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SNOBFIT

class SNOBFIT(maxiter=1000, maxfail=10, maxmp=None, verbose=False)[Quellcode]

Bases: Optimizer

Stable Noisy Optimization by Branch and FIT algorithm.

SnobFit is used for the optimization of derivative-free, noisy objective functions providing robust and fast solutions of problems with continuous variables varying within bound.

Uses skquant.opt installed with pip install scikit-quant. For further detail, please refer to https://github.com/scikit-quant/scikit-quant and https://qat4chem.lbl.gov/software.

Parameter
  • maxiter (int) – Maximum number of function evaluations.

  • maxmp (Optional[int]) – Maximum number of model points requested for the local fit. Default = 2 * number of parameters + 6 set to this value when None.

  • maxfail (int) – Maximum number of failures to improve the solution. Stops the algorithm after maxfail is reached.

  • verbose (bool) – Provide verbose (debugging) output.

Verursacht

Methods

get_support_level

Returns support level dictionary.

gradient_num_diff

We compute the gradient with the numeric differentiation in the parallel way, around the point x_center.

minimize

Minimize the scalar function.

print_options

Print algorithm-specific options.

set_max_evals_grouped

Set max evals grouped

set_options

Sets or updates values in the options dictionary.

wrap_function

Wrap the function to implicitly inject the args at the call of the function.

Attributes

bounds_support_level

Returns bounds support level

gradient_support_level

Returns gradient support level

initial_point_support_level

Returns initial point support level

is_bounds_ignored

Returns is bounds ignored

is_bounds_required

Returns is bounds required

is_bounds_supported

Returns is bounds supported

is_gradient_ignored

Returns is gradient ignored

is_gradient_required

Returns is gradient required

is_gradient_supported

Returns is gradient supported

is_initial_point_ignored

Returns is initial point ignored

is_initial_point_required

Returns is initial point required

is_initial_point_supported

Returns is initial point supported

setting

Return setting

settings
Rückgabetyp

Dict[str, Any]