code: def generate_prior_hsgp(cov_name: str):
      """Generate a prior configuration for an HSGP term
  
      The 'prior' for the HSGP term refers to a dictionary of priors. This dictionary contains
      Prior instances for the parameters of the covariance function.
  
      Parameters
      ----------
      cov_name : str
          The name of a covariance function
  
      Returns
      -------
      dict[str, Prior]
          The priors for the parameters of the covariance function
      """
      config = HSGP_COV_PARAMS_DEFAULT_PRIORS[cov_name]
      priors = {}
      for param, dist in config.items():
          priors[param] = Prior(dist, **SETTINGS_DISTRIBUTIONS[dist])
      return priors
  
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 2 for calling a global function with example usage: generate_prior_hsgp(cov_name) and returns: priors