human
Write me a Python code to find    zero given the following:
I wrote the below code

    def phi_and_derivative(alpha, suf, s, Delta):
        'Function    of    which    to    find    zero.\n                                \n                                It    is    defined    as    "norm    of    regularized    (by    alpha)    least-squares\n                                solution    minus    `Delta`".    Refer    to    [1]_.\n                                '
        denom = ((s ** 2) + alpha)
        p_norm = norm((suf / denom))
        phi = (p_norm - Delta)
        phi_prime = ((- np.sum(((suf ** 2) / (denom ** 3)))) / p_norm)
        return (phi, phi_prime)
    suf = (s * uf)
    if (m >= n):
        threshold = ((EPS * m) * s[0])
        full_rank = (s[(-1)] > threshold)
    else:
        full_rank = False
    if full_rank:
        p = (- V.dot((uf / s)))
        if (norm(p) <= Delta):
            return (p, 0.0, 0)
    alpha_upper = (norm(suf) / Delta)
    if full_rank:
        (phi, phi_prime) = phi_and_derivative(0.0, suf, s, Delta)
        alpha_lower = ((- phi) / phi_prime)
    else:
        alpha_lower = 0.0
    if ((initial_alpha is None) or ((not full_rank) and (initial_alpha == 0))):
        alpha = max((0.001 * alpha_upper), ((alpha_lower * alpha_upper) ** 0.5))
    else:
        alpha = initial_alpha
    for it in range(max_iter):
        if ((alpha < alpha_lower) or (alpha > alpha_upper)):
            alpha = max((0.001 * alpha_upper), ((alpha_lower * alpha_upper) ** 0.5))
        (phi, phi_prime) = phi_and_derivative(alpha, suf, s, Delta)
        if (phi < 0):
            alpha_upper = alpha
        ratio = (phi / phi_prime)
        alpha_lower = max(alpha_lower, (alpha - ratio))
        alpha -= (((phi + Delta) * ratio) / Delta)
        if (np.abs(phi) < (rtol * Delta)):
            break
    p = (- V.dot((suf / ((s ** 2) + alpha))))
    p *= (Delta / norm(p))
    return (p, alpha, (it + 1))

What's a good function header?
assistant
#Here is Python code to find    zero.

def solve_lsq_trust_region(n, m, uf, s, V, Delta, initial_alpha=None, rtol=0.01, max_iter=10):