CADETProcess.fractionation.FractionationOptimizer.evaluate#

FractionationOptimizer.evaluate(simulation_results: SimulationResults, purity_required: float | list[float], components: list[str] | None = None, use_total_concentration_components: bool = True, ranking: str | list[float] | int = 'equal', obj_fun: Callable | None = None, n_objectives: int = 1, bad_metrics: float | list[float] = 0, minimize: bool = True, allow_empty_fractions: bool = True, scale_trust_radius: bool = False, ignore_failed: bool = False, return_optimization_results: bool = False, save_results: bool = False) → Fractionator | tuple[Fractionator, OptimizationResults]#

Optimize the fractionation times with respect to purity constraints.

Parameters:

simulation_resultsSimulationResults: Results containing the chromatograms for fractionation.
purity_requiredfloat or array_like: Minimum required purity for components. If is float, the same value is assumed for all components.
componentslist: List of components to consider in the fractionation process.
use_total_concentration_componentsbool, Default=True: Flag wheter to use the total concentration components.
rankingstr | list[float] | int, optional, default=”equal”: Weighting factors for individual components. If integer, only component of that index is used. If None, the same value is assumed for all components. The default is None.
obj_funfunction, optional: Objective function used for OptimizationProblem. If COBYLA is used, must return single objective. If is None, the mass of all components is maximized.
n_objectivesint, optional: Number of objectives returned by obj_fun. The default is 1.
bad_metricsfloat or list of floats, optional: Values to be returned if evaluation of objective function failes. The default is 0.
minimizebool, optional: If True, the obj_fun is assumed to return a value that is to be minimized. The default it True.
allow_empty_fractions: bool, optional: If True, allow empty fractions. The default is True.
scale_trust_radius: bool, optional: If True, scale initial trust radius depending on linear constraints and initial values. The default is False.
ignore_failedbool, optional: Ignore failed optimization and use initial values. The default is False.
return_optimization_resultsbool, optional: If True, return optimization results. Otherwise, return fractionation object. The default is False.
save_resultsbool, optional: If True, save optimization results. The default is False.

Returns:

Fractionator or OptimizationResults: The Fractionator object with optimized cut times or the OptimizationResults object.

Raises:

TypeError: If simulation_results is not an instance of SimulationResults.
CADETProcessError: If simulation_results do not contain chromatograms.
Warning: If purity requirements cannot be fulfilled.

CADETProcess.fractionation.FractionationOptimizer.evaluate

Contents

CADETProcess.fractionation.FractionationOptimizer.evaluate#