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):
      """
      In this case, args aren't used, since this information is taken
      directly from the corpus categories.
  
      Returns
      -------
      np.array, scores
      """
      if self.tdf_ is None:
          raise Exception(
              "Use set_categories('category name', ['not category name', ...]) "
              + "to set the category of interest"
          )
  
      y_i = self.tdf_["cat"]
      y_j = self.tdf_["ncat"]
      n_i, n_j = y_i.sum(), y_j.sum()
      delta_i_j = np.log(
          (y_i + self.constant) / (self.constant + n_i - y_i)
      ) - np.log((y_j + self.constant) / (self.constant + n_j - y_j))
      return delta_i_j
  
file_path: scattertext/scattertext/termscoring/LogOddsRatio.py
imports: import numpy
  import pandas
  from scattertext.termscoring.CorpusBasedTermScorer import CorpusBasedTermScorer
label_desc: Use image node_id 2 for calling the LogOddsRatio obj's underlying member method code with example usage: obj.get_scores() and returns: delta_i_j