code: def write_csv(
          self, filename, variables=None, alpha=0.05, start=0, batches=100,
              chain=None, quantiles=(2.5, 25, 50, 75, 97.5)):
          
  
          # Append 'csv' suffix if there is no suffix on the filename
          if filename.find('.') == -1:
              filename += '.csv'
  
          outfile = open(filename, 'w')
  
          # Write header to file
          header = 'Parameter, Mean, SD, MC Error, Lower 95% HPD, Upper 95% HPD, '
          header += ', '.join(['q%s' % i for i in quantiles])
          outfile.write(header + '\n')
  
          stats = self.stats(
              variables=variables,
              alpha=alpha,
              start=start,
              batches=batches,
              chain=chain,
              quantiles=quantiles)
  
          if variables is None:
              variables = sorted(stats.keys())
  
          buffer = str()
          for param in variables:
  
              values = stats[param]
  
              try:
                  # Multivariate node
                  shape = values['mean'].shape
                  indices = list(itertools.product(*[range(i) for i in shape]))
  
                  for i in indices:
                      buffer += self._csv_str(param, values, quantiles, i)
  
              except AttributeError:
                  # Scalar node
                  buffer += self._csv_str(param, values, quantiles)
  
          outfile.write(buffer)
  
          outfile.close()
docs: Save summary statistics to a csv table.
  
          :Parameters:
  
          filename : string
            Filename to save output.
  
          variables : iterable
            List or array of variables for which statistics are to be
            generated. If it is not specified, all the tallied variables
            are summarized.
  
          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).