code: def sampleset(self, factor_step=0.05, **kwargs):
          
          w1, w2 = self.bounding_box(**kwargs)
          dw = factor_step * self.fwhm
  
          if self._n_models == 1:
              w = np.arange(w1, w2, dw)
          else:
              w = list(map(np.arange, w1, w2, dw))
  
          return np.asarray(w)
docs: Return ``x`` array that samples the feature.
  
          Parameters
          ----------
          factor_step : float
              Factor for sample step calculation. The step is calculated
              using ``factor_step * self.fwhm``.
  
          kwargs : dict
              Keyword(s) for ``bounding_box`` calculation.