1 files changed, 18 insertions, 31 deletions

diff --git a/km-find.c b/km-find.c
index 3716123..657c645 100644
--- a/km-find.c
+++ b/km-find.c
@@ -5,11 +5,6 @@
 
 #define MIN_CLUSTER_DISTANCE 0.0001
 
-typedef struct {
-  float sum,
-        silouette;
-} find_solve_data_t;
-
 static float
 get_mean_cluster_size(
   const km_set_t * const set
@@ -24,7 +19,7 @@ get_mean_cluster_size(
     }
   }
 
-  return (num_filled > 0) ? sum / num_filled : 0;
+  return (num_filled > 0) ? (sum / num_filled) : 0;
 }
 
 static void
@@ -33,12 +28,12 @@ find_solve_on_stats(
   const km_solve_stats_t * const stats,
   void * const cb_data
 ) {
-  find_solve_data_t * const solve_data = cb_data;
+  km_find_data_t * const find_data = cb_data;
   UNUSED(set);
 
   // save total sum and silouette
-  solve_data->sum = stats->sum;
-  solve_data->silouette = stats->silouette;
+  find_data->distance_sum = stats->sum;
+  find_data->silouette = stats->silouette;
 }
 
 static const km_solve_cbs_t
@@ -67,7 +62,7 @@ km_find(
     return false;
   }
 
-  float best_score = 0.0;
+  float best_silouette = -2.0;
   for (size_t i = 2; i < cbs->max_clusters; i++) {
     for (size_t j = 0; j < cbs->num_tests; j++) {
       // init cluster set
@@ -77,42 +72,34 @@ km_find(
         return false;
       }
 
-      // init solve data
-      find_solve_data_t solve_data = {
-        .sum        = 0,
-        .silouette  = 0,
+      // init find data
+      km_find_data_t find_data = {
+        .cluster_set        = &cs,
+        .num_clusters       = i,
       };
 
       // solve test
-      if (!km_solve(&cs, set, &FIND_SOLVE_CBS, &solve_data)) {
+      // (populates sum and silouette)
+      if (!km_solve(&cs, set, &FIND_SOLVE_CBS, &find_data)) {
         // return failure
         return false;
       }
 
-      // init result data
-      const km_find_data_t result = {
-        .cluster_set        = &cs,
-        .num_clusters       = i,
-        .distance_sum       = solve_data.sum,
-        .silouette          = solve_data.silouette,
-        .mean_cluster_size  = get_mean_cluster_size(&cs),
-      };
+      // populate mean cluster size
+      find_data.mean_cluster_size = get_mean_cluster_size(&cs);
 
       // emit result
-      cbs->on_data(&result, cb_data);
-
-      // score result
-      const float score = solve_data.silouette;
+      cbs->on_data(&find_data, cb_data);
 
-      if (score > best_score) {
+      if (find_data.silouette > best_silouette) {
         // emit new best result
-        if (cbs->on_best && !cbs->on_best(score, &cs, cb_data)) {
+        if (cbs->on_best && !cbs->on_best(find_data.silouette, &cs, cb_data)) {
           // return failure
           return false;
         }
 
-        // update best score
-        best_score = score;
+        // update best silouette
+        best_silouette = find_data.silouette;
       }
 
       // finalize cluster set