def testAverage(self):
clst1 = DPCluster(0.5, self.mu1, self.sig)
clst3 = DPCluster(0.5, self.mu1, self.sig)
clst5 = DPCluster(0.5, self.mu1, self.sig)
clst7 = DPCluster(0.5, self.mu1, self.sig)
clst2 = DPCluster(0.5, self.mu2, self.sig)
clst4 = DPCluster(0.5, self.mu2, self.sig)
clst6 = DPCluster(0.5, self.mu2, self.sig)
clst8 = DPCluster(0.5, self.mu2, self.sig)
lt = {}
for i in range(8):
lt[i] = i
mix = OrderedDPMixture(
[clst1, clst2, clst3, clst4, clst5, clst6, clst7, clst8],
lt,
niter=4)
avg = mix.average()
assert len(avg.clusters) == 2
assert all(avg.mus[0] == self.mu1)
assert all(avg.mus[1] == self.mu2)
assert all(avg.sigmas[0] == self.sig)
assert all(avg.sigmas[1] == self.sig)
assert avg.pis[0] == 0.5, 'pis should be 0.5 but is %f' % avg.pis()[0]
assert avg.pis[1] == 0.5, 'pis should be 0.5 but is %f' % avg.pis()[0]
def testLast(self):
clst1 = DPCluster(0.5, self.mu1, self.sig)
clst3 = DPCluster(0.5, self.mu1 + 3, self.sig)
clst5 = DPCluster(0.5, self.mu1 + 5, self.sig)
clst7 = DPCluster(0.5, self.mu1 + 7, self.sig)
clst2 = DPCluster(0.5, self.mu2 + 2, self.sig)
clst4 = DPCluster(0.5, self.mu2 + 4, self.sig)
clst6 = DPCluster(0.5, self.mu2 + 6, self.sig)
clst8 = DPCluster(0.5, self.mu2 + 8, self.sig)
lt = {}
for i in range(8):
lt[i] = i
mix = OrderedDPMixture(
[clst1, clst2, clst3, clst4, clst5, clst6, clst7, clst8],
lt,
niter=4)
new_r = mix.last()
assert len(new_r.clusters) == 2
assert all(new_r.clusters[0].mu == clst7.mu)
assert all(new_r.clusters[1].mu == clst8.mu)
new_r = mix.last(2)
assert len(new_r.clusters) == 4
assert all(new_r.clusters[0].mu == clst5.mu)
assert all(new_r.clusters[1].mu == clst6.mu)
assert all(new_r.clusters[2].mu == clst7.mu)
assert all(new_r.clusters[3].mu == clst8.mu)
try:
new_r = mix.last(10)
except ValueError:
pass
def testLast(self):
clst1 = DPCluster(0.5, self.mu1, self.sig)
clst3 = DPCluster(0.5, self.mu1 + 3, self.sig)
clst5 = DPCluster(0.5, self.mu1 + 5, self.sig)
clst7 = DPCluster(0.5, self.mu1 + 7, self.sig)
clst2 = DPCluster(0.5, self.mu2 + 2, self.sig)
clst4 = DPCluster(0.5, self.mu2 + 4, self.sig)
clst6 = DPCluster(0.5, self.mu2 + 6, self.sig)
clst8 = DPCluster(0.5, self.mu2 + 8, self.sig)
lt = {}
for i in range(8):
lt[i] = i
mix = OrderedDPMixture([clst1, clst2, clst3, clst4, clst5, clst6, clst7, clst8], lt, niter=4)
new_r = mix.last()
assert len(new_r.clusters) == 2
assert all(new_r.clusters[0].mu == clst7.mu)
assert all(new_r.clusters[1].mu == clst8.mu)
new_r = mix.last(2)
assert len(new_r.clusters) == 4
assert all(new_r.clusters[0].mu == clst5.mu)
assert all(new_r.clusters[1].mu == clst6.mu)
assert all(new_r.clusters[2].mu == clst7.mu)
assert all(new_r.clusters[3].mu == clst8.mu)
def setUp(self):
self.mu1 = array([0, 0, 0])
self.sig = eye(3)
self.mu2 = array([5, 5, 5])
self.clust1 = DPCluster(.5 / 3, self.mu1, self.sig)
self.clust2 = DPCluster(.5 / 3, self.mu2, self.sig)
self.clusters = [
self.clust1, self.clust2, self.clust1, self.clust2, self.clust1,
self.clust2
]
self.lookup = {0: 1, 1: 2, 2: 3, 3: 4, 4: 5, 5: 5}
self.mix = OrderedDPMixture(self.clusters,
self.lookup,
niter=3,
identified=True)
def setUp(self):
self.mu1 = array([0, 0, 0])
self.sig = eye(3)
self.mu2 = array([5, 5, 5])
self.clust1 = DPCluster(.5 / 3, self.mu1, self.sig)
self.clust2 = DPCluster(.5 / 3, self.mu2, self.sig)
self.clusters = [self.clust1, self.clust2, self.clust1, self.clust2,
self.clust1, self.clust2]
self.lookup = {0:1, 1:2, 2:3, 3:4, 4:5, 5:5}
self.mix = OrderedDPMixture(self.clusters, self.lookup, niter=3, identified=True)
def testAverage(self):
clst1 = DPCluster(0.5, self.mu1, self.sig)
clst3 = DPCluster(0.5, self.mu1, self.sig)
clst5 = DPCluster(0.5, self.mu1, self.sig)
clst7 = DPCluster(0.5, self.mu1, self.sig)
clst2 = DPCluster(0.5, self.mu2, self.sig)
clst4 = DPCluster(0.5, self.mu2, self.sig)
clst6 = DPCluster(0.5, self.mu2, self.sig)
clst8 = DPCluster(0.5, self.mu2, self.sig)
lt = {}
for i in range(8):
lt[i] = i
mix = OrderedDPMixture([clst1, clst2, clst3, clst4, clst5, clst6, clst7, clst8], lt, niter=4)
avg = mix.average()
assert len(avg.clusters) == 2
assert all(avg.mus[0] == self.mu1)
assert all(avg.mus[1] == self.mu2)
assert all(avg.sigmas[0] == self.sig)
assert all(avg.sigmas[1] == self.sig)
assert avg.pis[0] == 0.5, 'pis should be 0.5 but is %f' % avg.pis()[0]
assert avg.pis[1] == 0.5, 'pis should be 0.5 but is %f' % avg.pis()[0]
class OrderedDp_mixtureTestCase(unittest.TestCase):
def setUp(self):
self.mu1 = array([0, 0, 0])
self.sig = eye(3)
self.mu2 = array([5, 5, 5])
self.clust1 = DPCluster(.5 / 3, self.mu1, self.sig)
self.clust2 = DPCluster(.5 / 3, self.mu2, self.sig)
self.clusters = [
self.clust1, self.clust2, self.clust1, self.clust2, self.clust1,
self.clust2
]
self.lookup = {0: 1, 1: 2, 2: 3, 3: 4, 4: 5, 5: 5}
self.mix = OrderedDPMixture(self.clusters,
self.lookup,
niter=3,
identified=True)
def tearDown(self):
pass
def testprob(self):
pnt = array([1, 1, 1])
for i in [self.clust1, self.clust2]:
assert i.prob(pnt) <= 1, 'prob of clst %s is > 1' % i
assert i.prob(pnt) >= 0, 'prob of clst %s is < 0' % i
def testmixprob(self):
pnt = array([1, 1, 1])
assert self.mix.prob(pnt)[0] == self.clust1.prob(
pnt), 'mixture generates different prob then compoent 1'
assert self.mix.prob(pnt)[1] == self.clust2.prob(
pnt), 'mixture generates different prob then compoent 2'
def testclassify(self):
pnt = array([self.mu1, self.mu2])
assert self.mix.classify(pnt)[0] == self.lookup[
0], 'classify classifys mu1 as belonging to something else'
assert self.mix.classify(pnt)[1] == self.lookup[
1], 'classify classifys m21 as belonging to something else'
def testMakeModal(self):
modal = self.mix.make_modal()
# modal = ModalDPMixture([self.clst1, self.clst2],
# { 0: [0], 1: [1]},
# [self.mu1, self.mu2])
pnt = array([self.mu1, self.mu2])
assert modal.classify(
array([self.mu1, self.mu2, self.mu1, self.mu2, self.mu1,
self.mu2])).tolist() in [[1, 0, 1, 0, 1, 0],
[0, 1, 0, 1, 0,
1]], 'classify not working'
# assert self.mix.classify(self.mu1) == self.lookup[modal.classify(self.mu1)], 'derived modal mixture is wrong'
# assert self.mix.classify(pnt)[0] == self.lookup[modal.classify(pnt)[0]], 'derived modal mixture is wrong'
# assert self.mix.classify(pnt)[1] == self.lookup[modal.classify(pnt)[1]], 'derived modal mixture is wrong'
modal = self.mix.make_modal(delta=9)
assert modal.classify(
array([self.mu1, self.mu2, self.mu1, self.mu2, self.mu1,
self.mu2])).tolist() == [0, 0, 0, 0, 0,
0], 'classify not working'
def testAverage(self):
clst1 = DPCluster(0.5, self.mu1, self.sig)
clst3 = DPCluster(0.5, self.mu1, self.sig)
clst5 = DPCluster(0.5, self.mu1, self.sig)
clst7 = DPCluster(0.5, self.mu1, self.sig)
clst2 = DPCluster(0.5, self.mu2, self.sig)
clst4 = DPCluster(0.5, self.mu2, self.sig)
clst6 = DPCluster(0.5, self.mu2, self.sig)
clst8 = DPCluster(0.5, self.mu2, self.sig)
lt = {}
for i in range(8):
lt[i] = i
mix = OrderedDPMixture(
[clst1, clst2, clst3, clst4, clst5, clst6, clst7, clst8],
lt,
niter=4)
avg = mix.average()
assert len(avg.clusters) == 2
assert all(avg.mus[0] == self.mu1)
assert all(avg.mus[1] == self.mu2)
assert all(avg.sigmas[0] == self.sig)
assert all(avg.sigmas[1] == self.sig)
assert avg.pis[0] == 0.5, 'pis should be 0.5 but is %f' % avg.pis()[0]
assert avg.pis[1] == 0.5, 'pis should be 0.5 but is %f' % avg.pis()[0]
def testLast(self):
clst1 = DPCluster(0.5, self.mu1, self.sig)
clst3 = DPCluster(0.5, self.mu1 + 3, self.sig)
clst5 = DPCluster(0.5, self.mu1 + 5, self.sig)
clst7 = DPCluster(0.5, self.mu1 + 7, self.sig)
clst2 = DPCluster(0.5, self.mu2 + 2, self.sig)
clst4 = DPCluster(0.5, self.mu2 + 4, self.sig)
clst6 = DPCluster(0.5, self.mu2 + 6, self.sig)
clst8 = DPCluster(0.5, self.mu2 + 8, self.sig)
lt = {}
for i in range(8):
lt[i] = i
mix = OrderedDPMixture(
[clst1, clst2, clst3, clst4, clst5, clst6, clst7, clst8],
lt,
niter=4)
new_r = mix.last()
assert len(new_r.clusters) == 2
assert all(new_r.clusters[0].mu == clst7.mu)
assert all(new_r.clusters[1].mu == clst8.mu)
new_r = mix.last(2)
assert len(new_r.clusters) == 4
assert all(new_r.clusters[0].mu == clst5.mu)
assert all(new_r.clusters[1].mu == clst6.mu)
assert all(new_r.clusters[2].mu == clst7.mu)
assert all(new_r.clusters[3].mu == clst8.mu)
try:
new_r = mix.last(10)
except ValueError:
pass
def testDraw(self):
x = self.mix.draw(10)
assert x.shape[0] == 10, "Number of drawed rows is wrong"
assert x.shape[1] == 3, "number of drawed columns is wrong"
def testarith(self):
adder = 3
array_adder = array([1, 2, 3])
# add
b = self.mix + adder
self.assertIsInstance(b, OrderedDPMixture,
'integer addition return wrong type')
assert_equal(b.mus[0], self.mix.mus[0] + adder,
'integer addition returned wrong value')
c = self.mix + array_adder
self.assertIsInstance(c, OrderedDPMixture,
'array addition return wrong type')
assert_array_equal(c.mus[0], self.mix.mus[0] + array_adder,
'array addition returned wrong value')
# radd
b = adder + self.mix
self.assertIsInstance(b, OrderedDPMixture,
'integer addition return wrong type')
assert_array_equal(b.mus[0], adder + self.mix.mus[0],
'integer addition returned wrong value')
c = array_adder + self.mix
self.assertIsInstance(c, OrderedDPMixture,
'array addition return wrong type')
assert_array_equal(c.mus[0], array_adder + self.mix.mus[0],
'array addition returned wrong value')
# sub
b = self.mix - adder
self.assertIsInstance(b, OrderedDPMixture,
'integer subtraction return wrong type')
assert_array_equal(b.mus[0], self.mix.mus[0] - adder,
'integer subtraction returned wrong value')
c = self.mix - array_adder
self.assertIsInstance(c, OrderedDPMixture,
'array subtraction return wrong type')
assert_array_equal(c.mus[0], self.mix.mus[0] - array_adder,
'array subtraction returned wrong value')
# rsub
b = adder - self.mix
self.assertIsInstance(b, OrderedDPMixture,
'integer subtraction return wrong type')
assert_array_equal(b.mus[0], adder - self.mix.mus[0],
'integer subtraction returned wrong value')
c = array_adder - self.mix
self.assertIsInstance(c, OrderedDPMixture,
'array subtraction return wrong type')
assert_array_equal(c.mus[0], array_adder - self.mix.mus[0],
'array subtraction returned wrong value')
# mul
b = self.mix * adder
self.assertIsInstance(b, OrderedDPMixture,
'integer multiplication return wrong type')
assert_array_equal(b.mus[0], self.mix.mus[0] * adder,
'integer multiplication returned wrong value')
c = self.mix * array_adder
self.assertIsInstance(c, OrderedDPMixture,
'array multiplicaton return wrong type')
assert_array_equal(c.mus[0], dot(self.mix.mus[0], array_adder),
'array multiplication returned wrong value')
# rmul
b = adder * self.mix
self.assertIsInstance(b, OrderedDPMixture,
'integer multiplication return wrong type')
assert_array_equal(b.mus[0], adder * self.mix.mus[0],
'integer multiplication returned wrong value')
c = array_adder * self.mix
self.assertIsInstance(c, OrderedDPMixture,
'array multiplication return wrong type')
assert_array_equal(c.mus[0], dot(array_adder, self.mix.mus[0]),
'array multiplication returned wrong value')
def testgetitem(self):
assert_equal(self.mu1, self.mix[0].mu, 'getitem failed')
self.mix[0] = self.clust2
assert_equal(self.mu2, self.mix[0].mu, 'getitem failed')
self.mix[0] = self.clust1
def testgetiteration(self):
self.assertIsInstance(self.mix.get_iteration(2), DPMixture,
'get_iteration failed')
self.assertEqual(len(self.mix.get_iteration(2).clusters), 2,
'get_iteration return wrong number of clusters')
self.assertIsInstance(self.mix.get_iteration([0, 2]), DPMixture,
'get_iteration failed')
self.assertEqual(len(self.mix.get_iteration([0, 2]).clusters), 4,
'get_iteration return wrong number of clusters')
def testEnumerateClusters(self):
k = 0
for i, j in self.mix.enumerate_clusters():
self.assertIsInstance(i, int)
self.assertEqual(i, self.lookup[k],
'failed to return the right number')
self.assertIs(
j, self.mix[k],
'fialed to return the right cluster when enumerating')
k += 1
def testEnumeratePis(self):
k = 0
for i, j in self.mix.enumerate_pis():
self.assertIsInstance(i, int)
self.assertEqual(i, self.lookup[k],
'failed to return the right number')
self.assertIs(j, self.mix[k].pi,
'fialed to return the right pi when enumerating')
k += 1
def testEnumerateMus(self):
k = 0
for i, j in self.mix.enumerate_mus():
self.assertIsInstance(i, int)
self.assertEqual(i, self.lookup[k],
'failed to return the right number')
self.assertIs(j, self.mix[k].mu,
'fialed to return the right mean when enumerating')
k += 1
def testEnumerateSigmas(self):
k = 0
for i, j in self.mix.enumerate_sigmas():
self.assertIsInstance(i, int)
self.assertEqual(i, self.lookup[k],
'failed to return the right number')
self.assertIs(
j, self.mix[k].sigma,
'fialed to return the right covariance when enumerating')
k += 1
class OrderedDPMixtureTestCase(unittest.TestCase):
def setUp(self):
self.mu1 = array([0, 0, 0])
self.sig = eye(3)
self.mu2 = array([5, 5, 5])
self.clust1 = DPCluster(.5/3, self.mu1, self.sig)
self.clust2 = DPCluster(.5/3, self.mu2, self.sig)
self.clusters = [self.clust1, self.clust2, self.clust1, self.clust2,
self.clust1, self.clust2]
self.lookup = {0:1, 1:2, 2:3, 3:4, 4:5, 5:5}
self.mix = OrderedDPMixture(
self.clusters,
self.lookup,
niter=3,
identified=True)
def tearDown(self):
pass
def testprob(self):
pnt = array([1, 1, 1])
for i in [self.clust1, self.clust2]:
assert i.prob(pnt) <= 1, 'prob of clst %s is > 1' % i
assert i.prob(pnt) >= 0, 'prob of clst %s is < 0' % i
def testmixprob(self):
pnt = array([1, 1, 1])
assert self.mix.prob(pnt)[0] == self.clust1.prob(pnt), 'mixture generates different prob then compoent 1'
assert self.mix.prob(pnt)[1] == self.clust2.prob(pnt), 'mixture generates different prob then compoent 2'
def testclassify(self):
pnt = array([self.mu1, self.mu2])
assert self.mix.classify(pnt)[0] == self.lookup[0], 'classify classifys mu1 as belonging to something else'
assert self.mix.classify(pnt)[1] == self.lookup[1], 'classify classifys m21 as belonging to something else'
def testMakeModal(self):
modal = self.mix.make_modal()
pnt = array([self.mu1, self.mu2])
assert modal.classify(array([self.mu1, self.mu2, self.mu1, self.mu2, self.mu1, self.mu2])).tolist() == [ 0, 1, 0, 1, 0, 1], 'classify not working'
assert self.mix.classify(self.mu1) == self.lookup[modal.classify(self.mu1)], 'derived modal mixture is wrong'
assert self.mix.classify(pnt)[0] == self.lookup[modal.classify(pnt)[0]], 'derived modal mixture is wrong'
assert self.mix.classify(pnt)[1] == self.lookup[modal.classify(pnt)[1]], 'derived modal mixture is wrong'
modal = self.mix.make_modal(delta=9)
assert modal.classify(array([self.mu1, self.mu2, self.mu1, self.mu2, self.mu1, self.mu2])).tolist() == [0, 0, 0, 0, 0, 0], 'classify not working'
def testAverage(self):
clst1 = DPCluster(0.5, self.mu1, self.sig)
clst3 = DPCluster(0.5, self.mu1, self.sig)
clst5 = DPCluster(0.5, self.mu1, self.sig)
clst7 = DPCluster(0.5, self.mu1, self.sig)
clst2 = DPCluster(0.5, self.mu2, self.sig)
clst4 = DPCluster(0.5, self.mu2, self.sig)
clst6 = DPCluster(0.5, self.mu2, self.sig)
clst8 = DPCluster(0.5, self.mu2, self.sig)
lt = {}
for i in range(8):
lt[i] = i
mix = OrderedDPMixture([clst1, clst2, clst3, clst4, clst5, clst6, clst7, clst8], lt, niter=4)
avg = mix.average()
assert len(avg.clusters) == 2
assert all(avg.mus[0] == self.mu1)
assert all(avg.mus[1] == self.mu2)
assert all(avg.sigmas[0] == self.sig)
assert all(avg.sigmas[1] == self.sig)
assert avg.pis[0] == 0.5, 'pis should be 0.5 but is %f' % avg.pis()[0]
assert avg.pis[1] == 0.5, 'pis should be 0.5 but is %f' % avg.pis()[0]
def testLast(self):
clst1 = DPCluster(0.5, self.mu1, self.sig)
clst3 = DPCluster(0.5, self.mu1 + 3, self.sig)
clst5 = DPCluster(0.5, self.mu1 + 5, self.sig)
clst7 = DPCluster(0.5, self.mu1 + 7, self.sig)
clst2 = DPCluster(0.5, self.mu2 + 2, self.sig)
clst4 = DPCluster(0.5, self.mu2 + 4, self.sig)
clst6 = DPCluster(0.5, self.mu2 + 6, self.sig)
clst8 = DPCluster(0.5, self.mu2 + 8, self.sig)
lt = {}
for i in range(8):
lt[i] = i
mix = OrderedDPMixture([clst1, clst2, clst3, clst4, clst5, clst6, clst7, clst8], lt, niter=4)
new_r = mix.last()
assert len(new_r.clusters) == 2
assert all(new_r.clusters[0].mu == clst7.mu)
assert all(new_r.clusters[1].mu == clst8.mu)
new_r = mix.last(2)
assert len(new_r.clusters) == 4
assert all(new_r.clusters[0].mu == clst5.mu)
assert all(new_r.clusters[1].mu == clst6.mu)
assert all(new_r.clusters[2].mu == clst7.mu)
assert all(new_r.clusters[3].mu == clst8.mu)
def testDraw(self):
x = self.mix.draw(10)
assert x.shape[0] == 10, "Number of drawed rows is wrong"
assert x.shape[1] == 3, "number of drawed columns is wrong"
def testarith(self):
adder = 3
array_adder = array([1, 2, 3])
# add
b = self.mix + adder
self.assertIsInstance(b, OrderedDPMixture, 'integer addition return wrong type')
assert_equal(b.mus[0], self.mix.mus[0] + adder,
'integer addition returned wrong value')
c = self.mix + array_adder
self.assertIsInstance(c, OrderedDPMixture, 'array addition return wrong type')
assert_array_equal(c.mus[0], self.mix.mus[0] + array_adder,
'array addition returned wrong value')
# radd
b = adder + self.mix
self.assertIsInstance(b, OrderedDPMixture, 'integer addition return wrong type')
assert_array_equal(b.mus[0], adder + self.mix.mus[0],
'integer addition returned wrong value')
c = array_adder + self.mix
self.assertIsInstance(c, OrderedDPMixture, 'array addition return wrong type')
assert_array_equal(c.mus[0], array_adder + self.mix.mus[0],
'array addition returned wrong value')
# sub
b = self.mix - adder
self.assertIsInstance(b, OrderedDPMixture, 'integer subtraction return wrong type')
assert_array_equal(b.mus[0], self.mix.mus[0] - adder,
'integer subtraction returned wrong value')
c = self.mix - array_adder
self.assertIsInstance(c, OrderedDPMixture, 'array subtraction return wrong type')
assert_array_equal(c.mus[0], self.mix.mus[0] - array_adder,
'array subtraction returned wrong value')
# rsub
b = adder - self.mix
self.assertIsInstance(b, OrderedDPMixture, 'integer subtraction return wrong type')
assert_array_equal(b.mus[0], adder - self.mix.mus[0],
'integer subtraction returned wrong value')
c = array_adder - self.mix
self.assertIsInstance(c, OrderedDPMixture, 'array subtraction return wrong type')
assert_array_equal(c.mus[0], array_adder - self.mix.mus[0],
'array subtraction returned wrong value')
# mul
b = self.mix * adder
self.assertIsInstance(b, OrderedDPMixture, 'integer multiplication return wrong type')
assert_array_equal(b.mus[0], self.mix.mus[0] * adder,
'integer multiplication returned wrong value')
c = self.mix * array_adder
self.assertIsInstance(c, OrderedDPMixture, 'array multiplicaton return wrong type')
assert_array_equal(c.mus[0], dot(self.mix.mus[0], array_adder),
'array multiplication returned wrong value')
# rmul
b = adder * self.mix
self.assertIsInstance(b, OrderedDPMixture, 'integer multiplication return wrong type')
assert_array_equal(b.mus[0], adder * self.mix.mus[0],
'integer multiplication returned wrong value')
c = array_adder * self.mix
self.assertIsInstance(c, OrderedDPMixture, 'array multiplication return wrong type')
assert_array_equal(c.mus[0], dot(array_adder, self.mix.mus[0]),
'array multiplication returned wrong value')
def testgetitem(self):
assert_equal(self.mu1, self.mix[0].mu, 'getitem failed')
self.mix[0] = self.clust2
assert_equal(self.mu2, self.mix[0].mu, 'getitem failed')
self.mix[0] = self.clust1
def testgetiteration(self):
self.assertIsInstance(self.mix.get_iteration(2), DPMixture,
'get_iteration failed')
self.assertEqual(len(self.mix.get_iteration(2).clusters), 2,
'get_iteration return wrong number of clusters')
self.assertIsInstance(self.mix.get_iteration([0,2]), DPMixture,
'get_iteration failed')
self.assertEqual(len(self.mix.get_iteration([0,2]).clusters), 4,
'get_iteration return wrong number of clusters')
def testEnumerateClusters(self):
k = 0
for i,j in self.mix.enumerate_clusters():
self.assertIsInstance(i, int)
self.assertEqual(i, self.lookup[k], 'failed to return the right number')
self.assertIs(j, self.mix[k], 'failed to return the right cluster when enumerating')
k += 1
def testEnumeratePis(self):
k = 0
for i,j in self.mix.enumerate_pis():
self.assertIsInstance(i, int)
self.assertEqual(i, self.lookup[k], 'failed to return the right number')
self.assertIs(j, self.mix[k].pi, 'failed to return the right pi when enumerating')
k += 1
def testEnumerateMus(self):
k = 0
for i, j in self.mix.enumerate_mus():
self.assertIsInstance(i, int)
self.assertEqual(i, self.lookup[k], 'failed to return the right number')
self.assertIs(j, self.mix[k].mu, 'failed to return the right mean when enumerating')
k += 1
def testEnumerateSigmas(self):
k = 0
for i, j in self.mix.enumerate_sigmas():
self.assertIsInstance(i, int)
self.assertEqual(i, self.lookup[k], 'failed to return the right number')
self.assertIs(j, self.mix[k].sigma, 'failed to return the right covariance when enumerating')
k += 1
