This file is indexed.

/usr/include/linbox/algorithms/gauss-gf2.h is in liblinbox-dev 1.4.2-3.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
/* linbox/algorithms/gauss-gf2.h
 * Copyright (C) 2009 The LinBox group
 * Written by JG Dumas
 *
 * Time-stamp: <23 Mar 12 17:28:19 Jean-Guillaume.Dumas@imag.fr>
 *
 * 
 * ========LICENCE========
 * This file is part of the library LinBox.
 * 
 * LinBox is free software: you can redistribute it and/or modify
 * it under the terms of the  GNU Lesser General Public
 * License as published by the Free Software Foundation; either
 * version 2.1 of the License, or (at your option) any later version.
 * 
 * This library is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 * Lesser General Public License for more details.
 * 
 * You should have received a copy of the GNU Lesser General Public
 * License along with this library; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
 * ========LICENCE========
 *.
 *
 * SparseSeqMatrix is container< container< size_t > >
 * as e.g. linbox/blackbox/zo-gf2.h
 */

#ifndef __LINBOX_gauss_gf2_H
#define __LINBOX_gauss_gf2_H

#include "linbox/util/debug.h"
#include "linbox/util/commentator.h"
#include "linbox/field/gf2.h"
#include "linbox/vector/vector-domain.h"
#include "linbox/algorithms/gauss.h"
#include "linbox/blackbox/zo-gf2.h"

/** @file algorithms/gauss-gf2.h
 * @brief  Gauss elimination and applications for sparse matrices on \f$F_2\f$.
 * Rank, nullspace, solve...
 */


namespace LinBox
{

	template <>
	class GaussDomain<GF2> {
	public:
		typedef GF2 Field;
		typedef Field::Element Element;

		// Preferred Matrix type
		typedef ZeroOne<GF2> Matrix;

	public:

		/** \brief The field parameter is the domain  over which to perform computations.
		 */
		GaussDomain (const Field &) {}

		//Copy constructor
		///
		GaussDomain (const GaussDomain &)  {}

		/** accessor for the field of computation.
		*/
		const Field &field () const { return *(new GF2()); }

		/** @name rank
		  Callers of the different rank routines
		  @li  The "in" suffix indicates in place computation
		  @li  Without Ni, Nj, the SparseSeqMatrix parameter must be a vector of sparse
		  row vectors, NOT storing any zero.
		  @li  Calls @link rankinLinearPivoting@endlink (by default) or @link rankinNoReordering@endlink
		  */
		//@{
		///
		///
		template <class SparseSeqMatrix> unsigned long& rankin(unsigned long &Rank,
		SparseSeqMatrix        &A,
		unsigned long  Ni,
		unsigned long  Nj,
		SparseEliminationTraits::PivotStrategy   reord = SparseEliminationTraits::PIVOT_LINEAR) const ;

		///
		template <class SparseSeqMatrix> unsigned long& rankin(unsigned long &Rank,
		SparseSeqMatrix        &A,
		SparseEliminationTraits::PivotStrategy   reord = SparseEliminationTraits::PIVOT_LINEAR) const;

		///
		template <class SparseSeqMatrix> unsigned long& rank(unsigned long &rk,
		const SparseSeqMatrix        &A,
		unsigned long  Ni,
		unsigned long  Nj,
		SparseEliminationTraits::PivotStrategy   reord = SparseEliminationTraits::PIVOT_LINEAR) const ;

		///
		template <class SparseSeqMatrix> unsigned long& rank(unsigned long &rk,
		const SparseSeqMatrix        &A,
		SparseEliminationTraits::PivotStrategy   reord = SparseEliminationTraits::PIVOT_LINEAR) const ;

		//@}

		/** @name det
		  Callers of the different determinant routines\\
		  -/ The "in" suffix indicates in place computation\\
		  -/ Without Ni, Nj, the SparseSeqMatrix parameter must be a vector of sparse
		  row vectors, NOT storing any zero.\\
		  -/ Calls @link LinearPivoting@endlink (by default) or @link NoReordering@endlink
		  */
		//@{
		///
		template <class SparseSeqMatrix> Element& detin(Element &determinant,
		SparseSeqMatrix        &A,
		SparseEliminationTraits::PivotStrategy   reord = SparseEliminationTraits::PIVOT_LINEAR) const;
		///
		template <class SparseSeqMatrix> Element& detin(Element &determinant,
		SparseSeqMatrix        &A,
		unsigned long  Ni,
		unsigned long  Nj,
		SparseEliminationTraits::PivotStrategy   reord = SparseEliminationTraits::PIVOT_LINEAR) const;
		///
		template <class SparseSeqMatrix> Element& det(Element &determinant,
		const SparseSeqMatrix        &A,
		SparseEliminationTraits::PivotStrategy   reord = SparseEliminationTraits::PIVOT_LINEAR) const;
		///
		template <class SparseSeqMatrix> Element& det(Element &determinant,
		const SparseSeqMatrix        &A,
		unsigned long  Ni,
		unsigned long  Nj,
		SparseEliminationTraits::PivotStrategy   reord = SparseEliminationTraits::PIVOT_LINEAR) const;
		//@}


		/** \brief Sparse in place Gaussian elimination with reordering to reduce fill-in.
		 * pivots are chosen in sparsest column of sparsest row.
		 * This runs in linear overhead.
		 * It is similar in spirit but different from Markovitz' approach.
		 *
		 * \pre Using : SparseFindPivot(..., density) for sparsest column, and
		 * eliminate (..., density)
		 *
		 * The SparseSeqMatrix parameter must meet the LinBox sparse matrix interface.
		 * [check details].
		 * The computedet indicates whether the algorithm must compute the determionant as it goes
		 *
		 * @bib
		 * - Jean-Guillaume Dumas and Gilles Villard,
		 * <i>Computing the rank of sparse matrices over finite fields.</i>
		 * In Ganzha et~al. CASC'2002, pages 47--62.
		 */
		template <class SparseSeqMatrix, class Perm>
		unsigned long& QLUPin(unsigned long &Rank,
				      Element& determinant,
				      Perm          &Q,
				      SparseSeqMatrix	    &L,
				      SparseSeqMatrix        &U,
				      Perm	    &P,
				      unsigned long Ni,
				      unsigned long Nj) const;

		template <class SparseSeqMatrix, class Perm, class Vector1, class Vector2>
		Vector1& solve(Vector1& x, Vector1& w, unsigned long Rank, const Perm& Q, const SparseSeqMatrix& L, const SparseSeqMatrix& U, const Perm& P, const Vector2& b) const;


		template <class SparseSeqMatrix, class Vector1, class Vector2>
		Vector1& solvein(Vector1& x,
				 SparseSeqMatrix        &A,
				 const Vector2& b) const;

		template <class SparseSeqMatrix, class Vector1, class Vector2, class Random>
		Vector1& solvein(Vector1& x,
				 SparseSeqMatrix        &A,
				 const Vector2& b, Random& generator) const;


		template <class SparseSeqMatrix, class Perm>
		unsigned long& InPlaceLinearPivoting(unsigned long &Rank,
						     Element& determinant,
						     SparseSeqMatrix        &A,
						     Perm                   &P,
						     unsigned long Ni,
						     unsigned long Nj) const;
		template <class SparseSeqMatrix>
		unsigned long& NoReordering (unsigned long & Rank, Element& , SparseSeqMatrix &, unsigned long , unsigned long ) const
		{
			std::cerr << "Sparse elimination over GF2 without reordering not implemented" << std::endl;
			return Rank;
		}


	protected:

		//-----------------------------------------
		// Sparse elimination using a pivot row :
		// lc <-- lc - lc[k]/lp[0] * lp
		// D is the number of elements per column
		//   it is updated and used for reordering
		// Vector is a vector of Pair (lin_pair.h)
		//-----------------------------------------
		template <class Vector, class D>
		void eliminateBinary (Element             & headpivot,
				      Vector              &lignecourante,
				      const Vector        &lignepivot,
				      const unsigned long indcol,
				      const long indpermut,
				      const unsigned long npiv,
				      D                   &columns) const;

		template <class Vector>
		void permuteBinary (Vector              &lignecourante,
				    const unsigned long &indcol,
				    const long &indpermut) const;

		//------------------------------------------
		// Looking for a non-zero pivot in a row
		// Using the column density for reordering
		// Pivot is chosen as to :
		// 1. Row density is minimum
		// 2. Column density is minimum for this row
		//------------------------------------------
		template <class Vector, class D>
		void SparseFindPivotBinary (Vector &lignepivot, unsigned long &indcol, long &indpermut, D &columns, Element& determinant) const;

		//------------------------------------------
		// Looking for a non-zero pivot in a row
		// No reordering
		//------------------------------------------
		template <class Vector>
		void SparseFindPivotBinary (Vector &lignepivot, unsigned long &indcol, long &indpermut, Element& determinant) const;

	};
} // namespace LinBox

#include "linbox/algorithms/gauss/gauss-gf2.inl"
#include "linbox/algorithms/gauss/gauss-pivot-gf2.inl"
#include "linbox/algorithms/gauss/gauss-elim-gf2.inl"
#include "linbox/algorithms/gauss/gauss-rank-gf2.inl"
#include "linbox/algorithms/gauss/gauss-solve-gf2.inl"

#endif // __LINBOX_gauss_gf2_H


// vim:sts=8:sw=8:ts=8:noet:sr:cino=>s,f0,{0,g0,(0,:0,t0,+0,=s
// Local Variables:
// mode: C++
// tab-width: 8
// indent-tabs-mode: nil
// c-basic-offset: 8
// End: