code: def generic_test_adjust_anomalous_data(
      value_col, adj_df_info, adj_values
  ):
      """Generic test for the results of any given scenario"""
      augmented_df = adj_df_info["augmented_df"]
      adjusted_df = adj_df_info["adjusted_df"]
      assert list(adjusted_df.columns) == ["ts", "y", "z"]
      assert list(augmented_df.columns) == [
          "ts",
          "y",
          "z",
          ANOMALY_COL,
          f"adjusted_{value_col}",
      ]
      assert_equal(
          adjusted_df[value_col],
          augmented_df[f"adjusted_{value_col}"],
          check_names=False,
      )
      assert_equal(
          augmented_df[: len(adj_values)][f"adjusted_{value_col}"],
          adj_values,
          check_names=False,
      )
  
imports: import datetime
  import warnings
  import numpy
  import pandas
  from greykite.common.constants import ADJUSTMENT_DELTA_COL
  from greykite.common.constants import ANOMALY_COL
  from greykite.common.constants import END_TIME_COL
  from greykite.common.constants import EVENT_DF_LABEL_COL
  from greykite.common.constants import METRIC_COL
  from greykite.common.constants import START_TIME_COL
  from greykite.common.constants import TIME_COL
  from greykite.common.constants import VALUE_COL
  from greykite.common.constants import TimeFeaturesEnum
  from greykite.common.features.timeseries_features import add_daily_events
  from greykite.common.features.timeseries_features import build_time_features_df
  from greykite.common.features.timeseries_features import fourier_series_multi_fcn
  from greykite.common.features.timeseries_features import get_default_origin_for_time_vars
  from greykite.common.features.timeseries_features import get_fourier_col_name
  from greykite.common.features.timeseries_features import get_holidays
  from greykite.common.python_utils import assert_equal
label_desc: Use image node_id 8 for calling a global function with example usage: generic_test_adjust_anomalous_data(value_col, adj_df_info, adj_values) without return types