return classification
if __name__ == "__main__":
if len(sys.argv) < 3:
print(sys.argv[0] + " <lexicon_filepath> " + "<narrative_filepath>")
quit()
lexicon_filepath = sys.argv[1]
narrative_filepath = sys.argv[2]
# Lexicon is a dict indexed by words of the english dictionary.
# Each value is a list of tuples [(nrc_emotion, association)]
lexicon = parse_nrc_lexicon(lexicon_filepath)
# Narrative is a dict indexed by sentence id.
# Each value is a tuple (sentence, rpg_emotion)
narrative = rpg_ec.parse_narrative_data(narrative_filepath)
# Classify a narrative according to rpg_emotions:
classification = classify_narrative(narrative, lexicon, 20)
# Calculate confusion matrix
confusion_matrix = rpg_ec.rpg_create_confusion_matrix(
narrative, classification)
rpg_ec.rpg_print_confusion_matrix(confusion_matrix)
print(rpg_ec.calculate_accuracy(confusion_matrix))
rpg_ec.rpg_print_classification(classification, "classification.txt")
atualTrans = 3
else:
linhas[linha - 1]['emotion'] = 'agitated'
linhas[linha - 1]['prob'] = prob
atual = 'agitated'
atualTrans = 4
cont = cont + 1
inicio = inicio + 1
for x in range(0, len(linhas)):
str1 = ' '.join(linhas[x]['arranjo'])
classification[x + 1] = (str1, str(linhas[x]['emotion']))
narrative = rpg_ec.parse_narrative_data('datasets/ep' +
str(episodio) + '.txt')
confusion_matrix = rpg_ec.rpg_create_confusion_matrix(
narrative, classification)
resultado = rpg_ec.calculate_accuracy(confusion_matrix)
## resultEp1Accura.append(resultado)
## limiarArray.append(limiar)
## janelaArray.append(janela)
DifTransicao = 0
def calculateDifference(transition, episodio, TransEps):
DifTrans = 0
if transition >= TransEps[episodio - 1]:
DifTrans = transition - TransEps[episodio - 1]