def preAll():
dts.setSize(7000000)
dts.setFile('../data/twitter.tweets.json', '../emojiOutput/afterPre.txt',
'../log/EmojiPre.log')
dts.openFiles()
__preProcess()
dts.closeFiles()
def __testfind():
dts.setSize(3830000)
dts.setFile('../emojiOutput/afterPre.txt', '../emojiOutput/EmoAll.txt',
'../log/divideEmoticons')
dts.openFiles()
dts.loop(__testEmo, 'test emoji')
dts.closeFiles()
def bigram():
dts.setFile('../output/afterPre.txt', '../output/BiDict.txt',
'../log/bigram.txt')
dts.setSize(25000000)
dts.openFiles()
make_bigram()
dts.closeFiles()
def select_bigram():
dts.setFile('../output/BiDict.txt', '../output/select_bigram.txt',
'../log/select_bigram')
dts.setSize(389920)
dts.openFiles()
dts.loop_with_param(__filter_bigram, [100, 100000], 'filter_bigram')
dts.closeFiles()
def topicFilter():
dts.setSize(14000000)
dts.setFile("/home/server2103/dump/twitter.tweet.json",
"../entityOutput/topictwitter", "../log/matchtwitter")
dts.openFiles()
dts.loop(filterHashtags, 'filterHashtags')
dts.closeFiles()
def select_dict():
dts.setFile('../output/Dict_raw.txt', '../output/Dict_select.txt',
'../log/idf_select.log')
dts.setSize(214884)
dts.openFiles()
dts.loop_with_param(__filter_range, [1000, 34400], 'filter Dict_raw')
dts.closeFiles()
def featureUnigram():
topicList = [ur"#emabiggestfans1d", ur"#emabiggestfansjustinbieber", ur"#p**n", ur"#ipad", ur"#halloween", ur"#emabiggestfans5sos", ur"#stealmygirl", ur"#thewalkingdead", ur"#ebola", ur"#emabiggestfansarianagrande", ur"#lol"]
for hashtag in topicList:
topic = hashtag[1:]
dts.setSize( 50000 )
dts.setFile( '../entityOutput/topictwitter', '../entityOutput/topicTwitter_'+topic, '../log/topicTwitterFeatvect')
dts.openFiles()
dts.loop_with_param( __dealLine, [ hashtag, ],'Generating Unigram With Tag:'+topic )
dts.closeFiles()
def featureVectorParse():
dts.setSize(10000)
dts.setFile('../data/featvect', '../emojiOutput/featureWang10000_no01',
'../log/featureWang')
dts.openFiles()
dts.loop(__lineParse, 'parse featvect')
dts.writeL(str(name_dict))
dts.closeFiles()
def divideHashtag():
dts.setSize(1000000)
dts.setFile('../hashOutput/afterPre.txt',
'../hashOutput/divideHashtag.txt', '../log/divideHashtag.log')
dts.openFiles()
dts.loop(__divide, 'divide by Hashtag')
for emo in EmoList:
print 'label %d \t: %d' % (emo['label'], emo['cnt'])
dts.writeL('label %d \t: %d\n' % (emo['label'], emo['cnt']))
dts.closeFiles()
def divideEmoticons():
dts.setSize(3830000)
dts.setFile('../emojiOutput/EafterPre.txt', '', '../log/divideEmoticons')
dts.openFiles()
for emo in Emotions:
emo['fileptr'] = codecs.open(outputDir + emo['filename'], 'w', 'utf-8')
dts.loop_with_param(__divide, [
3000,
], 'divide Emotions')
for emo in Emotions:
print '%s\t:\t%d' % (emo['filename'], emo['cnt'])
emo['fileptr'].close()
dts.closeFiles()
def __cleanDup():
dts.openFiles()
tw = set()
def __push():
text = dts.readlineI()
tw.add(text)
dts.loop(__push, 'push into set')
print 'start write to file %s' % dts.ofileName
cnt = 0
for text in tw:
dts.writeO(text)
cnt += 1
print 'write finished, tot tweet left: %d' % cnt
dts.closeFiles()
def featureGenerator():
dts.setSize(5000)
dts.setFile( '../emojiOutput/afterPre.txt', '../emojiOutput/feature5000.txt', '../log/emojiFeatureGenerator.log' )
dts.openFiles()
__featureGenerator_init()
for emo in devideEmotion.Emotions:
filename = devideEmotion.outputDir + emo['filename']
ifile = codecs.open( filename, 'r', 'utf-8' )
#print 'Processing %s:' % emo['filename']
dts.loop_with_param( __g_each_tweet, [emo['label'], ifile] , emo['filename'] )
ifile.close()
#dts.loop( __g_each_tweet, 'feature Generator' )
dts.closeFiles()
def featureVectorParse():
topicList = [ur"#emabiggestfans1d", ur"#emabiggestfansjustinbieber", ur"#p**n", ur"#ipad", ur"#halloween", ur"#emabiggestfans5sos", ur"#stealmygirl", ur"#thewalkingdead", ur"#ebola", ur"#emabiggestfansarianagrande", ur"#lol"]
dfile = codecs.open( '../log/featureWang', 'r', 'utf-8' )
line = dfile.readline()
global name_dict
name_dict = eval( line )
dfile.close()
for topic in topicList:
ifilename = '../entityOutput/topicTwitter_' + topic[1:]
ofilename = '../entityOutput/topicFeat_' + topic[1:]
lfilename = '../log/featureVectorParse_entity'
dts.setSize( 50000 )
dts.setFile( ifilename, ofilename, lfilename )
dts.openFiles()
dts.loop( __lineParse, 'parse featvect:' + topic )
dts.closeFiles()
def labelCounter():
dts.setSize(100000)
dts.setFile('../data/featvect', '', '../log/featvectLabelCount')
dts.openFiles()
global counter
for x in range(9):
counter[x] = 0
dts.loop(__line, 'parse featvect')
sum = 0
for x in range(9):
sum += counter[x]
for x in range(9):
print 'Label\t%d\t:%d (%.2f%%)' % (
x, counter[x], float(counter[x] * 100.0) / float(sum))
dts.writeL('Label\t%d\t:%d (%.2f%%)\n' %
(x, counter[x], float(counter[x] * 100.0) / float(sum)))
print 'Sum\t\t:%d' % sum
dts.closeFiles()
def make_dict():
dts.setFile('../output/afterPre.txt', '../output/Dict_raw.txt',
'../log/idf.log')
dts.setSize(25770000)
dts.openFiles()
dict = {}
dts.loop_with_param(__calcIDF, dict, 'calc the Idf')
print 'start sort and print'
cnt = 0
pcnt = 0
CntDistribution = {}
CNT_MAX = 1000000
for x in range(CNT_MAX + 1):
CntDistribution[x] = 0
for key, value in [(k, dict[k]) for k in sorted(dict.keys())]:
if value > 10 and value < 364600:
dts.writeO('%s:%d\n' % (key, value))
pcnt += 1
cnt += 1
if (value > 364600):
print key
if (value > CNT_MAX * 10):
CntDistribution[CNT_MAX] += 1
else:
CntDistribution[value / 10] += 1
print '%d words output' % pcnt
dts.writeL('%d words output\n' % pcnt)
print 'printing range log'
ncnt = 0
for x in range(CNT_MAX):
ncnt += CntDistribution[x]
dts.writeL('%7d~%7d:\t%d\n' % (x * 10, (x + 1) * 10, cnt - ncnt))
dts.closeFiles()
def filterEmoticons():
dts.setSize( 310000 )
dts.setFile( '../data/tweet_noRT_noDup.txt', '../tmp/filter.out', '../log/filterEmoticons.log' )
dts.openFiles()
dts.loop( __cleanTweet, 'clean Tweets' )
dts.closeFiles()
loop_lfilename = '../Compare_Output/ans_unihash_'
all_ofilename = '../emojiOutput/feautre_unihash_all'
all_lfilename = '../Compare_Output/ans_unihash_all'
elif __type == 'UnigramEmoticon_run':
DictDir = '../emojiOutput/UnigramEmoticonDict'
loop_ofilename = '../emojiOutput/feautre_uniemo_'
loop_lfilename = '../Compare_Output/ans_uniemo_'
all_ofilename = '../emojiOutput/feautre_uniemo_all'
all_lfilename = '../Compare_Output/ans_uniemo_all'
load_Index()
for Emo in divideByEmoji.Emotions:
ifilename = divideByEmoji.OutputDir + Emo['name']
ofilename = loop_ofilename + Emo['name']
lfilename = loop_lfilename + Emo['name']
dts.setSize(100000)
dts.setFile(ifilename, ofilename, lfilename)
dts.openFiles()
PC = 0
dts.loop(parse_line, 'generating ' + Emo['name'])
dts.closeFiles()
ifilename = '../emojiOutput/featre_all'
dts.setSize(100000)
dts.setFile(ifilename, all_ofilename, all_lfilename)
dts.openFiles()
dts.loop(parse_line, 'generating all')
dts.closeFiles()
pass
