>> I realize NumPy != Matlab, but I'd wager that most users would think >> that this is the natural behavior...... > > Well, that behavior won't happen. We won't mutate the dtype of the array > because > of assignment. Matlab has copy(-on-write) semantics for things like slices > while > we have view semantics. We can't safely do the reallocation of memory [1].
That's fair enough. But then I think NumPy should consistently typecheck all assignmetns and throw an exception if the user attempts an assignment which looses information. If you point me to a file where assignments are done (particularly from array elements to array elements) I can see if I can figure out how to fix it & then submit a patch. But I won't promise anything! My brain hurts already after analyzing this "feature"..... :-) Cheers, Stuart Brorson Interactive Supercomputing, inc. 135 Beaver Street | Waltham | MA | 02452 | USA http://www.interactivesupercomputing.com/ _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
