[search]
    nwalkers -> int
        The number of walkers in the ensemble used to sample parameter space.
    nsteps -> int
        The number of steps that must be taken by every walker. The `NonLinearSearch` will thus run for nwalkers *
        nsteps iterations.

[initialize]
    method -> str
        The method used to generate where walkers are initialized in parameter space, with options:
            ball (default):
                Walkers are initialized by randomly drawing unit values from a uniform distribution between the
                initialize_ball_lower_limit and initialize_ball_upper_limit values. It is recommended these limits are
                small, such that all walkers begin close to one another.
            prior:
                Walkers are initialized by randomly drawing unit values from a uniform distribution between 0 and 1,
                thus being distributed over the prior.
    ball_lower_limit -> float
        The lower limit of the uniform distribution unit values are drawn from when initializing walkers using the
        ball method.
    ball_upper_limit -> float
        The upper limit of the uniform distribution unit values are drawn from when initializing walkers using the
        ball method.

[auto_correlation]
    check_for_convergence -> bool
        Whether the auto-correlation lengths of the Emcee samples are checked to determine the stopping criteria.
        If `True`, this option may terminate the Emcee run before the input number of steps, nsteps, has
        been performed. If `False` nstep samples will be taken.
    check_size -> int
        The length of the samples used to check the auto-correlation lengths (from the latest sample backwards).
        For convergence, the auto-correlations must not change over a certain range of samples. A longer check-size
        thus requires more samples meet the auto-correlation threshold, taking longer to terminate sampling.
        However, shorter chains risk stopping sampling early due to noise.
    required_length -> int
        The length an auto_correlation chain must be for it to be used to evaluate whether its change threshold is
        sufficiently small to terminate sampling early.
    change_threshold -> float
        The threshold value by which if the change in auto_correlations is below sampling will be terminated early.

[prior_passer]
sigma=3.0
use_errors=True
use_widths=True

[parallel]
    number_of_cores -> 1
        The number of cores Emcee sampling is performed using a Python multiprocessing Pool instance. If 1, a pool
        instance is not created and the job runs in serial.