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 ------------------------------------------------------------------------- Using Tomcat but need to do more? Need to support web services, security? Get stuff done quickly with pre-integrated technology to make your job easier Download IBM WebSphere Application Server v.1.0.1 based on Apache Geronimo http://sel.as-us.falkag.net/sel?cmd=lnk&kid=120709&bid=263057&dat=121642 _______________________________________________ Numpy-discussion mailing list Numpy-discussion@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/numpy-discussion
