code: def exp_trans(base=None, **kwargs):
      
      # default to e
      if base is None:
          name = 'power_e'
          base = np.exp(1)
      else:
          name = 'power_{}'.format(base)
  
      # transform function
      def transform(x):
          return base ** x
  
      # inverse function
      def inverse(x):
          return np.log(x)/np.log(base)
  
      kwargs['base'] = base
      return trans_new(name, transform, inverse, **kwargs)
docs: Create a exponential transform class for *base*
  
      This is inverse of the log transform.
  
      Parameters
      ----------
      base : float
          Base of the logarithm
      kwargs : dict
          Keyword arguments passed onto
          :func:`trans_new`. Should not include
          the `transform` or `inverse`.
  
      Returns
      -------
      out : type
          Exponential transform class