Changes between Version 26 and Version 27 of MaskedArray

Timestamp:

12/10/06 14:01:29 (6 years ago)

Author:

pierregm

Comment:

Update link to attachment

MaskedArray

@@ -154 +154 @@
 As a regular user of MaskedArray, I became increasingly frustrated with the subclassing of masked arrays (even if I can only blame my inexperience). I needed to develop a class of arrays that could store some additional information along with numerical values, while keeping the possibility for missing data (picture storing a series of dates along with measurements). I started to implement such a class, but then quickly realized that any additional information disappeared when processing these subarrays (for example, adding a constant value to a subarray would erase its dates). I ended up writing the equivalent of {{{numpy.core.ma}}} for my particular class, ufuncs included. Everything went fine until I needed to subclass my new class, when more problems showed up: some attributes of the new subclass were lost during processing. I identified the culprit as MaskedArray, which returns masked ndarrays when I expected masked arrays of my class. I was preparing myself to rewrite numpy.core.ma when I forced myself to learn how to subclass ndarrays. As I became more familiar with the {{{__new__}}} and {{{__array_finalize__}}} methods, I started to wonder why masked arrays were objects, and not ndarrays, and whether it wouldn't be more convenient for subclassing if they did behave like regular ndarrays.
 
-The new {{{maskedarray}}} [attachment:maskedarray.py package ] is what I eventually come up with. The main differences with the initial {{{numpy.core.ma}}} package are that {{{MaskedArray}}} is now a subclass of {{{ndarray}}} and that the {{{_data}}} section can now be any subclass of {{{ndarray}}} (well, it should work in most cases, some tweaking might required here and there). Apart from a couple of issues listed below, the behavior of the new {{{MaskedArray}}} class reproduces the old one. It is quite likely to be significantly slower, though: I was more interested into a clear organization than in performance, so I tended to use wrappers liberally. I'm sure  we can improve that rather easily. Note that I didn't try to time any methods.
-I also attach a unittest suite ([attachment:test_maskedarray.py here]), modeled after the standard numpy one, along with some utilities for testing ([attachment:masked_testutils.py here]). The old {{{test_ma}}} can also be run with the new package but it does fail in some places, see below.
+The new {{{maskedarray}}} [attachment:maskedarray-1.00.dev0040.tar.gz package ] is what I eventually come up with. The main differences with the initial {{{numpy.core.ma}}} package are that {{{MaskedArray}}} is now a subclass of {{{ndarray}}} and that the {{{_data}}} section can now be any subclass of {{{ndarray}}} (well, it should work in most cases, some tweaking might required here and there). Apart from a couple of issues listed below, the behavior of the new {{{MaskedArray}}} class reproduces the old one. It is quite likely to be significantly slower, though: I was more interested into a clear organization than in performance, so I tended to use wrappers liberally. I'm sure  we can improve that rather easily. Note that I didn't try to time any methods.
+I also attach a unittest suite, modeled after the standard numpy one, along with some utilities for testing ([attachment:masked_testutils.py here]). The old {{{test_ma}}} can also be run with the new package but it does fail in some places, see below.
 
 Note that if the subclass has some special methods and attributes, they are not propagated to the masked version: this would require a modification of the {{{__getattribute__}}} method (first trying {{{ndarray.__getattribute__}}}, then trying {{{self._data.__getattribute__}}} if an exception is raised in the first place), which really slows things down.