本文整理汇总了C++中BigMatrix::block方法的典型用法代码示例。如果您正苦于以下问题：C++ BigMatrix::block方法的具体用法？C++ BigMatrix::block怎么用？C++ BigMatrix::block使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类BigMatrix的用法示例。
在下文中一共展示了BigMatrix::block方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: diagonalmatrices
template<typename MatrixType> void diagonalmatrices(const MatrixType& m)
{
typedef typename MatrixType::Index Index;
typedef typename MatrixType::Scalar Scalar;
enum { Rows = MatrixType::RowsAtCompileTime, Cols = MatrixType::ColsAtCompileTime };
typedef Matrix<Scalar, Rows, 1> VectorType;
typedef Matrix<Scalar, 1, Cols> RowVectorType;
typedef Matrix<Scalar, Rows, Rows> SquareMatrixType;
typedef DiagonalMatrix<Scalar, Rows> LeftDiagonalMatrix;
typedef DiagonalMatrix<Scalar, Cols> RightDiagonalMatrix;
typedef Matrix<Scalar, Rows==Dynamic?Dynamic:2*Rows, Cols==Dynamic?Dynamic:2*Cols> BigMatrix;
Index rows = m.rows();
Index cols = m.cols();
MatrixType m1 = MatrixType::Random(rows, cols),
m2 = MatrixType::Random(rows, cols);
VectorType v1 = VectorType::Random(rows),
v2 = VectorType::Random(rows);
RowVectorType rv1 = RowVectorType::Random(cols),
rv2 = RowVectorType::Random(cols);
LeftDiagonalMatrix ldm1(v1), ldm2(v2);
RightDiagonalMatrix rdm1(rv1), rdm2(rv2);
Scalar s1 = internal::random<Scalar>();
SquareMatrixType sq_m1 (v1.asDiagonal());
VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix());
sq_m1 = v1.asDiagonal();
VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix());
SquareMatrixType sq_m2 = v1.asDiagonal();
VERIFY_IS_APPROX(sq_m1, sq_m2);
ldm1 = v1.asDiagonal();
LeftDiagonalMatrix ldm3(v1);
VERIFY_IS_APPROX(ldm1.diagonal(), ldm3.diagonal());
LeftDiagonalMatrix ldm4 = v1.asDiagonal();
VERIFY_IS_APPROX(ldm1.diagonal(), ldm4.diagonal());
sq_m1.block(0,0,rows,rows) = ldm1;
VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix());
sq_m1.transpose() = ldm1;
VERIFY_IS_APPROX(sq_m1, ldm1.toDenseMatrix());
Index i = internal::random<Index>(0, rows-1);
Index j = internal::random<Index>(0, cols-1);
VERIFY_IS_APPROX( ((ldm1 * m1)(i,j)) , ldm1.diagonal()(i) * m1(i,j) );
VERIFY_IS_APPROX( ((ldm1 * (m1+m2))(i,j)) , ldm1.diagonal()(i) * (m1+m2)(i,j) );
VERIFY_IS_APPROX( ((m1 * rdm1)(i,j)) , rdm1.diagonal()(j) * m1(i,j) );
VERIFY_IS_APPROX( ((v1.asDiagonal() * m1)(i,j)) , v1(i) * m1(i,j) );
VERIFY_IS_APPROX( ((m1 * rv1.asDiagonal())(i,j)) , rv1(j) * m1(i,j) );
VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * m1)(i,j)) , (v1+v2)(i) * m1(i,j) );
VERIFY_IS_APPROX( (((v1+v2).asDiagonal() * (m1+m2))(i,j)) , (v1+v2)(i) * (m1+m2)(i,j) );
VERIFY_IS_APPROX( ((m1 * (rv1+rv2).asDiagonal())(i,j)) , (rv1+rv2)(j) * m1(i,j) );
VERIFY_IS_APPROX( (((m1+m2) * (rv1+rv2).asDiagonal())(i,j)) , (rv1+rv2)(j) * (m1+m2)(i,j) );
BigMatrix big;
big.setZero(2*rows, 2*cols);
big.block(i,j,rows,cols) = m1;
big.block(i,j,rows,cols) = v1.asDiagonal() * big.block(i,j,rows,cols);
VERIFY_IS_APPROX((big.block(i,j,rows,cols)) , v1.asDiagonal() * m1 );
big.block(i,j,rows,cols) = m1;
big.block(i,j,rows,cols) = big.block(i,j,rows,cols) * rv1.asDiagonal();
VERIFY_IS_APPROX((big.block(i,j,rows,cols)) , m1 * rv1.asDiagonal() );
// scalar multiple
VERIFY_IS_APPROX(LeftDiagonalMatrix(ldm1*s1).diagonal(), ldm1.diagonal() * s1);
VERIFY_IS_APPROX(LeftDiagonalMatrix(s1*ldm1).diagonal(), s1 * ldm1.diagonal());
VERIFY_IS_APPROX(m1 * (rdm1 * s1), (m1 * rdm1) * s1);
VERIFY_IS_APPROX(m1 * (s1 * rdm1), (m1 * rdm1) * s1);
// Diagonal to dense
sq_m1.setRandom();
sq_m2 = sq_m1;
VERIFY_IS_APPROX( (sq_m1 += (s1*v1).asDiagonal()), sq_m2 += (s1*v1).asDiagonal().toDenseMatrix() );
VERIFY_IS_APPROX( (sq_m1 -= (s1*v1).asDiagonal()), sq_m2 -= (s1*v1).asDiagonal().toDenseMatrix() );
VERIFY_IS_APPROX( (sq_m1 = (s1*v1).asDiagonal()), (s1*v1).asDiagonal().toDenseMatrix() );
}