API Reference: EmbeddingState

class moddr.embedding_state.EmbeddingState(embedding: dict[int, ndarray[tuple[int, ...], dtype[float32]]], graph: Graph | None = None, title: str | None = None, obj_id: float | None = None, partition: dict[int, list[int]] | None = None, community_centers: dict[int, ndarray[tuple[int, ...], dtype[float32]]] | None = None, labels: dict[int, float] | None = None)[source]

Bases: object

EmbeddingState is a data class representing the state of an embedding, including its associated graph, metadata, metrics, and partitioning information.

obj_id

(Unique) identifier for the embedding object.

Type:

float

graph

Graph structure associated with the embedding.

Type:

nx.Graph

embedding

Dictionary mapping node indices to their embedding vectors.

Type:

dict[int, npt.NDArray[np.float32]]

metadata

Dictionary containing metadata about dimensionality reduction, community detection, and layout methods.

Type:

MetaDataDict

metrics

Dictionary containing various evaluation metrics for the embedding.

Type:

MetricsDict

title

Title or description of the embedding object.

Type:

str

partition

Dictionary mapping community indices to lists of node indices.

Type:

dict[int, list[int]]

community_centers

Dictionary mapping community indices to their center vectors.

Type:

dict[int, npt.NDArray[np.float32]]

labels

Dictionary mapping node indices to label values. Can be used e.g. for coloring or categorization.

Type:

dict[int, float]

__init__(embedding, graph=None, title=None, obj_id=None, com_partition=None, community_centers=None, labels=None)[source]

Initializes an EmbeddingState instance with the provided embedding, graph, title, object ID, partitioning, community centers, and labels. If any argument is None, a default value is assigned.

__str__()[source]

Returns a formatted string representation of the EmbeddingState, including object ID, title, embedding shape, graph statistics, metadata, and metrics.