| /external/eigen/doc/examples/ |
| TutorialLinAlgSetThreshold.cpp | 12 FullPivLU<Matrix2d> lu(A);
13 cout << "By default, the rank of A is found to be " << lu.rank() << endl;
14 lu.setThreshold(1e-5);
15 cout << "With threshold 1e-5, the rank of A is found to be " << lu.rank() << endl;
|
| TutorialInplaceLU.cpp | 21 PartialPivLU<Ref<MatrixXd> > lu(A);
26 cout << "Here is the matrix storing the L and U factors:\n" << lu.matrixLU() << endl;
32 VectorXd x = lu.solve(b);
38 x = lu.solve(b);
44 lu.compute(A);
45 x = lu.solve(b);
52 lu.compute(A1);
57 x = lu.solve(b);
|
| Tutorial_PartialLU_solve.cpp | 2 #include <Eigen/LU>
16 Vector3f x = A.lu().solve(b);
|
| /external/eigen/doc/snippets/ |
| class_FullPivLU.cpp | 5 Eigen::FullPivLU<Matrix5x3> lu(m);
6 cout << "Here is, up to permutations, its LU decomposition matrix:"
7 << endl << lu.matrixLU() << endl;
10 l.block<5,3>(0,0).triangularView<StrictlyLower>() = lu.matrixLU();
13 Matrix5x3 u = lu.matrixLU().triangularView<Upper>();
16 cout << lu.permutationP().inverse() * l * u * lu.permutationQ().inverse() << endl;
|
| Tutorial_solve_singular.cpp | 8 x = A.lu().solve(b);
|
| PartialPivLU_solve.cpp | 5 MatrixXd X = A.lu().solve(B);
|
| /external/iproute2/ip/ |
| iplink_macvlan.c | 23 #define pfx_err(lu, ...) { \
24 fprintf(stderr, "%s: ", lu->id); \
29 static void print_explain(struct link_util *lu, FILE *f)
33 lu->id
37 static void explain(struct link_util *lu)
39 print_explain(lu, stderr);
49 static int macvlan_parse_opt(struct link_util *lu, int argc, char **argv,
72 explain(lu);
75 pfx_err(lu, "unknown option \"%s\"?", *argv);
76 explain(lu);
[all...] |
| iplink_ipvlan.c | 38 static int ipvlan_parse_opt(struct link_util *lu, int argc, char **argv,
69 static void ipvlan_print_opt(struct link_util *lu, FILE *f, struct rtattr *tb[])
86 static void ipvlan_print_help(struct link_util *lu, int argc, char **argv,
|
| iplink_vrf.c | 31 static int vrf_parse_opt(struct link_util *lu, int argc, char **argv,
58 static void vrf_print_opt(struct link_util *lu, FILE *f, struct rtattr *tb[])
67 static void vrf_print_help(struct link_util *lu, int argc, char **argv,
|
| iplink_ipoib.c | 44 static int ipoib_parse_opt(struct link_util *lu, int argc, char **argv,
83 static void ipoib_print_opt(struct link_util *lu, FILE *f, struct rtattr *tb[])
113 static void ipoib_print_help(struct link_util *lu, int argc, char **argv,
|
| iplink_bridge.c | 42 static int bridge_parse_opt(struct link_util *lu, int argc, char **argv,
118 static void bridge_print_opt(struct link_util *lu, FILE *f, struct rtattr *tb[])
160 static void bridge_print_help(struct link_util *lu, int argc, char **argv,
|
| iplink_hsr.c | 44 static int hsr_parse_opt(struct link_util *lu, int argc, char **argv,
83 static void hsr_print_opt(struct link_util *lu, FILE *f, struct rtattr *tb[])
129 static void hsr_print_help(struct link_util *lu, int argc, char **argv,
|
| /external/eigen/test/ |
| lu.cpp | 11 #include <Eigen/LU>
24 LU.h
65 FullPivLU<MatrixType> lu; local
70 lu.setThreshold(RealScalar(0.01));
71 lu.compute(m1);
74 u = lu.matrixLU().template triangularView<Upper>();
77 = lu.matrixLU().block(0,0,rows,(std::min)(rows,cols));
79 VERIFY_IS_APPROX(lu.permutationP() * m1 * lu.permutationQ(), l*u);
81 KernelMatrixType m1kernel = lu.kernel()
133 FullPivLU<MatrixType> lu; local
224 FullPivLU<MatrixType> lu; local
[all...] |
| /external/eigen/failtest/ |
| fullpivlu_int.cpp | 1 #include "../Eigen/LU"
13 FullPivLU<Matrix<SCALAR,Dynamic,Dynamic> > lu(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
|
| partialpivlu_int.cpp | 1 #include "../Eigen/LU"
13 PartialPivLU<Matrix<SCALAR,Dynamic,Dynamic> > lu(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10));
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/linear/ |
| LUDecompositionImpl.java | 27 * L, U and P that satisfy: PA = LU, L is lower triangular, and U is
38 /** Default bound to determine effective singularity in LU decomposition */
41 /** Entries of LU decomposition. */
42 private double lu[][]; field in class:LUDecompositionImpl
44 /** Pivot permutation associated with LU decomposition */
47 /** Parity of the permutation associated with the LU decomposition */
63 * Calculates the LU-decomposition of the given matrix.
73 * Calculates the LU-decomposition of the given matrix.
87 lu = matrix.getData();
107 final double[] luRow = lu[row]
235 private final double lu[][]; field in class:LUDecompositionImpl.Solver
[all...] |
| FieldLUDecompositionImpl.java | 30 * L, U and P that satisfy: PA = LU, L is lower triangular, and U is
46 /** Entries of LU decomposition. */
47 private T lu[][]; field in class:FieldLUDecompositionImpl
49 /** Pivot permutation associated with LU decomposition */
52 /** Parity of the permutation associated with the LU decomposition */
68 * Calculates the LU-decomposition of the given matrix.
81 lu = matrix.getData();
101 final T[] luRow = lu[row];
104 sum = sum.subtract(luRow[i].multiply(lu[i][col]));
112 final T[] luRow = lu[row]
232 private final T lu[][]; field in class:FieldLUDecompositionImpl.Solver
[all...] |
| BigMatrixImpl.java | 28 * LU decompostion</a> to support linear system
31 * The LU decompostion is performed as needed, to support the following operations: <ul>
39 * The LU decomposition is stored and reused on subsequent calls. If matrix
43 * LU decomposition will not be discarded. In this case, you need to
64 /** Bound to determine effective singularity in LU decomposition */
73 /** Entries of cached LU decomposition.
76 protected BigDecimal lu[][] = null; field in class:BigMatrixImpl
78 /** Permutation associated with LU decomposition */
81 /** Parity of the permutation associated with the LU decomposition */
114 lu = null
[all...] |
| /external/webrtc/webrtc/modules/video_coding/test/ |
| plotReceiveTrace.m | 27 [tempres, count] = sscanf(line, 'DEBUG ; (%u:%u:%u:%u |%*lu)%13c:');
47 [p, count] = sscanf(message, 'ExtrapolateLocalTime(%lu)=%lu ms');
54 [p, count] = sscanf(message, 'Packet seqNo %u of frame %lu at %lu');
61 [p, count] = sscanf(message, 'First packet of frame %lu at %lu');
68 [p, count] = sscanf(message, 'Decoding timestamp %lu at %lu');
75 [p, count] = sscanf(message, 'Render frame %lu at %lu. Render delay %lu, required delay %lu, max decode time %lu, min total delay %lu')
[all...] |
| /external/eigen/lapack/ |
| lu.cpp | 11 #include <Eigen/LU>
13 // computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges
45 // with a general N-by-N matrix A using the LU factorization computed by GETRF
62 MatrixType lu(a,*n,*n,*lda);
70 lu.triangularView<UnitLower>().solveInPlace(B);
71 lu.triangularView<Upper>().solveInPlace(B);
75 lu.triangularView<Upper>().transpose().solveInPlace(B);
76 lu.triangularView<UnitLower>().transpose().solveInPlace(B);
81 lu.triangularView<Upper>().adjoint().solveInPlace(B);
82 lu.triangularView<UnitLower>().adjoint().solveInPlace(B)
[all...] |
| /external/eigen/Eigen/src/LU/ |
| PartialPivLU.h | 46 * \brief LU decomposition of a matrix with partial pivoting, and related features
48 * \tparam _MatrixType the type of the matrix of which we are computing the LU decomposition
50 * This class represents a LU decomposition of a \b square \b invertible matrix, with partial pivoting: the matrix A
54 * Typically, partial pivoting LU decomposition is only considered numerically stable for square invertible
59 * The guaranteed safe alternative, working for all matrices, is the full pivoting LU decomposition, provided
62 * This is \b not a rank-revealing LU decomposition. Many features are intentionally absent from this class,
65 * This LU decomposition is suitable to invert invertible matrices. It is what MatrixBase::inverse() uses
69 * The data of the LU decomposition can be directly accessed through the methods matrixLU(), permutationP().
110 * \param matrix the matrix of which to compute the LU decomposition.
120 * \param matrix the matrix of which to compute the LU decomposition
604 MatrixBase<Derived>::lu() const function in class:Eigen::MatrixBase
[all...] |
| /bionic/libm/upstream-freebsd/lib/msun/src/ |
| s_ilogbl.c | 35 m = 1lu << (LDBL_MANL_SIZE - 1);
39 m = 1lu << (LDBL_MANH_SIZE - 1);
|
| s_logbl.c | 38 m = 1lu << (LDBL_MANL_SIZE - 1);
42 m = 1lu << (LDBL_MANH_SIZE - 1);
|
| /external/eigen/bench/ |
| sparse_lu.cpp | 43 #include <Eigen/LU>
50 SparseLU<EigenSparseMatrix,Backend> lu(sm1, flags);
52 if (lu.succeeded())
62 ok = lu.solve(b,&x);
101 FullPivLU<DenseMatrix> lu(m1);
107 lu.solve(b,&x);
|
| /external/bison/data/ |
| glr.c | [all...] |
