block_diag(*arrs)
Given the inputs A, B and C, the output will have these arrays arranged on the diagonal:
[[A, 0, 0], [0, B, 0], [0, 0, C]]
If all the input arrays are square, the output is known as a block diagonal matrix.
Empty sequences (i.e., array-likes of zero size) will not be ignored. Noteworthy, both [] and [[]] are treated as matrices with shape (1,0)
.
Input arrays. A 1-D array or array_like sequence of length :None:None:`n` is treated as a 2-D array with shape (1,n)
.
Create a block diagonal matrix from provided arrays.
>>> from scipy.linalg import block_diag
... A = [[1, 0],
... [0, 1]]
... B = [[3, 4, 5],
... [6, 7, 8]]
... C = [[7]]
... P = np.zeros((2, 0), dtype='int32')
... block_diag(A, B, C) array([[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]])
>>> block_diag(A, P, B, C) array([[1, 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, 6, 7, 8, 0], [0, 0, 0, 0, 0, 7]])
>>> block_diag(1.0, [2, 3], [[4, 5], [6, 7]]) array([[ 1., 0., 0., 0., 0.], [ 0., 2., 3., 0., 0.], [ 0., 0., 0., 4., 5.], [ 0., 0., 0., 6., 7.]])See :
The following pages refer to to this document either explicitly or contain code examples using this.
scipy.linalg._special_matrices.block_diag
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