The Python matrix is divided into upper triangular and diagonal three matrices

diagonal

Return specified diagonals.

diagflat

Create a 2-d array with the flattened input as a diagonal.

trace

Sum along diagonals.

triu

Upper triangle of an array.

tril

Lower triangle of an array.

first, the lower triangular array and the upper triangular array on the diagonal of a square are extracted (if only the upper and lower triangular arrays are needed, the second parameter in the Tril/triu is removed)

on the code (both Tril and Triu are returned in the form of array, and the mat is used to convert back to the matrix):

>>> m = Np.mat ("1,2,3;4,5,6;7,8,9")>>> Mmatrix ([[1, 2, 3],        [4, 5, 6],        [7, 8, 9]])>>> L = Np.tril (m,-1)>>>< c11> Larray ([[0, 0, 0],       [4, 0, 0],       [7, 8, 0]])>>> U = Np.triu (m,1) 
      >>>2, 3],       6],       [0, 0, 0]])

There are two ways to extract the elements on the diagonal as a single matrix:

1, using Np.diag two times, and then use mat conversion back to the matrix:

>>> D = np.diag (Np.diag (m))>>> Darray ([[1, 0, 0],       5, 0],       9]])>>> D = Np.mat (d)>>> Dmatrix ([[1, 0, 0],        5, 0],        9])

2, the use of the lower triangular matrix minus the next triangle matrix (that is, the lower triangular array under the diagonal):

>>> D = Np.tril (m)- L>>> Darray ([[[1, 0, 0]       ,5, 0]       ,9  ]])>>> D = Np.mat (d)>>> Dmatrix ([[1, 0, 0],        5, 0],        /C11>9]])

The Python matrix is divided into upper triangular and diagonal three matrices