def fermat(n):
from _primefac._arith import isqrt
x = isqrt(n) + 1
y = isqrt(x**2 - n)
while True:
w = x**2 - n - y**2
if w == 0:
break
if w > 0:
y += 1
else:
x += 1
return x + y
def williams_pp1(n):
from _primefac._arith import ispower, ilog, isqrt, gcd
from _primefac._prime import isprime, primegen
from six.moves import xrange
import itertools
if isprime(n):
return n
m = ispower(n)
if m:
return m
for v in itertools.count(1):
for p in primegen():
e = ilog(isqrt(n), p)
if e == 0:
break
for _ in xrange(e):
v = mlucas(v, p, n)
g = gcd(v - 2, n)
if 1 < g < n:
return g
if g == n:
break
def _isprime(n, tb=(3, 5, 7, 11), eb=(2, ), mrb=()): # TODO: more streamlining
from _primefac import _arith
# tb: trial division basis
# eb: Euler's test basis
# mrb: Miller-Rabin basis
# This test suite's first false positve is unknown but has been shown to
# be greater than 2**64.
# Infinitely many are thought to exist.
if n % 2 == 0 or n < 13 or n == _arith.isqrt(n)**2:
# Remove evens, squares, and numbers less than 13
return n in (2, 3, 5, 7, 11)
if any(n % p == 0 for p in tb):
return n in tb # Trial division
for b in eb: # Euler's test
if b >= n:
continue
if not pow(b, n - 1, n) == 1:
return False
r = n - 1
while r % 2 == 0:
r //= 2
c = pow(b, r, n)
if c == 1:
continue
while c != 1 and c != n - 1:
c = pow(c, 2, n)
if c == 1:
return False
s, d = pfactor(n)
if not sprp(n, 2, s, d):
return False
if n < 2047:
return True
# BPSW has two phases: SPRP with base 2 and SLPRP.
# We just did the SPRP; now we do the SLPRP:
if n >= 3825123056546413051:
d = 5
while True:
if _arith.gcd(d, n) > 1:
p, q = 0, 0
break
if _arith.jacobi(d, n) == -1:
p, q = 1, (1 - d) // 4
break
d = -d - 2 * d // abs(d)
if p == 0:
return n == d
s, t = pfactor(n + 2)
u, v, u2, v2, m = 1, p, 1, p, t // 2
k = q
while m > 0:
u2, v2, q = (u2 * v2) % n, (v2 * v2 - 2 * q) % n, (q * q) % n
if m % 2 == 1:
u, v = u2 * v + u * v2, v2 * v + u2 * u * d
if u % 2 == 1:
u += n
if v % 2 == 1:
v += n
u, v, k = (u // 2) % n, (v // 2) % n, (q * k) % n
m //= 2
if (u == 0) or (v == 0):
return True
for _ in xrange(1, s):
v, k = (v * v - 2 * k) % n, (k * k) % n
if v == 0:
return True
return False
if not mrb:
if n < 1373653:
mrb = [3]
elif n < 25326001:
mrb = [3, 5]
elif n < 3215031751:
mrb = [3, 5, 7]
elif n < 2152302898747:
mrb = [3, 5, 7, 11]
elif n < 3474749660383:
mrb = [3, 5, 6, 11, 13]
elif n < 341550071728321:
# This number is also a false positive for primes(19+1).
mrb = [3, 5, 7, 11, 13, 17]
elif n < 3825123056546413051:
# Also a false positive for primes(31+1).
mrb = [3, 5, 7, 11, 13, 17, 19, 23]
# Miller-Rabin
return all(sprp(n, b, s, d) for b in mrb)
def mpqs(n):
"""
When the bound proves insufficiently large, we throw out all our work and
start over.
TODO: When this happens, get more data, but don't trash what we already
have.
TODO: Rewrite to get a few more relations before proceeding to the
linear algebra.
TODO: When we need to increase the bound, what is the optimal increment?
"""
from _primefac._arith import ispower, isqrt, ilog, gcd, mod_sqrt, legendre
from _primefac._arith import modinv
from _primefac._prime import isprime, nextprime
from _primefac._util import listprod, mpz
from six.moves import xrange
from math import log
# Special cases: this function poorly handles primes and perfect powers:
m = ispower(n)
if m:
return m
if isprime(n):
return n
root_2n = isqrt(2 * n)
bound = ilog(n**6, 10)**2 # formula chosen by experiment
while True:
try:
prime, mod_root, log_p, num_prime = [], [], [], 0
# find a number of small primes for which n is a quadratic residue
p = 2
while p < bound or num_prime < 3:
leg = legendre(n % p, p)
if leg == 1:
prime += [p]
# the rhs was [int(mod_sqrt(n, p))].
# If we get errors, put it back.
mod_root += [mod_sqrt(n, p)]
log_p += [log(p, 10)]
num_prime += 1
elif leg == 0:
return p
p = nextprime(p)
x_max = len(prime) * 60 # size of the sieve
# maximum value on the sieved range
m_val = (x_max * root_2n) >> 1
"""
fudging the threshold down a bit makes it easier to find powers of
primes as factors as well as partial-partial relationships, but it
also makes the smoothness check slower. there's a happy medium
somewhere, depending on how efficient the smoothness check is
"""
thresh = log(m_val, 10) * 0.735
# skip small primes. they contribute very little to the log sum
# and add a lot of unnecessary entries to the table instead, fudge
# the threshold down a bit, assuming ~1/4 of them pass
min_prime = mpz(thresh * 3)
fudge = sum(log_p[i] for i, p in enumerate(prime) if p < min_prime)
fudge = fudge // 4
thresh -= fudge
smooth, used_prime, partial = [], set(), {}
num_smooth, num_used_prime, num_partial = 0, 0, 0
num_poly, root_A = 0, isqrt(root_2n // x_max)
while num_smooth <= num_used_prime:
# find an integer value A such that:
# A is =~ sqrt(2*n) // x_max
# A is a perfect square
# sqrt(A) is prime, and n is a quadratic residue mod sqrt(A)
while True:
root_A = nextprime(root_A)
leg = legendre(n, root_A)
if leg == 1:
break
elif leg == 0:
return root_A
A = root_A**2
# solve for an adequate B. B*B is a quadratic residue mod n,
# such that B*B-A*C = n. this is unsolvable if n is not a
# quadratic residue mod sqrt(A)
b = mod_sqrt(n, root_A)
B = (b + (n - b * b) * modinv(b + b, root_A)) % A
C = (B * B - n) // A # B*B-A*C = n <=> C = (B*B-n)//A
num_poly += 1
# sieve for prime factors
sums, i = [0.0] * (2 * x_max), 0
for p in prime:
if p < min_prime:
i += 1
continue
logp = log_p[i]
g = gcd(A, p)
inv_A = modinv(A // g, p // g) * g
# modular root of the quadratic
a, b, k = (mpz(((mod_root[i] - B) * inv_A) % p),
mpz(((p - mod_root[i] - B) * inv_A) % p), 0)
while k < x_max:
if k + a < x_max:
sums[k + a] += logp
if k + b < x_max:
sums[k + b] += logp
if k:
sums[k - a + x_max] += logp
sums[k - b + x_max] += logp
k += p
i += 1
# check for smooths
i = 0
for v in sums:
if v > thresh:
x, vec, sqr = x_max - i if i > x_max else i, set(), []
# because B*B-n = A*C
# (A*x+B)^2 - n = A*A*x*x+2*A*B*x + B*B - n
# = A*(A*x*x+2*B*x+C)
# gives the congruency
# (A*x+B)^2 = A*(A*x*x+2*B*x+C) (mod n)
# because A is chosen to be square, it doesn't
# need to be sieved
sieve_val = (A * x + 2 * B) * x + C
if sieve_val < 0:
vec, sieve_val = {-1}, -sieve_val
for p in prime:
while sieve_val % p == 0:
if p in vec:
"""
track perfect sqr facs to avoid sqrting
something huge at the end
"""
sqr += [p]
vec ^= {p}
sieve_val = mpz(sieve_val // p)
if sieve_val == 1: # smooth
smooth += [(vec, (sqr, (A * x + B), root_A))]
used_prime |= vec
elif sieve_val in partial:
"""
combine two partials to make a (xor) smooth that
is, every prime factor with an odd power is in our
factor base
"""
pair_vec, pair_vals = partial[sieve_val]
sqr += list(vec & pair_vec) + [sieve_val]
vec ^= pair_vec
smooth += [(vec, (sqr + pair_vals[0],
(A * x + B) * pair_vals[1],
root_A * pair_vals[2]))]
used_prime |= vec
num_partial += 1
else:
# save partial for later pairing
partial[sieve_val] = (vec, (sqr, A * x + B,
root_A))
i += 1
num_smooth, num_used_prime = len(smooth), len(used_prime)
used_prime = sorted(list(used_prime))
# set up bit fields for gaussian elimination
masks, mask, bitfields = [], 1, [0] * num_used_prime
for vec, _ in smooth:
masks += [mask]
i = 0
for p in used_prime:
if p in vec:
bitfields[i] |= mask
i += 1
mask <<= 1
# row echelon form
offset = 0
null_cols = []
for col in xrange(num_smooth):
pivot = bitfields[col - offset] & masks[
col] == 0 # This occasionally throws IndexErrors.
# TODO: figure out why it throws errors and fix it.
for row in xrange(col + 1 - offset, num_used_prime):
if bitfields[row] & masks[col]:
if pivot:
bitfields[col - offset], bitfields[
row], pivot = bitfields[row], bitfields[
col - offset], False
else:
bitfields[row] ^= bitfields[col - offset]
if pivot:
null_cols += [col]
offset += 1
# reduced row echelon form
for row in xrange(num_used_prime):
mask = bitfields[row] & -bitfields[row] # lowest set bit
for up_row in xrange(row):
if bitfields[up_row] & mask:
bitfields[up_row] ^= bitfields[row]
# check for non-trivial congruencies
# TODO: if none exist, check combinations of null space columns...
# if _still_ none exist, sieve more values
for col in null_cols:
all_vec, (lh, rh, rA) = smooth[col]
lhs = lh # sieved values (left hand side)
rhs = [rh] # sieved values - n (right hand side)
rAs = [rA] # root_As (cofactor of lhs)
i = 0
for field in bitfields:
if field & masks[col]:
vec, (lh, rh, rA) = smooth[i]
lhs += list(all_vec & vec) + lh
all_vec ^= vec
rhs += [rh]
rAs += [rA]
i += 1
factor = gcd(listprod(rAs) * listprod(lhs) - listprod(rhs), n)
if 1 < factor < n:
return factor
except IndexError:
pass
bound *= 1.2
