def test_Lee09_and_WittMao94():
"""
test Lee et al. 2009 and Witt & Mao 1994 finite source calculation
"""
t_vec = np.array([3.5, 2., 1., 0.5, 0.])
# The values below were calculated using code developed by P. Mroz.
expected_0 = np.array([1.01084060513, 1.06962639343, 1.42451408166,
2.02334097551, 2.13919086656])
expected_1 = np.array([1.01110609638, 1.07461016241, 1.57232954942,
2.21990790526, 2.39458814753])
expected_2 = np.array([1.0110829794, 1.07404148634, 1.55620547462,
2.24809136704, 2.44503143812])
# The last values are for 2-parameter LD with same settings and lambda=0.3.
# Correction is:
# -lambda*(1-1.25*sqrt(costh))
# and for 1-parameter LD we used:
# 1-gamma*(1-1.5*costh)
# Test uniform source first.
params_0 = mm.ModelParameters(
{'t_0': 0., 'u_0': 0.5, 't_E': 1., 'rho': 1.})
mag_curve_0 = mm.MagnificationCurve(times=t_vec, parameters=params_0)
methods_0 = [-5., 'finite_source_uniform_Lee09', 5.]
mag_curve_0.set_magnification_methods(methods_0, 'point_source')
results_0 = mag_curve_0.get_point_lens_magnification()
np.testing.assert_almost_equal(expected_0, results_0, decimal=4)
# Then test 1-parameter limb-darkening.
params_1 = mm.ModelParameters(
{'t_0': 0., 'u_0': 0.1, 't_E': 1., 'rho': 1.})
mag_curve_1 = mm.MagnificationCurve(times=t_vec, parameters=params_1,
gamma=0.5)
methods_1 = [-5., 'finite_source_LD_Lee09', 5.]
mag_curve_1.set_magnification_methods(methods_1, 'point_source')
results_1 = mag_curve_1.get_point_lens_magnification()
np.testing.assert_almost_equal(expected_1, results_1, decimal=3)
# Tests for Witt & Mao 1994 start here
methods_2 = [-5., 'finite_source_uniform_WittMao94', 5.]
mag_curve_0.set_magnification_methods(methods_2, 'point_source')
results_2 = mag_curve_0.get_point_lens_magnification()
np.testing.assert_almost_equal(expected_0, results_2, decimal=4)
methods_3 = [-5., 'finite_source_LD_WittMao94', 5.]
mag_curve_1.set_magnification_methods(methods_3, 'point_source')
results_3 = mag_curve_1.get_point_lens_magnification()
np.testing.assert_almost_equal(expected_1, results_3, decimal=3)
def test_fspl():
"""
check if FSPL magnification is calculate properly
"""
t_0 = 2456789.012345
t_E = 23.4567
u_0 = 1e-4
rho = 1e-3
gamma = 0.56789
t_vec = np.array([-(rho**2-u_0**2)**0.5, 0., ((0.5*rho)**2-u_0**2)**0.5])
t_vec = t_vec * t_E + t_0
params = mm.ModelParameters(
{'t_0': t_0, 'u_0': u_0, 't_E': t_E, 'rho': rho})
mag_curve = mm.MagnificationCurve(
times=t_vec, parameters=params, gamma=gamma)
methods = [t_0-t_E, 'finite_source_LD_Yoo04', t_0+t_E]
mag_curve.set_magnification_methods(methods, 'point_source')
results = mag_curve.get_point_lens_magnification()
u = np.array([rho, u_0, 0.5*rho])
pspl = (u**2 + 2.) / np.sqrt(u**2 * (u**2 + 4.))
expected = np.array([1.27323965-gamma*0.09489869,
0.19949906-gamma*-0.03492121,
0.93421546-gamma*-0.09655794])
# These values were calculated by Andy Gould (file b0b1.dat).
expected *= pspl
np.testing.assert_almost_equal(expected/results, 1., decimal=4)
def test_magnification_type():
"""
Check type of magnification returned for model with t_eff.
At some point it was astropy quantity.
"""
parameters = mm.ModelParameters({'t_0': 1., 't_eff': 0.2, 't_E': 3.})
magnification_curve = mm.MagnificationCurve(2., parameters)
assert type(magnification_curve.get_magnification()) == np.ndarray
def test_PSPL_for_binary():
"""
test PSPL model used in a model that is defined as binary
"""
t_0 = 1000.
t_E = 20.
u_0 = 1.
t_vec = np.array([10., 100.]) * t_E + t_0
params = mm.ModelParameters({
't_0': t_0, 'u_0': u_0, 't_E': t_E, 's': 1.2, 'q': 0.1, 'alpha': 0.})
mag_curve = mm.MagnificationCurve(times=t_vec, parameters=params)
mag_curve.set_magnification_methods(None, 'point_source_point_lens')
u2 = u_0**2 + ((t_vec - t_0) / t_E)**2
pspl = (u2 + 2.) / np.sqrt(u2 * (u2 + 4.))
np.testing.assert_almost_equal(pspl, mag_curve.get_magnification())
#set up the time array for t_0-2t_E to t_0+2t_E
t_gc = julian.from_jd(t_0,'jd')
t_start = julian.to_jd(t_gc - datetime.timedelta(days=2*t_E),fmt='jd')
t_end = julian.to_jd(t_gc + datetime.timedelta(days=2*t_E),fmt='jd')
times = np.linspace(t_start,t_end,100)
#change the unit for the times array to t_E
times_plot = (times-t_0)/t_E
#set up PSPL model
#model_PSPL= mm.MagnificationCurve(times,params,coords='18:00:00 -30:00:00')
model_PSPL_1= mm.MagnificationCurve(times,params,coords='18:00:00 -30:00:00')
params.u_0 = 0.3
model_PSPL_2= mm.MagnificationCurve(times,params,coords='18:00:00 -30:00:00')
params.u_0 = 1.0
model_PSPL_3= mm.MagnificationCurve(times,params,coords='18:00:00 -30:00:00')
#get light curve data for different u_0
curve_1 = model_PSPL_1.get_point_lens_magnification()
curve_2 = model_PSPL_2.get_point_lens_magnification()
curve_3 = model_PSPL_3.get_point_lens_magnification()
"""
model_PSPL.parameters.u_0 = 0.3
print(model_PSPL.parameters)
curve_2 = model_PSPL.get_point_lens_magnification()