params_wisc2.yml

# Global parameters
global:
    # Healpix resolution
    nside: 2048
    # Output directory
    output_dir: '/mnt/extraspace/nikfilippas/yxgxk/output_lensing'

jk:
    # Do you want to do jackknives?
    do: True
    # Healpix resolution defining the jackknife regions
    nside: 8
    # Should we store the mode-coupling matrix?
    store_mcm: False

# Information about ell bandpowers
bandpowers:
    # Bandpower mode
    type: "linlog"
    # Constant width
    nlb: 20
    # Threshold between linear and logarithmic
    lsplit: 52
    # Width of linar part
    nlb_lin: 10
    # Number of logarithmic bins
    nb_log: 20

# Masks
# Add an entry for each mask used in the analysis
masks:
    # Given each mask a unique name (key)
    mask_lowz: "data/maps/mask_v3.fits"
    mask_tsz: "data/maps/mask_planck60.fits"
    mask_545: "data/maps/mask_planck20.fits"

# Maps
maps:
    - name: "wisc2"
      type: "g"
      map: "data/maps/2dstarsub_WISC_cleaned_public.bin_0.15_z_0.2.Pix512.fits"
      mask: "mask_lowz"
      dndz: "data/dndz/WISC_bin2.txt"
      beam: False
      model:
          M0:  10.549518891252172
          M1:  11.794952075732667
          Mmin:  10.549518891252172
          alpha:  1.0
          b_hydro:  0.18613969938649388
          beta_gal:  1.0
          beta_max:  1.0
          fc:  1.0
          r_corr:  -0.6007288486023787
          sigma_lnM:  0.15
          width: 0.8510867851364564
      systematics:
        - 'scos_plates'
        - 'Star_contamination/2dstarcorr_WISC_cleaned_public.bin_0.15_z_0.2.Pix512.fits'
        - 'data/maps/lambda_sfd_ebv.fits'
    - name: "y_milca"
      type: "y"
      map: "data/maps/milca_ymaps.fits"
      mask: "mask_tsz"
      beam: 10.
      systematics:
        - 'data/maps/lambda_sfd_ebv.fits'
    - name: "dust_545"
      type: "d"
      map: "data/maps/HFI_SkyMap_545_2048_R2.02_full.fits"
      mask: "mask_545"
      beam: 10.

# MCMC
mcmc:
    # Name for this run
    run_name: 'lmin10_kmax1_tinker08_ymilca_wnarrow'
    # Maximum wavenumber in units of 1/Mpc
    kmax: 1.
    # Number of samples in redshift for each bin
    nz_points_g: 32
    # Use logarithmic sampling in redshift?
    z_log_sampling: True
    # Correct the halo model in the transition regime?
    hm_correct: True
    # Print debug information?
    debug: False
    # Emcee parameters
    n_walkers: 24
    n_steps: 0
    # Continue MCMC from previous iteration?
    continue_mcmc: True
    # Save parameters (separated by whitespace)
    save_par: False
    # Cosmological mass function
    mfunc: 'tinker'
    # Halo bias model
    hbias: 'tinker10'


# Model parameters
params:
    # Each item here corresponds to one of the parameters
    # used in our model
    - name: "M0"
      # Label for plotting
      label: "M_0"
      # Is this the same as another parameter? If so, put its name here.
      alias: "Mmin"
      # Is this a free parameter?
      vary: False
      # Fiducial value
      value: 10.549518891252172
      # Prior
      prior:
          # Allowed: "Gaussian" or "TopHat"
          type: "TopHat"
          # If "TopHat", put edges here.
          # If "Gaussian", put [mean,sigma].
          values: [10.,16.]
    - name: "M1"
      label: "M_1"
      vary: True
      value: 11.794952075732667
      prior:
          type: "TopHat"
          values: [10.,16.]
    - name: "Mmin"
      label: "M_{\\rm min}"
      vary: True
      value: 10.549518891252172
      prior:
          type: "TopHat"
          values: [10.,16.]
    - name: "fc"
      label: "f_c"
      vary: False
      value: 1.
      prior:
          type: "TopHat"
          values: [0.,1.]
    - name: "alpha"
      label: "\\alpha"
      vary: False
      value: 1.
      prior:
          type: "TopHat"
          values: [0.,3.]
    - name: "beta_max"
      label: "\\beta_{\\rm max}"
      alias: "beta_gal"
    - name: "beta_gal"
      label: "beta_g"
      vary: False
      value: 1.
      prior:
          type: "TopHat"
          values: [0.1,10.]
    - name: "sigma_lnM"
      label: "\\sigma_{{\\rm ln}M}"
      vary: False
      value: 0.15
      prior:
          type: "TopHat"
          values: [0.01,1.]
    - name: "b_hydro"
      label: "b_H"
      vary: True
      value: 0.18613969938649388
      prior:
          type: "TopHat"
          values: [0.,1.]
    - name: "r_corr"
      label: "\\rho_{gy}"
      vary: True
      value: -0.6007288486023787
      prior:
          type: "TopHat"
          values: [-1.,1.]
    - name: "width"
      label: "w_{N(z)}"
      vary: True
      value: 0.8510867851364564
      prior:
          type: "TopHat"
          values: [0.8, 1.2]

# List all the different combinations of
# power spectra you want to analyze
data_vectors:
    - type: 'Cl'
      name: 'wisc2'
      covar_type: 'comb_m'
      twopoints:
          - tracers: ['wisc2','wisc2']
            lmin: 10
          - tracers: ['wisc2','y_milca']
            lmin: 0