def test_PJaffa_density_deflection(self):
"""
tests whether the unit conversion between the lensing parameter 'sigma0' and the units in the density profile are ok
:return:
"""
from lenstronomy.LensModel.Profiles.p_jaffe import PJaffe as Model
lensModel = Model()
sigma0 = 1.
Ra = 0.2
Rs = 2.
rho0 = lensModel.sigma2rho(sigma0, Ra, Rs)
kwargs_lens = {
'sigma0': sigma0,
'Ra': Ra,
'Rs': Rs,
'center_x': 0,
'center_y': 0
}
kwargs_density = {'rho0': rho0, 'Ra': Ra, 'Rs': Rs}
r = 1.
mass_2d = lensModel.mass_2d(r, **kwargs_density)
alpha_mass = mass_2d / r
alpha_r, _ = lensModel.derivatives(r, 0, **kwargs_lens)
npt.assert_almost_equal(alpha_mass / np.pi, alpha_r, decimal=5)
def __init__(self, mass, x, y, r3d, mdef, z, sub_flag, lens_cosmo_instance,
args, unique_tag):
"""
See documentation in base class (Halos/halo_base.py)
"""
self._lens_cosmo = lens_cosmo_instance
self._prof = PJaffe()
super(PJaffeSubhalo,
self).__init__(mass, x, y, r3d, mdef, z, sub_flag,
lens_cosmo_instance, args, unique_tag)
class PJaffe(object):
"""
class for pseudo Jaffe lens light (2d projected light/mass distribution)
"""
param_names = ['amp', 'Ra', 'Rs', 'center_x', 'center_y']
lower_limit_default = {
'amp': 0,
'Ra': 0,
'Rs': 0,
'center_x': -100,
'center_y': -100
}
upper_limit_default = {
'amp': 100,
'Ra': 100,
'Rs': 100,
'center_x': 100,
'center_y': 100
}
def __init__(self):
from lenstronomy.LensModel.Profiles.p_jaffe import PJaffe as PJaffe_lens
self.lens = PJaffe_lens()
def function(self, x, y, amp, Ra, Rs, center_x=0, center_y=0):
"""
:param x:
:param y:
:param amp:
:param a:
:param s:
:param center_x:
:param center_y:
:return:
"""
rho0 = self.lens.sigma2rho(amp, Ra, Rs)
return self.lens.density_2d(x, y, rho0, Ra, Rs, center_x, center_y)
def light_3d(self, r, amp, Ra, Rs):
"""
:param y:
:param amp:
:param Rs:
:param center_x:
:param center_y:
:return:
"""
rho0 = self.lens.sigma2rho(amp, Ra, Rs)
return self.lens.density(r, rho0, Ra, Rs)
def assert_lens_integrals(self, Model, kwargs):
"""
checks whether the integral in projection of the density_lens() function is the convergence
:param Model: lens model instance
:param kwargs: keyword arguments of lens model
:return:
"""
lensModel = Model()
int_profile = ProfileIntegrals(lensModel)
r = 2.
kappa_num = int_profile.density_2d(r, kwargs, lens_param=True)
f_xx, f_yy, f_xy = lensModel.hessian(r, 0, **kwargs)
kappa = 1./2 * (f_xx + f_yy)
npt.assert_almost_equal(kappa_num, kappa, decimal=2)
def assert_integrals(self, Model, kwargs):
lensModel = Model()
int_profile = ProfileIntegrals(lensModel)
r = 2.
density2d_num = int_profile.density_2d(r, kwargs)
density2d = lensModel.density_2d(r, 0, **kwargs)
npt.assert_almost_equal(density2d / density2d_num, 1., decimal=1)
mass_2d_num = int_profile.mass_enclosed_2d(r, kwargs)
mass_2d = lensModel.mass_2d(r, **kwargs)
npt.assert_almost_equal(mass_2d / mass_2d_num, 1, decimal=1)
mass_3d_num = int_profile.mass_enclosed_3d(r, kwargs)
mass_3d = lensModel.mass_3d(r, **kwargs)
npt.assert_almost_equal(mass_3d / mass_3d_num, 1, decimal=2)
def setup(self):
mass = 10**7.
x = 0.5
y = 1.
r3d = np.sqrt(1 + 0.5 ** 2 + 70**2)
self.r3d = r3d
mdef = 'PJAFFE'
self.z = 0.25
sub_flag = True
self.H0 = 70
self.omega_baryon = 0.03
self.omega_DM = 0.25
self.sigma8 = 0.82
curvature = 'flat'
self.ns = 0.9608
cosmo_params = {'H0': self.H0, 'Om0': self.omega_baryon + self.omega_DM, 'Ob0': self.omega_baryon,
'sigma8': self.sigma8, 'ns': self.ns, 'curvature': curvature}
self._dm, self._bar = self.omega_DM, self.omega_baryon
cosmo = Cosmology(cosmo_kwargs=cosmo_params)
self.lens_cosmo = LensCosmo(self.z, 2., cosmo)
kwargs_suppression = {'c_scale': 10.5, 'c_power': -0.2}
suppression_model = 'polynomial'
profile_args = {'RocheNorm': 1.2, 'RocheNu': 2/3,
'evaluate_mc_at_zlens': True,
'log_mc': 0., 'kwargs_suppression': kwargs_suppression,
'suppression_model': suppression_model, 'c_scatter': False,
'mc_model': 'diemer19', 'LOS_truncation_factor': 40,
'mc_mdef': '200c',
'c_scatter_dex': 0.1}
self.profile_args = profile_args
self.mass_subhalo = mass
self.subhalo = PJaffeSubhalo(mass, x, y, r3d, mdef, self.z,
sub_flag, self.lens_cosmo,
profile_args, unique_tag=np.random.rand())
mass_field_halo = 10 ** 7.
sub_flag = False
self.mass_field_halo = mass_field_halo
self.field_halo = PJaffeSubhalo(self.mass_field_halo, x, y, r3d, mdef, self.z,
sub_flag, self.lens_cosmo,
profile_args, unique_tag=np.random.rand())
self._model_lenstronomy = PJaffe()
def test_sie_density_deflection(self):
"""
tests whether the unit conversion between the lensing parameter 'sigma0' and the units in the density profile are ok
:return:
"""
from lenstronomy.LensModel.Profiles.sie import SIE as Model
lensModel = Model()
theta_E = 1.
rho0 = lensModel.theta2rho(theta_E)
kwargs_lens = {'theta_E': theta_E, 'e1': 0, 'e2': 0}
kwargs_density = {'rho0': rho0, 'e1': 0, 'e2': 0}
r = .5
mass_2d = lensModel.mass_2d(r, **kwargs_density)
alpha_mass = mass_2d / r
alpha_r, _ = lensModel.derivatives(r, 0, **kwargs_lens)
npt.assert_almost_equal(alpha_mass / np.pi, alpha_r, decimal=5)
def test_nfw_density_deflection(self):
"""
tests whether the unit conversion between the lensing parameter 'sigma0' and the units in the density profile are ok
:return:
"""
from lenstronomy.LensModel.Profiles.nfw import NFW as Model
lensModel = Model()
alpha_Rs = 1.
Rs = 2.
rho0 = lensModel.alpha2rho0(alpha_Rs, Rs)
kwargs_lens = {'alpha_Rs': alpha_Rs, 'Rs': Rs}
kwargs_density = {'rho0': rho0, 'Rs': Rs}
r = 2.
mass_2d = lensModel.mass_2d(r, **kwargs_density)
alpha_mass = mass_2d / r
alpha_r, _ = lensModel.derivatives(r, 0, **kwargs_lens)
npt.assert_almost_equal(alpha_mass / np.pi, alpha_r, decimal=5)
def test_gaussian_density_deflection(self):
"""
tests whether the unit conversion between the lensing parameter 'sigma0' and the units in the density profile are ok
:return:
"""
from lenstronomy.LensModel.Profiles.gaussian_kappa import GaussianKappa as Model
lensModel = Model()
amp = 1. / 4.
sigma = 2.
amp_lens = lensModel._amp3d_to_2d(amp, sigma, sigma)
kwargs_lens = {'amp': amp_lens, 'sigma': sigma}
kwargs_density = {'amp': amp, 'sigma': sigma}
r = .5
mass_2d = lensModel.mass_2d(r, **kwargs_density)
alpha_mass = mass_2d / r
alpha_r, _ = lensModel.derivatives(r, 0, **kwargs_lens)
npt.assert_almost_equal(alpha_mass / np.pi, alpha_r, decimal=5)
def assert_lens_integrals(self, Model, kwargs, pi_convention=True):
"""
checks whether the integral in projection of the density_lens() function is the convergence
:param Model: lens model instance
:param kwargs: keyword arguments of lens model
:return:
"""
lensModel = Model()
int_profile = ProfileIntegrals(lensModel)
r = 2.
kappa_num = int_profile.density_2d(r, kwargs, lens_param=True)
f_xx, f_xy, f_yx, f_yy = lensModel.hessian(r, 0, **kwargs)
kappa = 1. / 2 * (f_xx + f_yy)
npt.assert_almost_equal(kappa_num, kappa, decimal=2)
try:
del kwargs['center_x']
del kwargs['center_y']
except:
pass
bool_mass_2d_lens = False
try:
mass_2d = lensModel.mass_2d_lens(r, **kwargs)
bool_mass_2d_lens = True
except:
pass
if bool_mass_2d_lens:
alpha_x, alpha_y = lensModel.derivatives(r, 0, **kwargs)
alpha = np.sqrt(alpha_x**2 + alpha_y**2)
if pi_convention:
npt.assert_almost_equal(alpha, mass_2d / r / np.pi, decimal=5)
else:
npt.assert_almost_equal(alpha, mass_2d / r, decimal=5)
try:
mass_3d = lensModel.mass_3d_lens(r, **kwargs)
bool_mass_3d_lens = True
except:
bool_mass_3d_lens = False
if bool_mass_3d_lens:
mass_3d_num = int_profile.mass_enclosed_3d(r,
kwargs_profile=kwargs,
lens_param=True)
print(mass_3d, mass_3d_num, 'test num')
npt.assert_almost_equal(mass_3d / mass_3d_num, 1, decimal=2)
def assert_lens_integrals(self, Model, kwargs):
"""
checks whether the integral in projection of the density_lens() function is the convergence
:param Model: lens model instance
:param kwargs: keyword arguments of lens model
:return:
"""
lensModel = Model()
int_profile = ProfileIntegrals(lensModel)
r = 2.
kappa_num = int_profile.density_2d(r, kwargs, lens_param=True)
f_xx, f_yy, f_xy = lensModel.hessian(r, 0, **kwargs)
kappa = 1. / 2 * (f_xx + f_yy)
npt.assert_almost_equal(kappa_num, kappa, decimal=2)
if hasattr(lensModel, 'mass_2d_lens'):
mass_2d = lensModel.mass_2d_lens(r, **kwargs)
alpha_x, alpha_y = lensModel.derivatives(r, 0, **kwargs)
alpha = np.sqrt(alpha_x**2 + alpha_y**2)
npt.assert_almost_equal(alpha, mass_2d / r / np.pi, decimal=5)
def __init__(self):
self.spherical = PJaffe()
self._diff = 0.000001
class TestPjaffeHalo(object):
def setup(self):
mass = 10**7.
x = 0.5
y = 1.
r3d = np.sqrt(1 + 0.5 ** 2 + 70**2)
self.r3d = r3d
mdef = 'PJAFFE'
self.z = 0.25
sub_flag = True
self.H0 = 70
self.omega_baryon = 0.03
self.omega_DM = 0.25
self.sigma8 = 0.82
curvature = 'flat'
self.ns = 0.9608
cosmo_params = {'H0': self.H0, 'Om0': self.omega_baryon + self.omega_DM, 'Ob0': self.omega_baryon,
'sigma8': self.sigma8, 'ns': self.ns, 'curvature': curvature}
self._dm, self._bar = self.omega_DM, self.omega_baryon
cosmo = Cosmology(cosmo_kwargs=cosmo_params)
self.lens_cosmo = LensCosmo(self.z, 2., cosmo)
kwargs_suppression = {'c_scale': 10.5, 'c_power': -0.2}
suppression_model = 'polynomial'
profile_args = {'RocheNorm': 1.2, 'RocheNu': 2/3,
'evaluate_mc_at_zlens': True,
'log_mc': 0., 'kwargs_suppression': kwargs_suppression,
'suppression_model': suppression_model, 'c_scatter': False,
'mc_model': 'diemer19', 'LOS_truncation_factor': 40,
'mc_mdef': '200c',
'c_scatter_dex': 0.1}
self.profile_args = profile_args
self.mass_subhalo = mass
self.subhalo = PJaffeSubhalo(mass, x, y, r3d, mdef, self.z,
sub_flag, self.lens_cosmo,
profile_args, unique_tag=np.random.rand())
mass_field_halo = 10 ** 7.
sub_flag = False
self.mass_field_halo = mass_field_halo
self.field_halo = PJaffeSubhalo(self.mass_field_halo, x, y, r3d, mdef, self.z,
sub_flag, self.lens_cosmo,
profile_args, unique_tag=np.random.rand())
self._model_lenstronomy = PJaffe()
def test_lenstronomy_ID(self):
id = self.subhalo.lenstronomy_ID
npt.assert_string_equal(id[0], 'PJAFFE')
id = self.field_halo.lenstronomy_ID
npt.assert_string_equal(id[0], 'PJAFFE')
def test_z_infall(self):
z_infall = self.subhalo.z_infall
npt.assert_equal(True, self.z <= z_infall)
def test_total_mass(self):
c = float(self.subhalo.profile_args)
rhos, rs, r200 = self.lens_cosmo.NFW_params_physical(self.subhalo.mass, c, self.z)
fc = np.log(1 + c) - c / (1 + c)
m_nfw = 4 * np.pi * rs ** 3 * rhos * fc
lenstronomy_kwargs, _ = self.subhalo.lenstronomy_params
sigma0, ra, rs = lenstronomy_kwargs[0]['sigma0'], lenstronomy_kwargs[0]['Ra'], lenstronomy_kwargs[0]['Rs']
arcsec_to_kpc = self.lens_cosmo.cosmo.kpc_proper_per_asec(self.z)
ra *= arcsec_to_kpc ** -1
rs *= arcsec_to_kpc ** -1
rho = self.subhalo._rho(m_nfw, rs, ra, c*rs)
m3d = self._model_lenstronomy.mass_3d(c*rs, rho, ra, rs)
npt.assert_almost_equal(np.log10(m3d), np.log10(m_nfw))
def test_profile_args(self):
profile_args = self.subhalo.profile_args
(c) = profile_args
con = concentration(self.lens_cosmo.cosmo.h * self.mass_subhalo, '200c', self.z,
model='diemer19')
npt.assert_almost_equal(c/con, 1, 2)
profile_args = self.field_halo.profile_args
(c) = profile_args
con = concentration(self.lens_cosmo.cosmo.h * self.mass_field_halo, '200c', self.z,
model='diemer19')
npt.assert_almost_equal(c / con, 1, 2)
profile_args = self.field_halo.profile_args
(c) = profile_args
con = concentration(self.lens_cosmo.cosmo.h * self.mass_subhalo, '200c', self.z,
model='diemer19')
npt.assert_almost_equal(c / con, 1, 2)
profile_args = self.field_halo.profile_args
(c) = profile_args
con = concentration(self.lens_cosmo.cosmo.h * self.mass_field_halo, '200c', self.z,
model='diemer19')
npt.assert_almost_equal(c / con, 1, 2)
def test_params_physical(self):
params_physical = self.subhalo.params_physical
npt.assert_equal(len(params_physical), 4)
class PJaffe_Ellipse(LensProfileBase):
"""
class to compute the DUAL PSEUDO ISOTHERMAL ELLIPTICAL MASS DISTRIBUTION
based on Eliasdottir (2007) https://arxiv.org/pdf/0710.5636.pdf Appendix A
with the ellipticity implemented in the potential
Module name: 'PJAFFE_ELLIPSE';
An alternative name is dPIED.
The 3D density distribution is
.. math::
\\rho(r) = \\frac{\\rho_0}{(1+r^2/Ra^2)(1+r^2/Rs^2)}
with :math:`Rs > Ra`.
The projected density is
.. math::
\\Sigma(R) = \\Sigma_0 \\frac{Ra Rs}{Rs-Ra}\\left(\\frac{1}{\\sqrt{Ra^2+R^2}} - \\frac{1}{\\sqrt{Rs^2+R^2}} \\right)
with
.. math::
\\Sigma_0 = \\pi \\rho_0 \\frac{Ra Rs}{Rs + Ra}
In the lensing parameterization,
.. math::
\\sigma_0 = \\frac{\\Sigma_0}{\\Sigma_{\\rm crit}}
"""
param_names = ['sigma0', 'Ra', 'Rs', 'e1', 'e2', 'center_x', 'center_y']
lower_limit_default = {
'sigma0': 0,
'Ra': 0,
'Rs': 0,
'e1': -0.5,
'e2': -0.5,
'center_x': -100,
'center_y': -100
}
upper_limit_default = {
'sigma0': 10,
'Ra': 100,
'Rs': 100,
'e1': 0.5,
'e2': 0.5,
'center_x': 100,
'center_y': 100
}
def __init__(self):
self.spherical = PJaffe()
self._diff = 0.000001
super(PJaffe_Ellipse, self).__init__()
def function(self, x, y, sigma0, Ra, Rs, e1, e2, center_x=0, center_y=0):
"""
returns double integral of NFW profile
"""
x_, y_ = param_util.transform_e1e2_square_average(
x, y, e1, e2, center_x, center_y)
f_ = self.spherical.function(x_, y_, sigma0, Ra, Rs)
return f_
def derivatives(self,
x,
y,
sigma0,
Ra,
Rs,
e1,
e2,
center_x=0,
center_y=0):
"""
returns df/dx and df/dy of the function (integral of NFW)
"""
phi_G, q = param_util.ellipticity2phi_q(e1, e2)
x_, y_ = param_util.transform_e1e2_square_average(
x, y, e1, e2, center_x, center_y)
e = param_util.q2e(q)
cos_phi = np.cos(phi_G)
sin_phi = np.sin(phi_G)
f_x_prim, f_y_prim = self.spherical.derivatives(x_,
y_,
sigma0,
Ra,
Rs,
center_x=0,
center_y=0)
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, sigma0, Ra, Rs, e1, e2, center_x=0, center_y=0):
"""
returns Hessian matrix of function d^2f/dx^2, d^2/dxdy, d^2/dydx, d^f/dy^2
"""
alpha_ra, alpha_dec = self.derivatives(x, y, sigma0, Ra, Rs, e1, e2,
center_x, center_y)
diff = self._diff
alpha_ra_dx, alpha_dec_dx = self.derivatives(x + diff, y, sigma0, Ra,
Rs, e1, e2, center_x,
center_y)
alpha_ra_dy, alpha_dec_dy = self.derivatives(x, y + diff, sigma0, Ra,
Rs, 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, sigma0, Ra, Rs, e1=0, e2=0):
"""
:param r:
:param sigma0:
:param Ra:
:param Rs:
:param e1:
:param e2:
:return:
"""
return self.spherical.mass_3d_lens(r, sigma0, Ra, Rs)
class TestP_JAFFW(object):
"""
tests the Gaussian methods
"""
def setup(self):
self.profile = PJaffe()
def test_function(self):
x = np.array([1])
y = np.array([2])
sigma0 = 1.
Ra, Rs = 0.5, 0.8
values = self.profile.function(x, y, sigma0, Ra, Rs)
npt.assert_almost_equal(values[0], 0.87301557036070054, decimal=8)
x = np.array([0])
y = np.array([0])
sigma0 = 1.
Ra, Rs = 0.5, 0.8
values = self.profile.function(x, y, sigma0, Ra, Rs)
npt.assert_almost_equal(values[0], 0.20267440905756931, decimal=8)
x = np.array([2, 3, 4])
y = np.array([1, 1, 1])
values = self.profile.function(x, y, sigma0, Ra, Rs)
npt.assert_almost_equal(values[0], 0.87301557036070054, decimal=8)
npt.assert_almost_equal(values[1], 1.0842781309377669, decimal=8)
npt.assert_almost_equal(values[2], 1.2588604178849985, decimal=8)
def test_derivatives(self):
x = np.array([1])
y = np.array([2])
sigma0 = 1.
Ra, Rs = 0.5, 0.8
f_x, f_y = self.profile.derivatives(x, y, sigma0, Ra, Rs)
npt.assert_almost_equal(f_x[0], 0.11542369603751264, decimal=8)
npt.assert_almost_equal(f_y[0], 0.23084739207502528, decimal=8)
x = np.array([0])
y = np.array([0])
f_x, f_y = self.profile.derivatives(x, y, sigma0, Ra, Rs)
assert f_x[0] == 0
assert f_y[0] == 0
x = np.array([1, 3, 4])
y = np.array([2, 1, 1])
values = self.profile.derivatives(x, y, sigma0, Ra, Rs)
npt.assert_almost_equal(values[0][0], 0.11542369603751264, decimal=8)
npt.assert_almost_equal(values[1][0], 0.23084739207502528, decimal=8)
npt.assert_almost_equal(values[0][1], 0.19172866612512479, decimal=8)
npt.assert_almost_equal(values[1][1], 0.063909555375041588, decimal=8)
def test_hessian(self):
x = np.array([1])
y = np.array([2])
sigma0 = 1.
Ra, Rs = 0.5, 0.8
f_xx, f_xy, f_yx, f_yy = self.profile.hessian(x, y, sigma0, Ra, Rs)
npt.assert_almost_equal(f_xx[0], 0.077446121589827679, decimal=8)
npt.assert_almost_equal(f_yy[0], -0.036486601753227141, decimal=8)
npt.assert_almost_equal(f_xy[0], -0.075955148895369876, decimal=8)
x = np.array([1, 3, 4])
y = np.array([2, 1, 1])
values = self.profile.hessian(x, y, sigma0, Ra, Rs)
npt.assert_almost_equal(values[0][0], 0.077446121589827679, decimal=8)
npt.assert_almost_equal(values[3][0], -0.036486601753227141, decimal=8)
npt.assert_almost_equal(values[1][0], values[2][0], decimal=8)
def test_mass_tot(self):
rho0 = 1.
Ra, Rs = 0.5, 0.8
values = self.profile.mass_tot(rho0, Ra, Rs)
npt.assert_almost_equal(values, 2.429441083345073, decimal=10)
def test_mass_3d_lens(self):
mass = self.profile.mass_3d_lens(r=1, sigma0=1, Ra=0.5, Rs=0.8)
npt.assert_almost_equal(mass, 0.87077306005349242, decimal=8)
def test_grav_pot(self):
x = 1
y = 2
rho0 = 1.
r = np.sqrt(x**2 + y**2)
Ra, Rs = 0.5, 0.8
grav_pot = self.profile.grav_pot(r, rho0, Ra, Rs)
npt.assert_almost_equal(grav_pot, 0.89106542283974155, decimal=10)
def __init__(self):
from lenstronomy.LensModel.Profiles.p_jaffe import PJaffe as PJaffe_lens
self.lens = PJaffe_lens()
class PJaffeSubhalo(Halo):
"""
Class that defines a halo modeled as a Psuedo-Jaffe profile.
The profile is normalized such that the Psuedo-Jaffe profile has the same mass within r200 as an NFW profile with mass
M200. The scale radius of the Psuedo-Jafee profile is the same as the NFW profile
"""
def __init__(self, mass, x, y, r3d, mdef, z, sub_flag, lens_cosmo_instance,
args, unique_tag):
"""
See documentation in base class (Halos/halo_base.py)
"""
self._lens_cosmo = lens_cosmo_instance
self._prof = PJaffe()
super(PJaffeSubhalo,
self).__init__(mass, x, y, r3d, mdef, z, sub_flag,
lens_cosmo_instance, args, unique_tag)
@property
def params_physical(self):
"""
See documentation in base class (Halos/halo_base.py)
"""
if not hasattr(self, '_params_physical'):
concentration = self.profile_args
rhos, rs, r200 = self._lens_cosmo.NFW_params_physical(
self.mass, concentration, self.z)
_, rs_kpc, r200_kpc = self._lens_cosmo.NFW_params_physical(
self.mass, concentration, self.z)
ra_kpc = 0.01 * rs_kpc
rho = self._rho(self.mass, rs_kpc, ra_kpc, r200)
self._params_physical = {
'rhos': rhos,
'rs': rs,
'r200': r200,
'rho': rho
}
return self._params_physical
@property
def lenstronomy_params(self):
"""
See documentation in base class (Halos/halo_base.py)
"""
if not hasattr(self, '_lenstronomy_args'):
kpc_to_arcsec = 1 / self._lens_cosmo.cosmo.kpc_proper_per_asec(
self.z)
(concentration) = self.profile_args
rhos_kpc, rs_kpc, r200_kpc = self._lens_cosmo.NFW_params_physical(
self.mass, concentration, self.z)
ra_kpc = 0.01 * rs_kpc
ra_arcsec = ra_kpc * kpc_to_arcsec
rs_arcsec = rs_kpc * kpc_to_arcsec
rmatch = r200_kpc
rmatch_arcsec = rmatch * kpc_to_arcsec
xmatch = rmatch / rs_kpc
fx = np.log(1 + xmatch) - xmatch / (1 + xmatch)
m_nfw = 4 * np.pi * rs_kpc**3 * rhos_kpc * fx
rho = self._rho(m_nfw, rs_arcsec, ra_arcsec, rmatch_arcsec)
sigma0 = self._prof.rho2sigma(rho, ra_arcsec, rs_arcsec)
sigma_crit_kpc = self._lens_cosmo.get_sigma_crit_lensing(
self.z, self._lens_cosmo.z_source) * 0.001**2
sigma0 *= (sigma_crit_kpc / kpc_to_arcsec**2)**-1
self._lenstronomy_args = [{
'center_x': self.x,
'center_y': self.y,
'Ra': ra_arcsec,
'Rs': rs_arcsec,
'sigma0': sigma0
}]
return self._lenstronomy_args, None
def _rho(self, m, rs, ra, r_match):
"""
returns the central density of a PJaffe halo such that the resulting halo has the mass m within r_match
:param m:
:param ra:
:param r_match:
:return:
"""
f = (ra * np.arctan(r_match / ra) -
rs * np.arctan(r_match / rs)) / (ra**2 - rs**2)
rho = m / (4 * np.pi * ra**2 * rs**2 * f)
return rho
@property
def lenstronomy_ID(self):
"""
See documentation in base class (Halos/halo_base.py)
"""
return ['PJAFFE']
@property
def profile_args(self):
"""
See documentation in base class (Halos/halo_base.py)
"""
if not hasattr(self, '_profile_args'):
if self._args['evaluate_mc_at_zlens']:
z_eval = self.z
else:
z_eval = self.z_infall
concentration = self._lens_cosmo.NFW_concentration(
self.mass, z_eval, self._args['mc_model'],
self._args['mc_mdef'], self._args['log_mc'],
self._args['c_scatter'], self._args['c_scatter_dex'],
self._args['kwargs_suppression'],
self._args['suppression_model'])
self._profile_args = (concentration)
return self._profile_args
class TestP_JAFFW(object):
"""
tests the Gaussian methods
"""
def setup(self):
self.profile = PJaffe()
def test_function(self):
x = np.array([1])
y = np.array([2])
sigma0 = 1.
Ra, Rs = 0.5, 0.8
values = self.profile.function(x, y, sigma0, Ra, Rs)
assert values[0] == 0.87301557036070054
x = np.array([0])
y = np.array([0])
sigma0 = 1.
Ra, Rs = 0.5, 0.8
values = self.profile.function(x, y, sigma0, Ra, Rs)
assert values[0] == 0.20267440905756931
x = np.array([2, 3, 4])
y = np.array([1, 1, 1])
values = self.profile.function(x, y, sigma0, Ra, Rs)
assert values[0] == 0.87301557036070054
assert values[1] == 1.0842781309377669
assert values[2] == 1.2588604178849985
def test_derivatives(self):
x = np.array([1])
y = np.array([2])
sigma0 = 1.
Ra, Rs = 0.5, 0.8
f_x, f_y = self.profile.derivatives(x, y, sigma0, Ra, Rs)
assert f_x[0] == 0.11542369603751264
assert f_y[0] == 0.23084739207502528
x = np.array([0])
y = np.array([0])
f_x, f_y = self.profile.derivatives(x, y, sigma0, Ra, Rs)
assert f_x[0] == 0
assert f_y[0] == 0
x = np.array([1, 3, 4])
y = np.array([2, 1, 1])
values = self.profile.derivatives(x, y, sigma0, Ra, Rs)
assert values[0][0] == 0.11542369603751264
assert values[1][0] == 0.23084739207502528
assert values[0][1] == 0.19172866612512479
assert values[1][1] == 0.063909555375041588
def test_hessian(self):
x = np.array([1])
y = np.array([2])
sigma0 = 1.
Ra, Rs = 0.5, 0.8
f_xx, f_yy, f_xy = self.profile.hessian(x, y, sigma0, Ra, Rs)
assert f_xx[0] == 0.077446121589827679
assert f_yy[0] == -0.036486601753227141
assert f_xy[0] == -0.075955148895369876
x = np.array([1, 3, 4])
y = np.array([2, 1, 1])
values = self.profile.hessian(x, y, sigma0, Ra, Rs)
assert values[0][0] == 0.077446121589827679
assert values[1][0] == -0.036486601753227141
assert values[2][0] == -0.075955148895369876
assert values[0][1] == -0.037260794616683197
assert values[1][1] == 0.052668405375961035
assert values[2][1] == -0.033723449997241584
def test_mass_tot(self):
rho0 = 1.
Ra, Rs = 0.5, 0.8
values = self.profile.mass_tot(rho0, Ra, Rs)
npt.assert_almost_equal(values, 2.429441083345073, decimal=10)
def test_mass_3d_lens(self):
mass = self.profile.mass_3d_lens(r=1, sigma0=1, Ra=0.5, Rs=0.8)
npt.assert_almost_equal(mass, 0.87077306005349242, decimal=8)
def test_grav_pot(self):
x = 1
y = 2
rho0 = 1.
Ra, Rs = 0.5, 0.8
grav_pot = self.profile.grav_pot(x,
y,
rho0,
Ra,
Rs,
center_x=0,
center_y=0)
npt.assert_almost_equal(grav_pot, 0.89106542283974155, decimal=10)
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 __init__(self):
self.spherical = PJaffe()
self._diff = 0.000001
super(PJaffe_Ellipse, self).__init__()
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, 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)
class PJaffe_Ellipse(object):
"""
this class contains functions concerning the NFW profile
relation are: R_200 = c * Rs
"""
def __init__(self):
self.spherical = PJaffe()
self._diff = 0.000001
def function(self, x, y, sigma0, Ra, Rs, q, phi_G, center_x=0, center_y=0):
"""
returns double integral of NFW profile
"""
x_shift = x - center_x
y_shift = y - center_y
cos_phi = np.cos(phi_G)
sin_phi = np.sin(phi_G)
e = min(abs(1. - q), 0.99)
x_ = (cos_phi * x_shift + sin_phi * y_shift) * np.sqrt(1 - e)
y_ = (-sin_phi * x_shift + cos_phi * y_shift) * np.sqrt(1 + e)
f_ = self.spherical.function(x_, y_, sigma0, Ra, Rs)
return f_
def derivatives(self,
x,
y,
sigma0,
Ra,
Rs,
q,
phi_G,
center_x=0,
center_y=0):
"""
returns df/dx and df/dy of the function (integral of NFW)
"""
x_shift = x - center_x
y_shift = y - center_y
cos_phi = np.cos(phi_G)
sin_phi = np.sin(phi_G)
e = min(abs(1. - q), 0.99)
x_ = (cos_phi * x_shift + sin_phi * y_shift) * np.sqrt(1 - e)
y_ = (-sin_phi * x_shift + cos_phi * y_shift) * np.sqrt(1 + e)
f_x_prim, f_y_prim = self.spherical.derivatives(x_,
y_,
sigma0,
Ra,
Rs,
center_x=0,
center_y=0)
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, sigma0, Ra, Rs, q, phi_G, center_x=0, center_y=0):
"""
returns Hessian matrix of function d^2f/dx^2, d^f/dy^2, d^2/dxdy
"""
alpha_ra, alpha_dec = self.derivatives(x, y, sigma0, Ra, Rs, q, phi_G,
center_x, center_y)
diff = self._diff
alpha_ra_dx, alpha_dec_dx = self.derivatives(x + diff, y, sigma0, Ra,
Rs, q, phi_G, center_x,
center_y)
alpha_ra_dy, alpha_dec_dy = self.derivatives(x, y + diff, sigma0, Ra,
Rs, q, phi_G, 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_yy, f_xy
def mass_3d_lens(self, r, sigma0, Ra, Rs, q=1, phi_G=0):
"""
:param r:
:param sigma0:
:param Ra:
:param Rs:
:param q:
:param phi_G:
:return:
"""
return self.spherical.mass_3d_lens(r, sigma0, Ra, Rs)
class PJaffe_Ellipse(LensProfileBase):
"""
this class contains functions concerning the NFW profile
relation are: R_200 = c * Rs
"""
param_names = ['sigma0', 'Ra', 'Rs', 'e1', 'e2', 'center_x', 'center_y']
lower_limit_default = {
'sigma0': 0,
'Ra': 0,
'Rs': 0,
'e1': -0.5,
'e2': -0.5,
'center_x': -100,
'center_y': -100
}
upper_limit_default = {
'sigma0': 10,
'Ra': 100,
'Rs': 100,
'e1': 0.5,
'e2': 0.5,
'center_x': 100,
'center_y': 100
}
def __init__(self):
self.spherical = PJaffe()
self._diff = 0.000001
super(PJaffe_Ellipse, self).__init__()
def function(self, x, y, sigma0, Ra, Rs, e1, e2, center_x=0, center_y=0):
"""
returns double integral of NFW profile
"""
phi_G, q = param_util.ellipticity2phi_q(e1, e2)
x_shift = x - center_x
y_shift = y - center_y
cos_phi = np.cos(phi_G)
sin_phi = np.sin(phi_G)
e = min(abs(1. - q), 0.99)
x_ = (cos_phi * x_shift + sin_phi * y_shift) * np.sqrt(1 - e)
y_ = (-sin_phi * x_shift + cos_phi * y_shift) * np.sqrt(1 + e)
f_ = self.spherical.function(x_, y_, sigma0, Ra, Rs)
return f_
def derivatives(self,
x,
y,
sigma0,
Ra,
Rs,
e1,
e2,
center_x=0,
center_y=0):
"""
returns df/dx and df/dy of the function (integral of NFW)
"""
phi_G, q = param_util.ellipticity2phi_q(e1, e2)
x_shift = x - center_x
y_shift = y - center_y
cos_phi = np.cos(phi_G)
sin_phi = np.sin(phi_G)
e = min(abs(1. - q), 0.99)
x_ = (cos_phi * x_shift + sin_phi * y_shift) * np.sqrt(1 - e)
y_ = (-sin_phi * x_shift + cos_phi * y_shift) * np.sqrt(1 + e)
f_x_prim, f_y_prim = self.spherical.derivatives(x_,
y_,
sigma0,
Ra,
Rs,
center_x=0,
center_y=0)
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, sigma0, Ra, Rs, e1, e2, center_x=0, center_y=0):
"""
returns Hessian matrix of function d^2f/dx^2, d^f/dy^2, d^2/dxdy
"""
alpha_ra, alpha_dec = self.derivatives(x, y, sigma0, Ra, Rs, e1, e2,
center_x, center_y)
diff = self._diff
alpha_ra_dx, alpha_dec_dx = self.derivatives(x + diff, y, sigma0, Ra,
Rs, e1, e2, center_x,
center_y)
alpha_ra_dy, alpha_dec_dy = self.derivatives(x, y + diff, sigma0, Ra,
Rs, 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_yy, f_xy
def mass_3d_lens(self, r, sigma0, Ra, Rs, e1=0, e2=0):
"""
:param r:
:param sigma0:
:param Ra:
:param Rs:
:param q:
:param phi_G:
:return:
"""
return self.spherical.mass_3d_lens(r, sigma0, Ra, Rs)
def setup(self):
self.profile = PJaffe()