def testRawProbabilities(self):
model = NgramsModel(2)
model.count( self.corpusfile )
probas = model.probabilities( method="raw" )
self.assertEqual(len(probas), 2)
unigram = probas[0]
for token,value,bo in unigram:
if token=="a":
self.assertEqual(value, 15)
if token=='b':
self.assertEqual(value, 10)
if token=='c':
self.assertEqual(value, 4)
if token=='d':
self.assertEqual(value, 3)
if token==START_SENT_SYMBOL:
self.assertEqual(value, 0)
if token==END_SENT_SYMBOL:
self.assertEqual(value, 3)
bigram = probas[1]
for token,value,bo in bigram:
if token=="a b":
self.assertEqual(value, 7)
if token=="b a":
self.assertEqual(value, 4)
if token==START_SENT_SYMBOL+' a':
self.assertEqual(value, 3)
if token=='b '+END_SENT_SYMBOL:
self.assertEqual(value, 3)
probas = model.probabilities( method="lograw" )
self.assertEqual(len(probas), 2)
unigram = probas[0]
for token,value,bo in unigram:
if token=="a":
self.assertEqual(value, math.log(15, 10))
if token=='b':
self.assertEqual(value, math.log(10, 10))
if token=='c':
self.assertEqual(value, math.log(4, 10))
if token=='d':
self.assertEqual(value, math.log(3, 10))
if token==START_SENT_SYMBOL:
self.assertEqual(value, -99)
if token==END_SENT_SYMBOL:
self.assertEqual(value, math.log(3, 10))
bigram = probas[1]
for token,value,bo in bigram:
if token=="a b":
self.assertEqual(value, math.log(7, 10))
if token=="b a":
self.assertEqual(value, math.log(4, 10))
if token==START_SENT_SYMBOL+' a':
self.assertEqual(value, math.log(3, 10))
if token=='b '+END_SENT_SYMBOL:
self.assertEqual(value, math.log(3, 10))
def testCount(self):
model = NgramsModel(2)
model.count( self.corpusfile )
self.assertEqual(len(model._ngramcounts), 2)
ngramcounter = model._ngramcounts[0]
self.assertEqual(ngramcounter.get_count('a'), 15)
self.assertEqual(ngramcounter.get_count('b'), 10)
self.assertEqual(ngramcounter.get_count('c'), 4)
self.assertEqual(ngramcounter.get_count('d'), 3)
self.assertEqual(ngramcounter.get_count(START_SENT_SYMBOL), 0)
self.assertEqual(ngramcounter.get_count(END_SENT_SYMBOL), 3)
ngramcounter = model._ngramcounts[1]
self.assertEqual(ngramcounter.get_count('a b'), 7)
self.assertEqual(ngramcounter.get_count('b a'), 4)
self.assertEqual(ngramcounter.get_count('d b'), 1)
self.assertEqual(ngramcounter.get_count('d c'), 2)
self.assertEqual(ngramcounter.get_count(START_SENT_SYMBOL+' a'), 3)
self.assertEqual(ngramcounter.get_count('b '+END_SENT_SYMBOL), 3)
def testARPA(self):
fn1 = os.path.join(TEMP,"model1.arpa")
fn2 = os.path.join(TEMP,"model2.arpa")
model = NgramsModel(3)
model.count( self.corpusfile )
probas = model.probabilities("logml")
arpaio = ArpaIO()
arpaio.set( probas )
arpaio.save( fn1 )
slm1 = SLM()
slm1.load_from_arpa( fn1 )
slm1.save_as_arpa( fn2 )
slm2 = SLM()
slm2.load_from_arpa( fn2 )
m1 = slm1.model
m2 = slm2.model
self.assertTrue( compare(m1,m2) )
# ----------------------------------------------------------------------------
# Main program
# ----------------------------------------------------------------------------
# ---------------------------------
# 1. Create a NgramsModel
model = NgramsModel( args.n )
if args.r:
model.set_vocab( args.r )
# ---------------------------------
# 2. Estimate counts of each n-gram
model.count( *(args.i) )
# ---------------------------------
# 3. Estimate probabilities
probas = model.probabilities( args.m )
# ---------------------------------
# 4. Write in an ARPA file
arpaio = ArpaIO()
arpaio.set( probas )
arpaio.save( args.o )
# ---------------------------------------------------------------------------
def testMaximumLikelihoodProbabilities(self):
model = NgramsModel(3)
model.count( self.corpusfile )
probas = model.probabilities( method="ml" )
self.assertEqual(len(probas), 3)
unigram = probas[0]
for token,value,bo in unigram:
if token=="a":
self.assertEqual(round(value,6), 0.428571)
if token=="b":
self.assertEqual(round(value,6), 0.285714)
if token=="c":
self.assertEqual(round(value,6), 0.114286)
if token=="d":
self.assertEqual(round(value,6), 0.085714)
if token==START_SENT_SYMBOL:
self.assertEqual(round(value,6), 0.)
if token==END_SENT_SYMBOL:
self.assertEqual(round(value,6), 0.085714)
bigram = probas[1]
for token,value,bo in bigram:
if token=="a b":
self.assertEqual(round(value,6), 0.466667)
if token=="b a":
self.assertEqual(round(value,6), 0.400000)
trigram = probas[2]
for token,value,bo in trigram:
if token=="a b a":
self.assertEqual(round(value,6), 0.142857)
if token==START_SENT_SYMBOL+"a a":
self.assertEqual(round(value,6), 0.500000)
if token=="a b"+END_SENT_SYMBOL:
self.assertEqual(round(value,6), 0.428571)
probas = model.probabilities( method="logml" )
self.assertEqual(len(probas), 3)
unigram = probas[0]
for token,value,bo in unigram:
if token=="a":
self.assertEqual(round(value,6), round(math.log(0.42857143,10),6))
if token=="b":
self.assertEqual(round(value,6), round(math.log(0.28571429,10),6))
if token=="c":
self.assertEqual(round(value,6), round(math.log(0.11428571,10),6))
if token=="d":
self.assertEqual(round(value,6), round(math.log(0.08571429,10),6))
if token==START_SENT_SYMBOL:
self.assertEqual(round(value,6), -99.000000)
if token==END_SENT_SYMBOL:
self.assertEqual(round(value,6), round(math.log(0.08571429,10),6))
bigram = probas[1]
for token,value,bo in bigram:
if token=="a b":
self.assertEqual(round(value,6), round(math.log(0.466667,10),6))
if token=="b a":
self.assertEqual(round(value,6), round(math.log(0.400000,10),6))
trigram = probas[2]
for token,value,bo in trigram:
if token=="a b a":
self.assertEqual(round(value,6), round(math.log(0.142857,10),6))
if token==START_SENT_SYMBOL+"a a":
self.assertEqual(round(value,6), round(math.log(0.500000,10),6))
if token=="a b"+END_SENT_SYMBOL:
self.assertEqual(round(value,6), round(math.log(0.428571,10),6))