从Matlab到C ++特征矩阵运算-向量归一化 [英] From Matlab to C++ Eigen matrix operations - vector normalization

问题描述

将一些Matlab代码转换为C ++.

Converting some Matlab code to C++.

问题(在C ++中如何操作):

Questions (how to in C++):

1. 将两个向量串联在一起. (已经找到了解决方案)

1. Concatenate two vectors in a matrix. (already found the solution)

归一化每个数组("pts" col)除以其第3个值

Normalize each array ("pts" col) dividing it by its 3rd value

1和2的Matlab代码

Matlab code for 1 and 2:

% 1. A 3x1 vector. d0, d1 double.
B = [d0*A (d0+d1)*A]; % B is 3x2

% 2. Normalize a set of 3D points
% Divide each col by its 3rd value
% pts 3xN. C 3xN.
% If N = 1 you can do: C = pts./pts(3); if not:
C = bsxfun(@rdivide, pts, pts(3,:));

1和2的C ++代码

C++ code for 1 and 2:

// 1. Found the solution for that one!
B << d0*A, (d0 + d1)*A;

// 2. 
for (int i=0, i<N; i++)
{
    // Something like this, but Eigen may have a better solution that I don't know.
    C.block<3,1>(0,i) = C.block<3,1>(0,i)/C(0,i);
}

我希望这个问题现在更加清楚².

I hope the question is more clear now².

推荐答案

对于#2:

C = C.array().rowwise() / C.row(2).array();

仅数组具有针对行和列部分约简定义的乘法和除法运算符.当您将其分配回C

Only arrays have multiplication and division operators defined for row and column partial reductions. The array converts back to a matrix when you assign it back into C

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