def load_matrix_file(filepath,
randomize=False,
seed=None,
float_type="double"):
"""
Load matrix from file, LLL reduce (and randomize).
:param filepath: Load matrix from this file
:param randomize: Randomize the basis
:param seed: Seed for randomization
:returns: lattice basis and BKZ object
"""
A = IntegerMatrix.from_file(filepath)
A = LLL.reduction(A)
A = IntegerMatrix.from_matrix(A, int_type="long")
M = GSO.Mat(A, float_type=float_type)
bkz = BKZReduction(M)
if seed is not None:
FPLLL.set_random_seed(seed)
if randomize:
bkz.randomize_block(0, A.nrows, density=A.ncols // 4)
LLL.reduction(A)
M = GSO.Mat(A, float_type=float_type)
bkz = BKZReduction(M)
bkz.lll_obj() # to initialize bkz.M etc
return A, bkz
def load_challenge_and_randomize(n):
A_pre = IntegerMatrix.from_file("svpchallenge/svpchallengedim%dseed0.txt" %
n)
LLL.reduction(A_pre)
A = IntegerMatrix.from_matrix(A_pre, int_type="long")
params = fplll_bkz.Param(block_size=n,
max_loops=1,
strategies=fplll_bkz.DEFAULT_STRATEGY,
flags=fplll_bkz.GH_BND,
min_success_probability=.8)
bkz = BKZReduction(A)
bkz.lll_obj()
bkz.randomize_block(0, n, density=n / 4)
bkz.lll_obj()
return A, bkz
print "OPPORT_ENUM", {
"n": n,
"Time": round(ENUM_TIME, 2),
"ghf": round(r0 / gh, 4)
}
AV_ENUM += ENUM_TIME / sample_rep
########### Timing SubSieve
A, bkz = load_challenge_and_randomize(n)
SUBSIEVE_START = time()
d = iterated_sub_sieve(A, goal=goal)
SUBSIEVE_TIME = time() - SUBSIEVE_START
bkz = BKZReduction(A)
bkz.lll_obj()
r0 = bkz.M.get_r(0, 0)
print "SUB_SIEVE ", {
"n": n,
"Time": round(SUBSIEVE_TIME, 2),
"ghf": round(r0 / gh, 4)
}, {
"d": d
}
AV_SIEVE += SUBSIEVE_TIME / sample_rep
print
print "OPPORT_ENUM average :", AV_ENUM
print "SUB_SIEVE average :", AV_SIEVE
print "ratio :", AV_SIEVE / AV_ENUM