Refactor the AI into a web worker, but it's untested.
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parent
edb6362688
commit
4708fdbd6e
7 changed files with 251 additions and 51 deletions
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@ -10,8 +10,8 @@ export default {
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// The border around gateways that we should consult the AI on.
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border: {
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lat: 0.05,
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lng: 0.1
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lat: 0.1,
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lng: 0.2
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},
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// The resolution of the coverage map
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@ -1,19 +1,20 @@
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"use strict";
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import path from 'path';
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import L from 'leaflet';
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import {
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loadLayersModel as tf_loadLayersModel,
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tensor as tf_tensor
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} from '@tensorflow/tfjs';
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import chroma from 'chroma-js';
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import GetFromUrl from './Helpers/GetFromUrl.mjs';
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import Config from './ClientConfig.mjs';
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import { normalise } from '../../common/Math.mjs';
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import AIWorker from './Worker/AI.worker.mjs';
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class LayerAI {
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/**
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* Computes a bounding box that exactly encompasses all the gateways in
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* the index.
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* @return {{north:number,south:number,east:number,west:number}} The computed bounding box
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*/
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get gateway_bounds() {
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let result = {
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east: Infinity,
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@ -31,30 +32,107 @@ class LayerAI {
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return result;
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}
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/**
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* Initialises a new Leaflet AI layer instance.
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* @param {[type]} map [description]
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*/
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constructor(map) {
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this.map = map;
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this.gateways = new Map();
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this.worker = new AIWorker();
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this.map_bounds = null;
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}
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/**
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* Sets up the Web Worker that does the TensorFlow prediction.
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* Using a web worker avoids hanging the main thread.
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* @return {Promise} A Promise that resolves when setup is complete.
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*/
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worker_setup() {
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// Arrow functions inherit the parent scope, including the "this"
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// special variable.
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return new Promise((resolve, reject) => {
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// Attach the listener first
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this.worker.addEventListener("message", (event) => {
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if(event.data.event !== "setup-complete") {
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reject(`Error: AIWorker responded with event ${event.data.event}, but 'setup-complete' was expected.`, event.data);
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return;
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}
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resolve();
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}, { once: true });
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// Ask the web worker to set itself up
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this.worker.postMessage({
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event: "setup",
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bounds: this.gateway_bounds,
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index: this.index
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});
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})
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}
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/**
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* Uses the Web Worker to predict a row of signal strength values.
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* @param {number} latitude The latitude for which predictions should be made.
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* @return {Promise<number[]>} A Promise returning the array of predictions calculated by the web worker.
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*/
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worker_predict_row(latitude) {
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return new Promise((resolve, reject) => {
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// Attach the event listener....
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this.worker.addEventListener("message", (event) => {
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if(event.data.event !== "result") {
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reject(`Error: AIWorker responded with event ${event.data.event}, but 'result' was expected.`, event.data);
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return;
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}
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resolve(event.data);
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}, { once: true });
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// ....and send the request
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this.worker.postMessage({
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event: "predict-row",
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latitude
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});
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});
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}
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/**
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* Sets up the Leaflet AI visualisation layer.
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* @return {Promise} A promise that resolves when setup is complete.
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*/
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async setup() {
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// Download the index file that tells us where the gateways and their
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// trained models are located
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this.index = JSON.parse(
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await GetFromUrl(Config.ai_index_file)
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);
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console.log(this.index);
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for(let gateway of this.index.index) {
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this.gateways.set(
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gateway.id,
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await tf_loadLayersModel(`${window.location.href}/${path.dirname(Config.ai_index_file)}/${gateway.id}/model.json`)
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);
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}
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// Figure out the bounds of the map we're going to generate
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this.map_bounds = this.gateway_bounds;
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map_bounds.north += Config.border.lat;
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map_bounds.south -= Config.border.lat;
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this.layer = this.generate_layer();
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map_bounds.east += Config.border.lng;
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map_bounds.west -= Config.border.lng;
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// Setup the web worker
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await this.worker_setup();
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// Generate the Leaflet layer
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this.layer = await this.generate_layer();
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this.layer.addTo(this.map);
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console.log("[Layer/AI] Complete");
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}
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generate_layer() {
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/**
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* Generates and returns the Leaflet layer containing the AI-predicted
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* values.
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* @return {Promise} A Promise that resolves to the generated Leaflet layer.
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*/
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async generate_layer() {
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console.log("[Layer/AI] Rendering map");
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let map = this.render_map();
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console.log("[Layer/AI] Passing to Leaflet");
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@ -70,15 +148,12 @@ class LayerAI {
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});
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}
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render_map() {
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// FUTURE: Do this in a web worker?
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let map_bounds = this.gateway_bounds;
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map_bounds.north += Config.border.lat;
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map_bounds.south -= Config.border.lat;
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map_bounds.east += Config.border.lng;
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map_bounds.west -= Config.border.lng;
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/**
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* Uses a Web Worker and pre-trained AIs to generate a GeoJSON map of
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* signal strength for a bounding box around the known gateways.
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* @return {Promise} A Promise that resolves to a GeoJSON array representing the map.
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*/
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async render_map() {
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let coverage = [],
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colour_scale = chroma.scale([
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Config.colour_scale.min,
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@ -88,28 +163,24 @@ class LayerAI {
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this.index.properties.rssi_max
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);
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for(let lat = map_bounds.south; lat < map_bounds.north; lat += Config.step.lat) {
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for(let lng = map_bounds.west; lng < map_bounds.east; lng += Config.step.lng) {
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let max_predicted_rssi = -Infinity;
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for(let [, ai] of this.gateways) {
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let next_prediction = ai.predict(
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tf_tensor([ lat, lng ], [1, 2])
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);
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max_predicted_rssi = Math.max(
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max_predicted_rssi,
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next_prediction.arraySync()[0][0]
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);
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}
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max_predicted_rssi = normalise(max_predicted_rssi,
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{ min: 0, max: 1 },
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{
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min: this.index.properties.rssi_min,
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max: this.index.properties.rssi_max
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}
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);
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let stats = {
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rssi_min: Infinity,
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rssi_max: -Infinity
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};
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for(let lat = this.map_bounds.south; lat < this.map_bounds.north; lat += Config.step.lat) {
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let next_row = await worker_predict_row(lat);
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let lng = this.map_bounds.west;
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for(let value of next_row) {
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// Keep up with the statistics
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if(value > stats.rssi_max)
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stats.rssi_max = value;
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if(value < stats.rssi_min)
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stats.rssi_min = value;
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// Generate the GeoJSON feature for this cell of the map
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coverage.push({
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type: "Feature",
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geometry: {
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@ -125,12 +196,16 @@ class LayerAI {
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]
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},
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properties: {
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colour: colour_scale(max_predicted_rssi).toString()
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colour: colour_scale(value).toString()
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}
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})
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});
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lng += Config.step.lng;
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}
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}
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console.log(stats);
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return coverage;
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}
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}
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26
client_src/js/Worker/AI.worker.mjs
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26
client_src/js/Worker/AI.worker.mjs
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@ -0,0 +1,26 @@
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export default function(self) {
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let ai_wrapper = new AIWrapper();
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self.addEventListener("message", async (event) => {
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console.log(event.data);
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switch(event.data.event) {
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case "setup":
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await ai_wrapper.setup(event.data.setup_info);
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self.postMessage({
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"event": "setup-complete"
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});
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break;
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case "predict-row":
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let message = await ai_wrapper.predict_row(event.data.latitude);
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message.event = "result";
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self.postMessage(message);
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break;
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case "end":
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self.close();
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break;
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}
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});
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}
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84
client_src/js/Worker/AIWrapper.mjs
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84
client_src/js/Worker/AIWrapper.mjs
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@ -0,0 +1,84 @@
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"use strict";
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import path from 'path';
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import {
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loadLayersModel as tf_loadLayersModel,
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tensor as tf_tensor
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} from '@tensorflow/tfjs';
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import { normalise } from '../../common/Math.mjs';
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import Config from '../ClientConfig.mjs';
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class AIWrapper {
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constructor() {
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this.setup_complete = false;
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this.map_bounds = null;
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this.index = null;
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this.gateways = new Map();
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}
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async setup({ bounds, index }) {
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this.map_bounds = bounds;
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this.index = index;
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for(let gateway of this.index.index) {
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this.gateways.set(
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gateway.id,
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await tf_loadLayersModel(`${window.location.href}/${path.dirname(Config.ai_index_file)}/${gateway.id}/model.json`)
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);
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}
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this.setup_complete = true;
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}
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predict_row(lat) {
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if(!setup_complete)
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throw new Error("Error: Can't do predictions until the setup is complete.");
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let results = [],
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stats = {
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rssi_min: Infinity,
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rssi_max: -Infinity
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};
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for(let lng = this.map_bounds.west; lng < this.map_bounds.east; lng += Config.step.lng) {
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let max_predicted_rssi = -Infinity;
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for(let [, ai] of this.gateways) {
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let next_prediction = this.predict_value(lat, lng)
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max_predicted_rssi = Math.max(
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max_predicted_rssi,
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next_prediction
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);
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}
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max_predicted_rssi = normalise(max_predicted_rssi,
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{ min: 0, max: 1 },
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{
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min: this.index.properties.rssi_min,
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max: this.index.properties.rssi_max
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}
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);
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if(max_predicted_rssi > stats.rssi_max)
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stats.rssi_max = max_predicted_rssi;
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if(max_predicted_rssi < stats.rssi_min)
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stats.rssi_min = max_predicted_rssi;
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result.push(max_predicted_rssi);
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}
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return { result, stats };
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}
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predict_value(latitude, longitude) {
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return ai.predict(
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tf_tensor([ latitude, longitude ], [1, 2])
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).arraySync()[0][0];
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}
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}
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export default AIWrapper;
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9
package-lock.json
generated
9
package-lock.json
generated
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@ -3892,6 +3892,15 @@
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"terser": "^4.1.0"
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}
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},
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"rollup-plugin-webworkify": {
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"version": "0.0.4",
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"resolved": "https://registry.npmjs.org/rollup-plugin-webworkify/-/rollup-plugin-webworkify-0.0.4.tgz",
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"integrity": "sha512-GvDPdz7qeakeB26cinVpxPgOBWHx/p3xua/itRXZ/30gGOK5QZeb/iu/9V4M7Zuhwmo2UPR1rViVX8OCqmhi1g==",
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"dev": true,
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"requires": {
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"rollup-pluginutils": "^2"
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}
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},
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"rollup-pluginutils": {
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"version": "2.8.1",
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"resolved": "https://registry.npmjs.org/rollup-pluginutils/-/rollup-pluginutils-2.8.1.tgz",
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@ -43,6 +43,7 @@
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"rollup-plugin-commonjs": "^10.0.1",
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"rollup-plugin-node-resolve": "^5.2.0",
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"rollup-plugin-postcss": "^2.0.3",
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"rollup-plugin-replace": "^2.2.0"
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"rollup-plugin-replace": "^2.2.0",
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"rollup-plugin-webworkify": "0.0.4"
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}
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}
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import { terser } from "rollup-plugin-terser";
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import replace from 'rollup-plugin-replace';
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import builtins from '@joseph184/rollup-plugin-node-builtins';
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import webworkify from 'rollup-plugin-webworkify';
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// import json from 'rollup-plugin-json';
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import postcss_import from 'postcss-import';
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}),
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webworkify({
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pattern: '**/*.worker.mjs'
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}),
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postcss({
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plugins: [
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postcss_import({}),
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