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) –
- to_json(self, 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
- _x_as_fit_parameters(self, x)[source]¶
Convert numerical parameter vector to fit parameters.
- 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]) –