nvmd/libkdtree

libkdtree++ is an STL-like C++ template container implementation of k-dimensional space sorting, using a kd-tree. It sports a theoretically unlimited number of dimensions, and can store any data structure

libkdtree++ =========== libkdtree++ is a C++ template container implementation of k-dimensional space sorting, using a kd-tree. It: - sports an unlimited number of dimensions (in theory) - can store any data structure, access and comparison between the individual dimensional components defaults to the bracket operator, in the range `[0, k-1]` and the `std::less` functor by default, but other accessors and comparator can be defined. - has support for custom allocators - implements iterators - provides standard find as well as range queries - has amortised `O(lg n)` time (`O(n lg n)` worst case) on most operations (insert/erase/find optimised) and worst-case `O(n)` space. - provides a means to rebalance and thus optimise the tree. - exists in its own namespace - uses STL coding style, basing a lot of the code on `stl_tree.h` Please leave bugreports on Github Issues page . Historical background --------------------- In the past, this library was available from . This page seems to be gone now, available only via WebArchive. This is a mirror and a fork of that original repository, created in 2011 and maintained ever since. Notes of the original author a preserved below. Installation ------------ As there is no need to compile any files, you can just: ```sh $ ./configure $ sudo make install ``` It now also supports cmake, which can be used to build the examples and tests. To build with cmake: ```sh $ mkdir build $ cd build $ cmake .. $ make ``` You can use cmake to build the tests and examples on Windows with Visual C++. Use the windows cmake to create a Visual C++ solution and build that. Note that `cmake` and `./configure` is not needed at all in order to use kdtree in your application. As libkdtree++ is a header-only library, you just need to #in