On Monday 25 June 2007 05:12:01 Jesper Larsen wrote: > Hi numpy users, > > I have a masked array. I am looping over the elements of this array and > sometimes want to set a value to missing. Normally this can be done by: > > myarray.mask[i] = True
Mmh. Experience shows that directly accessing the mask can lead to bad surprises. To mask a series of values in an array, the easiest (and recommended method) is myarray[i] = masked where 'i' can be whatever object used for indexing (an integer, a sequence, a slice...). > Does anyone by the way have any pointers to documentation of the masked > array features of numpy? I know that it is treated in the numarray manual > but it seems like there are some important syntax differences that make > this manual of little use in that regard. I can't really point you to any documentation. The differences of syntax should be minimal. We could however start a wiki page. A side issue is the kind of implementation of masked arrays you want. There are currently two, one directly accessible through numpy.core.ma, another available in the sandbox of the scipy svn site, as maskedarray. This latter considers MaskedArray as a subclass of ndarray, which makes it easier to define subclasses. Moreover, it gives access to soft/hard masks, masked records, more stats functions, and thanks to Eric Firing, can be used directly with matplotlib... I'd be quite happy if you could give it a try and send me your feedback. _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
