param_names: SIM_c
    SIM_RV
    SIM_beta
    SIM_x1
    SIM_EBV
    STEP
    SCATTER

parameters_to_condition_on:
    [
        "c",
        "mB",
        "x1",
        "zHD",
        "cERR",
        "mBERR",
        "x1ERR",
        "MU",
        "HOST_LOGMASS",
        "MURES",
    ]

sim_parameters:
    n_sim: 60_000
    n_batch: 500
    simname: "/global/cfs/cdirs/lsst/www/DESC_TD_PUBLIC/users/bastienc/kestrel/posteriors/sims.v5.MIX.h5"
    posteriorname: "/global/cfs/cdirs/lsst/www/DESC_TD_PUBLIC/users/bastienc/kestrel/posteriors/posterior.v5.MIX.pt"

#Optional key; for use with run_nre.py. Otherwise leave as None
Models_Comparison: KESTREL_LOG.yml
    KESTREL_2COLOURS.yml

Data_File: "/global/cfs/cdirs/lsst/www/DESC_TD_PUBLIC/users/bastienc/kestrel//data_files/DES5YR.FITRES.gz"
Simbank_File: "/global/cfs/cdirs/lsst/www/DESC_TD_PUBLIC/users/bastienc/kestrel/sim_bank/SIM_BANK_SB.FITRES.gz"

#Population_B:
#    Priors:
#      SIM_c:       [“(-.1, 0)“, “(0.02, 0.1)“]
#      SIM_RV:      [“(1.5,4)“, “(0.5,2)“]
#      SIM_beta:    [“(1,2)“, “(0.05, 0.3)“]
#      SIM_x1:      [“(-2,2)“, “(0.2, 1)“]
#      SIM_x1_EVOL: [“(-1,1)“]
#      SIM_EBV:     [“(0.05, 0.5)“]
#      STEP:        [“(-0.2,0.2)“]
#      SCATTER:     [“(0,0.1)“]
#    mixing_prior:   “(0, 1)”

#########################
# Dictionaries
#########################

Functions:
    SIM_c: DistGaussian #The shape of this parameter.
    SIM_RV: DistGaussian
    SIM_EBV: DistExponential
    SIM_beta: DistGaussian
    SIM_x1: DistGaussian_EVOL

Splits:
    SIM_RV: ["Stepwise", "HOST_LOGMASS", 10] #A list containing the split parameter and location
    SIM_EBV: ["Stepwise", "HOST_LOGMASS", 10]
    STEP: ["Stepwise", "HOST_LOGMASS", 10]
    SIM_x1: ["Linear", "HOST_LOGMASS", None]

#If using higher-order functions such as DistLogistic, which require two parameters
#this dictionary tells the correlation parameter.
#ONLY works when/if calling 2-parameter functions.
Correlations:
    SIM_c: None
    SIM_RV: None
    SIM_EBV: None
    SIM_beta: None
    SIM_x1: HOST_LOGMASS

# We assume BoxUniform priors for our parameters;
# so each tuple needs to include the lower and upper bound you expect for that parameter.
# Gaussians are formatted as mu then sigma

Priors:
    SIM_c: ["(-.1, 0)", "(0.02, 0.1)"]
    SIM_EBV: ["(0.05, 0.5)"]
    SIM_beta: ["(1,2)", "(0.05, 0.3)"]
    SIM_x1: ["(-2,2)", "(0.2, 1)"]
    SIM_x1_EVOL: ["(-0.2,0.2)"]
    STEP: ["(-0.2,0.2)"]
    SCATTER: ["(0,0.1)"]
    SIM_RV: ["(1.5,4)", "(0.5,2)"]
#    SIM_RV:   ["(1,3)","(-1.5, 2.1)", "(0,.5)"] #L, k, sigma

# Fancy latex labels for plotting. Add as you see fit.
Latex_Names:
    DistExponential: [r'$\tau$']
    DistGaussian: [r'$\mu$', r'$\sigma$']
    DistGaussian_EVOL: [r'$\mu$', r'$\sigma$', r'$\mu slope$']
    SIM_c: r"$c_{int}$"
    SIM_beta: r"$\beta_{int}$"
    SIM_RV: r"$R_V$"
    SIM_EBV: r"$EBV$"
    SIM_x1: r"$x_1$"
    STEP: r'$\gamma$'
    SCATTER: r'$\sigma_{int}$'
    DistLogistic: [r"$L$", r"$k$", r'$\sigma$']
