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"""Index for fast matching of token sets.""" |
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3
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import collections |
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5
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6
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class TokenSet: |
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"""Represents a set of tokens (expressed as integer token IDs) that can |
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be matched with another set of tokens. A TokenSet can optionally |
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9
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be associated with a subject from the vocabulary.""" |
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def __init__(self, tokens, subject_id=None, is_pref=False): |
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self._tokens = set(tokens) |
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self.subject_id = subject_id |
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self.is_pref = is_pref |
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def __len__(self): |
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return len(self._tokens) |
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def __iter__(self): |
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return iter(self._tokens) |
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def contains(self, other): |
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"""Returns True iff the tokens in the other TokenSet are all |
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included within this TokenSet.""" |
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return other._tokens.issubset(self._tokens) |
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def sample(self): |
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"""Return an arbitrary token from this TokenSet, or None if empty""" |
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try: |
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return next(iter(self._tokens)) |
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except StopIteration: |
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return None |
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class TokenSetIndex: |
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"""A searchable index of TokenSets (representing vocabulary terms)""" |
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def __init__(self): |
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self._index = collections.defaultdict(set) |
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def __len__(self): |
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return len(self._index) |
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def add(self, tset): |
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"""Add a TokenSet into this index""" |
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token = tset.sample() |
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if token is not None: |
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self._index[token].add(tset) |
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def search(self, tset): |
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"""Return the TokenSets that are contained in the given TokenSet. |
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The matches are returned as a list of (TokenSet, ambiguity) pairs |
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where ambiguity is an integer indicating the number of other TokenSets |
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that also match the same tokens.""" |
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subj_tsets = {} |
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subj_ambiguity = collections.Counter() |
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for token in tset: |
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for ts in self._index[token]: |
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if not tset.contains(ts): |
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continue |
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if ts.subject_id not in subj_tsets or \ |
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not subj_tsets[ts.subject_id].is_pref: |
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subj_tsets[ts.subject_id] = ts |
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for ts in subj_tsets.values(): |
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for other in subj_tsets.values(): |
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if ts == other: |
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continue |
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if other.contains(ts): |
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subj_ambiguity.update([ts.subject_id]) |
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return [(ts, subj_ambiguity[ts.subject_id]) |
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for uri, ts in subj_tsets.items()] |
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NatLibFi /
Annif
