2d:null 2e:["$","title",null,{"children":"LTL Shipping for .... | Texoport's Workspace | Observable"}] 33:T54c,## Approach * We arbitrarily select four cities in the USA, Columbus, Los Angeles, Detroit, and Austin and select Columbus as the origin city * For each of the above cities, we arbitrarily select a hub, and several companies that work with said hub * We randomly generate between 8 and 10 items to be shipped from each company in Columbus. An item could be a fridge, a washing machine, an AC, or a dish washer. We specify that both fridges and washing machines require the use of liftgates to dismount, so they must be assigned to trucks that have them * Using the *Flexible Directions* API, we find optimal paths for trucks from each of the companies close to Columbus to the Columbus Hub * We allocate ${inputs.nTrucksAtOriginHub} long haul trucks to the Columbus Hub, and use the *Route Optimization API* to find optimal paths and item distributions for each of the trucks. The capacity of each long haul truck is **${inputs.longHaulTruckCapacity} pounds**. * We allocate ${inputs.nTrucksAtDestinationHubs} short haul trucks to each of the Destination Hubs, and the capacity of each short haul truck is **${inputs.shortHaulTruckCapacity} pounds**. * Once the items have made their way to the Destination Hubs, we use the *Route Optimization API* once again to distribute them to short haul trucks, to be taken to their destinations.34:T4ac,mvrpInputs = { const locations = []; const pickupLocationIndex = 0; locations.push(transformPoint(data.origin.hub.location)); let locationIndex = 1; let pickupId = 0; let deliveryId = 0; let jobId = 0; const jobs = []; const hubLocationIndices = {}; for (const cityCode of _.keys(data.destinations)) { hubLocationIndices[cityCode] = locationIndex++; const hubLocation = data.destinations[cityCode].hub.location; locations.push(transformPoint(hubLocation)); } const items = _.flatMap(data.origin.companies, "items"); for (const item of items) { const deliveryLocationIndex = hubLocationIndices[item.regionId]; jobs.push({ id: jobId++, location_index: deliveryLocationIndex, delivery: [itemWeights[item.type]], // akin to amount pickup: [itemWeights[item.type]] // akin to amount }); } const vehicles = []; for (const truck of trucksAtOriginHub) { vehicles.push({ id: truck.id, capacity: [truck.capacity], start_index: 0 }); } return { depots: [{ id: 0, location_index: 0 }], locations: { id: 1, location: locations.join("|") }, jobs, vehicles }; }35:T5f7,mvrpFromDestinationHubs = { async function performMVRP(cityCode) { const destination = data.destinations[cityCode]; const locations = [transformPoint(destination.hub.location)]; const hubLocationIndex = 0; const items = _.flatMap(data.origin.companies, (c) => c.items).filter( (c) => c.regionId === cityCode ); let jobId = 0; const jobs = []; let locationIndex = 1; for (let i = 0; i < items.length; i++) { const item = items[i]; const company = data.destinationsMap.get(item.destinationId); jobs.push({ id: jobId++, delivery: [itemWeights[item.type]], location_index: locationIndex++, skills: itemSkills[item.type] }); locations.push(transformPoint(company.location)); } let vehicles = []; for (let i = 0; i < inputs.nTrucksAtDestinationHubs; i++) { vehicles.push({ id: i, // randomly decide if a truck has a liftgate or not skills: _.random() ? [] : [0], start_index: hubLocationIndex, capacity: [inputs.shortHaulTruckCapacity], // get the truck to return to the destination hub end_index: hubLocationIndex }); } const result = await MVRP({ locations: { id: 1, location: locations.join("|") }, jobs, vehicles }); return { cityCode, ...result }; } const destinationKeys = _.keys(data.destinations); return Promise.all(_.map(destinationKeys, performMVRP)); }36:T42d,async function MVRP(data) { const optimizeRequestUrl = `https://api.nextbillion.io/optimise-mvrp?` + `key=${API_KEY}`; const optimizeRequest = await axios .post(optimizeRequestUrl, { ...data, options: { objective: { minimise_num_depots: false, travel_cost: "distance" }, routing: { mode: "truck" } } }) .then((res) => res.data); const mvrpRequestId = optimizeRequest.id; const previewurl = `https://nb-playground-staging.netlify.app/optimization-tester?apiKey=${API_KEY}&requestID=${mvrpRequestId}`; const getResultUrl = `https://api.nextbillion.io/optimise-mvrp/result?id=${mvrpRequestId}&key=${API_KEY}`; // Wait until the Route Optimization result is ready let attempts = 0; while (attempts < 10) { const result = await axios({ url: getResultUrl, method: "GET" }); if ( result.data && result.data.status === "Ok" && result.data.message == "" ) { return result.data; } attempts++; await new Promise((resolve) => setTimeout(resolve, 5 * 1000)); } }37:T750,data = { const cityCodes = _.keys(CITIES); const pickDetails = (info) => _.pick(info, ["name", "location", "postalCode"]); const destinationRegionMap = new Map(); let destinationId = 0; let destinations = {}; const destinationsMap = new Map(); for (const [cityCode, locations] of Object.entries(initialData)) { if (cityCode === "columbus") continue; const companies = []; for (let i = 0; i < locations.length; i++) { if (i === 0) continue; const id = destinationId; destinationRegionMap.set(destinationId, locations[i].city); destinationsMap.set(destinationId, locations[i]); companies.push({ id, ...pickDetails(locations[i]) }); destinationId++; } destinations[cityCode] = { hub: pickDetails(locations[0]), companies }; } const nDestinations = _.flatMap(_.values(destinations), "companies").length; const originLocations = initialData["columbus"]; let truckIdx = 0; const origin = { hub: pickDetails(originLocations[0]), companies: _.map(originLocations.slice(1), (info) => { const details = pickDetails(info); const nItems = _.random(8, 10); const itemTypes = _.map(_.times(nItems), () => _.sample(_.keys(itemWeights)) ); const truck = { name: `${faker.vehicle.manufacturer()} ${faker.vehicle.model()}`, vin: faker.vehicle.vin(), id: truckIdx++ }; const items = _.map(itemTypes, (itemType) => { const destinationId = _.random(nDestinations - 1); return { type: itemType, destinationId, regionId: destinationRegionMap.get(destinationId) }; }); return { ...details, items, truck }; }) }; return { origin, destinations, destinationsMap }; }38:T49c,CITIES = { return { columbus: { name: "Columbus", state: "Ohio", centroid: [-83.001647, 39.963483], addresses: [ "240 E 5th Ave #376", "3374 Dempsey Rd", "5465 Village Grove Ln", "4320 Grouse Ct", "210 Cross St, Unionville Center" ] }, austin: { name: "Austin", state: "Texas", centroid: [-97.7431, 30.2672], addresses: [ "5005 Woodrow Ave", "1329 Dalton Ln", "900 Bouldin Ave", "7409 Ranch Rd 620 N", "3651 E Whitestone Blvd" ] }, la: { name: "Los Angeles", state: "California", centroid: [-118.243683, 34.052235], addresses: [ "727 San Pedro St", "151 N Garfield Ave", "1249 W Gage Ave", "11745 Idalene St", "11454 Segrell Way" ] }, detroit: { name: "Detroit", state: "Michigan", centroid: [-83.045753, 42.331429], addresses: [ "9300-9398 John R St", "20729 W Seven Mile Rd", "522 St Clair Ave, Grosse Pointe", "7143 Plainview Ave", "16351 E 10 Mile Rd" ] } }; }39:[{"id":"74cd69efd767c32e0db39605c9243b0a4b4b9dbdd03ded587f722b4dabe1ad786a70a094cb96bdf27aef23be1defaceb44616e26a43b6334b8495f3f44630ba0","href":"https://static.observableusercontent.com/files/74cd69efd767c32e0db39605c9243b0a4b4b9dbdd03ded587f722b4dabe1ad786a70a094cb96bdf27aef23be1defaceb44616e26a43b6334b8495f3f44630ba0","name":"image.png","type":"image/png","lastModified":1691251947530.524,"size":301721},{"id":"74cd69efd767c32e0db39605c9243b0a4b4b9dbdd03ded587f722b4dabe1ad786a70a094cb96bdf27aef23be1defaceb44616e26a43b6334b8495f3f44630ba0","href":"https://static.observableusercontent.com/files/74cd69efd767c32e0db39605c9243b0a4b4b9dbdd03ded587f722b4dabe1ad786a70a094cb96bdf27aef23be1defaceb44616e26a43b6334b8495f3f44630ba0","name":"image@1.png","type":"image/png","lastModified":1691252386237.811,"size":301721},{"id":"74cd69efd767c32e0db39605c9243b0a4b4b9dbdd03ded587f722b4dabe1ad786a70a094cb96bdf27aef23be1defaceb44616e26a43b6334b8495f3f44630ba0","href":"https://static.observableusercontent.com/files/74cd69efd767c32e0db39605c9243b0a4b4b9dbdd03ded587f722b4dabe1ad786a70a094cb96bdf27aef23be1defaceb44616e26a43b6334b8495f3f44630ba0","name":"image@2.png","type":"image/png","lastModified":1691253267804.422,"size":301721}] 31:{"id":"48fc2d7a5c4f56b9","slug":"ltl-shipping","title":"LTL Shipping for ....","thumbnail":"2cfee7ef7ec3780c78d78de50d0ebbb94af9705b4e2ac6906ac559093f4208c9","access_level":"public","create_time":"$D2023-08-02T17:40:04.361Z","update_time":"$D2023-08-08T05:34:16.087Z","view_time":null,"first_public_time":"$D2023-08-02T17:40:04.361Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"787ce1766e2f8353","login":"texoslab","name":"Texoport's Workspace","avatar_url":"https://avatars-next.observableusercontent.com/c682b2e46f70c9b6b07bd1cb3e910d7f8e5a9c164a6363b06edaf7bb932301ff","tier":"starter_2024"},"version":2110,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"3a4237a77d0ee063","login":"texoport","name":"Texoport","avatar_url":"https://avatars-next.observableusercontent.com/cc7f2661bbd43a7d4b462619d45c31c6398091f9b8e8b000546719e1bdf9cc36","tier":null}],"members":[{"type":"individual","id":"3a4237a77d0ee063","login":"texoport","name":"Texoport","avatar_url":"https://avatars-next.observableusercontent.com/cc7f2661bbd43a7d4b462619d45c31c6398091f9b8e8b000546719e1bdf9cc36","tier":null,"role":"editor"},{"type":"team","id":"787ce1766e2f8353","login":"texoslab","name":"Texoport's Workspace","avatar_url":"https://avatars-next.observableusercontent.com/c682b2e46f70c9b6b07bd1cb3e910d7f8e5a9c164a6363b06edaf7bb932301ff","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":2,"collection":null,"type":"notebook","body":{"title":"LTL Shipping for ....","cells":[{"id":0,"value":"# LTL Shipping for ....","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1864,"value":"## Background\nIn this notebook, we showcase an implementation of Volume LTL using several of NextBillion.ai's APIs, including the Route Optimization API, the Flexible Directions API, and the Web Maps SDK.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1875,"value":"## Problem Statement\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2072,"value":"Change problem statement: delivering to local electrical shops\n\ngive destination companies random electric shop names like Tom's Appliances blah blah\n\nchange the problem statement so that each origin place is a manufacturer of one particular product; use real companies\n\ndo 50-100 items per manufacturer","pinned":true,"hidden":true,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1883,"value":"$33","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1982,"value":"## Constraints\nFor the sake of simplicity, we make the following assumptions in this solution. Please note that the Route Optimization API is capable of handling more complex scenarios\n* We only take into account the weight of items, and not their volume. The *Route Optimization API* is [capable of handling multi-dimensional quantities](https://docs.nextbillion.ai/docs/optimization/api/route-optimization-v2).","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2058,"value":"itemWeights","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1994,"value":"Note: this demo has the possibility of generating a large number of Route Optimization transactions against the key being used and should only be used with evaluation/demo API keys.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":45,"value":"viewof API_KEY = secret2(\"apiKey\", {\n title: \"NextBillion.ai API Key\",\n submit: \"Set\",\n description:\n \"Contact support@nextbillion.ai to get your API key\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1999,"value":"## Parameters","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1055,"value":"viewof inputs = {\n return guard(({ template, ...rest }) => {\n return Inputs.form(\n {\n nTrucksAtOriginHub: Inputs.select([5, 10, 15], {\n label: \"Number of trucks (long haul) at Origin hub\",\n value: 10\n }),\n nTrucksAtDestinationHubs: Inputs.select([5, 10, 15], {\n label: \"Number of trucks (short haul) at the Destination hubs (each)\",\n value: 10\n }),\n longHaulTruckCapacity: Inputs.select([10000, 15000, 20000], {\n label: \"Long haul truck capacity\",\n value: 5000\n }),\n shortHaulTruckCapacity: Inputs.select([2000, 3000, 4000, 5000], {\n label: \"Short haul truck capacity\",\n value: 1000\n })\n },\n {\n template\n }\n );\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2093,"value":"^ rename short haul truck capacity to final delivery truck capacity","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2099,"value":"A table showing manufacturers and their products(one product each, for now), along with product details","pinned":false,"hidden":true,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1058,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2006,"value":"## Data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2040,"value":"### Items","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2044,"value":"add who is shipping","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":2066,"value":"itemsTable.filter((i) => i[\"Dest City\"] === \"Los Angeles\").length","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2018,"value":"itemsTable = _.flatMap(data.origin.companies, \"items\").map((item) => {\n const destination = data.destinationsMap.get(item.destinationId);\n return {\n \"Item Type\": _.replace(item.type, \"_\", \" \"),\n \"Dest City\": CITIES[item.regionId].name,\n \"Dest Addr\": destination.name,\n \"Dest Coordinates\": destination.location.join(\", \")\n };\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2020,"value":"itemsTable","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":621,"value":"### Origin Companies to Origin Hub","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":768,"value":"companiesToOriginHubDirections = Promise.all(\n data.origin.companies.map((company) =>\n getDirection(company.location, data.origin.hub.location)\n )\n)","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2046,"value":"icons\n\ndistance + eta(travel time) on road segments\n\ncall it origin hub","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":891,"value":"createMap(\"map-2\", CITIES.columbus.centroid, 10, (nbmap) => {\n drawHub(nbmap.map, data.origin.hub);\n data.origin.companies.forEach((company) => drawCompany(nbmap.map, company));\n companiesToOriginHubDirections.forEach((directions, i) => {\n drawRoute(nbmap.map, `route-${i}`, directions[0].geometry, COLORS[i]);\n });\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1028,"value":"### MVRP from the Origin Hub to the Destination Hubs","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1361,"value":"trucksAtOriginHub = {\n const trucks = [];\n\n for (let i = 0; i < inputs.nTrucksAtOriginHub; i++) {\n trucks.push({\n id: i,\n name: LONG_HAUL_TRUCKS[i],\n vin: faker.vehicle.vin(),\n capacity: inputs.longHaulTruckCapacity\n });\n }\n\n return trucks;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1034,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1402,"value":"mvrpLongHaul = {\n const result = await MVRP(mvrpInputs);\n return result;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1485,"value":"longHaulRoutes = mvrpLongHaul.result.routes","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2055,"value":"table of trucks info\n* name, destination\nalso show which long haul truck got how many number of x items ","pinned":false,"hidden":true,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1492,"value":"viewof selectedLongHaulRoute = Inputs.select(longHaulRoutes, {\n format: (route) => trucksAtOriginHub[route.vehicle].name\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1495,"value":"createMap(\"long-haul-mvrp-result\", USA_CENTROID, 3, (nbmap) => {\n drawRoute(nbmap.map, \"route\", selectedLongHaulRoute.geometry);\n\n function getUniqueCoordinates(coords) {\n const uniqueCoords = new Set(coords.map(JSON.stringify));\n return Array.from(uniqueCoords).map(JSON.parse);\n }\n const uniqueSteps = getUniqueCoordinates(\n selectedLongHaulRoute.steps.map((s) => s.location)\n );\n\n uniqueSteps.forEach((location, idx) => {\n drawStepIdx(nbmap.map, location.slice().reverse(), idx + 1);\n });\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1612,"value":"### Delivering orders from the Destination Hub to Stores","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":1640,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1707,"value":"viewof selectedDestination = Inputs.select(mvrpFromDestinationHubs, {\n format: (r) => CITIES[r.cityCode].name\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1835,"value":"viewof selectedDestinationTrucks = Inputs.checkbox(\n selectedDestination.result.routes,\n {\n format: (r) => `Truck ${r.vehicle}`,\n value: selectedDestination.result.routes\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1759,"value":"createMap(\n \"map-3\",\n CITIES[selectedDestination.cityCode].centroid,\n 10,\n (nbmap) => {\n data.destinations[selectedDestination.cityCode].companies.map((company) => {\n drawCompany(nbmap.map, company);\n });\n drawHub(nbmap.map, data.destinations[selectedDestination.cityCode].hub);\n selectedDestinationTrucks.forEach((route, i) => {\n drawRoute(nbmap.map, `route-${i}`, route.geometry, COLORS[route.vehicle]);\n });\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":463,"value":"# Functions","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":818,"value":"async function getDirection(\n origin,\n destination,\n options = {\n mode: \"truck\",\n option: \"flexible\",\n route_type: \"shortest\",\n truck_size: \"200,210,600\"\n }\n) {\n const baseUrl = \"https://api.nextbillion.io/directions/json\";\n const from = `origin=${transformPoint(origin)}`;\n const to = `destination=${transformPoint(destination)}`;\n const mode = `mode=${options.mode}`;\n const option = `option=${options.option}`;\n const truck_size = `truck_size=${option.truck_size}`;\n const routeType = `route_type=${options.route_type}`;\n const url = `${baseUrl}?${from}&${to}&${mode}&${routeType}&${option}&key=${API_KEY}`;\n const result = await fetch(url);\n return result.json().then((r) => r.routes);\n}","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":894,"value":"function drawRoute(map, source, geometry, color = \"#7e22ce\", width = 3) {\n if (!map.getSource(source)) {\n map.addSource(source, {\n type: \"geojson\",\n data: {\n type: \"Feature\",\n geometry: {\n type: \"LineString\",\n coordinates: nextbillion.utils.polyline\n .decode(geometry, 5)\n .map((c) => c.reverse())\n }\n }\n });\n\n map.addLayer({\n id: source,\n type: \"line\",\n source,\n layout: { \"line-join\": \"round\", \"line-cap\": \"round\" },\n paint: { \"line-color\": color, \"line-width\": width }\n });\n }\n}","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":815,"value":"function transformPoint(p) {\n return [p[1], p[0]].join(\",\");\n}","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":770,"value":"$36","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":588,"value":"function drawHub(map, hub) {\n const hubLocation = { lat: hub.location[1], lng: hub.location[0] };\n const element = document.createElement(\"div\");\n element.innerText = \"Origin Hub\";\n element.style.fontSize = \"20px\";\n element.style.padding = \"5px\";\n element.style.backgroundColor = \"black\";\n element.style.color = \"white\";\n new nextbillion.maps.Marker({ element }).setLngLat(hubLocation).addTo(map);\n}","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1538,"value":"function drawStepIdx(map, location, stepIdx) {\n const stepIdxLocation = { lat: location[1], lng: location[0] };\n const element = document.createElement(\"div\");\n element.innerText = stepIdx;\n element.style.fontSize = \"15px\";\n element.style.padding = \"5px\";\n element.style.backgroundColor = \"gray\";\n element.style.color = \"white\";\n element.style.borderRadius = \"5em\";\n new nextbillion.maps.Marker({ element })\n .setLngLat(stepIdxLocation)\n .addTo(map);\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":590,"value":"function drawCompany(map, company) {\n const element = document.createElement(\"div\");\n element.innerHTML = `\n

Company

${company.name}

\n `;\n element.style.fontSize = \"15px\";\n element.style.padding = \"5px\";\n element.style.backgroundColor = \"gray\";\n element.style.color = \"white\";\n new nextbillion.maps.Marker({ element })\n .setLngLat({\n lat: company.location[1],\n lng: company.location[0]\n })\n .addTo(map);\n}","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":466,"value":"function* createMap(id, center, zoom = 10, onLoad) {\n if (!data) return;\n const container = html`\n

\n `;\n yield container;\n\n const nbmap = (container.value = new nextbillion.maps.Map({\n container: document.getElementById(id),\n center: {\n lat: center[1],\n lng: center[0]\n },\n zoom,\n maxZoom: 15,\n minZoom: 0,\n style: \"https://api.nextbillion.io/maps/streets/style.json\",\n scrollZoom: true\n }));\n\n nbmap.on(\"load\", () => {\n onLoad(nbmap);\n });\n}","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":457,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":57,"value":"### Constants","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":58,"value":"itemWeights = {\n return {\n ac: 300,\n fridge: 1000,\n washing_machine: 800,\n dish_washer: 500\n };\n}","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1411,"value":"itemSkills = {\n return {\n ac: [],\n fridge: [0],\n washing_machine: [0],\n dish_washer: []\n };\n}","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":648,"value":"CITY_CENTROIDS = _.mapValues(CITIES, (c) => c.centroid)","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1156,"value":"initialData = {\n // We use the NextBillion Geocoding API to retrieve information about an address\n async function geocode(name, cityCode) {\n const city = CITIES[cityCode];\n const baseUrl = \"https://api.nextbillion.io/h/geocode\";\n const q = `q=${name}`;\n const qq = `qq=city=${city.name};state=${city.state}`;\n const country = `in=countryCode:USA`;\n const url = `${baseUrl}?key=${API_KEY}&${qq}&${q}&limit=1&${country}`;\n const result = await fetch(url).then((r) => r.json());\n const location = result.items[0].position;\n return {\n name,\n city: cityCode,\n location: [location.lng, location.lat],\n postalCode: result.items[0].address.postalCode\n };\n } \n\n const result = await Promise.all(\n _.flatMap(_.keys(CITIES), (c) =>\n CITIES[c].addresses.map((address) => [address, c])\n ).map((address) => geocode(address[0], address[1]))\n ).then((result) => _.groupBy(result, \"city\"));\n\n return result;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":255,"value":"$37","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1380,"value":"LONG_HAUL_TRUCKS = [\n \"T680\",\n \"579\",\n \"Cascadia\",\n \"VNL\",\n \"LT\",\n \"Anthem\",\n \"5700XE\",\n \"T880\",\n \"389\",\n \"Coronado\",\n \"VNR\",\n \"LoneStar\",\n \"Pinnacle\",\n \"4900\",\n \"W990\"\n]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1524,"value":"USA_CENTROID = [-99.0909, 39.8355]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":130,"value":"$38","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1829,"value":"COLORS = [\n \"#e6194b\",\n \"#3cb44b\",\n \"#ffe119\",\n \"#4363d8\",\n \"#f58231\",\n \"#911eb4\",\n \"#46f0f0\",\n \"#f032e6\",\n \"#bcf60c\",\n \"#fabebe\",\n \"#008080\",\n \"#e6beff\",\n \"#9a6324\",\n \"#fffac8\",\n \"#800000\",\n \"#aaffc3\",\n \"#808000\",\n \"#ffd8b1\",\n \"#000075\",\n \"#808080\"\n]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1832,"value":"_.sampleSize(COLORS, 4)","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":53,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":629,"value":"### Imports","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":469,"value":"nextbillion.setApiKey(API_KEY)","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":418,"value":"faker = require(\"https://unpkg.com/faker@5.3.1/dist/faker.min.js\")","pinned":true,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":775,"value":"axios = {\n let axios = await require(\"axios\");\n return axios;\n}","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":453,"value":"import {\n guard,\n colors,\n renderPolygon,\n d3Delaunay,\n findExtremeCoordinates\n} from \"@texoslab/nbai-helpers\"","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"import {\n nextbillion,\n secret2,\n styles,\n routeStyles\n} from \"@nbai/nextbillion-ai-dependencies\"","pinned":false,"hidden":true,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":533,"value":"html`Add the stylesheet for the NB.ai SDK
<link href=\"https://maps-gl.nextbillion.io/maps/v2/api/css\" rel=\"stylesheet\">`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":554,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"}],"files":"$W39","stdlib":"1","titling":"auto"}} 32:"$31:body"