/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/rank/ |
H A D | Median.java | 17 package org.apache.commons.math.stat.descriptive.rank;
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H A D | Max.java | 17 package org.apache.commons.math.stat.descriptive.rank;
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H A D | Min.java | 17 package org.apache.commons.math.stat.descriptive.rank;
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H A D | Percentile.java | 17 package org.apache.commons.math.stat.descriptive.rank;
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/external/apache-commons-math/src/main/java/org/apache/commons/math/stat/ranking/ |
H A D | RankingAlgorithm.java | 21 * Interface representing a rank transformation. 28 * <p>Performs a rank transformation on the input data, returning an array 40 double[] rank (double[] data); method in interface:RankingAlgorithm
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H A D | NaturalRanking.java | 46 * <th><code>rank(data)</code></th> 190 public double[] rank(double[] data) { method in class:NaturalRanking
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/external/mesa3d/src/gallium/drivers/llvmpipe/ |
H A D | lp_fence.c | 38 * The rank will be the number of bins in the scene. Whenever a rendering 40 * the counter == the rank, the fence is finished. 42 * \param rank the expected finished value of the fence counter. 45 lp_fence_create(unsigned rank) argument 59 fence->rank = rank; 83 * When the counter == the rank, the fence is finished. 94 assert(fence->count <= fence->rank); 97 debug_printf("%s count=%u rank=%u\n", __FUNCTION__, 98 fence->count, fence->rank); [all...] |
H A D | lp_fence.h | 50 unsigned rank; member in struct:lp_fence 56 lp_fence_create(unsigned rank);
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/external/clang/test/Analysis/ |
H A D | MemRegion.cpp | 8 int rank = 0; local 9 MPI_Comm_rank(MPI_COMM_WORLD, &rank); 15 int rank = 0; local 16 MPI_Comm_rank(MPI_COMM_WORLD, &rank); 22 int rank = 0; local 23 MPI_Comm_rank(MPI_COMM_WORLD, &rank); 31 int rank = 0; local 32 MPI_Comm_rank(MPI_COMM_WORLD, &rank); 40 int rank = 0; local 41 MPI_Comm_rank(MPI_COMM_WORLD, &rank); [all...] |
H A D | mpichecker.cpp | 6 int rank = 0; local 8 MPI_Comm_rank(MPI_COMM_WORLD, &rank); 9 if (rank >= 0) { 11 MPI_Isend(&buf, 1, MPI_DOUBLE, rank + 1, 0, MPI_COMM_WORLD, &sendReq1); 12 MPI_Irecv(&buf, 1, MPI_DOUBLE, rank - 1, 0, MPI_COMM_WORLD, &recvReq1); 20 int rank = 0; local 22 MPI_Comm_rank(MPI_COMM_WORLD, &rank); 23 if (rank >= 0) { 25 MPI_Isend(&buf, 1, MPI_DOUBLE, rank + 1, 0, MPI_COMM_WORLD, &sendReq1); 26 MPI_Irecv(&buf, 1, MPI_DOUBLE, rank 33 int rank = 0; local 58 int rank = 0; local 72 int rank = 0; local 86 int rank = 0; local 100 int rank = 0; local 110 int rank = 0; local 131 int rank = 0; local 138 int rank = 0; local 147 int rank = 0; local 154 int rank = 0; local 163 int rank = 0; local 179 int rank = 0; local 193 int rank = 0; local 207 int rank = 0; local 220 int rank = 0; local 239 int rank = 0; local 261 int rank = 0; local 277 int rank = 0; local [all...] |
/external/apache-commons-math/src/main/java/org/apache/commons/math/random/ |
H A D | CorrelatedRandomVectorGenerator.java | 54 * the rank of the covariance matrix, and it is the dimension of the 79 private int rank; field in class:CorrelatedRandomVectorGenerator 111 normalized = new double[rank]; 139 normalized = new double[rank]; 160 /** Get the rank of the covariance matrix. 161 * The rank is the number of independent rows in the covariance 164 * @return rank of the square matrix. 168 return rank; 201 rank = 0; 205 swap[rank] [all...] |
/external/eigen/Eigen/src/misc/ |
H A D | Kernel.h | 45 m_rank(dec.rank()), 51 inline Index rank() const { return m_rank; } function in struct:Eigen::internal::kernel_retval_base 72 using Base::rank; \
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H A D | Image.h | 28 Dynamic, // we don't know at compile time the dimension of the image (the rank) 43 : m_dec(dec), m_rank(dec.rank()), 50 inline Index rank() const { return m_rank; } function in struct:Eigen::internal::image_retval_base 74 using Base::rank; \
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/external/guava/guava/src/com/google/common/collect/ |
H A D | ExplicitOrdering.java | 40 return rank(left) - rank(right); // safe because both are nonnegative 43 private int rank(T value) { method in class:ExplicitOrdering 44 Integer rank = rankMap.get(value); 45 if (rank == null) { 48 return rank; 54 int rank = 0; 56 builder.put(value, rank++);
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/external/jemalloc/src/ |
H A D | witness.c | 5 witness_init(witness_t *witness, const char *name, witness_rank_t rank, argument 10 witness->rank = rank; 23 malloc_printf("<jemalloc>: Lock rank order reversal:"); 25 malloc_printf(" %s(%u)", w->name, w->rank); 27 malloc_printf(" %s(%u)\n", witness->name, witness->rank); 45 witness->rank); 63 witness->rank); 84 malloc_printf(" %s(%u)", w->name, w->rank);
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H A D | mutex.c | 72 malloc_mutex_init(malloc_mutex_t *mutex, const char *name, witness_rank_t rank) argument 109 witness_init(&mutex->witness, name, rank, NULL); 135 mutex->witness.rank)) {
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/external/eigen/test/ |
H A D | qr_fullpivoting.cpp | 23 rank = internal::random<Index>(1, (std::min)(rows, cols)-1); local 28 createRandomPIMatrixOfRank(rank,rows,cols,m1); 30 VERIFY_IS_EQUAL(rank, qr.rank()); 31 VERIFY_IS_EQUAL(cols - qr.rank(), qr.dimensionOfKernel());
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H A D | lu.cpp | 56 Index rank = internal::random<Index>(1, (std::min)(rows, cols)-1); local 63 createRandomPIMatrixOfRank(rank, rows, cols, m1); 67 // The special value 0.01 below works well in tests. Keep in mind that we're only computing the rank 85 VERIFY(rank == lu.rank()); 86 VERIFY(cols - lu.rank() == lu.dimensionOfKernel()); 91 VERIFY(m1image.fullPivLu().rank() == rank); 143 VERIFY(size == lu.rank()); 232 VERIFY_RAISES_ASSERT(lu.rank()) [all...] |
/external/eigen/unsupported/Eigen/CXX11/src/Tensor/ |
H A D | TensorIO.h | 69 static const int rank = internal::array_size<Dimensions>::value; local 70 internal::TensorPrinter<Evaluator, rank>::run(os, tensor);
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/external/eigen/unsupported/Eigen/src/LevenbergMarquardt/ |
H A D | LMpar.h | 58 /* jacobian is rank-deficient, obtain a least squares solution. */ 60 // const Index rank = qr.nonzeroPivots(); // exactly double(0.) 61 const Index rank = qr.rank(); // use a threshold local 63 wa1.tail(n-rank).setZero(); 65 wa1.head(rank) = s.topLeftCorner(rank,rank).template triangularView<Upper>().solve(qtb.head(rank)); 81 /* if the jacobian is not rank deficien [all...] |
/external/apache-commons-math/src/main/java/org/apache/commons/math/estimation/ |
H A D | LevenbergMarquardtEstimator.java | 32 * to their jacobian column norm. Only the rank of the matrix and some loop bounds 128 private int rank; field in class:LevenbergMarquardtEstimator 501 // jacobian is rank-deficient, obtain a least squares solution 502 for (int j = 0; j < rank; ++j) { 505 for (int j = rank; j < cols; ++j) { 508 for (int k = rank - 1; k >= 0; --k) { 535 // if the jacobian is not rank deficient, the Newton step provides 540 if (rank == solvedCols) { 793 * <p>This decomposition handles rank deficient cases since the tranformations 836 rank [all...] |
/external/apache-commons-math/src/main/java/org/apache/commons/math/optimization/general/ |
H A D | LevenbergMarquardtOptimizer.java | 35 * to their jacobian column norm. Only the rank of the matrix and some loop bounds 125 private int rank; field in class:LevenbergMarquardtOptimizer 232 * rank of the matrix is reduced. 508 // jacobian is rank-deficient, obtain a least squares solution 509 for (int j = 0; j < rank; ++j) { 512 for (int j = rank; j < cols; ++j) { 515 for (int k = rank - 1; k >= 0; --k) { 540 // if the jacobian is not rank deficient, the Newton step provides 545 if (rank == solvedCols) { 793 * <p>This decomposition handles rank deficien [all...] |
/external/eigen/unsupported/Eigen/src/NonLinearOptimization/ |
H A D | lmpar.h | 39 /* jacobian is rank-deficient, obtain a least squares solution. */ 70 /* if the jacobian is not rank deficient, the newton */ 196 /* jacobian is rank-deficient, obtain a least squares solution. */ 198 // const Index rank = qr.nonzeroPivots(); // exactly double(0.) 199 const Index rank = qr.rank(); // use a threshold local 201 wa1.tail(n-rank).setZero(); 202 qr.matrixQR().topLeftCorner(rank, rank).template triangularView<Upper>().solveInPlace(wa1.head(rank)); [all...] |
/external/ImageMagick/MagickCore/ |
H A D | matrix.c | 439 % double **vectors,const size_t rank,const size_t number_vectors) 448 % o rank: The size of the matrix (both rows and columns). 454 % Note that the 'matrix' is given as a 'array of row pointers' of rank size. 460 % of columns, with each column array the same 'rank' size as 'matrix'. 490 double **vectors,const size_t rank,const size_t number_vectors) 518 columns=(ssize_t *) AcquireQuantumMemory(rank,sizeof(*columns)); 519 rows=(ssize_t *) AcquireQuantumMemory(rank,sizeof(*rows)); 520 pivots=(ssize_t *) AcquireQuantumMemory(rank,sizeof(*pivots)); 532 (void) ResetMagickMemory(columns,0,rank*sizeof(*columns)); 533 (void) ResetMagickMemory(rows,0,rank*sizeo 483 GaussJordanElimination(double **matrix, double **vectors,const size_t rank,const size_t number_vectors) argument 832 LeastSquaresAddTerms(double **matrix,double **vectors, const double *terms,const double *results,const size_t rank, const size_t number_vectors) argument [all...] |
/external/eigen/Eigen/src/QR/ |
H A D | HouseholderQR.h | 34 * Note that no pivoting is performed. This is \b not a rank-revealing decomposition. 352 const Index rank = (std::min)(rows(), cols()); local 359 m_qr.leftCols(rank), 360 m_hCoeffs.head(rank)).transpose() 363 m_qr.topLeftCorner(rank, rank) 365 .solveInPlace(c.topRows(rank)); 367 dst.topRows(rank) = c.topRows(rank); 368 dst.bottomRows(cols()-rank) [all...] |