On Thu, Jun 23, 2011 at 3:44 PM, Robert Kern <[email protected]> wrote:
> On Thu, Jun 23, 2011 at 15:53, Mark Wiebe <[email protected]> wrote: > > Enthought has asked me to look into the "missing data" problem and how > NumPy > > could treat it better. I've considered the different ideas of adding > dtype > > variants with a special signal value and masked arrays, and concluded > that > > adding masks to the core ndarray appears is the best way to deal with the > > problem in general. > > I've written a NEP that proposes a particular design, viewable here: > > > https://github.com/m-paradox/numpy/blob/cmaskedarray/doc/neps/c-masked-array.rst > > There are some questions at the bottom of the NEP which definitely need > > discussion to find the best design choices. Please read, and let me know > of > > all the errors and gaps you find in the document. > > One thing that could use more explanation is how your proposal > improves on the status quo, i.e. numpy.ma. As far as I can see, you > are mostly just shuffling around the functionality that already > exists. There has been a continual desire for something like R's NA > values by people who are very familiar with both R and numpy's masked > arrays. Both have their uses, and as Nathaniel points out, R's > approach seems to be very well-liked by a lot of users. In essence, > *that's* the "missing data problem" that you were charged with: making > happy the users who are currently dissatisfied with masked arrays. It > doesn't seem to me that moving the functionality from numpy.ma to > numpy.ndarray resolves any of their issues. > > So we are looking for unhappy users ;) Making the functionality, whatever it turns out to be, faster, more complete, and easier to use also seems a worthy goal. Chuck
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