AnchorSelection

class AnchorSelection(num_anchors=32)[source]

Anchor entity selection strategy.

Initialize the strategy.

Parameters: num_anchors (int) – the number of anchor nodes to select. # TODO: allow relative

Methods Summary

`__call__`(edge_index[, known_anchors])	Select anchor nodes.
`filter_unique`(anchor_ranking, known_anchors)	Filter out already known anchors, and select from remaining ones afterwards.
`iter_extra_repr`()	Extra components for __repr__.

Methods Documentation

abstract __call__(edge_index, known_anchors=None)[source]

Select anchor nodes.

Note

the number of selected anchors may be smaller than \(k\), if there are less entities present in the edge index.

Parameters

edge_index (ndarray) – shape: (m, 2) the edge_index, i.e., adjacency list.
known_anchors (Optional[ndarray]) – numpy.ndarray an array of already known anchors for getting only unique anchors

Return type

ndarray

Returns

(k,) the selected entity ids

filter_unique(anchor_ranking, known_anchors)[source]

Filter out already known anchors, and select from remaining ones afterwards.

Note

the output size may be smaller, if there are not enough candidates remaining.

Parameters

anchor_ranking (ndarray) – shape: (n,) the anchor node IDs sorted by preference, where the first one is the most preferrable.
known_anchors (Optional[ndarray]) – shape: (m,) a collection of already known anchors

Return type

ndarray

Returns

shape: (m + num_anchors,) the extended anchors, i.e., the known ones and num_anchors novel ones.

iter_extra_repr()[source]

Extra components for __repr__.