Blame view
fvn_sparse/UMFPACK/Include/umfpack_triplet_to_col.h
10.2 KB
422234dc3 git-svn-id: https... |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 |
/* ========================================================================== */ /* === umfpack_triplet_to_col =============================================== */ /* ========================================================================== */ /* -------------------------------------------------------------------------- */ /* UMFPACK Copyright (c) Timothy A. Davis, CISE, */ /* Univ. of Florida. All Rights Reserved. See ../Doc/License for License. */ /* web: http://www.cise.ufl.edu/research/sparse/umfpack */ /* -------------------------------------------------------------------------- */ int umfpack_di_triplet_to_col ( int n_row, int n_col, int nz, const int Ti [ ], const int Tj [ ], const double Tx [ ], int Ap [ ], int Ai [ ], double Ax [ ], int Map [ ] ) ; UF_long umfpack_dl_triplet_to_col ( UF_long n_row, UF_long n_col, UF_long nz, const UF_long Ti [ ], const UF_long Tj [ ], const double Tx [ ], UF_long Ap [ ], UF_long Ai [ ], double Ax [ ], UF_long Map [ ] ) ; int umfpack_zi_triplet_to_col ( int n_row, int n_col, int nz, const int Ti [ ], const int Tj [ ], const double Tx [ ], const double Tz [ ], int Ap [ ], int Ai [ ], double Ax [ ], double Az [ ], int Map [ ] ) ; UF_long umfpack_zl_triplet_to_col ( UF_long n_row, UF_long n_col, UF_long nz, const UF_long Ti [ ], const UF_long Tj [ ], const double Tx [ ], const double Tz [ ], UF_long Ap [ ], UF_long Ai [ ], double Ax [ ], double Az [ ], UF_long Map [ ] ) ; /* double int Syntax: #include "umfpack.h" int n_row, n_col, nz, *Ti, *Tj, *Ap, *Ai, status, *Map ; double *Tx, *Ax ; status = umfpack_di_triplet_to_col (n_row, n_col, nz, Ti, Tj, Tx, Ap, Ai, Ax, Map) ; double UF_long Syntax: #include "umfpack.h" UF_long n_row, n_col, nz, *Ti, *Tj, *Ap, *Ai, status, *Map ; double *Tx, *Ax ; status = umfpack_dl_triplet_to_col (n_row, n_col, nz, Ti, Tj, Tx, Ap, Ai, Ax, Map) ; complex int Syntax: #include "umfpack.h" int n_row, n_col, nz, *Ti, *Tj, *Ap, *Ai, status, *Map ; double *Tx, *Tz, *Ax, *Az ; status = umfpack_zi_triplet_to_col (n_row, n_col, nz, Ti, Tj, Tx, Tz, Ap, Ai, Ax, Az, Map) ; UF_long Syntax: #include "umfpack.h" UF_long n_row, n_col, nz, *Ti, *Tj, *Ap, *Ai, status, *Map ; double *Tx, *Tz, *Ax, *Az ; status = umfpack_zl_triplet_to_col (n_row, n_col, nz, Ti, Tj, Tx, Tz, Ap, Ai, Ax, Az, Map) ; packed complex Syntax: Same as above, except Tz and Az are NULL. Purpose: Converts a sparse matrix from "triplet" form to compressed-column form. Analogous to A = spconvert (Ti, Tj, Tx + Tz*1i) in MATLAB, except that zero entries present in the triplet form are present in A. The triplet form of a matrix is a very simple data structure for basic sparse matrix operations. For example, suppose you wish to factorize a matrix A coming from a finite element method, in which A is a sum of dense submatrices, A = E1 + E2 + E3 + ... . The entries in each element matrix Ei can be concatenated together in the three triplet arrays, and any overlap between the elements will be correctly summed by umfpack_*_triplet_to_col. Transposing a matrix in triplet form is simple; just interchange the use of Ti and Tj. You can construct the complex conjugate transpose by negating Tz, for the complex versions. Permuting a matrix in triplet form is also simple. If you want the matrix PAQ, or A (P,Q) in MATLAB notation, where P [k] = i means that row i of A is the kth row of PAQ and Q [k] = j means that column j of A is the kth column of PAQ, then do the following. First, create inverse permutations Pinv and Qinv such that Pinv [i] = k if P [k] = i and Qinv [j] = k if Q [k] = j. Next, for the mth triplet (Ti [m], Tj [m], Tx [m], Tz [m]), replace Ti [m] with Pinv [Ti [m]] and replace Tj [m] with Qinv [Tj [m]]. If you have a column-form matrix with duplicate entries or unsorted columns, you can sort it and sum up the duplicates by first converting it to triplet form with umfpack_*_col_to_triplet, and then converting it back with umfpack_*_triplet_to_col. Constructing a submatrix is also easy. Just scan the triplets and remove those entries outside the desired subset of 0...n_row-1 and 0...n_col-1, and renumber the indices according to their position in the subset. You can do all these operations on a column-form matrix by first converting it to triplet form with umfpack_*_col_to_triplet, doing the operation on the triplet form, and then converting it back with umfpack_*_triplet_to_col. The only operation not supported easily in the triplet form is the multiplication of two sparse matrices (UMFPACK does not provide this operation). You can print the input triplet form with umfpack_*_report_triplet, and the output matrix with umfpack_*_report_matrix. The matrix may be singular (nz can be zero, and empty rows and/or columns may exist). It may also be rectangular and/or complex. Returns: UMFPACK_OK if successful. UMFPACK_ERROR_argument_missing if Ap, Ai, Ti, and/or Tj are missing. UMFPACK_ERROR_n_nonpositive if n_row <= 0 or n_col <= 0. UMFPACK_ERROR_invalid_matrix if nz < 0, or if for any k, Ti [k] and/or Tj [k] are not in the range 0 to n_row-1 or 0 to n_col-1, respectively. UMFPACK_ERROR_out_of_memory if unable to allocate sufficient workspace. Arguments: Int n_row ; Input argument, not modified. Int n_col ; Input argument, not modified. A is an n_row-by-n_col matrix. Restriction: n_row > 0 and n_col > 0. All row and column indices in the triplet form must be in the range 0 to n_row-1 and 0 to n_col-1, respectively. Int nz ; Input argument, not modified. The number of entries in the triplet form of the matrix. Restriction: nz >= 0. Int Ti [nz] ; Input argument, not modified. Int Tj [nz] ; Input argument, not modified. double Tx [nz] ; Input argument, not modified. Size 2*nz if Tz or Az are NULL. double Tz [nz] ; Input argument, not modified, for complex versions. Ti, Tj, Tx, and Tz hold the "triplet" form of a sparse matrix. The kth nonzero entry is in row i = Ti [k], column j = Tj [k], and the real part of a_ij is Tx [k]. The imaginary part of a_ij is Tz [k], for complex versions. The row and column indices i and j must be in the range 0 to n_row-1 and 0 to n_col-1, respectively. Duplicate entries may be present; they are summed in the output matrix. This is not an error condition. The "triplets" may be in any order. Tx, Tz, Ax, and Az are optional. Ax is computed only if both Ax and Tx are present (not (double *) NULL). This is not error condition; the routine can create just the pattern of the output matrix from the pattern of the triplets. If Az or Tz are NULL, then both real and imaginary parts are contained in Tx[0..2*nz-1], with Tx[2*k] and Tx[2*k+1] being the real and imaginary part of the kth entry. Int Ap [n_col+1] ; Output argument. Ap is an integer array of size n_col+1 on input. On output, Ap holds the "pointers" for the column form of the sparse matrix A. Column j of the matrix A is held in Ai [(Ap [j]) ... (Ap [j+1]-1)]. The first entry, Ap [0], is zero, and Ap [j] <= Ap [j+1] holds for all j in the range 0 to n_col-1. The value nz2 = Ap [n_col] is thus the total number of entries in the pattern of the matrix A. Equivalently, the number of duplicate triplets is nz - Ap [n_col]. Int Ai [nz] ; Output argument. Ai is an integer array of size nz on input. Note that only the first Ap [n_col] entries are used. The nonzero pattern (row indices) for column j is stored in Ai [(Ap [j]) ... (Ap [j+1]-1)]. The row indices in a given column j are in ascending order, and no duplicate row indices are present. Row indices are in the range 0 to n_col-1 (the matrix is 0-based). double Ax [nz] ; Output argument. Size 2*nz if Tz or Az are NULL. double Az [nz] ; Output argument for complex versions. Ax and Az (for the complex versions) are double arrays of size nz on input. Note that only the first Ap [n_col] entries are used in both arrays. Ax is optional; if Tx and/or Ax are not present (a (double *) NULL pointer), then Ax is not computed. If present, Ax holds the numerical values of the the real part of the sparse matrix A and Az holds the imaginary parts. The nonzero pattern (row indices) for column j is stored in Ai [(Ap [j]) ... (Ap [j+1]-1)], and the corresponding numerical values are stored in Ax [(Ap [j]) ... (Ap [j+1]-1)]. The imaginary parts are stored in Az [(Ap [j]) ... (Ap [j+1]-1)], for the complex versions. If Az or Tz are NULL, then both real and imaginary parts are returned in Ax[0..2*nz2-1], with Ax[2*k] and Ax[2*k+1] being the real and imaginary part of the kth entry. int Map [nz] ; Optional output argument. If Map is present (a non-NULL pointer to an Int array of size nz), then on output it holds the position of the triplets in the column-form matrix. That is, suppose p = Map [k], and the k-th triplet is i=Ti[k], j=Tj[k], and aij=Tx[k]. Then i=Ai[p], and aij will have been summed into Ax[p] (or simply aij=Ax[p] if there were no duplicate entries also in row i and column j). Also, Ap[j] <= p < Ap[j+1]. The Map array is not computed if it is (Int *) NULL. The Map array is useful for converting a subsequent triplet form matrix with the same pattern as the first one, without calling this routine. If Ti and Tj do not change, then Ap, and Ai can be reused from the prior call to umfpack_*_triplet_to_col. You only need to recompute Ax (and Az for the split complex version). This code excerpt properly sums up all duplicate values (for the real version): for (p = 0 ; p < Ap [n_col] ; p++) Ax [p] = 0 ; for (k = 0 ; k < nz ; k++) Ax [Map [k]] += Tx [k] ; This feature is useful (along with the reuse of the Symbolic object) if you need to factorize a sequence of triplet matrices with identical nonzero pattern (the order of the triplets in the Ti,Tj,Tx arrays must also remain unchanged). It is faster than calling this routine for each matrix, and requires no workspace. */ |