def METHOD_NAME(self):
    """
    Another test to check behavior after deleting an entire label class from the sparse array.
    This one ensures that different blocks have different max label values before the delete occurs.
    """
    op = self.op
    slicing = self.slicing
    data = self.data
    # assert op.maxLabel.value == 2
    # Choose slicings that do NOT intersect with any of the previous data or with each other
    # The goal is to make sure that the data for each slice ends up in a separate block
    slicing1 = numpy.s_[0:1, 60:65, 0:10, 3:7, 0:1]
    slicing2 = numpy.s_[0:1, 90:95, 0:90, 3:7, 0:1]
    expectedData = self.data[...]
    labels1 = numpy.ndarray(slicing2shape(slicing1), dtype=numpy.uint8)
    labels1[...] = 1
    op.LabelSinkInput[slicing1] = labels1
    expectedData[slicing1] = labels1
    labels2 = numpy.ndarray(slicing2shape(slicing2), dtype=numpy.uint8)
    labels2[...] = 2
    op.LabelSinkInput[slicing2] = labels2
    expectedData[slicing2] = labels2
    # Sanity check:
    # Does the data contain our new labels?
    assert (op.Output[...].wait() == expectedData).all()
    assert expectedData.max() == 2
    # assert op.maxLabel.value == 2
    # Delete label 1
    op.DeleteLabel.setValue(1)
    outputData = op.Output[...].wait()
    # Expected: All 1s removed
    expectedData = numpy.where(expectedData == 1, 0, expectedData)
    # expectedData = numpy.where(expectedData == 2, 1, expectedData)
    assert (outputData[...] == expectedData[...]).all()
    # assert op.maxLabel.value == expectedData.max() == 1