summarize_modelfit_results#

pharmpy.modeling.summarize_modelfit_results(models, include_all_estimation_steps=False)[source]#

Summarize results of model runs

Summarize different results after fitting a model, includes runtime, ofv, and parameter estimates (with errors). If include_all_estimation_steps is False, only the last estimation step will be included (note that in that case, the minimization_successful value will be referring to the last estimation step, if last step is evaluation it will go backwards until it finds an estimation step that wasn’t an evaluation).

Parameters:

  • models (list, Model) – List of models or single model

  • include_all_estimation_steps (bool) – Whether to include all estimation steps, default is False

Returns:

pd.DataFrame – A DataFrame of modelfit results with model name and estmation step as index.

Examples

>>> from pharmpy.modeling import load_example_model, summarize_modelfit_results
>>> model = load_example_model("pheno")
>>> summarize_modelfit_results(model) 
                 description  minimization_successful ...        ofv  ... runtime_total  ...
pheno PHENOBARB SIMPLE MODEL                     True ... 586.276056  ...           4.0  ...