petab.measurements

Functions operating on the PEtab measurement table

Functions

`assert_overrides_match_parameter_count`(...)	Ensure that number of parameters in the observable definition matches the number of overrides in `measurement_df`
`create_measurement_df`()	Create empty measurement dataframe
`get_measurement_df`(measurement_file)	Read the provided measurement file into a `pandas.Dataframe`.
`get_measurement_parameter_ids`(measurement_df)	Return list of ID of parameters which occur in measurement table as observable or noise parameter overrides.
`get_rows_for_condition`(measurement_df, condition)	Extract rows in measurement_df for condition according to 'preequilibrationConditionId' and 'simulationConditionId' in condition.
`get_simulation_conditions`(measurement_df)	Create a table of separate simulation conditions.
`measurement_is_at_steady_state`(time)	Check whether a measurement is at steady state.
`measurements_have_replicates`(measurement_df)	Tests whether the measurements come with replicates
`split_parameter_replacement_list`(list_string)	Split values in observableParameters and noiseParameters in measurement table.
`write_measurement_df`(df, filename)	Write PEtab measurement table

petab.measurements.assert_overrides_match_parameter_count(measurement_df: DataFrame, observable_df: DataFrame) → None[source]

Ensure that number of parameters in the observable definition matches the number of overrides in measurement_df

Parameters:

measurement_df – PEtab measurement table
observable_df – PEtab observable table

petab.measurements.create_measurement_df() → DataFrame[source]

Create empty measurement dataframe

Returns:: Created DataFrame

petab.measurements.get_measurement_df(measurement_file: None | str | Path | DataFrame) → DataFrame[source]

Read the provided measurement file into a pandas.Dataframe.

Parameters:: measurement_file – Name of file to read from or pandas.Dataframe
Returns:: Measurement DataFrame

petab.measurements.get_measurement_parameter_ids(measurement_df: DataFrame) → List[str][source]

Return list of ID of parameters which occur in measurement table as observable or noise parameter overrides.

Parameters:: measurement_df – PEtab measurement DataFrame
Returns:: List of parameter IDs

petab.measurements.get_rows_for_condition(measurement_df: DataFrame, condition: Series | DataFrame | Dict) → DataFrame[source]

Extract rows in measurement_df for condition according to ‘preequilibrationConditionId’ and ‘simulationConditionId’ in condition.

Parameters:

measurement_df – PEtab measurement DataFrame
condition – DataFrame with single row (or Series) and columns ‘preequilibrationConditionId’ and ‘simulationConditionId’. Or dictionary with those keys.

Returns:

The subselection of rows in measurement_df for the condition condition.

petab.measurements.get_simulation_conditions(measurement_df: DataFrame) → DataFrame[source]

Create a table of separate simulation conditions. A simulation condition is a specific combination of simulationConditionId and preequilibrationConditionId.

Parameters:: measurement_df – PEtab measurement table
Returns:: Dataframe with columns ‘simulationConditionId’ and ‘preequilibrationConditionId’. All-null columns will be omitted. Missing ‘preequilibrationConditionId’s will be set to ‘’ (empty string).

petab.measurements.measurement_is_at_steady_state(time: float) → bool[source]

Check whether a measurement is at steady state.

Parameters:: time – The time.
Returns:: Whether the measurement is at steady state.

petab.measurements.measurements_have_replicates(measurement_df: DataFrame) → bool[source]

Tests whether the measurements come with replicates

Parameters:: measurement_df – Measurement table
Returns:: True if there are replicates, False otherwise

petab.measurements.split_parameter_replacement_list(list_string: str | Number, delim: str = ';') → List[str | Number][source]

Split values in observableParameters and noiseParameters in measurement table.

Parameters:

list_string – delim-separated stringified list
delim – delimiter

Returns:

List of split values. Numeric values may be converted to float, and parameter IDs are kept as strings.

petab.measurements.write_measurement_df(df: DataFrame, filename: str | Path) → None[source]

Write PEtab measurement table

Parameters:

df – PEtab measurement table
filename – Destination file name