试图实现一个 C++ 库，需要一些关于如何与它交互的指针

Question

我在 C++ 方面相对缺乏经验，正在尝试将库编译为 DLL 以便在 Unity 中使用。至于生成 DLL 并与之交互，我已经成功地调用了下面的函数并且 return Unity 中的虚拟值，不用担心。

我苦苦挣扎的地方是如何与这个 Approximate Nearest Neighbour 库进行交互，并且可以使用一些指针。（如果不下载上面链接的源代码并亲自查看，这可能是一个很难定义的问题，但我会尽量使其简单）

在Unity中，我有一个三维数组（points[] = float[x,y,z]），在space中有一个查询点（float[x,y,z]） .我希望将此数据输入类似下面的函数（我已从 ann_sample.cpp 修改 - 原始链接在底部），并且 return 最近的邻居到这一点。

我的函数

int myInit(float x, float y, float z, int numPoints, int maxPoints, int nn)
{
    int                 nPts;                   
    ANNpointArray       dataPts;                
    ANNpoint            queryPt;                
    ANNidxArray         nnIdx;                  
    ANNdistArray        dists;                  
    ANNkd_tree* kdTree;                         

    int dimension = 3;
    
    queryPt = annAllocPt(dimension , x);                        //This only expects the dimension, and a coord - I assume this is pre-allocation? 
    dataPts = annAllocPts(maxPoints, dimension);    //Again, this does not expect the coordinate (xyz) data, is pre-allocating the array?
    nnIdx = new ANNidx[nn];                         // more pre-allocating?
    dists = new ANNdist[nn];                        // more pre-allocating?

    nPts = numPoints;           
                        
    //Should we be populating the actual queryPt and dataPts here?
    //at the moment, these are still empty?

    kdTree = new ANNkd_tree(                    // build search structure
        dataPts,                                // the data points
        nPts,                                   // number of points
        dimension);                             // dimension of space


    kdTree->annkSearch(                     // search
            queryPt,                        // query point
            nn,                             // number of near neighbors
            nnIdx,                          // nearest neighbors (returned)
            dists,                          // distance (returned)
            eps);                           // error bound
    
    annClose();                                 // done with ANN

    return nnIdx[0];  //this is the nearest neighbor  
}

原函数 （这需要命令行输入 - 即 ann_sample [-d dim] [-max mpts] [-nn k] [-e eps] [-df data] [-qf query]）

int main(int argc, char **argv)
{
    int                 nPts;                   // actual number of data points
    ANNpointArray       dataPts;                // data points
    ANNpoint            queryPt;                // query point
    ANNidxArray         nnIdx;                  // near neighbor indices
    ANNdistArray        dists;                  // near neighbor distances
    ANNkd_tree*         kdTree;                 // search structure

    getArgs(argc, argv);                        // read command-line arguments

    queryPt = annAllocPt(dim);                  // allocate query point
    dataPts = annAllocPts(maxPts, dim);         // allocate data points
    nnIdx = new ANNidx[k];                      // allocate near neigh indices
    dists = new ANNdist[k];                     // allocate near neighbor dists

    nPts = 0;                                   // read data points

    cout << "Data Points:\n";
    while (nPts < maxPts && readPt(*dataIn, dataPts[nPts])) {
        printPt(cout, dataPts[nPts]);
        nPts++;
    }

    kdTree = new ANNkd_tree(                    // build search structure
                    dataPts,                    // the data points
                    nPts,                       // number of points
                    dim);                       // dimension of space

    while (readPt(*queryIn, queryPt)) {         // read query points
        cout << "Query point: ";                // echo query point
        printPt(cout, queryPt);

        kdTree->annkSearch(                     // search
                queryPt,                        // query point
                k,                              // number of near neighbors
                nnIdx,                          // nearest neighbors (returned)
                dists,                          // distance (returned)
                eps);                           // error bound

        cout << "\tNN:\tIndex\tDistance\n";
        for (int i = 0; i < k; i++) {           // print summary
            dists[i] = sqrt(dists[i]);          // unsquare distance
            cout << "\t" << i << "\t" << nnIdx[i] << "\t" << dists[i] << "\n";
        }
    }
    delete [] nnIdx;                            // clean things up
    delete [] dists;
    delete kdTree;
    annClose();                                 // done with ANN

    return EXIT_SUCCESS;
}

正如您在我的评论中看到的那样，我无法确定实际输入数据的位置和方式，即上面提到的我的点数组。

似乎正在使用以下代码填充数据（在参考函数中），通过使用“istream”class，但我不明白这是如何工作的，或者我将如何模拟它。

    while (nPts < maxPts && readPt(*dataIn, dataPts[nPts])) {
        printPt(cout, dataPts[nPts]);
        nPts++;
    }

... 

bool readPt(istream &in, ANNpoint p)            // read point (false on EOF)
{
    for (int i = 0; i < dim; i++) {
        if(!(in >> p[i])) return false;
    }
    return true;
}

Answer 1

更新：
把这一切写出来显然是我在正确方向上需要的推动力！以防将来它与任何人相关，我与之交互的方式相当简单。

我将几个二维数组传递到 C++ 插件中，然后将其转换为 ANNpointArrays。鉴于它是 C++，我需要首先实例化适当大小的数组，然后填充如下：

    float qPoints[][3]

    .....

    for (int i = 0; i < nQueryPts; i++) {
        for (int j = 0; j < dimension; j++)
        {
            queryPts[i][j] = qPoints[i][j];
        }
    }

有了这个之后，运行在我的每个查询点上进行 annKSearch 就相对简单了，返回最近邻的整数数组和距离的浮点数。我需要学习一些关于如何在 C++ 中传递和实例化数组的知识，但这比我想象的要容易得多！

没有人在读它 - 但这对我来说是一个有用的练习，我把这个问题留下来以防其他人试图在 C# 中实现这个库！

试图实现一个 C++ 库，需要一些关于如何与它交互的指针

Attempting to implement a C++ library, need some pointers on how to interface with it

c#

c++

unity3d

approximate-nn-searching