def register(self, divisor, isprime=Unknown):
"""
Register a divisor of the number, if the divisor is a true
divisor of the number. The number is divided by the divisor
as many times as possible.
"""
for base, index in self.factors:
if base == divisor:
if isprime and not self.primality[base]:
self.setPrimality(base, isprime)
break
common_divisor = gcd.gcd(base, divisor)
if common_divisor == 1:
continue
# common_divisor > 1:
if common_divisor == divisor:
if isprime:
self.setPrimality(divisor, isprime)
k, coprime = arith1.vp(base, common_divisor)
while not gcd.coprime(common_divisor, coprime):
# try a smaller factor
common_divisor = gcd.gcd(common_divisor, coprime)
k, coprime = arith1.vp(base, common_divisor)
if k:
if coprime > 1:
self.replace(base, [(common_divisor, k), (coprime, 1)])
else:
self.replace(base, [(common_divisor, k)])
else: # common_divisor properly divides divisor.
self.register(common_divisor)
self.register(divisor // common_divisor)
def rhomethod(n, **options):
"""
Find a non-trivial factor of n using Pollard's rho algorithm.
The implementation refers the explanation in C.Pomerance's book.
"""
# verbosity
verbose = options.get('verbose', False)
if not verbose:
_silence()
if n <= 3:
return 1
g = n
while g == n:
# x^2 + a is iterated. Starting value x = u.
a = bigrandom.randrange(1, n - 2)
u = v = bigrandom.randrange(0, n - 1)
_log.info("%d %d" % (a, u))
g = gcd.gcd((v**2 + v + a) % n - u, n)
while g == 1:
u = (u**2 + a) % n
v = ((pow(v, 2, n) + a)**2 + a) % n
g = gcd.gcd(v - u, n)
if not verbose:
_verbose()
return g
def rhomethod(n, **options):
"""
Find a non-trivial factor of n using Pollard's rho algorithm.
The implementation refers the explanation in C.Pomerance's book.
"""
# verbosity
verbose = options.get('verbose', False)
if not verbose:
_silence()
if n <= 3:
return 1
g = n
while g == n:
a = bigrandom.randrange(1, n-2)
u = v = bigrandom.randrange(0, n-1)
_log.info("%d %d" % (a, u))
g = gcd.gcd((v**2 + v + a) % n - u, n)
while g == 1:
u = (u**2 + a) % n
v = ((pow(v, 2, n) + a)**2 + a) % n
g = gcd.gcd(v - u, n)
if not verbose:
_verbose()
return g
def register(self, divisor, isprime=Unknown):
"""
Register a divisor of the number, if the divisor is a true
divisor of the number. The number is divided by the divisor
as many times as possible.
"""
for base, index in self.factors:
if base == divisor:
if isprime and not self.primality[base]:
self.setPrimality(base, isprime)
break
common_divisor = gcd.gcd(base, divisor)
if common_divisor == 1:
continue
# common_divisor > 1:
if common_divisor == divisor:
if isprime:
self.setPrimality(divisor, isprime)
k, coprime = arith1.vp(base, common_divisor)
while not gcd.coprime(common_divisor, coprime):
# try a smaller factor
common_divisor = gcd.gcd(common_divisor, coprime)
k, coprime = arith1.vp(base, common_divisor)
if k:
if coprime > 1:
self.replace(base, [(common_divisor, k), (coprime, 1)])
else:
self.replace(base, [(common_divisor, k)])
else: # common_divisor properly divides divisor.
self.register(common_divisor)
self.register(divisor // common_divisor)
def aks(n):
"""
AKS ( Cyclotomic Congruence Test ) primality test for a natural number.
Input: a natural number n ( n > 1 ).
Output: n is prime => return True
n is not prime => return False.
"""
import nzmath.multiplicative as multiplicative
if arith1.powerDetection(n)[1] != 1: #Power Detection
return False
lg = math.log(n, 2)
k = int(lg * lg)
start = 3
while 1:
d = gcd.gcd(start, n)
if 1 < d < n:
return False
x = n % start
N = x
for i in range(1, k + 1):
if N == 1:
break
N = (N * x) % start
if i == k:
r = start
break
start += 1
d = gcd.gcd(r, n)
if 1 < d < n:
return False
if n <= r:
return True
e = multiplicative.euler(r) #Cyclotomic Conguence
e = math.sqrt(e)
e = int(e * lg)
for b in range(1, e + 1):
f = array_poly.ArrayPolyMod([b, 1], n)
total = array_poly.ArrayPolyMod([1], n)
count = n
while count > 0:
if count & 1:
total = total * f
total = _aks_mod(total, r)
f = f.power()
f = _aks_mod(f, r)
count = count >> 1
total_poly = total.coefficients_to_dict()
if total_poly != {0: b, n % r: 1}:
return False
return True
def pmom(n, **options):
"""
This function tries to find a non-trivial factor of n using
Algorithm 8.8.2 (p-1 first stage) of Cohen's book.
In case of N = pow(2,i), this program will not terminate.
"""
# verbosity
verbose = options.get('verbose', False)
if not verbose:
_silence()
# initialize
x = y = 2
primes = []
if 'B' in options:
B = options['B']
else:
B = 10000
for q in prime.generator():
primes.append(q)
if q > B:
if gcd.gcd(x - 1, n) == 1:
if not verbose:
_verbose()
return 1
x = y
break
q1 = q
l = B // q
while q1 <= l:
q1 *= q
x = pow(x, q1, n)
if len(primes) >= 20:
if gcd.gcd(x - 1, n) == 1:
primes, y = [], x
else:
x = y
break
for q in primes:
q1 = q
while q1 <= B:
x = pow(x, q, n)
g = gcd.gcd(x - 1, n)
if g != 1:
if not verbose:
_verbose()
if g == n:
return 1
return g
q1 *= q
def pmom(n, **options):
"""
This function tries to find a non-trivial factor of n using
Algorithm 8.8.2 (p-1 first stage) of Cohen's book.
In case of N = pow(2,i), this program will not terminate.
"""
# verbosity
verbose = options.get('verbose', False)
if not verbose:
_silence()
# initialize
x , B = 2 , 10000001
y = x
primes = []
for q in prime.generator():
primes.append(q)
if q > B:
if gcd.gcd(x-1, n) == 1:
if not verbose:
_verbose()
return 1
x = y
break
q1 = q
l = B//q
while q1 <= l:
q1 *= q
x = pow(x, q1, n)
if len(primes) >= 20:
if gcd.gcd(x-1, n) == 1:
primes, y = [], x
else:
x = y
break
for q in primes:
q1 = q
while q1 <= B:
x = pow(x, q, n)
g = gcd.gcd(x-1, n)
if g != 1:
if not verbose:
_verbose()
if g == n:
return 1
return g
q1 *= q
def sub8(self, q, k, n, J):
s = J.get(3, q)
J3 = J.get(3, q)
m = len(s)
sx_z = {1: s}
x = 3
step = 2
while m > x:
z_4b = Zeta(m)
i = x
j = 1
while i != 0:
z_4b[j] = J3[i]
i = (i + x) % m
j += 1
z_4b[0] = J3[0]
sx_z[x] = z_4b
s = pow(sx_z[x], x, n) * s
step = 8 - step
x += step
s = pow(s, n // m, n)
r = n % m
step = 2
x = 3
while m > x:
c = r * x
if c > m:
s = pow(sx_z[x], c // m, n) * s
step = 8 - step
x += step
r = r & 7
if r == 5 or r == 7:
s = J.get(2, q).promote(m) * s
s = +(s % n)
if s.weight() == 1 and s.mass() == 1:
if gcd.gcd(m, s.z.index(1)) == 1 and pow(q,
(n - 1) >> 1, n) == n - 1:
self.done(2)
return True
elif s.weight() == 1 and s.mass() == n - 1:
if gcd.gcd(m, s.z.index(n - 1)) == 1 and pow(q, (n - 1) >> 1,
n) == n - 1:
self.done(2)
return True
return False
def dumas(target, p):
"""
Return True if target is irreducible, False if reducible
or None if undecidable.
Dumas's criterion is the following. Let f = \sum a_i X^i be a
integer coefficient polynomial with degree n, and p be a prime
number. f is irreducible if
(I) gcd(n, v(a_n) - v(a_0)) == 1
(where v(m) denotes the number e that p**e divide m but
p**(e+1) doesn't)
(II) for any i (0 < i < n), (i, v(a_i)) is above the line connecting
(0, v(a_0)) and (n, v(a_n)).
This criterion includes Eisenstein's case.
"""
segments = dict((d, arith1.vp(c, p=p)[0]) for (d, c) in target)
# (I)
degree = target.degree()
if abs(gcd.gcd(degree, segments[degree] - segments[0])) != 1:
return None
# (II)
#(segments[degree] - segments[0]) / degree * x + segment[0] < segments[x]
slope = segments[degree] - segments[0]
if all(slope * x <= degree * (v - segments[0])
for x, v in segments.iteritems()):
return True
# the criterion doesn't work
return None
def primePowerTest(n):
"""
This program using Algo. 1.7.5 in Cohen's book judges whether
n is of the form p**k with prime p or not.
If it is True, then (p,k) will be returned,
otherwise (n,0).
"""
if n % 2 == 1:
q = n
while True:
if not prime.primeq(q):
a = 2
while prime.spsp(n, a):
a += 1
d = gcd.gcd(pow(a,q,q) - a, q)
if d == 1 or d == q:
return (n, 0)
else:
q = d
else:
p = q
break
else:
p = 2
k, q = arith1.vp(n, p)
if q == 1:
return (p, k)
else:
return (n, 0)
def change_base_module(self, other_base):
"""
change base_module to other_base_module
(i.e. represent with respect to base_module)
"""
if self.base == other_base:
return self
n = self.number_field.degree
if isinstance(other_base, list):
other_base = matrix.FieldSquareMatrix(n,
[vector.Vector(other_base[i]) for i in range(n)])
else: # matrix repr
other_base = other_base.copy()
tr_base_mat, tr_base_denom = _toIntegerMatrix(
other_base.inverse(self.base))
denom = tr_base_denom * self.denominator
mat_repr, numer = _toIntegerMatrix(
tr_base_mat * self.mat_repr, 2)
d = gcd.gcd(denom, numer)
if d != 1:
denom = ring.exact_division(denom, d)
numer = ring.exact_division(numer, d)
if numer != 1:
mat_repr = numer * mat_repr
return self.__class__([mat_repr, denom], self.number_field, other_base)
def primePowerTest(n):
"""
This program using Algo. 1.7.5 in Cohen's book judges whether
n is of the form p**k with prime p or not.
If it is True, then (p,k) will be returned,
otherwise (n,0).
"""
if n & 1:
q = n
while True:
if not prime.primeq(q):
a = 2
while prime.spsp(n, a):
a += 1
d = gcd.gcd(pow(a,q,q) - a, q)
if d == 1 or d == q:
return (n, 0)
q = d
else:
p = q
break
else:
p = 2
k, q = arith1.vp(n, p)
if q == 1:
return (p, k)
else:
return (n, 0)
def to_HNFRepresentation(self):
"""
Transform self to the corresponding ideal as HNF representation
"""
int_ring = self.number_field.integer_ring()
n = self.number_field.degree
polynomial = self.number_field.polynomial
k = len(self.generator)
# separate coeff and denom for generators and base
gen_denom = reduce( gcd.lcm,
(self.generator[j].denom for j in range(k)) )
gen_list = [gen_denom * self.generator[j] for j in range(k)]
base_int, base_denom = _toIntegerMatrix(int_ring)
base_alg = [BasicAlgNumber([base_int[j], 1],
polynomial) for j in range(1, n + 1)]
repr_mat_list = []
for gen in gen_list:
for base in base_alg:
new_gen = gen * base
repr_mat_list.append(
vector.Vector([new_gen.coeff[j] for j in range(n)]))
mat_repr = matrix.RingMatrix(n, n * k, repr_mat_list)
new_mat_repr, numer = _toIntegerMatrix(mat_repr, 2)
denom = gen_denom * base_denom
denom_gcd = gcd.gcd(numer, denom)
if denom_gcd != 1:
denom = ring.exact_division(denom, denom_gcd)
numer = ring.exact_division(numer, denom_gcd)
if numer != 1:
new_mat_repr = numer * new_mat_repr
else:
new_mat_repr = mat_repr
return Ideal([new_mat_repr, denom], self.number_field)
def qs(n, s, f):
"""
This is main function of QS
Arguments are (composite_number, sieve_range, factorbase_size)
You must input these 3 arguments.
"""
a = time.time()
Q = QS(n, s, f)
_log.info("Sieve range is [ %d , %d ] , Factorbase size = %d , Max Factorbase %d" % (Q.move_range[0], Q.move_range[-1], len(Q.FB), Q.maxFB))
Q.run_sieve()
V = Elimination(Q.smooth)
A = V.gaussian()
_log.info("Found %d linearly dependent relations" % len(A))
answerX_Y = []
N_factors = []
for i in A:
B = V.history[i].keys()
X = 1
Y = 1
for j in B:
X *= Q.smooth[j][1][0]
Y *= Q.smooth[j][1][1]
Y = Y % Q.number
X = sqrt_modn(X, Q.number)
answerX_Y.append(X-Y)
for k in answerX_Y:
if k != 0:
factor = gcd.gcd(k, Q.number)
if factor not in N_factors and factor != 1 and \
factor != Q.number and prime.primeq(factor) == 1:
N_factors.append(factor)
N_factors.sort()
_log.info("Total time = %f sec" % (time.time()-a))
_log.info(str(N_factors))
def change_base_module(self, other_base):
"""
change base_module to other_base_module
(i.e. represent with respect to base_module)
"""
if self.base == other_base:
return self
n = self.number_field.degree
if isinstance(other_base, list):
other_base = matrix.FieldSquareMatrix(n,
[vector.Vector(other_base[i]) for i in range(n)])
else: # matrix repr
other_base = other_base.copy()
tr_base_mat, tr_base_denom = _toIntegerMatrix(
other_base.inverse(self.base))
denom = tr_base_denom * self.denominator
mat_repr, numer = _toIntegerMatrix(
tr_base_mat * self.mat_repr, 2)
d = gcd.gcd(denom, numer)
if d != 1:
denom = ring.exact_division(denom, d)
numer = ring.exact_division(numer, d)
if numer != 1:
mat_repr = numer * mat_repr
return self.__class__([mat_repr, denom], self.number_field, other_base)
def to_HNFRepresentation(self):
"""
Transform self to the corresponding ideal as HNF representation
"""
int_ring = self.number_field.integer_ring()
n = self.number_field.degree
polynomial = self.number_field.polynomial
k = len(self.generator)
# separate coeff and denom for generators and base
gen_denom = reduce( gcd.lcm,
(self.generator[j].denom for j in range(k)) )
gen_list = [gen_denom * self.generator[j] for j in range(k)]
base_int, base_denom = _toIntegerMatrix(int_ring)
base_alg = [BasicAlgNumber([base_int[j], 1],
polynomial) for j in range(1, n + 1)]
repr_mat_list = []
for gen in gen_list:
for base in base_alg:
new_gen = gen * base
repr_mat_list.append(
vector.Vector([new_gen.coeff[j] for j in range(n)]))
mat_repr = matrix.RingMatrix(n, n * k, repr_mat_list)
new_mat_repr, numer = _toIntegerMatrix(mat_repr, 2)
denom = gen_denom * base_denom
denom_gcd = gcd.gcd(numer, denom)
if denom_gcd != 1:
denom = ring.exact_division(denom, denom_gcd)
numer = ring.exact_division(numer, denom_gcd)
if numer != 1:
new_mat_repr = numer * new_mat_repr
else:
new_mat_repr = mat_repr
return Ideal([new_mat_repr, denom], self.number_field)
def get_random_curve_with_point(cls, curve_type, n, bounds):
"""
Return the curve with parameter C and a point Q on the curve,
according to the curve_type, factorization target n and the
bounds for stages.
curve_type should be one of the module constants corresponding
to parameters:
S: Suyama's parameter selection strategy
B: Bernstein's [2:1], [16,18,4,2]
A1: Asuncion's [2:1], [4,14,1,1]
A2: Asuncion's [2:1], [16,174,4,41]
A3: Asuncion's [3:1], [9,48,1,2]
A4: Asuncion's [3:1], [9,39,1,1]
A5: Asuncion's [4:1], [16,84,1,1]
N3: Nakamura's [2:1], [28,22,7,3]
This is a class method.
"""
bound = bounds.first
if curve_type not in cls._CURVE_TYPES:
raise ValueError("Input curve_type is wrong.")
if curve_type == SUYAMA:
t = n
while _gcd.gcd(t, n) != 1:
sigma = random.randrange(6, bound + 1)
u, v = (sigma**2 - 5) % n, (4 * sigma) % n
t = 4 * (u**3) * v
d = _arith1.inverse(t, n)
curve = cls((((u - v)**3 * (3 * u + v)) * d - 2) % n)
start_point = Point(pow(u, 3, n), pow(v, 3, n))
elif curve_type == BERNSTEIN:
d = random.randrange(1, bound + 1)
start_point = Point(2, 1)
curve = cls((4 * d + 2) % n)
elif curve_type == ASUNCION1:
d = random.randrange(1, bound + 1)
start_point = Point(2, 1)
curve = cls((d + 1) % n)
elif curve_type == ASUNCION2:
d = random.randrange(1, bound + 1)
start_point = Point(2, 1)
curve = cls((4 * d + 41) % n)
elif curve_type == ASUNCION3:
d = random.randrange(1, bound + 1)
start_point = Point(3, 1)
curve = cls((d + 2) % n)
elif curve_type == ASUNCION4:
d = random.randrange(1, bound + 1)
start_point = Point(3, 1)
curve = cls((d + 1) % n)
elif curve_type == ASUNCION5:
d = random.randrange(1, bound + 1)
start_point = Point(4, 1)
curve = cls((d + 1) % n)
elif curve_type == NAKAMURA3:
d = random.randrange(1, bound + 1)
start_point = Point(2, 1)
curve = cls((7 * d + 3) % n)
return curve, start_point
def sub8(self, q, k, n, J):
s = J.get(3, q)
J3 = J.get(3, q)
m = len(s)
sx_z = {1:s}
x = 3
step = 2
while m > x:
z_4b = Zeta(m)
i = x
j = 1
while i != 0:
z_4b[j] = J3[i]
i = (i + x) % m
j += 1
z_4b[0] = J3[0]
sx_z[x] = z_4b
s = pow(sx_z[x], x, n) * s
step = 8 - step
x += step
s = pow(s, n//m, n)
r = n % m
step = 2
x = 3
while m > x:
c = r*x
if c > m:
s = pow(sx_z[x], c//m, n) * s
step = 8 - step
x += step
r = r % 8
if r == 5 or r == 7:
s = J.get(2, q).promote(m) * s
s = +(s % n)
if s.weight() == 1 and s.mass() == 1:
if gcd.gcd(m, s.z.index(1)) == 1 and pow(q, (n-1)//2, n) == n-1:
self.done(2)
return True
elif s.weight() == 1 and s.mass() == n-1:
if gcd.gcd(m, s.z.index(n-1)) == 1 and pow(q, (n-1)//2, n) == n-1:
self.done(2)
return True
return False
def ecm(n, curve_type=A1, incs=3, trials=20, **options):
"""
Find a factor of n with Elliptic Curve Method.
An unsuccessful factorization returns 1.
There are a few optional arguments.
By 'curve_type', the function choose a family of curves.
Please use a module constant to specify the curve_type.
The second optional argument 'incs' specifies the number of times
for changing bounds. The function repeats factorization trials
several times changing curves with a fixed bounds.
The last optional argument 'trials' can control how quickly move
on to the next higher bounds.
"""
# verbosity
verbose = options.get('verbose', False)
if verbose:
_log.setLevel(logging.DEBUG)
_log.debug("verbose")
else:
_log.setLevel(logging.NOTSET)
# trivial checks
if _prime.primeq(n):
_log.info("%d is prime!" % n)
return n
if _gcd.gcd(n, 6) != 1:
_log.info("%d is not coprime to 6!" % n)
if n % 2 == 0:
return 2
if n % 3 == 0:
return 3
# main loop
bounds = Bounds(n)
for inc in range(incs):
_log.info("bounds increment %d times" % inc)
_log.debug("Bounds B1, B2 = %s" % (bounds, ))
for trial in range(trials):
_log.info("Trial #: %d" % (trial + 1))
curve, point = Curve.get_random_curve_with_point(
curve_type, n, bounds)
_log.debug("Curve param: %d" % curve.c)
g = stage1(n, bounds, curve, point)
if 1 < g < n:
return g
g = stage2(n, bounds, curve, point)
if 1 < g < n:
return g
bounds.increment()
_log.info("ECM 2 step test failed!")
if not verbose:
_log.setLevel(logging.DEBUG)
return 1
def ecm(n, curve_type=A1, incs=3, trials=20, **options):
"""
Find a factor of n with Elliptic Curve Method.
An unsuccessful factorization returns 1.
There are a few optional arguments.
By 'curve_type', the function choose a family of curves.
Please use a module constant to specify the curve_type.
The second optional argument 'incs' specifies the number of times
for changing bounds. The function repeats factorization trials
several times changing curves with a fixed bounds.
The last optional argument 'trials' can control how quickly move
on to the next higher bounds.
"""
# verbosity
verbose = options.get('verbose', False)
if verbose:
_log.setLevel(logging.DEBUG)
_log.debug("verbose")
else:
_log.setLevel(logging.NOTSET)
# trivial checks
if _prime.primeq(n):
_log.info("%d is prime!" % n)
return n
if _gcd.gcd(n, 6) != 1:
_log.info("%d is not coprime to 6!" % n)
if n % 2 == 0:
return 2
if n % 3 == 0:
return 3
# main loop
bounds = Bounds(n)
for inc in range(incs):
_log.info("bounds increment %d times" % inc)
_log.debug("Bounds B1, B2 = %s" % (bounds,))
for trial in range(trials):
_log.info("Trial #: %d" % (trial + 1))
curve, point = Curve.get_random_curve_with_point(curve_type, n, bounds)
_log.debug("Curve param: %d" % curve.c)
g = stage1(n, bounds, curve, point)
if 1 < g < n:
return g
g = stage2(n, bounds, curve, point)
if 1 < g < n:
return g
bounds.increment()
_log.info("ECM 2 step test failed!")
if not verbose:
_log.setLevel(logging.DEBUG)
return 1
def twoElementRepresentation(self):
# refer to [Poh-Zas]
# Algorithm 4.7.10 and Exercise 29 in CCANT
"""
Reduce the number of generator to only two elements
Warning: If self is not a prime ideal, this method is not efficient
"""
k = len(self.generator)
gen_denom = reduce( gcd.lcm,
(self.generator[j].denom for j in range(k)) )
gen_list = [gen_denom * self.generator[j] for j in range(k)]
int_I = Ideal_with_generator(gen_list)
R = 1
norm_I = int_I.norm()
l_I = int_I.smallest_rational()
if l_I.denominator > 1:
raise ValueError, "input an integral ideal"
else:
l_I = l_I.numerator
while True:
lmda = [R for i in range(k)]
while lmda[0] > 0:
alpha = lmda[0] * gen_list[0]
for i in range(1, k):
alpha += lmda[i] * gen_list[i]
if gcd.gcd(
norm_I, ring.exact_division(
alpha.norm(), norm_I)
) == 1 or gcd.gcd(
norm_I, ring.exact_division(
(alpha + l_I).norm(), norm_I)) == 1:
l_I_ori = BasicAlgNumber(
[[l_I] + [0] * (self.number_field.degree - 1),
gen_denom], self.number_field.polynomial)
alpha_ori = BasicAlgNumber([alpha.coeff,
gen_denom], self.number_field.polynomial)
return Ideal_with_generator([l_I_ori, alpha_ori])
for j in range(k)[::-1]:
if lmda[j] != -R:
lmda[j] -= 1
break
else:
lmda[j] = R
R += 1
def twoElementRepresentation(self):
# refer to [Poh-Zas]
# Algorithm 4.7.10 and Exercise 29 in CCANT
"""
Reduce the number of generator to only two elements
Warning: If self is not a prime ideal, this method is not efficient
"""
k = len(self.generator)
gen_denom = reduce(gcd.lcm,
(self.generator[j].denom for j in range(k)))
gen_list = [gen_denom * self.generator[j] for j in range(k)]
int_I = Ideal_with_generator(gen_list)
R = 1
norm_I = int_I.norm()
l_I = int_I.smallest_rational()
if l_I.denominator > 1:
raise ValueError, "input an integral ideal"
else:
l_I = l_I.numerator
while True:
lmda = [R for i in range(k)]
while lmda[0] > 0:
alpha = lmda[0] * gen_list[0]
for i in range(1, k):
alpha += lmda[i] * gen_list[i]
if gcd.gcd(norm_I, ring.exact_division(
alpha.norm(), norm_I)) == 1 or gcd.gcd(
norm_I,
ring.exact_division(
(alpha + l_I).norm(), norm_I)) == 1:
l_I_ori = BasicAlgNumber(
[[l_I] + [0] *
(self.number_field.degree - 1), gen_denom],
self.number_field.polynomial)
alpha_ori = BasicAlgNumber([alpha.coeff, gen_denom],
self.number_field.polynomial)
return Ideal_with_generator([l_I_ori, alpha_ori])
for j in range(k)[::-1]:
if lmda[j] != -R:
lmda[j] -= 1
break
else:
lmda[j] = R
R += 1
def _simplify(self):
"""
simplify self.denominator
"""
mat_repr, numer = _toIntegerMatrix(self.mat_repr, 2)
denom_gcd = gcd.gcd(numer, self.denominator)
if denom_gcd != 1:
self.denominator = ring.exact_division(self.denominator, denom_gcd)
self.mat_repr = Submodule.fromMatrix(
ring.exact_division(numer, denom_gcd) * mat_repr)
def _simplify(self):
"""
simplify self.denominator
"""
mat_repr, numer = _toIntegerMatrix(self.mat_repr, 2)
denom_gcd = gcd.gcd(numer, self.denominator)
if denom_gcd != 1:
self.denominator = ring.exact_division(self.denominator, denom_gcd)
self.mat_repr = Submodule.fromMatrix(
ring.exact_division(numer, denom_gcd) * mat_repr)
def get_random_curve_with_point(cls, curve_type, n, bounds):
"""
Return the curve with parameter C and a point Q on the curve,
according to the curve_type, factorization target n and the
bounds for stages.
curve_type should be one of the module constants corresponding
to parameters:
S: Suyama's parameter selection strategy
B: Bernstein's [2:1], [16,18,4,2]
A1: Asuncion's [2:1], [4,14,1,1]
A2: Asuncion's [2:1], [16,174,4,41]
A3: Asuncion's [3:1], [9,48,1,2]
A4: Asuncion's [3:1], [9,39,1,1]
A5: Asuncion's [4:1], [16,84,1,1]
This is a class method.
"""
bound = bounds.first
if curve_type not in cls._CURVE_TYPES:
raise ValueError("Input curve_type is wrong.")
if curve_type == SUYAMA:
t = n
while _gcd.gcd(t, n) != 1:
sigma = random.randrange(6, bound + 1)
u, v = (sigma**2 - 5) % n, (4*sigma) % n
t = 4*(u**3)*v
d = _arith1.inverse(t, n)
curve = cls((((u - v)**3 * (3*u + v)) * d - 2) % n)
start_point = Point(pow(u, 3, n), pow(v, 3, n))
elif curve_type == BERNSTEIN:
d = random.randrange(1, bound + 1)
start_point = Point(2, 1)
curve = cls((4*d + 2) % n)
elif curve_type == ASUNCION1:
d = random.randrange(1, bound + 1)
start_point = Point(2, 1)
curve = cls((d + 1) % n)
elif curve_type == ASUNCION2:
d = random.randrange(1, bound + 1)
start_point = Point(2, 1)
curve = cls((4*d + 41) % n)
elif curve_type == ASUNCION3:
d = random.randrange(1, bound + 1)
start_point = Point(3, 1)
curve = cls((d + 2) % n)
elif curve_type == ASUNCION4:
d = random.randrange(1, bound + 1)
start_point = Point(3, 1)
curve = cls((d + 1) % n)
elif curve_type == ASUNCION5:
d = random.randrange(1, bound + 1)
start_point = Point(4, 1)
curve = cls((d + 1) % n)
return curve, start_point
def bigprimeq(z):
"""
Giving up rigorous proof of primality, return True for a probable
prime.
"""
if int(z) != z:
raise ValueError("non-integer for primeq()")
elif z <= 1:
return False
elif gcd.gcd(z, PRIMONIAL_31) > 1:
return (z in PRIMES_LE_31)
return millerRabin(z)
def bigprimeq(z):
"""
Giving up rigorous proof of primality, return True for a probable
prime.
"""
if int(z) != z:
raise ValueError("non-integer for primeq()")
elif z <= 1:
return False
elif gcd.gcd(z, 510510) > 1:
return (z in (2, 3, 5, 7, 11, 13, 17))
return millerRabin(z)
def _toIntegerMatrix(mat, option=0):
"""
transform a (including integral) rational matrix to
some integral matrix as the following
[option]
0: return integral-matrix, denominator
(mat = 1/denominator * integral-matrix)
1: return integral-matrix, denominator, numerator
(mat = numerator/denominator * reduced-int-matrix)
2: return integral-matrix, numerator (assuming mat is integral)
(mat = numerator * numerator-reduced-rational-matrix)
"""
def getDenominator(ele):
"""
get the denominator of ele
"""
if rational.isIntegerObject(ele):
return 1
else: # rational
return ele.denominator
def getNumerator(ele):
"""
get the numerator of ele
"""
if rational.isIntegerObject(ele):
return ele
else: # rational
return ele.numerator
if isinstance(mat, vector.Vector):
mat = mat.toMatrix(True)
if option <= 1:
denom = mat.reduce(
lambda x, y: gcd.lcm(x, getDenominator(y)), 1)
new_mat = mat.map(
lambda x: getNumerator(x) * ring.exact_division(
denom, getDenominator(x)))
if option == 0:
return Submodule.fromMatrix(new_mat), denom
else:
new_mat = mat
numer = new_mat.reduce(
lambda x, y: gcd.gcd(x, getNumerator(y)))
if numer != 0:
new_mat2 = new_mat.map(
lambda x: ring.exact_division(getNumerator(x), numer))
else:
new_mat2 = new_mat
if option == 1:
return Submodule.fromMatrix(new_mat2), denom, numer
else:
return Submodule.fromMatrix(new_mat2), numer
def _toIntegerMatrix(mat, option=0):
"""
transform a (including integral) rational matrix to
some integral matrix as the following
[option]
0: return integral-matrix, denominator
(mat = 1/denominator * integral-matrix)
1: return integral-matrix, denominator, numerator
(mat = numerator/denominator * reduced-int-matrix)
2: return integral-matrix, numerator (assuming mat is integral)
(mat = numerator * numerator-reduced-rational-matrix)
"""
def getDenominator(ele):
"""
get the denominator of ele
"""
if rational.isIntegerObject(ele):
return 1
else: # rational
return ele.denominator
def getNumerator(ele):
"""
get the numerator of ele
"""
if rational.isIntegerObject(ele):
return ele
else: # rational
return ele.numerator
if isinstance(mat, vector.Vector):
mat = mat.toMatrix(True)
if option <= 1:
denom = mat.reduce(
lambda x, y: gcd.lcm(x, getDenominator(y)), 1)
new_mat = mat.map(
lambda x: getNumerator(x) * ring.exact_division(
denom, getDenominator(x)))
if option == 0:
return Submodule.fromMatrix(new_mat), denom
else:
new_mat = mat
numer = new_mat.reduce(
lambda x, y: gcd.gcd(x, getNumerator(y)))
if numer != 0:
new_mat2 = new_mat.map(
lambda x: ring.exact_division(getNumerator(x), numer))
else:
new_mat2 = new_mat
if option == 1:
return Submodule.fromMatrix(new_mat2), denom, numer
else:
return Submodule.fromMatrix(new_mat2), numer
def stage1(n, bounds, C, Q):
"""
ECM stage 1 for factoring n.
The upper bound for primes to be tested is bounds.first.
It uses curve C and starting point Q.
"""
for p in _prime.generator_eratosthenes(bounds.first):
q = p
while q < bounds.first:
Q = mul(Q, p, C, n)
q *= p
g = _gcd.gcd(Q.z, n)
_log.debug("Stage 1: %d" % g)
return g
def stage1(n, bounds, C, Q):
"""
ECM stage 1 for factoring n.
The upper bound for primes to be tested is bounds.first.
It uses curve C and starting point Q.
"""
for p in _prime.generator_eratosthenes(bounds.first):
q = p
while q < bounds.first:
Q = mul(Q, p, C, n)
q *= p
g = _gcd.gcd(Q.z, n)
_log.debug("Stage 1: %d" % g)
return g
def stage2(n, bounds, C, Q):
"""
ECM stage 2 for factoring n.
The upper bounds for primes to be tested are stored in bounds.
It uses curve C and starting point Q.
"""
d1 = bounds.first + random.randrange(1, 16)
d2 = 0
while _gcd.gcd(d1, d2) != 1:
d2 = random.randrange(2, d1//5 + 1) # We want to keep d2 small
for i in range(1, bounds.second//d1):
if _gcd.gcd(i, d2) != 1:
continue
for j in range(1, d1//2):
if _gcd.gcd(j, d1) == 1:
Q = mul(Q, i*d1 + j*d2, C, n)
if i*d1 - j*d2 > bounds.first:
Q = mul(Q, i*d1 - j*d2, C, n)
g = _gcd.gcd(Q.z, n)
if 1 < g < n:
_log.debug("Stage 2: %d" % g)
return g
_log.debug("Stage 2: %d" % g)
return 1
def stage2(n, bounds, C, Q):
"""
ECM stage 2 for factoring n.
The upper bounds for primes to be tested are stored in bounds.
It uses curve C and starting point Q.
"""
d1 = bounds.first + random.randrange(1, 16)
d2 = 0
while _gcd.gcd(d1, d2) != 1:
d2 = random.randrange(2, d1 // 5 + 1) # We want to keep d2 small
for i in range(1, bounds.second // d1):
if _gcd.gcd(i, d2) != 1:
continue
for j in range(1, d1 // 2):
if _gcd.gcd(j, d1) == 1:
Q = mul(Q, i * d1 + j * d2, C, n)
if i * d1 - j * d2 > bounds.first:
Q = mul(Q, i * d1 - j * d2, C, n)
g = _gcd.gcd(Q.z, n)
if 1 < g < n:
_log.debug("Stage 2: %d" % g)
return g
_log.debug("Stage 2: %d" % g)
return 1
def _isprime(n, pdivisors=None):
"""
Return True iff n is prime.
The check is done without APR.
Assume that n is very small (less than 10**12) or
prime factorization of n - 1 is known (prime divisors are passed to
the optional argument pdivisors as a sequence).
"""
if gcd.gcd(n, PRIMONIAL_31) > 1:
return n in PRIMES_LE_31
elif n < 10**12:
# 1369 == 37**2
# 1662803 is the only prime base in smallSpsp which has not checked
return n < 1369 or n == 1662803 or smallSpsp(n)
else:
return full_euler(n, pdivisors)
def subodd(self, p, q, n, J):
"""
Return the sub result for odd key 'p'.
If it is True, the status of 'p' is flipped to 'done'.
"""
s = J.get(1, p, q)
Jpq = J.get(1, p, q)
m = s.size
for x in range(2, m):
if x % p == 0:
continue
sx = Zeta(m)
i = x
j = 1
while i > 0:
sx[j] = Jpq[i]
i = (i + x) % m
j += 1
sx[0] = Jpq[0]
sx = pow(sx, x, n)
s = s*sx % n
s = pow(s, n//m, n)
r = n % m
t = 1
for x in range(1, m):
if x % p == 0:
continue
c = (r*x) // m
if c:
tx = Zeta(m)
i = x
j = 1
while i > 0:
tx[j] = Jpq[i]
i = (i + x) % m
j += 1
tx[0] = Jpq[0]
tx = pow(tx, c, n)
t = t*tx % n
s = +(t*s % n)
if s.weight() == 1 and s.mass() == 1:
for i in range(1, m):
if gcd.gcd(m, s.z.index(1)) == 1:
self.done(p)
return True
return False
def subodd(self, p, q, n, J):
"""
Return the sub result for odd key 'p'.
If it is True, the status of 'p' is flipped to 'done'.
"""
s = J.get(1, p, q)
Jpq = J.get(1, p, q)
m = s.size
for x in range(2, m):
if x % p == 0:
continue
sx = Zeta(m)
i = x
j = 1
while i > 0:
sx[j] = Jpq[i]
i = (i + x) % m
j += 1
sx[0] = Jpq[0]
sx = pow(sx, x, n)
s = s * sx % n
s = pow(s, n // m, n)
r = n % m
t = 1
for x in range(1, m):
if x % p == 0:
continue
c = (r * x) // m
if c:
tx = Zeta(m)
i = x
j = 1
while i > 0:
tx[j] = Jpq[i]
i = (i + x) % m
j += 1
tx[0] = Jpq[0]
tx = pow(tx, c, n)
t = t * tx % n
s = +(t * s % n)
if s.weight() == 1 and s.mass() == 1:
for i in range(1, m):
if gcd.gcd(m, s.z.index(1)) == 1:
self.done(p)
return True
return False
def __init__(self, valuelist, polynomial, precompute=False):
if len(polynomial) != len(valuelist[0])+1:
raise ValueError
self.value = valuelist
self.coeff = valuelist[0]
self.denom = valuelist[1]
self.degree = len(polynomial) - 1
self.polynomial = polynomial
self.field = NumberField(self.polynomial)
Gcd = gcd.gcd_of_list(self.coeff)
GCD = gcd.gcd(Gcd[0], self.denom)
if GCD != 1:
self.coeff = [i//GCD for i in self.coeff]
self.denom = self.denom//GCD
if precompute:
self.getConj()
self.getApprox()
self.getCharPoly()
def __init__(self, valuelist, polynomial, precompute=False):
if len(polynomial) != len(valuelist[0]) + 1:
raise ValueError
self.value = valuelist
self.coeff = valuelist[0]
self.denom = valuelist[1]
self.degree = len(polynomial) - 1
self.polynomial = polynomial
self.field = NumberField(self.polynomial)
Gcd = gcd.gcd_of_list(self.coeff)
GCD = gcd.gcd(Gcd[0], self.denom)
if GCD != 1:
self.coeff = [i // GCD for i in self.coeff]
self.denom = self.denom // GCD
if precompute:
self.getConj()
self.getApprox()
self.getCharPoly()
def _scalar_mul(self, other):
"""
return other * self, assuming other is a scalar
(i.e. an element of self.number_field)
"""
# use other is an element of higher or lower degree number field ?
#if other.getRing() != self.number_field:
# raise NotImplementedError(
# "other is not a element of number field")
if not isinstance(other, BasicAlgNumber):
try:
other = other.ch_basic()
except:
raise NotImplementedError(
"other is not an element of a number field")
# represent other with respect to self.base
other_repr, pseudo_other_denom = _toIntegerMatrix(
self.base.inverse(vector.Vector(other.coeff)))
other_repr = other_repr[1]
# compute mul using self.base's multiplication
base_mul = self._base_multiplication()
n = self.number_field.degree
mat_repr = []
for k in range(1, self.mat_repr.column + 1):
mat_repr_ele = vector.Vector([0] * n)
for i1 in range(1, n + 1):
for i2 in range(1, n + 1):
mat_repr_ele += self.mat_repr[
i1, k] * other_repr[i2] * _symmetric_element(
i1, i2, base_mul)
mat_repr.append(mat_repr_ele)
mat_repr, denom, numer = _toIntegerMatrix(
matrix.FieldMatrix(n, len(mat_repr), mat_repr), 1)
denom = self.denominator * pseudo_other_denom * other.denom * denom
gcds = gcd.gcd(denom, numer)
if gcds != 1:
denom = ring.exact_division(denom, gcds)
numer = ring.exact_division(numer, gcds)
if numer != 1:
mat_repr = numer * mat_repr
else:
mat_repr = mat_repr
return self.__class__([mat_repr, denom], self.number_field, self.base)
def _scalar_mul(self, other):
"""
return other * self, assuming other is a scalar
(i.e. an element of self.number_field)
"""
# use other is an element of higher or lower degree number field ?
#if other.getRing() != self.number_field:
# raise NotImplementedError(
# "other is not a element of number field")
if not isinstance(other, BasicAlgNumber):
try:
other = other.ch_basic()
except:
raise NotImplementedError(
"other is not an element of a number field")
# represent other with respect to self.base
other_repr, pseudo_other_denom = _toIntegerMatrix(
self.base.inverse(vector.Vector(other.coeff)))
other_repr = other_repr[1]
# compute mul using self.base's multiplication
base_mul = self._base_multiplication()
n = self.number_field.degree
mat_repr = []
for k in range(1, self.mat_repr.column +1):
mat_repr_ele = vector.Vector([0] * n)
for i1 in range(1, n + 1):
for i2 in range(1, n + 1):
mat_repr_ele += self.mat_repr[i1, k] * other_repr[
i2] * _symmetric_element(i1, i2, base_mul)
mat_repr.append(mat_repr_ele)
mat_repr, denom, numer = _toIntegerMatrix(
matrix.FieldMatrix(n, len(mat_repr), mat_repr), 1)
denom = self.denominator * pseudo_other_denom * other.denom * denom
gcds = gcd.gcd(denom, numer)
if gcds != 1:
denom = ring.exact_division(denom, gcds)
numer = ring.exact_division(numer, gcds)
if numer != 1:
mat_repr = numer * mat_repr
else:
mat_repr = mat_repr
return self.__class__([mat_repr, denom], self.number_field, self.base)
def mpqsfind(n, s=0, f=0, m=0, verbose=False):
"""
This is main function of MPQS.
Arguments are (composite_number, sieve_range, factorbase_size, multiplier)
You must input composite_number at least.
"""
# verbosity
if verbose:
_log.setLevel(logging.DEBUG)
_log.debug("verbose")
else:
_log.setLevel(logging.NOTSET)
starttime = time.time()
M = MPQS(n, s, f, m)
_log.info("Sieve range is [%d, %d]" % (M.move_range[0], M.move_range[-1]))
_log.info("Factorbase size = %d, Max Factorbase %d" % (len(M.FB), M.maxFB))
M.get_vector()
N = M.number // M.multiplier
V = Elimination(M.smooth)
A = V.gaussian()
_log.info("Found %d linearly dependent relations" % len(A))
differences = []
for i in A:
B = V.history[i].keys()
X = 1
Y = 1
for j in B:
X *= M.smooth[j][1][0]
Y *= M.smooth[j][1][1]
Y = Y % M.number
X = arith1.floorsqrt(X) % M.number
if X != Y:
differences.append(X-Y)
for diff in differences:
divisor = gcd.gcd(diff, N)
if 1 < divisor < N:
_log.info("Total time = %f sec" % (time.time() - starttime))
return divisor
def primeq(n):
"""
A convenient function for primatilty test. It uses one of
trialDivision, smallSpsp or apr depending on the size of n.
"""
if int(n) != n:
raise ValueError("non-integer for primeq()")
if n <= 1:
return False
if gcd.gcd(n, PRIMONIAL_31) > 1:
return n in PRIMES_LE_31
if n < 2000000:
return trialDivision(n)
if not smallSpsp(n):
return False
if n < 10**12:
return True
if not GRH:
return apr(n)
else:
return miller(n)
def primeq(n):
"""
A convinient function for primatilty test. It uses one of
trialDivision, smallSpsp or apr depending on the size of n.
"""
if int(n) != n:
raise ValueError("non-integer for primeq()")
if n <= 1:
return False
if gcd.gcd(n, 510510) > 1:
return (n in (2, 3, 5, 7, 11, 13, 17))
if n < 2000000:
return trialDivision(n)
if not smallSpsp(n):
return False
if n < 10 ** 12:
return True
if not GRH:
return apr(n)
else:
return miller(n)
def _kernel_of_qpow(omega, q, p, minpoly, n):
"""
Return the kernel of q-th powering, which is a linear map over Fp.
q is a power of p which exceeds n.
(omega_j^q (mod theminpoly) = \sum a_i_j omega_i a_i_j in Fp)
"""
omega_poly = omega.get_polynomials()
denom = omega.denominator
theminpoly = minpoly.to_field_polynomial()
field_p = finitefield.FinitePrimeField.getInstance(p)
zero = field_p.zero
qpow = matrix.zeroMatrix(n, n, field_p) # Fp matrix
for j in range(n):
a_j = [zero] * n
omega_poly_j = uniutil.polynomial(enumerate(omega.basis[j]), Z)
omega_j_qpow = pow(omega_poly_j, q, minpoly)
redundancy = gcd.gcd(omega_j_qpow.content(), denom ** q)
omega_j_qpow = omega_j_qpow.coefficients_map(lambda c: c // redundancy)
essential = denom ** q // redundancy
while omega_j_qpow:
i = omega_j_qpow.degree()
a_ji = int(omega_j_qpow[i] / (omega_poly[i][i] * essential))
omega_j_qpow -= a_ji * (omega_poly[i] * essential)
if omega_j_qpow.degree() < i:
a_j[i] = field_p.createElement(a_ji)
else:
_log.debug("%s / %d" % (str(omega_j_qpow), essential))
_log.debug("j = %d, a_ji = %s" % (j, a_ji))
raise ValueError("omega is not a basis")
qpow.setColumn(j + 1, a_j)
result = qpow.kernel()
if result is None:
_log.debug("(_k_q): trivial kernel")
return matrix.zeroMatrix(n, 1, field_p)
else:
return result
def _kernel_of_qpow(omega, q, p, minpoly, n):
"""
Return the kernel of q-th powering, which is a linear map over Fp.
q is a power of p which exceeds n.
(omega_j^q (mod theminpoly) = \sum a_i_j omega_i a_i_j in Fp)
"""
omega_poly = omega.get_polynomials()
denom = omega.denominator
theminpoly = minpoly.to_field_polynomial()
field_p = finitefield.FinitePrimeField.getInstance(p)
zero = field_p.zero
qpow = matrix.zeroMatrix(n, n, field_p) # Fp matrix
for j in range(n):
a_j = [zero] * n
omega_poly_j = uniutil.polynomial(enumerate(omega.basis[j]), Z)
omega_j_qpow = pow(omega_poly_j, q, minpoly)
redundancy = gcd.gcd(omega_j_qpow.content(), denom ** q)
omega_j_qpow = omega_j_qpow.coefficients_map(lambda c: c // redundancy)
essential = denom ** q // redundancy
while omega_j_qpow:
i = omega_j_qpow.degree()
a_ji = int(omega_j_qpow[i] / (omega_poly[i][i] * essential))
omega_j_qpow -= a_ji * (omega_poly[i] * essential)
if omega_j_qpow.degree() < i:
a_j[i] = field_p.createElement(a_ji)
else:
_log.debug("%s / %d" % (str(omega_j_qpow), essential))
_log.debug("j = %d, a_ji = %s" % (j, a_ji))
raise ValueError("omega is not a basis")
qpow.setColumn(j + 1, a_j)
result = qpow.kernel()
if result is None:
_log.debug("(_k_q): trivial kernel")
return matrix.zeroMatrix(n, 1, field_p)
else:
return result
def _rational_mul(self, other):
"""
return other * self, assuming other is a rational element
"""
if rational.isIntegerObject(other):
other_numerator = rational.Integer(other)
other_denominator = rational.Integer(1)
else:
other_numerator = other.numerator
other_denominator = other.denominator
denom_gcd = gcd.gcd(self.denominator, other_numerator)
if denom_gcd != 1:
new_denominator = ring.exact_division(
self.denominator, denom_gcd) * other_denominator
multiply_num = other_numerator.exact_division(denom_gcd)
else:
new_denominator = self.denominator * other_denominator
multiply_num = other_numerator
new_module = self.__class__(
[self.mat_repr * multiply_num, new_denominator],
self.number_field, self.base, self.mat_repr.ishnf)
new_module._simplify()
return new_module
def inverse(self):
"""
Return the inverse ideal of self
"""
# Algorithm 4.8.21 in CCANT
field = self.number_field
# step 1 (Note that det(T)T^-1=(adjugate matrix of T))
T = Ideal._precompute_for_different(field)
d = int(T.determinant())
inv_different = Ideal([T.adjugateMatrix(), 1], field,
field.integer_ring())
# step 2
inv_I = self * inv_different # already base is taken for integer_ring
inv_I.toHNF()
# step 3
inv_mat, denom = _toIntegerMatrix(
(inv_I.mat_repr.transpose() * T).inverse(), 0)
numer = d * inv_I.denominator
gcd_denom = gcd.gcd(denom, numer)
if gcd_denom != 1:
denom = ring.exact_division(denom, gcd_denom)
numer = ring.exact_division(numer, gcd_denom)
return Ideal([numer * inv_mat, denom], field, field.integer_ring())
def __mul__(self, other):
if isinstance(other, BasicAlgNumber):
d = self.denom*other.denom
f = zpoly(self.polynomial)
g = zpoly(self.coeff)
h = zpoly(other.coeff)
j = (g * h).pseudo_mod(f)
jcoeff = [j[i] for i in range(self.degree)]
return BasicAlgNumber([jcoeff, d], self.polynomial)
elif isinstance(other, (int, long)):
Coeff = [i*other for i in self.coeff]
return BasicAlgNumber([Coeff, self.denom], self.polynomial)
elif isinstance(other, rational.Rational):
GCD = gcd.gcd(other.numerator, self.denom)
denom = self.denom * other.denominator
mul = other.numerator
if GCD != 1:
denom //= GCD
mul //= GCD
Coeff = [self.coeff[j] * mul for j in range(self.degree)]
return BasicAlgNumber([Coeff, denom], self.polynomial)
else:
return NotImplemented
def inverse(self):
"""
Return the inverse ideal of self
"""
# Algorithm 4.8.21 in CCANT
field = self.number_field
# step 1 (Note that det(T)T^-1=(adjugate matrix of T))
T = Ideal._precompute_for_different(field)
d = int(T.determinant())
inv_different = Ideal([T.adjugateMatrix(), 1], field,
field.integer_ring())
# step 2
inv_I = self * inv_different # already base is taken for integer_ring
inv_I.toHNF()
# step 3
inv_mat, denom = _toIntegerMatrix(
(inv_I.mat_repr.transpose() * T).inverse(), 0)
numer = d * inv_I.denominator
gcd_denom = gcd.gcd(denom, numer)
if gcd_denom != 1:
denom = ring.exact_division(denom, gcd_denom)
numer = ring.exact_division(numer, gcd_denom)
return Ideal([numer * inv_mat, denom], field, field.integer_ring())
def __mul__(self, other):
if isinstance(other, BasicAlgNumber):
d = self.denom * other.denom
f = zpoly(self.polynomial)
g = zpoly(self.coeff)
h = zpoly(other.coeff)
j = (g * h).pseudo_mod(f)
jcoeff = [j[i] for i in range(self.degree)]
return BasicAlgNumber([jcoeff, d], self.polynomial)
elif isinstance(other, int):
Coeff = [i * other for i in self.coeff]
return BasicAlgNumber([Coeff, self.denom], self.polynomial)
elif isinstance(other, rational.Rational):
GCD = gcd.gcd(other.numerator, self.denom)
denom = self.denom * other.denominator
mul = other.numerator
if GCD != 1:
denom //= GCD
mul //= GCD
Coeff = [self.coeff[j] * mul for j in range(self.degree)]
return BasicAlgNumber([Coeff, denom], self.polynomial)
else:
return NotImplemented
def _rational_mul(self, other):
"""
return other * self, assuming other is a rational element
"""
if rational.isIntegerObject(other):
other_numerator = rational.Integer(other)
other_denominator = rational.Integer(1)
else:
other_numerator = other.numerator
other_denominator = other.denominator
denom_gcd = gcd.gcd(self.denominator, other_numerator)
if denom_gcd != 1:
new_denominator = ring.exact_division(
self.denominator, denom_gcd) * other_denominator
multiply_num = other_numerator.exact_division(denom_gcd)
else:
new_denominator = self.denominator * other_denominator
multiply_num = other_numerator
new_module = self.__class__(
[self.mat_repr * multiply_num, new_denominator], self.number_field,
self.base, self.mat_repr.ishnf)
new_module._simplify()
return new_module
def _module_mul(self, other):
"""
return self * other as the multiplication of modules
"""
#if self.number_field != other.number_field:
# raise NotImplementedError
if self.base != other.base:
new_self = self.change_base_module(other.base)
else:
new_self = self.copy()
base_mul = other._base_multiplication()
n = self.number_field.degree
new_mat_repr = []
for k1 in range(1, new_self.mat_repr.column + 1):
for k2 in range(1, other.mat_repr.column + 1):
new_mat_repr_ele = vector.Vector([0] * n)
for i1 in range(1, n + 1):
for i2 in range(1, n + 1):
new_mat_repr_ele += new_self.mat_repr[
i1, k1] * other.mat_repr[i2, k2
] * _symmetric_element(i1, i2, base_mul)
new_mat_repr.append(new_mat_repr_ele)
new_mat_repr, denom, numer = _toIntegerMatrix(
matrix.FieldMatrix(n, len(new_mat_repr), new_mat_repr), 1)
denom = new_self.denominator * other.denominator * denom
gcds = gcd.gcd(denom, numer)
if gcds != 1:
denom = ring.exact_division(denom, gcds)
numer = ring.exact_division(numer, gcds)
if numer != 1:
mat_repr = numer * new_mat_repr
else:
mat_repr = new_mat_repr
sol = self.__class__(
[mat_repr, denom], self.number_field, other.base)
sol.toHNF()
return sol
def represent_element(self, other):
"""
represent other as a linear combination with generators of self
if other not in self, return False
Note that we do not assume self.mat_repr is HNF
"""
#if other not in self.number_field:
# return False
theta_repr = (self.base * self.mat_repr)
theta_repr.toFieldMatrix()
pseudo_vect_repr = theta_repr.inverseImage(
vector.Vector(other.coeff))
pseudo_vect_repr = pseudo_vect_repr[1]
gcd_self_other = gcd.gcd(self.denominator, other.denom)
multiply_numerator = self.denominator // gcd_self_other
multiply_denominator = other.denom // gcd_self_other
def getNumerator_and_Denominator(ele):
"""
get the pair of numerator and denominator of ele
"""
if rational.isIntegerObject(ele):
return (ele, 1)
else: # rational
return (ele.numerator, ele.denominator)
list_repr = []
for j in range(1, len(pseudo_vect_repr) + 1):
try:
numer, denom = getNumerator_and_Denominator(
pseudo_vect_repr[j])
list_repr_ele = ring.exact_division(
numer * multiply_numerator, denom * multiply_denominator)
list_repr.append(list_repr_ele)
except ValueError: # division is not exact
return False
return list_repr
def represent_element(self, other):
"""
represent other as a linear combination with generators of self
if other not in self, return False
Note that we do not assume self.mat_repr is HNF
"""
#if other not in self.number_field:
# return False
theta_repr = (self.base * self.mat_repr)
theta_repr.toFieldMatrix()
pseudo_vect_repr = theta_repr.inverseImage(
vector.Vector(other.coeff))
pseudo_vect_repr = pseudo_vect_repr[1]
gcd_self_other = gcd.gcd(self.denominator, other.denom)
multiply_numerator = self.denominator // gcd_self_other
multiply_denominator = other.denom // gcd_self_other
def getNumerator_and_Denominator(ele):
"""
get the pair of numerator and denominator of ele
"""
if rational.isIntegerObject(ele):
return (ele, 1)
else: # rational
return (ele.numerator, ele.denominator)
list_repr = []
for j in range(1, len(pseudo_vect_repr) + 1):
try:
numer, denom = getNumerator_and_Denominator(
pseudo_vect_repr[j])
list_repr_ele = ring.exact_division(
numer * multiply_numerator, denom * multiply_denominator)
list_repr.append(list_repr_ele)
except ValueError: # division is not exact
return False
return list_repr
def _module_mul(self, other):
"""
return self * other as the multiplication of modules
"""
#if self.number_field != other.number_field:
# raise NotImplementedError
if self.base != other.base:
new_self = self.change_base_module(other.base)
else:
new_self = self.copy()
base_mul = other._base_multiplication()
n = self.number_field.degree
new_mat_repr = []
for k1 in range(1, new_self.mat_repr.column + 1):
for k2 in range(1, other.mat_repr.column + 1):
new_mat_repr_ele = vector.Vector([0] * n)
for i1 in range(1, n + 1):
for i2 in range(1, n + 1):
new_mat_repr_ele += new_self.mat_repr[
i1, k1] * other.mat_repr[i2,
k2] * _symmetric_element(
i1, i2, base_mul)
new_mat_repr.append(new_mat_repr_ele)
new_mat_repr, denom, numer = _toIntegerMatrix(
matrix.FieldMatrix(n, len(new_mat_repr), new_mat_repr), 1)
denom = new_self.denominator * other.denominator * denom
gcds = gcd.gcd(denom, numer)
if gcds != 1:
denom = ring.exact_division(denom, gcds)
numer = ring.exact_division(numer, gcds)
if numer != 1:
mat_repr = numer * new_mat_repr
else:
mat_repr = new_mat_repr
sol = self.__class__([mat_repr, denom], self.number_field, other.base)
sol.toHNF()
return sol
def testGcd(self):
self.assertEqual(1, gcd.gcd(1, 2))
self.assertEqual(2, gcd.gcd(2, 4))
self.assertEqual(10, gcd.gcd(0, 10))
self.assertEqual(10, gcd.gcd(10, 0))
self.assertEqual(1, gcd.gcd(13, 21))
def _isprime(n):
if gcd.gcd(n, 510510) > 1:
return (n in (2, 3, 5, 7, 11, 13, 17))
return smallSpsp(n)
def gcd(self, n, m):
"""
Return the greatest common divisor of given 2 integers.
"""
a, b = abs(n), abs(m)
return Integer(gcd.gcd(a, b))
def mpqs(n, s=0, f=0, m=0):
"""
This is main function of MPQS.
Arguments are (composite_number, sieve_range, factorbase_size, multiplier)
You must input composite_number at least.
"""
T = time.time()
M = MPQS(n, s, f, m)
_log.info("Sieve range is [ %d , %d ] , Factorbase size = %d , Max Factorbase %d" % (M.move_range[0], M.move_range[-1], len(M.FB), M.maxFB))
M.get_vector()
N = M.number // M.multiplier
V = Elimination(M.smooth)
A = V.gaussian()
_log.info("Found %d linerly dependent relations" % len(A))
answerX_Y = []
N_prime_factors = []
N_factors = []
output = []
for i in A:
B = V.history[i].keys()
X = 1
Y = 1
for j in B:
X *= M.smooth[j][1][0]
Y *= M.smooth[j][1][1]
Y = Y % M.number
X = sqrt_modn(X, M.number)
if X != Y:
answerX_Y.append(X-Y)
NN = 1
for k in answerX_Y:
factor = gcd.gcd(k, N)
if factor not in N_factors and factor != 1 and factor != N \
and factor not in N_prime_factors:
if prime.primeq(factor):
NN = NN*factor
N_prime_factors.append(factor)
else:
N_factors.append(factor)
_log.info("Total time = %f sec" % (time.time() - T))
if NN == N:
_log.debug("Factored completely!")
N_prime_factors.sort()
for p in N_prime_factors:
N = N // p
i = arith1.vp(N, p, 1)[0]
output.append((p, i))
return output
elif NN != 1:
f = N // NN
if prime.primeq(f):
N_prime_factors.append(f)
_log.debug("Factored completely !")
N_prime_factors.sort()
for p in N_prime_factors:
N = N // p
i = arith1.vp(N, p, 1)[0]
output.append((p, i))
return output
for F in N_factors:
for FF in N_factors:
if F != FF:
Q = gcd.gcd(F, FF)
if prime.primeq(Q) and Q not in N_prime_factors:
N_prime_factors.append(Q)
NN = NN*Q
N_prime_factors.sort()
for P in N_prime_factors:
i, N = arith1.vp(N, P)
output.append((P, i))
if N == 1:
_log.debug("Factored completely!! ")
return output
for F in N_factors:
g = gcd.gcd(N, F)
if prime.primeq(g):
N_prime_factors.append(g)
N = N // g
i = arith1.vp(N, g, 1)[0]
output.append((g, i))
if N == 1:
_log.debug("Factored completely !! ")
return output
elif prime.primeq(N):
output.append((N, 1))
_log.debug("Factored completely!!! ")
return output
else:
N_factors.sort()
_log.error("Sorry, not factored completely")
return output, N_factors
def gcd(self, n, m):
"""
Return the greatest common divisor of given 2 integers.
"""
a, b = abs(n), abs(m)
return Integer(gcd.gcd(a, b))
