Hello,
The C-API change was committed in revision 5626:
http://scipy.org/scipy/numpy/changeset/5626
Please note that this change requires recompiling extension modules.
A draft of the release notes can be found here:
http://scipy.org/scipy/numpy/milestone/1.2.0
Please take a look and let me know
On Sun, Aug 10, 2008 at 19:37, Christoph T. Weidemann <[EMAIL PROTECTED]> wrote:
> The signature for numpy.compress() seems somewhat inconsistent with
> other functions, because the first argument it expects is not the
> array but the condition. This tends to throw me off when I use this
> function
The signature for numpy.compress() seems somewhat inconsistent with
other functions, because the first argument it expects is not the
array but the condition. This tends to throw me off when I use this
function, because the common order for other functions seems to be:
1) input array
2) function sp
On Sun, Aug 10, you wrote:
> What functionality, may I ask ?
I am working on a dimensioned array data structure that is a subclass
of ndarray and lets you keep track of the different dimensions of an
array, assign labels to them (and the different levels on each
dimensions) and allows for smart in
Dear Pythonistas,
How many times have we seen posts recently along the lines of "why is
it that 0.1 appears as 0.10001 in python?" that lead to
posters being sent to the definition of the IEEE 754 standard and the
decimal.py module? I am teaching an introductory numerical analysis
clas
On Sunday 10 August 2008 15:50:15 Christoph T. Weidemann wrote:
> Pierre,
> Thanks for the fast and informative answers!
Sorry again for the confusion, the first answer was definitely too fast...
> I used the base attribute to call ndarray functions on
> my derived class and obviously that faile
Pierre,
Thanks for the fast and informative answers!
On Sun you wrote:
> So no, you didn't do anything wrong. What behavior were you expecting ?
I was expecting that calls to self.base would produce identical
results for objects of the TestArray class, no matter how these calls
are triggered. I
On Sunday 10 August 2008 14:26:33 Christoph T. Weidemann wrote:
> Why whould tst.sort() show the correct base class and np.sort show
> NoneType as base class for tst?
> I'd appreciate any insights ...
Christoph,
I should take the time to read the question first before answering.
So, according to
You wrote:
> numpy functions will return arrays of the type which has the largest priority,
> with ndarrays a priority of 1 by default. If you set a Class variable
> __array_priority__ to a number larger than 1, that should fix your problem.
The following code produces the same behavior:
import n
On Sunday 10 August 2008 14:26:33 Christoph T. Weidemann wrote:
> Why whould tst.sort() show the correct base class and np.sort show
> NoneType as base class for tst?
> I'd appreciate any insights ...
numpy functions will return arrays of the type which has the largest priority,
with ndarrays a p
I've come across a strange behavior for classes subclassed from ndarray.
Here's a minimal example that illustrates the problem:
import numpy as np
class TestArray(np.ndarray):
def __new__(cls, data, info=None, dtype=None, copy=False):
subarr = np.array(data, dtype=dtype, copy=copy)
On Mon, Aug 4, 2008 at 7:07 AM, David Cournapeau
<[EMAIL PROTECTED]> wrote:
> Bruce Southey wrote:
>> Hi,
>> I installed the 'official binaries' on a Intel Celeron M 530 that
>> supports SSE2 and SSE3 running MS Vista. All tests passed and with
>> regards to the ticket: numpy.inner(F,F) resulted
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