def translaterev(text, language):
"""
translate(text, language) -> str
Translate text by spliting on spaces; search longest string from start
text : text to translate
language : target language
"""
pstring = PhraseString(text)
outxt = ''
Parts = pstring.words
remaining = len(Parts)
words = remaining
loop = 0
#print ('TRANSLATING')
while (remaining >= 1):
#print ('TRANSLATING'+str(loop))
parts = Parts[0:remaining]
cc = len(parts)
ss = [
''.join([st.word + st.breaker for st in parts[i:cc]])
for i in range(0, cc)
]
sep = parts[cc - 1].breaker
l = len(sep)
#print(remaining,cc,sep.encode('utf-8'))#,tr.encode('utf-8'))
tr = ''
#print ('LOOKING')
for i, s in enumerate(ss):
if l > 0:
phrase = s[:-l]
else:
phrase = s
tr, _ = getTranslation(phrase) #from dictionary
if (tr != ''):
print(cc - i, tr.encode('utf-8'))
tr = tr + sep
remaining -= cc - i - 1
break
elif (i == cc - 1):
tr = mapTranslate(s, language)
#print(-1,s,tr)
remaining -= 1
outxt = tr + outxt
final = ''.join([pstring.prefix, outxt, pstring.suffix])
return MTLangUtils.normalizeLangText(final, language), words, score
def translatenew(text,
language,
logforngrams=None,
logsentencengrams=None,
tagmode=False):
"""
translate(text, language) -> str
Translate text by spliting on spaces; search longest string from start
text : text to translate
language : target language
"""
global outxt, prstring, count, Start_transitions
pstring = PhraseString(text)
Parts = pstring.words
partsLength = len(Parts)
leng = partsLength
outxt = ''
count = count + 1
postposition = ['में', 'पर', 'की', 'के', 'का']
#print(count)
def Start_transitions(text):
print('Start_transitions')
print(text)
pstring = PhraseString(text)
Parts = pstring.words
partsLength = len(Parts)
global outxt
#print ("WORDS")
#print (partsLength)
#words=partsLength
loop = 0
tags = {}
while (loop < partsLength):
parts = Parts[loop:partsLength]
cc = len(parts)
#if cc>1:
ss = [
''.join([st.word + st.breaker for st in parts[0:cc - i]])
for i in range(0, cc)
]
tr = ''
for i, s in enumerate(ss):
#Remove last separator
sep = parts[cc - i - 1].breaker
l = len(sep)
if l > 0:
phrase = s[:-l]
else:
phrase = s
print(phrase)
#translate phrase get translation & attribute
tr, _, state = getTranslation(phrase) #from dictionary
if (phrase not in postposition):
tr, _, state = getTranslation(phrase)
feature = getWordEndFeatures(tr)
if (phrase == 'में' or phrase == 'पर'):
if (feature == 'er'):
feature = 1
else:
feature = 0
tr, _, state = getTranslation(str(feature))
print(feature)
if (phrase == 'की' or phrase == 'के' or phrase == 'का'):
tr, _, state = getTranslation(feature)
print(feature)
#print(tr)
if (tr != ''):
if tagmode:
tr = gettagstr(tags, tr)
tr = tr + sep
loop += (cc - i - 1)
#print ("SIZE")
#if (cc<=srcwords):
# print (cc-srcwords)
logthisnGram(phrase, tr, cc - i, logforngrams,
logsentencengrams)
break
elif (i == len(ss) - 1):
"""print ("SIZE*")
print (phrase)
print (cc-i)
"""
tr = mapTranslate(phrase, language)
#if not (phrase==tr):
#tr=tr+'*'
#print (tr.encode('utf-8'))
logthisnGram(phrase, tr, -1, logforngrams,
logsentencengrams)
tr = tr + sep
loop += 1
outxt += tr
print(outxt)
if (i == 0):
newState = 'End'
Parts = Parts[i:]
partsLength = len(Parts)
text = ''.join(
[st.word + st.breaker for st in Parts[0:partsLength]])
return (newState, text)
if (state == 'SHai'
): #move to the next state if second form of hai can come
newState = 'SecondHai'
Parts = Parts[(partsLength - i):]
partsLength = len(Parts)
text = ''.join(
[st.word + st.breaker for st in Parts[0:partsLength]])
return (newState, text)
else:
newState = 'Start' #else move to the original start function
Parts = Parts[(partsLength - i):]
partsLength = len(Parts)
#print('going')
#print(partsLength)
if (partsLength == 1):
newState = 'End'
return (newState, '')
text = ''.join(
[st.word + st.breaker for st in Parts[0:partsLength]])
return (newState, text)
global End_transitions
def End_transitions(txt): #end of state table
return ('End of the state', ' ')
global SecondHai_transitions
def SecondHai_transitions(text):
print(text)
pstring = PhraseString(text)
Parts = pstring.words
partsLength = len(Parts)
global outxt
#print ("WORDS")
#print (partsLength)
#words=partsLength
loop = 0
tags = {}
while (loop < partsLength):
parts = Parts[loop:partsLength]
cc = len(parts)
#if cc>1:
ss = [
''.join([st.word + st.breaker for st in parts[0:cc - i]])
for i in range(0, cc)
]
tr = ''
for i, s in enumerate(ss):
#Remove last separator
sep = parts[cc - i - 1].breaker
l = len(sep)
if l > 0:
phrase = s[:-l]
else:
phrase = s
#translate phrase get translation & attribute
if (phrase == 'है'):
tr = 'আছে'
outxt += tr
newState = 'End'
Parts = Parts[i:]
partsLength = len(Parts)
text = ''.join(
[st.word + st.breaker for st in Parts[0:partsLength]])
return (newState, text)
tr, _, state = getTranslation(phrase) #from dictionary
if (tr != ''):
if tagmode:
tr = gettagstr(tags, tr)
tr = tr + sep
loop += (cc - i - 1)
#print ("SIZE")
#if (cc<=srcwords):
# print (cc-srcwords)
logthisnGram(phrase, tr, cc - i, logforngrams,
logsentencengrams)
break
elif (i == len(ss) - 1):
"""print ("SIZE*")
print (phrase)
print (cc-i)
"""
tr = mapTranslate(phrase, language)
#if not (phrase==tr):
#tr=tr+'*'
#print (tr.encode('utf-8'))
logthisnGram(phrase, tr, -1, logforngrams,
logsentencengrams)
tr = tr + sep
loop += 1
outxt += tr
declare(text)
final = ''.join([pstring.prefix, outxt, pstring.suffix])
#final = outxt
print(final)
print(count)
score = 0.0
if logsentencengrams is not None:
score = logsentencengrams['Score']
return MTLangUtils.normalizeLangText(final, language), leng, score
def translatenewcontext(text,
language,
logforngrams=None,
logsentencengrams=None):
"""
translate(text, language) -> str
Translate text by spliting on spaces; search longest string from start
text : text to translate
language : target language
"""
pstring = PhraseString(text)
outxt = ''
Parts = pstring.words
partsLength = len(Parts)
#print ("WORDS")
#print (partsLength)
words = partsLength
loop = 0
while (loop < partsLength):
parts = Parts[loop:partsLength]
cc = len(parts)
#if cc>1:
ss = [
''.join([st.word + st.breaker for st in parts[0:cc - i]])
for i in range(0, cc)
]
tr = ''
for i, s in enumerate(ss):
#Remove last separator
sep = parts[cc - i - 1].breaker
srcwords = cc - i
print(srcwords)
l = len(sep)
if l > 0:
phrase = s[:-l]
else:
phrase = s
#translate phrase get translation & attribute
tr, _, srcngramwords = getTranslationWithContext(
phrase) #from dictionary
#tr,_ = getTranslation(phrase) #from dictionary
if (tr != ''):
if (srcwords > srcngramwords):
srcwords = srcngramwords
sep = parts[cc - srcwords - 1].breaker
tr = tr + sep
loop += (srcwords - 1)
#loop += (cc-srcwords-1)
#print ("SIZE")
#if (cc<=srcwords):
# print (cc-srcwords)
logthisnGram(phrase, tr, cc - srcwords, logforngrams,
logsentencengrams)
break
elif (i == len(ss) - 1):
"""print ("SIZE*")
print (phrase)
print (cc-i)
"""
tr = mapTranslate(phrase, language)
#if not (phrase==tr):
#tr=tr+'*'
#print (tr.encode('utf-8'))
logthisnGram(phrase, tr, -1, logforngrams, logsentencengrams)
tr = tr + sep
loop += 1
outxt += tr
final = ''.join([pstring.prefix, outxt, pstring.suffix])
score = 0.0
if logsentencengrams is not None:
score = logsentencengrams['Score']
return MTLangUtils.normalizeLangText(final, language), words, score