/external/eigen/doc/snippets/ |
TopicAliasing_mult1.cpp | 1 MatrixXf matA(2,2); 2 matA << 2, 0, 0, 2; 3 matA = matA * matA; 4 cout << matA;
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TopicAliasing_mult3.cpp | 1 MatrixXf matA(2,2); 2 matA << 2, 0, 0, 2; 3 matA.noalias() = matA * matA; 4 cout << matA;
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TopicAliasing_mult2.cpp | 1 MatrixXf matA(2,2), matB(2,2); 2 matA << 2, 0, 0, 2; 5 matB = matA * matA; 9 matB.noalias() = matA * matA;
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Tutorial_AdvancedInitialization_Block.cpp | 1 MatrixXf matA(2, 2); 2 matA << 1, 2, 3, 4; 4 matB << matA, matA/10, matA/10, matA;
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/external/eigen/Eigen/src/Eigenvalues/ |
GeneralizedSelfAdjointEigenSolver.h | 82 * \param[in] matA Selfadjoint matrix in matrix pencil. 91 * generalized eigenproblem \f$ Ax = \lambda B x \f$ with \a matA the 106 GeneralizedSelfAdjointEigenSolver(const MatrixType& matA, const MatrixType& matB, 108 : Base(matA.cols()) 110 compute(matA, matB, options); 115 * \param[in] matA Selfadjoint matrix in matrix pencil. 129 * with \a matA the selfadjoint matrix \f$ A \f$ and \a matB the positive definite 153 GeneralizedSelfAdjointEigenSolver& compute(const MatrixType& matA, const MatrixType& matB, 163 compute(const MatrixType& matA, const MatrixType& matB, int options) 165 eigen_assert(matA.cols()==matA.rows() && matB.rows()==matA.rows() && matB.cols()==matB.rows()) [all...] |
HessenbergDecomposition.h | 272 static void _compute(MatrixType& matA, CoeffVectorType& hCoeffs, VectorType& temp); 282 * Performs a tridiagonal decomposition of \a matA in place. 284 * \param matA the input selfadjoint matrix 287 * The result is written in the lower triangular part of \a matA. 294 void HessenbergDecomposition<MatrixType>::_compute(MatrixType& matA, CoeffVectorType& hCoeffs, VectorType& temp) 296 eigen_assert(matA.rows()==matA.cols()); 297 Index n = matA.rows(); 305 matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); 306 matA.col(i).coeffRef(i+1) = beta [all...] |
Tridiagonalization.h | 28 void tridiagonalization_inplace(MatrixType& matA, CoeffVectorType& hCoeffs); 324 * Performs a tridiagonal decomposition of the selfadjoint matrix \a matA in-place. 326 * \param[in,out] matA On input the selfadjoint matrix. Only the \b lower triangular part is referenced. 332 * and lower sub-diagonal of the matrix \a matA. 340 * \f$ v_i = [ 0, \ldots, 0, 1, matA(i+2,i), \ldots, matA(N-1,i) ]^T \f$. 347 void tridiagonalization_inplace(MatrixType& matA, CoeffVectorType& hCoeffs) 352 Index n = matA.rows(); 353 eigen_assert(n==matA.cols()); 361 matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta) [all...] |
/frameworks/rs/tests/java_api/RsBLAS_Benchmark/src/com/example/android/rs/blasbenchmark/ |
BNNMTest.java | 33 private Allocation matA; 227 matA = Allocation.createTyped(mRS, a_type); 230 matA.copyFrom(a_byte); 234 mBLAS.BNNM(matA, a_offset, matB, b_offset, matC, c_offset, c_mult_int); 297 matA = Allocation.createTyped(mRS, a_type); 301 matA.copyFrom(a_byte); 305 mBLAS.BNNM(matA, a_offset, matB, b_offset, matC, c_offset, c_mult_int); 346 matA = Allocation.createTyped(mRS, a_type); 350 matA.copyFrom(a_byte); 354 mBLAS.BNNM(matA, a_offset, matB, b_offset, matC, c_offset, c_mult_int) [all...] |
SGEMMTest.java | 33 private Allocation matA; 150 matA = Allocation.createTyped(mRS, a_type); 154 matA.copyFrom(a_float); 159 1.0f, matA, matB, 0.f, matC); 205 matA = Allocation.createTyped(mRS, a_type); 209 matA.copyFrom(a_float); 214 1.0f, matA, matB, 0.f, matC); 253 matA = Allocation.createTyped(mRS, a_type); 257 matA.copyFrom(a_float); 262 1.0f, matA, matB, 0.f, matC) [all...] |
GoogLeNet.java | 27 private ArrayList<Allocation> matA; 149 matA = new ArrayList<Allocation>(); 202 matA.add(A); 213 1.0f, matA.get(i), matB.get(i), 0.f, matC.get(i)); 225 mBLAS.BNNM(matA.get(i), a_offset, matB.get(i), b_offset, matC.get(i), c_offset, c_mult_int);
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/external/neven/Embedded/common/src/b_TensorEm/ |
Int32Mat.h | 106 * matA: the square matrix, array of size ( matWidthA * matWidthA ) 111 * tmpMatA: matrix of same size as matA 115 const int32* matA, 123 /** same as _solve(), but matA gets overwritten, and tmpMatA is not needed: 124 * saves memory when matA is large; 129 int32* matA,
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Int32Mat.c | 210 const int32* matA, 218 bbs_memcpy32( tmpMatA, matA, ( matWidthA * matWidthA ) * bbs_SIZEOF32( int32 ) ); 232 int32* matA, 246 int32* matL = matA;
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/frameworks/base/graphics/java/android/graphics/ |
ColorMatrix.java | 176 * as applying matB and then applying matA. 178 * It is legal for either matA or matB to be the same colormatrix as this. 181 public void setConcat(ColorMatrix matA, ColorMatrix matB) { 183 if (matA == this || matB == this) { 189 final float[] a = matA.mArray;
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/cts/tests/tests/rsblas/src/android/renderscript/cts/ |
IntrinsicBLAS.java | 239 for (Allocation matA : mMatrix) { 248 Element elemA = matA.getType().getElement(); 249 if (validateGEMV(elemA, trans, matA, vecX, incX, vecY, incY)) { 252 mBLAS.SGEMV(trans, alphaS, matA, vecX, incX, betaS, vecY, incY); 254 mBLAS.DGEMV(trans, alphaD, matA, vecX, incX, betaD, vecY, incY); 256 mBLAS.CGEMV(trans, alphaC, matA, vecX, incX, betaC, vecY, incY); 258 mBLAS.ZGEMV(trans, alphaZ, matA, vecX, incX, betaZ, vecY, incY); 265 mBLAS.SGEMV(trans, alphaS, matA, vecX, incX, betaS, vecY, incY); 270 mBLAS.DGEMV(trans, alphaD, matA, vecX, incX, betaD, vecY, incY); 275 mBLAS.CGEMV(trans, alphaC, matA, vecX, incX, betaC, vecY, incY) [all...] |
/external/opencv/cv/src/ |
cvcornersubpix.cpp | 233 CvMat matA, matInvA; 239 cvInitMatHeader( &matA, 2, 2, CV_64F, A ); 242 cvInvert( &matA, &matInvA, CV_SVD );
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/external/skia/src/effects/ |
SkColorMatrix.cpp | 132 void SkColorMatrix::setConcat(const SkColorMatrix& matA, const SkColorMatrix& matB) { 133 SetConcat(fMat, matA.fMat, matB.fMat);
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/external/eigen/test/ |
cholesky.cpp | 353 MatrixType matA; 354 matA << 1, 1, 1, 1; 357 VectorType vecX = matA.ldlt().solve(vecB); 358 VERIFY_IS_APPROX(matA * vecX, vecB);
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/external/eigen/blas/ |
level3_impl.h | 322 Matrix<Scalar,Dynamic,Dynamic,ColMajor> matA(size,size); 325 matA.triangularView<Upper>() = matrix(a,size,size,*lda); 326 matA.triangularView<Lower>() = matrix(a,size,size,*lda).transpose(); 330 matA.triangularView<Lower>() = matrix(a,size,size,*lda); 331 matA.triangularView<Upper>() = matrix(a,size,size,*lda).transpose(); 334 matrix(c, *m, *n, *ldc) += alpha * matA * matrix(b, *m, *n, *ldb); 336 matrix(c, *m, *n, *ldc) += alpha * matrix(b, *m, *n, *ldb) * matA; [all...] |
/external/opencv/cvaux/src/ |
cvepilines.cpp | [all...] |
/external/robolectric/v1/lib/main/ |
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/prebuilts/sdk/15/ |
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/prebuilts/sdk/17/ |
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