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Haversines are not Slow
The haversine is a function used to calculate the distance between a pair of latitude and longitude points while accounting for the assumption that the points are on a spherical globe. This package provides a fast, dataframe compatible, haversine function. For the first publication on the haversine calculation see Joseph de Mendoza y Ríos (1795) < https://books.google.cat/books?id=030t0OqlX2AC> (In Spanish).
Fast, Dependency-Free Geodesic Distance Calculations
Dependency-free, ultra fast calculation of geodesic
distances. Includes the reference nanometre-accuracy geodesic
distances of Karney (2013)
Smallest Enclosing Disc for Latitude and Longitude Points
Find the smallest circle that contains all longitude and latitude input points. From the generated center and radius, variable side polygons can be created, navigation based on bearing and distance can be applied, and more. Based on a modified version of Welzl's algorithm for smallest circle. Distance calculations are based on the haversine formula. Calculations for distance, midpoint, bearing and more are derived from < https://www.movable-type.co.uk>.
Leader Clustering Algorithm
The leader clustering algorithm provides a means for clustering a set of data points. Unlike many other clustering algorithms it does not require the user to specify the number of clusters, but instead requires the approximate radius of a cluster as its primary tuning parameter. The package provides a fast implementation of this algorithm in n-dimensions using Lp-distances (with special cases for p=1,2, and infinity) as well as for spatial data using the Haversine formula, which takes latitude/longitude pairs as inputs and clusters based on great circle distances.