Robert Kern <robert.kern <at> gmail.com> writes: > > Please install Fernando's datarray package, play with it, read its > documentation, then come back with objections or alternatives. I > really don't think you understand what is being proposed. >
Well the discussion has been pretty confusing. For mostly my benefit, here's my understanding of the proposal. Currently the only way to choose which axis of an array we want is by the indexing position. So to access a row of a 2d array (axis=0) a[0,:] or just a[0] # first row and a column (axis=1) a[:,0] # first column To choose an individual element along an axis we must use integer indices: a[0,3] # the element that is 1st along the 1st axis and # 4th along the 2nd axis Fernando's proposal would allow us to specify the axis by a name (called a label) instead of a position, and the element number by a name (called a tick) instead of an integer, while retaining the old position + integer indexing. Ticks are in effect "named indices". I can see the attraction of accessing an axis by name instead of indexing position, because it's easy to get confused over position when you've got a 2d or higher dimension array. But the utility of named indices is not so clear to me. As I understand it, these new arrays will still only be able to have a single type of data (one of float, str, int and so on). This seems to be pretty limiting. What is a use case for the new array type that can't be solved by structured/record arrays? Sounds like it was decided at the Sciy BOF they were a good idea, several people have implemented a version of them and Fernando and Gael have both said they find them useful, so they must have something going for them. Maybe Fernando or Gael could share an example where arrays with named axes and indices are especially useful, for the peanut gallery's benefit? Cheers, Neil _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion