code: def __init__(self, *args, **kwargs):
      super().__init__(*args, **kwargs)
  
      np.random.seed(1234)
      self.data = TimeSeriesGenerator(
          f=lambda x: np.sin(x * 0.2) + 0.5 * np.sin(x * 0.05),
          n=30000,
          x0=2,
          step=1.5,
          tdelta="55min",
      ).generate()
      logger.info(f"Data looks like:\n{self.data[:5]}")
  
      self.test_len = 4500
      self.vals_train = self.data[: -self.test_len]
      self.vals_test = self.data[-self.test_len :]
  
      self.model = DynamicBaseline(
          DynamicBaselineConfig(
              train_window="15d",
              wind_sz="1h",
              trends=["daily", "weekly"],
          )
      )
  
      logger.info("Training model...\n")
      self.model.train(self.vals_train)
  
imports: from functools import reduce
  import logging
  import os
  from os.path import abspath, dirname, join
  import sys
  import unittest
  import numpy
  import pandas
  from merlion.models.anomaly.dbl import DynamicBaseline, DynamicBaselineConfig, Trend
  from merlion.utils.ts_generator import GeneratorConcatenator, TimeSeriesGenerator
  from merlion.utils.resample import to_pd_datetime
label_desc: Use image node_id 1 to create a new TestDynamicBaseline object from inherited base classes: unittest with example: obj = TestDynamicBaseline()