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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.
The text was updated successfully, but these errors were encountered:
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.
The text was updated successfully, but these errors were encountered: