| /external/eigen/test/ |
| CMakeLists.txt | 21 set(EIGEN_TEST_MATRIX_DIR "" CACHE STRING "Enable testing of realword sparse matrices contained in the specified path")
24 message(STATUS "Test realworld sparse matrices: ${EIGEN_TEST_MATRIX_DIR}")
279 ei_add_property(EIGEN_TESTING_SUMMARY "Sparse lib flags: ${SPARSE_LIBS}\n")
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| /external/eigen/test/eigen2/ |
| eigen2_sparse_product.cpp | 10 #include "sparse.h"
40 // sparse * dense
46 // dense * sparse
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| /external/regex-re2/util/ |
| sparse_set.h | 38 // Representation for Sparse Sets, ACM Letters on Programming Languages
41 // For a generalization to sparse array, see sparse_array.h.
162 // Can sort the sparse array so that future iterations
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| /external/v8/test/mjsunit/ |
| sparse-array-reverse.js | 39 // Simple test of reverse on sparse array.
59 // CONG pseudo random number generator. Used for fuzzing the sparse array
70 // Fuzzing test of reverse on sparse array.
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| /system/extras/f2fs_utils/ |
| f2fs_ioutils.c | 48 #include <sparse/sparse.h>
179 // sparse file fills with zero by default.
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| /external/autotest/client/tests/wb_kupdate/ |
| wb_kupdate.py | 43 Reset the test. Reinitialize sparse file.
50 logging.debug('Cleanup - removing sparse file.')
60 Create and initialize the sparse file.
141 Check to see if the sparse file size increases.
199 @param sparse_file: the absolute path to the sparse file.
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| /external/ceres-solver/internal/ceres/ |
| program_evaluator.h | 38 // jacobian blocks in the passed sparse matrix.
41 // supporting writing to multiple sparse matrix formats. For example, when the
42 // ProgramEvaluator is parameterized for writing to block sparse matrices, the
44 // block sparse matrix by the user's CostFunction; there is no copying.
69 // // larger sparse jacobian.
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| sparse_normal_cholesky_solver.cc | 114 LOG(FATAL) << "Unknown sparse linear algebra library : "
151 // using a sparse Cholesky factorization. Notice that when compared
170 // outer_product_ is a compressed row sparse matrix and in lower
171 // triangular form, when mapped to a compressed column sparse
248 // using a sparse Cholesky factorization. Notice that when compared
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| evaluator.h | 102 // Build and return a sparse matrix for storing and working with the Jacobian
105 // sparse. Since the sparsity pattern of the Jacobian remains constant over
112 // of their client's requirements for the kind of sparse matrix storage and
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| schur_complement_solver.h | 97 // complement matrix is large and sparse. It requires that
99 // sparse Cholesky factorization of the Schur complement. This solver
162 // Sparse Cholesky factorization based solver.
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| /external/eigen/bench/ |
| sparse_product.cpp | 153 // eigen sparse matrices
155 std::cout << "Eigen sparse\t" << sm1.nonZeros()/(float(sm1.rows())*float(sm1.cols()))*100 << "% * "
186 // eigen dyn-sparse matrices
189 std::cout << "Eigen dyn-sparse\t" << m1.nonZeros()/(float(m1.rows())*float(m1.cols()))*100 << "% * "
266 std::cout << "GMM++ sparse\t" << nnzPerCol << "%\n";
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| sparse_trisolver.cpp | 96 // eigen sparse matrices
98 std::cout << "Eigen sparse\t" << density*100 << "%\n";
137 std::cout << "GMM++ sparse\t" << density*100 << "%\n";
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| /external/squashfs-tools/squashfs-tools/ |
| process_fragments.c | 64 int bytes = file_buffer->size, sparse = TRUE, value; local
70 sparse = FALSE;
76 return sparse;
276 int sparse = checksum_sparse(file_buffer); local
283 if(sparse_files && sparse) {
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| /system/extras/verity/fec/ |
| main.cpp | 110 " -S treat data as a sparse file\n"
219 if (ctx.inplace && ctx.sparse) {
220 FATAL("invalid parameters: inplace cannot be used with sparse "
281 {"sparse", no_argument, 0, 'S'},
301 ctx.sparse = true;
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| image.cpp | 37 #include <sparse/sparse.h>
215 if (ctx->sparse) {
216 FATAL("sparse files not supported\n");
223 if (ctx->sparse) {
318 /* TODO: support saving as a sparse file */
|
| /prebuilts/go/darwin-x86/src/archive/tar/ |
| reader_test.go | 59 file: "testdata/sparse-formats.tar",
62 Name: "sparse-gnu",
76 Name: "sparse-posix-0.0",
90 Name: "sparse-posix-0.1",
104 Name: "sparse-posix-1.0",
697 t.Errorf("Incorrect sparse map: got %v, wanted %v", sp, expected)
702 // This test uses lots of holes so the sparse header takes up more than two blocks
721 // Get an reader to read the sparse map
724 // Read the sparse map
730 t.Errorf("Incorrect sparse map: got %v, wanted %v", sp, expected
[all...] |
| /prebuilts/go/linux-x86/src/archive/tar/ |
| reader_test.go | 59 file: "testdata/sparse-formats.tar",
62 Name: "sparse-gnu",
76 Name: "sparse-posix-0.0",
90 Name: "sparse-posix-0.1",
104 Name: "sparse-posix-1.0",
697 t.Errorf("Incorrect sparse map: got %v, wanted %v", sp, expected)
702 // This test uses lots of holes so the sparse header takes up more than two blocks
721 // Get an reader to read the sparse map
724 // Read the sparse map
730 t.Errorf("Incorrect sparse map: got %v, wanted %v", sp, expected
[all...] |
| /external/ceres-solver/include/ceres/ |
| covariance.h | 155 // large sparse matrices efficiently. For small and moderate sized
232 // 2. EIGEN_SPARSE_QR uses the sparse QR factorization algorithm
239 // It is a moderately fast algorithm for sparse matrices.
241 // 3. SUITE_SPARSE_QR uses the SuiteSparseQR sparse QR
243 // multi threaded, so for large sparse sparse matrices it is
278 // sparse QR factorization algorithm. It is a fairly reliable
|
| /system/core/libsparse/ |
| output_file.c | 542 int64_t len, bool sparse, int chunks, bool crc)
566 if (sparse) {
572 if (sparse) {
632 int gz __unused, int sparse, int chunks, int crc)
647 ret = output_file_init(&outc->out, block_size, len, sparse, chunks, crc);
657 int gz, int sparse, int chunks, int crc)
673 ret = output_file_init(out, block_size, len, sparse, chunks, crc);
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| /system/core/toolbox/upstream-netbsd/bin/dd/ |
| dd.c | 82 static off_t pending = 0; /* pending seek if sparse */
452 /* If there are pending sparse blocks, make sure
453 * to write out the final block un-sparse
510 int sparse, i; local
511 sparse = 1; /* Is buffer sparse? */
514 sparse = 0;
517 if (sparse) {
527 err(EXIT_FAILURE, "%s: seek error creating sparse file",
543 st.sparse += pending/out.dbsz
[all...] |
| /external/eigen/Eigen/src/Core/ |
| Matrix.h | 75 * <dt><b>\anchor dense Dense versus sparse:</b></dt>
76 * <dd>This %Matrix class handles dense, not sparse matrices and vectors. For sparse matrices and vectors, see the Sparse module.
79 * This is unlike Sparse matrices and vectors where the coefficients are stored as a list of nonzero coefficients.</dd>
90 * If you want this behavior, see the Sparse module.</dd>
|
| /external/eigen/Eigen/src/UmfPackSupport/ |
| UmfPackSupport.h | 121 * \brief A sparse LU factorization and solver based on UmfPack
123 * This class allows to solve for A.X = B sparse linear problems via a LU factorization
124 * using the UmfPack library. The sparse matrix A must be squared and full rank.
125 * The vectors or matrices X and B can be either dense or sparse.
129 * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
201 /** Computes the sparse Cholesky decomposition of \a matrix
|
| /external/eigen/unsupported/Eigen/src/IterativeSolvers/ |
| GMRES.h | 43 * Iterative Methods for Sparse Linear Systems.
222 * \brief A GMRES solver for sparse square problems
224 * This class allows to solve for A.x = b sparse linear problems using a generalized minimal
225 * residual method. The vectors x and b can be either dense or sparse.
227 * \tparam _MatrixType the type of the sparse matrix A, can be a dense or a sparse matrix.
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| ConstrainedConjGrad.h | 52 // FIXME use sparse vectors ?
86 // FIXME add a generic "prune/filter" expression for both dense and sparse object to sparse
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/linear/ |
| OpenMapRealMatrix.java | 25 * Sparse matrix implementation based on an open addressed map.
41 /** Storage for (sparse) matrix elements. */
45 * Build a sparse matrix with the supplied row and column dimensions.
|
