All, As you might be aware, there are currently two concurrent implementations of masked arrays in numpy: * numpy.ma is the official implementation, but it is unclear whether it is still actively maintained. * maskedarray is the alternative I've been developing initially for my own purpose from numpy.ma. It is available in the scipy svn sandbox, but is already fully functional The main difference between numpy.ma and maskedarray is that the objects created by numpy.ma are NOT ndarrays, while maskedarray.MaskedArray is a full subclass of ndarrays. For example:

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import numpy, maskedarray x = numpy.ma.array([1,2], mask=[0,1]) isinstance(x, numpy.ndarray) False numpy.asanyarray(x) array([1,2]) Note that we just lost the mask...

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x = maskedarray.array([1,2], mask=[0,1]) isinstance(x, numpy.ndarray) True numpy.asanyarray(x) masked_array(data = [1 --],       mask = [False  True],       fill_value=999999) Note that the mask is conserved.

Having the masked array be a subclass of ndarray makes masked arrays easier to mix with other ndarray types and to subclass. An example of application is the TimeSeries package, where the main TimeSeries class is a subclass of maskedarray.MaskedArray. * Does anyone see any *disadvantages* to this aspect of maskedarray relative to numpy.ma? * What would be the requisites to move maskedarray out of the sandbox ? We hope to be able in the short term to either replace or at least merge the two implementations, once a couple of issues are addressed (but we can talk about that later...) Thanks a lot in advance for your feedback Pierre