On Do, 2014-07-17 at 09:48 -0400, Robert Lupton the Good wrote: > Having just re-read the PEP I'm concerned that this proposal leaves at least > one major (?) trap for naive users, namely > x = np.array([1, 10]) > print X.T@x > which will print 101, not [[1, 10], [10, 100]] > > Yes, I know why this is happening but it's still a problem -- the user said, > "I'm thinking matrices" when they wrote @ but the x.T had done the "wrong" > thing before the @ kicked in. And yes, a savvy user would have written x = > np.ones([[1, 10]]) (but then np.dot(x, x.T) isn't a scalar). > > This is the way things are at present, but with the new @ syntax coming in I > think we should consider fixing it. > > I can think of three possibilities: > 1. Leave this as a trap for the unwary, and a reason for people to > stick to np.matrix (np.matrix([1, 10]) behaves "correctly") > 2. Make x.T a syntax error for 1-D arrays. It's a no-op and IMHO a > trap. > 3. Make x.T promote the shape == (2,) array to (1, 2) and return a (2, > 1) array. This may be too magic, but it's my preferred solution. >
Making it a warning may be another option. Changing `.T` to promote to 2-d (also maybe to actually only transpose the last two axes for higher D arrays), could be nice, but getting there might take quite a long FutureWarning or even Error -> new feature cycle... - Sebastian > R > > > Implementation of @ (matrix multiplication) > > - will be in 3.5 ~ 18months > > - no work started yet -- have to make sure we do it. > > - @@ was not added. > > - The PEP for numpy is well-defined. Not much thinking to be done. (Good > > for a sprint) > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
