def case_continency_table(self, m, L):
if L > 0:
hi = np.random.randint(2, size=m).tolist()
hj = np.random.randint(2, size=m).tolist()
else:
hi = np.random.randint(2, size=m) * 2 - 1
hj = np.random.randint(2, size=m) * 2 - 1
hi, hj = hi.tolist(), hj.tolist()
# #
a, b, c, d = contingency_table(hi, hj)
self.assertEqual(a + b + c + d, m, "Wrong shape! a + b + c + d != m")
def test_multiclass_contingency_table_part3():
m = 31 # number of instances / samples
L = 2 # number of labels / classes
hi = (np.random.randint(L, size=m) * 2 - 1).tolist()
hj = (np.random.randint(L, size=m) * 2 - 1).tolist()
y = (np.random.randint(L, size=m) * 2 - 1).tolist()
#
Cij = multiclass_contingency_table(hi, hj, y)
a, b, c, d = contingency_table(hi, hj)
if not (((a == Cij[0][0]) and (d == Cij[1][1])) or ((a == Cij[1][1]) and (d == Cij[0][0]))):
raise AssertionError("Wrong values in shape.")
if not (((b == Cij[0][1]) and (c == Cij[1][0])) or ((b == Cij[1][0]) and (c == Cij[0][1]))):
raise AssertionError("Wrong values in shape.")
def test_multiclass_contingency_table_part3(self):
m = 31 # number of instances / samples
L = 2 # number of labels / classes
hi = (np.random.randint(L, size=m) * 2 - 1).tolist()
hj = (np.random.randint(L, size=m) * 2 - 1).tolist()
y = (np.random.randint(L, size=m) * 2 - 1).tolist()
Cij = multiclass_contingency_table(hi, hj, y)
a, b, c, d = contingency_table(hi, hj)
#
judge_ad = ((a == Cij[0][0]) and (d == Cij[1][1])) or \
((a == Cij[1][1]) and (d == Cij[0][0]))
judge_bc = ((b == Cij[0][1]) and (c == Cij[1][0])) or \
((b == Cij[1][0]) and (c == Cij[0][1]))
self.assertEqual(judge_ad, True, "Wrong values in shape.")
self.assertEqual(judge_bc, True, "Wrong values in shape.")
def case_contingency_table(m, L):
# m: number of instances / samples
# L: number of labels / classes
if L > 0:
hi = np.random.randint(2, size=m).tolist()
hj = np.random.randint(2, size=m).tolist()
else:
hi = np.random.randint(2, size=m) * 2 - 1
hj = np.random.randint(2, size=m) * 2 - 1
hi, hj = hi.tolist(), hj.tolist()
# #
a, b, c, d = contingency_table(hi, hj)
#
# print("hi", hi)
# print("hj", hj)
if not (a + b + c + d == m):
raise AssertionError("Wrong shape! a + b + c + d != m")
def Kappa_Statistic_binary(hi, hj, m):
a, b, c, d = contingency_table(hi, hj)
Theta_1 = (a + d) / float(m)
Theta_2 = ((a + b) * (a + c) + (c + d) * (b + d)) / (float(m)**2)
return (Theta_1 - Theta_2) / check_zero(1. - Theta_2)
def Correlation_Coefficient_binary(hi, hj):
a, b, c, d = contingency_table(hi, hj)
denominator = (a + b) * (a + c) * (c + d) * (b + d)
denominator = np.sqrt(denominator)
return (a * d - b * c) / check_zero(denominator)
def Q_Statistic_binary(hi, hj):
a, b, c, d = contingency_table(hi, hj)
tem = a * d + b * c
return (a * d - b * c) / check_zero(tem)
def Disagreement_Measure_binary(hi, hj, m):
_, b, c, _ = contingency_table(hi, hj)
return (b + c) / float(m)