def test_density_lens(self):
r = 1
kwargs = {'theta_E': 1, 'gamma': 2, 'e1': 0, 'e2': 0}
rho = self.EPL.density_lens(r, **kwargs)
from lenstronomy.LensModel.Profiles.spep import SPEP
spep = SPEP()
rho_spep = spep.density_lens(r, **kwargs)
npt.assert_almost_equal(rho, rho_spep, decimal=7)
class TestSPEMD(object):
"""
tests the Gaussian methods
"""
def setup(self):
from lenstronomy.LensModel.Profiles.pemd import PEMD
from lenstronomy.LensModel.Profiles.spep import SPEP
self.PEMD = PEMD(suppress_fastell=True)
self.SPEP = SPEP()
def test_function(self):
phi_E = 1.
gamma = 1.9
q = 0.9
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
x = np.array([1.])
y = np.array([2])
a = np.zeros_like(x)
values = self.PEMD.function(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(values[0], 2.1571106351401803, decimal=5)
else:
assert values == 0
a += values
x = np.array(1.)
y = np.array(2.)
a = np.zeros_like(x)
values = self.PEMD.function(x, y, phi_E, gamma, e1, e2)
print(x, values)
a += values
if fastell4py_bool:
npt.assert_almost_equal(values, 2.1571106351401803, decimal=5)
else:
assert values == 0
assert type(x) == type(values)
x = np.array([2, 3, 4])
y = np.array([1, 1, 1])
values = self.PEMD.function(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(values[0], 2.180188584782964, decimal=7)
npt.assert_almost_equal(values[1], 3.2097137160951874, decimal=7)
npt.assert_almost_equal(values[2], 4.3109976673748, decimal=7)
else:
npt.assert_almost_equal(values[0], 0, decimal=7)
npt.assert_almost_equal(values[1], 0, decimal=7)
npt.assert_almost_equal(values[2], 0, decimal=7)
def test_derivatives(self):
x = np.array([1])
y = np.array([2])
phi_E = 1.
gamma = 1.9
q = 0.9
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
f_x, f_y = self.PEMD.derivatives(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(f_x[0], 0.46664118422711387, decimal=7)
npt.assert_almost_equal(f_y[0], 0.9530892465981603, decimal=7)
else:
npt.assert_almost_equal(f_x[0], 0, decimal=7)
npt.assert_almost_equal(f_y[0], 0, decimal=7)
x = np.array([1., 3, 4])
y = np.array([2., 1, 1])
a = np.zeros_like(x)
values = self.PEMD.derivatives(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(values[0][0],
0.46664118422711387,
decimal=7)
npt.assert_almost_equal(values[1][0],
0.9530892465981603,
decimal=7)
npt.assert_almost_equal(values[0][1],
1.0722265330847958,
decimal=7)
npt.assert_almost_equal(values[1][1],
0.3140067377020791,
decimal=7)
else:
npt.assert_almost_equal(values[0][0], 0, decimal=7)
npt.assert_almost_equal(values[1][0], 0, decimal=7)
npt.assert_almost_equal(values[0][1], 0, decimal=7)
npt.assert_almost_equal(values[1][1], 0, decimal=7)
a += values[0]
x = 1.
y = 2.
phi_E = 1.
gamma = 1.9
q = 0.9
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
f_x, f_y = self.PEMD.derivatives(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(f_x, 0.46664118422711387, decimal=7)
npt.assert_almost_equal(f_y, 0.9530892465981603, decimal=7)
else:
npt.assert_almost_equal(f_x, 0, decimal=7)
npt.assert_almost_equal(f_y, 0, decimal=7)
x = 0.
y = 0.
f_x, f_y = self.PEMD.derivatives(x, y, phi_E, gamma, e1, e2)
assert f_x == 0.
assert f_y == 0.
def test_hessian(self):
x = np.array([1])
y = np.array([2])
phi_E = 1.
gamma = 1.9
q = 0.9
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
f_xx, f_xy, f_yx, f_yy = self.PEMD.hessian(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(f_xx, 0.4179041, decimal=7)
npt.assert_almost_equal(f_yy, 0.1404714, decimal=7)
npt.assert_almost_equal(f_xy, -0.1856134, decimal=7)
else:
npt.assert_almost_equal(f_xx, 0, decimal=7)
npt.assert_almost_equal(f_yy, 0, decimal=7)
npt.assert_almost_equal(f_xy, 0, decimal=7)
npt.assert_almost_equal(f_xy, f_yx, decimal=8)
x = 1.
y = 2.
phi_E = 1.
gamma = 1.9
q = 0.9
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
a = np.zeros_like(x)
f_xx, f_xy, f_yx, f_yy = self.PEMD.hessian(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(f_xx, 0.41790408341142493, decimal=7)
npt.assert_almost_equal(f_yy, 0.14047143086334482, decimal=7)
npt.assert_almost_equal(f_xy, -0.1856133848300859, decimal=7)
else:
npt.assert_almost_equal(f_xx, 0, decimal=7)
npt.assert_almost_equal(f_yy, 0, decimal=7)
npt.assert_almost_equal(f_xy, 0, decimal=7)
a += f_xx
x = np.array([1, 3, 4])
y = np.array([2, 1, 1])
values = self.PEMD.hessian(x, y, phi_E, gamma, e1, e2)
print(values, 'values')
if fastell4py_bool:
npt.assert_almost_equal(values[0][0],
0.41789957732890953,
decimal=5)
npt.assert_almost_equal(values[3][0],
0.14047593655054141,
decimal=5)
npt.assert_almost_equal(values[1][0],
-0.18560737698052343,
decimal=5)
npt.assert_almost_equal(values[0][1],
0.068359818958208918,
decimal=5)
npt.assert_almost_equal(values[3][1],
0.32494089371516482,
decimal=5)
npt.assert_almost_equal(values[1][1],
-0.097845438684594374,
decimal=5)
else:
npt.assert_almost_equal(values[0][0], 0, decimal=7)
def test_spep_spemd(self):
x = np.array([1])
y = np.array([0])
phi_E = 1.
gamma = 2.
q = 1.
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
f_x, f_y = self.PEMD.derivatives(x, y, phi_E, gamma, e1, e2)
f_x_spep, f_y_spep = self.SPEP.derivatives(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(f_x[0], f_x_spep[0], decimal=2)
else:
pass
theta_E = 2.
gamma = 2.
q = 1.
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
f_x, f_y = self.PEMD.derivatives(x, y, theta_E, gamma, e1, e2)
f_x_spep, f_y_spep = self.SPEP.derivatives(x, y, theta_E, gamma, e1,
e2)
if fastell4py_bool:
npt.assert_almost_equal(f_x[0], f_x_spep[0], decimal=2)
else:
pass
theta_E = 2.
gamma = 1.7
q = 1.
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
f_x, f_y = self.PEMD.derivatives(x, y, theta_E, gamma, e1, e2)
f_x_spep, f_y_spep = self.SPEP.derivatives(x, y, theta_E, gamma, e1,
e2)
if fastell4py_bool:
npt.assert_almost_equal(f_x[0], f_x_spep[0], decimal=4)
def test_bounds(self):
from lenstronomy.LensModel.Profiles.spemd import SPEMD
profile = SPEMD(suppress_fastell=True)
compute_bool = profile._parameter_constraints(q_fastell=-1,
gam=-1,
s2=-1,
q=-1)
assert compute_bool is False
def test_is_not_empty(self):
func = self.PEMD.spemd_smooth.is_not_empty
assert func(0.1, 0.2)
assert func([0.1], [0.2])
assert func((0.1, 0.3), (0.2, 0.4))
assert func(np.array([0.1]), np.array([0.2]))
assert not func([], [])
assert not func(np.array([]), np.array([]))
def test_density_lens(self):
r = 1
kwargs = {'theta_E': 1, 'gamma': 2, 'e1': 0, 'e2': 0}
rho = self.PEMD.density_lens(r, **kwargs)
rho_spep = self.SPEP.density_lens(r, **kwargs)
npt.assert_almost_equal(rho, rho_spep, decimal=7)
class TestSPEMD(object):
"""
tests the Gaussian methods
"""
def setup(self):
from lenstronomy.LensModel.Profiles.spemd import SPEMD
from lenstronomy.LensModel.Profiles.spep import SPEP
self.SPEMD = SPEMD()
self.SPEP = SPEP()
def test_function(self):
phi_E = 1.
gamma = 1.9
q = 0.9
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
x = np.array([1.])
y = np.array([2])
a = np.zeros_like(x)
values = self.SPEMD.function(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
assert values == 2.1567297115381039
else:
assert values == 0
a += values
x = np.array(1.)
y = np.array(2.)
a = np.zeros_like(x)
values = self.SPEMD.function(x, y, phi_E, gamma, e1, e2)
print(x, values)
a += values
if fastell4py_bool:
assert values == 2.1567297115381039
else:
assert values == 0
assert type(x) == type(values)
x = np.array([2, 3, 4])
y = np.array([1, 1, 1])
values = self.SPEMD.function(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(values[0], 2.1798076611034141, decimal=7)
npt.assert_almost_equal(values[1], 3.209319798597186, decimal=7)
npt.assert_almost_equal(values[2], 4.3105937398856398, decimal=7)
else:
npt.assert_almost_equal(values[0], 0, decimal=7)
npt.assert_almost_equal(values[1], 0, decimal=7)
npt.assert_almost_equal(values[2], 0, decimal=7)
def test_derivatives(self):
x = np.array([1])
y = np.array([2])
phi_E = 1.
gamma = 1.9
q = 0.9
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
f_x, f_y = self.SPEMD.derivatives(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(f_x[0], 0.46663367437984204, decimal=7)
npt.assert_almost_equal(f_y[0], 0.95307422686028065, decimal=7)
else:
npt.assert_almost_equal(f_x[0], 0, decimal=7)
npt.assert_almost_equal(f_y[0], 0, decimal=7)
x = np.array([1., 3, 4])
y = np.array([2., 1, 1])
a = np.zeros_like(x)
values = self.SPEMD.derivatives(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(values[0][0],
0.46663367437984204,
decimal=7)
npt.assert_almost_equal(values[1][0],
0.95307422686028065,
decimal=7)
npt.assert_almost_equal(values[0][1],
1.0722152681324291,
decimal=7)
npt.assert_almost_equal(values[1][1],
0.31400298272329669,
decimal=7)
else:
npt.assert_almost_equal(values[0][0], 0, decimal=7)
npt.assert_almost_equal(values[1][0], 0, decimal=7)
npt.assert_almost_equal(values[0][1], 0, decimal=7)
npt.assert_almost_equal(values[1][1], 0, decimal=7)
a += values[0]
x = 1.
y = 2.
phi_E = 1.
gamma = 1.9
q = 0.9
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
f_x, f_y = self.SPEMD.derivatives(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(f_x, 0.46663367437984204, decimal=7)
npt.assert_almost_equal(f_y, 0.95307422686028065, decimal=7)
else:
npt.assert_almost_equal(f_x, 0, decimal=7)
npt.assert_almost_equal(f_y, 0, decimal=7)
x = 0.
y = 0.
f_x, f_y = self.SPEMD.derivatives(x, y, phi_E, gamma, e1, e2)
assert f_x == 0.
assert f_y == 0.
def test_hessian(self):
x = np.array([1])
y = np.array([2])
phi_E = 1.
gamma = 1.9
q = 0.9
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
f_xx, f_yy, f_xy = self.SPEMD.hessian(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(f_xx, 0.41789957732890953, decimal=7)
npt.assert_almost_equal(f_yy, 0.14047593655054141, decimal=7)
npt.assert_almost_equal(f_xy, -0.18560737698052343, decimal=7)
else:
npt.assert_almost_equal(f_xx, 0, decimal=7)
npt.assert_almost_equal(f_yy, 0, decimal=7)
npt.assert_almost_equal(f_xy, 0, decimal=7)
x = 1.
y = 2.
phi_E = 1.
gamma = 1.9
q = 0.9
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
a = np.zeros_like(x)
f_xx, f_yy, f_xy = self.SPEMD.hessian(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(f_xx, 0.41789957732890953, decimal=7)
npt.assert_almost_equal(f_yy, 0.14047593655054141, decimal=7)
npt.assert_almost_equal(f_xy, -0.18560737698052343, decimal=7)
else:
npt.assert_almost_equal(f_xx, 0, decimal=7)
npt.assert_almost_equal(f_yy, 0, decimal=7)
npt.assert_almost_equal(f_xy, 0, decimal=7)
a += f_xx
x = np.array([1, 3, 4])
y = np.array([2, 1, 1])
values = self.SPEMD.hessian(x, y, phi_E, gamma, e1, e2)
print(values, 'values')
if fastell4py_bool:
npt.assert_almost_equal(values[0][0],
0.41789957732890953,
decimal=7)
npt.assert_almost_equal(values[1][0],
0.14047593655054141,
decimal=7)
npt.assert_almost_equal(values[2][0],
-0.18560737698052343,
decimal=7)
npt.assert_almost_equal(values[0][1],
0.068359818958208918,
decimal=7)
npt.assert_almost_equal(values[1][1],
0.32494089371516482,
decimal=7)
npt.assert_almost_equal(values[2][1],
-0.097845438684594374,
decimal=7)
else:
npt.assert_almost_equal(values[0][0], 0, decimal=7)
def test_spep_spemd(self):
x = np.array([1])
y = np.array([0])
phi_E = 1.
gamma = 2.
q = 1.
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
f_x, f_y = self.SPEMD.derivatives(x, y, phi_E, gamma, e1, e2)
f_x_spep, f_y_spep = self.SPEP.derivatives(x, y, phi_E, gamma, e1, e2)
if fastell4py_bool:
npt.assert_almost_equal(f_x[0], f_x_spep[0], decimal=2)
else:
pass
theta_E = 2.
gamma = 2.
q = 1.
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
f_x, f_y = self.SPEMD.derivatives(x, y, theta_E, gamma, e1, e2)
f_x_spep, f_y_spep = self.SPEP.derivatives(x, y, theta_E, gamma, e1,
e2)
if fastell4py_bool:
npt.assert_almost_equal(f_x[0], f_x_spep[0], decimal=2)
else:
pass
theta_E = 2.
gamma = 1.7
q = 1.
phi_G = 1.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
f_x, f_y = self.SPEMD.derivatives(x, y, theta_E, gamma, e1, e2)
f_x_spep, f_y_spep = self.SPEP.derivatives(x, y, theta_E, gamma, e1,
e2)
if fastell4py_bool:
npt.assert_almost_equal(f_x[0], f_x_spep[0], decimal=4)
def test_bounds(self):
from lenstronomy.LensModel.Profiles.spemd_smooth import SPEMD_SMOOTH
profile = SPEMD_SMOOTH()
theta_E, gamma, q, phi_G, s_scale = profile._parameter_constraints(
theta_E=-1, s_scale=0, gamma=3, q=2, phi_G=0)
assert theta_E == 0
def test_is_not_empty(self):
func = self.SPEMD.spemd_smooth.is_not_empty
assert func(0.1, 0.2)
assert func([0.1], [0.2])
assert func((0.1, 0.3), (0.2, 0.4))
assert func(np.array([0.1]), np.array([0.2]))
assert not func([], [])
assert not func(np.array([]), np.array([]))
def test_density_lens(self):
r = 1
kwargs = {'theta_E': 1, 'gamma': 2, 'e1': 0, 'e2': 0}
rho = self.SPEMD.density_lens(r, **kwargs)
rho_spep = self.SPEP.density_lens(r, **kwargs)
npt.assert_almost_equal(rho, rho_spep, decimal=7)
