/* ========================================================================= */ /* === AMD: approximate minimum degree ordering =========================== */ /* ========================================================================= */ /* ------------------------------------------------------------------------- */ /* AMD Version 2.4, Copyright (c) 1996-2013 by Timothy A. Davis, */ /* Patrick R. Amestoy, and Iain S. Duff. See ../README.txt for License. */ /* email: DrTimothyAldenDavis@gmail.com */ /* ------------------------------------------------------------------------- */ /* AMD finds a symmetric ordering P of a matrix A so that the Cholesky * factorization of P*A*P' has fewer nonzeros and takes less work than the * Cholesky factorization of A. If A is not symmetric, then it performs its * ordering on the matrix A+A'. Two sets of user-callable routines are * provided, one for scs_int integers and the other for SuiteSparse_long integers. * * The method is based on the approximate minimum degree algorithm, discussed * in Amestoy, Davis, and Duff, "An approximate degree ordering algorithm", * SIAM Journal of Matrix Analysis and Applications, vol. 17, no. 4, pp. * 886-905, 1996. This package can perform both the AMD ordering (with * aggressive absorption), and the AMDBAR ordering (without aggressive * absorption) discussed in the above paper. This package differs from the * Fortran codes discussed in the paper: * * (1) it can ignore "dense" rows and columns, leading to faster run times * (2) it computes the ordering of A+A' if A is not symmetric * (3) it is followed by a depth-first post-ordering of the assembly tree * (or supernodal elimination tree) * * For historical reasons, the Fortran versions, amd.f and amdbar.f, have * been left (nearly) unchanged. They compute the identical ordering as * described in the above paper. */ #ifndef AMD_H #define AMD_H /* make it easy for C++ programs to include AMD */ #ifdef __cplusplus extern "C" { #endif /* get the definition of size_t: */ #include #include "SuiteSparse_config.h" scs_int amd_order /* returns AMD_OK, AMD_OK_BUT_JUMBLED, * AMD_INVALID, or AMD_OUT_OF_MEMORY */ ( scs_int n, /* A is n-by-n. n must be >= 0. */ const scs_int Ap [ ], /* column pointers for A, of size n+1 */ const scs_int Ai [ ], /* row indices of A, of size nz = Ap [n] */ scs_int P [ ], /* output permutation, of size n */ scs_float Control [ ], /* input Control settings, of size AMD_CONTROL */ scs_float Info [ ] /* output Info statistics, of size AMD_INFO */ ) ; SuiteSparse_long amd_l_order /* see above for description of arguments */ ( SuiteSparse_long n, const SuiteSparse_long Ap [ ], const SuiteSparse_long Ai [ ], SuiteSparse_long P [ ], scs_float Control [ ], scs_float Info [ ] ) ; /* Input arguments (not modified): * * n: the matrix A is n-by-n. * Ap: an int/SuiteSparse_long array of size n+1, containing column * pointers of A. * Ai: an int/SuiteSparse_long array of size nz, containing the row * indices of A, where nz = Ap [n]. * Control: a scs_float array of size AMD_CONTROL, containing control * parameters. Defaults are used if Control is NULL. * * Output arguments (not defined on input): * * P: an int/SuiteSparse_long array of size n, containing the output * permutation. If row i is the kth pivot row, then P [k] = i. In * MATLAB notation, the reordered matrix is A (P,P). * Info: a scs_float array of size AMD_INFO, containing statistical * information. Ignored if Info is NULL. * * On input, the matrix A is stored in column-oriented form. The row indices * of nonzero entries in column j are stored in Ai [Ap [j] ... Ap [j+1]-1]. * * If the row indices appear in ascending order in each column, and there * are no duplicate entries, then amd_order is slightly more efficient in * terms of time and memory usage. If this condition does not hold, a copy * of the matrix is created (where these conditions do hold), and the copy is * ordered. This feature is new to v2.0 (v1.2 and earlier required this * condition to hold for the input matrix). * * Row indices must be in the range 0 to * n-1. Ap [0] must be zero, and thus nz = Ap [n] is the number of nonzeros * in A. The array Ap is of size n+1, and the array Ai is of size nz = Ap [n]. * The matrix does not need to be symmetric, and the diagonal does not need to * be present (if diagonal entries are present, they are ignored except for * the output statistic Info [AMD_NZDIAG]). The arrays Ai and Ap are not * modified. This form of the Ap and Ai arrays to represent the nonzero * pattern of the matrix A is the same as that used internally by MATLAB. * If you wish to use a more flexible input structure, please see the * umfpack_*_triplet_to_col routines in the UMFPACK package, at * http://www.suitesparse.com. * * Restrictions: n >= 0. Ap [0] = 0. Ap [j] <= Ap [j+1] for all j in the * range 0 to n-1. nz = Ap [n] >= 0. Ai [0..nz-1] must be in the range 0 * to n-1. Finally, Ai, Ap, and P must not be NULL. If any of these * restrictions are not met, AMD returns AMD_INVALID. * * AMD returns: * * AMD_OK if the matrix is valid and sufficient memory can be allocated to * perform the ordering. * * AMD_OUT_OF_MEMORY if not enough memory can be allocated. * * AMD_INVALID if the input arguments n, Ap, Ai are invalid, or if P is * NULL. * * AMD_OK_BUT_JUMBLED if the matrix had unsorted columns, and/or duplicate * entries, but was otherwise valid. * * The AMD routine first forms the pattern of the matrix A+A', and then * computes a fill-reducing ordering, P. If P [k] = i, then row/column i of * the original is the kth pivotal row. In MATLAB notation, the permuted * matrix is A (P,P), except that 0-based indexing is used instead of the * 1-based indexing in MATLAB. * * The Control array is used to set various parameters for AMD. If a NULL * pointer is passed, default values are used. The Control array is not * modified. * * Control [AMD_DENSE]: controls the threshold for "dense" rows/columns. * A dense row/column in A+A' can cause AMD to spend a lot of time in * ordering the matrix. If Control [AMD_DENSE] >= 0, rows/columns * with more than Control [AMD_DENSE] * sqrt (n) entries are ignored * during the ordering, and placed last in the output order. The * default value of Control [AMD_DENSE] is 10. If negative, no * rows/columns are treated as "dense". Rows/columns with 16 or * fewer off-diagonal entries are never considered "dense". * * Control [AMD_AGGRESSIVE]: controls whether or not to use aggressive * absorption, in which a prior element is absorbed into the current * element if is a subset of the current element, even if it is not * adjacent to the current pivot element (refer to Amestoy, Davis, * & Duff, 1996, for more details). The default value is nonzero, * which means to perform aggressive absorption. This nearly always * leads to a better ordering (because the approximate degrees are * more accurate) and a lower execution time. There are cases where * it can lead to a slightly worse ordering, however. To turn it off, * set Control [AMD_AGGRESSIVE] to 0. * * Control [2..4] are not used in the current version, but may be used in * future versions. * * The Info array provides statistics about the ordering on output. If it is * not present, the statistics are not returned. This is not an error * condition. * * Info [AMD_STATUS]: the return value of AMD, either AMD_OK, * AMD_OK_BUT_JUMBLED, AMD_OUT_OF_MEMORY, or AMD_INVALID. * * Info [AMD_N]: n, the size of the input matrix * * Info [AMD_NZ]: the number of nonzeros in A, nz = Ap [n] * * Info [AMD_SYMMETRY]: the symmetry of the matrix A. It is the number * of "matched" off-diagonal entries divided by the total number of * off-diagonal entries. An entry A(i,j) is matched if A(j,i) is also * an entry, for any pair (i,j) for which i != j. In MATLAB notation, * S = spones (A) ; * B = tril (S, -1) + triu (S, 1) ; * symmetry = nnz (B & B') / nnz (B) ; * * Info [AMD_NZDIAG]: the number of entries on the diagonal of A. * * Info [AMD_NZ_A_PLUS_AT]: the number of nonzeros in A+A', excluding the * diagonal. If A is perfectly symmetric (Info [AMD_SYMMETRY] = 1) * with a fully nonzero diagonal, then Info [AMD_NZ_A_PLUS_AT] = nz-n * (the smallest possible value). If A is perfectly unsymmetric * (Info [AMD_SYMMETRY] = 0, for an upper triangular matrix, for * example) with no diagonal, then Info [AMD_NZ_A_PLUS_AT] = 2*nz * (the largest possible value). * * Info [AMD_NDENSE]: the number of "dense" rows/columns of A+A' that were * removed from A prior to ordering. These are placed last in the * output order P. * * Info [AMD_MEMORY]: the amount of memory used by AMD, in bytes. In the * current version, this is 1.2 * Info [AMD_NZ_A_PLUS_AT] + 9*n * times the size of an integer. This is at most 2.4nz + 9n. This * excludes the size of the input arguments Ai, Ap, and P, which have * a total size of nz + 2*n + 1 integers. * * Info [AMD_NCMPA]: the number of garbage collections performed. * * Info [AMD_LNZ]: the number of nonzeros in L (excluding the diagonal). * This is a slight upper bound because mass elimination is combined * with the approximate degree update. It is a rough upper bound if * there are many "dense" rows/columns. The rest of the statistics, * below, are also slight or rough upper bounds, for the same reasons. * The post-ordering of the assembly tree might also not exactly * correspond to a true elimination tree postordering. * * Info [AMD_NDIV]: the number of divide operations for a subsequent LDL' * or LU factorization of the permuted matrix A (P,P). * * Info [AMD_NMULTSUBS_LDL]: the number of multiply-subtract pairs for a * subsequent LDL' factorization of A (P,P). * * Info [AMD_NMULTSUBS_LU]: the number of multiply-subtract pairs for a * subsequent LU factorization of A (P,P), assuming that no numerical * pivoting is required. * * Info [AMD_DMAX]: the maximum number of nonzeros in any column of L, * including the diagonal. * * Info [14..19] are not used in the current version, but may be used in * future versions. */ /* ------------------------------------------------------------------------- */ /* direct interface to AMD */ /* ------------------------------------------------------------------------- */ /* amd_2 is the primary AMD ordering routine. It is not meant to be * user-callable because of its restrictive inputs and because it destroys * the user's input matrix. It does not check its inputs for errors, either. * However, if you can work with these restrictions it can be faster than * amd_order and use less memory (assuming that you can create your own copy * of the matrix for AMD to destroy). Refer to AMD/Source/amd_2.c for a * description of each parameter. */ void amd_2 ( scs_int n, scs_int Pe [ ], scs_int Iw [ ], scs_int Len [ ], scs_int iwlen, scs_int pfree, scs_int Nv [ ], scs_int Next [ ], scs_int Last [ ], scs_int Head [ ], scs_int Elen [ ], scs_int Degree [ ], scs_int W [ ], scs_float Control [ ], scs_float Info [ ] ) ; void amd_l2 ( SuiteSparse_long n, SuiteSparse_long Pe [ ], SuiteSparse_long Iw [ ], SuiteSparse_long Len [ ], SuiteSparse_long iwlen, SuiteSparse_long pfree, SuiteSparse_long Nv [ ], SuiteSparse_long Next [ ], SuiteSparse_long Last [ ], SuiteSparse_long Head [ ], SuiteSparse_long Elen [ ], SuiteSparse_long Degree [ ], SuiteSparse_long W [ ], scs_float Control [ ], scs_float Info [ ] ) ; /* ------------------------------------------------------------------------- */ /* amd_valid */ /* ------------------------------------------------------------------------- */ /* Returns AMD_OK or AMD_OK_BUT_JUMBLED if the matrix is valid as input to * amd_order; the latter is returned if the matrix has unsorted and/or * duplicate row indices in one or more columns. Returns AMD_INVALID if the * matrix cannot be passed to amd_order. For amd_order, the matrix must also * be square. The first two arguments are the number of rows and the number * of columns of the matrix. For its use in AMD, these must both equal n. * * NOTE: this routine returned TRUE/FALSE in v1.2 and earlier. */ scs_int amd_valid ( scs_int n_row, /* # of rows */ scs_int n_col, /* # of columns */ const scs_int Ap [ ], /* column pointers, of size n_col+1 */ const scs_int Ai [ ] /* row indices, of size Ap [n_col] */ ) ; SuiteSparse_long amd_l_valid ( SuiteSparse_long n_row, SuiteSparse_long n_col, const SuiteSparse_long Ap [ ], const SuiteSparse_long Ai [ ] ) ; /* ------------------------------------------------------------------------- */ /* AMD memory manager and printf routines */ /* ------------------------------------------------------------------------- */ /* moved to SuiteSparse_config.c */ /* ------------------------------------------------------------------------- */ /* AMD Control and Info arrays */ /* ------------------------------------------------------------------------- */ /* amd_defaults: sets the default control settings */ void amd_defaults (scs_float Control [ ]) ; void amd_l_defaults (scs_float Control [ ]) ; /* amd_control: prints the control settings */ void amd_control (scs_float Control [ ]) ; void amd_l_control (scs_float Control [ ]) ; /* amd_info: prints the statistics */ void amd_info (scs_float Info [ ]) ; void amd_l_info (scs_float Info [ ]) ; #define AMD_CONTROL 5 /* size of Control array */ #define AMD_INFO 20 /* size of Info array */ /* contents of Control */ #define AMD_DENSE 0 /* "dense" if degree > Control [0] * sqrt (n) */ #define AMD_AGGRESSIVE 1 /* do aggressive absorption if Control [1] != 0 */ /* default Control settings */ #define AMD_DEFAULT_DENSE 10.0 /* default "dense" degree 10*sqrt(n) */ #define AMD_DEFAULT_AGGRESSIVE 1 /* do aggressive absorption by default */ /* contents of Info */ #define AMD_STATUS 0 /* return value of amd_order and amd_l_order */ #define AMD_N 1 /* A is n-by-n */ #define AMD_NZ 2 /* number of nonzeros in A */ #define AMD_SYMMETRY 3 /* symmetry of pattern (1 is sym., 0 is unsym.) */ #define AMD_NZDIAG 4 /* # of entries on diagonal */ #define AMD_NZ_A_PLUS_AT 5 /* nz in A+A' */ #define AMD_NDENSE 6 /* number of "dense" rows/columns in A */ #define AMD_MEMORY 7 /* amount of memory used by AMD */ #define AMD_NCMPA 8 /* number of garbage collections in AMD */ #define AMD_LNZ 9 /* approx. nz in L, excluding the diagonal */ #define AMD_NDIV 10 /* number of fl. point divides for LU and LDL' */ #define AMD_NMULTSUBS_LDL 11 /* number of fl. point (*,-) pairs for LDL' */ #define AMD_NMULTSUBS_LU 12 /* number of fl. point (*,-) pairs for LU */ #define AMD_DMAX 13 /* max nz. in any column of L, incl. diagonal */ /* ------------------------------------------------------------------------- */ /* return values of AMD */ /* ------------------------------------------------------------------------- */ #define AMD_OK 0 /* success */ #define AMD_OUT_OF_MEMORY -1 /* malloc failed, or problem too large */ #define AMD_INVALID -2 /* input arguments are not valid */ #define AMD_OK_BUT_JUMBLED 1 /* input matrix is OK for amd_order, but * columns were not sorted, and/or duplicate entries were present. AMD had * to do extra work before ordering the matrix. This is a warning, not an * error. */ /* ========================================================================== */ /* === AMD version ========================================================== */ /* ========================================================================== */ /* AMD Version 1.2 and later include the following definitions. * As an example, to test if the version you are using is 1.2 or later: * * #ifdef AMD_VERSION * if (AMD_VERSION >= AMD_VERSION_CODE (1,2)) ... * #endif * * This also works during compile-time: * * #if defined(AMD_VERSION) && (AMD_VERSION >= AMD_VERSION_CODE (1,2)) * printf ("This is version 1.2 or later\n") ; * #else * printf ("This is an early version\n") ; * #endif * * Versions 1.1 and earlier of AMD do not include a #define'd version number. */ #define AMD_DATE "May 4, 2016" #define AMD_VERSION_CODE(main,sub) ((main) * 1000 + (sub)) #define AMD_MAIN_VERSION 2 #define AMD_SUB_VERSION 4 #define AMD_SUBSUB_VERSION 6 #define AMD_VERSION AMD_VERSION_CODE(AMD_MAIN_VERSION,AMD_SUB_VERSION) #ifdef __cplusplus } #endif #endif