def METHOD_NAME():
    ce = np.array([-2., 0., 2.])
    cse = 2.
    cn = np.array([-3., -1.5, 0., 1.5, 3.])
    csn = 1.5
    # Dummy resisitvity model
    resgrid = np.array([
        [[100., 100., 100., 100., 100.], [150., 150., 150., 150., 150.], [100., 100., 100, 100., 100.]],
        [[150., 150., 150., 150., 150.], [100., 100., 100., 100., 100.], [150., 150., 150., 150., 150.]]
    ])
    # Transpose it to get [[Y], [X], [Z]]
    resgrid = resgrid.T
    tgx, tgy = np.meshgrid(np.arange(ce[0], ce[-1], cse),
                           np.arange(cn[0], cn[-1], csn))
    res_slice = conv._interpolate_slice(ce, cn, resgrid, 0, tgx, tgy, log_scale=True)
    expected = np.array([
        [2., 2.17609126],
        [2., 2.17609126],
        [2., 2.17609126],
        [2., 2.17609126],
    ])
    assert np.allclose(res_slice, expected)
    res_slice = conv._interpolate_slice(ce, cn, resgrid, 0, tgx, tgy, log_scale=False)
    expected = np.array(
        [[1024., 2381.063868],
         [1024., 2381.063868],
         [1024., 2381.063868],
         [1024., 2381.063868]]
    )
    assert np.allclose(res_slice, expected)