code: def cutout(vol, requested_bbox, steps, channel_slice=slice(None), parallel=1, 
    shared_memory_location=None, output_to_shared_memory=False):
    
    global fs_lock
  
    cloudpath_bbox = requested_bbox.expand_to_chunk_size(vol.underlying, offset=vol.voxel_offset)
    cloudpath_bbox = Bbox.clamp(cloudpath_bbox, vol.bounds)
    cloudpaths = list(chunknames(cloudpath_bbox, vol.bounds, vol.key, vol.underlying))
    shape = list(requested_bbox.size3()) + [ vol.num_channels ]
  
    handle = None
  
    if parallel == 1:
      if output_to_shared_memory:
        array_like, renderbuffer = shm.bbox2array(vol, requested_bbox, 
          location=shared_memory_location, lock=fs_lock)
        shm.track_mmap(array_like)
      else:
        renderbuffer = np.zeros(shape=shape, dtype=vol.dtype, order='F')
  
      def process(img3d, bbox):
        shade(renderbuffer, requested_bbox, img3d, bbox)
      download_multiple(vol, cloudpaths, fn=process)
    else:
      handle, renderbuffer = multi_process_cutout(vol, requested_bbox, cloudpaths, parallel, 
        shared_memory_location, output_to_shared_memory)
    
    renderbuffer = renderbuffer[ ::steps.x, ::steps.y, ::steps.z, channel_slice ]
    return VolumeCutout.from_volume(vol, renderbuffer, requested_bbox, handle=handle)
docs: Cutout a requested bounding box from storage and return it as a numpy array.