Changes between Version 25 and Version 26 of MaskedArray

Timestamp:

10/28/06 05:58:52 (7 years ago)

Author:

pierregm

Comment:

--

MaskedArray

@@ -156 +156 @@
 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.
+
+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. 
 
 === Main differences ===
@@ -208 +210 @@
   A basic consequence is that {{{matplotlib}}} will not recognize new masked arrays as such. The file {{{matplotlib/numerix/ma/__init__.py}}} must be modified to call the new package instead of {{{numpy.core.ma}}}.
 
+=== Revision notes ===
+10/28/2006 : Updated {{{put}}}, deleted {{{putmask}}} to match numpy 1.0
 
 === Masked records ===