src/adapters/a.kmeansClustering.c

   1 #include <R.h>
   2 #include <Rdefines.h>
   3 #include "sources/kmeansClustering.h"
   4 #include <cgds/Vector.h>
   5
   6 // k-means based on a distance matrix (nstart=10, maxiter=100)
   7 SEXP kmeansWithDistances(
   8     SEXP distances_,
   9     SEXP K_,
  10     SEXP nstart_,
  11     SEXP maxiter_
  12 ) {
  13     // get scalar arguments
  14     int K = INTEGER_VALUE(K_);
  15     int nstart = NUMERIC_VALUE(nstart_);
  16     int maxiter = INTEGER_VALUE(maxiter_);
  17
  18     // extract infos from M and get associate pointer
  19     SEXP dim = getAttrib(distances_, R_DimSymbol);
  20     int n = INTEGER(dim)[0];
  21     double* pDistances = REAL(distances_);
  22
  23     // Main call to core algorithm
  24     int* clusters = kmeansWithDistances_core(pDistances, n, K, nstart, maxiter);
  25
  26     // allocations and recopies to R vector object
  27     SEXP bestClusts;
  28     PROTECT(bestClusts = allocVector(INTSXP, n));
  29     int* pBestClusts = INTEGER(bestClusts);
  30     for (int i=0; i<n; i++)
  31         pBestClusts[i] = clusters[i] + 1; // add 1 to start labels at 1
  32     free(clusters);
  33
  34     // and return clusters
  35     UNPROTECT(1);
  36     return bestClusts;
  37 }