code: def get_default_prior(term_type, **kwargs):
      """Generate a Prior based on the default settings
  
      The following summarises default priors for each type of term:
  
      * intercept: Normal prior.
      * common: Normal prior.
      * intercept_flat: Uniform prior.
      * common_flat: Uniform prior.
      * group_specific: Normal prior where its sigma has a HalfNormal hyperprior.
      * group_specific_flat: Normal prior where its sigma has a HalfFlat hyperprior.
      * hsgp: The priors depend on the value passed to `kwargs["cov_func"]`.
          See `HSGP_COV_PARAMS_DEFAULT_PRIORS`.
  
      Parameters
      ----------
      term_type : str
          The type of the term for which the default prior is wanted.
  
      Raises
      ------
      ValueError
          If ``term_type`` is not within the values listed above.
  
      Returns
      -------
      prior: Prior
          The instance of Prior according to the ``term_type``.
      """
      if term_type in ["intercept", "common"]:
          prior = generate_prior("Normal")
      elif term_type in ["intercept_flat", "common_flat"]:
          prior = generate_prior("Flat")
      elif term_type == "group_specific":
          prior = generate_prior("Normal", sigma="HalfNormal")
      elif term_type == "group_specific_flat":
          prior = generate_prior("Normal", sigma="HalfFlat")
      elif term_type == "hsgp":
          prior = generate_prior_hsgp(kwargs["cov_func"])
      else:
          raise ValueError("Unrecognized term type.")
      return prior
  
file_path: bambi/bambi/defaults/utils.py
imports: from bambi.defaults.distributions import SETTINGS_DISTRIBUTIONS
  from bambi.defaults.hsgp import HSGP_COV_PARAMS_DEFAULT_PRIORS
  from bambi.families import Likelihood
  from bambi.priors import Prior
label_desc: Use image node_id 3 for calling a global function with example usage: get_default_prior(term_type) and returns: prior