I've just finished a first version of the numarray compatibility
module. It does not include all the names from the numarray name-space
but it does include the most important ones, I believe. It also
includes a slightly modified form of the numarray type-objects so that
NumPy can recognize them as dtypes. I do not have a lot of code to
test the compatibility layer with so any help will be appreciated.
The compatibility layer still requires changes to certain methods and
attributes on arrays. This is performed by the alter_code1.py module
which I will be finishing over the next few hours. Once that is ready
(and I've updated NumPy to work with the latest version of Python 2.5 in
SVN) I want to make a 1.0b2 release (no later than Friday). I would
appreciate it if several people could test the current SVN version of NumPy.
In order to support several of the features of NumArray that I had
missed, I engaged in a marathon coding sprint last night from about
6:00pm to 6:00am during which time I added output arguments to many of
the functions in NumPy, and a clipmode argument to several others. I
also added the C-API functions PyArray_OutputConverter and
PyArray_ClipmodeConverter to make it easy to get these arguments from
Python to C. This caused a change in the C-API that will require
re-compilation for 1.0b2. I'm sorry about that. I'm really pushing for
stability on the C-API. Now that the numarray compatibility module is
complete, I'm more confident that we won't need anymore changes to the
C-API for version 1.0. Of course, only when numpy 1.0final comes out
will that be a guarantee.
While I'm relatively confident about the changes to NumPy, the changes
were extensive enough that more testing is warranted including another
round of Valgrind tests. Unit-tests written to take advantage of the
new output arguments on several of the functions (take, put, compress,
clip, conjugate, argmax, argmin, and any function based on a ufunc
method -- like sum, product, any, all, etc.) are particularly needed.
If serious problems are discovered, then the 1.0b2 might be delayed
again, but I'm really pushing to get 1.0b2 out the door soon.
The numarray compatibility module and the oldnumeric compatibility
module should hopefully help people adapt their code more quickly to
NumPy. It's not fool-proof, though, so the best strategy is still to
write to NumPy :-) as soon as you can.
-Travis
|
