def test_hamilton_filter(): # read data data_dir = get_data_dir() data_dir = 'data' data = pd.read_csv(os.path.join(data_dir, "employment.csv"), names = ['year', 'employment', 'matlab_cyc', 'matlab_cyc_rw']) data['hamilton_cyc'], data['hamilton_trend'] = hamilton_filter(100*np.log(data['employment']), 8, 4) data['hamilton_cyc_rw'], data['hamilton_trend_rw'] = hamilton_filter(100*np.log(data['employment']), 8) assert_allclose(data['matlab_cyc'], data['hamilton_cyc'], rtol = 1e-07, atol = 1e-07) assert_allclose(data['matlab_cyc_rw'], data['hamilton_cyc_rw'])
# rng(42); [x_equiN_3 w_equiN_3] = qnwequi(n_3, a_3, b_3, 'N') # [x_equiW_3 w_equiW_3] = qnwequi(n_3, a_3, b_3, 'W') # [x_equiH_3 w_equiH_3] = qnwequi(n_3, a_3, b_3, 'H') # [x_equiR_3 w_equiR_3] = qnwequi(n_3, a_3, b_3, 'R') # [x_lege_3 w_lege_3] = qnwlege(n_3, a_3, b_3) # [x_norm_3 w_norm_3] = qnwnorm(n_3, mu_3d, sigma2_3d) # [x_logn_3 w_logn_3] = qnwlogn(n_3, mu_3d, sigma2_3d) # [x_simp_3 w_simp_3] = qnwsimp(n_3, a_3, b_3) # [x_trap_3 w_trap_3] = qnwtrap(n_3, a_3, b_3) # [x_unif_3 w_unif_3] = qnwunif(n_3, a_3, b_3) # [x_beta_3 w_beta_3] = qnwbeta(n_3, b_3, b_3+1.0) # [x_gamm_3 w_gamm_3] = qnwgamma(n_3, b_3) ### End MATLAB commands data_dir = get_data_dir() data = loadmat(os.path.join(data_dir, "matlab_quad.mat"), squeeze_me=True) # Unpack parameters from MATLAB a = data['a'] b = data['b'] n = data['n'] a_3 = data['a_3'] b_3 = data['b_3'] n_3 = data['n_3'] mu_3d = data['mu_3d'] sigma2_3d = data['sigma2_3d'] class TestQuadrect(unittest.TestCase):