pharmpy.tools Package#

Functions#

create_report(results, path)

Create standard report for results

fit(model_or_models[, esttool, path, context])

Fit models.

is_strictness_fulfilled(model, results, ...)

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

read_results(path)

Read results object from file

read_modelfit_results(path[, esttool])

Read results from external tool for a model

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_linearize([model, results, model_name, ...])

Linearize a model

run_modelfit([model_or_models, n])

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, model, results[, ...])

Run the structsearch tool.

run_tool(name, *args, **kwargs)

Run tool workflow

run_simulation([model])

Run the simulation tool.

summarize_modelfit_results(context[, ...])

Summarize results of model runs

write_results(results, path[, compression, csv])

Write results object to json (or csv) file