jax.numpy.ediff1d¶
-
jax.numpy.
ediff1d
(ary, to_end=None, to_begin=None)[source]¶ The differences between consecutive elements of an array.
LAX-backend implementation of
ediff1d()
. Unlike NumPy’s implementation of ediff1d,jax.numpy.ediff1d()
will not issue an error if castingto_end
orto_begin
to the type ofary
loses precision.Original docstring below.
- Parameters
ary (array_like) – If necessary, will be flattened before the differences are taken.
to_end (array_like, optional) – Number(s) to append at the end of the returned differences.
to_begin (array_like, optional) – Number(s) to prepend at the beginning of the returned differences.
- Returns
ediff1d – The differences. Loosely, this is
ary.flat[1:] - ary.flat[:-1]
.- Return type
See also
Notes
When applied to masked arrays, this function drops the mask information if the to_begin and/or to_end parameters are used.
Examples
>>> x = np.array([1, 2, 4, 7, 0]) >>> np.ediff1d(x) array([ 1, 2, 3, -7])
>>> np.ediff1d(x, to_begin=-99, to_end=np.array([88, 99])) array([-99, 1, 2, ..., -7, 88, 99])
The returned array is always 1D.
>>> y = [[1, 2, 4], [1, 6, 24]] >>> np.ediff1d(y) array([ 1, 2, -3, 5, 18])