25:["$","title",null,{"children":"Tarrant county voting sites | Andrew Witherspoon | Observable"}] 49:Te36,map = { // Create container const container = yield htl.html`

`; // Require Leaflet library const L = await require("leaflet@1.9.4"); // Initialize map const map = L.map(container); L.tileLayer( "https://tiles.stadiamaps.com/tiles/stamen_toner_lite/{z}/{x}/{y}{r}.png", { attribution: '© OpenStreetMap' } ).addTo(map); const bounds = []; // 1. Color scale function for Choropleth let colorScale = d3 .scaleLinear() .domain( d3.extent( precincts2026WithDistances.features.map( (d) => d.properties[selectedMetric] ) ) ) .range(["#fcfbfd", "#61409b"]); // 2. Add Choropleth Layer from geoRaceProcessed const choroplethLayer = L.geoJSON(precincts2026WithDistances, { style: (feature) => { const val = feature.properties[selectedMetric] ?? 0; return { fillColor: colorScale(val), weight: 1, opacity: 0.8, color: "#ffffff", fillOpacity: 0.55 }; }, onEachFeature: (feature, layer) => { const val = feature.properties[selectedMetric] ?? 0; const pctStr = val <= 1 ? (val * 100).toFixed(1) + "%" : val.toFixed(1) + "%"; layer.bindTooltip(`

Precinct
${selectedMetric}: ${pctStr}

`); } }).addTo(map); // 3. Helper function to plot site categories const createCategoryLayer = (sites, color, categoryName) => { const layerGroup = L.layerGroup(); sites.forEach((site) => { const lat = site.latitude ?? site.lat; const lng = site.longitude ?? site.lng; if (lat && lng) { bounds.push([lat, lng]); L.circleMarker([lat, lng], { radius: 4, fillColor: color, color: "#ffffff", weight: 1.5, opacity: 1, fillOpacity: 0.85 }) .bindPopup( `

${categoryName}
${site.name}
${lat.toFixed(5)}, ${lng.toFixed(5)}

` ) .addTo(layerGroup); } }); return layerGroup; }; // Create site layers const removedLayer = createCategoryLayer( analysis.removedOldSites, "#ef4444", "Removed Site" ).addTo(map); const retainedLayer = createCategoryLayer( analysis.retainedOldSites, "#22c55e", "Retained Site" ).addTo(map); const newLayer = createCategoryLayer( analysis.brandNewSites, "#3b82f6", "Brand New Site" ).addTo(map); // Send choropleth layer behind points choroplethLayer.bringToBack(); // 4. Add toggleable layer controls in the top-right const overlayMaps = { [`🔴 Removed Sites (${analysis.removedOldSites.length})`]: removedLayer, [`🟢 Retained Sites (${analysis.retainedOldSites.length})`]: retainedLayer, [`🔵 Brand New Sites (${analysis.brandNewSites.length})`]: newLayer, Distance: choroplethLayer }; L.control.layers(null, overlayMaps, { collapsed: false }).addTo(map); // Auto-fit view to match all plotted points if (bounds.length > 0) { map.fitBounds(bounds, { padding: [30, 30] }); } else { map.setView([32.75, -97.33], 10); } // Ensure map resizes smoothly inside Observable container setTimeout(() => map.invalidateSize(), 250); }4a:T4cb,Plot.plot({ title: "Change in distance from voting site between current and proposed plan", subtitle: `Average distance from center of precinct to nearest site, among precicincts that are at least ${ demoThreshold * 100 }% of demographic`, marginLeft: 100, marginRight: 50, insetLeft: 50, x: { type: "linear", label: "Miles" }, y: { tickSize: null, label: null, tickFormat: (d) => `${d} (${ beforeAndAfterDistances.find((f) => f.group == d).numberOfPrecincts })` }, marks: [ Plot.arrow(beforeAndAfterDistances, { x1: "beforeDistance", y1: "group", x2: "afterDistance", y2: "group", stroke: "red", sort: { y: "x2", reverse: true } }), Plot.dot(beforeAndAfterDistances, { x: "beforeDistance", y: "group", fill: "grey" }), Plot.text(beforeAndAfterDistances, { text: "beforeDistance", x: "beforeDistance", y: "group", fill: "grey", textAnchor: "end", dx: -5 }), Plot.text(beforeAndAfterDistances, { text: "afterDistance", x: "afterDistance", y: "group", fill: "red", textAnchor: "start", dx: 5 }) ] })4b:T642,analysis = { const retainedOldSites = []; const removedOldSites = []; const brandNewSites = []; oldSites.forEach((oldSite) => { const latA = oldSite.latitude ?? oldSite.lat; const lngA = oldSite.longitude ?? oldSite.lng; const match = proposedSites.find((propSite) => { const latB = propSite.latitude ?? propSite.lat; const lngB = propSite.longitude ?? propSite.lng; const dist = getHaversineDistance(latA, lngA, latB, lngB); if (dist <= options.exactDistanceMeters) return true; if ( dist <= options.maxDistanceMeters && getStringSimilarity(oldSite.name, propSite.name) >= options.minNameSimilarity ) { return true; } return false; }); if (match) retainedOldSites.push(oldSite); else removedOldSites.push(oldSite); }); proposedSites.forEach((propSite) => { const latB = propSite.latitude ?? propSite.lat; const lngB = propSite.longitude ?? propSite.lng; const match = oldSites.find((oldSite) => { const latA = oldSite.latitude ?? oldSite.lat; const lngA = oldSite.longitude ?? oldSite.lng; const dist = getHaversineDistance(latA, lngA, latB, lngB); if (dist <= options.exactDistanceMeters) return true; if ( dist <= options.maxDistanceMeters && getStringSimilarity(oldSite.name, propSite.name) >= options.minNameSimilarity ) { return true; } return false; }); if (!match) brandNewSites.push(propSite); }); return { retainedOldSites, removedOldSites, brandNewSites }; }4c:T472,tractsWithClosureRates = { // Convert site arrays to Turf FeatureCollections const oldPoints = turf.featureCollection( oldSites.map((s) => turf.point([s.longitude ?? s.lng, s.latitude ?? s.lat])) ); const removedPoints = turf.featureCollection( analysis.removedOldSites.map((s) => turf.point([s.longitude ?? s.lng, s.latitude ?? s.lat]) ) ); return { ...geoRaceProcessed, features: geoRaceProcessed.features.map((tract) => { // Count points falling inside this tract const totalOld = turf.pointsWithinPolygon(oldPoints, tract).features .length; const totalRemoved = turf.pointsWithinPolygon(removedPoints, tract) .features.length; // Only calculate rate if the tract originally had at least 1 site const closureRate = totalOld > 0 ? totalRemoved / totalOld : null; return { ...tract, properties: { ...tract.properties, old_sites_count: totalOld, removed_sites_count: totalRemoved, closure_rate: closureRate // Value between 0.0 (0%) and 1.0 (100%), or null } }; }) }; }4d:T5e2,closureTierComparison = { // Only evaluate tracts that had 1 or more original polling sites const activeTracts = tractsWithClosureRates.features .map((f) => f.properties) .filter((p) => p.old_sites_count > 0); const fullyClosed = activeTracts.filter((p) => p.closure_rate === 1.0); const partiallyClosed = activeTracts.filter( (p) => p.closure_rate > 0 && p.closure_rate < 1.0 ); const noClosures = activeTracts.filter((p) => p.closure_rate === 0.0); const calcMean = (arr, key) => arr.length ? arr.reduce((sum, item) => sum + (item[key] || 0), 0) / arr.length : 0; return [ { "Closure Tier": "100% Closed (Lost All Sites)", "Tract Count": fullyClosed.length, "Avg % Nonwhite": calcMean(fullyClosed, "pct_nonwhite"), "Avg % Black": calcMean(fullyClosed, "pct_black"), "Avg % Hispanic": calcMean(fullyClosed, "pct_hispanic") }, { "Closure Tier": "Partially Closed (1%–99% Lost)", "Tract Count": partiallyClosed.length, "Avg % Nonwhite": calcMean(partiallyClosed, "pct_nonwhite"), "Avg % Black": calcMean(partiallyClosed, "pct_black"), "Avg % Hispanic": calcMean(partiallyClosed, "pct_hispanic") }, { "Closure Tier": "0% Closed (No Losses)", "Tract Count": noClosures.length, "Avg % Nonwhite": calcMean(noClosures, "pct_nonwhite"), "Avg % Black": calcMean(noClosures, "pct_black"), "Avg % Hispanic": calcMean(noClosures, "pct_hispanic") } ]; }4e:T6d4,function addNearestSiteDistances(precinctsGeoJSON, oldSites, proposedSites, options = { units: "miles" }) { // Convert site arrays to Turf FeatureCollections (GeoJSON expects [longitude, latitude]) const oldPoints = turf.featureCollection( oldSites .filter(s => (s.longitude ?? s.lng) && (s.latitude ?? s.lat)) .map(s => turf.point([s.longitude ?? s.lng, s.latitude ?? s.lat], { ...s })) ); const proposedPoints = turf.featureCollection( proposedSites .filter(s => (s.longitude ?? s.lng) && (s.latitude ?? s.lat)) .map(s => turf.point([s.longitude ?? s.lng, s.latitude ?? s.lat], { ...s })) ); return { ...precinctsGeoJSON, features: precinctsGeoJSON.features.map(feature => { // 1. Get centroid of the precinct polygon const center = turf.centroid(feature); // 2. Find nearest old site & distance const nearestOld = turf.nearestPoint(center, oldPoints); const distOld = turf.distance(center, nearestOld, { units: options.units }); // 3. Find nearest proposed site & distance const nearestProposed = turf.nearestPoint(center, proposedPoints); const distProposed = turf.distance(center, nearestProposed, { units: options.units }); const distChange = distProposed - distOld; // Positive = further travel, Negative = closer travel return { ...feature, properties: { ...feature.properties, dist_old_site: +distOld.toFixed(2), dist_proposed_site: +distProposed.toFixed(2), dist_change: +distChange.toFixed(2), nearest_old_name: nearestOld.properties.name ?? null, nearest_proposed_name: nearestProposed.properties.name ?? null } }; }) }; }4f:T41e,function findRemovedSites(originalList, newList, options = {}) { const { maxDistanceMeters = 150, // Distance buffer cutoff exactDistanceMeters = 15, // Immediate match distance minNameSimilarity = 0.45 // 45% similarity threshold } = options; return originalList.filter((siteA) => { // Check if siteA exists anywhere in newList const existsInNewList = newList.some((siteB) => { const dist = getHaversineDistance( siteA.latitude, siteA.longitude, siteB.latitude, siteB.longitude ); // Match 1: Pins are virtually on top of each other if (dist <= exactDistanceMeters) return true; // Match 2: Pins are within proximity buffer AND names are similar if (dist <= maxDistanceMeters) { const similarity = getStringSimilarity(siteA.name, siteB.name); if (similarity >= minNameSimilarity) return true; } return false; }); // If no match was found in newList, keep it in the "removed" output return !existsInNewList; }); }50:[{"id":"ae25114fb511031c21aaebd9adf633f729e170266196917fe402cd68ceb429d7a5bd0252b0846bb376b9266d0c2423b0ed6aede86d582f68587137ab1cf5ffff","href":"https://static.observableusercontent.com/files/ae25114fb511031c21aaebd9adf633f729e170266196917fe402cd68ceb429d7a5bd0252b0846bb376b9266d0c2423b0ed6aede86d582f68587137ab1cf5ffff","name":"Tarrant county election day sites 2024 - 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Summary Results

Original Sites: ${oldSites.length}
Proposed Sites: ${proposedSites.length}
Retained Sites: ${analysis.retainedOldSites.length}
Removed Sites: ${analysis.removedOldSites.length}
Newly Added Sites: ${analysis.brandNewSites.length}

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":578,"value":"viewof selectedMetric = Inputs.radio(\n new Map([\n [\"Distance from old site\", \"dist_old_site\"],\n [\"Distance from proposed site\", \"dist_proposed_site\"]\n ]),\n { value: \"dist_old_site\", label: \"Map choropleth\" }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":508,"value":"$49","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":740,"value":"viewof selectedDemographic = Inputs.radio(\n new Map([\n [\"% White\", \"WhitePct\"],\n [\"% Minority\", \"MinorityPc\"],\n [\"% Hispanic\", \"HispanicPc\"],\n [\"% Black\", \"BlackPct\"],\n [\"% Asian\", \"AsianPct\"],\n [\"% Dem\", \"DemPct\"],\n [\"% GOP\", \"RepPct\"]\n ]),\n { value: \"WhitePct\", label: \"Scatter demographic\" }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":676,"value":"Plot.plot({\n title: `Change in distance from voting site, by %${selectedDemographic\n .split(\"P\")[0]\n .toLowerCase()}`,\n subtitle: \"Each dot is a precinct\",\n x: { type: \"linear\", domain: [0, 1], grid: true },\n y: { type: \"linear\", grid: true },\n color: { scheme: \"PiYG\" },\n width: 400,\n marks: [\n Plot.dot(precincts2026WithDistances.features, {\n x: selectedDemographic,\n y: \"dist_change\",\n fill: \"dist_change\",\n fillOpacity: 0.5,\n tip: true\n }),\n Plot.linearRegressionY(precincts2026WithDistances.features, {\n x: selectedDemographic,\n y: \"dist_change\"\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":778,"value":"viewof demoThreshold = Inputs.range([0, 1], {\n label: \"Demographic threshold\",\n step: 0.05,\n value: 0.5\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":787,"value":"$4a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":823,"value":"Plot.plot({\n title:\n \"Change in distance from voting site between current and proposed plan\",\n subtitle: `Average distance from center of precinct to nearest site, among precicincts that are at least ${\n demoThreshold * 100\n }% of demographic`,\n marginLeft: 100,\n marginRight: 50,\n insetLeft: 50,\n x: {\n type: \"linear\",\n label: \"Miles\"\n },\n y: {\n tickSize: null,\n label: null,\n tickFormat: (d) =>\n `${d} (${\n beforeAndAfterDistances.find((f) => f.group == d).numberOfPrecincts\n })`\n },\n marks: [\n Plot.barX(beforeAndAfterDistances, {\n x: \"change\",\n y: \"group\",\n sort: { y: \"x\", reverse: true }\n }),\n Plot.text(beforeAndAfterDistances, {\n text: \"change\",\n x: (d) => `+${d.change}`,\n y: \"group\",\n fill: \"white\",\n textAnchor: \"end\",\n dx: -5\n })\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":9,"value":"***\n## Analysis","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":493,"value":"viewof options = Inputs.form({\n maxDistanceMeters: Inputs.range([50, 500], {\n value: 200,\n step: 10,\n label: \"Max Buffer Distance (m)\"\n }),\n exactDistanceMeters: Inputs.range([5, 50], {\n value: 25,\n step: 5,\n label: \"Exact Match Distance (m)\"\n }),\n minNameSimilarity: Inputs.range([0, 1], {\n value: 0.4,\n step: 0.05,\n label: \"Min Name Similarity\"\n })\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":501,"value":"$4b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":527,"value":"function processRaceGeo() {\n let final = { type: \"FeatureCollection\", features: [] };\n\n Array.from(geoRace.features).map((d) => {\n let obj = {\n ...d\n };\n\n d.properties.pct_nonwhite = makePercent(\n (d.properties.TOT_POP24 - d.properties.WHT_NHSP24) /\n d.properties.TOT_POP24\n );\n d.properties.pct_black = makePercent(\n d.properties.BLK_NHSP24 / d.properties.TOT_POP24\n );\n d.properties.pct_hispanic = makePercent(\n d.properties.HSP_POP24 / d.properties.TOT_POP24\n );\n\n final.features.push(obj);\n });\n return final;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":530,"value":"geoRaceProcessed = processRaceGeo()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":553,"value":"// Join removed sites to Census Tracts\ntractsWithCounts = {\n // Convert site array to Turf FeatureCollection of points\n const sitePoints = turf.featureCollection(\n analysis.removedOldSites.map((s) =>\n turf.point([s.longitude, s.latitude], { name: s.name })\n )\n );\n\n // Clone tracts GeoJSON and count points per polygon\n return {\n ...geoRaceProcessed,\n features: geoRaceProcessed.features.map((tract) => {\n // Find all removed sites inside this tract\n const ptsInside = turf.pointsWithinPolygon(sitePoints, tract);\n const removedCount = ptsInside.features.length;\n\n return {\n ...tract,\n properties: {\n ...tract.properties,\n removed_count: removedCount,\n has_removal: removedCount > 0\n }\n };\n })\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":558,"value":"demographicComparison = {\n const allTracts = tractsWithCounts.features.map((f) => f.properties);\n\n const tractsWithRemovals = allTracts.filter((t) => t.has_removal);\n const tractsWithoutRemovals = allTracts.filter((t) => !t.has_removal);\n\n const calcMean = (arr, key) =>\n arr.reduce((sum, item) => sum + (item[key] || 0), 0) / arr.length;\n\n return [\n {\n Group: \"Tracts WITH Removals\",\n TractCount: tractsWithRemovals.length,\n Avg_Pct_Nonwhite: calcMean(tractsWithRemovals, \"pct_nonwhite\"),\n Avg_Pct_Black: calcMean(tractsWithRemovals, \"pct_black\"),\n Avg_Pct_Hispanic: calcMean(tractsWithRemovals, \"pct_hispanic\")\n },\n {\n Group: \"Tracts WITHOUT Removals\",\n TractCount: tractsWithoutRemovals.length,\n Avg_Pct_Nonwhite: calcMean(tractsWithoutRemovals, \"pct_nonwhite\"),\n Avg_Pct_Black: calcMean(tractsWithoutRemovals, \"pct_black\"),\n Avg_Pct_Hispanic: calcMean(tractsWithoutRemovals, \"pct_hispanic\")\n }\n ];\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":563,"value":"correlations = {\n const props = tractsWithCounts.features.map((f) => f.properties);\n const removals = props.map((p) => p.removed_count);\n\n return {\n nonwhite_correlation: getPearsonCorrelation(\n props.map((p) => p.pct_nonwhite || 0),\n removals\n ).toFixed(3),\n black_correlation: getPearsonCorrelation(\n props.map((p) => p.pct_black || 0),\n removals\n ).toFixed(3),\n hispanic_correlation: getPearsonCorrelation(\n props.map((p) => p.pct_hispanic || 0),\n removals\n ).toFixed(3)\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":569,"value":"$4c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":572,"value":"$4d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":575,"value":"closureRateCorrelations = {\n const activeTracts = tractsWithClosureRates.features\n .map((f) => f.properties)\n .filter((p) => p.old_sites_count > 0);\n\n const rates = activeTracts.map((p) => p.closure_rate);\n\n return {\n nonwhite_rate_correlation: getPearsonCorrelation(\n activeTracts.map((p) => p.pct_nonwhite || 0),\n rates\n ).toFixed(3),\n black_rate_correlation: getPearsonCorrelation(\n activeTracts.map((p) => p.pct_black || 0),\n rates\n ).toFixed(3),\n hispanic_rate_correlation: getPearsonCorrelation(\n activeTracts.map((p) => p.pct_hispanic || 0),\n rates\n ).toFixed(3)\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":668,"value":"$4e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":670,"value":"precincts2026WithDistances = addNearestSiteDistances(\n precincts2026Geo,\n oldSites,\n proposedSites,\n { units: \"miles\" }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":770,"value":"function processBeforeAndAfterDistances() {\n let final = [];\n let groups = [\n \"Total\",\n \"WhitePct\",\n \"MinorityPc\",\n \"HispanicPc\",\n \"BlackPct\",\n \"AsianPct\",\n \"DemPct\",\n \"RepPct\"\n ];\n\n groups.forEach((group) => {\n let match = precincts2026WithDistances.features.filter(\n (f) => f.properties[group] >= demoThreshold\n );\n if (group == \"Total\") {\n match = precincts2026WithDistances.features;\n }\n let beforeDistance = +d3\n .mean(match, (d) => d.properties.dist_old_site)\n .toFixed(2);\n let afterDistance = +d3\n .mean(match, (d) => d.properties.dist_proposed_site)\n .toFixed(2);\n let obj = {\n group,\n numberOfPrecincts: match.length,\n beforeDistance,\n afterDistance,\n change: afterDistance - beforeDistance\n };\n final.push(obj);\n });\n return final;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":772,"value":"beforeAndAfterDistances = processBeforeAndAfterDistances()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":11,"value":"***\n## Data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":431,"value":"oldSites = FileAttachment(\"Tarrant county election day sites 2024 - Sheet1.csv\")\n .csv({ typed: true })\n .then((data) =>\n data.map((d) => {\n let obj = {\n name: d[\"Polling place\"],\n latitude: d.Latitude,\n longitude: d.Longitude\n };\n return obj;\n })\n )","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":449,"value":"proposedSites = FileAttachment(\"my_maps_pins.csv\")\n .csv({ typed: true })\n .then((data) => data.filter((f) => f.color_hex == \"0288D1\"))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":520,"value":"topoRace = FileAttachment(\"tx_race_2024_t.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":523,"value":"geoRace = topojson.feature(topoRace, topoRace.objects.tx_race_2024_t)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":594,"value":"vtdTopo = FileAttachment(\"VTDs_24PG.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":597,"value":"vtdGeo = topojson.feature(vtdTopo, vtdTopo.objects.VTDs_24PG)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":616,"value":"precincts2026Topo = FileAttachment(\"precincts-2026-with-data.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":661,"value":"precincts2026Geo = topojson.feature(\n precincts2026Topo,\n precincts2026Topo.objects.POLYGON\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":13,"value":"***\n## Utilities","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":15,"value":"function formatNumber(x) {\n return x.toString().replace(/\\B(?=(\\d{3})+(?!\\d))/g, \",\");\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":17,"value":"function slugify(text) {\n return text\n .toString()\n .toLowerCase()\n .replace(/\\s+/g, \"-\") // Replace spaces with -\n .replace(/[^\\w\\-]+/g, \"\") // Remove all non-word chars\n .replace(/\\-\\-+/g, \"-\") // Replace multiple - with single -\n .replace(/^-+/, \"\") // Trim - from start of text\n .replace(/-+$/, \"\"); // Trim - from end of text\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":469,"value":"function getHaversineDistance(lat1, lon1, lat2, lon2) {\n const R = 6371000;\n const dLat = ((lat2 - lat1) * Math.PI) / 180;\n const dLon = ((lon2 - lon1) * Math.PI) / 180;\n const a =\n Math.sin(dLat / 2) * Math.sin(dLat / 2) +\n Math.cos((lat1 * Math.PI) / 180) *\n Math.cos((lat2 * Math.PI) / 180) *\n Math.sin(dLon / 2) *\n Math.sin(dLon / 2);\n return R * 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1 - a));\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":471,"value":"function getStringSimilarity(str1 = \"\", str2 = \"\") {\n const s1 = str1.toLowerCase().replace(/[^a-z0-9]/g, \"\");\n const s2 = str2.toLowerCase().replace(/[^a-z0-9]/g, \"\");\n\n if (s1 === s2) return 1.0;\n if (s1.length < 2 || s2.length < 2) return 0.0;\n\n const bigrams1 = new Map();\n for (let i = 0; i < s1.length - 1; i++) {\n const bigram = s1.substring(i, i + 2);\n bigrams1.set(bigram, (bigrams1.get(bigram) || 0) + 1);\n }\n\n let intersection = 0;\n for (let i = 0; i < s2.length - 1; i++) {\n const bigram = s2.substring(i, i + 2);\n const count = bigrams1.get(bigram) || 0;\n if (count > 0) {\n bigrams1.set(bigram, count - 1);\n intersection++;\n }\n }\n\n return (2.0 * intersection) / (s1.length + s2.length - 2);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":475,"value":"$4f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":546,"value":"function getPearsonCorrelation(xArray, yArray) {\n const n = xArray.length;\n const meanX = xArray.reduce((a, b) => a + b, 0) / n;\n const meanY = yArray.reduce((a, b) => a + b, 0) / n;\n\n let num = 0;\n let denX = 0;\n let denY = 0;\n\n for (let i = 0; i < n; i++) {\n const dx = xArray[i] - meanX;\n const dy = yArray[i] - meanY;\n num += dx * dy;\n denX += dx * dx;\n denY += dy * dy;\n }\n\n return num / (Math.sqrt(denX) * Math.sqrt(denY));\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":511,"value":"htl.html``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":538,"value":"function makePercent(num) {\n return +(num*100).toFixed(2)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":542,"value":"turf = require(\"@turf/turf@6\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W50","stdlib":"1"}} 24:null