MATLAB与C＆＃x2B;＆＃x2B;的结果/输出不正确/输出使用特征矩阵

Question

我将我的MATLAB代码与C ++进行比较，并获得不正确的输出，以简单简单。

我的MATLAB代码：

Ny = 10; 
ygl = -cos(pi*(0:Ny)/Ny)'; %Gauss-Lobatto chebyshev points 
%Chebyshev matrix: 

VGL = cos(acos(ygl(:))*(0:Ny)); 
dVGL = diag(1./sqrt(1-ygl.^2))*sin(acos(ygl)*(0:Ny))*diag(0:Ny);

C ++代码：

    static const int ny = 10; 
    std::vector<double> ygl(ny+1); 

    for (int i = 0; i< ny+1; i++){
        ygl[i] = -1. * cos(((i) * EIGEN_PI )/ny); //This is correct
    
    }
    Eigen::Matrix< double, ny+1, 1> v ;
    v.setZero();

    Eigen::Matrix< double, ny+1, 1> v1 ;
    v1.setZero();

    Eigen::Matrix< double, ny+1, ny+1> m; 
    m.setZero();

    Eigen::Matrix< double, ny+1, ny+1> m1;
    m1.setZero();

    Eigen::Matrix< double, ny+1, ny+1> dv; 
    dv.setZero();
    
    for (int j = 0; j < ny+1; j++){
            v[j] = 1./(sqrt(1-pow(ygl[j],2)));
            v1[j] = 1. * (j);
        
    }
    m = v.array().sqrt().matrix().asDiagonal(); //this is correct
    m1 = v1.array().matrix().asDiagonal(); //this is correct

    for (int i = 0; i < ny+1; i++){
        for (int j = 0; j < ny+1; j++){
            dv(j + ny*i) = m(j) * sin(acos(ygl[j]) * (i)) * m1(j); //this is incorrect
            cout << dv(j + ny*i) << "\n";
        }
    }

您可以看到，发现两个列向量V和V1的对角线矩阵是正确的，但是当将额外的术语乘以时，请完全放弃结果。我不确定它是否像此处的操作顺序一样简单。

为了为这个特定示例提供更多上下文，正确的输出应该看起来像：

 NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN
         0    1.0000   -3.8042    7.8541  -12.3107   16.1803  -18.4661   18.3262  -15.2169    9.0000    0.0000
         0    1.0000   -3.2361    4.8541   -4.0000   -0.0000    6.0000  -11.3262   12.9443   -9.0000   -0.0000
         0    1.0000   -2.3511    1.1459    2.9062   -6.1803    4.3593    2.6738   -9.4046    9.0000    0.0000
         0    1.0000   -1.2361   -1.8541    4.0000    0.0000   -6.0000    4.3262    4.9443   -9.0000   -0.0000
         0    1.0000   -0.0000   -3.0000    0.0000    5.0000   -0.0000   -7.0000    0.0000    9.0000   -0.0000
         0    1.0000    1.2361   -1.8541   -4.0000   -0.0000    6.0000    4.3262   -4.9443   -9.0000   -0.0000
         0    1.0000    2.3511    1.1459   -2.9062   -6.1803   -4.3593    2.6738    9.4046    9.0000   -0.0000
         0    1.0000    3.2361    4.8541    4.0000   -0.0000   -6.0000  -11.3262  -12.9443   -9.0000    0.0000
         0    1.0000    3.8042    7.8541   12.3107   16.1803   18.4661   18.3262   15.2169    9.0000   -0.0000
       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN       NaN

%%%%%%%%%%%%%%； 在从评论中提出@cris Luengo的建议之后。我有以下内容，

Eigen::Matrix< double, 1, ny+1> v1;//rewrote v1[j] = 1. * (j); from for loop
v1.setZero();
std::iota(v1.begin(), v1.end(), 0);

for (int j = 0; j < ny+1; j++){
            v[j] = 1./(sqrt(1-pow(ygl[j],2)));
            //v1[j] = 1. * (j); 
    }
m = v.array().matrix().asDiagonal(); 
m1 = v1.array().matrix().asDiagonal(); 
    
    for (int i = 0; i < ny+1; i++){
        for (int j = 0; j < ny+1; j++){
            ygl[j] = -1. * cos(((j) * EIGEN_PI )/ny);//this is correct
            dv(j + ny*i) =   sin(acos(ygl[j]) * (i));//this is correct

        }
    }
dv1 = (m) * (dv) * (m1);
std::cout << dv1 << "\n"; //this is incorrect