def nrootb(self, index, bits):
"""
Approximately compute the inverse of index-th root and return it.
b stands for binary search. It should be used for:
1 <= bits <= ceil(lg(8 * index))
"""
# lgy - 1 < lg self <= lgy
lgy = arith1.log(self.abscissa) + self.exponent
if DyadicRational(lgy, 1) < self:
lgy += 1
assert DyadicRational(lgy - 1, 1) < self <= DyadicRational(lgy, 1)
lgr = -lgy // index
ebound = 66 * (2 * index + 1)
bound = arith1.log(ebound)
if 2**bound < ebound:
bound += 1
rbound = DyadicRational(-10, 993)
one = DyadicRational(0, 1)
z = DyadicRational(lgr, 1) + DyadicRational(lgr - 1, 1)
for j in range(1, bits):
r = (z.power(index, bound) * self.trunc(bound)).trunc(bound)
if r <= rbound:
z += DyadicRational(lgr - j - 1, 1)
if r > one:
z = z.sub(DyadicRational(lgr - j - 1, 1))
return z
def __init__(self, n):
"""
Create a Bounds object from target number n.
"""
if _arith1.log(n, 10) < 20:
self.first = 1000
elif _arith1.log(n, 10) < 25:
self.first = 10000
else:
self.first = 100000
self.second = self.first * 50
def __init__(self, n):
"""
Create a Bounds object from target number n.
"""
if _arith1.log(n, 10) < 20:
self.first = 1000
elif _arith1.log(n, 10) < 25:
self.first = 10000
else:
self.first = 100000
self.second = self.first * 50
def zassenhaus(f):
"""
zassenhaus(f) -> list of factors of f.
Factor a squarefree monic integer coefficient polynomial f with
Berlekamp-Zassenhaus method.
"""
# keep leading coefficient
lf = f.leading_coefficient()
# p-adic factorization
p, fp_factors = padic_factorization(f)
if len(fp_factors) == 1:
return [f]
# purge leading coefficient from factors
for i, g in enumerate(fp_factors):
if g.degree() == 0:
del fp_factors[i]
break
# lift to Mignotte bound
blm = upper_bound_of_coefficient(f)
bound = p**(arith1.log(2 * blm, p) + 1)
# Hensel lifting
lf_inv_modq = intresidue.IntegerResidueClass(lf, bound).inverse()
fq = f.coefficients_map(lambda c:
(lf_inv_modq * c).minimumAbsolute()) # fq is monic
fq_factors, q = hensel.lift_upto(fq, fp_factors, p, bound)
return brute_force_search(f, fq_factors, bound)
def _squarefree_decomp(p, field, base_multiply):
"""
decompose (p) as (p)= A_1 (A_2)^2 (A_3)^2 ..., where each A_i is squarefree
"""
#CCANT Algo 6.2.9 step 2-5
n = field.degree
int_basis = field.integer_ring()
# step 2
log_n_p = arith1.log(n, p)
q = p ** log_n_p
if q < n:
q *= p
base_p = _kernel_of_qpow(int_basis, q, p, field)
I_p_over_pO = base_p
# step 3
K_lst = [I_p_over_pO]
while K_lst[-1]: # K[-1] is zero matrix in F_p
K_lst.append(_mul_mod_pO(K_lst[0], K_lst[-1], base_multiply))
i = len(K_lst)
# step 4
J_lst = [K_lst[0]]
for j in range(1, i):
J_lst.append(_div_mod_pO(K_lst[j], K_lst[j - 1], base_multiply, p))
# step 5
H_lst = []
for j in range(i - 1):
H_lst.append(_div_mod_pO(J_lst[j], J_lst[j + 1], base_multiply, p))
H_lst.append(J_lst[-1])
return H_lst
def _squarefree_decomp(p, field, base_multiply):
"""
decompose (p) as (p)= A_1 (A_2)^2 (A_3)^2 ..., where each A_i is squarefree
"""
#CCANT Algo 6.2.9 step 2-5
n = field.degree
int_basis = field.integer_ring()
# step 2
log_n_p = arith1.log(n, p)
q = p ** log_n_p
if q < n:
q *= p
base_p = _kernel_of_qpow(int_basis, q, p, field)
I_p_over_pO = base_p
# step 3
K_lst = [I_p_over_pO]
while K_lst[-1]: # K[-1] is zero matrix in F_p
K_lst.append(_mul_mod_pO(K_lst[0], K_lst[-1], base_multiply))
i = len(K_lst)
# step 4
J_lst = [K_lst[0]]
for j in range(1, i):
J_lst.append(_div_mod_pO(K_lst[j], K_lst[j - 1], base_multiply, p))
# step 5
H_lst = []
for j in range(i - 1):
H_lst.append(_div_mod_pO(J_lst[j], J_lst[j + 1], base_multiply, p))
H_lst.append(J_lst[-1])
return H_lst
def zassenhaus(f):
"""
zassenhaus(f) -> list of factors of f.
Factor a squarefree monic integer coefficient polynomial f with
Berlekamp-Zassenhaus method.
"""
# keep leading coefficient
lf = f.leading_coefficient()
# p-adic factorization
p, fp_factors = padic_factorization(f)
if len(fp_factors) == 1:
return [f]
# purge leading coefficient from factors
for i,g in enumerate(fp_factors):
if g.degree() == 0:
del fp_factors[i]
break
# lift to Mignotte bound
blm = upper_bound_of_coefficient(f)
bound = p**(arith1.log(2*blm,p)+1)
# Hensel lifting
lf_inv_modq = intresidue.IntegerResidueClass(lf, bound).inverse()
fq = f.coefficients_map(lambda c: (lf_inv_modq*c).minimumAbsolute()) # fq is monic
fq_factors, q = hensel.lift_upto(fq, fp_factors, p, bound)
return brute_force_search(f, fq_factors, bound)
def FFT(f, bound):
"""
Fast Fourier Transform.
This function returns the result of valuations of f by fast fourier transform
against number of bound different values.
"""
count = 1 << (bound >> 1)
mod = count + 1
if isinstance(f, ArrayPoly):
coefficients = f.coefficients[:]
else:
coefficients = f[:]
coefficients.extend([0] * (bound - len(coefficients)))
shuf_coefficients = perfect_shuffle(coefficients)
shuf_coefficients = [min_abs_mod(i, mod) for i in shuf_coefficients]
bound_log = arith1.log(bound, 2)
for i in range(1, bound_log + 1):
m = 1 << i
wm = count
wm = wm % mod
w = 1
m1 = m >> 1
for j in range(m1):
for k in range(j, bound, m):
m2 = k + m1
plus = shuf_coefficients[k]
minus = w * shuf_coefficients[m2]
shuf_coefficients[k] = (plus + minus) % mod
shuf_coefficients[m2] = (plus - minus) % mod
w = w * wm
shuf_coefficietns = [min_abs_mod(i, mod) for i in shuf_coefficients]
count = arith1.floorsqrt(count)
return shuf_coefficients
def nroot(self, index, bits):
lg8k = arith1.log(8 * index)
if 2**lg8k < 8 * index:
lg8k += 1
if bits <= lg8k:
return self.nrootb(index, bits)
else:
return self.nrootn(index, bits)
def ceillog(n, base=2):
"""
Return ceiling of log(n, 2)
"""
floor = arith1.log(n, base)
if base**floor == n:
return floor
else:
return floor + 1
def __init__(self, n, sieverange, factorbase):
self.number = n
self.sqrt_n = int(math.sqrt(n))
for i in [2,3,5,7,11,17,19]:
if n % i == 0:
raise ValueError("This number is divided by %d" % i)
self.digit = arith1.log(self.number, 10) + 1
self.Srange = sieverange
self.FBN = factorbase
self.move_range = range(self.sqrt_n-self.Srange, self.sqrt_n+self.Srange+1)
i = 0
k = 0
factor_base = [-1]
FB_log = [0]
while True:
ii = primes_table[i]
if arith1.legendre(self.number, ii) == 1:
factor_base.append(ii)
FB_log.append(primes_log_table[i])
k += 1
i += 1
if k == self.FBN:
break
else:
i += 1
self.FB = factor_base
self.FB_log = FB_log
self.maxFB = factor_base[-1]
N_sqrt_list = []
for i in self.FB:
if i != 2 and i != -1:
e = int(math.log(2*self.Srange, i))
N_sqrt_modp = sqroot_power(self.number, i, e)
N_sqrt_list.append(N_sqrt_modp)
self.solution = N_sqrt_list #This is square roots of N on Z/pZ, p in factor base.
poly_table = []
log_poly = []
minus_val = []
for j in self.move_range:
jj = (j**2)-self.number
if jj < 0:
jj = -jj
minus_val.append(j-self.sqrt_n+self.Srange)
elif jj == 0:
jj = 1
lj = int((math.log(jj)*30)*0.97) # 0.97 is an erroe
poly_table.append(jj)
log_poly.append(lj)
self.poly_table = poly_table # This is Q(x) value , x in [-M+sqrt_n,M+sqrt_n].
self.log_poly = log_poly # This is log(Q(x)) value.
self.minus_check = minus_val # This is "x" that Q(x) is minus value.
def __init__(self, exponent, abscissa):
self.exponent = exponent
self.abscissa = abscissa
if self.abscissa:
while not (self.abscissa & 1):
self.exponent += 1
self.abscissa >>= 1
# f - 1 <= lg abscissa < f
self.log_absc = arith1.log(self.abscissa)
if 2**self.log_absc <= self.abscissa:
self.log_absc += 1
def perfect_power_detection(n):
"""
Return (m, k) if n = m**k.
Note that k is the smallest possible and m still can be a perfect
power; if n is not a perfect power, it returns (n, 1).
"""
f = arith1.log(n) + 1
y = DyadicRational(0, n).nroot(1, 3 + (f - 1) // 2 + 1)
for p in prime.generator_eratosthenes(f):
x = _is_kth_power(n, p, y, f)
if x != 0:
return (x, p)
return (n, 1)
def div(self, divisor, bits):
"""
Divide a dyadic rational by a positive integer divisor within
precision bits and return the result.
"""
# lgd - 1 < lg divisor <= lgd
lgd = arith1.log(divisor)
if 2**lgd < divisor:
lgd += 1
offset = self.log_absc - lgd - bits
if offset < 0:
abscissa = (self.abscissa << -offset) // divisor
else:
abscissa = self.abscissa // (divisor << offset)
return DyadicRational(self.exponent + offset, abscissa)
def miller(n):
"""
Miller's primality test.
This test is valid under GRH.
"""
s, t = arith1.vp(n - 1, 2)
# The O-constant 2 by E.Bach
## ln(n) = log_2(n)/log_2(e) = ln(2) * log_2(n)
## 2 * ln(2) ** 2 <= 0.960906027836404
bound = min(n - 1, 960906027836404 * (arith1.log(n) + 1)**2 // 10**15 + 1)
_log.info("bound: %d" % bound)
for b in range(2, bound):
if not spsp(n, b, s, t):
return False
return True
def miller(n):
"""
Miller's primality test.
This test is valid under GRH.
"""
s, t = arith1.vp(n - 1, 2)
# The O-constant 2 by E.Bach
## 2 log(n) = 2 log_2(n)/log_2(e) = 2 log(2) log_2(n)
## 2 log(2) <= 1.3862943611198906
bound = min(n - 2, 13862943611198906 * arith1.log(n) // 10 ** 16) + 1
_log.info("bound: %d" % bound)
for b in range(2, bound):
if not spsp(n, b, s, t):
return False
return True
def _p_maximal(p, e, minpoly_coeff):
"""
Return p-maximal basis with some related informations.
The arguments:
p: the prime
e: the exponent
minpoly_coeff: (intefer) list of coefficients of the minimal
polynomial of theta
"""
# Apply the Dedekind criterion
finished, omega = Dedekind(minpoly_coeff, p, e)
if finished:
_log.info("Dedekind(%d)" % p)
return omega
# main loop to construct p-maximal order
minpoly = uniutil.polynomial(enumerate(minpoly_coeff), Z)
theminpoly = minpoly.to_field_polynomial()
n = theminpoly.degree()
q = p ** (arith1.log(n, p) + 1)
while True:
# Ip: radical of pO
# Ip = <alpha>, l = dim Ip/pO (essential part of Ip)
alpha, l = _p_radical(omega, p, q, minpoly, n)
# instead of step 9 big matrix,
# Kida's LN section 2.2
# Up = {x in Ip | xIp \subset pIp} = <zeta> + p<omega>
zeta = _p_module(alpha, l, p, theminpoly)
if zeta.rank == 0:
# no new basis is found
break
# new order
# 1/p Up = 1/p<zeta> + <omega>
omega2 = zeta / p + omega
if all(o1 == o2 for o1, o2 in zip(omega.basis, omega2.basis)):
break
omega = omega2
# now <omega> is p-maximal.
return omega
def _p_maximal(p, e, minpoly_coeff):
"""
Return p-maximal basis with some related informations.
The arguments:
p: the prime
e: the exponent
minpoly_coeff: (intefer) list of coefficients of the minimal
polynomial of theta
"""
# Apply the Dedekind criterion
finished, omega = Dedekind(minpoly_coeff, p, e)
if finished:
_log.info("Dedekind(%d)" % p)
return omega
# main loop to construct p-maximal order
minpoly = uniutil.polynomial(enumerate(minpoly_coeff), Z)
theminpoly = minpoly.to_field_polynomial()
n = theminpoly.degree()
q = p ** (arith1.log(n, p) + 1)
while True:
# Ip: radical of pO
# Ip = <alpha>, l = dim Ip/pO (essential part of Ip)
alpha, l = _p_radical(omega, p, q, minpoly, n)
# instead of step 9 big matrix,
# Kida's LN section 2.2
# Up = {x in Ip | xIp \subset pIp} = <zeta> + p<omega>
zeta = _p_module(alpha, l, p, theminpoly)
if zeta.rank == 0:
# no new basis is found
break
# new order
# 1/p Up = 1/p<zeta> + <omega>
omega2 = zeta / p + omega
if all(o1 == o2 for o1, o2 in zip(omega.basis, omega2.basis)):
break
omega = omega2
# now <omega> is p-maximal.
return omega
def _power_sign(n, x, k, f):
"""
Return the sign of n - x**k. All of n, x, and k are positive
integers.
"""
lg8k = arith1.log(k) + 3
if 2**lg8k < 8 * k:
lg8k += 1
bound = 1
drn = DyadicRational(0, n)
while True:
r = DyadicRational(0, x).power(k, bound + lg8k)
if drn < r:
return -1
elif r * (DyadicRational(0, 1) + DyadicRational(-bound, 1)) <= drn:
return 1
elif bound >= f:
return 0
bound = min(2 * bound, f)
def randrange(start, stop=None, step=1):
"""
Choose a random item from range([start,] stop[, step]).
(Return long integer.)
see random.randrange
"""
if stop is None:
if abs(start) < sys.maxint:
return _random.randrange(start)
elif abs(stop - start) < sys.maxint:
return _random.randrange(start, stop, step)
negative_step = False
if stop is None:
start, stop = 0, start
if step < 0:
start, stop, step = -start, -stop, -step
negative_step = True
_validate_for_randrange(start, stop, step)
if (stop - start) % step != 0:
v = (stop - start)//step + 1
else:
v = (stop - start)//step
bitlength = arith1.log(v, base=2)
if v != 2**bitlength:
bitlength += 1
randomized = v + 1 # to pass the first test
while randomized >= v:
randomized = 0
for i in range(bitlength):
if random() < 0.5:
randomized += 1 << i
result = randomized * step + start
if negative_step:
return -result
return result
def randrange(start, stop=None, step=1):
"""
Choose a random item from range([start,] stop[, step]).
(Return long integer.)
see random.randrange
"""
if stop is None:
if abs(start) < sys.maxint:
return _random.randrange(start)
elif abs(stop - start) < sys.maxint:
return _random.randrange(start, stop, step)
negative_step = False
if stop is None:
start, stop = 0, start
if step < 0:
start, stop, step = -start, -stop, -step
negative_step = True
_validate_for_randrange(start, stop, step)
if (stop - start) % step != 0:
v = (stop - start) // step + 1
else:
v = (stop - start) // step
bitlength = arith1.log(v, base=2)
if v != 2**bitlength:
bitlength += 1
randomized = v + 1 # to pass the first test
while randomized >= v:
randomized = 0
for i in range(bitlength):
if random() < 0.5:
randomized += 1 << i
result = randomized * step + start
if negative_step:
return -result
return result
def nrootn(self, index, bits):
"""
Approximately compute the inverse of index-th root and return it.
n stands for Newton's method. It should be used for:
bits > ceil(lg(8 * index))
"""
lgk = arith1.log(index)
if 2**lgk < index:
lgk += 1
lg2k = lgk + 1
lg8k = lgk + 3
smallbits = lg2k + (bits - lg2k - 1) // 2 + 1
bound = 2 * smallbits + 4 - lgk
if smallbits <= lg8k:
z = self.nrootb(index, smallbits)
else:
z = self.nrootn(index, smallbits)
r2 = z.trunc(bound).mul(index + 1)
r3 = (z.power(index + 1, bound) * self.trunc(bound)).trunc(bound)
r4 = r2.sub(r3).div(index, bound)
return r4
def __init__(self, n, sieverange=0, factorbase=0, multiplier=0):
self.number = n
_log.info("The number is %d MPQS starting" % n)
if prime.primeq(self.number):
raise ValueError("This number is Prime Number")
for i in [2,3,5,7,11,13]:
if n % i == 0:
raise ValueError("This number is divided by %d" % i)
self.sievingtime = 0
self.coefficienttime = 0
self.d_list = []
self.a_list = []
self.b_list = []
#Decide prameters for each digits
self.digit = arith1.log(self.number, 10) + 1
if sieverange != 0:
self.Srange = sieverange
if factorbase != 0:
self.FBN = factorbase
elif self.digit < 9:
self.FBN = parameters_for_mpqs[0][1]
else:
self.FBN = parameters_for_mpqs[self.digit-9][1]
elif factorbase != 0:
self.FBN = factorbase
if self.digit < 9:
self.Srange = parameters_for_mpqs[0][0]
else:
self.Srange = parameters_for_mpqs[self.digit-9][0]
elif self.digit < 9:
self.Srange = parameters_for_mpqs[0][0]
self.FBN = parameters_for_mpqs[0][1]
elif self.digit > 53:
self.Srange = parameters_for_mpqs[44][0]
self.FBN = parameters_for_mpqs[44][1]
else:
self.Srange = parameters_for_mpqs[self.digit-9][0]
self.FBN = parameters_for_mpqs[self.digit-9][1]
self.move_range = range(-self.Srange, self.Srange+1)
# Decide k such that k*n = 1 (mod4) and k*n has many factor base
if multiplier == 0:
self.sqrt_state = []
for i in [3,5,7,11,13]:
s = arith1.legendre(self.number, i)
self.sqrt_state.append(s)
index8 = (self.number % 8) // 2
j = 0
while self.sqrt_state != prime_8[index8][j][1]:
j += 1
k = prime_8[index8][j][0]
else:
if n % 4 == 1:
k = 1
else:
if multiplier == 1:
raise ValueError("This number is 3 mod 4 ")
else:
k = multiplier
self.number = k*self.number
self.multiplier = k
_log.info("%d - digits Number" % self.digit)
_log.info("Multiplier is %d" % self.multiplier)
# Table of (log p) , p in FB
i = 0
k = 0
factor_base = [-1]
FB_log = [0]
while k < self.FBN:
ii = primes_table[i]
if arith1.legendre(self.number,ii) == 1:
factor_base.append(ii)
FB_log.append(primes_log_table[i])
k += 1
i += 1
self.FB = factor_base
self.FB_log = FB_log
self.maxFB = factor_base[-1]
# Solve x^2 = n (mod p^e)
N_sqrt_list = []
for i in self.FB:
if i != 2 and i != -1:
e = int(math.log(2*self.Srange, i))
N_sqrt_modp = sqroot_power(self.number, i, e)
N_sqrt_list.append(N_sqrt_modp)
self.Nsqrt = N_sqrt_list
def affine_multiple_method(lhs, field):
"""
Find and return a root of the equation lhs = 0 by brute force
search in the given field. If there is no root in the field,
ValueError is raised.
The first argument lhs is a univariate polynomial with
coefficients in a finite field. The second argument field is
an extension field of the field of coefficients of lhs.
Affine multiple A(X) is $\sum_{i=0}^{n} a_i X^{q^i} - a$ for some
a_i's and a in the coefficient field of lhs, which is a multiple
of the lhs.
"""
polynomial_ring = lhs.getRing()
coeff_field = lhs.getCoefficientRing()
q = card(coeff_field)
n = lhs.degree()
# residues = [x, x^q, x^{q^2}, ..., x^{q^{n-1}}]
residues = [lhs.mod(polynomial_ring.one.term_mul((1, 1)))] # x
for i in range(1, n):
residues.append(pow(residues[-1], q, lhs)) # x^{q^i}
# find a linear relation among residues and a constant
coeff_matrix = matrix.createMatrix(n, n, [coeff_field.zero] * (n**2),
coeff_field)
for j, residue in enumerate(residues):
for i in range(residue.degree() + 1):
coeff_matrix[i + 1, j + 1] = residue[i]
constant_components = [coeff_field.one] + [coeff_field.zero] * (n - 1)
constant_vector = vector.Vector(constant_components)
try:
relation_vector, kernel = coeff_matrix.solve(constant_vector)
for j in range(n, 0, -1):
if relation_vector[j]:
constant = relation_vector[j].inverse()
relation = [constant * c for c in relation_vector]
break
except matrix.NoInverseImage:
kernel_matrix = coeff_matrix.kernel()
relation_vector = kernel_matrix[1]
assert type(relation_vector) is vector.Vector
for j in range(n, 0, -1):
if relation_vector[j]:
normalizer = relation_vector[j].inverse()
relation = [normalizer * c for c in relation_vector]
constant = coeff_field.zero
break
# define L(X) = A(X) + constant
coeffs = {}
for i, relation_i in enumerate(relation):
coeffs[q**i] = relation_i
linearized = uniutil.polynomial(coeffs, coeff_field)
# Fq basis [1, X, ..., X^{s-1}]
qbasis = [1]
root = field.createElement(field.char)
s = arith1.log(card(field), q)
qbasis += [root**i for i in range(1, s)]
# represent L as Matrix
lmat = matrix.createMatrix(s, s, field.basefield)
for j, base in enumerate(qbasis):
imagei = linearized(base)
if imagei.getRing() == field.basefield:
lmat[1, j + 1] = imagei
else:
for i, coeff in imagei.rep.iterterms():
if coeff:
lmat[i + 1, j + 1] = coeff
# solve L(X) = the constant
constant_components = [constant] + [coeff_field.zero] * (s - 1)
constant_vector = vector.Vector(constant_components)
solution, kernel = lmat.solve(constant_vector)
assert lmat * solution == constant_vector
solutions = [solution]
for v in kernel:
for i in range(card(field.basefield)):
solutions.append(solution + i * v)
# roots of A(X) contains the solutions of lhs = 0
for t in bigrange.multirange([(card(field.basefield), )] * len(kernel)):
affine_root_vector = solution
for i, ti in enumerate(t):
affine_root_vector += ti * kernel[i]
affine_root = field.zero
for i, ai in enumerate(affine_root_vector):
affine_root += ai * qbasis[i]
if not lhs(affine_root):
return affine_root
raise ValueError("no root found")
def affine_multiple_method(lhs, field):
"""
Find and return a root of the equation lhs = 0 by brute force
search in the given field. If there is no root in the field,
ValueError is raised.
The first argument lhs is a univariate polynomial with
coefficients in a finite field. The second argument field is
an extension field of the field of coefficients of lhs.
Affine multiple A(X) is $\sum_{i=0}^{n} a_i X^{q^i} - a$ for some
a_i's and a in the coefficient field of lhs, which is a multiple
of the lhs.
"""
polynomial_ring = lhs.getRing()
coeff_field = lhs.getCoefficientRing()
q = card(coeff_field)
n = lhs.degree()
# residues = [x, x^q, x^{q^2}, ..., x^{q^{n-1}}]
residues = [lhs.mod(polynomial_ring.one.term_mul((1, 1)))] # x
for i in range(1, n):
residues.append(pow(residues[-1], q, lhs)) # x^{q^i}
# find a linear relation among residues and a constant
coeff_matrix = matrix.createMatrix(n, n, [coeff_field.zero] * (n**2), coeff_field)
for j, residue in enumerate(residues):
for i in range(residue.degree() + 1):
coeff_matrix[i + 1, j + 1] = residue[i]
constant_components = [coeff_field.one] + [coeff_field.zero] * (n - 1)
constant_vector = vector.Vector(constant_components)
try:
relation_vector, kernel = coeff_matrix.solve(constant_vector)
for j in range(n, 0, -1):
if relation_vector[j]:
constant = relation_vector[j].inverse()
relation = [constant * c for c in relation_vector]
break
except matrix.NoInverseImage:
kernel_matrix = coeff_matrix.kernel()
relation_vector = kernel_matrix[1]
assert type(relation_vector) is vector.Vector
for j in range(n, 0, -1):
if relation_vector[j]:
normalizer = relation_vector[j].inverse()
relation = [normalizer * c for c in relation_vector]
constant = coeff_field.zero
break
# define L(X) = A(X) + constant
coeffs = {}
for i, relation_i in enumerate(relation):
coeffs[q**i] = relation_i
linearized = uniutil.polynomial(coeffs, coeff_field)
# Fq basis [1, X, ..., X^{s-1}]
qbasis = [1]
root = field.createElement(field.char)
s = arith1.log(card(field), q)
qbasis += [root**i for i in range(1, s)]
# represent L as Matrix
lmat = matrix.createMatrix(s, s, field.basefield)
for j, base in enumerate(qbasis):
imagei = linearized(base)
if imagei.getRing() == field.basefield:
lmat[1, j + 1] = imagei
else:
for i, coeff in imagei.rep.iterterms():
if coeff:
lmat[i + 1, j + 1] = coeff
# solve L(X) = the constant
constant_components = [constant] + [coeff_field.zero] * (s - 1)
constant_vector = vector.Vector(constant_components)
solution, kernel = lmat.solve(constant_vector)
assert lmat * solution == constant_vector
solutions = [solution]
for v in kernel:
for i in range(card(field.basefield)):
solutions.append(solution + i * v)
# roots of A(X) contains the solutions of lhs = 0
for t in bigrange.multirange([(card(field.basefield),)] * len(kernel)):
affine_root_vector = solution
for i, ti in enumerate(t):
affine_root_vector += ti * kernel[i]
affine_root = field.zero
for i, ai in enumerate(affine_root_vector):
affine_root += ai * qbasis[i]
if not lhs(affine_root):
return affine_root
raise ValueError("no root found")
def testLog(self):
self.assertEqual(3, arith1.log(8, 2))
self.assertEqual(3, arith1.log(15, 2))
self.assertEqual(3, arith1.log(1000, 10))
self.assertEqual(9, arith1.log(1000000001, 10))
self.assertTrue(10**arith1.log(1000000001, 10) <= 1000000001)
