/**
@brief Test sieve by checking if function returns correct vector.
@param A input lattice
@param b shortest vector
@return
*/
template <class ZT> int test_sieve_alg(ZZ_mat<ZT> &A, IntVect &b, int alg)
{
GaussSieve<ZT, FP_NR<double>> gsieve(A, alg, 0, 0);
Z_NR<ZT> goal_norm;
goal_norm = 0;
gsieve.set_goal_norm2(goal_norm);
if (gsieve.alg == 3)
gsieve.run_3sieve();
else if (gsieve.alg == 4)
gsieve.run_4sieve();
else
gsieve.run_2sieve();
NumVect<Z_NR<ZT>> v = gsieve.return_first();
Z_NR<ZT> tmp;
Z_NR<ZT> norm_s;
Z_NR<ZT> norm_b;
for (int i = 0; i < A.get_cols(); i++)
{
tmp.mul(v[i], v[i]);
norm_s.add(norm_s, tmp);
tmp.mul(b[i], b[i]);
norm_b.add(norm_b, tmp);
}
if (norm_s != norm_b)
return 1;
return 0;
}
template <class ZT> int test_svp(ZZ_mat<ZT> &A, IntVect &b)
{
IntVect sol_coord; // In the LLL-reduced basis
IntVect sol_coord2; // In the initial basis
IntVect solution;
IntMatrix u;
int status =
lll_reduction(A, u, LLL_DEF_DELTA, LLL_DEF_ETA, LM_WRAPPER, FT_DEFAULT, 0, LLL_DEFAULT);
if (status != RED_SUCCESS)
{
cerr << "LLL reduction failed: " << get_red_status_str(status) << endl;
return status;
}
status = shortest_vector(A, sol_coord, SVPM_PROVED, SVP_DEFAULT);
if (status != RED_SUCCESS)
{
cerr << "Failure: " << get_red_status_str(status) << endl;
return status;
}
vector_matrix_product(sol_coord2, sol_coord, u);
vector_matrix_product(solution, sol_coord, A);
Z_NR<ZT> tmp;
Z_NR<ZT> norm_s;
Z_NR<ZT> norm_b;
for (int i = 0; i < A.get_cols(); i++)
{
tmp.mul(solution[i], solution[i]);
norm_s.add(norm_s, tmp);
tmp.mul(b[i], b[i]);
norm_b.add(norm_b, tmp);
}
if (norm_s != norm_b)
return 1;
return 0;
}