This file is indexed.

/usr/include/mmdb/linalg_.h is in libmmdb-dev 1.23.2.1-0ubuntu1.

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
//  =================================================================
//
//   CCP4 Coordinate Library: support of coordinate-related
//   functionality in protein crystallography applications.
//
//   Copyright (C) Eugene Krissinel 2000-2008.
//
//    This library is free software: you can redistribute it and/or
//    modify it under the terms of the GNU Lesser General Public
//    License version 3, modified in accordance with the provisions
//    of the license to address the requirements of UK law.
//
//    You should have received a copy of the modified GNU Lesser
//    General Public License along with this library. If not, copies
//    may be downloaded from http://www.ccp4.ac.uk/ccp4license.php
//
//    This program 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.
//
//  =================================================================
//
//    27.06.01   <--  Date of Last Modification.
//                   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
//  -----------------------------------------------------------------
//
//  **** Module  :  linalg_  <interface>
//       ~~~~~~~~~
//  **** Project :  MMDB  ( MacroMolecular Data Base )
//       ~~~~~~~~~
//
//  (C) E.Krissinel  2000-2008
//
//  =================================================================
//
//

#ifndef __LinAlg__
#define __LinAlg__

#ifndef  __MatType__
#include "mattype_.h"
#endif


//  ==========================  Jacobi  =============================


//  Diagonalization of symmetric matrices  by the method of Jacobi.
extern void  Jacobi ( int     N,     // dimension of the matrix
                      rmatrix A,     // matrix to diagonalize; the
                                     // lower triangle, except the
                                     // diagonal, will remain unchanged
                      rmatrix T,     // eigenvectors placed as columns
                      rvector Eigen, // vector of eigenvalues, orderd
                                     // by increasing
                      rvector Aik,   // working array
                      int &  Signal  // 0 <=> Ok, ItMax <=> iteration
                                     // limit exchausted.
                    );


//  A5.5.2  :  Perturbated Cholessky Decomposition
extern void  PbCholDecomp ( int        N,
                            rvector    HDiag,
                            realtype   MaxOff,
                            realtype   MachEps,
                            rmatrix    L,
                            realtype & MaxAdd );

//  A3.2.3a  :  Cholessky's   L - Solution  of
//              L*Y  =  B  ( given  B )
extern void  LSolve ( int N, rmatrix L, rvector B, rvector Y );

//  A3.2.3b  :  Cholessky's   LT - Solution  of
//              LT*X  =  Y  ( given  Y )
extern void  LTSolve ( int N, rmatrix L, rvector Y, rvector X );

//  A3.2.3   :  Solution of the equation    L*LT*S = G
//              by the  Cholessky's  method
extern void  ChSolve ( int N, rmatrix L, rvector G, rvector S );


//  ----------------------------------------------------

extern void  FastInverse (  int N, rmatrix A, ivector J0,
//#D                          realtype &  Det,
                            int & Signal );
//
//      13.09.90  <--  Last Modification Date
//                    ------------------------
//
// ================================================
//
//        Fast Inversion of the matrix  A
//      by the method of  GAUSS - JORDAN  .
//
// ------------------------------------------------
//
//          Input  parameters  are  :
//
//     N   -   dimension of the matrix
//     A   -   the matrix [1..N][1..N] to be inverted.
// ------------------------------------------------
//
//     J0  -   integer vector [1..N] for temporal storage
//
// ------------------------------------------------
//
//          Output parameters  are  :
//
//     A   -   the inverted matrix
//     Signal - the error key :
//            = 0   <=>   O'K
//             else
//            degeneration was found, and
//            the rang of matrix is  Signal-1.
//
//        Variable  Det  may return the determinant
//     of matrix A.  To obtain it, remove all comments
//     of form  //#D.
//
// ================================================


//  ----------------------------------------------------


void  SVD ( int    NA,    int     M,    int N,
            rmatrix A,    rmatrix U,    rmatrix V,
            rvector W,    rvector RV1,
            Boolean MatU, Boolean MatV,
            int & RetCode );
//
//      13.12.01  <--  Last Modification Date
//                    ------------------------
//
// ================================================
//
//         The    Singular Value Decomposition
//    of the matrix  A  by the algorithm from
//      G.Forsait, M.Malkolm, K.Mouler.  Numerical
//    methods of mathematical calculations //
//    M., Mir, 1980.
//
//         Matrix  A  is represented as
//
//         A  =  U * W * VT
//
// ------------------------------------------------
//
//  All dimensions are indexed from 1 on.
//
// ------------------------------------------------
//
//         Input  parameters:
//
//     NA  -   number of lines in A. NA may be
//           equal to M or N  only.  If NA=M
//           then usual SVD will be made. If MA=N
//           then matrix A is transposed before
//           the decomposition, and the meaning of
//           output parameters  U  and  V  is
//           swapped (U accepts VT and VT accepts U).
//           In other words, matrix  A  has physical
//           dimension of  M x N , same as U and V;
//           however the logical dimension of it
//           remains that of  N x M .
//     M   -   number of lines in  U
//     N   -   number of columns in  U,V and length
//           of  W,RV1 .  Always provide  M >= N  !
//     A   -   matrix [1..M][1..N] or [1..N][1..M]
//           to be decomposed. The matrix does not
//           change,  and it may coincide with  U  or
//           V, if NA=M (in which case  A  does change)
//     MatU -  compute  U , if set True
//     MatV -  compute  V , if set True
//     RV1  -  temporary array [1..N].
//     U    - should be always supplied as an array of
//            [1..M][1..N], M>=N .
//     V    - should be suuplied as an array of
//            [1..N][1..N] if MatV is True .
//
// ------------------------------------------------
//
//          Output parameters  are  :
//
//     W   -   N non-ordered singular values,
//           if  RetCode=0. If RetCode<>0, the
//           RetCode+1 ... N -th values are still
//           valid
//     U   -   matrix of right singular vectors
//           (arranged in columns),  corresponding
//           to the singular values in  W,  if
//           RetCode=0 and MatU is True.  If MatU
//           is False, U  is still used as a
//           temporary array. If RetCode<>0 then
//           the  RetCode+1 ... N -th vectors
//           are  valid
//     V   -   matrix of left singular vectors
//           (arranged in columns),  corresponding
//           to the singular values in  W,  if
//           RetCode=0 and MatV is True. If MatV
//           is False, V is not used and may be set
//           to NULL. If RetCode<>0 then the
//           RetCode+1 ... N -th vectors are valid
//     RetCode - the error key :
//            = 0   <=>   O'K
//              else
//            = k, if the k-th singular value
//                 was not computed after 30 iterations.
//
// ------------------------------------------------
//
//          Key  Variables  are  :
//
//     ItnLimit  -  the limit for iterations
//
//     This routine does not use any machine-dependent
//  constants.
//
// ================================================
//
//

void  OrderSVD ( int M, int N, rmatrix U, rmatrix V,
                 rvector W, Boolean MatU, Boolean MatV );


#endif