def test_prediction_full(self):
gmm0 = GMM(self.M, self.D, cvtype='full')
likelihood0 = gmm0.train(self.X)
Y0 = gmm0.predict(self.X)
gmm1 = GMM(self.M, self.D, cvtype='full')
likelihood1 = gmm1.train(self.X)
Y1 = gmm1.predict(self.X)
for a,b in zip(Y0, Y1): self.assertAlmostEqual(a,b)
self.assertTrue(len(set(Y0)) > 1)
def test_prediction_full(self):
print "test prediction full"
gmm0 = GMM(self.M, self.D, cvtype='full')
likelihood0 = gmm0.train(self.X)
Y0 = gmm0.predict(self.X)
gmm1 = GMM(self.M, self.D, cvtype='full')
likelihood1 = gmm1.train(self.X)
Y1 = gmm1.predict(self.X)
for a,b in zip(Y0, Y1): self.assertAlmostEqual(a,b, places=3)
self.assertTrue(len(set(Y0)) > 1)
def test_prediction_once(self):
gmm0 = GMM(self.M, self.D, cvtype='diag')
likelihood0 = gmm0.train(self.X)
Y0 = gmm0.predict(self.X)
gmm1 = GMM(self.M, self.D, cvtype='diag')
likelihood1 = gmm1.train(self.X)
Y1 = gmm1.predict(self.X)
for a, b in zip(Y0, Y1):
self.assertAlmostEqual(a, b)
self.assertTrue(len(set(Y0)) > 1)
def test_prediction_full(self):
print "test prediction full"
gmm0 = GMM(self.M, self.D, cvtype="full")
likelihood0 = gmm0.train(self.X)
Y0 = gmm0.predict(self.X)
gmm1 = GMM(self.M, self.D, cvtype="full")
likelihood1 = gmm1.train(self.X)
Y1 = gmm1.predict(self.X)
for a, b in zip(Y0, Y1):
self.assertAlmostEqual(a, b, places=3)
self.assertTrue(len(set(Y0)) > 1)