
import numpy
print
Hi all!I'm rewriting some swig-based extensions that implement intensive inner loops dealing with numeric/numpy arrays. The intention is to build these extensions by means of weave inline, ext_module, ext_function, etc. I'm not sure about how to point weave to my numpy instalation. By default it
On 8/25/06, Travis Oliphant [EMAIL PROTECTED] wrote:
[EMAIL PROTECTED] wrote:
Message: 4
Date: Thu, 24 Aug 2006 14:17:44 -0600
From: Travis Oliphant [EMAIL PROTECTED]
Subject: Re: [Numpy-discussion] (no subject)
To: Discussion of Numerical Python
[EMAIL PROTECTED] wrote:
On 8/25/06, Travis Oliphant [EMAIL PROTECTED] wrote:
[EMAIL PROTECTED] wrote:
Message: 4
Date: Thu, 24 Aug 2006 14:17:44 -0600
From: Travis Oliphant [EMAIL PROTECTED]
Subject: Re: [Numpy-discussion] (no subject)
To: Discussion of Numerical Python
Travis Oliphant wrote:
I think I prefer to just add the float, bool, object, unicode, str names
to the non-imported numpy
name-space.
which mean you get it with:
import numpy as N
N.float
but not with
from numpy import *
?
If that's what you mean, then I'm all for it!
-Chris
--
HI all,
Robin Dunn has been working on adding better support for dumping data
directly to wxPython from the num* packages. I've been talking to him
about the new array interface, and he might well support it
(particularly if one of us contributes code), but in the meantime, he's
got a number
Christopher Barker wrote:
HI all,
File
/usr/lib/python2.4/site-packages/wx-2.6-gtk2-unicode/wx/_core.py,
line 2814, in SetDataBuffer
return _core_.Image_SetDataBuffer(*args, **kwargs)
TypeError: non-character array cannot be interpreted as character buffer
If I try to pass in a
Christopher Barker wrote:
While I'm a great advocate of the new array protocol, it seems
supporting the buffer protocol also would be a good idea. I've enclosed
some simple test code. It works with numarray, but not numpy 1.0b4
Instead of
I.SetDataBuffer(some_array)
you can use
This is really a matplotlib problem.
From matplotlib users mailing-list archives:
From: Charlie Moad [EMAIL PROTECTED]
Snapshot build for use with numpy-1.0b3
2006-08-23 06:11
Here is a snapshot of svn this morning for those wanting to work with
the numpy beta. Both builds are for
Folks,
I keep running into the following problem since some recent update (I'm
currently running 1.0b3, but the problem occurred roughly around 0.9.8):
import numpy.core.ma as MA
x=MA.array([[1],[2]],mask=False)
x.sum(None)
/usr/lib64/python2.4/site-packages/numpy/core/ma.py in reduce(self,
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