"lib/mingle/ink.cpp",
"lib/mingle/ink.h",
"lib/mingle/nearest_neighbor_graph.cpp",
- "lib/mingle/nearest_neighbor_graph.h",
"lib/mingle/nearest_neighbor_graph_ann.cpp",
"lib/neatogen/adjust.c",
"lib/neatogen/adjust.h",
#include <mingle/nearest_neighbor_graph.h>
#include <vector>
-SparseMatrix nearest_neighbor_graph(int nPts, int num_neigbors, double *x, double eps){
+SparseMatrix nearest_neighbor_graph(int nPts, int num_neighbors, double *x, double eps){
/* Gives a nearest neighbor graph of a list of dim-dimendional points. The result is a sparse matrix
of nPts x nPts, with num_neigbors entries per row.
nPts: number of points
- num_neigbors: number of neighbors needed
+ num_neighbors: number of neighbors needed
dim: dimension == 4
eps: error tolerance
x: nPts*dim vector. The i-th point is x[i*dim : i*dim + dim - 1]
*/
int nz;
SparseMatrix A;
- int k = num_neigbors;
+ int k = num_neighbors;
#ifdef HAVE_ANN
/* need to *2 as we do two sweeps of neighbors, so could have repeats */
std::vector<int> jcn(nPts * k * 2);
std::vector<double> val(nPts * k * 2);
- nearest_neighbor_graph_ann(nPts, num_neigbors, eps, x, nz, irn, jcn, val);
+ nearest_neighbor_graph_ann(nPts, num_neighbors, eps, x, nz, irn, jcn, val);
A = SparseMatrix_from_coordinate_arrays(nz, nPts, nPts, irn.data(),
jcn.data(), val.data(),