On Tue, Apr 29, 2008 at 11:16:15PM +0200, Anne Archibald wrote: > On 29/04/2008, Gael Varoquaux <[EMAIL PROTECTED]> wrote: > > On Tue, Apr 29, 2008 at 11:03:58PM +0200, Anne Archibald wrote: > > > I am puzzled by this. What is the rationale for x[i,:] not being a 1-d > > > object?
> > It breaks A*B[i, :] where A and B are matrices. > Really? How? > In [26]: A = np.matrix([[1,0],[0,1],[1,1]]) > In [28]: A*np.ones(2) > Out[28]: matrix([[ 1., 1., 2.]]) > In [29]: np.ones(3)*A > Out[29]: matrix([[ 2., 2.]]) Yes, sorry, I am shameful. I should have thought a bit more before posting. There is no big problem with x[i,:] not being a 1-d object. The problem is for x[:, i]. However I would find it nice that, for linear algebra, x[i, :] == x[:, i].T This is the kind of behavior I expect, and we won't be getting it with 1D arrays. Cheers, Gaël _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
