Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Planck likelihood lowl_EE error cause montepython to stop #148

Open
svevoloch opened this issue Nov 2, 2021 · 0 comments
Open

Planck likelihood lowl_EE error cause montepython to stop #148

svevoloch opened this issue Nov 2, 2021 · 0 comments

Comments

@svevoloch
Copy link

svevoloch commented Nov 2, 2021

When I do the first run of montepython, everything works perfectly with the following .param file:

data.experiments=['Planck_highl_TTTEEE', 'Planck_lowl_EE', 'Planck_lowl_TT', 'bao_fs_boss_dr12', 'bao_boss']

data.parameters['omega_b'] = [ 2.2377, None, None, 0.015, 0.01, 'cosmo']
data.parameters['omega_cdm'] = [ 0.12010, None, None, 0.0013, 1, 'cosmo']
data.parameters['100*theta_s'] = [ 1.04110, None, None, 0.00030, 1, 'cosmo']
data.parameters['ln10^{10}A_s'] = [ 3.0447, None, None, 0.015, 1, 'cosmo']
data.parameters['n_s'] = [ 0.9659, None, None, 0.0042, 1, 'cosmo']
data.parameters['tau_reio'] = [ 0.0543, 0.004, None, 0.008, 1, 'cosmo']
data.parameters['m_ncdm'] = [0.15, 0., 1., 0.1, 1., 'cosmo']

data.parameters['A_cib_217'] = [ 47.2, 0, 200, 6.2593, 1, 'nuisance']
data.parameters['cib_index'] = [ -1.3, -1.3, -1.3, 0, 1, 'nuisance']
data.parameters['xi_sz_cib'] = [ 0.42, 0, 1, 0.33, 1, 'nuisance']
data.parameters['A_sz'] = [ 7.23, 0, 10, 1.4689, 1, 'nuisance']
data.parameters['ps_A_100_100'] = [ 251.0, 0, 400, 29.438, 1, 'nuisance']
data.parameters['ps_A_143_143'] = [ 47.4, 0, 400, 9.9484, 1, 'nuisance']
data.parameters['ps_A_143_217'] = [ 47.3, 0, 400, 11.356, 1, 'nuisance']
data.parameters['ps_A_217_217'] = [ 119.8, 0, 400, 10.256, 1, 'nuisance']
data.parameters['ksz_norm'] = [ 0.01, 0, 10, 2.7468, 1, 'nuisance']
data.parameters['gal545_A_100'] = [ 8.86, 0, 50, 1.8928, 1, 'nuisance']
data.parameters['gal545_A_143'] = [ 11.10, 0, 50, 1.8663, 1, 'nuisance']
data.parameters['gal545_A_143_217'] = [ 19.8, 0, 100, 3.8796, 1, 'nuisance']
data.parameters['gal545_A_217'] = [ 95.1, 0, 400, 6.9759, 1, 'nuisance']
data.parameters['galf_EE_A_100'] = [ 0.055, 0.055, 0.055, 0, 1, 'nuisance']
data.parameters['galf_EE_A_100_143'] = [ 0.040, 0.040, 0.040, 0, 1, 'nuisance']
data.parameters['galf_EE_A_100_217'] = [ 0.094, 0.094, 0.094, 0, 1, 'nuisance']
data.parameters['galf_EE_A_143'] = [ 0.086, 0.086, 0.086, 0, 1, 'nuisance']
data.parameters['galf_EE_A_143_217'] = [ 0.21, 0.21, 0.21, 0, 1, 'nuisance']
data.parameters['galf_EE_A_217'] = [ 0.70, 0.70, 0.70, 0, 1, 'nuisance']
data.parameters['galf_EE_index'] = [ -2.4, -2.4, -2.4, 0, 1, 'nuisance']
data.parameters['galf_TE_A_100'] = [ 0.114, 0, 10, 0.038762, 1, 'nuisance']
data.parameters['galf_TE_A_100_143'] = [ 0.134, 0, 10, 0.030096, 1, 'nuisance']
data.parameters['galf_TE_A_100_217'] = [ 0.482, 0, 10, 0.086185, 1, 'nuisance']
data.parameters['galf_TE_A_143'] = [ 0.224, 0, 10, 0.055126, 1, 'nuisance']
data.parameters['galf_TE_A_143_217'] = [ 0.664, 0, 10, 0.082349, 1, 'nuisance']
data.parameters['galf_TE_A_217'] = [ 2.08, 0, 10, 0.27175, 1, 'nuisance']
data.parameters['galf_TE_index'] = [ -2.4, -2.4, -2.4, 0, 1, 'nuisance']
data.parameters['calib_100T'] = [ 999.69, 0, 3000, 0.61251, 0.001, 'nuisance']
data.parameters['calib_217T'] = [ 998.16, 0, 3000, 0.63584, 0.001, 'nuisance']
data.parameters['calib_100P'] = [ 1.021, 1.021, 1.021, 0, 1, 'nuisance']
data.parameters['calib_143P'] = [ 0.966, 0.966, 0.966, 0, 1, 'nuisance']
data.parameters['calib_217P'] = [ 1.040, 1.040, 1.040, 0, 1, 'nuisance']
data.parameters['A_cnoise_e2e_100_100_EE'] = [ 1, 1, 1, 0, 1, 'nuisance']
data.parameters['A_cnoise_e2e_143_143_EE'] = [ 1, 1, 1, 0, 1, 'nuisance']
data.parameters['A_cnoise_e2e_217_217_EE'] = [ 1, 1, 1, 0, 1, 'nuisance']
data.parameters['A_sbpx_100_100_TT'] = [ 1, 1, 1, 0, 1, 'nuisance']
data.parameters['A_sbpx_143_143_TT'] = [ 1, 1, 1, 0, 1, 'nuisance']
data.parameters['A_sbpx_143_217_TT'] = [ 1, 1, 1, 0, 1, 'nuisance']
data.parameters['A_sbpx_217_217_TT'] = [ 1, 1, 1, 0, 1, 'nuisance']
data.parameters['A_sbpx_100_100_EE'] = [ 1, 1, 1, 0, 1, 'nuisance']
data.parameters['A_sbpx_100_143_EE'] = [ 1, 1, 1, 0, 1, 'nuisance']
data.parameters['A_sbpx_100_217_EE'] = [ 1, 1, 1, 0, 1, 'nuisance']
data.parameters['A_sbpx_143_143_EE'] = [ 1, 1, 1, 0, 1, 'nuisance']
data.parameters['A_sbpx_143_217_EE'] = [ 1, 1, 1, 0, 1, 'nuisance']
data.parameters['A_sbpx_217_217_EE'] = [ 1, 1, 1, 0, 1, 'nuisance']
data.parameters['A_planck'] = [ 1.00061, 0.9, 1.1, 0.0025, 1, 'nuisance']
data.parameters['A_pol'] = [ 1, 1, 1, 0, 1, 'nuisance']

data.parameters['z_reio'] = [1, None, None, 0, 1, 'derived']
data.parameters['Omega_Lambda'] = [1, None, None, 0, 1, 'derived']
#data.parameters['YHe'] = [1, None, None, 0, 1, 'derived']
data.parameters['H0'] = [0, None, None, 0, 1, 'derived']
data.parameters['A_s'] = [0, None, None, 0, 1e-9, 'derived']
data.parameters['sigma8'] = [0, None, None, 0, 1, 'derived']

data.cosmo_arguments['YHe'] = 0.2573
data.cosmo_arguments['k_pivot'] = 0.05

data.cosmo_arguments['ncdm_quadrature_strategy'] = 3
data.cosmo_arguments['ncdm_maximum_q'] = 10
data.cosmo_arguments['ncdm_N_momentum_bins'] = 15

data.cosmo_arguments['N_ur'] = 0.
data.cosmo_arguments['N_ncdm'] = 1

data.cosmo_arguments['output'] = 'mPk'
data.cosmo_arguments['P_k_max_h/Mpc'] = 1.

data.N=200000
data.write_step=1

After this, I pick the .bestfit data file and change the starting values of the given parameters to modify this .param file and try to re-run the simulations. But after ~ 3000 steps, montepython stops, giving the error

Traceback (most recent call last):
File "montepython/MontePython.py", line 40, in
sys.exit(run())
File "/home/svevoloch/Downloads/montepython_public-3.5/montepython/run.py", line 45, in run
sampler.run(cosmo, data, command_line)
File "/home/svevoloch/Downloads/montepython_public-3.5/montepython/sampler.py", line 46, in run
mcmc.chain(cosmo, data, command_line)
File "/home/svevoloch/Downloads/montepython_public-3.5/montepython/mcmc.py", line 787, in chain
newloglike = sampler.compute_lkl(cosmo, data)
File "/home/svevoloch/Downloads/montepython_public-3.5/montepython/sampler.py", line 776, in compute_lkl
value = likelihood.loglkl(cosmo, data)
File "/home/svevoloch/Downloads/montepython_public-3.5/montepython/likelihood_class.py", line 1052, in loglkl
lkl = self.clik(tot)[0]
File "lkl.pyx", line 90, in clik.lkl.clik.call
clik.lkl.CError: clik_compute(../src/clik.c:391)::ForwardError
distribution_lkl(../src/minipmc/distribution.c:219)::ForwardError
lklbs_lkl(../src/lklbs.c:219)::ForwardError
simall_lkl(../src/simall/clik_simall.c:48)::Error -1233 (multipole EE 6 too large (got 0.30044 expected <0.3))

This .param file was also tested by a different person, and he didn't have any issues, so it should not be the problem with entering the values to .param file.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant