code: def coverage_fraction(y, y_low, y_high):
      return np.mean(np.logical_and(y >= y_low, y <= y_high))
  
file_path: scikit-learn/examples/ensemble/plot_gradient_boosting_quantile.py
imports: import numpy
  from sklearn.model_selection import train_test_split
  from sklearn.ensemble import GradientBoostingRegressor
  from sklearn.metrics import mean_pinball_loss, mean_squared_error
  import matplotlib.pyplot
  import pandas
  from sklearn.experimental import enable_halving_search_cv
  from sklearn.model_selection import HalvingRandomSearchCV
  from sklearn.metrics import make_scorer
  from pprint import pprint
  from sklearn.base import clone
label_desc: Use image node_id 3 for calling a global function with example usage: coverage_fraction(y, y_low, y_high) and returns: np