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']