code: def test_pred_errors_against_linear():
      """Check prediction performance on airline dataset.
  
      For a small value of changepoint_prior_scale like 0.001 the
      ProphetPiecewiseLinearTrendForecaster must return a single straight trendline.
  
      Raises
      ------
      AssertionError - if the trend forecast is not compatible with a linear trend.
      """
      y = load_airline().to_timestamp(freq="M")
      fh = ForecastingHorizon(y.index, is_relative=False)
  
      pwl = ProphetPiecewiseLinearTrendForecaster(
          changepoint_prior_scale=0.001
      )
      y_pred_pwl = pwl.fit(y).predict(fh)
  
      linear = PolynomialTrendForecaster(degree=1)
      y_pred_linear = linear.fit(y).predict(fh)
  
      np.testing.assert_allclose(y_pred_pwl, y_pred_linear, rtol=0.04)
  
file_path: sktime/sktime/forecasting/trend/tests/test_pwl_trend.py
imports: import numpy
  import pandas
  import pytest
  from sktime.datasets import load_airline
  from sktime.forecasting.base import ForecastingHorizon
  from sktime.forecasting.trend import PolynomialTrendForecaster, ProphetPiecewiseLinearTrendForecaster
  from sktime.split import temporal_train_test_split
  from sktime.tests.test_switch import run_test_for_class
label_desc: Use image node_id 2 for calling a global function with example usage: test_pred_errors_against_linear() without return types