Correct comments

kdtree.pyx

@@ -76,7 +76,7 @@ cdef cypclass Counter activable:
 
     This can be useful for synchronisation for the caller after
     triggering the actors logic as it wait for the value of
-    the Coutner to reach a given one before moving on.
+    the Counter to reach a given one before moving on.
     """
 
     I_t _n
@@ -332,7 +332,7 @@ cdef cypclass NeighborsHeap activable:
 cdef cypclass Node activable:
     """A KDTree Node
 
-    Node delegate tasks to their children Nodes.
+    Node delegates tasks to their children Nodes.
 
     Some Nodes are set as Leaves when they are associated
     to ``leaf_size`` or less points.
@@ -396,19 +396,19 @@ cdef cypclass Node activable:
         if (end - start <= leaf_size):
             self._is_leaf = True
             # Adding to the global counter the number
-            # of samples the leaf is responsible of
+            # of samples the leaf is responsible of.
             counter.add(NULL, end - start)
             return
 
         # We partition the samples in two nodes on a given dimension,
-        # with the middle point as a pivot
+        # with the middle point as a pivot.
         partition_node_indices(data_ptr, indices_ptr, start, mid, end, dim, n_dims)
         self._point = data_ptr + mid
 
         self._left = consume Node()
         self._right = consume Node()
 
-        # Recursing on both partition
+        # Recursing on both partitions.
         self._left.build_node(NULL,
                               data_ptr, indices_ptr,
                               leaf_size, n_dims, next_dim,
@@ -429,7 +429,7 @@ cdef cypclass Node activable:
             D_t tmp
 
         if self._is_leaf:
-            # Computing all the euclideans distances here
+            # Computing all the euclideans distances here.
             for j in range(self._start, self._end):
                 dist = 0
                 for k in range(self._n_dims):
@@ -439,13 +439,13 @@ cdef cypclass Node activable:
                         )
                     dist += tmp * tmp
 
-                # The heap is doing the smart work of keeping
-                # the closest points for each query point i
+                # The heap is responsible for keeping the closest
+                # points for each query point i.
                 heaps.push(NULL, i, dist, self._indices_ptr[j])
 
             return
 
-        # TODO: one can implement a pruning strategy here
+        # TODO: one can implement a pruning strategy here.
         self._left.query(NULL, query_points, i, heaps)
         self._right.query(NULL, query_points, i, heaps)
 
@@ -509,7 +509,7 @@ cdef cypclass KDTree:
         # When object are activated (set as Actors), methods
         # are reified. When using those reified methods
         # a new argument is prepredend for a predicate,
-        # which we aren't using using here, hence the extra NULL.
+        # which we aren't using here, hence the extra NULL.
         #
         # Also using this separate method allowing using actors
         # because __init__ can't be reified.