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","."]
code: def __init__(self, top_analysis):
      self._container = {
          top_analysis.scale_id: {top_analysis.id: top_analysis}
      }
      self._children = {top_analysis.id: set()}
      self._scale_index = {top_analysis.id: top_analysis.scale_id}
      self._null_id = 0xFFFFFFFF
  
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 1 to create a new AnalysisContainer object  with example: obj = AnalysisContainer(top_analysis)