code: def test_BuildTimeseriesFeaturesTransformer_1():
      """Checks if the transformer class returns same output as build_time_features_df"""
      date_list = pd.date_range(
          start=datetime(2019, 1, 1), periods=100, freq="H"
      ).tolist()
      df = pd.DataFrame({"ts": date_list})
  
      timeseries_transform = BuildTimeseriesFeaturesTransformer(
          time_col="ts"
      )
      result = timeseries_transform.fit_transform(df)
      features_ts = build_time_features_df(
          dt=df["ts"], conti_year_origin=2019
      )
      expected = pd.concat([df, features_ts], axis=1)
      assert result.equals(expected)
  
file_path: greykite/greykite/tests/sklearn/transform/test_build_timeseries_features_transformer.py
imports: from datetime import datetime
  import pandas
  import pytest
  from sklearn.exceptions import NotFittedError
  from greykite.common.constants import VALUE_COL
  from greykite.common.features.timeseries_features import build_time_features_df
  from greykite.sklearn.transform.build_timeseries_features_transformer import BuildTimeseriesFeaturesTransformer
label_desc: Use image node_id 1 for calling a global function with example usage: test_BuildTimeseriesFeaturesTransformer_1() without return types