def test_expected_counts(self):
p0 = self.mu
T = self.T
N = 20
EC_n = expected_counts(T, p0, N)
"""
If p0 is the stationary vector the computation can
be carried out by a simple multiplication
"""
EC_true = N * self.mu[:, np.newaxis] * T
assert_allclose(EC_true, EC_n)
N = 2000
EC_n = expected_counts(T, p0, N)
"""
If p0 is the stationary vector the computation can
be carried out by a simple multiplication
"""
EC_true = N * self.mu[:, np.newaxis] * T
assert_allclose(EC_true, EC_n)
"""Zero length chain"""
N = 0
EC_n = expected_counts(T, p0, N)
EC_true = np.zeros(T.shape)
assert_allclose(EC_true, EC_n)
def test_expected_counts(self):
N = 50
T = self.T_sparse
p0 = self.mu_sparse
EC_n = expected_counts(T, p0, N)
D_mu = diags(self.mu_sparse, 0)
EC_true = N * D_mu.dot(T)
self.assertTrue(sparse_allclose(EC_true, EC_n))