code: def reg_n_correct(prediction, y, significance=None):
      """Calculates the number of correct predictions made by a conformal
      regression model.
      """
      if significance is not None:
          idx = int(significance * 100 - 1)
          prediction = prediction[:, :, idx]
  
      low = y >= prediction[:, 0]
      high = y <= prediction[:, 1]
      correct = low * high
  
      return y[correct].size
  
file_path: lightwood/lightwood/analysis/nc/metrics.py
imports: import numpy
label_desc: Use image node_id 1 for calling a global function with example usage: reg_n_correct(prediction, y, significance) and returns: y