| /external/eigen/unsupported/test/ |
| cxx11_tensor_contraction.cpp | 22 Tensor<float, 2, DataLayout> mat1(2, 3);
26 mat1.setRandom();
33 typedef TensorEvaluator<decltype(mat1.contract(mat2, dims3)), DefaultDevice> Evaluator;
34 Evaluator eval(mat1.contract(mat2, dims3), DefaultDevice());
40 VERIFY_IS_APPROX(mat4(0,0), mat1(0,0)*mat2(0,0) + mat1(1,0)*mat2(1,0));
41 VERIFY_IS_APPROX(mat4(0,1), mat1(0,0)*mat2(0,1) + mat1(1,0)*mat2(1,1));
42 VERIFY_IS_APPROX(mat4(0,2), mat1(0,0)*mat2(0,2) + mat1(1,0)*mat2(1,2))
[all...] |
| cxx11_tensor_comparisons.cpp | 19 Tensor<float, 3> mat1(2,3,7);
26 mat1.setRandom();
29 lt = mat1 < mat2;
30 le = mat1 <= mat2;
31 gt = mat1 > mat2;
32 ge = mat1 >= mat2;
37 VERIFY_IS_EQUAL(lt(i,j,k), mat1(i,j,k) < mat2(i,j,k));
38 VERIFY_IS_EQUAL(le(i,j,k), mat1(i,j,k) <= mat2(i,j,k));
39 VERIFY_IS_EQUAL(gt(i,j,k), mat1(i,j,k) > mat2(i,j,k));
40 VERIFY_IS_EQUAL(ge(i,j,k), mat1(i,j,k) >= mat2(i,j,k))
[all...] |
| cxx11_tensor_lvalue.cpp | 20 Tensor<float, 3> mat1(2,3,7);
24 mat1.setRandom();
26 mat3 = mat1;
32 VERIFY_IS_APPROX(mat3(i,j,k), mat1(i,j,k) + mat2(i,j,k));
|
| cxx11_tensor_of_const_values.cpp | 20 TensorMap<Tensor<const float, 2>> mat1(data1, 2, 3);
30 rslt1 = mat1;
34 Tensor<float, 2> rslt3 = mat1;
37 Tensor<float, 2> rslt5(mat1);
56 TensorMap<Tensor<const float, 2>> mat1(data1, 2, 3);
66 sum1 = mat1 + mat2;
68 sum2 = mat2 + mat1;
82 TensorMap<Tensor<const float, 2>> mat1(data1, 2, 3);
90 mat2 += mat1;
|
| cxx11_tensor_expr.cpp | 72 TensorMap<Tensor<float, 2>> mat1(data1, 2, 3);
76 mat1(0,0) = 0.0;
77 mat1(0,1) = 1.0;
78 mat1(0,2) = 2.0;
79 mat1(1,0) = 3.0;
80 mat1(1,1) = 4.0;
81 mat1(1,2) = 5.0;
92 mat3 = mat1.abs();
112 Tensor<float, 3> mat1(2,3,7);
119 mat1(i,j,k) = val
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| cxx11_tensor_fixed_size.cpp | 133 TensorMap<TensorFixedSize<float, Sizes<2, 3> > > mat1(data1,2,3);
137 VERIFY_IS_EQUAL((mat1.size()), 2*3);
138 VERIFY_IS_EQUAL(mat1.rank(), 2);
139 // VERIFY_IS_EQUAL((mat1.dimension(0)), 2);
140 // VERIFY_IS_EQUAL((mat1.dimension(1)), 3);
142 mat1(0,0) = 0.0;
143 mat1(0,1) = 1.0;
144 mat1(0,2) = 2.0;
145 mat1(1,0) = 3.0;
146 mat1(1,1) = 4.0
182 TensorFixedSize<float, Sizes<2, 3, 7> > mat1; local
228 TensorFixedSize<float, Sizes<2, 3, 7> > mat1; local
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| cxx11_tensor_assign.cpp | 74 Tensor<int, 2> mat1(2,3);
77 mat1(0,0) = 0;
78 mat1(0,1) = 1;
79 mat1(0,2) = 2;
80 mat1(1,0) = 3;
81 mat1(1,1) = 4;
82 mat1(1,2) = 5;
98 mat3 = mat1;
115 mat1.setZero();
117 mat1 = mat3
[all...] |
| cxx11_tensor_map.cpp | 71 Tensor<int, 2> mat1(2,3);
74 mat1(0,0) = 0;
75 mat1(0,1) = 1;
76 mat1(0,2) = 2;
77 mat1(1,0) = 3;
78 mat1(1,1) = 4;
79 mat1(1,2) = 5;
88 TensorMap<Tensor<const int, 2> > mat3(mat1.data(), 2, 3);
118 Tensor<int, 3> mat1(2,3,7);
125 mat1(i,j,k) = val
[all...] |
| cxx11_tensor_simple.cpp | 115 Tensor<int, 2> mat1(2,3);
118 mat1(0,0) = 0;
119 mat1(0,1) = 1;
120 mat1(0,2) = 2;
121 mat1(1,0) = 3;
122 mat1(1,1) = 4;
123 mat1(1,2) = 5;
132 VERIFY_IS_EQUAL((mat1.rank()), 2);
133 VERIFY_IS_EQUAL((mat1.size()), 6);
134 VERIFY_IS_EQUAL((mat1.dimensions()[0]), 2)
[all...] |
| cxx11_tensor_forced_eval.cpp | 25 TensorMap<Tensor<float, 2> > mat1(m1.data(), 3,3);
29 mat3 = mat1;
|
| cxx11_tensor_of_strings.cpp | 20 TensorMap<Tensor<std::string, 2>> mat1(data1, 2, 3);
34 rslt1 = mat1;
38 Tensor<std::string, 2> rslt3 = mat1;
41 Tensor<std::string, 2> rslt5(mat1);
|
| /external/vixl/examples/aarch64/ |
| neon-matrix-multiply.cc | 60 // mat1 -> x1
114 float mat1[kLength], mat2[kLength], output[kLength]; local
121 // float mat1[kLength] = { 1.0f, 52.03f, 4.43f, ... };
124 mat1[0] = 1.0f;
125 mat1[4] = 2.0f;
126 mat1[8] = 3.0f;
127 mat1[12] = 4.0f;
128 mat1[1] = 52.03f;
129 mat1[5] = 12.24f;
130 mat1[9] = 53.56f
[all...] |
| /external/eigen/doc/snippets/ |
| Tutorial_AdvancedInitialization_ThreeWays.cpp | 2 MatrixXd mat1(size, size);
3 mat1.topLeftCorner(size/2, size/2) = MatrixXd::Zero(size/2, size/2);
4 mat1.topRightCorner(size/2, size/2) = MatrixXd::Identity(size/2, size/2);
5 mat1.bottomLeftCorner(size/2, size/2) = MatrixXd::Identity(size/2, size/2);
6 mat1.bottomRightCorner(size/2, size/2) = MatrixXd::Zero(size/2, size/2);
7 std::cout << mat1 << std::endl << std::endl;
|
| /external/eigen/test/ |
| evaluators.cpp | 244 MatrixXd mat1(6,6), mat2(6,6);
245 VERIFY_IS_APPROX_EVALUATOR(mat1, MatrixXd::Identity(6,6));
246 VERIFY_IS_APPROX_EVALUATOR(mat2, mat1);
247 copy_using_evaluator(mat2.transpose(), mat1);
248 VERIFY_IS_APPROX(mat2.transpose(), mat1);
256 VERIFY_IS_APPROX_EVALUATOR(mat2, mat1);
326 mat1.setRandom();
329 copy_using_evaluator(matXcd.real(), mat1);
331 matXcd_ref.real() = mat1;
349 VERIFY_IS_APPROX_EVALUATOR(vec1, mat1.rowwise().sum())
392 MatrixXd mat1, mat2, mat1ref, mat2ref; local
[all...] |
| product_large.cpp | 79 MatrixXf mat1(10,32); mat1.setRandom();
81 MatrixXf r1 = mat1.row(2)*mat2.transpose();
82 VERIFY_IS_APPROX(r1, (mat1.row(2)*mat2.transpose()).eval());
84 MatrixXf r2 = mat1.row(2)*mat2;
85 VERIFY_IS_APPROX(r2, (mat1.row(2)*mat2).eval());
|
| ref.cpp | 100 MatrixType mat1 = MatrixType::Random(size,size), local
101 mat2 = mat1,
132 RefMatWithStride rm5 = mat1.row(i).transpose();
133 VERIFY_IS_EQUAL(rm5, mat1.row(i).transpose());
136 VERIFY_IS_EQUAL(mat1, mat2);
139 VERIFY_IS_APPROX(mat1, mat2);
|
| /external/vixl/test/aarch64/examples/ |
| test-examples.cc | 252 float mat1[kLength], mat2[kLength], expected[kLength], output[kLength]; local
256 mat1[0] = 1.0f;
257 mat1[4] = 2.0f;
258 mat1[8] = 3.0f;
259 mat1[12] = 4.0f;
260 mat1[1] = 52.03f;
261 mat1[5] = 12.24f;
262 mat1[9] = 53.56f;
263 mat1[13] = 22.22f;
264 mat1[2] = 4.43f
[all...] |
| /external/autotest/client/site_tests/graphics_SanAngeles/src/ |
| matrixop.h | 14 // result = mat1 * mat2
16 Matrix4x4 mat1, Matrix4x4 mat2);
|
| matrixop.c | 20 void Matrix4x4_Multiply(Matrix4x4 result, Matrix4x4 mat1, Matrix4x4 mat2)
29 tmp[i*4 + j] += mat1[i*4 + k] * mat2[k*4 + j];
|
| /external/opencv/cxcore/src/ |
| cxnorm.cpp | 979 CvMat stub1, *mat1 = (CvMat*)imgB; local
[all...] |
| /external/opencv/cv/src/ |
| cvaccum.cpp | 594 CvMat stub1, *mat1 = (CvMat*)arrA; local
605 CV_CALL( mat1 = cvGetMat( mat1, &stub1, &coi1 ));
612 if( !CV_ARE_CNS_EQ( mat1, mat2 ) || !CV_ARE_CNS_EQ( mat1, sum ))
618 if( !CV_ARE_SIZES_EQ( mat1, sum ) || !CV_ARE_SIZES_EQ( mat2, sum ))
621 size = cvGetMatSize( mat1 );
622 type = CV_MAT_TYPE( mat1->type );
624 mat1_step = mat1->step;
637 if( CV_IS_MAT_CONT( mat1->type & mat2->type & sum->type )
[all...] |
| /external/eigen/Eigen/src/IterativeLinearSolvers/ |
| IncompleteLUT.h | 230 SparseMatrix<Scalar,ColMajor, StorageIndex> mat1 = amat; local
232 // FIXME for a matrix with nearly symmetric pattern, mat2+mat1 is the appropriate choice.
233 // on the other hand for a really non-symmetric pattern, mat2*mat1 should be prefered...
234 SparseMatrix<Scalar,ColMajor, StorageIndex> AtA = mat2 + mat1;
240 SparseMatrix<Scalar,ColMajor, StorageIndex> mat1 = amat;
242 ordering(mat1,m_Pinv);
|
| /prebuilts/gcc/linux-x86/host/x86_64-linux-glibc2.11-4.8/include/isl/ |
| mat.h | 56 __isl_give isl_mat *isl_mat_diagonal(__isl_take isl_mat *mat1,
105 int isl_mat_is_equal(__isl_keep isl_mat *mat1, __isl_keep isl_mat *mat2);
|
| /prebuilts/gcc/linux-x86/host/x86_64-linux-glibc2.15-4.8/include/isl/ |
| mat.h | 56 __isl_give isl_mat *isl_mat_diagonal(__isl_take isl_mat *mat1,
105 int isl_mat_is_equal(__isl_keep isl_mat *mat1, __isl_keep isl_mat *mat2);
|
| /external/opencv/cxcore/include/ |
| cxtypes.h | 593 #define CV_ARE_TYPES_EQ(mat1, mat2) \
594 ((((mat1)->type ^ (mat2)->type) & CV_MAT_TYPE_MASK) == 0)
596 #define CV_ARE_CNS_EQ(mat1, mat2) \
597 ((((mat1)->type ^ (mat2)->type) & CV_MAT_CN_MASK) == 0)
599 #define CV_ARE_DEPTHS_EQ(mat1, mat2) \
600 ((((mat1)->type ^ (mat2)->type) & CV_MAT_DEPTH_MASK) == 0)
602 #define CV_ARE_SIZES_EQ(mat1, mat2) \
603 ((mat1)->rows == (mat2)->rows && (mat1)->cols == (mat2)->cols)
[all...] |
