Hi Sameer
On Mon, Aug 20, 2007 at 06:26:30PM -0500, Sameer DCosta wrote:
> On 8/20/07, Stefan van der Walt <[EMAIL PROTECTED]> wrote:
> Thanks Stefan for offering to take a closer look. I have attached a
> patch against the latest svn which fixes this problem.
Yup, right on the money. The __seta
I'm pleased to announce the release of NumPy 1.0.3.1
This a minor bug fix release, which enables the latest release of
SciPy to build.
Bug-fixes
===
* Add back get_path to numpy.distutils.misc_utils
* Fix 64-bit zgeqrf
* Add parenthesis around GETPTR macros
Thank you to everybody who
On 8/20/07, Geoffrey Zhu <[EMAIL PROTECTED]> wrote:
>
> Hi Everyone,
>
> I am wondering if there is an "extended" outer product. Take the
> example in "Guide to Numpy." Instead of doing an multiplication, I
> want to call a custom function for each pair.
>
> >>> print outer([1,2,3],[10,100,1000])
>
Robert Kern wrote:
> If you can code your function such that it only uses operations that broadcast
> (i.e. operators and ufuncs) and avoids things like branching or loops, then
> you
> can just use numpy.newaxis on the first array.
>
> from numpy import array, newaxis
> x = array([1, 2, 3])
On 8/20/07, Stefan van der Walt <[EMAIL PROTECTED]> wrote:
>
> This looks like a bug, since
>
> a[0][0] = 0
>
> works fine. I'll take a closer look and make sure.
>
Thanks Stefan for offering to take a closer look. I have attached a
patch against the latest svn which fixes this problem.
Both thi
Geoffrey Zhu wrote:
> Hi Everyone,
>
> I am wondering if there is an "extended" outer product. Take the
> example in "Guide to Numpy." Instead of doing an multiplication, I
> want to call a custom function for each pair.
>
print outer([1,2,3],[10,100,1000])
>
> [[ 10 100 1000]
> [ 20 200 20
Hi Everyone,
I am wondering if there is an "extended" outer product. Take the
example in "Guide to Numpy." Instead of doing an multiplication, I
want to call a custom function for each pair.
>>> print outer([1,2,3],[10,100,1000])
[[ 10 100 1000]
[ 20 200 2000]
[ 30 300 3000]]
So I want:
[
[f
On Mon, Aug 20, 2007 at 08:34:53AM -0500, Sameer DCosta wrote:
> In the example below I have a record array *a* that has a column
> *col1". I am trying to set the first element of a.col1 to zero in two
> different ways.
>
> 1. a[0].col1 = 0 (This fails silently)
> 2. a.col1[0] = 0 (This works fin
Hi Matthew
On Fri, Aug 17, 2007 at 01:11:41PM +0100, Matthew Brett wrote:
> I noticed that allclose does not always behave correctly for arrays with infs.
>
> I've attached a test script for allclose, and here's an alternative
> implementation that I believe behaves correctly.
Thanks for the pat
On Sat, Aug 18, 2007 at 01:51:50AM -0600, Travis Oliphant wrote:
> > Not any more! See the revised PEP 007,
> > http://www.python.org/dev/peps/pep-0007/
> >
> > In Python 3000 (and in the 2.x series, in new source files),
> > we'll switch to a different indentation style: 4 spaces per i
Hi,
In the example below I have a record array *a* that has a column
*col1". I am trying to set the first element of a.col1 to zero in two
different ways.
1. a[0].col1 = 0 (This fails silently)
2. a.col1[0] = 0 (This works fine)
I am using the latest svn version of numpy. Is this a bug? or is t
On 8/20/07, mark <[EMAIL PROTECTED]> wrote:
> b = a>5
>
> a[not b] or a[!b] don't work. So it's gotta be something different.
a[~b]
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Hello - I am wondering what the better way is to select part of an
array.
Say I have an array a:
a = arange(10)
Now I want to select the values larger than 5
a[ a>5 ]
and later I need the values smaller or equal to 5
a[ a<=5 ]
It seems that doing the comparison twice is extra work (especiall
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