On 07/01/2011 10:27 AM, Charles R Harris wrote: > > > On Fri, Jul 1, 2011 at 1:39 PM, Christopher Barker > <chris.bar...@noaa.gov <mailto:chris.bar...@noaa.gov>> wrote: > > Joe Harrington wrote: > > All > > that has to happen is to allow the sense of the mask to be FALSE > = the > > data are bad, TRUE = the data are good, and allow (not require) the > > mask to be of any numerical type, or at least of integer type as well > > as boolean. > > quick note on this: I like the "FALSE == good" way, because: > > instead of good and bad we think "masked" and "unmasked", then we have: > > False = "unmasked" = "regular old data" > True = "masked" = "something special about the data > > The default for "something special" is "bad" (or "missing" , or > "ignore"), but the cool thing is that if you use an int: > > 0 = "unmasked" > 1 = "masked because of one thing" > 2 = "masked because of another" > etc., etc. > > This could be pretty powerful > > > I don't think the false/true dichotomy isn't something to worry about, > it is an implementation detail that is hidden from the user...
But Joe's point and Chris's seemingly opposite (in terms of the Boolean value of the mask) point are that if it is not completely hidden, and if it is not restricted to be Boolean but is merely treated as Boolean with True meaning NA or Ignore, then it can be more powerful because it can carry additional information without affecting its Boolean functionality as a mask in ufuncs. Although I might use such a capability if it existed, to reduce the need to have a separate flags array corresponding to a given data array, I think that for my own purposes this is very low priority, and chances are I would often use a separate flags array even if the underlying mask were not restricted to Boolean. Eric > > Chuck _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion