code: def _maxabs_scaler_unscale_timeseries_numpy(
      data, scaler, scaler_index
  ):
      data_unscale = np.zeros(data.shape)
      feature_counter = 0
      for i in scaler_index:
          value_max_abs = scaler.max_abs_[i]
          data_unscale[:, :, feature_counter] = (
              data[:, :, feature_counter] * value_max_abs
          )
          feature_counter += 1
      return data_unscale
  
file_path: analytics-zoo/pyzoo/zoo/chronos/data/utils/scale.py
imports: import numpy
  import pandas
  from sklearn.preprocessing import StandardScaler, MaxAbsScaler, MinMaxScaler, RobustScaler
label_desc: Use image node_id 2 for calling a global function with example usage: _maxabs_scaler_unscale_timeseries_numpy(data, scaler, scaler_index) and returns: data_unscale