code: def summary(self, variables=None, alpha=0.05, start=0, batches=100,
                  chain=None, roundto=3):
          
  
          # If no names provided, run them all
          if variables is None:
              variables = self._variables_to_tally
          else:
              variables = [
                  self.__dict__[
                      i] for i in variables if self.__dict__[
                          i] in self._variables_to_tally]
  
          # Loop over nodes
          for variable in variables:
              variable.summary(
                  alpha=alpha, start=start, batches=batches, chain=chain,
                  roundto=roundto)
docs: Generate a pretty-printed summary of the model's variables.
  
          :Parameters:
          alpha : float
            The alpha level for generating posterior intervals. Defaults to
            0.05.
  
          start : int
            The starting index from which to summarize (each) chain. Defaults
            to zero.
  
          batches : int
            Batch size for calculating standard deviation for non-independent
            samples. Defaults to 100.
  
          chain : int
            The index for which chain to summarize. Defaults to None (all
            chains).
  
          roundto : int
            The number of digits to round posterior statistics.
  
          quantiles : tuple or list
            The desired quantiles to be calculated. Defaults to (2.5, 25, 50, 75, 97.5).