[Numpy-discussion] Rationale for returning type-wrapped min() / max() scalars? (was: Problem with ufunc of a numpy.ndarray derived class)
Hans Meine
meine at informatik.uni-hamburg.de
Fri Jul 29 06:12:19 EDT 2011
Am Freitag, 29. Juli 2011, 11:31:24 schrieb Hans Meine:
> Am Donnerstag, 28. Juli 2011, 17:42:38 schrieb Matthew Brett:
> > Was there a particular case you ran into where this was a problem?
> [...]
> Basically, the problem arose because our ndarray subclass does not support
> zero-rank-instances fully. (And previously, there was no need for that.)
I just reproduced the problem, it was this exception:
/home/hmeine/new_numpy/lib64/python2.6/site-packages/vigra/arraytypes.pyc in
reshape(self, shape, order)
587
588 def reshape(self, shape, order='C'):
--> 589 res = numpy.ndarray.reshape(self, shape, order)
590 res.axistags = AxisTags(res.ndim)
591 return res
TypeError: an integer is required
The problem is that 'self' has become a zero-rank array, and those cannot be
reshaped in order to add singleton dimensions anymore. IOW, if you implement
sth. like broadcasting, this is made much harder.
Best,
Hans
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