code: def test_lev_predict_intervals():
      model = pf.SEGARCH(data=data, q=2, p=2)
      model.add_leverage()
      x = model.fit()
      predictions = model.predict(h=10, intervals=True)
      assert np.all(
          predictions["99% Prediction Interval"].values + 0.000001
          >= predictions["95% Prediction Interval"].values
      )
      assert np.all(
          predictions["95% Prediction Interval"].values + 0.000001
          >= predictions["5% Prediction Interval"].values
      )
      assert np.all(
          predictions["5% Prediction Interval"].values + 0.000001
          >= predictions["1% Prediction Interval"].values
      )
  
imports: import numpy
  import pyflux
  import pandas
  from pandas.io.data import DataReader
  from datetime import datetime
label_desc: Use image node_id 39 for calling a global function with example usage: test_lev_predict_intervals() without return types