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Daniel Gilman
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import numpy.testing as npt | ||
from pyHalo.Halos.lens_cosmo import LensCosmo | ||
from pyHalo.Halos.HaloModels.powerlaw import PowerLawSubhalo, PowerLawFieldHalo | ||
from pyHalo.Halos.HaloModels.NFW import NFWFieldHalo | ||
from pyHalo.Halos.concentration import ConcentrationDiemerJoyce | ||
from lenstronomy.LensModel.Profiles.splcore import SPLCORE | ||
from lenstronomy.LensModel.Profiles.nfw import NFW | ||
import pytest | ||
from astropy.cosmology import FlatLambdaCDM | ||
from pyHalo.Cosmology.cosmology import Cosmology | ||
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class TestSPLCORE(object): | ||
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def setup_method(self): | ||
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astropy = FlatLambdaCDM(70.0, 0.3) | ||
cosmo = Cosmology(astropy_instance=astropy) | ||
self.zhalo = 0.5 | ||
self.zsource = 2.0 | ||
self.lens_cosmo = LensCosmo(self.zhalo, self.zsource, cosmo) | ||
self.nfw_profile_lenstronomy = NFW() | ||
self.splcore = SPLCORE() | ||
self.truncation_class = None | ||
self.concentration_class = ConcentrationDiemerJoyce(self.lens_cosmo, scatter=False) | ||
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def test_lenstronomy_params(self): | ||
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m = 10 ** 8 | ||
x = 0.5 | ||
y = 1.0 | ||
r3d = 100 | ||
is_subhalo = False | ||
gamma = 2.7 | ||
x_match = 2.9 | ||
unique_tag = 1.0 | ||
kwargs_profile = {'log_slope_halo': gamma, 'x_match': x_match, 'x_core_halo': 0.075, | ||
'evaluate_mc_at_zlens': True} | ||
splcore = PowerLawFieldHalo(m, x, y, r3d, self.zhalo, is_subhalo, self.lens_cosmo, kwargs_profile, | ||
self.truncation_class, self.concentration_class, unique_tag) | ||
nfw = NFWFieldHalo(m, x, y, r3d, self.zhalo, is_subhalo, self.lens_cosmo, kwargs_profile, | ||
self.truncation_class, self.concentration_class, unique_tag) | ||
kwargs_nfw_profile = nfw.lenstronomy_params[0][0] | ||
kwargs_splcore_profile = splcore.lenstronomy_params[0][0] | ||
npt.assert_almost_equal(kwargs_splcore_profile['r_core'], | ||
kwargs_nfw_profile['Rs'] * kwargs_profile['x_core_halo'], 5) | ||
id = splcore.lenstronomy_ID | ||
npt.assert_string_equal('SPL_CORE', id[0]) | ||
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def test_enclosed_mass(self): | ||
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m = 10 ** 8 | ||
x = 0.5 | ||
y = 1.0 | ||
r3d = 100 | ||
is_subhalo = False | ||
gamma = 2.8 | ||
x_match = 3.5 | ||
unique_tag = 1.0 | ||
kwargs_profile = {'log_slope_halo': gamma, 'x_match': x_match, 'x_core_halo': 0.075, | ||
'evaluate_mc_at_zlens': True} | ||
splcore = PowerLawFieldHalo(m, x, y, r3d, self.zhalo, is_subhalo, self.lens_cosmo, kwargs_profile, | ||
self.truncation_class, self.concentration_class, unique_tag) | ||
nfw = NFWFieldHalo(m, x, y, r3d, self.zhalo, is_subhalo, self.lens_cosmo, kwargs_profile, | ||
self.truncation_class, self.concentration_class, unique_tag) | ||
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kwargs_splcore = splcore.lenstronomy_params[0][0] | ||
kwargs_nfw = nfw.lenstronomy_params[0][0] | ||
rmatch = x_match * kwargs_nfw['Rs'] | ||
m3d_nfw = self.nfw_profile_lenstronomy.mass_3d_lens(rmatch, kwargs_nfw['Rs'], | ||
kwargs_nfw['alpha_Rs']) | ||
m3d = self.splcore.mass_3d_lens(rmatch, kwargs_splcore['sigma0'], | ||
kwargs_splcore['r_core'], kwargs_splcore['gamma']) | ||
npt.assert_almost_equal(m3d_nfw/m3d, 1.0, 4) | ||
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def test_concentration_redshift_eval(self): | ||
m = 10 ** 8 | ||
x = 0.5 | ||
y = 1.0 | ||
r3d = 100 | ||
gamma = 2.6 | ||
x_match = 2.5 | ||
unique_tag = 1.0 | ||
kwargs_profile = {'log_slope_halo': gamma, 'x_match': x_match, 'x_core_halo': 0.075, | ||
'evaluate_mc_at_zlens': False} | ||
splcore = PowerLawFieldHalo(m, x, y, r3d, self.zhalo, False, self.lens_cosmo, kwargs_profile, | ||
self.truncation_class, self.concentration_class, unique_tag) | ||
splcore_subhalo = PowerLawSubhalo(m, x, y, r3d, self.zhalo, True, self.lens_cosmo, kwargs_profile, | ||
self.truncation_class, self.concentration_class, unique_tag) | ||
c = splcore.profile_args[0] | ||
c_sub = splcore_subhalo.profile_args[0] | ||
npt.assert_equal(False, c==c_sub) | ||
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if __name__ == '__main__': | ||
pytest.main() |