Comments (3)
I don't think that's necessary. It's very predictable, isn't it? Are you thinking about adding to the number of calls in optimize?
from diff.
Yes, it's kind of predictable, the number of evaluations implicitly follows from the method. I think that we should explicitly write the number in the docs. I wanted to know your opinion.
And yes, I was having optimize in mind even though I think it would be nice if we didn't mix the stats from the method itself and from fd approximations. Speaking of optimize, we will need to provide a mechanism for calling Gradient and/or Hessian that sets OriginKnown and Value.
from diff.
If we want to support this, I think it should be implemented with functions. For example, func HessianEvals(stencil Stencil, originKnown bool) int
.
Feel free to re-open this issue in the main repository if you think it's still a good idea.
from diff.
Related Issues (9)
- fd: lacks package doc comment
- Add finite difference approximation of the Jacobian HOT 1
- diff: Add finite difference approximation of the Hessian HOT 3
- fd: guard against function modification HOT 1
- Don't repeat origin calculations
- Change default formula in Gradient to Forward?
- Check formula for repeated location
- diff: Add finite difference support for the Laplacian HOT 1
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