class_docstr: Scale prior distributions parameters.
class_docstr_tok: ["Scale","prior","distributions","parameters","."]
code: def scale_threshold(self):
      if isinstance(self.model.family, Cumulative):
          threshold = self.model.components["threshold"]
          if (
              isinstance(threshold, ConstantComponent)
              and threshold.prior.auto_scale
          ):
              response_level_n = len(
                  np.unique(self.response_component.response_term.data)
              )
              mu = np.round(
                  np.linspace(-2, 2, num=response_level_n - 1), 2
              )
              threshold.prior = Prior(
                  "Normal",
                  mu=mu,
                  sigma=1,
                  transform=pm.distributions.transforms.ordered,
              )
      elif isinstance(self.model.family, StoppingRatio):
          threshold = self.model.components["threshold"]
          if (
              isinstance(threshold, ConstantComponent)
              and threshold.prior.auto_scale
          ):
              response_level_n = len(
                  np.unique(self.response_component.response_term.data)
              )
              mu = np.zeros(response_level_n - 1)
              threshold.prior = Prior("Normal", mu=mu, sigma=1)
  
file_path: bambi/bambi/priors/scaler.py
imports: import numpy
  import pymc
  from bambi.families.univariate import Cumulative, Gaussian, StoppingRatio, StudentT, VonMises
  from bambi.model_components import ConstantComponent
  from bambi.priors.prior import Prior
label_desc: Use image node_id 8 for calling the PriorScaler obj's underlying member method code with example usage: obj.scale_threshold() without return types