diff --git a/python/amici/petab_objective.py b/python/amici/petab_objective.py index 0cb8b4d9d2..6144547f0a 100644 --- a/python/amici/petab_objective.py +++ b/python/amici/petab_objective.py @@ -66,18 +66,18 @@ def simulate_petab( will be used). To be provided as dict, mapping PEtab problem parameters to SBML IDs. :param simulation_conditions: - Result of `petab.get_simulation_conditions`. Can be provided to save - time if this has be obtained before. - Not required if `edatas` and `parameter_mapping` are provided. + Result of :py:func:`petab.get_simulation_conditions`. Can be provided + to save time if this has be obtained before. + Not required if ``edatas`` and ``parameter_mapping`` are provided. :param edatas: Experimental data. Parameters are inserted in-place for simulation. :param parameter_mapping: Optional precomputed PEtab parameter mapping for efficiency, as - generated by `create_parameter_mapping`. + generated by :py:func:`create_parameter_mapping`. :param scaled_parameters: - If True, problem_parameters are assumed to be on the scale provided - in the PEtab parameter table and will be unscaled. If False, they - are assumed to be in linear scale. + If ``True``, ``problem_parameters`` are assumed to be on the scale + provided in the PEtab parameter table and will be unscaled. + If ``False``, they are assumed to be in linear scale. :param log_level: Log level, see :mod:`amici.logging` module. :param num_threads: @@ -90,10 +90,8 @@ def simulate_petab( :return: Dictionary of - * cost function value (LLH), - * const function sensitivity w.r.t. parameters (SLLH), - (**NOTE**: Sensitivities are computed for the scaled parameters) - * list of `ReturnData` (RDATAS), + * cost function value (``LLH``), + * list of :class:`amici.amici.ReturnData` (``RDATAS``), corresponding to the different simulation conditions. For ordering of simulation conditions, see @@ -185,15 +183,15 @@ def create_parameterized_edatas( will be used). To be provided as dict, mapping PEtab problem parameters to SBML IDs. :param scaled_parameters: - If True, problem_parameters are assumed to be on the scale provided - in the PEtab parameter table and will be unscaled. If False, they - are assumed to be in linear scale. + If ``True``, ``problem_parameters`` are assumed to be on the scale + provided in the PEtab parameter table and will be unscaled. + If ``False``, they are assumed to be in linear scale. :param parameter_mapping: Optional precomputed PEtab parameter mapping for efficiency, as - generated by `create_parameter_mapping`. + generated by :func:`create_parameter_mapping`. :param simulation_conditions: - Result of `petab.get_simulation_conditions`. Can be provided to save - time if this has been obtained before. + Result of :func:`petab.get_simulation_conditions`. Can be provided to + save time if this has been obtained before. :return: List with one :class:`amici.amici.ExpData` per simulation condition, @@ -242,11 +240,11 @@ def create_parameter_mapping( :param petab_problem: PEtab problem :param simulation_conditions: - Result of `petab.get_simulation_conditions`. Can be provided to save - time if this has been obtained before. + Result of :func:`petab.get_simulation_conditions`. Can be provided to + save time if this has been obtained before. :param scaled_parameters: - If True, problem_parameters are assumed to be on the scale provided - in the PEtab parameter table and will be unscaled. If False, they + If ``True``, problem_parameters are assumed to be on the scale provided + in the PEtab parameter table and will be unscaled. If ``False``, they are assumed to be in linear scale. :param amici_model: AMICI model. @@ -303,8 +301,8 @@ def create_parameter_mapping_for_condition( :param parameter_mapping_for_condition: Preliminary parameter mapping for condition. :param condition: - pandas.DataFrame row with preequilibrationConditionId and - simulationConditionId. + :class:`pandas.DataFrame` row with ``preequilibrationConditionId`` and + ``simulationConditionId``. :param petab_problem: Underlying PEtab problem. :param amici_model: @@ -493,8 +491,8 @@ def create_edatas( :param petab_problem: Underlying PEtab problem. :param simulation_conditions: - Result of `petab.get_simulation_conditions`. Can be provided to save - time if this has be obtained before. + Result of :func:`petab.get_simulation_conditions`. Can be provided to + save time if this has be obtained before. :return: List with one :class:`amici.amici.ExpData` per simulation condition, @@ -547,10 +545,10 @@ def create_edata_for_condition( Sets timepoints, observed data and sigmas. :param condition: - pandas.DataFrame row with preequilibrationConditionId and - simulationConditionId. + :class:`pandas.DataFrame` row with ``preequilibrationConditionId`` and + ``simulationConditionId``. :param measurement_df: - pandas.DataFrame with measurements for the given condition. + :class:`pandas.DataFrame` with measurements for the given condition. :param amici_model: AMICI model :param petab_problem: @@ -721,20 +719,20 @@ def rdatas_to_measurement_df( measurement_df: pd.DataFrame) -> pd.DataFrame: """ Create a measurement dataframe in the PEtab format from the passed - `rdatas` and own information. + ``rdatas`` and own information. :param rdatas: A sequence of rdatas with the ordering of - `petab.get_simulation_conditions`. + :func:`petab.get_simulation_conditions`. :param model: - AMICI model used to generate `rdatas`. + AMICI model used to generate ``rdatas``. :param measurement_df: - PEtab measurement table used to generate `rdatas`. + PEtab measurement table used to generate ``rdatas``. :return: - A dataframe built from the rdatas in the format of `measurement_df`. + A dataframe built from the rdatas in the format of ``measurement_df``. """ simulation_conditions = petab.get_simulation_conditions( measurement_df) @@ -778,10 +776,11 @@ def rdatas_to_simulation_df( rdatas: Sequence[amici.ReturnData], model: AmiciModel, measurement_df: pd.DataFrame) -> pd.DataFrame: - """Create a PEtab simulation dataframe from amici.ReturnDatas. + """Create a PEtab simulation dataframe from + :class:`amici.amici.ReturnData` s. - See ``rdatas_to_measurement_df`` for details, only that model outputs - will appear in column "simulation" instead of "measurement".""" + See :func:`rdatas_to_measurement_df` for details, only that model outputs + will appear in column ``simulation`` instead of ``measurement``.""" df = rdatas_to_measurement_df(rdatas=rdatas, model=model, measurement_df=measurement_df)