Ticket #1937: trac1937_LLL_doc.patch

File trac1937_LLL_doc.patch, 3.3 KB (added by malb, 14 years ago)
• sage/matrix/matrix_integer_dense.pyx

# HG changeset patch
# User Martin Albrecht <malb@informatik.uni-bremen.de>
# Date 1201345112 0
# Node ID e1d15edce9a1a181024f7bb023e66667a915536e
# Parent  91998f13b187fc782b1f2ec71ecf8005a9c5f825
documentation fixes for LLL documentation (fixes #1937)

diff -r 91998f13b187 -r e1d15edce9a1 sage/matrix/matrix_integer_dense.pyx
 a cdef class Matrix_integer_dense(matrix_d def LLL(self, delta=None, eta=None, algorithm=None, fp=None, prec=0, early_red = False, use_givens = False): r""" Returns LLL reduced or approximated LLL reduced lattice R for self. this matrix interpreted as a lattice. A lattice is (delta, eta)-LLL-reduce if the two following conditions hold: A lattice $(b_1, b_2, ..., b_d)$ is $(\delta, \eta)$-LLL-reduced if the two following conditions hold: (a) For any $i>j$, we have $|mu_{i, j}| <= \eta$, (b) For any $i/$ and $b_i^*$ is the $i$-th vector of the Gram-Schmidt orthogonalisation of $(b_1, b_2, ..., b_d)$. The default reduction parameters are $\delta=3/4$ and $eta=0.501$. The parameters $\delta$ and $\eta$ must satisfy: $0.25 < \delta <= 1.0$ and $0.5 <= \eta < sqrt(\delta)$. $0.25 < \delta <= 1.0$ and $0.5 <= \eta < sqrt(\delta)$. Polynomial time complexity is only guaranteed for $\delta < 1$. If we can compute the determinant of self using this method, we also cache it. Note that in general this only happens when The lattice is returned as a matrix. Also the rank (and the determinant) of self are cached if those are computed during the reduction. Note that in general this only happens when self.rank() == self.ncols() and the exact algorithm is used. INPUT: cdef class Matrix_integer_dense(matrix_d use_givens -- use Givens orthogonalization (default: False) only applicable to approximate reductions and NTL. This is more stable but slower. Also, if the verbose level is >= 2, some more verbose output is printed during the calculation if NTL is used. cdef class Matrix_integer_dense(matrix_d sage: add([Q[i]*M[i] for i in range(n)]) -1 ALGORITHM: Uses NTL or fpLLL. ALGORITHM: Uses the NTL library by Victor Shoup or fpLLL library by Damien Stehle depending on the chosen algorithm. REFERENCES: ntl.mat_ZZ or sage.libs.fplll.fplll for details on the used algorithms. REFERENCES: \code{ntl.mat_ZZ} or \code{sage.libs.fplll.fplll} for details on the used algorithms. """ import sage.libs.ntl.all