Module « scipy.linalg »

Fonction block_diag - module scipy.linalg

Signature de la fonction block_diag

def block_diag(*arrs) 

Description

block_diag.__doc__

    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
    --------
    >>> 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.]])