Add description

1 files changed, 42 insertions, 0 deletions

diff --git a/meowpp/dsa/KD_Tree.h b/meowpp/dsa/KD_Tree.h
index 0abc358..2e55d12 100644
--- a/meowpp/dsa/KD_Tree.h
+++ b/meowpp/dsa/KD_Tree.h
@@ -68,6 +68,48 @@ namespace meow{
       void   clear();
       void   reset(size_t _dimension);
   };
+  /*********************************************************
+    @asciidoc
+    === meow:: *KD_Tree<Keys, Key, Value>* (C++ class)
+    .Description
+    `KD_Tree` is *K-dimension tree*, which is a dictionary(key->value).
+    Where the type if key is a *K-dimension vector* .
+    
+   .Template Request
+   * `Keys` should has `operator[]` to allow the KD_Tree access the k-dimensions
+   * `Key` should has `operator*`, `operator+`
+    
+    .Support Methods
+    * N <- numbers of element in the kd-tree
+    * K <- dimensions
+    * `Keys` is the tyepname of the vector
+    * `Key` is the typename of the element in the vector
+    * `Value` is the typename of value
+   [options="header",width="100%",cols="1>,1<s,5<,1<,2<,10<",grid="rows"]
+   |=======================================================================
+   |Const?|Name| Parameters| Return Type| Time Complexity| Description
+   |const|root|(size_t number)|size_t|very fast|
+   ||insert|(Key const& k, Value v)|void|O(1)|Insert a pair (k->v)
+   || build|()|void|O(KN logN) | Build the data structure(the `insert()` 
+   method will not build the data structure immediately)
+   |const|query|(Keys const& point, int k)|Value|O(kN ^1-1/k^ ) |
+   Using Euclidean-Distance to find the k-nearest neighbor from `point` .
+   And return the corrosponding value
+   |const|query|(Keys const& point, int k)|std::vector<Value>|O(kN ^1-1/k^ ) |
+   Using Euclidean-Distance to find all the x-nearest neighbor from `point` ,
+   where x <= k. And return an array of all the corrosponding value.
+   ||clear|()|O(1)|Clear all data
+   ||reset|(size_t dimension)|O(1)|Clear all data and then
+   set the this->dimension be `dimension`
+   |=======================================================================
+NOTE: O(kN ^1-1/k^ ) is reference from wiki. +
+`query()` and `rangeQuery()` will run `build()` first if you called `insert()`
+before call them. And `build()` is very slow, so you should not use this class
+as a dynamic tree
+
+'''
+@asciidoc-
+   *********************************************************/
 }
 
 #include "KD_Tree.hpp"