def processFile(filename): file = open(filename) sentences = file.readlines() text = " ".join(sentences) tokens = tokeniseContents(text) output = open(filename+".pk","wb") pickle.dump(sentences, output) output.close() return tokens
def processFile(filename):
file = open(filename)
sentences = file.readlines()
text = " ".join(sentences)
tokens = tokeniseContents(text)
output = open(filename + ".pk", "wb")
pickle.dump(sentences, output)
output.close()
return tokens
def processFile(filename): file = open(filename) sentences = file.readlines() text = " ".join(sentences) tokens = tokeniseContents(text) output = open(filename+".pk","wb") pickle.dump(sentences, output) output.close() tagged = [nltk.pos_tag(nltk.tokenize.word_tokenize(s)) for s in sentences] print filename output = open(filename+".tagged.pk","wb") pickle.dump(tagged, output) output.close() return tokens
def processSentence(sentence,vocabList):
#PROCESSSENTENCE preprocesses a sentence and
#returns a list of word_indices
# word_indices = PROCESSSENTENCE(sentence,vocabList) preprocesses
# a sentence and returns a list of indices of the
# words contained in the sentence, based on the vocabList.
#
# Init return value
word_indices = {}
# ========================== Tokenize Sentence ===========================
tokens = tokeniseContents(sentence)
# Process file
l = 0
for token in tokens:
# Skip the word if it is too short
if len(token) < 1:
continue
# Look up the word in the dictionary and add to word_indices if
# found
# ====================== YOUR CODE HERE ======================
# Instructions: Fill in this function to add the index of str to
# word_indices if it is in the vocabulary. At this point
# of the code, you have a stemmed word from the email in
# the variable str. You should look up str in the
# vocabulary list (vocabList). If a match exists, you
# should add the index of the word to the word_indices
# vector. Concretely, if str = 'action', then you should
# look up the vocabulary list to find where in vocabList
# 'action' appears. For example, if vocabList{18} =
# 'action', then, you should add 18 to the word_indices
# vector (e.g., word_indices = [word_indices ; 18]; ).
#
# Note: vocabList{idx} returns a the word with index idx in the
# vocabulary list.
#
# Note: You can use strcmp(str1, str2) to compare two strings (str1 and
# str2). It will return 1 only if the two strings are equivalent.
#
#keyboard
#pdb.set_trace()
index = vocabList.get(token)
if index is not None:
word_indices.update({index:1})
# =============================================================
# Print to screen, ensuring that the output lines are not too long
#if l + len(token) + 1 > 78:
#print '\n'
#l = 0
#print token
#l = l + len(token) + 1
# Print footer
#fprintf('\n\n=========================\n');
return word_indices
def processSentence(sentence, vocabList):
#PROCESSSENTENCE preprocesses a sentence and
#returns a list of word_indices
# word_indices = PROCESSSENTENCE(sentence,vocabList) preprocesses
# a sentence and returns a list of indices of the
# words contained in the sentence, based on the vocabList.
#
# Init return value
word_indices = {}
# ========================== Tokenize Sentence ===========================
tokens = tokeniseContents(sentence)
# Process file
l = 0
for token in tokens:
# Skip the word if it is too short
if len(token) < 1:
continue
# Look up the word in the dictionary and add to word_indices if
# found
# ====================== YOUR CODE HERE ======================
# Instructions: Fill in this function to add the index of str to
# word_indices if it is in the vocabulary. At this point
# of the code, you have a stemmed word from the email in
# the variable str. You should look up str in the
# vocabulary list (vocabList). If a match exists, you
# should add the index of the word to the word_indices
# vector. Concretely, if str = 'action', then you should
# look up the vocabulary list to find where in vocabList
# 'action' appears. For example, if vocabList{18} =
# 'action', then, you should add 18 to the word_indices
# vector (e.g., word_indices = [word_indices ; 18]; ).
#
# Note: vocabList{idx} returns a the word with index idx in the
# vocabulary list.
#
# Note: You can use strcmp(str1, str2) to compare two strings (str1 and
# str2). It will return 1 only if the two strings are equivalent.
#
#keyboard
#pdb.set_trace()
index = vocabList.get(token)
if index is not None:
word_indices.update({index: 1})
# =============================================================
# Print to screen, ensuring that the output lines are not too long
#if l + len(token) + 1 > 78:
#print '\n'
#l = 0
#print token
#l = l + len(token) + 1
# Print footer
#fprintf('\n\n=========================\n');
return word_indices
def testURL(self):
self.assertEqual(tokeniseContents("Hello http://www.google.com/search?q=hello"), ['hello','httpaddr'])
def testNumber(self):
self.assertEqual(tokeniseContents("Hello 1 2 3"), ['hello','number','number','number'])
def testDollar(self):
self.assertEqual(tokeniseContents("Hello $$$"), ['hello','dollar'])
def testEmail(self):
self.assertEqual(tokeniseContents("Hello [email protected]"), ['hello','emailaddr'])
def testDollar(self):
self.assertEqual(tokeniseContents("Hello $$$"), ['hello', 'dollar'])
def testNumber(self):
self.assertEqual(tokeniseContents("Hello 1 2 3"),
['hello', 'number', 'number', 'number'])
def testEmail(self):
self.assertEqual(tokeniseContents("Hello [email protected]"),
['hello', 'emailaddr'])
def testURL(self):
self.assertEqual(
tokeniseContents("Hello http://www.google.com/search?q=hello"),
['hello', 'httpaddr'])
