def METHOD_NAME(self):
    # Generic parameters for 1-D tests.
    nx1 = 100
    nx2 = 200
    nx3 = 50
    xRange1 = (0.0, 1.0)
    xRange2 = (1.0, 2.0)
    xRange3 = (2.0, 3.0)
    # Construct the NodeLists to be distributed
    self.eos = GammaLawGasMKS1d(2.0, 2.0)
    self.WT = TableKernel1d(BSplineKernel1d())
    self.nodes1 = makeFluidNodeList1d("nodes1", self.eos)
    self.nodes2 = makeFluidNodeList1d("nodes2", self.eos)
    self.nodes3 = makeFluidNodeList1d("nodes3", self.eos)
    for (nodes, nGlobal, globalRange) in ((self.nodes1, nx1, xRange1),
                                          (self.nodes2, nx2, xRange2),
                                          (self.nodes3, nx3, xRange3)):
        globalIDs, xNodes = randomDistribute(domainID,
                                             nDomains,
                                             nGlobal,
                                             globalRange)
        n = len(globalIDs)
        nodes.numInternalNodes = n
        HNodes = determineHField(nGlobal, n, globalRange)
        for i in range(n):
            nodes.mass()[i] = 1.0
            nodes.positions()[i].x = xNodes[i]
            nodes.Hfield()[i].xx = HNodes[i]
        nodes.neighbor().updateNodes()
    # Put the distributed NodeLists into a DataBase.
    self.dataBase = DataBase1d()
    self.dataBase.appendNodeList(self.nodes1)
    self.dataBase.appendNodeList(self.nodes2)
    self.dataBase.appendNodeList(self.nodes3)
    assert mpi.allreduce(self.nodes1.numInternalNodes, mpi.SUM) == nx1
    assert mpi.allreduce(self.nodes2.numInternalNodes, mpi.SUM) == nx2
    assert mpi.allreduce(self.nodes3.numInternalNodes, mpi.SUM) == nx3
    return