code: def create_data(self):
      num_train_samples = 1000
      num_test_samples = 400
      input_time_steps = 24
      input_feature_dim = 1
      output_time_steps = 5
      output_feature_dim = 1
  
      def get_x_y(num_samples):
          x = np.random.rand(
              num_samples, input_time_steps, input_feature_dim
          ).astype(np.float32)
          y = x[:, -output_time_steps:, :] * 2 + np.random.rand(
              num_samples, output_time_steps, output_feature_dim
          ).astype(np.float32)
          return x, y
  
      train_data = get_x_y(num_train_samples)
      test_data = get_x_y(num_test_samples)
  
      return train_data, test_data
  
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 3 for calling the TestThresholdDetector obj's underlying member method code with example usage: obj.create_data() and returns: train_data,  test_data, x,  y