X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=code%2Fstage1%2Fsrc%2FAlgorithm%2Fpam.c;h=60e3efe49075a6828e8469028b42cf0480d8738e;hb=73d68777d709e054cf74e806e23b0bdefda9462a;hp=ecd72c390fc45b55e12ea403dd81032479436fbb;hpb=f9f51b6ab4c7280dd521da675353252d7b078984;p=epclust.git

diff --git a/code/stage1/src/Algorithm/pam.c b/code/stage1/src/Algorithm/pam.c
index ecd72c3..60e3efe 100644
--- a/code/stage1/src/Algorithm/pam.c
+++ b/code/stage1/src/Algorithm/pam.c
@@ -27,11 +27,11 @@ static void sample(uint32_t* v, uint32_t n, uint32_t k)
 
 // assign a vector (represented by its dissimilarities to others, as dissimilarities[index,])
 // to a cluster, represented by its center ==> output is integer in 0..K-1
-static uint32_t assignCluster(uint32_t index, Real* dissimilarities,
+static uint32_t assignCluster(uint32_t index, float* dissimilarities,
 	uint32_t* centers, uint32_t n, uint32_t K)
 {
 	uint32_t minIndex = 0;
-	Real minDist = dissimilarities[index * n + centers[0]];
+	float minDist = dissimilarities[index * n + centers[0]];
 
 	for (uint32_t j = 1; j < K; j++)
 	{
@@ -46,8 +46,8 @@ static uint32_t assignCluster(uint32_t index, Real* dissimilarities,
 }
 
 // assign centers given a clustering, and also compute corresponding distortion
-static void assign_centers(uint32_t nbClusters, Vector** clusters, Real* dissimilarities,
-	uint32_t nbItems, uint32_t* ctrs, Real* distor)
+static void assign_centers(uint32_t nbClusters, Vector** clusters, float* dissimilarities,
+	uint32_t nbItems, uint32_t* ctrs, float* distor)
 {
 	*distor = 0.0;
 	// TODO [heuristic]: checking only a neighborhood of the former center ?
@@ -55,13 +55,13 @@ static void assign_centers(uint32_t nbClusters, Vector** clusters, Real* dissimi
 	{
 		// If the cluster is empty, choose a center at random (pathological case...)
 		uint32_t minIndex = get_rand_int() % nbItems;
-		Real minSumDist = INFINITY;
+		float minSumDist = INFINITY;
 		for (uint32_t i = 0; i < vector_size(clusters[j]); i++)
 		{
 			uint32_t index1;
 			vector_get(clusters[j], i, index1);
 			// attempt to use current index as center
-			Real sumDist = 0.0;
+			float sumDist = 0.0;
 			for (uint32_t ii = 0; ii < vector_size(clusters[j]); ii++)
 			{
 				uint32_t index2;
@@ -80,7 +80,7 @@ static void assign_centers(uint32_t nbClusters, Vector** clusters, Real* dissimi
 }
 
 // Core PAM algorithm from a dissimilarity matrix; (e.g. nstart=10, maxiter=100)
-void pam(Real* dissimilarities, uint32_t nbItems, uint32_t nbClusters, int clustOnMedoids,
+void pam(float* dissimilarities, uint32_t nbItems, uint32_t nbClusters, int clustOnMedoids,
 	uint32_t nbStart, uint32_t maxNbIter, Result_t* result)
 {
 	uint32_t* ctrs = result->medoids_ranks; //shorthand
@@ -93,7 +93,7 @@ void pam(Real* dissimilarities, uint32_t nbItems, uint32_t nbClusters, int clust
 		bestClusts[j] = vector_new(uint32_t);
 	}
 
-	Real lastDistor, distor, bestDistor = INFINITY;
+	float lastDistor, distor, bestDistor = INFINITY;
 	for (uint32_t startKount = 0; startKount < nbStart; startKount++)
 	{
 		// centers (random) [re]initialization