def loadSentiment_value(catalog):
valueSentimentFile = cf.data_dir + 'sentiment_values.csv'
input_file = csv.DictReader(open(valueSentimentFile, encoding='utf-8'),
delimiter=",")
for valuesent in input_file:
model.addSentiment(catalog, valuesent)
def loadSentiments(analyzer):
sentimentsfile = cf.data_dir + 'sentiment_values.csv'
input_file = csv.DictReader(open(sentimentsfile, encoding="utf-8"),
delimiter=",")
for sentiment in input_file:
model.addSentiment(analyzer, sentiment)
return analyzer
def loadSentiment(analyzer):
"""
Carga los valores de sentimientos del archivo csv.
"""
sentimentsfile = cf.data_dir + 'subsamples-small/sentiment_values.csv'
input_file = csv.DictReader(open(sentimentsfile, encoding='utf-8'))
for sentimentValue in input_file:
model.addSentiment(analyzer, sentimentValue)
def loadData(catalog):
TSfile = cf.data_dir + 'user_track_hashtag_timestamp-small.csv'
ts_sub = csv.DictReader(open(TSfile, encoding='utf-8'))
for register in ts_sub:
model.createmap2file(catalog, register, 'track')
HVfile = cf.data_dir + 'sentiment_values.csv'
sv_file = csv.DictReader(open(HVfile, encoding='utf-8'))
for pair in sv_file:
model.addSentiment(catalog, pair)
Dfile = cf.data_dir + 'context_content_features-small.csv'
main_file = csv.DictReader(open(Dfile, encoding='utf-8'))
for event in main_file:
model.addEvent(catalog, event)
def loadData(analyzer, hashtag, sentiments, context):
"""
Carga los datos de los archivos CSV en el modelo
"""
hashtagsfile = cf.data_dir + hashtag
hashtag_file = csv.DictReader(open(hashtagsfile, encoding="utf-8"),
delimiter=",")
contextfile = cf.data_dir + context
context_file = csv.DictReader(open(contextfile, encoding="utf-8"),
delimiter=",")
sentimentsfile = cf.data_dir + sentiments
sentiments_file = csv.DictReader(open(sentimentsfile, encoding="utf-8"),
delimiter=",")
for event in context_file:
model.addEvent(analyzer, event)
posEvent = 1
for hastag in hashtag_file:
posEvent = model.addHashtag(analyzer, hastag, posEvent)
model.crearArboles(analyzer)
for sentiment in sentiments_file:
model.addSentiment(analyzer, sentiment)
return analyzer
def loadSentiment(catalog):
sfile = cf.data_dir + 'subsamples-small/sentiment_values.csv'
input_file = csv.DictReader(open(sfile, encoding='utf-8'), delimiter=",")
for line in input_file:
model.addSentiment(catalog, line)
def loadSentiment(cat, sentiment):
sfile = cf.data_dir + "subsamples-small" + "\\" + sentiment
input_file = csv.DictReader(open(sfile, encoding="utf-8"), delimiter=",")
for sent in input_file:
model.addSentiment(cat, sent)
print("Se cargó el archivo de Sentiment Values")