Python randtest.tn函数代码示例

def test_hyper():
    raises(TypeError, 'hyper(1, 2, z)')

    assert hyper((1, 2),(1,), z) == hyper(Tuple(1, 2), Tuple(1), z)

    h = hyper((1, 2), (3, 4, 5), z)
    assert h.ap == Tuple(1, 2)
    assert h.bq == Tuple(3, 4, 5)
    assert h.argument == z
    assert h.is_commutative is True

    # just a few checks to make sure that all arguments go where they should
    assert tn(hyper(Tuple(), Tuple(), z), exp(z), z)
    assert tn(z*hyper((1, 1), Tuple(2), -z), log(1 + z), z)

    # differentiation
    h = hyper((randcplx(), randcplx(), randcplx()), (randcplx(), randcplx()), z)
    assert td(h, z)

    a1, a2, b1, b2, b3 = symbols('a1:3, b1:4')
    assert hyper((a1, a2), (b1, b2, b3), z).diff(z) == \
             a1*a2/(b1*b2*b3) * hyper((a1+1, a2+1), (b1+1, b2+1, b3+1), z)

    # differentiation wrt parameters is not supported
    raises(NotImplementedError, 'hyper((z,), (), z).diff(z)')

def test_uppergamma():
    from sympy import meijerg, exp_polar, I, expint
    assert uppergamma(4, 0) == 6
    assert uppergamma(x, y).diff(y) == -y**(x-1)*exp(-y)
    assert td(uppergamma(randcplx(), y), y)
    assert uppergamma(x, y).diff(x) == \
           uppergamma(x, y)*log(y) + meijerg([], [1, 1], [0, 0, x], [], y)
    assert td(uppergamma(x, randcplx()), x)

    assert uppergamma(S.Half, x) == sqrt(pi)*(1 - erf(sqrt(x)))
    assert not uppergamma(S.Half - 3, x).has(uppergamma)
    assert not uppergamma(S.Half + 3, x).has(uppergamma)
    assert uppergamma(S.Half, x, evaluate=False).has(uppergamma)
    assert tn(uppergamma(S.Half + 3, x, evaluate=False),
              uppergamma(S.Half + 3, x), x)
    assert tn(uppergamma(S.Half - 3, x, evaluate=False),
              uppergamma(S.Half - 3, x), x)

    assert uppergamma(x, y).rewrite(lowergamma) == gamma(x) - lowergamma(x, y)

    assert tn_branch(-3, uppergamma)
    assert tn_branch(-4, uppergamma)
    assert tn_branch(S(1)/3, uppergamma)
    assert tn_branch(pi, uppergamma)
    assert uppergamma(3, exp_polar(4*pi*I)*x) == uppergamma(3, x)
    assert uppergamma(y, exp_polar(5*pi*I)*x) == \
           exp(4*I*pi*y)*uppergamma(y, x*exp_polar(pi*I)) + gamma(y)*(1-exp(4*pi*I*y))
    assert uppergamma(-2, exp_polar(5*pi*I)*x) == \
           uppergamma(-2, x*exp_polar(I*pi)) - 2*pi*I

    assert uppergamma(-2, x) == expint(3, x)/x**2
    assert uppergamma(x, y).rewrite(expint) == y**x*expint(-x + 1, y)

def test_partial_simp():
    # First test that hypergeometric function formulae work.
    a, b, c, d, e = map(lambda _: randcplx(), range(5))
    for func in [Hyper_Function([a, b, c], [d, e]),
            Hyper_Function([], [a, b, c, d, e])]:
        f = build_hypergeometric_formula(func)
        z = f.z
        assert f.closed_form == func(z)
        deriv1 = f.B.diff(z)*z
        deriv2 = f.M*f.B
        for func1, func2 in zip(deriv1, deriv2):
            assert tn(func1, func2, z)

    # Now test that formulae are partially simplified.
    from sympy.abc import a, b, z
    assert hyperexpand(hyper([3, a], [1, b], z)) == \
        (-a*b/2 + a*z/2 + 2*a)*hyper([a + 1], [b], z) \
        + (a*b/2 - 2*a + 1)*hyper([a], [b], z)
    assert tn(
        hyperexpand(hyper([3, d], [1, e], z)), hyper([3, d], [1, e], z), z)
    assert hyperexpand(hyper([3], [1, a, b], z)) == \
        hyper((), (a, b), z) \
        + z*hyper((), (a + 1, b), z)/(2*a) \
        - z*(b - 4)*hyper((), (a + 1, b + 1), z)/(2*a*b)
    assert tn(
        hyperexpand(hyper([3], [1, d, e], z)), hyper([3], [1, d, e], z), z)

def test_lowergamma():
    from sympy import meijerg, exp_polar, I, expint
    assert lowergamma(x, y).diff(y) == y**(x-1)*exp(-y)
    assert td(lowergamma(randcplx(), y), y)
    assert lowergamma(x, y).diff(x) == \
           gamma(x)*polygamma(0, x) - uppergamma(x, y)*log(y) \
           + meijerg([], [1, 1], [0, 0, x], [], y)

    assert lowergamma(S.Half, x) == sqrt(pi)*erf(sqrt(x))
    assert not lowergamma(S.Half - 3, x).has(lowergamma)
    assert not lowergamma(S.Half + 3, x).has(lowergamma)
    assert lowergamma(S.Half, x, evaluate=False).has(lowergamma)
    assert tn(lowergamma(S.Half + 3, x, evaluate=False),
              lowergamma(S.Half + 3, x), x)
    assert tn(lowergamma(S.Half - 3, x, evaluate=False),
              lowergamma(S.Half - 3, x), x)

    assert lowergamma(x, y).rewrite(uppergamma) == gamma(x) - uppergamma(x, y)

    assert tn_branch(-3, lowergamma)
    assert tn_branch(-4, lowergamma)
    assert tn_branch(S(1)/3, lowergamma)
    assert tn_branch(pi, lowergamma)
    assert lowergamma(3, exp_polar(4*pi*I)*x) == lowergamma(3, x)
    assert lowergamma(y, exp_polar(5*pi*I)*x) == \
           exp(4*I*pi*y)*lowergamma(y, x*exp_polar(pi*I))
    assert lowergamma(-2, exp_polar(5*pi*I)*x) == \
           lowergamma(-2, x*exp_polar(I*pi)) + 2*pi*I

    assert lowergamma(x, y).rewrite(expint) == -y**x*expint(-x + 1, y) + gamma(x)
    k = Symbol('k', integer=True)
    assert lowergamma(k, y).rewrite(expint) == -y**k*expint(-k + 1, y) + gamma(k)
    k = Symbol('k', integer=True, positive=False)
    assert lowergamma(k, y).rewrite(expint) == lowergamma(k, y)

def test_K():
    assert K(0) == pi/2
    assert K(S(1)/2) == 8*pi**(S(3)/2)/gamma(-S(1)/4)**2
    assert K(1) == zoo
    assert K(-1) == gamma(S(1)/4)**2/(4*sqrt(2*pi))
    assert K(oo) == 0
    assert K(-oo) == 0
    assert K(I*oo) == 0
    assert K(-I*oo) == 0
    assert K(zoo) == 0

    assert K(z).diff(z) == (E(z) - (1 - z)*K(z))/(2*z*(1 - z))
    assert td(K(z), z)

    zi = Symbol('z', real=False)
    assert K(zi).conjugate() == K(zi.conjugate())
    zr = Symbol('z', real=True, negative=True)
    assert K(zr).conjugate() == K(zr)

    assert K(z).rewrite(hyper) == \
        (pi/2)*hyper((S.Half, S.Half), (S.One,), z)
    assert tn(K(z), (pi/2)*hyper((S.Half, S.Half), (S.One,), z))
    assert K(z).rewrite(meijerg) == \
        meijerg(((S.Half, S.Half), []), ((S.Zero,), (S.Zero,)), -z)/2
    assert tn(K(z), meijerg(((S.Half, S.Half), []), ((S.Zero,), (S.Zero,)), -z)/2)

def test_formulae():
    from sympy.simplify.hyperexpand import FormulaCollection
    formulae = FormulaCollection().formulae
    for formula in formulae:
        h = formula.func(formula.z)
        rep = {}
        for n, sym in enumerate(formula.symbols):
            rep[sym] = randcplx(n)

        # NOTE hyperexpand returns truly branched functions. We know we are
        #      on the main sheet, but numerical evaluation can still go wrong
        #      (e.g. if exp_polar cannot be evalf'd).
        #      Just replace all exp_polar by exp, this usually works.

        # first test if the closed-form is actually correct
        h = h.subs(rep)
        closed_form = formula.closed_form.subs(rep).rewrite('nonrepsmall')
        z = formula.z
        assert tn(h, closed_form.replace(exp_polar, exp), z)

        # now test the computed matrix
        cl = (formula.C * formula.B)[0].subs(rep).rewrite('nonrepsmall')
        assert tn(closed_form.replace(
            exp_polar, exp), cl.replace(exp_polar, exp), z)
        deriv1 = z*formula.B.applyfunc(lambda t: t.rewrite(
            'nonrepsmall')).diff(z)
        deriv2 = formula.M * formula.B
        for d1, d2 in zip(deriv1, deriv2):
            assert tn(d1.subs(rep).replace(exp_polar, exp),
                      d2.subs(rep).rewrite('nonrepsmall').replace(exp_polar, exp), z)

def test_meijerg():
    # carefully set up the parameters.
    # NOTE: this used to fail sometimes. I believe it is fixed, but if you
    #       hit an inexplicable test failure here, please let me know the seed.
    a1, a2 = map(lambda n: randcplx() - 5*I - n*I, range(2))
    b1, b2 = map(lambda n: randcplx() + 5*I + n*I, range(2))
    b3, b4, b5, a3, a4, a5 = map(lambda n: randcplx(), range(6))
    g = meijerg([a1], [a3, a4], [b1], [b3, b4], z)

    assert ReduceOrder.meijer_minus(3, 4) is None
    assert ReduceOrder.meijer_plus(4, 3) is None

    g2 = meijerg([a1, a2], [a3, a4], [b1], [b3, b4, a2], z)
    assert tn(ReduceOrder.meijer_plus(a2, a2).apply(g, op), g2, z)

    g2 = meijerg([a1, a2], [a3, a4], [b1], [b3, b4, a2 + 1], z)
    assert tn(ReduceOrder.meijer_plus(a2, a2 + 1).apply(g, op), g2, z)

    g2 = meijerg([a1, a2 - 1], [a3, a4], [b1], [b3, b4, a2 + 2], z)
    assert tn(ReduceOrder.meijer_plus(a2 - 1, a2 + 2).apply(g, op), g2, z)

    g2 = meijerg([a1], [a3, a4, b2 - 1], [b1, b2 + 2], [b3, b4], z)
    assert tn(ReduceOrder.meijer_minus(b2 + 2, b2 - 1).apply(g, op), g2, z, tol=1e-6)

    # test several-step reduction
    an = [a1, a2]
    bq = [b3, b4, a2 + 1]
    ap = [a3, a4, b2 - 1]
    bm = [b1, b2 + 1]
    niq, ops = reduce_order_meijer(IndexQuadruple(an, ap, bm, bq))
    assert niq.an == (a1,)
    assert set(niq.ap) == set([a3, a4])
    assert niq.bm == (b1,)
    assert set(niq.bq) == set([b3, b4])
    assert tn(apply_operators(g, ops, op), meijerg(an, ap, bm, bq, z), z)

def test_E():
    assert E(z, 0) == z
    assert E(0, m) == 0
    assert E(i*pi/2, m) == i*E(m)
    assert E(z, oo) == zoo
    assert E(z, -oo) == zoo
    assert E(0) == pi/2
    assert E(1) == 1
    assert E(oo) == I*oo
    assert E(-oo) == oo
    assert E(zoo) == zoo

    assert E(-z, m) == -E(z, m)

    assert E(z, m).diff(z) == sqrt(1 - m*sin(z)**2)
    assert E(z, m).diff(m) == (E(z, m) - F(z, m))/(2*m)
    assert E(z).diff(z) == (E(z) - K(z))/(2*z)
    r = randcplx()
    assert td(E(r, m), m)
    assert td(E(z, r), z)
    assert td(E(z), z)

    mi = Symbol('m', real=False)
    assert E(z, mi).conjugate() == E(z.conjugate(), mi.conjugate())
    mr = Symbol('m', real=True, negative=True)
    assert E(z, mr).conjugate() == E(z.conjugate(), mr)

    assert E(z).rewrite(hyper) == (pi/2)*hyper((-S.Half, S.Half), (S.One,), z)
    assert tn(E(z), (pi/2)*hyper((-S.Half, S.Half), (S.One,), z))
    assert E(z).rewrite(meijerg) == \
        -meijerg(((S.Half, S(3)/2), []), ((S.Zero,), (S.Zero,)), -z)/4
    assert tn(E(z), -meijerg(((S.Half, S(3)/2), []), ((S.Zero,), (S.Zero,)), -z)/4)

def test_meijerg_formulae():
    from sympy.simplify.hyperexpand import MeijerFormulaCollection
    formulae = MeijerFormulaCollection().formulae
    for sig in formulae:
        for formula in formulae[sig]:
            g = meijerg(formula.func.an, formula.func.ap,
                        formula.func.bm, formula.func.bq,
                        formula.z)
            rep = {}
            for sym in formula.symbols:
                rep[sym] = randcplx()

            # first test if the closed-form is actually correct
            g = g.subs(rep)
            closed_form = formula.closed_form.subs(rep)
            z = formula.z
            assert tn(g, closed_form, z)

            # now test the computed matrix
            cl = (formula.C * formula.B)[0].subs(rep)
            assert tn(closed_form, cl, z)
            deriv1 = z*formula.B.diff(z)
            deriv2 = formula.M * formula.B
            for d1, d2 in zip(deriv1, deriv2):
                assert tn(d1.subs(rep), d2.subs(rep), z)

def test_conjugate():
    from sympy import conjugate, I, Symbol
    n, z, x = Symbol('n'), Symbol('z', real=False), Symbol('x', real=True)
    y, t = Symbol('y', real=True, positive=True), Symbol('t', negative=True)

    for f in [besseli, besselj, besselk, bessely, hankel1, hankel2]:
        assert f(n, -1).conjugate() != f(conjugate(n), -1)
        assert f(n, x).conjugate() != f(conjugate(n), x)
        assert f(n, t).conjugate() != f(conjugate(n), t)

    rz = randcplx(b=0.5)

    for f in [besseli, besselj, besselk, bessely]:
        assert f(n, 1 + I).conjugate() == f(conjugate(n), 1 - I)
        assert f(n, 0).conjugate() == f(conjugate(n), 0)
        assert f(n, 1).conjugate() == f(conjugate(n), 1)
        assert f(n, z).conjugate() == f(conjugate(n), conjugate(z))
        assert f(n, y).conjugate() == f(conjugate(n), y)
        assert tn(f(n, rz).conjugate(), f(conjugate(n), conjugate(rz)))

    assert hankel1(n, 1 + I).conjugate() == hankel2(conjugate(n), 1 - I)
    assert hankel1(n, 0).conjugate() == hankel2(conjugate(n), 0)
    assert hankel1(n, 1).conjugate() == hankel2(conjugate(n), 1)
    assert hankel1(n, y).conjugate() == hankel2(conjugate(n), y)
    assert hankel1(n, z).conjugate() == hankel2(conjugate(n), conjugate(z))
    assert tn(hankel1(n, rz).conjugate(), hankel2(conjugate(n), conjugate(rz)))

    assert hankel2(n, 1 + I).conjugate() == hankel1(conjugate(n), 1 - I)
    assert hankel2(n, 0).conjugate() == hankel1(conjugate(n), 0)
    assert hankel2(n, 1).conjugate() == hankel1(conjugate(n), 1)
    assert hankel2(n, y).conjugate() == hankel1(conjugate(n), y)
    assert hankel2(n, z).conjugate() == hankel1(conjugate(n), conjugate(z))
    assert tn(hankel2(n, rz).conjugate(), hankel1(conjugate(n), conjugate(rz)))

def test_plan():
    assert devise_plan(Hyper_Function([0], ()),
            Hyper_Function([0], ()), z) == []
    with raises(ValueError):
        devise_plan(Hyper_Function([1], ()), Hyper_Function((), ()), z)
    with raises(ValueError):
        devise_plan(Hyper_Function([2], [1]), Hyper_Function([2], [2]), z)
    with raises(ValueError):
        devise_plan(Hyper_Function([2], []), Hyper_Function([S("1/2")], []), z)

    # We cannot use pi/(10000 + n) because polys is insanely slow.
    a1, a2, b1 = map(lambda n: randcplx(n), range(3))
    b1 += 2*I
    h = hyper([a1, a2], [b1], z)

    h2 = hyper((a1 + 1, a2), [b1], z)
    assert tn(apply_operators(h,
        devise_plan(Hyper_Function((a1 + 1, a2), [b1]),
            Hyper_Function((a1, a2), [b1]), z), op),
        h2, z)

    h2 = hyper((a1 + 1, a2 - 1), [b1], z)
    assert tn(apply_operators(h,
        devise_plan(Hyper_Function((a1 + 1, a2 - 1), [b1]),
            Hyper_Function((a1, a2), [b1]), z), op),
        h2, z)

def test_K():
    assert K(0) == pi / 2
    assert K(S(1) / 2) == 8 * pi ** (S(3) / 2) / gamma(-S(1) / 4) ** 2
    assert K(1) == zoo
    assert K(-1) == gamma(S(1) / 4) ** 2 / (4 * sqrt(2 * pi))
    assert K(oo) == 0
    assert K(-oo) == 0
    assert K(I * oo) == 0
    assert K(-I * oo) == 0
    assert K(zoo) == 0

    assert K(z).diff(z) == (E(z) - (1 - z) * K(z)) / (2 * z * (1 - z))
    assert td(K(z), z)

    zi = Symbol("z", real=False)
    assert K(zi).conjugate() == K(zi.conjugate())
    zr = Symbol("z", real=True, negative=True)
    assert K(zr).conjugate() == K(zr)

    assert K(z).rewrite(hyper) == (pi / 2) * hyper((S.Half, S.Half), (S.One,), z)
    assert tn(K(z), (pi / 2) * hyper((S.Half, S.Half), (S.One,), z))
    assert K(z).rewrite(meijerg) == meijerg(((S.Half, S.Half), []), ((S.Zero,), (S.Zero,)), -z) / 2
    assert tn(K(z), meijerg(((S.Half, S.Half), []), ((S.Zero,), (S.Zero,)), -z) / 2)

    assert K(z).series(
        z
    ) == pi / 2 + pi * z / 8 + 9 * pi * z ** 2 / 128 + 25 * pi * z ** 3 / 512 + 1225 * pi * z ** 4 / 32768 + 3969 * pi * z ** 5 / 131072 + O(
        z ** 6
    )

    def t(func, hyp, z):
        """ Test that func is a valid representation of hyp. """
        # First test that func agrees with hyp for small z
        if not tn(func.rewrite('nonrepsmall'), hyp, z,
                  a=S(-1)/2, b=S(-1)/2, c=S(1)/2, d=S(1)/2):
            return False
        # Next check that the two small representations agree.
        if not tn(
            func.rewrite('nonrepsmall').subs(
                z, exp_polar(I*pi)*z).replace(exp_polar, exp),
            func.subs(z, exp_polar(I*pi)*z).rewrite('nonrepsmall'),
                z, a=S(-1)/2, b=S(-1)/2, c=S(1)/2, d=S(1)/2):
            return False
        # Next check continuity along exp_polar(I*pi)*t
        expr = func.subs(z, exp_polar(I*pi)*z).rewrite('nonrep')
        if abs(expr.subs(z, 1 + 1e-15).n() - expr.subs(z, 1 - 1e-15).n()) > 1e-10:
            return False
        # Finally check continuity of the big reps.

        def dosubs(func, a, b):
            rv = func.subs(z, exp_polar(a)*z).rewrite('nonrep')
            return rv.subs(z, exp_polar(b)*z).replace(exp_polar, exp)
        for n in [0, 1, 2, 3, 4, -1, -2, -3, -4]:
            expr1 = dosubs(func, 2*I*pi*n, I*pi/2)
            expr2 = dosubs(func, 2*I*pi*n + I*pi, -I*pi/2)
            if not tn(expr1, expr2, z):
                return False
            expr1 = dosubs(func, 2*I*pi*(n + 1), -I*pi/2)
            expr2 = dosubs(func, 2*I*pi*n + I*pi, I*pi/2)
            if not tn(expr1, expr2, z):
                return False
        return True

def test_hyper():
    raises(TypeError, lambda: hyper(1, 2, z))

    assert hyper((1, 2), (1,), z) == hyper(Tuple(1, 2), Tuple(1), z)

    h = hyper((1, 2), (3, 4, 5), z)
    assert h.ap == Tuple(1, 2)
    assert h.bq == Tuple(3, 4, 5)
    assert h.argument == z
    assert h.is_commutative is True

    # just a few checks to make sure that all arguments go where they should
    assert tn(hyper(Tuple(), Tuple(), z), exp(z), z)
    assert tn(z*hyper((1, 1), Tuple(2), -z), log(1 + z), z)

    # differentiation
    h = hyper(
        (randcplx(), randcplx(), randcplx()), (randcplx(), randcplx()), z)
    assert td(h, z)

    a1, a2, b1, b2, b3 = symbols('a1:3, b1:4')
    assert hyper((a1, a2), (b1, b2, b3), z).diff(z) == \
        a1*a2/(b1*b2*b3) * hyper((a1 + 1, a2 + 1), (b1 + 1, b2 + 1, b3 + 1), z)

    # differentiation wrt parameters is not supported
    assert hyper([z], [], z).diff(z) == Derivative(hyper([z], [], z), z)

    # hyper is unbranched wrt parameters
    from sympy import polar_lift
    assert hyper([polar_lift(z)], [polar_lift(k)], polar_lift(x)) == \
        hyper([z], [k], polar_lift(x))

def test_rewrite():
    from sympy import polar_lift, exp, I

    assert besselj(n, z).rewrite(jn) == sqrt(2*z/pi)*jn(n - S(1)/2, z)
    assert bessely(n, z).rewrite(yn) == sqrt(2*z/pi)*yn(n - S(1)/2, z)
    assert besseli(n, z).rewrite(besselj) == \
        exp(-I*n*pi/2)*besselj(n, polar_lift(I)*z)
    assert besselj(n, z).rewrite(besseli) == \
        exp(I*n*pi/2)*besseli(n, polar_lift(-I)*z)

    nu = randcplx()

    assert tn(besselj(nu, z), besselj(nu, z).rewrite(besseli), z)
    assert tn(besselj(nu, z), besselj(nu, z).rewrite(bessely), z)

    assert tn(besseli(nu, z), besseli(nu, z).rewrite(besselj), z)
    assert tn(besseli(nu, z), besseli(nu, z).rewrite(bessely), z)

    assert tn(bessely(nu, z), bessely(nu, z).rewrite(besselj), z)
    assert tn(bessely(nu, z), bessely(nu, z).rewrite(besseli), z)

    assert tn(besselk(nu, z), besselk(nu, z).rewrite(besselj), z)
    assert tn(besselk(nu, z), besselk(nu, z).rewrite(besseli), z)
    assert tn(besselk(nu, z), besselk(nu, z).rewrite(bessely), z)

    # check that a rewrite was triggered, when the order is set to a generic
    # symbol 'nu'
    assert yn(nu, z) != yn(nu, z).rewrite(jn)
    assert hn1(nu, z) != hn1(nu, z).rewrite(jn)
    assert hn2(nu, z) != hn2(nu, z).rewrite(jn)
    assert jn(nu, z) != jn(nu, z).rewrite(yn)
    assert hn1(nu, z) != hn1(nu, z).rewrite(yn)
    assert hn2(nu, z) != hn2(nu, z).rewrite(yn)

    # rewriting spherical bessel functions (SBFs) w.r.t. besselj, bessely is
    # not allowed if a generic symbol 'nu' is used as the order of the SBFs
    # to avoid inconsistencies (the order of bessel[jy] is allowed to be
    # complex-valued, whereas SBFs are defined only for integer orders)
    order = nu
    for f in (besselj, bessely):
        assert hn1(order, z) == hn1(order, z).rewrite(f)
        assert hn2(order, z) == hn2(order, z).rewrite(f)

    assert jn(order, z).rewrite(besselj) == sqrt(2)*sqrt(pi)*sqrt(1/z)*besselj(order + S(1)/2, z)/2
    assert jn(order, z).rewrite(bessely) == (-1)**nu*sqrt(2)*sqrt(pi)*sqrt(1/z)*bessely(-order - S(1)/2, z)/2

    # for integral orders rewriting SBFs w.r.t bessel[jy] is allowed
    N = Symbol('n', integer=True)
    ri = randint(-11, 10)
    for order in (ri, N):
        for f in (besselj, bessely):
            assert yn(order, z) != yn(order, z).rewrite(f)
            assert jn(order, z) != jn(order, z).rewrite(f)
            assert hn1(order, z) != hn1(order, z).rewrite(f)
            assert hn2(order, z) != hn2(order, z).rewrite(f)

    for func, refunc in product((yn, jn, hn1, hn2),
                                (jn, yn, besselj, bessely)):
        assert tn(func(ri, z), func(ri, z).rewrite(refunc), z)