class_docstr: Cut Operator
  
  Parameters
  ----------
  feature : Expression
      feature instance
  l : int
      l > 0, delete the first l elements of feature (default is None, which means 0)
  r : int
      r < 0, delete the last -r elements of feature (default is None, which means 0)
  Returns
  ----------
  feature:
      A series with the first l and last -r elements deleted from the feature.
      Note: It is deleted from the raw data, not the sliced data
class_docstr_tok: ["Cut","Operator","Parameters","--","--","--","--","--","feature",":","Expression","feature","instance","l",":","int","l",">","0",",","delete","the","first","l","elements","of","feature","(","default","is","None",",","which","means","0",")","r",":","int","r","<","0",",","delete","the","last","-r","elements","of","feature","(","default","is","None",",","which","means","0",")","Returns","--","--","--","--","--","feature",":","A","series","with","the","first","l","and","last","-r","elements","deleted","from","the","feature",".","Note",":","It","is","deleted","from","the","raw","data",",","not","the","sliced","data"]
code: def __init__(self, feature, l=None, r=None):
      self.l = l
      self.r = r
      if (self.l is not None and self.l <= 0) or (
          self.r is not None and self.r >= 0
      ):
          raise ValueError("Cut operator l should > 0 and r should < 0")
  
      super(Cut, self).__init__(feature)
  
imports: import numpy
  import pandas
  import importlib
  from qlib.data.ops import ElemOperator, PairOperator
  from qlib.config import C
  from qlib.data.cache import H
  from qlib.data.data import Cal
  from qlib.contrib.ops.high_freq import get_calendar_day
label_desc: Use image node_id 1 to create a new Cut object from inherited base classes: ElemOperator with example: obj = Cut(feature, l, r)