2009/10/20 Sebastian Walter :
> On Tue, Oct 20, 2009 at 5:45 AM, Anne Archibald
> wrote:
>> 2009/10/19 Sebastian Walter :
>>>
>>> I'm all for generic (u)funcs since they might come handy for me since
>>> I'm doing lots of operation on arrays of polynomials.
>>
>> Just as a side note, if you don't
Hi Travis,
On Mon, Oct 19, 2009 at 6:29 PM, Travis Oliphant wrote:
>
> On Oct 17, 2009, at 7:49 AM, Darren Dale wrote:
[...]
>> When calling numpy functions:
>>
>> 1) __input_prepare__ provides an opportunity to operate on the inputs
>> to yield versions that are compatible with the operation (th
On Tue, Oct 20, 2009 at 5:24 AM, Sebastian Walter
wrote:
> I'm not very familiar with the underlying C-API of numpy, so this has
> to be taken with a grain of salt.
>
> The reason why I'm curious about the genericity is that it would be
> awesome to have:
> 1) ufuncs like sin, cos, exp... to work
I'm not very familiar with the underlying C-API of numpy, so this has
to be taken with a grain of salt.
The reason why I'm curious about the genericity is that it would be
awesome to have:
1) ufuncs like sin, cos, exp... to work on arrays of any object (this
works already)
2) funcs like dot, eig,
On Tue, Oct 20, 2009 at 5:45 AM, Anne Archibald
wrote:
> 2009/10/19 Sebastian Walter :
>>
>> I'm all for generic (u)funcs since they might come handy for me since
>> I'm doing lots of operation on arrays of polynomials.
>
> Just as a side note, if you don't mind my asking, what sorts of
> operatio
2009/10/19 Sebastian Walter :
>
> I'm all for generic (u)funcs since they might come handy for me since
> I'm doing lots of operation on arrays of polynomials.
Just as a side note, if you don't mind my asking, what sorts of
operations do you do on arrays of polynomials? In a thread on
scipy-dev we
On Oct 17, 2009, at 7:49 AM, Darren Dale wrote:
> numpy's functions, especially ufuncs, have had some ability to support
> subclasses through the ndarray.__array_wrap__ method, which provides
> masked arrays or quantities (for example) with an opportunity to set
> the class and metadata of the ou
On Mon, Oct 19, 2009 at 3:10 AM, Sebastian Walter
wrote:
> On Sat, Oct 17, 2009 at 2:49 PM, Darren Dale wrote:
>> numpy's functions, especially ufuncs, have had some ability to support
>> subclasses through the ndarray.__array_wrap__ method, which provides
>> masked arrays or quantities (for exam
On Sat, Oct 17, 2009 at 2:49 PM, Darren Dale wrote:
> numpy's functions, especially ufuncs, have had some ability to support
> subclasses through the ndarray.__array_wrap__ method, which provides
> masked arrays or quantities (for example) with an opportunity to set
> the class and metadata of the
On Sat, Oct 17, 2009 at 6:45 PM, Charles R Harris
wrote:
>
>
> On Sat, Oct 17, 2009 at 6:49 AM, Darren Dale wrote:
[...]
>> I think it will be not too difficult to document this overall scheme:
>>
>> When calling numpy functions:
>>
>> 1) __input_prepare__ provides an opportunity to operate on th
On Sat, Oct 17, 2009 at 6:49 AM, Darren Dale wrote:
> numpy's functions, especially ufuncs, have had some ability to support
> subclasses through the ndarray.__array_wrap__ method, which provides
> masked arrays or quantities (for example) with an opportunity to set
> the class and metadata of th
numpy's functions, especially ufuncs, have had some ability to support
subclasses through the ndarray.__array_wrap__ method, which provides
masked arrays or quantities (for example) with an opportunity to set
the class and metadata of the output array at the end of an operation.
An example is
q1 =
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