void run() {
// Do some validation of the arguments
if (graph.rows() != graph.cols()) {
throw std::invalid_argument("Matrix must be square");
}
if (graph.any_element_is_inf_or_nan()) {
throw std::invalid_argument("Matrix includes Inf or NaN values");
}
if (graph.any_element_is_negative()) {
throw std::invalid_argument("Matrix includes negative values");
}
if (!is_symmetric(graph)) {
throw std::invalid_argument("Matrix must be symmetric");
}
if (!clustering.empty() && (int)clustering.size() != graph.rows()) {
throw std::invalid_argument("Initial value must have same size as the matrix");
}
// initialize Clustering object
params.lossfun = lossfun.get();
srand(seed);
Clustering clus(graph,params);
if (!clustering.empty()) {
clus.set_clustering(clustering);
}
// perform clustering
if (optimize) {
clus.optimize();
}
// outputs
clustering = clus.get_clustering();
loss = clus.get_loss();
num_clusters = clus.num_clusters();
}
