Awhile back there were good signs that SciPy would end up with a `diff` module: https://github.com/scipy/scipy/issues/2035 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 http://code.google.com/p/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 _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
