Hi, I'd like to kick off some discussion on general issues I've encountered while developing the quaternion dtype (see other thread, and the code at: https://github.com/martinling/numpy_quaternion)
The basic issue is that the attributes of ndarray cannot be adapted to the dtype of a given array. Indeed, their behaviour can't be changed at all without patching numpy itself. There are essentially four cases of the problem: 1. Attributes which do the wrong thing even though there is a mechanism that should let them do the right thing, e.g: >>> a = array([quaternion(1,2,3,4), quaternion(5,6,7,8)]) >>> conjugate(a) # correct, calls conjugate ufunc I defined array([quaternion(1, -2, -3, -4), quaternion(5, -6, -7, -8)], dtype=quaternion) >>> a.conjugate() # incorrect, why doesn't it do the same? array([quaternion(1, 2, 3, 4), quaternion(5, 6, 7, 8)], dtype=quaternion) >>> min(a) # works, calls min ufunc I defined quaternion(1, 2, 3, 4) >>> a.min() # fails, why doesn't it do the same? ValueError: No cast function available. 2. Attributes that do the wrong thing with no mechanism to override them: >>> array([q.real for q in a]) array([ 1., 5.]) >>> a.real # would like this to return the same, can't make it do so array([quaternion(1, 2, 3, 4), quaternion(5, 6, 7, 8)], dtype=quaternion) 3. Attributes that don't exist and could be added to suit the dtype: >>> array([q.y for q in a]) array([ 3., 7.]) >>> a.y # would like this to return the same, can't make it do so AttributeError: 'numpy.ndarray' object has no attribute 'y' 4. Attributes that already exist and make no sense for some dtypes: >>> sa = array(['foo', 'bar', 'baz']) >>> sa.imag # why can I even do this? array(['', '', ''], dtype='|S3') We had Ń•ome discussion about this at the SciPy conference sprints and the consensus seemed to be that allowing dtypes to customize the attributes of ndarrays would be a good thing. This would also be useful for struct arrays, datetime arrays, etc. What do people think? Martin _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
