使用Armadillo库计算Dunn指数时遇越界错误与NaN结果求助

开发大型算法时，尝试用Armadillo库计算Dunn指数，运行代码后输出Dunn's index:-nan(ind)，且触发索引越界错误。已确认数据格式合适、数据对齐正确，无空簇及缺失数据，但仍无法解决问题。

测试代码 #

#include <iostream>
#include <armadillo>

using namespace std;
using namespace arma;

double dunns(int clusters_number, const mat& distM, const uvec& ind) {
    // Determine the number of unique clusters
    int i = max(ind);
    vec denominator;

    for (int i2 = 1; i2 <= i; ++i2) {
        uvec indi = find(ind == i2);
        uvec indj = find(ind != i2);

        // Check if indi and indj are not empty
        if (!indi.is_empty() && !indj.is_empty()) {
            mat temp;

            // Check if indices are within bounds before submatrix extraction
            if (indi.max() < distM.n_rows && indj.max() < distM.n_cols) {
                temp = distM.submat(indi, indj);
                denominator = join_cols(denominator, vectorise(temp));
            }
            else {
                // Debugging: Print indices that caused the error
                cout << "Error: Indices out of bounds for Cluster " << i2 << endl;
            }
        }
    }

    double num = 0.0;  // Initialize num to 0.0

    // Check if denominator is not empty before finding the minimum
    if (!denominator.is_empty()) {
        num = min(denominator);
    }

    mat neg_obs = zeros<mat>(distM.n_rows, distM.n_cols);

    for (int ix = 1; ix <= i; ++ix) {
        uvec indxs = find(ind == ix);

        // Check if indxs is not empty
        if (!indxs.is_empty()) {
            // Check if indices are within bounds before setting elements
            if (indxs.max() < distM.n_rows) {
                neg_obs.submat(indxs, indxs).fill(1.0);
            }
        }
    }

    // Print intermediate values
    cout << "Intermediate Values:" << endl;
    cout << "Denominator: " << denominator << endl;
    cout << "num: " << num << endl;

    mat dem = neg_obs % distM;
    double max_dem = max(max(dem));

    // Print max_dem
    cout << "max_dem: " << max_dem << endl;

    double DI = num / max_dem;
    return DI;
}

int main() {
    // New inputs for testing
    int clusters_number = 2;

    // Modified dissimilarity matrix (4x4)
    mat distM(4, 4);
    distM << 0.0 << 1.0 << 2.0 << 3.0
        << 1.0 << 0.0 << 1.0 << 2.0
        << 2.0 << 1.0 << 0.0 << 1.0
        << 3.0 << 2.0 << 1.0 << 0.0;

    // Modified cluster indices (4x1)
    arma::uvec ind;
    ind << 1 << 1 << 2 << 2;

    // Print the input dissimilarity matrix
    cout << "Dissimilarity Matrix:" << endl;
    cout << distM << endl;

    // Print the cluster indices
    cout << "Cluster Indices:" << endl;
    cout << ind << endl;

    double DI = dunns(clusters_number, distM, ind);

    cout << "Dunn's Index: " << DI << endl;

    return 0;
}

已排查情况 #

• 使用double类型存储相异矩阵，arma::uvec存储簇索引，格式合理
• 数据点与簇索引对齐正确
• 无空簇及缺失数据
• 仍在子矩阵提取时触发越界错误

内容的提问来源于stack exchange，提问作者Duplic8e