| /external/eigen/unsupported/Eigen/src/KroneckerProduct/ |
| KroneckerTensorProduct.h | 41 * Kronecker tensor product helper function for matrices, where at least one is sparse
117 * Computes Kronecker tensor product of a dense and a sparse matrix
120 * \param b Sparse matrix b
130 * Computes Kronecker tensor product of a sparse and a dense matrix
132 * \param a Sparse matrix a
143 * Computes Kronecker tensor product of two sparse matrices
145 * \param a Sparse matrix a
146 * \param b Sparse matrix b
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| /external/smali/smali/src/test/resources/LexerTest/ |
| DirectiveTest.tokens | 20 SPARSE_SWITCH_DIRECTIVE(".sparse-switch")
21 END_SPARSE_SWITCH_DIRECTIVE(".end sparse-switch")
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| /external/eigen/doc/ |
| SparseQuickReference.dox | 2 /** \page SparseQuickRefPage Quick reference guide for sparse matrices
17 In this page, we give a quick summary of the main operations available for sparse matrices in the class SparseMatrix. First, it is recommended to read first the introductory tutorial at \ref TutorialSparse. The important point to have in mind when working on sparse matrices is how they are stored :
18 i.e either row major or column major. The default is column major. Most arithmetic operations on sparse matrices will assert that they have the same storage order. Moreover, when interacting with external libraries that are not yet supported by Eigen, it is important to know how to send the required matrix pointers.
21 SparseMatrix is the core class to build and manipulate sparse matrices in Eigen. It takes as template parameters the Scalar type and the storage order, either RowMajor or ColumnMajor. The default is ColumnMajor.
24 SparseMatrix<double> sm1(1000,1000); // 1000x1000 compressed sparse matrix of double.
43 Insertions of values in the sparse matrix can be done directly by looping over nonzero elements and use the insert() function
82 sm1.isVector(); // Check if sm1 is a sparse vector or a sparse matrix
89 It is easy to perform arithmetic operations on sparse matrices provided that the dimensions are adequate and that the matrices have the same storage ord (…)
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| /external/chromium/net/disk_cache/ |
| disk_cache.h | 194 // Sparse entries support:
196 // A Backend implementation can support sparse entries, so the cache keeps
202 // There are only two streams for sparse entries: a regular control stream
204 // WriteData), and one sparse stream that must me accessed through the sparse-
205 // aware API that follows. Calling a non-sparse aware method with an index
207 // behavior. Using a sparse-aware method with an entry that was not stored
208 // using the same API, or with a backend that doesn't support sparse entries
224 // The sparse methods don't support multiple simultaneous IO operations to the
236 // Behaves like ReadData() except that this method is used to access sparse
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| /external/llvm/include/llvm/ADT/ |
| SparseSet.h | 1 //===--- llvm/ADT/SparseSet.h - Sparse set ----------------------*- C++ -*-===//
11 // Briggs, Torczon, "An efficient representation for sparse sets", ACM Letters
14 // A sparse set holds a small number of objects identified by integer keys from
15 // a moderately sized universe. The sparse set uses more memory than other
97 /// SparseSet contains a dense vector holding all the objects and a sparse
99 /// the sparse array which is the size of the key universe. The SparseT
103 /// When SparseT is uint32_t, find() only touches 2 cache lines, but the sparse
107 /// lines, but the sparse array is 4x smaller. N is the number of elements in
124 SparseT *Sparse;
141 SparseSet() : Sparse(0), Universe(0) {
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| /external/eigen/Eigen/src/SparseCore/ |
| SparseDiagonalProduct.h | 15 // The product of a diagonal matrix with a sparse matrix can be easily
18 // 1 - diag * row-major sparse
19 // => each inner vector <=> scalar * sparse vector product
21 // 2 - diag * col-major sparse
22 // => each inner vector <=> densevector * sparse vector cwise product
37 typedef Sparse StorageKind;
86 eigen_assert(lhs.cols() == rhs.rows() && "invalid sparse matrix * diagonal matrix product");
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| SparseProduct.h | 73 typedef Sparse StorageKind;
156 // sparse = sparse * sparse
165 /** \returns an expression of the product of two sparse matrices.
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| /external/ceres-solver/internal/ceres/ |
| sparse_normal_cholesky_solver.h | 31 // A solver for sparse linear least squares problem based on solving
32 // the normal equations via a sparse cholesky factorization.
47 // Solves the normal equations (A'A + D'D) x = A'b, using the CHOLMOD sparse
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| block_sparse_matrix.h | 31 // Implementation of the SparseMatrix interface for block sparse
51 // the lazy block sparse matrix implementation.
57 // Convert this matrix into a triplet sparse matrix.
81 // manipulating block sparse matrices. The block structure is stored
90 // Construct a block sparse matrix with a fully initialized
98 // Construct a block sparse matrix from a protocol buffer.
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| block_jacobian_writer.h | 31 // A jacobian writer that writes to block sparse matrices. The "writer" name is
34 // makes a jacobians array which has direct pointers into the block sparse
79 // The block sparse matrix that this writer writes to is stored as a set of
81 // "double* values_" member of the block sparse matrix contains all of these
85 // In the case of a block sparse jacobian, the jacobian writer needs a way to
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| /external/smali/smali-integration-tests/src/test/smali/junit-tests/InstructionTests/Format31t/ |
| Format31t.smali | 101 sparse-switch v0, :SparseSwitch
123 .sparse-switch
129 .end sparse-switch
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| /external/v8/test/mjsunit/ |
| array-functions-prototype-misc.js | 179 var sparse = [];
180 sparse[pos + 1000] = 'is ';
181 sparse[pos + 271828] = 'time ';
182 sparse[pos + 31415] = 'the ';
183 sparse[pos + 012260199] = 'all ';
184 sparse[-1] = 'foo';
185 sparse[pos + 22591927] = 'good ';
186 sparse[pos + 1618033] = 'for ';
187 sparse[pos + 91] = ': Now ';
188 sparse[pos + 86720199] = 'men.'
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| /external/eigen/test/eigen2/ |
| CMakeLists.txt | 49 # no support for eigen2 sparse module
|
| /external/eigen/test/ |
| sparse_solver.h | 10 #include "sparse.h"
27 std::cerr << "sparse solver testing: factorization failed (check_sparse_solving)\n";
34 std::cerr << "sparse solver testing: solving failed\n";
37 VERIFY(oldb.isApprox(b) && "sparse solver testing: the rhs should not be modified!");
47 std::cerr << "sparse solver testing: factorization failed (check_sparse_solving)\n";
54 std::cerr << "sparse solver testing: solving failed\n";
57 VERIFY(oldb.isApprox(b) && "sparse solver testing: the rhs should not be modified!");
67 VERIFY(oldb.isApprox(b) && "sparse solver testing: the rhs should not be modified!");
84 std::cerr << "sparse solver testing: factorization failed (check_sparse_solving_real_cases)\n";
91 std::cerr << "sparse solver testing: solving failed\n"
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| sparse_solvers.cpp | 10 #include "sparse.h"
83 // lower - sparse
90 // upper - sparse
|
| /external/eigen/doc/special_examples/ |
| Tutorial_sparse_example_details.cpp | 1 #include <Eigen/Sparse>
5 typedef Eigen::SparseMatrix<double> SpMat; // declares a column-major sparse matrix type of double
|
| /system/core/libsparse/ |
| sparse_format.h | 28 __le32 total_blks; /* total blocks in the non-sparse output image */
29 __le32 total_chunks; /* total chunks in the sparse input image */
|
| /system/extras/ext4_utils/ |
| ext2simg.c | 28 #include <sparse/sparse.h>
53 fprintf(stderr, " -S don't use sparse output format\n");
183 int sparse = 1; local
199 sparse = 0;
249 write_ext4_image(outfd, gzip, sparse, crc);
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| make_ext4fs_main.c | 68 int sparse = 0; local
128 sparse = 1;
164 if (wipe && sparse) {
165 fprintf(stderr, "Cannot specifiy both wipe and sparse\n");
204 sparse, crc, wipe, sehnd, verbose);
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| /external/eigen/unsupported/Eigen/src/SparseExtra/ |
| RandomSetter.h | 96 * \brief The RandomSetter is a wrapper object allowing to set/update a sparse matrix with random access
98 * \param SparseMatrixType the type of the sparse matrix we are updating
99 * \param MapTraits a traits class representing the map implementation used for the temporary sparse storage.
104 * This class temporarily represents a sparse matrix object using a generic map implementation allowing for
106 * in the RandomSetter constructor, while the sparse matrix is updated back at destruction time. This strategy
138 * - \#include <google/dense_hash_map> yourself \b before Eigen/Sparse header
175 /** Constructs a random setter object from the sparse matrix \a target
178 * a sparse matrix from scratch, then you must set it to zero first using the
208 /** Destructor updating back the sparse matrix target */
274 // moreover those 2^OuterPacketBits coeffs are likely to be sparse, an so only
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| /external/eigen/bench/ |
| sparse_cholesky.cpp | 4 #include <Eigen/Sparse>
74 // std::cout << "sparse\n" << chol.matrixL() << "%\n";
93 std::cout << "Generate sparse matrix (might take a while)...\n";
126 // eigen sparse matrices
127 doEigen<Eigen::DefaultBackend>("Eigen/Sparse", sm1, Eigen::IncompleteFactorization);
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| sparse_dense_product.cpp | 91 // eigen sparse matrices
93 std::cout << "Eigen sparse\t" << sm1.nonZeros()/float(sm1.rows()*sm1.cols())*100 << "%\n";
106 // std::cout << "Eigen dyn-sparse\t" << m1.nonZeros()/float(m1.rows()*m1.cols())*100 << "%\n";
118 std::cout << "GMM++ sparse\t" << density*100 << "%\n";
137 std::cout << "ublas sparse\t" << density*100 << "%\n";
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| /dalvik/dexgen/src/com/android/dexgen/dex/code/ |
| SwitchData.java | 28 * in either a "packed" or "sparse" form.
46 /** whether the output table will be packed (vs. sparse) */
183 sb.append(packed ? "packed" : "sparse");
219 * Gets the size of a sparse table for the given cases, in 16-bit code
223 * @return {@code > 0;} the sparse table size
250 * would be as small or smaller than 5/4 of the sparse
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| /dalvik/dx/src/com/android/dx/dex/code/ |
| SwitchData.java | 29 * in either a "packed" or "sparse" form.
47 /** whether the output table will be packed (vs. sparse) */
184 sb.append(packed ? "packed" : "sparse");
220 * Gets the size of a sparse table for the given cases, in 16-bit code
224 * @return {@code > 0;} the sparse table size
251 * would be as small or smaller than 5/4 of the sparse
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| /external/dexmaker/src/dx/java/com/android/dx/dex/code/ |
| SwitchData.java | 29 * in either a "packed" or "sparse" form.
47 /** whether the output table will be packed (vs. sparse) */
184 sb.append(packed ? "packed" : "sparse");
220 * Gets the size of a sparse table for the given cases, in 16-bit code
224 * @return {@code > 0;} the sparse table size
251 * would be as small or smaller than 5/4 of the sparse
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