Calculate n-th order difference between array elements along a given axis.
JAX implementation of numpy.diff().
The first order difference is computed by a[i+1] - a[i], and the n-th order difference is computed n times recursively.
a (ArrayLike) – input array. Must have a.ndim >= 1.
n (int) – int, optional, default=1. Order of the difference. Specifies the number of times the difference is computed. If n=0, no difference is computed and input is returned as is.
axis (int) – int, optional, default=-1. Specifies the axis along which the difference is computed. The difference is computed along axis -1 by default.
prepend (ArrayLike | None) – scalar or array, optional, default=None. Specifies the values to be prepended along axis before computing the difference.
append (ArrayLike | None) – scalar or array, optional, default=None. Specifies the values to be appended along axis before computing the difference.
An array containing the n-th order difference between the elements of a.
Examples
jnp.diff computes the first order difference along axis, by default.
>>> a = jnp.array([[1, 5, 2, 9],
... [3, 8, 7, 4]])
>>> jnp.diff(a)
Array([[ 4, -3, 7],
[ 5, -1, -3]], dtype=int32)
When n = 2, second order difference is computed along axis.
>>> jnp.diff(a, n=2)
Array([[-7, 10],
[-6, -2]], dtype=int32)
When prepend = 2, it is prepended to a along axis before computing the difference.
>>> jnp.diff(a, prepend=2)
Array([[-1, 4, -3, 7],
[ 1, 5, -1, -3]], dtype=int32)
When append = jnp.array([[3],[1]]), it is appended to a along axis before computing the difference.
>>> jnp.diff(a, append=jnp.array([[3],[1]]))
Array([[ 4, -3, 7, -6],
[ 5, -1, -3, -3]], dtype=int32)
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