This is a perform for resolving non-linear least squares troubles. It makes use of a way which combines the traditional Levenberg-Marquardt method with a quasi-newton tactic.
This perform is identical to the find_min_bobyqa program apart from that it negates the target functionality just before executing optimization. Thus this perform will try to find the maximizer of the objective in lieu of the minimizer.
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Testing: Crafting any code devoid of an experiment is considered the most significantly terrible thing you can do. 1 ought to compose all of the experiments, but time limitations are the actual avoidance.
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Observe that BOBYQA only will work on functions of two or maybe more variables. Therefore if you must conduct by-product-totally free optimization over a operate of just one variable then you must utilize the find_max_single_variable functionality.
Just take care to be sure proper bounds-checking and every other checking that look here needs to occur to circumvent an out of bounds difficulty.
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