more

Author: gagolews

README.md

@@ -159,7 +159,8 @@ are fat, *The 4th CGC Workshop on Computational Geometry*, 1999.
 
 March, W.B., Parikshit, R., Gray, A.G., Fast Euclidean minimum spanning
 tree: Algorithm, analysis, and applications,
-*Proc. 16th ACM SIGKDD Intl. Conf. Knowledge Discovery and Data Mining (KDD '10)*, 2010, 603–612.
+*Proc. 16th ACM SIGKDD Intl. Conf. Knowledge Discovery and Data Mining (KDD '10)*,
+2010, 603–612.
 
 Olson C.F., Parallel algorithms for hierarchical clustering,
 *Parallel Computing* **21**(8), 1995, 1313–1325.
@@ -177,5 +178,5 @@ Optimizing search strategies in K-d Trees,
 2001.
 
 
-See the package's [homepage](https://quitefastmst.gagolewski.com/)
+See **quitefastmst**'s [homepage](https://quitefastmst.gagolewski.com/)
 for more references.

src/c_kdtree.h

@@ -347,7 +347,7 @@ class kdtree
             }
         }
         // The sliding midpoint rule:
-        FLOAT split_val = 0.5*(root->bbox_min[split_dim] + root->bbox_max[split_dim]);  // midrange
+        FLOAT split_val = 0.5f*(root->bbox_min[split_dim] + root->bbox_max[split_dim]);  // midrange
 
         // this doesn't improve:
         // size_t cnt = 0;

src/c_kdtree_boruvka.h

@@ -900,7 +900,7 @@ class kdtree_boruvka : public kdtree<FLOAT, D, DISTANCE, NODE>
         #if OPENMP_IS_ENABLED
         #pragma omp parallel for schedule(static)
         #endif
-        for (size_t l=0; l<leaves.size(); ++l) {
+        for (Py_ssize_t l=0; l<this->nleaves; ++l) {
             NODE* curleaf = leaves[l];
 
             if (curleaf->cluster_repr >= 0 && curleaf->idx_to - curleaf->idx_from > 1)  // all elems in the same cluster