class DPMixtureTestCase(unittest.TestCase):
def setUp(self):
self.mu1 = array([0, 0, 0])
self.sig = eye(3)
self.mu2 = array([5, 5, 5])
self.cluster1 = DPCluster(.5 / 3, self.mu1, self.sig)
self.cluster2 = DPCluster(.5 / 3, self.mu2, self.sig)
self.clusters = [
self.cluster1, self.cluster2, self.cluster1, self.cluster2,
self.cluster1, self.cluster2
]
self.mix = DPMixture(self.clusters, niter=3, identified=True)
def tearDown(self):
pass
def test_prob(self):
pnt = array([[1, 1, 1]])
for i in [self.cluster1, self.cluster2]:
assert i.prob(pnt) <= 1, 'prob of cluster %s is > 1' % i
assert i.prob(pnt) >= 0, 'prob of cluster %s is < 0' % i
def test_mix_prob(self):
pnt = array([1, 1, 1])
assert self.mix.prob(pnt)[0] == \
self.cluster1.prob(pnt), \
'mixture generates different prob then component 1'
assert self.mix.prob(pnt)[1] == \
self.cluster2.prob(pnt), \
'mixture generates different prob then component 2'
def test_classify(self):
pnt = array([self.mu1, self.mu2])
assert self.mix.classify(pnt)[0] == \
0, \
'classify classifies mu1 as belonging to something else'
assert self.mix.classify(pnt)[1] == \
1, \
'classify classifies m21 as belonging to something else'
def test_make_modal(self):
modal = self.mix.make_modal()
assert modal.classify(
array([self.mu1, self.mu2, self.mu1, self.mu2, self.mu1,
self.mu2])).tolist() == [1, 0, 1, 0, 1,
0], 'classify not working'
#TODO do actual lookup.
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 test_average(self):
cluster1 = DPCluster(0.5, self.mu1, self.sig)
cluster3 = DPCluster(0.5, self.mu1, self.sig)
cluster5 = DPCluster(0.5, self.mu1, self.sig)
cluster7 = DPCluster(0.5, self.mu1, self.sig)
cluster2 = DPCluster(0.5, self.mu2, self.sig)
cluster4 = DPCluster(0.5, self.mu2, self.sig)
cluster6 = DPCluster(0.5, self.mu2, self.sig)
cluster8 = DPCluster(0.5, self.mu2, self.sig)
mix = DPMixture([
cluster1, cluster2, cluster3, cluster4, cluster5, cluster6,
cluster7, cluster8
],
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 test_last(self):
cluster1 = DPCluster(0.5, self.mu1, self.sig)
cluster3 = DPCluster(0.5, self.mu1 + 3, self.sig)
cluster5 = DPCluster(0.5, self.mu1 + 5, self.sig)
cluster7 = DPCluster(0.5, self.mu1 + 7, self.sig)
cluster2 = DPCluster(0.5, self.mu2 + 2, self.sig)
cluster4 = DPCluster(0.5, self.mu2 + 4, self.sig)
cluster6 = DPCluster(0.5, self.mu2 + 6, self.sig)
cluster8 = DPCluster(0.5, self.mu2 + 8, self.sig)
mix = DPMixture([
cluster1, cluster2, cluster3, cluster4, cluster5, cluster6,
cluster7, cluster8
],
niter=4)
new_r = mix.last()
assert len(new_r.clusters) == 2
assert all(new_r.clusters[0].mu == cluster7.mu)
assert all(new_r.clusters[1].mu == cluster8.mu)
new_r = mix.last(2)
assert len(new_r.clusters) == 4
assert all(new_r.clusters[0].mu == cluster5.mu)
assert all(new_r.clusters[1].mu == cluster6.mu)
assert all(new_r.clusters[2].mu == cluster7.mu)
assert all(new_r.clusters[3].mu == cluster8.mu)
def test_draw(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 test_arithmetic(self):
adder = 3
array_adder = array([1, 2, 3])
mat_adder = 2 * eye(3)
# add
b = self.mix + adder
self.assertIsInstance(b, DPMixture,
'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, DPMixture, '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, DPMixture,
'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, DPMixture, '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, DPMixture,
'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, DPMixture,
'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, DPMixture,
'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, DPMixture,
'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, DPMixture,
'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, DPMixture,
'array multiplication return wrong type')
assert_array_equal(c.mus[0], dot(self.mix.mus[0], array_adder),
'array multiplication returned wrong value')
d = self.mix * mat_adder
self.assertIsInstance(d, DPMixture,
'array multiplication return wrong type')
assert_array_equal(d.mus[0], dot(self.mix.mus[0], mat_adder),
'array multiplication returned wrong value')
# rmul
b = adder * self.mix
self.assertIsInstance(b, DPMixture,
'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, DPMixture,
'array multiplication return wrong type')
assert_array_equal(c.mus[0], dot(array_adder, self.mix.mus[0]),
'array multiplication returned wrong value')
d = mat_adder * self.mix
self.assertIsInstance(d, DPMixture,
'array multiplication return wrong type')
assert_array_equal(d.mus[0], dot(mat_adder, self.mix.mus[0]),
'array multiplication returned wrong value')
assert_array_equal(d.sigmas[0],
dot(mat_adder, dot(self.mix.sigmas[0], mat_adder)),
'array multiplication failed')
def test_get_item(self):
assert_equal(self.mu1, self.mix[0].mu, 'getitem failed')
self.mix[0] = self.cluster2
assert_equal(self.mu2, self.mix[0].mu, 'getitem failed')
self.mix[0] = self.cluster1
def test_get_iteration(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 test_enumerate_clusters(self):
for i, j in self.mix.enumerate_clusters():
self.assertIsInstance(i, int)
self.assertIs(
j, self.mix[i],
'failed to return the right cluster when enumerating')
def test_enumerate_pis(self):
for i, j in self.mix.enumerate_pis():
self.assertIsInstance(i, int)
self.assertIs(j, self.mix[i].pi,
'failed to return the right pi when enumerating')
def test_enumerate_mus(self):
for i, j in self.mix.enumerate_mus():
self.assertIsInstance(i, int)
self.assertIs(j, self.mix[i].mu,
'failed to return the right mean when enumerating')
def test_enumerate_sigmas(self):
for i, j in self.mix.enumerate_sigmas():
self.assertIsInstance(i, int)
self.assertIs(
j, self.mix[i].sigma,
'failed to return the right covariance when enumerating')
class Dp_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.mix = DPMixture(self.clusters, niter=3, identified=True)
def tearDown(self):
pass
def testprob(self):
pnt = array([[1, 1, 1]])
print pnt.shape
for i in [self.clust1, self.clust2]:
print i.prob(pnt)
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] == 0, 'classify classifys mu1 as belonging to something else'
assert self.mix.classify(pnt)[1] == 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() == [1, 0, 1, 0, 1, 0], 'classify not working'
# TODO do actual lookup.
# assert self.mix.classify(self.mu1) == modal.classify(self.mu1), 'derived modal mixture is wrong'
# assert self.mix.classify(pnt)[0] == modal.classify(pnt)[0], 'derived modal mixture is wrong'
# assert self.mix.classify(pnt)[1] == 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)
mix = DPMixture([clst1, clst2, clst3, clst4, clst5, clst6, clst7, clst8], 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)
mix = DPMixture([clst1, clst2, clst3, clst4, clst5, clst6, clst7, clst8], 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])
mat_adder = 2 * eye(3)
# add
b = self.mix + adder
self.assertIsInstance(b, DPMixture, '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, DPMixture, '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, DPMixture, '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, DPMixture, '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, DPMixture, '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, DPMixture, '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, DPMixture, '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, DPMixture, '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, DPMixture, '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, DPMixture, 'array multiplicaton return wrong type')
assert_array_equal(c.mus[0], dot(self.mix.mus[0], array_adder),
'array multiplication returned wrong value')
d = self.mix * mat_adder
self.assertIsInstance(d, DPMixture, 'array multiplicaton return wrong type')
assert_array_equal(d.mus[0], dot(self.mix.mus[0], mat_adder),
'array multiplication returned wrong value')
# rmul
b = adder * self.mix
self.assertIsInstance(b, DPMixture, '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, DPMixture, 'array multiplication return wrong type')
assert_array_equal(c.mus[0], dot(array_adder, self.mix.mus[0]),
'array multiplication returned wrong value')
d = mat_adder * self.mix
self.assertIsInstance(d, DPMixture, 'array multiplicaton return wrong type')
assert_array_equal(d.mus[0], dot(mat_adder, self.mix.mus[0]),
'array multiplication returned wrong value')
assert_array_equal(d.sigmas[0], dot(mat_adder, dot(self.mix.sigmas[0], mat_adder)),
'array multiplcation failed')
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):
for i, j in self.mix.enumerate_clusters():
self.assertIsInstance(i, int)
self.assertIs(j, self.mix[i], 'fialed to return the right cluster when enumerating')
def testEnumeratePis(self):
for i, j in self.mix.enumerate_pis():
self.assertIsInstance(i, int)
self.assertIs(j, self.mix[i].pi, 'fialed to return the right pi when enumerating')
def testEnumerateMus(self):
for i, j in self.mix.enumerate_mus():
self.assertIsInstance(i, int)
self.assertIs(j, self.mix[i].mu, 'fialed to return the right mean when enumerating')
def testEnumerateSigmas(self):
for i, j in self.mix.enumerate_sigmas():
self.assertIsInstance(i, int)
self.assertIs(j, self.mix[i].sigma, 'fialed to return the right covariance when enumerating')
class Dp_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.mix = DPMixture(self.clusters, niter=3, identified=True)
def tearDown(self):
pass
def testprob(self):
pnt = array([[1, 1, 1]])
print pnt.shape
for i in [self.clust1, self.clust2]:
print i.prob(pnt)
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] == 0, 'classify classifys mu1 as belonging to something else'
assert self.mix.classify(pnt)[
1] == 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'
# TODO do actual lookup.
# assert self.mix.classify(self.mu1) == modal.classify(self.mu1), 'derived modal mixture is wrong'
# assert self.mix.classify(pnt)[0] == modal.classify(pnt)[0], 'derived modal mixture is wrong'
# assert self.mix.classify(pnt)[1] == 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)
mix = DPMixture(
[clst1, clst2, clst3, clst4, clst5, clst6, clst7, clst8], 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)
mix = DPMixture(
[clst1, clst2, clst3, clst4, clst5, clst6, clst7, clst8], 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])
mat_adder = 2 * eye(3)
# add
b = self.mix + adder
self.assertIsInstance(b, DPMixture,
'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, DPMixture, '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, DPMixture,
'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, DPMixture, '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, DPMixture,
'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, DPMixture,
'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, DPMixture,
'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, DPMixture,
'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, DPMixture,
'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, DPMixture,
'array multiplicaton return wrong type')
assert_array_equal(c.mus[0], dot(self.mix.mus[0], array_adder),
'array multiplication returned wrong value')
d = self.mix * mat_adder
self.assertIsInstance(d, DPMixture,
'array multiplicaton return wrong type')
assert_array_equal(d.mus[0], dot(self.mix.mus[0], mat_adder),
'array multiplication returned wrong value')
# rmul
b = adder * self.mix
self.assertIsInstance(b, DPMixture,
'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, DPMixture,
'array multiplication return wrong type')
assert_array_equal(c.mus[0], dot(array_adder, self.mix.mus[0]),
'array multiplication returned wrong value')
d = mat_adder * self.mix
self.assertIsInstance(d, DPMixture,
'array multiplicaton return wrong type')
assert_array_equal(d.mus[0], dot(mat_adder, self.mix.mus[0]),
'array multiplication returned wrong value')
assert_array_equal(d.sigmas[0],
dot(mat_adder, dot(self.mix.sigmas[0], mat_adder)),
'array multiplcation failed')
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):
for i, j in self.mix.enumerate_clusters():
self.assertIsInstance(i, int)
self.assertIs(
j, self.mix[i],
'fialed to return the right cluster when enumerating')
def testEnumeratePis(self):
for i, j in self.mix.enumerate_pis():
self.assertIsInstance(i, int)
self.assertIs(j, self.mix[i].pi,
'fialed to return the right pi when enumerating')
def testEnumerateMus(self):
for i, j in self.mix.enumerate_mus():
self.assertIsInstance(i, int)
self.assertIs(j, self.mix[i].mu,
'fialed to return the right mean when enumerating')
def testEnumerateSigmas(self):
for i, j in self.mix.enumerate_sigmas():
self.assertIsInstance(i, int)
self.assertIs(
j, self.mix[i].sigma,
'fialed to return the right covariance when enumerating')