class_docstr: A dict of dicts to store analyses
  
  Parameters
  ----------
  top_analysis: :class:`Analysis`
      The Analysis at the highest scale level containing all landmarks
      
  Notes
  -----
  The outer dict represents the scales and
  the inner dicts at scale level are indexed by the unique
  self-generated Analysis ids.
class_docstr_tok: ["A","dict","of","dicts","to","store","analyses","Parameters","--","--","--","--","--","top_analysis",":",":","class",":","`","Analysis","`","The","Analysis","at","the","highest","scale","level","containing","all","landmarks","Notes","--","--","-","The","outer","dict","represents","the","scales","and","the","inner","dicts","at","scale","level","are","indexed","by","the","unique","self-generated","Analysis","ids","."]
docstr: To used for comparing an older copy with the current analysis container
docstr_tok: ["To","used","for","comparing","an","older","copy","with","the","current","analysis","container"]
code: def __eq__(self, other):
      """To used for comparing an older copy with the current analysis container"""
      if not isinstance(other, AnalysisContainer):
          # don't attempt to compare against unrelated types
          return False
  
      if not other._scale_index == self._scale_index:
          return False
  
      for key, value in self._children:
          other_value = other._children[key]
          if not other_value == value:
              return False
  
      return True
  
file_path: nptsne/src/nptsne/hsne_analysis/analysis_model.py
imports: from ..libs._nptsne._hsne_analysis import EmbedderType, Analysis
  import numpy
label_desc: Use image node_id 2 for calling the AnalysisContainer obj's underlying member method code with example usage: obj.__eq__(other) and returns: True, False, False, False