44:["$","title",null,{"children":"Untitled | Jose.carmona-sanchez | Observable"}] 4c:Td7c,//codifies the codebook and excel file into human readable text. EG spreadsheet stores democracy = 2, but what does that even mean? //so it instead gives us labels.democracy[2] = "evidence of democracy" more or less const labels = { polisity: {1: "Certain", 1.5: "Probable", 2: "Likely", 3: "Uncertain"}, hellenicity: {0: "Unknown", 1: "Greek", 2: "Mixed", 3: "Barbarian"}, inout: {1: "Ends before 400", 2: "Exists 400–323", 3: "Founded 400–323", 4: "Refounded 400–323", 5: "Ends 400–323"}, area1: {0: "Unknown", 1: "<25 km²", 2: "25–100 km²", 3: "100–200 km²", 4: "200–500 km²", 5: "500–1000 km²", 6: "1000–2000 km²", 7: ">2000 km²"}, silver: {6: "By 500 BCE", 5: "499–400 BCE", 4: "399–300 BCE"}, bronze: {6: "By 500 BCE", 5: "499–400 BCE", 4: "399–300 BCE"}, grid: {0: "No evidence", 7: "7th c. or earlier", 6: "6th c.", 5: "5th c.", 4: "4th c."}, victors: {0: "No victories", 1: "1 festival", 2: "2 festivals", 3: "3 festivals", 4: "All 4 festivals"}, proxenoi: {0: "No evidence", 1: "Received only", 2: "Granted only", 3: "Both"}, democracy: {0: "Unknown", 1: "No evidence", 2: "Evidence"}, walls: {0: "Unwalled / no evidence", 1: "Fortified"}, delian: {0: "Not attested", 1: "Member"}, koinon: {0: "No / no evidence", 1: "Member"} }; //variables is a list describing each column: the data key, a human-friendly name, and a type. It’s there so dropdowns and scales can be generated const variables = [ {key: "staseis", label: "Staseis, 500–300 BCE", type: "numeric"}, {key: "prom1", label: "Prominence 1 (HN text columns)", type: "numeric"}, {key: "prom2", label: "Prominence 2 (LGPN names)", type: "numeric"}, {key: "prom3", label: "Prominence 3 (city-ethnic mentions)", type: "numeric"}, {key: "area2", label: "Intramural area (ha)", type: "numeric"}, {key: "colonies", label: "Colonies founded", type: "numeric"}, {key: "elevation", label: "Elevation (m, approx.)", type: "numeric"}, {key: "area1", label: "Territory size", type: "ordinal"}, {key: "victors", label: "Panhellenic victories", type: "ordinal"}, {key: "silver", label: "First silver coinage", type: "ordinal"}, {key: "bronze", label: "First bronze coinage", type: "ordinal"}, {key: "grid", label: "Grid planning", type: "ordinal"}, {key: "polisity", label: "Certainty it is a polis", type: "categorical"}, {key: "hellenicity", label: "Hellenicity", type: "categorical"}, {key: "inout", label: "Existence during period", type: "categorical"}, {key: "proxenoi", label: "Proxeny activity", type: "categorical"}, {key: "democracy", label: "Democracy", type: "categorical"}, {key: "walls", label: "City walls", type: "categorical"}, {key: "delian", label: "Delian League member", type: "categorical"}, {key: "koinon", label: "Koinon member", type: "categorical"}, {key: "region", label: "Region", type: "categorical"} ]; // looks up the key of some column to give human understandable "label" for pop ups and shit const labelOf = (key, v) => v == null ? "No data" : (labels[key]?.[v] ?? String(v));4d:T7dd,// n = number // blank cell => null // otherwise convert v (value) to a number function n(v) { if (v == null || v === "") return null; return +v; } // maps the columns to labels const polis = rows.map(r => { const d = { id: n(r["polis#"]), name: r["Name"], polisity: n(r["Polisity"]), hellenicity: n(r["Hellenicity"]), inout: n(r["In/out"]), staseis: n(r["staseis"]), prom1: n(r["prom 1"]), prom2: n(r["prom 2"]), prom3: n(r["prom 3"]), area1: n(r["area 1"]), area2: n(r["area 2"]), silver: n(r["Silver"]), bronze: n(r["Bronze"]), grid: n(r["Grid"]), colonies: n(r["Colonies"]), victors: n(r["Victors"]), proxenoi: n(r["Proxenoi"]), democracy: n(r["Democracy"]), walls: n(r["Walls"]), delian: n(r["Delian L"]), koinon: n(r["Koinon"]), region: r["Region name"], regionId: n(r["Region #"]), lat: n(r["Latitude"]), lon: n(r["Longitude"]), pleiades: r["Pleiades link"], elevation: n(r["Elevation m"]) }; // // these lines can be uncommented as block to "narrow" the excel file right away // // prom1 has best correlation with staseis so this is like "evidence based" // d.stasisPerProm = d.prom1 ? d.staseis / d.prom1 : null; // //existed 400–323 if we want to narrow it down right away // d.fullPeriod = d.inout === 2; return d; }).filter(d => d.name); //This filters the data that is sent to the plotting cell by checking it has valid lat and lon then filters out data dynamicallly based on selecitons made in dropdown above the map const mapped = polis.filter(d => d.lat != null && d.lon != null && //d.polisity === selectedPolisity (selectedPolisity == "All" || Number(d.polisity) === Number(selectedPolisity)) && (selectedHellenicity == "All" || d.hellenicity === selectedHellenicity) && (selectedDemocracy == "All" || Number(d.democracy) === Number(selectedDemocracy)) && (selectedProxenoi == "All" || Number(d.proxenoi) === Number(selectedProxenoi)) && (selectedArea1 == "All" || Number(d.area1) === Number(selectedArea1)) );4e:T714,// Create a Leaflet control object for the legend const legend = L.control({ position: 'bottomright' }); legend.onAdd = function (map) { // Create a container div const div = L.DomUtil.create('div', 'map-legend'); // Apply container styling entirely using inline styles div.style.backgroundColor = 'rgba(255, 255, 255, 0.9)'; div.style.padding = '10px'; div.style.borderRadius = '5px'; div.style.boxShadow = '0 0 15px rgba(0,0,0,0.2)'; div.style.fontFamily = 'Arial, sans-serif'; div.style.fontSize = '14px'; div.style.lineHeight = '20px'; div.style.color = '#333'; const legendItems = [ { color: "#170101", text: '≥ 20' }, { color: "#5d2311", text: '9-19' }, { color: "#a34520", text: '4-8' }, { color: "#bb7b30", text: '3-4' }, { color: "#9a9e68", text: '1-2' }, { color: "#79c0a0", text: '0' }, ]; // Add a title to the legend div.innerHTML = 'Staseis Value'; // Loop through items and generate HTML with inline-styled color circles legendItems.forEach(item => { div.innerHTML += `

${item.text}

`; }); return div; }; // Add the legend to your existing map instance legend.addTo(map); 4f:T563,//some stuff using the excel file info -> regrabs 5 randoms from excel file every time cell is run //if error "cannot read properties of undefined (reading 'appendChild')" //or "undefined is not an object (evaluating 'this.getPane().appendChild')" //go up and rerun the map cell and it should go away //const sample = [...mapped].sort(() => Math.random() - 0.5).slice(0, 5); function getColor(value) { return value >= 20 ? "#170101" ://"#1E0206" ://"#6e1a1a" ://"#6e1a1a" ://"pink" :9DD6BB value >= 12 && value < 20 ? "#5d2311" ://"#291620" ://"#a33b1c" ://"yellow" : value >= 8 && value < 12 ? "#a34520" ://"#312838" ://"#bd822b" ://"green" : value >= 3 && value < 8 ? "#bb7b30" ://"#2C3A4B" ://"#d4a83c" ://"darkblue" : value >= 1 && value < 3 ? "#9a9e68" ://"#285965" ://"#d5d352" ://"red" :c8c676 value >= 0 && value < 1 ? "#79c0a0" ://"#2E7E7D" ://"#d9f7c1" ://"orange" :b0e5c4 "red"; } const markers = mapped.map(d => L.circleMarker([d.lat, d.lon], { radius: 4, color: getColor(d.staseis), weight: 1, fillColor: getColor(d.staseis), fillOpacity: 1//0.85 }) .bindPopup(popupHTML(d)) .bindTooltip(d.name)//, d.polisity .addTo(map) ); //map.fitBounds(L.featureGroup(markers).getBounds().pad(0.2)); invalidation.then(() => map.remove());50:T6a8,// First value of each CSV was read as the header, so add it back const mse_vals = [Number(mse_nums.columns[0]), ...mse_nums.map((d) => Number(Object.values(d)[0]))]; const r2_vals = [Number(r2_nums.columns[0]), ...r2_nums.map((d) => Number(Object.values(d)[0]))]; const pred_by_header = headers.map((h, i) => ({ header: h, pred: Object.values(y_pred[i]).map(Number), mse: mse_vals[i], r2: r2_vals[i] })); // Sorted by R² (best first) const sorted_models = pred_by_header.slice().sort((a, b) => b.r2 - a.r2); const sorted_headers = sorted_models.map((d) => d.header); // Frame colour: grey for R² ≈ 0, green for high R² const frameColor = d3.scaleLinear([0, 0.3], ["#bbbbbb", "#2a9d4b"]).clamp(true); function makePlot({header, pred, mse, r2}, i) { const test = test_data.map((d, j) => ({x: d[header], y: d.staseis, pred: pred[j]})) .filter((d) => d.x != null && d.y != null); return Plot.plot({ title: header, subtitle: `R² = ${r2.toFixed(3)} · MSE = ${mse.toFixed(3)}`, width: 300, height: 220, marginLeft: i % 5 === 0 ? 30 : 10, marginBottom: 30, style: {fontSize: "10px"}, x: {label: header, ticks: 5}, y: {label: "Staseis", domain: [0, 15], axis: i % 5 === 0 ? "left" : null, grid: true}, marks: [ Plot.frame({stroke: frameColor(r2), strokeWidth: 2}), Plot.dot(test, {x: "x", y: "y", stroke: "darkorange", r: 2.5, tip: true}), Plot.line(test, Plot.groupX({y: "mean"}, {x: "x", y: "pred", stroke: "red", strokeWidth: 2})) ] }); } display(html`

${sorted_models.map((d, i) => html`

${makePlot(d, i)}

`)}

`);51:T6b3,//builds map //these variables make the map cell rerun every time the dropdown selection is changed so that it dosen't go blank and you have to manually refresh the cell every time. Observable dosen't rerun a cell unless a variable it uses has been changed, and it dosen't count dynamically tracked variables like mapped, so if you want it to keep dynamically updaing you need to make it think its using the variables that changes mapped directly var TheseAreJust = selectedPolisity var RandomVariables = selectedHellenicity var ToMakeItUpdate = selectedDemocracy var whatShouldICallThese = selectedProxenoi var awkwardSilence = selectedArea1 //var SoHowAboutThatWeahter const div = display(document.createElement("div")); div.style = "height: 400px;"; const map = L.map(div, { minZoom: 2, maxBounds: [[-90, -180], [90, 180]], maxBoundsViscosity: 1.0 }).setView([39.487, 18.896], 4); // this version has streets and cities and all that fun jazz, if needed // L.tileLayer("https://tile.openstreetmap.org/{z}/{x}/{y}.png", { // attribution: '© OpenStreetMap' // }).addTo(map); //dont freak out, the api key is fine being visible since it can be restricted to specific referers when requesting the key //also i didnt give them my credit card so even if it's a problem its not actually. //this map has less shit on it. L.tileLayer('https://basemaps.cartocdn.com/rastertiles/voyager/{z}/{x}/{y}.png?key=cb1_4t96_1_1fa178804b2907c226ccf3bc', { subdomains: "abcd", attribution: '© OpenStreetMap ©CARTO', noWrap: true, }).addTo(map); 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polis_data =FileAttachment(\"polis_data.xlsx\").xlsx();","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":43,"value":"const data = polis_data.sheet(\"Sheet1\", { headers: true });\ndisplay(data)","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":39,"value":"const y_pred = FileAttachment(\"all_y_pred.csv\").csv();\nconst mse_nums = FileAttachment(\"mse_nums.csv\").csv();\nconst r2_nums = FileAttachment(\"r2_nums.csv\").csv();\nconst used_headers = 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onMapClick);","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":30,"value":"$4e","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":19,"value":"$4f","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":18,"value":"const popupHTML = d => `\n ${d.name}
${d.region}
\n Episodes of Staseis: ${d.staseis}
\n Democracy: ${labelOf(\"democracy\", d.democracy)}
\n Walls: ${labelOf(\"walls\", d.walls)}
\n Territory: ${labelOf(\"area1\", d.area1)}
\n Polisity: ${labelOf(\"polisity\", d.polisity)}
\n Pleiades`;","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1,"value":"# Polis Data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":48,"value":"# Linear Regression Feature Analysis","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":46,"value":"const metrics = pred_by_header.map(({header, mse, r2}) => ({header, mse, r2}));\n\nconst mse_plot = Plot.plot({\n title: \"MSE by Feature (Test Set)\",\n width: 740,\n height: 240,\n marginBottom: 45,\n x: {domain: sorted_headers, label: null, tickRotate: -25},\n y: {label: null, grid: true},\n marks: [\n Plot.barY(metrics, {x: \"header\", y: \"mse\", fill: \"steelblue\", tip: true}),\n Plot.ruleY([0])\n ]\n});\n\nconst r2_plot = Plot.plot({\n title: \"R² by Feature (Test Set)\",\n width: 740,\n height: 240,\n marginBottom: 45,\n x: {domain: sorted_headers, label: null, tickRotate: -25},\n y: {label: null, grid: true},\n marks: [\n Plot.barY(metrics, {x: \"header\", y: \"r2\", fill: \"darkorange\", tip: true}),\n Plot.ruleY([0])\n ]\n});\n\ndisplay(html`

${mse_plot}

${r2_plot}

`);","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":47,"value":"$50","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":49,"value":"\n \n Linear regression analysis was ran on 10 different features that had very minimal nan values. The result shown above show the linear regression model trained on the 10 different feartures (solid line) while test points are scatterd. Stesasis is the y -axis for all graphs.\n \n","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":22,"value":"viewof selectedPolisity = Inputs.select(\n new Map([\n [\"All\", \"All\"],\n [\"Certain\", 1],\n [\"Probable\", 1.5],\n [\"Likely\", 2],\n [\"Uncertain\", 3],\n ]),\n {\n label: \"Polisity:\",\n value: \"All\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":27,"value":"viewof selectedHellenicity = Inputs.select(\n new Map([\n [\"All\", \"All\"],\n [\"Unknown\", 0],\n [\"Greek\", 1],\n [\"Mixed\", 2],\n [\"Barbarian\", 3],\n ]),\n {\n label: \"Hellenicity:\",\n value: \"All\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":37,"value":"Variables most likely to correlate to propensity for staseis as determined by a linear regression analysis:","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":32,"value":"viewof selectedDemocracy = Inputs.select(\n new Map([\n [\"All\", \"All\"],\n [\"Unknown\", 0],\n [\"No evidence of democracy\", 1],\n [\"Evidence for democracy\", 2],\n ]),\n {\n label: \"Democracy:\",\n value: \"All\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":34,"value":"viewof selectedProxenoi = Inputs.select(\n new Map([\n [\"All\", \"All\"],\n [\"No evidence for proxenoi\", 0],\n [\"Polis received proxenoi from other polis\", 1],\n [\"Polis gave, i.e. granted proxenia to citizens of other states\", 2],\n [\"Polis both gave and received\", 3]\n ]),\n {\n label: \"Proxenoi:\",\n value: \"All\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":36,"value":"viewof selectedArea1 = Inputs.select(\n new Map([\n [\"All\", \"All\"],\n [\"Area unknown or unlocated\", 0],\n [\"Less than 25 km²\", 1],\n [\"25 - 100 km²\", 2],\n [\"100-200 km²\", 3],\n [\"200-500 km²\", 4],\n [\"500-1,000 km²\", 5],\n [\"1,000 - 2,000 km²\", 6],\n [\"More than 2,000 km²\", 7],\n ]),\n {\n label: \"Total area controlled by a given polis:\",\n value: \"All\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3,"value":"$51","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"//stuff from the leaflet tutorial condensed so its not a bunch of cells that display as \n\n\n//var marker = L.marker([42.10240033, 9.511828]).addTo(map);\n\n//var circle = L.circle([41.50240033, 9.911828], {\n// color: 'red',\n // fillColor: '#f03',\n // fillOpacity: 0.5,\n // radius: 15000\n//}).addTo(map);\n\n//marker.bindPopup(\"Hello world!
I am a popup.\").openPopup();\n//circle.bindPopup(\"I am a circle.\");\n\n//var popup = L.popup()\n // .setLatLng([40.50240033, 10.911828])\n // .setContent(\"I am a standalone popup.\")\n // .openOn(map);","pinned":false,"hidden":false,"mode":"ts","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W52","stdlib":"2"}} 24:null