code: def _intersect_1d(breaks):
      """
      Internal utility to intersect chunks for 1d after preprocessing.
  
      >>> new = cumdims_label(((2, 3), (2, 2, 1)), 'n')
      >>> old = cumdims_label(((2, 2, 1), (5,)), 'o')
  
      >>> _intersect_1d(_breakpoints(old[0], new[0]))  # doctest: +NORMALIZE_WHITESPACE
      [[(0, slice(0, 2, None))],
       [(1, slice(0, 2, None)), (2, slice(0, 1, None))]]
      >>> _intersect_1d(_breakpoints(old[1], new[1]))  # doctest: +NORMALIZE_WHITESPACE
      [[(0, slice(0, 2, None))],
       [(0, slice(2, 4, None))],
       [(0, slice(4, 5, None))]]
  
      Parameters
      ----------
  
      breaks: list of tuples
          Each tuple is ('o', 8) or ('n', 8)
          These are pairs of 'o' old or new 'n'
          indicator with a corresponding cumulative sum,
          or breakpoint (a position along the chunking axis).
          The list of pairs is already ordered by breakpoint.
          Note that an 'o' pair always occurs BEFORE
          an 'n' pair if both share the same breakpoint.
      Uses 'o' and 'n' to make new tuples of slices for
      the new block crosswalk to old blocks.
      """
      # EXPLANATION:
      # We know each new chunk is obtained from the old chunks, but
      # from which ones and how? This function provides the answer.
      # On return, each new chunk is represented as a list of slices
      # of the old chunks. Therefore,  paired with each slice is the
      # index of the old chunk to which that slice refers.
      # NOTE: if any nonzero-size new chunks extend beyond the total
      #    span of the old chunks, then those new chunks are assumed
      #    to be obtained from an imaginary old chunk that extends
      #    from the end of that total span to infinity. The chunk-
      #    index of this imaginary chunk follows in consecutive order
      #    from the chunk-indices of the actual old chunks.
  
      # First, let us determine the index of the last old_chunk:
      o_pairs = [pair for pair in breaks if pair[0] == "o"]
      last_old_chunk_idx = len(o_pairs) - 2
      last_o_br = o_pairs[-1][1]  # end of range spanning all old chunks
  
      start = 0  # start of a slice of an old chunk
      last_end = 0
      old_idx = 0  # index of old chunk
      last_o_end = 0
      ret = []  # will hold the list of new chunks
      ret_next = (
          []
      )  # will hold the list of slices comprising one new chunk
      for idx in range(1, len(breaks)):  # Note start from the 2nd pair
          # the interval between any two consecutive breakpoints is a potential
          # new chunk:
          label, br = breaks[idx]
          last_label, last_br = breaks[idx - 1]
          if last_label == "n":
              # This always denotes the end of a new chunk or the start
              # of the next new chunk or both
              start = last_end
              if ret_next:
                  ret.append(ret_next)
                  ret_next = []
          else:
              start = 0
          end = br - last_br + start  # end of a slice of an old chunk
          last_end = end
          if br == last_br:
              # Here we have a zero-size interval between the previous and
              # current breakpoints. This should not result in a slice unless
              # this interval's end-points (`last_label` and `label`) are both
              # equal to 'n'
              if label == "o":
                  old_idx += 1
                  last_o_end = end
              if label == "n" and last_label == "n":
                  if br == last_o_br:
                      # zero-size new chunks located at the edge of the range
                      # spanning all the old chunks are assumed to come from the
                      # end of the last old chunk:
                      slc = slice(last_o_end, last_o_end)
                      ret_next.append((last_old_chunk_idx, slc))
                      continue
              else:
                  continue
          ret_next.append((old_idx, slice(start, end)))
          if label == "o":
              old_idx += 1
              start = 0
              last_o_end = end
  
      if ret_next:
          ret.append(ret_next)
  
      return ret
  
imports: from __future__ import annotations
  import heapq
  import math
  from functools import reduce
  from itertools import chain, count, product
  from operator import add, itemgetter, mul
  from warnings import warn
  import numpy
  import tlz
  from tlz import accumulate
  from dask import config
  from dask.array.chunk import getitem
  from dask.array.core import Array, concatenate3, normalize_chunks
  from dask.array.utils import validate_axis
  from dask.array.wrap import empty
  from dask.base import tokenize
  from dask.highlevelgraph import HighLevelGraph
  from dask.utils import parse_bytes
label_desc: Use image node_id 3 for calling a global function with example usage: _intersect_1d(breaks) and returns: ret