On Tue, Mar 11, 2008 at 2:10 PM, Alexander Michael <lxander.m@gmail.com> wrote:
I have a function that I would like to work with both MaskedArray's and ndarray's. The only blocker for this particular function is the need to create some stand-in data that is appropriately either a MaskedArray or an ndarray. Currently I have:
dummy = numpy.ones(data.shape, dtype=bool)
where data has a dtype of float. I've already discovered that numpy.ones_like "does the right thing", but how do I do the equivalent in conjunction with declaring a new dtype?
Said another way, how can a create arrays of the same class and (possibly) shape as an existing array, but with a different dtype?
dummy = numpy.ones(data.shape, dtype=bool).view(type(data)) -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco