Inputs

This module contains the objects used to organise input data to RAT to be fed into the C++ module.

Converts python models to the necessary inputs for the compiled RAT code

class RATapi.inputs.FileHandles(files=None)

Class to defer creation of custom file handles.

Parameters:

files (ClassList[CustomFile]) – A list of custom file models.

get_handle(index)

Returns file handle for a given custom file.

Parameters:

index (int) – The index of the custom file.

RATapi.inputs.append_data_background(data, background)

Append background data to contrast data.

Parameters:

• data (np.array) – The contrast data to which we are appending a background.

• background (np.array) – The background data to append to the contrast.

Returns:

The contrast data with background data appended as two additional columns.

Return type:

np.array

RATapi.inputs.check_indices(problem)

Checks the indices in contrast lists in a ProblemDefinition object lie within the range of the corresponding parameter lists.

Parameters:

problem (RAT.rat_core.ProblemDefinition) – The problem input used in the compiled RAT code.

Return type:

None

RATapi.inputs.get_python_handle(file_name, function_name, path='')

Get the function handle from a function defined in a python module located anywhere within the filesystem.

Parameters:

• file_name (str) – The name of the file containing the function of interest.

• function_name (str) – The name of the function we wish to obtain the handle for within the module.

• path (str) – The path to the file containing the function (default is “”, which represent the working directory).

Returns:

handle – The handle of the function defined in the python module file.

Return type:

Callable

RATapi.inputs.make_controls(input_controls)

Converts the controls object to the format required by the compiled RAT code.

Parameters:

• input_controls (RAT.Controls) – The controls model, which defines algorithmic properties.

• checks (Rat.rat_core.Checks) – States whether or not to fit each parameter defined in the project.

Returns:

controls – The controls object used in the compiled RAT code.

Return type:

RAT.rat_core.Control

RATapi.inputs.make_data_present(project)

Constructs the “dataPresent” field of the problem input required for the compiled RAT code.

Parameters:

project (RAT.Project) – The project model, which defines the physical system under study.

Returns:

The “dataPresent” field of the problem input used in the compiled RAT code.

Return type:

list[int]

RATapi.inputs.make_input(project, controls)

Constructs the inputs required for the compiled RAT code using the data defined in the input project and controls.

Parameters:

• project (RAT.Project) – The project model, which defines the physical system under study.

• controls (RAT.Controls) – The controls model, which defines algorithmic properties.

Returns:

• problem (RAT.rat_core.ProblemDefinition) – The problem input used in the compiled RAT code.

• limits (RAT.rat_core.Limits) – A list of min/max values for each parameter defined in the project.

• priors (RAT.rat_core.Priors) – The priors defined for each parameter in the project.

• cpp_controls (RAT.rat_core.Control) – The controls object used in the compiled RAT code.

Return type:

tuple[ProblemDefinition, Limits, Priors, Control]

RATapi.inputs.make_problem(project, checks)

Constructs the problem input required for the compiled RAT code.

Parameters:

• project (RAT.Project) – The project model, which defines the physical system under study.

• checks (Checks)

Returns:

problem – The problem input used in the compiled RAT code.

Return type:

RAT.rat_core.ProblemDefinition

RATapi.inputs.make_resample(project)

Constructs the “resample” field of the problem input required for the compiled RAT code.

Parameters:

project (RAT.Project) – The project model, which defines the physical system under study.

Returns:

The “resample” field of the problem input used in the compiled RAT code.

Return type:

list[int]