On 3/24/07, Sebastian Haase <[EMAIL PROTECTED]> wrote: > > > > Then of course, there's r_ and c_: > > > > c = numpy.c_[a,b] > > > > c = numpy.r_[a[None],b[None]].T > > > > --bb > So, > None is the same as newaxis - right?
Yes, newaxis is None. None is newaxis. Same thing. I just don't see much advantage in spelling it numpy.newaxis, since it's pretty common and not likely to ever change. > But what is a[None] vs. a[:,N.newaxis] ? a[None] is the same as a[None,:]. It prepends the new axis, so a shape of (5,) becomes (1,5), a "row vector" a[:,None] puts the new axis after the first axis, so shape of (5,) becomes (5,1) a "column vector" a[None,:,None] puts a new axis both before and after, so (5,) becomes (1,5,1). If 'a' is higher dimensional, the same kind of thing goes. Wherever None/newaxis appears in the index, insert a new axis there in the result. Say A is shape (2,3,4), then A[:,None,:,None] is shape (2,1,3,1,4). (Same as A[:,None,:,None,:] since unspecified trailing indices are always taken to be ':') --bb _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
