A Golang implementation of the Jenks natural breaks optimization algorithm. It is a data clustering algorithm designed to determine the best arrangement of values into different classes, seeking to reduce the variance within classes and maximize the variance between classes.
This is a fork of ThinkingLogic/jenks which adds new features, bug fixes, and performance improvements.
Ported from a javascript version - itself ported from Fortran and described here by Tom MacWright.
import "github.com/ThinkingLogic/jenks"
//...
data := []float64{1.1, 2.1, 3.1, 12.1, 13.1, 14.1, 21.1, 22.1, 23.1, 27.1, 28.1, 29.1}
breaks := jenks.NaturalBreaks(data, 4)
// [1.1, 12.1, 21.1, 27.1]
rounded := jenks.Round(breaks, data)
// [0, 10, 20, 27]
allBreaks := jenks.AllNaturalBreaks(data, 4)
// [ [1.1, 21.1]
// [1.1, 12.1, 21.1]
// [1.1, 12.1, 21.1, 27.1] ]
This software is Licenced under the MIT License.
Please note that the javascript version this was ported from is broken, specifically this line:
kclass[countNum - 1] = data[lower_class_limits[k][countNum] - 2];
should be:
kclass[countNum - 1] = data[lower_class_limits[k][countNum] - 1];
- it has been fixed here, along with a number of minor improvements (such as not returning the upper bound so that the length of the returned slice matches the requested number of classes).