class_docstr: Iterable/indexable class for time series data with context data
  Numpy arrays are sufficient time series data alone is needed
  
  Parameters
  ----------
  ts_data : array-like, shape (N, )
      time series data
  context_data : array-like (N, )
      contextual data
code: def __next__(self):
      if self.index == self.N:
          raise StopIteration
      self.index = self.index + 1
      return TS_Data(
          self.ts_data[self.index], self.context_data[self.index]
      )
  
file_path: seglearn/seglearn/base.py
imports: import numpy
label_desc: Use image node_id 5 for calling the TS_Data obj's underlying member method code with example usage: obj.__next__() and returns: TS_Data