def get_good_pos_ngrams(self):
"""
Gets a set of gramatically correct part of speech sequences from an input file called essaycorpus.txt
Returns the set and caches the file
"""
if (os.path.isfile(NGRAM_PATH)):
good_pos_ngrams = pickle.load(open(NGRAM_PATH, 'rb'))
elif os.path.isfile(ESSAY_CORPUS_PATH):
essay_corpus = open(ESSAY_CORPUS_PATH).read()
essay_corpus = util_functions.sub_chars(essay_corpus)
good_pos_ngrams = util_functions.regenerate_good_tokens(
essay_corpus)
pickle.dump(good_pos_ngrams, open(NGRAM_PATH, 'wb'))
else:
#Hard coded list in case the needed files cannot be found
good_pos_ngrams = [
'NN PRP', 'NN PRP .', 'NN PRP . DT', 'PRP .', 'PRP . DT',
'PRP . DT NNP', '. DT', '. DT NNP', '. DT NNP NNP', 'DT NNP',
'DT NNP NNP', 'DT NNP NNP NNP', 'NNP NNP', 'NNP NNP NNP',
'NNP NNP NNP NNP', 'NNP NNP NNP .', 'NNP NNP .',
'NNP NNP . TO', 'NNP .', 'NNP . TO', 'NNP . TO NNP', '. TO',
'. TO NNP', '. TO NNP NNP', 'TO NNP', 'TO NNP NNP'
]
return set(good_pos_ngrams)
def update_prompt(self, prompt_text):
"""
Update the default prompt string, which is "".
prompt_text should be a string.
Returns the prompt as a confirmation.
"""
if(isinstance(prompt_text, basestring)):
self._prompt = util_functions.sub_chars(prompt_text)
ret = self._prompt
else:
raise util_functions.InputError(prompt_text, "Invalid prompt. Need to enter a string value.")
return ret
def update_prompt(self, prompt_text):
"""
Update the default prompt string, which is "".
prompt_text should be a string.
Returns the prompt as a confirmation.
"""
if (type(prompt_text) == type("text")):
self._prompt = util_functions.sub_chars(prompt_text)
ret = self._prompt
else:
raise util_functions.InputError(
prompt_text, "Invalid prompt. Need to enter a string value.")
return ret
def get_good_pos_ngrams(self):
"""
Gets a set of gramatically correct part of speech sequences from an input file called essaycorpus.txt
Returns the set and caches the file
"""
if(os.path.isfile(NGRAM_PATH)):
good_pos_ngrams = pickle.load(open(NGRAM_PATH, 'rb'))
elif os.path.isfile(ESSAY_CORPUS_PATH):
essay_corpus = open(ESSAY_CORPUS_PATH).read()
essay_corpus = util_functions.sub_chars(essay_corpus)
good_pos_ngrams = util_functions.regenerate_good_tokens(essay_corpus)
pickle.dump(good_pos_ngrams, open(NGRAM_PATH, 'wb'))
else:
#Hard coded list in case the needed files cannot be found
good_pos_ngrams=['NN PRP', 'NN PRP .', 'NN PRP . DT', 'PRP .', 'PRP . DT', 'PRP . DT NNP', '. DT',
'. DT NNP', '. DT NNP NNP', 'DT NNP', 'DT NNP NNP', 'DT NNP NNP NNP', 'NNP NNP',
'NNP NNP NNP', 'NNP NNP NNP NNP', 'NNP NNP NNP .', 'NNP NNP .', 'NNP NNP . TO',
'NNP .', 'NNP . TO', 'NNP . TO NNP', '. TO', '. TO NNP', '. TO NNP NNP',
'TO NNP', 'TO NNP NNP']
return set(good_pos_ngrams)
def add_essay(self, essay_text, essay_score, essay_generated=0):
"""
Add new (essay_text,essay_score) pair to the essay set.
essay_text must be a string.
essay_score must be an int.
essay_generated should not be changed by the user.
Returns a confirmation that essay was added.
"""
# Get maximum current essay id, or set to 0 if this is the first essay added
if(len(self._id) > 0):
max_id = max(self._id)
else:
max_id = 0
# Verify that essay_score is an int, essay_text is a string, and essay_generated equals 0 or 1
try:
essay_text = essay_text.encode('ascii', 'ignore')
if len(essay_text) < 5:
essay_text = "Invalid essay."
except:
log.exception("Could not parse essay into ascii.")
try:
# Try conversion of types
essay_score = int(essay_score)
essay_text = str(essay_text)
except:
# Nothing needed here, will return error in any case.
log.exception("Invalid type for essay score : {0} or essay text : {1}".format(type(essay_score), type(essay_text)))
if isinstance(essay_score, int) and isinstance(essay_text, basestring)\
and (essay_generated == 0 or essay_generated == 1):
self._id.append(max_id + 1)
self._score.append(essay_score)
# Clean text by removing non digit/work/punctuation characters
try:
essay_text = str(essay_text.encode('ascii', 'ignore'))
except:
essay_text = (essay_text.decode('utf-8', 'replace')).encode('ascii', 'ignore')
cleaned_essay = util_functions.sub_chars(essay_text).lower()
if(len(cleaned_essay) > MAXIMUM_ESSAY_LENGTH):
cleaned_essay = cleaned_essay[0:MAXIMUM_ESSAY_LENGTH]
self._text.append(cleaned_essay)
# Spell correct text using aspell
cleaned_text, spell_errors, markup_text = util_functions.spell_correct(self._text[len(self._text) - 1])
self._clean_text.append(cleaned_text)
self._spelling_errors.append(spell_errors)
self._markup_text.append(markup_text)
# Tokenize text
self._tokens.append(nltk.word_tokenize(self._clean_text[len(self._clean_text) - 1]))
# Part of speech tag text
self._pos.append(nltk.pos_tag(self._clean_text[len(self._clean_text) - 1].split(" ")))
self._generated.append(essay_generated)
# Stem spell corrected text
porter = nltk.PorterStemmer()
por_toks = " ".join([porter.stem(w) for w in self._tokens[len(self._tokens) - 1]])
self._clean_stem_text.append(por_toks)
ret = "text: " + self._text[len(self._text) - 1] + " score: " + str(essay_score)
else:
raise util_functions.InputError(essay_text, "arguments need to be in format "
"(text,score). text needs to be string,"
" score needs to be int.")
def add_essay(self, essay_text, essay_score, essay_generated=0):
"""
Add new (essay_text,essay_score) pair to the essay set.
essay_text must be a string.
essay_score must be an int.
essay_generated should not be changed by the user.
Returns a confirmation that essay was added.
"""
# Get maximum current essay id, or set to 0 if this is the first essay added
if (len(self._id) > 0):
max_id = max(self._id)
else:
max_id = 0
# Verify that essay_score is an int, essay_text is a string, and essay_generated equals 0 or 1
try:
essay_text = essay_text.encode('ascii', 'ignore')
if len(essay_text) < 5:
essay_text = "Invalid essay."
except:
log.exception("Could not parse essay into ascii.")
try:
#Try conversion of types
essay_score = int(essay_score)
essay_text = str(essay_text)
except:
#Nothing needed here, will return error in any case.
log.exception(
"Invalid type for essay score : {0} or essay text : {1}".
format(type(essay_score), type(essay_text)))
if isinstance(essay_score,int) and isinstance(essay_text, basestring)\
and (essay_generated == 0 or essay_generated == 1):
self._id.append(max_id + 1)
self._score.append(essay_score)
# Clean text by removing non digit/work/punctuation characters
try:
essay_text = str(essay_text.encode('ascii', 'ignore'))
except:
essay_text = (essay_text.decode('utf-8', 'replace')).encode(
'ascii', 'ignore')
cleaned_essay = util_functions.sub_chars(essay_text).lower()
if (len(cleaned_essay) > MAXIMUM_ESSAY_LENGTH):
cleaned_essay = cleaned_essay[0:MAXIMUM_ESSAY_LENGTH]
self._text.append(cleaned_essay)
# Spell correct text using aspell
cleaned_text, spell_errors, markup_text = util_functions.spell_correct(
self._text[len(self._text) - 1])
self._clean_text.append(cleaned_text)
self._spelling_errors.append(spell_errors)
self._markup_text.append(markup_text)
# Tokenize text
self._tokens.append(
nltk.word_tokenize(self._clean_text[len(self._clean_text) -
1]))
# Part of speech tag text
self._pos.append(
nltk.pos_tag(self._clean_text[len(self._clean_text) -
1].split(" ")))
self._generated.append(essay_generated)
# Stem spell corrected text
porter = nltk.PorterStemmer()
por_toks = " ".join(
[porter.stem(w) for w in self._tokens[len(self._tokens) - 1]])
self._clean_stem_text.append(por_toks)
ret = "text: " + self._text[len(self._text) -
1] + " score: " + str(essay_score)
else:
raise util_functions.InputError(
essay_text, "arguments need to be in format "
"(text,score). text needs to be string,"
" score needs to be int.")
