class_docstr: Base class for interfacing prophet and neuralprophet.
class_docstr_tok: ["Base","class","for","interfacing","prophet","and","neuralprophet","."]
docstr: Check arguments for changepoints and assign related arguments.
  
  Returns
  -------
  self
docstr_tok: ["Check","arguments","for","changepoints","and","assign","related","arguments",".","Returns","--","--","--","-","self"]
code: def _check_changepoints(self):
      """Check arguments for changepoints and assign related arguments.
  
      Returns
      -------
      self
      """
      if self.changepoints is not None:
          self.changepoints = pd.Series(
              pd.to_datetime(self.changepoints), name="ds"
          )
          self.n_changepoints = len(self.changepoints)
          self.specified_changepoints = True
      else:
          self.specified_changepoints = False
      return self
  
imports: import os
  import pandas
  from sktime.forecasting.base import BaseForecaster
label_desc: Use image node_id 10 for calling the _ProphetAdapter obj's underlying member method code with example usage: obj._check_changepoints() and returns: self