diff options
| -rw-r--r-- | python/src/sa/default_scorer.pxi | 74 |
1 files changed, 0 insertions, 74 deletions
diff --git a/python/src/sa/default_scorer.pxi b/python/src/sa/default_scorer.pxi deleted file mode 100644 index 483f4743..00000000 --- a/python/src/sa/default_scorer.pxi +++ /dev/null @@ -1,74 +0,0 @@ -from libc.stdlib cimport malloc, realloc, free -from libc.math cimport log10 - -MAXSCORE = -99 -EgivenFCoherent = 0 -SampleCountF = 1 -CountEF = 2 -MaxLexFgivenE = 3 -MaxLexEgivenF = 4 -IsSingletonF = 5 -IsSingletonFE = 6 -NFEATURES = 7 - -cdef class DefaultScorer(Scorer): - cdef BiLex ttable - cdef int* fid - - def __dealloc__(self): - free(self.fid) - - def __init__(self, BiLex ttable): - self.ttable = ttable - self.fid = <int*> malloc(NFEATURES*sizeof(int)) - cdef unsigned i - for i, fnames in enumerate(('EgivenFCoherent', 'SampleCountF', 'CountEF', - 'MaxLexFgivenE', 'MaxLexEgivenF', 'IsSingletonF', 'IsSingletonFE')): - self.fid[i] = FD.index(fnames) - - cdef FeatureVector score(self, Phrase fphrase, Phrase ephrase, - unsigned paircount, unsigned fcount, unsigned fsample_count): - cdef FeatureVector scores = FeatureVector() - - # EgivenFCoherent - cdef float efc = <float>paircount/fsample_count - scores.set(self.fid[EgivenFCoherent], -log10(efc) if efc > 0 else MAXSCORE) - - # SampleCountF - scores.set(self.fid[SampleCountF], log10(1 + fsample_count)) - - # CountEF - scores.set(self.fid[CountEF], log10(1 + paircount)) - - # MaxLexFgivenE TODO typify - ewords = ephrase.words - ewords.append('NULL') - cdef float mlfe = 0, max_score = -1 - for f in fphrase.words: - for e in ewords: - score = self.ttable.get_score(f, e, 1) - if score > max_score: - max_score = score - mlfe += -log10(max_score) if max_score > 0 else MAXSCORE - scores.set(self.fid[MaxLexFgivenE], mlfe) - - # MaxLexEgivenF TODO same - fwords = fphrase.words - fwords.append('NULL') - cdef float mlef = 0 - max_score = -1 - for e in ephrase.words: - for f in fwords: - score = self.ttable.get_score(f, e, 0) - if score > max_score: - max_score = score - mlef += -log10(max_score) if max_score > 0 else MAXSCORE - scores.set(self.fid[MaxLexEgivenF], mlef) - - # IsSingletonF - scores.set(self.fid[IsSingletonF], (fcount == 1)) - - # IsSingletonFE - scores.set(self.fid[IsSingletonFE], (paircount == 1)) - - return scores |