code: def test_manspec_with_tsfreq_step(load_split_data):
      # Test that manual_selection works for with provided arguments
      # Should ignore feature scope and raise warning for second_of_minute,
      # since ts_freq = "M" is provided.
      # (dummies with frequency higher than ts_freq)
      pipe = DateTimeFeatures(
          ts_freq="M",
          feature_scope="comprehensive",
          manual_selection=["year", "second_of_minute"],
          keep_original_columns=True,
      )
      test_manspec_with_tsfreq = pipe.fit_transform(load_split_data)
      return test_manspec_with_tsfreq
  
imports: import numpy
  import pandas
  import pytest
  from pandas.testing import assert_frame_equal
  from sktime.datasets import load_airline, load_longley, load_PBS_dataset
  from sktime.split import temporal_train_test_split
  from sktime.tests.test_switch import run_test_for_class
  from sktime.transformations.series.date import DateTimeFeatures
  from sktime.utils._testing.hierarchical import _make_hierarchical
label_desc: Use image node_id 8 for calling a global function with example usage: test_manspec_with_tsfreq_step(load_split_data) and returns: test_manspec_with_tsfreq