Function global_cluster_embeddings

_cluster_utils.py:179–190

(
    embeddings: np.ndarray,
    dim: int,
    n_neighbors: int = 15,
    metric: str = "cosine",
)

    return list_data

def global_cluster_embeddings(
    embeddings: np.ndarray,
    dim: int,
    n_neighbors: int = 15,
    metric: str = "cosine",
) -> np.ndarray:
    if n_neighbors is None:
        n_neighbors = int((len(embeddings) - 1) ** 0.5)
    reduced_embeddings = umap.UMAP(
        n_neighbors=n_neighbors, n_components=dim, metric=metric
    ).fit_transform(embeddings)
    return reduced_embeddings


def local_cluster_embeddings(