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fit.result

Result of optimization.

OptimizationResult 

OptimizationResult(
    parameters,
    fits,
    trajectories,
    sid=None,
    opid=None,
    settings=None,
)

Bases: ObjectJSONEncoder

Result of optimization problem.

Initialize optimization result.

Provides access to the FitParameters, the individual fits, and the trajectories of the fits. The settings and the id of the problem are stored with the result, a report of the fit needs them.

Parameters:

Name Type Description Default
parameters Iterable[FitParameter]

fit parameters of the optimization problem.

 required
fits list[OptimizeResult]

results of the single optimizations.

 required
trajectories list

trajectories of the single optimizations.

 required
sid str | None

identifier of the result, created from the time by default.

 None
opid str | None

id of the optimization problem the result belongs to.

 None
settings FitSettings | dict[str, Any] | None

settings the fit was run with.

 None

settings_stored property 

settings_stored

Settings the fit was run with.

Raises:

Type Description
ValueError

if the result carries no settings, e.g., because it was created by hand.

size property 

size

Get number of optimization runs in result.

xopt property 

xopt

Numerical values of optimal parameters.

xopt_fit_parameters property 

xopt_fit_parameters

Optimal parameters as Fit parameters.

to_tsv 

to_tsv(path)

Store fit results as TSV.

to_dict 

to_dict()

Convert to dictionary.

to_json 

to_json(path=None)

Store OptimizationResult as json.

Uses the to_dict method.

from_json staticmethod 

from_json(json_info)

Load OptimizationResult from Path or str.

:param json_info: :return:

parameter_set 

parameter_set(k=0, sid=None)

Get the parameters of a single optimization run.

The runs are ordered by increasing cost, so k=0 is the best fit.

Parameters:

Name Type Description Default
k int

index of the run in the results ordered by cost.

 0
sid str | None

identifier of the set, <result id>_<k> by default.

 None

Returns:

Type Description
ParameterSet

The parameter set of the run.

Raises:

Type Description
IndexError

if the result has no run k.

parameter_sets 

parameter_sets(size=1)

Get the parameters of the best optimization runs.

Parameters:

Name Type Description Default
size int

number of runs, ordered by increasing cost.

 1

Returns:

Type Description
ParameterSets

The parameter sets of the best runs.

combine staticmethod 

combine(opt_results)

Combine results from multiple parameter fitting experiments.

Raises:

Type Description
ValueError

if no results are given.

process_traces staticmethod 

process_traces(parameters, trajectories)

Process the trajectories of the optimizations.

process_fits staticmethod 

process_fits(parameters, fits)

Process the optimization results, sorted by increasing cost.

report 

report(path=None, print_output=True)

Report of optimization.

bound_warnings 

bound_warnings(parameters, x, rtol=0.05)

Warn about optimal parameters which ended up on their bounds.

A parameter on its bound means that the optimum is outside of the box in which the parameter was allowed to vary.

The distance to a bound is relative to the interval of the parameter. The optimization runs in logarithmic parameter space, so the distance is measured there as well whenever the bounds and the value are positive.

Parameters:

Name Type Description Default
parameters list[FitParameter]

fitted parameters with their bounds.

 required
x ndarray

optimal values of the parameters.

 required
rtol float

relative distance to a bound which is reported.

 0.05

Returns:

Type Description
list[str]

Messages for the parameters which are within rtol of one of their bounds.