void save_current_iteration(List& trace_x, List& trace_pi, List& trace_A, List& trace_B, List& log_posterior, List& trace_switching_prob,
arma::ivec x, NumericVector pi, NumericMatrix A, NumericMatrix B, double& loglik, NumericVector switching_prob,
int index){
IntegerVector xx(x.begin(), x.end());
trace_x[index] = clone(xx);
trace_pi[index] = clone(pi);
trace_A[index] = clone(A);
trace_B[index] = clone(B);
log_posterior[index] = clone(wrap(loglik));
trace_switching_prob[index] = clone(switching_prob);
}
// [[Rcpp::export]]
arma::mat sgd(arma::mat& coords,
arma::ivec& targets_i, // vary randomly
arma::ivec& sources_j, // ordered
arma::ivec& ps, // N+1 length vector of indices to start of each row j in vector is
arma::vec& weights, // w{ij}
const double& gamma,
const double& rho,
const arma::uword& n_samples,
const int& M,
const double& alpha,
const Rcpp::Nullable<Rcpp::NumericVector> momentum,
const bool& useDegree,
const Rcpp::Nullable<Rcpp::NumericVector> seed,
const Rcpp::Nullable<Rcpp::NumericVector> threads,
const bool verbose) {
#ifdef _OPENMP
checkCRAN(threads);
#endif
const dimidxtype D = coords.n_rows;
const vertexidxtype N = coords.n_cols;
const edgeidxtype E = targets_i.n_elem;
Visualizer* v;
if (momentum.isNull()) v = new Visualizer(
sources_j.memptr(), targets_i.memptr(), coords.memptr(),
D, N, E,
rho, n_samples,
M, alpha, gamma);
else {
float moment = NumericVector(momentum)[0];
if (moment < 0) throw Rcpp::exception("Momentum cannot be negative.");
if (moment > 0.95) throw Rcpp::exception("Bad things happen when momentum is > 0.95.");
v = new MomentumVisualizer(
sources_j.memptr(), targets_i.memptr(), coords.memptr(),
D, N, E,
rho, n_samples, moment,
M, alpha, gamma);
}
distancetype* negweights = new distancetype[N];
std::fill(negweights, negweights + N, 0);
if (useDegree) {
std::for_each(targets_i.begin(), targets_i.end(), [&negweights](const sword& e) {negweights[e]++;});
} else {
for (vertexidxtype p = 0; p < N; ++p) {
for (edgeidxtype e = ps[p]; e != ps[p + 1]; ++e) {
negweights[p] += weights[e];
}
}
}
std::for_each(negweights, negweights + N, [](distancetype& weight) {weight = pow(weight, 0.75);});
v -> initAlias(weights.memptr(), negweights, seed);
delete[] negweights;
const uword batchSize = BATCHSIZE;
#ifdef _OPENMP
const unsigned int ts = omp_get_max_threads();
#else
const unsigned int ts = 2;
#endif
Progress progress(max((uword) ts, n_samples / BATCHSIZE), verbose);
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (unsigned int t = 0; t < ts; ++t) {
v->thread(progress, batchSize);
}
delete v;
return coords;
}