code: def test_get_anomaly_df_from_outliers_small_data_size():
      """Tests `get_anomaly_df_from_outliers`."""
      value_col = "y"
      freq = "D"
      # Tests when outliers exist.
      # The outliers are to be identified and saved to `anomaly_df`.
      # This example contains less data
      ts = pd.date_range(
          start="2020-01-01", end="2020-05-01", freq=freq
      )
      y = list(range(len(ts)))
      # Let's overwrite the third value to be an outlier
      y[2] = 1000
  
      df = pd.DataFrame({TIME_COL: ts, value_col: y})
  
      expected_anomaly_df = pd.DataFrame(
          {
              START_TIME_COL: pd.to_datetime(["2020-01-03"]),
              END_TIME_COL: pd.to_datetime(["2020-01-03"]),
          }
      )
  
      anomaly_df = get_anomaly_df_from_outliers(
          df=df,
          time_col=TIME_COL,
          value_col=value_col,
          freq=freq,
          trim_percent=1.0,
      )
      assert_equal(anomaly_df, expected_anomaly_df)
  
      # Disables trimming by setting it to zero.
      # In this case, we do not expect an empty dataframe
      anomaly_df = get_anomaly_df_from_outliers(
          df=df,
          time_col=TIME_COL,
          value_col=value_col,
          freq=freq,
          trim_percent=0.0,
      )
      expected_anomaly_df = pd.DataFrame(
          columns=[START_TIME_COL, END_TIME_COL]
      )
      assert_equal(anomaly_df, expected_anomaly_df)
  
imports: import itertools
  import numpy
  import pandas
  import pytest
  from testfixtures import LogCapture
  from greykite.common.constants import ANOMALY_COL
  from greykite.common.constants import END_TIME_COL
  from greykite.common.constants import LOGGER_NAME
  from greykite.common.constants import START_TIME_COL
  from greykite.common.constants import TIME_COL
  from greykite.common.constants import TimeFeaturesEnum
  from greykite.common.testing_utils import assert_equal
  from greykite.detection.detector.ad_utils import add_new_params_to_records
  from greykite.detection.detector.ad_utils import get_anomaly_df
  from greykite.detection.detector.ad_utils import get_anomaly_df_from_outliers
  from greykite.detection.detector.ad_utils import get_canonical_anomaly_df
  from greykite.detection.detector.ad_utils import get_timestamp_ceil
  from greykite.detection.detector.ad_utils import get_timestamp_floor
  from greykite.detection.detector.ad_utils import optimize_df_with_constraints
  from greykite.detection.detector.ad_utils import partial_return
  from greykite.detection.detector.ad_utils import validate_volatility_features
  from greykite.detection.detector.ad_utils import vertical_concat_dfs
label_desc: Use image node_id 14 for calling a global function with example usage: test_get_anomaly_df_from_outliers_small_data_size() without return types