def __init__(self):
"""
"""
self.tnfw = TNFW()
self._diff = 0.0000000001
super(TNFW_ELLIPSE, self).__init__()
class TestcoreTNFWDeflection(object):
def setup(self):
self.interp = CoreTNFWDeflection()
self.tnfw = TNFW()
def test_deflection_point(self):
x = 0.
y = 0.
Rs = 0.1
r_core = 0.04
r_trunc = 0.5
norm = 1.
alpha_origin = self.interp(x, y, Rs, r_core, r_trunc, norm)
npt.assert_almost_equal(alpha_origin, 0.)
x = Rs/np.sqrt(2)
y = Rs/np.sqrt(2)
alpha_Rs = 10.
alpha_tnfw,_ = self.tnfw.derivatives(Rs, 0., Rs, alpha_Rs, r_trunc)
alpha_rs_x, alpha_rs_y = self.interp(x, y, Rs, r_core, r_trunc, norm=1.)
alpha_rs_interp_x, alpha_rs_interp_y = self.interp(x, y, Rs, r_core,
r_trunc, norm=alpha_tnfw)
npt.assert_almost_equal(alpha_rs_interp_x / alpha_rs_x, alpha_tnfw)
npt.assert_almost_equal(alpha_rs_interp_y / alpha_rs_y, alpha_tnfw)
def test_deflection_array(self):
x = np.array([0., 0.])
y = 0.
Rs = 0.1
r_core = 0.04
r_trunc = 0.5
norm = 1.
alpha_origin_x, alpha_origin_y = self.interp(x, y, Rs, r_core, r_trunc, norm)
npt.assert_almost_equal(alpha_origin_y, 0.)
npt.assert_almost_equal(alpha_origin_x, 0.)
x = np.array([Rs / np.sqrt(2), Rs/np.sqrt(2)])
y = np.array([Rs / np.sqrt(2), Rs/np.sqrt(2)])
alpha_Rs = 10.
alpha_tnfw, _ = self.tnfw.derivatives(Rs, 0., Rs, alpha_Rs, r_trunc)
alpha_rs_interp_x, alpha_rs_interp_y = self.interp(x, y, Rs, r_core, r_trunc, norm=1.)
alpha_rs = self.interp(x, y, Rs, r_core, r_trunc, norm=alpha_tnfw)
npt.assert_almost_equal(alpha_rs / alpha_rs_interp_x, alpha_tnfw)
npt.assert_almost_equal(alpha_rs / alpha_rs_interp_y, alpha_tnfw)
def __init__(self):
self.deflections = 10**log_deflection_angle
self.tau = np.arange(1, 31, 1)
self.beta = np.arange(0.0025, 1.005, 0.005)
log_xnfw = np.log10(np.logspace(-3, 2, 100))
self.split = []
self.log_xmin, self.log_xmax = log_xnfw[0], log_xnfw[-1]
self._betamin = self.beta[0]
self._betamax = self.beta[-1]
self._delta_beta = self.beta[2] - self.beta[1]
self._logx_domain = log_xnfw
self._tau_min = self.tau[0]
self._tau_max = self.tau[-1]
self._delta_tau = self.tau[1] - self.tau[0]
interp_list = []
for i, bi in enumerate(self.beta):
interp_list_tau = []
for j, tj in enumerate(self.tau):
interp = interp1d(log_xnfw, log_deflection_angle[i, j, :])
interp_list_tau.append(interp)
interp_list.append(interp_list_tau)
self._interp_list = interp_list
self._tnfw_profile = TNFW()
def setup(self):
self.nfw = NFW()
self.tnfw = TNFW()
class TestTNFW(object):
def setup(self):
self.nfw = NFW()
self.tnfw = TNFW()
def test_deflection(self):
Rs = 0.2
alpha_Rs = 0.1
r_trunc = 1000000000000 * Rs
x = np.linspace(0.0 * Rs, 5 * Rs, 1000)
y = np.linspace(0., 1, 1000)
xdef_t, ydef_t = self.tnfw.derivatives(x, y, Rs, alpha_Rs, r_trunc)
xdef, ydef = self.nfw.derivatives(x, y, Rs, alpha_Rs)
np.testing.assert_almost_equal(xdef_t, xdef, 5)
np.testing.assert_almost_equal(ydef_t, ydef, 5)
def test_potential(self):
Rs = 0.2
alpha_Rs = 0.1
r_trunc = 1000000000000 * Rs
x = np.linspace(0.1 * Rs, 5 * Rs, 1000)
y = np.linspace(0.2, 1, 1000)
pot_t = self.tnfw.function(x, y, Rs, alpha_Rs, r_trunc)
pot = self.nfw.function(x, y, Rs, alpha_Rs)
np.testing.assert_almost_equal(pot, pot_t, 4)
Rs = 0.2
alpha_Rs = 0.1
r_trunc = 1000000000000 * Rs
x = np.linspace(0.1, 0.7, 100)
pot1 = self.tnfw.function(x, 0, Rs, alpha_Rs, r_trunc)
pot_nfw1 = self.nfw.function(x, 0, Rs, alpha_Rs)
npt.assert_almost_equal(pot1, pot_nfw1, 5)
def test_gamma(self):
Rs = 0.2
alpha_Rs = 0.1
r_trunc = 1000000000000 * Rs
x = np.linspace(0.1 * Rs, 5 * Rs, 1000)
y = np.linspace(0.2, 1, 1000)
g1t, g2t = self.tnfw.nfwGamma((x**2 + y**2)**.5, Rs, alpha_Rs, r_trunc,
x, y)
g1, g2 = self.nfw.nfwGamma((x**2 + y**2)**.5, Rs, alpha_Rs, x, y)
np.testing.assert_almost_equal(g1t, g1, 5)
np.testing.assert_almost_equal(g2t, g2, 5)
def test_hessian(self):
Rs = 0.2
alpha_Rs = 0.1
r_trunc = 1000000000000 * Rs
x = np.linspace(0.1 * Rs, 5 * Rs, 100)
y = np.linspace(0.2, 1, 100)
xxt, yyt, xyt = self.tnfw.hessian(x, y, Rs, alpha_Rs, r_trunc)
xx, yy, xy = self.nfw.hessian(x, y, Rs, alpha_Rs)
np.testing.assert_almost_equal(xy, xyt, 4)
np.testing.assert_almost_equal(yy, yyt, 4)
np.testing.assert_almost_equal(xy, xyt, 4)
Rs = 0.2
r_trunc = 5
xxt, yyt, xyt = self.tnfw.hessian(Rs, 0, Rs, alpha_Rs, r_trunc)
xxt_delta, yyt_delta, xyt_delta = self.tnfw.hessian(
Rs + 0.000001, 0, Rs, alpha_Rs, r_trunc)
npt.assert_almost_equal(xxt, xxt_delta, decimal=6)
def test_density_2d(self):
Rs = 0.2
alpha_Rs = 0.1
r_trunc = 1000000000000 * Rs
x = np.linspace(0.1 * Rs, 3 * Rs, 1000)
y = np.linspace(0.2, 0.5, 1000)
kappa_t = self.tnfw.density_2d(x, y, Rs, alpha_Rs, r_trunc)
kappa = self.nfw.density_2d(x, y, Rs, alpha_Rs)
np.testing.assert_almost_equal(kappa, kappa_t, 5)
def test_transform(self):
rho0, Rs = 1, 2
trs = self.tnfw._rho02alpha(rho0, Rs)
rho_out = self.tnfw._alpha2rho0(trs, Rs)
npt.assert_almost_equal(rho0, rho_out)
def test_numerical_derivatives(self):
Rs = 0.2
alpha_Rs = 0.1
r_trunc = 1.5 * Rs
diff = 1e-9
x0, y0 = 0.1, 0.1
x_def_t, y_def_t = self.tnfw.derivatives(x0, y0, Rs, alpha_Rs, r_trunc)
x_def_t_deltax, _ = self.tnfw.derivatives(x0 + diff, y0, Rs, alpha_Rs,
r_trunc)
x_def_t_deltay, y_def_t_deltay = self.tnfw.derivatives(
x0, y0 + diff, Rs, alpha_Rs, r_trunc)
actual = self.tnfw.hessian(x0, y0, Rs, alpha_Rs, r_trunc)
f_xx_approx = (x_def_t_deltax - x_def_t) * diff**-1
f_yy_approx = (y_def_t_deltay - y_def_t) * diff**-1
f_xy_approx = (x_def_t_deltay - y_def_t) * diff**-1
numerical = [f_xx_approx, f_yy_approx, f_xy_approx]
for (approx, true) in zip(numerical, actual):
npt.assert_almost_equal(approx, true)
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
class TNFW_ELLIPSE(LensProfileBase):
"""
this class contains functions concerning the truncated NFW profile with an ellipticity defined in the potential
parameterization of alpha_Rs, Rs and r_trunc is the same as for the spherical NFW profile
from Glose & Kneib: https://cds.cern.ch/record/529584/files/0112138.pdf
relation are: R_200 = c * Rs
"""
profile_name = 'TNFW_ELLIPSE'
param_names = [
'Rs', 'alpha_Rs', 'r_trunc', 'e1', 'e2', 'center_x', 'center_y'
]
lower_limit_default = {
'Rs': 0,
'alpha_Rs': 0,
'r_trunc': 0,
'e1': -0.5,
'e2': -0.5,
'center_x': -100,
'center_y': -100
}
upper_limit_default = {
'Rs': 100,
'alpha_Rs': 10,
'r_trunc': 100,
'e1': 0.5,
'e2': 0.5,
'center_x': 100,
'center_y': 100
}
def __init__(self):
"""
"""
self.tnfw = TNFW()
self._diff = 0.0000000001
super(TNFW_ELLIPSE, self).__init__()
def function(self,
x,
y,
Rs,
alpha_Rs,
r_trunc,
e1,
e2,
center_x=0,
center_y=0):
"""
returns elliptically distorted NFW lensing potential
:param x: angular position (normally in units of arc seconds)
:param y: angular position (normally in units of arc seconds)
:param Rs: turn over point in the slope of the NFW profile in angular unit
:param alpha_Rs: deflection (angular units) at projected Rs
:param r_trunc: truncation radius
:param e1: eccentricity component in x-direction
:param e2: eccentricity component in y-direction
:param center_x: center of halo (in angular units)
:param center_y: center of halo (in angular units)
:return: lensing potential
"""
x_, y_ = param_util.transform_e1e2_square_average(
x, y, e1, e2, center_x, center_y)
R_ = np.sqrt(x_**2 + y_**2)
rho0_input = self.tnfw.alpha2rho0(alpha_Rs=alpha_Rs, Rs=Rs)
Rs = np.maximum(Rs, 0.0000001)
#if Rs < 0.0000001:
# Rs = 0.0000001
f_ = self.tnfw.nfwPot(R_, Rs, rho0_input, r_trunc)
return f_
def derivatives(self,
x,
y,
Rs,
alpha_Rs,
r_trunc,
e1,
e2,
center_x=0,
center_y=0):
"""
returns df/dx and df/dy of the function, calculated as an elliptically distorted deflection angle of the
spherical NFW profile
:param x: angular position (normally in units of arc seconds)
:param y: angular position (normally in units of arc seconds)
:param Rs: turn over point in the slope of the NFW profile in angular unit
:param alpha_Rs: deflection (angular units) at projected Rs
:param r_trunc: truncation radius
:param e1: eccentricity component in x-direction
:param e2: eccentricity component in y-direction
:param center_x: center of halo (in angular units)
:param center_y: center of halo (in angular units)
:return: deflection in x-direction, deflection in y-direction
"""
x_, y_ = param_util.transform_e1e2_square_average(
x, y, e1, e2, center_x, center_y)
phi_G, q = param_util.ellipticity2phi_q(e1, e2)
cos_phi = np.cos(phi_G)
sin_phi = np.sin(phi_G)
e = param_util.q2e(q)
# e = abs(1 - q)
R_ = np.sqrt(x_**2 + y_**2)
rho0_input = self.tnfw.alpha2rho0(alpha_Rs=alpha_Rs, Rs=Rs)
Rs = np.maximum(Rs, 0.0000001)
#if Rs < 0.0000001:
# Rs = 0.0000001
f_x_prim, f_y_prim = self.tnfw.nfwAlpha(R_, Rs, rho0_input, r_trunc,
x_, y_)
f_x_prim *= np.sqrt(1 - e)
f_y_prim *= np.sqrt(1 + e)
f_x = cos_phi * f_x_prim - sin_phi * f_y_prim
f_y = sin_phi * f_x_prim + cos_phi * f_y_prim
return f_x, f_y
def hessian(self,
x,
y,
Rs,
alpha_Rs,
r_trunc,
e1,
e2,
center_x=0,
center_y=0):
"""
returns Hessian matrix of function d^2f/dx^2, d^f/dy^2, d^2/dxdy
the calculation is performed as a numerical differential from the deflection field. Analytical relations are possible
:param x: angular position (normally in units of arc seconds)
:param y: angular position (normally in units of arc seconds)
:param Rs: turn over point in the slope of the NFW profile in angular unit
:param alpha_Rs: deflection (angular units) at projected Rs
:param r_trunc: truncation radius
:param e1: eccentricity component in x-direction
:param e2: eccentricity component in y-direction
:param center_x: center of halo (in angular units)
:param center_y: center of halo (in angular units)
:return: d^2f/dx^2, d^2/dxdy, d^2/dydx, d^f/dy^2
"""
alpha_ra, alpha_dec = self.derivatives(x, y, Rs, alpha_Rs, r_trunc, e1,
e2, center_x, center_y)
diff = self._diff
alpha_ra_dx, alpha_dec_dx = self.derivatives(x + diff, y, Rs, alpha_Rs,
r_trunc, e1, e2, center_x,
center_y)
alpha_ra_dy, alpha_dec_dy = self.derivatives(x, y + diff, Rs, alpha_Rs,
r_trunc, e1, e2, center_x,
center_y)
f_xx = (alpha_ra_dx - alpha_ra) / diff
f_xy = (alpha_ra_dy - alpha_ra) / diff
f_yx = (alpha_dec_dx - alpha_dec) / diff
f_yy = (alpha_dec_dy - alpha_dec) / diff
return f_xx, f_xy, f_yx, f_yy
def mass_3d_lens(self, r, Rs, alpha_Rs, r_trunc, e1=1, e2=0):
"""
:param r: radius (in angular units)
:param Rs: turn-over radius of NFW profile
:param alpha_Rs: deflection at Rs
:param r_trunc: truncation radius
:param e1: eccentricity component in x-direction
:param e2: eccentricity component in y-direction
:return:
"""
return self.tnfw.mass_3d_lens(r, Rs, alpha_Rs, r_trunc)
def density_lens(self, r, Rs, alpha_Rs, r_trunc, e1=1, e2=0):
"""
computes the density at 3d radius r given lens model parameterization.
The integral in the LOS projection of this quantity results in the convergence quantity.
:param r: 3d radios
:param Rs: turn-over radius of NFW profile
:param alpha_Rs: deflection at Rs
:param r_trunc: truncation radius
:param e1: eccentricity component in x-direction
:param e2: eccentricity component in y-direction
:return: density rho(r)
"""
return self.tnfw.density_lens(r, Rs, alpha_Rs, r_trunc)
def setup(self):
self.interp = CoreTNFWDeflection()
self.tnfw = TNFW()
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)
class TestTNFW(object):
def setup(self):
self.nfw = NFW()
self.tnfw = TNFW()
def test_deflection(self):
Rs = 0.2
alpha_Rs = 0.1
r_trunc = 1000000000000 * Rs
x = np.linspace(0.0 * Rs, 5 * Rs, 1000)
y = np.linspace(0., 1, 1000)
xdef_t, ydef_t = self.tnfw.derivatives(x, y, Rs, alpha_Rs, r_trunc)
xdef, ydef = self.nfw.derivatives(x, y, Rs, alpha_Rs)
np.testing.assert_almost_equal(xdef_t, xdef, 5)
np.testing.assert_almost_equal(ydef_t, ydef, 5)
def test_potential_limit(self):
Rs = 0.2
alpha_Rs = 0.1
r_trunc = 1000000000000 * Rs
x = np.linspace(0.1 * Rs, 5 * Rs, 1000)
y = np.linspace(0.2, 1, 1000)
pot_t = self.tnfw.function(x, y, Rs, alpha_Rs, r_trunc)
pot = self.nfw.function(x, y, Rs, alpha_Rs)
np.testing.assert_almost_equal(pot, pot_t, 4)
def test_potential_derivative(self):
Rs = 1.2
alpha_Rs = 1
r_trunc = 3 * Rs
R = np.linspace(0.5 * Rs, 2.2 * Rs, 5000)
dx = R[1] - R[0]
alpha_tnfw = self.tnfw.nfwAlpha(R, Rs, 1, r_trunc, R, 0)[0]
potential_array = self.tnfw.nfwPot(R, Rs, 1, r_trunc)
alpha_tnfw_num_array = np.gradient(potential_array, dx)
potential_from_float = [
self.tnfw.nfwPot(R_i, Rs, 1, r_trunc) for R_i in R
]
alpha_tnfw_num_from_float = np.gradient(potential_from_float, dx)
npt.assert_almost_equal(alpha_tnfw_num_array, alpha_tnfw, 4)
npt.assert_almost_equal(alpha_tnfw_num_from_float, alpha_tnfw, 4)
def test_gamma(self):
Rs = 0.2
alpha_Rs = 0.1
r_trunc = 1000000000000 * Rs
x = np.linspace(0.1 * Rs, 5 * Rs, 1000)
y = np.linspace(0.2, 1, 1000)
g1t, g2t = self.tnfw.nfwGamma((x**2 + y**2)**.5, Rs, alpha_Rs, r_trunc,
x, y)
g1, g2 = self.nfw.nfwGamma((x**2 + y**2)**.5, Rs, alpha_Rs, x, y)
np.testing.assert_almost_equal(g1t, g1, 5)
np.testing.assert_almost_equal(g2t, g2, 5)
def test_hessian(self):
Rs = 0.2
alpha_Rs = 0.1
r_trunc = 1000000000000 * Rs
x = np.linspace(0.1 * Rs, 5 * Rs, 100)
y = np.linspace(0.2, 1, 100)
xxt, yyt, xyt = self.tnfw.hessian(x, y, Rs, alpha_Rs, r_trunc)
xx, yy, xy = self.nfw.hessian(x, y, Rs, alpha_Rs)
np.testing.assert_almost_equal(xy, xyt, 4)
np.testing.assert_almost_equal(yy, yyt, 4)
np.testing.assert_almost_equal(xy, xyt, 4)
Rs = 0.2
r_trunc = 5
xxt, yyt, xyt = self.tnfw.hessian(Rs, 0, Rs, alpha_Rs, r_trunc)
xxt_delta, yyt_delta, xyt_delta = self.tnfw.hessian(
Rs + 0.000001, 0, Rs, alpha_Rs, r_trunc)
npt.assert_almost_equal(xxt, xxt_delta, decimal=6)
def test_density_2d(self):
Rs = 0.2
alpha_Rs = 0.1
r_trunc = 1000000000000 * Rs
x = np.linspace(0.1 * Rs, 3 * Rs, 1000)
y = np.linspace(0.2, 0.5, 1000)
kappa_t = self.tnfw.density_2d(x, y, Rs, alpha_Rs, r_trunc)
kappa = self.nfw.density_2d(x, y, Rs, alpha_Rs)
np.testing.assert_almost_equal(kappa, kappa_t, 5)
def test_transform(self):
rho0, Rs = 1, 2
trs = self.tnfw._rho02alpha(rho0, Rs)
rho_out = self.tnfw._alpha2rho0(trs, Rs)
npt.assert_almost_equal(rho0, rho_out)
def test_numerical_derivatives(self):
Rs = 0.2
alpha_Rs = 0.1
r_trunc = 1.5 * Rs
diff = 1e-9
x0, y0 = 0.1, 0.1
x_def_t, y_def_t = self.tnfw.derivatives(x0, y0, Rs, alpha_Rs, r_trunc)
x_def_t_deltax, _ = self.tnfw.derivatives(x0 + diff, y0, Rs, alpha_Rs,
r_trunc)
x_def_t_deltay, y_def_t_deltay = self.tnfw.derivatives(
x0, y0 + diff, Rs, alpha_Rs, r_trunc)
actual = self.tnfw.hessian(x0, y0, Rs, alpha_Rs, r_trunc)
f_xx_approx = (x_def_t_deltax - x_def_t) * diff**-1
f_yy_approx = (y_def_t_deltay - y_def_t) * diff**-1
f_xy_approx = (x_def_t_deltay - y_def_t) * diff**-1
numerical = [f_xx_approx, f_yy_approx, f_xy_approx]
for (approx, true) in zip(numerical, actual):
npt.assert_almost_equal(approx, true)
def test_F_function_at_one(self):
f_tnfw = self.tnfw.F(1.)
npt.assert_(f_tnfw == 1)
f_tnfw = self.tnfw.F(np.ones((2, 2)))
f_tnfw = f_tnfw.ravel()
for value in f_tnfw:
npt.assert_(value == 1)
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))
def _deflection_function(self, x, y, rs, r_core, r_trunc, norm):
tnfw = TNFW()
return tnfw.derivatives(x, y, rs, norm, r_trunc)
def setup(self):
self.tnfw = TNFW()
self.nfw_e = NFW_ELLIPSE()
self.tnfw_e = TNFW_ELLIPSE()
class TestNFWELLIPSE(object):
"""
tests the Gaussian methods
"""
def setup(self):
self.tnfw = TNFW()
self.nfw_e = NFW_ELLIPSE()
self.tnfw_e = TNFW_ELLIPSE()
def test_function(self):
x = np.linspace(start=0.1, stop=10, num=10)
y = np.linspace(start=0.1, stop=10, num=10)
# test round case against TNFW
kwargs_tnfw_e_round = {
'Rs': 1,
'alpha_Rs': 0.1,
'r_trunc': 5,
'e1': 0.,
'e2': 0
}
kwargs_tnfw_round = {'Rs': 1, 'alpha_Rs': 0.1, 'r_trunc': 5}
f_e = self.tnfw_e.function(x, y, **kwargs_tnfw_e_round)
f_r = self.tnfw.function(x, y, **kwargs_tnfw_round)
npt.assert_almost_equal(f_e, f_r, decimal=5)
# test elliptical case with r_trunc -> infinity against NFW_ELLIPSE
kwargs_tnfw_e = {
'Rs': 1,
'alpha_Rs': 0.1,
'r_trunc': 500,
'e1': 0.2,
'e2': -0.01
}
kwargs_nfw_e = {'Rs': 1, 'alpha_Rs': 0.1, 'e1': 0.2, 'e2': -0.01}
f_te = self.tnfw_e.function(x, y, **kwargs_tnfw_e)
f_e = self.nfw_e.function(x, y, **kwargs_nfw_e)
npt.assert_almost_equal(f_te, f_e, decimal=3)
def test_derivatives(self):
x = np.linspace(start=0.1, stop=10, num=10)
y = np.linspace(start=0.1, stop=10, num=10)
# test round case against TNFW
kwargs_tnfw_e_round = {
'Rs': 1,
'alpha_Rs': 0.1,
'r_trunc': 5,
'e1': 0.,
'e2': 0
}
kwargs_tnfw_round = {'Rs': 1, 'alpha_Rs': 0.1, 'r_trunc': 5}
f_xe, f_ye = self.tnfw_e.derivatives(x, y, **kwargs_tnfw_e_round)
f_xr, f_yr = self.tnfw.derivatives(x, y, **kwargs_tnfw_round)
npt.assert_almost_equal(f_xe, f_xr, decimal=5)
npt.assert_almost_equal(f_ye, f_yr, decimal=5)
# test elliptical case with r_trunc -> infinity against NFW_ELLIPSE
kwargs_tnfw_e = {
'Rs': 1,
'alpha_Rs': 0.1,
'r_trunc': 500,
'e1': 0.2,
'e2': -0.01
}
kwargs_nfw_e = {'Rs': 1, 'alpha_Rs': 0.1, 'e1': 0.2, 'e2': -0.01}
out_te = self.tnfw_e.derivatives(x, y, **kwargs_tnfw_e)
out_e = self.nfw_e.derivatives(x, y, **kwargs_nfw_e)
npt.assert_almost_equal(out_te, out_e, decimal=3)
def test_hessian(self):
x = np.linspace(start=0.1, stop=10, num=10)
y = np.linspace(start=0.1, stop=10, num=10)
# test round case against TNFW
kwargs_tnfw_e_round = {
'Rs': 1,
'alpha_Rs': 0.1,
'r_trunc': 5,
'e1': 0.,
'e2': 0
}
kwargs_tnfw_round = {'Rs': 1, 'alpha_Rs': 0.1, 'r_trunc': 5}
out_e = self.tnfw_e.hessian(x, y, **kwargs_tnfw_e_round)
out_r = self.tnfw.hessian(x, y, **kwargs_tnfw_round)
npt.assert_almost_equal(out_e, out_r, decimal=4)
# test elliptical case with r_trunc -> infinity against NFW_ELLIPSE
kwargs_tnfw_e = {
'Rs': 1,
'alpha_Rs': 0.1,
'r_trunc': 500,
'e1': 0.2,
'e2': -0.01
}
kwargs_nfw_e = {'Rs': 1, 'alpha_Rs': 0.1, 'e1': 0.2, 'e2': -0.01}
out_te = self.tnfw_e.hessian(x, y, **kwargs_tnfw_e)
out_e = self.nfw_e.hessian(x, y, **kwargs_nfw_e)
npt.assert_almost_equal(out_te, out_e, decimal=3)
def test_mass_3d_lens(self):
with npt.assert_raises(ValueError):
kwargs_tnfw_e = {
'Rs': 1,
'alpha_Rs': 0.1,
'r_trunc': 5,
'e1': 0.1,
'e2': -0.02
}
self.tnfw_e.mass_3d_lens(1, **kwargs_tnfw_e)
def test_density_lens(self):
with npt.assert_raises(ValueError):
kwargs_tnfw_e = {
'Rs': 1,
'alpha_Rs': 0.1,
'r_trunc': 5,
'e1': 0.1,
'e2': -0.02
}
self.tnfw_e.density_lens(1, **kwargs_tnfw_e)
