code: def test_pred_with_explicit_changepoints():
      """Check functionality with explicit changepoints.
  
      When changepoints are passed to the ProphetPiecewiseLinearTrendForecaster
      the prediction has to be different then the automatic detection because the
      changepoints are forcefully added.
  
      Raises
      ------
      AssertionError - if adding a changepoint has no effect on the trend prediction.
      """
      y = load_airline().to_timestamp(freq="M")
      y_train, y_test = temporal_train_test_split(y)
  
      fh = ForecastingHorizon(y_test.index, is_relative=False)
      a = ProphetPiecewiseLinearTrendForecaster(
          changepoints=["1953-05-31"]
      )
      b = ProphetPiecewiseLinearTrendForecaster()
  
      slope_a = a.fit(y_train).predict(fh).diff().mean()
      slope_b = b.fit(y_train).predict(fh).diff().mean()
  
      assert not np.allclose(slope_a, slope_b, rtol=0.1)
  
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 3 for calling a global function with example usage: test_pred_with_explicit_changepoints() without return types