TSlackTree
==========
A 2D version of a KDTree for TPoint datatype

Note:
  For more dimensions, and/or floating point values, along with category or
  index reference see TKDTree.

-----

TSlackTree.Init
---------------
```
procedure TSlackTree.Init(TPA: TPointArray);
```

Builds the KDTree.

Time complexity average is O(n log n)

-----

TSlackTree.IndexOf
------------------
```
function TSlackTree.IndexOf(P: TPoint): Integer;
```

Search and find the index for use in TSlackTree.Data for a given point `p`

Time complexity average is O(log n)

-----

TSlackTree.Find
---------------
```
function TSlackTree.Find(P: TPoint): PSlackNode;
```

Search and find the given point `p`, returns a node, a pointer to the tree node.

Time complexity average is O(log n)

-----

TSlackTree.Hide
---------------
```
procedure TSlackTree.Hide(idx:Integer);
```

Hide the node (by index) so that queries will not return it.

Time complexity average is O(1)

-----

TSlackTree.Hide
---------------
```
function TSlackTree.Hide(P: TPoint): Boolean; overload;
```

Hide the node (by TPoint) so that queries will not return it.

Time complexity average is O(log n)

-----

TSlackTree.RawNearest
---------------------
```
function TSlackTree.RawNearest(P: TPoint; NotEqual: Boolean = False): PSlackNode;
```

Returns the closest node to the point given.

Time complexity average is O(log n)

-----

TSlackTree.Nearest
------------------
```
function TSlackTree.Nearest(P: TPoint; NotEqual :Boolean = False): TPoint;
```

Returns the closest point to the point given.

Time complexity average is O(log n)

-----

TSlackTree.RawKNearest
----------------------
```
function TSlackTree.RawKNearest(P: TPoint; k:Integer; NotEqual: Boolean = False): TSlackRefArray;
```

Returns the **k** closest node to the point given.

Time complexity average is O(k * log n)

-----

TSlackTree.KNearest
-------------------
```
function TSlackTree.KNearest(P: TPoint; k:Integer; NotEqual: Boolean = False): TPointArray;
```

Returns the **k** closest points to the point given.

Time complexity average is O(k * log n)

-----

TSlackTree.RawRangeQuery
------------------------
```
function TSlackTree.RawRangeQuery(B:TBox): TSlackRefArray;
```

-----

TSlackTree.RangeQuery
---------------------
```
function TSlackTree.RangeQuery(B:TBox; hide:Boolean = False): TPointArray;
```

Returns all the points that are within the given box.

Time complexity average is O(k * log n)
where **k** is the number of points returned

-----

TSlackTree.RangeQueryEx
-----------------------
```
function TSlackTree.RangeQueryEx(query:TPoint; xRad,yRad:Double; hide: Boolean = False): TPointArray;
```

Returns all the points that are within the given range **xRad** and **yRad**.

Time complexity average is O(k * log n)
where **k** is the number of points returned

-----

TSlackTree.RangeQueryEx
-----------------------
```
function TSlackTree.RangeQueryEx(query:TPoint; xmin,ymin,xmax,ymax: Double; hide: Boolean = False): TPointArray;
```

Returns all the points that are further away than xmin, and ymin, but closer than xmax, and ymax from the query.

Time complexity average is O(k * log n)
where **k** is the number of points returned

-----

TSlackTree.Clusters
-------------------
```
function TSlackTree.Clusters(xRad,yRad: Single): T2DPointArray;
```

Like TPA.Cluster, but acts on the points in the tree, and allows you to use floats for xRad, and yRad.
This methods also exists in TKDTree and works in n dimensions.

Time complexity average is between O(n) and O(n log n)

Speedwise, once the tree is built this method is on pair with ClusterTPA.

-----

TSlackTree.RefArray
-------------------
```
function TSlackTree.RefArray: TSlackRefArray;
```