+scalar_t Clusterer::distance_to_centroid(scalar_t *x, int k) {
+ scalar_t dist = 0;
+ for(int d = 0; d < _dim; d++) {
+ dist += sq(_cluster_means[k][d] - x[d]) / (2 * _cluster_var[k][d]);
+ dist += 0.5 * log(_cluster_var[k][d]);
+ ASSERT(!isnan(dist) && !isinf(dist));
+ }
+ return dist;
+}
+
+void Clusterer::initialize_clusters(int nb_points, scalar_t **points) {
+ int *used = new int[nb_points];
+ for(int k = 0; k < nb_points; k++) { used[k] = 0; }
+ for(int k = 0; k < _nb_clusters; k++) {
+ int l;
+ do { l = int(drand48() * nb_points); } while(used[l]);
+ for(int d = 0; d < _dim; d++) {
+ _cluster_means[k][d] = points[l][d];
+ _cluster_var[k][d] = 1.0;
+ }
+ used[l] = 1;
+ }
+ delete[] used;
+}
+