code: def test_02_02_shape_sparse_implicit(self):
      r = numpy.random.RandomState()
      r.seed(102)
      ijv = numpy.core.records.fromarrays(
          [r.randint(0, 10, size=20) for _ in range(3)],
          [
              (
                  cellprofiler_core.utilities.hdf5_dict.HDF5ObjectSet.AXIS_Y,
                  numpy.uint32,
                  1,
              ),
              (
                  cellprofiler_core.utilities.hdf5_dict.HDF5ObjectSet.AXIS_X,
                  numpy.uint32,
                  1,
              ),
              (
                  cellprofiler_core.utilities.hdf5_dict.HDF5ObjectSet.AXIS_LABELS,
                  numpy.uint32,
                  1,
              ),
          ],
      )
      ijv[
          cellprofiler_core.utilities.hdf5_dict.HDF5ObjectSet.AXIS_X
      ] = 11
      ijv[
          cellprofiler_core.utilities.hdf5_dict.HDF5ObjectSet.AXIS_Y
      ] = 31
      shape = (1, 1, 1, 33, 13)
      s = cellprofiler_core.object.Segmentation(sparse=ijv)
      assert not s.has_shape()
      assert tuple(s.shape) == shape
  
file_path: CellProfiler/tests/core/object/test_segmentation.py
imports: import numpy
  import numpy.testing
  import cellprofiler_core.image
  import cellprofiler_core.object
  import cellprofiler_core.utilities.hdf5_dict
label_desc: Use image node_id 5 for calling the TestSegmentation obj's underlying member method code with example usage: obj.test_02_02_shape_sparse_implicit() without return types