petab.core¶

PEtab core functions (or functions that don’t fit anywhere else)

Functions

`concat_tables`(tables, …)	Concatenate DataFrames provided as DataFrames or filenames, and a parser
`flatten_timepoint_specific_output_overrides`(…)	Flatten timepoint-specific output parameter overrides.
`get_notnull_columns`(df, candidates)	Return list of `df`-columns in `candidates` which are not all null/nan.
`get_observable_id`(parameter_id)	Get PEtab observable ID from PEtab-style sigma or observable AssignmentRule-target `parameter_id`.
`get_simulation_df`(simulation_file)	Read PEtab simulation table
`get_visualization_df`(visualization_file)	Read PEtab visualization table
`parameter_is_offset_parameter`(parameter, formula)	Check if is offset parameter.
`parameter_is_scaling_parameter`(parameter, …)	Check if is scaling parameter.
`to_float_if_float`(x)	Return input as float if possible, otherwise return as is
`write_simulation_df`(df, filename)	Write PEtab simulation table
`write_visualization_df`(df, filename)	Write PEtab visualization table

petab.core.concat_tables(tables: Union[str, pandas.core.frame.DataFrame, Iterable[Union[pandas.core.frame.DataFrame, str]]], file_parser: Optional[Callable] = None) → pandas.core.frame.DataFrame¶

Concatenate DataFrames provided as DataFrames or filenames, and a parser

Parameters:	tables – Iterable of tables to join, as DataFrame or filename. file_parser – Function used to read the table in case filenames are provided, accepting a filename as only argument.
Returns:	The concatenated DataFrames

petab.core.flatten_timepoint_specific_output_overrides(petab_problem: petab.problem.Problem) → None¶

Flatten timepoint-specific output parameter overrides.

If the PEtab problem definition has timepoint-specific observableParameters or noiseParameters for the same observable, replace those by replicating the respective observable.

This is a helper function for some tools which may not support such timepoint-specific mappings. The observable table and measurement table are modified in place.

Parameters:	petab_problem – PEtab problem to work on

petab.core.get_notnull_columns(df: pandas.core.frame.DataFrame, candidates: Iterable[T_co])¶

Return list of df-columns in candidates which are not all null/nan.

The output can e.g. be used as input for pandas.DataFrame.groupby.

Parameters:	df – Dataframe candidates – Columns of `df` to consider

petab.core.get_observable_id(parameter_id: str) → str¶

Get PEtab observable ID from PEtab-style sigma or observable AssignmentRule-target parameter_id.

e.g. for ‘observable_obs1’ -> ‘obs1’, for ‘sigma_obs1’ -> ‘obs1’

Parameters:	parameter_id – Some parameter ID
Returns:	Observable ID

petab.core.get_simulation_df(simulation_file: str) → pandas.core.frame.DataFrame¶

Read PEtab simulation table

Parameters:	simulation_file – URL or filename of PEtab simulation table
Returns:	Simulation DataFrame

petab.core.get_visualization_df(visualization_file: str) → pandas.core.frame.DataFrame¶

Read PEtab visualization table

Parameters:	visualization_file – URL or filename of PEtab visualization table
Returns:	Visualization DataFrame

petab.core.parameter_is_offset_parameter(parameter: str, formula: str) → bool¶

Check if is offset parameter.

Parameters:	parameter – Some identifier. formula – Some sympy-compatible formula.
Returns:	`True` if parameter `parameter` is an offset parameter with positive sign in formula `formula`.

petab.core.parameter_is_scaling_parameter(parameter: str, formula: str) → bool¶

Check if is scaling parameter.

Parameters:

parameter – Some identifier.
formula – Some sympy-compatible formula.

Returns:

True if parameter parameter is a scaling parameter in formula: formula.

petab.core.to_float_if_float(x: Any) → Any¶

Return input as float if possible, otherwise return as is

Parameters:	x – Anything
Returns:	`x` as float if possible, otherwise `x`

petab.core.write_simulation_df(df: pandas.core.frame.DataFrame, filename: str) → None¶

Write PEtab simulation table

Parameters:	df – PEtab simulation table filename – Destination file name

petab.core.write_visualization_df(df: pandas.core.frame.DataFrame, filename: str) → None¶

Write PEtab visualization table

Parameters:	df – PEtab visualization table filename – Destination file name