EXAMPLE_MCMC17.yaml

timing: False
debug: False
stop_at_error: False

likelihood:
  kids.kids_cosmic_shear:
    path: ./external_modules/data/kids
    data_file: kids_baseline_all.dataset
    integration_accuracy: 0 

params:
  As_1e9:
    prior:
      min: 0.5
      max: 5
    ref:
      dist: norm
      loc: 2.866
      scale: 0.65
    proposal: 0.4
    latex: 10^9 A_\mathrm{s})
    drop: true
    renames: A
  As:
    value: 'lambda As_1e9: 1e-9 * As_1e9'
    latex: A_\mathrm{s}
  ns:
    prior:
      min: 0.87
      max: 1.07
    ref:
      dist: norm
      loc: 0.928
      scale: 0.01
    proposal: 0.01
    latex: n_\mathrm{s}
  H0:
    prior:
      min: 55
      max: 91
    ref:
      dist: norm
      loc: 71.1
      scale: 5
    proposal: 3
    latex: H_0
  omegab:
    prior:
      min: 0.03
      max: 0.07
    ref:
      dist: norm
      loc: 0.0455
      scale: 0.004
    proposal: 0.004
    latex: \Omega_\mathrm{b}
    drop: true
  omegam:
    prior:
      min: 0.1
      max: 0.9
    ref:
      dist: norm
      loc: 0.211
      scale: 0.02
    proposal: 0.02
    latex: \Omega_\mathrm{m}
    drop: true
  mnu:
    value: 0.06
    latex: \m_\\nu
  w:
    value: -1
    latex: w_{0,\mathrm{DE}}
  tau:
    value: 0.0697186
    latex: \tau_\mathrm{reio}
  # ------------------------------------------------------------------------
  # ------------------------------------------------------------------------
  # ------------------------------------------------------------------------
  omegabh2:
    value: 'lambda omegab, H0: omegab*(H0/100)**2'
    latex: \Omega_\mathrm{b} h^2
  omegach2:
    value: 'lambda omegam, omegab, mnu, H0: (omegam-omegab)*(H0/100)**2-(mnu*(3.046/3)**0.75)/94.0708'
    latex: \Omega_\mathrm{c} h^2
  omegal:
    latex: \Omega_\Lambda
  omegamh2:
    derived: 'lambda omegam, H0: omegam*(H0/100)**2'
    latex: \Omega_\mathrm{m} h^2
  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}
  omegan2:
    latex: \Omega_\mathrm{\\nu} h^2
  omegan:
    derived: 'lambda omegan2, H0: omegan2/((H0/100)**2)'
    latex: \Omega_\mathrm{\\nu}
  # ------------------------------------------------------------------------
  # ------------------------------------------------------------------------
  # ------------------------------------------------------------------------
  # KIDS CS nuissance parameter begins
  # ------------------------------------------------------------------------
  # ------------------------------------------------------------------------
  # ------------------------------------------------------------------------
  # Shear calibration parameters
  KIDS_M1:
    prior:
      dist: norm
      loc: 0.0
      scale: 0.005
    ref:
      dist: norm
      loc: 0.0
      scale: 0.005
    proposal: 0.005
    latex: m_\mathrm{}^1
  KIDS_M2:
    prior:
      dist: norm
      loc: 0.0
      scale: 0.005
    ref:
      dist: norm
      loc: 0.0
      scale: 0.005
    proposal: 0.005
    latex: m_\mathrm{}^2
  KIDS_M3:
    prior:
      dist: norm
      loc: 0.0
      scale: 0.005
    ref:
      dist: norm
      loc: 0.0
      scale: 0.005
    proposal: 0.005
    latex: m_\mathrm{}^3
  KIDS_M4:
    prior:
      dist: norm
      loc: 0.0
      scale: 0.005
    ref:
      dist: norm
      loc: 0.0
      scale: 0.005
    proposal: 0.005
    latex: m_\mathrm{}^4
  KIDS_M5:
    prior:
      dist: norm
      loc: 0.0
      scale: 0.005
    ref:
      dist: norm
      loc: 0.0
      scale: 0.005
    proposal: 0.005
    latex: m_\mathrm{}^5
  # ------------------------------------------------------------------------
  # Intrinsic alignment
  KIDS_A1_1:
    prior:
      min: -5
      max:  5
    ref:
      dist: norm
      loc: 0.7
      scale: 0.5
    proposal: 0.5
    latex: A_\mathrm{1-IA}^1
  KIDS_A1_2:
    prior:
      min: -5
      max:  5
    ref:
      dist: norm
      loc: -1.7
      scale: 0.5
    proposal: 0.5
    latex: A_\mathrm{1-IA}^2
  KIDS_A1_3:
    value: 0.0
    latex: A_\mathrm{1-IA}^3
  KIDS_A1_4:
    value: 0.0
    latex: A_\mathrm{1-IA}^4
  KIDS_A1_5:
    value: 0.0
    latex: A_\mathrm{1-IA}^5
  # ------------------------------------------------------------------------
  KIDS_BARYON_Q1:
    prior:
      min: -3
      max: 9
    ref:
      dist: norm
      loc: 3
      scale: 5
    proposal: 1
    latex: Q1_\mathrm{KiDS}^1
  KIDS_BARYON_Q2:
    value: 0.0
    latex: BQ2_\mathrm{KiDS}^2
  KIDS_BARYON_Q3:
    value: 0.0
    latex: BQ3_\mathrm{KiDS}^1
  KIDS_BARYON_Q4:
    value: 0.0
    latex: BQ4_\mathrm{KiDS}^2
  # ------------------------------------------------------------------------
  # ------------------------------------------------------------------------
  # ------------------------------------------------------------------------
  # KIDS CS nuissance parameter ends
  # ------------------------------------------------------------------------
  # ------------------------------------------------------------------------
  # ------------------------------------------------------------------------
   
theory:
  camb:
    path: ./external_modules/code/CAMB
    use_renames: True
    extra_args:
      halofit_version: takahashi
      AccuracyBoost: 1.1
      lens_potential_accuracy: 1.00
      num_massive_neutrinos: 1
      nnu: 3.046
      dark_energy_model: ppf
      accurate_massive_neutrino_transfers: false
      k_per_logint: 20

sampler:
  mcmc:
    # ---------------------------------------------------------------------
    # File (w/ path) or matrix defining a covariance matrix for the proposal:
    # - null (default): will be generated from params info (prior and proposal)
    # - matrix: remember to set `covmat_params` to the parameters in the matrix
    covmat: 
    covmat_params:
    # ---------------------------------------------------------------------
    # ---------------------------------------------------------------------
    # Proposal covariance matrix learning
    # ---------------------------------------------------------------------
    # ---------------------------------------------------------------------
    learn_proposal: True
    # Don't learn if convergence better than...
    learn_proposal_Rminus1_min: 0.03
    # Don't learn if convergence is worse than...
    learn_proposal_Rminus1_max: 50.
    # (even earlier if a param is not in the given covariance matrix)
    learn_proposal_Rminus1_max_early: 2000.
    # ---------------------------------------------------------------------
    # ---------------------------------------------------------------------
    # Convergence and stopping
    # ---------------------------------------------------------------------
    # ---------------------------------------------------------------------
    # Maximum number of posterior evaluations
    max_samples: .inf
    # Gelman-Rubin R-1 on means
    Rminus1_stop: 0.02
    # Gelman-Rubin R-1 on std deviations
    Rminus1_cl_stop: 0.2
    Rminus1_cl_level: 0.95
    # ---------------------------------------------------------------------
    # ---------------------------------------------------------------------
    # Exploiting speed hierarchy
    # ---------------------------------------------------------------------
    # ---------------------------------------------------------------------
    measure_speeds: False
    drag: False
    oversample_power: 0.25
    oversample_thin: True
    blocking:
      - [1,
          [
            As_1e9, ns, H0, omegab, omegam
          ]
        ]
      - [5,
          [
            KIDS_DZ_S1, KIDS_DZ_S2, KIDS_DZ_S3, KIDS_DZ_S4, KIDS_DZ_S5, KIDS_A1_1, KIDS_A1_2
          ]
        ]
      - [25,
          [
            KIDS_M1, KIDS_M2, KIDS_M3, KIDS_M4, KIDS_M5, KIDS_BARYON_Q1
          ]
        ]
    # ---------------------------------------------------------------------
    # ---------------------------------------------------------------------
    # Avoid chain getting suck forever
    # ---------------------------------------------------------------------
    # ---------------------------------------------------------------------
    max_tries: 10000
    burn_in: 0
    # ---------------------------------------------------------------------
    # ---------------------------------------------------------------------
    # When no MPI used, number of fractions of the chain to compare
    # ---------------------------------------------------------------------
    # ---------------------------------------------------------------------
    Rminus1_single_split: 4

output: ./projects/kids/chains/EXAMPLE_MCMC17