def test_lens_model_correspondence(self):
"""
here we test the proportionality of the convergence of the lens model with the surface brightness of the light
model
"""
chameleon_lens = ChameleonLens()
chameleon = Chameleon()
x, y = util.make_grid(numPix=100, deltapix=0.1)
e1, e2 = 0., 0
w_c, w_t = 0.5, 1.
kwargs_light = {'amp': 1., 'w_c': w_c, 'w_t': w_t, 'e1': e1, 'e2': e2}
kwargs_lens = {
'alpha_1': 1.,
'w_c': w_c,
'w_t': w_t,
'e1': e1,
'e2': e2
}
flux = chameleon.function(x=x, y=y, **kwargs_light)
f_xx, f_xy, f_yx, f_yy = chameleon_lens.hessian(x=x,
y=y,
**kwargs_lens)
kappa = 1 / 2. * (f_xx + f_yy)
# flux2d = util.array2image(flux)
# kappa2d = util.array2image(kappa)
npt.assert_almost_equal(flux / np.mean(flux),
kappa / np.mean(kappa),
decimal=3)
def test_derivatives(self):
"""
:return:
"""
triplechameleon = TripleChameleon()
chameleon = Chameleon()
x = np.linspace(0.1, 10, 10)
phi_G, q = 0.3, 0.8
ratio12 = 2.
ratio13 = 3
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
kwargs_light = {'alpha_1': 1., 'ratio12': ratio12, 'ratio13': ratio13, 'w_c1': .5, 'w_t1': 1., 'e11': e1,
'e21': e2,
'w_c2': .1, 'w_t2': .5, 'e12': e1, 'e22': e2,
'w_c3': .1, 'w_t3': .5, 'e13': e1, 'e23': e2
}
amp1 = 1. / (1. + 1. / ratio12 + 1. / ratio13)
amp2 = amp1 / ratio12
amp3 = amp1 / ratio13
kwargs_1 = {'alpha_1': amp1, 'w_c': .5, 'w_t': 1., 'e1': e1, 'e2': e2}
kwargs_2 = {'alpha_1': amp2, 'w_c': .1, 'w_t': .5, 'e1': e1, 'e2': e2}
kwargs_3 = {'alpha_1': amp3, 'w_c': .1, 'w_t': .5, 'e1': e1, 'e2': e2}
f_x, f_y = triplechameleon.derivatives(x=x, y=1., **kwargs_light)
f_x1, f_y1 = chameleon.derivatives(x=x, y=1., **kwargs_1)
f_x2, f_y2 = chameleon.derivatives(x=x, y=1., **kwargs_2)
f_x3, f_y3 = chameleon.derivatives(x=x, y=1., **kwargs_3)
npt.assert_almost_equal(f_x, f_x1 + f_x2 + f_x3, decimal=8)
npt.assert_almost_equal(f_y, f_y1 + f_y2 + f_y3, decimal=8)
def test_hessian(self):
"""
:return:
"""
doublechameleon = DoubleChameleon()
chameleon = Chameleon()
x = np.linspace(0.1, 10, 10)
phi_G, q = 0.3, 0.8
theta_E = 1.
ratio = 2.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
kwargs_lens = {'alpha_1': theta_E, 'ratio': ratio, 'w_c1': .5, 'w_t1': 1., 'e11': e1, 'e21': e2, 'w_c2': .1, 'w_t2': .5, 'e12': e1, 'e22': e2}
kwargs_light = {'amp': theta_E, 'ratio': ratio, 'w_c1': .5, 'w_t1': 1., 'e11': e1, 'e21': e2, 'w_c2': .1, 'w_t2': .5, 'e12': e1, 'e22': e2}
kwargs_1 = {'alpha_1': theta_E / (1 + 1./ratio), 'w_c': .5, 'w_t': 1., 'e1': e1, 'e2': e2}
kwargs_2 = {'alpha_1': theta_E / (1 + ratio), 'w_c': .1, 'w_t': .5, 'e1': e1, 'e2': e2}
f_xx, f_yy, f_xy = doublechameleon.hessian(x=x, y=1., **kwargs_lens)
f_xx1, f_yy1, f_xy1 = chameleon.hessian(x=x, y=1., **kwargs_1)
f_xx2, f_yy2, f_xy2 = chameleon.hessian(x=x, y=1., **kwargs_2)
npt.assert_almost_equal(f_xx, f_xx1 + f_xx2, decimal=8)
npt.assert_almost_equal(f_yy, f_yy1 + f_yy2, decimal=8)
npt.assert_almost_equal(f_xy, f_xy1 + f_xy2, decimal=8)
light = DoubleChameleonLight()
f_xx, f_yy, f_xy = doublechameleon.hessian(x=np.linspace(0, 1, 10), y=np.zeros(10), **kwargs_lens)
kappa = 1./2 * (f_xx + f_yy)
kappa_norm = kappa / np.mean(kappa)
flux = light.function(x=np.linspace(0, 1, 10), y=np.zeros(10), **kwargs_light)
flux_norm = flux / np.mean(flux)
npt.assert_almost_equal(kappa_norm, flux_norm, decimal=5)
class Chameleon(object):
"""
class of the Chameleon model (See Dutton+ 2011, Suyu+2014) an elliptical truncated double isothermal profile
"""
param_names = ['amp', 'w_c', 'w_t', 'e1', 'e2', 'center_x', 'center_y']
lower_limit_default = {'amp': 0, 'w_c': 0, 'w_t': 0, 'e1': -0.5, 'e2': -0.5, 'center_x': -100, 'center_y': -100}
upper_limit_default = {'amp': 100, 'w_c': 100, 'w_t': 100, 'e1': 0.5, 'e2': 0.5, 'center_x': 100, 'center_y': 100}
def __init__(self):
self.nie = NIE()
self._chameleonLens = ChameleonLens()
def function(self, x, y, amp, w_c, w_t, e1, e2, center_x=0, center_y=0):
"""
:param x: ra-coordinate
:param y: dec-coordinate
:param w_c:
:param w_t:
:param amp: amplitude of first power-law flux
:param e1: eccentricity parameter
:param e2: eccentricity parameter
:param center_x: center
:param center_y: center
:return: flux of chameleon profile
"""
amp_new, w_c, w_t, s_scale_1, s_scale_2 = self._chameleonLens.param_convert(amp, w_c, w_t, e1, e2)
flux1 = self.nie.function(x, y, 1, e1, e2, s_scale_1, center_x, center_y)
flux2 = self.nie.function(x, y, 1, e1, e2, s_scale_2, center_x, center_y)
flux = amp_new * (flux1 - flux2)
return flux
def light_3d(self, r, amp, w_c, w_t, e1, e2, center_x=0, center_y=0):
"""
:param r: 3d radius
:param w_c:
:param w_t:
:param amp: amplitude of first power-law flux
:param e1: eccentricity parameter
:param e2: eccentricity parameter
:param center_x: center
:param center_y: center
:return: 3d flux of chameleon profile at radius r
"""
amp_new, w_c, w_t, s_scale_1, s_scale_2 = self._chameleonLens.param_convert(amp, w_c, w_t, e1, e2)
flux1 = self.nie.light_3d(r, 1, e1, e2, s_scale_1, center_x, center_y)
flux2 = self.nie.light_3d(r, 1, e1, e2, s_scale_2, center_x, center_y)
flux = amp_new * (flux1 - flux2)
return flux
def test_hessian(self):
"""
:return:
"""
triplechameleon = TripleChameleon()
chameleon = Chameleon()
x = np.linspace(0.1, 10, 10)
phi_G, q = 0.3, 0.8
ratio12 = 2.
ratio13 = 3
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
kwargs_lens = {'alpha_1': 1., 'ratio12': ratio12, 'ratio13': ratio13, 'w_c1': .5, 'w_t1': 1., 'e11': e1,
'e21': e2,
'w_c2': .1, 'w_t2': .5, 'e12': e1, 'e22': e2,
'w_c3': .1, 'w_t3': .5, 'e13': e1, 'e23': e2
}
kwargs_light = {'amp': 1., 'ratio12': ratio12, 'ratio13': ratio13, 'w_c1': .5, 'w_t1': 1., 'e11': e1,
'e21': e2,
'w_c2': .1, 'w_t2': .5, 'e12': e1, 'e22': e2,
'w_c3': .1, 'w_t3': .5, 'e13': e1, 'e23': e2
}
amp1 = 1. / (1. + 1. / ratio12 + 1. / ratio13)
amp2 = amp1 / ratio12
amp3 = amp1 / ratio13
kwargs_1 = {'alpha_1': amp1, 'w_c': .5, 'w_t': 1., 'e1': e1, 'e2': e2}
kwargs_2 = {'alpha_1': amp2, 'w_c': .1, 'w_t': .5, 'e1': e1, 'e2': e2}
kwargs_3 = {'alpha_1': amp3, 'w_c': .1, 'w_t': .5, 'e1': e1, 'e2': e2}
f_xx, f_yy, f_xy = triplechameleon.hessian(x=x, y=1., **kwargs_lens)
f_xx1, f_yy1, f_xy1 = chameleon.hessian(x=x, y=1., **kwargs_1)
f_xx2, f_yy2, f_xy2 = chameleon.hessian(x=x, y=1., **kwargs_2)
f_xx3, f_yy3, f_xy3 = chameleon.hessian(x=x, y=1., **kwargs_3)
npt.assert_almost_equal(f_xx, f_xx1 + f_xx2 + f_xx3, decimal=8)
npt.assert_almost_equal(f_yy, f_yy1 + f_yy2 + f_yy3, decimal=8)
npt.assert_almost_equal(f_xy, f_xy1 + f_xy2 + f_xy3, decimal=8)
light = TripleChameleonLight()
f_xx, f_yy, f_xy = triplechameleon.hessian(x=np.linspace(0, 1, 10), y=np.zeros(10), **kwargs_lens)
kappa = 1./2 * (f_xx + f_yy)
kappa_norm = kappa / np.mean(kappa)
flux = light.function(x=np.linspace(0, 1, 10), y=np.zeros(10), **kwargs_light)
flux_norm = flux / np.mean(flux)
npt.assert_almost_equal(kappa_norm, flux_norm, decimal=5)
def test_derivatives(self):
"""
:return:
"""
doublechameleon = DoubleChameleon()
chameleon = Chameleon()
x = np.linspace(0.1, 10, 10)
phi_G, q = 0.3, 0.8
theta_E = 1.
ratio = 2.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
kwargs_light = {
'theta_E': 1.,
'ratio': 2,
'w_c1': .5,
'w_t1': 1.,
'e11': e1,
'e21': e2,
'w_c2': .1,
'w_t2': .5,
'e12': e1,
'e22': e2
}
kwargs_1 = {
'theta_E': theta_E / (1 + 1. / ratio),
'w_c': .5,
'w_t': 1.,
'e1': e1,
'e2': e2
}
kwargs_2 = {
'theta_E': theta_E / (1 + ratio),
'w_c': .1,
'w_t': .5,
'e1': e1,
'e2': e2
}
f_x, f_y = doublechameleon.derivatives(x=x, y=1., **kwargs_light)
f_x1, f_y1 = chameleon.derivatives(x=x, y=1., **kwargs_1)
f_x2, f_y2 = chameleon.derivatives(x=x, y=1., **kwargs_2)
npt.assert_almost_equal(f_x, f_x1 + f_x2, decimal=8)
npt.assert_almost_equal(f_y, f_y1 + f_y2, decimal=8)
def test_function(self):
"""
:return:
"""
doublechameleon = DoubleChameleon()
chameleon = Chameleon()
x = np.linspace(0.1, 10, 10)
phi_G, q = 0.3, 0.8
theta_E = 1.
ratio = 2.
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
kwargs_light = {
'alpha_1': 1.,
'ratio': 2,
'w_c1': .5,
'w_t1': 1.,
'e11': e1,
'e21': e2,
'w_c2': .1,
'w_t2': .5,
'e12': e1,
'e22': e2
}
kwargs_1 = {
'alpha_1': theta_E / (1 + 1. / ratio),
'w_c': .5,
'w_t': 1.,
'e1': e1,
'e2': e2
}
kwargs_2 = {
'alpha_1': theta_E / (1 + ratio),
'w_c': .1,
'w_t': .5,
'e1': e1,
'e2': e2
}
flux = doublechameleon.function(x=x, y=1., **kwargs_light)
flux1 = chameleon.function(x=x, y=1., **kwargs_1)
flux2 = chameleon.function(x=x, y=1., **kwargs_2)
npt.assert_almost_equal(flux, flux1 + flux2, decimal=8)
class Chameleon(object):
"""
class of the Chameleon model (See Suyu+2014) an elliptical truncated double isothermal profile
"""
param_names = ['amp', 'w_c', 'w_t', 'e1', 'e2', 'center_x', 'center_y']
lower_limit_default = {
'amp': 0,
'w_c': 0,
'w_t': 0,
'e1': -0.5,
'e2': -0.5,
'center_x': -100,
'center_y': -100
}
upper_limit_default = {
'amp': 100,
'w_c': 100,
'w_t': 100,
'e1': 0.5,
'e2': 0.5,
'center_x': 100,
'center_y': 100
}
def __init__(self):
self.nie = NIE()
self._chameleonLens = ChameleonLens()
def function(self, x, y, amp, w_c, w_t, e1, e2, center_x=0, center_y=0):
"""
:param x: ra-coordinate
:param y: dec-coordinate
:param amp: amplitude of first power-law flux
:param flux_ratio: ratio of amplitudes of first to second power-law profile
:param gamma1: power-law slope
:param gamma2: power-law slope
:param e1: ellipticity parameter
:param e2: ellipticity parameter
:param center_x: center
:param center_y: center
:return: flux of chameleon profile
"""
amp_new, w_c, w_t = self._chameleonLens._theta_convert(amp, w_c, w_t)
phi_G, q = param_util.ellipticity2phi_q(e1, e2)
s_scale_1 = np.sqrt(4 * w_c**2 / (1. + q)**2)
s_scale_2 = np.sqrt(4 * w_t**2 / (1. + q)**2)
flux1 = self.nie.function(x, y, 1, e1, e2, s_scale_1, center_x,
center_y)
flux2 = self.nie.function(x, y, 1, e1, e2, s_scale_2, center_x,
center_y)
flux = amp_new / (1. + q) * (flux1 - flux2)
return flux
class TestChameleon(object):
"""
class to test the Moffat profile
"""
def setup(self):
self.chameleon = Chameleon()
self.nie = NIE()
def test_theta_E_convert(self):
w_c, w_t = 2, 1
theta_E_convert, w_c, w_t = self.chameleon._theta_E_convert(theta_E=1,
w_c=w_c,
w_t=w_t)
assert w_c == 1
assert w_t == 2
def test_function(self):
"""
:return:
"""
x = np.linspace(0.1, 10, 10)
w_c, w_t = 0.5, 1.
phi_G, q = 0.3, 0.8
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
kwargs_light = {
'theta_E': 1.,
'w_c': .5,
'w_t': 1.,
'e1': e1,
'e2': e2
}
theta_E_convert, w_c, w_t = self.chameleon._theta_E_convert(theta_E=1,
w_c=0.5,
w_t=1.)
s_scale_1 = np.sqrt(4 * w_c**2 / (1. + q)**2)
s_scale_2 = np.sqrt(4 * w_t**2 / (1. + q)**2)
kwargs_1 = {
'theta_E': theta_E_convert,
's_scale': s_scale_1,
'e1': e1,
'e2': e2
}
kwargs_2 = {
'theta_E': theta_E_convert,
's_scale': s_scale_2,
'e1': e1,
'e2': e2
}
f_ = self.chameleon.function(x=x, y=1., **kwargs_light)
f_1 = self.nie.function(x=x, y=1., **kwargs_1)
f_2 = self.nie.function(x=x, y=1., **kwargs_2)
npt.assert_almost_equal(f_, (f_1 - f_2), decimal=5)
def test_derivatives(self):
"""
:return:
"""
x = np.linspace(0.1, 10, 10)
w_c, w_t = 0.5, 1.
phi_G, q = 0.3, 0.8
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
kwargs_light = {
'theta_E': 1.,
'w_c': .5,
'w_t': 1.,
'e1': e1,
'e2': e2
}
theta_E_convert, w_c, w_t = self.chameleon._theta_E_convert(theta_E=1,
w_c=0.5,
w_t=1.)
s_scale_1 = np.sqrt(4 * w_c**2 / (1. + q)**2)
s_scale_2 = np.sqrt(4 * w_t**2 / (1. + q)**2)
kwargs_1 = {
'theta_E': theta_E_convert,
's_scale': s_scale_1,
'e1': e1,
'e2': e2
}
kwargs_2 = {
'theta_E': theta_E_convert,
's_scale': s_scale_2,
'e1': e1,
'e2': e2
}
f_x, f_y = self.chameleon.derivatives(x=x, y=1., **kwargs_light)
f_x_1, f_y_1 = self.nie.derivatives(x=x, y=1., **kwargs_1)
f_x_2, f_y_2 = self.nie.derivatives(x=x, y=1., **kwargs_2)
npt.assert_almost_equal(f_x, (f_x_1 - f_x_2), decimal=5)
npt.assert_almost_equal(f_y, (f_y_1 - f_y_2), decimal=5)
f_x, f_y = self.chameleon.derivatives(x=1, y=0., **kwargs_light)
npt.assert_almost_equal(f_x, 1, decimal=1)
def test_hessian(self):
"""
:return:
"""
x = np.linspace(0.1, 10, 10)
w_c, w_t = 0.5, 1.
phi_G, q = 0.3, 0.8
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
kwargs_light = {
'theta_E': 1.,
'w_c': .5,
'w_t': 1.,
'e1': e1,
'e2': e2
}
theta_E_convert, w_c, w_t = self.chameleon._theta_E_convert(theta_E=1,
w_c=0.5,
w_t=1.)
s_scale_1 = np.sqrt(4 * w_c**2 / (1. + q)**2)
s_scale_2 = np.sqrt(4 * w_t**2 / (1. + q)**2)
kwargs_1 = {
'theta_E': theta_E_convert,
's_scale': s_scale_1,
'e1': e1,
'e2': e2
}
kwargs_2 = {
'theta_E': theta_E_convert,
's_scale': s_scale_2,
'e1': e1,
'e2': e2
}
f_xx, f_yy, f_xy = self.chameleon.hessian(x=x, y=1., **kwargs_light)
f_xx_1, f_yy_1, f_xy_1 = self.nie.hessian(x=x, y=1., **kwargs_1)
f_xx_2, f_yy_2, f_xy_2 = self.nie.hessian(x=x, y=1., **kwargs_2)
npt.assert_almost_equal(f_xx, (f_xx_1 - f_xx_2), decimal=5)
npt.assert_almost_equal(f_yy, (f_yy_1 - f_yy_2), decimal=5)
npt.assert_almost_equal(f_xy, (f_xy_1 - f_xy_2), decimal=5)
def setup(self):
self.chameleon = Chameleon()
self.nie = NIE()
def _import_class(lens_type, custom_class, z_lens=None, z_source=None):
"""
:param lens_type: string, lens model type
:param custom_class: custom class
:param z_lens: lens redshift # currently only used in NFW_MC model as this is redshift dependent
:param z_source: source redshift # currently only used in NFW_MC model as this is redshift dependent
:return: class instance of the lens model type
"""
if lens_type == 'SHIFT':
from lenstronomy.LensModel.Profiles.alpha_shift import Shift
return Shift()
elif lens_type == 'SHEAR':
from lenstronomy.LensModel.Profiles.shear import Shear
return Shear()
elif lens_type == 'SHEAR_GAMMA_PSI':
from lenstronomy.LensModel.Profiles.shear import ShearGammaPsi
return ShearGammaPsi()
elif lens_type == 'CONVERGENCE':
from lenstronomy.LensModel.Profiles.convergence import Convergence
return Convergence()
elif lens_type == 'FLEXION':
from lenstronomy.LensModel.Profiles.flexion import Flexion
return Flexion()
elif lens_type == 'FLEXIONFG':
from lenstronomy.LensModel.Profiles.flexionfg import Flexionfg
return Flexionfg()
elif lens_type == 'POINT_MASS':
from lenstronomy.LensModel.Profiles.point_mass import PointMass
return PointMass()
elif lens_type == 'SIS':
from lenstronomy.LensModel.Profiles.sis import SIS
return SIS()
elif lens_type == 'SIS_TRUNCATED':
from lenstronomy.LensModel.Profiles.sis_truncate import SIS_truncate
return SIS_truncate()
elif lens_type == 'SIE':
from lenstronomy.LensModel.Profiles.sie import SIE
return SIE()
elif lens_type == 'SPP':
from lenstronomy.LensModel.Profiles.spp import SPP
return SPP()
elif lens_type == 'NIE':
from lenstronomy.LensModel.Profiles.nie import NIE
return NIE()
elif lens_type == 'NIE_SIMPLE':
from lenstronomy.LensModel.Profiles.nie import NIEMajorAxis
return NIEMajorAxis()
elif lens_type == 'CHAMELEON':
from lenstronomy.LensModel.Profiles.chameleon import Chameleon
return Chameleon()
elif lens_type == 'DOUBLE_CHAMELEON':
from lenstronomy.LensModel.Profiles.chameleon import DoubleChameleon
return DoubleChameleon()
elif lens_type == 'TRIPLE_CHAMELEON':
from lenstronomy.LensModel.Profiles.chameleon import TripleChameleon
return TripleChameleon()
elif lens_type == 'SPEP':
from lenstronomy.LensModel.Profiles.spep import SPEP
return SPEP()
elif lens_type == 'SPEMD':
from lenstronomy.LensModel.Profiles.spemd import SPEMD
return SPEMD()
elif lens_type == 'SPEMD_SMOOTH':
from lenstronomy.LensModel.Profiles.spemd_smooth import SPEMD_SMOOTH
return SPEMD_SMOOTH()
elif lens_type == 'NFW':
from lenstronomy.LensModel.Profiles.nfw import NFW
return NFW()
elif lens_type == 'NFW_ELLIPSE':
from lenstronomy.LensModel.Profiles.nfw_ellipse import NFW_ELLIPSE
return NFW_ELLIPSE()
elif lens_type == 'NFW_ELLIPSE_GAUSS_DEC':
from lenstronomy.LensModel.Profiles.gauss_decomposition import NFWEllipseGaussDec
return NFWEllipseGaussDec()
elif lens_type == 'TNFW':
from lenstronomy.LensModel.Profiles.tnfw import TNFW
return TNFW()
elif lens_type == 'CNFW':
from lenstronomy.LensModel.Profiles.cnfw import CNFW
return CNFW()
elif lens_type == 'CNFW_ELLIPSE':
from lenstronomy.LensModel.Profiles.cnfw_ellipse import CNFW_ELLIPSE
return CNFW_ELLIPSE()
elif lens_type == 'CTNFW_GAUSS_DEC':
from lenstronomy.LensModel.Profiles.gauss_decomposition import CTNFWGaussDec
return CTNFWGaussDec()
elif lens_type == 'NFW_MC':
from lenstronomy.LensModel.Profiles.nfw_mass_concentration import NFWMC
return NFWMC(z_lens=z_lens, z_source=z_source)
elif lens_type == 'SERSIC':
from lenstronomy.LensModel.Profiles.sersic import Sersic
return Sersic()
elif lens_type == 'SERSIC_ELLIPSE_POTENTIAL':
from lenstronomy.LensModel.Profiles.sersic_ellipse_potential import SersicEllipse
return SersicEllipse()
elif lens_type == 'SERSIC_ELLIPSE_KAPPA':
from lenstronomy.LensModel.Profiles.sersic_ellipse_kappa import SersicEllipseKappa
return SersicEllipseKappa()
elif lens_type == 'SERSIC_ELLIPSE_GAUSS_DEC':
from lenstronomy.LensModel.Profiles.gauss_decomposition \
import SersicEllipseGaussDec
return SersicEllipseGaussDec()
elif lens_type == 'PJAFFE':
from lenstronomy.LensModel.Profiles.p_jaffe import PJaffe
return PJaffe()
elif lens_type == 'PJAFFE_ELLIPSE':
from lenstronomy.LensModel.Profiles.p_jaffe_ellipse import PJaffe_Ellipse
return PJaffe_Ellipse()
elif lens_type == 'HERNQUIST':
from lenstronomy.LensModel.Profiles.hernquist import Hernquist
return Hernquist()
elif lens_type == 'HERNQUIST_ELLIPSE':
from lenstronomy.LensModel.Profiles.hernquist_ellipse import Hernquist_Ellipse
return Hernquist_Ellipse()
elif lens_type == 'GAUSSIAN':
from lenstronomy.LensModel.Profiles.gaussian_potential import Gaussian
return Gaussian()
elif lens_type == 'GAUSSIAN_KAPPA':
from lenstronomy.LensModel.Profiles.gaussian_kappa import GaussianKappa
return GaussianKappa()
elif lens_type == 'GAUSSIAN_ELLIPSE_KAPPA':
from lenstronomy.LensModel.Profiles.gaussian_ellipse_kappa import GaussianEllipseKappa
return GaussianEllipseKappa()
elif lens_type == 'GAUSSIAN_ELLIPSE_POTENTIAL':
from lenstronomy.LensModel.Profiles.gaussian_ellipse_potential import GaussianEllipsePotential
return GaussianEllipsePotential()
elif lens_type == 'MULTI_GAUSSIAN_KAPPA':
from lenstronomy.LensModel.Profiles.multi_gaussian_kappa import MultiGaussianKappa
return MultiGaussianKappa()
elif lens_type == 'MULTI_GAUSSIAN_KAPPA_ELLIPSE':
from lenstronomy.LensModel.Profiles.multi_gaussian_kappa import MultiGaussianKappaEllipse
return MultiGaussianKappaEllipse()
elif lens_type == 'INTERPOL':
from lenstronomy.LensModel.Profiles.interpol import Interpol
return Interpol()
elif lens_type == 'INTERPOL_SCALED':
from lenstronomy.LensModel.Profiles.interpol import InterpolScaled
return InterpolScaled()
elif lens_type == 'SHAPELETS_POLAR':
from lenstronomy.LensModel.Profiles.shapelet_pot_polar import PolarShapelets
return PolarShapelets()
elif lens_type == 'SHAPELETS_CART':
from lenstronomy.LensModel.Profiles.shapelet_pot_cartesian import CartShapelets
return CartShapelets()
elif lens_type == 'DIPOLE':
from lenstronomy.LensModel.Profiles.dipole import Dipole
return Dipole()
elif lens_type == 'CURVED_ARC':
from lenstronomy.LensModel.Profiles.curved_arc import CurvedArc
return CurvedArc()
elif lens_type == 'ARC_PERT':
from lenstronomy.LensModel.Profiles.arc_perturbations import ArcPerturbations
return ArcPerturbations()
elif lens_type == 'coreBURKERT':
from lenstronomy.LensModel.Profiles.coreBurkert import CoreBurkert
return CoreBurkert()
elif lens_type == 'CORED_DENSITY':
from lenstronomy.LensModel.Profiles.cored_density import CoredDensity
return CoredDensity()
elif lens_type == 'CORED_DENSITY_2':
from lenstronomy.LensModel.Profiles.cored_density_2 import CoredDensity2
return CoredDensity2()
elif lens_type == 'CORED_DENSITY_MST':
from lenstronomy.LensModel.Profiles.cored_density_mst import CoredDensityMST
return CoredDensityMST(profile_type='CORED_DENSITY')
elif lens_type == 'CORED_DENSITY_2_MST':
from lenstronomy.LensModel.Profiles.cored_density_mst import CoredDensityMST
return CoredDensityMST(profile_type='CORED_DENSITY_2')
elif lens_type == 'NumericalAlpha':
from lenstronomy.LensModel.Profiles.numerical_deflections import NumericalAlpha
return NumericalAlpha(custom_class)
else:
raise ValueError('%s is not a valid lens model' % lens_type)
def __init__(self, lens_model_list, **kwargs):
"""
:param lens_model_list: list of strings with lens model names
:param foreground_shear: bool, when True, models a foreground non-linear shear distortion
"""
self.func_list = []
self._foreground_shear = False
for i, lens_type in enumerate(lens_model_list):
if lens_type == 'SHEAR':
from lenstronomy.LensModel.Profiles.external_shear import ExternalShear
self.func_list.append(ExternalShear())
elif lens_type == 'CONVERGENCE':
from lenstronomy.LensModel.Profiles.mass_sheet import MassSheet
self.func_list.append(MassSheet())
elif lens_type == 'FLEXION':
from lenstronomy.LensModel.Profiles.flexion import Flexion
self.func_list.append(Flexion())
elif lens_type == 'POINT_MASS':
from lenstronomy.LensModel.Profiles.point_mass import PointMass
self.func_list.append(PointMass())
elif lens_type == 'SIS':
from lenstronomy.LensModel.Profiles.sis import SIS
self.func_list.append(SIS())
elif lens_type == 'SIS_TRUNCATED':
from lenstronomy.LensModel.Profiles.sis_truncate import SIS_truncate
self.func_list.append(SIS_truncate())
elif lens_type == 'SIE':
from lenstronomy.LensModel.Profiles.sie import SIE
self.func_list.append(SIE())
elif lens_type == 'SPP':
from lenstronomy.LensModel.Profiles.spp import SPP
self.func_list.append(SPP())
elif lens_type == 'NIE':
from lenstronomy.LensModel.Profiles.nie import NIE
self.func_list.append(NIE())
elif lens_type == 'NIE_SIMPLE':
from lenstronomy.LensModel.Profiles.nie import NIE_simple
self.func_list.append(NIE_simple())
elif lens_type == 'CHAMELEON':
from lenstronomy.LensModel.Profiles.chameleon import Chameleon
self.func_list.append(Chameleon())
elif lens_type == 'DOUBLE_CHAMELEON':
from lenstronomy.LensModel.Profiles.chameleon import DoubleChameleon
self.func_list.append(DoubleChameleon())
elif lens_type == 'SPEP':
from lenstronomy.LensModel.Profiles.spep import SPEP
self.func_list.append(SPEP())
elif lens_type == 'SPEMD':
from lenstronomy.LensModel.Profiles.spemd import SPEMD
self.func_list.append(SPEMD())
elif lens_type == 'SPEMD_SMOOTH':
from lenstronomy.LensModel.Profiles.spemd_smooth import SPEMD_SMOOTH
self.func_list.append(SPEMD_SMOOTH())
elif lens_type == 'NFW':
from lenstronomy.LensModel.Profiles.nfw import NFW
self.func_list.append(NFW(**kwargs))
elif lens_type == 'NFW_ELLIPSE':
from lenstronomy.LensModel.Profiles.nfw_ellipse import NFW_ELLIPSE
self.func_list.append(
NFW_ELLIPSE(interpol=False,
num_interp_X=1000,
max_interp_X=100))
elif lens_type == 'TNFW':
from lenstronomy.LensModel.Profiles.tnfw import TNFW
self.func_list.append(TNFW())
elif lens_type == 'SERSIC':
from lenstronomy.LensModel.Profiles.sersic import Sersic
self.func_list.append(Sersic())
elif lens_type == 'SERSIC_ELLIPSE':
from lenstronomy.LensModel.Profiles.sersic_ellipse import SersicEllipse
self.func_list.append(SersicEllipse())
elif lens_type == 'PJAFFE':
from lenstronomy.LensModel.Profiles.p_jaffe import PJaffe
self.func_list.append(PJaffe())
elif lens_type == 'PJAFFE_ELLIPSE':
from lenstronomy.LensModel.Profiles.p_jaffe_ellipse import PJaffe_Ellipse
self.func_list.append(PJaffe_Ellipse())
elif lens_type == 'HERNQUIST':
from lenstronomy.LensModel.Profiles.hernquist import Hernquist
self.func_list.append(Hernquist())
elif lens_type == 'HERNQUIST_ELLIPSE':
from lenstronomy.LensModel.Profiles.hernquist_ellipse import Hernquist_Ellipse
self.func_list.append(Hernquist_Ellipse())
elif lens_type == 'GAUSSIAN':
from lenstronomy.LensModel.Profiles.gaussian_potential import Gaussian
self.func_list.append(Gaussian())
elif lens_type == 'GAUSSIAN_KAPPA':
from lenstronomy.LensModel.Profiles.gaussian_kappa import GaussianKappa
self.func_list.append(GaussianKappa())
elif lens_type == 'GAUSSIAN_KAPPA_ELLIPSE':
from lenstronomy.LensModel.Profiles.gaussian_kappa_ellipse import GaussianKappaEllipse
self.func_list.append(GaussianKappaEllipse())
elif lens_type == 'MULTI_GAUSSIAN_KAPPA':
from lenstronomy.LensModel.Profiles.multi_gaussian_kappa import MultiGaussianKappa
self.func_list.append(MultiGaussianKappa())
elif lens_type == 'MULTI_GAUSSIAN_KAPPA_ELLIPSE':
from lenstronomy.LensModel.Profiles.multi_gaussian_kappa import MultiGaussianKappaEllipse
self.func_list.append(MultiGaussianKappaEllipse())
elif lens_type == 'INTERPOL':
from lenstronomy.LensModel.Profiles.interpol import Interpol_func
self.func_list.append(
Interpol_func(grid=False, min_grid_number=100))
elif lens_type == 'INTERPOL_SCALED':
from lenstronomy.LensModel.Profiles.interpol import Interpol_func_scaled
self.func_list.append(
Interpol_func_scaled(grid=False, min_grid_number=100))
elif lens_type == 'SHAPELETS_POLAR':
from lenstronomy.LensModel.Profiles.shapelet_pot_polar import PolarShapelets
self.func_list.append(PolarShapelets())
elif lens_type == 'SHAPELETS_CART':
from lenstronomy.LensModel.Profiles.shapelet_pot_cartesian import CartShapelets
self.func_list.append(CartShapelets())
elif lens_type == 'DIPOLE':
from lenstronomy.LensModel.Profiles.dipole import Dipole
self.func_list.append(Dipole())
elif lens_type == 'FOREGROUND_SHEAR':
from lenstronomy.LensModel.Profiles.external_shear import ExternalShear
self.func_list.append(ExternalShear())
self._foreground_shear = True
self._foreground_shear_idex = i
else:
raise ValueError('%s is not a valid lens model' % lens_type)
self._model_list = lens_model_list
def _import_class(self, lens_type, i, custom_class):
if lens_type == 'SHIFT':
from lenstronomy.LensModel.Profiles.alpha_shift import Shift
return Shift()
elif lens_type == 'SHEAR':
from lenstronomy.LensModel.Profiles.shear import Shear
return Shear()
elif lens_type == 'CONVERGENCE':
from lenstronomy.LensModel.Profiles.convergence import Convergence
return Convergence()
elif lens_type == 'FLEXION':
from lenstronomy.LensModel.Profiles.flexion import Flexion
return Flexion()
elif lens_type == 'POINT_MASS':
from lenstronomy.LensModel.Profiles.point_mass import PointMass
return PointMass()
elif lens_type == 'SIS':
from lenstronomy.LensModel.Profiles.sis import SIS
return SIS()
elif lens_type == 'SIS_TRUNCATED':
from lenstronomy.LensModel.Profiles.sis_truncate import SIS_truncate
return SIS_truncate()
elif lens_type == 'SIE':
from lenstronomy.LensModel.Profiles.sie import SIE
return SIE()
elif lens_type == 'SPP':
from lenstronomy.LensModel.Profiles.spp import SPP
return SPP()
elif lens_type == 'NIE':
from lenstronomy.LensModel.Profiles.nie import NIE
return NIE()
elif lens_type == 'NIE_SIMPLE':
from lenstronomy.LensModel.Profiles.nie import NIE_simple
return NIE_simple()
elif lens_type == 'CHAMELEON':
from lenstronomy.LensModel.Profiles.chameleon import Chameleon
return Chameleon()
elif lens_type == 'DOUBLE_CHAMELEON':
from lenstronomy.LensModel.Profiles.chameleon import DoubleChameleon
return DoubleChameleon()
elif lens_type == 'SPEP':
from lenstronomy.LensModel.Profiles.spep import SPEP
return SPEP()
elif lens_type == 'SPEMD':
from lenstronomy.LensModel.Profiles.spemd import SPEMD
return SPEMD()
elif lens_type == 'SPEMD_SMOOTH':
from lenstronomy.LensModel.Profiles.spemd_smooth import SPEMD_SMOOTH
return SPEMD_SMOOTH()
elif lens_type == 'NFW':
from lenstronomy.LensModel.Profiles.nfw import NFW
return NFW()
elif lens_type == 'NFW_ELLIPSE':
from lenstronomy.LensModel.Profiles.nfw_ellipse import NFW_ELLIPSE
return NFW_ELLIPSE()
elif lens_type == 'TNFW':
from lenstronomy.LensModel.Profiles.tnfw import TNFW
return TNFW()
elif lens_type == 'CNFW':
from lenstronomy.LensModel.Profiles.cnfw import CNFW
return CNFW()
elif lens_type == 'SERSIC':
from lenstronomy.LensModel.Profiles.sersic import Sersic
return Sersic()
elif lens_type == 'SERSIC_ELLIPSE':
from lenstronomy.LensModel.Profiles.sersic_ellipse import SersicEllipse
return SersicEllipse()
elif lens_type == 'PJAFFE':
from lenstronomy.LensModel.Profiles.p_jaffe import PJaffe
return PJaffe()
elif lens_type == 'PJAFFE_ELLIPSE':
from lenstronomy.LensModel.Profiles.p_jaffe_ellipse import PJaffe_Ellipse
return PJaffe_Ellipse()
elif lens_type == 'HERNQUIST':
from lenstronomy.LensModel.Profiles.hernquist import Hernquist
return Hernquist()
elif lens_type == 'HERNQUIST_ELLIPSE':
from lenstronomy.LensModel.Profiles.hernquist_ellipse import Hernquist_Ellipse
return Hernquist_Ellipse()
elif lens_type == 'GAUSSIAN':
from lenstronomy.LensModel.Profiles.gaussian_potential import Gaussian
return Gaussian()
elif lens_type == 'GAUSSIAN_KAPPA':
from lenstronomy.LensModel.Profiles.gaussian_kappa import GaussianKappa
return GaussianKappa()
elif lens_type == 'GAUSSIAN_KAPPA_ELLIPSE':
from lenstronomy.LensModel.Profiles.gaussian_kappa_ellipse import GaussianKappaEllipse
return GaussianKappaEllipse()
elif lens_type == 'MULTI_GAUSSIAN_KAPPA':
from lenstronomy.LensModel.Profiles.multi_gaussian_kappa import MultiGaussianKappa
return MultiGaussianKappa()
elif lens_type == 'MULTI_GAUSSIAN_KAPPA_ELLIPSE':
from lenstronomy.LensModel.Profiles.multi_gaussian_kappa import MultiGaussianKappaEllipse
return MultiGaussianKappaEllipse()
elif lens_type == 'INTERPOL':
from lenstronomy.LensModel.Profiles.interpol import Interpol
return Interpol(grid=False, min_grid_number=100)
elif lens_type == 'INTERPOL_SCALED':
from lenstronomy.LensModel.Profiles.interpol import InterpolScaled
return InterpolScaled()
elif lens_type == 'SHAPELETS_POLAR':
from lenstronomy.LensModel.Profiles.shapelet_pot_polar import PolarShapelets
return PolarShapelets()
elif lens_type == 'SHAPELETS_CART':
from lenstronomy.LensModel.Profiles.shapelet_pot_cartesian import CartShapelets
return CartShapelets()
elif lens_type == 'DIPOLE':
from lenstronomy.LensModel.Profiles.dipole import Dipole
return Dipole()
elif lens_type == 'FOREGROUND_SHEAR':
from lenstronomy.LensModel.Profiles.shear import Shear
self._foreground_shear = True
self._foreground_shear_idex = i
return Shear()
elif lens_type == 'coreBURKERT':
from lenstronomy.LensModel.Profiles.coreBurkert import coreBurkert
return coreBurkert()
elif lens_type == 'NumericalAlpha':
from lenstronomy.LensModel.Profiles.numerical_deflections import NumericalAlpha
return NumericalAlpha(custom_class[i])
else:
raise ValueError('%s is not a valid lens model' % lens_type)
def _import_class(lens_type,
custom_class,
kwargs_interp,
z_lens=None,
z_source=None):
"""
:param lens_type: string, lens model type
:param custom_class: custom class
:param z_lens: lens redshift # currently only used in NFW_MC model as this is redshift dependent
:param z_source: source redshift # currently only used in NFW_MC model as this is redshift dependent
:param kwargs_interp: interpolation keyword arguments specifying the numerics.
See description in the Interpolate() class. Only applicable for 'INTERPOL' and 'INTERPOL_SCALED' models.
:return: class instance of the lens model type
"""
if lens_type == 'SHIFT':
from lenstronomy.LensModel.Profiles.constant_shift import Shift
return Shift()
elif lens_type == 'NIE_POTENTIAL':
from lenstronomy.LensModel.Profiles.nie_potential import NIE_POTENTIAL
return NIE_POTENTIAL()
elif lens_type == 'CONST_MAG':
from lenstronomy.LensModel.Profiles.const_mag import ConstMag
return ConstMag()
elif lens_type == 'SHEAR':
from lenstronomy.LensModel.Profiles.shear import Shear
return Shear()
elif lens_type == 'SHEAR_GAMMA_PSI':
from lenstronomy.LensModel.Profiles.shear import ShearGammaPsi
return ShearGammaPsi()
elif lens_type == 'SHEAR_REDUCED':
from lenstronomy.LensModel.Profiles.shear import ShearReduced
return ShearReduced()
elif lens_type == 'CONVERGENCE':
from lenstronomy.LensModel.Profiles.convergence import Convergence
return Convergence()
elif lens_type == 'HESSIAN':
from lenstronomy.LensModel.Profiles.hessian import Hessian
return Hessian()
elif lens_type == 'FLEXION':
from lenstronomy.LensModel.Profiles.flexion import Flexion
return Flexion()
elif lens_type == 'FLEXIONFG':
from lenstronomy.LensModel.Profiles.flexionfg import Flexionfg
return Flexionfg()
elif lens_type == 'POINT_MASS':
from lenstronomy.LensModel.Profiles.point_mass import PointMass
return PointMass()
elif lens_type == 'SIS':
from lenstronomy.LensModel.Profiles.sis import SIS
return SIS()
elif lens_type == 'SIS_TRUNCATED':
from lenstronomy.LensModel.Profiles.sis_truncate import SIS_truncate
return SIS_truncate()
elif lens_type == 'SIE':
from lenstronomy.LensModel.Profiles.sie import SIE
return SIE()
elif lens_type == 'SPP':
from lenstronomy.LensModel.Profiles.spp import SPP
return SPP()
elif lens_type == 'NIE':
from lenstronomy.LensModel.Profiles.nie import NIE
return NIE()
elif lens_type == 'NIE_SIMPLE':
from lenstronomy.LensModel.Profiles.nie import NIEMajorAxis
return NIEMajorAxis()
elif lens_type == 'CHAMELEON':
from lenstronomy.LensModel.Profiles.chameleon import Chameleon
return Chameleon()
elif lens_type == 'DOUBLE_CHAMELEON':
from lenstronomy.LensModel.Profiles.chameleon import DoubleChameleon
return DoubleChameleon()
elif lens_type == 'TRIPLE_CHAMELEON':
from lenstronomy.LensModel.Profiles.chameleon import TripleChameleon
return TripleChameleon()
elif lens_type == 'SPEP':
from lenstronomy.LensModel.Profiles.spep import SPEP
return SPEP()
elif lens_type == 'PEMD':
from lenstronomy.LensModel.Profiles.pemd import PEMD
return PEMD()
elif lens_type == 'SPEMD':
from lenstronomy.LensModel.Profiles.spemd import SPEMD
return SPEMD()
elif lens_type == 'EPL':
from lenstronomy.LensModel.Profiles.epl import EPL
return EPL()
elif lens_type == 'EPL_NUMBA':
from lenstronomy.LensModel.Profiles.epl_numba import EPL_numba
return EPL_numba()
elif lens_type == 'SPL_CORE':
from lenstronomy.LensModel.Profiles.splcore import SPLCORE
return SPLCORE()
elif lens_type == 'NFW':
from lenstronomy.LensModel.Profiles.nfw import NFW
return NFW()
elif lens_type == 'NFW_ELLIPSE':
from lenstronomy.LensModel.Profiles.nfw_ellipse import NFW_ELLIPSE
return NFW_ELLIPSE()
elif lens_type == 'NFW_ELLIPSE_GAUSS_DEC':
from lenstronomy.LensModel.Profiles.gauss_decomposition import NFWEllipseGaussDec
return NFWEllipseGaussDec()
elif lens_type == 'NFW_ELLIPSE_CSE':
from lenstronomy.LensModel.Profiles.nfw_ellipse_cse import NFW_ELLIPSE_CSE
return NFW_ELLIPSE_CSE()
elif lens_type == 'TNFW':
from lenstronomy.LensModel.Profiles.tnfw import TNFW
return TNFW()
elif lens_type == 'TNFW_ELLIPSE':
from lenstronomy.LensModel.Profiles.tnfw_ellipse import TNFW_ELLIPSE
return TNFW_ELLIPSE()
elif lens_type == 'CNFW':
from lenstronomy.LensModel.Profiles.cnfw import CNFW
return CNFW()
elif lens_type == 'CNFW_ELLIPSE':
from lenstronomy.LensModel.Profiles.cnfw_ellipse import CNFW_ELLIPSE
return CNFW_ELLIPSE()
elif lens_type == 'CTNFW_GAUSS_DEC':
from lenstronomy.LensModel.Profiles.gauss_decomposition import CTNFWGaussDec
return CTNFWGaussDec()
elif lens_type == 'NFW_MC':
from lenstronomy.LensModel.Profiles.nfw_mass_concentration import NFWMC
return NFWMC(z_lens=z_lens, z_source=z_source)
elif lens_type == 'SERSIC':
from lenstronomy.LensModel.Profiles.sersic import Sersic
return Sersic()
elif lens_type == 'SERSIC_ELLIPSE_POTENTIAL':
from lenstronomy.LensModel.Profiles.sersic_ellipse_potential import SersicEllipse
return SersicEllipse()
elif lens_type == 'SERSIC_ELLIPSE_KAPPA':
from lenstronomy.LensModel.Profiles.sersic_ellipse_kappa import SersicEllipseKappa
return SersicEllipseKappa()
elif lens_type == 'SERSIC_ELLIPSE_GAUSS_DEC':
from lenstronomy.LensModel.Profiles.gauss_decomposition import SersicEllipseGaussDec
return SersicEllipseGaussDec()
elif lens_type == 'PJAFFE':
from lenstronomy.LensModel.Profiles.p_jaffe import PJaffe
return PJaffe()
elif lens_type == 'PJAFFE_ELLIPSE':
from lenstronomy.LensModel.Profiles.p_jaffe_ellipse import PJaffe_Ellipse
return PJaffe_Ellipse()
elif lens_type == 'HERNQUIST':
from lenstronomy.LensModel.Profiles.hernquist import Hernquist
return Hernquist()
elif lens_type == 'HERNQUIST_ELLIPSE':
from lenstronomy.LensModel.Profiles.hernquist_ellipse import Hernquist_Ellipse
return Hernquist_Ellipse()
elif lens_type == 'HERNQUIST_ELLIPSE_CSE':
from lenstronomy.LensModel.Profiles.hernquist_ellipse_cse import HernquistEllipseCSE
return HernquistEllipseCSE()
elif lens_type == 'GAUSSIAN':
from lenstronomy.LensModel.Profiles.gaussian_potential import Gaussian
return Gaussian()
elif lens_type == 'GAUSSIAN_KAPPA':
from lenstronomy.LensModel.Profiles.gaussian_kappa import GaussianKappa
return GaussianKappa()
elif lens_type == 'GAUSSIAN_ELLIPSE_KAPPA':
from lenstronomy.LensModel.Profiles.gaussian_ellipse_kappa import GaussianEllipseKappa
return GaussianEllipseKappa()
elif lens_type == 'GAUSSIAN_ELLIPSE_POTENTIAL':
from lenstronomy.LensModel.Profiles.gaussian_ellipse_potential import GaussianEllipsePotential
return GaussianEllipsePotential()
elif lens_type == 'MULTI_GAUSSIAN_KAPPA':
from lenstronomy.LensModel.Profiles.multi_gaussian_kappa import MultiGaussianKappa
return MultiGaussianKappa()
elif lens_type == 'MULTI_GAUSSIAN_KAPPA_ELLIPSE':
from lenstronomy.LensModel.Profiles.multi_gaussian_kappa import MultiGaussianKappaEllipse
return MultiGaussianKappaEllipse()
elif lens_type == 'INTERPOL':
from lenstronomy.LensModel.Profiles.interpol import Interpol
return Interpol(**kwargs_interp)
elif lens_type == 'INTERPOL_SCALED':
from lenstronomy.LensModel.Profiles.interpol import InterpolScaled
return InterpolScaled(**kwargs_interp)
elif lens_type == 'SHAPELETS_POLAR':
from lenstronomy.LensModel.Profiles.shapelet_pot_polar import PolarShapelets
return PolarShapelets()
elif lens_type == 'SHAPELETS_CART':
from lenstronomy.LensModel.Profiles.shapelet_pot_cartesian import CartShapelets
return CartShapelets()
elif lens_type == 'DIPOLE':
from lenstronomy.LensModel.Profiles.dipole import Dipole
return Dipole()
elif lens_type == 'CURVED_ARC_CONST':
from lenstronomy.LensModel.Profiles.curved_arc_const import CurvedArcConst
return CurvedArcConst()
elif lens_type == 'CURVED_ARC_CONST_MST':
from lenstronomy.LensModel.Profiles.curved_arc_const import CurvedArcConstMST
return CurvedArcConstMST()
elif lens_type == 'CURVED_ARC_SPP':
from lenstronomy.LensModel.Profiles.curved_arc_spp import CurvedArcSPP
return CurvedArcSPP()
elif lens_type == 'CURVED_ARC_SIS_MST':
from lenstronomy.LensModel.Profiles.curved_arc_sis_mst import CurvedArcSISMST
return CurvedArcSISMST()
elif lens_type == 'CURVED_ARC_SPT':
from lenstronomy.LensModel.Profiles.curved_arc_spt import CurvedArcSPT
return CurvedArcSPT()
elif lens_type == 'CURVED_ARC_TAN_DIFF':
from lenstronomy.LensModel.Profiles.curved_arc_tan_diff import CurvedArcTanDiff
return CurvedArcTanDiff()
elif lens_type == 'ARC_PERT':
from lenstronomy.LensModel.Profiles.arc_perturbations import ArcPerturbations
return ArcPerturbations()
elif lens_type == 'coreBURKERT':
from lenstronomy.LensModel.Profiles.coreBurkert import CoreBurkert
return CoreBurkert()
elif lens_type == 'CORED_DENSITY':
from lenstronomy.LensModel.Profiles.cored_density import CoredDensity
return CoredDensity()
elif lens_type == 'CORED_DENSITY_2':
from lenstronomy.LensModel.Profiles.cored_density_2 import CoredDensity2
return CoredDensity2()
elif lens_type == 'CORED_DENSITY_EXP':
from lenstronomy.LensModel.Profiles.cored_density_exp import CoredDensityExp
return CoredDensityExp()
elif lens_type == 'CORED_DENSITY_MST':
from lenstronomy.LensModel.Profiles.cored_density_mst import CoredDensityMST
return CoredDensityMST(profile_type='CORED_DENSITY')
elif lens_type == 'CORED_DENSITY_2_MST':
from lenstronomy.LensModel.Profiles.cored_density_mst import CoredDensityMST
return CoredDensityMST(profile_type='CORED_DENSITY_2')
elif lens_type == 'CORED_DENSITY_EXP_MST':
from lenstronomy.LensModel.Profiles.cored_density_mst import CoredDensityMST
return CoredDensityMST(profile_type='CORED_DENSITY_EXP')
elif lens_type == 'NumericalAlpha':
from lenstronomy.LensModel.Profiles.numerical_deflections import NumericalAlpha
return NumericalAlpha(custom_class)
elif lens_type == 'MULTIPOLE':
from lenstronomy.LensModel.Profiles.multipole import Multipole
return Multipole()
elif lens_type == 'CSE':
from lenstronomy.LensModel.Profiles.cored_steep_ellipsoid import CSE
return CSE()
elif lens_type == 'ElliSLICE':
from lenstronomy.LensModel.Profiles.elliptical_density_slice import ElliSLICE
return ElliSLICE()
elif lens_type == 'ULDM':
from lenstronomy.LensModel.Profiles.uldm import Uldm
return Uldm()
elif lens_type == 'CORED_DENSITY_ULDM_MST':
from lenstronomy.LensModel.Profiles.cored_density_mst import CoredDensityMST
return CoredDensityMST(profile_type='CORED_DENSITY_ULDM')
else:
raise ValueError(
'%s is not a valid lens model. Supported are: %s.' %
(lens_type, _SUPPORTED_MODELS))
class TestChameleon(object):
"""
class to test the Moffat profile
"""
def setup(self):
self.chameleon = Chameleon()
self.nie = NIE()
def test_theta_E_convert(self):
w_c, w_t = 2, 1
theta_E_convert, w_c, w_t, s_scale_1, s_scale_2 = self.chameleon.param_convert(
alpha_1=1, w_c=w_c, w_t=w_t, e1=0, e2=0)
assert w_c == 1
assert w_t == 2
assert theta_E_convert == 0
def test_function(self):
"""
:return:
"""
x = np.linspace(0.1, 10, 10)
w_c, w_t = 0.5, 1.
phi_G, q = 0.3, 0.8
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
kwargs_light = {
'alpha_1': 1.,
'w_c': .5,
'w_t': 1.,
'e1': e1,
'e2': e2
}
theta_E_convert, w_c, w_t, s_scale_1, s_scale_2 = self.chameleon.param_convert(
alpha_1=1, w_c=0.5, w_t=1., e1=e1, e2=e2)
kwargs_1 = {
'theta_E': theta_E_convert,
's_scale': s_scale_1,
'e1': e1,
'e2': e2
}
kwargs_2 = {
'theta_E': theta_E_convert,
's_scale': s_scale_2,
'e1': e1,
'e2': e2
}
f_ = self.chameleon.function(x=x, y=1., **kwargs_light)
f_1 = self.nie.function(x=x, y=1., **kwargs_1)
f_2 = self.nie.function(x=x, y=1., **kwargs_2)
npt.assert_almost_equal(f_, (f_1 - f_2), decimal=5)
def test_derivatives(self):
"""
:return:
"""
x = np.linspace(0.1, 10, 10)
w_c, w_t = 0.5, 1.
phi_G, q = 0.3, 0.8
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
kwargs_light = {
'alpha_1': 1.,
'w_c': .5,
'w_t': 1.,
'e1': e1,
'e2': e2
}
theta_E_convert, w_c, w_t, s_scale_1, s_scale_2 = self.chameleon.param_convert(
alpha_1=1, w_c=0.5, w_t=1., e1=e1, e2=e2)
kwargs_1 = {
'theta_E': theta_E_convert,
's_scale': s_scale_1,
'e1': e1,
'e2': e2
}
kwargs_2 = {
'theta_E': theta_E_convert,
's_scale': s_scale_2,
'e1': e1,
'e2': e2
}
f_x, f_y = self.chameleon.derivatives(x=x, y=1., **kwargs_light)
f_x_1, f_y_1 = self.nie.derivatives(x=x, y=1., **kwargs_1)
f_x_2, f_y_2 = self.nie.derivatives(x=x, y=1., **kwargs_2)
npt.assert_almost_equal(f_x, (f_x_1 - f_x_2), decimal=5)
npt.assert_almost_equal(f_y, (f_y_1 - f_y_2), decimal=5)
f_x, f_y = self.chameleon.derivatives(x=1, y=0., **kwargs_light)
npt.assert_almost_equal(f_x, 1, decimal=1)
def test_hessian(self):
"""
:return:
"""
x = np.linspace(0.1, 10, 10)
w_c, w_t = 0.5, 1.
phi_G, q = 0.3, 0.8
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
kwargs_light = {
'alpha_1': 1.,
'w_c': .5,
'w_t': 1.,
'e1': e1,
'e2': e2
}
theta_E_convert, w_c, w_t, s_scale_1, s_scale_2 = self.chameleon.param_convert(
alpha_1=1, w_c=0.5, w_t=1., e1=e1, e2=e2)
kwargs_1 = {
'theta_E': theta_E_convert,
's_scale': s_scale_1,
'e1': e1,
'e2': e2
}
kwargs_2 = {
'theta_E': theta_E_convert,
's_scale': s_scale_2,
'e1': e1,
'e2': e2
}
f_xx, f_xy, f_yx, f_yy = self.chameleon.hessian(x=x,
y=1.,
**kwargs_light)
f_xx_1, f_xy_1, f_yx_1, f_yy_1 = self.nie.hessian(x=x,
y=1.,
**kwargs_1)
f_xx_2, f_xy_2, f_yx_2, f_yy_2 = self.nie.hessian(x=x,
y=1.,
**kwargs_2)
npt.assert_almost_equal(f_xx, (f_xx_1 - f_xx_2), decimal=5)
npt.assert_almost_equal(f_yy, (f_yy_1 - f_yy_2), decimal=5)
npt.assert_almost_equal(f_xy, (f_xy_1 - f_xy_2), decimal=5)
npt.assert_almost_equal(f_yx, (f_yx_1 - f_yx_2), decimal=5)
def test_static(self):
x, y = 1., 1.
phi_G, q = 0.3, 0.8
e1, e2 = param_util.phi_q2_ellipticity(phi_G, q)
kwargs_light = {
'alpha_1': 1.,
'w_c': .5,
'w_t': 1.,
'e1': e1,
'e2': e2
}
f_ = self.chameleon.function(x, y, **kwargs_light)
self.chameleon.set_static(**kwargs_light)
f_static = self.chameleon.function(x, y, **kwargs_light)
npt.assert_almost_equal(f_, f_static, decimal=8)
self.chameleon.set_dynamic()
kwargs_light = {
'alpha_1': 2.,
'w_c': .5,
'w_t': 1.,
'e1': e1,
'e2': e2
}
f_dyn = self.chameleon.function(x, y, **kwargs_light)
assert f_dyn != f_static
def __init__(self):
self.nie = NIE()
self._chameleonLens = ChameleonLens()
