def METHOD_NAME(self, n = 100):
    dense = np.arange(n*n).reshape(n,n)
    R1 = Resolution(dense)
    assert scipy.sparse.isspmatrix_dia(R1),'Resolution is not recognized as a scipy.sparse.dia_matrix.'
    assert len(R1.offsets) == desispec.resolution.default_ndiag, 'Resolution.offsets has wrong size'
    R2 = Resolution(R1)
    assert np.array_equal(R1.toarray(),R2.toarray()),'Constructor broken for dia_matrix input.'
    R3 = Resolution(R1.data)
    assert np.array_equal(R1.toarray(),R3.toarray()),'Constructor broken for array data input.'
    sparse = scipy.sparse.dia_matrix((R1.data[::-1],R1.offsets[::-1]),(n,n))
    R4 = Resolution(sparse)
    assert np.array_equal(R1.toarray(),R4.toarray()),'Constructor broken for permuted offsets input.'
    R5 = Resolution(R1.to_fits_array())
    assert np.array_equal(R1.toarray(),R5.toarray()),'to_fits_array() is broken.'
    #- test different sizes of input diagonals
    for ndiag in [3,5,11]:
        R6 = Resolution(np.ones((ndiag, n)))
        assert len(R6.offsets) == ndiag, 'Constructor broken for ndiag={}'.format(ndiag)
    #- An even number if diagonals is not allowed
    try:
        ndiag = 10
        R7 = Resolution(np.ones((ndiag, n)))
        raise RuntimeError('Incorrectly created Resolution with even number of diagonals')
    except ValueError as err:
        #- it correctly raised an error, so pass
        pass
    #- Test creation with sigmas - it should conserve flux
    R9 = Resolution(np.linspace(1.0, 2.0, n))
    self.assertTrue(np.allclose(np.sum(R9.data, axis=0), 1.0))