2014-08-08 16:37 GMT+02:00 Eelco Hoogendoorn
Do it in pure numpy? How about copying the source of numdifftools?
Of course it is a solution. I was just wondering if it exist something similar in the numpy/scipy packages so I do not have to use a new third party library to do that.
What exactly is the obstacle to using numdifftools? There seem to be no licensing issues. In my experience, its a crafty piece of work; and calculating a hessian correctly, accounting for all kinds of nasty floating point issues, is no walk in the park. Even if an analytical derivative isn't too big a pain in the ass to implement, there is a good chance that what numdifftools does is more numerically stable (though in all likelihood much slower).
The only good reason for a specialized solution I can think of is speed; but be aware what you are trading it in for. If speed is your major concern though, you really cant go wrong with Theano.
http://deeplearning.net/software/theano/library/gradient.html#theano.gradien...
Thanks, it seems that NumDiffTools is the way to go.
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