使用 Eigen C++ 库将每个矩阵列与每个向量元素相乘
我需要使用 Eigen C++ 库 将每个矩阵列乘以每个向量元素.我试过 colwise 没有成功.
I need to multiply each matrix column by each vector element using Eigen C++ library. I tried colwise without success.
示例数据:
Eigen::Matrix3Xf A(3,2); //3x2
A << 1 2,
2 2,
3 5;
Eigen::Vector3f V = Eigen::Vector3f(2, 3);
//Expected result
C = A.colwise()*V;
//C
//2 6,
//4 6,
//6 15
//this means C 1st col by V first element and C 2nd col by V 2nd element.
矩阵 A 可以有 3xN 和 V Nx1.含义 (cols x rowls).
Matrix A can have 3xN and V Nx1. Meaning (cols x rowls).
推荐答案
我会这样做:
Eigen::Matrix3Xf A(3, 2); // 3x2
A << 1, 2, 2, 2, 3, 5;
Eigen::Vector3f V = Eigen::Vector3f(1, 2, 3);
const Eigen::Matrix3Xf C = A.array().colwise() * V.array();
std::cout << C << std::endl;
示例输出:
1 2
4 4
9 15
说明
你很接近，诀窍是使用 .array() 来做广播乘法.
colwiseReturnType 没有 .array() 方法，所以我们必须在 A 的数组视图上做我们的 colwise 恶作剧.
colwiseReturnType doesn't have a .array() method, so we have to do our colwise shenanigans on the array view of A.
如果你想计算两个向量的元素乘积(最酷的酷猫称之为 Hadamard 产品)，你可以做
If you want to compute the element-wise product of two vectors (The coolest of cool cats call this the Hadamard Product), you can do
Eigen::Vector3f a = ...;
Eigen::Vector3f b = ...;
Eigen::Vector3f elementwise_product = a.array() * b.array();
以上代码以列方式执行的操作.
Which is what the above code is doing, in a columnwise fashion.
要解决行情况，您可以使用 .rowwise()，并且您需要一个额外的 transpose() 以使事情适合
To address the row case, you can use .rowwise(), and you'll need an extra transpose() to make things fit
Eigen::Matrix<float, 3, 2> A; // 3x2
A << 1, 2, 2, 2, 3, 5;
Eigen::Vector2f V = Eigen::Vector2f(2, 3);
// Expected result
Eigen::Matrix<float, 3, 2> C = A.array().rowwise() * V.transpose().array();
std::cout << C << std::endl;
示例输出:
2 6
4 6
6 15
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