2014-08-08 16:37 GMT+02:00 Eelco Hoogendoorn <hoogendoorn.eelco@gmail.com>:
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.



Thanks, it seems that NumDiffTools is the way to go.
 
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