code: def predict(self, x, *args, **kwargs):
          
          if not self.model:
              raise Exception('Not trained. Train first')
  
          points = self._dimensionality_check(x, ext='points')
  
          return self.execute(points, *args, **kwargs)[0]
docs: Parameters
          ----------
          x: ndarray
              array of Points, (x, y) pairs of shape (N, 2) for 2d kriging
              array of Points, (x, y, z) pairs of shape (N, 3) for 3d kriging
  
          Returns
          -------
          Prediction array