[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
`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.
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