We present a new regular grid search algorithm for quick fixed-radius nearest-neighbor lookup developed in Python. This module indexes a set of k-dimensional points in a regular grid, with optional periodic conditions, providing a fast approach for nearest neighbors queries. In this first installment, we provide three types of queries: bubble, shell and the nth-nearest. For these queries we include three different metrics of interest in astronomy, namely, the euclidean, the haversine and the Vincenty, the last two in spherical coordinates. We also provide the possibility of using a custom distance function. This package results particularly useful for large datasets where a brute-force search turns impractical.

我们提出了一种新的常规网格搜索算法，用于以Python开发的快速固定半径最近邻居查找。该模块使用可选的周期性条件在规则网格中索引一组k维点，从而为最近的邻居查询提供了一种快速的方法。在第一部分中，我们提供三种类型的查询：bubble，shell和nth-nearest。对于这些查询，我们包括三种不同的天文学关注指标，即欧几里得，haversine和Vincenty，最后两个是球形坐标。我们还提供了使用自定义距离功能的可能性。该程序包结果对于蛮力搜索变得不切实际的大型数据集特别有用。