config_bayesian_ITC_one_to_two.yaml

# Configuration file for Bayesian inference run

# Define the name for this specific run. This will be used for creating output directories.
run_name: "xxxx_xx_xx_one_to_two_binding"

# If set to True, the script will attempt to continue a previous run with the same run_name.
# In this case, other input parameters will be loaded from the config file saved in the run_name folder.
continue_run: False

# Define the names of the binding states (e.g., different complexes formed).
binding_states: ['mono-ligated','di-ligated']
# Define the names of the components involved in the binding.
names_components: ['monomer','dimer']
# Define the degeneracy of each binding stage. This accounts for micro/macro degeneracy due to multiple equivalent binding sites.
degeneracy_micro_macro: [2,1]
# Define the stoichiometry of each component in each binding stage.
# Each inner list represents a binding stage, and the values correspond to the components in names_components.
components_binding_states: [[1,1],[2,1]]
# Define the bounds for the free energy (g) and enthalpy (h) parameters for each binding state.
# The first half of the bounds are for free energy, and the second half are for enthalpy,
# in the order defined by binding_states.
bounds: [[-20.0, 0.0],#g_mono
        [-45.0, 5.0],#g_di
        [-20.0, 0.0],#h_mono
        [-55.0, 15.0],#h_di 
        ]

# Define combinations of binding states for calculating differential free energy and enthalpy.
# These combinations are used to enforce constraints or define priors on differences between binding stages.
dd_combinations: [[-2,1]]
# Define names for the differential combinations.
dd_names: ['dd']
# Define the bounds for the differential free energy values.
# If a single bound is provided, it is applied to all differential combinations.
ddg_bounds: [[-5,5]]
# Define the bounds for the differential enthalpy values.
# If a single bound is provided, it is applied to all differential combinations.
ddh_bounds: [[-15,15]]

# Define the effective number of samples for the Bayesian inference sampler (Pocomc).
n_effective: 1024
# Define the total number of steps for the Bayesian inference run.
n_total: 4096

# If True, use a posterior distribution from a previous run as a prior.
posterior: False
# Path to the data directory of the previous run if posterior is True.
posterior_path: 'data_posterior/'
# Indices of parameters in the posterior data to be used if posterior is True.
posterior_indices: []

# If True, apply filtering based on concentration ratio during prior sampling for isotherms.
filtering: True
# Define the shape of the prior distribution for isotherm parameters ('uniform', 'gaussian', or 'lognormal').
prior_shape: 'lognormal'
# If True, use a Jeffreys prior for the sigma parameter of the isotherms.
jeffreys_sigma: False
# If True, automatically determine the bound for the h0 parameter based on isotherm data.
h0_auto: True

# Define the prior width for the concentration parameters of the isotherms. 1=100%
# Values only important for initial plotting or in case of non-hierarchical run, but structure should fit prior_width_bounds
# Can be a single value applied to all components/isotherms or a list of values or a list of lists of values and values
width: [1,1]  # more complicated example: width: [[0.3,1],0.3] has two different priors for the first component, which is used when is specified in order_isotherms

# Define the bounds for the prior width parameter(s). 
# Can be a simple [[0,2]] if using the same hyperparameter to model all concentration errors with a range of 0 to 200% or [[0,2],[0,2]] if one prior per component for a two component system
# For simple Bayesian run that is non-hierarchical leave empty []
prior_width_bounds: [[0,2],[0,2]] # more complicated example: prior_width_bounds: [[[0,2],[0,2]],[0,2]] has two different priors for the first component, which is used when is specified in order_isotherms

# Define the prior width bounds used for the components of each isotherms. If width is a simple list of values and there is no specification necessary, leave empty []
# This is a list of lists, where each inner list corresponds to a component and contains the indices
# of the respective prior_width_bounds entry used as a prior range for that specific isotherm
order_isotherms: [] # more complicated example: order_isotherms: [[0,1,1],[0,0,0]]

# List of file paths to the isotherm data files.
isotherms: ['isotherms/syn_2_4_dimsyr_True.csv',
            'isotherms/syn_2_6_dimsyr_True.csv',
            'isotherms/syn_6_2_dimsyr_False.csv',
            ]

# Number of CPU cores to use for parallel processing in Pocomc.
kernels: 1