From 5494a86ea9f10322f259b08467e83e59b0d6d237 Mon Sep 17 00:00:00 2001
From: Jose Luis Blanco-Claraco <joseluisblancoc@gmail.com>
Date: Fri, 16 Jun 2023 00:51:19 +0200
Subject: [PATCH] FIX: Avoid segfault if saving an empty index

Closes #205
---
 CHANGELOG.md                  |  2 ++
 examples/saveload_example.cpp | 10 ++++++++++
 include/nanoflann.hpp         | 20 +++++++++++---------
 3 files changed, 23 insertions(+), 9 deletions(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 86d92299..c2d63a1f 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -22,6 +22,8 @@ nanoflann 1.5.0: UNRELEASED
    - Add examples with GUI (requires [mrpt-gui](https://docs.mrpt.org/reference/latest/group_mrpt_gui_grp.html)):
      - nanoflann_gui_example_R3: Radius search on R³ Euclidean space.
      - nanoflann_gui_example_bearings: NN search on non-Euclidean spaces.
+ * BUGFIXES:
+     - Avoid segfault if saving an empty index (Closes [#205](https://github.com/jlblancoc/nanoflann/issues/205)).
 
 nanoflann 1.4.3: Released Jul 24, 2022
  * Added flag SkipInitialBuildIndex to allow not wasting time building a tree when it will be loaded from a file later on ([PR #171](https://github.com/jlblancoc/nanoflann/pull/171)).
diff --git a/examples/saveload_example.cpp b/examples/saveload_example.cpp
index b5d62e8c..bfb7f090 100644
--- a/examples/saveload_example.cpp
+++ b/examples/saveload_example.cpp
@@ -96,6 +96,16 @@ void kdtree_save_load_demo(const size_t N)
         std::cout << "ret_index=" << ret_index
                   << " out_dist_sqr=" << out_dist_sqr << std::endl;
     }
+
+    // Stress test: try to save an empty index
+    {
+        PointCloud<double> emptyCloud;
+        my_kd_tree_t       index(3 /*dim*/, emptyCloud);
+        std::ofstream      f("index2.bin", std::ofstream::binary);
+        if (f.bad()) throw std::runtime_error("Error writing index file!");
+        index.saveIndex(f);
+        f.close();
+    }
 }
 
 int main()
diff --git a/include/nanoflann.hpp b/include/nanoflann.hpp
index 305b25a4..c2c80fd8 100644
--- a/include/nanoflann.hpp
+++ b/include/nanoflann.hpp
@@ -418,7 +418,9 @@ struct L1_Adaptor
         /* Process last 0-3 components.  Not needed for standard vector lengths.
          */
         while (a < last)
-        { result += std::abs(*a++ - data_source.kdtree_get_pt(b_idx, d++)); }
+        {
+            result += std::abs(*a++ - data_source.kdtree_get_pt(b_idx, d++));
+        }
         return result;
     }
 
@@ -1362,7 +1364,7 @@ class KDTreeBaseClass
         save_value(stream, obj.root_bbox_);
         save_value(stream, obj.leaf_max_size_);
         save_value(stream, obj.vAcc_);
-        save_tree(obj, stream, obj.root_node_);
+        if (obj.root_node_) save_tree(obj, stream, obj.root_node_);
     }
 
     /**  Loads a previous index from a binary file.
@@ -1784,8 +1786,7 @@ class KDTreeSingleIndexAdaptor
         }
 
         /* Call recursively to search next level down. */
-        if (!searchLevel(
-                result_set, vec, bestChild, mindist, dists, epsError))
+        if (!searchLevel(result_set, vec, bestChild, mindist, dists, epsError))
         {
             // the resultset doesn't want to receive any more points, we're done
             // searching!
@@ -1793,7 +1794,7 @@ class KDTreeSingleIndexAdaptor
         }
 
         DistanceType dst = dists[idx];
-        mindist        = mindist + cut_dist - dst;
+        mindist          = mindist + cut_dist - dst;
         dists[idx]       = cut_dist;
         if (mindist * epsError <= result_set.worstDist())
         {
@@ -2217,12 +2218,11 @@ class KDTreeSingleIndexDynamicAdaptor_
         searchLevel(result_set, vec, bestChild, mindist, dists, epsError);
 
         DistanceType dst = dists[idx];
-        mindist        = mindist + cut_dist - dst;
+        mindist          = mindist + cut_dist - dst;
         dists[idx]       = cut_dist;
         if (mindist * epsError <= result_set.worstDist())
         {
-            searchLevel(
-                result_set, vec, otherChild, mindist, dists, epsError);
+            searchLevel(result_set, vec, otherChild, mindist, dists, epsError);
         }
         dists[idx] = dst;
     }
@@ -2440,7 +2440,9 @@ class KDTreeSingleIndexDynamicAdaptor
         const SearchParameters& searchParams = {}) const
     {
         for (size_t i = 0; i < treeCount_; i++)
-        { index_[i].findNeighbors(result, &vec[0], searchParams); }
+        {
+            index_[i].findNeighbors(result, &vec[0], searchParams);
+        }
         return result.full();
     }
 };