code: def from_config(cls, cp, section, variable_args):
          
          # we'll retrieve the setting for cyclic_domain directly
          additional_opts = {'cyclic_domain': cp.has_option_tag(section,
                                              'cyclic_domain', variable_args)}
          return bounded.bounded_from_config(cls, cp, section, variable_args,
                                             bounds_required=False,
                                             additional_opts=additional_opts)
docs: Returns a distribution based on a configuration file.
  
          The parameters for the distribution are retrieved from the section
          titled "[`section`-`variable_args`]" in the config file. By default,
          only the name of the distribution (`uniform_angle`) needs to be
          specified. This will results in a uniform prior on `[0, 2pi)`. To
          make the domain cyclic, add `cyclic_domain =`. To specify boundaries
          that are not `[0, 2pi)`, add `(min|max)-var` arguments, where `var`
          is the name of the variable.
  
          For example, this will initialize a variable called `theta` with a
          uniform distribution on `[0, 2pi)` without cyclic boundaries:
  
          .. code-block:: ini
  
              [{section}-theta]
              name = uniform_angle
  
          This will make the domain cyclic on `[0, 2pi)`:
  
          .. code-block:: ini
  
              [{section}-theta]
              name = uniform_angle
              cyclic_domain =
  
          Parameters
          ----------
          cp : pycbc.workflow.WorkflowConfigParser
              A parsed configuration file that contains the distribution
              options.
          section : str
              Name of the section in the configuration file.
          variable_args : str
              The names of the parameters for this distribution, separated by
              ``VARARGS_DELIM``. These must appear in the "tag" part
              of the section header.
  
          Returns
          -------
          UniformAngle
              A distribution instance from the pycbc.inference.prior module.