void TSNE<NDims>::computeGradient(double* P, unsigned int* inp_row_P, unsigned int* inp_col_P, double* inp_val_P, double* Y, unsigned int N, int D, double* dC, double theta)
{
// Construct space-partitioning tree on current map
SPTree<NDims>* tree = new SPTree<NDims>(Y, N);
// Compute all terms required for t-SNE gradient
double* pos_f = (double*) calloc(N * D, sizeof(double));
double* neg_f = (double*) calloc(N * D, sizeof(double));
if(pos_f == NULL || neg_f == NULL) { Rcpp::stop("Memory allocation failed!\n"); }
tree->computeEdgeForces(inp_row_P, inp_col_P, inp_val_P, N, pos_f, num_threads);
// Storing the output to sum in single-threaded mode; avoid randomness in rounding errors.
std::vector<double> output(N);
#pragma omp parallel for schedule(guided) num_threads(num_threads)
for (unsigned int n = 0; n < N; n++) {
output[n]=tree->computeNonEdgeForces(n, theta, neg_f + n * D);
}
double sum_Q = .0;
for (unsigned int n=0; n<N; ++n) {
sum_Q += output[n];
}
// Compute final t-SNE gradient
for(unsigned int i = 0; i < N * D; i++) {
dC[i] = pos_f[i] - (neg_f[i] / sum_Q);
}
free(pos_f);
free(neg_f);
delete tree;
}
// Compute gradient of the t-SNE cost function (using Barnes-Hut algorithm)
void TSNE::computeGradient(double* P, int* inp_row_P, int* inp_col_P, double* inp_val_P, double* Y, int N, int D, double* dC, double theta)
{
// Construct space-partitioning tree on current map
SPTree* tree = new SPTree(D, Y, N);
// Compute all terms required for t-SNE gradient
double sum_Q = .0;
double* pos_f = (double*) calloc(N * D, sizeof(double));
double* neg_f = (double*) calloc(N * D, sizeof(double));
if(pos_f == NULL || neg_f == NULL) { cout<<"Memory allocation failed!\n"; }
tree->computeEdgeForces(inp_row_P, inp_col_P, inp_val_P, N, pos_f);
for(int n = 0; n < N; n++) tree->computeNonEdgeForces(n, theta, neg_f + n * D, &sum_Q);
// Compute final t-SNE gradient
for(int i = 0; i < N * D; i++) {
dC[i] = pos_f[i] - (neg_f[i] / sum_Q);
}
free(pos_f);
free(neg_f);
delete tree;
}
