init commit of added index of nearest node

Fix node name and also old missing bug with indices for empty result

@@ -107,1 +107,4 @@
 }
+
+template<typename Fn>
+inline int BLI_kdtree_nd_(find_nearest_cb)(const KDTree *tree,

@@ -324,6 +324,7 @@ DefNode(GeometryNode, GEO_NODE_FLIP_FACES, 0, "FLIP_FACES", FlipFaces, "Flip Fac
 DefNode(GeometryNode, GEO_NODE_GEOMETRY_TO_INSTANCE, 0, "GEOMETRY_TO_INSTANCE", GeometryToInstance, "Geometry to Instance", "Convert each input geometry into an instance, which can be much faster than the Join Geometry node when the inputs are large")
 DefNode(GeometryNode, GEO_NODE_IMAGE_INFO, 0, "IMAGE_INFO", ImageInfo, "Image Info", "Retrieve information about an image")
 DefNode(GeometryNode, GEO_NODE_IMAGE_TEXTURE, def_geo_image_texture, "IMAGE_TEXTURE", ImageTexture, "Image Texture", "Sample values from an image texture")
+DefNode(GeometryNode, GEO_NODE_INDEX_OF_NEAREST, 0, "INDEX_OF_NEAREST", IndexOfNearest, "Index of Nearest", "Index of nearest element by groups condition")

@@ -0,0 +8,4 @@
+#include "BLI_multi_value_map.hh"
+#include "BLI_task.hh"
+
+#include "BKE_geometry_fields.hh"

@@ -0,0 +12,4 @@
+
+#include "node_geometry_util.hh"
+
+#include "UI_interface.h"

@@ -0,0 +21,4 @@
+{
+  b.add_input<decl::Vector>("Position").implicit_field(implicit_field_inputs::position);
+
+  b.add_input<decl::Int>("Self Group ID").supports_field().hide_value().default_value(0);

@@ -0,0 +22,4 @@
+  b.add_input<decl::Vector>("Position").implicit_field(implicit_field_inputs::position);
+
+  b.add_input<decl::Int>("Self Group ID").supports_field().hide_value().default_value(0);
+  b.add_input<decl::Int>("Group ID to Search").supports_field().hide_value().default_value(0);

@@ -0,0 +68,4 @@
+    const VArray<int> group = evaluator.get_evaluated<int>(1);
+    const VArray<int> search_group = evaluator.get_evaluated<int>(2);
+
+    const bool group_use = !group.is_single();

@@ -0,0 +95,4 @@
+                                 }
+                               });
+
+    for (int key : in_group.keys()) {

@@ -0,0 +162,4 @@
+{
+  const Field<float3> position = params.extract_input<Field<float3>>("Position");
+
+  const Field<int> self_group = params.extract_input<Field<int>>("Self Group ID");

@@ -0,0 +75,4 @@
+    MultiValueMap<int, int64_t> out_group;
+    Array<int> indices(mask.min_array_size());
+
+    threading::parallel_invoke((indices.size() > 512) && group_to_find_use && group_use,

@@ -0,0 +77,4 @@
+
+    for (const int key : in_group.keys()) {
+      /* Never empty. */
+      const IndexMask self_points(use_group ? IndexMask(in_group.lookup(key)) : mask);

@@ -0,0 +86,4 @@
+        continue;
+      }
+
+      KDTree_3d *tree = BLI_kdtree_3d_new(search_points.size());

@@ -0,0 +119,4 @@
+
+      /* The grain size should be larger as each tree gets smaller. */
+      const int avg_tree_size = group_ids.size() / group_mask_storage.size();
+      const int grain_size = std::max(8192 / avg_tree_size, 1);

@@ -0,0 +122,4 @@
+      const int grain_size = std::max(8192 / avg_tree_size, 1);
+      threading::parallel_for(tree_masks.index_range(), grain_size, [&](const IndexRange range) {
+        for (const int i : range) {
+          const IndexMask tree_mask = tree_masks[i];

@@ -108,0 +110,4 @@
+inline int BLI_kdtree_nd_(find_nearest_cb_cpp)(const KDTree *tree,
+                                               const float co[KD_DIMS],
+                                               KDTreeNearest *r_nearest,
+                                               const Fn &fn)

@@ -0,0 +63,4 @@
+                           MutableSpan<int> r_indices)
+{
+  threading::parallel_for(mask.index_range(), 512, [&](const IndexRange range) {
+    mask.slice(range).foreach_index([&tree, positions, r_indices](const int index) {

@@ -0,0 +108,4 @@
+    VectorSet<int> group_indexing;
+    Vector<Vector<int>> mask_indices;
+    Vector<Vector<int>> tree_indices;
+    Vector<KDTree_3d *> forest;

@@ -0,0 +130,4 @@
+      }
+    }
+
+    threading::parallel_for(group_indexing.index_range(), 8, [&](const IndexRange range) {

@@ -0,0 +28,4 @@
+  return tree;
+}
+
+static KDTree_3d *build_kdtree(const Span<float3> &positions, const IndexRange range)

@@ -0,0 +48,4 @@
+
+    Array<int> indices(mask.min_array_size());
+
+    const auto nearest_for = [this, &positions](const IndexMask mask, MutableSpan<int> r_indices) {

@@ -0,0 +112,4 @@
+      group_indexing.add(group_id);
+    }
+
+    Vector<Vector<int>> mask_indices(group_indexing.size());

@@ -0,0 +113,4 @@
+    }
+
+    Vector<Vector<int>> mask_indices(group_indexing.size());
+    Vector<Vector<int>> tree_indices(group_indexing.size());

@@ -0,0 +127,4 @@
+
+    threading::parallel_invoke(
+        mask.size() + domain_size > 1024,
+        [&]() { build_group_masks(mask, mask_indices); },

@@ -0,0 +201,4 @@
+      return VArray<bool>::ForSingle(true, mask.min_array_size());
+    }
+
+    /* When a group ID is contained in the set, it means there is only one element with that ID. */

@@ -0,0 +91,4 @@
+      group_indexing.add(group_id);
+    }
+
+    const bool mask_is_cheap = mask.size() < domain_size / 2;

@@ -0,0 +111,4 @@
+    };
+
+    threading::parallel_invoke(
+        domain_size > 1024 && mask_is_cheap,

@@ -0,0 +86,4 @@
+    }
+
+    VectorSet<int> group_indexing;
+

@@ -0,0 +92,4 @@
+      group_indexing.add(group_id);
+    }
+
+    const bool use_cheap_mask = mask.size() < domain_size / 2;

@@ -0,0 +102,4 @@
+      mask_indices.reinitialize(group_indexing.size());
+    }
+    else {
+      result.reinitialize(domain_size);

@@ -0,0 +118,4 @@
+
+    threading::parallel_invoke(
+        domain_size > 1024 && use_cheap_mask,
+        [&]() {

@@ -0,0 +127,4 @@
+
+    threading::parallel_for(group_indexing.index_range(), 256, [&](const IndexRange range) {
+      for (const int index : range) {
+        const Span<int64_t> mask_of_tree = tree_indices[index];

@@ -0,0 +128,4 @@
+    threading::parallel_for(group_indexing.index_range(), 256, [&](const IndexRange range) {
+      for (const int index : range) {
+        const Span<int64_t> mask_of_tree = tree_indices[index];
+        KDTree_3d &tree = *build_kdtree(positions, mask_of_tree);