[SciPy-user] Arrayfns in numpy?

Souheil Inati souheil.inati@nyu....
Wed Mar 7 07:58:16 CST 2007


I agree with Dave and Robert's view of the three layers of  
functionality.  I am agnostic as to whether layers 1 and 2 should be  
one package or two as long as the API for both is extremely stable.

In this scheme, the old numeric compatibility layer is part of level 2.

-Souheil

On Mar 7, 2007, at 7:09 AM, Robert Cimrman wrote:

> Dave wrote:
>> On Tue, 06 Mar 2007 Travis Oliphant wrote:
>>> That is generally what we believe as well.  The problem is that  
>>> Numeric
>>> already included several additional features.   Trying to  
>>> maintain some
>>> semblance of backward compatibility is why NumPy has not shrunk  
>>> even more.
>>
>>> Because the interp function was already in Numeric and is not  
>>> that big,
>>> perhaps it should be added to NumPy.
>>
>> >snip
>>
>> In summary:
>> +1 interpolation for numpy,
>> -1 new dependencies for numpy,
>> +1 balanced practical approach to adding numpy features
>
> As Dave correctly mentioned, there are three levels of functionality:
> 1. core of numpy (ndarray) - basic array handling
> 2. 'general purpose' functions (like interp, linalg.*, ...) with no
> external dependencies, no fortran, easy to install
> 3. full scipy
>
> Currently, 1. and 2. are in one package (numpy) - why not make two?
>
> r.



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