Hi Ariel,
I think that the docstring in 1.9 is fine (has the 1.9 result). The docs online (for all of numpy) are still on version 1.8, though.
I think that enabling the old behavior might be useful, if only so that I can write code that behaves consistently across these two versions of numpy. For now, I might just copy over the 1.8 code into my project.
Hmm, I got this with 1.9.0: Examples -------- >>> x = np.array([1, 2, 4, 7, 11, 16], dtype=np.float) >>> np.gradient(x) array([ 1. , 1.5, 2.5, 3.5, 4.5, 5. ]) >>> np.gradient(x, 2) array([ 0.5 , 0.75, 1.25, 1.75, 2.25, 2.5 ]) >>> np.gradient(np.array([[1, 2, 6], [3, 4, 5]], dtype=np.float)) [array([[ 2., 2., -1.], [ 2., 2., -1.]]), array([[ 1. , 2.5, 4. ], [ 1. , 1. , 1. ]])] In [5]: x =np.array([1, 2, 4, 7, 11, 16], dtype=np.float) In [6]: print(np.gradient(x)) [ 0.5 1.5 2.5 3.5 4.5 5.5] In [7]: print(np.gradient(x, 2)) [ 0.25 0.75 1.25 1.75 2.25 2.75] … I think there is a point for supporting the old behaviour besides backwards-compatibility or any sort of Matlab-compliance as I’d probably like to be able to restrict a function to linear/1st order differences in cases where I know the input to be not well-behaved. +1 for an order=2 or maxorder=2 flag Cheers, Derek