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#!/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)
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