remove the Gauss sieve

use g6k instead

docs/tutorial.rst

@@ -203,23 +203,7 @@ To compute the norm of a shortest vector of the lattice generated by the rows of
     >>> A[0].norm()
     8.602325267042627
 
-
-Also, the ``GaussSieve`` algorithm [MV]_ is implemented,
-
-::
-
-    >>> from fpylll import GaussSieve
-    >>> FPLLL.set_random_seed(0x1337)
-    >>> A = IntegerMatrix.random(30, "qary", k=15, q=127)
-    >>> v = GaussSieve(A, algorithm=2)()
-    >>> tuple(map(lambda x: -1*x, v)) if v[1] < 0 else v
-    (0, 2, 0, -2, 2, -1, -1, -4, -5, 2, 2, 4, 1, 3, -1, 0, 3, -1, -4, -2, -2, 4, -3, -1, -3, -9, -2, 1, 3, 6)
-    >>> print(A[0])
-    (1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 67, 119, 27, 122, 124, 109, 43, 58, 11, 120, 47, 48, 40, 21, 5)
-    >>> A[0].norm()
-    296.36801446849825
-
-The previous code returns a Shortest vector of the lattice generated by :math:`{\bf A}` using ``GaussSieve`` algorithm. For the Closest Vector Problem, fplll (and so fpylll) uses enumeration::
+For the Closest Vector Problem, fplll (and so fpylll) uses enumeration::
 
     >>> from fpylll import CVP
     >>> A = IntegerMatrix.from_matrix([[1,2,3,4],[30,4,4,5],[1,-2,3,4]])

setup.py

@@ -211,7 +211,6 @@ def _get_have_long_double(self):
     Extension("fpylll.fplll.enumeration", ["src/fpylll/fplll/enumeration.pyx"], fplll=True),
     Extension("fpylll.fplll.svpcvp", ["src/fpylll/fplll/svpcvp.pyx"], fplll=True),
     Extension("fpylll.fplll.pruner", ["src/fpylll/fplll/pruner.pyx"], fplll=True),
-    Extension("fpylll.fplll.sieve_gauss", ["src/fpylll/fplll/sieve_gauss.pyx"], fplll=True),
     Extension("fpylll.util", ["src/fpylll/util.pyx"], fplll=True),
     Extension("fpylll.io", ["src/fpylll/io.pyx"], fplll=True),
     Extension("fpylll.config", ["src/fpylll/config.pyx"], fplll=True),

src/fpylll/__init__.py

@@ -9,7 +9,6 @@
 from .fplll.svpcvp import SVP
 from .fplll.svpcvp import CVP
 from .fplll.pruner import Pruning
-from .fplll.sieve_gauss import GaussSieve
 from .util import ReductionError
 from .util import FPLLL
 __version__ = "0.5.2dev"

src/fpylll/fplll/decl.pxd

@@ -16,7 +16,6 @@ IF HAVE_QD:
 from .fplll cimport dpe_t
 from .fplll cimport Z_NR, FP_NR
 from .fplll cimport ZZ_mat, MatGSOInterface, LLLReduction, BKZAutoAbort, BKZReduction, Enumeration
-from .fplll cimport GaussSieve
 from .fplll cimport Evaluator, FastEvaluator, ErrorBoundedEvaluator, FastErrorBoundedEvaluator, Pruner
 
 from libcpp.vector cimport vector
@@ -83,10 +82,6 @@ ctypedef union zz_mat_core_t:
     ZZ_mat[long]  *long
     ZZ_mat[mpz_t] *mpz
 
-ctypedef union gauss_sieve_core_t:
-    GaussSieve[long, FP_NR[double]]   *long_d
-    GaussSieve[mpz_t, FP_NR[double]]  *mpz_d
-
 ctypedef struct z_nr_t:
     Z_NR[long] long
     Z_NR[mpz_t] mpz

src/fpylll/fplll/fplll.pxd

@@ -956,26 +956,6 @@ cdef extern from "fplll/pruner/pruner.h" namespace "fplll":
     FT svp_probability[FT](const vector[double] &pr)
 
 
-
-# Sieving
-
-cdef extern from "fplll/sieve/sieve_gauss.h" namespace "fplll":
-    cdef cppclass GaussSieve[ZT, FT]:
-        GaussSieve(ZZ_mat[ZT] &B, int algorithm, bool verbose, int seed)
-
-        bool sieve(Z_NR[ZT] target_norm)
-
-        void set_verbose(bool verbose)
-        bool verbose
-
-        int alg
-
-        # norms/listsize for all iterations
-        vector[Z_NR[ZT]] iters_norm
-        vector[long] iters_ls
-
-        NumVect[Z_NR[ZT]] return_first()
-
 # Threads
 
 cdef extern from "fplll/threadpool.h" namespace "fplll":