def main():
start = time.time()
om_lambdas = np.linspace(0., 0.99, 50)
z_lens_initial = 0.5
# om_k = 0.1
start_thetas = np.array([1 / 3600 / 180 * np.pi] * 50) # 1 arcsec
step_size = 1e-9
first = True
filename = 'data/experiment.csv'
to_file = True
print(filename)
cosmo = LambdaCDM(H0=70, Om0=1, Ode0=0)
dang_lens = cosmo.angular_diameter_distance(z_lens_initial).value
comoving_lens = cosmo.comoving_transverse_distance(z_lens_initial).value
theta = start_thetas[0]
thetas = []
dl = []
ms = []
com_lens = []
exit_rhs = []
enter_phis = []
alphas = []
om_ks = []
raw_rs = []
for om in tqdm(om_lambdas):
om_k = 0
om_m = 1 - om - om_k
k = omk2k(om_k, H_0)
ms.append(M)
z_lens = binary_search(0, z_lens_initial, dang_lens, om_m, om)
comoving_lens = dang_lens * (1 + z_lens)
# dang_lens = comoving_lens / (1+z_lens)
# print("dang_lens", dang_lens)
# print("z_lens", z_lens)
# print(get_distances(0.5, Omega_Lambda=om, Omega_m=om_m))
# comoving_lens, dang_lens = get_distances(z_lens, Omega_Lambda=om, Omega_m=om_m)
# cosmo = LambdaCDM(H0=70, Om0=om_m, Ode0=om)
# dang_lens = cosmo.angular_diameter_distance(z_lens).value
# comoving_lens = cosmo.comoving_transverse_distance(z_lens).value
dl.append(dang_lens)
com_lens.append(comoving_lens)
thetas.append(theta)
alpha, exit_rh, enter_phi, raw_r, source_a = solve(
theta,
plot=False,
comoving_lens=comoving_lens,
Omega_Lambda=om,
Omega_m=om_m,
dt=step_size)
exit_rhs.append(exit_rh)
enter_phis.append(enter_phi)
alphas.append(alpha)
om_ks.append(om_k)
raw_rs.append(raw_r)
thetas = np.array(thetas)
dl = np.array(dl)
ms = np.array(ms)
com_lens = np.array(com_lens)
exit_rhs = np.array(exit_rhs)
enter_phis = np.array(enter_phis)
alphas = np.array(alphas)
om_ks = np.array(om_ks)
raw_rs = np.array(raw_rs)
# print("lengths", len(thetas), len(dl), len(ms), len(com_lens), len(exit_rhs), len(enter_phis), len(alphas))
df = pd.DataFrame({
'DL': dl,
'M': ms,
'om_lambdas': om_lambdas,
'step': [step_size] * len(thetas),
'theta': thetas,
'comoving_lens': com_lens,
'exit_rhs': exit_rhs,
'enter_phis': enter_phis,
'alphas': alphas,
'om_ks': om_ks,
'raw_rs': raw_rs,
})
if to_file:
if first:
df.to_csv(filename, index=False)
first = False
else:
df.to_csv(filename, index=False, header=False, mode='a')
print("Time taken: {}".format(time.time() - start))
def main():
start = time.time()
om_lambdas = np.linspace(0.99, 0.999, 1)
z_lens_all = np.linspace(.5, 1.2, 1)
# om_m = 0.5
om_k = 0
# start_thetas = np.array([8e-7]*50)
start_thetas = np.array([0.5 / 3600 / 180 * np.pi] * 50) # 1 arcsec
step_size = 1e-7
first = True
filename = 'data/ltb2.csv'
to_file = False
print(filename)
for theta, z_lens in tqdm(list(zip(start_thetas, z_lens_all))):
thetas = []
dl = []
ms = []
com_lens = []
exit_rhs = []
enter_phis = []
alphas = []
om_ks = []
raw_rs = []
for om in tqdm(om_lambdas):
# om_k = 1-om-om_m
om_m = 1 - om
k = omk2k(om_k, H_0)
ms.append(M)
# comoving_lens, dang_lens = get_distances(z_lens, Omega_Lambda=om, Omega_m=om_m)
cosmo = LambdaCDM(H0=70, Om0=om_m, Ode0=om)
dang_lens = cosmo.angular_diameter_distance(z_lens).value
comoving_lens = cosmo.comoving_transverse_distance(z_lens).value
dl.append(dang_lens)
com_lens.append(comoving_lens)
thetas.append(theta)
alpha, exit_rh, enter_phi, raw_r, source_a = solve(
theta,
plot=True,
comoving_lens=comoving_lens,
Omega_Lambda=om,
Omega_m=om_m,
dt=step_size)
exit_rhs.append(exit_rh)
enter_phis.append(enter_phi)
alphas.append(alpha)
om_ks.append(om_k)
raw_rs.append(raw_r)
# R = dang_lens*theta
# dls = cosmo.angular_diameter_distance_z1z2(z_lens, 1/source_a-1)
# ds = cosmo.angular_diameter_distance_z1z2(0, 1/source_a-1)
# print(dls, ds)
# print("dang_s", get_distances(1./source_a-1, Omega_Lambda=om, Omega_m=om_m))
# dang_s = source_a*chi2r(k, r2chi(k, raw_r) + r2chi(k, comoving_lens))
# print("dang_s from numerical", dang_s, source_a*raw_r)
# print("raw_rs", raw_r)
# r0 = 1/(1/R + M/R**2 + 3/16*M**2/R**3)
# print("r0", r0)
# A_frw = 4*M/R + 15*np.pi*M**2/4/R**2 + 401/12*M**3/R**3
# frw = comoving_lens/(A_frw/theta -1)
# print("R", dang_lens*theta)
# # alpha2 = (comoving_lens + raw_r)/raw_r*theta
# # alpha2 = np.arctan(np.tan(theta)*chi2r(k, r2chi(k, raw_r)+r2chi(k, comoving_lens))/raw_r) + theta
# alpha2 = chi2r(k, r2chi(k, raw_r)+r2chi(k, comoving_lens))/raw_r*theta
# print("A_frw", A_frw, alpha)
# print("compare", alpha/A_frw-1)
# print(dang_s*theta/raw_r/6.62068423e-01)
# chi_s = r2chi(k, r) + r2chi(k, comoving_lens)
# d_s = a*chi2r(k, chi_s)
# d_ls = a * r
# ds.append(d_s)
# dls.append(d_ls)
thetas = np.array(thetas)
dl = np.array(dl)
ms = np.array(ms)
com_lens = np.array(com_lens)
exit_rhs = np.array(exit_rhs)
enter_phis = np.array(enter_phis)
alphas = np.array(alphas)
om_ks = np.array(om_ks)
raw_rs = np.array(raw_rs)
# print("lengths", len(thetas), len(dl), len(ms), len(com_lens), len(exit_rhs), len(enter_phis), len(alphas))
df = pd.DataFrame({
'DL': dl,
'M': ms,
'om_lambdas': om_lambdas,
'step': [step_size] * len(thetas),
'theta': thetas,
'z_lens': [z_lens] * len(thetas),
'comoving_lens': com_lens,
'exit_rhs': exit_rhs,
'enter_phis': enter_phis,
'alphas': alphas,
'om_ks': om_ks,
'raw_rs': raw_rs,
})
if to_file:
if first:
df.to_csv(filename, index=False)
first = False
else:
df.to_csv(filename, index=False, header=False, mode='a')
print("Time taken: {}".format(time.time() - start))
def main():
start = time.time()
om_lambdas = np.linspace(0., 0.99, 1)
z_lens_all = np.linspace(.5, 1.2, 1)
om_m = 1
om = 0
om_k = 0
start_thetas = np.array([1 / 3600 / 180 * np.pi] * 50) # 1 arcsec
step_size = 1e-9
first = True
filename = 'data/errors.csv'
to_file = True
print(filename)
thetas = []
dl = []
ms = []
com_lens = []
exit_rhs = []
enter_phis = []
alphas = []
om_ks = []
raw_rs = []
z_lens = 0.5
theta = 1 / 3600 / 180 * np.pi
tolerances = np.linspace(1e-14, 1e-12, 1000)
for t in tqdm(tolerances):
global tols
tols['rtol'] = t
k = omk2k(om_k, H_0)
ms.append(M)
# comoving_lens, dang_lens = get_distances(z_lens, Omega_Lambda=om, Omega_m=om_m)
cosmo = LambdaCDM(H0=70, Om0=om_m, Ode0=om)
dang_lens = cosmo.angular_diameter_distance(z_lens).value
comoving_lens = cosmo.comoving_transverse_distance(z_lens).value
# print("comoving_lens", comoving_lens)
dl.append(dang_lens)
com_lens.append(comoving_lens)
thetas.append(theta)
alpha, exit_rh, enter_phi, raw_r, source_a = solve(
theta,
plot=False,
comoving_lens=comoving_lens,
Omega_Lambda=om,
Omega_m=om_m,
dt=step_size)
exit_rhs.append(exit_rh)
enter_phis.append(enter_phi)
alphas.append(alpha)
om_ks.append(om_k)
raw_rs.append(raw_r)
# R = dang_lens*theta
# dls = cosmo.angular_diameter_distance_z1z2(z_lens, 1/source_a-1)
# ds = cosmo.angular_diameter_distance_z1z2(0, 1/source_a-1)
# print(dls, ds)
# print("dang_s", get_distances(1./source_a-1, Omega_Lambda=om, Omega_m=om_m))
# dang_s = source_a*chi2r(k, r2chi(k, raw_r) + r2chi(k, comoving_lens))
# print("dang_s from numerical", dang_s, source_a*raw_r)
# print("raw_rs", raw_r)
# r0 = 1/(1/R + M/R**2 + 3/16*M**2/R**3)
# print("r0", r0)
# A_frw = 4*M/R + 15*np.pi*M**2/4/R**2 + 401/12*M**3/R**3
# frw = comoving_lens/(A_frw/theta -1)
# print("R", dang_lens*theta)
# # alpha2 = (comoving_lens + raw_r)/raw_r*theta
# # alpha2 = np.arctan(np.tan(theta)*chi2r(k, r2chi(k, raw_r)+r2chi(k, comoving_lens))/raw_r) + theta
# alpha2 = chi2r(k, r2chi(k, raw_r)+r2chi(k, comoving_lens))/raw_r*theta
# print("A_frw", A_frw, alpha)
# print("compare", alpha/A_frw-1)
# print(dang_s*theta/raw_r/6.62068423e-01)
# chi_s = r2chi(k, r) + r2chi(k, comoving_lens)
# d_s = a*chi2r(k, chi_s)
# d_ls = a * r
# ds.append(d_s)
# dls.append(d_ls)
thetas = np.array(thetas)
dl = np.array(dl)
ms = np.array(ms)
com_lens = np.array(com_lens)
exit_rhs = np.array(exit_rhs)
enter_phis = np.array(enter_phis)
alphas = np.array(alphas)
om_ks = np.array(om_ks)
raw_rs = np.array(raw_rs)
# print("lengths", len(thetas), len(dl), len(ms), len(com_lens), len(exit_rhs), len(enter_phis), len(alphas))
df = pd.DataFrame({'raw_rs': raw_rs, 'tols': tolerances})
if to_file:
if first:
df.to_csv(filename, index=False)
first = False
else:
df.to_csv(filename, index=False, header=False, mode='a')
print("Time taken: {}".format(time.time() - start))
