这是一个小而有效的程序来执行的K -近邻搜索算法，此算法利用JIT 理论加速循环，比向量化有效解决了大量数据的精度问题。甚至比kd-tree效果要佳。

K-nearest neighbor search已经广泛应用在科学与工程上，比如模式识别，数据挖掘和信号处理。

-This is a small and effective procedures to implement the K- nearest neighbor search algorithm, this algorithm JIT theoretical acceleration cycle, than to quantify an effective solution to the large amounts of data accuracy problems. Even more than the effect of kd-tree to be good. K-nearest neighbor search has been widely used in science and engineering, such as pattern recognition, data mining and signal processing.