class_docstr: Base class used for filling in the gaps in time series with simple methods.
  Methods from the SimpleGapFiller class can be used for comparison with more
  complex models in class ModelGapFiller
  
  Args:
      gap_value: value, which identify gap elements in array
class_docstr_tok: ["Base","class","used","for","filling","in","the","gaps","in","time","series","with","simple","methods",".","Methods","from","the","SimpleGapFiller","class","can","be","used","for","comparison","with","more","complex","models","in","class","ModelGapFiller","Args",":","gap_value",":","value",",","which","identify","gap","elements","in","array"]
docstr: Method allows parsing source array with gaps indexes
  
  Args:
      gap_list: array with indexes of gaps in array
  
  Returns:
      a list with separated gaps in continuous intervals
docstr_tok: ["Method","allows","parsing","source","array","with","gaps","indexes","Args",":","gap_list",":","array","with","indexes","of","gaps","in","array","Returns",":","a","list","with","separated","gaps","in","continuous","intervals"]
code: def _parse_gap_ids(self, gap_list: Union[List, np.ndarray]) -> list:
      """Method allows parsing source array with gaps indexes
  
      Args:
          gap_list: array with indexes of gaps in array
  
      Returns:
          a list with separated gaps in continuous intervals
      """
  
      new_gap_list = []
      local_gaps = []
      for index, gap in enumerate(gap_list):
          if index == 0:
              local_gaps.append(gap)
          else:
              prev_gap = gap_list[index - 1]
              if gap - prev_gap > 1:
                  # There is a "gap" between gaps
                  new_gap_list.append(local_gaps)
  
                  local_gaps = []
                  local_gaps.append(gap)
              else:
                  local_gaps.append(gap)
      new_gap_list.append(local_gaps)
  
      return new_gap_list
  
imports: from copy import deepcopy
  from typing import List, Union
  import numpy
  from golem.core.log import default_log
  from scipy import interpolate
  from fedot.core.data.data import InputData
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
label_desc: Use image node_id 5 for calling the SimpleGapFiller obj's underlying member method code with example usage: obj._parse_gap_ids(gap_list) and returns: new_gap_list