Sometimes it is useful to "clone" a row or column vector to a matrix. By cloning I mean converting a row vector such as [1, 2, 3] Into a matrix [[1, 2, 3], [1, 2, 3], [1, 2, 3]] or a column vector such as [[1], [2], [3]] into [[1, 1, 1] [2, 2, 2] [3, 3, 3]] In MATLAB or octave this is done pretty easily: x = [1, 2, 3] a = ones(3, 1) * x a = 1 2 3 1 2 3 1 2 3 b = (x') * ones(1, 3) b = 1 1 1 2 2 2 3 3 3 I want to repeat this in numpy, but unsuccessfully In [14]: x = array([1, 2, 3]) In [14]: ones((3, 1)) * x Out[14]: array([[ 1., 2., 3.], [ 1., 2., 3.], [ 1., 2., 3.]]) # so far so good In [16]: x.transpose() * ones((1, 3)) Out[16]: array([[ 1., 2., 3.]]) # DAMN # I end up with In [17]: (ones((3, 1)) * x).transpose() Out[17]: array([[ 1., 1., 1.], [ 2., 2., 2.], [ 3., 3., 3.]]) Why wasn't the first method (In [16]) working? Is there a way to achieve this task in python in a more elegant way? Continue reading...
