code: def test_fit_score(self):
      train_data, test_data = self.create_data()
      forecaster = TCNForecaster(
          past_seq_len=24,
          future_seq_len=5,
          input_feature_num=1,
          output_feature_num=1,
      )
      forecaster.fit(train_data, epochs=1)
      y_test_pred = forecaster.predict(test_data[0])
      y_test = test_data[1]
  
      # find anomaly using a manual set threshold
      td = ThresholdDetector()
      td.set_params(pattern_threshold=10, trend_threshold=(-3, 3))
      td.fit(y_test, y_test_pred)
      anomaly_scores = td.score()["anomaly score"]
      assert len(list(np.where(anomaly_scores > 0)[0])) == 0
      anomaly_indexes = td.anomaly_indexes()["anomaly index"]
      assert len(anomaly_indexes) == 0
  
file_path: BigDL/python/chronos/test/bigdl/chronos/detector/anomaly/test_th_detector.py
imports: import pytest
  import numpy
  import pandas
  from unittest import TestCase
  from bigdl.chronos.utils import LazyImport
  from bigdl.chronos.detector.anomaly import ThresholdDetector
  from ...None import op_torch
label_desc: Use image node_id 4 for calling the TestThresholdDetector obj's underlying member method code with example usage: obj.test_fit_score() without return types