VectorOpsMixin#

class scikitplot.annoy.VectorOpsMixin[source]#

High-level vector operations for Annoy-like objects.

A class mixing this in MUST provide: - get_nns_by_item(item: int, n: int, *, search_k: int = -1,

include_distances: bool = False)

  • get_nns_by_vector(vector: Sequence[float], n: int, *, search_k: int = -1,

    include_distances: bool = False)

  • get_item_vector(item: int) -> Sequence[float]

This mixin does not assume any extra C-API features.

get_neighbor_ids_by_item(item, n, *, search_k=-1, include_self=False, include_distances=False)[source]#
Parameters:
Return type:

List[int] | Tuple[List[int], List[float]]

get_neighbor_ids_by_vector(vector, n, *, search_k=-1, include_distances=False, include_self=False, exclude_item=None, exclude_item_ids=None)[source]#
Parameters:
Return type:

List[int] | Tuple[List[int], List[float]]

get_neighbor_vectors_by_item(item, n, *, search_k=-1, include_self=False, include_distances=False, as_numpy=False, dtype='float32')[source]#
Parameters:
Return type:

List[Sequence[float]] | ndarray | Tuple[List[Sequence[float]] | ndarray, List[float]]

get_neighbor_vectors_by_vector(vector, n, *, search_k=-1, include_distances=False, include_self=False, exclude_item=None, exclude_item_ids=None, as_numpy=False, dtype='float32')[source]#
Parameters:
Return type:

List[Sequence[float]] | ndarray | Tuple[List[Sequence[float]] | ndarray, List[float]]

iter_neighbor_vectors_by_item(item, n, *, search_k=-1, include_self=False)[source]#
Parameters:
iter_neighbor_vectors_by_vector(vector, n, *, search_k=-1, include_self=False, exclude_item=None, exclude_item_ids=None)[source]#
Parameters: