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Fonction fill_diagonal - module numpy.matlib

Signature de la fonction fill_diagonal

def fill_diagonal(a, val, wrap=False) 

Description

fill_diagonal.__doc__

Fill the main diagonal of the given array of any dimensionality.

    For an array `a` with ``a.ndim >= 2``, the diagonal is the list of
    locations with indices ``a[i, ..., i]`` all identical. This function
    modifies the input array in-place, it does not return a value.

    Parameters
    ----------
    a : array, at least 2-D.
      Array whose diagonal is to be filled, it gets modified in-place.

    val : scalar or array_like
      Value(s) to write on the diagonal. If `val` is scalar, the value is
      written along the diagonal. If array-like, the flattened `val` is
      written along the diagonal, repeating if necessary to fill all
      diagonal entries.

    wrap : bool
      For tall matrices in NumPy version up to 1.6.2, the
      diagonal "wrapped" after N columns. You can have this behavior
      with this option. This affects only tall matrices.

    See also
    --------
    diag_indices, diag_indices_from

    Notes
    -----
    .. versionadded:: 1.4.0

    This functionality can be obtained via `diag_indices`, but internally
    this version uses a much faster implementation that never constructs the
    indices and uses simple slicing.

    Examples
    --------
    >>> a = np.zeros((3, 3), int)
    >>> np.fill_diagonal(a, 5)
    >>> a
    array([[5, 0, 0],
           [0, 5, 0],
           [0, 0, 5]])

    The same function can operate on a 4-D array:

    >>> a = np.zeros((3, 3, 3, 3), int)
    >>> np.fill_diagonal(a, 4)

    We only show a few blocks for clarity:

    >>> a[0, 0]
    array([[4, 0, 0],
           [0, 0, 0],
           [0, 0, 0]])
    >>> a[1, 1]
    array([[0, 0, 0],
           [0, 4, 0],
           [0, 0, 0]])
    >>> a[2, 2]
    array([[0, 0, 0],
           [0, 0, 0],
           [0, 0, 4]])

    The wrap option affects only tall matrices:

    >>> # tall matrices no wrap
    >>> a = np.zeros((5, 3), int)
    >>> np.fill_diagonal(a, 4)
    >>> a
    array([[4, 0, 0],
           [0, 4, 0],
           [0, 0, 4],
           [0, 0, 0],
           [0, 0, 0]])

    >>> # tall matrices wrap
    >>> a = np.zeros((5, 3), int)
    >>> np.fill_diagonal(a, 4, wrap=True)
    >>> a
    array([[4, 0, 0],
           [0, 4, 0],
           [0, 0, 4],
           [0, 0, 0],
           [4, 0, 0]])

    >>> # wide matrices
    >>> a = np.zeros((3, 5), int)
    >>> np.fill_diagonal(a, 4, wrap=True)
    >>> a
    array([[4, 0, 0, 0, 0],
           [0, 4, 0, 0, 0],
           [0, 0, 4, 0, 0]])

    The anti-diagonal can be filled by reversing the order of elements
    using either `numpy.flipud` or `numpy.fliplr`.

    >>> a = np.zeros((3, 3), int);
    >>> np.fill_diagonal(np.fliplr(a), [1,2,3])  # Horizontal flip
    >>> a
    array([[0, 0, 1],
           [0, 2, 0],
           [3, 0, 0]])
    >>> np.fill_diagonal(np.flipud(a), [1,2,3])  # Vertical flip
    >>> a
    array([[0, 0, 3],
           [0, 2, 0],
           [1, 0, 0]])

    Note that the order in which the diagonal is filled varies depending
    on the flip function.