C++_Eigen函数库用法笔记——Matrix and Vector Arithmetic

时间：2016-03-09 20:56:45 阅读：425 评论：0 收藏：0 [点我收藏+]

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Addition and subtraction

Scalar multiplication and division
Transposition

Matrix-matrix and matrix-vector multiplication

Trace(求迹的和)

Addition and subtraction
- binary operator + as in a+b
- binary operator - as in a-b
- unary operator - as in -a
- compound operator += as in a+=b
- compound operator -= as in a-=b
  #include <iostream>
  
  #include <Eigen/Dense>
  
  using namespace Eigen;
  
  int main()
  
  {
  
  Matrix2d a;
  
  a << 1, 2,
  
  3, 4;
  
  MatrixXd b(2,2);
  
  b << 2, 3,
  
  1, 4;
  
  std::cout << "a + b =\n" << a + b << std::endl;
  
  std::cout << "a - b =\n" << a - b << std::endl;
  
  std::cout << "Doing a += b;" << std::endl;
  
  a += b;
  
  std::cout << "Now a =\n" << a << std::endl;
  
  Vector3d v(1,2,3);
  
  Vector3d w(1,0,0);
  
  std::cout << "-v + w - v =\n" << -v + w - v << std::endl;
  
  }
  a + b =
  3 5
  4 8
  a - b =
  -1 -1
  2 0
  Doing a += b;
  Now a =
  3 5
  4 8
  -v + w - v =
  -1
  -4
  -6
Scalar multiplication and division
- binary operator * as in matrix*scalar
- binary operator * as in scalar*matrix
- binary operator / as in matrix/scalar
- compound operator *= as in matrix*=scalar
- compound operator /= as in matrix/=scalar
  
  #include <iostream>
  
  #include <Eigen/Dense>
  
  using namespace Eigen;
  
  int main()
  
  {
  
  Matrix2d a;
  
  a << 1, 2,
  
  3, 4;
  
  Vector3d v(1,2,3);
  
  std::cout << "a * 2.5 =\n" << a * 2.5 << std::endl;
  
  std::cout << "0.1 * v =\n" << 0.1 * v << std::endl;
  
  std::cout << "Doing v *= 2;" << std::endl;
  
  v *= 2;
  
  std::cout << "Now v =\n" << v << std::endl;
  
  }
  a * 2.5 =
  2.5 5
  7.5 10
  0.1 * v =
  0.1
  0.2
  0.3
  Doing v *= 2;
  Now v =
  2
  4
  6
Transposition

MatrixXcf a = MatrixXcf::Random(2,2);

cout << "Here is the matrix a\n" << a << endl;

cout << "Here is the matrix a^T\n" << a.transpose() << endl;
Here is the matrix a
(-0.211,0.68) (-0.605,0.823)
(0.597,0.566) (0.536,-0.33)
Here is the matrix a^T
(-0.211,0.68) (0.597,0.566)
(-0.605,0.823) (0.536,-0.33)

the instruction a = a.transpose() does not replace a with its transpose

For in-place transposition,simply use the transposeInPlace()

MatrixXf a(2,3); a << 1, 2, 3, 4, 5, 6;

cout << "Here is the initial matrix a:\n" << a << endl;

a.transposeInPlace();

cout << "and after being transposed:\n" << a << endl;

Matrix-matrix and matrix-vector multiplication
- binary operator * as in a*b
- compound operator *= as in a*=b (this multiplies on the right: a*=b is equivalent to a = a*b
  #include <iostream>
  
  #include <Eigen/Dense>
  
  using namespace Eigen;
  
  int main()
  
  {
  
  Matrix2d mat;
  
  mat << 1, 2,
  
  3, 4;
  
  Vector2d u(-1,1), v(2,0);
  
  std::cout << "Here is mat*mat:\n" << mat*mat << std::endl;
  
  std::cout << "Here is mat*u:\n" << mat*u << std::endl;
  
  std::cout << "Here is u^T*mat:\n" << u.transpose()*mat << std::endl;
  
  std::cout << "Here is u^T*v:\n" << u.transpose()*v << std::endl;
  
  std::cout << "Here is u*v^T:\n" << u*v.transpose() << std::endl;
  
  std::cout << "Let‘s multiply mat by itself" << std::endl;
  
  mat = mat*mat;
  
  std::cout << "Now mat is mat:\n" << mat << std::endl;
  
  }
  Here is mat*mat:
  7 10
  15 22
  Here is mat*u:
  1
  1
  Here is u^T*mat:
  2 2
  Here is u^T*v:
  -2
  Here is u*v^T:
  -2 -0
  2 0
  Let‘s multiply mat by itself
  Now mat is mat:
  7 10
  15 22

Trace(求迹的和)

#include <iostream>

#include <Eigen/Dense>

using namespace std;

int main()

{

Eigen::Matrix2d mat;

mat << 1, 2,

3, 4;
cout << "Here is mat.trace(): " << mat.trace() << endl;

}
Here is mat.trace(): 5

C++_Eigen函数库用法笔记——Matrix and Vector Arithmetic

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原文地址：http://www.cnblogs.com/ymxiansen/p/5259554.html

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