class_docstr: Class for averaging chord evaluation scores, averaging piecewise (i.e.
  ignoring the lengths of the pieces). For a detailed description of the
  available metrics, refer to ChordEvaluation.
  
  Parameters
  ----------
  eval_objects : list
      Evaluation objects.
  name : str, optional
      Name to be displayed.
class_docstr_tok: ["Class","for","averaging","chord","evaluation","scores",",","averaging","piecewise","(","i.e",".","ignoring","the","lengths","of","the","pieces",")",".","For","a","detailed","description","of","the","available","metrics",",","refer","to","ChordEvaluation",".","Parameters","--","--","--","--","--","eval_objects",":","list","Evaluation","objects",".","name",":","str",",","optional","Name","to","be","displayed","."]
code: def root(self):
      return np.mean([e.root for e in self.eval_objects])
  
imports: import numpy
  from .None import evaluation_io, EvaluationMixin
  from ..io import load_chords
label_desc: Use image node_id 3 for calling the ChordMeanEvaluation obj's underlying member method code with example usage: obj.root() and returns: np