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authorChris Dyer <cdyer@cs.cmu.edu>2012-07-27 17:31:00 -0400
committerChris Dyer <cdyer@cs.cmu.edu>2012-07-27 17:31:00 -0400
commitb317e0efd2398d75d70e027bb1e2cf442e683981 (patch)
treeec34aff0ce4e8fb9704d1cd2b7abf00cb9a25b9a /sa-extract/context_model.py
parentb2a8bccb2bd713d9ec081cf3dad0162c2cb492d8 (diff)
remove old suffix array extractor (use the one in python/ instead)
Diffstat (limited to 'sa-extract/context_model.py')
-rw-r--r--sa-extract/context_model.py234
1 files changed, 0 insertions, 234 deletions
diff --git a/sa-extract/context_model.py b/sa-extract/context_model.py
deleted file mode 100644
index 8cb6c174..00000000
--- a/sa-extract/context_model.py
+++ /dev/null
@@ -1,234 +0,0 @@
-#!/usr/bin/env python
-import sys
-import model
-import sym
-import log
-import math
-
-class ContextModel(model.Model):
- '''A ContextModel is one that is computed using information
- from the Context object'''
-
- def __init__(self, context_manager, default=0.0):
- model.Model.__init__(self)
- self.wordless = 0
- self.initial = None
- self.default = default
- self.context_manager = context_manager
- self.id = self.context_manager.add_model(self)
-
- '''The next feature is true if the model depends in
- some way on the entire input sentence; that is, if
- it cannot be scored when created, but must be scored
- no earlier than during the input method (note that
- this is less strict than stateful)'''
- self.contextual = True
- ''' It may seem somewhat counterintuitive that a
- ContextModel can be non-contextual, but a good
- example is the rule probabilites; although these
- are computed using the Context object, they don't
- really depend in any way on context'''
-
-
- '''inherited from model.Model, called once for each input sentence'''
- def input(self, fwords, meta):
- # all ContextModels must make this call
- self.context_manager.input(self, fwords, meta)
-
-
- '''This function will be called via the input method
- only for contextual models'''
- def compute_contextual_score(self, r):
- return 0.0
-
- '''This function is only called on rule creation for
- contextless models'''
- def compute_contextless_score(self, fphrase, ephrase, paircount, fcount, fsample_count):
- return 0.0
-
- '''Stateless models should not need to
- override this function, unless they define
- something for model.TO_GOAL'''
- def transition (self, r, antstates, i, j, j1=None):
- return (None, 0.0)
-
- def estimate(self, r):
- return r.getscore("context", self.id)
-
- def transition(self, r, antstates, i, j, j1=None):
- return (None, r.getscore("context", self.id))
-
- def finaltransition(self, state):
- return 0.0
-
- def rescore(self, ewords, score):
- return score
-
-
-
-'''p(e|f)'''
-class EgivenF(ContextModel):
-
- def __init__(self, context_manager, default=0.0):
- ContextModel.__init__(self, context_manager)
- self.contextual = False
-
- def compute_contextless_score(self, fphrase, ephrase, paircount, fcount, fsample_count):
- prob = float(paircount)/float(fcount)
- return -math.log10(prob)
-
-class CountEF(ContextModel):
-
- def __init__(self, context_manager, default=0.0):
- ContextModel.__init__(self, context_manager)
- self.contextual = False
-
- def compute_contextless_score(self, fphrase, ephrase, paircount, fcount, fsample_count):
- return math.log10(1.0 + float(paircount))
-
-class SampleCountF(ContextModel):
-
- def __init__(self, context_manager, default=0.0):
- ContextModel.__init__(self, context_manager)
- self.contextual = False
-
- def compute_contextless_score(self, fphrase, ephrase, paircount, fcount, fsample_count):
- return math.log10(1.0 + float(fsample_count))
-
-
-
-class EgivenFCoherent(ContextModel):
-
- def __init__(self, context_manager, default=0.0):
- ContextModel.__init__(self, context_manager)
- self.contextual = False
-
- def compute_contextless_score(self, fphrase, ephrase, paircount, fcount, fsample_count):
- prob = float(paircount)/float(fsample_count)
- #print "paircount=",paircount," , fsample_count=",fsample_count,", prob=",prob
- if (prob == 0.0): return 99.0
- return -math.log10(prob)
-
-
-
-class CoherenceProb(ContextModel):
-
- def __init__(self, context_manager, default=0.0):
- ContextModel.__init__(self, context_manager)
- self.contextual = False
-
- def compute_contextless_score(self, fphrase, ephrase, paircount, fcount, fsample_count):
- prob = float(fcount)/float(fsample_count)
- return -math.log10(prob)
-
-
-
-class MaxLexEgivenF(ContextModel):
-
- def __init__(self, context_manager, ttable, col=0):
- ContextModel.__init__(self, context_manager)
- self.ttable = ttable
- self.col = col
- self.wordless = 0
- self.initial = None
- self.contextual = False
-
-
- def compute_contextless_score(self, fphrase, ephrase, paircount, fcount, fsample_count):
- totalscore = 1.0
- fwords = map(sym.tostring, filter(lambda x: not sym.isvar(x), fphrase))
- fwords.append("NULL")
- ewords = map(sym.tostring, filter(lambda x: not sym.isvar(x), ephrase))
- for e in ewords:
- maxScore = 0.0
- for f in fwords:
- score = self.ttable.get_score(f, e, self.col)
- #print "score(MaxLexEgivenF) = ",score
- if score > maxScore:
- maxScore = score
- totalscore *= maxScore
- if totalscore == 0.0:
- return 999
- else:
- return -math.log10(totalscore)
-
-
-class MaxLexFgivenE(ContextModel):
-
- def __init__(self, context_manager, ttable, col=1):
- ContextModel.__init__(self, context_manager)
- self.ttable = ttable
- self.col = col
- self.wordless = 0
- self.initial = None
- self.contextual = False
-
-
- def compute_contextless_score(self, fphrase, ephrase, paircount, fcount, fsample_count):
- totalscore = 1.0
- fwords = map(sym.tostring, filter(lambda x: not sym.isvar(x), fphrase))
- ewords = map(sym.tostring, filter(lambda x: not sym.isvar(x), ephrase))
- ewords.append("NULL")
- for f in fwords:
- maxScore = 0.0
- for e in ewords:
- score = self.ttable.get_score(f, e, self.col)
- #print "score(MaxLexFgivenE) = ",score
- if score > maxScore:
- maxScore = score
- totalscore *= maxScore
- if totalscore == 0.0:
- return 999
- else:
- return -math.log10(totalscore)
-
-
-class IsSingletonF(ContextModel):
-
- def __init__(self, context_manager, default=0.0):
- ContextModel.__init__(self, context_manager)
- self.contextual = False
-
- def compute_contextless_score(self, fphrase, ephrase, paircount, fcount, fsample_count):
- return (fcount==1)
-
-
-class IsSingletonFE(ContextModel):
-
- def __init__(self, context_manager, default=0.0):
- ContextModel.__init__(self, context_manager)
- self.contextual = False
-
- def compute_contextless_score(self, fphrase, ephrase, paircount, fcount, fsample_count):
- return (paircount==1)
-
-class IsNotSingletonF(ContextModel):
-
- def __init__(self, context_manager, default=0.0):
- ContextModel.__init__(self, context_manager)
- self.contextual = False
-
- def compute_contextless_score(self, fphrase, ephrase, paircount, fcount, fsample_count):
- return (fcount>1)
-
-
-class IsNotSingletonFE(ContextModel):
-
- def __init__(self, context_manager, default=0.0):
- ContextModel.__init__(self, context_manager)
- self.contextual = False
-
- def compute_contextless_score(self, fphrase, ephrase, paircount, fcount, fsample_count):
- return (paircount>1)
-
-
-class IsFEGreaterThanZero(ContextModel):
-
- def __init__(self, context_manager, default=0.0):
- ContextModel.__init__(self, context_manager)
- self.contextual = False
-
- def compute_contextless_score(self, fphrase, ephrase, paircount, fcount, fsample_count):
- return (paircount > 0.01)
-
-