src/glpspm.c
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     1 /* glpspm.c */
       
     2 
       
     3 /***********************************************************************
       
     4 *  This code is part of GLPK (GNU Linear Programming Kit).
       
     5 *
       
     6 *  Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008,
       
     7 *  2009, 2010 Andrew Makhorin, Department for Applied Informatics,
       
     8 *  Moscow Aviation Institute, Moscow, Russia. All rights reserved.
       
     9 *  E-mail: <mao@gnu.org>.
       
    10 *
       
    11 *  GLPK is free software: you can redistribute it and/or modify it
       
    12 *  under the terms of the GNU General Public License as published by
       
    13 *  the Free Software Foundation, either version 3 of the License, or
       
    14 *  (at your option) any later version.
       
    15 *
       
    16 *  GLPK is distributed in the hope that it will be useful, but WITHOUT
       
    17 *  ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
       
    18 *  or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
       
    19 *  License for more details.
       
    20 *
       
    21 *  You should have received a copy of the GNU General Public License
       
    22 *  along with GLPK. If not, see <http://www.gnu.org/licenses/>.
       
    23 ***********************************************************************/
       
    24 
       
    25 #include "glphbm.h"
       
    26 #include "glprgr.h"
       
    27 #include "glpspm.h"
       
    28 
       
    29 /***********************************************************************
       
    30 *  NAME
       
    31 *
       
    32 *  spm_create_mat - create general sparse matrix
       
    33 *
       
    34 *  SYNOPSIS
       
    35 *
       
    36 *  #include "glpspm.h"
       
    37 *  SPM *spm_create_mat(int m, int n);
       
    38 *
       
    39 *  DESCRIPTION
       
    40 *
       
    41 *  The routine spm_create_mat creates a general sparse matrix having
       
    42 *  m rows and n columns. Being created the matrix is zero (empty), i.e.
       
    43 *  has no elements.
       
    44 *
       
    45 *  RETURNS
       
    46 *
       
    47 *  The routine returns a pointer to the matrix created. */
       
    48 
       
    49 SPM *spm_create_mat(int m, int n)
       
    50 {     SPM *A;
       
    51       xassert(0 <= m && m < INT_MAX);
       
    52       xassert(0 <= n && n < INT_MAX);
       
    53       A = xmalloc(sizeof(SPM));
       
    54       A->m = m;
       
    55       A->n = n;
       
    56       if (m == 0 || n == 0)
       
    57       {  A->pool = NULL;
       
    58          A->row = NULL;
       
    59          A->col = NULL;
       
    60       }
       
    61       else
       
    62       {  int i, j;
       
    63          A->pool = dmp_create_pool();
       
    64          A->row = xcalloc(1+m, sizeof(SPME *));
       
    65          for (i = 1; i <= m; i++) A->row[i] = NULL;
       
    66          A->col = xcalloc(1+n, sizeof(SPME *));
       
    67          for (j = 1; j <= n; j++) A->col[j] = NULL;
       
    68       }
       
    69       return A;
       
    70 }
       
    71 
       
    72 /***********************************************************************
       
    73 *  NAME
       
    74 *
       
    75 *  spm_new_elem - add new element to sparse matrix
       
    76 *
       
    77 *  SYNOPSIS
       
    78 *
       
    79 *  #include "glpspm.h"
       
    80 *  SPME *spm_new_elem(SPM *A, int i, int j, double val);
       
    81 *
       
    82 *  DESCRIPTION
       
    83 *
       
    84 *  The routine spm_new_elem adds a new element to the specified sparse
       
    85 *  matrix. Parameters i, j, and val specify the row number, the column
       
    86 *  number, and a numerical value of the element, respectively.
       
    87 *
       
    88 *  RETURNS
       
    89 *
       
    90 *  The routine returns a pointer to the new element added. */
       
    91 
       
    92 SPME *spm_new_elem(SPM *A, int i, int j, double val)
       
    93 {     SPME *e;
       
    94       xassert(1 <= i && i <= A->m);
       
    95       xassert(1 <= j && j <= A->n);
       
    96       e = dmp_get_atom(A->pool, sizeof(SPME));
       
    97       e->i = i;
       
    98       e->j = j;
       
    99       e->val = val;
       
   100       e->r_prev = NULL;
       
   101       e->r_next = A->row[i];
       
   102       if (e->r_next != NULL) e->r_next->r_prev = e;
       
   103       e->c_prev = NULL;
       
   104       e->c_next = A->col[j];
       
   105       if (e->c_next != NULL) e->c_next->c_prev = e;
       
   106       A->row[i] = A->col[j] = e;
       
   107       return e;
       
   108 }
       
   109 
       
   110 /***********************************************************************
       
   111 *  NAME
       
   112 *
       
   113 *  spm_delete_mat - delete general sparse matrix
       
   114 *
       
   115 *  SYNOPSIS
       
   116 *
       
   117 *  #include "glpspm.h"
       
   118 *  void spm_delete_mat(SPM *A);
       
   119 *
       
   120 *  DESCRIPTION
       
   121 *
       
   122 *  The routine deletes the specified general sparse matrix freeing all
       
   123 *  the memory allocated to this object. */
       
   124 
       
   125 void spm_delete_mat(SPM *A)
       
   126 {     /* delete sparse matrix */
       
   127       if (A->pool != NULL) dmp_delete_pool(A->pool);
       
   128       if (A->row != NULL) xfree(A->row);
       
   129       if (A->col != NULL) xfree(A->col);
       
   130       xfree(A);
       
   131       return;
       
   132 }
       
   133 
       
   134 /***********************************************************************
       
   135 *  NAME
       
   136 *
       
   137 *  spm_test_mat_e - create test sparse matrix of E(n,c) class
       
   138 *
       
   139 *  SYNOPSIS
       
   140 *
       
   141 *  #include "glpspm.h"
       
   142 *  SPM *spm_test_mat_e(int n, int c);
       
   143 *
       
   144 *  DESCRIPTION
       
   145 *
       
   146 *  The routine spm_test_mat_e creates a test sparse matrix of E(n,c)
       
   147 *  class as described in the book: Ole 0sterby, Zahari Zlatev. Direct
       
   148 *  Methods for Sparse Matrices. Springer-Verlag, 1983.
       
   149 *
       
   150 *  Matrix of E(n,c) class is a symmetric positive definite matrix of
       
   151 *  the order n. It has the number 4 on its main diagonal and the number
       
   152 *  -1 on its four co-diagonals, two of which are neighbour to the main
       
   153 *  diagonal and two others are shifted from the main diagonal on the
       
   154 *  distance c.
       
   155 *
       
   156 *  It is necessary that n >= 3 and 2 <= c <= n-1.
       
   157 *
       
   158 *  RETURNS
       
   159 *
       
   160 *  The routine returns a pointer to the matrix created. */
       
   161 
       
   162 SPM *spm_test_mat_e(int n, int c)
       
   163 {     SPM *A;
       
   164       int i;
       
   165       xassert(n >= 3 && 2 <= c && c <= n-1);
       
   166       A = spm_create_mat(n, n);
       
   167       for (i = 1; i <= n; i++)
       
   168          spm_new_elem(A, i, i, 4.0);
       
   169       for (i = 1; i <= n-1; i++)
       
   170       {  spm_new_elem(A, i, i+1, -1.0);
       
   171          spm_new_elem(A, i+1, i, -1.0);
       
   172       }
       
   173       for (i = 1; i <= n-c; i++)
       
   174       {  spm_new_elem(A, i, i+c, -1.0);
       
   175          spm_new_elem(A, i+c, i, -1.0);
       
   176       }
       
   177       return A;
       
   178 }
       
   179 
       
   180 /***********************************************************************
       
   181 *  NAME
       
   182 *
       
   183 *  spm_test_mat_d - create test sparse matrix of D(n,c) class
       
   184 *
       
   185 *  SYNOPSIS
       
   186 *
       
   187 *  #include "glpspm.h"
       
   188 *  SPM *spm_test_mat_d(int n, int c);
       
   189 *
       
   190 *  DESCRIPTION
       
   191 *
       
   192 *  The routine spm_test_mat_d creates a test sparse matrix of D(n,c)
       
   193 *  class as described in the book: Ole 0sterby, Zahari Zlatev. Direct
       
   194 *  Methods for Sparse Matrices. Springer-Verlag, 1983.
       
   195 *
       
   196 *  Matrix of D(n,c) class is a non-singular matrix of the order n. It
       
   197 *  has unity main diagonal, three co-diagonals above the main diagonal
       
   198 *  on the distance c, which are cyclically continued below the main
       
   199 *  diagonal, and a triangle block of the size 10x10 in the upper right
       
   200 *  corner.
       
   201 *
       
   202 *  It is necessary that n >= 14 and 1 <= c <= n-13.
       
   203 *
       
   204 *  RETURNS
       
   205 *
       
   206 *  The routine returns a pointer to the matrix created. */
       
   207 
       
   208 SPM *spm_test_mat_d(int n, int c)
       
   209 {     SPM *A;
       
   210       int i, j;
       
   211       xassert(n >= 14 && 1 <= c && c <= n-13);
       
   212       A = spm_create_mat(n, n);
       
   213       for (i = 1; i <= n; i++)
       
   214          spm_new_elem(A, i, i, 1.0);
       
   215       for (i = 1; i <= n-c; i++)
       
   216          spm_new_elem(A, i, i+c, (double)(i+1));
       
   217       for (i = n-c+1; i <= n; i++)
       
   218          spm_new_elem(A, i, i-n+c, (double)(i+1));
       
   219       for (i = 1; i <= n-c-1; i++)
       
   220          spm_new_elem(A, i, i+c+1, (double)(-i));
       
   221       for (i = n-c; i <= n; i++)
       
   222          spm_new_elem(A, i, i-n+c+1, (double)(-i));
       
   223       for (i = 1; i <= n-c-2; i++)
       
   224          spm_new_elem(A, i, i+c+2, 16.0);
       
   225       for (i = n-c-1; i <= n; i++)
       
   226          spm_new_elem(A, i, i-n+c+2, 16.0);
       
   227       for (j = 1; j <= 10; j++)
       
   228          for (i = 1; i <= 11-j; i++)
       
   229             spm_new_elem(A, i, n-11+i+j, 100.0 * (double)j);
       
   230       return A;
       
   231 }
       
   232 
       
   233 /***********************************************************************
       
   234 *  NAME
       
   235 *
       
   236 *  spm_show_mat - write sparse matrix pattern in BMP file format
       
   237 *
       
   238 *  SYNOPSIS
       
   239 *
       
   240 *  #include "glpspm.h"
       
   241 *  int spm_show_mat(const SPM *A, const char *fname);
       
   242 *
       
   243 *  DESCRIPTION
       
   244 *
       
   245 *  The routine spm_show_mat writes pattern of the specified sparse
       
   246 *  matrix in uncompressed BMP file format (Windows bitmap) to a binary
       
   247 *  file whose name is specified by the character string fname.
       
   248 *
       
   249 *  Each pixel corresponds to one matrix element. The pixel colors have
       
   250 *  the following meaning:
       
   251 *
       
   252 *  Black    structurally zero element
       
   253 *  White    positive element
       
   254 *  Cyan     negative element
       
   255 *  Green    zero element
       
   256 *  Red      duplicate element
       
   257 *
       
   258 *  RETURNS
       
   259 *
       
   260 *  If no error occured, the routine returns zero. Otherwise, it prints
       
   261 *  an appropriate error message and returns non-zero. */
       
   262 
       
   263 int spm_show_mat(const SPM *A, const char *fname)
       
   264 {     int m = A->m;
       
   265       int n = A->n;
       
   266       int i, j, k, ret;
       
   267       char *map;
       
   268       xprintf("spm_show_mat: writing matrix pattern to `%s'...\n",
       
   269          fname);
       
   270       xassert(1 <= m && m <= 32767);
       
   271       xassert(1 <= n && n <= 32767);
       
   272       map = xmalloc(m * n);
       
   273       memset(map, 0x08, m * n);
       
   274       for (i = 1; i <= m; i++)
       
   275       {  SPME *e;
       
   276          for (e = A->row[i]; e != NULL; e = e->r_next)
       
   277          {  j = e->j;
       
   278             xassert(1 <= j && j <= n);
       
   279             k = n * (i - 1) + (j - 1);
       
   280             if (map[k] != 0x08)
       
   281                map[k] = 0x0C;
       
   282             else if (e->val > 0.0)
       
   283                map[k] = 0x0F;
       
   284             else if (e->val < 0.0)
       
   285                map[k] = 0x0B;
       
   286             else
       
   287                map[k] = 0x0A;
       
   288          }
       
   289       }
       
   290       ret = rgr_write_bmp16(fname, m, n, map);
       
   291       xfree(map);
       
   292       return ret;
       
   293 }
       
   294 
       
   295 /***********************************************************************
       
   296 *  NAME
       
   297 *
       
   298 *  spm_read_hbm - read sparse matrix in Harwell-Boeing format
       
   299 *
       
   300 *  SYNOPSIS
       
   301 *
       
   302 *  #include "glpspm.h"
       
   303 *  SPM *spm_read_hbm(const char *fname);
       
   304 *
       
   305 *  DESCRIPTION
       
   306 *
       
   307 *  The routine spm_read_hbm reads a sparse matrix in the Harwell-Boeing
       
   308 *  format from a text file whose name is the character string fname.
       
   309 *
       
   310 *  Detailed description of the Harwell-Boeing format recognised by this
       
   311 *  routine can be found in the following report:
       
   312 *
       
   313 *  I.S.Duff, R.G.Grimes, J.G.Lewis. User's Guide for the Harwell-Boeing
       
   314 *  Sparse Matrix Collection (Release I), TR/PA/92/86, October 1992.
       
   315 *
       
   316 *  NOTE
       
   317 *
       
   318 *  The routine spm_read_hbm reads the matrix "as is", due to which zero
       
   319 *  and/or duplicate elements can appear in the matrix.
       
   320 *
       
   321 *  RETURNS
       
   322 *
       
   323 *  If no error occured, the routine returns a pointer to the matrix
       
   324 *  created. Otherwise, the routine prints an appropriate error message
       
   325 *  and returns NULL. */
       
   326 
       
   327 SPM *spm_read_hbm(const char *fname)
       
   328 {     SPM *A = NULL;
       
   329       HBM *hbm;
       
   330       int nrow, ncol, nnzero, i, j, beg, end, ptr, *colptr, *rowind;
       
   331       double val, *values;
       
   332       char *mxtype;
       
   333       hbm = hbm_read_mat(fname);
       
   334       if (hbm == NULL)
       
   335       {  xprintf("spm_read_hbm: unable to read matrix\n");
       
   336          goto fini;
       
   337       }
       
   338       mxtype = hbm->mxtype;
       
   339       nrow = hbm->nrow;
       
   340       ncol = hbm->ncol;
       
   341       nnzero = hbm->nnzero;
       
   342       colptr = hbm->colptr;
       
   343       rowind = hbm->rowind;
       
   344       values = hbm->values;
       
   345       if (!(strcmp(mxtype, "RSA") == 0 || strcmp(mxtype, "PSA") == 0 ||
       
   346             strcmp(mxtype, "RUA") == 0 || strcmp(mxtype, "PUA") == 0 ||
       
   347             strcmp(mxtype, "RRA") == 0 || strcmp(mxtype, "PRA") == 0))
       
   348       {  xprintf("spm_read_hbm: matrix type `%s' not supported\n",
       
   349             mxtype);
       
   350          goto fini;
       
   351       }
       
   352       A = spm_create_mat(nrow, ncol);
       
   353       if (mxtype[1] == 'S' || mxtype[1] == 'U')
       
   354          xassert(nrow == ncol);
       
   355       for (j = 1; j <= ncol; j++)
       
   356       {  beg = colptr[j];
       
   357          end = colptr[j+1];
       
   358          xassert(1 <= beg && beg <= end && end <= nnzero + 1);
       
   359          for (ptr = beg; ptr < end; ptr++)
       
   360          {  i = rowind[ptr];
       
   361             xassert(1 <= i && i <= nrow);
       
   362             if (mxtype[0] == 'R')
       
   363                val = values[ptr];
       
   364             else
       
   365                val = 1.0;
       
   366             spm_new_elem(A, i, j, val);
       
   367             if (mxtype[1] == 'S' && i != j)
       
   368                spm_new_elem(A, j, i, val);
       
   369          }
       
   370       }
       
   371 fini: if (hbm != NULL) hbm_free_mat(hbm);
       
   372       return A;
       
   373 }
       
   374 
       
   375 /***********************************************************************
       
   376 *  NAME
       
   377 *
       
   378 *  spm_count_nnz - determine number of non-zeros in sparse matrix
       
   379 *
       
   380 *  SYNOPSIS
       
   381 *
       
   382 *  #include "glpspm.h"
       
   383 *  int spm_count_nnz(const SPM *A);
       
   384 *
       
   385 *  RETURNS
       
   386 *
       
   387 *  The routine spm_count_nnz returns the number of structural non-zero
       
   388 *  elements in the specified sparse matrix. */
       
   389 
       
   390 int spm_count_nnz(const SPM *A)
       
   391 {     SPME *e;
       
   392       int i, nnz = 0;
       
   393       for (i = 1; i <= A->m; i++)
       
   394          for (e = A->row[i]; e != NULL; e = e->r_next) nnz++;
       
   395       return nnz;
       
   396 }
       
   397 
       
   398 /***********************************************************************
       
   399 *  NAME
       
   400 *
       
   401 *  spm_drop_zeros - remove zero elements from sparse matrix
       
   402 *
       
   403 *  SYNOPSIS
       
   404 *
       
   405 *  #include "glpspm.h"
       
   406 *  int spm_drop_zeros(SPM *A, double eps);
       
   407 *
       
   408 *  DESCRIPTION
       
   409 *
       
   410 *  The routine spm_drop_zeros removes all elements from the specified
       
   411 *  sparse matrix, whose absolute value is less than eps.
       
   412 *
       
   413 *  If the parameter eps is 0, only zero elements are removed from the
       
   414 *  matrix.
       
   415 *
       
   416 *  RETURNS
       
   417 *
       
   418 *  The routine returns the number of elements removed. */
       
   419 
       
   420 int spm_drop_zeros(SPM *A, double eps)
       
   421 {     SPME *e, *next;
       
   422       int i, count = 0;
       
   423       for (i = 1; i <= A->m; i++)
       
   424       {  for (e = A->row[i]; e != NULL; e = next)
       
   425          {  next = e->r_next;
       
   426             if (e->val == 0.0 || fabs(e->val) < eps)
       
   427             {  /* remove element from the row list */
       
   428                if (e->r_prev == NULL)
       
   429                   A->row[e->i] = e->r_next;
       
   430                else
       
   431                   e->r_prev->r_next = e->r_next;
       
   432                if (e->r_next == NULL)
       
   433                   ;
       
   434                else
       
   435                   e->r_next->r_prev = e->r_prev;
       
   436                /* remove element from the column list */
       
   437                if (e->c_prev == NULL)
       
   438                   A->col[e->j] = e->c_next;
       
   439                else
       
   440                   e->c_prev->c_next = e->c_next;
       
   441                if (e->c_next == NULL)
       
   442                   ;
       
   443                else
       
   444                   e->c_next->c_prev = e->c_prev;
       
   445                /* return element to the memory pool */
       
   446                dmp_free_atom(A->pool, e, sizeof(SPME));
       
   447                count++;
       
   448             }
       
   449          }
       
   450       }
       
   451       return count;
       
   452 }
       
   453 
       
   454 /***********************************************************************
       
   455 *  NAME
       
   456 *
       
   457 *  spm_read_mat - read sparse matrix from text file
       
   458 *
       
   459 *  SYNOPSIS
       
   460 *
       
   461 *  #include "glpspm.h"
       
   462 *  SPM *spm_read_mat(const char *fname);
       
   463 *
       
   464 *  DESCRIPTION
       
   465 *
       
   466 *  The routine reads a sparse matrix from a text file whose name is
       
   467 *  specified by the parameter fname.
       
   468 *
       
   469 *  For the file format see description of the routine spm_write_mat.
       
   470 *
       
   471 *  RETURNS
       
   472 *
       
   473 *  On success the routine returns a pointer to the matrix created,
       
   474 *  otherwise NULL. */
       
   475 
       
   476 #if 1
       
   477 SPM *spm_read_mat(const char *fname)
       
   478 {     xassert(fname != fname);
       
   479       return NULL;
       
   480 }
       
   481 #else
       
   482 SPM *spm_read_mat(const char *fname)
       
   483 {     SPM *A = NULL;
       
   484       PDS *pds;
       
   485       jmp_buf jump;
       
   486       int i, j, k, m, n, nnz, fail = 0;
       
   487       double val;
       
   488       xprintf("spm_read_mat: reading matrix from `%s'...\n", fname);
       
   489       pds = pds_open_file(fname);
       
   490       if (pds == NULL)
       
   491       {  xprintf("spm_read_mat: unable to open `%s' - %s\n", fname,
       
   492             strerror(errno));
       
   493          fail = 1;
       
   494          goto done;
       
   495       }
       
   496       if (setjmp(jump))
       
   497       {  fail = 1;
       
   498          goto done;
       
   499       }
       
   500       pds_set_jump(pds, jump);
       
   501       /* number of rows, number of columns, number of non-zeros */
       
   502       m = pds_scan_int(pds);
       
   503       if (m < 0)
       
   504          pds_error(pds, "invalid number of rows\n");
       
   505       n = pds_scan_int(pds);
       
   506       if (n < 0)
       
   507          pds_error(pds, "invalid number of columns\n");
       
   508       nnz = pds_scan_int(pds);
       
   509       if (nnz < 0)
       
   510          pds_error(pds, "invalid number of non-zeros\n");
       
   511       /* create matrix */
       
   512       xprintf("spm_read_mat: %d rows, %d columns, %d non-zeros\n",
       
   513          m, n, nnz);
       
   514       A = spm_create_mat(m, n);
       
   515       /* read matrix elements */
       
   516       for (k = 1; k <= nnz; k++)
       
   517       {  /* row index, column index, element value */
       
   518          i = pds_scan_int(pds);
       
   519          if (!(1 <= i && i <= m))
       
   520             pds_error(pds, "row index out of range\n");
       
   521          j = pds_scan_int(pds);
       
   522          if (!(1 <= j && j <= n))
       
   523             pds_error(pds, "column index out of range\n");
       
   524          val = pds_scan_num(pds);
       
   525          /* add new element to the matrix */
       
   526          spm_new_elem(A, i, j, val);
       
   527       }
       
   528       xprintf("spm_read_mat: %d lines were read\n", pds->count);
       
   529 done: if (pds != NULL) pds_close_file(pds);
       
   530       if (fail && A != NULL) spm_delete_mat(A), A = NULL;
       
   531       return A;
       
   532 }
       
   533 #endif
       
   534 
       
   535 /***********************************************************************
       
   536 *  NAME
       
   537 *
       
   538 *  spm_write_mat - write sparse matrix to text file
       
   539 *
       
   540 *  SYNOPSIS
       
   541 *
       
   542 *  #include "glpspm.h"
       
   543 *  int spm_write_mat(const SPM *A, const char *fname);
       
   544 *
       
   545 *  DESCRIPTION
       
   546 *
       
   547 *  The routine spm_write_mat writes the specified sparse matrix to a
       
   548 *  text file whose name is specified by the parameter fname. This file
       
   549 *  can be read back with the routine spm_read_mat.
       
   550 *
       
   551 *  RETURNS
       
   552 *
       
   553 *  On success the routine returns zero, otherwise non-zero.
       
   554 *
       
   555 *  FILE FORMAT
       
   556 *
       
   557 *  The file created by the routine spm_write_mat is a plain text file,
       
   558 *  which contains the following information:
       
   559 *
       
   560 *     m n nnz
       
   561 *     row[1] col[1] val[1]
       
   562 *     row[2] col[2] val[2]
       
   563 *     . . .
       
   564 *     row[nnz] col[nnz] val[nnz]
       
   565 *
       
   566 *  where:
       
   567 *  m is the number of rows;
       
   568 *  n is the number of columns;
       
   569 *  nnz is the number of non-zeros;
       
   570 *  row[k], k = 1,...,nnz, are row indices;
       
   571 *  col[k], k = 1,...,nnz, are column indices;
       
   572 *  val[k], k = 1,...,nnz, are element values. */
       
   573 
       
   574 #if 1
       
   575 int spm_write_mat(const SPM *A, const char *fname)
       
   576 {     xassert(A != A);
       
   577       xassert(fname != fname);
       
   578       return 0;
       
   579 }
       
   580 #else
       
   581 int spm_write_mat(const SPM *A, const char *fname)
       
   582 {     FILE *fp;
       
   583       int i, nnz, ret = 0;
       
   584       xprintf("spm_write_mat: writing matrix to `%s'...\n", fname);
       
   585       fp = fopen(fname, "w");
       
   586       if (fp == NULL)
       
   587       {  xprintf("spm_write_mat: unable to create `%s' - %s\n", fname,
       
   588             strerror(errno));
       
   589          ret = 1;
       
   590          goto done;
       
   591       }
       
   592       /* number of rows, number of columns, number of non-zeros */
       
   593       nnz = spm_count_nnz(A);
       
   594       fprintf(fp, "%d %d %d\n", A->m, A->n, nnz);
       
   595       /* walk through rows of the matrix */
       
   596       for (i = 1; i <= A->m; i++)
       
   597       {  SPME *e;
       
   598          /* walk through elements of i-th row */
       
   599          for (e = A->row[i]; e != NULL; e = e->r_next)
       
   600          {  /* row index, column index, element value */
       
   601             fprintf(fp, "%d %d %.*g\n", e->i, e->j, DBL_DIG, e->val);
       
   602          }
       
   603       }
       
   604       fflush(fp);
       
   605       if (ferror(fp))
       
   606       {  xprintf("spm_write_mat: writing error on `%s' - %s\n", fname,
       
   607             strerror(errno));
       
   608          ret = 1;
       
   609          goto done;
       
   610       }
       
   611       xprintf("spm_write_mat: %d lines were written\n", 1 + nnz);
       
   612 done: if (fp != NULL) fclose(fp);
       
   613       return ret;
       
   614 }
       
   615 #endif
       
   616 
       
   617 /***********************************************************************
       
   618 *  NAME
       
   619 *
       
   620 *  spm_transpose - transpose sparse matrix
       
   621 *
       
   622 *  SYNOPSIS
       
   623 *
       
   624 *  #include "glpspm.h"
       
   625 *  SPM *spm_transpose(const SPM *A);
       
   626 *
       
   627 *  RETURNS
       
   628 *
       
   629 *  The routine computes and returns sparse matrix B, which is a matrix
       
   630 *  transposed to sparse matrix A. */
       
   631 
       
   632 SPM *spm_transpose(const SPM *A)
       
   633 {     SPM *B;
       
   634       int i;
       
   635       B = spm_create_mat(A->n, A->m);
       
   636       for (i = 1; i <= A->m; i++)
       
   637       {  SPME *e;
       
   638          for (e = A->row[i]; e != NULL; e = e->r_next)
       
   639             spm_new_elem(B, e->j, i, e->val);
       
   640       }
       
   641       return B;
       
   642 }
       
   643 
       
   644 SPM *spm_add_sym(const SPM *A, const SPM *B)
       
   645 {     /* add two sparse matrices (symbolic phase) */
       
   646       SPM *C;
       
   647       int i, j, *flag;
       
   648       xassert(A->m == B->m);
       
   649       xassert(A->n == B->n);
       
   650       /* create resultant matrix */
       
   651       C = spm_create_mat(A->m, A->n);
       
   652       /* allocate and clear the flag array */
       
   653       flag = xcalloc(1+C->n, sizeof(int));
       
   654       for (j = 1; j <= C->n; j++)
       
   655          flag[j] = 0;
       
   656       /* compute pattern of C = A + B */
       
   657       for (i = 1; i <= C->m; i++)
       
   658       {  SPME *e;
       
   659          /* at the beginning i-th row of C is empty */
       
   660          /* (i-th row of C) := (i-th row of C) union (i-th row of A) */
       
   661          for (e = A->row[i]; e != NULL; e = e->r_next)
       
   662          {  /* (note that i-th row of A may have duplicate elements) */
       
   663             j = e->j;
       
   664             if (!flag[j])
       
   665             {  spm_new_elem(C, i, j, 0.0);
       
   666                flag[j] = 1;
       
   667             }
       
   668          }
       
   669          /* (i-th row of C) := (i-th row of C) union (i-th row of B) */
       
   670          for (e = B->row[i]; e != NULL; e = e->r_next)
       
   671          {  /* (note that i-th row of B may have duplicate elements) */
       
   672             j = e->j;
       
   673             if (!flag[j])
       
   674             {  spm_new_elem(C, i, j, 0.0);
       
   675                flag[j] = 1;
       
   676             }
       
   677          }
       
   678          /* reset the flag array */
       
   679          for (e = C->row[i]; e != NULL; e = e->r_next)
       
   680             flag[e->j] = 0;
       
   681       }
       
   682       /* check and deallocate the flag array */
       
   683       for (j = 1; j <= C->n; j++)
       
   684          xassert(!flag[j]);
       
   685       xfree(flag);
       
   686       return C;
       
   687 }
       
   688 
       
   689 void spm_add_num(SPM *C, double alfa, const SPM *A, double beta,
       
   690       const SPM *B)
       
   691 {     /* add two sparse matrices (numeric phase) */
       
   692       int i, j;
       
   693       double *work;
       
   694       /* allocate and clear the working array */
       
   695       work = xcalloc(1+C->n, sizeof(double));
       
   696       for (j = 1; j <= C->n; j++)
       
   697          work[j] = 0.0;
       
   698       /* compute matrix C = alfa * A + beta * B */
       
   699       for (i = 1; i <= C->n; i++)
       
   700       {  SPME *e;
       
   701          /* work := alfa * (i-th row of A) + beta * (i-th row of B) */
       
   702          /* (note that A and/or B may have duplicate elements) */
       
   703          for (e = A->row[i]; e != NULL; e = e->r_next)
       
   704             work[e->j] += alfa * e->val;
       
   705          for (e = B->row[i]; e != NULL; e = e->r_next)
       
   706             work[e->j] += beta * e->val;
       
   707          /* (i-th row of C) := work, work := 0 */
       
   708          for (e = C->row[i]; e != NULL; e = e->r_next)
       
   709          {  j = e->j;
       
   710             e->val = work[j];
       
   711             work[j] = 0.0;
       
   712          }
       
   713       }
       
   714       /* check and deallocate the working array */
       
   715       for (j = 1; j <= C->n; j++)
       
   716          xassert(work[j] == 0.0);
       
   717       xfree(work);
       
   718       return;
       
   719 }
       
   720 
       
   721 SPM *spm_add_mat(double alfa, const SPM *A, double beta, const SPM *B)
       
   722 {     /* add two sparse matrices (driver routine) */
       
   723       SPM *C;
       
   724       C = spm_add_sym(A, B);
       
   725       spm_add_num(C, alfa, A, beta, B);
       
   726       return C;
       
   727 }
       
   728 
       
   729 SPM *spm_mul_sym(const SPM *A, const SPM *B)
       
   730 {     /* multiply two sparse matrices (symbolic phase) */
       
   731       int i, j, k, *flag;
       
   732       SPM *C;
       
   733       xassert(A->n == B->m);
       
   734       /* create resultant matrix */
       
   735       C = spm_create_mat(A->m, B->n);
       
   736       /* allocate and clear the flag array */
       
   737       flag = xcalloc(1+C->n, sizeof(int));
       
   738       for (j = 1; j <= C->n; j++)
       
   739          flag[j] = 0;
       
   740       /* compute pattern of C = A * B */
       
   741       for (i = 1; i <= C->m; i++)
       
   742       {  SPME *e, *ee;
       
   743          /* compute pattern of i-th row of C */
       
   744          for (e = A->row[i]; e != NULL; e = e->r_next)
       
   745          {  k = e->j;
       
   746             for (ee = B->row[k]; ee != NULL; ee = ee->r_next)
       
   747             {  j = ee->j;
       
   748                /* if a[i,k] != 0 and b[k,j] != 0 then c[i,j] != 0 */
       
   749                if (!flag[j])
       
   750                {  /* c[i,j] does not exist, so create it */
       
   751                   spm_new_elem(C, i, j, 0.0);
       
   752                   flag[j] = 1;
       
   753                }
       
   754             }
       
   755          }
       
   756          /* reset the flag array */
       
   757          for (e = C->row[i]; e != NULL; e = e->r_next)
       
   758             flag[e->j] = 0;
       
   759       }
       
   760       /* check and deallocate the flag array */
       
   761       for (j = 1; j <= C->n; j++)
       
   762          xassert(!flag[j]);
       
   763       xfree(flag);
       
   764       return C;
       
   765 }
       
   766 
       
   767 void spm_mul_num(SPM *C, const SPM *A, const SPM *B)
       
   768 {     /* multiply two sparse matrices (numeric phase) */
       
   769       int i, j;
       
   770       double *work;
       
   771       /* allocate and clear the working array */
       
   772       work = xcalloc(1+A->n, sizeof(double));
       
   773       for (j = 1; j <= A->n; j++)
       
   774          work[j] = 0.0;
       
   775       /* compute matrix C = A * B */
       
   776       for (i = 1; i <= C->m; i++)
       
   777       {  SPME *e, *ee;
       
   778          double temp;
       
   779          /* work := (i-th row of A) */
       
   780          /* (note that A may have duplicate elements) */
       
   781          for (e = A->row[i]; e != NULL; e = e->r_next)
       
   782             work[e->j] += e->val;
       
   783          /* compute i-th row of C */
       
   784          for (e = C->row[i]; e != NULL; e = e->r_next)
       
   785          {  j = e->j;
       
   786             /* c[i,j] := work * (j-th column of B) */
       
   787             temp = 0.0;
       
   788             for (ee = B->col[j]; ee != NULL; ee = ee->c_next)
       
   789                temp += work[ee->i] * ee->val;
       
   790             e->val = temp;
       
   791          }
       
   792          /* reset the working array */
       
   793          for (e = A->row[i]; e != NULL; e = e->r_next)
       
   794             work[e->j] = 0.0;
       
   795       }
       
   796       /* check and deallocate the working array */
       
   797       for (j = 1; j <= A->n; j++)
       
   798          xassert(work[j] == 0.0);
       
   799       xfree(work);
       
   800       return;
       
   801 }
       
   802 
       
   803 SPM *spm_mul_mat(const SPM *A, const SPM *B)
       
   804 {     /* multiply two sparse matrices (driver routine) */
       
   805       SPM *C;
       
   806       C = spm_mul_sym(A, B);
       
   807       spm_mul_num(C, A, B);
       
   808       return C;
       
   809 }
       
   810 
       
   811 PER *spm_create_per(int n)
       
   812 {     /* create permutation matrix */
       
   813       PER *P;
       
   814       int k;
       
   815       xassert(n >= 0);
       
   816       P = xmalloc(sizeof(PER));
       
   817       P->n = n;
       
   818       P->row = xcalloc(1+n, sizeof(int));
       
   819       P->col = xcalloc(1+n, sizeof(int));
       
   820       /* initially it is identity matrix */
       
   821       for (k = 1; k <= n; k++)
       
   822          P->row[k] = P->col[k] = k;
       
   823       return P;
       
   824 }
       
   825 
       
   826 void spm_check_per(PER *P)
       
   827 {     /* check permutation matrix for correctness */
       
   828       int i, j;
       
   829       xassert(P->n >= 0);
       
   830       for (i = 1; i <= P->n; i++)
       
   831       {  j = P->row[i];
       
   832          xassert(1 <= j && j <= P->n);
       
   833          xassert(P->col[j] == i);
       
   834       }
       
   835       return;
       
   836 }
       
   837 
       
   838 void spm_delete_per(PER *P)
       
   839 {     /* delete permutation matrix */
       
   840       xfree(P->row);
       
   841       xfree(P->col);
       
   842       xfree(P);
       
   843       return;
       
   844 }
       
   845 
       
   846 /* eof */