class_docstr: Discrete Wavelet Transform Transformer.
  
  Performs the Haar wavelet transformation on a time series.
  
  Parameters
  ----------
  num_levels : int, number of levels to perform the Haar wavelet
               transformation.
class_docstr_tok: ["Discrete","Wavelet","Transform","Transformer",".","Performs","the","Haar","wavelet","transformation","on","a","time","series",".","Parameters","--","--","--","--","--","num_levels",":","int",",","number","of","levels","to","perform","the","Haar","wavelet","transformation","."]
code: def __init__(self, num_levels=3):
      self.num_levels = num_levels
      super().__init__()
  
file_path: sktime/sktime/transformations/panel/dwt.py
imports: import math
  import numpy
  import pandas
  from sktime.datatypes import convert
  from sktime.transformations.base import BaseTransformer
label_desc: Use image node_id 1 to create a new DWTTransformer object from inherited base classes: BaseTransformer with example: obj = DWTTransformer(num_levels)