minimizers_scipy¶
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class
zfit.minimizers.minimizers_scipy.
Scipy
(minimizer='L-BFGS-B', tolerance=None, verbosity=5, name=None, **minimizer_options)[source]¶ Bases:
zfit.minimizers.baseminimizer.BaseMinimizer
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copy
()¶
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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
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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.
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tolerance
¶
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