I'm relatively new to python/numpy. I have a 3D numpy array of TxNxN. It contains a sequence of symmetrical NxN matrices. I want convert it to a 2D array of TxM (where M = N(N 1)/2). How can I do that? I can certainly use 3 loops, but I thought there probably better ways to do that in python/numpy.
CodePudding user response:
It seems that you want to get the upper triangle or lower triangle of each symmetric matrix. A simple method is to generate a mask array and apply it to each 2D array:
>>> e
array([[[0, 1, 2, 3],
[1, 2, 3, 0],
[2, 3, 0, 1],
[3, 0, 1, 2]],
[[1, 2, 3, 4],
[2, 3, 4, 1],
[3, 4, 1, 2],
[4, 1, 2, 3]],
[[2, 3, 4, 5],
[3, 4, 5, 2],
[4, 5, 2, 3],
[5, 2, 3, 4]]])
>>> ii, jj = np.indices(e.shape[1:])
>>> jj >= ii
array([[ True, True, True, True],
[False, True, True, True],
[False, False, True, True],
[False, False, False, True]])
>>> e[:, jj >= ii]
array([[0, 1, 2, 3, 2, 3, 0, 0, 1, 2],
[1, 2, 3, 4, 3, 4, 1, 1, 2, 3],
[2, 3, 4, 5, 4, 5, 2, 2, 3, 4]])