I have an array like below:
poles = numpy.array([[-1+1j], [-1-1j], [-2+3j], [-2-3j]])
Its shape is (4,1).
When I use the numpy.diag like below:
LA = numpy.diag(poles)
The output is [-1.+1.j] while I'm expecting to see a diagonal matrix.
Can someone explain what is going on and what should be done to see a diagonal matrix?
I also tried to change the shape to (1,4) but the result didn't change.
The function you are looking for is np.fill_diagonal. This will set the diagonal values of an array. You'll have to create the array first:
arr = np.zeros((4, 4), dtype=np.complex64))
np.fill_diagonal(arr, poles)
arr is now:
array([[-1.+1.j, 0.+0.j, 0.+0.j, 0.+0.j],
[ 0.+0.j, -1.-1.j, 0.+0.j, 0.+0.j],
[ 0.+0.j, 0.+0.j, -2.+3.j, 0.+0.j],
[ 0.+0.j, 0.+0.j, 0.+0.j, -2.-3.j]], dtype=complex64)
np.diagonal, on the other hand, retrieves the values in the diagonal. Output of np.diagonal(arr) is:
array([-1.+1.j, -1.-1.j, -2.+3.j, -2.-3.j], dtype=complex64)
In your example, you are retrieving the diagonal of poles, which only has one value in the diagonal since one of the axes is only length 1.
np.diagwill take the diagonal values of your array, which there is only one item since one of your axes is only length 1.