fiddy.extensions.amici package

Submodules

fiddy.extensions.amici.amici module

fiddy.extensions.amici.amici.fiddy_array_transpose(array: ndarray, variable: str) → Tuple[int]
fiddy.extensions.amici.amici.flatten(arrays: Dict[str, ndarray[Any, dtype[float64]]]) → ndarray[Any, dtype[float64]]
fiddy.extensions.amici.amici.rdata_array_transpose(array: ndarray, variable: str) → Tuple[int]
fiddy.extensions.amici.amici.rdata_to_array(rdata: <MagicMock name='mock.AmiciReturnData' id='140508573588624'>)

Convert AMICI return data to fiddy output.

Parameters:

rdata – The AMICI return data.

Returns:

The converted return data.

fiddy.extensions.amici.amici.reshape(array: ndarray[Any, dtype[float64]], structure: Tuple[int, int, Tuple[int, ...]], sensitivities: bool = False) → Dict[str, ndarray[Any, dtype[float64]]]
fiddy.extensions.amici.amici.run_amici_simulation_to_cached_functions(amici_model: <MagicMock name='mock.AmiciModel' id='140508573588432'>, *args, cache: bool = True, output_keys: ~typing.List[str] = None, parameter_ids: ~typing.List[str] = None, amici_solver: <MagicMock name='mock.AmiciSolver' id='140508573588240'> = None, amici_edata: <MagicMock name='mock.AmiciExpData' id='140508573636880'> = None, derivative_variables: ~typing.List[str] = None, **kwargs)

Convert amici.runAmiciSimulation to fiddy functions.

Parameters:

  • derivative_variables – The variables that derivatives will be computed or approximated for. See the keys of all_rdata_derivatives for options.

  • parameter_ids – The IDs that correspond to the values in the parameter vector that is simulated.

  • Returns – function, derivatives and structure

fiddy.extensions.amici.amici.simulate_petab_to_cached_functions(petab_problem: ~petab.problem.Problem, amici_model: <MagicMock name='mock.Model' id='140508573642320'>, parameter_ids: ~typing.List[str] = None, cache: bool = True, precreate_edatas: bool = True, precreate_parameter_mapping: bool = True, simulate_petab: ~typing.Callable[[~typing.Any], str] = None, **kwargs) → Tuple[Callable[[ndarray[Any, dtype[float64]]], ndarray[Any, dtype[float64]]], Callable[[ndarray[Any, dtype[float64]]], ndarray[Any, dtype[float64]]]]

Convert amici.petab_objective.simulate_petab to fiddy functions.

Note that all gradients are provided on linear scale. The correction from ‘log10’ scale is automatically done.

Parameters:

  • simulate_petab – A method to simulate PEtab problems with AMICI, e.g. amici.petab_objective.simulate_petab.

  • parameter_ids – The IDs of the parameters, in the order that parameter values will be supplied. Defaults to petab_problem.parameter_df.index.

  • petab_problem – The PEtab problem.

  • cache – Whether to cache the function call.

  • precreate_edatas – Whether to create the AMICI measurements object in advance, to save time.

  • precreate_parameter_mapping – Whether to create the AMICI parameter mapping object in advance, to save time.

  • **kwargs – Passed to simulate_petab.

Returns:

tuple

1: A method to compute the function at a point. 2: A method to compute the gradient at a point.

fiddy.extensions.amici.amici.transform_gradient_lin_to_lin(gradient_value, parameter_value)
fiddy.extensions.amici.amici.transform_gradient_lin_to_log(gradient_value, parameter_value)
fiddy.extensions.amici.amici.transform_gradient_lin_to_log10(gradient_value, parameter_value)

Module contents