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# numpy.fill_diagonal

`numpy.``fill_diagonal`(a, val, wrap=False)

  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, ..., 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 Value to be written on the diagonal, its type must be compatible with that of the array a. 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 affect only tall matrices.

  See also

  `diag_indices`, `diag_indices_from`

  Notes

  New in version 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]])

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

  > [0, 4, 0], [0, 0, 4], [0, 0, 0], [4, 0, 0]])

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

  > [0, 4, 0, 0, 0], [0, 0, 4, 0, 0]])

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