class_docstr: TruncatedNormal Distribution
  ----
  This class contains methods relating to the truncated normal distribution for time series.
docstr: PDF for Truncated Normal prior
  
  Parameters
  ----------
  mu : float
      Latent variable for which the prior is being formed over
  
  Returns
  ----------
  - p(mu)
code: def pdf(self, mu):
      """
      PDF for Truncated Normal prior
  
      Parameters
      ----------
      mu : float
          Latent variable for which the prior is being formed over
  
      Returns
      ----------
      - p(mu)
      """
      if self.transform is not None:
          mu = self.transform(mu)
      if mu < self.lower and self.lower is not None:
          return 0.0
      elif mu > self.upper and self.upper is not None:
          return 0.0
      else:
          return (1 / float(self.sigma0)) * np.exp(
              -(0.5 * (mu - self.mu0) ** 2) / float(self.sigma0**2)
          )
  
file_path: pyflux/pyflux/families/truncated_normal.py
imports: import numpy
  import scipy.stats
  import scipy.special
  from .family import Family
label_desc: Use image node_id 3 for calling the TruncatedNormal obj's underlying member method code with example usage: obj.pdf(mu) and returns: int, int, unknown