Eigen matlab matrix operation for C + + matrix Library

Compared with other matrix libraries, the Eigen only needs to copy all of the include files to the specified location, without compiling and using the Eigen (Visit), in addition, the use of MATLAB matrix operation is simulated;

The above characteristics, so that it has a good practicality.

Attach the test code for learning and use.

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;//Define a matrix and assign a value Matr Ixxd m (2,2); m (0,0) = 3;m (1,0) = 2.5;m (0,1) = -1;m (All) = M (1,0) + m (0,1); cout << ' [' << cnt++ << '] ' &L  t;< ":" << "m=" << endl;cout << m << endl;cout << "m.cols () =" << m.cols () <<    ", m.rows () =" << m.rows () << ", size () =" << m.size () << Endl << endl;m << 1, 2, 3, 4; Pre-column cout << ' [' << cnt++ << '] ' << ': ' << ' comma assignment, m= ' << endl;cout << m   << endl;cout << "m first line:" << m (1) << endl;//produces a random matrix matrixxd m1 = Matrixxd::random (3,3); 3 X 3 random matrix with values between 1 and 1 cout << ' [' << cnt++ << '] ' << ': ' << ' m1 = ' << Endl << M1 << Endl << Endl; Matrixxd m2 = Matrixxd::constant (3,3,1.2);  3 x 3 matrix with a value of 1.2 cout << ' [' << cnt++ << '] ' << ': ' << ' m2 = ' << endl;cout <<  M2 << endl << endl;m1 = (m1 + m2) * 5;cout << ' [' << cnt++ << '] ' << ': ' << "M1 = (m1 + m2) * 5 =" << Endl << M1 << endl << endl;//vector assignment multiplied by matrix---comma-initializationvectorxd V (  3); v << 1, 2, 3;cout << ' [' << cnt++ << '] "<<": V "<< Endl << v << Endl << endl;cout << ' [' << cnt++ << '] ' << ' m1 * v = ' << Endl << M1 * v << E NDL << endl;//Vectorxd v1 (3) for vectors by loop, for (int i = 0; i < 3; i++) v1 (i) = I;cout << ' [' << cnt++ &LT;&L T "]" << "column vector v1=" << endl << v1 << endl << endl;//line vector rvector rv;for (int i = 0; I < 3; i++) RV (i) = I;cout << ' [' << cnt++ << '] ' << ' line vector: ' << rv << endl << Endl///Matrix resize Matrixxd m3 = matrixxd::random (3, 4); cout << ' [' << cnt++ << '] ' << ': ' << ' m3 = "<< endl;cout << m3 << endl << endl;cout <<" M3.resize (5, 5) = "<< endl;m3.resize (5   , 5); Do not maintain the original value cout << m3 << Endl << Endl; Matrixxd m4= Matrixxd::random (3, 3); cout << ' [' << cnt++ << '] ' << ': ' << ' m4 = ' <&lt ; Endl;cout << M4 << endl;//matrix transpose transpose cout << "M4 transpose =" << endl;cout << m4.transpose () < < endl;//matrix conjugate transpose cout << M4 conjugate = << endl;cout << m4.conjugate () << endl;// Adjoint transpose of the matrix cout << "m4.adjoint=" << endl;cout << m4.adjoint () << Endl << endl;//matrix with scalar +,- , x,/operation Matrixxd ma = matrixxd::random (2, 3) with the operation of the Matrix and the vector Matrixxd vb = Matrixxd::random (3, 1); cout << ' [' << cnt++ << '] ' << ': ' << ' ma = ' <&l T Endl;cout << ma << endl;cout << "VB =" << endl;cout << vb << endl;cout << "Ma * vb =" << endl;cout << ma * vb &    lt;< Endl; Dot dot multiplication and cross fork product, see reference return 0;}

Operation Result:

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

[1]: comma assignment, m=
1 2
3 4
First line of M: 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] Column vector v1=
0
1
2

[8] Line vector: 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

[Ten]: M4 =
-0.514226-0.686642-0.782382
-0.725537-0.198111 0.997849
0.608354-0.740419-0.563486
M4 transpose =
-0.514226-0.725537 0.608354
-0.686642-0.198111-0.740419
-0.782382 0.997849-0.563486
M4 conjugate =
-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

[one]: 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

Eigen matlab matrix operation for C + + matrix Library