code: def __get_scores_for_category(
      self, category, tdf, term_freqs, non_text, corpus
  ):
      if self.term_scorer is not None:
          if (
              inherits_from(self.term_scorer, "CorpusBasedTermScorer")
              and type(self.term_scorer) == ABCMeta
          ):
              scorer = self.term_scorer(
                  corpus, **self.term_scorer_kwargs
              )
          else:
              scorer = self.term_scorer
          if non_text:
              scorer = scorer.use_metadata()
          scorer = scorer.set_categories(category_name=category)
          return scorer.get_scores()
      return self.scorer_function(
          tdf[str(category)], term_freqs - tdf[str(category)]
      )
  
file_path: scattertext/scattertext/categorygrouping/rank_embedder.py
imports: from abc import ABCMeta
  from typing import Optional, Callable, Dict
  import numpy
  import pandas
  from scattertext.TermDocMatrix import TermDocMatrix
  from scattertext.termscoring.RankDifference import RankDifference
  from scattertext.termscoring.CorpusBasedTermScorer import CorpusBasedTermScorer
  from scattertext.categorygrouping.characteristic_embedder_base import CategoryEmbedderABC
  from scattertext.util import inherits_from
label_desc: Use image node_id 3 for calling the RankEmbedder obj's underlying member method code with example usage: obj.__get_scores_for_category(category, tdf, term_freqs, non_text, corpus) and returns: self, scorer