SciPy

numpy.fill_diagonal

numpy.fill_diagonal(a, val, wrap=False)[source]

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.

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) >>> 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) >>> 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) >>> fill_diagonal(a, 4, wrap=True) >>> a array([[4, 0, 0, 0, 0],

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

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