code: def forecast_test(clf, X, y):
      yv = yvals(y)
      clf.fit(X, y)
      yp = clf.predict(X)
      ytr, yp2 = clf.transform_predict(X, y)
      assert np.all(np.isin(np.unique(ytr), yv))
      assert len(ytr) == len(yp2)
      assert np.all(yp == yp2)
      score = clf.score(X, y)
      assert 1.0 >= score >= 0.0
  
file_path: seglearn/seglearn/tests/test_pipe.py
imports: import numpy
  import pandas
  import pytest
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.linear_model import Ridge
  from sklearn.model_selection import cross_validate
  from sklearn.preprocessing import StandardScaler
  from seglearn.base import TS_Data
  from seglearn.pipe import Pype
  from seglearn.transform import FeatureRep, SegmentX, SegmentXY, SegmentXYForecast, PadTrunc
label_desc: Use image node_id 8 for calling a global function with example usage: forecast_test(clf, X, y) without return types