Thanks Travis.
Do I understand correctly that the only way to be really safe is to make a
copy and not to export a reference to it?
Because anybody having a reference to the owner of the data can override the
flag?
Cheers,
Martin
On Wednesday 20 September 2006 20:18, Travis Oliphant wrote:
Hi,
I just installed rc1 on an AMD64 machine. but I get this error message when
trying to import it:
Python 2.4.3 (#1, Sep 21 2006, 13:06:42)
[GCC 4.1.1 (Gentoo 4.1.1)] on linux2
Type help, copyright, credits or license for more information.
import numpy
Traceback (most recent call last):
Hi all,
Is it possible to put masked values into recarrays, I need a array with
heterogenous types of datas (datetime objects in the first col, all others
are float) but with missing values in some records. For the moment, I don't
find any solution for that. I have tried with arrays of
On 9/21/06, Peter Bienstman [EMAIL PROTECTED] wrote:
Hi,I just installed rc1 on an AMD64 machine. but I get this error message whentrying to import it:Python 2.4.3 (#1, Sep 21 2006, 13:06:42)[GCC 4.1.1 (Gentoo 4.1.1)] on linux2Type help, copyright, credits or license for more information.
import
Charles R Harris wrote:
Travis,
A few questions.
1) I can't find any systematic code testing units, although there seem
to be tests for regressions and such. Is there a place we should be
putting such tests?
All tests are placed under the tests directory of the corresponding
sub-package.
Are able to use doxygen for Python code ? I thought it only worked for C (and
alike) ?
There is an ugly-hack :)
http://i31www.ira.uka.de/~baas/pydoxy/
But I wouldn't recommend using it, rather stick with Epydoc.
--
Louis Cordier [EMAIL PROTECTED] cell: +27721472305
Point45 Entertainment
Lionel Roubeyrie wrote:
Hi all,
Is it possible to put masked values into recarrays, I need a array with
heterogenous types of datas (datetime objects in the first col, all others
are float) but with missing values in some records. For the moment, I don't
find any solution for that.
Either
Hi,
It's in the array interface specification:
http://numpy.scipy.org/array_interface.shtml
I was interested in the 't' (bitfield) type - is there an example of
usage somewhere?
In [13]: dtype('t8')
---
Matthew Brett wrote:
Hi,
It's in the array interface specification:
http://numpy.scipy.org/array_interface.shtml
I was interested in the 't' (bitfield) type - is there an example of
usage somewhere?
No, It's not implemented in NumPy. It's just part of the array
interface
Lionel Roubeyrie wrote:
find any solution for that. I have tried with arrays of dtype=object, but I
have problem when I want to compute min, max, ... with an error like:
TypeError: function not supported for these types, and can't coerce safely to
supported types.
I just added support
Hi,
On 9/21/06, Robert Kern [EMAIL PROTECTED] wrote:
Steve Lianoglou wrote: So .. I guess I'm wondering why we want to break from the standard?We don't as far as Python code goes. The code that Chuck added Doxygen-stylecomments to was C code. I presume he was simply answering Sebastian's question
On Thu, 21 Sep 2006 11:34:42 -0700
Tim Hochberg [EMAIL PROTECTED] wrote:
Tim Hochberg wrote:
Robert Kern wrote:
David M. Cooke wrote:
On Wed, Sep 20, 2006 at 03:01:18AM -0500, Robert Kern wrote:
Let me offer a third path: the algorithms used for .mean()
David M. Cooke wrote:
Conclusions:
- If you're going to calculate everything in single precision, use Kahan
summation. Using it in double-precision also helps.
- If you can use a double-precision accumulator, it's much better than any of
the techniques in single-precision only.
- for
On Thursday 21 September 2006 18:24, Travis Oliphant wrote:
Martin Wiechert wrote:
Thanks Travis.
Do I understand correctly that the only way to be really safe is to make
a copy and not to export a reference to it?
Because anybody having a reference to the owner of the data can override
David M. Cooke wrote:
On Thu, 21 Sep 2006 11:34:42 -0700
Tim Hochberg [EMAIL PROTECTED] wrote:
Tim Hochberg wrote:
Robert Kern wrote:
David M. Cooke wrote:
On Wed, Sep 20, 2006 at 03:01:18AM -0500, Robert Kern wrote:
Let
Hi,
on linux I get an error when trying to build a rpm package from numpy 1.0rc1:
building extension numpy.core.umath sources
adding 'build/src.linux-i686-2.4/numpy/core/config.h' to sources.
executing numpy/core/code_generators/generate_ufunc_api.py
adding
On Thursday 21 September 2006 15:28, Tim Hochberg wrote:
David M. Cooke wrote:
On Thu, 21 Sep 2006 11:34:42 -0700
Tim Hochberg [EMAIL PROTECTED] wrote:
Tim Hochberg wrote:
Robert Kern wrote:
David M. Cooke wrote:
On Wed, Sep 20, 2006 at 03:01:18AM -0500, Robert Kern wrote:
Let me
On 9/20/06, Bill Baxter [EMAIL PROTECTED] wrote:
Hey Andrew, point taken, but I think it would be better if someone whoactually knows the full extent of the change made the edit.I knowzeros and ones changed.Did anything else?Anyway, I'm surprised the release notes page is publicly editable.
I'm
Apparently numpy.matrixmultiply got moved into
numpy.oldnumeric.matrixmultiply at some point (or rather ceased to be
imported into the numpy namespace). Is there any list of all such
methods that got banished? This would be nice to have in the release
notes.
--bb
Hi,
from 1.0b1 to 1.0rc1 the default behaviour of take seems to have changed when
omitting the axis argument:
In [13]: a = reshape(arange(12),(3,4))
In [14]: take(a,[2,3])
Out[14]: array([2, 3])
In [15]: take(a,[2,3],1)
Out[15]:
array([[ 2, 3],
[ 6, 7],
[10, 11]])
Is this
Is there some way to get the equivalent of repmat() for ndim == 1 and ndim 2.
For ndim == 1, repmat always returns a 2-d array, instead of remaining 1-d.
For ndim 2, repmat just doesn't work.
Maybe we could add a 'reparray', with the signature:
reparray(A, repeats, axis=None)
where repeats is
Bill Baxter wbaxter at gmail.com writes:
Yep, check the release notes:
http://www.scipy.org/ReleaseNotes/NumPy_1.0
search for 'take' on that page to find out what others have changed as well.
--bb
Ok. Does axis=None then mean, that take(a, ind) operates on the flattened array?
This it at
Folks,
I'm running into the following problem with putmask on take.
import numpy
x = N.arange(12.)
m = [1, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1]
i = N.nonzero(m)[0]
w = N.array([-1, -2, -3, -4.])
x.putmask(w,m)
x.take(i)
N.allclose(x.take(i),w)
False
I'm wondering ifit is intentional, or
Cleaning out and rebuilding did the trick!
Thanks,
Peter
On Thursday 21 September 2006 18:33,
[EMAIL PROTECTED] wrote:
Subject: Re: [Numpy-discussion] 1.0rc1 doesn't seem to work on AMD64
snip
I don't see this running the latest from svn on AMD64 here. Not sayin'
there might not be a
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