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jax.numpy.fill_diagonal — JAX documentation

jax.numpy.fill_diagonal(a, val, wrap=False, *, inplace=True)[source]#

Return a copy of the array with the diagonal overwritten.

JAX implementation of numpy.fill_diagonal().

The semantics of numpy.fill_diagonal() are to modify arrays in-place, which is not possible for JAX’s immutable arrays. The JAX version returns a modified copy of the input, and adds the inplace parameter which must be set to False` by the user as a reminder of this API difference.

Parameters:

• a (ArrayLike) – input array. Must have a.ndim >= 2. If a.ndim >= 3, then all dimensions must be the same size.

• val (ArrayLike) – scalar or array with which to fill the diagonal. If an array, it will be flattened and repeated to fill the diagonal entries.

• inplace (bool) – must be set to False to indicate that the input is not modified in-place, but rather a modified copy is returned.

• wrap (bool)

Returns:

A copy of a with the diagonal set to val.

Return type:

Array

Examples

>>> x = jnp.zeros((3, 3), dtype=int)
>>> jnp.fill_diagonal(x, jnp.array([1, 2, 3]), inplace=False)
Array([[1, 0, 0],
       [0, 2, 0],
       [0, 0, 3]], dtype=int32)

Unlike numpy.fill_diagonal(), the input x is not modified.

If the diagonal value has too many entries, it will be truncated

>>> jnp.fill_diagonal(x, jnp.arange(100, 200), inplace=False)
Array([[100,   0,   0],
       [  0, 101,   0],
       [  0,   0, 102]], dtype=int32)

If the diagonal has too few entries, it will be repeated:

>>> x = jnp.zeros((4, 4), dtype=int)
>>> jnp.fill_diagonal(x, jnp.array([3, 4]), inplace=False)
Array([[3, 0, 0, 0],
       [0, 4, 0, 0],
       [0, 0, 3, 0],
       [0, 0, 0, 4]], dtype=int32)

For non-square arrays, the diagonal of the leading square slice is filled:

>>> x = jnp.zeros((3, 5), dtype=int)
>>> jnp.fill_diagonal(x, 1, inplace=False)
Array([[1, 0, 0, 0, 0],
       [0, 1, 0, 0, 0],
       [0, 0, 1, 0, 0]], dtype=int32)

And for square N-dimensional arrays, the N-dimensional diagonal is filled:

>>> y = jnp.zeros((2, 2, 2))
>>> jnp.fill_diagonal(y, 1, inplace=False)
Array([[[1., 0.],
        [0., 0.]],

       [[0., 0.],
        [0., 1.]]], dtype=float32)

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