A general description of configs in PyAutoLens is provided here, checkout their associated doc file for a more
 detailed description of every config.

### General ###

    Customizes general PyAutoLens settings such as the frequency of logging and backing up,

### Priors ###

Default:

    The default priors used on every model component in PyAutoLens (e.g. light proiles, mass profiles, etc.), for
    example if they use a UniformPrior or GausssianPrior and the range of values sampled.

Limit:

    The limits between which a parameter may be sampled. For example, the axis_ratio of light and mass profiles has
    limits 0.0 -> 1.0 to prevent unphysical models.

Width:

    The width of the GaussianPrior used for each parameter if its priors are initialized via linking from a previous
    phase.


### Visualize ###

General:

    General visualization setting like the matplotlib backend and what features should be included on an image (e.g.
    the critical curves, origin, mask, etc.)

Plots:

    For a lens model analsys what figures should be output to hard-disk during the analysis (e.g. images of the data,
    results of a fit,  etc.).

Figures:

    Customize the matplotlib settings of how figures appear in PyAutoLens by default (e.g. their figsize, ticksize,
    colormap, etc.).

Subplots:

    Customize the matplotlib settings of how subplots appear in PyAutoLens by default (e.g. their figsize, ticksize,
    colormap, etc.).


### Non-Linear ###

    Customize the default non-linear optimizer settings used by PyAutoLens.


### Label ###

    The labels used for every model parameter on certain figures (e.g. the label for centres are y an x and for an
    axis ratio is q).

### Label Format ###

    The format of certain results output by PyAutoLens (e.g. the mass format is {:.4e}, meaning it is output as an
    exponential to 4 dp).

### Radial Minimum ###

    Mass profiles which use numerical integration to compute deflection angles can break for numerical values very near
    (0.0, 0.0). The values in radial minimum specify to what precision values of (0.0, 0.0) and adjusted to prevent this.