eric jones wrote: >Hey all, > >I am playing around with sub-classing the new-fangled float64 objects >and friends. I really like the new ndarray subclassing features >(__array_finalize__, etc.), and was exploring whether or not the scalars >worked the same way. I've stubbed my toe right out of the blocks >though. I can sub-class from standard python floats just fine, but when >I try to do the same from float64, I get a traceback. (examples below) >Anyone have ideas on how to do this correctly? > >
Unfortunately, the array scalars were not originally designed to be sub-classed. I believe I later set the flag saying they "could be" sub-classable. However, I did not alter the tp_new code to actually use the type information passed in as the first argument to actually create an instance of the sub-class --- effectively making the array scalars *not* sub-classable. Thus, the _arrtype_new code would need to be changed in scalartypes.inc.src to fix this. Notice that in Python the float_new command does a special check for when a sub-type is requested and calls float_subtype_new which creates a regular float and then copies the data over to the sub-type. This special-check is not done in the tp_new function (<name>_arrtype_new) and so float64.__new__ will *always* return the array scalars are still not sub-classable (except for the void scalar). This could be changed, and needs to happen before sub-classing of array scalars will work. -Travis _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
