Python ntheory.nextprime函数代码示例

def main7():
    seed(0)
    p = nextprime(randrange(2**96))
    q = nextprime(randrange(2**97))
    n = p * q
    print(p, q, n)
    print(qsieve(n))

def main4():
    print(crack_when_pq_close(23360947609))
    p = nextprime(2**128)
    print(p)
    q = nextprime(p)
    print(q)
    print(crack_when_pq_close(p * q))

def dmp_zz_collins_resultant(f, g, u, K):
    """
    Collins's modular resultant algorithm in `Z[X]`.

    Examples
    ========

    >>> from sympy.polys.domains import ZZ
    >>> from sympy.polys.euclidtools import dmp_zz_collins_resultant

    >>> f = ZZ.map([[1], [1, 2]])
    >>> g = ZZ.map([[2, 1], [3]])

    >>> dmp_zz_collins_resultant(f, g, 1, ZZ)
    [-2, -5, 1]

    """

    n = dmp_degree(f, u)
    m = dmp_degree(g, u)

    if n < 0 or m < 0:
        return dmp_zero(u-1)

    A = dmp_max_norm(f, u, K)
    B = dmp_max_norm(g, u, K)

    a = dmp_ground_LC(f, u, K)
    b = dmp_ground_LC(g, u, K)

    v = u - 1

    B = K(2)*K.factorial(n+m)*A**m*B**n
    r, p, P = dmp_zero(v), K.one, K.one

    while P <= B:
        p = K(nextprime(p))

        while not (a % p) or not (b % p):
            p = K(nextprime(p))

        F = dmp_ground_trunc(f, p, u, K)
        G = dmp_ground_trunc(g, p, u, K)

        try:
            R = dmp_zz_modular_resultant(F, G, p, u, K)
        except HomomorphismFailed:
            continue

        if K.is_one(P):
            r = R
        else:
            r = dmp_apply_pairs(r, R, _collins_crt, (P, p, K), v, K)

        P *= p

    return r

def dmp_zz_collins_resultant(f, g, u, K):
    """
    Collins's modular resultant algorithm in `Z[X]`.

    Examples
    ========

    >>> from sympy.polys import ring, ZZ
    >>> R, x,y = ring("x,y", ZZ)

    >>> f = x + y + 2
    >>> g = 2*x*y + x + 3

    >>> R.dmp_zz_collins_resultant(f, g)
    -2*y**2 - 5*y + 1

    """

    n = dmp_degree(f, u)
    m = dmp_degree(g, u)

    if n < 0 or m < 0:
        return dmp_zero(u - 1)

    A = dmp_max_norm(f, u, K)
    B = dmp_max_norm(g, u, K)

    a = dmp_ground_LC(f, u, K)
    b = dmp_ground_LC(g, u, K)

    v = u - 1

    B = K(2)*K.factorial(K(n + m))*A**m*B**n
    r, p, P = dmp_zero(v), K.one, K.one

    while P <= B:
        p = K(nextprime(p))

        while not (a % p) or not (b % p):
            p = K(nextprime(p))

        F = dmp_ground_trunc(f, p, u, K)
        G = dmp_ground_trunc(g, p, u, K)

        try:
            R = dmp_zz_modular_resultant(F, G, p, u, K)
        except HomomorphismFailed:
            continue

        if K.is_one(P):
            r = R
        else:
            r = dmp_apply_pairs(r, R, _collins_crt, (P, p, K), v, K)

        P *= p

    return r

def rsa(bits):
    p = nextprime(randrange(2**(bits // 2 + 1)))
    q = nextprime(randrange(2**(bits // 2 + 1)))
    n = p * q
    phi_n = (p - 1) * (q - 1)
    while True:
        e = randrange(1, phi_n)
        if gcd(e, phi_n) == 1:
            break
    d = inv_mod(e, phi_n)
    return e, d, n

def GetLongestConsSumPrimes(step,limit):
	sum = step
	count = 1
	i = nextprime(step)
	while (sum + i)<limit:
		sum += i
		count += 1
		i = nextprime(i)
		
	while isprime(sum) == False :	
		i = prevprime(i)
		sum -= i
		count -= 1

	return (count,sum)

def swinnerton_dyer_poly(n, x=None, **args):
    """Generates n-th Swinnerton-Dyer polynomial in `x`.  """
    if n <= 0:
        raise ValueError(
            "can't generate Swinnerton-Dyer polynomial of order %s" % n)

    if x is not None:
        x, cls = sympify(x), Poly
    else:
        x, cls = Dummy('x'), PurePoly

    p, elts = 2, [[x, -sqrt(2)],
                  [x, sqrt(2)]]

    for i in xrange(2, n + 1):
        p, _elts = nextprime(p), []

        neg_sqrt = -sqrt(p)
        pos_sqrt = +sqrt(p)

        for elt in elts:
            _elts.append(elt + [neg_sqrt])
            _elts.append(elt + [pos_sqrt])

        elts = _elts

    poly = []

    for elt in elts:
        poly.append(Add(*elt))

    if not args.get('polys', False):
        return Mul(*poly).expand()
    else:
        return PurePoly(Mul(*poly), x)

def swinnerton_dyer_poly(n, x=None, **args):
    """Generates n-th Swinnerton-Dyer polynomial in `x`.  """
    from numberfields import minimal_polynomial
    if n <= 0:
        raise ValueError(
            "can't generate Swinnerton-Dyer polynomial of order %s" % n)

    if x is not None:
        sympify(x)
    else:
        x = Dummy('x')

    if n > 3:
        p = 2
        a = [sqrt(2)]
        for i in xrange(2, n + 1):
            p = nextprime(p)
            a.append(sqrt(p))
        return minimal_polynomial(Add(*a), x, polys=args.get('polys', False))

    if n == 1:
        ex = x**2 - 2
    elif n == 2:
        ex = x**4 - 10*x**2 + 1
    elif n == 3:
        ex = x**8 - 40*x**6 + 352*x**4 - 960*x**2 + 576
    if not args.get('polys', False):
        return ex
    else:
        return PurePoly(ex, x)

def swinnerton_dyer_poly(n, x=None, **args):
    """Generates n-th Swinnerton-Dyer polynomial in `x`.  """
    if n <= 0:
        raise ValueError("can't generate Swinnerton-Dyer polynomial of order %s" % n)

    if x is not None:
        x = sympify(x)
    else:
        x = Symbol('x', dummy=True)

    p, elts = 2, [[x, -2**Rational(1,2)],
                  [x,  2**Rational(1,2)]]

    for i in xrange(2, n+1):
        p, _elts = nextprime(p), []

        neg_sqrt = -p**Rational(1,2)
        pos_sqrt = +p**Rational(1,2)

        for elt in elts:
            _elts.append(elt + [neg_sqrt])
            _elts.append(elt + [pos_sqrt])

        elts = _elts

    poly = []

    for elt in elts:
        poly.append(Add(*elt))

    if not args.get('polys', False):
        return Mul(*poly).expand()
    else:
        return Poly(Mul(*poly))

def test_generate():
    assert nextprime(-4) == 2
    assert nextprime(2) == 3
    assert nextprime(5) == 7
    assert nextprime(90) == 97
    assert nextprime(10**40) == (10**40 + 121)
    assert prevprime(3) == 2
    assert prevprime(7) == 5
    assert prevprime(97) == 89
    assert prevprime(10**40) == (10**40 - 17)
    assert list(primerange(2, 7)) == [2, 3, 5]
    assert list(primerange(2, 10)) == [2, 3, 5, 7]
    assert list(primerange(1050, 1100)) == [1051, 1061, \
        1063, 1069, 1087, 1091, 1093, 1097]
    s = Sieve()
    for i in range(30, 2350, 376):
        for j in range(2, 5096, 1139):
            A = list(s.primerange(i, i+j))
            B = list(primerange(i, i+j))
            assert A == B
    s = Sieve()
    assert s[10] == 29

def doProblem():
	LIMIT = 1000000
	step = 2
	maxLength = 0
	maxIndex = 0
	maxSum = 0
	while step < (LIMIT-maxSum):
		if GetLongestConsSumPrimes(step,LIMIT)[0] > maxLength:
			maxLength = GetLongestConsSumPrimes(step,LIMIT)[0]
			maxSum = GetLongestConsSumPrimes(step,LIMIT)[1]
			maxIndex = step
			print(maxIndex,maxLength,maxSum)
		step = nextprime(step)
	return (maxIndex,maxLength,maxSum)

def _inv_totient_estimate(m):
    """
    Find ``(L, U)`` such that ``L <= phi^-1(m) <= U``.

    Examples
    ========

    >>> from sympy.polys.polyroots import _inv_totient_estimate

    >>> _inv_totient_estimate(192)
    (192, 840)
    >>> _inv_totient_estimate(400)
    (400, 1750)

    """
    primes = [ d + 1 for d in divisors(m) if isprime(d + 1) ]

    a, b = 1, 1

    for p in primes:
        a *= p
        b *= p - 1

    L = m
    U = int(math.ceil(m*(float(a)/b)))

    P = p = 2
    primes = []

    while P <= U:
        p = nextprime(p)
        primes.append(p)
        P *= p

    P //= p
    b = 1

    for p in primes[:-1]:
        b *= p - 1

    U = int(math.ceil(m*(float(P)/b)))

    return L, U

def test_generate():
    assert nextprime(-4) == 2
    assert nextprime(2) == 3
    assert nextprime(5) == 7
    assert nextprime(12) == 13
    assert nextprime(90) == 97
    assert nextprime(10**40) == (10**40 + 121)
    assert prevprime(3) == 2
    assert prevprime(7) == 5
    assert prevprime(13) == 11
    assert prevprime(97) == 89
    assert prevprime(10**40) == (10**40 - 17)
    assert list(primerange(2, 7)) == [2, 3, 5]
    assert list(primerange(2, 10)) == [2, 3, 5, 7]
    assert list(primerange(1050, 1100)) == [1051, 1061,
        1063, 1069, 1087, 1091, 1093, 1097]
    s = Sieve()
    for i in range(30, 2350, 376):
        for j in range(2, 5096, 1139):
            A = list(s.primerange(i, i + j))
            B = list(primerange(i, i + j))
            assert A == B
    s = Sieve()
    assert s[10] == 29

    assert nextprime(2, 2) == 5

    raises(ValueError, lambda: totient(0))

    raises(ValueError, lambda: reduced_totient(0))

    raises(ValueError, lambda: primorial(0))

    assert mr(1, [2]) is False

    func = lambda i: (i**2 + 1) % 51
    assert next(cycle_length(func, 4)) == (6, 2)
    assert list(cycle_length(func, 4, values=True)) == \
        [17, 35, 2, 5, 26, 14, 44, 50, 2, 5, 26, 14]
    assert next(cycle_length(func, 4, nmax=5)) == (5, None)
    assert list(cycle_length(func, 4, nmax=5, values=True)) == \
        [17, 35, 2, 5, 26]

def swinnerton_dyer_poly(n, x=None, polys=False):
    """Generates n-th Swinnerton-Dyer polynomial in `x`.

    Parameters
    ----------
    n : int
        `n` decides the order of polynomial
    x : optional
    polys : bool, optional
        ``polys=True`` returns an expression, otherwise
        (default) returns an expression.
    """
    from .numberfields import minimal_polynomial
    if n <= 0:
        raise ValueError(
            "can't generate Swinnerton-Dyer polynomial of order %s" % n)

    if x is not None:
        sympify(x)
    else:
        x = Dummy('x')

    if n > 3:
        p = 2
        a = [sqrt(2)]
        for i in range(2, n + 1):
            p = nextprime(p)
            a.append(sqrt(p))
        return minimal_polynomial(Add(*a), x, polys=args.get('polys', False))

    if n == 1:
        ex = x**2 - 2
    elif n == 2:
        ex = x**4 - 10*x**2 + 1
    elif n == 3:
        ex = x**8 - 40*x**6 + 352*x**4 - 960*x**2 + 576

    return PurePoly(ex, x) if polys else ex

def dmp_zz_wang(f, u, K, **args):
    """Factor primitive square-free polynomials in `Z[X]`.

       Given a multivariate polynomial `f` in `Z[x_1,...,x_n]`, which
       is primitive and square-free in `x_1`, computes factorization
       of `f` into irreducibles over integers.

       The procedure is based on Wang's Enhanced Extended Zassenhaus
       algorithm. The algorithm works by viewing `f` as a univariate
       polynomial in `Z[x_2,...,x_n][x_1]`, for which an evaluation
       mapping is computed::

                         x_2 -> a_2, ..., x_n -> a_n

       where `a_i`, for `i = 2, ..., n`, are carefully chosen integers.
       The mapping is used to transform `f` into a univariate polynomial
       in `Z[x_1]`, which can be factored efficiently using Zassenhaus
       algorithm. The last step is to lift univariate factors to obtain
       true multivariate factors. For this purpose a parallel Hensel
       lifting procedure is used.

       References
       ==========

       .. [Wang78] P. S. Wang, An Improved Multivariate Polynomial Factoring
           Algorithm, Math. of Computation 32, 1978, pp. 1215--1231

       .. [Geddes92] K. Geddes, S. R. Czapor, G. Labahn, Algorithms for
           Computer Algebra, Springer, 1992, pp. 264--272
    """
    ct, T = dmp_zz_factor(dmp_LC(f, K), u-1, K)

    b = dmp_zz_mignotte_bound(f, u, K)
    p = K(nextprime(b))

    eez_mod = args.get('mod', None)

    if eez_mod is None:
        if u == 1:
            eez_mod = 2
        else:
            eez_mod = 1

    history, configs, A, r = set([]), [], [K.zero]*u, None

    try:
        cs, s, E = dmp_zz_wang_test_points(f, T, ct, A, u, K)

        _, H = dup_zz_factor_sqf(s, K)

        r = len(H)

        if r == 1:
            return [f]

        bad_points = set([tuple(A)])
        configs = [(s, cs, E, H, A)]
    except EvaluationFailed:
        pass

    while len(configs) < EEZ_NUM_OK:
        for _ in xrange(EEZ_NUM_TRY):
            A = [ K(randint(-eez_mod, eez_mod)) for _ in xrange(u) ]

            if tuple(A) not in history:
                history.add(tuple(A))
            else:
                continue

            try:
                cs, s, E = dmp_zz_wang_test_points(f, T, ct, A, u, K)
            except EvaluationFailed:
                continue

            _, H = dup_zz_factor_sqf(s, K)

            rr = len(H)

            if r is not None:
                if rr != r: # pragma: no cover
                    if rr < r:
                        configs, r = [], rr
                    else:
                        continue
            else:
                r = rr

            if r == 1:
                return [f]

            configs.append((s, cs, E, H, A))

            if len(configs) == EEZ_NUM_OK:
                break
        else:
            eez_mod += EEZ_MOD_STEP

    s_norm, s_arg, i = None, 0, 0

    for s, _, _, _, _ in configs:
#.........这里部分代码省略.........