minimizer_tfp

class zfit.minimizers.minimizer_tfp.BFGS(strategy: zfit.minimizers.baseminimizer.ZfitStrategy = None, tolerance: float = 1e-05, verbosity: int = 5, max_calls: int = 3000, name: str = 'BFGS_TFP', options: Mapping = None)[source]

Bases: zfit.minimizers.baseminimizer.BaseMinimizer

Parameters
  • strategy (ZfitStrategy) – Strategy that handles NaN and more (to come, experimental)

  • tolerance (float) – Difference between the function value that suffices to stop minimization

  • verbosity – The higher, the more is printed. Between 1 and 10 typically

  • max_calls (int) – Maximum number of calls, approximate

  • name – Name of the Minimizer

  • options – A dict containing the options given to the minimization function, overriding the default

copy()
minimize(loss: zfit.core.interfaces.ZfitLoss, params: Optional[Iterable[zfit.core.interfaces.ZfitParameter]] = None) → zfit.minimizers.fitresult.FitResult

Fully minimize the loss with respect to params.

Parameters
  • loss (ZfitLoss) – Loss to be minimized.

  • params (list(zfit.Parameter) – The parameters with respect to which to minimize the loss. If None, the parameters will be taken from the loss.

Returns

The fit result.

Return type

FitResult

step(loss, params: Union[Iterable[zfit.core.interfaces.ZfitParameter], None, Iterable[str]] = None)

Perform a single step in the minimization (if implemented).

Parameters

() (params) –

Returns:

Raises

MinimizeStepNotImplementedError – if the step method is not implemented in the minimizer.

property tolerance