Hi Jason,
On Tue, Aug 31, 2010 at 2:56 PM, Jason McCampbell wrote:
> Hi Chuck (and anyone else interested),
>
> I updated the refactoring page on the NumPy developer wiki (seems to be
> down or I'd paste in the link). It certainly isn't complete, but there are
> a lot more details about the dat
On Thu, Sep 2, 2010 at 10:03 AM, Charles R Harris
wrote:
>
>
> On Wed, Sep 1, 2010 at 3:30 PM, Michael Gilbert
> wrote:
>>
>> On Wed, 1 Sep 2010 21:15:22 + (UTC), Pauli Virtanen wrote:
>> > Wed, 01 Sep 2010 16:26:59 -0400, Michael Gilbert wrote:
>> > > I've been using numpy's float96 class la
On Wed, Sep 1, 2010 at 3:30 PM, Michael Gilbert wrote:
> On Wed, 1 Sep 2010 21:15:22 + (UTC), Pauli Virtanen wrote:
> > Wed, 01 Sep 2010 16:26:59 -0400, Michael Gilbert wrote:
> > > I've been using numpy's float96 class lately, and I've run into some
> > > strange precision errors.
> > [clip]
On 09/01/10 22:30, Michael Gilbert wrote:
> Interesting. float96( '0.0001' ) also seems to evaluate to the first
> result. I assume that it also does a float64( '0.0001' ) conversion
> first. I understand that you can't change how python passes in floats,
> but wouldn't it be better to exactly han
On 1 September 2010 19:24, Neal Becker wrote:
> It seems if I call kron with 2 C-contiguous arrays, it returns an F-
> contiguous array. Any reason for this (it's not what I wanted)?
>
Try numpy.linalg.inv ...
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It seems if I call kron with 2 C-contiguous arrays, it returns an F-
contiguous array. Any reason for this (it's not what I wanted)?
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On 1 September 2010 17:54, Thomas Robitaille
wrote:
> Hi,
>
> I'm trying to extract sub-sections of a multidimensional array while keeping
> the number of dimensions the same. If I just select a specific element along
> a given direction, then the number of dimensions goes down by one:
>
im
Wed, 01 Sep 2010 17:54:26 -0400, Thomas Robitaille wrote:
> >>> a[[0],:,:].shape
> (1, 10, 10)
[clip]
> so I can get around the issue, but just wanted to check whether the
> issue with a[[0],:,[5]] is a bug?
No. The syntax does not mean what you think it means, see
http://docs.scipy.org/doc/numpy
Thomas Robitaille wrote:
> Hi,
>
> I'm trying to extract sub-sections of a multidimensional array while keeping
> the number of dimensions the same. If I just select a specific element along
> a given direction, then the number of dimensions goes down by one:
>
>
>
> In fact, I can get what
Hi,
I'm trying to extract sub-sections of a multidimensional array while keeping
the number of dimensions the same. If I just select a specific element along a
given direction, then the number of dimensions goes down by one:
>>> import numpy as np
>>> a = np.zeros((10,10,10))
>>> a.shape
(10, 1
On Wed, 1 Sep 2010 21:15:22 + (UTC), Pauli Virtanen wrote:
> Wed, 01 Sep 2010 16:26:59 -0400, Michael Gilbert wrote:
> > I've been using numpy's float96 class lately, and I've run into some
> > strange precision errors.
> [clip]
> > >>> x = numpy.array( [0.01] , numpy.float96 )
> [clip]
> > I
Wed, 01 Sep 2010 16:26:59 -0400, Michael Gilbert wrote:
> I've been using numpy's float96 class lately, and I've run into some
> strange precision errors.
[clip]
> >>> x = numpy.array( [0.01] , numpy.float96 )
[clip]
> I would expect the float96 calculation to also produce 0.0 exactly as
> found
On Wed, Sep 1, 2010 at 2:26 PM, Michael Gilbert wrote:
> Hi,
>
> I've been using numpy's float96 class lately, and I've run into some
> strange precision errors. See example below:
>
> >>> import numpy
> >>> numpy.version.version
> '1.5.0'
> >>> sys.version
> '3.1.2 (release31-maint, Jul 8
Hi,
I've been using numpy's float96 class lately, and I've run into some
strange precision errors. See example below:
>>> import numpy
>>> numpy.version.version
'1.5.0'
>>> sys.version
'3.1.2 (release31-maint, Jul 8 2010, 01:16:48) \n[GCC 4.4.4]'
>>> x = numpy.array( [0.01] , numpy.
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Hi,
I'm having a little Problem that might be trivial.
I'm trying to use a nupmy array within a c++ method and having some trouble.
The PyArray is not parsed correctly and PyArg_ParseTuple returns 0.
Appreciate any help.
#include "Python.h"
#include
void fromMatrix(PyObject *args){
_import_a
On Tue, Aug 31, 2010 at 2:56 PM, Jason McCampbell wrote:
> Hi Chuck (and anyone else interested),
>
> I updated the refactoring page on the NumPy developer wiki (seems to be
> down or I'd paste in the link). It certainly isn't complete, but there are
> a lot more details about the data structure
On Wed, Sep 1, 2010 at 11:31 AM, John Salvatier
wrote:
> Hello,
>
> I would like to update my numpydoc so it works with sphinx 1.0, but I am
> not sure where the dev version is; can someone point me in the right
> direction?
>
> In numpy trunk, under doc/sphinxext/. That works *only* with sphinx 1
is it really the covariance matrix you want to invert? Or do you want
to compute something like
x^T C^{-1} x,
where x is an array of size N and C an array of size (N,N)?
It would also be interesting to know how the covariance matrix gets computed
and what its condition number is, at least approxim
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