petab.problem

PEtab Problem class

Functions

get_default_condition_file_name(model_name)

Get file name according to proposed convention

get_default_measurement_file_name(model_name)

Get file name according to proposed convention

get_default_parameter_file_name(model_name)

Get file name according to proposed convention

get_default_sbml_file_name(model_name[, folder])

Get file name according to proposed convention

Classes

Problem(sbml_model, sbml_reader, …)

PEtab parameter estimation problem as defined by
class petab.problem.Problem(sbml_model: Optional[libsbml.Model] = None, sbml_reader: Optional[libsbml.SBMLReader] = None, sbml_document: Optional[libsbml.SBMLDocument] = None, condition_df: Optional[pandas.core.frame.DataFrame] = None, measurement_df: Optional[pandas.core.frame.DataFrame] = None, parameter_df: Optional[pandas.core.frame.DataFrame] = None, visualization_df: Optional[pandas.core.frame.DataFrame] = None, observable_df: Optional[pandas.core.frame.DataFrame] = None)

Bases: object

PEtab parameter estimation problem as defined by

  • SBML model

  • condition table

  • measurement table

  • parameter table

  • observables table

Optionally it may contain visualization tables.

condition_df

PEtab condition table

measurement_df

PEtab measurement table

parameter_df

PEtab parameter table

observable_df

PEtab observable table

visualization_df

PEtab visualization table

sbml_reader

Stored to keep object alive.

sbml_document

Stored to keep object alive.

sbml_model

PEtab SBML model

_apply_mask(v: List, free: bool = True, fixed: bool = True)

Apply mask of only free or only fixed values.

Parameters

  • v – The full vector the mask is to be applied to.

  • free – Whether to return free parameters, i.e. parameters to estimate.

  • fixed – Whether to return fixed parameters, i.e. parameters not to estimate.

Returns

The reduced vector with applied mask.

Return type

v

create_parameter_df(*args, **kwargs)

Create a new PEtab parameter table

See create_parameter_df

static from_combine(filename: str) → petab.problem.Problem

Read PEtab COMBINE archive (http://co.mbine.org/documents/archive).

See also create_combine_archive.

Parameters

filename – Path to the PEtab-COMBINE archive

Returns

A petab.Problem instance.

static from_files(sbml_file: Optional[str] = None, condition_file: Optional[str] = None, measurement_file: Optional[Union[str, Iterable[str]]] = None, parameter_file: Optional[Union[str, List[str]]] = None, visualization_files: Optional[Union[str, Iterable[str]]] = None, observable_files: Optional[Union[str, Iterable[str]]] = None) → petab.problem.Problem

Factory method to load model and tables from files.

Parameters

  • sbml_file – PEtab SBML model

  • condition_file – PEtab condition table

  • measurement_file – PEtab measurement table

  • parameter_file – PEtab parameter table

  • visualization_files – PEtab visualization tables

  • observable_files – PEtab observables tables

static from_folder(folder: str, model_name: Optional[str] = None) → petab.problem.Problem

Factory method to use the standard folder structure and file names, i.e.

${model_name}/
  +-- experimentalCondition_${model_name}.tsv
  +-- measurementData_${model_name}.tsv
  +-- model_${model_name}.xml
  +-- parameters_${model_name}.tsv
Parameters

  • folder – Path to the directory in which the files are located.

  • model_name – If specified, overrides the model component in the file names. Defaults to the last component of folder.

static from_yaml(yaml_config: Union[Dict, str]) → petab.problem.Problem

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

Parameters

yaml_config – PEtab configuration as dictionary or YAML file name

get_lb(free: bool = True, fixed: bool = True, scaled: bool = False)

Generic function to get lower parameter bounds.

Parameters

  • free – Whether to return free parameters, i.e. parameters to estimate.

  • fixed – Whether to return fixed parameters, i.e. parameters not to estimate.

  • scaled – Whether to scale the values according to the parameter scale, or return them on linear scale.

Returns

The lower parameter bounds.

Return type

v

get_model_parameters()

See petab.sbml.get_model_parameters

get_noise_distributions()

See get_noise_distributions.

get_observable_ids()

Returns dictionary of observable ids.

get_observables(remove: bool = False)

Returns dictionary of observables definitions. See assignment_rules_to_dict for details.

get_optimization_parameter_scales()

Return list of optimization parameter scaling strings.

See petab.parameters.get_optimization_parameters.

get_optimization_parameters()

Return list of optimization parameter IDs.

See petab.parameters.get_optimization_parameters.

get_optimization_to_simulation_parameter_mapping(warn_unmapped: bool = True, scaled_parameters: bool = False)

See get_simulation_to_optimization_parameter_mapping.

get_sigmas(remove: bool = False)

Return dictionary of observableId => sigma as defined in the SBML model. This does not include parameter mappings defined in the measurement table.

get_simulation_conditions_from_measurement_df()

See petab.get_simulation_conditions

get_ub(free: bool = True, fixed: bool = True, scaled: bool = False)

Generic function to get upper parameter bounds.

Parameters

  • free – Whether to return free parameters, i.e. parameters to estimate.

  • fixed – Whether to return fixed parameters, i.e. parameters not to estimate.

  • scaled – Whether to scale the values according to the parameter scale, or return them on linear scale.

Returns

The upper parameter bounds.

Return type

v

get_x_ids(free: bool = True, fixed: bool = True)

Generic function to get parameter ids.

Parameters

  • free – Whether to return free parameters, i.e. parameters to estimate.

  • fixed – Whether to return fixed parameters, i.e. parameters not to estimate.

Returns

The parameter ids.

Return type

v

get_x_nominal(free: bool = True, fixed: bool = True, scaled: bool = False)

Generic function to get parameter nominal values.

Parameters

  • free – Whether to return free parameters, i.e. parameters to estimate.

  • fixed – Whether to return fixed parameters, i.e. parameters not to estimate.

  • scaled – Whether to scale the values according to the parameter scale, or return them on linear scale.

Returns

The parameter nominal values.

Return type

v

property lb

Parameter table lower bounds.

property lb_scaled

Parameter table lower bounds with applied parameter scaling

sample_parameter_startpoints(n_starts: int = 100)

Create starting points for optimization

See sample_parameter_startpoints

to_files(sbml_file: Optional[str] = None, condition_file: Optional[str] = None, measurement_file: Optional[str] = None, parameter_file: Optional[str] = None, visualization_file: Optional[str] = None, observable_file: Optional[str] = None, yaml_file: Optional[str] = None) → None

Write PEtab tables to files for this problem

Writes PEtab files for those entities for which a destination was passed.

NOTE: If this instance was created from multiple measurement or visualization tables, they will be merged and written to a single file.

Parameters

  • sbml_file – SBML model destination

  • condition_file – Condition table destination

  • measurement_file – Measurement table destination

  • parameter_file – Parameter table destination

  • visualization_file – Visualization table destination

  • observable_file – Observables table destination

  • yaml_file – YAML file destination

Raises

  • ValueError – If a destination was provided for a non-existing

  • entity. –

property ub

Parameter table upper bounds

property ub_scaled

Parameter table upper bounds with applied parameter scaling

property x_fixed_ids

Parameter table parameter IDs, for fixed parameters.

property x_fixed_indices

Parameter table non-estimated parameter indices.

property x_free_ids

Parameter table parameter IDs, for free parameters.

property x_free_indices

Parameter table estimated parameter indices.

property x_ids

Parameter table parameter IDs

property x_nominal

Parameter table nominal values

property x_nominal_fixed

Parameter table nominal values, for fixed parameters.

property x_nominal_fixed_scaled

Parameter table nominal values with applied parameter scaling, for fixed parameters.

property x_nominal_free

Parameter table nominal values, for free parameters.

property x_nominal_free_scaled

Parameter table nominal values with applied parameter scaling, for free parameters.

property x_nominal_scaled

Parameter table nominal values with applied parameter scaling

petab.problem.get_default_condition_file_name(model_name: str, folder: str = '')

Get file name according to proposed convention

petab.problem.get_default_measurement_file_name(model_name: str, folder: str = '')

Get file name according to proposed convention

petab.problem.get_default_parameter_file_name(model_name: str, folder: str = '')

Get file name according to proposed convention

petab.problem.get_default_sbml_file_name(model_name: str, folder: str = '')

Get file name according to proposed convention

petab.problem.warn(message, category=None, stacklevel=1, source=None)

Issue a warning, or maybe ignore it or raise an exception.