amici.petab_import_pysb

PySB-PEtab Import

Import a model in the PySB-adapted petab (https://github.com/PEtab-dev/PEtab) format into AMICI.

Functions

create_dummy_sbml(pysb_model[, observable_ids])	Create SBML dummy model for to use PySB models with PEtab.
import_model_pysb(petab_problem[, ...])	Create AMICI model from PySB-PEtab problem

Classes

PysbPetabProblem([pysb_model])

Representation of a PySB-model-based PEtab problem

class amici.petab_import_pysb.PysbPetabProblem(pysb_model=None, *args, **kwargs)

Representation of a PySB-model-based PEtab problem

This class extends petab.Problem with a PySB model. The model is augmented with the observation model based on the PEtab observable table. For now, a dummy SBML model is created which allows used the existing SBML-PEtab API.

Variables

pysb_model – PySB model instance from of this PEtab problem.

static from_files(condition_file=None, measurement_file=None, parameter_file=None, visualization_files=None, observable_files=None, pysb_model_file=None, flatten=False)

Factory method to load model and tables from files.

Parameters

• condition_file (typing.Union[str, pathlib.Path, typing.Iterable[typing.Union[str, pathlib.Path]], None]) – PEtab condition table

• measurement_file (typing.Union[str, pathlib.Path, typing.Iterable[typing.Union[str, pathlib.Path]], None]) – PEtab measurement table

• parameter_file (typing.Union[str, pathlib.Path, typing.Iterable[typing.Union[str, pathlib.Path]], None]) – PEtab parameter table

• visualization_files (typing.Union[str, pathlib.Path, typing.Iterable[typing.Union[str, pathlib.Path]], None]) – PEtab visualization tables

• observable_files (typing.Union[str, pathlib.Path, typing.Iterable[typing.Union[str, pathlib.Path]], None]) – PEtab observables tables

• pysb_model_file (typing.Union[str, pathlib.Path, None]) – PySB model file

• flatten (bool) – Flatten the petab problem

Return type

amici.petab_import_pysb.PysbPetabProblem

Returns

Petab Problem

static from_yaml(yaml_config, flatten=False)

Factory method to load model and tables as specified by YAML file.

NOTE: The PySB model is currently expected in the YAML file under sbml_files.

Parameters

• yaml_config (typing.Union[typing.Dict, pathlib.Path, str]) – PEtab configuration as dictionary or YAML file name

• flatten (bool) – Flatten the petab problem

Return type

amici.petab_import_pysb.PysbPetabProblem

Returns

Petab Problem

amici.petab_import_pysb.create_dummy_sbml(pysb_model, observable_ids=None)

Create SBML dummy model for to use PySB models with PEtab.

Model must at least contain PEtab problem parameter and noise parameters for observables.

Parameters

• pysb_model (pysb.core.Model) – PySB model

• observable_ids (typing.Optional[typing.Iterable[str]]) – Observable IDs

Return type

typing.Tuple[libsbml.Model, libsbml.SBMLDocument]

Returns

A dummy SBML model and document.

amici.petab_import_pysb.import_model_pysb(petab_problem, model_output_dir=None, verbose=True, model_name=None, **kwargs)

Create AMICI model from PySB-PEtab problem

Parameters

• petab_problem (amici.petab_import_pysb.PysbPetabProblem) – PySB PEtab problem

• model_output_dir (typing.Union[pathlib.Path, str, None]) – Directory to write the model code to. Will be created if doesn’t exist. Defaults to current directory.

• verbose (typing.Union[bool, int, None]) – Print/log extra information.

• model_name (typing.Optional[str]) – Name of the generated model module

• kwargs – Additional keyword arguments to be passed to amici.pysb_import.pysb2amici().

Return type

None