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frontend/node_modules/@turf/clusters-kmeans/LICENSE

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+The MIT License (MIT)
+
+Copyright (c) 2017 TurfJS
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the "Software"), to deal in
+the Software without restriction, including without limitation the rights to
+use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
+the Software, and to permit persons to whom the Software is furnished to do so,
+subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
+FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
+COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
+IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
+CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

frontend/node_modules/@turf/clusters-kmeans/README.md

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+# @turf/clusters-kmeans
+
+<!-- Generated by documentation.js. Update this documentation by updating the source code. -->
+
+## clustersKmeans
+
+Takes a set of [points][1] and partition them into clusters using the k-mean .
+It uses the [k-means algorithm][2]
+
+**Parameters**
+
+-   `points` **[FeatureCollection][3]&lt;[Point][4]>** to be clustered
+-   `options` **[Object][5]** Optional parameters (optional, default `{}`)
+    -   `options.numberOfClusters` **[number][6]** numberOfClusters that will be generated (optional, default `Math.sqrt(numberOfPoints/2)`)
+    -   `options.mutate` **[boolean][7]** allows GeoJSON input to be mutated (significant performance increase if true) (optional, default `false`)
+
+**Examples**
+
+```javascript
+// create random points with random z-values in their properties
+var points = turf.randomPoint(100, {bbox: [0, 30, 20, 50]});
+var options = {numberOfClusters: 7};
+var clustered = turf.clustersKmeans(points, options);
+
+//addToMap
+var addToMap = [clustered];
+```
+
+Returns **[FeatureCollection][3]&lt;[Point][4]>** Clustered Points with an additional two properties associated to each Feature:-   {number} cluster - the associated clusterId
+-   {[number, number]} centroid - Centroid of the cluster [Longitude, Latitude]
+
+[1]: https://tools.ietf.org/html/rfc7946#section-3.1.2
+
+[2]: https://en.wikipedia.org/wiki/K-means_clustering
+
+[3]: https://tools.ietf.org/html/rfc7946#section-3.3
+
+[4]: https://tools.ietf.org/html/rfc7946#section-3.1.2
+
+[5]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Object
+
+[6]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number
+
+[7]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Boolean
+
+<!-- This file is automatically generated. Please don't edit it directly:
+if you find an error, edit the source file (likely index.js), and re-run
+./scripts/generate-readmes in the turf project. -->
+
+---
+
+This module is part of the [Turfjs project](http://turfjs.org/), an open source
+module collection dedicated to geographic algorithms. It is maintained in the
+[Turfjs/turf](https://github.com/Turfjs/turf) repository, where you can create
+PRs and issues.
+
+### Installation
+
+Install this module individually:
+
+```sh
+$ npm install @turf/clusters-kmeans
+```
+
+Or install the Turf module that includes it as a function:
+
+```sh
+$ npm install @turf/turf
+```

frontend/node_modules/@turf/clusters-kmeans/dist/es/index.js

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+import clone from "@turf/clone";
+import { coordAll, featureEach } from "@turf/meta";
+import skmeans from "skmeans";
+/**
+ * Takes a set of {@link Point|points} and partition them into clusters using the k-mean .
+ * It uses the [k-means algorithm](https://en.wikipedia.org/wiki/K-means_clustering)
+ *
+ * @name clustersKmeans
+ * @param {FeatureCollection<Point>} points to be clustered
+ * @param {Object} [options={}] Optional parameters
+ * @param {number} [options.numberOfClusters=Math.sqrt(numberOfPoints/2)] numberOfClusters that will be generated
+ * @param {boolean} [options.mutate=false] allows GeoJSON input to be mutated (significant performance increase if true)
+ * @returns {FeatureCollection<Point>} Clustered Points with an additional two properties associated to each Feature:
+ * - {number} cluster - the associated clusterId
+ * - {[number, number]} centroid - Centroid of the cluster [Longitude, Latitude]
+ * @example
+ * // create random points with random z-values in their properties
+ * var points = turf.randomPoint(100, {bbox: [0, 30, 20, 50]});
+ * var options = {numberOfClusters: 7};
+ * var clustered = turf.clustersKmeans(points, options);
+ *
+ * //addToMap
+ * var addToMap = [clustered];
+ */
+function clustersKmeans(points, options) {
+    if (options === void 0) { options = {}; }
+    // Default Params
+    var count = points.features.length;
+    options.numberOfClusters =
+        options.numberOfClusters || Math.round(Math.sqrt(count / 2));
+    // numberOfClusters can't be greater than the number of points
+    // fallbacks to count
+    if (options.numberOfClusters > count)
+        options.numberOfClusters = count;
+    // Clone points to prevent any mutations (enabled by default)
+    if (options.mutate !== true)
+        points = clone(points);
+    // collect points coordinates
+    var data = coordAll(points);
+    // create seed to avoid skmeans to drift
+    var initialCentroids = data.slice(0, options.numberOfClusters);
+    // create skmeans clusters
+    var skmeansResult = skmeans(data, options.numberOfClusters, initialCentroids);
+    // store centroids {clusterId: [number, number]}
+    var centroids = {};
+    skmeansResult.centroids.forEach(function (coord, idx) {
+        centroids[idx] = coord;
+    });
+    // add associated cluster number
+    featureEach(points, function (point, index) {
+        var clusterId = skmeansResult.idxs[index];
+        point.properties.cluster = clusterId;
+        point.properties.centroid = centroids[clusterId];
+    });
+    return points;
+}
+export default clustersKmeans;

frontend/node_modules/@turf/clusters-kmeans/dist/es/package.json

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+{"type":"module"}

frontend/node_modules/@turf/clusters-kmeans/dist/js/index.d.ts

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+import { FeatureCollection, Point, Properties } from "@turf/helpers";
+export declare type KmeansProps = Properties & {
+    cluster?: number;
+    centroid?: [number, number];
+};
+/**
+ * Takes a set of {@link Point|points} and partition them into clusters using the k-mean .
+ * It uses the [k-means algorithm](https://en.wikipedia.org/wiki/K-means_clustering)
+ *
+ * @name clustersKmeans
+ * @param {FeatureCollection<Point>} points to be clustered
+ * @param {Object} [options={}] Optional parameters
+ * @param {number} [options.numberOfClusters=Math.sqrt(numberOfPoints/2)] numberOfClusters that will be generated
+ * @param {boolean} [options.mutate=false] allows GeoJSON input to be mutated (significant performance increase if true)
+ * @returns {FeatureCollection<Point>} Clustered Points with an additional two properties associated to each Feature:
+ * - {number} cluster - the associated clusterId
+ * - {[number, number]} centroid - Centroid of the cluster [Longitude, Latitude]
+ * @example
+ * // create random points with random z-values in their properties
+ * var points = turf.randomPoint(100, {bbox: [0, 30, 20, 50]});
+ * var options = {numberOfClusters: 7};
+ * var clustered = turf.clustersKmeans(points, options);
+ *
+ * //addToMap
+ * var addToMap = [clustered];
+ */
+declare function clustersKmeans(points: FeatureCollection<Point>, options?: {
+    numberOfClusters?: number;
+    mutate?: boolean;
+}): FeatureCollection<Point, KmeansProps>;
+export default clustersKmeans;

frontend/node_modules/@turf/clusters-kmeans/dist/js/index.js

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+"use strict";
+var __importDefault = (this && this.__importDefault) || function (mod) {
+    return (mod && mod.__esModule) ? mod : { "default": mod };
+};
+Object.defineProperty(exports, "__esModule", { value: true });
+var clone_1 = __importDefault(require("@turf/clone"));
+var meta_1 = require("@turf/meta");
+var skmeans_1 = __importDefault(require("skmeans"));
+/**
+ * Takes a set of {@link Point|points} and partition them into clusters using the k-mean .
+ * It uses the [k-means algorithm](https://en.wikipedia.org/wiki/K-means_clustering)
+ *
+ * @name clustersKmeans
+ * @param {FeatureCollection<Point>} points to be clustered
+ * @param {Object} [options={}] Optional parameters
+ * @param {number} [options.numberOfClusters=Math.sqrt(numberOfPoints/2)] numberOfClusters that will be generated
+ * @param {boolean} [options.mutate=false] allows GeoJSON input to be mutated (significant performance increase if true)
+ * @returns {FeatureCollection<Point>} Clustered Points with an additional two properties associated to each Feature:
+ * - {number} cluster - the associated clusterId
+ * - {[number, number]} centroid - Centroid of the cluster [Longitude, Latitude]
+ * @example
+ * // create random points with random z-values in their properties
+ * var points = turf.randomPoint(100, {bbox: [0, 30, 20, 50]});
+ * var options = {numberOfClusters: 7};
+ * var clustered = turf.clustersKmeans(points, options);
+ *
+ * //addToMap
+ * var addToMap = [clustered];
+ */
+function clustersKmeans(points, options) {
+    if (options === void 0) { options = {}; }
+    // Default Params
+    var count = points.features.length;
+    options.numberOfClusters =
+        options.numberOfClusters || Math.round(Math.sqrt(count / 2));
+    // numberOfClusters can't be greater than the number of points
+    // fallbacks to count
+    if (options.numberOfClusters > count)
+        options.numberOfClusters = count;
+    // Clone points to prevent any mutations (enabled by default)
+    if (options.mutate !== true)
+        points = clone_1.default(points);
+    // collect points coordinates
+    var data = meta_1.coordAll(points);
+    // create seed to avoid skmeans to drift
+    var initialCentroids = data.slice(0, options.numberOfClusters);
+    // create skmeans clusters
+    var skmeansResult = skmeans_1.default(data, options.numberOfClusters, initialCentroids);
+    // store centroids {clusterId: [number, number]}
+    var centroids = {};
+    skmeansResult.centroids.forEach(function (coord, idx) {
+        centroids[idx] = coord;
+    });
+    // add associated cluster number
+    meta_1.featureEach(points, function (point, index) {
+        var clusterId = skmeansResult.idxs[index];
+        point.properties.cluster = clusterId;
+        point.properties.centroid = centroids[clusterId];
+    });
+    return points;
+}
+exports.default = clustersKmeans;

frontend/node_modules/@turf/clusters-kmeans/package.json

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+{
+  "name": "@turf/clusters-kmeans",
+  "version": "6.5.0",
+  "description": "turf clusters-kmeans module",
+  "author": "Turf Authors",
+  "contributors": [
+    "David Gómez Matarrodona <@solzimer>",
+    "Stefano Borghi <@stebogit>",
+    "Denis Carriere <@DenisCarriere>"
+  ],
+  "license": "MIT",
+  "bugs": {
+    "url": "https://github.com/Turfjs/turf/issues"
+  },
+  "homepage": "https://github.com/Turfjs/turf",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/Turfjs/turf.git"
+  },
+  "funding": "https://opencollective.com/turf",
+  "publishConfig": {
+    "access": "public"
+  },
+  "keywords": [
+    "turf",
+    "geojson",
+    "cluster",
+    "clusters",
+    "clustering",
+    "k-means"
+  ],
+  "main": "dist/js/index.js",
+  "module": "dist/es/index.js",
+  "exports": {
+    "./package.json": "./package.json",
+    ".": {
+      "import": "./dist/es/index.js",
+      "require": "./dist/js/index.js"
+    }
+  },
+  "types": "dist/js/index.d.ts",
+  "sideEffects": false,
+  "files": [
+    "dist"
+  ],
+  "scripts": {
+    "bench": "ts-node bench.js",
+    "build": "npm-run-all build:*",
+    "build:es": "tsc --outDir dist/es --module esnext --declaration false && echo '{\"type\":\"module\"}' > dist/es/package.json",
+    "build:js": "tsc",
+    "docs": "node ../../scripts/generate-readmes",
+    "test": "npm-run-all test:*",
+    "test:tape": "ts-node -r esm test.js",
+    "test:types": "tsc --esModuleInterop --noEmit types.ts"
+  },
+  "devDependencies": {
+    "@turf/centroid": "^6.5.0",
+    "@turf/clusters": "^6.5.0",
+    "@turf/random": "^6.5.0",
+    "@types/skmeans": "^0.11.2",
+    "@types/tape": "*",
+    "benchmark": "*",
+    "chromatism": "*",
+    "concaveman": "*",
+    "load-json-file": "*",
+    "matrix-to-grid": "*",
+    "npm-run-all": "*",
+    "tape": "*",
+    "ts-node": "*",
+    "tslint": "*",
+    "typescript": "*",
+    "write-json-file": "*"
+  },
+  "dependencies": {
+    "@turf/clone": "^6.5.0",
+    "@turf/helpers": "^6.5.0",
+    "@turf/invariant": "^6.5.0",
+    "@turf/meta": "^6.5.0",
+    "skmeans": "0.9.7"
+  },
+  "gitHead": "5375941072b90d489389db22b43bfe809d5e451e"
+}