OptimizeResult#

class gammapy.modeling.OptimizeResult(models, nfev, total_stat, trace, minuit=None, **kwargs)[source]#

Bases: FitStepResult

Optimize result object.

Parameters:

modelsDatasetModels: Best fit models.
nfevint: Number of function evaluations.
total_statfloat: Value of the fit statistic at minimum.
traceTable: Parameter trace from the optimisation.
minuitMinuit, optional: Minuit object. Default is None.
kwargsdict: Extra kwargs are passed to the backend.

Attributes Summary

`backend`	Optimizer backend used for the fit.
`message`	Optimizer status message.
`method`	Optimizer method used for the fit.
`minuit`	Minuit object.
`models`	Best fit models.
`nfev`	Number of function evaluations.
`parameters`	Best fit parameters.
`success`	Fit success status flag.
`total_stat`	Value of the fit statistic at minimum.
`trace`	Parameter trace from the optimisation.

Methods Summary

Convert to dictionary.

Attributes Documentation

backend#: Optimizer backend used for the fit.

message#: Optimizer status message.

method#: Optimizer method used for the fit.

minuit#: Minuit object.

models#: Best fit models.

nfev#: Number of function evaluations.

parameters#: Best fit parameters.

success#: Fit success status flag.

total_stat#: Value of the fit statistic at minimum.

trace#: Parameter trace from the optimisation.

Methods Documentation

to_dict()[source]#: Convert to dictionary.