def test_realistic(self):
"""
realistic test example
:return:
"""
light_profile_list = ['HERNQUIST_ELLIPSE', 'PJAFFE_ELLIPSE']
kwargs_light = [{
'Rs': 0.10535462602138289,
'q': 0.46728323131925864,
'center_x': -0.02678473951679429,
'center_y': 0.88691126347462712,
'phi_G': 0.74260706384506325,
'sigma0': 3.7114695634960109
}, {
'Rs': 0.44955054610388684,
'q': 0.66582356813012267,
'center_x': 0.019536801118136753,
'center_y': 0.0218888643537157,
'Ra': 0.0010000053334891974,
'phi_G': -0.33379268413794494,
'sigma0': 967.00280526319796
}]
lightProfile = LightProfile(light_profile_list)
R = 0.01
light2d = lightProfile.light_2d(R=R, kwargs_list=kwargs_light)
out = integrate.quad(
lambda x: lightProfile.light_3d(np.sqrt(R**2 + x**2), kwargs_light
), 0, 100)
print out, 'out'
npt.assert_almost_equal(light2d / (out[0] * 2), 1., decimal=3)
def test_light_3d(self):
lightProfile = LightProfile(profile_list=['HERNQUIST'])
r = np.logspace(-2, 2, 100)
kwargs_profile = [{'sigma0': 1., 'Rs': 0.5}]
light_3d = lightProfile.light_3d_interp(r, kwargs_profile)
light_3d_exact = lightProfile.light_3d(r, kwargs_profile)
for i in range(len(r)):
npt.assert_almost_equal(light_3d[i] / light_3d_exact[i],
1,
decimal=3)
def test_draw_light_PJaffe(self):
lightProfile = LightProfile(profile_list=['PJAFFE'])
kwargs_profile = [{'sigma0': 1., 'Rs': 0.5, 'Ra': 0.2}]
r_list = lightProfile.draw_light_2d(kwargs_profile, n=50000)
bins = np.linspace(0, 1, 10)
hist, bins_hist = np.histogram(r_list, bins=bins, normed=True)
light2d = lightProfile.light_2d(R=(bins_hist[1:] + bins_hist[:-1]) /
2.,
kwargs_list=kwargs_profile)
light2d *= (bins_hist[1:] + bins_hist[:-1]) / 2.
light2d /= np.sum(light2d)
hist /= np.sum(hist)
#print light2d / hist
npt.assert_almost_equal(light2d[4] / hist[4], 1, decimal=2)
lightProfile = LightProfile(profile_list=['PJAFFE'],
kwargs_numerics={
'min_interpolate': 0.0001,
'max_interpolate': 20.
})
kwargs_profile = [{'sigma0': 1., 'Rs': 0.04, 'Ra': 0.02}]
r_list = lightProfile.draw_light_2d(kwargs_profile, n=50000)
bins = np.linspace(0., 0.1, 10)
hist, bins_hist = np.histogram(r_list, bins=bins, normed=True)
light2d = lightProfile.light_2d(R=(bins_hist[1:] + bins_hist[:-1]) /
2.,
kwargs_list=kwargs_profile)
light2d *= (bins_hist[1:] + bins_hist[:-1]) / 2.
light2d /= np.sum(light2d)
hist /= np.sum(hist)
print light2d / hist
npt.assert_almost_equal(light2d[4] / hist[4], 1, decimal=2)
def test_draw_light(self):
lightProfile = LightProfile(profile_list=['HERNQUIST'])
kwargs_profile = [{'sigma0': 1., 'Rs': 0.8}]
r_list = lightProfile.draw_light_2d(kwargs_profile, n=100000)
bins = np.linspace(0., 1, 20)
hist, bins_hist = np.histogram(r_list, bins=bins, normed=True)
light2d = lightProfile.light_2d(R=(bins_hist[1:] + bins_hist[:-1]) /
2.,
kwargs_list=kwargs_profile)
light2d *= (bins_hist[1:] + bins_hist[:-1]) / 2.
light2d /= np.sum(light2d)
hist /= np.sum(hist)
print light2d / hist
for i in range(len(hist)):
print bins_hist[i], i, light2d[i] / hist[i]
npt.assert_almost_equal(light2d[i] / hist[i], 1, decimal=1)
def test_projected_light_integral_hernquist(self):
"""
:return:
"""
light_profile_list = ['HERNQUIST']
r_eff = 1.
kwargs_light = [{
'Rs': r_eff,
'sigma0': 1.
}] # effective half light radius (2d projected) in arcsec
lightProfile = LightProfile(light_profile_list)
R = 2
light2d = lightProfile.light_2d(R=R, kwargs_list=kwargs_light)
out = integrate.quad(
lambda x: lightProfile.light_3d(np.sqrt(R**2 + x**2), kwargs_light
), 0, 100)
npt.assert_almost_equal(light2d, out[0] * 2, decimal=3)
def test_projected_light_integral_pjaffe(self):
"""
:return:
"""
light_profile_list = ['PJAFFE']
kwargs_light = [{
'Rs': .5,
'Ra': 0.01,
'sigma0': 1.
}] # effective half light radius (2d projected) in arcsec
lightProfile = LightProfile(light_profile_list)
R = 0.01
light2d = lightProfile.light_2d(R=R, kwargs_list=kwargs_light)
out = integrate.quad(
lambda x: lightProfile.light_3d(np.sqrt(R**2 + x**2), kwargs_light
), 0, 100)
print out, 'out'
npt.assert_almost_equal(light2d / (out[0] * 2), 1., decimal=3)
def test_realistic_0(self):
"""
realistic test example
:return:
"""
light_profile_list = ['HERNQUIST']
kwargs_light = [{
'Rs': 0.10535462602138289,
'center_x': -0.02678473951679429,
'center_y': 0.88691126347462712,
'sigma0': 3.7114695634960109
}]
lightProfile = LightProfile(light_profile_list)
R = 0.01
light2d = lightProfile.light_2d(R=R, kwargs_list=kwargs_light)
out = integrate.quad(
lambda x: lightProfile.light_3d(np.sqrt(R**2 + x**2), kwargs_light
), 0, 100)
print out, 'out'
npt.assert_almost_equal(light2d / (out[0] * 2), 1., decimal=3)