def graphSentenceWordUse(sentences, top=0, fileName=args.args.file):
num = len(sentences) + 1
chart = pygal.StackedBar(print_labels=True, show_legend=False)
chart.title = 'Word Use By Sentence'
if top > 0:
chart.title += ' Of Top ' + str(top) + ' Words'
mostUsed = most_used_words.mostUsed(fileName, top=top)
mostUsed = {word['label']: word['value'] \
for word in mostUsed}
chart.x_labels = map(str, range(1, num))
sentencesByWord = [[taxonomy.sanitize(word) for word in sentence.split()] \
for sentence in sentences]
allWords = {}
for sentence in sentencesByWord:
for word in sentence:
allWords[word] = {'label': word, 'value': 0}
wordCounts = [copy.deepcopy(allWords) for sentence in sentencesByWord]
for i in xrange(0, len(sentencesByWord)):
for word in sentencesByWord[i]:
wordCounts[i][word]['value'] += 1
perWord = {}
for i in xrange(0, len(wordCounts)):
for word in wordCounts[i]:
if not word in perWord:
perWord[word] = []
if wordCounts[i][word]['value'] < 1 or \
(top > 0 and not word in mostUsed):
wordCounts[i][word]['label'] = ''
wordCounts[i][word]['value'] = 0
perWord[word].append(wordCounts[i][word])
for word in perWord:
chart.add(word, perWord[word])
fileName = chart.title.lower().replace(' ', '_')
chart.render_to_png(taxonomy.outdir(fileName + '.png'))
def graphSentenceWordUse(sentences, top=0, fileName=args.args.file):
num = len(sentences) + 1
chart = pygal.StackedBar(print_labels=True, show_legend=False)
chart.title = 'Word Use By Sentence'
if top > 0:
chart.title += ' Of Top ' + str(top) + ' Words'
mostUsed = most_used_words.mostUsed(fileName, top=top)
mostUsed = {word['label']: word['value'] \
for word in mostUsed}
chart.x_labels = map(str, range(1, num))
sentencesByWord = [[taxonomy.sanitize(word) for word in sentence.split()] \
for sentence in sentences]
allWords = {}
for sentence in sentencesByWord:
for word in sentence:
allWords[word] = {'label': word, 'value': 0}
wordCounts = [copy.deepcopy(allWords) for sentence in sentencesByWord]
for i in xrange(0, len(sentencesByWord)):
for word in sentencesByWord[i]:
wordCounts[i][word]['value'] += 1
perWord = {}
for i in xrange(0, len(wordCounts)):
for word in wordCounts[i]:
if not word in perWord:
perWord[word] = []
if wordCounts[i][word]['value'] < 1 or \
(top > 0 and not word in mostUsed):
wordCounts[i][word]['label'] = ''
wordCounts[i][word]['value'] = 0
perWord[word].append(wordCounts[i][word])
for word in perWord:
chart.add(word, perWord[word])
fileName = chart.title.lower().replace(' ', '_')
chart.render_to_png(taxonomy.outdir(fileName + '.png'))
def mostUsed(fileName, top=10):
fileData = taxonomy.readFile(fileName)
section = [taxonomy.sanitize(word) for word in fileData.split()]
wordCounts = {word: 0 for word in section}
for word in section:
wordCounts[word] += 1
allWords = [{'label': word, 'value': wordCounts[word]} \
for word in wordCounts]
allWords = sorted(allWords, key=lambda x: x['value'], reverse=True)
topWords = allWords[:top]
return topWords
def mostUsed(fileName, top=10):
fileData = taxonomy.readFile(fileName)
section = [taxonomy.sanitize(word) for word in fileData.split()]
wordCounts = {word: 0 for word in section}
for word in section:
wordCounts[word] += 1
allWords = [{'label': word, 'value': wordCounts[word]} \
for word in wordCounts]
allWords = sorted(allWords, key=lambda x: x['value'], reverse=True)
topWords = allWords[:top]
return topWords
def handleSentence(sentence, num):
sentence = sentence.strip()
words = sentence.split()
wordTypes = []
for i in xrange(0, len(words)):
clearScreen()
before = ' '.join(words[:i]) + ' '
if i == 0:
before = ''
display = before + colorama.Fore.RED + words[i] \
+ colorama.Style.RESET_ALL + ' ' + ' '.join(words[i + 1:])
word = taxonomy.sanitize(words[i])
info = taxonomy.word(word)
print info['definition']
print ''
del info['definition']
del info['_id']
print info
print ''
for j in xrange(1, len(taxonomy.TYPES)):
print j, taxonomy.TYPES[j - 1]
print ''
print display
print ''
res = inp('What kind of word is this? ')
if res == '':
res = info['type'][-1]
else:
res = taxonomy.TYPES[int(res) - 1]
wordTypes.append(res)
if 'type' in info and isinstance(info['type'], list) and \
not res in info['type']:
info['type'].append(res)
else:
info['type'] = [res]
mongo.coll.update_one({'_id': word}, {'$set': {'type': info['type']}}, \
upsert=False)
try:
mongo.coll.insert_one({
'_id': num,
'sentence': words,
'types': wordTypes
})
except Exception as e:
print e
time.sleep(1)
def handleSentence(sentence, num):
sentence = sentence.strip()
words = sentence.split()
wordTypes = []
for i in xrange(0, len(words)):
clearScreen()
before = ' '.join(words[:i]) + ' '
if i == 0:
before = ''
display = before + colorama.Fore.RED + words[i] \
+ colorama.Style.RESET_ALL + ' ' + ' '.join(words[i + 1:])
word = taxonomy.sanitize(words[i])
info = taxonomy.word(word)
print info['definition']
print ''
del info['definition']
del info['_id']
print info
print ''
for j in xrange(1, len(taxonomy.TYPES)):
print j, taxonomy.TYPES[j - 1]
print ''
print display
print ''
res = inp('What kind of word is this? ')
if res == '':
res = info['type'][-1]
else:
res = taxonomy.TYPES[int(res) - 1]
wordTypes.append(res)
if 'type' in info and isinstance(info['type'], list) and \
not res in info['type']:
info['type'].append(res)
else:
info['type'] = [res]
mongo.coll.update_one({'_id': word}, {'$set': {'type': info['type']}}, \
upsert=False)
try:
mongo.coll.insert_one({'_id': num, 'sentence': words, 'types': wordTypes})
except Exception as e:
print e
time.sleep(1)
def test_sanitize(self):
real = 'some string'
test = 'S!O@,M$E%% S^&*T(R):;I,.N\'\"G<>.,'
res = taxonomy.sanitize(test)
self.assertEqual(res, real)
def test_sanitize(self):
real = 'some string'
test = 'S!O@,M$E%% S^&*T(R):;I,.N\'\"G<>.,'
res = taxonomy.sanitize(test)
self.assertEqual(res, real)
