mindspore.scipy.linalg.block_diag
- mindspore.scipy.linalg.block_diag(*arrs)[source]
Create a block diagonal matrix from provided arrays.
Given the list of Tensors A, B, and C, the output will have these Tensors arranged on the diagonal:
[[A, 0, 0], [0, B, 0], [0, 0, C]]
Note
block_diag is not supported on Windows platform yet.
- Parameters
arrs (list) – up to 2-D Input Tensors. One or more Tensors, the dimension of Tensors should be 0-D, 1-D or 2-D.
- Returns
Tensor with A, B, C, … on the diagonal which has the same dtype as A.
- Raises
ValueError – If there are Tensors with dimensions higher than 2 in all arguments.
- Supported Platforms:
GPU
CPU
Examples
>>> import numpy as onp >>> from mindspore import Tensor >>> from mindspore.scipy.linalg import block_diag >>> A = Tensor(onp.array([[1, 0], [0, 1]])) >>> B = Tensor(onp.array([[3, 4, 5], [6, 7, 8]])) >>> C = Tensor(onp.array([[7]])) >>> P = Tensor(onp.zeros((2, ), dtype='int32')) >>> print(block_diag(A, B, C)) [[1 0 0 0 0 0] [0 1 0 0 0 0] [0 0 3 4 5 0] [0 0 6 7 8 0] [0 0 0 0 0 7]] >>> print(block_diag(A, P, B, C)) [[1 0 0 0 0 0 0 0] [0 1 0 0 0 0 0 0] [0 0 0 0 0 0 0 0] [0 0 0 0 3 4 5 0] [0 0 0 0 6 7 8 0] [0 0 0 0 0 0 0 7]]