code: def test_normalize():
      length = 100
      days = pd.date_range(start="2017-01-01", periods=length)
      y = np.ones(length)
      y[1] = 0
      y[2] = 2
      y[3] = 3.3
      df = pd.DataFrame({"ds": days, "y": y})
      m = NeuralProphet(
          epochs=EPOCHS,
          batch_size=BATCH_SIZE,
          learning_rate=LR,
          normalize="soft",
      )
      df, _, _, _ = df_utils.prep_or_copy_df(df)
      # with config
      m.config_normalization.init_data_params(
          df,
          m.config_lagged_regressors,
          m.config_regressors,
          m.config_events,
      )
      _normalize(df=df, config_normalization=m.config_normalization)
      m.config_normalization.unknown_data_normalization = True
      _normalize(df=df, config_normalization=m.config_normalization)
      m.config_normalization.unknown_data_normalization = False
      # using config for utils
      df = df.drop("ID", axis=1)
      df_utils.normalize(df, m.config_normalization.global_data_params)
      df_utils.normalize(
          df, m.config_normalization.local_data_params["__df__"]
      )
  
      # with utils
      local_data_params, global_data_params = df_utils.init_data_params(
          df=df,
          normalize=m.config_normalization.normalize,
          config_lagged_regressors=m.config_lagged_regressors,
          config_regressors=m.config_regressors,
          config_events=m.config_events,
          global_normalization=m.config_normalization.global_normalization,
          global_time_normalization=m.config_normalization.global_time_normalization,
      )
      df_utils.normalize(df, global_data_params)
      df_utils.normalize(df, local_data_params["__df__"])
  
imports: import logging
  import os
  import pathlib
  import matplotlib.pyplot
  import numpy
  import pandas
  import pytest
  from torch.utils.data import DataLoader
  from neuralprophet import NeuralProphet, configure, df_utils, time_dataset
  from neuralprophet.data.process import _create_dataset, _handle_missing_data
  from neuralprophet.data.transform import _normalize
label_desc: Use image node_id 3 for calling a global function with example usage: test_normalize() without return types