Eigen中创建/删除3D数组的方法是否合规？有无标准实现方式？

Is Your Current Approach Feasible? #

Short answer: Yes, it works—but it comes with some notable caveats:

• Manual memory management puts all the responsibility on you to call Array3Ddel every time; miss it, or let an exception slip through before deletion, and you’ll end up with memory leaks.
• The structure is a flat array of ArrayXXf objects, which can hurt cache performance compared to a single contiguous block of memory (though each ArrayXXf does store its data contiguously internally).
• Accessing elements with array[i](j,k) is functional, but not as intuitive as a native 3D structure.

Standardized 3D Array Solutions in Eigen #

Eigen offers two polished approaches for working with 3D arrays, depending on your needs:

1. Use Eigen’s Tensor Module (Official Multidimensional Support)

Eigen has a dedicated Tensor module built specifically for n-dimensional arrays (including 3D). It handles memory automatically, supports advanced operations like broadcasting, slicing, and parallelization, and uses intuitive 3D indexing.

First, include the required header:

#include <Eigen/Tensor>

Example initialization and usage:

// Define dimensions for the 3D tensor
int dims[3] = {2, 3, 4};
Eigen::Tensor<float, 3> tensor(dims[0], dims[1], dims[2]);

// Fill the tensor with a constant value
tensor.setConstant(5.0f);

// Access elements using 3D indices: tensor(i,j,k)
float val = tensor(0, 1, 2);

No manual deletion is needed—the tensor manages its own memory and will free it automatically when it goes out of scope.

2. Nested STL Containers + Eigen Arrays (No Tensor Module Required)

If you want to stick with Eigen’s core Array types and avoid the Tensor module, replace your manual dynamic array with a std::vector of ArrayXXf. This eliminates the risk of memory leaks by letting the STL handle memory management:

#include <vector>
#include <Eigen/Dense>

std::vector<Eigen::ArrayXXf> create3DArray(int dims[3], float val) {
    std::vector<Eigen::ArrayXXf> array(dims[0]);
    for (int i = 0; i < dims[0]; ++i) {
        array[i] = Eigen::ArrayXXf::Ones(dims[1], dims[2]) * val;
    }
    return array;
}

// Usage example
int main() {
    int dims[3] = {3, 2, 2};
    auto my3DArray = create3DArray(dims, 2.5f);
    // Access elements with my3DArray[i](j,k)
    // No need to manually delete—vector cleans up automatically when it goes out of scope
    return 0;
}

Final Recommendations #

• If you need advanced 3D operations (like convolution, reshaping, or multi-axis math), go with the Tensor module—it’s purpose-built for this kind of work.
• For simple 3D storage paired with core Eigen array operations, use std::vector<ArrayXXf> to avoid the headaches of manual memory management.

内容的提问来源于stack exchange，提问作者Jaewon Lee