code: def _get_mask_byte1_variable_info() -> dict:
      shape = _shape_for_resolution(1000)
      data = np.zeros((shape[0], shape[1]), dtype=np.uint16)
      row_dim_name = "Cell_Along_Swath_1km:mod35"
      col_dim_name = "Cell_Across_Swath_1km:mod35"
      return {
          "MODIS_Cloud_Mask": {
              "data": data,
              "type": SDC.UINT16,
              "fill_value": 9999,
              "attrs": {
                  # dim_labels are just unique dimension names, may not match exactly with real world files
                  "dim_labels": [row_dim_name, col_dim_name],
                  "valid_range": (0, 4),
                  "scale_factor": 2,
                  "add_offset": -1,
              },
          },
          "MODIS_Simple_LandSea_Mask": {
              "data": data,
              "type": SDC.UINT16,
              "fill_value": 9999,
              "attrs": {
                  # dim_labels are just unique dimension names, may not match exactly with real world files
                  "dim_labels": [row_dim_name, col_dim_name],
                  "valid_range": (0, 4),
                  "scale_factor": 2,
                  "add_offset": -1,
              },
          },
          "MODIS_Snow_Ice_Flag": {
              "data": data,
              "type": SDC.UINT16,
              "fill_value": 9999,
              "attrs": {
                  # dim_labels are just unique dimension names, may not match exactly with real world files
                  "dim_labels": [row_dim_name, col_dim_name],
                  "valid_range": (0, 2),
                  "scale_factor": 2,
                  "add_offset": -1,
              },
          },
      }
  
imports: from __future__ import annotations
  from datetime import datetime, timedelta
  from typing import Optional
  import numpy
  import pytest
  from pyhdf.SD import SD, SDC
label_desc: Use image node_id 29 for calling a global function with example usage: _get_mask_byte1_variable_info() and returns: dict