def test_cramer(self):
dc = DependenceCoef(self.X, self.Y)
self.T_cramer = np.subtract(self.T, self.T_cramer_expect)
self.T_cramer = np.square(self.T_cramer)
self.x2 = np.sum(np.divide(self.T_cramer, self.T_cramer_expect))
self.cramer = math.sqrt(self.x2 / (self.total * min(self.r-1,self.s-1)))
self.assertEqual(dc.cramer(), self.cramer, 'cramer coeff failed')
dc = DependenceCoef(self.X, self.X)
self.assertEqual(dc.cramer(), 1.0, 'cramer coeff failed')
def test_cramer(self):
dc = DependenceCoef(self.X, self.Y)
self.T_cramer = np.subtract(self.T, self.T_cramer_expect)
self.T_cramer = np.square(self.T_cramer)
self.x2 = np.sum(np.divide(self.T_cramer, self.T_cramer_expect))
self.cramer = math.sqrt(self.x2 /
(self.total * min(self.r - 1, self.s - 1)))
self.assertEqual(dc.cramer(), self.cramer, 'cramer coeff failed')
dc = DependenceCoef(self.X, self.X)
self.assertEqual(dc.cramer(), 1.0, 'cramer coeff failed')
