Modifyng CAMB with Cobaya

Use of Cobaya. camb, CLASS, cosmomc, compilers, etc.
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Helena Garcia
Posts: 26
Joined: October 05 2021
Affiliation: UCI

Modifyng CAMB with Cobaya

Post by Helena Garcia » July 12 2022

I wanted to run cobaya with EDE modifying the .ini file that the CAMB that cobaya uses reads. How can I make cobaya read a modified .ini file for CAMB?
Thank you!

Antony Lewis
Posts: 1932
Joined: September 23 2004
Affiliation: University of Sussex
Contact:

Re: Modifyng CAMB with Cobaya

Post by Antony Lewis » July 12 2022

You need to pass the relevant parameters via the Cobaya input yaml file.

Helena Garcia
Posts: 26
Joined: October 05 2021
Affiliation: UCI

Re: Modifyng CAMB with Cobaya

Post by Helena Garcia » July 12 2022

That is what I did! I followed the instructions if the documentation. I added the extra parameters of modified CAMB in the theory block and in the params block (I paste the modified part of the .yaml file at the end of this message). But when I run cobaya I get the following error:

cobaya.log.LoggedError: Could not find anything to use input parameter(s) {'extra_param_1', 'extra_param_2'}.

I want to modify the dark energy model, if I was running CAMB I would input a different .ini file (setting dark_energy_model = 'EarlyQuintessence' ), but I don't know how to do this with cobaya. Do you know how can I get cobaya to identify the extra input parameters?

Thank you in advance!

Code: Select all

theory:
  camb:
    extra_args:
     extra_param_1:
     extra_param_2:
params:
   extra_param_1:
    prior:
      min: 0
      max: 1
    ref:
      dist: norm
      loc: 0.5
      scale: 0.1
    proposal: 0.05
    latex: '{\rm{extra_param_1}}'
   extra_param_2:
    prior:
      min: 0
      max: 1
    ref:
      dist: norm
      loc: 0.5
      scale: 0.1
    proposal: 0.05
    latex: '{\rm{extra_param_2}}'

Antony Lewis
Posts: 1932
Joined: September 23 2004
Affiliation: University of Sussex
Contact:

Re: Modifyng CAMB with Cobaya

Post by Antony Lewis » July 13 2022

There's no parameter called "extra_param_1" in the supplied CAMB.

you need to set dark_energy_model in the extra_args input, and use the actual parameter names when sampling (not in extra_args).

Helena Garcia
Posts: 26
Joined: October 05 2021
Affiliation: UCI

Re: Modifyng CAMB with Cobaya

Post by Helena Garcia » July 14 2022

Thank you so much! I got it running now, but I still have an issue when using the minimizer. I get this error

calc_zc_fde: NO PEAK
[0 : minimize] *ERROR* Cannot reproduce log minimum to within 0.01. Maybe your likelihood is stochastic or large numerical error? Recomputed min: -inf (was -1.79769e+308) at array([3.05057809e+00, 9.69716464e-01, 1.04123281e+00, 2.22220221e-02,..])

Do you know what can be wrong?

Here is my .yaml file

Code: Select all

theory:
  camb:
    extra_args:
      halofit_version: mead
      bbn_predictor: PArthENoPE_880.2_standard.dat
      lens_potential_accuracy: 1
      num_massive_neutrinos: 1
      nnu: 3.046
      theta_H0_range:
      - 20
      - 100
      dark_energy_model: EarlyQuintessence 
      n: 3
likelihood:
  planck_2018_lowl.TT: null
  planck_2018_lowl.EE: null
  planck_2018_highl_plik.TTTEEE: null
  bao.sdss_dr16_baoplus_lrg: null
  bao.sdss_dr16_baoplus_lyauto: null
  bao.sdss_dr16_baoplus_lyxqso: null
  bao.sdss_dr16_baoplus_qso: null
params:
  logA:
    prior:
      min: 1.61
      max: 3.91
    ref:
      dist: norm
      loc: 3.05
      scale: 0.001
    proposal: 0.001
    latex: \log(10^{10} A_\mathrm{s})
    drop: true
  As:
    value: 'lambda logA: 1e-10*np.exp(logA)'
    latex: A_\mathrm{s}
  ns:
    prior:
      min: 0.8
      max: 1.2
    ref:
      dist: norm
      loc: 0.965
      scale: 0.004
    proposal: 0.002
    latex: n_\mathrm{s}
  theta_MC_100:
    prior:
      min: 0.5
      max: 10
    ref:
      dist: norm
      loc: 1.04109
      scale: 0.0004
    proposal: 0.0002
    latex: 100\theta_\mathrm{MC}
    drop: true
    renames: theta
  cosmomc_theta:
    value: 'lambda theta_MC_100: 1.e-2*theta_MC_100'
    derived: false
  H0:
    latex: H_0
    min: 20
    max: 100
  ombh2:
    prior:
      min: 0.005
      max: 0.1
    ref:
      dist: norm
      loc: 0.0224
      scale: 0.0001
    proposal: 0.0001
    latex: \Omega_\mathrm{b} h^2
  omch2:
    prior:
      min: 0.001
      max: 0.99
    ref:
      dist: norm
      loc: 0.12
      scale: 0.001
    proposal: 0.0005
    latex: \Omega_\mathrm{c} h^2
  omegam:
    latex: \Omega_\mathrm{m}
  omegamh2:
    derived: 'lambda omegam, H0: omegam*(H0/100)**2'
    latex: \Omega_\mathrm{m} h^2
  mnu: 0.06
  YHe:
    latex: Y_\mathrm{P}
  Y_p:
    latex: Y_P^\mathrm{BBN}
  DHBBN:
    derived: 'lambda DH: 10**5*DH'
    latex: 10^5 \mathrm{D}/\mathrm{H}
  tau:
    prior:
      min: 0.01
      max: 0.8
    ref:
      dist: norm
      loc: 0.055
      scale: 0.006
    proposal: 0.003
    latex: \tau_\mathrm{reio}
  zre:
    latex: z_\mathrm{re}
  sigma8:
    latex: \sigma_8
  s8h5:
    derived: 'lambda sigma8, H0: sigma8*(H0*1e-2)**(-0.5)'
    latex: \sigma_8/h^{0.5}
  s8omegamp5:
    derived: 'lambda sigma8, omegam: sigma8*omegam**0.5'
    latex: \sigma_8 \Omega_\mathrm{m}^{0.5}
  s8omegamp25:
    derived: 'lambda sigma8, omegam: sigma8*omegam**0.25'
    latex: \sigma_8 \Omega_\mathrm{m}^{0.25}
  A:
    derived: 'lambda As: 1e9*As'
    latex: 10^9 A_\mathrm{s}
  clamp:
    derived: 'lambda As, tau: 1e9*As*np.exp(-2*tau)'
    latex: 10^9 A_\mathrm{s} e^{-2\tau}
  age:
    latex: '{\rm{Age}}/\mathrm{Gyr}'
  rdrag:
    latex: r_\mathrm{drag}
  fde_zc:
    prior:
      min: 0
      max: 0.5
    ref:
      dist: norm
      loc: 0.1
      scale: 0.01
    proposal: 0.005
    latex: '{\rm{fde_zc}}'
  zc:
    prior:
      min: 0
      max: 100000
    ref:
      dist: norm
      loc: 10000
      scale: 0.1
    proposal: 0.05
    latex: '{\rm{criticalz}}'
sampler:
  minimize:
    method: bobyqa
    ignore_prior: False
    max_evals: 1e6d
    best_of: 2
    confidence_for_unbounded: 0.9999995 
output: /volumes/data2/cobaya/
debug: true

Ali Rida Khalife
Posts: 18
Joined: October 31 2022
Affiliation: Institut d'Astrophysique de Paris

Re: Modifyng CAMB with Cobaya

Post by Ali Rida Khalife » March 03 2023

Hello!
I'm having the same error. Did you manage to solve it in the end? If yes, could you please describe how?
Thanks!

Antony Lewis
Posts: 1932
Joined: September 23 2004
Affiliation: University of Sussex
Contact:

Re: Modifyng CAMB with Cobaya

Post by Antony Lewis » March 06 2023

If the code cannot solve your model for z_c, you may need to change the definition of the parameters that are used for sampling. If mcmc works but minimize is not, maybe the parameters are getting out of the range where this works somehow.

Ali Rida Khalife
Posts: 18
Joined: October 31 2022
Affiliation: Institut d'Astrophysique de Paris

Re: Modifyng CAMB with Cobaya

Post by Ali Rida Khalife » March 09 2023

So the code is sampling, but then it produces this
calc_zc_fde: NO PEAK
and then it crashes with a segmentation fault. Here's the yaml file I'm using:

Code: Select all

output: EDE_Plk/CAMB
resume: True
timing: True
debug: True
theory:
  camb:
    extra_args:
      halofit_version: mead
      bbn_predictor: PArthENoPE_880.2_standard.dat
      lens_potential_accuracy: 1
      num_massive_neutrinos: 1
      nnu: 3.046
      theta_H0_range:
      - 20
      - 100
      dark_energy_model: 'EarlyQuintessence'
      use_zc: True
      n: 3
      AccuracyBoost: 2
      #f: 0.05
      #m: 5E-27
likelihood:
  planck_2018_lowl.TT: null
  planck_2018_lowl.EE: null
  planck_2018_highl_plik.TTTEEE: null
  planck_2018_lensing.clik: null
params:
  logA:
    prior:
      min: 1.61
      max: 3.91
    ref:
      dist: norm
      loc: 3.05
      scale: 0.001
    proposal: 0.001
    latex: \log(10^{10} A_\mathrm{s})
    drop: true
  As:
    value: 'lambda logA: 1e-10*np.exp(logA)'
    latex: A_\mathrm{s}
  ns:
    prior:
      min: 0.8
      max: 1.2
    ref:
      dist: norm
      loc: 0.965
      scale: 0.004
    proposal: 0.002
    latex: n_\mathrm{s}
  theta_MC_100:
    prior:
      min: 0.5
      max: 10
    ref:
      dist: norm
      loc: 1.04109
      scale: 0.0004
    proposal: 0.0002
    latex: 100\theta_\mathrm{MC}
    drop: true
    renames: theta
  cosmomc_theta:
    value: 'lambda theta_MC_100: 1.e-2*theta_MC_100'
    derived: false
  H0:
    latex: H_0
    min: 20
    max: 100
  ombh2:
    prior:
      min: 0.005
      max: 0.1
    ref:
      dist: norm
      loc: 0.0224
      scale: 0.0001
    proposal: 0.0001
    latex: \Omega_\mathrm{b} h^2
  omch2:
    prior:
      min: 0.001
      max: 0.99
    ref:
      dist: norm
      loc: 0.12
      scale: 0.001
    proposal: 0.0005
    latex: \Omega_\mathrm{c} h^2
  omegam:
    latex: \Omega_\mathrm{m}
  omegamh2:
    derived: 'lambda omegam, H0: omegam*(H0/100)**2'
    latex: \Omega_\mathrm{m} h^2
  mnu: 0.06
  omega_de:
    latex: \Omega_\Lambda
  YHe:
    latex: Y_\mathrm{P}
  Y_p:
    latex: Y_P^\mathrm{BBN}
  DHBBN:
    derived: 'lambda DH: 10**5*DH'
    latex: 10^5 \mathrm{D}/\mathrm{H}
  tau:
    prior:
      min: 0.01
      max: 0.8
    ref:
      dist: norm
      loc: 0.055
      scale: 0.006
    proposal: 0.003
    latex: \tau_\mathrm{reio}
  zrei:
    latex: z_\mathrm{re}
  sigma8:
    latex: \sigma_8
  s8h5:
    derived: 'lambda sigma8, H0: sigma8*(H0*1e-2)**(-0.5)'
    latex: \sigma_8/h^{0.5}
  s8omegamp5:
    derived: 'lambda sigma8, omegam: sigma8*omegam**0.5'
    latex: \sigma_8 \Omega_\mathrm{m}^{0.5}
  s8omegamp25:
    derived: 'lambda sigma8, omegam: sigma8*omegam**0.25'
    latex: \sigma_8 \Omega_\mathrm{m}^{0.25}
  A:
    derived: 'lambda As: 1e9*As'
    latex: 10^9 A_\mathrm{s}
  clamp:
    derived: 'lambda As, tau: 1e9*As*np.exp(-2*tau)'
    latex: 10^9 A_\mathrm{s} e^{-2\tau}
  age:
    latex: '{\rm{Age}}/\mathrm{Gyr}'
  rdrag:
    latex: r_\mathrm{drag}
  fde_zc:
    prior:
      min: 0
      max: 0.5
    ref:
      dist: norm
      loc: 0.1
      scale: 0.04
    proposal: 0.02
    latex: '{\rm{fde_zc}}'
  zc:
    prior:
      min: 1000
      max: 32000
    ref:
      dist: norm
      loc: 4200
      scale: 10
    proposal: 5
    latex: '{\rm{criticalz}}'
  theta_i:
       prior:
         min: 0
         max: 5
       ref:
         dist: norm
         loc: 2.2
         scale: 0.6
       proposal: 0.2
sampler:
  mcmc:
    output_every: 1
    drag: true
    oversample_power: 0.4
    proposal_scale: 1.9
    covmat: auto
    Rminus1_stop: 0.02
    Rminus1_cl_stop: 0.4
And here's the log file:

Code: Select all

[0 : output] Output to be read-from/written-into folder 'EDE_Plk', with prefix 'CAMB'
[0 : output] Found existing info files with the requested output prefix: 'EDE_Plk/CAMB'
[0 : output] Will delete previous products ('force' was requested).
[0 : prior] *WARNING* External prior 'SZ' loaded. Mind that it might not be normalized!
[0 : camb] `camb` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/code/CAMB/camb
[1 : camb] `camb` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/code/CAMB/camb
[2 : camb] `camb` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/code/CAMB/camb
[0 : planck_2018_lowl.tt] `clik` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/cliks/clik-15.1/lib/python/site-packages/clik
[1 : planck_2018_lowl.tt] `clik` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/cliks/clik-15.1/lib/python/site-packages/clik
[2 : planck_2018_lowl.tt] `clik` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/cliks/clik-15.1/lib/python/site-packages/clik
----
clik version clik_15.0-8-g8eaebd55f2cd
  gibbs_gauss b13c8fda-1837-41b5-ae2d-78d6b723fcf1
----
clik version clik_15.0-8-g8eaebd55f2cd
  gibbs_gauss b13c8fda-1837-41b5-ae2d-78d6b723fcf1
----
clik version clik_15.0-8-g8eaebd55f2cd
  gibbs_gauss b13c8fda-1837-41b5-ae2d-78d6b723fcf1
Checking likelihood '/data83/NEUCosmos/khalife/Codes/data/planck_2018/baseline/plc_3.0/low_l/commander/commander_dx12_v3_2_29.clik' on test data. got -11.6257 expected -11.6257 (diff -1.07424e-09)
----
Checking likelihood '/data83/NEUCosmos/khalife/Codes/data/planck_2018/baseline/plc_3.0/low_l/commander/commander_dx12_v3_2_29.clik' on test data. got -11.6257 expected -11.6257 (diff -1.07424e-09)
----
Checking likelihood '/data83/NEUCosmos/khalife/Codes/data/planck_2018/baseline/plc_3.0/low_l/commander/commander_dx12_v3_2_29.clik' on test data. got -11.6257 expected -11.6257 (diff -1.07424e-09)
----
[0 : planck_2018_lowl.ee] `clik` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/cliks/clik-15.1/lib/python/site-packages/clik
[1 : planck_2018_lowl.ee] `clik` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/cliks/clik-15.1/lib/python/site-packages/clik
[2 : planck_2018_lowl.ee] `clik` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/cliks/clik-15.1/lib/python/site-packages/clik
Initializing SimAll
Initializing SimAll
Initializing SimAll
----
clik version clik_15.0-8-g8eaebd55f2cd
  simall simall_EE_BB_TE
----
clik version clik_15.0-8-g8eaebd55f2cd
  simall simall_EE_BB_TE
----
clik version clik_15.0-8-g8eaebd55f2cd
  simall simall_EE_BB_TE
Checking likelihood '/data83/NEUCosmos/khalife/Codes/data/planck_2018/baseline/plc_3.0/low_l/simall/simall_100x143_offlike5_EE_Aplanck_B.clik' on test data. got -197.99 expected -197.99 (diff -4.1778e-08)
----
Checking likelihood '/data83/NEUCosmos/khalife/Codes/data/planck_2018/baseline/plc_3.0/low_l/simall/simall_100x143_offlike5_EE_Aplanck_B.clik' on test data. got -197.99 expected -197.99 (diff -4.1778e-08)
----
Checking likelihood '/data83/NEUCosmos/khalife/Codes/data/planck_2018/baseline/plc_3.0/low_l/simall/simall_100x143_offlike5_EE_Aplanck_B.clik' on test data. got -197.99 expected -197.99 (diff -4.1778e-08)
----
[2 : planck_2018_highl_plik.ttteee] `clik` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/cliks/clik-15.1/lib/python/site-packages/clik
[1 : planck_2018_highl_plik.ttteee] `clik` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/cliks/clik-15.1/lib/python/site-packages/clik
[0 : planck_2018_highl_plik.ttteee] `clik` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/cliks/clik-15.1/lib/python/site-packages/clik
----
clik version clik_15.0-8-g8eaebd55f2cd
  smica
----
clik version clik_15.0-8-g8eaebd55f2cd
  smica
----
clik version clik_15.0-8-g8eaebd55f2cd
  smica
Checking likelihood '/data83/NEUCosmos/khalife/Codes/data/planck_2018/baseline/plc_3.0/hi_l/plik/plik_rd12_HM_v22b_TTTEEE.clik' on test data. got -1172.47 expected -1172.47 (diff -4.34054e-07)
----
Checking likelihood '/data83/NEUCosmos/khalife/Codes/data/planck_2018/baseline/plc_3.0/hi_l/plik/plik_rd12_HM_v22b_TTTEEE.clik' on test data. got -1172.47 expected -1172.47 (diff -4.34053e-07)
----
[1 : planck_2018_lensing.clik] `clik` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/cliks/clik-15.1/lib/python/site-packages/clik
[2 : planck_2018_lensing.clik] `clik` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/cliks/clik-15.1/lib/python/site-packages/clik
Checking likelihood '/data83/NEUCosmos/khalife/Codes/data/planck_2018/baseline/plc_3.0/hi_l/plik/plik_rd12_HM_v22b_TTTEEE.clik' on test data. got -1172.47 expected -1172.47 (diff -4.34053e-07)
----
[0 : planck_2018_lensing.clik] `clik` module loaded successfully from /automnt/data83/NEUCosmos/khalife/Codes/cliks/clik-15.1/lib/python/site-packages/clik
Checking lensing likelihood '/data83/NEUCosmos/khalife/Codes/data/planck_2018/baseline/plc_3.0/lensing/smicadx12_Dec5_ftl_mv2_ndclpp_p_teb_consext8.clik_lensing' on test data. got -4.42102
Checking lensing likelihood '/data83/NEUCosmos/khalife/Codes/data/planck_2018/baseline/plc_3.0/lensing/smicadx12_Dec5_ftl_mv2_ndclpp_p_teb_consext8.clik_lensing' on test data. got -4.42102
Checking lensing likelihood '/data83/NEUCosmos/khalife/Codes/data/planck_2018/baseline/plc_3.0/lensing/smicadx12_Dec5_ftl_mv2_ndclpp_p_teb_consext8.clik_lensing' on test data. got -4.42102
[2 : mcmc] Getting initial point... (this may take a few seconds)
[1 : mcmc] Getting initial point... (this may take a few seconds)
[0 : mcmc] Getting initial point... (this may take a few seconds)
[0 : model] Measuring speeds... (this may take a few seconds)
[0 : model] Setting measured speeds (per sec): {planck_2018_lowl.TT: 1710.0, planck_2018_lowl.EE: 5630.0, planck_2018_highl_plik.TTTEEE: 65.5, planck_2018_lensing.clik: 517.0, camb.transfers: 0.195, camb: 0.607}
[0 : mcmc] Dragging with number of interpolating steps:
[0 : mcmc] *  1 : [['theta_MC_100', 'ombh2', 'omch2', 'tau', 'fde_zc', 'zc', 'theta_i'], ['logA', 'ns']]
[0 : mcmc] * 23 : [['A_planck'], ['calib_100T', 'calib_217T', 'A_cib_217', 'xi_sz_cib', 'A_sz', 'ksz_norm', 'gal545_A_100', 'gal545_A_143', 'gal545_A_143_217', 'gal545_A_217', 'ps_A_100_100', 'ps_A_143_143', 'ps_A_143_217', 'ps_A_217_217', 'galf_TE_A_100', 'galf_TE_A_100_143', 'galf_TE_A_100_217', 'galf_TE_A_143', 'galf_TE_A_143_217', 'galf_TE_A_217']]
[0 : mcmc] Covariance matrix selected automatically: {packages_path}/data/planck_supp_data_and_covmats/covmats/base_plikHM_TTTEEE_lowl_lowE_lensing.covmat
[0 : mcmc] Covariance matrix loaded for params ['ombh2', 'omch2', 'theta_MC_100', 'tau', 'logA', 'ns', 'A_planck', 'A_cib_217', 'xi_sz_cib', 'A_sz', 'ps_A_100_100', 'ps_A_143_143', 'ps_A_143_217', 'ps_A_217_217', 'ksz_norm', 'gal545_A_100', 'gal545_A_143', 'gal545_A_143_217', 'gal545_A_217', 'galf_TE_A_100', 'galf_TE_A_100_143', 'galf_TE_A_100_217', 'galf_TE_A_143', 'galf_TE_A_143_217', 'galf_TE_A_217', 'calib_100T', 'calib_217T']
[0 : mcmc] Missing proposal covariance for params ['fde_zc', 'zc', 'theta_i']
[0 : mcmc] Covariance matrix not complete. We will start learning the covariance of the proposal earlier: R-1 = 30 (would be 2 if all params loaded).
[1 : mcmc] Initial point: logA:3.049237, ns:0.9606397, theta_MC_100:1.041005, ombh2:0.0224096, omch2:0.1187131, tau:0.05641889, fde_zc:0.1191923, zc:4192.139, theta_i:2.965275, A_planck:1.001187, calib_100T:1.00115, calib_217T:0.998998, A_cib_217:62.83952, xi_sz_cib:0.05040397, A_sz:8.684164, ksz_norm:1.901204, gal545_A_100:7.313156, gal545_A_143:8.812706, gal545_A_143_217:19.22069, gal545_A_217:86.86567, ps_A_100_100:274.6556, ps_A_143_143:46.83286, ps_A_143_217:65.41392, ps_A_217_217:106.6884, galf_TE_A_100:0.1965717, galf_TE_A_100_143:0.2090315, galf_TE_A_100_217:0.4443052, galf_TE_A_143:0.1697768, galf_TE_A_143_217:0.6507495, galf_TE_A_217:1.858804
[0 : mcmc] Initial point: logA:3.049833, ns:0.9640953, theta_MC_100:1.041178, ombh2:0.02237474, omch2:0.1206368, tau:0.06037543, fde_zc:0.08318263, zc:4201.407, theta_i:2.24477, A_planck:0.9993208, calib_100T:1.000006, calib_217T:0.9975029, A_cib_217:63.77512, xi_sz_cib:0.01366124, A_sz:7.916333, ksz_norm:4.191227, gal545_A_100:6.983335, gal545_A_143:8.814809, gal545_A_143_217:19.043, gal545_A_217:97.76369, ps_A_100_100:202.1501, ps_A_143_143:62.51444, ps_A_143_217:35.85611, ps_A_217_217:95.74191, galf_TE_A_100:0.1333498, galf_TE_A_100_143:0.153631, galf_TE_A_100_217:0.3660849, galf_TE_A_143:0.2177076, galf_TE_A_143_217:0.7676181, galf_TE_A_217:1.753931
[2 : mcmc] Initial point: logA:3.049223, ns:0.9576636, theta_MC_100:1.041503, ombh2:0.02233509, omch2:0.1204348, tau:0.05078489, fde_zc:0.1086363, zc:4208.301, theta_i:2.559472, A_planck:0.9941897, calib_100T:1.000382, calib_217T:0.9977389, A_cib_217:78.98343, xi_sz_cib:0.1513652, A_sz:6.118284, ksz_norm:1.646877, gal545_A_100:6.29323, gal545_A_143:10.1022, gal545_A_143_217:22.41352, gal545_A_217:76.90788, ps_A_100_100:287.3958, ps_A_143_143:66.17432, ps_A_143_217:50.24537, ps_A_217_217:131.827, galf_TE_A_100:0.1131071, galf_TE_A_100_143:0.120637, galf_TE_A_100_217:0.3947619, galf_TE_A_143:0.05798746, galf_TE_A_143_217:0.6069476, galf_TE_A_217:1.994025
[0 : mcmc] Sampling!
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[2 : mcmc] Learn + convergence test @ 360 samples accepted.
[2 : likelihoodcollection] Average computation time:
   planck_2018_lowl.TT : 0.000266055 s (4893 evaluations, 1.30181 s total)
   planck_2018_lowl.EE : 0.000135869 s (4893 evaluations, 0.664807 s total)
   planck_2018_highl_plik.TTTEEE : 0.0150708 s (43724 evaluations, 658.954 s total)
   planck_2018_lensing.clik : 0.00322109 s (4893 evaluations, 15.7608 s total)
[2 : theorycollection] Average computation time:
   camb.transfers : 5.13089 s (845 evaluations, 4335.6 s total)
   camb : 1.58266 s (1145 evaluations, 1812.15 s total)
[2 : mcmc] Ready to check convergence and learn a new proposal covmat (waiting for the rest...)
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[i31:300389:0:300389] Caught signal 11 (Segmentation fault: address not mapped to object at address 0x7f342e6113b8)
==== backtrace (tid: 300389) ====
 0  /lib64/libucs.so.0(ucs_handle_error+0x2dc) [0x7f383aae3edc]
 1  /lib64/libucs.so.0(+0x2b0bc) [0x7f383aae40bc]
 2  /lib64/libucs.so.0(+0x2b28a) [0x7f383aae428a]
 3  /lib64/libpthread.so.0(+0x12cf0) [0x7f3cb230ecf0]
 4  /automnt/data83/NEUCosmos/khalife/Codes/code/CAMB/camb/camblib.so(+0xa65e7) [0x7f382f1575e7]
 5  /automnt/data83/NEUCosmos/khalife/Codes/code/CAMB/camb/camblib.so(massivenu_mp_rho_err_+0x14) [0x7f382f3fc034]
 6  /automnt/data83/NEUCosmos/khalife/Codes/code/CAMB/camb/camblib.so(+0x1e04dd) [0x7f382f2914dd]
 7  /automnt/data83/NEUCosmos/khalife/Codes/code/CAMB/camb/camblib.so(+0x1deefa) [0x7f382f28fefa]
 8  /automnt/data83/NEUCosmos/khalife/Codes/code/CAMB/camb/camblib.so(camb_mp_camb_getresults_+0x16ea) [0x7f382f28adda]
 9  /automnt/data83/NEUCosmos/khalife/Codes/code/CAMB/camb/camblib.so(handles_mp_cambdata_gettransfers_+0x16) [0x7f382f364a56]
10  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/lib/python3.9/lib-dynload/../../libffi.so.7(+0x84f5) [0x7f3b7c40d4f5]
11  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/lib/python3.9/lib-dynload/../../libffi.so.7(+0x67e6) [0x7f3b7c40b7e6]
12  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/lib/python3.9/lib-dynload/_ctypes.cpython-39-x86_64-linux-gnu.so(+0x16d4d) [0x7f3b7c627d4d]
13  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/lib/python3.9/lib-dynload/_ctypes.cpython-39-x86_64-linux-gnu.so(+0x1888b) [0x7f3b7c62988b]
14  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyObject_MakeTpCall+0x32c) [0x55bcd76e588c]
15  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyEval_EvalFrameDefault+0x4b22) [0x55bcd76e1262]
16  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x140764) [0x55bcd76db764]
17  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x161645) [0x55bcd76fc645]
18  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyEval_EvalFrameDefault+0x11fb) [0x55bcd76dd93b]
19  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x140764) [0x55bcd76db764]
20  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyFunction_Vectorcall+0xf5) [0x55bcd76eda25]
21  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyEval_EvalFrameDefault+0x11fb) [0x55bcd76dd93b]
22  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x140764) [0x55bcd76db764]
23  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x161645) [0x55bcd76fc645]
24  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(PyObject_Call+0xb4) [0x55bcd76fced4]
25  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyEval_EvalFrameDefault+0x3c62) [0x55bcd76e03a2]
26  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x140764) [0x55bcd76db764]
27  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x161645) [0x55bcd76fc645]
28  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyEval_EvalFrameDefault+0x11fb) [0x55bcd76dd93b]
29  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x140764) [0x55bcd76db764]
30  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x161645) [0x55bcd76fc645]
31  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyEval_EvalFrameDefault+0x11fb) [0x55bcd76dd93b]
32  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x140764) [0x55bcd76db764]
33  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyFunction_Vectorcall+0xf5) [0x55bcd76eda25]
34  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyEval_EvalFrameDefault+0x67a) [0x55bcd76dcdba]
35  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x152d6b) [0x55bcd76edd6b]
36  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x1615a3) [0x55bcd76fc5a3]
37  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyEval_EvalFrameDefault+0x4cff) [0x55bcd76e143f]
38  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x152d6b) [0x55bcd76edd6b]
39  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyEval_EvalFrameDefault+0x67a) [0x55bcd76dcdba]
40  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x140764) [0x55bcd76db764]
41  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyFunction_Vectorcall+0xf5) [0x55bcd76eda25]
42  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(PyObject_Call+0xb4) [0x55bcd76fced4]
43  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyEval_EvalFrameDefault+0x3c62) [0x55bcd76e03a2]
44  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x152d6b) [0x55bcd76edd6b]
45  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyEval_EvalFrameDefault+0x3c7) [0x55bcd76dcb07]
46  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x140764) [0x55bcd76db764]
47  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(_PyEval_EvalCodeWithName+0x5b) [0x55bcd76db34b]
48  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(PyEval_EvalCodeEx+0x55) [0x55bcd76db2c5]
49  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(PyEval_EvalCode+0x2b) [0x55bcd779682b]
50  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x230ef0) [0x55bcd77cbef0]
51  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x22c626) [0x55bcd77c7626]
52  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x9866f) [0x55bcd763366f]
53  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(PyRun_SimpleFileExFlags+0x1b5) [0x55bcd77c0655]
54  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(Py_RunMain+0x38d) [0x55bcd77bd12d]
55  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(Py_BytesMain+0x39) [0x55bcd77885b9]
56  /lib64/libc.so.6(__libc_start_main+0xe5) [0x7f3cb17e6d85]
57  /softs/intelpython/intelpython3-2022.2.0.8762/intelpython/python3.9/bin/python(+0x1ed43b) [0x55bcd778843b]
=================================

===================================================================================
=   BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES
=   RANK 0 PID 300387 RUNNING AT i31
=   KILLED BY SIGNAL: 9 (Killed)
===================================================================================

===================================================================================
=   BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES
=   RANK 1 PID 300388 RUNNING AT i31
=   KILLED BY SIGNAL: 9 (Killed)
===================================================================================

===================================================================================
=   BAD TERMINATION OF ONE OF YOUR APPLICATION PROCESSES
=   RANK 2 PID 300389 RUNNING AT i31
=   KILLED BY SIGNAL: 11 (Segmentation fault)
===================================================================================

Antony Lewis
Posts: 1932
Joined: September 23 2004
Affiliation: University of Sussex
Contact:

"

Post by Antony Lewis » March 10 2023

I don't know if you have modified the code, but in any case I would run CAMB separately with the problem parameters and try to understand the issue.

(note the comment at the top of DarkEnergyQuintessence.f90: "This module is not well tested, use at your own risk!")

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