def test_init_hac_(self):
w_lags = 2
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
yd2, q2 = utils.set_endog(self.y, self.X, self.w, None, None, w_lags,
True)
self.X = np.hstack((np.ones(self.y.shape), self.X))
gwk = pysal.kernelW_from_shapefile(
pysal.examples.get_path('columbus.shp'),
k=15,
function='triangular',
fixed=False)
base_gm_lag = BaseGM_Lag(self.y,
self.X,
yend=yd2,
q=q2,
w=self.w.sparse,
w_lags=w_lags,
robust='hac',
gwk=gwk)
tbetas = np.array([[4.53017056e+01], [6.20888617e-01],
[-4.80723451e-01], [2.83622122e-02]])
np.testing.assert_array_almost_equal(base_gm_lag.betas, tbetas)
dbetas = D.se_betas(base_gm_lag)
se_betas = np.array([19.08513569, 0.51769543, 0.18244862, 0.35460553])
np.testing.assert_array_almost_equal(dbetas, se_betas)
def test_n_k(self):
w_lags = 2
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
yd2, q2 = utils.set_endog(self.y, self.X, self.w, None, None, w_lags,
True)
self.X = np.hstack((np.ones(self.y.shape), self.X))
reg = BaseGM_Lag(self.y,
self.X,
yend=yd2,
q=q2,
w=self.w.sparse,
w_lags=w_lags,
sig2n_k=True)
betas = np.array([[4.53017056e+01], [6.20888617e-01],
[-4.80723451e-01], [2.83622122e-02]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
vm = np.array([
[
3.49389596e+02, -5.36394351e+00, -2.81960968e+00,
-4.35694515e+00
],
[-5.36394351e+00, 2.99965892e-01, 6.44054000e-02, -3.13108972e-02],
[-2.81960968e+00, 6.44054000e-02, 3.61800155e-02, 1.61095854e-02],
[-4.35694515e+00, -3.13108972e-02, 1.61095854e-02, 1.09698285e-01]
])
np.testing.assert_array_almost_equal(reg.vm, vm, 7)
def test_model(self):
# Only spatial lag
yd2, q2 = utils.set_endog(self.y, self.X, self.w, None, None, 1, True)
self.X = np.hstack((np.ones(self.y.shape),self.X))
self.X = sparse.csr_matrix(self.X)
reg = HET.BaseGM_Combo_Het(self.y, self.X, yend=yd2, q=q2, w=self.w.sparse, step1c=True)
betas = np.array([[ 57.7778574 ], [ 0.73034922], [ -0.59257362], [ -0.2230231 ], [ 0.56636724]])
np.testing.assert_array_almost_equal(reg.betas,betas,7)
u = np.array([ 25.65156033])
np.testing.assert_array_almost_equal(reg.u[0],u,7)
ef = np.array([ 31.87664403])
np.testing.assert_array_almost_equal(reg.e_filtered[0],ef,7)
predy = np.array([ 54.81544267])
np.testing.assert_array_almost_equal(reg.predy[0],predy,7)
n = 49
self.assertAlmostEqual(reg.n,n)
k = 4
self.assertAlmostEqual(reg.k,k)
y = np.array([ 80.467003])
np.testing.assert_array_almost_equal(reg.y[0],y,7)
x = np.array([ 1. , 19.531 , 15.72598])
np.testing.assert_array_almost_equal(reg.x[0].toarray()[0],x,7)
yend = np.array([ 35.4585005])
np.testing.assert_array_almost_equal(reg.yend[0],yend,7)
q = np.array([ 18.594 , 24.7142675])
np.testing.assert_array_almost_equal(reg.q[0],q,7)
z = np.array([ 1. , 19.531 , 15.72598 , 35.4585005])
np.testing.assert_array_almost_equal(reg.z[0].toarray()[0],z,7)
i_s = 'Maximum number of iterations reached.'
np.testing.assert_string_equal(reg.iter_stop,i_s)
its = 1
self.assertAlmostEqual(reg.iteration,its,7)
my = 38.436224469387746
self.assertAlmostEqual(reg.mean_y,my)
stdy = 18.466069465206047
self.assertAlmostEqual(reg.std_y,stdy,7)
vm = np.array([[ 4.86218274e+02, -2.77268729e+00, -1.59987770e+00,
-1.01969471e+01, 2.74302006e+00],
[ -2.77268729e+00, 1.04680972e-01, 2.51172238e-02,
1.95136385e-03, 3.70052723e-03],
[ -1.59987770e+00, 2.51172238e-02, 2.15655720e-02,
7.65868344e-03, -7.30173070e-03],
[ -1.01969471e+01, 1.95136385e-03, 7.65868344e-03,
2.78273684e-01, -6.89402590e-02],
[ 2.74302006e+00, 3.70052723e-03, -7.30173070e-03,
-6.89402590e-02, 7.12034037e-02]])
np.testing.assert_array_almost_equal(reg.vm,vm,6)
hth = np.array([[ 4.90000000e+01, 7.04371999e+02, 1.72131237e+03,
7.24743592e+02, 1.70735413e+03],
[ 7.04371999e+02, 1.16866734e+04, 2.15575320e+04,
1.10925200e+04, 2.23848036e+04],
[ 1.72131237e+03, 2.15575320e+04, 7.39058986e+04,
2.34796298e+04, 6.70145378e+04],
[ 7.24743592e+02, 1.10925200e+04, 2.34796298e+04,
1.16146226e+04, 2.30304624e+04],
[ 1.70735413e+03, 2.23848036e+04, 6.70145378e+04,
2.30304624e+04, 6.69879858e+04]])
np.testing.assert_array_almost_equal(reg.hth,hth,4)
def test_init_white_(self):
w_lags = 2
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
yd2, q2 = utils.set_endog(self.y, self.X, self.w, None, None, w_lags, True)
self.X = np.hstack((np.ones(self.y.shape), self.X))
base_gm_lag = BaseGM_Lag(self.y, self.X, yend=yd2, q=q2, w=self.w.sparse, w_lags=w_lags, robust="white")
tbetas = np.array([[4.53017056e01], [6.20888617e-01], [-4.80723451e-01], [2.83622122e-02]])
np.testing.assert_array_almost_equal(base_gm_lag.betas, tbetas)
dbetas = D.se_betas(base_gm_lag)
se_betas = np.array([20.47077481, 0.50613931, 0.20138425, 0.38028295])
np.testing.assert_array_almost_equal(dbetas, se_betas)
def test_init_white_(self):
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
yd2, q2 = utils.set_endog(self.y, self.X, self.w, None, None, 2, True)
self.X = np.hstack((np.ones(self.y.shape),self.X))
self.X = SP.csr_matrix(self.X)
base_gm_lag = BaseGM_Lag(self.y, self.X, yend=yd2, q=q2, w=self.w, w_lags=2, robust='white')
tbetas = np.array([[ 4.53017056e+01], [ 6.20888617e-01], [ -4.80723451e-01], [ 2.83622122e-02]])
np.testing.assert_array_almost_equal(base_gm_lag.betas, tbetas)
dbetas = D.se_betas(base_gm_lag)
se_betas = np.array([ 20.47077481, 0.50613931, 0.20138425, 0.38028295 ])
np.testing.assert_array_almost_equal(dbetas, se_betas)
def test_init_hac_(self):
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
yd2, q2 = utils.set_endog(self.y, self.X, self.w, None, None, 2, True)
self.X = np.hstack((np.ones(self.y.shape),self.X))
self.X = SP.csr_matrix(self.X)
gwk = pysal.kernelW_from_shapefile(pysal.examples.get_path('columbus.shp'),k=15,function='triangular', fixed=False)
base_gm_lag = BaseGM_Lag(self.y, self.X, yend=yd2, q=q2, w=self.w, w_lags=2, robust='hac', gwk=gwk)
tbetas = np.array([[ 4.53017056e+01], [ 6.20888617e-01], [ -4.80723451e-01], [ 2.83622122e-02]])
np.testing.assert_array_almost_equal(base_gm_lag.betas, tbetas)
dbetas = D.se_betas(base_gm_lag)
se_betas = np.array([ 19.08513569, 0.51769543, 0.18244862, 0.35460553])
np.testing.assert_array_almost_equal(dbetas, se_betas)
def test_lag_q(self):
w_lags = 2
X = np.array(self.db.by_col("INC"))
self.X = np.reshape(X, (49, 1))
yd = np.array(self.db.by_col("CRIME"))
yd = np.reshape(yd, (49, 1))
q = np.array(self.db.by_col("DISCBD"))
q = np.reshape(q, (49, 1))
yd2, q2 = utils.set_endog(self.y, self.X, self.w, yd, q, w_lags, False)
self.X = np.hstack((np.ones(self.y.shape), self.X))
reg = BaseGM_Lag(self.y, self.X, w=self.w.sparse, yend=yd2, q=q2, w_lags=w_lags, lag_q=False)
tbetas = np.array([[108.83261383], [-0.48041099], [-1.18950006], [-0.56140186]])
np.testing.assert_array_almost_equal(tbetas, reg.betas)
dbetas = D.se_betas(reg)
se_betas = np.array([58.33203837, 1.09100446, 0.62315167, 0.68088777])
np.testing.assert_array_almost_equal(dbetas, se_betas)
def test_init_discbd(self):
w_lags = 2
X = np.array(self.db.by_col("INC"))
self.X = np.reshape(X, (49, 1))
yd = np.array(self.db.by_col("CRIME"))
yd = np.reshape(yd, (49, 1))
q = np.array(self.db.by_col("DISCBD"))
q = np.reshape(q, (49, 1))
yd2, q2 = utils.set_endog(self.y, self.X, self.w, yd, q, w_lags, True)
self.X = np.hstack((np.ones(self.y.shape), self.X))
reg = BaseGM_Lag(self.y, self.X, w=self.w.sparse, yend=yd2, q=q2, w_lags=w_lags)
tbetas = np.array([[100.79359082], [-0.50215501], [-1.14881711], [-0.38235022]])
np.testing.assert_array_almost_equal(tbetas, reg.betas)
dbetas = D.se_betas(reg)
se_betas = np.array([53.0829123, 1.02511494, 0.57589064, 0.59891744])
np.testing.assert_array_almost_equal(dbetas, se_betas)
def test_lag_q(self):
X = np.array(self.db.by_col("INC"))
self.X = np.reshape(X, (49,1))
yd = np.array(self.db.by_col("CRIME"))
yd = np.reshape(yd, (49,1))
q = np.array(self.db.by_col("DISCBD"))
q = np.reshape(q, (49,1))
yd2, q2 = utils.set_endog(self.y, self.X, self.w, yd, q, 2, False)
self.X = np.hstack((np.ones(self.y.shape),self.X))
self.X = SP.csr_matrix(self.X)
reg = BaseGM_Lag(self.y, self.X, yend=yd2, q=q2, w=self.w, w_lags=2, lag_q=False)
tbetas = np.array( [[ 108.83261383], [ -0.48041099], [ -1.18950006], [ -0.56140186]])
np.testing.assert_array_almost_equal(tbetas, reg.betas)
dbetas = D.se_betas(reg)
se_betas = np.array([ 58.33203837, 1.09100446, 0.62315167, 0.68088777])
np.testing.assert_array_almost_equal(dbetas, se_betas)
def test_n_k(self):
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
yd2, q2 = utils.set_endog(self.y, self.X, self.w, None, None, 2, True)
self.X = np.hstack((np.ones(self.y.shape),self.X))
self.X = SP.csr_matrix(self.X)
reg = BaseGM_Lag(self.y, self.X, yend=yd2, q=q2, w=self.w, w_lags=2, sig2n_k=True)
betas = np. array([[ 4.53017056e+01], [ 6.20888617e-01], [ -4.80723451e-01], [ 2.83622122e-02]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
vm = np.array( [[ 3.49389596e+02, -5.36394351e+00, -2.81960968e+00, -4.35694515e+00],
[ -5.36394351e+00, 2.99965892e-01, 6.44054000e-02, -3.13108972e-02],
[ -2.81960968e+00, 6.44054000e-02, 3.61800155e-02, 1.61095854e-02],
[ -4.35694515e+00, -3.13108972e-02, 1.61095854e-02, 1.09698285e-01]])
np.testing.assert_array_almost_equal(reg.vm, vm, 7)
def test_init_discbd(self):
X = np.array(self.db.by_col("INC"))
self.X = np.reshape(X, (49,1))
yd = np.array(self.db.by_col("CRIME"))
yd = np.reshape(yd, (49,1))
q = np.array(self.db.by_col("DISCBD"))
q = np.reshape(q, (49,1))
yd2, q2 = utils.set_endog(self.y, self.X, self.w, yd, q, 2, True)
self.X = np.hstack((np.ones(self.y.shape),self.X))
self.X = SP.csr_matrix(self.X)
reg = BaseGM_Lag(self.y, self.X, yend=yd2, q=q2, w=self.w, w_lags=2)
tbetas = np.array([[ 100.79359082], [ -0.50215501], [ -1.14881711], [ -0.38235022]])
np.testing.assert_array_almost_equal(tbetas, reg.betas)
dbetas = D.se_betas(reg)
se_betas = np.array([ 53.0829123 , 1.02511494, 0.57589064, 0.59891744 ])
np.testing.assert_array_almost_equal(dbetas, se_betas)
def test_model(self):
yd2, q2 = utils.set_endog(self.y, self.X, self.w, None, None, 1, True)
self.X = np.hstack((np.ones(self.y.shape),self.X))
self.X = sparse.csr_matrix(self.X)
reg = HOM.BaseGM_Combo_Hom(self.y, self.X, yend=yd2, q=q2, w=self.w.sparse, A1='hom_sc')
np.testing.assert_array_almost_equal(reg.y[0],np.array([80.467003]),7)
x = np.array([ 1. , 19.531])
np.testing.assert_array_almost_equal(reg.x[0].toarray()[0],x,7)
betas = np.array([[ 10.12541428], [ 1.56832263], [ 0.15132076], [ 0.21033397]])
np.testing.assert_array_almost_equal(reg.betas,betas,7)
np.testing.assert_array_almost_equal(reg.u[0],np.array([34.3450723]),7)
np.testing.assert_array_almost_equal(reg.e_filtered[0],np.array([ 36.6149682]),7)
np.testing.assert_array_almost_equal(reg.predy[0],np.array([ 46.1219307]),7)
self.assertAlmostEquals(reg.n,49,7)
self.assertAlmostEquals(reg.k,3,7)
vm = np.array([[ 2.33694742e+02, -6.66856869e-01, -5.58304254e+00, 4.85488380e+00], [ -6.66856869e-01, 1.94241504e-01, -5.42327138e-02, 5.37225570e-02], [ -5.58304254e+00, -5.42327138e-02, 1.63860721e-01, -1.44425498e-01], [ 4.85488380e+00, 5.37225570e-02, -1.44425498e-01, 1.78622255e-01]])
np.testing.assert_array_almost_equal(reg.vm,vm,6)
z = np.array([ 1. , 19.531 , 35.4585005])
np.testing.assert_array_almost_equal(reg.z[0].toarray()[0],z,7)
h = np.array([ 1. , 19.531, 18.594])
np.testing.assert_array_almost_equal(reg.h[0].toarray()[0],h,7)
yend = np.array([ 35.4585005])
np.testing.assert_array_almost_equal(reg.yend[0],yend,7)
q = np.array([ 18.594])
np.testing.assert_array_almost_equal(reg.q[0],q,7)
i_s = 'Maximum number of iterations reached.'
self.assertAlmostEqual(reg.iter_stop,i_s,7)
its = 1
self.assertAlmostEqual(reg.iteration,its,7)
my = 38.436224469387746
self.assertAlmostEqual(reg.mean_y,my)
std_y = 18.466069465206047
self.assertAlmostEqual(reg.std_y,std_y)
sig2 = 232.22680644168395
self.assertAlmostEqual(reg.sig2,sig2, places=6)
hth = np.array([[ 49. , 704.371999 , 724.7435916 ], [ 704.371999 , 11686.67338121, 11092.519988 ], [ 724.7435916 , 11092.519988 , 11614.62257048]])
np.testing.assert_array_almost_equal(reg.hth,hth,4)
def test___init__(self):
w_lags = 2
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
yd2, q2 = utils.set_endog(self.y, self.X, self.w, None, None, w_lags, True)
self.X = np.hstack((np.ones(self.y.shape), self.X))
reg = BaseGM_Lag(self.y, self.X, yend=yd2, q=q2, w=self.w.sparse, w_lags=w_lags)
betas = np.array([[4.53017056e01], [6.20888617e-01], [-4.80723451e-01], [2.83622122e-02]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
h_0 = np.array([1.0, 19.531, 15.72598, 18.594, 24.7142675, 13.72216667, 27.82929567])
np.testing.assert_array_almost_equal(reg.h[0], h_0)
hth = np.array([49.0, 704.371999, 1721.312371, 724.7435916, 1707.35412945, 711.31248483, 1729.63201243])
np.testing.assert_array_almost_equal(reg.hth[0], hth, 7)
hthi = np.array(
[
7.33701328e00,
2.27764882e-02,
2.18153588e-02,
-5.11035447e-02,
1.22515181e-03,
-2.38079378e-01,
-1.20149133e-01,
]
)
np.testing.assert_array_almost_equal(reg.hthi[0], hthi, 7)
self.assertEqual(reg.k, 4)
self.assertEqual(reg.kstar, 1)
self.assertAlmostEqual(reg.mean_y, 38.436224469387746, 7)
self.assertEqual(reg.n, 49)
pfora1a2 = np.array([80.5588479, -1.06625281, -0.61703759, -1.10071931])
np.testing.assert_array_almost_equal(reg.pfora1a2[0], pfora1a2, 7)
predy_5 = np.array([[50.87411532], [50.76969931], [41.77223722], [33.44262382], [28.77418036]])
np.testing.assert_array_almost_equal(reg.predy[0:5], predy_5, 7)
q_5 = np.array([18.594, 24.7142675, 13.72216667, 27.82929567])
np.testing.assert_array_almost_equal(reg.q[0], q_5)
self.assertAlmostEqual(reg.sig2n_k, 234.54258763039289, 7)
self.assertAlmostEqual(reg.sig2n, 215.39625394627919, 7)
self.assertAlmostEqual(reg.sig2, 215.39625394627919, 7)
self.assertAlmostEqual(reg.std_y, 18.466069465206047, 7)
u_5 = np.array([[29.59288768], [-6.20269831], [-15.42223722], [-0.24262282], [-5.54918036]])
np.testing.assert_array_almost_equal(reg.u[0:5], u_5, 7)
self.assertAlmostEqual(reg.utu, 10554.41644336768, 7)
varb = np.array(
[
[1.48966377e00, -2.28698061e-02, -1.20217386e-02, -1.85763498e-02],
[-2.28698061e-02, 1.27893998e-03, 2.74600023e-04, -1.33497705e-04],
[-1.20217386e-02, 2.74600023e-04, 1.54257766e-04, 6.86851184e-05],
[-1.85763498e-02, -1.33497705e-04, 6.86851184e-05, 4.67711582e-04],
]
)
np.testing.assert_array_almost_equal(reg.varb, varb, 7)
vm = np.array(
[
[3.20867996e02, -4.92607057e00, -2.58943746e00, -4.00127615e00],
[-4.92607057e00, 2.75478880e-01, 5.91478163e-02, -2.87549056e-02],
[-2.58943746e00, 5.91478163e-02, 3.32265449e-02, 1.47945172e-02],
[-4.00127615e00, -2.87549056e-02, 1.47945172e-02, 1.00743323e-01],
]
)
np.testing.assert_array_almost_equal(reg.vm, vm, 6)
x_0 = np.array([1.0, 19.531, 15.72598])
np.testing.assert_array_almost_equal(reg.x[0], x_0, 7)
y_5 = np.array([[80.467003], [44.567001], [26.35], [33.200001], [23.225]])
np.testing.assert_array_almost_equal(reg.y[0:5], y_5, 7)
yend_5 = np.array([[35.4585005], [46.67233467], [45.36475125], [32.81675025], [30.81785714]])
np.testing.assert_array_almost_equal(reg.yend[0:5], yend_5, 7)
z_0 = np.array([1.0, 19.531, 15.72598, 35.4585005])
np.testing.assert_array_almost_equal(reg.z[0], z_0, 7)
zthhthi = np.array(
[
[
1.00000000e00,
-2.22044605e-16,
-2.22044605e-16,
2.22044605e-16,
4.44089210e-16,
0.00000000e00,
-8.88178420e-16,
],
[
0.00000000e00,
1.00000000e00,
-3.55271368e-15,
3.55271368e-15,
-7.10542736e-15,
7.10542736e-14,
0.00000000e00,
],
[
1.81898940e-12,
2.84217094e-14,
1.00000000e00,
0.00000000e00,
-2.84217094e-14,
5.68434189e-14,
5.68434189e-14,
],
[
-8.31133940e00,
-3.76104678e-01,
-2.07028208e-01,
1.32618931e00,
-8.04284562e-01,
1.30527047e00,
1.39136816e00,
],
]
)
np.testing.assert_array_almost_equal(reg.zthhthi, zthhthi, 7)
def test___init__(self):
w_lags = 2
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
yd2, q2 = utils.set_endog(self.y, self.X, self.w, None, None, w_lags,
True)
self.X = np.hstack((np.ones(self.y.shape), self.X))
reg = BaseGM_Lag(self.y,
self.X,
yend=yd2,
q=q2,
w=self.w.sparse,
w_lags=w_lags)
betas = np.array([[4.53017056e+01], [6.20888617e-01],
[-4.80723451e-01], [2.83622122e-02]])
np.testing.assert_array_almost_equal(reg.betas, betas, 7)
h_0 = np.array([
1., 19.531, 15.72598, 18.594, 24.7142675, 13.72216667, 27.82929567
])
np.testing.assert_array_almost_equal(reg.h[0], h_0)
hth = np.array([
49., 704.371999, 1721.312371, 724.7435916, 1707.35412945,
711.31248483, 1729.63201243
])
np.testing.assert_array_almost_equal(reg.hth[0], hth, 7)
hthi = np.array([
7.33701328e+00, 2.27764882e-02, 2.18153588e-02, -5.11035447e-02,
1.22515181e-03, -2.38079378e-01, -1.20149133e-01
])
np.testing.assert_array_almost_equal(reg.hthi[0], hthi, 7)
self.assertEqual(reg.k, 4)
self.assertEqual(reg.kstar, 1)
self.assertAlmostEqual(reg.mean_y, 38.436224469387746, 7)
self.assertEqual(reg.n, 49)
pfora1a2 = np.array(
[80.5588479, -1.06625281, -0.61703759, -1.10071931])
np.testing.assert_array_almost_equal(reg.pfora1a2[0], pfora1a2, 7)
predy_5 = np.array([[50.87411532], [50.76969931], [41.77223722],
[33.44262382], [28.77418036]])
np.testing.assert_array_almost_equal(reg.predy[0:5], predy_5, 7)
q_5 = np.array([18.594, 24.7142675, 13.72216667, 27.82929567])
np.testing.assert_array_almost_equal(reg.q[0], q_5)
self.assertAlmostEqual(reg.sig2n_k, 234.54258763039289, 7)
self.assertAlmostEqual(reg.sig2n, 215.39625394627919, 7)
self.assertAlmostEqual(reg.sig2, 215.39625394627919, 7)
self.assertAlmostEqual(reg.std_y, 18.466069465206047, 7)
u_5 = np.array([[29.59288768], [-6.20269831], [-15.42223722],
[-0.24262282], [-5.54918036]])
np.testing.assert_array_almost_equal(reg.u[0:5], u_5, 7)
self.assertAlmostEqual(reg.utu, 10554.41644336768, 7)
varb = np.array([
[
1.48966377e+00, -2.28698061e-02, -1.20217386e-02,
-1.85763498e-02
],
[-2.28698061e-02, 1.27893998e-03, 2.74600023e-04, -1.33497705e-04],
[-1.20217386e-02, 2.74600023e-04, 1.54257766e-04, 6.86851184e-05],
[-1.85763498e-02, -1.33497705e-04, 6.86851184e-05, 4.67711582e-04]
])
np.testing.assert_array_almost_equal(reg.varb, varb, 7)
vm = np.array([
[
3.20867996e+02, -4.92607057e+00, -2.58943746e+00,
-4.00127615e+00
],
[-4.92607057e+00, 2.75478880e-01, 5.91478163e-02, -2.87549056e-02],
[-2.58943746e+00, 5.91478163e-02, 3.32265449e-02, 1.47945172e-02],
[-4.00127615e+00, -2.87549056e-02, 1.47945172e-02, 1.00743323e-01]
])
np.testing.assert_array_almost_equal(reg.vm, vm, 6)
x_0 = np.array([1., 19.531, 15.72598])
np.testing.assert_array_almost_equal(reg.x[0], x_0, 7)
y_5 = np.array([[80.467003], [44.567001], [26.35], [33.200001],
[23.225]])
np.testing.assert_array_almost_equal(reg.y[0:5], y_5, 7)
yend_5 = np.array([[35.4585005], [46.67233467], [45.36475125],
[32.81675025], [30.81785714]])
np.testing.assert_array_almost_equal(reg.yend[0:5], yend_5, 7)
z_0 = np.array([1., 19.531, 15.72598, 35.4585005])
np.testing.assert_array_almost_equal(reg.z[0], z_0, 7)
zthhthi = np.array([[
1.00000000e+00, -2.22044605e-16, -2.22044605e-16, 2.22044605e-16,
4.44089210e-16, 0.00000000e+00, -8.88178420e-16
],
[
0.00000000e+00, 1.00000000e+00,
-3.55271368e-15, 3.55271368e-15,
-7.10542736e-15, 7.10542736e-14, 0.00000000e+00
],
[
1.81898940e-12, 2.84217094e-14, 1.00000000e+00,
0.00000000e+00, -2.84217094e-14,
5.68434189e-14, 5.68434189e-14
],
[
-8.31133940e+00, -3.76104678e-01,
-2.07028208e-01, 1.32618931e+00,
-8.04284562e-01, 1.30527047e+00, 1.39136816e+00
]])
np.testing.assert_array_almost_equal(reg.zthhthi, zthhthi, 7)
