Hey all, After reading all the discussion around masked arrays and getting input from as many people as possible, it is clear that there is still disagreement about what to do, but there have been some fruitful discussions that ensued.
This isn't really new as there was significant disagreement about what to do when the masked array code was initially checked in to master. So, in order to move forward, Mark and I are going to work together with whomever else is willing to help with an effort that is in the spirit of my third proposal but has a few adjustments. The idea will be fleshed out in more detail as it progresses, but the basic concept is to create an (experimental) ndmasked object in NumPy 1.7 and leave the actual ndarray object unchanged. While the details need to be worked out here, a goal is to have the C-API work with both ndmasked arrays and arrayobjects (possibly by defining a base-class C-level structure that both ndarrays inherit from). This might also be a good way for Dag to experiment with his ideas as well but that is not an explicit goal. One way this could work, for example is to have PyArrayObject * be the base-class array (essentially the same C-structure we have now with a HASMASK flag). Then, the ndmasked object could inherit from PyArrayObject * as well but add more members to the C-structure. I think this is the easiest thing to do and requires the least amount of code-change. It is also possible to define an abstract base-class PyArrayObject * that both ndarray and ndmasked inherit from. That way ndarray and ndmasked are siblings even though the ndarray would essentially *be* the PyArrayObject * --- just with a different type-hierarchy on the python side. This work will take some time and, therefore, I don't expect 1.7 to be released prior to SciPy Austin with an end of June target date. The timing will largely depend on what time is available from people interested in resolving the situation. Mark and I will have some availability for this work in June but not a great deal (about 2 man-weeks total between us). If there are others who can step in and help, it will help accelerate the process. Best regards, -Travis _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
