Rectangle use accessors too.

haidark · Jan 8, 2017 · ca8a9d1 · ca8a9d1
1 parent 2e5e6e6
commit ca8a9d1
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Showing 4 changed files with 27 additions and 32 deletions.
diff --git a/scipy/spatial/ckdtree/src/distance.h b/scipy/spatial/ckdtree/src/distance.h
@@ -8,10 +8,10 @@ struct Dist1D {
         /* Compute the minimum/maximum distance along dimension k between points in
          * two hyperrectangles.
          */
-        *min = dmax(0, dmax(rect1.mins[k] - rect2.maxes[k],
-                              rect2.mins[k] - rect1.maxes[k]));
-        *max = dmax(rect1.maxes[k] - rect2.mins[k],
-                              rect2.maxes[k] - rect1.mins[k]);
+        *min = dmax(0, dmax(rect1.mins()[k] - rect2.maxes()[k],
+                              rect2.mins()[k] - rect1.maxes()[k]));
+        *max = dmax(rect1.maxes()[k] - rect2.mins()[k],
+                              rect2.maxes()[k] - rect1.mins()[k]);
     }
 
     static inline npy_float64

diff --git a/scipy/spatial/ckdtree/src/distance_box.h b/scipy/spatial/ckdtree/src/distance_box.h
@@ -85,8 +85,8 @@ struct BoxDist1D {
         /* Compute the minimum/maximum distance along dimension k between points in
          * two hyperrectangles.
          */
-        _interval_interval_1d(rect1.mins[k] - rect2.maxes[k],
-                    rect1.maxes[k] - rect2.mins[k], min, max,
+        _interval_interval_1d(rect1.mins()[k] - rect2.maxes()[k],
+                    rect1.maxes()[k] - rect2.mins()[k], min, max,
                     tree->raw_boxsize_data[k], tree->raw_boxsize_data[k + rect1.m]);
     }
 

diff --git a/scipy/spatial/ckdtree/src/query_ball_point.cxx b/scipy/spatial/ckdtree/src/query_ball_point.cxx
@@ -63,7 +63,7 @@ traverse_checking(const ckdtree *self,
         lnode = node;
         const npy_float64 p = tracker->p;
         const npy_float64 tub = tracker->upper_bound;
-        const npy_float64 *tpt = tracker->rect1.mins;
+        const npy_float64 *tpt = tracker->rect1.mins();
         const npy_float64 *data = self->raw_data;
         const npy_intp *indices = self->raw_indices;
         const npy_intp m = self->m;
@@ -127,7 +127,7 @@ query_ball_point(const ckdtree *self, const npy_float64 *x,
                     Rectangle point(m, x + i * m, x + i * m);
                     int j;
                     for(j=0; j<m; ++j) {
-                        point.maxes[j] = point.mins[j] = _wrap(point.mins[j], self->raw_boxsize_data[j]);
+                        point.maxes()[j] = point.mins()[j] = _wrap(point.mins()[j], self->raw_boxsize_data[j]);
                     }
                     HANDLE(NPY_LIKELY(p == 2), BoxMinkowskiDistP2)
                     HANDLE(p == 1, BoxMinkowskiDistP1)

diff --git a/scipy/spatial/ckdtree/src/rectangle.h b/scipy/spatial/ckdtree/src/rectangle.h
@@ -27,32 +27,27 @@ struct Rectangle {
 
     const npy_intp m;
 
-    std::vector<npy_float64> buf;
-
-    npy_float64 * maxes;
-    npy_float64 * mins;
-    npy_float64 * side_distances;
+    /* the last const is to allow const Rectangle to use these functions;
+     * also notice we had to mark buf mutable to avoid writing non const version
+     * of the same accessors. */
+    npy_float64 * const maxes() const { return &buf[0]; }
+    npy_float64 * const mins() const { return &buf[0] + m; }
+    npy_float64 * const side_distances() const { return &buf[0] + m + m; }
 
     Rectangle(const npy_intp _m,
               const npy_float64 *_mins,
               const npy_float64 *_maxes) : m(_m), buf(3 * m) {
 
         /* copy array data */
-        mins = &buf[0];
-        maxes = &buf[m];
-        side_distances = &buf[2 * m];
-
         /* FIXME: use std::vector ? */
-        std::memcpy((void*)mins, (void*)_mins, m*sizeof(npy_float64));
-        std::memcpy((void*)maxes, (void*)_maxes, m*sizeof(npy_float64));
+        std::memcpy((void*)mins(), (void*)_mins, m*sizeof(npy_float64));
+        std::memcpy((void*)maxes(), (void*)_maxes, m*sizeof(npy_float64));
     };
 
-    Rectangle(const Rectangle& rect) : m(rect.m), buf(rect.buf) {
-        mins = &buf[0];
-        maxes = &buf[m];
-        side_distances = &buf[2 * m];
-    };
+    Rectangle(const Rectangle& rect) : m(rect.m), buf(rect.buf) {};
 
+    private:
+        mutable std::vector<npy_float64> buf;
 };
 
 #include "ckdtree_methods.h"
@@ -191,8 +186,8 @@ template<typename MinMaxDist>
         item->split_dim = split_dim;
         item->min_distance = min_distance;
         item->max_distance = max_distance;
-        item->min_along_dim = rect->mins[split_dim];
-        item->max_along_dim = rect->maxes[split_dim];
+        item->min_along_dim = rect->mins()[split_dim];
+        item->max_along_dim = rect->maxes()[split_dim];
 
         /* update min/max distances */
         npy_float64 min, max;
@@ -203,9 +198,9 @@ template<typename MinMaxDist>
         max_distance -= max;
 
         if (direction == LESS)
-            rect->maxes[split_dim] = split_val;
+            rect->maxes()[split_dim] = split_val;
         else
-            rect->mins[split_dim] = split_val;
+            rect->mins()[split_dim] = split_val;
 
         MinMaxDist::interval_interval_p(tree, rect1, rect2, split_dim, p, &min, &max);
 
@@ -239,12 +234,12 @@ template<typename MinMaxDist>
         max_distance = item->max_distance;
 
         if (item->which == 1) {
-            rect1.mins[item->split_dim] = item->min_along_dim;
-            rect1.maxes[item->split_dim] = item->max_along_dim;
+            rect1.mins()[item->split_dim] = item->min_along_dim;
+            rect1.maxes()[item->split_dim] = item->max_along_dim;
         }
         else {
-            rect2.mins[item->split_dim] = item->min_along_dim;
-            rect2.maxes[item->split_dim] = item->max_along_dim;
+            rect2.mins()[item->split_dim] = item->min_along_dim;
+            rect2.maxes()[item->split_dim] = item->max_along_dim;
         }
     };