class_docstr: Simple Maths from Kilgariff (2009).
  
  
  Stephanie Evert. 2023. Measuring Keyness. https://osf.io/x8z9n.
  
  Adam Kilgariff. 2009. Simple Maths for Keywords. Proc. Corpus Linguistics.
  https://www.semanticscholar.org/paper/Simple-Maths-for-Keywords-Kilgarriff/69bd0a8a964e9b3b0b4394fe0d9d602d6a5a0453
docstr: In this case, args aren't used, since this information is taken
  directly from the corpus categories.
  
  Returns
  -------
  np.array, scores
docstr_tok: ["In","this","case",",","args","are","n't","used",",","since","this","information","is","taken","directly","from","the","corpus","categories",".","Returns","--","--","--","-","np.array",",","scores"]
code: def get_scores(self, *args) -> pd.Series:
      """
      In this case, args aren't used, since this information is taken
      directly from the corpus categories.
  
      Returns
      -------
      np.array, scores
      """
      cat_X, ncat_X = self._get_cat_and_ncat(self._get_X())
      N1 = self._get_cat_size()
      N2 = self._get_ncat_size()
      if len(args) == 0:
          f1 = cat_X.sum(axis=0).A1
          f2 = ncat_X.sum(axis=0).A1
      else:
          f1, f2 = self.__get_f1_f2_from_args(args)
  
      p1 = f1 / N1
      p2 = f2 / N2
      res = (self.coef_ * p1 + self.lambda_) / (
          self.coef_ * p2 + self.lambda_
      )
      if self.log_:
          print("LOG")
          res = np.log(res) / np.log(2)
      return pd.Series(res, index=self._get_terms())
  
imports: import numpy
  import pandas
  from scattertext.termscoring.CorpusBasedTermScorer import CorpusBasedTermScorer
label_desc: Use image node_id 2 for calling the SimpleMaths obj's underlying member method code with example usage: obj.get_scores() and returns: pd