+ hQ&RtRtRtRtRRltR#)z# Tools for comparing ranked lists. c#"\V4p\V4pVFpW V,W,, 3xK R# \dK1i;i5i)zFinds the difference between the values in ranks1 and ranks2 for keys present in both dicts. If the arguments are not dicts, they are converted from (key, rank) sequences. N)dictKeyError)ranks1ranks2ks&& 7/usr/lib/python3/dist-packages/nltk/metrics/spearman.py _rank_distsr sO &\F &\F  AY** *   s%A>A A  A A  Ac^p^p\W4FwrEW5V,, pV^, pK ^^V,W"V,^, ,, , # \dR#i;i)aEReturns the Spearman correlation coefficient for two rankings, which should be dicts or sequences of (key, rank). The coefficient ranges from -1.0 (ranks are opposite) to 1.0 (ranks are identical), and is only calculated for keys in both rankings (for meaningful results, remove keys present in only one list before ranking).g)r ZeroDivisionError)rrnresrds&& rspearman_correlationrsh A CF+ 1u  Q,AGqEAI/00 s*A A,+A,c&R\V44#)z|Given a sequence, yields each element with an increasing rank, suitable for use as an argument to ``spearman_correlation``. c3,"TF wrW!3xK R#5i)N).0irs& r &ranks_from_sequence..1s .~tqQF~s) enumerate)seqs&rranks_from_sequencer-s /y~ ..c#"Rp^p\V4F(wpwrV\Wb, 4V8dTpYS3xTpK* R# \dLi;i5i)zGiven a sequence of (key, score) tuples, yields each key with an increasing rank, tying with previous key's rank if the difference between their scores is less than rank_gap. Suitable for use as an argument to ``spearman_correlation``. N)rabs TypeError)scoresrank_gap prev_scorerankrkeyscores&& rranks_from_scoresr$4sa J D$V,r&s $/r