class_docstr: This implements wrapper for gensim lsa and tfidf analysis of text collection
code: def __init__(
      self,
      text_process,
      model,
      dictionary,
      tfidf,
      tfidf_index,
      lsa,
      lsa_index,
  ):
      self._text_process = text_process
      self._model = model
      self._dictionary = dictionary
      self._tfidf = tfidf
      self._tfidf_index = tfidf_index
      self._lsa = lsa
      self._lsa_index = lsa_index
  
file_path: sematch/sematch/semantic/analysis.py
imports: from gensim import corpora, models, similarities, matutils
label_desc: Use image node_id 1 to create a new TextAnalysis object  with example: obj = TextAnalysis(text_process, model, dictionary, tfidf, tfidf_index, lsa, lsa_index)