Olivier Verdier-2 wrote: > > There would be a much simpler solution than allowing a new operator. Just > allow the numpy function dot to take more than two arguments. Then A*B*C > in > matrix notation would simply be: > dot(A,B,C) > > with arrays. Wouldn't that make everybody happy? Plus it does not break > backward compatibility. Am I missing something? >
That wouldn't make me happy because it is not the same syntax as a binary infix operator. Introducing a new operator for matrix multiply (and possibly matrix exponentiation) does not break backward compatibility - how could it, given that the python language does not yet support the new operator? Going back to Alan Isaac's example: 1) beta = (X.T*X).I * X.T * Y 2) beta = np.dot(np.dot(la.inv(np.dot(X.T,X)),X.T),Y) With a multiple arguments to dot, 2) becomes: 3) beta = np.dot(la.inv(np.dot(X.T, X)), X.T, Y) This is somewhat better than 2) but not as nice as 1) IMO. Seeing 1) with @'s would take some getting used but I think we would adjust. For ".I" I would propose that ".I" be added to nd-arrays that inverts each matrix of the last two dimensions, so for example if X is 3D then X.I is the same as np.array([inv(Xi) for Xi in X]). This is also backwards compatible. With this behavior and the one I proposed for @, by adding preceding dimensions we are allowing doing matrix algebra on collections of matrices (although it looks like we might need a new .T that just swaps the last two dimensions to really pull that off). But a ".I" attribute and its behavior needn't be bundled with whatever proposal we wish to make to the python community for a new operator of course. Regards, Tom K. -- View this message in context: http://www.nabble.com/matrix-default-to-column-vector--tp23652920p23910425.html Sent from the Numpy-discussion mailing list archive at Nabble.com. _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
