31:T45c,## What this does Andriy Burkov noticed that by appending 'vs' to a google query, google will helpfully autosuggest alternatives to the thing ([linkedIn.com](https://www.linkedin.com/posts/andriyburkov_this-simple-hack-will-save-you-a-ton-of-time-activity-6675799581655203840-1XuH/ )). ![image@2.png](${await FileAttachment("image@2.png").url()}) David Foster realized that you could take those suggestions and apply to trick again to find more alternatives. When you repeatedly do this you can generate a nice graph which will span a topic area ([medium.com](https://medium.com/applied-data-science/the-google-vs-trick-618c8fd5359f)). David had some nice tricks for pruning the graph based on connectivity to try and keep the algorithm on topic. What was missing was an online tool for doing this. So this tool implements David's algorithm but online. It follows the principles of moldable development, it is end user programmable, so if you want to explore your own ideas from expanding google auto-suggestions you can just [fork this notebook](https://observablehq.com/@observablehq/fork-suggest-merge). 32:T525,## Controls

control help

${md` The UI controls below let you control the expansion of a topic. *reinitialize* - resets all state *starting term* - the thing are we looking alternatives for. Put whatever you want to research in here! *single term results only* - whether to ignore suggestions that have more than one word (*e.g.* redis pro). Normally not very useful but sometimes it can help prune the results set. *max term fanout* - How many suggestions should we feedback each iteration? If you use a high number, the graph will find lots of very weakly related concepts. If you use a low number it with be very focussed on the target term and only on close alternatives. David Foster defaults to 5, I have needed high numbers to dial up the sensitivity. *max distance* - How far from the starting term should we explore? *min connectedness* - the number of disjoint pathways that must be present to a vertex to be included in the ego graph. This often has the effect of pruning topic confusions caused by synonyms. Note you can also manually prune vertices too if needed. *auto run* - controls whether the algorithm is run a single step at a time or fully automatic. ⚠️ If you think your search has gone off the rails, untick this to halt the search!`}

33:T7d9,async function step() { if (unvisited.size > 0) { console.log("step..."); function findNearestUnvisited(v) { var current = stepDijkstra({ seed: { id: v, distance: 0 }, adjacent: (u) => [...(edges.get(u)?.keys() || [])] .map((v) => ({ id: v, distance: edgeDistance(u, v) })) .filter((e) => !exclude.has(e.id)) }); while (current.lastVertex && !unvisited.has(current.lastVertex.id)) { current = stepDijkstra(current); } return current.lastVertex?.id; } const u = findNearestUnvisited(initialTerm); unvisited.delete(u); const neighbours = await suggestionsFromGoogle({ term: u }); for (let edge of neighbours) { if (!edges.has(edge.source)) { edges.set(edge.source, new Map()); } const outgoingEdges = edges.get(edge.source); let v = edge.target; outgoingEdges.set(v, { source: edge.source, target: edge.target, weight: edge.weight }); const alt = distance.get(edge.source) + edgeDistance(edge.source, edge.target); if (distance.get(v) === undefined) { distance.set(v, alt); if (alt < maxDistance) unvisited.add(v); } else if (alt < distance.get(v)) { distance.set(v, alt); } } console.log("step: notify epoch"); try { viewof epoch.value = viewof epoch.value + 1; viewof epoch.dispatchEvent(new Event("input", { bubbles: true })); } catch (err) { console.log(err); } if (unvisited.size == 0) { console.log("step: nearly ending, notify latest version"); viewof version.value = viewof version.value + 1; viewof version.dispatchEvent(new Event("input", { bubbles: true })); } else { if (viewof autoRun.value) { // continue setTimeout(step, 100); } } } else { console.log("step: ending, no unvisted nodes"); } }34:[{"id":"d35859fb70678f8eecea94791dc2f07a19fe255bf78809a814927a01948fd29e013d73245fadebb4da402baca166f7b13b99a9943e963f9eb4d2411a3ec1f2b7","href":"https://static.observableusercontent.com/files/d35859fb70678f8eecea94791dc2f07a19fe255bf78809a814927a01948fd29e013d73245fadebb4da402baca166f7b13b99a9943e963f9eb4d2411a3ec1f2b7","name":"poodle (7).json","type":"application/json","lastModified":1650006676787.163,"size":37085},{"id":"a80e9adffe3237ce8402f769fcb5423faaf8dcbbeca57f6b2574472950555a06bc6789e9c2df634a86deb59ec2c2a81ebf258a9d2d52e9fc003bc5de520bb19d","href":"https://static.observableusercontent.com/files/a80e9adffe3237ce8402f769fcb5423faaf8dcbbeca57f6b2574472950555a06bc6789e9c2df634a86deb59ec2c2a81ebf258a9d2d52e9fc003bc5de520bb19d","name":"image@1.png","type":"image/png","lastModified":1649665106282.24,"size":207689},{"id":"17ad1408bf1c54d4874bb9a2dcccb12109e06ba19a3982f788292b11cfbb4a8e612461bfac0c6cd412a5202f638d78a3edc1fd4cd19dbe20938f49dee65c9c44","href":"https://static.observableusercontent.com/files/17ad1408bf1c54d4874bb9a2dcccb12109e06ba19a3982f788292b11cfbb4a8e612461bfac0c6cd412a5202f638d78a3edc1fd4cd19dbe20938f49dee65c9c44","name":"image@2.png","type":"image/png","lastModified":1649665491394.14,"size":63624},{"id":"9c61cbb2aa4ecacfe5089fb149d1f634a18ede7108dcc3a1dacd2a9a2298efe92468db45f9c142f6c26594ce4dac49fbdf5f8941e5c0175edb19959e48e97ba5","href":"https://static.observableusercontent.com/files/9c61cbb2aa4ecacfe5089fb149d1f634a18ede7108dcc3a1dacd2a9a2298efe92468db45f9c142f6c26594ce4dac49fbdf5f8941e5c0175edb19959e48e97ba5","name":"poodle (6).json","type":"application/json","lastModified":1649927626127.743,"size":57357},{"id":"e03b974a2dcc8317f3b9eb2385cdf572a12641671b4adaeae7941bc6efdfcdc0df70899ce536de7a6bc39b33acd09f9d3f2d2725ae5238ac098cde74f6d223b8","href":"https://static.observableusercontent.com/files/e03b974a2dcc8317f3b9eb2385cdf572a12641671b4adaeae7941bc6efdfcdc0df70899ce536de7a6bc39b33acd09f9d3f2d2725ae5238ac098cde74f6d223b8","name":"egograph.png","type":"image/png","lastModified":1650010871665.211,"size":411124}] 2f:{"title":"The Google 'VS' trick","cells":[{"id":0,"value":"# The Google 'VS' trick\n\nOutsource tedious research to the hive mind. This tool implements the [Google Search 'VS' trick](https://medium.com/applied-data-science/the-google-vs-trick-618c8fd5359f) to find common alternatives to things. Starting with a term like 'Poodle', we ask Google for search suggestions of 'Poodle VS' which will find alternatives to poodles that people often consider on the internet. This can be used to perform basic market research (e.g. find me React alternatives), medicine (find me ibuprofen alternatives) and product choices (Peloton alternatives) it will even find you choices for philosophical schools-of-thought!","pinned":false,"hidden":false,"mode":"md"},{"id":1481,"value":"FileAttachment(\"egograph.png\").image({ style: \"max-width: 640px\" })","pinned":false,"hidden":false,"mode":"ojs"},{"id":1025,"value":"$31","pinned":false,"hidden":false,"mode":"md"},{"id":953,"value":"## Login with a comment\n\nThis kind of tool could easily spam Google. I have enacted a login requirement to prevent that from happening. It is part of system to enforce result pooling across users.\n\nSo you need an Observable account and to leave a comment on this notebook to use the tool.\n\n*also you can disable notifications in the notebook burger menu / settings*","pinned":false,"hidden":false,"mode":"md"},{"id":963,"value":"viewof user = createLogin()","pinned":false,"hidden":false,"mode":"ojs"},{"id":943,"value":"### Save & load","pinned":false,"hidden":false,"mode":"md"},{"id":297,"value":"htl.html`

${Inputs.button(\n \"download graph\",\n {\n reduce: () => {\n downloadObjectAsJson(\n {\n unvisited: [...unvisited],\n distance: [...distance.entries()],\n exclude: [...exclude],\n edges: allEdges,\n directed: false,\n links: links.map((l) => ({\n ...l,\n source: l.source.id,\n target: l.target.id\n })),\n nodes: [\n ...links.reduce((n, l) => {\n n.add(l.source);\n n.add(l.target);\n return n;\n }, new Set())\n ]\n },\n initialTerm\n );\n }\n }\n)}\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":746,"value":"viewof upload = fileInput({\n prompt: \"upload graph file to initialize\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":568,"value":"$32","pinned":false,"hidden":false,"mode":"md"},{"id":1291,"value":"Inputs.button(\"reset\", {\n label: \"reinitialize\",\n reduce: reset\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":212,"value":"viewof initialTermRaw = Inputs.bind(\n Inputs.text({\n minlength: 3,\n label: \"Starting term\",\n placeholder: \"term, e.g. redis\"\n }),\n localStorageView(\"topic_search_term\")\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":189,"value":"viewof SINGLE_RESULTS_ONLY = Inputs.bind(\n Inputs.toggle({\n label: \"Single term results only\"\n }),\n localStorageView(\"topic_search_singles\", { json: true })\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":180,"value":"viewof MAX_RESULTS = Inputs.bind(\n Inputs.range([1, 10], {\n label: \"max term fanout\",\n step: 1,\n value: 5\n }),\n localStorageView(\"topic_search_fanout\", { defaultValue: 5, json: true})\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":225,"value":"viewof maxDistance = Inputs.bind(\n Inputs.range([1, 200], { label: \"max distance\", step: 1, value: 5 }),\n localStorageView(\"topic_search_radius\", {defaultValue: 5, json: true})\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":564,"value":"viewof k = Inputs.bind(\n Inputs.range([1, 2], {\n label: \"min connectedness\",\n step: 1,\n value: 2\n }),\n localStorageView(\"topic_search_connectedness\", {\n defaultValue: 2\n })\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":319,"value":"viewof autoRun = (user,\nInputs.bind(\n Inputs.toggle({ label: \"auto run\", value: false }),\n localStorageView(\"topic_search_autorun\", {\n json: true\n })\n))","pinned":false,"hidden":false,"mode":"ojs"},{"id":240,"value":"(user,\nInputs.button(autoRun ? \"run\" : \"step\", {\n label: \"run algorithm\",\n reduce: step\n}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":1385,"value":"new Promise((resolve) =>\n setTimeout(\n () =>\n resolve(\n viewof user?.value?.uid\n ? md``\n : md`⚠️ you need to login to use this tool`\n ),\n 1000\n )\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":668,"value":"### last edge expansion","pinned":false,"hidden":false,"mode":"md"},{"id":626,"value":"Inputs.table(filteredSuggestions)","pinned":false,"hidden":false,"mode":"ojs"},{"id":368,"value":"## Ego Graph for ${initialTerm}","pinned":false,"hidden":false,"mode":"md"},{"id":437,"value":"viewof visualization","pinned":false,"hidden":false,"mode":"ojs"},{"id":1419,"value":"{\n if (visualization.selected)\n return Inputs.button(\"exclude selected vertex\", {\n reduce: () => deleteVertex(visualization.selected.id)\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1044,"value":"### Nodes","pinned":false,"hidden":false,"mode":"md"},{"id":1278,"value":"viewof results = Inputs.search(nodes)","pinned":false,"hidden":false,"mode":"ojs"},{"id":478,"value":"viewof toDelete = (epoch, Inputs.table(results, { sort: \"depth\" }))","pinned":false,"hidden":false,"mode":"ojs"},{"id":1054,"value":"toDelete.length == nodes.length\n ? md`*delete nodes by first selecting their hidden checkbox on the left*`\n : Inputs.button(\"exclude selected nodes\", {\n reduce: () => {\n toDelete.forEach((del) => {\n deleteVertex(del.id);\n });\n }\n })","pinned":false,"hidden":false,"mode":"ojs"},{"id":1309,"value":"allEdges = (epoch,\n[...edges.values()].reduce((acc, map) => acc.concat([...map.values()]), []))","pinned":false,"hidden":false,"mode":"ojs"},{"id":383,"value":"nodes = (epoch,\n[\n ...allEdges.reduce((set, edge) => {\n set.add(edge.source);\n set.add(edge.target);\n return set;\n }, new Set())\n]\n .map((n) => ({\n id: n,\n count: allEdges.reduce(\n (c, e) => c + (e.target === n ? 1 : 0) + (e.source === n ? 1 : 0),\n 0\n ),\n depth: distance.get(n)\n }))\n .filter((d) => d.depth < maxDistance))","pinned":false,"hidden":false,"mode":"ojs"},{"id":824,"value":"linksRaw = (epoch,\nallEdges\n .map((e) => ({\n ...e,\n source: nodes.find((n) => n.id === e.source),\n target: nodes.find((n) => n.id === e.target),\n distance: edgeDistance(e.source, e.target)\n }))\n .filter((l) => l.source && l.target))","pinned":false,"hidden":false,"mode":"ojs"},{"id":802,"value":"unidirectedLinks = linksRaw.filter((l) => {\n const source = l.source.id;\n const target = l.target.id;\n if (source < target) return true;\n else return !edges.get(`${target}->${source}`);\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":853,"value":"adj = {\n const adj = new Map();\n unidirectedLinks.forEach((link) => {\n if (!adj.has(link.source.id)) adj.set(link.source.id, []);\n if (!adj.has(link.target.id)) adj.set(link.target.id, []);\n adj.get(link.source.id).push(link.target.id);\n adj.get(link.target.id).push(link.source.id);\n });\n\n return adj;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":829,"value":"links = {\n if (k == 1) return unidirectedLinks;\n else if (k == 2) {\n // Do a quick DFS to the articulation points\n const articulations = articulationPoints(initialTerm, adj);\n const unvisisted = new Set([initialTerm]);\n const visited = new Set();\n while (unvisisted.size > 0) {\n const next = unvisisted.values().next().value;\n unvisisted.delete(next);\n visited.add(next);\n if (articulations.has(next) && next !== initialTerm) {\n } else {\n (adj.get(next) || [])\n .filter((v) => !visited.has(v))\n .forEach((v) => unvisisted.add(v));\n }\n }\n return unidirectedLinks.filter(\n (e) => visited.has(e.source.id) && visited.has(e.target.id)\n );\n } else {\n throw new Error();\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":434,"value":"chartData = (epoch,\n{\n directed: false,\n links: links.map((l) => ({ ...l, source: l.source.id, target: l.target.id })),\n nodes: [\n ...links.reduce((n, l) => {\n n.add(l.source);\n n.add(l.target);\n return n;\n }, new Set())\n ]\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":431,"value":"import { viewof visualization } with { chartData as data } from \"@tomlarkworthy/ego-graph\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":356,"value":"### algorithm state","pinned":false,"hidden":false,"mode":"md"},{"id":585,"value":"viewof version = Inputs.input(0)","pinned":false,"hidden":false,"mode":"ojs"},{"id":609,"value":"viewof epoch = Inputs.input(0)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1004,"value":"initialTerm = initialTermRaw.toLowerCase()","pinned":false,"hidden":false,"mode":"ojs"},{"id":233,"value":"unvisited = new Set([initialTerm])","pinned":false,"hidden":false,"mode":"ojs"},{"id":1306,"value":"distance = new Map([[initialTerm, 0]])","pinned":false,"hidden":false,"mode":"ojs"},{"id":1402,"value":"exclude = (initialTerm, new Set())","pinned":false,"hidden":false,"mode":"ojs"},{"id":334,"value":"edges = (initialTerm, new Map())","pinned":false,"hidden":false,"mode":"ojs"},{"id":1305,"value":"edgeDistance = (u, v) =>\n (1 +\n 2 * MAX_RESULTS -\n (edges.get(u)?.get(v)?.weight || 0) -\n (edges.get(v)?.get(u)?.weight || 0)) /\n (2 * MAX_RESULTS + 1)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1304,"value":"import { step as stepDijkstra } from \"@tomlarkworthy/dijkstra\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":256,"value":"$33","pinned":true,"hidden":false,"mode":"ojs"},{"id":1328,"value":"uploadData = await upload.json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":757,"value":"onUpload = {\n unvisited.clear();\n distance.clear();\n edges.clear();\n uploadData.unvisited.forEach((v) => unvisited.add(v));\n uploadData.exclude.forEach((v) => exclude.add(v));\n uploadData.distance.forEach(([k, v]) => distance.set(k, v));\n uploadData.edges.forEach((e) => {\n if (!edges.has(e.source)) edges.set(e.source, new Map());\n edges.get(e.source).set(e.target, e);\n });\n viewof version.value += 1;\n viewof version.dispatchEvent(new Event(\"input\", { bubbles: true }));\n viewof epoch.value += 1;\n viewof epoch.dispatchEvent(new Event(\"input\", { bubbles: true }));\n\n return uploadData;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1378,"value":"onPageLoadInitialTerm = {\n if (!window.didPageLoad && viewof initialTermRaw.value === undefined) {\n viewof initialTermRaw.value = \"poodle\";\n viewof initialTermRaw.dispatchEvent(new Event(\"input\", { bubbles: true }));\n }\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":795,"value":"onPageLoad = {\n if (!window.didPageLoad && viewof initialTermRaw.value === \"poodle\") {\n window.didPageLoad = true;\n const data = await FileAttachment(\"poodle (7).json\").json();\n data.exclude.forEach((v) => exclude.add(v));\n data.unvisited.forEach((v) => unvisited.add(v));\n data.distance.forEach(([k, v]) => distance.set(k, v));\n data.edges.forEach((e) => {\n if (!edges.has(e.source)) edges.set(e.source, new Map());\n edges.get(e.source).set(e.target, e);\n });\n viewof version.value += 1;\n viewof version.dispatchEvent(new Event(\"input\", { bubbles: true }));\n viewof epoch.value += 1;\n viewof epoch.dispatchEvent(new Event(\"input\", { bubbles: true }));\n return data;\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":913,"value":"reset = () => {\n unvisited.clear();\n distance.clear();\n edges.clear();\n unvisited.add(initialTerm);\n distance.set(initialTerm, 0);\n viewof version.value += 1;\n viewof version.dispatchEvent(new Event(\"input\", { bubbles: true }));\n viewof epoch.value += 1;\n viewof epoch.dispatchEvent(new Event(\"input\", { bubbles: true }));\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1432,"value":"allEdges","pinned":true,"hidden":false,"mode":"ojs"},{"id":1449,"value":"allEdges.filter((e) => e.target === \"loveramics\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":1425,"value":"deleteVertex = (id) => {\n const edgesToDelete = allEdges.filter(\n (e) => e.source === id || e.target === id\n );\n edgesToDelete.forEach((e) => {\n if (e.source === id) edges.delete(id);\n if (e.target === id) {\n const outgoing = edges.get(e.source);\n if (outgoing) outgoing.delete(e.target);\n }\n });\n\n exclude.add(id);\n\n viewof epoch.value++;\n viewof epoch.dispatchEvent(new Event(\"input\", { bubbles: true }));\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":41,"value":"### suggestqueries.google.com","pinned":false,"hidden":false,"mode":"md"},{"id":163,"value":"defaultSuggestionsFilter = (suggestions, { term, seperator } = {}) => {\n term = term.toLowerCase();\n let w = MAX_RESULTS;\n return suggestions.reduce((suggestions, suggestion) => {\n if (\n suggestions.length < MAX_RESULTS &&\n suggestion.startsWith(term + \" \" + seperator + \" \", \"\")\n ) {\n // Trim \"term VS\" repeated prefix\n suggestion = suggestion.replace(term + \" \" + seperator + \" \", \"\");\n\n // If SINGLE_RESULTS_ONLY we check for a single term\n if (!SINGLE_RESULTS_ONLY || suggestion.split(\" \").length === 1) {\n // There may be several alternatives (e.g. covid vs flu vs cold\n const alternatives = suggestion.split(` ${seperator} `);\n alternatives.forEach((alternative) => {\n suggestions.push({\n source: term,\n target: alternative,\n weight: w--\n });\n });\n }\n }\n return suggestions;\n }, []);\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":203,"value":"### *suggestionsFromGoogle({term, filter, seperator})*","pinned":false,"hidden":false,"mode":"md"},{"id":62,"value":"suggestionsFromGoogle = function ({\n term,\n filter = defaultSuggestionsFilter,\n seperator = \"vs\"\n} = {}) {\n return viewof suggestionsFromGoogleParams.send({\n term,\n filter,\n seperator\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":46,"value":"viewof suggestionsFromGoogleParams = flowQueue({\n timeout_ms: 10000\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":102,"value":"suggestionsFromGoogleParams","pinned":false,"hidden":false,"mode":"ojs"},{"id":968,"value":"// This is a specialist proxy that does some black magic to avoid rate limits,\n// but also it caches responses so we do not hit google with the same query twice.\n// It does not work with anything else other than suggestqueries.google.com\nproxy = \"https://europe-west1-endpointservice.cloudfunctions.net/proxy\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":639,"value":"url = `${proxy}/suggestqueries.google.com/complete/search?output=toolbar&hl=en&q=${encodeURIComponent(\n suggestionsFromGoogleParams.term + \" \" + suggestionsFromGoogleParams.seperator\n)}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":6,"value":"googleResponse = fetch(url, {\n headers: {\n Authorization: `Bearer ${await user.getIdToken()}`\n }\n})","pinned":true,"hidden":false,"mode":"ojs"},{"id":15,"value":"googleResponseBody = {\n if (googleResponse.status == 200) {\n return googleResponse.text();\n } else {\n const err = new Error(await googleResponse.text());\n viewof suggestionsFromGoogleParams.reject(err);\n throw err;\n }\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":69,"value":"googleResponseDoc = parser.parseFromString(googleResponseBody, \"text/xml\")","pinned":true,"hidden":false,"mode":"ojs"},{"id":73,"value":"unfilteredSuggestions = [\n ...googleResponseDoc.querySelectorAll(\"suggestion\")\n].map((e) => e.getAttribute(\"data\"))","pinned":false,"hidden":false,"mode":"ojs"},{"id":106,"value":"filteredSuggestions = suggestionsFromGoogleParams.filter(\n unfilteredSuggestions,\n {\n term: suggestionsFromGoogleParams.term,\n seperator: suggestionsFromGoogleParams.seperator\n }\n)","pinned":true,"hidden":false,"mode":"ojs"},{"id":121,"value":"viewof suggestionsFromGoogleParams.respond(filteredSuggestions)","pinned":true,"hidden":false,"mode":"ojs"},{"id":67,"value":"parser = new DOMParser()","pinned":false,"hidden":false,"mode":"ojs"},{"id":1247,"value":"### Articulation Points\n\nArticulation points are vertices that separate biconnected components.","pinned":false,"hidden":false,"mode":"md"},{"id":1252,"value":"function articulationPoints(initialTerm, adj) {\n const visisted = new Set();\n const depth = new Map();\n const low = new Map();\n const parent = new Map();\n const articulations = new Set();\n\n function articulationPointsFn(i, d) {\n visisted.add(i);\n depth.set(i, d);\n low.set(i, d);\n var childCount = 0;\n var isArticulation = false;\n\n const adjacent = adj.get(i) || [];\n adjacent.forEach((ni) => {\n if (!visisted.has(ni)) {\n parent.set(ni, i);\n articulationPointsFn(ni, d + 1);\n childCount++;\n if (low.get(ni) >= depth.get(i)) isArticulation = true;\n low.set(i, Math.min(low.get(i), low.get(ni)));\n } else if (parent.get(i) !== ni) {\n low.set(i, Math.min(low.get(i), depth.get(ni)));\n }\n });\n\n if (\n (parent.get(i) !== undefined && isArticulation) ||\n (parent.get(i) === undefined && childCount > 1)\n ) {\n articulations.add(i);\n }\n }\n\n articulationPointsFn(initialTerm, 0);\n return articulations;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":715,"value":"### Download As JSON","pinned":false,"hidden":false,"mode":"md"},{"id":719,"value":"// https://stackoverflow.com/a/30800715/862295\nfunction downloadObjectAsJson(exportObj, exportName) {\n var dataStr =\n \"data:text/json;charset=utf-8,\" +\n encodeURIComponent(JSON.stringify(exportObj));\n var downloadAnchorNode = document.createElement(\"a\");\n downloadAnchorNode.setAttribute(\"href\", dataStr);\n downloadAnchorNode.setAttribute(\"download\", exportName + \".json\");\n document.body.appendChild(downloadAnchorNode); // required for firefox\n downloadAnchorNode.click();\n downloadAnchorNode.remove();\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":696,"value":"### Style","pinned":false,"hidden":false,"mode":"md"},{"id":706,"value":"ns = Inputs.text().classList[0]","pinned":false,"hidden":false,"mode":"ojs"},{"id":702,"value":"","pinned":true,"hidden":false,"mode":"html"},{"id":51,"value":"### Cache","pinned":false,"hidden":false,"mode":"md"},{"id":85,"value":"import { flowQueue } from \"@tomlarkworthy/flow-queue\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":326,"value":"import { localStorageView } from \"@tomlarkworthy/local-storage-view\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":744,"value":"import { fileInput } from \"@tomlarkworthy/fileinput\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":958,"value":"import { createLogin } from \"@endpointservices/endpoint-login-with-comment\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1030,"value":"import { view } from \"@tomlarkworthy/view\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1225,"value":"import { tweet } from \"@mbostock/tweet\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1472,"value":"import { footer } from \"@endpointservices/footer-with-backups\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":1497,"value":"footer","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W34","stdlib":"1","titling":"auto"}