def test_attributes(self):
h = hmm.MultinomialHMM(self.n_components)
self.assertEqual(h.n_components, self.n_components)
h.startprob_ = self.startprob
h.transmat_ = self.transmat
h.emissionprob_ = self.emissionprob
assert_array_almost_equal(h.emissionprob_, self.emissionprob)
with assert_raises(ValueError):
h.emissionprob_ = []
h._check()
with assert_raises(ValueError):
h.emissionprob_ = np.zeros(
(self.n_components - 2, self.n_features))
h._check()
def test_attributes(self):
h = hmm.MultinomialHMM(self.n_components)
self.assertEqual(h.n_components, self.n_components)
h.startprob_ = self.startprob
h.transmat_ = self.transmat
h.emissionprob_ = self.emissionprob
assert_array_almost_equal(h.emissionprob_, self.emissionprob)
with assert_raises(ValueError):
h.emissionprob_ = []
h._check()
with assert_raises(ValueError):
h.emissionprob_ = np.zeros((self.n_components - 2,
self.n_features))
h._check()
def test_bad_covariance_type(self):
with assert_raises(ValueError):
h = hmm.GaussianHMM(20, covariance_type='badcovariance_type')
h.means_ = self.means
h.covars_ = []
h.startprob_ = self.startprob
h.transmat_ = self.transmat
h._check()
def test_bad_covariance_type(self):
with assert_raises(ValueError):
h = hmm.GaussianHMM(20, covariance_type='badcovariance_type')
h.means_ = self.means
h.covars_ = []
h.startprob_ = self.startprob
h.transmat_ = self.transmat
h._check()
def test_base_hmm_attributes(self):
n_components = 20
startprob = self.prng.rand(n_components)
startprob = startprob / startprob.sum()
transmat = self.prng.rand(n_components, n_components)
transmat /= np.tile(
transmat.sum(axis=1)[:, np.newaxis], (1, n_components))
h = StubHMM(n_components)
self.assertEqual(h.n_components, n_components)
h.startprob_ = startprob
assert_array_almost_equal(h.startprob_, startprob)
with assert_raises(ValueError):
h.startprob_ = 2 * startprob
h._check()
with assert_raises(ValueError):
h.startprob_ = []
h._check()
with assert_raises(ValueError):
h.startprob_ = np.zeros((n_components - 2, 2))
h._check()
h.startprob_ = startprob
h.transmat_ = transmat
assert_array_almost_equal(h.transmat_, transmat)
with assert_raises(ValueError):
h.transmat_ = 2 * transmat
h._check()
with assert_raises(ValueError):
h.transmat_ = []
h._check()
with assert_raises(ValueError):
h.transmat_ = np.zeros((n_components - 2, n_components))
h._check()
def test_base_hmm_attributes(self):
n_components = 20
startprob = self.prng.rand(n_components)
startprob = startprob / startprob.sum()
transmat = self.prng.rand(n_components, n_components)
transmat /= np.tile(transmat.sum(axis=1)
[:, np.newaxis], (1, n_components))
h = StubHMM(n_components)
self.assertEqual(h.n_components, n_components)
h.startprob_ = startprob
assert_array_almost_equal(h.startprob_, startprob)
with assert_raises(ValueError):
h.startprob_ = 2 * startprob
h._check()
with assert_raises(ValueError):
h.startprob_ = []
h._check()
with assert_raises(ValueError):
h.startprob_ = np.zeros((n_components - 2, 2))
h._check()
h.startprob_ = startprob
h.transmat_ = transmat
assert_array_almost_equal(h.transmat_, transmat)
with assert_raises(ValueError):
h.transmat_ = 2 * transmat
h._check()
with assert_raises(ValueError):
h.transmat_ = []
h._check()
with assert_raises(ValueError):
h.transmat_ = np.zeros((n_components - 2, n_components))
h._check()
