code: def __init__(self, *args, **kwargs):
      super().__init__(*args, **kwargs)
  
      self.csv_name = join(rootdir, "data", "example.csv")
      data = csv_to_time_series(self.csv_name, timestamp_unit="ms")
      self.data = TemporalResample("15min")(
          data.univariates[data.names[0]].to_ts()
      )
      self.labels = data.univariates[data.names[1]].to_ts()
      logger.info(f"Data looks like:\n{self.data[:5]}")
  
      # Test Prophet
      self.test_len = math.ceil(len(self.data) / 5)
      self.vals_train = self.data[: -self.test_len]
      self.vals_test = self.data[-self.test_len :]
  
imports: import logging
  import math
  import os
  from os.path import abspath, dirname, join
  import sys
  import unittest
  from merlion.transform.base import Identity
  from merlion.transform.moving_average import DifferenceTransform
  from merlion.transform.normalize import BoxCoxTransform
  from merlion.transform.resample import TemporalResample
  from merlion.models.anomaly.forecast_based.prophet import ProphetDetector, ProphetDetectorConfig
  from merlion.models.forecast.trees import LGBMForecaster, LGBMForecasterConfig
  from merlion.plot import plot_anoms, plot_anoms_plotly
  from merlion.utils.data_io import csv_to_time_series
label_desc: Use image node_id 1 to create a new TestPlot object from inherited base classes: unittest with example: obj = TestPlot()