code: def test_flag_jumps_strict_with_both_cols_in_all_args(
      timeseries_dataframe,
  ):
      """
      Test provided strict behaves as expected
      (only col1 and col2 flagged).
      """
      df = timeseries_dataframe
      orig_cols = df.columns
  
      expected = np.zeros((10, 2), dtype=int)
      expected_cols = ["col1_jump_flag", "col2_jump_flag"]
      expected_df = pd.DataFrame(
          expected, columns=expected_cols, index=df.index
      )
  
      # Exercise
      df = df.flag_jumps(
          scale=dict(col1="absolute", col2="percentage"),
          direction=dict(col1="increasing", col2="any"),
          threshold=dict(col1=1, col2=2),
          strict=True,
      )
  
      # Verify
      assert list(df.columns) == list(orig_cols) + expected_cols
      assert df.filter(regex="flag").equals(expected_df)
  
imports: import numpy
  import pandas
  import pytest
  import janitor.timeseries
  from janitor.errors import JanitorError
  from janitor.timeseries import _flag_jumps_single_col
label_desc: Use image node_id 17 for calling a global function with example usage: test_flag_jumps_strict_with_both_cols_in_all_args(timeseries_dataframe) without return types