| /external/eigen/test/ |
| conservative_resize.cpp | 40 const Index rows = internal::random<Index>(1,50); local
43 m.conservativeResize(rows,cols);
44 VERIFY_IS_APPROX(m, n.block(0,0,rows,cols));
50 const Index rows = internal::random<Index>(50,75); local
53 m.conservativeResizeLike(MatrixType::Zero(rows,cols));
54 VERIFY_IS_APPROX(m.block(0,0,n.rows(),n.cols()), n);
55 VERIFY( rows<=50 || m.block(50,0,rows-50,cols).sum() == Scalar(0) );
56 VERIFY( cols<=50 || m.block(0,50,rows,cols-50).sum() == Scalar(0) );
77 m.conservativeResize(m.rows(),1)
[all...] |
| corners.cpp | 19 Index rows = m.rows(); local
22 Index r = internal::random<Index>(1,rows);
25 MatrixType matrix = MatrixType::Random(rows,cols);
26 const MatrixType const_matrix = MatrixType::Random(rows,cols);
30 COMPARE_CORNER(bottomLeftCorner(r,c), block(rows-r,0,r,c));
31 COMPARE_CORNER(bottomRightCorner(r,c), block(rows-r,cols-c,r,c));
33 Index sr = internal::random<Index>(1,rows) - 1;
34 Index nr = internal::random<Index>(1,rows-sr);
40 COMPARE_CORNER(bottomRows(r), block(rows-r,0,r,cols))
52 rows = MatrixType::RowsAtCompileTime, enumerator in enum:__anon12060
[all...] |
| dontalign.cpp | 27 Index rows = m.rows(); local
30 MatrixType a = MatrixType::Random(rows,cols);
31 SquareMatrixType square = SquareMatrixType::Random(rows,rows);
32 VectorType v = VectorType::Random(rows);
43 Scalar* array = internal::aligned_new<Scalar>(rows);
44 v = VectorType::MapAligned(array, rows);
45 internal::aligned_delete(array, rows);
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| eigen2support.cpp | 20 Index rows = m.rows(); local
23 MatrixType m1 = MatrixType::Random(rows, cols),
24 m3(rows, cols);
31 VERIFY_IS_APPROX(m1.cwise() + s1, MatrixType::Constant(rows,cols,s1) + m1);
32 VERIFY_IS_APPROX((m1*Scalar(2)).cwise() - s2, (m1+m1) - MatrixType::Constant(rows,cols,s2) );
44 VERIFY_IS_EQUAL((m1.col(0).end(1)), (m1.col(0).segment(rows-1,1)));
45 VERIFY_IS_EQUAL((m1.col(0).template end<1>()), (m1.col(0).segment(rows-1,1)));
|
| eigensolver_complex.cpp | 17 by checking that the k-th power sums are equal for k = 1, ..., vec1.rows() */
25 VERIFY(vec1.rows() == vec2.rows());
26 for (int k = 1; k <= vec1.rows(); ++k)
39 Index rows = m.rows(); local
45 MatrixType a = MatrixType::Random(rows,cols);
60 ei2.setMaxIterations(ComplexSchur<MatrixType>::m_maxIterationsPerRow * rows).compute(a);
64 if (rows > 2) {
75 MatrixType z = MatrixType::Zero(rows,cols)
[all...] |
| eigensolver_generalized_real.cpp | 20 Index rows = m.rows(); local
26 MatrixType a = MatrixType::Random(rows,cols);
27 MatrixType b = MatrixType::Random(rows,cols);
28 MatrixType a1 = MatrixType::Random(rows,cols);
29 MatrixType b1 = MatrixType::Random(rows,cols);
|
| inverse.cpp | 21 Index rows = m.rows(); local
26 MatrixType m1(rows, cols),
27 m2(rows, cols),
28 identity = MatrixType::Identity(rows, rows);
29 createRandomPIMatrixOfRank(rows,rows,rows,m1);
64 VectorType v3 = VectorType::Random(rows);
[all...] |
| jacobi.cpp | 18 Index rows = m.rows(); local
28 const MatrixType a(MatrixType::Random(rows, cols));
35 Index p = internal::random<Index>(0, rows-1);
38 q = internal::random<Index>(0, rows-1);
|
| linearstructure.cpp | 21 Index rows = m.rows(); local
26 MatrixType m1 = MatrixType::Random(rows, cols),
27 m2 = MatrixType::Random(rows, cols),
28 m3(rows, cols);
33 Index r = internal::random<Index>(0, rows-1),
65 VERIFY_IS_APPROX(m1+m1.block(0,0,rows,cols), m1+m1);
66 VERIFY_IS_APPROX(m1.cwiseProduct(m1.block(0,0,rows,cols)), m1.cwiseProduct(m1));
67 VERIFY_IS_APPROX(m1 - m1.block(0,0,rows,cols), m1 - m1);
68 VERIFY_IS_APPROX(m1.block(0,0,rows,cols) * s1, m1 * s1)
[all...] |
| mapstaticmethods.cpp | 72 int rows = m.rows(), cols = m.cols(); local
76 PlainObjectType::Map(ptr, rows, cols).setZero();
77 PlainObjectType::MapAligned(ptr, rows, cols).setZero();
78 PlainObjectType::Map(const_ptr, rows, cols).sum();
79 PlainObjectType::MapAligned(const_ptr, rows, cols).sum();
81 PlainObjectType::Map(ptr, rows, cols, InnerStride<>(i)).setZero();
82 PlainObjectType::MapAligned(ptr, rows, cols, InnerStride<>(i)).setZero();
83 PlainObjectType::Map(const_ptr, rows, cols, InnerStride<>(i)).sum();
84 PlainObjectType::MapAligned(const_ptr, rows, cols, InnerStride<>(i)).sum()
[all...] |
| mapstride.cpp | 56 Index rows = _m.rows(), cols = _m.cols(); local
58 MatrixType m = MatrixType::Random(rows,cols);
60 Index arraysize = 2*(rows+4)*(cols+4);
69 Map<MatrixType, Alignment, OuterStride<Dynamic> > map(array, rows, cols, OuterStride<Dynamic>(m.innerSize()+1));
88 map(array, rows, cols, OuterStride<OuterStrideAtCompileTime>(m.innerSize()+4));
101 Map<MatrixType, Alignment, Stride<Dynamic,Dynamic> > map(array, rows, cols, Stride<Dynamic,Dynamic>(2*m.innerSize()+1, 2));
|
| miscmatrices.cpp | 20 Index rows = m.rows(); local
23 Index r = internal::random<Index>(0, rows-1), r2 = internal::random<Index>(0, rows-1), c = internal::random<Index>(0, cols-1);
24 VERIFY_IS_APPROX(MatrixType::Ones(rows,cols)(r,c), static_cast<Scalar>(1));
25 MatrixType m1 = MatrixType::Ones(rows,cols);
27 VectorType v1 = VectorType::Random(rows);
33 square = MatrixType::Zero(rows, rows);
34 square.diagonal() = VectorType::Ones(rows);
[all...] |
| product_trmv.cpp | 21 Index rows = m.rows(); local
24 MatrixType m1 = MatrixType::Random(rows, cols),
25 m3(rows, cols);
26 VectorType v1 = VectorType::Random(rows);
30 m1 = MatrixType::Random(rows, cols);
|
| qtvector.cpp | 23 Index rows = m.rows(); local
25 MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols);
26 QVector<MatrixType> v(10, MatrixType(rows,cols)), w(20, y);
|
| /external/eigen/test/eigen2/ |
| eigen2_basicstuff.cpp | 17 int rows = m.rows(); local
22 MatrixType m1 = MatrixType::Random(rows, cols),
23 m2 = MatrixType::Random(rows, cols),
24 m3(rows, cols),
25 mzero = MatrixType::Zero(rows, cols),
26 square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>::Random(rows, rows);
27 VectorType v1 = VectorType::Random(rows),
28 vzero = VectorType::Zero(rows);
[all...] |
| eigen2_linearstructure.cpp | 21 int rows = m.rows(); local
26 MatrixType m1 = MatrixType::Random(rows, cols),
27 m2 = MatrixType::Random(rows, cols),
28 m3(rows, cols);
33 int r = ei_random<int>(0, rows-1),
65 VERIFY_IS_APPROX(m1+m1.block(0,0,rows,cols), m1+m1);
66 VERIFY_IS_APPROX(m1.cwise() * m1.block(0,0,rows,cols), m1.cwise() * m1);
67 VERIFY_IS_APPROX(m1 - m1.block(0,0,rows,cols), m1 - m1);
68 VERIFY_IS_APPROX(m1.block(0,0,rows,cols) * s1, m1 * s1)
[all...] |
| eigen2_map.cpp | 42 int rows = m.rows(), cols = m.cols(), size = rows*cols; local
52 Map<MatrixType, Aligned>(array1, rows, cols) = MatrixType::Ones(rows,cols);
53 Map<MatrixType>(array2, rows, cols) = Map<MatrixType>((const Scalar*)array1, rows, cols); // test non-const-correctness support in eigen2
54 Map<MatrixType>(array3unaligned, rows, cols) = Map<MatrixType>(array1, rows, cols);
55 MatrixType ma1 = Map<MatrixType>(array1, rows, cols)
[all...] |
| eigen2_miscmatrices.cpp | 21 int rows = m.rows(); local
24 int r = ei_random<int>(0, rows-1), r2 = ei_random<int>(0, rows-1), c = ei_random<int>(0, cols-1);
25 VERIFY_IS_APPROX(MatrixType::Ones(rows,cols)(r,c), static_cast<Scalar>(1));
26 MatrixType m1 = MatrixType::Ones(rows,cols);
28 VectorType v1 = VectorType::Random(rows);
34 square = MatrixType::Zero(rows, rows);
35 square.diagonal() = VectorType::Ones(rows);
[all...] |
| eigen2_newstdvector.cpp | 18 int rows = m.rows(); local
20 MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols);
21 std::vector<MatrixType,Eigen::aligned_allocator<MatrixType> > v(10, MatrixType(rows,cols)), w(20, y);
|
| eigen2_nomalloc.cpp | 29 int rows = m.rows(); local
32 MatrixType m1 = MatrixType::Random(rows, cols),
33 m2 = MatrixType::Random(rows, cols);
37 int r = ei_random<int>(0, rows-1),
42 VERIFY_IS_APPROX(m1.cwise() * m1.block(0,0,rows,cols), m1.cwise() * m1);
|
| eigen2_qtvector.cpp | 23 int rows = m.rows(); local
25 MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols);
26 QVector<MatrixType> v(10, MatrixType(rows,cols)), w(20, y);
|
| eigen2_stdvector.cpp | 17 int rows = m.rows(); local
19 MatrixType x = MatrixType::Random(rows,cols), y = MatrixType::Random(rows,cols);
20 std::vector<MatrixType, aligned_allocator<MatrixType> > v(10, MatrixType(rows,cols)), w(20, y);
|
| eigen2_sum.cpp | 16 int rows = m.rows(); local
19 MatrixType m1 = MatrixType::Random(rows, cols);
21 VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows, cols).sum(), Scalar(1));
22 VERIFY_IS_APPROX(MatrixType::Ones(rows, cols).sum(), Scalar(float(rows*cols))); // the float() here to shut up excessive MSVC warning about int->complex conversion being lossy
24 for(int i = 0; i < rows; i++) for(int j = 0; j < cols; j++) x += m1(i,j);
|
| eigen2_svd.cpp | 18 int rows = m.rows(); local
23 MatrixType a = MatrixType::Random(rows,cols);
25 Matrix<Scalar, MatrixType::RowsAtCompileTime, 1>::Random(rows,1);
34 MatrixType sigma = MatrixType::Zero(rows,cols);
35 MatrixType matU = MatrixType::Zero(rows,rows);
37 matU.block(0,0,rows,cols) = svd.matrixU();
42 if (rows==cols)
46 MatrixType a1 = MatrixType::Random(rows,cols)
[all...] |
| eigen2_swap.cpp | 31 int rows = m.rows(); local
35 MatrixType m1 = MatrixType::Random(rows,cols);
36 MatrixType m2 = MatrixType::Random(rows,cols) + Scalar(100) * MatrixType::Identity(rows,cols);
37 OtherMatrixType m3 = OtherMatrixType::Random(rows,cols) + Scalar(200) * OtherMatrixType::Identity(rows,cols);
58 m1.swap(m2.block(0,0,rows,cols));
|
