sbmlsim.fit.result
¶
Result of optimization.
Module Contents¶
Classes¶
Result of optimization problem. |
Attributes¶
- class sbmlsim.fit.result.OptimizationResult(parameters, fits, trajectories, sid=None)[source]¶
Bases:
sbmlsim.serialization.ObjectJSONEncoder
Result of optimization problem.
- Parameters:
parameters (Iterable[sbmlsim.fit.objects.FitParameter]) –
fits (List[scipy.optimize.OptimizeResult]) –
trajectories (List) –
sid (str) –
- property xopt: numpy.ndarray[source]¶
Numerical values of optimal parameters.
- Return type:
numpy.ndarray
- property xopt_fit_parameters: List[sbmlsim.fit.objects.FitParameter][source]¶
Optimal parameters as Fit parameters.
- Return type:
- to_json(path=None)[source]¶
Store OptimizationResult as json.
Uses the to_dict method.
- Parameters:
path (Optional[pathlib.Path]) –
- Return type:
Union[str, pathlib.Path]
- static from_json(json_info)[source]¶
Load OptimizationResult from Path or str.
- Parameters:
json_info (Union[str, pathlib.Path]) –
- Returns:
- Return type:
- static combine(opt_results)[source]¶
Combine results from multiple parameter fitting experiments.
- Parameters:
opt_results (List[OptimizationResult]) –
- Return type:
- static process_traces(parameters, trajectories)[source]¶
Process the optimization results.
- Parameters:
parameters (List[sbmlsim.fit.objects.FitParameter]) –
- static process_fits(parameters, fits)[source]¶
Process the optimization results.
- Parameters:
parameters (List[sbmlsim.fit.objects.FitParameter]) –
fits (List[scipy.optimize.OptimizeResult]) –