def test_dame_gender_csv2names(self): g = Gender() names = g.csv2names(path='files/names/partial.csv') self.assertTrue(len(names) > 10) names = g.csv2names(path='files/names/min.csv') self.assertEqual( ['Pierre', 'Raul', 'Adriano', 'Ralf', 'Guillermo', 'Sabina'], names) names = g.csv2names(path='files/names/min.csv', surnames=False) self.assertEqual( ['Pierre', 'Raul', 'Adriano', 'Ralf', 'Guillermo', 'Sabina'], names) names = g.csv2names(path='files/names/min.csv', surnames=True) self.assertEqual( [['Pierre', 'grivel'], ['Raul', 'serapioni'], ['Adriano', 'moura'], ['Ralf', 'kieser'], ['Guillermo', 'leon-de-la-barra'], ['Sabina', 'pannek']], names)
def test_dame_gender_csv2names_method_returns_correct_result(self): g = Gender() names = g.csv2names(path='files/names/partial.csv') self.assertTrue(len(names) > 10)
if (('F' == prob) or ('F ' == prob) or (prob == '?F') or (prob == '1F')): female = female + 1 elif (('M' == prob) or ('M ' == prob) or ('?M' == prob) or ('1M' == prob)): male = male + 1 if (female > male): print("gender: female") if (male > female): print("gender: male") elif (male == female): print("gender: unknown") print("you can try predict with --ml") elif (args.total == "luciahelena"): g = Gender() males = g.csv2names(path="files/names/allnoundefined.males.csv") females = g.csv2names(path="files/names/allnoundefined.females.csv") print("%s was classified as: " % args.name) if (args.name in males): print("male") elif (args.name in females): print("female") else: print("this name was not classified as male or female") elif ((args.verbose) or (args.total == "all")): num_males = s.name_frec(args.name, dataset="ine")['males'] num_females = s.name_frec(args.name, dataset="ine")['females'] print("%s males for %s from INE.es" % (num_males, args.name)) print("%s females for %s from INE.es" % (num_females, args.name)) num_males = s.name_frec(args.name, dataset="uy")['males']