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")