Refactor a bit Hierarchical clustering to fix clone.

src/shogun/clustering/Hierarchical.cpp

@@ -26,31 +26,42 @@ struct pair
 #endif // DOXYGEN_SHOULD_SKIP_THIS
 
 CHierarchical::CHierarchical()
-: CDistanceMachine(), merges(3), dimensions(0), assignment(NULL),
-	table_size(0), pairs(NULL), merge_distance(NULL)
+: CDistanceMachine()
 {
+	init();
 	register_parameters();
 }
 
 CHierarchical::CHierarchical(int32_t merges_, CDistance* d)
-: CDistanceMachine(), merges(merges_), dimensions(0), assignment(NULL),
-	table_size(0), pairs(NULL), merge_distance(NULL)
+: CDistanceMachine()
 {
+	init();
+	merges = merges_;
 	set_distance(d);
 	register_parameters();
 }
 
-static int PAIRS_DIM_0 = 2;
+void CHierarchical::init()
+{
+	merges = 3;
+	dimensions = 0;
+	assignment = NULL;
+	assignment_len = 0;
+	table_size = 0;
+	pairs = NULL;
+	pairs_len = 0;
+	merge_distance = NULL;
+	merge_distance_len = 0;
+}
 
 void CHierarchical::register_parameters()
 {
 	watch_param("merges", &merges);
 	watch_param("dimensions", &dimensions);
-	watch_param("assignment_size", &assignment_size);
-	watch_param("assignment", &assignment, &table_size);
+	watch_param("assignment", &assignment, &assignment_len);
 	watch_param("table_size", &table_size);
-	watch_param("pairs", &pairs, &PAIRS_DIM_0, &merges);
-	watch_param("merge_distance", &merge_distance, &merges);
+	watch_param("pairs", &pairs, &pairs_len);
+	watch_param("merge_distance", &merge_distance, &merge_distance_len);
 }
 
 CHierarchical::~CHierarchical()
@@ -82,10 +93,12 @@ bool CHierarchical::train_machine(CFeatures* data)
 
 	SG_FREE(merge_distance);
 	merge_distance=SG_MALLOC(float64_t, num);
+	merge_distance_len=num;
 	SGVector<float64_t>::fill_vector(merge_distance, num, -1.0);
 
 	SG_FREE(assignment);
 	assignment=SG_MALLOC(int32_t, num);
+	assignment_len = num;
 	SGVector<int32_t>::range_fill_vector(assignment, num);
 
 	SG_FREE(pairs);
@@ -155,7 +168,6 @@ bool CHierarchical::train_machine(CFeatures* data)
 	}
 	pb.complete();
 
-	assignment_size=num;
 	table_size=l-1;
 	ASSERT(table_size>0)
 	SG_FREE(distances);

src/shogun/clustering/Hierarchical.h

@@ -122,7 +122,10 @@ class CHierarchical : public CDistanceMachine
 		virtual bool train_require_labels() const { return false; }
 
 	private:
-		/** Register all parameters */
+		/** Initialize attributes */
+		void init();
+
+		/** Register all parameters (aka this class' attributes) */
 		void register_parameters();
 
 	protected:
@@ -132,20 +135,20 @@ class CHierarchical : public CDistanceMachine
 		/// number of dimensions
 		int32_t dimensions;
 
-		/// size of assignment table
-		int32_t assignment_size;
-
 		/// cluster assignment for the num_points
 		int32_t* assignment;
+		int32_t assignment_len;
 
 		/// size of the below tables
 		int32_t table_size;
 
 		/// tuples of i/j
 		int32_t* pairs;
+		int32_t pairs_len;
 
 		/// distance at which pair i/j was added
 		float64_t* merge_distance;
+		int32_t merge_distance_len;
 };
 }
 #endif

src/shogun/metric/LMNNImpl.h

@@ -81,7 +81,7 @@ class CLMNNImpl
 		static void check_training_setup(CFeatures* features, const CLabels* labels, SGMatrix<float64_t>& init_transform);
 
 		/**
-		 * for each feature in x, find its target neighbors; this is, its k
+		 * for each feature in x, find its target neighbors; that is, its k
 		 * nearest neighbors with the same label as indicated by y
 		 */
 		static SGMatrix<index_t> find_target_nn(CDenseFeatures<float64_t>* x, CMulticlassLabels* y, int32_t k);