Reggie Dugard wrote: >On Wed, 2007-02-07 at 14:36 -0700, Travis Oliphant wrote: > > >>Sturla Molden wrote: >> >> >> >>>>def __new__(cls,...) >>>> ... >>>> (H, edges) = numpy.histogramdd(..) >>>> cls.__defaultedges = edges >>>> >>>>def __array_finalize__(self, obj): >>>> if not hasattr(self, 'edges'): >>>> self.edges = self.__defaultedges >>>> >>>> >>>> >>>> >>>So in order to get an instance attribute, one has to temporarily define it >>>as a class attribute? >>> >>> >>> >>No, you don't *have* to do it this way for all instance attributes. >> >>In this example, the user was trying to keep the edges computed during >>the __new__ method as an attribute. What are the possibilities? >> >>1) Use the __new__ method to create the object in full and then store >>the edges in some kind of global (or class global) variable. >> >>This solution because it uses global variables has all of the thread >>problems global variables bring. >> >>2) Create a "dummy" arrayobject in the __new__ method and fill it in >>(i.e. using setstate or resize) during the __init__ method where the >>instance attribute is actually set. >> >> >> >I'm probably missing something obvious here, but why can't you just >attach the attribute to the actual object in the __new__ method before >returning it. For example: > > Good point. I guess I thought the OP had tried that already. It turns out it works fine, too.
The __array_finalize__ is useful if you want the attribute to be carried around when arrays are created automatically internally (after math operations for example). -Travis _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
