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cosmopower_quick_evaluate.yaml
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output: /data2f-a/Workspace/moyer/cosmo/chains/first_test/chains
likelihood:
bao.sdss_dr7_mgs: # SDSS MGS
path: /tmp/cobaya_utilities/data/
bao.sdss_dr12_consensus_bao: # Boss DR11 like likelihood
path: /tmp/cobaya_utilities/data/
bao.sixdf_2011_bao: #F. Beutler et al 6dF likelihood
#soliket.sz_binned_cluster_counts.binned_cc.binned_cc_likelihood:
soliket.BinnedClusterLikelihood :
#tcat_file: 'SZ_cat.txt'
#snrcut: 6.
#experiment: 'Planck'
# bin_z_min_cluster_counts : 0.0
# bin_z_max_cluster_counts : 1.0
# bin_dz_cluster_counts : 0.1
# bin_dlog10_snr: 0.25
debug: True
verbose: True
stop_at_error: True
theorypred:
choose_theory: classy_sz
theory:
classy_szfast.classy_sz.classy_sz:
use_class_sz_fast_mode : 1
stop_at_error: true
extra_args:
#cosmo_model : 3 # w cdm 0= Lambda cdm 1= nuCDM 2 =
output : sz_cluster_counts_fft #sz_cluster_counts
mass function : T08M500c
#concentration parameter: B13
B: 1.25
N_ur: 2.0328
N_ncdm: 1
m_ncdm: 0.06
T_ncdm: 0.71611
M_min : 5e11
M_max : 5e15
ndim_redshifts : 80
#szcounts_fft_nz: 100,
n_z_dndlnM : 80,
n_m_dndlnM : 80,
has_selection_function : 1
experiment : 0 # Planck
y_m_relation : 0
signal-to-noise_cut-off_for_survey_cluster_completeness : 6.0
# sz_selection_function_thetas_file: /cosmo/moyer/Desktop/cosmopo/nemo_sim_thetas_120923_30bins.txt
# sz_selection_function_skyfracs_file: /cosmo/moyer/Desktop/cosmopo/nemo_sim_skyfracs_120923_30bins.txt
# sz_selection_function_ylims_file: /cosmo/moyer/Desktop/cosmopo/nemo_sim_ylims_120923_30bins.txt
SZ_cat_file: /cosmo/moyer/Desktop/SOLikeT/soliket/clusters/input_files/SZ_cat.txt
# A_ym: 1.9e-05
# B_ym: 0.08
# C_ym: 0.0
sigmaM_ym : 0.075 #dispersion intrinsèque relation d'échelle
# m_pivot_ym_[Msun]: 425000000000000.0
non_linear: halofit
# use_m500c_in_ym_relation: 0
# use_m200c_in_ym_relation: 1
use_skyaveraged_noise : 0 # changer de 1 à 0 suite aux conseil de Boris
# N_samp_fftw: 2048
z_min: 0.0
z_max: 1.0
# szcounts_fft_z_min: 0.0
# szcounts_fft_z_max: 2.0
# tol_dlnm_dlnq: 0.01
# ntab_dlnm_dlnq: 80
# szcounts_qmax_fft_padded: 200.0
# sigma_derivative: 0
# szcc_dof: 3.0
# szcc_qtrunc: 2.0
# HMF_prescription_NCDM: 1
# no_spline_in_tinker: 1
use_planck_binned_proba : 1 # not in example
tau_reio: 0.054 # planck 2018 value (in abstract of 1807.06209)
YHe: BBN
input_verbose : 0
background_verbose: 0
perturbations_verbose: 0
bin_z_min_cluster_counts : 0.0
bin_z_max_cluster_counts : 1.0
bin_dz_cluster_counts : 0.1
bin_dlog10_snr: 0.25
dlny : 0.1
lnymin : -30
lnymax : -2
# alpha_ym : 1.789
# ystar_ym : -0.186
dlnM_cluster_count_completeness_grid : 0.1
cluster_count_completeness_grid_z_cutoff_low : 0.2
cluster_count_completeness_grid_z_cutoff_mid : 0.5
dz_cluster_count_completeness_grid_low_z : 0.01
dz_cluster_count_completeness_grid_mid_z : 0.01
dz_cluster_count_completeness_grid_high_z : 0.1
ndim_masses : 80
k_per_decade_class_sz : 20.
k_min_for_pk_class_sz : 1e-3
k_max_for_pk_class_sz : 1e1
P_k_max_h/Mpc : 1e1
class_sz_verbose: 0
params:
# theta_MC_100:
# prior:
# min: 0.5
# max: 10
# ref:
# dist: norm
# loc: 9.5232346E-01
# scale: 0.0004
# proposal: 0.0002
# latex: 100\theta_\mathrm{MC}
# drop: true
# renames: theta
# 100*theta_s:
# value: 'lambda theta_MC_100: theta_MC_100'
# derived: false
H0:
prior:
min: 50.
max: 80.
ref:
dist: norm
loc: 68
scale: 0.1
proposal: 0.1
logA:
prior:
min: 1.61
max: 4
ref:
dist: norm
loc: 2.87
scale: 0.01
proposal: 0.01
# drop: true
latex: \log(10^{10} A_\mathrm{s})
# A_s:
# value: 'lambda logA: 1e-10*np.exp(logA)'
# latex: A_\mathrm{s}
n_s:
prior:
min: 0.8
max: 1.2
ref:
dist: norm
loc: 0.964
scale: 0.01
proposal: 0.01
latex: n_\mathrm{s}
# B:
# prior:
# min: 1.0
# max: 2.0
# ref:
# dist: norm
# loc: 1.25
# scale: 0.02
# proposal: 0.02
# latex: B
# sigmaM_ym :
# prior:
# min: 0
# max: 1
# ref:
# dist: norm
# loc: 0.075
# scale: 0.1
# proposal: 0.1
# alpha_ym :
# prior:
# min: 1
# max: 3
# ref:
# dist: norm
# loc: 1.789
# scale: 0.1
# proposal: 0.1
# ystar_ym :
# prior:
# min: -1
# max: 0
# ref:
# dist: norm
# loc: -0.186
# scale: 0.1
# proposal: 0.1
#B:
# prior:
# min: 1.
# max: 2.
# ref:
# dist: norm
# loc: 1.71
# scale: 0.02
# proposal: 0.02
# latex: B
omega_b:
prior:
min: 0.005 #avant 0.01933
max: 0.02533 # avanr 0.02533
ref:
dist: norm
loc: 0.0224
scale: 0.005
proposal: 0.005
latex: \Omega_\mathrm{b}h^2
omega_cdm:
prior:
min: 0.001 #avant 0.08
max: 0.99 # avant 0.2
ref:
dist: norm
loc: 0.125
scale: 0.005
proposal: 0.005
latex: \Omega_\mathrm{c}h^2
# F_sz:
# derived: 'lambda sigma8, Omega_m, B, H0: (sigma8/0.8)*(Omega_m/0.3)**0.35*(B/1.25)**-0.35*(H0/70.)**-0.20'
# latex: F_\mathrm{sz}
#sigma8:
# latex: \sigma_8
Omega_m:
latex: \Omega_\mathrm{m}
prior:
omega_b_prior: 'lambda omega_b: stats.norm.logpdf(omega_b, loc=0.022, scale=0.002)'
n_s_prior: 'lambda n_s: stats.norm.logpdf(n_s, loc=0.964, scale=0.014)'
# B_prior: 'lambda B: stats.norm.logpdf(B, loc=1.2820,scale=0.17)'
sampler:
#settings for covmat see https://cobaya.readthedocs.io/en/latest/sampler_mcmc.html
# mcmc:
# #covmat: /archeops/moyer/Desktop/cosmopo/class_sz_unbinned_cluster_counts_planck.covmat
# #remettre la bonne covmat de cette analyse plus tard?
# Rminus1_stop: 0.5 # remettre à 0.01 apres?
# #Rminus1_cl_stop : 0.4
# burn_in: 100
# # drag: true
# proposal_scale: 1.2
# learn_proposal: True
# #learn_every: 40
# learn_proposal_Rminus1_max: 2.
# learn_proposal_Rminus1_max_early: 80.0
# max_tries : 1000
evaluate:
override:
# #parameter values:
omega_cdm: 0.125
omega_b: 0.0224
#logA: 2.95
sigma_8: 0.81
n_s: 0.96
H0: 69.
#theta_MC_100: 1.043612
debug : False
timing: true