macro_eeg_model.config.nodes_processor

macro_eeg_model.config.nodes_processor#

Classes#

NodesProcessor

A class to process given brain regions into their corresponding indices in

Module Contents#

class macro_eeg_model.config.nodes_processor.NodesProcessor(given_nodes, relay_station)[source]#

A class to process given brain regions into their corresponding indices in the Julich brain parcellation by finding the final generation children of the given nodes.

given_nodes#

List of nodes to be processed.

Type:

list

relay_station#

The relay station node, if any, that connects different brain regions.

Type:

str

_areas_dict#

A dictionary mapping brain areas to their hierarchical structure using src.data_prep.areas_terminology_parser.AreasTerminologyParser.parse_into_dict().

Type:

dict

__init__(given_nodes, relay_station)[source]#

Initializes the NodesProcessor with the provided nodes, relay station, and whether to separate left and right brain nodes.

Parameters:

  • given_nodes (list) – List of nodes to be processed.

  • relay_station (str) – The relay station node, if any.

get_nodes_indices()[source]#

Processes the nodes and the relay station, if any, and retrieves their corresponding indices using _process_nodes().

Returns:

A tuple containing relay nodes, relay nodes indices, interaction nodes, and interaction nodes indices.

Return type:

tuple

_process_nodes(nodes)[source]#

Processes a list of nodes and retrieves their corresponding indices using _get_nodes_and_indices().

Parameters:

nodes (list) – List of nodes to be processed.

Returns:

A tuple containing the processed nodes and their indices.

Return type:

tuple

_get_nodes_and_indices(node)[source]#

Retrieves the final generation nodes and their corresponding indices for a given brain region (node). Uses _initialize_nodes_and_indices() to set up initial structures, _find_final_generation_children() to locate the final generation nodes, and _populate_nodes_indices() to assign indices based on the Julich brain parcellation.

Parameters:

node (str) – The name of the brain region (node) to retrieve indices for.

Returns:

A tuple containing:

  • nodes: list of nodes corresponding to the brain region.

  • nodes_indices: dictionary mapping each node to its corresponding indices.

Return type:

tuple

_initialize_nodes_and_indices(node)[source]#

Initializes the nodes and their corresponding indices, considering left and right brain separation.

Parameters:

node (str) – The node to initialize.

Returns:

A tuple containing the initialized nodes and their indices.

Return type:

tuple

_find_final_generation_children(dictionary, target, found=False)[source]#

Recursively finds the final generation children of a target node in the areas dictionary.

Parameters:

  • dictionary (dict) – The dictionary containing hierarchical brain area mappings (initially _areas_dict).

  • target (str) – The target node to find children for.

  • found (bool, optional) – Whether the target node has been found (default is False).

Returns:

A list of final generation children nodes.

Return type:

list

_populate_nodes_indices(nodes_indices, children, node)[source]#

Populates the nodes indices with the corresponding Julich labels.

Parameters:

  • nodes_indices (dict) – The dictionary to populate with node indices.

  • children (list) – The list of child nodes to process.

  • node (str) – The original node being processed.

Returns:

The populated nodes indices.

Return type:

dict

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