On 28 June 2013 17:33, Charles R Harris <[email protected]> wrote: > On Fri, Jun 28, 2013 at 5:27 AM, Richard Hattersley <[email protected]> > wrote: >> So: >> np.array([scalar]) => np.array([scalar], dtype=my_dtype) >> But: >> np.array(scalar) => np.array(scalar, dtype=object) > > So the scalar case (0 dimensional array) doesn't work right. Hmm, what > happens when you index the first array? Does subclassing the generic type > work in 1.6?
Indexing into the first array works fine. So something like `a[0]` calls my_dtype->f->getitem which creates a new scalar instance, and something like `a[:1]` creates a new view with the correct dtype. > My impression is that subclassing the generic type should be required, but I > don't see where it is documented :( Can you elaborate on why the generic type should be required? Do you think it might cause problems elsewhere? (FYI I've also tested with a patched version of v1.6.2 which fixes the typo which prevents the use of user-defined dtypes with ufuncs, and that functionality seems to work fine too.) > Anyway, what is the problem with the > third party code? Is there no chance that you can get hold of it to fix it? Unfortunately it's out of my control. Regards, Richard _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
