C++矩阵库Eigen的仿Matlab矩阵运算

与其他矩阵库相比，Eigen（Visit）相比，Eigen只需要拷贝所有include文件到指定位置，无需编译即可使用;此外，用法上模仿Matlab矩阵操作;

上述特点，使其具有很好的实用性。

附上测试代码，以便学习和使用。

//http://eigen.tuxfamily.org/dox/group__QuickRefPage.html#include <iostream>#include <Eigen/Dense>using namespace std;using namespace Eigen;typedef Matrix<float, 1, 3> RVector;int main(){int cnt = 0;//定义一个矩阵并赋值MatrixXd m(2,2);m(0,0) = 3;m(1,0) = 2.5;m(0,1) = -1;m(1,1) = m(1,0) + m(0,1);cout << '[' << cnt++ << "] " << ": " << "m=" << endl;cout << m << endl;cout << "m.cols()=" << m.cols() << ", m.rows()=" << m.rows() << ", size()=" << m.size() << endl << endl;m << 1, 2, 3, 4;   //先行后列cout << '[' << cnt++ << "] " << ": " << "comma赋值，m=" << endl;cout << m << endl;cout << "m的第一行:" << m(1) << endl;//产生一个随机矩阵MatrixXd m1 = MatrixXd::Random(3,3);   //3 X 3 随机矩阵，值介于-1到1之间cout << '[' << cnt++ << "] " << ": " << "m1 =" << endl << m1 << endl << endl;MatrixXd m2 = MatrixXd::Constant(3,3,1.2);  //3 x 3 值为1.2的矩阵cout << '[' << cnt++ << "] " << ": " <<  "m2 = " << endl;cout << m2 << endl << endl;m1 = (m1 + m2) * 5;cout << '[' << cnt++ << "] " << ": " <<  "m1 = (m1 + m2) * 5 =" << endl << m1 << endl << endl;//向量赋值与矩阵相乘---Comma-initializationVectorXd v(3);v << 1, 2, 3;cout << '[' << cnt++ << "] " << ": v" << endl << v << endl << endl;cout << '[' << cnt++ << "] " << "m1 * v =" << endl << m1 * v << endl << endl;//通过循环为向量赋值VectorXd v1(3);for(int i = 0; i < 3; i++)v1(i) = i;cout << '[' << cnt++ << "] " << "列向量v1=" << endl << v1 << endl << endl;//行向量RVector rv;for(int i = 0; i < 3; i++)rv(i) = i;cout << '[' << cnt++ << "] " << "行向量：" << rv << endl << endl;//矩阵重新调整大小MatrixXd m3 = MatrixXd::Random(3, 4);cout << '[' << cnt++ << "] " << ": " <<  "m3 = " << endl;cout << m3 << endl << endl;cout << "m3.resize(5, 5)=" << endl;m3.resize(5, 5);   //不保持原值cout << m3 << endl << endl;MatrixXd m4= MatrixXd::Random(3, 3);cout << '[' << cnt++ << "] " << ": " <<  "m4 = " << endl;cout << m4 << endl;//矩阵的transpose转置cout << "M4转置=" << endl;cout << m4.transpose() << endl;//矩阵的conjugate转置cout << "M4共轭=" << endl;cout << m4.conjugate() << endl;//矩阵的adjoint转置cout << "M4.adjoint=" << endl;cout << m4.adjoint() << endl << endl;//矩阵与标量的+，-，×，/运算略//矩阵与矢量的运算MatrixXd ma = MatrixXd::Random(2, 3);MatrixXd vb = MatrixXd::Random(3, 1);cout << '[' << cnt++ << "] " << ": " <<  "ma = " << endl;cout << ma << endl;cout << "vb = " << endl;cout << vb << endl;cout << "ma * vb = " << endl;cout << ma * vb << endl;    //dot点乘和cross叉积略，见参考return 0;}

运行结果：

[0] : m=
  3  -1
2.5 1.5
m.cols()=2, m.rows()=2, size()=4

[1] : comma赋值，m=
1 2
3 4
m的第一行:3
[2] : m1 =
 0.680375   0.59688 -0.329554
-0.211234  0.823295  0.536459
 0.566198 -0.604897 -0.444451

[3] : m2 =
1.2 1.2 1.2
1.2 1.2 1.2
1.2 1.2 1.2

[4] : m1 = (m1 + m2) * 5 =
9.40188  8.9844 4.35223
4.94383 10.1165  8.6823
8.83099 2.97551 3.77775

[5] : v
1
2
3

[6] m1 * v =
40.4274
51.2237
26.1153

[7] 列向量v1=
0
1
2

[8] 行向量：0 1 2

[9] : m3 =
   0.10794  -0.270431    0.83239  -0.716795
-0.0452059  0.0268018   0.271423   0.213938
  0.257742   0.904459   0.434594  -0.967399

m3.resize(5, 5)=
6.91676e-310            0            0            0            0
6.91676e-310            0            0            0            0
  2.122e-314            0            0            0            0
  3.7008e-33            0            0            0            0
7.23757e-320            0            0            0            0

[10] : m4 =
-0.514226 -0.686642 -0.782382
-0.725537 -0.198111  0.997849
 0.608354 -0.740419 -0.563486
M4转置=
-0.514226 -0.725537  0.608354
-0.686642 -0.198111 -0.740419
-0.782382  0.997849 -0.563486
M4共轭=
-0.514226 -0.686642 -0.782382
-0.725537 -0.198111  0.997849
 0.608354 -0.740419 -0.563486
M4.adjoint=
-0.514226 -0.725537  0.608354
-0.686642 -0.198111 -0.740419
-0.782382  0.997849 -0.563486

[11] : ma =
0.0258648   0.22528  0.275105
 0.678224 -0.407937 0.0485744
vb =
-0.012834
  0.94555
-0.414966
ma * vb =
0.0985221
-0.414586