lemon-project-template-glpk
diff deps/glpk/src/colamd/colamd.c @ 9:33de93886c88
Import GLPK 4.47
author | Alpar Juttner <alpar@cs.elte.hu> |
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date | Sun, 06 Nov 2011 20:59:10 +0100 |
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1.1 --- /dev/null Thu Jan 01 00:00:00 1970 +0000 1.2 +++ b/deps/glpk/src/colamd/colamd.c Sun Nov 06 20:59:10 2011 +0100 1.3 @@ -0,0 +1,3622 @@ 1.4 +/* ========================================================================== */ 1.5 +/* === colamd/symamd - a sparse matrix column ordering algorithm ============ */ 1.6 +/* ========================================================================== */ 1.7 + 1.8 +/* COLAMD / SYMAMD 1.9 + 1.10 + colamd: an approximate minimum degree column ordering algorithm, 1.11 + for LU factorization of symmetric or unsymmetric matrices, 1.12 + QR factorization, least squares, interior point methods for 1.13 + linear programming problems, and other related problems. 1.14 + 1.15 + symamd: an approximate minimum degree ordering algorithm for Cholesky 1.16 + factorization of symmetric matrices. 1.17 + 1.18 + Purpose: 1.19 + 1.20 + Colamd computes a permutation Q such that the Cholesky factorization of 1.21 + (AQ)'(AQ) has less fill-in and requires fewer floating point operations 1.22 + than A'A. This also provides a good ordering for sparse partial 1.23 + pivoting methods, P(AQ) = LU, where Q is computed prior to numerical 1.24 + factorization, and P is computed during numerical factorization via 1.25 + conventional partial pivoting with row interchanges. Colamd is the 1.26 + column ordering method used in SuperLU, part of the ScaLAPACK library. 1.27 + It is also available as built-in function in MATLAB Version 6, 1.28 + available from MathWorks, Inc. (http://www.mathworks.com). This 1.29 + routine can be used in place of colmmd in MATLAB. 1.30 + 1.31 + Symamd computes a permutation P of a symmetric matrix A such that the 1.32 + Cholesky factorization of PAP' has less fill-in and requires fewer 1.33 + floating point operations than A. Symamd constructs a matrix M such 1.34 + that M'M has the same nonzero pattern of A, and then orders the columns 1.35 + of M using colmmd. The column ordering of M is then returned as the 1.36 + row and column ordering P of A. 1.37 + 1.38 + Authors: 1.39 + 1.40 + The authors of the code itself are Stefan I. Larimore and Timothy A. 1.41 + Davis (davis at cise.ufl.edu), University of Florida. The algorithm was 1.42 + developed in collaboration with John Gilbert, Xerox PARC, and Esmond 1.43 + Ng, Oak Ridge National Laboratory. 1.44 + 1.45 + Acknowledgements: 1.46 + 1.47 + This work was supported by the National Science Foundation, under 1.48 + grants DMS-9504974 and DMS-9803599. 1.49 + 1.50 + Copyright and License: 1.51 + 1.52 + Copyright (c) 1998-2007, Timothy A. Davis, All Rights Reserved. 1.53 + COLAMD is also available under alternate licenses, contact T. Davis 1.54 + for details. 1.55 + 1.56 + This library is free software; you can redistribute it and/or 1.57 + modify it under the terms of the GNU Lesser General Public 1.58 + License as published by the Free Software Foundation; either 1.59 + version 2.1 of the License, or (at your option) any later version. 1.60 + 1.61 + This library is distributed in the hope that it will be useful, 1.62 + but WITHOUT ANY WARRANTY; without even the implied warranty of 1.63 + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU 1.64 + Lesser General Public License for more details. 1.65 + 1.66 + You should have received a copy of the GNU Lesser General Public 1.67 + License along with this library; if not, write to the Free Software 1.68 + Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 1.69 + USA 1.70 + 1.71 + Permission is hereby granted to use or copy this program under the 1.72 + terms of the GNU LGPL, provided that the Copyright, this License, 1.73 + and the Availability of the original version is retained on all copies. 1.74 + User documentation of any code that uses this code or any modified 1.75 + version of this code must cite the Copyright, this License, the 1.76 + Availability note, and "Used by permission." Permission to modify 1.77 + the code and to distribute modified code is granted, provided the 1.78 + Copyright, this License, and the Availability note are retained, 1.79 + and a notice that the code was modified is included. 1.80 + 1.81 + Availability: 1.82 + 1.83 + The colamd/symamd library is available at 1.84 + 1.85 + http://www.cise.ufl.edu/research/sparse/colamd/ 1.86 + 1.87 + This is the http://www.cise.ufl.edu/research/sparse/colamd/colamd.c 1.88 + file. It requires the colamd.h file. It is required by the colamdmex.c 1.89 + and symamdmex.c files, for the MATLAB interface to colamd and symamd. 1.90 + Appears as ACM Algorithm 836. 1.91 + 1.92 + See the ChangeLog file for changes since Version 1.0. 1.93 + 1.94 + References: 1.95 + 1.96 + T. A. Davis, J. R. Gilbert, S. Larimore, E. Ng, An approximate column 1.97 + minimum degree ordering algorithm, ACM Transactions on Mathematical 1.98 + Software, vol. 30, no. 3., pp. 353-376, 2004. 1.99 + 1.100 + T. A. Davis, J. R. Gilbert, S. Larimore, E. Ng, Algorithm 836: COLAMD, 1.101 + an approximate column minimum degree ordering algorithm, ACM 1.102 + Transactions on Mathematical Software, vol. 30, no. 3., pp. 377-380, 1.103 + 2004. 1.104 + 1.105 +*/ 1.106 + 1.107 +/* ========================================================================== */ 1.108 +/* === Description of user-callable routines ================================ */ 1.109 +/* ========================================================================== */ 1.110 + 1.111 +/* COLAMD includes both int and UF_long versions of all its routines. The 1.112 + * description below is for the int version. For UF_long, all int arguments 1.113 + * become UF_long. UF_long is normally defined as long, except for WIN64. 1.114 + 1.115 + ---------------------------------------------------------------------------- 1.116 + colamd_recommended: 1.117 + ---------------------------------------------------------------------------- 1.118 + 1.119 + C syntax: 1.120 + 1.121 + #include "colamd.h" 1.122 + size_t colamd_recommended (int nnz, int n_row, int n_col) ; 1.123 + size_t colamd_l_recommended (UF_long nnz, UF_long n_row, 1.124 + UF_long n_col) ; 1.125 + 1.126 + Purpose: 1.127 + 1.128 + Returns recommended value of Alen for use by colamd. Returns 0 1.129 + if any input argument is negative. The use of this routine 1.130 + is optional. Not needed for symamd, which dynamically allocates 1.131 + its own memory. 1.132 + 1.133 + Note that in v2.4 and earlier, these routines returned int or long. 1.134 + They now return a value of type size_t. 1.135 + 1.136 + Arguments (all input arguments): 1.137 + 1.138 + int nnz ; Number of nonzeros in the matrix A. This must 1.139 + be the same value as p [n_col] in the call to 1.140 + colamd - otherwise you will get a wrong value 1.141 + of the recommended memory to use. 1.142 + 1.143 + int n_row ; Number of rows in the matrix A. 1.144 + 1.145 + int n_col ; Number of columns in the matrix A. 1.146 + 1.147 + ---------------------------------------------------------------------------- 1.148 + colamd_set_defaults: 1.149 + ---------------------------------------------------------------------------- 1.150 + 1.151 + C syntax: 1.152 + 1.153 + #include "colamd.h" 1.154 + colamd_set_defaults (double knobs [COLAMD_KNOBS]) ; 1.155 + colamd_l_set_defaults (double knobs [COLAMD_KNOBS]) ; 1.156 + 1.157 + Purpose: 1.158 + 1.159 + Sets the default parameters. The use of this routine is optional. 1.160 + 1.161 + Arguments: 1.162 + 1.163 + double knobs [COLAMD_KNOBS] ; Output only. 1.164 + 1.165 + NOTE: the meaning of the dense row/col knobs has changed in v2.4 1.166 + 1.167 + knobs [0] and knobs [1] control dense row and col detection: 1.168 + 1.169 + Colamd: rows with more than 1.170 + max (16, knobs [COLAMD_DENSE_ROW] * sqrt (n_col)) 1.171 + entries are removed prior to ordering. Columns with more than 1.172 + max (16, knobs [COLAMD_DENSE_COL] * sqrt (MIN (n_row,n_col))) 1.173 + entries are removed prior to 1.174 + ordering, and placed last in the output column ordering. 1.175 + 1.176 + Symamd: uses only knobs [COLAMD_DENSE_ROW], which is knobs [0]. 1.177 + Rows and columns with more than 1.178 + max (16, knobs [COLAMD_DENSE_ROW] * sqrt (n)) 1.179 + entries are removed prior to ordering, and placed last in the 1.180 + output ordering. 1.181 + 1.182 + COLAMD_DENSE_ROW and COLAMD_DENSE_COL are defined as 0 and 1, 1.183 + respectively, in colamd.h. Default values of these two knobs 1.184 + are both 10. Currently, only knobs [0] and knobs [1] are 1.185 + used, but future versions may use more knobs. If so, they will 1.186 + be properly set to their defaults by the future version of 1.187 + colamd_set_defaults, so that the code that calls colamd will 1.188 + not need to change, assuming that you either use 1.189 + colamd_set_defaults, or pass a (double *) NULL pointer as the 1.190 + knobs array to colamd or symamd. 1.191 + 1.192 + knobs [2]: aggressive absorption 1.193 + 1.194 + knobs [COLAMD_AGGRESSIVE] controls whether or not to do 1.195 + aggressive absorption during the ordering. Default is TRUE. 1.196 + 1.197 + 1.198 + ---------------------------------------------------------------------------- 1.199 + colamd: 1.200 + ---------------------------------------------------------------------------- 1.201 + 1.202 + C syntax: 1.203 + 1.204 + #include "colamd.h" 1.205 + int colamd (int n_row, int n_col, int Alen, int *A, int *p, 1.206 + double knobs [COLAMD_KNOBS], int stats [COLAMD_STATS]) ; 1.207 + UF_long colamd_l (UF_long n_row, UF_long n_col, UF_long Alen, 1.208 + UF_long *A, UF_long *p, double knobs [COLAMD_KNOBS], 1.209 + UF_long stats [COLAMD_STATS]) ; 1.210 + 1.211 + Purpose: 1.212 + 1.213 + Computes a column ordering (Q) of A such that P(AQ)=LU or 1.214 + (AQ)'AQ=LL' have less fill-in and require fewer floating point 1.215 + operations than factorizing the unpermuted matrix A or A'A, 1.216 + respectively. 1.217 + 1.218 + Returns: 1.219 + 1.220 + TRUE (1) if successful, FALSE (0) otherwise. 1.221 + 1.222 + Arguments: 1.223 + 1.224 + int n_row ; Input argument. 1.225 + 1.226 + Number of rows in the matrix A. 1.227 + Restriction: n_row >= 0. 1.228 + Colamd returns FALSE if n_row is negative. 1.229 + 1.230 + int n_col ; Input argument. 1.231 + 1.232 + Number of columns in the matrix A. 1.233 + Restriction: n_col >= 0. 1.234 + Colamd returns FALSE if n_col is negative. 1.235 + 1.236 + int Alen ; Input argument. 1.237 + 1.238 + Restriction (see note): 1.239 + Alen >= 2*nnz + 6*(n_col+1) + 4*(n_row+1) + n_col 1.240 + Colamd returns FALSE if these conditions are not met. 1.241 + 1.242 + Note: this restriction makes an modest assumption regarding 1.243 + the size of the two typedef's structures in colamd.h. 1.244 + We do, however, guarantee that 1.245 + 1.246 + Alen >= colamd_recommended (nnz, n_row, n_col) 1.247 + 1.248 + will be sufficient. Note: the macro version does not check 1.249 + for integer overflow, and thus is not recommended. Use 1.250 + the colamd_recommended routine instead. 1.251 + 1.252 + int A [Alen] ; Input argument, undefined on output. 1.253 + 1.254 + A is an integer array of size Alen. Alen must be at least as 1.255 + large as the bare minimum value given above, but this is very 1.256 + low, and can result in excessive run time. For best 1.257 + performance, we recommend that Alen be greater than or equal to 1.258 + colamd_recommended (nnz, n_row, n_col), which adds 1.259 + nnz/5 to the bare minimum value given above. 1.260 + 1.261 + On input, the row indices of the entries in column c of the 1.262 + matrix are held in A [(p [c]) ... (p [c+1]-1)]. The row indices 1.263 + in a given column c need not be in ascending order, and 1.264 + duplicate row indices may be be present. However, colamd will 1.265 + work a little faster if both of these conditions are met 1.266 + (Colamd puts the matrix into this format, if it finds that the 1.267 + the conditions are not met). 1.268 + 1.269 + The matrix is 0-based. That is, rows are in the range 0 to 1.270 + n_row-1, and columns are in the range 0 to n_col-1. Colamd 1.271 + returns FALSE if any row index is out of range. 1.272 + 1.273 + The contents of A are modified during ordering, and are 1.274 + undefined on output. 1.275 + 1.276 + int p [n_col+1] ; Both input and output argument. 1.277 + 1.278 + p is an integer array of size n_col+1. On input, it holds the 1.279 + "pointers" for the column form of the matrix A. Column c of 1.280 + the matrix A is held in A [(p [c]) ... (p [c+1]-1)]. The first 1.281 + entry, p [0], must be zero, and p [c] <= p [c+1] must hold 1.282 + for all c in the range 0 to n_col-1. The value p [n_col] is 1.283 + thus the total number of entries in the pattern of the matrix A. 1.284 + Colamd returns FALSE if these conditions are not met. 1.285 + 1.286 + On output, if colamd returns TRUE, the array p holds the column 1.287 + permutation (Q, for P(AQ)=LU or (AQ)'(AQ)=LL'), where p [0] is 1.288 + the first column index in the new ordering, and p [n_col-1] is 1.289 + the last. That is, p [k] = j means that column j of A is the 1.290 + kth pivot column, in AQ, where k is in the range 0 to n_col-1 1.291 + (p [0] = j means that column j of A is the first column in AQ). 1.292 + 1.293 + If colamd returns FALSE, then no permutation is returned, and 1.294 + p is undefined on output. 1.295 + 1.296 + double knobs [COLAMD_KNOBS] ; Input argument. 1.297 + 1.298 + See colamd_set_defaults for a description. 1.299 + 1.300 + int stats [COLAMD_STATS] ; Output argument. 1.301 + 1.302 + Statistics on the ordering, and error status. 1.303 + See colamd.h for related definitions. 1.304 + Colamd returns FALSE if stats is not present. 1.305 + 1.306 + stats [0]: number of dense or empty rows ignored. 1.307 + 1.308 + stats [1]: number of dense or empty columns ignored (and 1.309 + ordered last in the output permutation p) 1.310 + Note that a row can become "empty" if it 1.311 + contains only "dense" and/or "empty" columns, 1.312 + and similarly a column can become "empty" if it 1.313 + only contains "dense" and/or "empty" rows. 1.314 + 1.315 + stats [2]: number of garbage collections performed. 1.316 + This can be excessively high if Alen is close 1.317 + to the minimum required value. 1.318 + 1.319 + stats [3]: status code. < 0 is an error code. 1.320 + > 1 is a warning or notice. 1.321 + 1.322 + 0 OK. Each column of the input matrix contained 1.323 + row indices in increasing order, with no 1.324 + duplicates. 1.325 + 1.326 + 1 OK, but columns of input matrix were jumbled 1.327 + (unsorted columns or duplicate entries). Colamd 1.328 + had to do some extra work to sort the matrix 1.329 + first and remove duplicate entries, but it 1.330 + still was able to return a valid permutation 1.331 + (return value of colamd was TRUE). 1.332 + 1.333 + stats [4]: highest numbered column that 1.334 + is unsorted or has duplicate 1.335 + entries. 1.336 + stats [5]: last seen duplicate or 1.337 + unsorted row index. 1.338 + stats [6]: number of duplicate or 1.339 + unsorted row indices. 1.340 + 1.341 + -1 A is a null pointer 1.342 + 1.343 + -2 p is a null pointer 1.344 + 1.345 + -3 n_row is negative 1.346 + 1.347 + stats [4]: n_row 1.348 + 1.349 + -4 n_col is negative 1.350 + 1.351 + stats [4]: n_col 1.352 + 1.353 + -5 number of nonzeros in matrix is negative 1.354 + 1.355 + stats [4]: number of nonzeros, p [n_col] 1.356 + 1.357 + -6 p [0] is nonzero 1.358 + 1.359 + stats [4]: p [0] 1.360 + 1.361 + -7 A is too small 1.362 + 1.363 + stats [4]: required size 1.364 + stats [5]: actual size (Alen) 1.365 + 1.366 + -8 a column has a negative number of entries 1.367 + 1.368 + stats [4]: column with < 0 entries 1.369 + stats [5]: number of entries in col 1.370 + 1.371 + -9 a row index is out of bounds 1.372 + 1.373 + stats [4]: column with bad row index 1.374 + stats [5]: bad row index 1.375 + stats [6]: n_row, # of rows of matrx 1.376 + 1.377 + -10 (unused; see symamd.c) 1.378 + 1.379 + -999 (unused; see symamd.c) 1.380 + 1.381 + Future versions may return more statistics in the stats array. 1.382 + 1.383 + Example: 1.384 + 1.385 + See http://www.cise.ufl.edu/research/sparse/colamd/example.c 1.386 + for a complete example. 1.387 + 1.388 + To order the columns of a 5-by-4 matrix with 11 nonzero entries in 1.389 + the following nonzero pattern 1.390 + 1.391 + x 0 x 0 1.392 + x 0 x x 1.393 + 0 x x 0 1.394 + 0 0 x x 1.395 + x x 0 0 1.396 + 1.397 + with default knobs and no output statistics, do the following: 1.398 + 1.399 + #include "colamd.h" 1.400 + #define ALEN 100 1.401 + int A [ALEN] = {0, 1, 4, 2, 4, 0, 1, 2, 3, 1, 3} ; 1.402 + int p [ ] = {0, 3, 5, 9, 11} ; 1.403 + int stats [COLAMD_STATS] ; 1.404 + colamd (5, 4, ALEN, A, p, (double *) NULL, stats) ; 1.405 + 1.406 + The permutation is returned in the array p, and A is destroyed. 1.407 + 1.408 + ---------------------------------------------------------------------------- 1.409 + symamd: 1.410 + ---------------------------------------------------------------------------- 1.411 + 1.412 + C syntax: 1.413 + 1.414 + #include "colamd.h" 1.415 + int symamd (int n, int *A, int *p, int *perm, 1.416 + double knobs [COLAMD_KNOBS], int stats [COLAMD_STATS], 1.417 + void (*allocate) (size_t, size_t), void (*release) (void *)) ; 1.418 + UF_long symamd_l (UF_long n, UF_long *A, UF_long *p, UF_long *perm, 1.419 + double knobs [COLAMD_KNOBS], UF_long stats [COLAMD_STATS], 1.420 + void (*allocate) (size_t, size_t), void (*release) (void *)) ; 1.421 + 1.422 + Purpose: 1.423 + 1.424 + The symamd routine computes an ordering P of a symmetric sparse 1.425 + matrix A such that the Cholesky factorization PAP' = LL' remains 1.426 + sparse. It is based on a column ordering of a matrix M constructed 1.427 + so that the nonzero pattern of M'M is the same as A. The matrix A 1.428 + is assumed to be symmetric; only the strictly lower triangular part 1.429 + is accessed. You must pass your selected memory allocator (usually 1.430 + calloc/free or mxCalloc/mxFree) to symamd, for it to allocate 1.431 + memory for the temporary matrix M. 1.432 + 1.433 + Returns: 1.434 + 1.435 + TRUE (1) if successful, FALSE (0) otherwise. 1.436 + 1.437 + Arguments: 1.438 + 1.439 + int n ; Input argument. 1.440 + 1.441 + Number of rows and columns in the symmetrix matrix A. 1.442 + Restriction: n >= 0. 1.443 + Symamd returns FALSE if n is negative. 1.444 + 1.445 + int A [nnz] ; Input argument. 1.446 + 1.447 + A is an integer array of size nnz, where nnz = p [n]. 1.448 + 1.449 + The row indices of the entries in column c of the matrix are 1.450 + held in A [(p [c]) ... (p [c+1]-1)]. The row indices in a 1.451 + given column c need not be in ascending order, and duplicate 1.452 + row indices may be present. However, symamd will run faster 1.453 + if the columns are in sorted order with no duplicate entries. 1.454 + 1.455 + The matrix is 0-based. That is, rows are in the range 0 to 1.456 + n-1, and columns are in the range 0 to n-1. Symamd 1.457 + returns FALSE if any row index is out of range. 1.458 + 1.459 + The contents of A are not modified. 1.460 + 1.461 + int p [n+1] ; Input argument. 1.462 + 1.463 + p is an integer array of size n+1. On input, it holds the 1.464 + "pointers" for the column form of the matrix A. Column c of 1.465 + the matrix A is held in A [(p [c]) ... (p [c+1]-1)]. The first 1.466 + entry, p [0], must be zero, and p [c] <= p [c+1] must hold 1.467 + for all c in the range 0 to n-1. The value p [n] is 1.468 + thus the total number of entries in the pattern of the matrix A. 1.469 + Symamd returns FALSE if these conditions are not met. 1.470 + 1.471 + The contents of p are not modified. 1.472 + 1.473 + int perm [n+1] ; Output argument. 1.474 + 1.475 + On output, if symamd returns TRUE, the array perm holds the 1.476 + permutation P, where perm [0] is the first index in the new 1.477 + ordering, and perm [n-1] is the last. That is, perm [k] = j 1.478 + means that row and column j of A is the kth column in PAP', 1.479 + where k is in the range 0 to n-1 (perm [0] = j means 1.480 + that row and column j of A are the first row and column in 1.481 + PAP'). The array is used as a workspace during the ordering, 1.482 + which is why it must be of length n+1, not just n. 1.483 + 1.484 + double knobs [COLAMD_KNOBS] ; Input argument. 1.485 + 1.486 + See colamd_set_defaults for a description. 1.487 + 1.488 + int stats [COLAMD_STATS] ; Output argument. 1.489 + 1.490 + Statistics on the ordering, and error status. 1.491 + See colamd.h for related definitions. 1.492 + Symamd returns FALSE if stats is not present. 1.493 + 1.494 + stats [0]: number of dense or empty row and columns ignored 1.495 + (and ordered last in the output permutation 1.496 + perm). Note that a row/column can become 1.497 + "empty" if it contains only "dense" and/or 1.498 + "empty" columns/rows. 1.499 + 1.500 + stats [1]: (same as stats [0]) 1.501 + 1.502 + stats [2]: number of garbage collections performed. 1.503 + 1.504 + stats [3]: status code. < 0 is an error code. 1.505 + > 1 is a warning or notice. 1.506 + 1.507 + 0 OK. Each column of the input matrix contained 1.508 + row indices in increasing order, with no 1.509 + duplicates. 1.510 + 1.511 + 1 OK, but columns of input matrix were jumbled 1.512 + (unsorted columns or duplicate entries). Symamd 1.513 + had to do some extra work to sort the matrix 1.514 + first and remove duplicate entries, but it 1.515 + still was able to return a valid permutation 1.516 + (return value of symamd was TRUE). 1.517 + 1.518 + stats [4]: highest numbered column that 1.519 + is unsorted or has duplicate 1.520 + entries. 1.521 + stats [5]: last seen duplicate or 1.522 + unsorted row index. 1.523 + stats [6]: number of duplicate or 1.524 + unsorted row indices. 1.525 + 1.526 + -1 A is a null pointer 1.527 + 1.528 + -2 p is a null pointer 1.529 + 1.530 + -3 (unused, see colamd.c) 1.531 + 1.532 + -4 n is negative 1.533 + 1.534 + stats [4]: n 1.535 + 1.536 + -5 number of nonzeros in matrix is negative 1.537 + 1.538 + stats [4]: # of nonzeros (p [n]). 1.539 + 1.540 + -6 p [0] is nonzero 1.541 + 1.542 + stats [4]: p [0] 1.543 + 1.544 + -7 (unused) 1.545 + 1.546 + -8 a column has a negative number of entries 1.547 + 1.548 + stats [4]: column with < 0 entries 1.549 + stats [5]: number of entries in col 1.550 + 1.551 + -9 a row index is out of bounds 1.552 + 1.553 + stats [4]: column with bad row index 1.554 + stats [5]: bad row index 1.555 + stats [6]: n_row, # of rows of matrx 1.556 + 1.557 + -10 out of memory (unable to allocate temporary 1.558 + workspace for M or count arrays using the 1.559 + "allocate" routine passed into symamd). 1.560 + 1.561 + Future versions may return more statistics in the stats array. 1.562 + 1.563 + void * (*allocate) (size_t, size_t) 1.564 + 1.565 + A pointer to a function providing memory allocation. The 1.566 + allocated memory must be returned initialized to zero. For a 1.567 + C application, this argument should normally be a pointer to 1.568 + calloc. For a MATLAB mexFunction, the routine mxCalloc is 1.569 + passed instead. 1.570 + 1.571 + void (*release) (size_t, size_t) 1.572 + 1.573 + A pointer to a function that frees memory allocated by the 1.574 + memory allocation routine above. For a C application, this 1.575 + argument should normally be a pointer to free. For a MATLAB 1.576 + mexFunction, the routine mxFree is passed instead. 1.577 + 1.578 + 1.579 + ---------------------------------------------------------------------------- 1.580 + colamd_report: 1.581 + ---------------------------------------------------------------------------- 1.582 + 1.583 + C syntax: 1.584 + 1.585 + #include "colamd.h" 1.586 + colamd_report (int stats [COLAMD_STATS]) ; 1.587 + colamd_l_report (UF_long stats [COLAMD_STATS]) ; 1.588 + 1.589 + Purpose: 1.590 + 1.591 + Prints the error status and statistics recorded in the stats 1.592 + array on the standard error output (for a standard C routine) 1.593 + or on the MATLAB output (for a mexFunction). 1.594 + 1.595 + Arguments: 1.596 + 1.597 + int stats [COLAMD_STATS] ; Input only. Statistics from colamd. 1.598 + 1.599 + 1.600 + ---------------------------------------------------------------------------- 1.601 + symamd_report: 1.602 + ---------------------------------------------------------------------------- 1.603 + 1.604 + C syntax: 1.605 + 1.606 + #include "colamd.h" 1.607 + symamd_report (int stats [COLAMD_STATS]) ; 1.608 + symamd_l_report (UF_long stats [COLAMD_STATS]) ; 1.609 + 1.610 + Purpose: 1.611 + 1.612 + Prints the error status and statistics recorded in the stats 1.613 + array on the standard error output (for a standard C routine) 1.614 + or on the MATLAB output (for a mexFunction). 1.615 + 1.616 + Arguments: 1.617 + 1.618 + int stats [COLAMD_STATS] ; Input only. Statistics from symamd. 1.619 + 1.620 + 1.621 +*/ 1.622 + 1.623 +/* ========================================================================== */ 1.624 +/* === Scaffolding code definitions ======================================== */ 1.625 +/* ========================================================================== */ 1.626 + 1.627 +/* Ensure that debugging is turned off: */ 1.628 +#ifndef NDEBUG 1.629 +#define NDEBUG 1.630 +#endif 1.631 + 1.632 +/* turn on debugging by uncommenting the following line 1.633 + #undef NDEBUG 1.634 +*/ 1.635 + 1.636 +/* 1.637 + Our "scaffolding code" philosophy: In our opinion, well-written library 1.638 + code should keep its "debugging" code, and just normally have it turned off 1.639 + by the compiler so as not to interfere with performance. This serves 1.640 + several purposes: 1.641 + 1.642 + (1) assertions act as comments to the reader, telling you what the code 1.643 + expects at that point. All assertions will always be true (unless 1.644 + there really is a bug, of course). 1.645 + 1.646 + (2) leaving in the scaffolding code assists anyone who would like to modify 1.647 + the code, or understand the algorithm (by reading the debugging output, 1.648 + one can get a glimpse into what the code is doing). 1.649 + 1.650 + (3) (gasp!) for actually finding bugs. This code has been heavily tested 1.651 + and "should" be fully functional and bug-free ... but you never know... 1.652 + 1.653 + The code will become outrageously slow when debugging is 1.654 + enabled. To control the level of debugging output, set an environment 1.655 + variable D to 0 (little), 1 (some), 2, 3, or 4 (lots). When debugging, 1.656 + you should see the following message on the standard output: 1.657 + 1.658 + colamd: debug version, D = 1 (THIS WILL BE SLOW!) 1.659 + 1.660 + or a similar message for symamd. If you don't, then debugging has not 1.661 + been enabled. 1.662 + 1.663 +*/ 1.664 + 1.665 +/* ========================================================================== */ 1.666 +/* === Include files ======================================================== */ 1.667 +/* ========================================================================== */ 1.668 + 1.669 +#include "colamd.h" 1.670 + 1.671 +#if 0 /* by mao */ 1.672 +#include <limits.h> 1.673 +#include <math.h> 1.674 + 1.675 +#ifdef MATLAB_MEX_FILE 1.676 +#include "mex.h" 1.677 +#include "matrix.h" 1.678 +#endif /* MATLAB_MEX_FILE */ 1.679 + 1.680 +#if !defined (NPRINT) || !defined (NDEBUG) 1.681 +#include <stdio.h> 1.682 +#endif 1.683 + 1.684 +#ifndef NULL 1.685 +#define NULL ((void *) 0) 1.686 +#endif 1.687 +#endif 1.688 + 1.689 +/* ========================================================================== */ 1.690 +/* === int or UF_long ======================================================= */ 1.691 +/* ========================================================================== */ 1.692 + 1.693 +#if 0 /* by mao */ 1.694 +/* define UF_long */ 1.695 +#include "UFconfig.h" 1.696 +#endif 1.697 + 1.698 +#ifdef DLONG 1.699 + 1.700 +#define Int UF_long 1.701 +#define ID UF_long_id 1.702 +#define Int_MAX UF_long_max 1.703 + 1.704 +#define COLAMD_recommended colamd_l_recommended 1.705 +#define COLAMD_set_defaults colamd_l_set_defaults 1.706 +#define COLAMD_MAIN colamd_l 1.707 +#define SYMAMD_MAIN symamd_l 1.708 +#define COLAMD_report colamd_l_report 1.709 +#define SYMAMD_report symamd_l_report 1.710 + 1.711 +#else 1.712 + 1.713 +#define Int int 1.714 +#define ID "%d" 1.715 +#define Int_MAX INT_MAX 1.716 + 1.717 +#define COLAMD_recommended colamd_recommended 1.718 +#define COLAMD_set_defaults colamd_set_defaults 1.719 +#define COLAMD_MAIN colamd 1.720 +#define SYMAMD_MAIN symamd 1.721 +#define COLAMD_report colamd_report 1.722 +#define SYMAMD_report symamd_report 1.723 + 1.724 +#endif 1.725 + 1.726 +/* ========================================================================== */ 1.727 +/* === Row and Column structures ============================================ */ 1.728 +/* ========================================================================== */ 1.729 + 1.730 +/* User code that makes use of the colamd/symamd routines need not directly */ 1.731 +/* reference these structures. They are used only for colamd_recommended. */ 1.732 + 1.733 +typedef struct Colamd_Col_struct 1.734 +{ 1.735 + Int start ; /* index for A of first row in this column, or DEAD */ 1.736 + /* if column is dead */ 1.737 + Int length ; /* number of rows in this column */ 1.738 + union 1.739 + { 1.740 + Int thickness ; /* number of original columns represented by this */ 1.741 + /* col, if the column is alive */ 1.742 + Int parent ; /* parent in parent tree super-column structure, if */ 1.743 + /* the column is dead */ 1.744 + } shared1 ; 1.745 + union 1.746 + { 1.747 + Int score ; /* the score used to maintain heap, if col is alive */ 1.748 + Int order ; /* pivot ordering of this column, if col is dead */ 1.749 + } shared2 ; 1.750 + union 1.751 + { 1.752 + Int headhash ; /* head of a hash bucket, if col is at the head of */ 1.753 + /* a degree list */ 1.754 + Int hash ; /* hash value, if col is not in a degree list */ 1.755 + Int prev ; /* previous column in degree list, if col is in a */ 1.756 + /* degree list (but not at the head of a degree list) */ 1.757 + } shared3 ; 1.758 + union 1.759 + { 1.760 + Int degree_next ; /* next column, if col is in a degree list */ 1.761 + Int hash_next ; /* next column, if col is in a hash list */ 1.762 + } shared4 ; 1.763 + 1.764 +} Colamd_Col ; 1.765 + 1.766 +typedef struct Colamd_Row_struct 1.767 +{ 1.768 + Int start ; /* index for A of first col in this row */ 1.769 + Int length ; /* number of principal columns in this row */ 1.770 + union 1.771 + { 1.772 + Int degree ; /* number of principal & non-principal columns in row */ 1.773 + Int p ; /* used as a row pointer in init_rows_cols () */ 1.774 + } shared1 ; 1.775 + union 1.776 + { 1.777 + Int mark ; /* for computing set differences and marking dead rows*/ 1.778 + Int first_column ;/* first column in row (used in garbage collection) */ 1.779 + } shared2 ; 1.780 + 1.781 +} Colamd_Row ; 1.782 + 1.783 +/* ========================================================================== */ 1.784 +/* === Definitions ========================================================== */ 1.785 +/* ========================================================================== */ 1.786 + 1.787 +/* Routines are either PUBLIC (user-callable) or PRIVATE (not user-callable) */ 1.788 +#define PUBLIC 1.789 +#define PRIVATE static 1.790 + 1.791 +#define DENSE_DEGREE(alpha,n) \ 1.792 + ((Int) MAX (16.0, (alpha) * sqrt ((double) (n)))) 1.793 + 1.794 +#define MAX(a,b) (((a) > (b)) ? (a) : (b)) 1.795 +#define MIN(a,b) (((a) < (b)) ? (a) : (b)) 1.796 + 1.797 +#define ONES_COMPLEMENT(r) (-(r)-1) 1.798 + 1.799 +/* -------------------------------------------------------------------------- */ 1.800 +/* Change for version 2.1: define TRUE and FALSE only if not yet defined */ 1.801 +/* -------------------------------------------------------------------------- */ 1.802 + 1.803 +#ifndef TRUE 1.804 +#define TRUE (1) 1.805 +#endif 1.806 + 1.807 +#ifndef FALSE 1.808 +#define FALSE (0) 1.809 +#endif 1.810 + 1.811 +/* -------------------------------------------------------------------------- */ 1.812 + 1.813 +#define EMPTY (-1) 1.814 + 1.815 +/* Row and column status */ 1.816 +#define ALIVE (0) 1.817 +#define DEAD (-1) 1.818 + 1.819 +/* Column status */ 1.820 +#define DEAD_PRINCIPAL (-1) 1.821 +#define DEAD_NON_PRINCIPAL (-2) 1.822 + 1.823 +/* Macros for row and column status update and checking. */ 1.824 +#define ROW_IS_DEAD(r) ROW_IS_MARKED_DEAD (Row[r].shared2.mark) 1.825 +#define ROW_IS_MARKED_DEAD(row_mark) (row_mark < ALIVE) 1.826 +#define ROW_IS_ALIVE(r) (Row [r].shared2.mark >= ALIVE) 1.827 +#define COL_IS_DEAD(c) (Col [c].start < ALIVE) 1.828 +#define COL_IS_ALIVE(c) (Col [c].start >= ALIVE) 1.829 +#define COL_IS_DEAD_PRINCIPAL(c) (Col [c].start == DEAD_PRINCIPAL) 1.830 +#define KILL_ROW(r) { Row [r].shared2.mark = DEAD ; } 1.831 +#define KILL_PRINCIPAL_COL(c) { Col [c].start = DEAD_PRINCIPAL ; } 1.832 +#define KILL_NON_PRINCIPAL_COL(c) { Col [c].start = DEAD_NON_PRINCIPAL ; } 1.833 + 1.834 +/* ========================================================================== */ 1.835 +/* === Colamd reporting mechanism =========================================== */ 1.836 +/* ========================================================================== */ 1.837 + 1.838 +#if defined (MATLAB_MEX_FILE) || defined (MATHWORKS) 1.839 +/* In MATLAB, matrices are 1-based to the user, but 0-based internally */ 1.840 +#define INDEX(i) ((i)+1) 1.841 +#else 1.842 +/* In C, matrices are 0-based and indices are reported as such in *_report */ 1.843 +#define INDEX(i) (i) 1.844 +#endif 1.845 + 1.846 +/* All output goes through the PRINTF macro. */ 1.847 +#define PRINTF(params) { if (colamd_printf != NULL) (void) colamd_printf params ; } 1.848 + 1.849 +/* ========================================================================== */ 1.850 +/* === Prototypes of PRIVATE routines ======================================= */ 1.851 +/* ========================================================================== */ 1.852 + 1.853 +PRIVATE Int init_rows_cols 1.854 +( 1.855 + Int n_row, 1.856 + Int n_col, 1.857 + Colamd_Row Row [], 1.858 + Colamd_Col Col [], 1.859 + Int A [], 1.860 + Int p [], 1.861 + Int stats [COLAMD_STATS] 1.862 +) ; 1.863 + 1.864 +PRIVATE void init_scoring 1.865 +( 1.866 + Int n_row, 1.867 + Int n_col, 1.868 + Colamd_Row Row [], 1.869 + Colamd_Col Col [], 1.870 + Int A [], 1.871 + Int head [], 1.872 + double knobs [COLAMD_KNOBS], 1.873 + Int *p_n_row2, 1.874 + Int *p_n_col2, 1.875 + Int *p_max_deg 1.876 +) ; 1.877 + 1.878 +PRIVATE Int find_ordering 1.879 +( 1.880 + Int n_row, 1.881 + Int n_col, 1.882 + Int Alen, 1.883 + Colamd_Row Row [], 1.884 + Colamd_Col Col [], 1.885 + Int A [], 1.886 + Int head [], 1.887 + Int n_col2, 1.888 + Int max_deg, 1.889 + Int pfree, 1.890 + Int aggressive 1.891 +) ; 1.892 + 1.893 +PRIVATE void order_children 1.894 +( 1.895 + Int n_col, 1.896 + Colamd_Col Col [], 1.897 + Int p [] 1.898 +) ; 1.899 + 1.900 +PRIVATE void detect_super_cols 1.901 +( 1.902 + 1.903 +#ifndef NDEBUG 1.904 + Int n_col, 1.905 + Colamd_Row Row [], 1.906 +#endif /* NDEBUG */ 1.907 + 1.908 + Colamd_Col Col [], 1.909 + Int A [], 1.910 + Int head [], 1.911 + Int row_start, 1.912 + Int row_length 1.913 +) ; 1.914 + 1.915 +PRIVATE Int garbage_collection 1.916 +( 1.917 + Int n_row, 1.918 + Int n_col, 1.919 + Colamd_Row Row [], 1.920 + Colamd_Col Col [], 1.921 + Int A [], 1.922 + Int *pfree 1.923 +) ; 1.924 + 1.925 +PRIVATE Int clear_mark 1.926 +( 1.927 + Int tag_mark, 1.928 + Int max_mark, 1.929 + Int n_row, 1.930 + Colamd_Row Row [] 1.931 +) ; 1.932 + 1.933 +PRIVATE void print_report 1.934 +( 1.935 + char *method, 1.936 + Int stats [COLAMD_STATS] 1.937 +) ; 1.938 + 1.939 +/* ========================================================================== */ 1.940 +/* === Debugging prototypes and definitions ================================= */ 1.941 +/* ========================================================================== */ 1.942 + 1.943 +#ifndef NDEBUG 1.944 + 1.945 +#if 0 /* by mao */ 1.946 +#include <assert.h> 1.947 +#endif 1.948 + 1.949 +/* colamd_debug is the *ONLY* global variable, and is only */ 1.950 +/* present when debugging */ 1.951 + 1.952 +PRIVATE Int colamd_debug = 0 ; /* debug print level */ 1.953 + 1.954 +#define DEBUG0(params) { PRINTF (params) ; } 1.955 +#define DEBUG1(params) { if (colamd_debug >= 1) PRINTF (params) ; } 1.956 +#define DEBUG2(params) { if (colamd_debug >= 2) PRINTF (params) ; } 1.957 +#define DEBUG3(params) { if (colamd_debug >= 3) PRINTF (params) ; } 1.958 +#define DEBUG4(params) { if (colamd_debug >= 4) PRINTF (params) ; } 1.959 + 1.960 +#if 0 /* by mao */ 1.961 +#ifdef MATLAB_MEX_FILE 1.962 +#define ASSERT(expression) (mxAssert ((expression), "")) 1.963 +#else 1.964 +#define ASSERT(expression) (assert (expression)) 1.965 +#endif /* MATLAB_MEX_FILE */ 1.966 +#else 1.967 +#define ASSERT xassert 1.968 +#endif 1.969 + 1.970 +PRIVATE void colamd_get_debug /* gets the debug print level from getenv */ 1.971 +( 1.972 + char *method 1.973 +) ; 1.974 + 1.975 +PRIVATE void debug_deg_lists 1.976 +( 1.977 + Int n_row, 1.978 + Int n_col, 1.979 + Colamd_Row Row [], 1.980 + Colamd_Col Col [], 1.981 + Int head [], 1.982 + Int min_score, 1.983 + Int should, 1.984 + Int max_deg 1.985 +) ; 1.986 + 1.987 +PRIVATE void debug_mark 1.988 +( 1.989 + Int n_row, 1.990 + Colamd_Row Row [], 1.991 + Int tag_mark, 1.992 + Int max_mark 1.993 +) ; 1.994 + 1.995 +PRIVATE void debug_matrix 1.996 +( 1.997 + Int n_row, 1.998 + Int n_col, 1.999 + Colamd_Row Row [], 1.1000 + Colamd_Col Col [], 1.1001 + Int A [] 1.1002 +) ; 1.1003 + 1.1004 +PRIVATE void debug_structures 1.1005 +( 1.1006 + Int n_row, 1.1007 + Int n_col, 1.1008 + Colamd_Row Row [], 1.1009 + Colamd_Col Col [], 1.1010 + Int A [], 1.1011 + Int n_col2 1.1012 +) ; 1.1013 + 1.1014 +#else /* NDEBUG */ 1.1015 + 1.1016 +/* === No debugging ========================================================= */ 1.1017 + 1.1018 +#define DEBUG0(params) ; 1.1019 +#define DEBUG1(params) ; 1.1020 +#define DEBUG2(params) ; 1.1021 +#define DEBUG3(params) ; 1.1022 +#define DEBUG4(params) ; 1.1023 + 1.1024 +#define ASSERT(expression) 1.1025 + 1.1026 +#endif /* NDEBUG */ 1.1027 + 1.1028 +/* ========================================================================== */ 1.1029 +/* === USER-CALLABLE ROUTINES: ============================================== */ 1.1030 +/* ========================================================================== */ 1.1031 + 1.1032 +/* ========================================================================== */ 1.1033 +/* === colamd_recommended =================================================== */ 1.1034 +/* ========================================================================== */ 1.1035 + 1.1036 +/* 1.1037 + The colamd_recommended routine returns the suggested size for Alen. This 1.1038 + value has been determined to provide good balance between the number of 1.1039 + garbage collections and the memory requirements for colamd. If any 1.1040 + argument is negative, or if integer overflow occurs, a 0 is returned as an 1.1041 + error condition. 2*nnz space is required for the row and column 1.1042 + indices of the matrix. COLAMD_C (n_col) + COLAMD_R (n_row) space is 1.1043 + required for the Col and Row arrays, respectively, which are internal to 1.1044 + colamd (roughly 6*n_col + 4*n_row). An additional n_col space is the 1.1045 + minimal amount of "elbow room", and nnz/5 more space is recommended for 1.1046 + run time efficiency. 1.1047 + 1.1048 + Alen is approximately 2.2*nnz + 7*n_col + 4*n_row + 10. 1.1049 + 1.1050 + This function is not needed when using symamd. 1.1051 +*/ 1.1052 + 1.1053 +/* add two values of type size_t, and check for integer overflow */ 1.1054 +static size_t t_add (size_t a, size_t b, int *ok) 1.1055 +{ 1.1056 + (*ok) = (*ok) && ((a + b) >= MAX (a,b)) ; 1.1057 + return ((*ok) ? (a + b) : 0) ; 1.1058 +} 1.1059 + 1.1060 +/* compute a*k where k is a small integer, and check for integer overflow */ 1.1061 +static size_t t_mult (size_t a, size_t k, int *ok) 1.1062 +{ 1.1063 + size_t i, s = 0 ; 1.1064 + for (i = 0 ; i < k ; i++) 1.1065 + { 1.1066 + s = t_add (s, a, ok) ; 1.1067 + } 1.1068 + return (s) ; 1.1069 +} 1.1070 + 1.1071 +/* size of the Col and Row structures */ 1.1072 +#define COLAMD_C(n_col,ok) \ 1.1073 + ((t_mult (t_add (n_col, 1, ok), sizeof (Colamd_Col), ok) / sizeof (Int))) 1.1074 + 1.1075 +#define COLAMD_R(n_row,ok) \ 1.1076 + ((t_mult (t_add (n_row, 1, ok), sizeof (Colamd_Row), ok) / sizeof (Int))) 1.1077 + 1.1078 + 1.1079 +PUBLIC size_t COLAMD_recommended /* returns recommended value of Alen. */ 1.1080 +( 1.1081 + /* === Parameters ======================================================= */ 1.1082 + 1.1083 + Int nnz, /* number of nonzeros in A */ 1.1084 + Int n_row, /* number of rows in A */ 1.1085 + Int n_col /* number of columns in A */ 1.1086 +) 1.1087 +{ 1.1088 + size_t s, c, r ; 1.1089 + int ok = TRUE ; 1.1090 + if (nnz < 0 || n_row < 0 || n_col < 0) 1.1091 + { 1.1092 + return (0) ; 1.1093 + } 1.1094 + s = t_mult (nnz, 2, &ok) ; /* 2*nnz */ 1.1095 + c = COLAMD_C (n_col, &ok) ; /* size of column structures */ 1.1096 + r = COLAMD_R (n_row, &ok) ; /* size of row structures */ 1.1097 + s = t_add (s, c, &ok) ; 1.1098 + s = t_add (s, r, &ok) ; 1.1099 + s = t_add (s, n_col, &ok) ; /* elbow room */ 1.1100 + s = t_add (s, nnz/5, &ok) ; /* elbow room */ 1.1101 + ok = ok && (s < Int_MAX) ; 1.1102 + return (ok ? s : 0) ; 1.1103 +} 1.1104 + 1.1105 + 1.1106 +/* ========================================================================== */ 1.1107 +/* === colamd_set_defaults ================================================== */ 1.1108 +/* ========================================================================== */ 1.1109 + 1.1110 +/* 1.1111 + The colamd_set_defaults routine sets the default values of the user- 1.1112 + controllable parameters for colamd and symamd: 1.1113 + 1.1114 + Colamd: rows with more than max (16, knobs [0] * sqrt (n_col)) 1.1115 + entries are removed prior to ordering. Columns with more than 1.1116 + max (16, knobs [1] * sqrt (MIN (n_row,n_col))) entries are removed 1.1117 + prior to ordering, and placed last in the output column ordering. 1.1118 + 1.1119 + Symamd: Rows and columns with more than max (16, knobs [0] * sqrt (n)) 1.1120 + entries are removed prior to ordering, and placed last in the 1.1121 + output ordering. 1.1122 + 1.1123 + knobs [0] dense row control 1.1124 + 1.1125 + knobs [1] dense column control 1.1126 + 1.1127 + knobs [2] if nonzero, do aggresive absorption 1.1128 + 1.1129 + knobs [3..19] unused, but future versions might use this 1.1130 + 1.1131 +*/ 1.1132 + 1.1133 +PUBLIC void COLAMD_set_defaults 1.1134 +( 1.1135 + /* === Parameters ======================================================= */ 1.1136 + 1.1137 + double knobs [COLAMD_KNOBS] /* knob array */ 1.1138 +) 1.1139 +{ 1.1140 + /* === Local variables ================================================== */ 1.1141 + 1.1142 + Int i ; 1.1143 + 1.1144 + if (!knobs) 1.1145 + { 1.1146 + return ; /* no knobs to initialize */ 1.1147 + } 1.1148 + for (i = 0 ; i < COLAMD_KNOBS ; i++) 1.1149 + { 1.1150 + knobs [i] = 0 ; 1.1151 + } 1.1152 + knobs [COLAMD_DENSE_ROW] = 10 ; 1.1153 + knobs [COLAMD_DENSE_COL] = 10 ; 1.1154 + knobs [COLAMD_AGGRESSIVE] = TRUE ; /* default: do aggressive absorption*/ 1.1155 +} 1.1156 + 1.1157 + 1.1158 +/* ========================================================================== */ 1.1159 +/* === symamd =============================================================== */ 1.1160 +/* ========================================================================== */ 1.1161 + 1.1162 +PUBLIC Int SYMAMD_MAIN /* return TRUE if OK, FALSE otherwise */ 1.1163 +( 1.1164 + /* === Parameters ======================================================= */ 1.1165 + 1.1166 + Int n, /* number of rows and columns of A */ 1.1167 + Int A [], /* row indices of A */ 1.1168 + Int p [], /* column pointers of A */ 1.1169 + Int perm [], /* output permutation, size n+1 */ 1.1170 + double knobs [COLAMD_KNOBS], /* parameters (uses defaults if NULL) */ 1.1171 + Int stats [COLAMD_STATS], /* output statistics and error codes */ 1.1172 + void * (*allocate) (size_t, size_t), 1.1173 + /* pointer to calloc (ANSI C) or */ 1.1174 + /* mxCalloc (for MATLAB mexFunction) */ 1.1175 + void (*release) (void *) 1.1176 + /* pointer to free (ANSI C) or */ 1.1177 + /* mxFree (for MATLAB mexFunction) */ 1.1178 +) 1.1179 +{ 1.1180 + /* === Local variables ================================================== */ 1.1181 + 1.1182 + Int *count ; /* length of each column of M, and col pointer*/ 1.1183 + Int *mark ; /* mark array for finding duplicate entries */ 1.1184 + Int *M ; /* row indices of matrix M */ 1.1185 + size_t Mlen ; /* length of M */ 1.1186 + Int n_row ; /* number of rows in M */ 1.1187 + Int nnz ; /* number of entries in A */ 1.1188 + Int i ; /* row index of A */ 1.1189 + Int j ; /* column index of A */ 1.1190 + Int k ; /* row index of M */ 1.1191 + Int mnz ; /* number of nonzeros in M */ 1.1192 + Int pp ; /* index into a column of A */ 1.1193 + Int last_row ; /* last row seen in the current column */ 1.1194 + Int length ; /* number of nonzeros in a column */ 1.1195 + 1.1196 + double cknobs [COLAMD_KNOBS] ; /* knobs for colamd */ 1.1197 + double default_knobs [COLAMD_KNOBS] ; /* default knobs for colamd */ 1.1198 + 1.1199 +#ifndef NDEBUG 1.1200 + colamd_get_debug ("symamd") ; 1.1201 +#endif /* NDEBUG */ 1.1202 + 1.1203 + /* === Check the input arguments ======================================== */ 1.1204 + 1.1205 + if (!stats) 1.1206 + { 1.1207 + DEBUG0 (("symamd: stats not present\n")) ; 1.1208 + return (FALSE) ; 1.1209 + } 1.1210 + for (i = 0 ; i < COLAMD_STATS ; i++) 1.1211 + { 1.1212 + stats [i] = 0 ; 1.1213 + } 1.1214 + stats [COLAMD_STATUS] = COLAMD_OK ; 1.1215 + stats [COLAMD_INFO1] = -1 ; 1.1216 + stats [COLAMD_INFO2] = -1 ; 1.1217 + 1.1218 + if (!A) 1.1219 + { 1.1220 + stats [COLAMD_STATUS] = COLAMD_ERROR_A_not_present ; 1.1221 + DEBUG0 (("symamd: A not present\n")) ; 1.1222 + return (FALSE) ; 1.1223 + } 1.1224 + 1.1225 + if (!p) /* p is not present */ 1.1226 + { 1.1227 + stats [COLAMD_STATUS] = COLAMD_ERROR_p_not_present ; 1.1228 + DEBUG0 (("symamd: p not present\n")) ; 1.1229 + return (FALSE) ; 1.1230 + } 1.1231 + 1.1232 + if (n < 0) /* n must be >= 0 */ 1.1233 + { 1.1234 + stats [COLAMD_STATUS] = COLAMD_ERROR_ncol_negative ; 1.1235 + stats [COLAMD_INFO1] = n ; 1.1236 + DEBUG0 (("symamd: n negative %d\n", n)) ; 1.1237 + return (FALSE) ; 1.1238 + } 1.1239 + 1.1240 + nnz = p [n] ; 1.1241 + if (nnz < 0) /* nnz must be >= 0 */ 1.1242 + { 1.1243 + stats [COLAMD_STATUS] = COLAMD_ERROR_nnz_negative ; 1.1244 + stats [COLAMD_INFO1] = nnz ; 1.1245 + DEBUG0 (("symamd: number of entries negative %d\n", nnz)) ; 1.1246 + return (FALSE) ; 1.1247 + } 1.1248 + 1.1249 + if (p [0] != 0) 1.1250 + { 1.1251 + stats [COLAMD_STATUS] = COLAMD_ERROR_p0_nonzero ; 1.1252 + stats [COLAMD_INFO1] = p [0] ; 1.1253 + DEBUG0 (("symamd: p[0] not zero %d\n", p [0])) ; 1.1254 + return (FALSE) ; 1.1255 + } 1.1256 + 1.1257 + /* === If no knobs, set default knobs =================================== */ 1.1258 + 1.1259 + if (!knobs) 1.1260 + { 1.1261 + COLAMD_set_defaults (default_knobs) ; 1.1262 + knobs = default_knobs ; 1.1263 + } 1.1264 + 1.1265 + /* === Allocate count and mark ========================================== */ 1.1266 + 1.1267 + count = (Int *) ((*allocate) (n+1, sizeof (Int))) ; 1.1268 + if (!count) 1.1269 + { 1.1270 + stats [COLAMD_STATUS] = COLAMD_ERROR_out_of_memory ; 1.1271 + DEBUG0 (("symamd: allocate count (size %d) failed\n", n+1)) ; 1.1272 + return (FALSE) ; 1.1273 + } 1.1274 + 1.1275 + mark = (Int *) ((*allocate) (n+1, sizeof (Int))) ; 1.1276 + if (!mark) 1.1277 + { 1.1278 + stats [COLAMD_STATUS] = COLAMD_ERROR_out_of_memory ; 1.1279 + (*release) ((void *) count) ; 1.1280 + DEBUG0 (("symamd: allocate mark (size %d) failed\n", n+1)) ; 1.1281 + return (FALSE) ; 1.1282 + } 1.1283 + 1.1284 + /* === Compute column counts of M, check if A is valid ================== */ 1.1285 + 1.1286 + stats [COLAMD_INFO3] = 0 ; /* number of duplicate or unsorted row indices*/ 1.1287 + 1.1288 + for (i = 0 ; i < n ; i++) 1.1289 + { 1.1290 + mark [i] = -1 ; 1.1291 + } 1.1292 + 1.1293 + for (j = 0 ; j < n ; j++) 1.1294 + { 1.1295 + last_row = -1 ; 1.1296 + 1.1297 + length = p [j+1] - p [j] ; 1.1298 + if (length < 0) 1.1299 + { 1.1300 + /* column pointers must be non-decreasing */ 1.1301 + stats [COLAMD_STATUS] = COLAMD_ERROR_col_length_negative ; 1.1302 + stats [COLAMD_INFO1] = j ; 1.1303 + stats [COLAMD_INFO2] = length ; 1.1304 + (*release) ((void *) count) ; 1.1305 + (*release) ((void *) mark) ; 1.1306 + DEBUG0 (("symamd: col %d negative length %d\n", j, length)) ; 1.1307 + return (FALSE) ; 1.1308 + } 1.1309 + 1.1310 + for (pp = p [j] ; pp < p [j+1] ; pp++) 1.1311 + { 1.1312 + i = A [pp] ; 1.1313 + if (i < 0 || i >= n) 1.1314 + { 1.1315 + /* row index i, in column j, is out of bounds */ 1.1316 + stats [COLAMD_STATUS] = COLAMD_ERROR_row_index_out_of_bounds ; 1.1317 + stats [COLAMD_INFO1] = j ; 1.1318 + stats [COLAMD_INFO2] = i ; 1.1319 + stats [COLAMD_INFO3] = n ; 1.1320 + (*release) ((void *) count) ; 1.1321 + (*release) ((void *) mark) ; 1.1322 + DEBUG0 (("symamd: row %d col %d out of bounds\n", i, j)) ; 1.1323 + return (FALSE) ; 1.1324 + } 1.1325 + 1.1326 + if (i <= last_row || mark [i] == j) 1.1327 + { 1.1328 + /* row index is unsorted or repeated (or both), thus col */ 1.1329 + /* is jumbled. This is a notice, not an error condition. */ 1.1330 + stats [COLAMD_STATUS] = COLAMD_OK_BUT_JUMBLED ; 1.1331 + stats [COLAMD_INFO1] = j ; 1.1332 + stats [COLAMD_INFO2] = i ; 1.1333 + (stats [COLAMD_INFO3]) ++ ; 1.1334 + DEBUG1 (("symamd: row %d col %d unsorted/duplicate\n", i, j)) ; 1.1335 + } 1.1336 + 1.1337 + if (i > j && mark [i] != j) 1.1338 + { 1.1339 + /* row k of M will contain column indices i and j */ 1.1340 + count [i]++ ; 1.1341 + count [j]++ ; 1.1342 + } 1.1343 + 1.1344 + /* mark the row as having been seen in this column */ 1.1345 + mark [i] = j ; 1.1346 + 1.1347 + last_row = i ; 1.1348 + } 1.1349 + } 1.1350 + 1.1351 + /* v2.4: removed free(mark) */ 1.1352 + 1.1353 + /* === Compute column pointers of M ===================================== */ 1.1354 + 1.1355 + /* use output permutation, perm, for column pointers of M */ 1.1356 + perm [0] = 0 ; 1.1357 + for (j = 1 ; j <= n ; j++) 1.1358 + { 1.1359 + perm [j] = perm [j-1] + count [j-1] ; 1.1360 + } 1.1361 + for (j = 0 ; j < n ; j++) 1.1362 + { 1.1363 + count [j] = perm [j] ; 1.1364 + } 1.1365 + 1.1366 + /* === Construct M ====================================================== */ 1.1367 + 1.1368 + mnz = perm [n] ; 1.1369 + n_row = mnz / 2 ; 1.1370 + Mlen = COLAMD_recommended (mnz, n_row, n) ; 1.1371 + M = (Int *) ((*allocate) (Mlen, sizeof (Int))) ; 1.1372 + DEBUG0 (("symamd: M is %d-by-%d with %d entries, Mlen = %g\n", 1.1373 + n_row, n, mnz, (double) Mlen)) ; 1.1374 + 1.1375 + if (!M) 1.1376 + { 1.1377 + stats [COLAMD_STATUS] = COLAMD_ERROR_out_of_memory ; 1.1378 + (*release) ((void *) count) ; 1.1379 + (*release) ((void *) mark) ; 1.1380 + DEBUG0 (("symamd: allocate M (size %g) failed\n", (double) Mlen)) ; 1.1381 + return (FALSE) ; 1.1382 + } 1.1383 + 1.1384 + k = 0 ; 1.1385 + 1.1386 + if (stats [COLAMD_STATUS] == COLAMD_OK) 1.1387 + { 1.1388 + /* Matrix is OK */ 1.1389 + for (j = 0 ; j < n ; j++) 1.1390 + { 1.1391 + ASSERT (p [j+1] - p [j] >= 0) ; 1.1392 + for (pp = p [j] ; pp < p [j+1] ; pp++) 1.1393 + { 1.1394 + i = A [pp] ; 1.1395 + ASSERT (i >= 0 && i < n) ; 1.1396 + if (i > j) 1.1397 + { 1.1398 + /* row k of M contains column indices i and j */ 1.1399 + M [count [i]++] = k ; 1.1400 + M [count [j]++] = k ; 1.1401 + k++ ; 1.1402 + } 1.1403 + } 1.1404 + } 1.1405 + } 1.1406 + else 1.1407 + { 1.1408 + /* Matrix is jumbled. Do not add duplicates to M. Unsorted cols OK. */ 1.1409 + DEBUG0 (("symamd: Duplicates in A.\n")) ; 1.1410 + for (i = 0 ; i < n ; i++) 1.1411 + { 1.1412 + mark [i] = -1 ; 1.1413 + } 1.1414 + for (j = 0 ; j < n ; j++) 1.1415 + { 1.1416 + ASSERT (p [j+1] - p [j] >= 0) ; 1.1417 + for (pp = p [j] ; pp < p [j+1] ; pp++) 1.1418 + { 1.1419 + i = A [pp] ; 1.1420 + ASSERT (i >= 0 && i < n) ; 1.1421 + if (i > j && mark [i] != j) 1.1422 + { 1.1423 + /* row k of M contains column indices i and j */ 1.1424 + M [count [i]++] = k ; 1.1425 + M [count [j]++] = k ; 1.1426 + k++ ; 1.1427 + mark [i] = j ; 1.1428 + } 1.1429 + } 1.1430 + } 1.1431 + /* v2.4: free(mark) moved below */ 1.1432 + } 1.1433 + 1.1434 + /* count and mark no longer needed */ 1.1435 + (*release) ((void *) count) ; 1.1436 + (*release) ((void *) mark) ; /* v2.4: free (mark) moved here */ 1.1437 + ASSERT (k == n_row) ; 1.1438 + 1.1439 + /* === Adjust the knobs for M =========================================== */ 1.1440 + 1.1441 + for (i = 0 ; i < COLAMD_KNOBS ; i++) 1.1442 + { 1.1443 + cknobs [i] = knobs [i] ; 1.1444 + } 1.1445 + 1.1446 + /* there are no dense rows in M */ 1.1447 + cknobs [COLAMD_DENSE_ROW] = -1 ; 1.1448 + cknobs [COLAMD_DENSE_COL] = knobs [COLAMD_DENSE_ROW] ; 1.1449 + 1.1450 + /* === Order the columns of M =========================================== */ 1.1451 + 1.1452 + /* v2.4: colamd cannot fail here, so the error check is removed */ 1.1453 + (void) COLAMD_MAIN (n_row, n, (Int) Mlen, M, perm, cknobs, stats) ; 1.1454 + 1.1455 + /* Note that the output permutation is now in perm */ 1.1456 + 1.1457 + /* === get the statistics for symamd from colamd ======================== */ 1.1458 + 1.1459 + /* a dense column in colamd means a dense row and col in symamd */ 1.1460 + stats [COLAMD_DENSE_ROW] = stats [COLAMD_DENSE_COL] ; 1.1461 + 1.1462 + /* === Free M =========================================================== */ 1.1463 + 1.1464 + (*release) ((void *) M) ; 1.1465 + DEBUG0 (("symamd: done.\n")) ; 1.1466 + return (TRUE) ; 1.1467 + 1.1468 +} 1.1469 + 1.1470 +/* ========================================================================== */ 1.1471 +/* === colamd =============================================================== */ 1.1472 +/* ========================================================================== */ 1.1473 + 1.1474 +/* 1.1475 + The colamd routine computes a column ordering Q of a sparse matrix 1.1476 + A such that the LU factorization P(AQ) = LU remains sparse, where P is 1.1477 + selected via partial pivoting. The routine can also be viewed as 1.1478 + providing a permutation Q such that the Cholesky factorization 1.1479 + (AQ)'(AQ) = LL' remains sparse. 1.1480 +*/ 1.1481 + 1.1482 +PUBLIC Int COLAMD_MAIN /* returns TRUE if successful, FALSE otherwise*/ 1.1483 +( 1.1484 + /* === Parameters ======================================================= */ 1.1485 + 1.1486 + Int n_row, /* number of rows in A */ 1.1487 + Int n_col, /* number of columns in A */ 1.1488 + Int Alen, /* length of A */ 1.1489 + Int A [], /* row indices of A */ 1.1490 + Int p [], /* pointers to columns in A */ 1.1491 + double knobs [COLAMD_KNOBS],/* parameters (uses defaults if NULL) */ 1.1492 + Int stats [COLAMD_STATS] /* output statistics and error codes */ 1.1493 +) 1.1494 +{ 1.1495 + /* === Local variables ================================================== */ 1.1496 + 1.1497 + Int i ; /* loop index */ 1.1498 + Int nnz ; /* nonzeros in A */ 1.1499 + size_t Row_size ; /* size of Row [], in integers */ 1.1500 + size_t Col_size ; /* size of Col [], in integers */ 1.1501 + size_t need ; /* minimum required length of A */ 1.1502 + Colamd_Row *Row ; /* pointer into A of Row [0..n_row] array */ 1.1503 + Colamd_Col *Col ; /* pointer into A of Col [0..n_col] array */ 1.1504 + Int n_col2 ; /* number of non-dense, non-empty columns */ 1.1505 + Int n_row2 ; /* number of non-dense, non-empty rows */ 1.1506 + Int ngarbage ; /* number of garbage collections performed */ 1.1507 + Int max_deg ; /* maximum row degree */ 1.1508 + double default_knobs [COLAMD_KNOBS] ; /* default knobs array */ 1.1509 + Int aggressive ; /* do aggressive absorption */ 1.1510 + int ok ; 1.1511 + 1.1512 +#ifndef NDEBUG 1.1513 + colamd_get_debug ("colamd") ; 1.1514 +#endif /* NDEBUG */ 1.1515 + 1.1516 + /* === Check the input arguments ======================================== */ 1.1517 + 1.1518 + if (!stats) 1.1519 + { 1.1520 + DEBUG0 (("colamd: stats not present\n")) ; 1.1521 + return (FALSE) ; 1.1522 + } 1.1523 + for (i = 0 ; i < COLAMD_STATS ; i++) 1.1524 + { 1.1525 + stats [i] = 0 ; 1.1526 + } 1.1527 + stats [COLAMD_STATUS] = COLAMD_OK ; 1.1528 + stats [COLAMD_INFO1] = -1 ; 1.1529 + stats [COLAMD_INFO2] = -1 ; 1.1530 + 1.1531 + if (!A) /* A is not present */ 1.1532 + { 1.1533 + stats [COLAMD_STATUS] = COLAMD_ERROR_A_not_present ; 1.1534 + DEBUG0 (("colamd: A not present\n")) ; 1.1535 + return (FALSE) ; 1.1536 + } 1.1537 + 1.1538 + if (!p) /* p is not present */ 1.1539 + { 1.1540 + stats [COLAMD_STATUS] = COLAMD_ERROR_p_not_present ; 1.1541 + DEBUG0 (("colamd: p not present\n")) ; 1.1542 + return (FALSE) ; 1.1543 + } 1.1544 + 1.1545 + if (n_row < 0) /* n_row must be >= 0 */ 1.1546 + { 1.1547 + stats [COLAMD_STATUS] = COLAMD_ERROR_nrow_negative ; 1.1548 + stats [COLAMD_INFO1] = n_row ; 1.1549 + DEBUG0 (("colamd: nrow negative %d\n", n_row)) ; 1.1550 + return (FALSE) ; 1.1551 + } 1.1552 + 1.1553 + if (n_col < 0) /* n_col must be >= 0 */ 1.1554 + { 1.1555 + stats [COLAMD_STATUS] = COLAMD_ERROR_ncol_negative ; 1.1556 + stats [COLAMD_INFO1] = n_col ; 1.1557 + DEBUG0 (("colamd: ncol negative %d\n", n_col)) ; 1.1558 + return (FALSE) ; 1.1559 + } 1.1560 + 1.1561 + nnz = p [n_col] ; 1.1562 + if (nnz < 0) /* nnz must be >= 0 */ 1.1563 + { 1.1564 + stats [COLAMD_STATUS] = COLAMD_ERROR_nnz_negative ; 1.1565 + stats [COLAMD_INFO1] = nnz ; 1.1566 + DEBUG0 (("colamd: number of entries negative %d\n", nnz)) ; 1.1567 + return (FALSE) ; 1.1568 + } 1.1569 + 1.1570 + if (p [0] != 0) 1.1571 + { 1.1572 + stats [COLAMD_STATUS] = COLAMD_ERROR_p0_nonzero ; 1.1573 + stats [COLAMD_INFO1] = p [0] ; 1.1574 + DEBUG0 (("colamd: p[0] not zero %d\n", p [0])) ; 1.1575 + return (FALSE) ; 1.1576 + } 1.1577 + 1.1578 + /* === If no knobs, set default knobs =================================== */ 1.1579 + 1.1580 + if (!knobs) 1.1581 + { 1.1582 + COLAMD_set_defaults (default_knobs) ; 1.1583 + knobs = default_knobs ; 1.1584 + } 1.1585 + 1.1586 + aggressive = (knobs [COLAMD_AGGRESSIVE] != FALSE) ; 1.1587 + 1.1588 + /* === Allocate the Row and Col arrays from array A ===================== */ 1.1589 + 1.1590 + ok = TRUE ; 1.1591 + Col_size = COLAMD_C (n_col, &ok) ; /* size of Col array of structs */ 1.1592 + Row_size = COLAMD_R (n_row, &ok) ; /* size of Row array of structs */ 1.1593 + 1.1594 + /* need = 2*nnz + n_col + Col_size + Row_size ; */ 1.1595 + need = t_mult (nnz, 2, &ok) ; 1.1596 + need = t_add (need, n_col, &ok) ; 1.1597 + need = t_add (need, Col_size, &ok) ; 1.1598 + need = t_add (need, Row_size, &ok) ; 1.1599 + 1.1600 + if (!ok || need > (size_t) Alen || need > Int_MAX) 1.1601 + { 1.1602 + /* not enough space in array A to perform the ordering */ 1.1603 + stats [COLAMD_STATUS] = COLAMD_ERROR_A_too_small ; 1.1604 + stats [COLAMD_INFO1] = need ; 1.1605 + stats [COLAMD_INFO2] = Alen ; 1.1606 + DEBUG0 (("colamd: Need Alen >= %d, given only Alen = %d\n", need,Alen)); 1.1607 + return (FALSE) ; 1.1608 + } 1.1609 + 1.1610 + Alen -= Col_size + Row_size ; 1.1611 + Col = (Colamd_Col *) &A [Alen] ; 1.1612 + Row = (Colamd_Row *) &A [Alen + Col_size] ; 1.1613 + 1.1614 + /* === Construct the row and column data structures ===================== */ 1.1615 + 1.1616 + if (!init_rows_cols (n_row, n_col, Row, Col, A, p, stats)) 1.1617 + { 1.1618 + /* input matrix is invalid */ 1.1619 + DEBUG0 (("colamd: Matrix invalid\n")) ; 1.1620 + return (FALSE) ; 1.1621 + } 1.1622 + 1.1623 + /* === Initialize scores, kill dense rows/columns ======================= */ 1.1624 + 1.1625 + init_scoring (n_row, n_col, Row, Col, A, p, knobs, 1.1626 + &n_row2, &n_col2, &max_deg) ; 1.1627 + 1.1628 + /* === Order the supercolumns =========================================== */ 1.1629 + 1.1630 + ngarbage = find_ordering (n_row, n_col, Alen, Row, Col, A, p, 1.1631 + n_col2, max_deg, 2*nnz, aggressive) ; 1.1632 + 1.1633 + /* === Order the non-principal columns ================================== */ 1.1634 + 1.1635 + order_children (n_col, Col, p) ; 1.1636 + 1.1637 + /* === Return statistics in stats ======================================= */ 1.1638 + 1.1639 + stats [COLAMD_DENSE_ROW] = n_row - n_row2 ; 1.1640 + stats [COLAMD_DENSE_COL] = n_col - n_col2 ; 1.1641 + stats [COLAMD_DEFRAG_COUNT] = ngarbage ; 1.1642 + DEBUG0 (("colamd: done.\n")) ; 1.1643 + return (TRUE) ; 1.1644 +} 1.1645 + 1.1646 + 1.1647 +/* ========================================================================== */ 1.1648 +/* === colamd_report ======================================================== */ 1.1649 +/* ========================================================================== */ 1.1650 + 1.1651 +PUBLIC void COLAMD_report 1.1652 +( 1.1653 + Int stats [COLAMD_STATS] 1.1654 +) 1.1655 +{ 1.1656 + print_report ("colamd", stats) ; 1.1657 +} 1.1658 + 1.1659 + 1.1660 +/* ========================================================================== */ 1.1661 +/* === symamd_report ======================================================== */ 1.1662 +/* ========================================================================== */ 1.1663 + 1.1664 +PUBLIC void SYMAMD_report 1.1665 +( 1.1666 + Int stats [COLAMD_STATS] 1.1667 +) 1.1668 +{ 1.1669 + print_report ("symamd", stats) ; 1.1670 +} 1.1671 + 1.1672 + 1.1673 + 1.1674 +/* ========================================================================== */ 1.1675 +/* === NON-USER-CALLABLE ROUTINES: ========================================== */ 1.1676 +/* ========================================================================== */ 1.1677 + 1.1678 +/* There are no user-callable routines beyond this point in the file */ 1.1679 + 1.1680 + 1.1681 +/* ========================================================================== */ 1.1682 +/* === init_rows_cols ======================================================= */ 1.1683 +/* ========================================================================== */ 1.1684 + 1.1685 +/* 1.1686 + Takes the column form of the matrix in A and creates the row form of the 1.1687 + matrix. Also, row and column attributes are stored in the Col and Row 1.1688 + structs. If the columns are un-sorted or contain duplicate row indices, 1.1689 + this routine will also sort and remove duplicate row indices from the 1.1690 + column form of the matrix. Returns FALSE if the matrix is invalid, 1.1691 + TRUE otherwise. Not user-callable. 1.1692 +*/ 1.1693 + 1.1694 +PRIVATE Int init_rows_cols /* returns TRUE if OK, or FALSE otherwise */ 1.1695 +( 1.1696 + /* === Parameters ======================================================= */ 1.1697 + 1.1698 + Int n_row, /* number of rows of A */ 1.1699 + Int n_col, /* number of columns of A */ 1.1700 + Colamd_Row Row [], /* of size n_row+1 */ 1.1701 + Colamd_Col Col [], /* of size n_col+1 */ 1.1702 + Int A [], /* row indices of A, of size Alen */ 1.1703 + Int p [], /* pointers to columns in A, of size n_col+1 */ 1.1704 + Int stats [COLAMD_STATS] /* colamd statistics */ 1.1705 +) 1.1706 +{ 1.1707 + /* === Local variables ================================================== */ 1.1708 + 1.1709 + Int col ; /* a column index */ 1.1710 + Int row ; /* a row index */ 1.1711 + Int *cp ; /* a column pointer */ 1.1712 + Int *cp_end ; /* a pointer to the end of a column */ 1.1713 + Int *rp ; /* a row pointer */ 1.1714 + Int *rp_end ; /* a pointer to the end of a row */ 1.1715 + Int last_row ; /* previous row */ 1.1716 + 1.1717 + /* === Initialize columns, and check column pointers ==================== */ 1.1718 + 1.1719 + for (col = 0 ; col < n_col ; col++) 1.1720 + { 1.1721 + Col [col].start = p [col] ; 1.1722 + Col [col].length = p [col+1] - p [col] ; 1.1723 + 1.1724 + if (Col [col].length < 0) 1.1725 + { 1.1726 + /* column pointers must be non-decreasing */ 1.1727 + stats [COLAMD_STATUS] = COLAMD_ERROR_col_length_negative ; 1.1728 + stats [COLAMD_INFO1] = col ; 1.1729 + stats [COLAMD_INFO2] = Col [col].length ; 1.1730 + DEBUG0 (("colamd: col %d length %d < 0\n", col, Col [col].length)) ; 1.1731 + return (FALSE) ; 1.1732 + } 1.1733 + 1.1734 + Col [col].shared1.thickness = 1 ; 1.1735 + Col [col].shared2.score = 0 ; 1.1736 + Col [col].shared3.prev = EMPTY ; 1.1737 + Col [col].shared4.degree_next = EMPTY ; 1.1738 + } 1.1739 + 1.1740 + /* p [0..n_col] no longer needed, used as "head" in subsequent routines */ 1.1741 + 1.1742 + /* === Scan columns, compute row degrees, and check row indices ========= */ 1.1743 + 1.1744 + stats [COLAMD_INFO3] = 0 ; /* number of duplicate or unsorted row indices*/ 1.1745 + 1.1746 + for (row = 0 ; row < n_row ; row++) 1.1747 + { 1.1748 + Row [row].length = 0 ; 1.1749 + Row [row].shared2.mark = -1 ; 1.1750 + } 1.1751 + 1.1752 + for (col = 0 ; col < n_col ; col++) 1.1753 + { 1.1754 + last_row = -1 ; 1.1755 + 1.1756 + cp = &A [p [col]] ; 1.1757 + cp_end = &A [p [col+1]] ; 1.1758 + 1.1759 + while (cp < cp_end) 1.1760 + { 1.1761 + row = *cp++ ; 1.1762 + 1.1763 + /* make sure row indices within range */ 1.1764 + if (row < 0 || row >= n_row) 1.1765 + { 1.1766 + stats [COLAMD_STATUS] = COLAMD_ERROR_row_index_out_of_bounds ; 1.1767 + stats [COLAMD_INFO1] = col ; 1.1768 + stats [COLAMD_INFO2] = row ; 1.1769 + stats [COLAMD_INFO3] = n_row ; 1.1770 + DEBUG0 (("colamd: row %d col %d out of bounds\n", row, col)) ; 1.1771 + return (FALSE) ; 1.1772 + } 1.1773 + 1.1774 + if (row <= last_row || Row [row].shared2.mark == col) 1.1775 + { 1.1776 + /* row index are unsorted or repeated (or both), thus col */ 1.1777 + /* is jumbled. This is a notice, not an error condition. */ 1.1778 + stats [COLAMD_STATUS] = COLAMD_OK_BUT_JUMBLED ; 1.1779 + stats [COLAMD_INFO1] = col ; 1.1780 + stats [COLAMD_INFO2] = row ; 1.1781 + (stats [COLAMD_INFO3]) ++ ; 1.1782 + DEBUG1 (("colamd: row %d col %d unsorted/duplicate\n",row,col)); 1.1783 + } 1.1784 + 1.1785 + if (Row [row].shared2.mark != col) 1.1786 + { 1.1787 + Row [row].length++ ; 1.1788 + } 1.1789 + else 1.1790 + { 1.1791 + /* this is a repeated entry in the column, */ 1.1792 + /* it will be removed */ 1.1793 + Col [col].length-- ; 1.1794 + } 1.1795 + 1.1796 + /* mark the row as having been seen in this column */ 1.1797 + Row [row].shared2.mark = col ; 1.1798 + 1.1799 + last_row = row ; 1.1800 + } 1.1801 + } 1.1802 + 1.1803 + /* === Compute row pointers ============================================= */ 1.1804 + 1.1805 + /* row form of the matrix starts directly after the column */ 1.1806 + /* form of matrix in A */ 1.1807 + Row [0].start = p [n_col] ; 1.1808 + Row [0].shared1.p = Row [0].start ; 1.1809 + Row [0].shared2.mark = -1 ; 1.1810 + for (row = 1 ; row < n_row ; row++) 1.1811 + { 1.1812 + Row [row].start = Row [row-1].start + Row [row-1].length ; 1.1813 + Row [row].shared1.p = Row [row].start ; 1.1814 + Row [row].shared2.mark = -1 ; 1.1815 + } 1.1816 + 1.1817 + /* === Create row form ================================================== */ 1.1818 + 1.1819 + if (stats [COLAMD_STATUS] == COLAMD_OK_BUT_JUMBLED) 1.1820 + { 1.1821 + /* if cols jumbled, watch for repeated row indices */ 1.1822 + for (col = 0 ; col < n_col ; col++) 1.1823 + { 1.1824 + cp = &A [p [col]] ; 1.1825 + cp_end = &A [p [col+1]] ; 1.1826 + while (cp < cp_end) 1.1827 + { 1.1828 + row = *cp++ ; 1.1829 + if (Row [row].shared2.mark != col) 1.1830 + { 1.1831 + A [(Row [row].shared1.p)++] = col ; 1.1832 + Row [row].shared2.mark = col ; 1.1833 + } 1.1834 + } 1.1835 + } 1.1836 + } 1.1837 + else 1.1838 + { 1.1839 + /* if cols not jumbled, we don't need the mark (this is faster) */ 1.1840 + for (col = 0 ; col < n_col ; col++) 1.1841 + { 1.1842 + cp = &A [p [col]] ; 1.1843 + cp_end = &A [p [col+1]] ; 1.1844 + while (cp < cp_end) 1.1845 + { 1.1846 + A [(Row [*cp++].shared1.p)++] = col ; 1.1847 + } 1.1848 + } 1.1849 + } 1.1850 + 1.1851 + /* === Clear the row marks and set row degrees ========================== */ 1.1852 + 1.1853 + for (row = 0 ; row < n_row ; row++) 1.1854 + { 1.1855 + Row [row].shared2.mark = 0 ; 1.1856 + Row [row].shared1.degree = Row [row].length ; 1.1857 + } 1.1858 + 1.1859 + /* === See if we need to re-create columns ============================== */ 1.1860 + 1.1861 + if (stats [COLAMD_STATUS] == COLAMD_OK_BUT_JUMBLED) 1.1862 + { 1.1863 + DEBUG0 (("colamd: reconstructing column form, matrix jumbled\n")) ; 1.1864 + 1.1865 +#ifndef NDEBUG 1.1866 + /* make sure column lengths are correct */ 1.1867 + for (col = 0 ; col < n_col ; col++) 1.1868 + { 1.1869 + p [col] = Col [col].length ; 1.1870 + } 1.1871 + for (row = 0 ; row < n_row ; row++) 1.1872 + { 1.1873 + rp = &A [Row [row].start] ; 1.1874 + rp_end = rp + Row [row].length ; 1.1875 + while (rp < rp_end) 1.1876 + { 1.1877 + p [*rp++]-- ; 1.1878 + } 1.1879 + } 1.1880 + for (col = 0 ; col < n_col ; col++) 1.1881 + { 1.1882 + ASSERT (p [col] == 0) ; 1.1883 + } 1.1884 + /* now p is all zero (different than when debugging is turned off) */ 1.1885 +#endif /* NDEBUG */ 1.1886 + 1.1887 + /* === Compute col pointers ========================================= */ 1.1888 + 1.1889 + /* col form of the matrix starts at A [0]. */ 1.1890 + /* Note, we may have a gap between the col form and the row */ 1.1891 + /* form if there were duplicate entries, if so, it will be */ 1.1892 + /* removed upon the first garbage collection */ 1.1893 + Col [0].start = 0 ; 1.1894 + p [0] = Col [0].start ; 1.1895 + for (col = 1 ; col < n_col ; col++) 1.1896 + { 1.1897 + /* note that the lengths here are for pruned columns, i.e. */ 1.1898 + /* no duplicate row indices will exist for these columns */ 1.1899 + Col [col].start = Col [col-1].start + Col [col-1].length ; 1.1900 + p [col] = Col [col].start ; 1.1901 + } 1.1902 + 1.1903 + /* === Re-create col form =========================================== */ 1.1904 + 1.1905 + for (row = 0 ; row < n_row ; row++) 1.1906 + { 1.1907 + rp = &A [Row [row].start] ; 1.1908 + rp_end = rp + Row [row].length ; 1.1909 + while (rp < rp_end) 1.1910 + { 1.1911 + A [(p [*rp++])++] = row ; 1.1912 + } 1.1913 + } 1.1914 + } 1.1915 + 1.1916 + /* === Done. Matrix is not (or no longer) jumbled ====================== */ 1.1917 + 1.1918 + return (TRUE) ; 1.1919 +} 1.1920 + 1.1921 + 1.1922 +/* ========================================================================== */ 1.1923 +/* === init_scoring ========================================================= */ 1.1924 +/* ========================================================================== */ 1.1925 + 1.1926 +/* 1.1927 + Kills dense or empty columns and rows, calculates an initial score for 1.1928 + each column, and places all columns in the degree lists. Not user-callable. 1.1929 +*/ 1.1930 + 1.1931 +PRIVATE void init_scoring 1.1932 +( 1.1933 + /* === Parameters ======================================================= */ 1.1934 + 1.1935 + Int n_row, /* number of rows of A */ 1.1936 + Int n_col, /* number of columns of A */ 1.1937 + Colamd_Row Row [], /* of size n_row+1 */ 1.1938 + Colamd_Col Col [], /* of size n_col+1 */ 1.1939 + Int A [], /* column form and row form of A */ 1.1940 + Int head [], /* of size n_col+1 */ 1.1941 + double knobs [COLAMD_KNOBS],/* parameters */ 1.1942 + Int *p_n_row2, /* number of non-dense, non-empty rows */ 1.1943 + Int *p_n_col2, /* number of non-dense, non-empty columns */ 1.1944 + Int *p_max_deg /* maximum row degree */ 1.1945 +) 1.1946 +{ 1.1947 + /* === Local variables ================================================== */ 1.1948 + 1.1949 + Int c ; /* a column index */ 1.1950 + Int r, row ; /* a row index */ 1.1951 + Int *cp ; /* a column pointer */ 1.1952 + Int deg ; /* degree of a row or column */ 1.1953 + Int *cp_end ; /* a pointer to the end of a column */ 1.1954 + Int *new_cp ; /* new column pointer */ 1.1955 + Int col_length ; /* length of pruned column */ 1.1956 + Int score ; /* current column score */ 1.1957 + Int n_col2 ; /* number of non-dense, non-empty columns */ 1.1958 + Int n_row2 ; /* number of non-dense, non-empty rows */ 1.1959 + Int dense_row_count ; /* remove rows with more entries than this */ 1.1960 + Int dense_col_count ; /* remove cols with more entries than this */ 1.1961 + Int min_score ; /* smallest column score */ 1.1962 + Int max_deg ; /* maximum row degree */ 1.1963 + Int next_col ; /* Used to add to degree list.*/ 1.1964 + 1.1965 +#ifndef NDEBUG 1.1966 + Int debug_count ; /* debug only. */ 1.1967 +#endif /* NDEBUG */ 1.1968 + 1.1969 + /* === Extract knobs ==================================================== */ 1.1970 + 1.1971 + /* Note: if knobs contains a NaN, this is undefined: */ 1.1972 + if (knobs [COLAMD_DENSE_ROW] < 0) 1.1973 + { 1.1974 + /* only remove completely dense rows */ 1.1975 + dense_row_count = n_col-1 ; 1.1976 + } 1.1977 + else 1.1978 + { 1.1979 + dense_row_count = DENSE_DEGREE (knobs [COLAMD_DENSE_ROW], n_col) ; 1.1980 + } 1.1981 + if (knobs [COLAMD_DENSE_COL] < 0) 1.1982 + { 1.1983 + /* only remove completely dense columns */ 1.1984 + dense_col_count = n_row-1 ; 1.1985 + } 1.1986 + else 1.1987 + { 1.1988 + dense_col_count = 1.1989 + DENSE_DEGREE (knobs [COLAMD_DENSE_COL], MIN (n_row, n_col)) ; 1.1990 + } 1.1991 + 1.1992 + DEBUG1 (("colamd: densecount: %d %d\n", dense_row_count, dense_col_count)) ; 1.1993 + max_deg = 0 ; 1.1994 + n_col2 = n_col ; 1.1995 + n_row2 = n_row ; 1.1996 + 1.1997 + /* === Kill empty columns =============================================== */ 1.1998 + 1.1999 + /* Put the empty columns at the end in their natural order, so that LU */ 1.2000 + /* factorization can proceed as far as possible. */ 1.2001 + for (c = n_col-1 ; c >= 0 ; c--) 1.2002 + { 1.2003 + deg = Col [c].length ; 1.2004 + if (deg == 0) 1.2005 + { 1.2006 + /* this is a empty column, kill and order it last */ 1.2007 + Col [c].shared2.order = --n_col2 ; 1.2008 + KILL_PRINCIPAL_COL (c) ; 1.2009 + } 1.2010 + } 1.2011 + DEBUG1 (("colamd: null columns killed: %d\n", n_col - n_col2)) ; 1.2012 + 1.2013 + /* === Kill dense columns =============================================== */ 1.2014 + 1.2015 + /* Put the dense columns at the end, in their natural order */ 1.2016 + for (c = n_col-1 ; c >= 0 ; c--) 1.2017 + { 1.2018 + /* skip any dead columns */ 1.2019 + if (COL_IS_DEAD (c)) 1.2020 + { 1.2021 + continue ; 1.2022 + } 1.2023 + deg = Col [c].length ; 1.2024 + if (deg > dense_col_count) 1.2025 + { 1.2026 + /* this is a dense column, kill and order it last */ 1.2027 + Col [c].shared2.order = --n_col2 ; 1.2028 + /* decrement the row degrees */ 1.2029 + cp = &A [Col [c].start] ; 1.2030 + cp_end = cp + Col [c].length ; 1.2031 + while (cp < cp_end) 1.2032 + { 1.2033 + Row [*cp++].shared1.degree-- ; 1.2034 + } 1.2035 + KILL_PRINCIPAL_COL (c) ; 1.2036 + } 1.2037 + } 1.2038 + DEBUG1 (("colamd: Dense and null columns killed: %d\n", n_col - n_col2)) ; 1.2039 + 1.2040 + /* === Kill dense and empty rows ======================================== */ 1.2041 + 1.2042 + for (r = 0 ; r < n_row ; r++) 1.2043 + { 1.2044 + deg = Row [r].shared1.degree ; 1.2045 + ASSERT (deg >= 0 && deg <= n_col) ; 1.2046 + if (deg > dense_row_count || deg == 0) 1.2047 + { 1.2048 + /* kill a dense or empty row */ 1.2049 + KILL_ROW (r) ; 1.2050 + --n_row2 ; 1.2051 + } 1.2052 + else 1.2053 + { 1.2054 + /* keep track of max degree of remaining rows */ 1.2055 + max_deg = MAX (max_deg, deg) ; 1.2056 + } 1.2057 + } 1.2058 + DEBUG1 (("colamd: Dense and null rows killed: %d\n", n_row - n_row2)) ; 1.2059 + 1.2060 + /* === Compute initial column scores ==================================== */ 1.2061 + 1.2062 + /* At this point the row degrees are accurate. They reflect the number */ 1.2063 + /* of "live" (non-dense) columns in each row. No empty rows exist. */ 1.2064 + /* Some "live" columns may contain only dead rows, however. These are */ 1.2065 + /* pruned in the code below. */ 1.2066 + 1.2067 + /* now find the initial matlab score for each column */ 1.2068 + for (c = n_col-1 ; c >= 0 ; c--) 1.2069 + { 1.2070 + /* skip dead column */ 1.2071 + if (COL_IS_DEAD (c)) 1.2072 + { 1.2073 + continue ; 1.2074 + } 1.2075 + score = 0 ; 1.2076 + cp = &A [Col [c].start] ; 1.2077 + new_cp = cp ; 1.2078 + cp_end = cp + Col [c].length ; 1.2079 + while (cp < cp_end) 1.2080 + { 1.2081 + /* get a row */ 1.2082 + row = *cp++ ; 1.2083 + /* skip if dead */ 1.2084 + if (ROW_IS_DEAD (row)) 1.2085 + { 1.2086 + continue ; 1.2087 + } 1.2088 + /* compact the column */ 1.2089 + *new_cp++ = row ; 1.2090 + /* add row's external degree */ 1.2091 + score += Row [row].shared1.degree - 1 ; 1.2092 + /* guard against integer overflow */ 1.2093 + score = MIN (score, n_col) ; 1.2094 + } 1.2095 + /* determine pruned column length */ 1.2096 + col_length = (Int) (new_cp - &A [Col [c].start]) ; 1.2097 + if (col_length == 0) 1.2098 + { 1.2099 + /* a newly-made null column (all rows in this col are "dense" */ 1.2100 + /* and have already been killed) */ 1.2101 + DEBUG2 (("Newly null killed: %d\n", c)) ; 1.2102 + Col [c].shared2.order = --n_col2 ; 1.2103 + KILL_PRINCIPAL_COL (c) ; 1.2104 + } 1.2105 + else 1.2106 + { 1.2107 + /* set column length and set score */ 1.2108 + ASSERT (score >= 0) ; 1.2109 + ASSERT (score <= n_col) ; 1.2110 + Col [c].length = col_length ; 1.2111 + Col [c].shared2.score = score ; 1.2112 + } 1.2113 + } 1.2114 + DEBUG1 (("colamd: Dense, null, and newly-null columns killed: %d\n", 1.2115 + n_col-n_col2)) ; 1.2116 + 1.2117 + /* At this point, all empty rows and columns are dead. All live columns */ 1.2118 + /* are "clean" (containing no dead rows) and simplicial (no supercolumns */ 1.2119 + /* yet). Rows may contain dead columns, but all live rows contain at */ 1.2120 + /* least one live column. */ 1.2121 + 1.2122 +#ifndef NDEBUG 1.2123 + debug_structures (n_row, n_col, Row, Col, A, n_col2) ; 1.2124 +#endif /* NDEBUG */ 1.2125 + 1.2126 + /* === Initialize degree lists ========================================== */ 1.2127 + 1.2128 +#ifndef NDEBUG 1.2129 + debug_count = 0 ; 1.2130 +#endif /* NDEBUG */ 1.2131 + 1.2132 + /* clear the hash buckets */ 1.2133 + for (c = 0 ; c <= n_col ; c++) 1.2134 + { 1.2135 + head [c] = EMPTY ; 1.2136 + } 1.2137 + min_score = n_col ; 1.2138 + /* place in reverse order, so low column indices are at the front */ 1.2139 + /* of the lists. This is to encourage natural tie-breaking */ 1.2140 + for (c = n_col-1 ; c >= 0 ; c--) 1.2141 + { 1.2142 + /* only add principal columns to degree lists */ 1.2143 + if (COL_IS_ALIVE (c)) 1.2144 + { 1.2145 + DEBUG4 (("place %d score %d minscore %d ncol %d\n", 1.2146 + c, Col [c].shared2.score, min_score, n_col)) ; 1.2147 + 1.2148 + /* === Add columns score to DList =============================== */ 1.2149 + 1.2150 + score = Col [c].shared2.score ; 1.2151 + 1.2152 + ASSERT (min_score >= 0) ; 1.2153 + ASSERT (min_score <= n_col) ; 1.2154 + ASSERT (score >= 0) ; 1.2155 + ASSERT (score <= n_col) ; 1.2156 + ASSERT (head [score] >= EMPTY) ; 1.2157 + 1.2158 + /* now add this column to dList at proper score location */ 1.2159 + next_col = head [score] ; 1.2160 + Col [c].shared3.prev = EMPTY ; 1.2161 + Col [c].shared4.degree_next = next_col ; 1.2162 + 1.2163 + /* if there already was a column with the same score, set its */ 1.2164 + /* previous pointer to this new column */ 1.2165 + if (next_col != EMPTY) 1.2166 + { 1.2167 + Col [next_col].shared3.prev = c ; 1.2168 + } 1.2169 + head [score] = c ; 1.2170 + 1.2171 + /* see if this score is less than current min */ 1.2172 + min_score = MIN (min_score, score) ; 1.2173 + 1.2174 +#ifndef NDEBUG 1.2175 + debug_count++ ; 1.2176 +#endif /* NDEBUG */ 1.2177 + 1.2178 + } 1.2179 + } 1.2180 + 1.2181 +#ifndef NDEBUG 1.2182 + DEBUG1 (("colamd: Live cols %d out of %d, non-princ: %d\n", 1.2183 + debug_count, n_col, n_col-debug_count)) ; 1.2184 + ASSERT (debug_count == n_col2) ; 1.2185 + debug_deg_lists (n_row, n_col, Row, Col, head, min_score, n_col2, max_deg) ; 1.2186 +#endif /* NDEBUG */ 1.2187 + 1.2188 + /* === Return number of remaining columns, and max row degree =========== */ 1.2189 + 1.2190 + *p_n_col2 = n_col2 ; 1.2191 + *p_n_row2 = n_row2 ; 1.2192 + *p_max_deg = max_deg ; 1.2193 +} 1.2194 + 1.2195 + 1.2196 +/* ========================================================================== */ 1.2197 +/* === find_ordering ======================================================== */ 1.2198 +/* ========================================================================== */ 1.2199 + 1.2200 +/* 1.2201 + Order the principal columns of the supercolumn form of the matrix 1.2202 + (no supercolumns on input). Uses a minimum approximate column minimum 1.2203 + degree ordering method. Not user-callable. 1.2204 +*/ 1.2205 + 1.2206 +PRIVATE Int find_ordering /* return the number of garbage collections */ 1.2207 +( 1.2208 + /* === Parameters ======================================================= */ 1.2209 + 1.2210 + Int n_row, /* number of rows of A */ 1.2211 + Int n_col, /* number of columns of A */ 1.2212 + Int Alen, /* size of A, 2*nnz + n_col or larger */ 1.2213 + Colamd_Row Row [], /* of size n_row+1 */ 1.2214 + Colamd_Col Col [], /* of size n_col+1 */ 1.2215 + Int A [], /* column form and row form of A */ 1.2216 + Int head [], /* of size n_col+1 */ 1.2217 + Int n_col2, /* Remaining columns to order */ 1.2218 + Int max_deg, /* Maximum row degree */ 1.2219 + Int pfree, /* index of first free slot (2*nnz on entry) */ 1.2220 + Int aggressive 1.2221 +) 1.2222 +{ 1.2223 + /* === Local variables ================================================== */ 1.2224 + 1.2225 + Int k ; /* current pivot ordering step */ 1.2226 + Int pivot_col ; /* current pivot column */ 1.2227 + Int *cp ; /* a column pointer */ 1.2228 + Int *rp ; /* a row pointer */ 1.2229 + Int pivot_row ; /* current pivot row */ 1.2230 + Int *new_cp ; /* modified column pointer */ 1.2231 + Int *new_rp ; /* modified row pointer */ 1.2232 + Int pivot_row_start ; /* pointer to start of pivot row */ 1.2233 + Int pivot_row_degree ; /* number of columns in pivot row */ 1.2234 + Int pivot_row_length ; /* number of supercolumns in pivot row */ 1.2235 + Int pivot_col_score ; /* score of pivot column */ 1.2236 + Int needed_memory ; /* free space needed for pivot row */ 1.2237 + Int *cp_end ; /* pointer to the end of a column */ 1.2238 + Int *rp_end ; /* pointer to the end of a row */ 1.2239 + Int row ; /* a row index */ 1.2240 + Int col ; /* a column index */ 1.2241 + Int max_score ; /* maximum possible score */ 1.2242 + Int cur_score ; /* score of current column */ 1.2243 + unsigned Int hash ; /* hash value for supernode detection */ 1.2244 + Int head_column ; /* head of hash bucket */ 1.2245 + Int first_col ; /* first column in hash bucket */ 1.2246 + Int tag_mark ; /* marker value for mark array */ 1.2247 + Int row_mark ; /* Row [row].shared2.mark */ 1.2248 + Int set_difference ; /* set difference size of row with pivot row */ 1.2249 + Int min_score ; /* smallest column score */ 1.2250 + Int col_thickness ; /* "thickness" (no. of columns in a supercol) */ 1.2251 + Int max_mark ; /* maximum value of tag_mark */ 1.2252 + Int pivot_col_thickness ; /* number of columns represented by pivot col */ 1.2253 + Int prev_col ; /* Used by Dlist operations. */ 1.2254 + Int next_col ; /* Used by Dlist operations. */ 1.2255 + Int ngarbage ; /* number of garbage collections performed */ 1.2256 + 1.2257 +#ifndef NDEBUG 1.2258 + Int debug_d ; /* debug loop counter */ 1.2259 + Int debug_step = 0 ; /* debug loop counter */ 1.2260 +#endif /* NDEBUG */ 1.2261 + 1.2262 + /* === Initialization and clear mark ==================================== */ 1.2263 + 1.2264 + max_mark = INT_MAX - n_col ; /* INT_MAX defined in <limits.h> */ 1.2265 + tag_mark = clear_mark (0, max_mark, n_row, Row) ; 1.2266 + min_score = 0 ; 1.2267 + ngarbage = 0 ; 1.2268 + DEBUG1 (("colamd: Ordering, n_col2=%d\n", n_col2)) ; 1.2269 + 1.2270 + /* === Order the columns ================================================ */ 1.2271 + 1.2272 + for (k = 0 ; k < n_col2 ; /* 'k' is incremented below */) 1.2273 + { 1.2274 + 1.2275 +#ifndef NDEBUG 1.2276 + if (debug_step % 100 == 0) 1.2277 + { 1.2278 + DEBUG2 (("\n... Step k: %d out of n_col2: %d\n", k, n_col2)) ; 1.2279 + } 1.2280 + else 1.2281 + { 1.2282 + DEBUG3 (("\n----------Step k: %d out of n_col2: %d\n", k, n_col2)) ; 1.2283 + } 1.2284 + debug_step++ ; 1.2285 + debug_deg_lists (n_row, n_col, Row, Col, head, 1.2286 + min_score, n_col2-k, max_deg) ; 1.2287 + debug_matrix (n_row, n_col, Row, Col, A) ; 1.2288 +#endif /* NDEBUG */ 1.2289 + 1.2290 + /* === Select pivot column, and order it ============================ */ 1.2291 + 1.2292 + /* make sure degree list isn't empty */ 1.2293 + ASSERT (min_score >= 0) ; 1.2294 + ASSERT (min_score <= n_col) ; 1.2295 + ASSERT (head [min_score] >= EMPTY) ; 1.2296 + 1.2297 +#ifndef NDEBUG 1.2298 + for (debug_d = 0 ; debug_d < min_score ; debug_d++) 1.2299 + { 1.2300 + ASSERT (head [debug_d] == EMPTY) ; 1.2301 + } 1.2302 +#endif /* NDEBUG */ 1.2303 + 1.2304 + /* get pivot column from head of minimum degree list */ 1.2305 + while (head [min_score] == EMPTY && min_score < n_col) 1.2306 + { 1.2307 + min_score++ ; 1.2308 + } 1.2309 + pivot_col = head [min_score] ; 1.2310 + ASSERT (pivot_col >= 0 && pivot_col <= n_col) ; 1.2311 + next_col = Col [pivot_col].shared4.degree_next ; 1.2312 + head [min_score] = next_col ; 1.2313 + if (next_col != EMPTY) 1.2314 + { 1.2315 + Col [next_col].shared3.prev = EMPTY ; 1.2316 + } 1.2317 + 1.2318 + ASSERT (COL_IS_ALIVE (pivot_col)) ; 1.2319 + 1.2320 + /* remember score for defrag check */ 1.2321 + pivot_col_score = Col [pivot_col].shared2.score ; 1.2322 + 1.2323 + /* the pivot column is the kth column in the pivot order */ 1.2324 + Col [pivot_col].shared2.order = k ; 1.2325 + 1.2326 + /* increment order count by column thickness */ 1.2327 + pivot_col_thickness = Col [pivot_col].shared1.thickness ; 1.2328 + k += pivot_col_thickness ; 1.2329 + ASSERT (pivot_col_thickness > 0) ; 1.2330 + DEBUG3 (("Pivot col: %d thick %d\n", pivot_col, pivot_col_thickness)) ; 1.2331 + 1.2332 + /* === Garbage_collection, if necessary ============================= */ 1.2333 + 1.2334 + needed_memory = MIN (pivot_col_score, n_col - k) ; 1.2335 + if (pfree + needed_memory >= Alen) 1.2336 + { 1.2337 + pfree = garbage_collection (n_row, n_col, Row, Col, A, &A [pfree]) ; 1.2338 + ngarbage++ ; 1.2339 + /* after garbage collection we will have enough */ 1.2340 + ASSERT (pfree + needed_memory < Alen) ; 1.2341 + /* garbage collection has wiped out the Row[].shared2.mark array */ 1.2342 + tag_mark = clear_mark (0, max_mark, n_row, Row) ; 1.2343 + 1.2344 +#ifndef NDEBUG 1.2345 + debug_matrix (n_row, n_col, Row, Col, A) ; 1.2346 +#endif /* NDEBUG */ 1.2347 + } 1.2348 + 1.2349 + /* === Compute pivot row pattern ==================================== */ 1.2350 + 1.2351 + /* get starting location for this new merged row */ 1.2352 + pivot_row_start = pfree ; 1.2353 + 1.2354 + /* initialize new row counts to zero */ 1.2355 + pivot_row_degree = 0 ; 1.2356 + 1.2357 + /* tag pivot column as having been visited so it isn't included */ 1.2358 + /* in merged pivot row */ 1.2359 + Col [pivot_col].shared1.thickness = -pivot_col_thickness ; 1.2360 + 1.2361 + /* pivot row is the union of all rows in the pivot column pattern */ 1.2362 + cp = &A [Col [pivot_col].start] ; 1.2363 + cp_end = cp + Col [pivot_col].length ; 1.2364 + while (cp < cp_end) 1.2365 + { 1.2366 + /* get a row */ 1.2367 + row = *cp++ ; 1.2368 + DEBUG4 (("Pivot col pattern %d %d\n", ROW_IS_ALIVE (row), row)) ; 1.2369 + /* skip if row is dead */ 1.2370 + if (ROW_IS_ALIVE (row)) 1.2371 + { 1.2372 + rp = &A [Row [row].start] ; 1.2373 + rp_end = rp + Row [row].length ; 1.2374 + while (rp < rp_end) 1.2375 + { 1.2376 + /* get a column */ 1.2377 + col = *rp++ ; 1.2378 + /* add the column, if alive and untagged */ 1.2379 + col_thickness = Col [col].shared1.thickness ; 1.2380 + if (col_thickness > 0 && COL_IS_ALIVE (col)) 1.2381 + { 1.2382 + /* tag column in pivot row */ 1.2383 + Col [col].shared1.thickness = -col_thickness ; 1.2384 + ASSERT (pfree < Alen) ; 1.2385 + /* place column in pivot row */ 1.2386 + A [pfree++] = col ; 1.2387 + pivot_row_degree += col_thickness ; 1.2388 + } 1.2389 + } 1.2390 + } 1.2391 + } 1.2392 + 1.2393 + /* clear tag on pivot column */ 1.2394 + Col [pivot_col].shared1.thickness = pivot_col_thickness ; 1.2395 + max_deg = MAX (max_deg, pivot_row_degree) ; 1.2396 + 1.2397 +#ifndef NDEBUG 1.2398 + DEBUG3 (("check2\n")) ; 1.2399 + debug_mark (n_row, Row, tag_mark, max_mark) ; 1.2400 +#endif /* NDEBUG */ 1.2401 + 1.2402 + /* === Kill all rows used to construct pivot row ==================== */ 1.2403 + 1.2404 + /* also kill pivot row, temporarily */ 1.2405 + cp = &A [Col [pivot_col].start] ; 1.2406 + cp_end = cp + Col [pivot_col].length ; 1.2407 + while (cp < cp_end) 1.2408 + { 1.2409 + /* may be killing an already dead row */ 1.2410 + row = *cp++ ; 1.2411 + DEBUG3 (("Kill row in pivot col: %d\n", row)) ; 1.2412 + KILL_ROW (row) ; 1.2413 + } 1.2414 + 1.2415 + /* === Select a row index to use as the new pivot row =============== */ 1.2416 + 1.2417 + pivot_row_length = pfree - pivot_row_start ; 1.2418 + if (pivot_row_length > 0) 1.2419 + { 1.2420 + /* pick the "pivot" row arbitrarily (first row in col) */ 1.2421 + pivot_row = A [Col [pivot_col].start] ; 1.2422 + DEBUG3 (("Pivotal row is %d\n", pivot_row)) ; 1.2423 + } 1.2424 + else 1.2425 + { 1.2426 + /* there is no pivot row, since it is of zero length */ 1.2427 + pivot_row = EMPTY ; 1.2428 + ASSERT (pivot_row_length == 0) ; 1.2429 + } 1.2430 + ASSERT (Col [pivot_col].length > 0 || pivot_row_length == 0) ; 1.2431 + 1.2432 + /* === Approximate degree computation =============================== */ 1.2433 + 1.2434 + /* Here begins the computation of the approximate degree. The column */ 1.2435 + /* score is the sum of the pivot row "length", plus the size of the */ 1.2436 + /* set differences of each row in the column minus the pattern of the */ 1.2437 + /* pivot row itself. The column ("thickness") itself is also */ 1.2438 + /* excluded from the column score (we thus use an approximate */ 1.2439 + /* external degree). */ 1.2440 + 1.2441 + /* The time taken by the following code (compute set differences, and */ 1.2442 + /* add them up) is proportional to the size of the data structure */ 1.2443 + /* being scanned - that is, the sum of the sizes of each column in */ 1.2444 + /* the pivot row. Thus, the amortized time to compute a column score */ 1.2445 + /* is proportional to the size of that column (where size, in this */ 1.2446 + /* context, is the column "length", or the number of row indices */ 1.2447 + /* in that column). The number of row indices in a column is */ 1.2448 + /* monotonically non-decreasing, from the length of the original */ 1.2449 + /* column on input to colamd. */ 1.2450 + 1.2451 + /* === Compute set differences ====================================== */ 1.2452 + 1.2453 + DEBUG3 (("** Computing set differences phase. **\n")) ; 1.2454 + 1.2455 + /* pivot row is currently dead - it will be revived later. */ 1.2456 + 1.2457 + DEBUG3 (("Pivot row: ")) ; 1.2458 + /* for each column in pivot row */ 1.2459 + rp = &A [pivot_row_start] ; 1.2460 + rp_end = rp + pivot_row_length ; 1.2461 + while (rp < rp_end) 1.2462 + { 1.2463 + col = *rp++ ; 1.2464 + ASSERT (COL_IS_ALIVE (col) && col != pivot_col) ; 1.2465 + DEBUG3 (("Col: %d\n", col)) ; 1.2466 + 1.2467 + /* clear tags used to construct pivot row pattern */ 1.2468 + col_thickness = -Col [col].shared1.thickness ; 1.2469 + ASSERT (col_thickness > 0) ; 1.2470 + Col [col].shared1.thickness = col_thickness ; 1.2471 + 1.2472 + /* === Remove column from degree list =========================== */ 1.2473 + 1.2474 + cur_score = Col [col].shared2.score ; 1.2475 + prev_col = Col [col].shared3.prev ; 1.2476 + next_col = Col [col].shared4.degree_next ; 1.2477 + ASSERT (cur_score >= 0) ; 1.2478 + ASSERT (cur_score <= n_col) ; 1.2479 + ASSERT (cur_score >= EMPTY) ; 1.2480 + if (prev_col == EMPTY) 1.2481 + { 1.2482 + head [cur_score] = next_col ; 1.2483 + } 1.2484 + else 1.2485 + { 1.2486 + Col [prev_col].shared4.degree_next = next_col ; 1.2487 + } 1.2488 + if (next_col != EMPTY) 1.2489 + { 1.2490 + Col [next_col].shared3.prev = prev_col ; 1.2491 + } 1.2492 + 1.2493 + /* === Scan the column ========================================== */ 1.2494 + 1.2495 + cp = &A [Col [col].start] ; 1.2496 + cp_end = cp + Col [col].length ; 1.2497 + while (cp < cp_end) 1.2498 + { 1.2499 + /* get a row */ 1.2500 + row = *cp++ ; 1.2501 + row_mark = Row [row].shared2.mark ; 1.2502 + /* skip if dead */ 1.2503 + if (ROW_IS_MARKED_DEAD (row_mark)) 1.2504 + { 1.2505 + continue ; 1.2506 + } 1.2507 + ASSERT (row != pivot_row) ; 1.2508 + set_difference = row_mark - tag_mark ; 1.2509 + /* check if the row has been seen yet */ 1.2510 + if (set_difference < 0) 1.2511 + { 1.2512 + ASSERT (Row [row].shared1.degree <= max_deg) ; 1.2513 + set_difference = Row [row].shared1.degree ; 1.2514 + } 1.2515 + /* subtract column thickness from this row's set difference */ 1.2516 + set_difference -= col_thickness ; 1.2517 + ASSERT (set_difference >= 0) ; 1.2518 + /* absorb this row if the set difference becomes zero */ 1.2519 + if (set_difference == 0 && aggressive) 1.2520 + { 1.2521 + DEBUG3 (("aggressive absorption. Row: %d\n", row)) ; 1.2522 + KILL_ROW (row) ; 1.2523 + } 1.2524 + else 1.2525 + { 1.2526 + /* save the new mark */ 1.2527 + Row [row].shared2.mark = set_difference + tag_mark ; 1.2528 + } 1.2529 + } 1.2530 + } 1.2531 + 1.2532 +#ifndef NDEBUG 1.2533 + debug_deg_lists (n_row, n_col, Row, Col, head, 1.2534 + min_score, n_col2-k-pivot_row_degree, max_deg) ; 1.2535 +#endif /* NDEBUG */ 1.2536 + 1.2537 + /* === Add up set differences for each column ======================= */ 1.2538 + 1.2539 + DEBUG3 (("** Adding set differences phase. **\n")) ; 1.2540 + 1.2541 + /* for each column in pivot row */ 1.2542 + rp = &A [pivot_row_start] ; 1.2543 + rp_end = rp + pivot_row_length ; 1.2544 + while (rp < rp_end) 1.2545 + { 1.2546 + /* get a column */ 1.2547 + col = *rp++ ; 1.2548 + ASSERT (COL_IS_ALIVE (col) && col != pivot_col) ; 1.2549 + hash = 0 ; 1.2550 + cur_score = 0 ; 1.2551 + cp = &A [Col [col].start] ; 1.2552 + /* compact the column */ 1.2553 + new_cp = cp ; 1.2554 + cp_end = cp + Col [col].length ; 1.2555 + 1.2556 + DEBUG4 (("Adding set diffs for Col: %d.\n", col)) ; 1.2557 + 1.2558 + while (cp < cp_end) 1.2559 + { 1.2560 + /* get a row */ 1.2561 + row = *cp++ ; 1.2562 + ASSERT(row >= 0 && row < n_row) ; 1.2563 + row_mark = Row [row].shared2.mark ; 1.2564 + /* skip if dead */ 1.2565 + if (ROW_IS_MARKED_DEAD (row_mark)) 1.2566 + { 1.2567 + DEBUG4 ((" Row %d, dead\n", row)) ; 1.2568 + continue ; 1.2569 + } 1.2570 + DEBUG4 ((" Row %d, set diff %d\n", row, row_mark-tag_mark)); 1.2571 + ASSERT (row_mark >= tag_mark) ; 1.2572 + /* compact the column */ 1.2573 + *new_cp++ = row ; 1.2574 + /* compute hash function */ 1.2575 + hash += row ; 1.2576 + /* add set difference */ 1.2577 + cur_score += row_mark - tag_mark ; 1.2578 + /* integer overflow... */ 1.2579 + cur_score = MIN (cur_score, n_col) ; 1.2580 + } 1.2581 + 1.2582 + /* recompute the column's length */ 1.2583 + Col [col].length = (Int) (new_cp - &A [Col [col].start]) ; 1.2584 + 1.2585 + /* === Further mass elimination ================================= */ 1.2586 + 1.2587 + if (Col [col].length == 0) 1.2588 + { 1.2589 + DEBUG4 (("further mass elimination. Col: %d\n", col)) ; 1.2590 + /* nothing left but the pivot row in this column */ 1.2591 + KILL_PRINCIPAL_COL (col) ; 1.2592 + pivot_row_degree -= Col [col].shared1.thickness ; 1.2593 + ASSERT (pivot_row_degree >= 0) ; 1.2594 + /* order it */ 1.2595 + Col [col].shared2.order = k ; 1.2596 + /* increment order count by column thickness */ 1.2597 + k += Col [col].shared1.thickness ; 1.2598 + } 1.2599 + else 1.2600 + { 1.2601 + /* === Prepare for supercolumn detection ==================== */ 1.2602 + 1.2603 + DEBUG4 (("Preparing supercol detection for Col: %d.\n", col)) ; 1.2604 + 1.2605 + /* save score so far */ 1.2606 + Col [col].shared2.score = cur_score ; 1.2607 + 1.2608 + /* add column to hash table, for supercolumn detection */ 1.2609 + hash %= n_col + 1 ; 1.2610 + 1.2611 + DEBUG4 ((" Hash = %d, n_col = %d.\n", hash, n_col)) ; 1.2612 + ASSERT (((Int) hash) <= n_col) ; 1.2613 + 1.2614 + head_column = head [hash] ; 1.2615 + if (head_column > EMPTY) 1.2616 + { 1.2617 + /* degree list "hash" is non-empty, use prev (shared3) of */ 1.2618 + /* first column in degree list as head of hash bucket */ 1.2619 + first_col = Col [head_column].shared3.headhash ; 1.2620 + Col [head_column].shared3.headhash = col ; 1.2621 + } 1.2622 + else 1.2623 + { 1.2624 + /* degree list "hash" is empty, use head as hash bucket */ 1.2625 + first_col = - (head_column + 2) ; 1.2626 + head [hash] = - (col + 2) ; 1.2627 + } 1.2628 + Col [col].shared4.hash_next = first_col ; 1.2629 + 1.2630 + /* save hash function in Col [col].shared3.hash */ 1.2631 + Col [col].shared3.hash = (Int) hash ; 1.2632 + ASSERT (COL_IS_ALIVE (col)) ; 1.2633 + } 1.2634 + } 1.2635 + 1.2636 + /* The approximate external column degree is now computed. */ 1.2637 + 1.2638 + /* === Supercolumn detection ======================================== */ 1.2639 + 1.2640 + DEBUG3 (("** Supercolumn detection phase. **\n")) ; 1.2641 + 1.2642 + detect_super_cols ( 1.2643 + 1.2644 +#ifndef NDEBUG 1.2645 + n_col, Row, 1.2646 +#endif /* NDEBUG */ 1.2647 + 1.2648 + Col, A, head, pivot_row_start, pivot_row_length) ; 1.2649 + 1.2650 + /* === Kill the pivotal column ====================================== */ 1.2651 + 1.2652 + KILL_PRINCIPAL_COL (pivot_col) ; 1.2653 + 1.2654 + /* === Clear mark =================================================== */ 1.2655 + 1.2656 + tag_mark = clear_mark (tag_mark+max_deg+1, max_mark, n_row, Row) ; 1.2657 + 1.2658 +#ifndef NDEBUG 1.2659 + DEBUG3 (("check3\n")) ; 1.2660 + debug_mark (n_row, Row, tag_mark, max_mark) ; 1.2661 +#endif /* NDEBUG */ 1.2662 + 1.2663 + /* === Finalize the new pivot row, and column scores ================ */ 1.2664 + 1.2665 + DEBUG3 (("** Finalize scores phase. **\n")) ; 1.2666 + 1.2667 + /* for each column in pivot row */ 1.2668 + rp = &A [pivot_row_start] ; 1.2669 + /* compact the pivot row */ 1.2670 + new_rp = rp ; 1.2671 + rp_end = rp + pivot_row_length ; 1.2672 + while (rp < rp_end) 1.2673 + { 1.2674 + col = *rp++ ; 1.2675 + /* skip dead columns */ 1.2676 + if (COL_IS_DEAD (col)) 1.2677 + { 1.2678 + continue ; 1.2679 + } 1.2680 + *new_rp++ = col ; 1.2681 + /* add new pivot row to column */ 1.2682 + A [Col [col].start + (Col [col].length++)] = pivot_row ; 1.2683 + 1.2684 + /* retrieve score so far and add on pivot row's degree. */ 1.2685 + /* (we wait until here for this in case the pivot */ 1.2686 + /* row's degree was reduced due to mass elimination). */ 1.2687 + cur_score = Col [col].shared2.score + pivot_row_degree ; 1.2688 + 1.2689 + /* calculate the max possible score as the number of */ 1.2690 + /* external columns minus the 'k' value minus the */ 1.2691 + /* columns thickness */ 1.2692 + max_score = n_col - k - Col [col].shared1.thickness ; 1.2693 + 1.2694 + /* make the score the external degree of the union-of-rows */ 1.2695 + cur_score -= Col [col].shared1.thickness ; 1.2696 + 1.2697 + /* make sure score is less or equal than the max score */ 1.2698 + cur_score = MIN (cur_score, max_score) ; 1.2699 + ASSERT (cur_score >= 0) ; 1.2700 + 1.2701 + /* store updated score */ 1.2702 + Col [col].shared2.score = cur_score ; 1.2703 + 1.2704 + /* === Place column back in degree list ========================= */ 1.2705 + 1.2706 + ASSERT (min_score >= 0) ; 1.2707 + ASSERT (min_score <= n_col) ; 1.2708 + ASSERT (cur_score >= 0) ; 1.2709 + ASSERT (cur_score <= n_col) ; 1.2710 + ASSERT (head [cur_score] >= EMPTY) ; 1.2711 + next_col = head [cur_score] ; 1.2712 + Col [col].shared4.degree_next = next_col ; 1.2713 + Col [col].shared3.prev = EMPTY ; 1.2714 + if (next_col != EMPTY) 1.2715 + { 1.2716 + Col [next_col].shared3.prev = col ; 1.2717 + } 1.2718 + head [cur_score] = col ; 1.2719 + 1.2720 + /* see if this score is less than current min */ 1.2721 + min_score = MIN (min_score, cur_score) ; 1.2722 + 1.2723 + } 1.2724 + 1.2725 +#ifndef NDEBUG 1.2726 + debug_deg_lists (n_row, n_col, Row, Col, head, 1.2727 + min_score, n_col2-k, max_deg) ; 1.2728 +#endif /* NDEBUG */ 1.2729 + 1.2730 + /* === Resurrect the new pivot row ================================== */ 1.2731 + 1.2732 + if (pivot_row_degree > 0) 1.2733 + { 1.2734 + /* update pivot row length to reflect any cols that were killed */ 1.2735 + /* during super-col detection and mass elimination */ 1.2736 + Row [pivot_row].start = pivot_row_start ; 1.2737 + Row [pivot_row].length = (Int) (new_rp - &A[pivot_row_start]) ; 1.2738 + ASSERT (Row [pivot_row].length > 0) ; 1.2739 + Row [pivot_row].shared1.degree = pivot_row_degree ; 1.2740 + Row [pivot_row].shared2.mark = 0 ; 1.2741 + /* pivot row is no longer dead */ 1.2742 + 1.2743 + DEBUG1 (("Resurrect Pivot_row %d deg: %d\n", 1.2744 + pivot_row, pivot_row_degree)) ; 1.2745 + } 1.2746 + } 1.2747 + 1.2748 + /* === All principal columns have now been ordered ====================== */ 1.2749 + 1.2750 + return (ngarbage) ; 1.2751 +} 1.2752 + 1.2753 + 1.2754 +/* ========================================================================== */ 1.2755 +/* === order_children ======================================================= */ 1.2756 +/* ========================================================================== */ 1.2757 + 1.2758 +/* 1.2759 + The find_ordering routine has ordered all of the principal columns (the 1.2760 + representatives of the supercolumns). The non-principal columns have not 1.2761 + yet been ordered. This routine orders those columns by walking up the 1.2762 + parent tree (a column is a child of the column which absorbed it). The 1.2763 + final permutation vector is then placed in p [0 ... n_col-1], with p [0] 1.2764 + being the first column, and p [n_col-1] being the last. It doesn't look 1.2765 + like it at first glance, but be assured that this routine takes time linear 1.2766 + in the number of columns. Although not immediately obvious, the time 1.2767 + taken by this routine is O (n_col), that is, linear in the number of 1.2768 + columns. Not user-callable. 1.2769 +*/ 1.2770 + 1.2771 +PRIVATE void order_children 1.2772 +( 1.2773 + /* === Parameters ======================================================= */ 1.2774 + 1.2775 + Int n_col, /* number of columns of A */ 1.2776 + Colamd_Col Col [], /* of size n_col+1 */ 1.2777 + Int p [] /* p [0 ... n_col-1] is the column permutation*/ 1.2778 +) 1.2779 +{ 1.2780 + /* === Local variables ================================================== */ 1.2781 + 1.2782 + Int i ; /* loop counter for all columns */ 1.2783 + Int c ; /* column index */ 1.2784 + Int parent ; /* index of column's parent */ 1.2785 + Int order ; /* column's order */ 1.2786 + 1.2787 + /* === Order each non-principal column ================================== */ 1.2788 + 1.2789 + for (i = 0 ; i < n_col ; i++) 1.2790 + { 1.2791 + /* find an un-ordered non-principal column */ 1.2792 + ASSERT (COL_IS_DEAD (i)) ; 1.2793 + if (!COL_IS_DEAD_PRINCIPAL (i) && Col [i].shared2.order == EMPTY) 1.2794 + { 1.2795 + parent = i ; 1.2796 + /* once found, find its principal parent */ 1.2797 + do 1.2798 + { 1.2799 + parent = Col [parent].shared1.parent ; 1.2800 + } while (!COL_IS_DEAD_PRINCIPAL (parent)) ; 1.2801 + 1.2802 + /* now, order all un-ordered non-principal columns along path */ 1.2803 + /* to this parent. collapse tree at the same time */ 1.2804 + c = i ; 1.2805 + /* get order of parent */ 1.2806 + order = Col [parent].shared2.order ; 1.2807 + 1.2808 + do 1.2809 + { 1.2810 + ASSERT (Col [c].shared2.order == EMPTY) ; 1.2811 + 1.2812 + /* order this column */ 1.2813 + Col [c].shared2.order = order++ ; 1.2814 + /* collaps tree */ 1.2815 + Col [c].shared1.parent = parent ; 1.2816 + 1.2817 + /* get immediate parent of this column */ 1.2818 + c = Col [c].shared1.parent ; 1.2819 + 1.2820 + /* continue until we hit an ordered column. There are */ 1.2821 + /* guarranteed not to be anymore unordered columns */ 1.2822 + /* above an ordered column */ 1.2823 + } while (Col [c].shared2.order == EMPTY) ; 1.2824 + 1.2825 + /* re-order the super_col parent to largest order for this group */ 1.2826 + Col [parent].shared2.order = order ; 1.2827 + } 1.2828 + } 1.2829 + 1.2830 + /* === Generate the permutation ========================================= */ 1.2831 + 1.2832 + for (c = 0 ; c < n_col ; c++) 1.2833 + { 1.2834 + p [Col [c].shared2.order] = c ; 1.2835 + } 1.2836 +} 1.2837 + 1.2838 + 1.2839 +/* ========================================================================== */ 1.2840 +/* === detect_super_cols ==================================================== */ 1.2841 +/* ========================================================================== */ 1.2842 + 1.2843 +/* 1.2844 + Detects supercolumns by finding matches between columns in the hash buckets. 1.2845 + Check amongst columns in the set A [row_start ... row_start + row_length-1]. 1.2846 + The columns under consideration are currently *not* in the degree lists, 1.2847 + and have already been placed in the hash buckets. 1.2848 + 1.2849 + The hash bucket for columns whose hash function is equal to h is stored 1.2850 + as follows: 1.2851 + 1.2852 + if head [h] is >= 0, then head [h] contains a degree list, so: 1.2853 + 1.2854 + head [h] is the first column in degree bucket h. 1.2855 + Col [head [h]].headhash gives the first column in hash bucket h. 1.2856 + 1.2857 + otherwise, the degree list is empty, and: 1.2858 + 1.2859 + -(head [h] + 2) is the first column in hash bucket h. 1.2860 + 1.2861 + For a column c in a hash bucket, Col [c].shared3.prev is NOT a "previous 1.2862 + column" pointer. Col [c].shared3.hash is used instead as the hash number 1.2863 + for that column. The value of Col [c].shared4.hash_next is the next column 1.2864 + in the same hash bucket. 1.2865 + 1.2866 + Assuming no, or "few" hash collisions, the time taken by this routine is 1.2867 + linear in the sum of the sizes (lengths) of each column whose score has 1.2868 + just been computed in the approximate degree computation. 1.2869 + Not user-callable. 1.2870 +*/ 1.2871 + 1.2872 +PRIVATE void detect_super_cols 1.2873 +( 1.2874 + /* === Parameters ======================================================= */ 1.2875 + 1.2876 +#ifndef NDEBUG 1.2877 + /* these two parameters are only needed when debugging is enabled: */ 1.2878 + Int n_col, /* number of columns of A */ 1.2879 + Colamd_Row Row [], /* of size n_row+1 */ 1.2880 +#endif /* NDEBUG */ 1.2881 + 1.2882 + Colamd_Col Col [], /* of size n_col+1 */ 1.2883 + Int A [], /* row indices of A */ 1.2884 + Int head [], /* head of degree lists and hash buckets */ 1.2885 + Int row_start, /* pointer to set of columns to check */ 1.2886 + Int row_length /* number of columns to check */ 1.2887 +) 1.2888 +{ 1.2889 + /* === Local variables ================================================== */ 1.2890 + 1.2891 + Int hash ; /* hash value for a column */ 1.2892 + Int *rp ; /* pointer to a row */ 1.2893 + Int c ; /* a column index */ 1.2894 + Int super_c ; /* column index of the column to absorb into */ 1.2895 + Int *cp1 ; /* column pointer for column super_c */ 1.2896 + Int *cp2 ; /* column pointer for column c */ 1.2897 + Int length ; /* length of column super_c */ 1.2898 + Int prev_c ; /* column preceding c in hash bucket */ 1.2899 + Int i ; /* loop counter */ 1.2900 + Int *rp_end ; /* pointer to the end of the row */ 1.2901 + Int col ; /* a column index in the row to check */ 1.2902 + Int head_column ; /* first column in hash bucket or degree list */ 1.2903 + Int first_col ; /* first column in hash bucket */ 1.2904 + 1.2905 + /* === Consider each column in the row ================================== */ 1.2906 + 1.2907 + rp = &A [row_start] ; 1.2908 + rp_end = rp + row_length ; 1.2909 + while (rp < rp_end) 1.2910 + { 1.2911 + col = *rp++ ; 1.2912 + if (COL_IS_DEAD (col)) 1.2913 + { 1.2914 + continue ; 1.2915 + } 1.2916 + 1.2917 + /* get hash number for this column */ 1.2918 + hash = Col [col].shared3.hash ; 1.2919 + ASSERT (hash <= n_col) ; 1.2920 + 1.2921 + /* === Get the first column in this hash bucket ===================== */ 1.2922 + 1.2923 + head_column = head [hash] ; 1.2924 + if (head_column > EMPTY) 1.2925 + { 1.2926 + first_col = Col [head_column].shared3.headhash ; 1.2927 + } 1.2928 + else 1.2929 + { 1.2930 + first_col = - (head_column + 2) ; 1.2931 + } 1.2932 + 1.2933 + /* === Consider each column in the hash bucket ====================== */ 1.2934 + 1.2935 + for (super_c = first_col ; super_c != EMPTY ; 1.2936 + super_c = Col [super_c].shared4.hash_next) 1.2937 + { 1.2938 + ASSERT (COL_IS_ALIVE (super_c)) ; 1.2939 + ASSERT (Col [super_c].shared3.hash == hash) ; 1.2940 + length = Col [super_c].length ; 1.2941 + 1.2942 + /* prev_c is the column preceding column c in the hash bucket */ 1.2943 + prev_c = super_c ; 1.2944 + 1.2945 + /* === Compare super_c with all columns after it ================ */ 1.2946 + 1.2947 + for (c = Col [super_c].shared4.hash_next ; 1.2948 + c != EMPTY ; c = Col [c].shared4.hash_next) 1.2949 + { 1.2950 + ASSERT (c != super_c) ; 1.2951 + ASSERT (COL_IS_ALIVE (c)) ; 1.2952 + ASSERT (Col [c].shared3.hash == hash) ; 1.2953 + 1.2954 + /* not identical if lengths or scores are different */ 1.2955 + if (Col [c].length != length || 1.2956 + Col [c].shared2.score != Col [super_c].shared2.score) 1.2957 + { 1.2958 + prev_c = c ; 1.2959 + continue ; 1.2960 + } 1.2961 + 1.2962 + /* compare the two columns */ 1.2963 + cp1 = &A [Col [super_c].start] ; 1.2964 + cp2 = &A [Col [c].start] ; 1.2965 + 1.2966 + for (i = 0 ; i < length ; i++) 1.2967 + { 1.2968 + /* the columns are "clean" (no dead rows) */ 1.2969 + ASSERT (ROW_IS_ALIVE (*cp1)) ; 1.2970 + ASSERT (ROW_IS_ALIVE (*cp2)) ; 1.2971 + /* row indices will same order for both supercols, */ 1.2972 + /* no gather scatter nessasary */ 1.2973 + if (*cp1++ != *cp2++) 1.2974 + { 1.2975 + break ; 1.2976 + } 1.2977 + } 1.2978 + 1.2979 + /* the two columns are different if the for-loop "broke" */ 1.2980 + if (i != length) 1.2981 + { 1.2982 + prev_c = c ; 1.2983 + continue ; 1.2984 + } 1.2985 + 1.2986 + /* === Got it! two columns are identical =================== */ 1.2987 + 1.2988 + ASSERT (Col [c].shared2.score == Col [super_c].shared2.score) ; 1.2989 + 1.2990 + Col [super_c].shared1.thickness += Col [c].shared1.thickness ; 1.2991 + Col [c].shared1.parent = super_c ; 1.2992 + KILL_NON_PRINCIPAL_COL (c) ; 1.2993 + /* order c later, in order_children() */ 1.2994 + Col [c].shared2.order = EMPTY ; 1.2995 + /* remove c from hash bucket */ 1.2996 + Col [prev_c].shared4.hash_next = Col [c].shared4.hash_next ; 1.2997 + } 1.2998 + } 1.2999 + 1.3000 + /* === Empty this hash bucket ======================================= */ 1.3001 + 1.3002 + if (head_column > EMPTY) 1.3003 + { 1.3004 + /* corresponding degree list "hash" is not empty */ 1.3005 + Col [head_column].shared3.headhash = EMPTY ; 1.3006 + } 1.3007 + else 1.3008 + { 1.3009 + /* corresponding degree list "hash" is empty */ 1.3010 + head [hash] = EMPTY ; 1.3011 + } 1.3012 + } 1.3013 +} 1.3014 + 1.3015 + 1.3016 +/* ========================================================================== */ 1.3017 +/* === garbage_collection =================================================== */ 1.3018 +/* ========================================================================== */ 1.3019 + 1.3020 +/* 1.3021 + Defragments and compacts columns and rows in the workspace A. Used when 1.3022 + all avaliable memory has been used while performing row merging. Returns 1.3023 + the index of the first free position in A, after garbage collection. The 1.3024 + time taken by this routine is linear is the size of the array A, which is 1.3025 + itself linear in the number of nonzeros in the input matrix. 1.3026 + Not user-callable. 1.3027 +*/ 1.3028 + 1.3029 +PRIVATE Int garbage_collection /* returns the new value of pfree */ 1.3030 +( 1.3031 + /* === Parameters ======================================================= */ 1.3032 + 1.3033 + Int n_row, /* number of rows */ 1.3034 + Int n_col, /* number of columns */ 1.3035 + Colamd_Row Row [], /* row info */ 1.3036 + Colamd_Col Col [], /* column info */ 1.3037 + Int A [], /* A [0 ... Alen-1] holds the matrix */ 1.3038 + Int *pfree /* &A [0] ... pfree is in use */ 1.3039 +) 1.3040 +{ 1.3041 + /* === Local variables ================================================== */ 1.3042 + 1.3043 + Int *psrc ; /* source pointer */ 1.3044 + Int *pdest ; /* destination pointer */ 1.3045 + Int j ; /* counter */ 1.3046 + Int r ; /* a row index */ 1.3047 + Int c ; /* a column index */ 1.3048 + Int length ; /* length of a row or column */ 1.3049 + 1.3050 +#ifndef NDEBUG 1.3051 + Int debug_rows ; 1.3052 + DEBUG2 (("Defrag..\n")) ; 1.3053 + for (psrc = &A[0] ; psrc < pfree ; psrc++) ASSERT (*psrc >= 0) ; 1.3054 + debug_rows = 0 ; 1.3055 +#endif /* NDEBUG */ 1.3056 + 1.3057 + /* === Defragment the columns =========================================== */ 1.3058 + 1.3059 + pdest = &A[0] ; 1.3060 + for (c = 0 ; c < n_col ; c++) 1.3061 + { 1.3062 + if (COL_IS_ALIVE (c)) 1.3063 + { 1.3064 + psrc = &A [Col [c].start] ; 1.3065 + 1.3066 + /* move and compact the column */ 1.3067 + ASSERT (pdest <= psrc) ; 1.3068 + Col [c].start = (Int) (pdest - &A [0]) ; 1.3069 + length = Col [c].length ; 1.3070 + for (j = 0 ; j < length ; j++) 1.3071 + { 1.3072 + r = *psrc++ ; 1.3073 + if (ROW_IS_ALIVE (r)) 1.3074 + { 1.3075 + *pdest++ = r ; 1.3076 + } 1.3077 + } 1.3078 + Col [c].length = (Int) (pdest - &A [Col [c].start]) ; 1.3079 + } 1.3080 + } 1.3081 + 1.3082 + /* === Prepare to defragment the rows =================================== */ 1.3083 + 1.3084 + for (r = 0 ; r < n_row ; r++) 1.3085 + { 1.3086 + if (ROW_IS_DEAD (r) || (Row [r].length == 0)) 1.3087 + { 1.3088 + /* This row is already dead, or is of zero length. Cannot compact 1.3089 + * a row of zero length, so kill it. NOTE: in the current version, 1.3090 + * there are no zero-length live rows. Kill the row (for the first 1.3091 + * time, or again) just to be safe. */ 1.3092 + KILL_ROW (r) ; 1.3093 + } 1.3094 + else 1.3095 + { 1.3096 + /* save first column index in Row [r].shared2.first_column */ 1.3097 + psrc = &A [Row [r].start] ; 1.3098 + Row [r].shared2.first_column = *psrc ; 1.3099 + ASSERT (ROW_IS_ALIVE (r)) ; 1.3100 + /* flag the start of the row with the one's complement of row */ 1.3101 + *psrc = ONES_COMPLEMENT (r) ; 1.3102 +#ifndef NDEBUG 1.3103 + debug_rows++ ; 1.3104 +#endif /* NDEBUG */ 1.3105 + } 1.3106 + } 1.3107 + 1.3108 + /* === Defragment the rows ============================================== */ 1.3109 + 1.3110 + psrc = pdest ; 1.3111 + while (psrc < pfree) 1.3112 + { 1.3113 + /* find a negative number ... the start of a row */ 1.3114 + if (*psrc++ < 0) 1.3115 + { 1.3116 + psrc-- ; 1.3117 + /* get the row index */ 1.3118 + r = ONES_COMPLEMENT (*psrc) ; 1.3119 + ASSERT (r >= 0 && r < n_row) ; 1.3120 + /* restore first column index */ 1.3121 + *psrc = Row [r].shared2.first_column ; 1.3122 + ASSERT (ROW_IS_ALIVE (r)) ; 1.3123 + ASSERT (Row [r].length > 0) ; 1.3124 + /* move and compact the row */ 1.3125 + ASSERT (pdest <= psrc) ; 1.3126 + Row [r].start = (Int) (pdest - &A [0]) ; 1.3127 + length = Row [r].length ; 1.3128 + for (j = 0 ; j < length ; j++) 1.3129 + { 1.3130 + c = *psrc++ ; 1.3131 + if (COL_IS_ALIVE (c)) 1.3132 + { 1.3133 + *pdest++ = c ; 1.3134 + } 1.3135 + } 1.3136 + Row [r].length = (Int) (pdest - &A [Row [r].start]) ; 1.3137 + ASSERT (Row [r].length > 0) ; 1.3138 +#ifndef NDEBUG 1.3139 + debug_rows-- ; 1.3140 +#endif /* NDEBUG */ 1.3141 + } 1.3142 + } 1.3143 + /* ensure we found all the rows */ 1.3144 + ASSERT (debug_rows == 0) ; 1.3145 + 1.3146 + /* === Return the new value of pfree ==================================== */ 1.3147 + 1.3148 + return ((Int) (pdest - &A [0])) ; 1.3149 +} 1.3150 + 1.3151 + 1.3152 +/* ========================================================================== */ 1.3153 +/* === clear_mark =========================================================== */ 1.3154 +/* ========================================================================== */ 1.3155 + 1.3156 +/* 1.3157 + Clears the Row [].shared2.mark array, and returns the new tag_mark. 1.3158 + Return value is the new tag_mark. Not user-callable. 1.3159 +*/ 1.3160 + 1.3161 +PRIVATE Int clear_mark /* return the new value for tag_mark */ 1.3162 +( 1.3163 + /* === Parameters ======================================================= */ 1.3164 + 1.3165 + Int tag_mark, /* new value of tag_mark */ 1.3166 + Int max_mark, /* max allowed value of tag_mark */ 1.3167 + 1.3168 + Int n_row, /* number of rows in A */ 1.3169 + Colamd_Row Row [] /* Row [0 ... n_row-1].shared2.mark is set to zero */ 1.3170 +) 1.3171 +{ 1.3172 + /* === Local variables ================================================== */ 1.3173 + 1.3174 + Int r ; 1.3175 + 1.3176 + if (tag_mark <= 0 || tag_mark >= max_mark) 1.3177 + { 1.3178 + for (r = 0 ; r < n_row ; r++) 1.3179 + { 1.3180 + if (ROW_IS_ALIVE (r)) 1.3181 + { 1.3182 + Row [r].shared2.mark = 0 ; 1.3183 + } 1.3184 + } 1.3185 + tag_mark = 1 ; 1.3186 + } 1.3187 + 1.3188 + return (tag_mark) ; 1.3189 +} 1.3190 + 1.3191 + 1.3192 +/* ========================================================================== */ 1.3193 +/* === print_report ========================================================= */ 1.3194 +/* ========================================================================== */ 1.3195 + 1.3196 +PRIVATE void print_report 1.3197 +( 1.3198 + char *method, 1.3199 + Int stats [COLAMD_STATS] 1.3200 +) 1.3201 +{ 1.3202 + 1.3203 + Int i1, i2, i3 ; 1.3204 + 1.3205 + PRINTF (("\n%s version %d.%d, %s: ", method, 1.3206 + COLAMD_MAIN_VERSION, COLAMD_SUB_VERSION, COLAMD_DATE)) ; 1.3207 + 1.3208 + if (!stats) 1.3209 + { 1.3210 + PRINTF (("No statistics available.\n")) ; 1.3211 + return ; 1.3212 + } 1.3213 + 1.3214 + i1 = stats [COLAMD_INFO1] ; 1.3215 + i2 = stats [COLAMD_INFO2] ; 1.3216 + i3 = stats [COLAMD_INFO3] ; 1.3217 + 1.3218 + if (stats [COLAMD_STATUS] >= 0) 1.3219 + { 1.3220 + PRINTF (("OK. ")) ; 1.3221 + } 1.3222 + else 1.3223 + { 1.3224 + PRINTF (("ERROR. ")) ; 1.3225 + } 1.3226 + 1.3227 + switch (stats [COLAMD_STATUS]) 1.3228 + { 1.3229 + 1.3230 + case COLAMD_OK_BUT_JUMBLED: 1.3231 + 1.3232 + PRINTF(("Matrix has unsorted or duplicate row indices.\n")) ; 1.3233 + 1.3234 + PRINTF(("%s: number of duplicate or out-of-order row indices: %d\n", 1.3235 + method, i3)) ; 1.3236 + 1.3237 + PRINTF(("%s: last seen duplicate or out-of-order row index: %d\n", 1.3238 + method, INDEX (i2))) ; 1.3239 + 1.3240 + PRINTF(("%s: last seen in column: %d", 1.3241 + method, INDEX (i1))) ; 1.3242 + 1.3243 + /* no break - fall through to next case instead */ 1.3244 + 1.3245 + case COLAMD_OK: 1.3246 + 1.3247 + PRINTF(("\n")) ; 1.3248 + 1.3249 + PRINTF(("%s: number of dense or empty rows ignored: %d\n", 1.3250 + method, stats [COLAMD_DENSE_ROW])) ; 1.3251 + 1.3252 + PRINTF(("%s: number of dense or empty columns ignored: %d\n", 1.3253 + method, stats [COLAMD_DENSE_COL])) ; 1.3254 + 1.3255 + PRINTF(("%s: number of garbage collections performed: %d\n", 1.3256 + method, stats [COLAMD_DEFRAG_COUNT])) ; 1.3257 + break ; 1.3258 + 1.3259 + case COLAMD_ERROR_A_not_present: 1.3260 + 1.3261 + PRINTF(("Array A (row indices of matrix) not present.\n")) ; 1.3262 + break ; 1.3263 + 1.3264 + case COLAMD_ERROR_p_not_present: 1.3265 + 1.3266 + PRINTF(("Array p (column pointers for matrix) not present.\n")) ; 1.3267 + break ; 1.3268 + 1.3269 + case COLAMD_ERROR_nrow_negative: 1.3270 + 1.3271 + PRINTF(("Invalid number of rows (%d).\n", i1)) ; 1.3272 + break ; 1.3273 + 1.3274 + case COLAMD_ERROR_ncol_negative: 1.3275 + 1.3276 + PRINTF(("Invalid number of columns (%d).\n", i1)) ; 1.3277 + break ; 1.3278 + 1.3279 + case COLAMD_ERROR_nnz_negative: 1.3280 + 1.3281 + PRINTF(("Invalid number of nonzero entries (%d).\n", i1)) ; 1.3282 + break ; 1.3283 + 1.3284 + case COLAMD_ERROR_p0_nonzero: 1.3285 + 1.3286 + PRINTF(("Invalid column pointer, p [0] = %d, must be zero.\n", i1)); 1.3287 + break ; 1.3288 + 1.3289 + case COLAMD_ERROR_A_too_small: 1.3290 + 1.3291 + PRINTF(("Array A too small.\n")) ; 1.3292 + PRINTF((" Need Alen >= %d, but given only Alen = %d.\n", 1.3293 + i1, i2)) ; 1.3294 + break ; 1.3295 + 1.3296 + case COLAMD_ERROR_col_length_negative: 1.3297 + 1.3298 + PRINTF 1.3299 + (("Column %d has a negative number of nonzero entries (%d).\n", 1.3300 + INDEX (i1), i2)) ; 1.3301 + break ; 1.3302 + 1.3303 + case COLAMD_ERROR_row_index_out_of_bounds: 1.3304 + 1.3305 + PRINTF 1.3306 + (("Row index (row %d) out of bounds (%d to %d) in column %d.\n", 1.3307 + INDEX (i2), INDEX (0), INDEX (i3-1), INDEX (i1))) ; 1.3308 + break ; 1.3309 + 1.3310 + case COLAMD_ERROR_out_of_memory: 1.3311 + 1.3312 + PRINTF(("Out of memory.\n")) ; 1.3313 + break ; 1.3314 + 1.3315 + /* v2.4: internal-error case deleted */ 1.3316 + } 1.3317 +} 1.3318 + 1.3319 + 1.3320 + 1.3321 + 1.3322 +/* ========================================================================== */ 1.3323 +/* === colamd debugging routines ============================================ */ 1.3324 +/* ========================================================================== */ 1.3325 + 1.3326 +/* When debugging is disabled, the remainder of this file is ignored. */ 1.3327 + 1.3328 +#ifndef NDEBUG 1.3329 + 1.3330 + 1.3331 +/* ========================================================================== */ 1.3332 +/* === debug_structures ===================================================== */ 1.3333 +/* ========================================================================== */ 1.3334 + 1.3335 +/* 1.3336 + At this point, all empty rows and columns are dead. All live columns 1.3337 + are "clean" (containing no dead rows) and simplicial (no supercolumns 1.3338 + yet). Rows may contain dead columns, but all live rows contain at 1.3339 + least one live column. 1.3340 +*/ 1.3341 + 1.3342 +PRIVATE void debug_structures 1.3343 +( 1.3344 + /* === Parameters ======================================================= */ 1.3345 + 1.3346 + Int n_row, 1.3347 + Int n_col, 1.3348 + Colamd_Row Row [], 1.3349 + Colamd_Col Col [], 1.3350 + Int A [], 1.3351 + Int n_col2 1.3352 +) 1.3353 +{ 1.3354 + /* === Local variables ================================================== */ 1.3355 + 1.3356 + Int i ; 1.3357 + Int c ; 1.3358 + Int *cp ; 1.3359 + Int *cp_end ; 1.3360 + Int len ; 1.3361 + Int score ; 1.3362 + Int r ; 1.3363 + Int *rp ; 1.3364 + Int *rp_end ; 1.3365 + Int deg ; 1.3366 + 1.3367 + /* === Check A, Row, and Col ============================================ */ 1.3368 + 1.3369 + for (c = 0 ; c < n_col ; c++) 1.3370 + { 1.3371 + if (COL_IS_ALIVE (c)) 1.3372 + { 1.3373 + len = Col [c].length ; 1.3374 + score = Col [c].shared2.score ; 1.3375 + DEBUG4 (("initial live col %5d %5d %5d\n", c, len, score)) ; 1.3376 + ASSERT (len > 0) ; 1.3377 + ASSERT (score >= 0) ; 1.3378 + ASSERT (Col [c].shared1.thickness == 1) ; 1.3379 + cp = &A [Col [c].start] ; 1.3380 + cp_end = cp + len ; 1.3381 + while (cp < cp_end) 1.3382 + { 1.3383 + r = *cp++ ; 1.3384 + ASSERT (ROW_IS_ALIVE (r)) ; 1.3385 + } 1.3386 + } 1.3387 + else 1.3388 + { 1.3389 + i = Col [c].shared2.order ; 1.3390 + ASSERT (i >= n_col2 && i < n_col) ; 1.3391 + } 1.3392 + } 1.3393 + 1.3394 + for (r = 0 ; r < n_row ; r++) 1.3395 + { 1.3396 + if (ROW_IS_ALIVE (r)) 1.3397 + { 1.3398 + i = 0 ; 1.3399 + len = Row [r].length ; 1.3400 + deg = Row [r].shared1.degree ; 1.3401 + ASSERT (len > 0) ; 1.3402 + ASSERT (deg > 0) ; 1.3403 + rp = &A [Row [r].start] ; 1.3404 + rp_end = rp + len ; 1.3405 + while (rp < rp_end) 1.3406 + { 1.3407 + c = *rp++ ; 1.3408 + if (COL_IS_ALIVE (c)) 1.3409 + { 1.3410 + i++ ; 1.3411 + } 1.3412 + } 1.3413 + ASSERT (i > 0) ; 1.3414 + } 1.3415 + } 1.3416 +} 1.3417 + 1.3418 + 1.3419 +/* ========================================================================== */ 1.3420 +/* === debug_deg_lists ====================================================== */ 1.3421 +/* ========================================================================== */ 1.3422 + 1.3423 +/* 1.3424 + Prints the contents of the degree lists. Counts the number of columns 1.3425 + in the degree list and compares it to the total it should have. Also 1.3426 + checks the row degrees. 1.3427 +*/ 1.3428 + 1.3429 +PRIVATE void debug_deg_lists 1.3430 +( 1.3431 + /* === Parameters ======================================================= */ 1.3432 + 1.3433 + Int n_row, 1.3434 + Int n_col, 1.3435 + Colamd_Row Row [], 1.3436 + Colamd_Col Col [], 1.3437 + Int head [], 1.3438 + Int min_score, 1.3439 + Int should, 1.3440 + Int max_deg 1.3441 +) 1.3442 +{ 1.3443 + /* === Local variables ================================================== */ 1.3444 + 1.3445 + Int deg ; 1.3446 + Int col ; 1.3447 + Int have ; 1.3448 + Int row ; 1.3449 + 1.3450 + /* === Check the degree lists =========================================== */ 1.3451 + 1.3452 + if (n_col > 10000 && colamd_debug <= 0) 1.3453 + { 1.3454 + return ; 1.3455 + } 1.3456 + have = 0 ; 1.3457 + DEBUG4 (("Degree lists: %d\n", min_score)) ; 1.3458 + for (deg = 0 ; deg <= n_col ; deg++) 1.3459 + { 1.3460 + col = head [deg] ; 1.3461 + if (col == EMPTY) 1.3462 + { 1.3463 + continue ; 1.3464 + } 1.3465 + DEBUG4 (("%d:", deg)) ; 1.3466 + while (col != EMPTY) 1.3467 + { 1.3468 + DEBUG4 ((" %d", col)) ; 1.3469 + have += Col [col].shared1.thickness ; 1.3470 + ASSERT (COL_IS_ALIVE (col)) ; 1.3471 + col = Col [col].shared4.degree_next ; 1.3472 + } 1.3473 + DEBUG4 (("\n")) ; 1.3474 + } 1.3475 + DEBUG4 (("should %d have %d\n", should, have)) ; 1.3476 + ASSERT (should == have) ; 1.3477 + 1.3478 + /* === Check the row degrees ============================================ */ 1.3479 + 1.3480 + if (n_row > 10000 && colamd_debug <= 0) 1.3481 + { 1.3482 + return ; 1.3483 + } 1.3484 + for (row = 0 ; row < n_row ; row++) 1.3485 + { 1.3486 + if (ROW_IS_ALIVE (row)) 1.3487 + { 1.3488 + ASSERT (Row [row].shared1.degree <= max_deg) ; 1.3489 + } 1.3490 + } 1.3491 +} 1.3492 + 1.3493 + 1.3494 +/* ========================================================================== */ 1.3495 +/* === debug_mark =========================================================== */ 1.3496 +/* ========================================================================== */ 1.3497 + 1.3498 +/* 1.3499 + Ensures that the tag_mark is less that the maximum and also ensures that 1.3500 + each entry in the mark array is less than the tag mark. 1.3501 +*/ 1.3502 + 1.3503 +PRIVATE void debug_mark 1.3504 +( 1.3505 + /* === Parameters ======================================================= */ 1.3506 + 1.3507 + Int n_row, 1.3508 + Colamd_Row Row [], 1.3509 + Int tag_mark, 1.3510 + Int max_mark 1.3511 +) 1.3512 +{ 1.3513 + /* === Local variables ================================================== */ 1.3514 + 1.3515 + Int r ; 1.3516 + 1.3517 + /* === Check the Row marks ============================================== */ 1.3518 + 1.3519 + ASSERT (tag_mark > 0 && tag_mark <= max_mark) ; 1.3520 + if (n_row > 10000 && colamd_debug <= 0) 1.3521 + { 1.3522 + return ; 1.3523 + } 1.3524 + for (r = 0 ; r < n_row ; r++) 1.3525 + { 1.3526 + ASSERT (Row [r].shared2.mark < tag_mark) ; 1.3527 + } 1.3528 +} 1.3529 + 1.3530 + 1.3531 +/* ========================================================================== */ 1.3532 +/* === debug_matrix ========================================================= */ 1.3533 +/* ========================================================================== */ 1.3534 + 1.3535 +/* 1.3536 + Prints out the contents of the columns and the rows. 1.3537 +*/ 1.3538 + 1.3539 +PRIVATE void debug_matrix 1.3540 +( 1.3541 + /* === Parameters ======================================================= */ 1.3542 + 1.3543 + Int n_row, 1.3544 + Int n_col, 1.3545 + Colamd_Row Row [], 1.3546 + Colamd_Col Col [], 1.3547 + Int A [] 1.3548 +) 1.3549 +{ 1.3550 + /* === Local variables ================================================== */ 1.3551 + 1.3552 + Int r ; 1.3553 + Int c ; 1.3554 + Int *rp ; 1.3555 + Int *rp_end ; 1.3556 + Int *cp ; 1.3557 + Int *cp_end ; 1.3558 + 1.3559 + /* === Dump the rows and columns of the matrix ========================== */ 1.3560 + 1.3561 + if (colamd_debug < 3) 1.3562 + { 1.3563 + return ; 1.3564 + } 1.3565 + DEBUG3 (("DUMP MATRIX:\n")) ; 1.3566 + for (r = 0 ; r < n_row ; r++) 1.3567 + { 1.3568 + DEBUG3 (("Row %d alive? %d\n", r, ROW_IS_ALIVE (r))) ; 1.3569 + if (ROW_IS_DEAD (r)) 1.3570 + { 1.3571 + continue ; 1.3572 + } 1.3573 + DEBUG3 (("start %d length %d degree %d\n", 1.3574 + Row [r].start, Row [r].length, Row [r].shared1.degree)) ; 1.3575 + rp = &A [Row [r].start] ; 1.3576 + rp_end = rp + Row [r].length ; 1.3577 + while (rp < rp_end) 1.3578 + { 1.3579 + c = *rp++ ; 1.3580 + DEBUG4 ((" %d col %d\n", COL_IS_ALIVE (c), c)) ; 1.3581 + } 1.3582 + } 1.3583 + 1.3584 + for (c = 0 ; c < n_col ; c++) 1.3585 + { 1.3586 + DEBUG3 (("Col %d alive? %d\n", c, COL_IS_ALIVE (c))) ; 1.3587 + if (COL_IS_DEAD (c)) 1.3588 + { 1.3589 + continue ; 1.3590 + } 1.3591 + DEBUG3 (("start %d length %d shared1 %d shared2 %d\n", 1.3592 + Col [c].start, Col [c].length, 1.3593 + Col [c].shared1.thickness, Col [c].shared2.score)) ; 1.3594 + cp = &A [Col [c].start] ; 1.3595 + cp_end = cp + Col [c].length ; 1.3596 + while (cp < cp_end) 1.3597 + { 1.3598 + r = *cp++ ; 1.3599 + DEBUG4 ((" %d row %d\n", ROW_IS_ALIVE (r), r)) ; 1.3600 + } 1.3601 + } 1.3602 +} 1.3603 + 1.3604 +PRIVATE void colamd_get_debug 1.3605 +( 1.3606 + char *method 1.3607 +) 1.3608 +{ 1.3609 + FILE *f ; 1.3610 + colamd_debug = 0 ; /* no debug printing */ 1.3611 + f = fopen ("debug", "r") ; 1.3612 + if (f == (FILE *) NULL) 1.3613 + { 1.3614 + colamd_debug = 0 ; 1.3615 + } 1.3616 + else 1.3617 + { 1.3618 + fscanf (f, "%d", &colamd_debug) ; 1.3619 + fclose (f) ; 1.3620 + } 1.3621 + DEBUG0 (("%s: debug version, D = %d (THIS WILL BE SLOW!)\n", 1.3622 + method, colamd_debug)) ; 1.3623 +} 1.3624 + 1.3625 +#endif /* NDEBUG */