IndexError: List index out of range

[Amoghsriv]

While running the scalar field model on Montepython, I'm getti ng the following error.
with CLASS v3.3.0
/!\ Detecting empty folder, logging the parameter file

Testing likelihoods for:
->flcdm_hz_lkl_new

Traceback (most recent call last):
File "/home/amoghsriv/cosmo/montepython_public/montepython/MontePython.py", line 40, in
sys.exit(run())
File "/home/amoghsriv/cosmo/montepython_public/montepython/run.py", line 31, in run
cosmo, data, command_line, success = safe_initialisation(
File "/home/amoghsriv/cosmo/montepython_public/montepython/run.py", line 191, in safe_initialisation
cosmo, data, command_line, success = initialise(custom_command)
File "/home/amoghsriv/cosmo/montepython_public/montepython/initialise.py", line 67, in initialise
data = Data(command_line, path)
File "/home/amoghsriv/cosmo/montepython_public/montepython/data.py", line 365, in init
self.group_parameters_in_blocks()
File "/home/amoghsriv/cosmo/montepython_public/montepython/data.py", line 670, in group_parameters_in_blocks
self.assign_over_sampling_indices()
File "/home/amoghsriv/cosmo/montepython_public/montepython/data.py", line 682, in assign_over_sampling_indices
[i for i in self.block_parameters if index < i][0])
IndexError: list index out of range

Here is my param file,

Experiment setup
data.experiments = ['fpcdm_hz_lkl_new']

Cosmological parameters
data.parameters['omega_b'] = [0.022, 0, 0.06, 0.001, 1, 'cosmo'] # Baryon density
data.parameters['omega_cdm'] = [0.12, 0, 0.50, 0.001, 1, 'cosmo'] # Cold dark matter density
data.parameters['h'] = [0.70, 0.50, 1.30, 0.005, 1, 'cosmo'] # Hubble parameter
data.parameters['Omega_scf'] = [1.0, None, None, 0.0, 1, 'cosmo']

data.parameters['scf_parameters__1'] = [0.05, 0.0, 1.0, 0.05, 1, 'cosmo']
data.parameters['scf_parameters__2'] = [0.05, 0.1, 2, 1.0, 1, 'cosmo']
data.parameters['scf_parameters__3'] = [0.0, None, None, 0.0, 1, 'cosmo']
data.parameters['scf_parameters__4'] = [0.0, None, None, 0.0, 1, 'cosmo']
data.parameters['scf_parameters__5'] = [1.0, None, None, 0.0, 1, 'cosmo']
data.parameters['scf_parameters__6'] = [0.0, None, None, 0.0, 1, 'cosmo']

data.cosmo_arguments['attractor_ic_scf'] = 'no'
data.cosmo_arguments['scf_tuning_index'] = 1

Derived parameters
data.parameters['omega_m'] = [0.1, 0, 0.6, 0.1, 1, 'derived']

Output folder
data.output = '/home/cosmo/outputfol/fpcdm_out'

Can you help me please debug this error?

[brinckmann]

Hi,

More than likely your problem is you can't have comments on the same lines as your parameters, put them on a separate line, i.e. use

# Baryon density
data.parameters['omega_b'] = [0.022, 0, 0.06, 0.001, 1, 'cosmo']

not
data.parameters['omega_b'] = [0.022, 0, 0.06, 0.001, 1, 'cosmo'] # Baryon density

Best,
Thejs

[Amoghsriv]

I've tried putting comments on the next line but still I'm getting the same error.

[Amoghsriv]

So, when I'm commenting the line
data.parameters['omega_m'] = [0.1, 0, 0.6, 0.1, 1, 'derived']

it's giving a different error
with CLASS v3.3.0
/!\ Detecting empty folder, logging the parameter file

Testing likelihoods for:
->flcdm_hz_lkl_new

Creating /home/amoghsriv/cosmo/outputfol/fpcdm_out/2025-04-14_5__1.txt

Deduced starting covariance matrix:

['omega_b', 'omega_cdm', 'h', 'scf_parameters__1', 'scf_parameters__2']
[[1.0e-06 0.0e+00 0.0e+00 0.0e+00 0.0e+00]
[0.0e+00 1.0e-06 0.0e+00 0.0e+00 0.0e+00]
[0.0e+00 0.0e+00 2.5e-05 0.0e+00 0.0e+00]
[0.0e+00 0.0e+00 0.0e+00 2.5e-03 0.0e+00]
[0.0e+00 0.0e+00 0.0e+00 0.0e+00 1.0e+00]]
Update routine is enabled with value 50 (recommended: 50)
This number is rescaled by cycle length 5 (N_slow + f_fast * N_fast) to 250
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Error in Class: background_init(L:819) :condition (pba->shooting_failed == TRUE) is true; Shooting failed, try optimising input_get_guess(). Error message:

input_shooting(L:653) :error in input_find_root(&xzero, &fevals, ppr->tol_shooting_deltax_rel, &fzw, errmsg);
=>input_find_root(L:963) :error in input_fzero_ridder(input_fzerofun_1d, x1, x2, tol_x_rel*(((fabs(x1))<(fabs(x2))) ? (fabs(x2)) : (fabs(x1)) ), pfzw, &f1, &f2, xzero, fevals, errmsg);
=>input_fzero_ridder(L:1067) :error in (*func)(xm, param, &fm, error_message);
=>input_fzerofun_1d(L:997) :error in input_try_unknown_parameters(&input, 1, pfzw, output, error_message);
=>input_try_unknown_parameters(L:1399) :error in background_init(&pr,&ba);
=>background_init(L:840) :error in background_find_equality(ppr,pba);
=>background_find_equality(L:2384) :error in background_at_tau(pba,tau_mid,long_info,inter_closeby,&index_tau_minus,pvecback);
=>background_at_tau(L:245) :error in background_z_of_tau(pba,tau,&z);
=>background_z_of_tau(L:341) :error in array_interpolate_spline( pba->tau_table, pba->bt_size, pba->z_table, pba->d2z_dtau2_table, 1, tau, &last_index, z, 1, pba->error_message);
=>array_interpolate_spline(L:1851) : x=1.125063e+02 > x_max=4.635518e-09

-LogLkl omega_b omega_cdm h scf_parameters__1scf_parameters__2

/!\ PyMultiNest detected but MultiNest likely not installed correctly. You can
safely ignore this if not running with option -m NS
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Error in Class: background_init(L:819) :condition (pba->shooting_failed == TRUE) is true; Shooting failed, try optimising input_get_guess(). Error message:

input_shooting(L:653) :error in input_find_root(&xzero, &fevals, ppr->tol_shooting_deltax_rel, &fzw, errmsg);
=>input_find_root(L:963) :error in input_fzero_ridder(input_fzerofun_1d, x1, x2, tol_x_rel*(((fabs(x1))<(fabs(x2))) ? (fabs(x2)) : (fabs(x1)) ), pfzw, &f1, &f2, xzero, fevals, errmsg);
=>input_fzero_ridder(L:1067) :error in (*func)(xm, param, &fm, error_message);
=>input_fzerofun_1d(L:997) :error in input_try_unknown_parameters(&input, 1, pfzw, output, error_message);
=>input_try_unknown_parameters(L:1399) :error in background_init(&pr,&ba);
=>background_init(L:840) :error in background_find_equality(ppr,pba);
=>background_find_equality(L:2384) :error in background_at_tau(pba,tau_mid,long_info,inter_closeby,&index_tau_minus,pvecback);
=>background_at_tau(L:245) :error in background_z_of_tau(pba,tau,&z);
=>background_z_of_tau(L:341) :error in array_interpolate_spline( pba->tau_table, pba->bt_size, pba->z_table, pba->d2z_dtau2_table, 1, tau, &last_index, z, 1, pba->error_message);
=>array_interpolate_spline(L:1851) : x=1.132355e+02 > x_max=4.635518e-09
Not using attractor initial conditions
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Error in Class: background_init(L:819) :condition (pba->shooting_failed == TRUE) is true; Shooting failed, try optimising input_get_guess(). Error message:

input_shooting(L:653) :error in input_find_root(&xzero, &fevals, ppr->tol_shooting_deltax_rel, &fzw, errmsg);
=>input_find_root(L:963) :error in input_fzero_ridder(input_fzerofun_1d, x1, x2, tol_x_rel*(((fabs(x1))<(fabs(x2))) ? (fabs(x2)) : (fabs(x1)) ), pfzw, &f1, &f2, xzero, fevals, errmsg);
=>input_fzero_ridder(L:1067) :error in (*func)(xm, param, &fm, error_message);
=>input_fzerofun_1d(L:997) :error in input_try_unknown_parameters(&input, 1, pfzw, output, error_message);
=>input_try_unknown_parameters(L:1399) :error in background_init(&pr,&ba);
=>background_init(L:840) :error in background_find_equality(ppr,pba);
=>background_find_equality(L:2384) :error in background_at_tau(pba,tau_mid,long_info,inter_closeby,&index_tau_minus,pvecback);
=>background_at_tau(L:245) :error in background_z_of_tau(pba,tau,&z);
=>background_z_of_tau(L:341) :error in array_interpolate_spline( pba->tau_table, pba->bt_size, pba->z_table, pba->d2z_dtau2_table, 1, tau, &last_index, z, 1, pba->error_message);
=>array_interpolate_spline(L:1851) : x=1.117816e+02 > x_max=4.635518e-09
5 1e+30 2.291480e-02 1.198732e-01 7.055961e-01 5.046281e-02 8.427067e-01

5 steps done, acceptance rate: 0.0

/!\ The acceptance rate is below 0.05. You might want to set the jumping factor
to a lower value than the default (2.4), with the option -f 1.5 for
instance.

[brinckmann]

Hi,

It's hard for me to guess what the problem is as I'm not familiar with the model, but perhaps your parameter starting guesses and/or parameter prior bounds are not appropriate. It doesn't seem to find a viable point in parameter space to start the MCMC run from. The code will try 100 times and in this case seems to have failed.

Best,
Thejs