class_docstr: Abstract base class for windows.
  
  Each subclass must implement a __call__ method that returns a list of lists of
  2-tuples. Each 2-tuple specifies the start and end of each window.
  
  These windows are grouped into a list that will (usually) cover the full time
  series. These lists are grouped into another list for situations where we consider
  windows of multiple scales.
docstr: Return the total number of windows in the set.
  
  Parameters
  ----------
  length: int, The length of the input path.
  
  Returns
  -------
  int: The number of windows.
docstr_tok: ["Return","the","total","number","of","windows","in","the","set",".","Parameters","--","--","--","--","--","length",":","int",",","The","length","of","the","input","path",".","Returns","--","--","--","-","int",":","The","number","of","windows","."]
code: def num_windows(self, length):
      """Return the total number of windows in the set.
  
      Parameters
      ----------
      length: int, The length of the input path.
  
      Returns
      -------
      int: The number of windows.
      """
      return sum([len(w) for w in self(length)])
  
imports: import collections
  import numpy
label_desc: Use image node_id 1 for calling the _Window obj's underlying member method code with example usage: obj.num_windows(length) and returns: sum