code: def y_clean():
      """Constructs a clean vector of random numbers, used in outlier removal tests."""
      sampler = np.random.default_rng(1317)
      # Defines two clean vectors, one for `fit` and one for `detect`.
      y_clean = np.arange(0, 998)
      # Add small noise
      y_clean = y_clean + sampler.normal(
          loc=0.0, scale=1.0, size=len(y_clean)
      )
  
      return y_clean
  
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 1 for calling a global function with example usage: y_clean() and returns: y_clean