docstr: Test conversion of sparse to 2D dense with overlapping labels
  
  dense output: label=2, c=1,t=1,z=1,y=3,x=2
  
      1 0
      1 0
      0 0
      ---
      0 0
      2 2
      0 0
docstr_tok: ["Test","conversion","of","sparse","to","2D","dense","with","overlapping","labels","dense","output",":","label=2",",","c=1",",","t=1",",","z=1",",","y=3",",","x=2","1","0","1","0","0","0","--","-","0","0","2","2","0","0"]
code: def test_02_03_sparse_to_2d_dense_overlap(self):
      """
      Test conversion of sparse to 2D dense with overlapping labels
  
      dense output: label=2, c=1,t=1,z=1,y=3,x=2
  
          1 0
          1 0
          0 0
          ---
          0 0
          2 2
          0 0
      """
      sparse = np.array(
          [(0, 0, 1), (1, 0, 1), (1, 0, 2), (1, 1, 2)],
          dtype=[
              (SPARSE_FIELD.y.value, "<u2"),
              (SPARSE_FIELD.x.value, "<u2"),
              (SPARSE_FIELD.label.value, "u1"),
          ],
      )
  
      dense_plain, dpi = lib_seg.convert_sparse_to_dense(sparse)
      dense_shaped, dsi = lib_seg.convert_sparse_to_dense(
          sparse, dense_shape=(1, 1, 1, 3, 2)
      )
  
      # + 1 padding
      dense_plain_expected = np.array(
          [[1, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 2, 2, 0, 0, 0, 0]],
          np.uint8,
      ).reshape((2, 1, 1, 1, 3, 3))
      dense_shaped_expected = np.array(
          [[1, 0, 1, 0, 0, 0], [0, 0, 2, 2, 0, 0]], np.uint8
      ).reshape((2, 1, 1, 1, 3, 2))
      indices_expected = [
          np.array([1], dtype=np.uint8),
          np.array([2], dtype=np.uint8),
      ]
  
      np.testing.assert_array_equal(dense_plain, dense_plain_expected)
      np.testing.assert_array_equal(dense_shaped, dense_shaped_expected)
      _check_indices(dpi, indices_expected)
      _check_indices(dsi, indices_expected)
  
imports: import numpy
  import centrosome.outline
  import cellprofiler_library.functions.segmentation
  from cellprofiler_library.functions.segmentation import SPARSE_FIELD
label_desc: Use image node_id 10 for calling the TestSegmentation obj's underlying member method code with example usage: obj.test_02_03_sparse_to_2d_dense_overlap() without return types