[Numpy-discussion] numerical gradient, Jacobian, and Hessian

Alan G Isaac alan.isaac at gmail.com
Sun Apr 20 10:55:35 EDT 2014

Awhile back there were good signs that SciPy
would end up with a `diff` module:
Is this still moving forward?

It would certainly be nice for SciPy to have intuitive
numerical gradients, Jacobians, and Hessians.  The last
two are I think missing altogether.  The first exists
as scipy.optimize.approx_fprime.

`approx_fprime` seems to work fine, but I suggest it
has the following drawbacks:
- it is hard to find (e.g., try doing a Google search
   on "scipy gradient" or "scipy numerical gradient"
- related, it is in the wrong location (scipy.optimize)
- the signature is odd: (x,f,dx) instead of (f,x,dx)
   (This matters for ease of recall and for teaching.)

In any case, as I understand it, the author's of numdifftools
expressed willingness to have their code moved into SciPy.
This seems like an excellent way forward.
There was talk of making this a summer of code project,
but that seems to have sputtered.

Alan Isaac

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