class_docstr: Beat evaluation class.
  
  Parameters
  ----------
  detections : str, list or numpy array
      Detected beats.
  annotations : str, list or numpy array
      Annotated ground truth beats.
  fmeasure_window : float, optional
      F-measure evaluation window [seconds]
  pscore_tolerance : float, optional
      P-Score tolerance [fraction of the median beat interval].
  cemgil_sigma : float, optional
      Sigma of Gaussian window for Cemgil accuracy.
  goto_threshold : float, optional
      Threshold for Goto error.
  goto_sigma : float, optional
      Sigma for Goto error.
  goto_mu : float, optional
      Mu for Goto error.
  continuity_phase_tolerance : float, optional
      Continuity phase tolerance.
  continuity_tempo_tolerance : float, optional
      Continuity tempo tolerance.
  information_gain_bins : int, optional
      Number of bins for for the information gain beat error histogram.
  offbeat : bool, optional
      Include offbeat variation.
  double : bool, optional
      Include double and half tempo variations (and offbeat thereof).
  triple : bool, optional
      Include triple and third tempo variations (and offbeats thereof).
  skip : float, optional
      Skip the first `skip` seconds for evaluation.
  downbeats : bool, optional
      Evaluate downbeats instead of beats.
  
  Notes
  -----
  The `offbeat`, `double`, and `triple` variations of the beat sequences are
  used only for AMLc/AMLt.
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code: def tostring(self, **kwargs):
      return tostring(self)
  
imports: from __future__ import absolute_import, division, print_function
  import warnings
  from functools import wraps
  import numpy
  from .None import MeanEvaluation, calc_absolute_errors, calc_errors, evaluation_io, find_closest_matches
  from .onsets import OnsetEvaluation
label_desc: Use image node_id 3 for calling the BeatEvaluation obj's underlying member method code with example usage: obj.tostring() and returns: tostring