code: def _robust_scaler_unscale_timeseries_numpy(
      data, scaler, scaler_index
  ):
      data_unscale = np.zeros(data.shape)
      feature_counter = 0
      for i in scaler_index:
          value_center = (
              0 if scaler.center_ is None else scaler.center_[i]
          )
          value_scale = 1 if scaler.scale_ is None else scaler.scale_[i]
          data_unscale[:, :, feature_counter] = (
              data[:, :, feature_counter] * value_scale + value_center
          )
          feature_counter += 1
      return data_unscale
  
file_path: BigDL/python/chronos/src/bigdl/chronos/data/utils/scale.py
imports: import numpy
  import pandas
  from sklearn.preprocessing import StandardScaler, MaxAbsScaler, MinMaxScaler, RobustScaler
label_desc: Use image node_id 4 for calling a global function with example usage: _robust_scaler_unscale_timeseries_numpy(data, scaler, scaler_index) and returns: data_unscale