class_docstr: Evaluation class for measuring Precision, Recall and F-measure of notes.
  
  Parameters
  ----------
  detections : str, list or numpy array
      Detected notes.
  annotations : str, list or numpy array
      Annotated ground truth notes.
  window : float, optional
      F-measure evaluation window [seconds]
  delay : float, optional
      Delay the detections `delay` seconds for evaluation.
docstr: Standard deviation of the errors.
docstr_tok: ["Standard","deviation","of","the","errors","."]
code: def std_error(self):
      """Standard deviation of the errors."""
      warnings.warn(
          "std_error is given for all notes, this will change!"
      )
      if len(self.errors) == 0:
          return np.nan
      return np.std(self.errors[:, 0])
  
imports: from __future__ import absolute_import, division, print_function
  import warnings
  import numpy
  from .None import evaluation_io, MultiClassEvaluation, SumEvaluation, MeanEvaluation
  from .onsets import onset_evaluation, OnsetEvaluation
  from ..io import load_notes
label_desc: Use image node_id 3 for calling the NoteEvaluation obj's underlying member method code with example usage: obj.std_error() and returns: np, np