[SciPy-user] Arrayfns in numpy?
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.
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
>>> 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.
>> 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?
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