summarize_individuals#

pharmpy.tools.summarize_individuals(models, models_res)[source]#

Creates a summary dataframe keyed by model-individual pairs for an input list of models.

Content of the various columns:

Column	Description
`outlier_count`	Number of observations with CWRES > 5
`ofv`	Individual OFV
`dofv_vs_parent`	Difference in individual OFV between this model and its parent model
`predicted_dofv`	Predicted dOFV if this individual was excluded
`predicted_residual`	Predicted residual

Parameters:

models (List[Model]) – Input models
models_res (List[ModelfitResults]) – Input results

Returns:

pd.DataFrame | None – The summary as a dataframe

Examples

>>> from pharmpy.modeling import *
>>> model = load_example_model("pheno")
>>> from pharmpy.tools import fit, summarize_individuals
>>> fit_results = fit(model)  
<Pharmpy model object pheno>
>>> from pharmpy.tools import run_tool 
>>> results = run_tool(
...     'modelsearch',
...     model=model,
...     mfl='ABSORPTION(ZO);PERIPHERALS([1, 2])',
...     algorithm='reduced_stepwise'
... ) 
>>> summarize_individuals([results.start_model, *results.models]) 