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