agentlib_flexquant.utils package

Submodules

agentlib_flexquant.utils.config_management module

agentlib_flexquant.utils.config_management.get_class_from_file(file_path: str, class_name: str) → ABCMeta

agentlib_flexquant.utils.config_management.get_flex_mpc_module_config(agent_config: AgentConfig, module_config: BaseModuleConfig, module_type: str)

Get a flexquant module config from an original agentlib module config.

agentlib_flexquant.utils.config_management.get_module(config: AgentConfig, module_type: str) → T

Extracts a module from a config based on its name.

agentlib_flexquant.utils.config_management.get_module_type_matching_dict(dictionary: dict) -> (<class 'dict'>, <class 'dict'>)

Create two dictionaries, which map the modules types of the agentlib_mpc modules to those of the flexquant modules.

This is done by using the MODULE_NAME_DICT.

agentlib_flexquant.utils.config_management.get_orig_module_type(config: AgentConfig) → str

Return the config type of the original MPC.

agentlib_flexquant.utils.config_management.to_dict_and_remove_unnecessary_fields(module: BaseModuleConfig) → dict

Remove unnecessary fields from the module to keep the created json simple.

agentlib_flexquant.utils.data_handling module

agentlib_flexquant.utils.data_handling.convert_timescale_of_index(df: DataFrame, from_unit: Literal['seconds', 'minutes', 'hours', 'days'], to_unit: {'seconds': 1, 'minutes': 60, 'hours': 3600, 'days': 86400}) → DataFrame

Convert the timescale of a dataframe index (from seconds) to the given time unit.

Parameters:

• from_unit – the time unit of the original index

• to_unit – the time unit to convert the index to

Returns:

A DataFrame with the converted index

agentlib_flexquant.utils.data_handling.fill_nans(series: Series, method: Literal['mean', 'interpolate']) → Series

Fill NaN values in the series with the given method.

Parameters:

• series – the series to be filled

• method – the method to be applied, there are two predefined - mean: fill NaN values with the mean of the following values. - interpolate: interpolate missing values.

Returns:

A pd.Series with nan filled.

agentlib_flexquant.utils.data_handling.strip_multi_index(series: Series) → Series

agentlib_flexquant.utils.interactive module

class agentlib_flexquant.utils.interactive.CustomBound(for_variable: str, lb_name: str | None = None, ub_name: str | None = None)

Bases: object

Dataclass to let the user define custom bounds for the mpc variables.

for_variable – The name of the variable to plot the bounds into lower bound – The lower bound of the variable as the name of the lower bound variable in the MPC upper bound – The upper bound of the variable as the name of the upper bound variable in the MPC

for_variable: str

lower_bound: str | None

upper_bound: str | None

class agentlib_flexquant.utils.interactive.Dashboard(flex_config: str | Path | FlexQuantConfig | None = None, simulator_agent_config: str | Path | AgentConfig | None = None, generated_flex_files_base_path: str | Path | None = None, results: str | Path | dict[str, dict[str, pandas.DataFrame]] = None, to_timescale: Literal['seconds', 'minutes', 'hours', 'days'] = 'hours', port: int = None)

Bases: Results

Class for the dashboard of flexquant

MPC_ITERATIONS: str = 'stats_iter_count'

bounds_key: str = 'bounds'

characteristic_times_accepted_key: str = 'characteristic_times_accepted'

characteristic_times_current_key: str = 'characteristic_times_current'

create_app(custom_bounds: CustomBound | list[agentlib_flexquant.utils.interactive.CustomBound] = None) → Dash

Create and return the Dash app without running it.

This method sets up the entire app layout and callbacks but doesn’t block by calling app.run(). This is useful for testing.

Parameters:

custom_bounds – optional arguments to show the comfort bounds

Returns:

The configured Dash application instance.

custom_bounds: list[agentlib_flexquant.utils.interactive.CustomBound] = []

label_negative: str = 'negative'

label_positive: str = 'positive'

show(custom_bounds: CustomBound | list[agentlib_flexquant.utils.interactive.CustomBound] = None)

Show the dashboard in a web browser containing:

– Statistics of the MPCs solver – The states, controls, and the power variable of the MPCs and the simulator – KPIs of the flexibility quantification – Markings of the characteristic flexibility times

Parameters:

custom_bounds – optional arguments to show the comfort bounds

agentlib_flexquant.utils.parsing module

class agentlib_flexquant.utils.parsing.SetupSystemModifier(mpc_data: BaselineMPCData | NFMPCData | PFMPCData, controls: list[agentlib_mpc.data_structures.mpc_datamodels.MPCVariable], binary_controls: list[agentlib_mpc.data_structures.mpc_datamodels.MPCVariable] | None)

Bases: NodeTransformer

A custom AST transformer for modifying the MPC model file.

This class traverses the AST of the input file, identifies the relevant classes and methods, and performs the necessary modifications.

get_leftmost_list(node: Tuple | BinOp | List) → List | None

Recursively traverse binary operations to get the leftmost list.

Parameters:

node – An AST node (could be a BinOp or directly a List)

Returns:

The leftmost List node found

modify_config_class_baseline(node: ClassDef)

Modify the config class of the baseline mpc.

Parameters:

node – The class definition node of the config.

modify_config_class_shadow(node: ClassDef)

Modify the config class of the shadow mpc.

Parameters:

node – The class definition node of the config.

modify_setup_system_baseline(node: FunctionDef)

Modify the setup_system method of the baseline mpc model class.

This method changes the return statement of the setup_system method and adds all necessary new lines of code.

Parameters:

node – The function definition node of setup_system.

modify_setup_system_shadow(node: FunctionDef)

Modify the setup_system method of the shadow mpc model class.

This method changes the return statement of the setup_system method and adds all necessary new lines of code.

Parameters:

node – The function definition node of setup_system.

visit_ClassDef(node: ClassDef) → ClassDef

Visit a class definition in the AST.

This method is called for each class definition in the AST. It identifies the BaselineMPCModelConfig and BaselineMPCModel classes and performs the necessary actions.

Parameters:

node – The class definition node in the AST.

Returns:

The possibly modified class definition node.

visit_Module(module: Module) → Module

Visit a module definition in the AST.

Append or delete the import statements at the top of the module.

Parameters:

module – The module definition node in the AST.

Returns:

The possibly modified module definition node.

agentlib_flexquant.utils.parsing.add_import_to_tree(name: str, alias: str, tree: Module) → Module

Add import to the module.

The statement ‘import name as alias’ will be added.

Parameters:

• name – name of the module to be imported

• alias – alias of the module

• tree – the tree to be imported

Returns:

The tree updated with the import statement

agentlib_flexquant.utils.parsing.add_input(name: str, value: bool | str | int, unit: str, description: str, type: str) → expr

Create an AST node for an input definition.

Parameters:

• name – The name of the input.

• value – The default value for the input. Can be a boolean, string, or integer.

• unit – The unit associated with the input value.

• description – A human-readable description of the input.

• type – The data type of the input (e.g., “float”, “int”, “string”).

Returns:

An abstract syntax tree (AST) call node representing the input definition.

Return type:

ast.Call

agentlib_flexquant.utils.parsing.add_output(name: str, unit: str, type: str, value: str | float, description: str) → expr

Create an AST node for an output definition.

Parameters:

• name – The name of the output.

• unit – The unit associated with the output value.

• type – The data type of the output (e.g., “float”, “string”).

• value – The value of the output. Can be a string or float.

• description – A human-readable description of the output.

Returns:

An abstract syntax tree (AST) call node representing the output definition.

Return type:

ast.expr

agentlib_flexquant.utils.parsing.add_parameter(name: str, value: int | float, unit: str, description: str) → expr

Create an AST node for a parameter definition.

Parameters:

• name – The name of the parameter.

• value – The value of the parameter. Can be an integer or float.

• unit – The unit associated with the parameter value.

• description – A human-readable description of the parameter.

Returns:

An abstract syntax tree (AST) call node representing the parameter definition.

Return type:

ast.expr

agentlib_flexquant.utils.parsing.create_ast_element(template_string: str) → expr

Convert a template string into an AST call node.

Parameters:

template_string – A Python code template string to parse.

Returns:

An abstract syntax tree (AST) expr node parsed from the template string.

Return type:

ast.Expr

agentlib_flexquant.utils.parsing.remove_all_imports_from_tree(tree: Module) → Module