def setUp(self):
self.pis = array(
[
[0.1, 0.1, 0.8],
[0.1, 0.8, 0.1],
[0.8, 0.1, 0.1]
]
)
self.mus = array([[2, 2], [3, 3], [4, 4]])
self.sigmas = array([eye(2), eye(2), eye(2)])
self.mix = HDPMixture(self.pis, self.mus, self.sigmas)
def setUp(self):
self.pis = array([[.1,.1,.8], [.1,.8,.1],[.8,.1,.1]])
self.mus = array([[2,2],[3,3],[4,4]])
self.sigmas = array([eye(2),eye(2),eye(2)])
self.mix = HDPMixture(self.pis,self.mus,self.sigmas)
class HDPMixtureTestCase(unittest.TestCase):
def setUp(self):
self.pis = array([[.1,.1,.8], [.1,.8,.1],[.8,.1,.1]])
self.mus = array([[2,2],[3,3],[4,4]])
self.sigmas = array([eye(2),eye(2),eye(2)])
self.mix = HDPMixture(self.pis,self.mus,self.sigmas)
def test_arith(self):
numpy.testing.assert_array_equal((self.mix+2).mus, self.mix.mus+2,
"Failed addition")
numpy.testing.assert_array_equal((self.mix*2).mus, self.mix.mus*2,
"Failed multiplication")
numpy.testing.assert_array_equal((self.mix*2).sigmas, self.mix.sigmas*4,
"failed multiplication")
numpy.testing.assert_equal((self.mix*2).sigmas.shape, self.mix.sigmas.shape, 'multiplication failed')
numpy.testing.assert_array_equal((self.mix+2).pis, self.mix.pis,
"addition changes pi values")
numpy.testing.assert_array_equal((self.mix*eye(2)).sigmas, self.mix.sigmas, 'multicplication failed')
def test_getitem(self):
single = self.mix[0]
self.assertIsInstance(single, DPMixture,
'get item didn\'t return a DPMixture')
sliced = self.mix[0:2]
self.assertIsInstance(sliced, list,
'get slice didn\'t return a list')
numpy.testing.assert_array_equal(self.mix[0].pis, self.pis[0,:], "returned pis wrong")
def test_len(self):
self.assertEqual(len(self.mix), 3, 'len returned the wrong value')
def test_iter(self):
count = 0
for i in self.mix:
self.assertIsInstance(i, DPMixture,
'get itterator didn\'t return a DPMixture')
count += 1
self.assertEqual(count, 3, 'itterator didn\'t return all the elements')
def test_stats(self):
prob = self.mix.prob(array([1,2]))
self.assertEqual(prob.shape, (3,3), 'probability return wrong shape')
self.assertLessEqual(prob.max(), 1, 'probability returnd a value > 1')
classified = self.mix.classify(array([1,2]))
self.assertEqual(classified.shape, (3,), 'probability return wrong shape,')
def test_average(self):
avg = self.mix.average()
numpy.testing.assert_array_equal(avg.mus, self.mix.mus, 'averaging got means wrong')
numpy.testing.assert_array_equal(avg.sigmas, self.mix.sigmas, 'averaging got variance wrong')
self.assertIsInstance(avg, HDPMixture, 'average returned wrong type of object')
self.assertEqual(len(avg),3, 'average return the wrong number of mixtures, %d' % len(avg))
def test_make_modal(self):
modal = self.mix.make_modal()
self.assertIsInstance(modal, ModalHDPMixture, 'make_modal failed to return ModalHDPMixture object')