code: def __init__(
      self,
      metric,
      method,
      value=None,
      curve_x=None,
      curve_y=None,
      curve_y_std=None,
      value_sign=None,
  ):
      self.metric = metric
      self.method = method
      self.value = value
      self.curve_x = curve_x
      self.curve_y = curve_y
      self.curve_y_std = curve_y_std
      self.value_sign = value_sign
      if self.value_sign is None and self.metric in sign_defaults:
          self.value_sign = sign_defaults[self.metric]
      if self.value is None:
          self.value = sklearn.metrics.auc(
              curve_x, (np.array(curve_y) - curve_y[0])
          )
  
imports: import numpy
  import sklearn
label_desc: Use image node_id 1 to create a new BenchmarkResult object  with example: obj = BenchmarkResult(metric, method, value, curve_x, curve_y, curve_y_std, value_sign)