def average(self, name, surname):
r = 0
count = 0
avg = 0
dgg = DameGenderGuesser()
guess1 = int(dgg.guess(name, binary="True"))
if (guess1 != 2):
r = r + guess1
count = count + 1
if (self.config['DEFAULT']['genderapi'] == 'yes'):
dga = DameGenderApi()
guess2 = int(dga.guess(name, binary="True"))
if (guess2 != 2):
r = r + guess2
count = count + 1
if (self.config['DEFAULT']['genderize'] == 'yes'):
dg = DameGenderize()
guess3 = int(dg.guess(name, binary="True"))
if (guess3 != 2):
r = r + guess3
count = count + 1
if (self.config['DEFAULT']['namsor'] == 'yes'):
dn = DameNamsor()
guess4 = int(dn.guess(str(name), str(surname), binary="True"))
if (guess4 != 2):
r = r + guess4
count = count + 1
avg = r / count
return avg
def test_dame_genderguesser_gender_list(self):
dgg = DameGenderGuesser()
gl = dgg.gender_list(path="files/names/partial.csv")
self.assertEqual(
gl,
[1, 1, 1, 1, 2, 1, 0, 0, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1])
self.assertEqual(len(gl), 21)
self.assertEqual(dgg.females, 3)
self.assertEqual(dgg.males, 16)
self.assertEqual(dgg.unknown, 2)
def test_dame_genderguesser_guess_list(self):
dgg = DameGenderGuesser()
self.assertEqual([
'male', 'male', 'male', 'male', 'male', 'male', 'female', 'female',
'male', 'male'
],
dgg.guess_list(path="files/names/partial.csv",
binary=False)[0:10])
self.assertEqual([1, 1, 1, 1, 1, 1, 0, 0, 1, 1],
dgg.guess_list(path="files/names/partial.csv",
binary=True)[0:10])
def test_dame_genderguesser_gender_list_method_returns_correct_result(
self):
dgg = DameGenderGuesser()
gl = dgg.gender_list()
self.assertEqual(
gl,
[1, 1, 1, 1, 2, 1, 0, 0, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1])
self.assertEqual(len(gl), 21)
self.assertEqual(dgg.females, 3)
self.assertEqual(dgg.males, 16)
self.assertEqual(dgg.unknown, 2)
def test_genderguesser_list(self):
dgg = DameGenderGuesser()
g1 = dgg.guess("Sara", binary=False)
self.assertEqual(g1, "female")
g2 = dgg.guess("Sara", binary=True)
self.assertEqual(g2, 0)
g3 = dgg.guess("Laura", binary=False)
self.assertEqual(g3, "female")
g4 = dgg.guess("Laura", binary=True)
self.assertEqual(g4, 0)
def test_dame_genderguesser_accuracy(self):
dgg = DameGenderGuesser()
gl1 = dgg.gender_list(path="files/names/partial.csv")
gl2 = dgg.guess_list(path="files/names/partial.csv", binary=True)
self.assertTrue(dgg.accuracy_score_dame(gl1, gl2) >= 0.5)
self.assertTrue(dgg.accuracy(path="files/names/partial.csv") >= 0.5)
if (dg.config['DEFAULT']['namsor'] == 'yes'):
dn = DameNamsor()
dn.pretty_gg_list(path=args.csv,
jsonf=args.jsondownloaded,
measure=args.measure,
api='Namsor')
if (dg.config['DEFAULT']['genderize'] == 'yes'):
dg = DameGenderize()
dg.pretty_gg_list(path=args.csv,
jsonf=args.jsondownloaded,
measure=args.measure,
api='Genderize')
dgg = DameGenderGuesser()
dgg.pretty_gg_list(path=args.csv,
jsonf=args.jsondownloaded,
measure=args.measure,
api='Genderguesser')
ds = DameSexmachine()
ds.pretty_gg_list(path=args.csv,
jsonf=args.jsondownloaded,
measure=args.measure,
api='Damegender')
if (dg.config['DEFAULT']['genderapi'] == 'yes'):
dga = DameGenderApi()
dga.pretty_gg_list(path=args.csv,
jsonf=args.jsondownloaded,
#print(dn.accuracy_score_dame([1, 1, 1, 1, 2, 1], [1, 1, 1, 1, 1, 1]))
#namsor_accuracy = dn.accuracy_score_dame([1, 1, 1, 1, 2, 1], [1, 1, 1, 1, 2, 1])
print("Namsor accuracy: %s" % namsor_accuracy)
dg = DameGenderize()
print("################### Genderize!!")
gl = dg.gender_list(path=args.csv)
print("Gender list: " + str(gl))
sl = dg.guess_list(path=args.csv, binary=True)
print("Guess list: " +str(gl))
genderize_accuracy = dg.accuracy_score_dame(gl,sl)
print("Genderize accuracy: %s" % genderize_accuracy)
dgg = DameGenderGuesser()
print("################### GenderGuesser!!")
gl = dgg.gender_list(path=args.csv)
print("Gender list: " + str(gl))
sl = dgg.guess_list(path=args.csv, binary=True)
print("Guess list: " +str(sl))
genderguesser_accuracy = dgg.accuracy_score_dame(gl,sl)
print("GenderGuesser accuracy: %s" % genderguesser_accuracy)
ds = DameSexmachine()
print("################### Dame Gender!!")
gl = ds.gender_list(path=args.csv)
print("Gender list: " + str(gl))
sl = ds.guess_list(path=args.csv, binary=True)
print("Guess list: " +str(sl))
print("Namsor confusion matrix:\n")
dn.print_confusion_matrix_dame(path=args.csv)
elif (args.dimensions == "3x3"):
namsor_confusion_matrix = dn.confusion_matrix(path=args.csv)
print("Namsor confusion matrix:\n %s" % namsor_confusion_matrix)
dg = DameGenderize()
if (args.dimensions == "3x2"):
print("Genderize confusion matrix:\n")
dg.print_confusion_matrix_dame(path=args.csv)
elif (args.dimensions == "3x3"):
dg = DameGenderize()
genderize_confusion_matrix = dg.confusion_matrix(path=args.csv)
print("Genderize confusion matrix:\n %s" % genderize_confusion_matrix)
dgg = DameGenderGuesser()
if (args.dimensions == "3x2"):
print("Gender Guesser confusion matrix:\n")
dgg.print_confusion_matrix_dame(path=args.csv)
elif (args.dimensions == "3x3"):
genderguesser_confusion_matrix = dgg.confusion_matrix(path=args.csv)
print("Gender Guesser confusion matrix:\n %s" % genderguesser_confusion_matrix)
ds = DameSexmachine()
if (args.dimensions == "3x2"):
print("Sexmachine confusion matrix:\n")
ds.print_confusion_matrix_dame(path=args.csv, ml=args.ml)
elif (args.dimensions == "3x3"):
ds = DameSexmachine()
sexmachine_confusion_matrix = ds.confusion_matrix(path=args.csv)
print("Sexmachine confusion matrix:\n %s" % sexmachine_confusion_matrix)
if (args.api == "all"):
dg = Gender()
if (dg.config['DEFAULT']['namsor'] == 'yes'):
dn = DameNamsor()
dn.pretty_cm(path=args.csv, jsonf=args.jsondownloaded, reverse=args.reverse, dimensions=args.dimensions, api=args.api.title())
if (dg.config['DEFAULT']['genderize'] == 'yes'):
dg = DameGenderize()
dg.pretty_cm(path=args.csv, jsonf=args.jsondownloaded, reverse=args.reverse, dimensions=args.dimensions, api=args.api.title())
# dg.print_confusion_matrix_gender(path=args.csv, dimensions=args.dimensions)
if (dg.config['DEFAULT']['genderapi'] == 'yes'):
dga = DameGenderApi()
dga.pretty_cm(path=args.csv, jsonf=args.jsondownloaded, reverse=args.reverse, dimensions=args.dimensions, api=args.api.title())
dgg = DameGenderGuesser()
dgg.print_confusion_matrix_gender(path=args.csv, dimensions=args.dimensions)
ds = DameSexmachine()
ds.pretty_cm(path=args.csv, jsonf=args.jsondownloaded, reverse=args.reverse, dimensions=args.dimensions, api=args.api.title())
if (dg.config['DEFAULT']['nameapi'] == 'yes'):
dna = DameNameapi()
dna.pretty_cm(path=args.csv, jsonf=args.jsondownloaded, reverse=args.reverse, dimensions=args.dimensions, api=args.api.title())
elif (args.api == "namsor"):
dn = DameNamsor()
dn.pretty_cm(path=args.csv, jsonf=args.jsondownloaded, reverse=args.reverse, dimensions=args.dimensions, api=args.api.title())
elif (args.api == "genderize"):
dg = DameGenderize()
gl1 = d.gender_list(path=args.csv)
if (os.path.isfile(args.jsondownloaded)):
gl2 = d.json2guess_list(jsonf=args.jsondownloaded, binary=True)
else:
gl2 = d.guess_list(path=args.csv, binary=True)
# gl2 = d.guess_list(path=args.csv, binary=True)
ec = d.error_coded(gl1, gl2)
print("+ The error code: %s" % ec)
ecwa = d.error_coded_without_na(gl1, gl2)
print("+ The error code without na: %s" % ecwa)
naCoded = d.na_coded(gl1, gl2)
print("+ The na coded: %s" % naCoded)
egb = d.error_gender_bias(gl1, gl2)
print("+ The error gender bias: %s" % egb)
elif (args.api == "genderguesser"):
d = DameGenderGuesser()
print("Gender Guesser with %s has: " % args.csv)
gl1 = d.gender_list(path=args.csv)
gl2 = d.guess_list(path=args.csv, binary=True)
ec = d.error_coded(gl1, gl2)
print("+ The error code: %s" % ec)
ecwa = d.error_coded_without_na(gl1, gl2)
print("+ The error code without na: %s" % ecwa)
naCoded = d.na_coded(gl1, gl2)
print("+ The na coded: %s" % naCoded)
egb = d.error_gender_bias(gl1, gl2)
print("+ The error gender bias: %s" % egb)
elif (args.api == "nameapi"):
d = DameNameapi()
print("Nameapi with %s has: " % args.csv)
gl1 = d.gender_list(path=args.csv)
def test_dame_genderguesser_accuracy_method_returns_correct_result(self):
dgg = DameGenderGuesser()
self.assertTrue(dgg.accuracy(path="files/names/partial.csv") >= 0.5)
import sys
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('name', help="Name to be detected")
parser.add_argument('--surname', help="Surname to be detected")
parser.add_argument("--api", choices=['namsor', 'genderize', 'genderguesser', 'genderapi', 'nameapi'], required=True)
#parser.add_argument('--prob', default="yes", choices=['yes', 'no'])
parser.add_argument('--version', action='version', version='0.1')
args = parser.parse_args()
du = DameUtils()
if (len(sys.argv) > 1):
if (args.api == "genderguesser"):
dgg = DameGenderGuesser()
print(dgg.guess(args.name))
elif (args.api == "genderapi"):
dga = DameGenderApi()
print(dga.guess(args.name, binary=False))
print("accuracy: " + str(dga.accuracy(args.name)))
elif (args.api == "genderize"):
dg = DameGenderize()
print(dg.guess(args.name))
print("probability: " + str(dg.prob(args.name)))
elif (args.api == "namsor"):
dn = DameNamsor()
if (du.is_not_blank(args.surname)):
print(dn.guess(str(args.name), str(args.surname)))
print("scale: " + str(dn.scale(str(args.name), str(args.surname))))
else: