code: def test_minmax_normalizer(self):
      data = [
          [-100.0, -5.0, 0.0, 5.0, 100.0],
          [-1000.0, -50.0, 0.0, 50.0, 1000.0],
          [-500.0, -405.0, -400.0, -395.0, -300.0],
          [300.0, 395.0, 400.0, 405.0, 500.0],
          [0.0, 1e3, 1e6, 1e9, 1e12],
      ]
      normalizer = MinMaxNormalizer()
      normalizer.prepare(data)
      reconstructed = normalizer.decode(normalizer.encode(data))
      self.assertTrue(np.allclose(data, reconstructed, atol=0.1))
  
file_path: lightwood/tests/unit_tests/encoder/time_series/test_timeseries_rnn.py
imports: import unittest
  import numpy
  import torch
  from lightwood.encoder.time_series.rnn import TimeSeriesEncoder
  from lightwood.encoder.helpers import MinMaxNormalizer, CatNormalizer
  import pandas
label_desc: Use image node_id 1 for calling the TestRnnEncoder obj's underlying member method code with example usage: obj.test_minmax_normalizer() without return types