3f:null 40:["$","title",null,{"children":"Visualizing a \"Dose\" App Backup | Aaron Artille | Observable"}] 46:T153e,function Timeline(scaleX, margin, height = 200) { let axis = {}; let nodes = {}; let originalScaleX = scaleX.copy(); const parts = ["yearly", "daily", "weekly", "grid", "yearlyGrid"]; const findDensityConfig = (map, value) => { for (const [limit, config] of map) { if (value < limit) { return config; } } return []; }; const ensureTimeFormat = (value = "") => { return typeof value !== "function" ? d3.utcFormat(value) : value; }; axis["yearly"] = (parentNode, density) => { const densityMap = [ [ 3, [ d3.utcMonth, (d) => { const startOfTheYear = d.getUTCMonth() === 0 && d.getUTCDate() === 1; const format = startOfTheYear ? "%Y – %B" : "%B"; return d3.utcFormat(format)(d); } ] ], [Infinity, [d3.utcYear, "%Y"]] ]; let [interval, format] = findDensityConfig(densityMap, density); format = ensureTimeFormat(format); const el = parentNode .attr("transform", `translate(0,${margin.top - 48})`) .call( d3.axisTop(scaleX).ticks(interval).tickFormat(format).tickSizeOuter(0) ); el.select(".domain").remove(); el.selectAll("text") .attr("y", 0) .attr("x", 6) .style("text-anchor", "start"); el.selectAll("line").attr("y1", -7).attr("y2", 6); }; axis["daily"] = (parentNode, density) => { const densityMap = [ [1, [d3.utcDay, "%-d"]], [3, [d3.utcDay, ""]], [8, [d3.utcMonth, "%B"]], [13, [d3.utcMonth, "%b"]], [22, [d3.utcMonth, (d) => d3.utcFormat("%B")(d).charAt(0)]], [33, [d3.utcMonth.every(3), "Q%q"]], [Infinity, [d3.utcMonth.every(3), ""]] ]; let [interval, format] = findDensityConfig(densityMap, density); format = ensureTimeFormat(format); const el = parentNode .attr("transform", `translate(0,${margin.top - 28})`) .call( d3.axisTop(scaleX).ticks(interval).tickFormat(format).tickSizeOuter(0) ); el.select(".domain").remove(); el.selectAll("text") .attr("y", 0) .attr("x", 6) .style("text-anchor", "start"); el.selectAll("line").attr("y1", -7).attr("y2", 0); }; axis["weekly"] = (parentNode, density) => { const densityMap = [ [10, [d3.utcMonday, (d) => +d3.utcFormat("%-V")(d)]], // monday as first of week and zero based [33, [d3.utcMonday, ""]], [Infinity, [d3.utcMonday.every(4), ""]] ]; let [interval, format] = findDensityConfig(densityMap, density); format = ensureTimeFormat(format); const el = parentNode .attr("transform", `translate(0,${margin.top - 8})`) .call( d3.axisTop(scaleX).ticks(interval).tickFormat(format).tickSizeOuter(0) ); el.select(".domain").remove(); el.selectAll("line").style( "visibility", density > densityMap[0][0] ? "visible" : "hidden" ); el.selectAll("text") .attr("y", 0) .attr("x", 6) .style("text-anchor", "start"); el.selectAll("line").attr("y1", -7).attr("y2", 0); }; axis["grid"] = (parentNode, density) => { const densityMap = [ [1, [d3.utcDay]], [8, [d3.utcMonday]], [22, [d3.utcMonth]], [Infinity, [d3.utcMonth.every(3)]] ]; const [interval] = findDensityConfig(densityMap, density); const el = parentNode .attr("transform", `translate(0,${margin.top})`) .call(d3.axisTop(scaleX).ticks(interval).tickSizeOuter(0)); el.select(".domain").remove(); el.selectAll("text").remove(); el.selectAll("line") .attr("y1", 0) .attr("y2", height - margin.top - margin.bottom); }; axis["yearlyGrid"] = (parentNode, density) => { const densityMap = [ [3, [d3.utcMonth, "%B"]], [Infinity, [d3.utcYear, "%Y"]] ]; let [interval, format] = findDensityConfig(densityMap, density); format = ensureTimeFormat(format); const el = parentNode .attr("transform", `translate(0,${margin.top})`) .call( d3.axisTop(scaleX).ticks(interval).tickFormat(format).tickSizeOuter(0) ); el.select(".domain").remove(); el.selectAll("text").remove(); el.selectAll("line") .attr("y1", 0) .attr("y2", height - margin.top - margin.bottom); }; const setup = () => { const svg = d3 .create("svg") .attr("width", width) .attr("height", height) .attr("viewBox", [0, 0, width, height]) .attr("style", "max-width: 100%; height: auto; height: intrinsic;"); const element = svg.node(); const rootNode = svg.append("g").classed("timeline-axis", true); parts.forEach((part) => { nodes[part] = rootNode.append("g").classed(part, true); }); const update = () => { // NOTE: Not used atm. // const [startDate, endDate] = scaleX.domain(); // const totalVisibleDays = Math.abs(startDate - endDate) / MS_PER_DAY; const density = Math.abs(scaleX.invert(0) - scaleX.invert(1)) / MS_PER_HOUR; // in pixels per hour parts.forEach((part) => { nodes[part].call(axis[part], density); }); }; const { zoom, reset } = zoomPlugin(svg, ({ transform }) => { scaleX = transform.rescaleX(originalScaleX); update(); }); update(); return { element, update, reset }; }; return setup(); }47:T400, import Plotly from "plotly.js-basic-dist"; // extract the doses data from the JSON object const doses = data.state.doses; // convert the doses to an array of objects const doseData = []; for (const year in doses) { for (const substance in doses[year]) { doses[year][substance].forEach(dose => { doseData.push({ year: +year, substance, time: new Date(dose.time), amount: dose.amount }); }); } } // group the doses by year and substance const groupedDoses = d3.group(doseData, d => d.substance); // create a time series plot for each substance for (const substance of groupedDoses.keys()) { const doses = groupedDoses.get(substance); const x = doses.map(d => d.time); const y = doses.map(d => d.amount); const trace = { x, y, mode: "lines", name: substance }; const layout = { title: `Doses of ${substance}`, xaxis: { title: "Time" }, yaxis: { title: "Amount" } }; Plotly.newPlot(`plot-${substance}`, [trace], layout); } 48:[{"id":"3bb6a466a9d7ffbc5424e6010bfc6cc97a0f1ed9b2a6b59ccbcbae23c9ffd614165d06772db7e6e532ad23e084456171851e12896b6e8c7e759185521dda89f0","href":"https://static.observableusercontent.com/files/3bb6a466a9d7ffbc5424e6010bfc6cc97a0f1ed9b2a6b59ccbcbae23c9ffd614165d06772db7e6e532ad23e084456171851e12896b6e8c7e759185521dda89f0","name":"dose-backup-1674450511919.json","type":"application/json","lastModified":1674452135459.436,"size":128488}] 44:{"id":"9b55f9d47a83390f","slug":"dose-app","title":"Visualizing a \"Dose\" App Backup","thumbnail":"08165a0007432acdfb6fccf38bd08907a79bd0b771938444bc6e6c46f5e5edf0","access_level":"public","create_time":"$D2023-01-23T05:30:38.567Z","update_time":"$D2023-10-10T07:34:34.775Z","view_time":null,"first_public_time":"$D2023-03-29T05:36:22.047Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"04b8206f80d64270","login":"ajar","name":"Aaron Artille","avatar_url":"https://avatars-next.observableusercontent.com/f5eb7142fc0c0a95aca35742379245ac8c6e27139754e3f2ba028475a8433f05","tier":"starter_2024","bio":"","following":false},"version":3326,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"f80791c532176d72","login":"ajar","name":"Aaron Artille","avatar_url":"https://avatars-next.observableusercontent.com/f5eb7142fc0c0a95aca35742379245ac8c6e27139754e3f2ba028475a8433f05","tier":null,"bio":"","following":false}],"members":[{"type":"individual","id":"f80791c532176d72","login":"ajar","name":"Aaron Artille","avatar_url":"https://avatars-next.observableusercontent.com/f5eb7142fc0c0a95aca35742379245ac8c6e27139754e3f2ba028475a8433f05","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":true,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Visualizing a \"Dose\" App Backup","cells":[{"id":0,"value":"# Visualizing a \"Dose\" App Backup\nPlaying around with real-world dose log data.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":62,"value":"Last night, a friend on Discord sent over his data from an Android app called _Dose_. This friend appears to have done some fairly comprehensive logging over the past couple of years which makes me pretty happy to see! As I literally have never heard of this app and I don't use Android (nor do I have the means to easily) right now, will need to take matters into my own hands for this one.\n\nI'll start by making a simple time series of his doses from inception to date, then we'll dig in a little deeper to see what other kinds of insights we can uncover here! Probably a lot of good information stored within this file. But maybe not. Nonzero chance it's _real_ boring.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":71,"value":"## Making Sense of User Data\n\nWhat he sent over was a single JSON document (`dose-backup-1674450511919.json`) which looks like the object seen below (you can click to expand it). Check it out:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":77,"value":"raw = FileAttachment(\"dose-backup-1674450511919.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":80,"value":"At first glance, it looks like the only immediately useful properties in that backup are `state.doses` and _maybe_ `state.substances`, though it seems the latter is a little spotty.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":137,"value":"### Doses\n\nYou'll notice that these logs are grouped by year here, then by drug, and then by day of the year. This isn't ideal for our purposes here. For reference, we're starting with this:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2629,"value":"raw.state.doses","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2638,"value":"But we can easily flatten and sort this. Things should look much cleaner if we remove the grouping and sort the dose data linearly in ascending order of the time when the dose was administered to/by the subject (here, it is a UNIX timestamp called `time`). That is, `time` is represented here as the number of seconds elapsed since the [Unix Epoch](https://en.wikipedia.org/wiki/Unix_time) (1970-01-01 00:01 UTC). Pretty cool to go from raw data to a workable time series, right? Anybody? Anyway, peep that below.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":156,"value":"doses1 = Object.entries(raw.state.doses)\n .flatMap(([year, yearDoses]) =>\n Object.values(yearDoses).flatMap((dose) => dose)\n )\n .sort((a, b) => a.time - b.time)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":250,"value":"Looking better for sure. One problem, though, is that it doesn't have the drug names included cleanly (anywhere in the document, actually). \n\nHowever, we can see IDs like `${doses1[0].id}` that contain the name of the substance. Let's extract that name and clean up a bunch of other stuff while we're at it. The end result will be a very simple log of doses.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2819,"value":"Object.values(doses1).map((dose) => {\n return {\n time: dose.time,\n name: dose.id,\n mass: dose.units?.mg\n };\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3062,"value":"data2 = {\n // extract the doses data from the JSON object\n const doses = raw.state.doses;\n\n // convert the doses to an array of objects\n const doseData = [];\n for (const year in doses) {\n for (const substance in doses[year]) {\n doses[year][substance].forEach((dose) => {\n let mass = dose.units.mg;\n doseData.push({\n time: new Date(dose.time),\n mass: mass,\n drug: lookupName(substance)\n });\n });\n }\n }\n return doseData;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3066,"value":"Plot.plot({\n marginRight: 150,\n insetRight: 150,\n width: 800,\n height: 1200,\ncolor: {\n type: \"categorical\",\n scheme: \"Category10\",\n legend: true\n },\n marks: [\n Plot.auto(data2, {x: \"time\", y: \"mass\", fy: \"drug\", color: \"drug\"})\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":526,"value":"## Incorporating External Data\n\nWe can now begin to map external data from such public sources as [PsychonautWiki](https://psychonautwiki.org) and [TripSit](https://tripsit.me) to get a fuller picture of what each dose meant to the subject over time.\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2816,"value":"### Pulling All Substances\n\n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":812,"value":"viewof table = Inputs.table(substances, { select: false })","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":874,"value":"#### Mapping Entries to Substances","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1129,"value":"function lookupName(name) {\n return name\n .replaceAll(\"custom:\", \"\")\n .replaceAll(\"(!q!)\", \"\")\n .replaceAll(\"-\", \"\")\n .replaceAll(\",\", \"\")\n .replaceAll(\":\", \"\")\n .replaceAll(\"desoxyn\", \"methamphetamine\")\n .replaceAll(\"xanax\", \"alprazolam\")\n .replaceAll(\"alprazolam\")\n .toLowerCase();\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":564,"value":"\n\n## Subjective Experience\n\nIn order to quantify a user's subjective experience at any point in time, we need to define a scale. One friend suggested a classic 7-point Likert scale in order to capture from the user how they are feeling. Because the user is not here now to say how they were feeling over time with respect to each dose log in the data provided, we'll need to figure this out retroactively in some way. Enter, for this, sentiment analysis.\n\n### Sentiment Analysis on User-Provided Notes\nSentiment analysis can be performed against freeform notes associated with these logs. For this, we can leverage OpenAI's GPT-3 API to first determine intent, then if it's a note about current mood, then we can try to figure where that may score on a seven-point Likert scale (which we will use for new entries to score new conditions).","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":3051,"value":"chart.element","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2971,"value":"chart = Timeline(scaleX, margin, 400)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2981,"value":"$46","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2986,"value":"scaleX = {\n function getDate(date) {\n return new Date(date.toISOString().split(\"T\")[0]);\n }\n\n const now = new Date();\n const until = new Date(years * MS_PER_YEAR + now.getTime());\n\n const nowDate = getDate(now);\n const untilDate = getDate(until);\n\n const timeScale = d3\n .scaleUtc()\n .domain([nowDate, untilDate])\n .range([margin.left, width - margin.right]);\n\n return timeScale;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3009,"value":"years = 10","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3011,"value":"margin = 40","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3002,"value":"import {\n zoomScaleExtent,\n getDays,\n MS_PER_DAY,\n MS_PER_HOUR,\n MS_PER_YEAR\n} from \"@bennyschudel/zoomable-timeline\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":505,"value":"## Past Year of Drug Use\n\nFor the most basic of assessments, we can begin by simply listing all of the doses chronologically as reported in the app data from above. That would look like this:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":735,"value":"viewof doseLog = Inputs.table(doseLogSearch)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":742,"value":"viewof doseLogSearch = Inputs.search(doses)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":800,"value":"### What did the user take most often?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2323,"value":"Plot.auto(doseLogSearch, {\n x: \"date\",\n y: \"drug\",\n color: { value: \"mg\", reduce: \"count\" }\n}).plot({\n color: { legend: true },\n marginRight: 30,\n marginLeft: 120,\n x: { grid: true },\n y: { grid: true, label: \"Substance Dosed\" }\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2367,"value":"doseLog.forEach((dose) => {\n dose.properDrug = _.find();\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2385,"value":"data = _.each(doseLog, (dose) => {\n dose.drug = _.find()\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2423,"value":"data1 = doses","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"data1","database":"$undefined"},{"id":2446,"value":"Plot.plot({\n marks: [\n Plot.auto(doses, {})\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2040,"value":"Plot.auto(doses, {\n x: \"date\",\n y: { value: \"mg\", reduce: \"sum\" },\n color: \"mg\",\n fy: \"drug\"\n}).plot({\n color: { legend: true },\n marginRight: 100,\n x: { grid: true },\n y: { grid: true }\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1472,"value":"Plot.plot({\n marks: [\n Plot.barX(\n doseLogSearch,\n Plot.groupY(\n { x: \"count\" },\n { y: \"drug\", sort: { y: \"x\", reverse: true, limit: 8 } }\n )\n ),\n Plot.ruleX([0])\n ]\n})","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1612,"value":"name = {\n return 1 + 2;\n}","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":139,"value":"### Substances","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":134,"value":"substances0 = raw.state.substances","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":682,"value":"## Appendix","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":771,"value":"import {\n graphql,\n entries,\n entriesByType,\n entryTypes,\n entryCount\n} with { myApiUrl as apiUrl } from \"@jerryjappinen/graphql\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":673,"value":"import { timelineBottom } from \"@notanaccent/timeline\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":706,"value":"import { table } from \"@tmcw/tables@531\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":679,"value":"d3 = require(\"d3@6\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":774,"value":"_graphqlRequest = import(\"https://cdn.skypack.dev/graphql-request@latest\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":816,"value":"// query PsychonautWiki's API\nsubstances = await _graphqlRequest\n .request(\n \"https://api.psychonautwiki.org\",\n `query {\n substances(limit: 9999) {\n name\n \t\tcommonNames\n roas {\n name\n dose {\n units\n threshold\n common { min max }\n light { min max }\n strong { min max }\n \theavy\n }\n duration {\n afterglow { min max units }\n comeup { min max units }\n duration { min max units }\n onset { min max units }\n peak { min max units }\n total { min max units }\n }\n bioavailability {\n min max\n }\n }\n \t\tclass { chemical psychoactive }\n\t\t crossTolerances\n effects {\n name url\n }\n }\n}`\n )\n .then((resp) => resp.substances)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2442,"value":"viewof search = Inputs.search(cars)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":11,"value":"import { stylesheet, theme } from 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