diff options
author | Patrick Simianer <simianer@cl.uni-heidelberg.de> | 2012-08-01 17:32:37 +0200 |
---|---|---|
committer | Patrick Simianer <simianer@cl.uni-heidelberg.de> | 2012-08-01 17:32:37 +0200 |
commit | 3f8e33cfe481a09c121a410e66a6074b5d05683e (patch) | |
tree | a41ecaf0bbb69fa91a581623abe89d41219c04f8 /python/cdec/scfg/features.py | |
parent | c139ce495861bb341e1b86a85ad4559f9ad53c14 (diff) | |
parent | 9fe0219562e5db25171cce8776381600ff9a5649 (diff) |
Merge remote-tracking branch 'upstream/master'
Diffstat (limited to 'python/cdec/scfg/features.py')
-rw-r--r-- | python/cdec/scfg/features.py | 62 |
1 files changed, 0 insertions, 62 deletions
diff --git a/python/cdec/scfg/features.py b/python/cdec/scfg/features.py deleted file mode 100644 index 6419cdd8..00000000 --- a/python/cdec/scfg/features.py +++ /dev/null @@ -1,62 +0,0 @@ -from __future__ import division -import math -import sym - -def contextless(feature): - feature.compute_contextless_score = feature - return feature - -MAXSCORE = 99 - -def EgivenF(fphrase, ephrase, paircount, fcount, fsample_count): # p(e|f) - return -math.log10(paircount/fcount) - -def CountEF(fphrase, ephrase, paircount, fcount, fsample_count): - return math.log10(1 + paircount) - -def SampleCountF(fphrase, ephrase, paircount, fcount, fsample_count): - return math.log10(1 + fsample_count) - -def EgivenFCoherent(fphrase, ephrase, paircount, fcount, fsample_count): - prob = paircount/fsample_count - return -math.log10(prob) if prob > 0 else MAXSCORE - -def CoherenceProb(fphrase, ephrase, paircount, fcount, fsample_count): - return -math.log10(fcount/fsample_count) - -def MaxLexEgivenF(ttable): - def feature(fphrase, ephrase, paircount, fcount, fsample_count): - fwords = [sym.tostring(w) for w in fphrase if not sym.isvar(w)] + ['NULL'] - ewords = (sym.tostring(w) for w in ephrase if not sym.isvar(w)) - def score(): - for e in ewords: - maxScore = max(ttable.get_score(f, e, 0) for f in fwords) - yield -math.log10(maxScore) if maxScore > 0 else MAXSCORE - return sum(score()) - return feature - -def MaxLexFgivenE(ttable): - def feature(fphrase, ephrase, paircount, fcount, fsample_count): - fwords = (sym.tostring(w) for w in fphrase if not sym.isvar(w)) - ewords = [sym.tostring(w) for w in ephrase if not sym.isvar(w)] + ['NULL'] - def score(): - for f in fwords: - maxScore = max(ttable.get_score(f, e, 1) for e in ewords) - yield -math.log10(maxScore) if maxScore > 0 else MAXSCORE - return sum(score()) - return feature - -def IsSingletonF(fphrase, ephrase, paircount, fcount, fsample_count): - return (fcount == 1) - -def IsSingletonFE(fphrase, ephrase, paircount, fcount, fsample_count): - return (paircount == 1) - -def IsNotSingletonF(fphrase, ephrase, paircount, fcount, fsample_count): - return (fcount > 1) - -def IsNotSingletonFE(fphrase, ephrase, paircount, fcount, fsample_count): - return (paircount > 1) - -def IsFEGreaterThanZero(fphrase, ephrase, paircount, fcount, fsample_count): - return (paircount > 0.01) |