63 lines
2.9 KiB
TypeScript
Executable File
63 lines
2.9 KiB
TypeScript
Executable File
import { FeatureCollection, Feature, Point, Position } from "@turf/helpers";
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/**
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* Takes a {@link FeatureCollection} of points and calculates the median center,
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* algorithimically. The median center is understood as the point that is
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* requires the least total travel from all other points.
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*
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* Turfjs has four different functions for calculating the center of a set of
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* data. Each is useful depending on circumstance.
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*
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* `@turf/center` finds the simple center of a dataset, by finding the
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* midpoint between the extents of the data. That is, it divides in half the
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* farthest east and farthest west point as well as the farthest north and
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* farthest south.
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*
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* `@turf/center-of-mass` imagines that the dataset is a sheet of paper.
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* The center of mass is where the sheet would balance on a fingertip.
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*
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* `@turf/center-mean` takes the averages of all the coordinates and
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* produces a value that respects that. Unlike `@turf/center`, it is
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* sensitive to clusters and outliers. It lands in the statistical middle of a
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* dataset, not the geographical. It can also be weighted, meaning certain
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* points are more important than others.
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*
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* `@turf/center-median` takes the mean center and tries to find, iteratively,
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* a new point that requires the least amount of travel from all the points in
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* the dataset. It is not as sensitive to outliers as `@turf/center-mean`, but it is
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* attracted to clustered data. It, too, can be weighted.
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*
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* **Bibliography**
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*
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* Harold W. Kuhn and Robert E. Kuenne, “An Efficient Algorithm for the
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* Numerical Solution of the Generalized Weber Problem in Spatial
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* Economics,” _Journal of Regional Science_ 4, no. 2 (1962): 21–33,
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* doi:{@link https://doi.org/10.1111/j.1467-9787.1962.tb00902.x}.
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*
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* James E. Burt, Gerald M. Barber, and David L. Rigby, _Elementary
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* Statistics for Geographers_, 3rd ed., New York: The Guilford
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* Press, 2009, 150–151.
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*
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* @name centerMedian
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* @param {FeatureCollection<any>} features Any GeoJSON Feature Collection
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* @param {Object} [options={}] Optional parameters
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* @param {string} [options.weight] the property name used to weight the center
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* @param {number} [options.tolerance=0.001] the difference in distance between candidate medians at which point the algorighim stops iterating.
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* @param {number} [options.counter=10] how many attempts to find the median, should the tolerance be insufficient.
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* @returns {Feature<Point>} The median center of the collection
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* @example
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* var points = turf.points([[0, 0], [1, 0], [0, 1], [5, 8]]);
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* var medianCenter = turf.centerMedian(points);
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*
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* //addToMap
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* var addToMap = [points, medianCenter]
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*/
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declare function centerMedian(features: FeatureCollection<any>, options?: {
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weight?: string;
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tolerance?: number;
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counter?: number;
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}): Feature<Point, {
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medianCandidates: Array<Position>;
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[key: string]: any;
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}>;
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export default centerMedian;
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