pharmpy.tools Package

Functions

create_report(results, path)	Create standard report for results
create_results(path, **kwargs)	Create/recalculate results object given path to run directory
fit(model_or_models[, tool, path])	Fit models.
is_strictness_fulfilled(res, model, statement)	Takes a ModelfitResults object and a statement as input and returns True/False if the evaluation of the statement is True/False.
load_example_modelfit_results(name)	Load the modelfit results of an example model
predict_influential_individuals(model, results)	Predict influential individuals for a model using a machine learning model.
predict_influential_outliers(model, results)	Predict influential outliers for a model using a machine learning model.
predict_outliers(model, results[, cutoff])	Predict outliers for a model using a machine learning model.
print_fit_summary(model, modelfit_results)	Print a summary of the model fit
rank_models(base_model, base_model_res, ...)	Ranks a list of models
read_results(path)	Read results object from file
read_modelfit_results(path)	Read results from external tool for a model
resume_tool(path)	Resume tool workflow from tool database path
retrieve_final_model(res)	Retrieve final model from a result object
retrieve_models(source[, names])	Retrieve models after a tool run
run_allometry([model, results, ...])	Run allometry tool.
run_amd(input[, results, modeltype, ...])	Run Automatic Model Development (AMD) tool
run_bootstrap(model[, results, resamples])	Run bootstrap tool
run_covsearch(search_space[, p_forward, ...])	Run COVsearch tool.
run_estmethod(algorithm[, methods, solvers, ...])	Run estmethod tool.
run_iivsearch([algorithm, iiv_strategy, ...])	Run IIVsearch tool.
run_iovsearch([column, list_of_parameters, ...])	Run IOVsearch tool.
run_modelfit([model_or_models, n, tool])	Run modelfit tool.
run_modelsearch(search_space, algorithm[, ...])	Run Modelsearch tool.
run_retries([model, results, ...])	Run retries tool.
run_ruvsearch([model, results, groups, ...])	Run the ruvsearch tool.
run_structsearch(type[, search_space, ...])	Run the structsearch tool.
run_tool(name, *args, **kwargs)	Run tool workflow
run_simulation([model])	Run the simulation tool.
summarize_errors(results)	Summarize errors and warnings from one or multiple model runs.
summarize_individuals(models, models_res)	Creates a summary dataframe keyed by model-individual pairs for an input list of models.
summarize_individuals_count_table([models, ...])	Create a count table for individual data
summarize_modelfit_results(results[, ...])	Summarize results of model runs
write_results(results, path[, lzma, csv])	Write results object to json (or csv) file
get_model_features(model[, supress_warnings])	Create an MFL representation of an input model