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Module « scipy.linalg »

Fonction block_diag - module scipy.linalg

Signature de la fonction block_diag

def block_diag(*arrs) 

Description

help(scipy.linalg.block_diag)

Create a block diagonal matrix from provided arrays.

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]]

Parameters
----------
A, B, C, ... : array_like, up to 2-D
    Input arrays.  A 1-D array or array_like sequence of length `n` is
    treated as a 2-D array with shape ``(1,n)``.

Returns
-------
D : ndarray
    Array with `A`, `B`, `C`, ... on the diagonal. `D` has the
    same dtype as `A`.

Notes
-----
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)``.

Examples
--------
>>> import numpy as np
>>> 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.]])

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