Notes from Tue 23 Nov 12:17:31 CET 2021 meeting

Makefile

 SHELL = /bin/bash
 PROJECT = kdtree
 
+# This can be change to use venv directly
 VENV_PATH=`conda info --base`/envs/${PROJECT}
 PIP_EXECUTABLE=${VENV_PATH}/bin/pip
 PYTHON_EXECUTABLE=${VENV_PATH}/bin/python

kdtree.pyx

@@ -518,12 +518,13 @@ cdef cypclass Node activable:
 
 cdef cypclass QueryActor activable:
 
-    D_t * query_points
+    D_t * query_points_ptr
     D_t * data_ptr
     I_t * node_bounds_ptr
     NodeData_t * node_data_ptr
     I_t * indices_ptr
     NeighborsHeaps heaps
+
     I_t idx_worker
     I_t idx_start
     I_t idx_end
@@ -533,7 +534,7 @@ cdef cypclass QueryActor activable:
 
     __init__(
         self,
-        D_t * query_points,
+        D_t * query_points_ptr,
         D_t * data_ptr,
         I_t * node_bounds_ptr,
         NodeData_t * node_data_ptr,
@@ -544,9 +545,9 @@ cdef cypclass QueryActor activable:
         I_t idx_end,
         I_t n_features,
         I_t n_nodes,
-        I_t node_bounds_ptr_offset,
+        I_t node_bounds_ptr_offset
     ):
-        self.query_points = query_points
+        self.query_points_ptr = query_points_ptr
         self.data_ptr = data_ptr
         self.node_bounds_ptr = node_bounds_ptr
         self.node_data_ptr = node_data_ptr
@@ -565,10 +566,21 @@ cdef cypclass QueryActor activable:
             D_t * query_point
             D_t reduced_dist_LB
 
+        # [[1 2 3],
+        #  [4 5 6],
+        #  [7 8 9]]
+
+        # F-ordered: [1 4 7 2 5 8 3 6 9]
+
         for idx_pt in range(idx_start, idx_end):
-            query_point = self.query_points + idx_pt * self.n_features
-            reduced_dist_LB = self.min_rdist(0, query_point)
-            self._query_single_depthfirst(0, idx_pt, reduced_dist_LB)
+            # We use C-ordering
+            query_point = self.query_points_ptr + idx_pt * self.n_features
+            reduced_dist_LB = self.min_rdist(idx_node=0, pt=query_point)
+            self._query_single_depthfirst(
+                idx_node=0,
+                idx_pt=idx_pt,
+                reduced_dist_LB=reduced_dist_LB,
+            )
 
     D_t min_rdist(self,
         I_t idx_node,
@@ -580,6 +592,7 @@ cdef cypclass QueryActor activable:
             I_t j
 
         for j in range(self.n_features):
+            # We use C-ordering
             node_min_j = deref(self.node_bounds_ptr + idx_node + j * self.n_nodes)
             node_max_j = deref(self.node_bounds_ptr + idx_node + j * self.n_nodes + self.node_bounds_ptr_offset)
 
@@ -606,7 +619,7 @@ cdef cypclass QueryActor activable:
         cdef D_t sq_dist, reduced_dist_LB_1, reduced_dist_LB_2
         cdef I_t i, idx_left_node, idx_right_node
 
-        cdef D_t * query_point = query_points + idx_pt * self.n_features
+        cdef D_t * query_point_ptr = query_points_ptr + idx_pt * self.n_features
 
         #------------------------------------------------------------
         # Case 1: query point is outside node radius:
@@ -621,7 +634,7 @@ cdef cypclass QueryActor activable:
         elif node_info.is_leaf:
             for i in range(node_info.idx_start, node_info.idx_end):
                 sq_dist = sqeuclidean_dist(
-                    x1=query_point,
+                    x1=query_point_ptr,
                     x2=self.data_ptr + self.indices_ptr[i] * self.n_features,
                     k=self.n_features,
                 )
@@ -633,8 +646,8 @@ cdef cypclass QueryActor activable:
         else:
             idx_left_node = 2 * idx_node + 1
             idx_right_node = idx_left_node + 1
-            reduced_dist_LB_1 = self.min_rdist(idx_left_node, query_point)
-            reduced_dist_LB_2 = self.min_rdist(idx_right_node, query_point)
+            reduced_dist_LB_1 = self.min_rdist(idx_left_node, query_point_ptr)
+            reduced_dist_LB_2 = self.min_rdist(idx_right_node, query_point_ptr)
 
             # recursively query subnodes
             if reduced_dist_LB_1 <= reduced_dist_LB_2:
@@ -765,7 +778,7 @@ cdef cypclass KDTree:
             I_t n_query = query_points.shape[0]
             I_t n_features = query_points.shape[1]
             I_t n_neighbors = knn_indices.shape[1]
-            D_t * _query_points = <D_t *> query_points.data
+            D_t * query_points_ptr = <D_t *> query_points.data
             D_t rdist_lower_bound
             I_t n_workers = omp_get_max_threads()
             I_t n_points_worker = <I_t> ceil(n_query / n_workers)
@@ -783,7 +796,8 @@ cdef cypclass KDTree:
 
         for idx_worker in range(n_workers):
             query_actor = consume QueryActor(
-                query_points,
+                query_points_ptr,
+                self._data_ptr,
                 self._node_bounds_ptr,
                 self._node_data_ptr,
                 self._indices_ptr,