I have a numpy array and corresponding row and column indices:
matrix = np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]])row_idx = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0,])col_idx = np.array([0, 1, 2, 0, 1, 2, 0, 1, 2])I would like to unravel the matrix by the groups specified by row_idx and col_idx. In the case of this example, the row_idx are all zero, so the elements would unravel by columns:
result = np.array([0, 3, 6, 1, 4, 7, 2, 5, 8])I have tried aggregate() from the numpy_groupies package, but it is both slow and returns an array combining np.arrays and ints (which makes further manipulation difficult and slow). Need something that will generalise to where the matrix has areas that are grouped by rows and other areas by columns based on the row_idx and col_idx.