40:null 41:["$","title",null,{"children":"Evaluate Climate Risks | Abebemulugeta2001 | Observable"}] 47:T480,// format admin selections - UPDATED geoImpactAdminSelectors = { const labelCountry = _lang(nbText.supportNbText.words.country.singular) const labelRegion = _lang(nbText.supportNbText.words.region.singular) const labelSubregion = _lang(nbText.supportNbText.words.subregion.singular) const labelWoreda = _lang(nbText.supportNbText.words.woreda.singular) console.log(selectAdmin3) return Inputs.form( [ Inputs.bind( Inputs.select(dataAdmin0, { label: labelCountry, format: (x) => x.label }), viewof selectAdmin0 ), Inputs.bind( Inputs.select(dataAdmin1, { label: labelRegion, format: (x) => x.label }), viewof selectAdmin1 ), Inputs.bind( Inputs.select(dataAdmin2, { label: labelSubregion, format: (x) => x.label }), viewof selectAdmin2 ), Inputs.bind( Inputs.select(dataAdmin3, { label: labelWoreda, format: (x) => x.label }), viewof selectAdmin3 ) ], { template: adminFormTemplate } ); }48:T1100,// define choices for the data value viewof selectGeoDataType = { // --- START OF CURRENCY CONVERSION LOGIC FOR MAP LAYER --- const DOLLAR_TO_BIRR_RATE = usdToEtbExchangeRate; // Function to convert a numerical dollar value to a Birr-formatted string const formatBirrFromDollar = (dollarValue) => { if (dollarValue === null || dollarValue === undefined || isNaN(dollarValue)) return "---"; const birrValue = dollarValue * DOLLAR_TO_BIRR_RATE; let birrOutput; let newMagnitudeLabel = ''; if (birrValue >= 1000000000000) { newMagnitudeLabel = 'T'; birrOutput = (birrValue / 1000000000000).toFixed(1); } else if (birrValue >= 1000000000) { newMagnitudeLabel = 'B'; birrOutput = (birrValue / 1000000000).toFixed(1); } else if (birrValue >= 1000000) { newMagnitudeLabel = 'M'; birrOutput = (birrValue / 1000000).toFixed(1); } else { birrOutput = Math.round(birrValue).toLocaleString(language.locale); } return `2005 ETB${birrOutput}${newMagnitudeLabel}`; }; // Function to show both Birr and Dollar in tooltips (map) - Birr without year, Dollar with year const formatBirrAndDollarFromDollar = (dollarValue) => { if (dollarValue === null || dollarValue === undefined || isNaN(dollarValue)) return "---"; const birrStr = formatBirrFromDollar(dollarValue).replace("2005 ", ""); const dollarStr = "2005 Int$" + formatUSD({locale: language.locale})(dollarValue).replace("$", ""); return `${birrStr} | ${dollarStr}`; }; // Function to format Birr for legend (similar to formatUSD but for ETB) const formatBirrLegend = (birrValue) => { if (birrValue === null || birrValue === undefined || isNaN(birrValue)) return ""; return formatUSD({locale: language.locale})(birrValue); }; // --- END OF CURRENCY CONVERSION LOGIC --- const options = [ { key: "population", // lookup id for data option dataColumn: "rural_pop", // data column label: _lang(nbText.africaMap.inputs.mapLayer.options.ruralPop.label), // label labelTip: _lang( nbText.africaMap.inputs.mapLayer.options.ruralPop.labelTip ), // label for tooltip labelLegend: _lang( nbText.africaMap.inputs.mapLayer.options.ruralPop.labelLegend ), // label for legend formatFunc: formatNumCompactShort({locale: language.locale}), // formatting function for raw data value formatFuncLegend: formatNumCompactShort({locale: language.locale}), // formatting function for legend colorRange: colorScales.range.yellowGreen, // color range colorUnknown: colorScales.unknown // unknown fill color }, { key: "urban_population", // lookup id for data option dataColumn: "urban_pop", // data column label: _lang(nbText.africaMap.inputs.mapLayer.options.urbanPop.label), // label labelTip: _lang( nbText.africaMap.inputs.mapLayer.options.urbanPop.labelTip ), // label for tooltip labelLegend: _lang( nbText.africaMap.inputs.mapLayer.options.urbanPop.labelLegend ), // label for legend formatFunc: formatNumCompactShort({locale: language.locale}), // formatting function for raw data value formatFuncLegend: formatNumCompactShort({locale: language.locale}), // formatting function for legend colorRange: colorScales.range.yellowGreen, // color range colorUnknown: colorScales.unknown // unknown fill color }, { key: "vop", dataColumn: "vop_total", label: _lang(nbText.africaMap.inputs.mapLayer.options.vop.label), labelTip: _lang(nbText.africaMap.inputs.mapLayer.options.vop.labelTip), labelLegend: Lang.reduceReplaceTemplateItems( _lang(nbText.africaMap.inputs.mapLayer.options.vop.labelLegend), [{ name: "unit", value: "2005 ETB" }] ), formatFunc: formatBirrAndDollarFromDollar, formatFuncLegend: (dollarValue) => formatBirrLegend(dollarValue * DOLLAR_TO_BIRR_RATE), colorRange: colorScales.range.yellowGreen, colorUnknown: colorScales.unknown } ]; return Inputs.radio( options.sort((a, b) => b.key.localeCompare(a.key)), { width: 300, label: _lang(nbText.africaMap.inputs.mapLayer.label), format: (x) => x.label, value: options.find((t) => t.key === "vop") } ); } 49:T120f,plotChoroplethGeoImpact = { const data = mapDataGeoImpact; const selector = selectGeoDataType; const vopCaption = _lang(nbText.vopNoteMd.caption); const missingDataLabel = Lang.reduceReplaceTemplateItems( _lang(nbText.missingMapDataBlurb), [{name: "data_label", value: selector.label}] ); // Use automatic projection - it works best for all admin levels const plot = Plot.plot({ width: mapWidth, height: 550, caption: `${missingDataLabel} ${vopCaption}`, color: { legend: true, label: selector.labelLegend, range: selector.colorRange, unknown: selector.colorUnknown, tickFormat: selector.formatFuncLegend, }, marks: [ // geo data - always show the main map Plot.geo(data.features, { fill: (d) => { const dataColumn = selector.dataColumn; const fillValue = d.properties.data ? d.properties.data[dataColumn] : null; let adjustedValue = fillValue; // Apply gender disaggregation if selected if (disaggFilter !== "All" && d.properties.data) { const genderRatio = disaggFilter === "Men" ? d.properties.data.gender_men : d.properties.data.gender_women; adjustedValue = fillValue * (genderRatio || 0.5); } return adjustedValue; }, stroke: "#fff", strokeWidth: 0.5 }), // admin2 highlight - show for all countries when subregion is selected Plot.geo(adminSelections.selectAdmin2.value ? data.features.filter(d => d.properties.admin2_name == adminSelections.selectAdmin2.value) : [], { fill: null, stroke: "#333", strokeWidth: 2.5 }), // admin3 highlight - ONLY FOR ETHIOPIA Plot.geo(adminSelections.selectAdmin0.value === "Ethiopia" && adminSelections.selectAdmin3.value ? data.features.filter(d => d.properties.admin3_name == adminSelections.selectAdmin3.value) : [], { fill: null, stroke: "#000", strokeWidth: 3 }), // geo pointer Plot.geo(data, Plot.pointer( Plot.centroid({ stroke: "#333", strokeWidth: 1.5, }))), // tooltip Plot.tip( data.features, Plot.pointer( Plot.centroid({ channels: { name: { label: getLowerLevelAdminLabel(), value: (d) => { if (d.properties.admin3_name) return d.properties.admin3_name; if (d.properties.admin2_name) return d.properties.admin2_name; if (d.properties.admin1_name) return d.properties.admin1_name; const translated = _lang(td.admin0_name.values?.[d.properties.admin_name]); return translated ?? d.properties.admin_name; } }, data: { label: selector.labelTip, value: (d) => { const dataColumn = selector.dataColumn; let value = d.properties.data ? d.properties.data[dataColumn] : undefined; // Apply gender disaggregation to tooltip if (disaggFilter !== "All" && d.properties.data) { const genderRatio = disaggFilter === "Men" ? d.properties.data.gender_men : d.properties.data.gender_women; value = value * (genderRatio || 0.5); } return value; }, } }, format: { name: true, data: (d) => selector.formatFunc(d) } }) ) ) ] }); // Wrap in a container to extract SVG after rendering const container = htl.html`

${styling}${plot}

`; // Use MutationObserver to extract SVG after it's rendered if (typeof MutationObserver !== 'undefined') { const observer = new MutationObserver((mutations, obs) => { const figure = container.querySelector('figure'); if (figure) { const svg = figure.querySelector('svg'); if (svg) { // Store the SVG reference on the container for export function to access container._exportSvg = svg; obs.disconnect(); } } }); // Start observing if (container.querySelector) { observer.observe(container, { childList: true, subtree: true }); } } return container; }4a:T66b0,viewof exportPlotChoroplethGeoImpact = { // Helper: Download blob const downloadBlob = (blob, filename) => { const url = URL.createObjectURL(blob); const a = document.createElement('a'); a.href = url; a.download = filename; a.style.display = 'none'; document.body.appendChild(a); a.click(); document.body.removeChild(a); setTimeout(() => URL.revokeObjectURL(url), 100); }; // Helper: Show notification const showNotification = (message, isError = false) => { const notification = html`

${message}

`; document.body.appendChild(notification); setTimeout(() => { if (notification.parentNode) { notification.parentNode.removeChild(notification); } }, isError ? 5000 : 3000); }; // Helper: Download as SVG const downloadAsSvg = (svg, filename) => { const clone = svg.cloneNode(true); const serializer = new XMLSerializer(); const svgString = serializer.serializeToString(clone); const blob = new Blob([svgString], { type: 'image/svg+xml' }); downloadBlob(blob, filename); }; // Helper: Download as raster (PNG/JPEG) const downloadAsRaster = (svg, filename, format) => { return new Promise((resolve, reject) => { const clone = svg.cloneNode(true); const serializer = new XMLSerializer(); let svgString = serializer.serializeToString(clone); if (!svgString.includes('\n' + svgString; } let width, height; const viewBox = svg.getAttribute('viewBox'); if (viewBox) { const parts = viewBox.split(/\s+|,/).filter(p => p).map(parseFloat); if (parts.length === 4) { width = parts[2]; height = parts[3]; } } if (!width || !height) { width = svg.getAttribute('width') ? parseFloat(svg.getAttribute('width')) : null; height = svg.getAttribute('height') ? parseFloat(svg.getAttribute('height')) : null; } if (!width || !height) { const rect = svg.getBoundingClientRect(); width = rect.width || 900; height = rect.height || 550; } const svgDataUrl = 'data:image/svg+xml;charset=utf-8,' + encodeURIComponent(svgString); const canvas = document.createElement('canvas'); const ctx = canvas.getContext('2d'); canvas.width = width; canvas.height = height; ctx.fillStyle = 'white'; ctx.fillRect(0, 0, width, height); const img = new Image(); img.crossOrigin = 'anonymous'; img.onload = () => { try { ctx.drawImage(img, 0, 0, width, height); canvas.toBlob( (blob) => { if (blob) { downloadBlob(blob, filename); resolve(); } else { reject(new Error('Failed to create blob from canvas')); } }, format === 'png' ? 'image/png' : 'image/jpeg', format === 'jpeg' || format === 'jpg' ? 0.92 : 1.0 ); } catch (drawError) { reject(new Error(`Failed to draw image: ${drawError.message}`)); } }; img.onerror = () => { reject(new Error('Failed to load SVG image')); }; img.src = svgDataUrl; }); }; // Helper: Download as CSV const downloadAsCsv = (data, filename) => { if (!data || data.length === 0) { throw new Error(_lang(nbText.export.noDataCsv)); } const headers = Object.keys(data[0]); const csvRows = []; csvRows.push(headers.join(',')); for (const row of data) { const values = headers.map(header => { const value = row[header]; if (value === null || value === undefined) return ''; const stringValue = String(value); if (stringValue.includes(',') || stringValue.includes('"') || stringValue.includes('\n')) { return `"${stringValue.replace(/"/g, '""')}"`; } return stringValue; }); csvRows.push(values.join(',')); } const csvContent = csvRows.join('\n'); const blob = new Blob([csvContent], { type: 'text/csv;charset=utf-8;' }); downloadBlob(blob, filename); }; // Helper: Download as JSON const downloadAsJson = (data, filename) => { const jsonString = JSON.stringify(data, null, 2); const blob = new Blob([jsonString], { type: 'application/json' }); downloadBlob(blob, filename); }; // Helper: Download as GeoJSON const downloadAsGeoJson = (geojson, filename) => { const jsonString = JSON.stringify(geojson, null, 2); const blob = new Blob([jsonString], { type: 'application/geo+json' }); downloadBlob(blob, filename); }; // Helper: Download as Shapefile (pure-JS, no external dependencies) const downloadAsShapefile = (geojson, filename) => { showNotification('Generating shapefile...', false); // CRC-32 table used by ZIP const crcTable = (() => { const t = new Uint32Array(256); for (let i = 0; i < 256; i++) { let c = i; for (let j = 0; j < 8; j++) c = (c & 1) ? (0xEDB88320 ^ (c >>> 1)) : (c >>> 1); t[i] = c; } return t; })(); const crc32 = (data) => { let crc = 0xFFFFFFFF; for (let i = 0; i < data.length; i++) crc = crcTable[(crc ^ data[i]) & 0xFF] ^ (crc >>> 8); return (crc ^ 0xFFFFFFFF) >>> 0; }; // Build .shp and .shx buffers from GeoJSON features const buildShapefiles = (features) => { // Pick shape type from first non-null geometry let shapeType = 5; for (const f of features) { if (!f.geometry) continue; if (f.geometry.type === 'Point' || f.geometry.type === 'MultiPoint') { shapeType = 1; break; } if (f.geometry.type === 'LineString' || f.geometry.type === 'MultiLineString') { shapeType = 3; break; } if (f.geometry.type === 'Polygon' || f.geometry.type === 'MultiPolygon') { shapeType = 5; break; } } const getRings = (geom) => { if (geom.type === 'Polygon') return geom.coordinates; if (geom.type === 'MultiPolygon') return geom.coordinates.flat(1); if (geom.type === 'LineString') return [geom.coordinates]; if (geom.type === 'MultiLineString') return geom.coordinates; return null; }; let gMinX = Infinity, gMinY = Infinity, gMaxX = -Infinity, gMaxY = -Infinity; const recs = features.map(f => { const geom = f.geometry; if (!geom) return { type: 0 }; if (shapeType === 1) { const coords = geom.type === 'Point' ? geom.coordinates : geom.coordinates[0]; const [x, y] = coords; if (x < gMinX) gMinX = x; if (y < gMinY) gMinY = y; if (x > gMaxX) gMaxX = x; if (y > gMaxY) gMaxY = y; return { type: 1, x, y, contentBytes: 20 }; } const rings = getRings(geom); if (!rings) return { type: 0 }; let minX = Infinity, minY = Infinity, maxX = -Infinity, maxY = -Infinity, totalPts = 0; for (const ring of rings) { for (const [px, py] of ring) { if (px < minX) minX = px; if (py < minY) minY = py; if (px > maxX) maxX = px; if (py > maxY) maxY = py; totalPts++; } } if (minX < gMinX) gMinX = minX; if (minY < gMinY) gMinY = minY; if (maxX > gMaxX) gMaxX = maxX; if (maxY > gMaxY) gMaxY = maxY; // 4 (type) + 32 (bbox) + 4 (numParts) + 4 (numPoints) + 4*rings + 16*pts const contentBytes = 44 + 4 * rings.length + 16 * totalPts; return { type: shapeType, rings, minX, minY, maxX, maxY, totalPts, contentBytes }; }); if (!isFinite(gMinX)) { gMinX = 0; gMinY = 0; gMaxX = 0; gMaxY = 0; } const HDR = 100; let shpSize = HDR; for (const r of recs) shpSize += 8 + (r.type === 0 ? 4 : r.contentBytes); const shpBuf = new Uint8Array(shpSize); const shxBuf = new Uint8Array(HDR + recs.length * 8); const sv = new DataView(shpBuf.buffer); const xv = new DataView(shxBuf.buffer); const writeHdr = (dv, fileLen) => { dv.setInt32(0, 9994, false); dv.setInt32(24, fileLen / 2, false); dv.setInt32(28, 1000, true); dv.setInt32(32, shapeType, true); dv.setFloat64(36, gMinX, true); dv.setFloat64(44, gMinY, true); dv.setFloat64(52, gMaxX, true); dv.setFloat64(60, gMaxY, true); }; writeHdr(sv, shpSize); writeHdr(xv, shxBuf.length); let shpOff = HDR; for (let i = 0; i < recs.length; i++) { const r = recs[i]; const cLen = r.type === 0 ? 4 : r.contentBytes; xv.setInt32(HDR + i * 8, shpOff / 2, false); xv.setInt32(HDR + i * 8 + 4, cLen / 2, false); sv.setInt32(shpOff, i + 1, false); sv.setInt32(shpOff + 4, cLen / 2, false); shpOff += 8; if (r.type === 0) { sv.setInt32(shpOff, 0, true); shpOff += 4; } else if (r.type === 1) { sv.setInt32(shpOff, 1, true); shpOff += 4; sv.setFloat64(shpOff, r.x, true); shpOff += 8; sv.setFloat64(shpOff, r.y, true); shpOff += 8; } else { sv.setInt32(shpOff, r.type, true); shpOff += 4; sv.setFloat64(shpOff, r.minX, true); shpOff += 8; sv.setFloat64(shpOff, r.minY, true); shpOff += 8; sv.setFloat64(shpOff, r.maxX, true); shpOff += 8; sv.setFloat64(shpOff, r.maxY, true); shpOff += 8; sv.setInt32(shpOff, r.rings.length, true); shpOff += 4; sv.setInt32(shpOff, r.totalPts, true); shpOff += 4; let ptIdx = 0; for (const ring of r.rings) { sv.setInt32(shpOff, ptIdx, true); shpOff += 4; ptIdx += ring.length; } for (const ring of r.rings) { for (const [px, py] of ring) { sv.setFloat64(shpOff, px, true); shpOff += 8; sv.setFloat64(shpOff, py, true); shpOff += 8; } } } } return { shp: shpBuf, shx: shxBuf }; }; // Build .dbf attribute table const buildDbf = (features) => { const enc = new TextEncoder(); const allProps = features.map(f => f.properties || {}); const allKeys = [...new Set(allProps.flatMap(p => Object.keys(p)))]; const fields = allKeys.slice(0, 255).map(key => { const name = key.substring(0, 10); const vals = allProps.map(p => p[key]).filter(v => v !== null && v !== undefined); const isNum = vals.length > 0 && vals.every(v => typeof v === 'number' || (typeof v === 'string' && v.trim() !== '' && !isNaN(+v)) ); if (isNum) { const hasDecimal = vals.some(v => !Number.isInteger(typeof v === 'number' ? v : +v)); return { name, key, type: 'N', length: hasDecimal ? 18 : 11, decimals: hasDecimal ? 6 : 0 }; } const maxLen = Math.min(254, Math.max(1, ...vals.map(v => enc.encode(String(v)).length))); return { name, key, type: 'C', length: maxLen, decimals: 0 }; }); const n = features.length; const hdrSize = 32 + fields.length * 32 + 1; const recSize = 1 + fields.reduce((s, f) => s + f.length, 0); const buf = new Uint8Array(hdrSize + n * recSize + 1); const dv = new DataView(buf.buffer); const now = new Date(); buf[0] = 3; buf[1] = now.getFullYear() - 1900; buf[2] = now.getMonth() + 1; buf[3] = now.getDate(); dv.setUint32(4, n, true); dv.setUint16(8, hdrSize, true); dv.setUint16(10, recSize, true); let fOff = 32; for (const f of fields) { const nb = enc.encode(f.name); for (let i = 0; i < 11; i++) buf[fOff + i] = i < nb.length ? nb[i] : 0; buf[fOff + 11] = f.type.charCodeAt(0); buf[fOff + 16] = f.length; buf[fOff + 17] = f.decimals; fOff += 32; } buf[fOff] = 0x0D; for (let i = 0; i < n; i++) { const props = allProps[i]; let rOff = hdrSize + i * recSize; buf[rOff++] = 0x20; for (const f of fields) { const raw = props[f.key]; let s; if (raw === null || raw === undefined) { s = ' '.repeat(f.length); } else if (f.type === 'N') { s = String(typeof raw === 'number' ? raw : +raw).padStart(f.length).substring(0, f.length); } else { s = String(raw).substring(0, f.length).padEnd(f.length); } const bytes = enc.encode(s); for (let j = 0; j < f.length; j++) buf[rOff + j] = j < bytes.length ? bytes[j] : 0x20; rOff += f.length; } } buf[buf.length - 1] = 0x1A; return buf; }; // Build WGS-84 .prj const buildPrj = () => new TextEncoder().encode( 'GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],' + 'PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]' ); // Build ZIP using STORE (no compression) — no external libs needed const buildZip = (files) => { const enc = new TextEncoder(); const localParts = []; const centralParts = []; let localOffset = 0; for (const { name, data } of files) { const nb = enc.encode(name); const crc = crc32(data); const size = data.length; const lh = new Uint8Array(30 + nb.length); const lv = new DataView(lh.buffer); lv.setUint32(0, 0x04034b50, true); lv.setUint16(4, 20, true); lv.setUint16(8, 0, true); // version, STORE lv.setUint32(14, crc, true); lv.setUint32(18, size, true); lv.setUint32(22, size, true); lv.setUint16(26, nb.length, true); lh.set(nb, 30); const cdh = new Uint8Array(46 + nb.length); const cv = new DataView(cdh.buffer); cv.setUint32(0, 0x02014b50, true); cv.setUint16(4, 20, true); cv.setUint16(6, 20, true); cv.setUint32(16, crc, true); cv.setUint32(20, size, true); cv.setUint32(24, size, true); cv.setUint16(28, nb.length, true); cv.setUint32(42, localOffset, true); cdh.set(nb, 46); localParts.push(lh, data); centralParts.push(cdh); localOffset += lh.length + size; } const cdirOffset = localOffset; const cdirSize = centralParts.reduce((s, p) => s + p.length, 0); const eocd = new Uint8Array(22); const ev = new DataView(eocd.buffer); ev.setUint32(0, 0x06054b50, true); ev.setUint16(8, files.length, true); ev.setUint16(10, files.length, true); ev.setUint32(12, cdirSize, true); ev.setUint32(16, cdirOffset, true); const all = [...localParts, ...centralParts, eocd]; const total = all.reduce((s, p) => s + p.length, 0); const out = new Uint8Array(total); let pos = 0; for (const p of all) { out.set(p, pos); pos += p.length; } return out; }; const { shp, shx } = buildShapefiles(geojson.features); const dbf = buildDbf(geojson.features); const prj = buildPrj(); const base = filename.replace(/\.[^.]+$/, ''); const zipData = buildZip([ { name: `${base}.shp`, data: shp }, { name: `${base}.shx`, data: shx }, { name: `${base}.dbf`, data: dbf }, { name: `${base}.prj`, data: prj }, ]); downloadBlob(new Blob([zipData], { type: 'application/zip' }), `${base}.zip`); }; // Find the main map SVG (keep your existing findMap function) const findMap = () => { const chartNode = plotChoroplethGeoImpact; if (!chartNode) { console.error('plotChoroplethGeoImpact is not available'); return null; } let figure = null; if (chartNode.tagName === 'FIGURE') { figure = chartNode; } else if (chartNode.querySelector) { figure = chartNode.querySelector('figure'); } if (!figure) { console.error('Figure element not found'); return null; } const allSvgs = figure.querySelectorAll('svg'); if (allSvgs.length === 0) { console.error('No SVG elements found'); return null; } const scoredSvgs = Array.from(allSvgs).map(svg => { const allPaths = svg.querySelectorAll('path'); const rect = svg.getBoundingClientRect(); const viewBox = svg.getAttribute('viewBox'); const width = svg.getAttribute('width'); const height = svg.getAttribute('height'); const geoPaths = Array.from(allPaths).filter(path => { const fill = path.getAttribute('fill'); const stroke = path.getAttribute('stroke'); return (fill && fill !== 'none' && fill !== 'transparent') || stroke === '#fff' || stroke === '#333' || stroke === '#000'; }); let score = 0; score += geoPaths.length * 10; if (viewBox) { const parts = viewBox.split(/\s+|,/).filter(p => p).map(parseFloat); if (parts.length === 4) { const svgWidth = parts[2]; const svgHeight = parts[3]; if (svgWidth > 800 && svgHeight > 400) score += 100; if (svgWidth > 600 && svgHeight > 300) score += 50; } } if (width && height) { const w = parseFloat(width); const h = parseFloat(height); if (w > 800 && h > 400) score += 100; if (w > 600 && h > 300) score += 50; } if (rect.width > 800 && rect.height > 400) score += 100; if (rect.width > 600 && rect.height > 300) score += 50; if (rect.width < 300 || rect.height < 200) score -= 200; if (svg.querySelector('g[clip-path]')) score += 50; return { svg, score }; }); scoredSvgs.sort((a, b) => b.score - a.score); const bestSvg = scoredSvgs[0]; if (!bestSvg || bestSvg.score < 50) { console.error('Could not identify main map SVG'); return null; } return bestSvg.svg; }; // Get GeoJSON from mapDataGeoImpact (keep your existing getGeoJson function) const getGeoJson = () => { const selector = selectGeoDataType; const currentDisaggFilter = typeof disaggFilter !== 'undefined' ? disaggFilter : "All"; const geojson = { type: "FeatureCollection", features: mapDataGeoImpact.features.map(feature => { const props = feature.properties; const data = props.data || {}; let dataValue = data[selector.dataColumn]; if (currentDisaggFilter !== "All" && data) { const genderRatio = currentDisaggFilter === "Men" ? data.gender_men : data.gender_women; dataValue = dataValue * (genderRatio || 0.5); } return { type: "Feature", geometry: feature.geometry, properties: { admin0_name: props.admin0_name || '', admin1_name: props.admin1_name || '', admin2_name: props.admin2_name || '', admin3_name: props.admin3_name || '', admin_name: props.admin_name || '', [selector.dataColumn]: dataValue !== undefined ? dataValue : null, original_value: data[selector.dataColumn] !== undefined ? data[selector.dataColumn] : null, gender_men: data.gender_men !== undefined ? data.gender_men : null, gender_women: data.gender_women !== undefined ? data.gender_women : null, ...Object.keys(data).reduce((acc, key) => { if (!['gender_men', 'gender_women'].includes(key) && key !== selector.dataColumn) { acc[`data_${key}`] = data[key]; } return acc; }, {}) } }; }) }; return geojson; }; // Get CSV data const getCsvData = () => { const selector = selectGeoDataType; const currentDisaggFilter = typeof disaggFilter !== 'undefined' ? disaggFilter : "All"; return mapDataGeoImpact.features.map(feature => { const props = feature.properties; const data = props.data || {}; let dataValue = data[selector.dataColumn]; if (currentDisaggFilter !== "All" && data) { const genderRatio = currentDisaggFilter === "Men" ? data.gender_men : data.gender_women; dataValue = dataValue * (genderRatio || 0.5); } return { admin0_name: props.admin0_name || '', admin1_name: props.admin1_name || '', admin2_name: props.admin2_name || '', admin3_name: props.admin3_name || '', admin_name: props.admin_name || '', [selector.dataColumn]: dataValue !== undefined ? dataValue : null, original_value: data[selector.dataColumn] !== undefined ? data[selector.dataColumn] : null, gender_men: data.gender_men !== undefined ? data.gender_men : null, gender_women: data.gender_women !== undefined ? data.gender_women : null, ...Object.keys(data).reduce((acc, key) => { if (!['gender_men', 'gender_women'].includes(key) && key !== selector.dataColumn) { acc[`data_${key}`] = data[key]; } return acc; }, {}) }; }); }; // Get JSON data const getJsonData = () => { return getCsvData(); }; // Main download function const downloadChart = async (format) => { const timestamp = new Date().toISOString().replace(/[:.]/g, '-').split('T')[0]; const selector = selectGeoDataType; const baseFilename = `geo-impact-map-${selector.dataColumn}-${timestamp}`; if (format === 'csv') { try { const csvData = getCsvData(); const filename = `${baseFilename}.csv`; downloadAsCsv(csvData, filename); showNotification(_lang(nbText.export.csvSuccess)); } catch (error) { console.error('CSV export failed:', error); showNotification(`${_lang(nbText.export.csvFailed)}: ${error.message || error}`, true); } return; } if (format === 'json') { try { const jsonData = getJsonData(); const filename = `${baseFilename}.json`; downloadAsJson(jsonData, filename); showNotification(_lang(nbText.export.jsonSuccess)); } catch (error) { console.error('JSON export failed:', error); showNotification(`${_lang(nbText.export.jsonFailed)}: ${error.message || error}`, true); } return; } if (format === 'geojson') { try { const geojson = getGeoJson(); const filename = `${baseFilename}.geojson`; downloadAsGeoJson(geojson, filename); showNotification(_lang(nbText.export.geojsonSuccess)); } catch (error) { console.error('GeoJSON export failed:', error); showNotification(`${_lang(nbText.export.geojsonFailed)}: ${error.message || error}`, true); } return; } if (format === 'shapefile') { try { const geojson = getGeoJson(); const filename = `${baseFilename}.shp`; downloadAsShapefile(geojson, filename); showNotification(_lang(nbText.export.shapefileSuccess)); } catch (error) { console.error('Shapefile export failed:', error); showNotification(`${_lang(nbText.export.shapefileFailed)}: ${error.message || error}`, true); } return; } const svg = findMap(); if (!svg) { const errorMsg = _lang(nbText.export.geoImpactMapNotFound); console.error(errorMsg); showNotification(errorMsg, true); return; } const filename = `${baseFilename}.${format}`; try { if (format === 'svg') { downloadAsSvg(svg, filename); showNotification(_lang(nbText.export.exportSuccess)); } else { await downloadAsRaster(svg, filename, format); showNotification(_lang(nbText.export.exportSuccess)); } } catch (error) { console.error('Download failed:', error); showNotification(`${_lang(nbText.export.downloadFailed)}: ${error.message || error}`, true); } }; // Create select element const select = html``; select.onchange = async (event) => { const format = event.target.value; if (format) { try { await downloadChart(format); event.target.value = ''; } catch (error) { console.error('Export error:', error); } } }; return html`

${_lang(nbText.export.titleGeoImpactMap)}

${select}

• ${_lang(nbText.export.hintPng)}

• ${_lang(nbText.export.hintJpeg)}

• ${_lang(nbText.export.hintSvgVector)}

• ${_lang(nbText.export.hintCsvData)}

• ${_lang(nbText.export.hintJsonData)}

• ${_lang(nbText.export.hintGeojson)}

• ${_lang(nbText.export.hintShapefile)}

`; } 4b:T12b8,// text insights for geo impact textDynamicInsights_geoImpact ={ // Build the full admin hierarchy string with all preceding admin levels const parts = []; // Always include admin0 (country) const admin0 = getAdminSelectionAdmin0(); if (admin0 && admin0.value) { const admin0Label = _lang(td.admin0_name.values?.[admin0.value ?? "SSA"]["article3"]); parts.push(admin0Label); } // Determine the last selected level to put in parentheses let lastLevel = null; // Check in reverse order (admin3 -> admin2 -> admin1) to find the most granular selection if (adminSelections.selectAdmin3 && adminSelections.selectAdmin3.value) { // If admin3 (woreda) is selected, include admin1 and admin2 in parts, put admin3 in parentheses if (adminSelections.selectAdmin1 && adminSelections.selectAdmin1.value) { parts.push(adminSelections.selectAdmin1.label); } if (adminSelections.selectAdmin2 && adminSelections.selectAdmin2.value) { parts.push(adminSelections.selectAdmin2.label); } lastLevel = adminSelections.selectAdmin3.label || adminSelections.selectAdmin3.value; } else if (adminSelections.selectAdmin2 && adminSelections.selectAdmin2.value) { // If admin2 (subregion) is selected (but no admin3), include admin1 in parts, put admin2 in parentheses if (adminSelections.selectAdmin1 && adminSelections.selectAdmin1.value) { parts.push(adminSelections.selectAdmin1.label); } lastLevel = adminSelections.selectAdmin2.label; } else if (adminSelections.selectAdmin1 && adminSelections.selectAdmin1.value) { // If admin1 (region) is selected (but no admin2), put admin1 in parentheses lastLevel = adminSelections.selectAdmin1.label; } // Build the final string let adminSelection; if (lastLevel) { adminSelection = parts.length > 0 ? `${parts.join(", ")} (${lastLevel})` : `(${lastLevel})`; } else { adminSelection = parts.length > 0 ? parts.join(", ") : getAdminSelection().label; } const i = dynamicInsights_geoImpact.insight; // Note: Values from dynamicInsights_geoImpact are already converted to Birr format // No need to convert again - just use them directly const translateCrop = (crop) => _lang(td.crop.values?.[crop]); // Custom function to handle filtering and list formatting // Values are already in Birr format from dynamicInsights_geoImpact const formatListInBirr = (items) => { // Filter out items with no data (data === 0, undefined, or label/value is "---") const filtered = items.filter((d) => d.data !== 0 && d.data !== undefined && d.label !== "---" && d.value !== "---" && d.label !== undefined && d.value !== undefined ); if (filtered.length === 0) { return "---"; } return filtered.map( (d, i) => `${ i == filtered.length - 1 && filtered.length > 1 ? `${_lang(nbText.supportNbText.words.and)} ` : "" }**${translateCrop(d.label)}** (**${d.value}**)` // Value is already in Birr format ).join(", "); }; const topCommoditiesList = formatListInBirr(i.topCommodities); const topLivestockList = formatListInBirr(i.topLivestock); // The rest of the code remains the same, using the Birr-converted values const langBasePath = nbText.africaMap.insights; const langOverview = Lang.reduceReplaceTemplateItems( _lang(langBasePath.insightOverview), [ { name: "admin_selection", value: adminSelection }, { name: "total_vop", value: i.totalVop } // Already in Birr format from dynamicInsights_geoImpact ] ); const langAreaAndPop = Lang.reduceReplaceTemplateItems( _lang(langBasePath.insightAreaAndPop), [ { name: "area", value: i.totalHa }, { name: "population", value: i.totalPop } ] ); const langTopCommodity = Lang.reduceReplaceTemplateItems( _lang(langBasePath.insightTopCommodity), [ { name: "commodity_word", value: "commodities" }, { name: "verb", value: topCommoditiesList.length == 1 ? _lang(nbText.supportNbText.words.toBe.singular) : _lang(nbText.supportNbText.words.toBe.plural) }, { name: "list_string", value: topCommoditiesList } ] ); const langTopLivestock = Lang.reduceReplaceTemplateItems( _lang(langBasePath.insightTopLivestock), [ { name: "verb", value: topLivestockList.length == 1 ? _lang(nbText.supportNbText.words.toBe.singular) : _lang(nbText.supportNbText.words.toBe.plural) }, { name: "list_string", value: topLivestockList } ] ); return md`${langOverview} ${langAreaAndPop} ${langTopCommodity} ${langTopLivestock}`; } 4c:T3551,hazardVopChart ={ // --- START OF CURRENCY CONVERSION LOGIC --- const formatBirr = (dollarValue) => formatCurrencyToBirr(dollarValue, { year: intDollarYear, includeCurrency: true }); // Birr (no year) and Dollar (with year) for tooltips - same as map/bar chart const formatBirrAndDollar = (dollarValue) => { if (dollarValue === null || dollarValue === undefined || isNaN(dollarValue)) return "---"; const birrStr = formatBirr(dollarValue).replace("2005 ", ""); const dollarStr = "2005 Int$" + formatUSD({locale: language.locale})(dollarValue).replace("$", ""); return `${birrStr} | ${dollarStr}`; }; // --- END OF CURRENCY CONVERSION LOGIC --- const chartType = (ChartType === "line" || ChartType === "bar") ? ChartType : "bar"; const labelPerc = _lang(nbText.climateRisks.compoundHazards.stackedBar.tooltipLabels.totalVop) const labelHazard = _lang(nbText.climateRisks.compoundHazards.stackedBar.tooltipLabels.hazard) const labelVop = _lang(nbText.climateRisks.compoundHazards.stackedBar.tooltipLabels.vopRisk) const xLabel = _lang(nbText.climateRisks.compoundHazards.stackedBar.xLabel) const marginLeft = _lang({en: 110, fr: 150}); const _anyData = T.tidy( data_hazardVoP, T.filter((d) => !["any", "no hazard"].includes(d.hazard)), // only hazard components T.groupBy( [ "admin0_name", "admin1_name", "admin2_name", "scenario", "timeframe", "severity", "crop" ], [ T.summarize({ vop_any: T.sum("vop") }) ] ) ); const _dataWithAnyColumn = T.tidy( data_hazardVoP, T.leftJoin(_anyData, { by: [ "admin0_name", "admin1_name", "admin2_name", "scenario", "timeframe", "crop", "severity" ] }) ); const data = _dataWithAnyColumn; const dataAny = data.filter((d) => d.hazard == "any"); // combined const dataBars = [ ...data.filter((d) => d.hazard !== "any" && d.vop !== 0) // remove the combined hazard ]; const yDomain = cropNames .filter((d) => { const availableCrops = _.uniq(dataBars.map((d) => d.crop)); return availableCrops.includes(d.crop); }) .sort((a,b) => { // sort by type, then name if (a.type < b.type) return -1 if (a.type > b.type) return 1 if (a.cropName < b.cropName) return -1 if (a.cropName > b.cropName) return 1 return 0 }) .map((d) => d.cropName); const vopCaption = _lang(nbText.vopNoteMd.caption); // Line chart implementation if (chartType === "line") { // Aggregate data by crop and hazard, ignoring admin fields // This ensures we show a single aggregated value per crop-hazard combination // even if the database returns multiple rows for different sub-units // (Plot.stackX in the bar chart handles this automatically, but line charts need explicit aggregation) // First, aggregate vop by crop and hazard const aggregatedVop = T.tidy( dataBars, T.groupBy( [ "crop", "hazard", "scenario", "timeframe", "severity" ], [ T.summarize({ vop: T.sum("vop") }) ] ) ); // Calculate vop_total as the sum of all vop values for each crop (across all hazards) const vopTotalByCrop = T.tidy( aggregatedVop, T.groupBy( [ "crop", "scenario", "timeframe", "severity" ], [ T.summarize({ vop_total: T.sum("vop") }) ] ) ); // Join vop_total back to aggregated data const aggregatedData = T.tidy( aggregatedVop, T.leftJoin(vopTotalByCrop, { by: ["crop", "scenario", "timeframe", "severity"] }) ); // Calculate vop_any as the sum of all vop values for each crop (same as vop_total for aggregated data) const aggregatedDataFinal = T.tidy( aggregatedData, T.mutate({ vop_any: (d) => d.vop_total // For aggregated data, vop_any equals vop_total }) ); // Prepare data for line chart: group by hazard, then sort by crop order // Ensure we only have one data point per crop-hazard combination // Clip percentage values to 0-100 range to prevent lines going off-chart const lineDataMap = new Map(); aggregatedDataFinal.forEach(d => { const key = `${d.crop}_${d.hazard}`; if (!lineDataMap.has(key)) { const percentage = Math.min(Math.max((d.vop / d.vop_total) * 100, 0), 100); // Clip to 0-100 lineDataMap.set(key, { crop: hazardPlotLookup.crops[d.crop], hazard: hazardPlotLookup.names[d.hazard], hazardKey: d.hazard, percentage: percentage, vop: d.vop, vop_total: d.vop_total, vop_any: d.vop_any || d.vop_total, cropKey: d.crop }); } }); const lineDataRaw = Array.from(lineDataMap.values()); // Group by hazard and ensure consistent crop order across all hazards // Use yDomain order (which is already sorted by type and name) for consistency const lineDataByHazard = {}; lineDataRaw.forEach(d => { if (!lineDataByHazard[d.hazard]) { lineDataByHazard[d.hazard] = []; } lineDataByHazard[d.hazard].push(d); }); // Show all hazards on the line chart (not filtered by selection) let lineData = []; let uniqueSortedCrops = yDomain; // Default to yDomain // Always show all hazards for line chart, sorted by yDomain order Object.keys(lineDataByHazard).forEach(hazard => { const hazardData = lineDataByHazard[hazard]; hazardData.sort((a, b) => { const indexA = yDomain.indexOf(a.crop); const indexB = yDomain.indexOf(b.crop); if (indexA === -1 && indexB === -1) return 0; if (indexA === -1) return 1; if (indexB === -1) return -1; return indexA - indexB; }); lineData.push(...hazardData); }); const plot = Plot.plot({ width, height: Math.max(400, uniqueSortedCrops.length * 25), // More compact spacing: 25px per crop instead of 60px marginLeft, marginRight: 85, marginTop: 40, marginBottom: Math.max(80, (uniqueSortedCrops.length > 0 ? uniqueSortedCrops.length : yDomain.length) * 2), // Increased bottom margin for vertical labels (at least 80px, or 2px per crop) caption: vopCaption, color: { domain: hazardPlotLookup.color.domain, range: hazardPlotLookup.color.range, legend: true }, x: { domain: uniqueSortedCrops.length > 0 ? uniqueSortedCrops : yDomain, // Use sorted crops if available, otherwise use yDomain label: null, axis: "bottom", padding: 0.1, // Add padding between crop labels to prevent overlap tickRotate: -90 // Rotate labels 90 degrees (vertical) to save horizontal space }, y: { domain: [0, 100], label: xLabel, axis: "left", grid: true, ticks: [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] // Ticks every 10 from 0 to 100 }, marks: [ // Lines for each hazard Plot.line( lineData, { x: "crop", y: "percentage", stroke: "hazard", strokeWidth: 2, // Slightly thinner lines for better visibility with many crops curve: "linear", // Use straight lines instead of curved z: "hazard" // Ensure lines are drawn in consistent order } ), // Points for each hazard-crop combination Plot.dot( lineData, { x: "crop", y: "percentage", fill: "hazard", stroke: "#fff", strokeWidth: 1, r: 3.5, // Smaller points (3.5 instead of 5) to reduce overlap channels: { perc: { label: labelPerc, value: (d) => { const percent = formatPercentWhole(d.vop_any / d.vop_total); const vop = formatBirrAndDollar(d.vop_any); return `${percent} (${vop})`; } }, hazard: { label: labelHazard, value: (d) => d.hazard }, vop: { label: labelVop, value: (d) => { const percent = formatPercentWhole(d.vop / d.vop_total); const vop = formatBirrAndDollar(d.vop); return `${percent} (${vop})`; } } }, tip: { format: { x: false, y: false, fill: false, vop: true, hazard: true, perc: true }, lineWidth: 50 // Match the bar chart tooltip width } } ) ] }); // Wrap in container and expose SVG for export const container = htl.html`

`; container.appendChild(plot); // Use MutationObserver to extract SVG once rendered const observer = new MutationObserver(() => { const figure = container.querySelector('figure'); if (figure) { const svgs = Array.from(figure.querySelectorAll('svg')); if (svgs.length > 0 && !container._exportSvg) { container._exportSvg = svgs.reduce((best, s) => s.children.length > best.children.length ? s : best); observer.disconnect(); } } }); observer.observe(container, { childList: true, subtree: true }); return container; } // Bar chart implementation (original) const plot = Plot.plot({ width, marginLeft, marginRight: 85, caption: vopCaption, color: { domain: hazardPlotLookup.color.domain, range: hazardPlotLookup.color.range, legend: true }, x: { ticks: 1, axis: "top", domain: [0, 100], grid: true, label: xLabel }, y: { domain: yDomain, label: null }, marks: [ // main y-axis Plot.axisY({ tickSize: 0 }), // pointer white-out Plot.axisY( Plot.pointerY({ fill: "white", textStroke: "white", textStrokeWidth: 2, tickSize: 0 }) ), // bold pointer Plot.axisY( Plot.pointerY({ fontWeight: "bold", tickSize: 0 }) ), // hazard component bars Plot.barX( dataBars, Plot.stackX( { order: hazardPlotLookup.color.domain }, { x: (d) => (d.vop / d.vop_total) * 100, y: (d) => hazardPlotLookup.crops[d.crop], fill: (d) => hazardPlotLookup.names[d.hazard], stroke: "#fff", strokeWidth: 0.25 } ) ), // tooltip Plot.tip( dataBars, Plot.pointerY( Plot.stackX( { order: hazardPlotLookup.color.domain }, { x: (d) => (d.vop / d.vop_total) * 100, y: (d) => hazardPlotLookup.crops[d.crop], fill: (d) => hazardPlotLookup.names[d.hazard], channels: { perc: { label: labelPerc, value: (d) => { const percent = formatPercentWhole(d.vop_any / d.vop_total); const vop = formatBirrAndDollar(d.vop_any); return `${percent} (${vop})`; } }, hazard: { label: labelHazard, value: (d) => hazardPlotLookup.names[d.hazard] }, vop: { label: labelVop, value: (d) => { const percent = formatPercentWhole(d.vop / d.vop_total); const vop = formatBirrAndDollar(d.vop); return `${percent} (${vop})`; } } }, format: { x: false, y: false, fill: false, vop: true, hazard: true, perc: true }, lineWidth: 50 } ) ) ), // total VoP, sidebar highlight Plot.textX( dataAny, Plot.pointerY({ x: 100, y: (d) => hazardPlotLookup.crops[d.crop], text: (d) => { const value = formatBirr(d.vop_total); return `${value}`; }, textAnchor: "start", dx: 5 }) ) ] }); // Wrap in container and expose SVG for export const container = htl.html`

${message}

${_lang(nbText.export.titleHazardVop)}

${select}

• ${_lang(nbText.export.hintPng)}

• ${_lang(nbText.export.hintJpeg)}

• ${_lang(nbText.export.hintSvgVector)}

• ${_lang(nbText.export.hintCsvData)}

• ${_lang(nbText.export.hintJsonData)}

`; } 4e:T10bf,// named: downloadChoroplethMap downloadChoroplethMap = { const downloadMap = async (format) => { await new Promise(resolve => setTimeout(resolve, 100)); const selectors = ['svg', '.observablehq--cell svg', 'main svg']; let svg = null; for (const selector of selectors) { const elements = document.querySelectorAll(selector); if (elements.length > 0) { svg = Array.from(elements).reduce((largest, current) => { const currentRect = current.getBoundingClientRect(); const largestRect = largest?.getBoundingClientRect(); return (!largest || currentRect.width > largestRect.width) ? current : largest; }, elements[0]); break; } } if (!svg) { alert(_lang(nbText.export.mapNotFound)); return; } const timestamp = new Date().toISOString().split('T')[0]; const filename = `choropleth-map-${timestamp}.${format}`; try { if (format === 'svg') { await downloadAsSvg(svg, filename); } else { await downloadAsRaster(svg, filename, format); } } catch (error) { alert(`${_lang(nbText.export.downloadFailed)}: ${error.message}`); } }; const downloadAsSvg = async (svg, filename) => { const clone = svg.cloneNode(true); const serializer = new XMLSerializer(); const svgString = serializer.serializeToString(clone); const blob = new Blob([svgString], { type: 'image/svg+xml' }); await downloadBlob(blob, filename); }; const downloadAsRaster = async (svg, filename, format) => { return new Promise((resolve, reject) => { const mimeType = format === 'png' ? 'image/png' : 'image/jpeg'; const rect = svg.getBoundingClientRect(); const width = rect.width || 800; const height = rect.height || 600; const canvas = document.createElement('canvas'); const ctx = canvas.getContext('2d'); canvas.width = width; canvas.height = height; if (format === 'jpg') { ctx.fillStyle = 'white'; ctx.fillRect(0, 0, width, height); } const svgString = new XMLSerializer().serializeToString(svg); const svgBlob = new Blob([svgString], { type: 'image/svg+xml' }); const url = URL.createObjectURL(svgBlob); const img = new Image(); img.onload = () => { ctx.drawImage(img, 0, 0, width, height); URL.revokeObjectURL(url); canvas.toBlob(async (blob) => { if (blob) { await downloadBlob(blob, filename); resolve(); } else { reject(new Error('Failed to create blob from canvas')); } }, mimeType, format === 'jpg' ? 0.92 : 1.0); }; img.onerror = () => { URL.revokeObjectURL(url); reject(new Error('Failed to load SVG image')); }; img.src = url; }); }; const downloadBlob = async (blob, filename) => { return new Promise((resolve) => { const url = URL.createObjectURL(blob); const a = document.createElement("a"); a.href = url; a.download = filename; document.body.appendChild(a); a.click(); document.body.removeChild(a); setTimeout(() => { URL.revokeObjectURL(url); resolve(); }, 100); }); }; // UI const select = html``; select.onchange = (event) => { const format = event.target.value; if (format) { downloadMap(format).finally(() => { event.target.value = ''; }); } }; return html`

${_lang(nbText.export.titleMap)}

${select}

• ${_lang(nbText.export.hintSvgMap)}

• ${_lang(nbText.export.hintPng)}

• ${_lang(nbText.export.hintJpeg)}

`; } 4f:T213c,export_35 = { const downloadBlob = (blob, filename) => { const url = URL.createObjectURL(blob); const a = document.createElement("a"); a.href = url; a.download = filename; a.style.display = "none"; document.body.appendChild(a); a.click(); document.body.removeChild(a); setTimeout(() => URL.revokeObjectURL(url), 100); }; const showNotification = (message, isError = false) => { const notification = html`

${message}

`; document.body.appendChild(notification); setTimeout(() => { if (notification.parentNode) notification.parentNode.removeChild(notification); }, isError ? 5000 : 3000); }; const downloadAsSvg = (svg, filename) => { const clone = svg.cloneNode(true); const serializer = new XMLSerializer(); const blob = new Blob([serializer.serializeToString(clone)], { type: "image/svg+xml" }); downloadBlob(blob, filename); }; const downloadAsRaster = (svg, filename, format) => { return new Promise((resolve, reject) => { const clone = svg.cloneNode(true); let svgString = new XMLSerializer().serializeToString(clone); if (!svgString.includes("\n" + svgString; } let width, height; const viewBox = svg.getAttribute("viewBox"); if (viewBox) { const parts = viewBox.split(/\s+|,/).filter(p => p).map(parseFloat); if (parts.length === 4) { width = parts[2]; height = parts[3]; } } if (!width || !height) { width = parseFloat(svg.getAttribute("width")) || svg.getBoundingClientRect().width || 900; height = parseFloat(svg.getAttribute("height")) || svg.getBoundingClientRect().height || 600; } const svgDataUrl = "data:image/svg+xml;charset=utf-8," + encodeURIComponent(svgString); const canvas = document.createElement("canvas"); const ctx = canvas.getContext("2d"); canvas.width = width; canvas.height = height; ctx.fillStyle = "white"; ctx.fillRect(0, 0, width, height); const img = new Image(); img.crossOrigin = "anonymous"; img.onload = () => { try { ctx.drawImage(img, 0, 0, width, height); canvas.toBlob((blob) => { if (blob) { downloadBlob(blob, filename); resolve(); } else reject(new Error("Failed to create blob")); }, format === "png" ? "image/png" : "image/jpeg", format === "jpeg" || format === "jpg" ? 0.92 : 1.0); } catch (e) { reject(e); } }; img.onerror = () => reject(new Error("Failed to load SVG")); img.src = svgDataUrl; }); }; const downloadAsPdf = (svg, filename) => { return new Promise((resolve, reject) => { const printWindow = window.open("", "_blank"); if (!printWindow) { reject(new Error(_lang(nbText.export.allowPopups))); return; } const clone = svg.cloneNode(true); const serializer = new XMLSerializer(); const svgString = serializer.serializeToString(clone); const width = svg.getAttribute("width") || svg.getBoundingClientRect().width || 900; const height = svg.getAttribute("height") || svg.getBoundingClientRect().height || 600; printWindow.document.write(`Export${svgString}`); printWindow.document.close(); printWindow.onload = () => { printWindow.print(); printWindow.onafterprint = () => { printWindow.close(); resolve(); }; }; }); }; const downloadAsCsv = (data, filename) => { if (!data || data.length === 0) throw new Error(_lang(nbText.export.noDataCsv)); const headers = Object.keys(data[0]); const rows = [headers.join(","), ...data.map(row => headers.map(h => { const v = row[h]; if (v == null) return ""; const s = String(v); return (s.includes(",") || s.includes('"') || s.includes("\n")) ? `"${s.replace(/"/g, '""')}"` : s; }).join(",") )]; downloadBlob(new Blob([rows.join("\n")], { type: "text/csv;charset=utf-8" }), filename); }; const downloadAsJson = (data, filename) => { downloadBlob(new Blob([JSON.stringify(data, null, 2)], { type: "application/json" }), filename); }; const getChartData = () => { return data_hazardVoP.filter(d => d.hazard === selectHazard && d.vop !== 0 && riskDataTypes.crop.crop.includes(d.crop) ).map(d => ({ admin0_name: d.admin0_name || "", admin1_name: d.admin1_name || "", admin2_name: d.admin2_name || "", crop: d.crop || "", hazard: d.hazard || "", scenario: d.scenario || "", timeframe: d.timeframe || "", severity: d.severity || "", vop: d.vop || 0, vop_total: d.vop_total || 0 })); }; const downloadChart = async (format) => { const ts = new Date().toISOString().replace(/[:.]/g, "-").split("T")[0]; const baseFilename = `crop-risk-chart-${selectHazard || "hazard"}-${ts}`; if (format === "csv") { try { const data = getChartData(); downloadAsCsv(data, `${baseFilename}.csv`); showNotification(_lang(nbText.export.csvSuccess)); } catch (e) { showNotification(`${_lang(nbText.export.csvFailed)}: ${e.message}`, true); } return; } if (format === "json") { try { const data = getChartData(); downloadAsJson(data, `${baseFilename}.json`); showNotification(_lang(nbText.export.jsonSuccess)); } catch (e) { showNotification(`${_lang(nbText.export.jsonFailed)}: ${e.message}`, true); } return; } await new Promise(r => setTimeout(r, 300)); const svg = _getSvgFromChart(chart_35); if (!svg) { showNotification(_lang(nbText.export.chartNotFound), true); return; } const filename = `${baseFilename}.${format === "jpeg" || format === "jpg" ? "jpg" : format}`; try { if (format === "svg") { downloadAsSvg(svg, filename); showNotification(_lang(nbText.export.exportSuccess)); } else if (format === "pdf") { await downloadAsPdf(svg, filename); showNotification(_lang(nbText.export.printDialogOpened)); } else { await downloadAsRaster(svg, filename, format); showNotification(_lang(nbText.export.exportSuccess)); } } catch (e) { showNotification(`${_lang(nbText.export.exportFailed)}: ${e.message}`, true); } }; const select = html``; select.onchange = async (e) => { const format = e.target.value; if (format) { try { await downloadChart(format); e.target.value = ""; } catch (err) { console.error("Export error:", err); } } }; return html`

${_lang(nbText.export.titleCropRisk)}

${select}

• ${_lang(nbText.export.hintPngJpegSvg)}

• ${_lang(nbText.export.hintPdf)}

• ${_lang(nbText.export.hintCsvJson)}

`; } 50:T2092,export_38 = { const downloadBlob = (blob, filename) => { const url = URL.createObjectURL(blob); const a = document.createElement("a"); a.href = url; a.download = filename; a.style.display = "none"; document.body.appendChild(a); a.click(); document.body.removeChild(a); setTimeout(() => URL.revokeObjectURL(url), 100); }; const showNotification = (message, isError = false) => { const notification = html`

${message}

`; document.body.appendChild(notification); setTimeout(() => { if (notification.parentNode) notification.parentNode.removeChild(notification); }, isError ? 5000 : 3000); }; const downloadAsSvg = (svg, filename) => { const clone = svg.cloneNode(true); const serializer = new XMLSerializer(); const blob = new Blob([serializer.serializeToString(clone)], { type: "image/svg+xml" }); downloadBlob(blob, filename); }; const downloadAsRaster = (svg, filename, format) => { return new Promise((resolve, reject) => { const clone = svg.cloneNode(true); let svgString = new XMLSerializer().serializeToString(clone); if (!svgString.includes("\n" + svgString; } let width, height; const viewBox = svg.getAttribute("viewBox"); if (viewBox) { const parts = viewBox.split(/\s+|,/).filter(p => p).map(parseFloat); if (parts.length === 4) { width = parts[2]; height = parts[3]; } } if (!width || !height) { width = parseFloat(svg.getAttribute("width")) || svg.getBoundingClientRect().width || 900; height = parseFloat(svg.getAttribute("height")) || svg.getBoundingClientRect().height || 600; } const svgDataUrl = "data:image/svg+xml;charset=utf-8," + encodeURIComponent(svgString); const canvas = document.createElement("canvas"); const ctx = canvas.getContext("2d"); canvas.width = width; canvas.height = height; ctx.fillStyle = "white"; ctx.fillRect(0, 0, width, height); const img = new Image(); img.crossOrigin = "anonymous"; img.onload = () => { try { ctx.drawImage(img, 0, 0, width, height); canvas.toBlob((blob) => { if (blob) { downloadBlob(blob, filename); resolve(); } else reject(new Error("Failed to create blob")); }, format === "png" ? "image/png" : "image/jpeg", format === "jpeg" || format === "jpg" ? 0.92 : 1.0); } catch (e) { reject(e); } }; img.onerror = () => reject(new Error("Failed to load SVG")); img.src = svgDataUrl; }); }; const downloadAsPdf = (svg, filename) => { return new Promise((resolve, reject) => { const printWindow = window.open("", "_blank"); if (!printWindow) { reject(new Error(_lang(nbText.export.allowPopups))); return; } const clone = svg.cloneNode(true); const serializer = new XMLSerializer(); const svgString = serializer.serializeToString(clone); printWindow.document.write(`Export${svgString}`); printWindow.document.close(); printWindow.onload = () => { printWindow.print(); printWindow.onafterprint = () => { printWindow.close(); resolve(); }; }; }); }; const downloadAsCsv = (data, filename) => { if (!data || data.length === 0) throw new Error(_lang(nbText.export.noDataCsv)); const headers = Object.keys(data[0]); const rows = [headers.join(","), ...data.map(row => headers.map(h => { const v = row[h]; if (v == null) return ""; const s = String(v); return (s.includes(",") || s.includes('"') || s.includes("\n")) ? `"${s.replace(/"/g, '""')}"` : s; }).join(",") )]; downloadBlob(new Blob([rows.join("\n")], { type: "text/csv;charset=utf-8" }), filename); }; const downloadAsJson = (data, filename) => { downloadBlob(new Blob([JSON.stringify(data, null, 2)], { type: "application/json" }), filename); }; const getChartData = () => { return data_hazardVoP.filter(d => d.hazard === selectHazard && d.vop !== 0 && riskDataTypes.crop.livestock.includes(d.crop) ).map(d => ({ admin0_name: d.admin0_name || "", admin1_name: d.admin1_name || "", admin2_name: d.admin2_name || "", crop: d.crop || "", hazard: d.hazard || "", scenario: d.scenario || "", timeframe: d.timeframe || "", severity: d.severity || "", vop: d.vop || 0, vop_total: d.vop_total || 0 })); }; const downloadChart = async (format) => { const ts = new Date().toISOString().replace(/[:.]/g, "-").split("T")[0]; const baseFilename = `livestock-risk-chart-${selectHazard || "hazard"}-${ts}`; if (format === "csv") { try { const data = getChartData(); downloadAsCsv(data, `${baseFilename}.csv`); showNotification(_lang(nbText.export.csvSuccess)); } catch (e) { showNotification(`${_lang(nbText.export.csvFailed)}: ${e.message}`, true); } return; } if (format === "json") { try { const data = getChartData(); downloadAsJson(data, `${baseFilename}.json`); showNotification(_lang(nbText.export.jsonSuccess)); } catch (e) { showNotification(`${_lang(nbText.export.jsonFailed)}: ${e.message}`, true); } return; } await new Promise(r => setTimeout(r, 300)); const svg = _getSvgFromChart(chart_38); if (!svg) { showNotification(_lang(nbText.export.chartNotFound), true); return; } const filename = `${baseFilename}.${format === "jpeg" || format === "jpg" ? "jpg" : format}`; try { if (format === "svg") { downloadAsSvg(svg, filename); showNotification(_lang(nbText.export.exportSuccess)); } else if (format === "pdf") { await downloadAsPdf(svg, filename); showNotification(_lang(nbText.export.printDialogOpened)); } else { await downloadAsRaster(svg, filename, format); showNotification(_lang(nbText.export.exportSuccess)); } } catch (e) { showNotification(`${_lang(nbText.export.exportFailed)}: ${e.message}`, true); } }; const select = html``; select.onchange = async (e) => { const format = e.target.value; if (format) { try { await downloadChart(format); e.target.value = ""; } catch (err) { console.error("Export error:", err); } } }; return html`

${_lang(nbText.export.titleLivestockRisk)}

${select}

• ${_lang(nbText.export.hintPngJpegSvg)}

• ${_lang(nbText.export.hintPdf)}

• ${_lang(nbText.export.hintCsvJson)}

`; } 51:Tff2,{ const selectedHazard = hazardPlotLookup.names[selectHazard]; // --- START OF CURRENCY CONVERSION AND FORMATTING LOGIC --- const DOLLAR_TO_BIRR_RATE = usdToEtbExchangeRate; const missingValue = "---"; // Function to convert a numerical dollar value to a Birr-formatted string const formatBirr = (dollarValue) => { if (dollarValue === null || dollarValue === undefined) return missingValue; const birrValue = dollarValue * DOLLAR_TO_BIRR_RATE; let birrOutput; let newMagnitudeLabel = ''; // Determine the new magnitude based on the converted value (to keep the number concise) if (birrValue >= 1000000000000) { newMagnitudeLabel = 'T'; // Trillion birrOutput = (birrValue / 1000000000000).toFixed(1); } else if (birrValue >= 1000000000) { newMagnitudeLabel = 'B'; // Billion birrOutput = (birrValue / 1000000000).toFixed(1); } else if (birrValue >= 1000000) { newMagnitudeLabel = 'M'; // Million birrOutput = (birrValue / 1000000).toFixed(1); } else { birrOutput = Math.round(birrValue).toLocaleString(language.locale); } // Return the final string: [Base Year] [New Currency] [New Value][Magnitude] // We hardcode '2005' as the base year, consistent with the original data's context. return `2005 ETB${birrOutput}${newMagnitudeLabel}`; }; // Birr (no year) and Dollar (with year) - same as tooltips const formatBirrAndDollar = (dollarValue) => { if (dollarValue === null || dollarValue === undefined) return missingValue; const birrStr = formatBirr(dollarValue).replace("2005 ", ""); const dollarStr = "2005 Int$" + formatUSD({locale: language.locale})(dollarValue).replace("$", ""); return `${birrStr} | ${dollarStr}`; }; function showResult(value) { return formatBirrAndDollar(value); } // --- END OF CURRENCY CONVERSION AND FORMATTING LOGIC --- const langLookup = { hazard: selectedHazard, hazardBlurb: Lang.reduceReplaceTemplateItems( _lang(nbText.climateRisks.hazardImpact.insights.hazardBlurb), [{name: "hazard_string", value: selectedHazard}] ), labels: { totalVopCrop: _lang( nbText.climateRisks.hazardImpact.insights.labels.totalVopCrop ), totalVopLivestock: _lang( nbText.climateRisks.hazardImpact.insights.labels.totalVopLivestock ), exposureCrop: _lang( nbText.climateRisks.hazardImpact.insights.labels.exposureCrop ), exposureLivestock: _lang( nbText.climateRisks.hazardImpact.insights.labels.exposureLivestock ) } }; const crop = insight_totalExposedVop.filter( (d) => d.totalExposedVop !== 0 && d.cropType == "crop" )?.[0]?.["totalExposedVop"]; const livestock = insight_totalExposedVop.filter( (d) => d.totalExposedVop !== 0 && d.cropType == "livestock" )?.[0]?.["totalExposedVop"]; const topCrop = insight_topCrops.filter( (d) => d.vop !== 0 && d.cropType == "crop" )?.[0]; const topLivestock = insight_topCrops.filter( (d) => d.vop !== 0 && d.cropType == "livestock" )?.[0]; // Updated to use formatBirrAndDollar (Birr | Dollar) const topCropString = topCrop !== undefined ? `**${hazardPlotLookup.crops[topCrop?.["crop"]]}** (**${formatBirrAndDollar( topCrop?.["vop"] )}**)` : `**${missingValue}**`; // Updated to use formatBirrAndDollar (Birr | Dollar) const topLivestockString = topLivestock !== undefined ? `**${ hazardPlotLookup.crops[topLivestock?.["crop"]] }** (**${formatBirrAndDollar(topLivestock?.["vop"])}**)` : `**${missingValue}**`; return md`${langLookup.hazardBlurb} - ${langLookup.labels.totalVopCrop}: **${showResult(crop)}** - ${langLookup.labels.totalVopLivestock}: **${showResult(livestock)}** - ${langLookup.labels.exposureCrop}: ${topCropString} - ${langLookup.labels.exposureLivestock}: ${topLivestockString} `; } 52:T84e,{ // --- START OF CURRENCY CONVERSION AND FORMATTING LOGIC --- const DOLLAR_TO_BIRR_RATE = usdToEtbExchangeRate; const missingValue = "---"; // Function to convert a numerical dollar value to a Birr-formatted string const formatBirr = (dollarValue) => { if (dollarValue === null || dollarValue === undefined) return missingValue; const birrValue = dollarValue * DOLLAR_TO_BIRR_RATE; let birrOutput; let newMagnitudeLabel = ''; // Determine the new magnitude based on the converted value if (birrValue >= 1000000000000) { newMagnitudeLabel = 'T'; // Trillion birrOutput = (birrValue / 1000000000000).toFixed(1); } else if (birrValue >= 1000000000) { newMagnitudeLabel = 'B'; // Billion birrOutput = (birrValue / 1000000000).toFixed(1); } else if (birrValue >= 1000000) { newMagnitudeLabel = 'M'; // Million birrOutput = (birrValue / 1000000).toFixed(1); } else { birrOutput = Math.round(birrValue).toLocaleString(language.locale); } // Return the final string: [Base Year] [New Currency] [New Value][Magnitude] return `2005 ETB${birrOutput}${newMagnitudeLabel}`; }; // Birr (no year) and Dollar (with year) - same as tooltips const formatBirrAndDollar = (dollarValue) => { if (dollarValue === null || dollarValue === undefined) return missingValue; const birrStr = formatBirr(dollarValue).replace("2005 ", ""); const dollarStr = "2005 Int$" + formatUSD({locale: language.locale})(dollarValue).replace("$", ""); return `${birrStr} | ${dollarStr}`; }; // --- END OF CURRENCY CONVERSION AND FORMATTING LOGIC --- const intro = _lang(nbText.climateRisks.hazardImpact.insights.blurbBiggestHazard) return md`${intro} - **${hazardPlotLookup.names[insight_rankedHazardVopTotals?.[0]?.['hazard']]}**: **${formatBirrAndDollar(insight_rankedHazardVopTotals?.[0]?.['totalVop'])}** - **${hazardPlotLookup.names[insight_rankedHazardVopTotals?.[1]?.['hazard']]}**: **${formatBirrAndDollar(insight_rankedHazardVopTotals?.[1]?.['totalVop'])}**` } 53:T44cf,plotChoroplethAdaptiveCapacity1 = { const data = mapFeaturesAdaptiveCapacity; const selector = selectAcDataTypeNew; const options = dataLayerOptionsAdaptiveCapacities; const chartType = (plotChoroplethAdaptiveCapacity1ChartType === "bar" || plotChoroplethAdaptiveCapacity1ChartType === "map") ? plotChoroplethAdaptiveCapacity1ChartType : "map"; const filler = selector.key === "edu" ? (c) => c ?? 0 : transformPercent; function _getOption(key, data = options) { return data.find((x) => x.key == key); } const missingDataLabel = Lang.reduceReplaceTemplateItems( _lang(nbText.missingMapDataBlurb), [{ name: "data_label", value: selector.label }] ); const { selectAdmin0, selectAdmin1, selectAdmin2, selectAdmin3 } = adminSelections; console.log("DEBUG: plotChoroplethAdaptiveCapacity1 - Features:", data.length); console.log("DEBUG: plotChoroplethAdaptiveCapacity1 - Sample feature:", data[0]?.properties); console.log("DEBUG: plotChoroplethAdaptiveCapacity1 - Admin selections:", { admin0: selectAdmin0.value, admin1: selectAdmin1.value, admin2: selectAdmin2.value, admin3: selectAdmin3.value }); if (selectAdmin2.value && selectAdmin0.value === "Ethiopia") { console.log("DEBUG: plotChoroplethAdaptiveCapacity1 - Woreda features:", data.filter(d => d.properties.admin2_name === selectAdmin2.value && d.properties.admin3_name).length); } // Determine the admin label based on the data structure // Check if we have woreda-level data (admin3_name exists) const hasWoredaData = data.length > 0 && data.some(d => d.properties.admin3_name); const adminLabel = hasWoredaData ? adminRegions.labels.admin3 : (selectAdmin0.value ? adminRegions.labels.admin2 : adminRegions.labels.admin0); // Bar chart implementation if (chartType === "bar") { // Filter features based on admin selections (same logic as map) let filteredFeatures = data; if (selectAdmin3?.value && selectAdmin0.value === "Ethiopia") { // Show woredas within selected subregion filteredFeatures = data.filter(d => d.properties.admin0_name === selectAdmin0.value && d.properties.admin1_name === selectAdmin1.value && d.properties.admin2_name === selectAdmin2.value && d.properties.admin3_name === selectAdmin3.value ); } else if (selectAdmin2?.value) { // Show woredas within selected subregion (if Ethiopia) or subregions if (selectAdmin0.value === "Ethiopia") { filteredFeatures = data.filter(d => d.properties.admin0_name === selectAdmin0.value && d.properties.admin1_name === selectAdmin1.value && d.properties.admin2_name === selectAdmin2.value && d.properties.admin3_name // Only woredas ); } else { filteredFeatures = data.filter(d => d.properties.admin0_name === selectAdmin0.value && d.properties.admin1_name === selectAdmin1.value && d.properties.admin2_name === selectAdmin2.value && !d.properties.admin3_name // Only subregions ); } } else if (selectAdmin1?.value) { // Show subregions within selected region filteredFeatures = data.filter(d => d.properties.admin0_name === selectAdmin0.value && d.properties.admin1_name === selectAdmin1.value && d.properties.admin2_name && !d.properties.admin3_name ); } else if (selectAdmin0?.value) { // Show subregions within selected country (since region-level data may not exist) filteredFeatures = data.filter(d => d.properties.admin0_name === selectAdmin0.value && d.properties.admin2_name && !d.properties.admin3_name ); } // Prepare bar chart data const barData = filteredFeatures.map(d => { const dataColumn = selector.dataColumn; let value = d.properties.data?.[dataColumn] ?? 0; if ((selector.key === "pov" || selector.key === "edu") && genderFilter !== "All" && d.properties.data) { const genderRatio = genderFilter === "Men" ? d.properties.data.gender_men : d.properties.data.gender_women; const ratioField = selector.key === "pov" ? (genderFilter === "Men" ? d.properties.data.poverty_men_ratio : d.properties.data.poverty_women_ratio) : (genderFilter === "Men" ? d.properties.data.edu_men_ratio : d.properties.data.edu_women_ratio); value = value * (ratioField || 0.5) / (genderRatio || 0.5); } // Get admin unit name let adminName; if (d.properties.admin3_name) { adminName = d.properties.admin3_name; } else if (d.properties.admin2_name) { adminName = d.properties.admin2_name; } else if (d.properties.admin1_name) { adminName = d.properties.admin1_name; } else { const translated = _lang(td.admin0_name.values?.[d.properties.admin_name]); adminName = translated ?? d.properties.admin_name; } return { name: adminName, value: filler(value), rawValue: value, properties: d.properties, data: d.properties.data }; }).filter(d => d.value !== null && d.value !== undefined); // Sort by value descending barData.sort((a, b) => b.value - a.value); // Dynamic bar height: use 30px per bar for few items, reduce proportionally for many items const barHeightPerItem = barData.length > 50 ? Math.max(10, 30 - (barData.length - 50) * 0.3) // Reduce by 0.3px for each item over 50, minimum 10px : 30; // Original thickness for 50 or fewer items return Plot.plot({ width: mapWidth * 1.5, // 50% wider for better bar distinction height: Math.max(300, barData.length * barHeightPerItem), marginLeft: 150, marginRight: 80, // Increased to prevent label overlap with "100" tick marginTop: 20, marginBottom: 20, caption: `${missingDataLabel} — Current selection: ${ selectAdmin3?.value || selectAdmin2?.value || selectAdmin1?.value || selectAdmin0?.value || "None" }`, color: { legend: true, range: selector.key === "pov" ? selector.colorDomain : selector.colorDomain.slice().reverse(), unknown: selector.colorUnknown, label: selector.labelLegend }, x: { domain: selector.key === "pov" ? [0, 100] : undefined, label: selector.label, grid: true, ticks: selector.key === "pov" ? [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100] : undefined }, y: { domain: barData.map(d => d.name).reverse(), // Reverse to show highest at top label: null }, marks: [ Plot.barX(barData, { x: "value", y: "name", fill: (d) => { // Use the same fill logic as the map const dataColumn = selector.dataColumn; let value = d.data?.[dataColumn] ?? 0; if ((selector.key === "pov" || selector.key === "edu") && genderFilter !== "All" && d.data) { const genderRatio = genderFilter === "Men" ? d.data.gender_men : d.data.gender_women; const ratioField = selector.key === "pov" ? (genderFilter === "Men" ? d.data.poverty_men_ratio : d.data.poverty_women_ratio) : (genderFilter === "Men" ? d.data.edu_men_ratio : d.data.edu_women_ratio); value = value * (ratioField || 0.5) / (genderRatio || 0.5); } return filler(value); }, channels: { name: { label: (() => { // Determine label based on admin level of first item const firstItem = barData[0]; if (!firstItem) return adminRegions.labels.admin0; if (firstItem.properties.admin3_name) return adminRegions.labels.admin3; if (firstItem.properties.admin2_name) return adminRegions.labels.admin2; if (firstItem.properties.admin1_name) return adminRegions.labels.admin1; return adminRegions.labels.admin0; })(), value: (d) => { // Show woreda name if it exists, otherwise show admin2 or admin0 if (d.properties.admin3_name) return d.properties.admin3_name; if (d.properties.admin2_name) return d.properties.admin2_name; if (d.properties.admin1_name) return d.properties.admin1_name; const translated = _lang(td.admin0_name.values?.[d.properties.admin_name]); return translated ?? d.properties.admin_name ?? d.name; } }, percent: { label: selector.label, value: (d) => { return selector.key === "edu" ? `${d.rawValue.toFixed(2)} Yrs` : `${formatPercentNoSymbol(transformPercent(d.rawValue))}%`; } }, totalPopulation: { label: selector.labelPop, value: (d) => { let value = d.data?.total_pop ?? 0; if ((selector.key === "pov" || selector.key === "edu") && genderFilter !== "All" && d.data) { const genderRatio = genderFilter === "Men" ? d.data.gender_men : d.data.gender_women; value = value * (genderRatio || 0.5); } return formatNumCompactShort({locale: language.locale})(value); } }, ac_pov: { label: _getOption("pov").label, value: (d) => { let value = d.data?.ac_pov ?? 0; if (selector.key === "pov" && genderFilter !== "All" && d.data) { const genderRatio = genderFilter === "Men" ? d.data.gender_men : d.data.gender_women; const povertyRatio = genderFilter === "Men" ? d.data.poverty_men_ratio : d.data.poverty_women_ratio; value = value * (povertyRatio || 0.5) / (genderRatio || 0.5); } return `${formatPercentNoSymbol(transformPercent(value))}%`; } }, ac_edu: { label: _getOption("edu").label, value: (d) => { let value = d.data?.ac_edu ?? 0; if (selector.key === "edu" && genderFilter !== "All" && d.data) { const eduRatio = genderFilter === "Men" ? d.data.edu_men_ratio : d.data.edu_women_ratio; value = value * (eduRatio || 0.5); } return `${value.toFixed(2)} Yrs`; } }, ac_fem: { label: _getOption("fem").label, value: (d) => { const value = d.data?.ac_fem ?? 0; return `${formatPercentNoSymbol(transformPercent(value))}%`; } } }, tip: { format: { name: true, totalPopulation: true, ac_pov: true, ac_edu: true, ac_fem: true, percent: true }, lineWidth: Infinity } }) ] }); } // Map visualization (original) return Plot.plot({ caption: `${missingDataLabel} — Current selection: ${ selectAdmin3?.value || selectAdmin2?.value || selectAdmin1?.value || selectAdmin0?.value || "None" }`, width: mapWidth, height: 550, color: { legend: true, range: selector.key === "pov" ? selector.colorDomain : selector.colorDomain.slice().reverse(), unknown: selector.colorUnknown, label: selector.labelLegend }, marks: [ // geo data Plot.geo(data, { fill: (d) => { const dataColumn = selector.dataColumn; let value = d.properties.data?.[dataColumn] ?? 0; if ((selector.key === "pov" || selector.key === "edu") && genderFilter !== "All" && d.properties.data) { const genderRatio = genderFilter === "Men" ? d.properties.data.gender_men : d.properties.data.gender_women; const ratioField = selector.key === "pov" ? (genderFilter === "Men" ? d.properties.data.poverty_men_ratio : d.properties.data.poverty_women_ratio) : (genderFilter === "Men" ? d.properties.data.edu_men_ratio : d.properties.data.edu_women_ratio); value = value * (ratioField || 0.5) / (genderRatio || 0.5); } return filler(value); }, stroke: "#fff", strokeWidth: 0.5 }), // admin2 highlight Plot.geo( selectAdmin2.value ? data.filter( (d) => d.properties.admin2_name === selectAdmin2.value ) : [], { fill: null, stroke: "#333", strokeWidth: 1.5 } ), // admin3 highlight Plot.geo( selectAdmin0.value === "Ethiopia" && selectAdmin3.value ? data.filter((d) => d.properties.admin3_name === selectAdmin3.value) : [], { fill: null, stroke: "#000", strokeWidth: 3 } ), // geo pointer Plot.geo( data, Plot.pointer( Plot.centroid({ stroke: "#333", strokeWidth: 1.5 }) ) ), // tooltip Plot.tip( data, Plot.pointer( Plot.centroid({ lineWidth: Infinity, channels: { name: { label: adminLabel, value: (d) => { if (d.properties.admin3_name) { return d.properties.admin3_name; } if (d.properties.admin2_name) { return d.properties.admin2_name; } const translated = _lang(td.admin0_name.values?.[d.properties.admin_name]); return translated ?? d.properties.admin_name; } }, percent: { label: selector.label, value: (d) => { const dataColumn = selector.dataColumn; let value = d.properties.data?.[dataColumn] ?? 0; if ((selector.key === "pov" || selector.key === "edu") && genderFilter !== "All" && d.properties.data) { const genderRatio = genderFilter === "Men" ? d.properties.data.gender_men : d.properties.data.gender_women; const ratioField = selector.key === "pov" ? (genderFilter === "Men" ? d.properties.data.poverty_men_ratio : d.properties.data.poverty_women_ratio) : (genderFilter === "Men" ? d.properties.data.edu_men_ratio : d.properties.data.edu_women_ratio); value = value * (ratioField || 0.5) / (genderRatio || 0.5); } return selector.key === "edu" ? `${value.toFixed(2)} Yrs` : `${formatPercentNoSymbol(transformPercent(value))}%`; } }, totalPopulation: { label: selector.labelPop, value: (d) => { let value = d.properties.data?.total_pop ?? 0; if ((selector.key === "pov" || selector.key === "edu") && genderFilter !== "All" && d.properties.data) { const genderRatio = genderFilter === "Men" ? d.properties.data.gender_men : d.properties.data.gender_women; value = value * (genderRatio || 0.5); } return formatNumCompactShort({locale: language.locale})(value); } }, ac_pov: { label: _getOption("pov").label, value: (d) => { let value = d.properties.data?.ac_pov ?? 0; if (selector.key === "pov" && genderFilter !== "All" && d.properties.data) { const genderRatio = genderFilter === "Men" ? d.properties.data.gender_men : d.properties.data.gender_women; const povertyRatio = genderFilter === "Men" ? d.properties.data.poverty_men_ratio : d.properties.data.poverty_women_ratio; value = value * (povertyRatio || 0.5) / (genderRatio || 0.5); } return `${formatPercentNoSymbol(transformPercent(value))}%`; } }, ac_edu: { label: _getOption("edu").label, value: (d) => { let value = d.properties.data?.ac_edu ?? 0; if (selector.key === "edu" && genderFilter !== "All" && d.properties.data) { const eduRatio = genderFilter === "Men" ? d.properties.data.edu_men_ratio : d.properties.data.edu_women_ratio; value = value * (eduRatio || 0.5); } return `${value.toFixed(2)} Yrs`; } }, ac_fem: { label: _getOption("fem").label, value: (d) => { const value = d.properties.data?.ac_fem ?? 0; return `${formatPercentNoSymbol(transformPercent(value))}%`; } } }, format: { name: true, totalPopulation: true, ac_pov: true, ac_edu: true, ac_fem: true } }) ) ) ] }); } 54:T6df6,viewof exportPlotChoroplethAdaptiveCapacity1 = { // Helper: Download blob const downloadBlob = (blob, filename) => { const url = URL.createObjectURL(blob); const a = document.createElement('a'); a.href = url; a.download = filename; a.style.display = 'none'; document.body.appendChild(a); a.click(); document.body.removeChild(a); setTimeout(() => URL.revokeObjectURL(url), 100); }; // Helper: Show notification const showNotification = (message, isError = false) => { const notification = html`

${message}

`; document.body.appendChild(notification); setTimeout(() => { if (notification.parentNode) { notification.parentNode.removeChild(notification); } }, isError ? 5000 : 3000); }; // Helper: Download as SVG const downloadAsSvg = (svg, filename) => { const clone = svg.cloneNode(true); const serializer = new XMLSerializer(); const svgString = serializer.serializeToString(clone); const blob = new Blob([svgString], { type: 'image/svg+xml' }); downloadBlob(blob, filename); }; // Helper: Download as raster (PNG/JPEG) - using data URL to avoid tainted canvas const downloadAsRaster = (svg, filename, format) => { return new Promise((resolve, reject) => { const clone = svg.cloneNode(true); const serializer = new XMLSerializer(); let svgString = serializer.serializeToString(clone); if (!svgString.includes('\n' + svgString; } // Get dimensions from viewBox or attributes let width, height; const viewBox = svg.getAttribute('viewBox'); if (viewBox) { const parts = viewBox.split(/\s+|,/).filter(p => p).map(parseFloat); if (parts.length === 4) { width = parts[2]; height = parts[3]; } } // Fallback to width/height attributes or bounding rect if (!width || !height) { width = svg.getAttribute('width') ? parseFloat(svg.getAttribute('width')) : null; height = svg.getAttribute('height') ? parseFloat(svg.getAttribute('height')) : null; } if (!width || !height) { const rect = svg.getBoundingClientRect(); width = rect.width || 900; height = rect.height || 550; } // Use data URL instead of blob URL to avoid tainted canvas const svgDataUrl = 'data:image/svg+xml;charset=utf-8,' + encodeURIComponent(svgString); const canvas = document.createElement('canvas'); const ctx = canvas.getContext('2d'); canvas.width = width; canvas.height = height; // Fill with white background for both PNG and JPEG ctx.fillStyle = 'white'; ctx.fillRect(0, 0, width, height); const img = new Image(); img.crossOrigin = 'anonymous'; img.onload = () => { try { ctx.drawImage(img, 0, 0, width, height); canvas.toBlob( (blob) => { if (blob) { downloadBlob(blob, filename); resolve(); } else { reject(new Error('Failed to create blob from canvas')); } }, format === 'png' ? 'image/png' : 'image/jpeg', format === 'jpeg' || format === 'jpg' ? 0.92 : 1.0 ); } catch (drawError) { reject(new Error(`Failed to draw image: ${drawError.message}`)); } }; img.onerror = () => { reject(new Error('Failed to load SVG image')); }; img.src = svgDataUrl; }); }; // Helper: Download as CSV const downloadAsCsv = (data, filename) => { if (!data || data.length === 0) { throw new Error(_lang(nbText.export.noDataCsv)); } const headers = Object.keys(data[0]); const csvRows = []; csvRows.push(headers.join(',')); for (const row of data) { const values = headers.map(header => { const value = row[header]; if (value === null || value === undefined) return ''; const stringValue = String(value); if (stringValue.includes(',') || stringValue.includes('"') || stringValue.includes('\n')) { return `"${stringValue.replace(/"/g, '""')}"`; } return stringValue; }); csvRows.push(values.join(',')); } const csvContent = csvRows.join('\n'); const blob = new Blob([csvContent], { type: 'text/csv;charset=utf-8;' }); downloadBlob(blob, filename); }; // Helper: Download as JSON const downloadAsJson = (data, filename) => { const jsonString = JSON.stringify(data, null, 2); const blob = new Blob([jsonString], { type: 'application/json' }); downloadBlob(blob, filename); }; // Helper: Download as GeoJSON const downloadAsGeoJson = (geojson, filename) => { const jsonString = JSON.stringify(geojson, null, 2); const blob = new Blob([jsonString], { type: 'application/geo+json' }); downloadBlob(blob, filename); }; // Helper: Download as Shapefile (pure-JS, no external dependencies) const downloadAsShapefile = (geojson, filename) => { showNotification('Generating shapefile...', false); const crcTable = (() => { const t = new Uint32Array(256); for (let i = 0; i < 256; i++) { let c = i; for (let j = 0; j < 8; j++) c = (c & 1) ? (0xEDB88320 ^ (c >>> 1)) : (c >>> 1); t[i] = c; } return t; })(); const crc32 = (data) => { let crc = 0xFFFFFFFF; for (let i = 0; i < data.length; i++) crc = crcTable[(crc ^ data[i]) & 0xFF] ^ (crc >>> 8); return (crc ^ 0xFFFFFFFF) >>> 0; }; const buildShapefiles = (features) => { let shapeType = 5; for (const f of features) { if (!f.geometry) continue; if (f.geometry.type === 'Point' || f.geometry.type === 'MultiPoint') { shapeType = 1; break; } if (f.geometry.type === 'LineString' || f.geometry.type === 'MultiLineString') { shapeType = 3; break; } if (f.geometry.type === 'Polygon' || f.geometry.type === 'MultiPolygon') { shapeType = 5; break; } } const getRings = (geom) => { if (geom.type === 'Polygon') return geom.coordinates; if (geom.type === 'MultiPolygon') return geom.coordinates.flat(1); if (geom.type === 'LineString') return [geom.coordinates]; if (geom.type === 'MultiLineString') return geom.coordinates; return null; }; let gMinX = Infinity, gMinY = Infinity, gMaxX = -Infinity, gMaxY = -Infinity; const recs = features.map(f => { const geom = f.geometry; if (!geom) return { type: 0 }; if (shapeType === 1) { const coords = geom.type === 'Point' ? geom.coordinates : geom.coordinates[0]; const [x, y] = coords; if (x < gMinX) gMinX = x; if (y < gMinY) gMinY = y; if (x > gMaxX) gMaxX = x; if (y > gMaxY) gMaxY = y; return { type: 1, x, y, contentBytes: 20 }; } const rings = getRings(geom); if (!rings) return { type: 0 }; let minX = Infinity, minY = Infinity, maxX = -Infinity, maxY = -Infinity, totalPts = 0; for (const ring of rings) { for (const [px, py] of ring) { if (px < minX) minX = px; if (py < minY) minY = py; if (px > maxX) maxX = px; if (py > maxY) maxY = py; totalPts++; } } if (minX < gMinX) gMinX = minX; if (minY < gMinY) gMinY = minY; if (maxX > gMaxX) gMaxX = maxX; if (maxY > gMaxY) gMaxY = maxY; const contentBytes = 44 + 4 * rings.length + 16 * totalPts; return { type: shapeType, rings, minX, minY, maxX, maxY, totalPts, contentBytes }; }); if (!isFinite(gMinX)) { gMinX = 0; gMinY = 0; gMaxX = 0; gMaxY = 0; } const HDR = 100; let shpSize = HDR; for (const r of recs) shpSize += 8 + (r.type === 0 ? 4 : r.contentBytes); const shpBuf = new Uint8Array(shpSize); const shxBuf = new Uint8Array(HDR + recs.length * 8); const sv = new DataView(shpBuf.buffer); const xv = new DataView(shxBuf.buffer); const writeHdr = (dv, fileLen) => { dv.setInt32(0, 9994, false); dv.setInt32(24, fileLen / 2, false); dv.setInt32(28, 1000, true); dv.setInt32(32, shapeType, true); dv.setFloat64(36, gMinX, true); dv.setFloat64(44, gMinY, true); dv.setFloat64(52, gMaxX, true); dv.setFloat64(60, gMaxY, true); }; writeHdr(sv, shpSize); writeHdr(xv, shxBuf.length); let shpOff = HDR; for (let i = 0; i < recs.length; i++) { const r = recs[i]; const cLen = r.type === 0 ? 4 : r.contentBytes; xv.setInt32(HDR + i * 8, shpOff / 2, false); xv.setInt32(HDR + i * 8 + 4, cLen / 2, false); sv.setInt32(shpOff, i + 1, false); sv.setInt32(shpOff + 4, cLen / 2, false); shpOff += 8; if (r.type === 0) { sv.setInt32(shpOff, 0, true); shpOff += 4; } else if (r.type === 1) { sv.setInt32(shpOff, 1, true); shpOff += 4; sv.setFloat64(shpOff, r.x, true); shpOff += 8; sv.setFloat64(shpOff, r.y, true); shpOff += 8; } else { sv.setInt32(shpOff, r.type, true); shpOff += 4; sv.setFloat64(shpOff, r.minX, true); shpOff += 8; sv.setFloat64(shpOff, r.minY, true); shpOff += 8; sv.setFloat64(shpOff, r.maxX, true); shpOff += 8; sv.setFloat64(shpOff, r.maxY, true); shpOff += 8; sv.setInt32(shpOff, r.rings.length, true); shpOff += 4; sv.setInt32(shpOff, r.totalPts, true); shpOff += 4; let ptIdx = 0; for (const ring of r.rings) { sv.setInt32(shpOff, ptIdx, true); shpOff += 4; ptIdx += ring.length; } for (const ring of r.rings) { for (const [px, py] of ring) { sv.setFloat64(shpOff, px, true); shpOff += 8; sv.setFloat64(shpOff, py, true); shpOff += 8; } } } } return { shp: shpBuf, shx: shxBuf }; }; const buildDbf = (features) => { const enc = new TextEncoder(); const allProps = features.map(f => f.properties || {}); const allKeys = [...new Set(allProps.flatMap(p => Object.keys(p)))]; const fields = allKeys.slice(0, 255).map(key => { const name = key.substring(0, 10); const vals = allProps.map(p => p[key]).filter(v => v !== null && v !== undefined); const isNum = vals.length > 0 && vals.every(v => typeof v === 'number' || (typeof v === 'string' && v.trim() !== '' && !isNaN(+v)) ); if (isNum) { const hasDecimal = vals.some(v => !Number.isInteger(typeof v === 'number' ? v : +v)); return { name, key, type: 'N', length: hasDecimal ? 18 : 11, decimals: hasDecimal ? 6 : 0 }; } const maxLen = Math.min(254, Math.max(1, ...vals.map(v => enc.encode(String(v)).length))); return { name, key, type: 'C', length: maxLen, decimals: 0 }; }); const n = features.length; const hdrSize = 32 + fields.length * 32 + 1; const recSize = 1 + fields.reduce((s, f) => s + f.length, 0); const buf = new Uint8Array(hdrSize + n * recSize + 1); const dv = new DataView(buf.buffer); const now = new Date(); buf[0] = 3; buf[1] = now.getFullYear() - 1900; buf[2] = now.getMonth() + 1; buf[3] = now.getDate(); dv.setUint32(4, n, true); dv.setUint16(8, hdrSize, true); dv.setUint16(10, recSize, true); let fOff = 32; for (const f of fields) { const nb = enc.encode(f.name); for (let i = 0; i < 11; i++) buf[fOff + i] = i < nb.length ? nb[i] : 0; buf[fOff + 11] = f.type.charCodeAt(0); buf[fOff + 16] = f.length; buf[fOff + 17] = f.decimals; fOff += 32; } buf[fOff] = 0x0D; for (let i = 0; i < n; i++) { const props = allProps[i]; let rOff = hdrSize + i * recSize; buf[rOff++] = 0x20; for (const f of fields) { const raw = props[f.key]; let s; if (raw === null || raw === undefined) { s = ' '.repeat(f.length); } else if (f.type === 'N') { s = String(typeof raw === 'number' ? raw : +raw).padStart(f.length).substring(0, f.length); } else { s = String(raw).substring(0, f.length).padEnd(f.length); } const bytes = enc.encode(s); for (let j = 0; j < f.length; j++) buf[rOff + j] = j < bytes.length ? bytes[j] : 0x20; rOff += f.length; } } buf[buf.length - 1] = 0x1A; return buf; }; const buildPrj = () => new TextEncoder().encode( 'GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],' + 'PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]]' ); const buildZip = (files) => { const enc = new TextEncoder(); const localParts = []; const centralParts = []; let localOffset = 0; for (const { name, data } of files) { const nb = enc.encode(name); const crc = crc32(data); const size = data.length; const lh = new Uint8Array(30 + nb.length); const lv = new DataView(lh.buffer); lv.setUint32(0, 0x04034b50, true); lv.setUint16(4, 20, true); lv.setUint16(8, 0, true); lv.setUint32(14, crc, true); lv.setUint32(18, size, true); lv.setUint32(22, size, true); lv.setUint16(26, nb.length, true); lh.set(nb, 30); const cdh = new Uint8Array(46 + nb.length); const cv = new DataView(cdh.buffer); cv.setUint32(0, 0x02014b50, true); cv.setUint16(4, 20, true); cv.setUint16(6, 20, true); cv.setUint32(16, crc, true); cv.setUint32(20, size, true); cv.setUint32(24, size, true); cv.setUint16(28, nb.length, true); cv.setUint32(42, localOffset, true); cdh.set(nb, 46); localParts.push(lh, data); centralParts.push(cdh); localOffset += lh.length + size; } const cdirOffset = localOffset; const cdirSize = centralParts.reduce((s, p) => s + p.length, 0); const eocd = new Uint8Array(22); const ev = new DataView(eocd.buffer); ev.setUint32(0, 0x06054b50, true); ev.setUint16(8, files.length, true); ev.setUint16(10, files.length, true); ev.setUint32(12, cdirSize, true); ev.setUint32(16, cdirOffset, true); const all = [...localParts, ...centralParts, eocd]; const total = all.reduce((s, p) => s + p.length, 0); const out = new Uint8Array(total); let pos = 0; for (const p of all) { out.set(p, pos); pos += p.length; } return out; }; const { shp, shx } = buildShapefiles(geojson.features); const dbf = buildDbf(geojson.features); const prj = buildPrj(); const base = filename.replace(/\.[^.]+$/, ''); const zipData = buildZip([ { name: `${base}.shp`, data: shp }, { name: `${base}.shx`, data: shx }, { name: `${base}.dbf`, data: dbf }, { name: `${base}.prj`, data: prj }, ]); downloadBlob(new Blob([zipData], { type: 'application/zip' }), `${base}.zip`); }; // Get the complete visualization (map or bar chart) with all elements const findMap = () => { const chartNode = plotChoroplethAdaptiveCapacity1; if (!chartNode) { console.error('plotChoroplethAdaptiveCapacity1 is not available'); return null; } // Plot.plot() returns a figure element let figure = null; if (chartNode.tagName === 'FIGURE') { figure = chartNode; } else if (chartNode.querySelector) { figure = chartNode.querySelector('figure'); } if (!figure) { console.error('Figure element not found in plotChoroplethAdaptiveCapacity1'); return null; } // Get the figure's bounding box const figureRect = figure.getBoundingClientRect(); // Get ALL SVGs from the figure const allSvgs = figure.querySelectorAll('svg'); if (allSvgs.length === 0) { console.error('No SVG elements found in figure'); return null; } console.log(`Found ${allSvgs.length} SVG(s) in figure`); // Find the main chart SVG (large one, not the small legend) const expectedWidth = mapWidth || 900; const expectedHeight = 550; let mainSvg = null; for (const svg of allSvgs) { const svgWidth = parseFloat(svg.getAttribute('width')) || 0; const svgHeight = parseFloat(svg.getAttribute('height')) || 0; const viewBox = svg.getAttribute('viewBox'); let vbWidth = 0, vbHeight = 0; if (viewBox) { const parts = viewBox.split(/\s+|,/).filter(p => p).map(parseFloat); if (parts.length === 4) { vbWidth = parts[2]; vbHeight = parts[3]; } } const rect = svg.getBoundingClientRect(); // Main chart SVG should be large (width > 600, height > 400) // Legend SVG is small (width < 300, height < 100) const isLarge = (svgWidth > 600 || vbWidth > 600 || rect.width > 600) && (svgHeight > 400 || vbHeight > 400 || rect.height > 400); if (isLarge) { mainSvg = svg; console.log('Found main chart SVG (large dimensions)'); break; } } // Fallback: use the largest SVG if (!mainSvg) { const svgArray = Array.from(allSvgs); svgArray.sort((a, b) => { const aSize = (parseFloat(a.getAttribute('width')) || 0) * (parseFloat(a.getAttribute('height')) || 0); const bSize = (parseFloat(b.getAttribute('width')) || 0) * (parseFloat(b.getAttribute('height')) || 0); return bSize - aSize; }); mainSvg = svgArray[0]; console.log('Using largest SVG as fallback'); } if (!mainSvg) { return null; } // Clone the main SVG - keep ALL elements including text labels const svgClone = mainSvg.cloneNode(true); // Only remove legend-specific elements, not chart text // Remove legend groups (identified by aria-label or class) const legendGroups = svgClone.querySelectorAll('g[aria-label*="legend"], g[class*="legend"], g[aria-label*="Legend"]'); legendGroups.forEach(group => { // Check if this is actually a legend (small, positioned at top/right) const groupRect = group.getBoundingClientRect(); const svgRect = mainSvg.getBoundingClientRect(); // Remove if it's a small group in the legend area (top 20% or right 20% of SVG) if (groupRect.width < svgRect.width * 0.3 && groupRect.height < svgRect.height * 0.2) { group.remove(); } }); // Remove small rects that are clearly legend bars (not chart bars) const allRects = svgClone.querySelectorAll('rect'); allRects.forEach(rect => { const rectWidth = parseFloat(rect.getAttribute('width')) || 0; const rectHeight = parseFloat(rect.getAttribute('height')) || 0; const x = parseFloat(rect.getAttribute('x')) || 0; const y = parseFloat(rect.getAttribute('y')) || 0; const svgWidth = parseFloat(svgClone.getAttribute('width')) || parseFloat(mainSvg.getAttribute('width')) || 900; const svgHeight = parseFloat(svgClone.getAttribute('height')) || parseFloat(mainSvg.getAttribute('height')) || 550; // Remove very small rects in the top/right area (legend area) // Keep rects that are chart bars (taller, in the main chart area) if (rectWidth < 300 && rectHeight < 50 && (y < svgHeight * 0.2 || x > svgWidth * 0.7)) { rect.remove(); } }); // Keep all text elements - they are part of the chart (axis labels, bar labels, etc.) // Don't remove any text - Plot.js includes all necessary labels in the SVG // Set dimensions based on the original SVG const width = parseFloat(mainSvg.getAttribute('width')) || expectedWidth; const height = parseFloat(mainSvg.getAttribute('height')) || expectedHeight; svgClone.setAttribute('width', width); svgClone.setAttribute('height', height); // Preserve viewBox if it exists const originalViewBox = mainSvg.getAttribute('viewBox'); if (originalViewBox) { svgClone.setAttribute('viewBox', originalViewBox); } else { svgClone.setAttribute('viewBox', `0 0 ${width} ${height}`); } // Add white background const bg = document.createElementNS('http://www.w3.org/2000/svg', 'rect'); bg.setAttribute('x', '0'); bg.setAttribute('y', '0'); bg.setAttribute('width', width); bg.setAttribute('height', height); bg.setAttribute('fill', 'white'); svgClone.insertBefore(bg, svgClone.firstChild); console.log(`Returning complete chart SVG: ${width}x${height}`); return svgClone; }; // Get GeoJSON from mapFeaturesAdaptiveCapacity (array of features) const getGeoJson = () => { const selector = selectAcDataTypeNew; const geojson = { type: "FeatureCollection", features: mapFeaturesAdaptiveCapacity.map(feature => ({ type: "Feature", geometry: feature.geometry, properties: { ...feature.properties, // Include data values in properties for GIS software ...(feature.properties.data ? feature.properties.data : {}), // Preserve admin names admin0_name: feature.properties.admin0_name, admin1_name: feature.properties.admin1_name, admin2_name: feature.properties.admin2_name, admin3_name: feature.properties.admin3_name, admin_name: feature.properties.admin_name, // Include the selected data column value for easy styling in GIS [selector.dataColumn]: feature.properties.data && feature.properties.data[selector.dataColumn] !== undefined ? feature.properties.data[selector.dataColumn] : null } })) }; return geojson; }; // Get CSV data from mapFeaturesAdaptiveCapacity const getCsvData = () => { const selector = selectAcDataTypeNew; return mapFeaturesAdaptiveCapacity.map(feature => { const props = feature.properties; const data = props.data || {}; return { admin0_name: props.admin0_name || '', admin1_name: props.admin1_name || '', admin2_name: props.admin2_name || '', admin3_name: props.admin3_name || '', admin_name: props.admin_name || '', [selector.dataColumn]: data[selector.dataColumn] !== undefined ? data[selector.dataColumn] : null, // Include all other data columns ...Object.keys(data).reduce((acc, key) => { acc[`data_${key}`] = data[key]; return acc; }, {}) }; }); }; // Get JSON data (tabular format) const getJsonData = () => { return getCsvData(); }; // Main download function const downloadChart = async (format) => { const timestamp = new Date().toISOString().replace(/[:.]/g, '-').split('T')[0]; const selector = selectAcDataTypeNew; const baseFilename = `adaptive-capacity-map-${selector.dataColumn}-${timestamp}`; if (format === 'csv') { try { const csvData = getCsvData(); const filename = `${baseFilename}.csv`; downloadAsCsv(csvData, filename); showNotification(_lang(nbText.export.csvSuccess)); } catch (error) { console.error('CSV export failed:', error); showNotification(`${_lang(nbText.export.csvFailed)}: ${error.message || error}`, true); } return; } if (format === 'json') { try { const jsonData = getJsonData(); const filename = `${baseFilename}.json`; downloadAsJson(jsonData, filename); showNotification(_lang(nbText.export.jsonSuccess)); } catch (error) { console.error('JSON export failed:', error); showNotification(`${_lang(nbText.export.jsonFailed)}: ${error.message || error}`, true); } return; } if (format === 'geojson') { try { const geojson = getGeoJson(); const filename = `${baseFilename}.geojson`; downloadAsGeoJson(geojson, filename); showNotification(_lang(nbText.export.geojsonSuccess)); } catch (error) { console.error('GeoJSON export failed:', error); showNotification(`${_lang(nbText.export.geojsonFailed)}: ${error.message || error}`, true); } return; } if (format === 'shapefile') { try { const geojson = getGeoJson(); const filename = `${baseFilename}.shp`; downloadAsShapefile(geojson, filename); showNotification(_lang(nbText.export.shapefileSuccess)); } catch (error) { console.error('Shapefile export failed:', error); showNotification(`${_lang(nbText.export.shapefileFailed)}: ${error.message || error}`, true); } return; } // Image formats (PNG, JPEG, SVG) const svg = findMap(); if (!svg) { const errorMsg = _lang(nbText.export.adaptiveCapacityMapNotFound); console.error(errorMsg); showNotification(errorMsg, true); return; } const filename = `${baseFilename}.${format}`; try { if (format === 'svg') { downloadAsSvg(svg, filename); showNotification(_lang(nbText.export.exportSuccess)); } else { await downloadAsRaster(svg, filename, format); showNotification(_lang(nbText.export.exportSuccess)); } } catch (error) { console.error('Download failed:', error); showNotification(`${_lang(nbText.export.downloadFailed)}: ${error.message || error}`, true); } }; // Create select element const select = html``; select.onchange = async (event) => { const format = event.target.value; if (format) { try { await downloadChart(format); event.target.value = ''; } catch (error) { console.error('Export error:', error); } } }; return html`

${_lang(nbText.export.titleAdaptiveCapacityMap)}

${select}

• ${_lang(nbText.export.hintPng)}

• ${_lang(nbText.export.hintJpeg)}

• ${_lang(nbText.export.hintSvgVector)}

• ${_lang(nbText.export.hintCsvData)}

• ${_lang(nbText.export.hintJsonData)}

• ${_lang(nbText.export.hintGeojson)}

• ${_lang(nbText.export.hintShapefile)}

`; } 55:Tfc8,textDynamicInsights_adaptiveCapacities2 = { // return md`TODO: based on icicle data` // dynamic insight based on selected region // Check if admin3 (woreda) is selected const admin3 = adminSelections.selectAdmin3?.value; const admin2 = adminSelections.selectAdmin2.value; const admin1 = adminSelections.selectAdmin1.value; const admin0 = adminSelections.selectAdmin0.label ?? globalSelection.label; // If admin3 is selected, show nested hierarchy: admin3 -> admin2 -> admin1 -> admin0 if (admin3 && adminSelections.selectAdmin0.value === "Ethiopia") { const admin3MadLib = adaptiveCapacityInsightMadLib2( dynamicInsights_adaptiveCapacity.insights.admin3, admin3 ); const admin2MadLib = adaptiveCapacityInsightMadLib2( dynamicInsights_adaptiveCapacity.insights.admin2, admin2 ); const admin1MadLib = adaptiveCapacityInsightMadLib2( dynamicInsights_adaptiveCapacity.insights.admin1, admin1 ); const admin0Insights = dynamicInsights_adaptiveCapacity.insights.admin0; const admin0MadLib = adaptiveCapacityInsightMadLib2( admin0Insights, admin0 ); const langWithinAdmin2 = Lang.reduceReplaceTemplateItems( _lang(nbText.adaptiveCapacities.insights.nestedLocationBlurb), [ { name: "admin_inner", value: admin3 }, { name: "admin_outer", value: admin2 } ] ); const withinAdmin2 = admin3 ? `${langWithinAdmin2}` : ``; const langWithinAdmin1 = Lang.reduceReplaceTemplateItems( _lang(nbText.adaptiveCapacities.insights.nestedLocationBlurb), [ { name: "admin_inner", value: admin2 }, { name: "admin_outer", value: admin1 } ] ); const withinAdmin1 = admin2 ? `${langWithinAdmin1}` : ``; const langWithinAdmin0 = Lang.reduceReplaceTemplateItems( _lang(nbText.adaptiveCapacities.insights.nestedLocationBlurb), [ { name: "admin_inner", value: admin1 }, { name: "admin_outer", value: admin0 } ] ); const withinAdmin0 = admin1 ? `${langWithinAdmin0}` : ``; // Text sections ------------------------------ const admin3Text = md`${admin3MadLib}`; const admin2Text = md`${withinAdmin2} ${admin2MadLib}`; const admin1Text = md`${withinAdmin1} ${admin1MadLib}`; const admin0Text = md`${withinAdmin0} ${admin0MadLib}`; // Final text ------------------------------ return md`${admin3 ? admin3Text : ""} ${admin2 ? admin2Text : ""} ${admin1 ? admin1Text : ""} ${admin0Insights ? admin0Text : ""} `; } // Otherwise, use existing logic for admin0/admin1/admin2 const admin2MadLib = adaptiveCapacityInsightMadLib2( dynamicInsights_adaptiveCapacity.insights.admin2, admin2 ); const admin1MadLib = adaptiveCapacityInsightMadLib2( dynamicInsights_adaptiveCapacity.insights.admin1, admin1 ); const admin0Insights = dynamicInsights_adaptiveCapacity.insights.admin0; const admin0MadLib = adaptiveCapacityInsightMadLib2( admin0Insights, admin0 ); const langWithinAdmin1 = Lang.reduceReplaceTemplateItems( _lang(nbText.adaptiveCapacities.insights.nestedLocationBlurb), [ { name: "admin_inner", value: admin2 }, { name: "admin_outer", value: admin1 } ] ); const withinAdmin1 = admin2 ? `${langWithinAdmin1}` : ``; const langWithinAdmin0 = Lang.reduceReplaceTemplateItems( _lang(nbText.adaptiveCapacities.insights.nestedLocationBlurb), [ { name: "admin_inner", value: admin1 }, { name: "admin_outer", value: admin0 } ] ); const withinAdmin0 = admin1 ? `${langWithinAdmin0}` : ``; // Text sections ------------------------------ const admin2Text = md`${admin2MadLib}`; const admin1Text = md`${withinAdmin1} ${admin1MadLib}`; const admin0Text = md`${withinAdmin0} ${admin0MadLib}`; // Final text ------------------------------ return md`${admin2 ? admin2Text : ""} ${admin1 ? admin1Text : ""} ${admin0Insights ? admin0Text : ""} `; }56:T40c,breadcrumb = { const svg = d3 .create("svg") .attr("viewBox", `0 0 ${breadcrumbWidth * 4.75} ${breadcrumbHeight}`) .style("font", "11px sans-serif") .style("margin", "2px"); const g = svg .selectAll("g") .data(icicle.sequence) .join("g") .attr("transform", (d, i) => `translate(${i * breadcrumbWidth}, 0)`); g.append("polygon") .attr("points", breadcrumbPoints) .attr("fill", (d) => icicle_color(d.data.name)) .attr("stroke", "white"); g.append("text") .attr("x", (breadcrumbWidth + 10) / 2) .attr("y", 15) .attr("dy", "0.35em") .attr("text-anchor", "middle") .attr("fill", "white") .text((d) => icicle_alias[d.data.name]); if (icicle.sequence.length > 1) { svg .append("text") .text(icicle.percentage > 0 ? icicle.percentage + "%" : "") .attr("x", (icicle.sequence.length + 0.25) * breadcrumbWidth) .attr("y", breadcrumbHeight / 2) .attr("dy", "0.35em") .attr("text-anchor", "middle"); } return svg.node(); }57:Tada,viewof icicle = { const root = partition(icicle_data); // const padding = 10; const svg = d3.create("svg"); // Make this into a view, so that the currently hovered sequence is available to the breadcrumb const element = svg.node(); element.value = { sequence: [], percentage: 0.0 }; svg .attr("viewBox", `0 0 ${width} ${height}`) .attr("class", "icicle-chart-svg") .style("font", "12px sans-serif"); svg .append("rect") .attr("width", width) .attr("height", height) .attr("fill", "none"); const segment = svg .append("g") .attr("transform", (d) => narrow ? `translate(${-root.y1}, 40)` : `translate(0, ${-root.y1 + 40})` ) .selectAll("rect") .data( root.descendants().filter((d) => { return d.depth; }) ) .join("rect") .attr("fill", (d) => icicle_color(d.data.name)) .attr("x", segmentX) .attr("y", segmentY) .attr("width", segmentWidth) .attr("height", segmentHeight) .on("mouseenter", (event, d) => { // Get the ancestors of the current segment, minus the root const sequence = d.ancestors().reverse().slice(1); // Highlight the ancestors segment.attr("fill-opacity", (node) => sequence.indexOf(node) >= 0 ? 1.0 : 0.3 ); const percentage = (100 * (d.value / root.value)).toPrecision(3); element.value = { sequence, percentage }; element.dispatchEvent(new CustomEvent("input")); }); svg.on("mouseleave", () => { segment.attr("fill-opacity", 1); // Update the value of this view element.value = { sequence: [], percentage: 0.0 }; element.dispatchEvent(new CustomEvent("input")); }); // add legend const colorScaleLang = _lang(nbText.adaptiveCapacities.delvingDeeper.plot.legend.domain) const colorScale = d3 .scaleOrdinal() .domain(colorScaleLang) .range(["#F4BB21", "#FC8A34", "#EC5A47"]); svg .append("rect") .attr("x", 1) .attr("y", 5) .attr("rx", 10) // Add rounded corners .attr("ry", 10) // Add rounded corners .attr("width", 300) // Adjust the width to fit the legend .attr("height", 30) // Adjust the height to fit the legend .attr("fill", "#fff") // .attr("stroke", "black"); const legend = svg .selectAll(".legend") .data(colorScale.domain()) .enter() .append("g") .attr("class", "legend") .attr("transform", function (d, i) { return "translate(" + (i * 100 + 25) + ",11)"; }); legend .append("rect") .attr("x", 0) .attr("width", 18) .attr("height", 18) .style("fill", colorScale); legend .append("text") .attr("x", 24) .attr("y", 9) .attr("dy", ".35em") .text(function (d) { return d; }); return element; }58:T1f63,export_icicle = { const downloadBlob = (blob, filename) => { const url = URL.createObjectURL(blob); const a = document.createElement("a"); a.href = url; a.download = filename; a.style.display = "none"; document.body.appendChild(a); a.click(); document.body.removeChild(a); setTimeout(() => URL.revokeObjectURL(url), 100); }; const showNotification = (message, isError = false) => { const notification = html`

${message}

`; document.body.appendChild(notification); setTimeout(() => { if (notification.parentNode) notification.parentNode.removeChild(notification); }, isError ? 5000 : 3000); }; const downloadAsSvg = (svg, filename) => { const clone = svg.cloneNode(true); const serializer = new XMLSerializer(); const blob = new Blob([serializer.serializeToString(clone)], { type: "image/svg+xml" }); downloadBlob(blob, filename); }; const downloadAsRaster = (svg, filename, format) => { return new Promise((resolve, reject) => { const clone = svg.cloneNode(true); let svgString = new XMLSerializer().serializeToString(clone); if (!svgString.includes("\n" + svgString; } let width, height; const viewBox = svg.getAttribute("viewBox"); if (viewBox) { const parts = viewBox.split(/\s+|,/).filter(p => p).map(parseFloat); if (parts.length === 4) { width = parts[2]; height = parts[3]; } } if (!width || !height) { width = parseFloat(svg.getAttribute("width")) || svg.getBoundingClientRect().width || 900; height = parseFloat(svg.getAttribute("height")) || svg.getBoundingClientRect().height || 600; } const svgDataUrl = "data:image/svg+xml;charset=utf-8," + encodeURIComponent(svgString); const canvas = document.createElement("canvas"); const ctx = canvas.getContext("2d"); canvas.width = width; canvas.height = height; ctx.fillStyle = "white"; ctx.fillRect(0, 0, width, height); const img = new Image(); img.crossOrigin = "anonymous"; img.onload = () => { try { ctx.drawImage(img, 0, 0, width, height); canvas.toBlob((blob) => { if (blob) { downloadBlob(blob, filename); resolve(); } else reject(new Error("Failed to create blob")); }, format === "png" ? "image/png" : "image/jpeg", format === "jpeg" || format === "jpg" ? 0.92 : 1.0); } catch (e) { reject(e); } }; img.onerror = () => reject(new Error("Failed to load SVG")); img.src = svgDataUrl; }); }; const downloadAsPdf = (svg, filename) => { return new Promise((resolve, reject) => { const printWindow = window.open("", "_blank"); if (!printWindow) { reject(new Error(_lang(nbText.export.allowPopups))); return; } const clone = svg.cloneNode(true); const serializer = new XMLSerializer(); const svgString = serializer.serializeToString(clone); printWindow.document.write(`Export${svgString}`); printWindow.document.close(); printWindow.onload = () => { printWindow.print(); printWindow.onafterprint = () => { printWindow.close(); resolve(); }; }; }); }; const downloadAsCsv = (data, filename) => { if (!data || data.length === 0) throw new Error(_lang(nbText.export.noDataCsv)); const headers = Object.keys(data[0]); const rows = [headers.join(","), ...data.map(row => headers.map(h => { const v = row[h]; if (v == null) return ""; const s = String(v); return (s.includes(",") || s.includes('"') || s.includes("\n")) ? `"${s.replace(/"/g, '""')}"` : s; }).join(",") )]; downloadBlob(new Blob([rows.join("\n")], { type: "text/csv;charset=utf-8" }), filename); }; const downloadAsJson = (data, filename) => { downloadBlob(new Blob([JSON.stringify(data, null, 2)], { type: "application/json" }), filename); }; const getChartData = async () => { let raw = icicle_raw; if (raw && typeof raw.then === "function") raw = await raw; if (!raw || !Array.isArray(raw)) return []; return raw.map(d => ({ path: d.path ?? "", value: d.value ?? 0 })); }; const downloadChart = async (format) => { const ts = new Date().toISOString().replace(/[:.]/g, "-").split("T")[0]; const baseFilename = `adaptive-capacity-icicle-${ts}`; if (format === "csv") { try { const data = await getChartData(); downloadAsCsv(data, `${baseFilename}.csv`); showNotification(_lang(nbText.export.csvSuccess)); } catch (e) { showNotification(`${_lang(nbText.export.csvFailed)}: ${e.message}`, true); } return; } if (format === "json") { try { const data = await getChartData(); downloadAsJson(data, `${baseFilename}.json`); showNotification(_lang(nbText.export.jsonSuccess)); } catch (e) { showNotification(`${_lang(nbText.export.jsonFailed)}: ${e.message}`, true); } return; } await new Promise(r => setTimeout(r, 300)); const svg = _getIcicleSvg(); if (!svg) { showNotification(_lang(nbText.export.icicleNotFound), true); return; } const filename = `${baseFilename}.${format === "jpeg" || format === "jpg" ? "jpg" : format}`; try { if (format === "svg") { downloadAsSvg(svg, filename); showNotification(_lang(nbText.export.exportSuccess)); } else if (format === "pdf") { await downloadAsPdf(svg, filename); showNotification(_lang(nbText.export.printDialogOpened)); } else { await downloadAsRaster(svg, filename, format); showNotification(_lang(nbText.export.exportSuccess)); } } catch (e) { showNotification(`${_lang(nbText.export.exportFailed)}: ${e.message}`, true); } }; const select = html``; select.onchange = async (e) => { const format = e.target.value; if (format) { try { await downloadChart(format); e.target.value = ""; } catch (err) { console.error("Export error:", err); } } }; return html`

${_lang(nbText.export.titleIcicle)}

${select}

• ${_lang(nbText.export.hintPngJpegSvg)}

• ${_lang(nbText.export.hintPdf)}

• ${_lang(nbText.export.hintCsvJson)}

`; } 59:T621,styling = { return !toggleCustomStyling ? "no custom styling" : htl.html`` }5a:T4cf,function tocOneliner({ selector = "h1", // selectors to include (can comma-separate, like "h1,h2,h3") heading = "In this notebook", // heading for ToC delim = ' | ', // delimiter between links skip = [], // text content for headers to exclude } = {}) { // return a one-liner table of contents // allow for skips // modified from https://observablehq.com/@mbostock/toc return Generators.observe(notify => { let headings = []; function observed() { let h = Array.from(document.querySelectorAll(selector)); h = h.filter((d) => !skip.includes(d.textContent)) if (h.length !== headings.length || h.some((h, i) => headings[i] !== h)) { notify(html`${heading}
${Array.from(headings = h, (h, i) => { const end = i === headings.length - 1 return Object.assign( html`${DOM.text(h.textContent)}${end ? '' : delim}`, {onclick: e => (e.preventDefault(), h.scrollIntoView())} ); })}`); } } const observer = new MutationObserver(observed); observer.observe(document.body, {childList: true, subtree: true}); observed(); return () => observer.disconnect(); }); }5b:T23bf,nbTextSupportNbText=({ supportNbText: { labels: { allRegions: { en: "All regions", am: "ሁሉም ክልሎች", or: "Aanaa hunda", ti: "ኩላት ክልላት", so: "Gobollada oo dhan", af: "Qadaanaa kee num kaysa" }, allSubregions: { en: "All subregions", am: "ሁሉም ንዑስ ክልሎች", or: "Aanaa gurguddaa hunda", ti: "ኩላት ንኡስ ክልላት", so: "Gobollada hoose oo dhan", af: "Qadaanaa diifaa kee num kaysa" }, allWoredas: { en: "All woredas", am: "ሁሉም ወረዳዎች", or: "Aanaa dachaa hunda", ti: "ኩላት ወረዳታት", so: "Degmooyinka oo dhan", af: "Qadaanaa kee num kaysa" }, quickInsights: { en: "Quick Insights", am: "ፈጣን ግንዛቤ", or: "Hubannoo saffisaan", ti: "ቀልጣፍ ርዕዮት", so: "Fahamka degdeg ah", af: "Argina xayawaan" }, language: { en: "Language", am: "ቋንቋ", or: "Afaan", ti: "ቋንቋ", so: "Luqad", af: "Af" }, tocTitle: { en: "In this notebook", am: "በዚህ ኖትቡክ ውስጥ", or: "Barruu kana keessatti", ti: "ኣብዚ ናይ ምዝገባ ወረቐት", so: "Buuggan kana ku saabsan", af: "Kutbata kana keessa" }, crop: { en: "Crop", am: "የምርት አይነት", or: "Miraa", ti: "ፍሬ", so: "Beer", af: "Midad" }, sort: { en: "Sort", am: "ማደርደር", or: "Hirmaawaa", ti: "ሰርዝ", so: "Kala saar", af: "Soorta" }, sortTotals: { en: "Sort totals", am: "ጠቅላላዎችን ማደርደር", or: "Waliigala hirmaawaa", ti: "ጠቕላላ ሰርዝ", so: "Wadarta kala saar", af: "Soorta guutaa" }, sortBars: { en: "Sort bars", am: "አሞሌዎችን ማደርደር", or: "Bara hirmaawaa", ti: "ኣሞሌታት ሰርዝ", so: "Baararka kala saar", af: "Soorta baarota" }, confidenceIntervals: { en: "Confidence intervals", am: "የመተማመን ክፍተቶች", or: "Giddugalee amanamaa", ti: "ናይ ምትእምማን ርጕማት", so: "Kala duwaha kalsoonida", af: "Dhaammata amanamaa" }, highlightAez: { en: "Highlight AEZ", am: "AEZ ምልክት ማድረግ", or: "AEZ mul'isaa", ti: "AEZ ኣለዝዕ", so: "Muuji AEZ", af: "AEZ mul'isi" }, highlightPractice: { en: "Highlight a practice", am: "ተግባር ምልክት ማድረግ", or: "Hojii mul'isaa", ti: "ልምዲ ኣለዝዕ", so: "Muuji hab", af: "Mida mul'isi" } }, phrases: { inTotal: { en: "In total, there are", am: "በጠቅላላው አሉ", or: "Waliigalaan, jiru", ti: "ብጠቕላላ ኣለዉ", so: "Wadarta guud, waxaa jira", af: "Guutuu keessa, fakkaata" }, specificHas: { en: `**:::item:::** has`, am: `**:::item:::** አለው`, or: `**:::item:::** qaba`, ti: `**:::item:::** ኣለዎ`, so: `**:::item:::** wuxuu leeyahay`, af: `**:::item:::** qaba` } }, words: { toBe: { singular: { en: "is", am: "ነው", or: "dha", ti: "እዩ", so: "waa", af: "yaaba" }, plural: { en: "are", am: "ናቸው", or: "ta'u", ti: "እዮም", so: "waa", af: "yaaba" } }, and: { en: "and", am: "እና", or: "fi", ti: "ከምኡ'ውን", so: "iyo", af: "kee" }, percentage: { singular: { en: "percentage", am: "በመቶ", or: "pireesentii", ti: "ብመቶ", so: "boqolkiiba", af: "pireesentii" }, plural: { en: "percentages", am: "በመቶዎች", or: "pireesentoowwan", ti: "ብመቶታት", so: "boqolkiibadyo", af: "pireesentiiwwan" } }, crop: { singular: { en: "crop", am: "የምርት አይነት", or: "miraa", ti: "ፍሬ", so: "beer", af: "midad" }, plural: { en: "crops", am: "የምርት አይነቶች", or: "miraan", ti: "ፍራጅ", so: "beero", af: "midadwaa" } }, country: { singular: { en: "country", am: "ሀገር", or: "biyya", ti: "ሃገር", so: "wadan", af: "badda" }, plural: { en: "countries", am: "ሀገራት", or: "biyyoota", ti: "ሃገራት", so: "wadamada", af: "baddi" } }, region: { singular: { en: "region", am: "ክልል", or: "naannoo", ti: "ክልል", so: "gobol", af: "qadaana" }, plural: { en: "regions", am: "ክልሎች", or: "naannolee", ti: "ክልላት", so: "gobollada", af: "qadaanoo" } }, subregion: { singular: { en: "subregion", am: "ንዑስ ክልል", or: "naannoo gurguddaa", ti: "ንኡስ ክልል", so: "gobol hoose", af: "qadaana diifa" }, plural: { en: "subregions", am: "ንዑስ ክልሎች", or: "naannolee gurguddaa", ti: "ንኡስ ክልላት", so: "gobollada hoose", af: "qadaanoo diifaa" } }, woreda: { singular: { en: "woreda", am: "ወረዳ", or: "aanaa", ti: "ወረዳ", so: "degmo", af: "qadaana" }, plural: { en: "woredas", am: "ወረዳዎች", or: "aanoolee", ti: "ወረዳታት", so: "degmooyinka", af: "qadaanoo" } }, commodity: { singular: { en: "commodity", am: "የግብይት እቃ", or: "bittaa", ti: "ዕቃ", so: "alaab", af: "meeshaa" }, plural: { en: "commodities", am: "የግብይት እቃዎች", or: "bittaan", ti: "ዕቃታት", so: "alaabta", af: "meeshaawaan" } }, overview: { en: "overview", am: "አጠቃላይ እይታ", or: "irra deebi'iinsa", ti: "ሓፈሻዊ መግለጺ", so: "dulmarka", af: "argina guutuu" }, practice: { singular: { en: "practice", am: "ተግባር", or: "hojii", ti: "ልምዲ", so: "hab", af: "mida" }, plural: { en: "practices", am: "ተግባራት", or: "hojjetoowwan", ti: "ልምድታት", so: "habab", af: "midi" } }, observation: { singular: { en: "observation", am: "ትንታኔ", or: "ilaalcha", ti: "ትንታነ", so: "dareen", af: "ilaalta" }, plural: { en: "observations", am: "ትንታኔዎች", or: "ilaalchawwan", ti: "ትንታነታት", so: "dareenada", af: "ilaaltoo" } }, increase: { en: "increase", am: "ጨምር", or: "dabalataa", ti: "ውሑድ", so: "kordhi", af: "badisi" }, decrease: { en: "decrease", am: "ቀንስ", or: "hir'isaa", ti: "ንእሽቶ", so: "yaree", af: "xiqqisi" } } } })5c:Tf19f,nbTextMethods=({ methods: { h1: { en: "Methods & Sources", am: "ዘዴዎች & ምንጮች", or: "Malaafi Uumamaa", ti: "ኣገባባት & ምንጪታት", so: "Hababka & Ilaaha", af: "Malaafi Uumamaa" }, section1: { en: "Datasets", am: "ዳታሴቶች", or: "Kuusoo Deetaa", ti: "ዳታሴታት", so: "Xog Ururinta", af: "Xog Ururiyo", subsections: { en: `### Exposure (Value of Production) - **[Crop value of production](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/exposure_catalog/mapspam2017/mapspam2017_vop_parquet/mapspam2017_vop_parquet.json)** data comes from MapSPAM 2017 V2r3 (Spatial Production Allocation Model) where production values are multiplied by country specific FAOstat international crop prices in (2005 International Dollars). An [international dollar](https://en.wikipedia.org/wiki/International_dollar) (2005) is a hypothetical unit of currency that has the same purchasing power parity as the U.S. dollar had in the United States in 2005, allowing for comparison of what consumers can buy in different countries with the same amount of money. This dataset is an updated version of MapSPAM specifically tailored for this project. It includes bug fixes and incorporates country-specific values of production instead of global averages. - **[Livestock value of production](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/exposure_catalog/GLW3_livestock/GLW3_livestock_vopPQ/GLW3_livestock_vopPQ.json)** in 2005 International Dollars were provided by the authors of [Herrero et al. (2013)](https://www.pnas.org/doi/full/10.1073/pnas.1308149110/). ### Adaptive Capacities - **[Population](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/population/worldpop_2020/pop_2020_parquet/pop_2020_parquet.json)** data is from the [WorldPop Unconstrained Global Mosaic](https://hub.worldpop.org/geodata/listing?id=64) for 2020. - **[Poverty](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/poverty/grdi/grdi_historical_2010-2020/grdi_historical_2010-2020.json)** data is from the [Global Gridded Deprivation Index](https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1). - **[Education](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/education_catalog/catalog.json)** data for the icicle plot is the mean male and female educational attainment from the [2005-2015 IHME Estimates for ages 15-49](https://ghdx.healthdata.org/record/ihme-data/africa-educational-attainment-geospatial-estimates-2000-2015). The education rate combines educational attainment with expected years of schooling in a [composite index as part of the Sub-national HDI](https://globaldatalab.org/shdi/metadata/edindex/). - **[Female Empowerment](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/women-and-gender/female-empowerment/GenderEquity_1995-2015/GenderEquity_1995-2015.json)** is a composite index of domestic violence, employment, reproductive healthcare, decision making power, and family planning. The index is from [Rettig, Erica (2022)](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/8GJKYW) and based on input data from the [DHS Program](https://dhsprogram.com). ### Boundaries [Administrative areas](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/boundary_catalog/geoBoundaries_SSA/collection.json) used in this notebook come from [geoBoundaries 6.0.0](https://github.com/wmgeolab/geoBoundaries). The gbHumanitarian boundaries are used and if not available then the gbOpen boundaries are substituted. ### Climate Hazards & Risk [Climate hazards](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/hazard_catalog/catalog.json) were calculated using five datasets [CHIRPS](https://www.chc.ucsb.edu/data/chirps)/[CHIRTS](https://www.chc.ucsb.edu/data/chirtsdaily), [AgERA5](https://doi.org/10.24381/cds.6c68c9bb), [CMIP6 projections](https://github.com/SantanderMetGroup/ATLAS), and [crop calendars](https://zenodo.org/records/5062513). Using the R workflows mentioned below, raw hazard data were converted to risk, intersected with exposure and extracted by administrative boundaries to generate tabular data in parquet form, for example [severe_adm_int.parquet](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/hazard_catalog/hazard_risk_vop_annual/annual_digital-atlas/hazards/hazard_risk_vop/annual/severe_adm_int.parquet/annual_digital-atlas/hazards/hazard_risk_vop/annual/severe_adm_int.parquet.json).`, am: `### ተጋላጭነት (የምርት ዋጋ) - **[የሰብል ምርት ዋጋ](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/exposure_catalog/mapspam2017/mapspam2017_vop_parquet/mapspam2017_vop_parquet.json)** መረጃ ከ MapSPAM 2017 V2r3 (የቦታ አመራረት ድልድል ሞዴል) የተገኘ ሲሆን የምርት ዋጋዎች በሀገር በተወሰነ የ FAOstat ዓለም አቀፍ የሰብል ዋጋዎች ተባዝተዋል (በ2005 ዓለም አቀፍ ዶላር)። አንድ [ዓለም አቀፍ ዶላር](https://en.wikipedia.org/wiki/International_dollar) (2005) በ2005 በዩናይትድ ስቴትስ እንደነበረው የአሜሪካ ዶላር ተመሳሳይ የመግዛት አቅም ያለው መላምታዊ የገንዘብ አሃድ ሲሆን ሸማቾች በተለያዩ አገሮች በተመሳሳይ የገንዘብ መጠን ምን መግዛት እንደሚችሉ ለማነጻጸር ያስችላል። ይህ የውሂብ ስብስብ ለዚህ ፕሮጀክት በተለይ የተበጀ የዘመነ የ MapSPAM ስሪት ነው። ሳንካ ጥገናዎችን ያካትታል እና ከዓለም አቀፍ አማካዮች ይልቅ ሀገር-ተኮር የምርት ዋጋዎችን ያካትታል። - **[የእንስሳት ምርት ዋጋ](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/exposure_catalog/GLW3_livestock/GLW3_livestock_vopPQ/GLW3_livestock_vopPQ.json)** በ2005 ዓለም አቀፍ ዶላር የቀረበው በ[Herrero et al. (2013)](https://www.pnas.org/doi/full/10.1073/pnas.1308149110/) ደራሲዎች ነው። ### መላመድ አቅሞች - **[የሕዝብ ብዛት](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/population/worldpop_2020/pop_2020_parquet/pop_2020_parquet.json)** መረጃ ከ [WorldPop Unconstrained Global Mosaic](https://hub.worldpop.org/geodata/listing?id=64) ለ2020 የተገኘ ነው። - **[ድህነት](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/poverty/grdi/grdi_historical_2010-2020/grdi_historical_2010-2020.json)** መረጃ ከ [Global Gridded Deprivation Index](https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1) የተገኘ ነው። - **[ትምህርት](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/education_catalog/catalog.json)** መረጃ ለአይሲክል ፕላት ከ[2005-2015 የIHME ግምቶች ለ15-49 ዓመት ዕድሜ](https://ghdx.healthdata.org/record/ihme-data/africa-educational-attainment-geospatial-estimates-2000-2015) የወንዶች እና የሴቶች አማካይ የትምህርት ደረጃ ነው። የትምህርት መጠኑ የትምህርት ደረጃን ከሚጠበቀው የትምህርት ዓመታት ጋር በ[ንዑስ-ብሔራዊ ኤችዲአይ አካል የሆነ ድብልቅ መረጃ ጠቋሚ](https://globaldatalab.org/shdi/metadata/edindex/) ያጣምራል። - **[የሴቶች አቅም ማጎልበት](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/women-and-gender/female-empowerment/GenderEquity_1995-2015/GenderEquity_1995-2015.json)** የቤት ውስጥ ጥቃት፣ የሥራ ስምሪት፣ የሥነ ተዋልዶ ጤና አጠባበቅ፣ የውሳኔ አሰጣጥ ሥልጣን እና የቤተሰብ ምጣኔ ድብልቅ መረጃ ጠቋሚ ነው። መረጃ ጠቋሚው ከ [Rettig, Erica (2022)](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/8GJKYW) የተገኘ ሲሆን ከ[DHS ፕሮግራም](https://dhsprogram.com) በተገኘ መረጃ ላይ የተመሠረተ ነው። ### ወሰኖች በዚህ ማስታወሻ ደብተር ውስጥ ጥቅም ላይ የዋሉ [የአስተዳደር አካባቢዎች](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/boundary_catalog/geoBoundaries_SSA/collection.json) ከ [geoBoundaries 6.0.0](https://github.com/wmgeolab/geoBoundaries) የተገኙ ናቸው። የ gbHumanitarian ድንበሮች ጥቅም ላይ ይውላሉ እና ካልተገኙ የ gbOpen ድንበሮች ይተካሉ። ### የአየር ንብረት አደጋዎች እና ስጋት [የአየር ንብረት አደጋዎች](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/hazard_catalog/catalog.json) የተሰሉት አምስት የውሂብ ስብስቦችን [CHIRPS](https://www.chc.ucsb.edu/data/chirps)/[CHIRTS](https://www.chc.ucsb.edu/data/chirtsdaily), [AgERA5](https://doi.org/10.24381/cds.6c68c9bb), [CMIP6 ትንበያዎች](https://github.com/SantanderMetGroup/ATLAS), እና [የሰብል የቀን መቁጠሪያዎች](https://zenodo.org/records/5062513) በመጠቀም ነው። ከዚህ በታች የተጠቀሱትን የ R የሥራ ሂደቶች በመጠቀም፣ ጥሬ የአደጋ መረጃ ወደ ስጋት ተለወጠ፣ ከተጋላጭነት ጋር ተገናኝቶ እና በአስተዳደር ድንበሮች ተወስዶ በፓርኬት መልክ ሰንጠረዥ ያለው መረጃ ለማመንጨት፣ ለምሳሌ [severe_adm_int.parquet](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/hazard_catalog/hazard_risk_vop_annual/annual_digital-atlas/hazards/hazard_risk_vop/annual/severe_adm_int.parquet/annual_digital-atlas/hazards/hazard_risk_vop/annual/severe_adm_int.parquet.json)።`, or: `### Saaxilamummaa (Gatii Oomisha) - **[Gatii oomisha midhaanii](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/exposure_catalog/mapspam2017/mapspam2017_vop_parquet/mapspam2017_vop_parquet.json)** randaa MapSPAM 2017 V2r3 (Spatial Production Allocation Model) irraa kan argame yoo ta'u, gatii oomishaa FAOstat gatii midhaanii idil-addunyaa biyya mata-mataatiin (Doolaara Idil-addunyaa 2005) baay'ee si'a ta'a. [Doolaara Idil-addunyaa](https://en.wikipedia.org/wiki/International_dollar) (2005) kun qaama maallaqaa tilmaamaa kan ta'e, humna bitaa fi gurguraa walqixa kan doolaara Ameerikaa biyya Ameerikaa keessa bara 2005 qabu yoo ta'u, maamiltoonni maallaqa walqixaatiin biyyoota adda-addaa keessatti maal bitachuu akka danda'an wal bira qabuu dandeessisa. Kuusaan deetaa kun MapSPAM fo'amee pirojektiif qophaa'e dha. Sirreeffama badiwwanii kan of keessaa qabu yoo ta'u, bakka walakkeewwan idil-addunyaatiin gatii oomishaa biyya mata-mataa kan of keessaa qabu dha. - **[Gatii oomisha horii](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/exposure_catalog/GLW3_livestock/GLW3_livestock_vopPQ/GLW3_livestock_vopPQ.json)** Doolaara Idil-addunyaa 2005 keessatti kan kennaman abbootii barreeffaa [Herrero et al. (2013)](https://www.pnas.org/doi/full/10.1073/pnas.1308149110/) ti. ### Dandeettiwwan Madaqinsaa - **[Baay'ina ummataa](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/population/worldpop_2020/pop_2020_parquet/pop_2020_parquet.json)** deetaan kun [WorldPop Unconstrained Global Mosaic](https://hub.worldpop.org/geodata/listing?id=64) irraa bara 2020f argame dha. - **[Hiyyummaa](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/poverty/grdi/grdi_historical_2010-2020/grdi_historical_2010-2020.json)** deetaan kun [Global Gridded Deprivation Index](https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1) irraa argame dha. - **[Barumsa](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/education_catalog/catalog.json)** deetaan kun kan icicle plot ti, kan dhiraa fi dubartii waliigala sadarkaa barumsaa [tilmaama IHME 2005-2015 umurii 15-49](https://ghdx.healthdata.org/record/ihme-data/africa-educational-attainment-geospatial-estimates-2000-2015) irraa argame dha. Sadarkaan barumsaa kun sadarkaa barumsaa fi waggaa barumsaa eegamu waliini [indeksii walitti-makuu HDI giddu-galeessaa](https://globaldatalab.org/shdi/metadata/edindex/) keessatti walitti makuun shallagame dha. - **[Abbaa humna dubartii gochuu](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/women-and-gender/female-empowerment/GenderEquity_1995-2015/GenderEquity_1995-2015.json)** indeksii walitti-makuu kan gummaa manaa, hojii, fayyaa walhormaataa, aangoo murteessuu, fi karoorfata maatii ti. Indeksiin kun [Rettig, Erica (2022)](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/8GJKYW) irraa kan argame fi deetaa [DHS Program](https://dhsprogram.com) irraa kan argame irratti hundaa'e dha. ### Daangaa Naannoonni [naannoo bulchiinsaa](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/boundary_catalog/geoBoundaries_SSA/collection.json) kitaaba yaadannoo kana keessatti fayyadaman [geoBoundaries 6.0.0](https://github.com/wmgeolab/geoBoundaries) irraa argaman. Daangaan gbHumanitarian fayyadama, yoo hin jiraanne garuu daangaan gbOpen bakka bu'a. ### Balawwan Qilleensaa fi Hatattama [Balawwan qilleensaa](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/hazard_catalog/catalog.json) kuusaa deetaa shan [CHIRPS](https://www.chc.ucsb.edu/data/chirps)/[CHIRTS](https://www.chc.ucsb.edu/data/chirtsdaily), [AgERA5](https://doi.org/10.24381/cds.6c68c9bb), [raagowwan CMIP6](https://github.com/SantanderMetGroup/ATLAS), fi [kalendarii midhaanii](https://zenodo.org/records/5062513) fayyadamuun shallagaman. Hojiiwwan R jala ibsaman fayyadamuun, deetaan balaa dheedhiin gara hatattamaatti jijjiirame, saaxilamummaa wajjin wal-qaxaamuree, fi daangaa bulchiinsaatiin baafamee kuusaa deetaa parquet uumameef, fakkeenyaaf [severe_adm_int.parquet](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/hazard_catalog/hazard_risk_vop_annual/annual_digital-atlas/hazards/hazard_risk_vop/annual/severe_adm_int.parquet/annual_digital-atlas/hazards/hazard_risk_vop/annual/severe_adm_int.parquet.json).`, ti: `### ተጋላጭነት (ዋጋ ምርት) - **[ዋጋ ምርት ሰብሊ](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/exposure_catalog/mapspam2017/mapspam2017_vop_parquet/mapspam2017_vop_parquet.json)** ሓበሬታ ካብ MapSPAM 2017 V2r3 (ኣብነታዊ ሞዴል ምደላል ምርት) ዝመጸ ኮይኑ፡ ዋጋታት ምርት ብሃገር-ብሃገር ብዝተወሰነ ዓለምለኻዊ ዋጋታት ሰብሊ FAOstat (ኣብ 2005 ዓለምለኻዊ ዶላር) ተባዚዙ ኣሎ። ሓደ [ዓለምለኻዊ ዶላር](https://en.wikipedia.org/wiki/International_dollar) (2005) ልክዕ ከምቲ ኣብ 2005 ኣብ ዩናይትድ ስቴትስ ዝነበረ ዶላር ኣመሪካ ተመሳሳሊ ዓቕሚ ምግዛእ ዘለዎ መላምታዊ ምዕራፍ ገንዘብ ኮይኑ፡ ሸማቶ ብተመሳሳሊ መጠን ገንዘብ ኣብ ፍልልያት ሃገራት እንታይ ከምዝገዝኡ ንምንጽጻር የኽእል። እዚ ስብስብ ሓበሬታ እዚ ብፍሉይ ንዝሃብካዮ ፕሮጀክት ዝተመሓየሸ ስሪት MapSPAM እዩ። ጽገናታት ሳንካ ዘጠቓልል ኮይኑ፡ ኣብ ክንዲ ዓለምለኻዊ ማእኸላት፡ ሃገር-ብሃገር ዝተለለዩ ዋጋታት ምርት ዘጠቓልል እዩ። - **[ዋጋ ምርት ማልሃ](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/exposure_catalog/GLW3_livestock/GLW3_livestock_vopPQ/GLW3_livestock_vopPQ.json)** ኣብ 2005 ዓለምለኻዊ ዶላር ብደራስቲ [Herrero et al. (2013)](https://www.pnas.org/doi/full/10.1073/pnas.1308149110/) ቀሪቡ ኣሎ። ### ናይ ምምሕያሽ ክእለታት - **[ብዝሒ ህዝቢ](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/population/worldpop_2020/pop_2020_parquet/pop_2020_parquet.json)** ሓበሬታ ካብ [WorldPop Unconstrained Global Mosaic](https://hub.worldpop.org/geodata/listing?id=64) ን2020 ዝተራእየ እዩ። - **[ድኽነት](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/poverty/grdi/grdi_historical_2010-2020/grdi_historical_2010-2020.json)** ሓበሬታ ካብ [Global Gridded Deprivation Index](https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1) ዝተራእየ እዩ። - **[ትምህርቲ](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/education_catalog/catalog.json)** ሓበሬታ ንኣይሲክል ፕላት ካብ [2005-2015 ግምታት IHME ንዕድመ 15-49](https://ghdx.healthdata.org/record/ihme-data/africa-educational-attainment-geospatial-estimates-2000-2015) ማእኸላይ ደረጃ ትምህርቲ ተባዕቶ ከምኡውን ኣንስተይቲ እዩ። መጠን ትምህርቲ እዚ ደረጃ ትምህርቲ ምስ ዝተጸበየ ዓመታት ትምህርቲ ብሓደ [ውሁድ ኢንዴክስ ከም ክፍሊ ንኡስ-ሃገራዊ HDI](https://globaldatalab.org/shdi/metadata/edindex/) የወሃድሎ። - **[ምሕያል ኣንስተይቲ](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/women-and-gender/female-empowerment/GenderEquity_1995-2015/GenderEquity_1995-2015.json)** ውሁድ ኢንዴክስ ናይ ውሽጢ ቤት ዓመጻ፡ ስራሕ፡ ጥንቃቐ ጥዕና ራህዋ፡ ስልጣን ውሳነ፡ ከምኡውን መደብ ስድራቤት እዩ። እቲ ኢንዴክስ ካብ [Rettig, Erica (2022)](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/8GJKYW) ዝተራእየ ኮይኑ፡ ኣብ [ፕሮግራም DHS](https://dhsprogram.com) ዝተራእየ ሓበሬታ ኣብ ዝተመስረተ እዩ። ### ዶባት ኣብዚ መዘከሪታ ዝተጠቕሙ [ከባቢታት ምምሕዳር](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/boundary_catalog/geoBoundaries_SSA/collection.json) ካብ [geoBoundaries 6.0.0](https://github.com/wmgeolab/geoBoundaries) ዝመጹ እዮም። ዞባታት gbHumanitarian ይጥቀሙ እሞ እንተዘይረኸቡ፡ ዞባታት gbOpen ይተንክዩ። ### ናይ ኩነታት ኣየር ሓዘናትን ሓደጋን [ናይ ኩነታት ኣየር ሓዘናት](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/hazard_catalog/catalog.json) ብምጥቃም ሓሙሽተ ስብስብታት ሓበሬታ [CHIRPS](https://www.chc.ucsb.edu/data/chirps)/[CHIRTS](https://www.chc.ucsb.edu/data/chirtsdaily), [AgERA5](https://doi.org/10.24381/cds.6c68c9bb), [CMIP6 ትንበያታት](https://github.com/SantanderMetGroup/ATLAS), ከምኡውን [ካሌንደር ሰብሊ](https://zenodo.org/records/5062513) ተሳኒሖም። ኣብ ታሕቲ እተጠቕሱ R ኣገባባት ስራሕ ብምጥቃም፡ ጥሬ ሓበሬታ ሓዘና ናብ ሓደጋ ተቐይሩ፡ ምስ ተጋላጭነት ተራኺቡ ከምኡውን ብዶባት ምምሕዳር ተወጢኡ ሰሌዳዊ ሓበሬታ ብፓርኬት መልክዕ ንምፍራይ ከምኡ እዩ ዝግበር፡ ንኣብነት [severe_adm_int.parquet](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/hazard_catalog/hazard_risk_vop_annual/annual_digital-atlas/hazards/hazard_risk_vop/annual/severe_adm_int.parquet/annual_digital-atlas/hazards/hazard_risk_vop/annual/severe_adm_int.parquet.json)።`, so: `### Soo-gaadhista (Qiimaha Wax-soosaarka) - **[Qiimaha wax-soosaarka dalagga](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/exposure_catalog/mapspam2017/mapspam2017_vop_parquet/mapspam2017_vop_parquet.json)** xogtu waxay ka timi MapSPAM 2017 V2r3 (Moodeelka Qoondaynta Wax-soosaarka Goobta) halkaasoo qiimaha wax-soosaarka lagu dhufto qiimaha dalagga caalamiga ah ee FAOstat ee waddan gaar ah (Doolarka Caalamiga ah ee 2005). [Doolar caalami](https://en.wikipedia.org/wiki/International_dollar) (2005) waa halbeeg lacageed oo mala awaal ah oo leh awood wax iibsigar oo la mid ah tii Doolarka Mareykanka uu ku lahaa Mareykanka 2005, taasoo u oggolaanaysa isbarbardhigga waxa macaamiishu ku iibsan karaan waddamo kala duwan isla lacag la mid ah. Xog ururintani waa nooc cusub oo MapSPAM ah oo si gaar ah loogu talagalay mashruucan. Waxay ka kooban tahay hagaajin khaladaad waxayna ku daraysaa qiimayaal wax-soosaar oo waddan gaar ah halkii laga isticmaali lahaa celcelis caalami ah. - **[Qiimaha wax-soosaarka xoolaha](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/exposure_catalog/GLW3_livestock/GLW3_livestock_vopPQ/GLW3_livestock_vopPQ.json)** oo ku jira Doolarka Caalamiga ah ee 2005 waxaa keenay qorayaasha [Herrero et al. (2013)](https://www.pnas.org/doi/full/10.1073/pnas.1308149110/). ### Awoodaha Laqabsiga - **[Tirada dadka](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/population/worldpop_2020/pop_2020_parquet/pop_2020_parquet.json)** xogtu waxay ka timid [WorldPop Isku-dhafka Caalamiga ah ee Aan Xaddidnayn](https://hub.worldpop.org/geodata/listing?id=64) sanadka 2020. - **[Saboolnimada](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/poverty/grdi/grdi_historical_2010-2020/grdi_historical_2010-2020.json)** xogtu waxay ka timid [Tusmaha Faqriga Shabakadaha Caalamiga ah](https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1). - **[Waxbarashada](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/education_catalog/catalog.json)** xogta loogu talagalay jaantuska barafka (icicle plot) waa celceliska heerka waxbarashada ragga iyo dumarka ee laga soo qaatay [Qiyaasaha IHME 2005-2015 ee da'da 15-49](https://ghdx.healthdata.org/record/ihme-data/africa-educational-attainment-geospatial-estimates-2000-2015). Heerka waxbarashadu wuxuu isku darayaa heerka waxbarasho iyo sannadaha waxbarasho ee la filayo [tusmaha isku dhafan oo qayb ka ah HDI-hoosaadka](https://globaldatalab.org/shdi/metadata/edindex/). - **[Kobcinta Haweenka](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/women-and-gender/female-empowerment/GenderEquity_1995-2015/GenderEquity_1995-2015.json)** waa tusme isku dhafan oo ka kooban rabshadaha qoyska, shaqo, daryeelka caafimaadka taranka, awooda go'aan qaadashada, iyo qorshaynta qoyska. Tusmuhu wuxuu ka yimid [Rettig, Erica (2022)](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/8GJKYW) wuxuuna ku salaysan yahay xogta laga helay [Barnaamijka DHS](https://dhsprogram.com). ### Xuduudaha [Meelaha maamulka](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/boundary_catalog/geoBoundaries_SSA/collection.json) ee buuggan xusuus qorka lagu isticmaalay waxay ka yimaadaan [geoBoundaries 6.0.0](https://github.com/wmgeolab/geoBoundaries). Xuduudaha gbHumanitarian waa la isticmaalaa haddii aan la heli karinna xuduudaha gbOpen ayaa beddela. ### Khataraha Cimilada & Halista [Xogta khataraha cimilada](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/hazard_catalog/catalog.json) waxaa lagu xisaabiyay iyadoo la adeegsanayo shan xog-ururin [CHIRPS](https://www.chc.ucsb.edu/data/chirps)/[CHIRTS](https://www.chc.ucsb.edu/data/chirtsdaily), [AgERA5](https://doi.org/10.24381/cds.6c68c9bb), [saadaasha CMIP6](https://github.com/SantanderMetGroup/ATLAS), iyo [jadwalka dalagga](https://zenodo.org/records/5062513). Iyadoo la adeegsanayo hababka R ee hoos ku xusan, xogta khatarta ceyriinka ah waxaa loo rogay halis, waxaa lagu dhex galay soo-gaadhista waxaana laga soo saaray xuduudaha maamulka si loo abuuro xog jadwalaysan oo qaab parquet ah, tusaale ahaan [severe_adm_int.parquet](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/hazard_catalog/hazard_risk_vop_annual/annual_digital-atlas/hazards/hazard_risk_vop/annual/severe_adm_int.parquet/annual_digital-atlas/hazards/hazard_risk_vop/annual/severe_adm_int.parquet.json).`, af: `### Exposer (Gali Qaxa) - **[Gali qaxa buqre](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/exposure_catalog/mapspam2017/mapspam2017_vop_parquet/mapspam2017_vop_parquet.json)** tàmox MapSPAM 2017 V2r3 (Spatial Production Allocation Model) kinni, gali qaxa tiddimime FAOstat gali buqre addunyâ (2005 Dolaar Addunyâ) kumatta. Inki [dolaar addunyâ](https://en.wikipedia.org/wiki/International_dollar) (2005) maalu naharsiino 2005 Amerika Dolaar takkeh gide akate le, makaaba mawwâ mawaaxik maalu inki gideh exaaxik camatteh xaamitaanak. Ah MapSPAM qusubey amal si taaxigey kinni. Mooqab baaxa leeh buqre qaxa addunyâ qaxak kal, qaxa baaxoh. - **[Gali qaxa lac](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/exposure_catalog/GLW3_livestock/GLW3_livestock_vopPQ/GLW3_livestock_vopPQ.json)** 2005 Dolaar Addunyâ tontiyab weelo [Herrero et al. (2013)](https://www.pnas.org/doi/full/10.1073/pnas.1308149110/) xagar keenik yemeete. ### Adaqsi dudda - **[Sinaa](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/population/worldpop_2020/pop_2020_parquet/pop_2020_parquet.json)** tàmox [WorldPop Unconstrained Global Mosaic](https://hub.worldpop.org/geodata/listing?id=64) 2020h tàmox. - **[Tudda](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/poverty/grdi/grdi_historical_2010-2020/grdi_historical_2010-2020.json)** tàmox [Global Gridded Deprivation Index](https://sedac.ciesin.columbia.edu/data/set/povmap-grdi-v1) kinni. - **[Barittó](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/education_catalog/catalog.json)** tàmox icicle plotuh, labhaa sayyoh fayya barittó macsaxi [2005-2015 IHME 15-49 sanat marih](https://ghdx.healthdata.org/record/ihme-data/africa-educational-attainment-geospatial-estimates-2000-2015) kinni. Barittó guyta barittó kee [sub-national HDIh indeksi gexsit](https://globaldatalab.org/shdi/metadata/edindex/) sarah yan sanat sarah. - **[Sayyó furma](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/adaptive-capacity/women-and-gender/female-empowerment/GenderEquity_1995-2015/GenderEquity_1995-2015.json)** indeksi gexsitay buxax umaminni, taama, qaafiyata wooqa, mekla abta dudda, kee buxah maxa. Indeksi [Rettig, Erica (2022)](https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/8GJKYW) xagar keenik yemeeteeh [DHS Program](https://dhsprogram.com) tàmoxul xisaabittal. ### Rámit Ah xaayo addat [ramit gexsit](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/boundary_catalog/geoBoundaries_SSA/collection.json) [geoBoundaries 6.0.0](https://github.com/wmgeolab/geoBoundaries) xagar keenik yemeete. gbHumanitarian ramit tiggileeh, matiggileek gbOpen ramit ciggiilima. ### Qaran Amóó kee Booddá [Qaran amóó](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/hazard_catalog/catalog.json) konoy tàmoxat cisab simte [CHIRPS](https://www.chc.ucsb.edu/data/chirps)/[CHIRTS](https://www.chc.ucsb.edu/data/chirtsdaily), [AgERA5](https://doi.org/10.24381/cds.6c68c9bb), [CMIP6 deedalittó](https://github.com/SantanderMetGroup/ATLAS), kee [buqre liisool](https://zenodo.org/records/5062513). R taama ruyyol gexsit taatak, qaran amóó tàmox booddáh korisse, exposer luk exxeexeeh, ramit gexsit exxeeh parquet adda tabular tàmox gineh, ceelallo [severe_adm_int.parquet](https://radiantearth.github.io/stac-browser/#/external/digital-atlas.s3.amazonaws.com/stac/public_stac/hazard_catalog/hazard_risk_vop_annual/annual_digital-atlas/hazards/hazard_risk_vop/annual/severe_adm_int.parquet/annual_digital-atlas/hazards/hazard_risk_vop/annual/severe_adm_int.parquet.json).` } }, section2: { en: "Methods", am: "ዘዴዎች", or: "Malalee", ti: "ኣገባባት", so: "Hababka", af: "Gexsitoota", subsections: { en: `### Climate Hazard Risk A detailed and replicable R workflow for generating raw climate hazards data is available at the [AdaptationAtlas/Hazards](https://github.com/AdaptationAtlas/hazards). The transformation of raw climate hazards into generic and crop-specific hazard risks was achieved using a separate, but equally replicable, R workflow, which can be found in the GitHub project [atlas/hazards_prototype](https://github.com/AdaptationAtlas/hazards_prototype). The process for calculating risk comprises several critical steps: 1. **Annual or Seasonal Summarization**: Raw hazard data is aligned with the [GGCMI Phase 3 crop calendar for maize](https://zenodo.org/records/5062513), then climate hazards are summarized at either annual or seasonal timescales. Future updates of the Atlas will incorporate crop-specific calendars. 2. **Occurrence**: For each season or year in a time series, we classify the risk of hazard occurrence (present/absent) across three severity levels (moderate, severe, extreme). Note, hazard severity is fixed to "severe" in this notebook. The specific hazards used in this analysis are: - **Dry** = number of soil water stress days [NDWS](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Severe risk = NDWS > 20 days (same across all crops and livestock). - **Heat (crops)** = days where maximum temperature > 35ºC [NTx35](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Severe risk = NTx35 > 20 days (same across all crops). - **Heat (livestock)** = thermal humidity index [THI](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Severe risk is livestock class specific, see Table 2 of [Thorton et al. 2021](https://doi.org/10.1111/gcb.15825). - **Wet** = number of waterlogging days [NDWL0](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Severe risk = NDWL0 > 5 days (same across all crops and livestock). More details on hazard definitions and thresholds for severity classes can found in the atlas/hazards wiki. Future 2024 updates of the Atlas will add crop specific maximum temperature thresholds and a notebook will be created to allow users to explore hazard risks in more detail. 3. **Risk**: We average the classified hazards over the years or seasons encompassed by the time-series to obtain an estimation of occurrence risk. 4. **Compound Risks**: To assess the risk of compound hazards, we multiply the risks associated with dry, heat, and wet conditions. This multiplication highlights areas where multiple hazards may coincide, posing greater risk to agricultural outputs. 5. **Integration with Economic Data**: Finally, we multiply the compound crop hazard risk data with crop value of production data. For example, if a crop is exposed to a hazard in 50% of growing seasons and the value of production is $2M/year then, on average, $1M of production is exposed to the hazard. The exposed value of production is then extracted by administrative areas to indicate potential economic impacts on crop production. ### Adaptive Capacity To calculate the population distribution according to adaptive capacity variables, we followed these steps: 1. **Data Classification**: We categorized the variables—poverty rates, Female Empowerment Index, and educational attainment—into three classes each. The classification of the Female Empowerment Index and poverty was based on the tertile distribution of the dataset. For educational attainment, we grouped the data into three categories: 0-1 years of education, 1-5 years of education, and over 5 years of education. 2. **Spatial Intersection**: Next, we spatially overlaid these classified variables with population data. This step identified the specific combination of variable classes for each population segment. 3. **Spatial Extraction**: We then extracted this overlaid data by administrative boundaries. This allowed us to quantify the population within each area, falling into each adaptive capacity category. Through this methodology, we generated a comprehensive dataset illustrating the distribution of the population by the three elements, encompassing every combination within each administrative region.`, am: `### የአየር ንብረት አደጋ ስጋት ጥሬ የአየር ንብረት አደጋዎችን ለማመንጨት ዝርዝር እና ተደጋጋሚ የሆነ የR የስራ ሂደት በ[AdaptationAtlas/Hazards](https://github.com/AdaptationAtlas/hazards) ይገኛል። ጥሬ የአየር ንብረት አደጋዎችን ወደ አጠቃላይ እና ሰብል-ተኮር አደጋዎች መቀየር የተከናወነው በተለየ፣ ነገር ግን እኩል ተደጋጋሚ በሆነ የR የስራ ሂደት ሲሆን ይህም በGitHub ፕሮጀክት [atlas/hazards_prototype](https://github.com/AdaptationAtlas/hazards_prototype) ይገኛል። ስጋትን የማስላት ሂደት በርካታ ወሳኝ ደረጃዎችን ያካትታል: 1. **ዓመታዊ ወይም ወቅታዊ ማጠቃለያ**: ጥሬ አደጋ መረጃ ከ[GGCMI ምዕራፍ 3 የበቆሎ ሰብል ቀን መቁጠሪያ](https://zenodo.org/records/5062513) ጋር ይስተካከላል፣ ከዚያም የአየር ንብረት አደጋዎች በዓመታዊ ወይም ወቅታዊ የጊዜ ገደቦች ተጠቃለዋል። የወደፊት የአትላስ ዝማኔዎች ሰብል-ተኮር የቀን መቁጠሪያዎችን ያካትታሉ። 2. **ክስተት**: በእያንዳንዱ ወቅት ወይም ዓመት በጊዜ ተከታታይ ውስጥ፣ የአደጋ ክስተትን (አሁን ያለ/የለም) በሦስት ከባድነት ደረጃዎች (መካከለኛ፣ ከባድ፣ ጽንፈኛ) እንመድባለን። በዚህ ማስታወሻ ደብተር ውስጥ፣ የአደጋ ከባድነት ወደ "ከባድ" ተቀምጧል። በዚህ ትንታኔ ውስጥ ጥቅም ላይ የዋሉት የተወሰኑ አደጋዎች የሚከተሉት ናቸው፦ - **ደረቅ** = የአፈር ውሃ ጭንቀት ቀናት ብዛት [NDWS](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). ከባድ ስጋት = NDWS > 20 ቀናት (በሁሉም ሰብሎች እና እንስሳት ላይ ተመሳሳይ ነው)። - **ሙቀት (ሰብሎች)** = ከፍተኛ የሙቀት መጠን > 35ºC የሆነባቸው ቀናት [NTx35](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). ከባድ ስጋት = NTx35 > 20 ቀናት (በሁሉም ሰብሎች ላይ ተመሳሳይ ነው)። - **ሙቀት (እንስሳት)** = የሙቀት እርጥበት መረጃ ጠቋሚ [THI](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). ከባድ ስጋት ለእንስሳት ክፍል የተለየ ነው፣ የ[Thorton et al. 2021](https://doi.org/10.1111/gcb.15825) ሠንጠረዥ 2ን ይመልከቱ። - **እርጥብ** = የውሃ መትረፍ ቀናት ብዛት [NDWL0](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). ከባድ ስጋት = NDWL0 > 5 ቀናት (በሁሉም ሰብሎች እና እንስሳት ላይ ተመሳሳይ ነው)። ስለ አደጋ ትርጓሜዎች እና ለከባድነት ክፍሎች ገደቦች ተጨማሪ ዝርዝሮች በአትላስ/አደጋዎች ዊኪ ውስጥ ይገኛሉ። የወደፊት 2024 የአትላስ ዝማኔዎች ሰብል-ተኮር ከፍተኛ የሙቀት መጠን ገደቦችን ያክላሉ እና ተጠቃሚዎች ስለ አደጋ ስጋቶች በበለጠ ዝርዝር እንዲመረምሩ የሚያስችል ማስታወሻ ደብተር ይፈጠራል። 3. **ስጋት**: የክስተት ስጋት ግምት ለማግኘት በጊዜ ተከታታይ ውስጥ በተካተቱት ዓመታት ወይም ወቅቶች ላይ የተመደቡትን አደጋዎች አማካይ እናደርጋለን። 4. **ድብልቅ ስጋቶች**: የተደባለቁ አደጋዎችን ስጋት ለመገምገም፣ ከደረቅ፣ ሙቀት እና እርጥብ ሁኔታዎች ጋር የተያያዙትን ስጋቶች እናባዛለን። ይህ ማባዛት በርካታ አደጋዎች ሊገጣጠሙ የሚችሉባቸውን አካባቢዎች ያሳያል፣ ይህም ለግብርና ምርት ከፍተኛ ስጋት ይፈጥራል። 5. **ከኢኮኖሚ መረጃ ጋር ውህደት**: በመጨረሻም፣ የተደባለቀውን የሰብል አደጋ ስጋት መረጃ ከሰብል ምርት ዋጋ መረጃ ጋር እናባዛለን። ለምሳሌ፣ አንድ ሰብል በ50% የማደጊያ ወቅቶች ውስጥ ለአደጋ ከተጋለጠ እና የምርት ዋጋው በዓመት 2 ሚሊዮን ዶላር ከሆነ፣ በአማካይ 1 ሚሊዮን ዶላር ዋጋ ያለው ምርት ለአደጋ ይጋለጣል። ከዚያም የተጋለጠው የምርት ዋጋ በአስተዳደር አካባቢዎች ተወስዶ በሰብል ምርት ላይ ሊከሰቱ የሚችሉ ኢኮኖሚያዊ ተፅእኖዎችን ለማመልከት ያስችላል። ### መላመድ አቅም እንደ መላመድ አቅም ተለዋዋጮች የሕዝብ ብዛት ስርጭትን ለማስላት የሚከተሉትን ደረጃዎች ተከትለናል፦ 1. **የውሂብ ምደባ**: ተለዋዋጮችን—የድህነት መጠኖች፣ የሴቶች አቅም ማጎልበት መረጃ ጠቋሚ፣ እና የትምህርት ደረጃ—እያንዳንዳቸውን በሦስት ክፍሎች መድበናል። የሴቶች አቅም ማጎልበት መረጃ ጠቋሚ እና የድህነት ምደባ በውሂብ ስብስቡ የሦስተኛ ደረጃ ስርጭት ላይ የተመሠረተ ነበር። ለትምህርት ደረጃ፣ ውሂቡን በሦስት ምድቦች አካፍለናል፦ 0-1 ዓመት ትምህርት፣ 1-5 ዓመት ትምህርት፣ እና ከ5 ዓመት በላይ ትምህርት። 2. **የቦታ መጋጠሚያ**: ቀጥሎም፣ እነዚህን የተመደቡ ተለዋዋጮች ከሕዝብ ብዛት መረጃ ጋር በቦታ ደረጃ አደራረብን ፈጠርን። ይህ ደረጃ ለእያንዳንዱ የሕዝብ ክፍል የተለዋዋጭ ክፍሎችን ልዩ ጥምረት ለይቷል። 3. **የቦታ ማውጣት**: ከዚያም ይህን የተደራረበ ውሂብ በአስተዳደር ወሰኖች አውጥተናል። ይህ በእያንዳንዱ አካባቢ ውስጥ ያለውን ሕዝብ ብዛት፣ በእያንዳንዱ የመላመድ አቅም ምድብ ውስጥ የሚወድቀውን ለመለካት አስችሎናል። በዚህ ዘዴ አማካኝነት፣ በእያንዳንዱ አስተዳደር ክልል ውስጥ እያንዳንዱን ጥምረት የሚያጠቃልል፣ በሦስቱ ንጥረ ነገሮች የሕዝብ ብዛት ስርጭትን የሚያሳይ አጠቃላይ የውሂብ ስብስብ አመንጭተናል።`, or: `### Hatattama Qilleensaa R hojii cimaa fi irra-deebiin hojjetamuu danda'u deetaa balaa qilleensaa dheedhii uumuuf [AdaptationAtlas/Hazards](https://github.com/AdaptationAtlas/hazards) irratti argama. Balaa qilleensaa dheedhii gara hatattama waliigalaa fi midhaan-midhaan geeddaruu hojii R adda ta'e, garuu wal-qixa irra-deebiin hojjetamuu danda'u fayyadamuun raawwatame, kan [atlas/hazards_prototype](https://github.com/AdaptationAtlas/hazards_prototype) GitHub pirojektii keessatti argamu danda'u. Hatattama shallaguu tarkaanfii hedduu kan of-keessaa qabu dha: 1. **Waliigala Waggaa ykn Gannaa**: Deetaan balaa dheedhii [GGCMI Phase 3 midhaan boqqoolloo yeroo](https://zenodo.org/records/5062513) wajjin wal-qixxeeffama, ergasii balaan qilleensaa yeroo waggaa ykn gannaa irratti waliigalfama. Fooyya'in Atlaas fuula duraa midhaan-midhaan yeroo of-keessaa qabaata. 2. **Uumama**: Ganna ykn waggaa hundaaf tartiiba yeroo keessatti, hatattama uumama balaa (jira/jiraachuu dhabuu) sadarkaa cimina sadii (giddu-galeessa, cimaa, baay'ee cimaa) keessatti ramadna. Hubadhu, kitaaba yaadannoo kana keessatti ciminni balaa "cimaa" jedhamee qabata. Balaan addaa qorannoo kana keessatti fayyadame kanneeni: - **Goga** = lakkoofsa guyyaa dhiibbaa bishaan lafaa [NDWS](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Hatattama cimaa = NDWS > 20 guyyaa (midhaanii fi horii hundaaf wal-fakkaata). - **Ho'a (midhaan)** = guyyaa ho'i ol'aanaan > 35ºC [NTx35](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Hatattama cimaa = NTx35 > 20 guyyaa (midhaan hundaaf wal-fakkaata). - **Ho'a (horii)** = qabxii jiidhina ho'aa [THI](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Hatattama cimaa gosa horiitiin adda, [Thorton et al. 2021](https://doi.org/10.1111/gcb.15825) keessaa Gabatee 2 ilaali. - **Jiidha** = lakkoofsa guyyaa bishaan guutummaa [NDWL0](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Hatattama cimaa = NDWL0 > 5 guyyaa (midhaanii fi horii hundaaf wal-fakkaata). Ibsa balaawwanii fi daangaa sadarkaa ciminaa irratti bal'inaan atlaas/hazards wiiwii keessatti argama. Fooyya'in Atlaas 2026tti itti-aanu daangaa ho'a ol'aanaa midhaan-midhaan dabala, kitaabni yaadannoo fayyadamtoonni hatattama balaa bal'inaan qorachuu danda'aniif ni uumama. 3. **Hatattama**: Hatattama uumama tilmaamuuf waggoota ykn gannawwan tartiiba yeroo keessatti ramadaman jiddu-galeessina. 4. **Hatattama Iddoo-Iddoo**: Hatattama balaa iddoo-iddoo tilmaamuuf, balaa goga, ho'a, fi jiidha wajjin wal-qabatan baay'isina. Baay'isinni kun balaan hedduun iddoo tokkotti walitti-dhufuu danda'an agarsiisa, bu'aa qonnaaf hatattama guddaa uuma. 5. **Deetaa Dinagdee wajjin Walitti-Makuu**: Dhuma irratti, deetaa hatattama balaa midhaanii iddoo-iddoo deetaa gatii oomisha midhaanii wajjin baay'isina. Fakkeenyaaf, yoo midhaan tokko gannaa guddinaa keessaa 50% keessatti balaaf saaxilamee fi gatii oomishaa $2M/waggaa yoo ta'e, giddu-galeessaan oomishaa $M1 balaaf saaxilama. Ergasiin gatii oomishaa saaxilame naannoo bulchiinsaatiin baafamee dhiibbaa dinagdee oomisha midhaanii irratti mul'isa. ### Dandeettii Madaqinsaa Hammi ummataa akkaataa jijjiiramoota dandeettii madaqinsaatti ramadamu shallaguuf tarkaanfii armaan gadii hordofne: 1. **Ramaddii Deetaa**: Jijjiiramoota—hammi hiyyummaa, Indeksii Abbaa-Humna Dubartii, fi sadarkaa barumsaa—ramaddii sadiitti qoqqoodne. Ramaddiin Indeksii Abbaa-Humna Dubartii fi hiyyummaa, raabsa sadarkaa-sadarkaa kuusaa deetaa irratti hundaa'e. Sadarkaa barumsaaf, deetaa ramaddii sadiitti gurmeessine: barumsaa waggaa 0-1, barumsaa waggaa 1-5, fi barumsaa waggaa 5 ol. 2. **Wal-qaxaamura Bakkaa**: Itti aansee, jijjiiramoota ramadamoo kana deetaa baay'ina ummataa irratti bakkaan wal-irra keenye. Tarkaanfiin kun qindaa'ina addaa ramaddii jijjiiramaa kutaa ummataa hundaaf adda baase. 3. **Baafata Bakkaa**: Sana booda deetaa wal-irra kenye kana daangaa bulchiinsaatiin baafne. Kun naannoo hunda keessatti, ramaddii dandeettii madaqinsaa hunda keessatti baay'ina ummataa shallaguu nu dandeessise. Malalee kana fayyadamuun, kuusaa deetaa bal'aa raabsa ummataa qabiyyee sadiitiin agarsiisu, naannoo bulchiinsa hunda keessatti qindaa'ina hunda kan of-keessaa qabu uumne.'`, ti: `### ሓደጋ ኩነታት ኣየር ዝርዝርን ምሉእ ተመላሊስካ ክትሰርሖ እትኽእልን ናይ R ኣገባብ ስራሕ ንጥሬ ሓዘናታት ኩነታት ኣየር ንምፍራይ ኣብ [AdaptationAtlas/Hazards](https://github.com/AdaptationAtlas/hazards) ይርከብ። እቲ ጥሬ ሓዘናታት ኩነታት ኣየር ናብ ኣጠቓላሊን ንሓሙም ዝተወሰነን ሓደጋ ምቕያር ብፍሉይ፡ ግን ከምቲ እቲ ኻልእ ምሉእ ተመላሊስካ ክትሰርሖ እትኽእል፡ ናይ R ኣገባብ ስራሕ ተፈጺሙ ኣሎ፡ እዚ ኣብቲ GitHub ፕሮጀክት [atlas/hazards_prototype](https://github.com/AdaptationAtlas/hazards_prototype) ክርከብ ይከኣል። እቲ ሓደጋ ምስላጥ ኣገባብ ብዙሓት ወሳኒ ስጉምትታት ዝሓቖፈ እዩ፦ 1. **ኣመታዊ ወይ ወቅታዊ ጠቅላላ**: ጥሬ ሓበሬታ ሓዘና ምስቲ [ናይ ሓሙም በቆሎ ካሌንደር GGCMI ደረጃ 3](https://zenodo.org/records/5062513) ይሰለፍ፡ ድሕሪኡ ሓዘናታት ኩነታት ኣየር ብኣመታዊ ወይ ብወቅታዊ ግዝያታት ተጠቓሊሎም። መጻኢ ዘምሕይሽ ናይቲ ኣትላስ ንሓሙም ዝተወሰኑ ካሌንደራት ከጠቓልል እዩ። 2. **ክስተት**: ንነፍሲ ወከፍ ወቅቲ ወይ ዓመት ኣብ ሰልፈ-ግዜ፡ ንሓደጋ ክስተት (ዘሎ/የለን) ኣብ ሰለስተ ደረጃታት ከቢድነት (ማእኸላይ፡ ከቢድ፡ ጽንፈኛ) ንምደቦም። ኣብዚ መዘከሪታ እዚ፡ ከቢድነት ሓዘና ናብ "ከቢድ" ተቐሚጡ ኣሎ። እቶም ኣብዚ ትንተና እዚ ጥቅም ልዕሊ ዝወደቑ ፍሉያት ሓዘናት እዚኦም እዮም፦ - **ነቃዕ** = ብዝሒ መዓልትታት ጭንቀት ማይ ሓመድ [NDWS](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). ከቢድ ሓደጋ = NDWS > 20 መዓልትታት (ንኹሉ ሓሙምን ማልሃን ሓደ እዩ)። - **ሙቐት (ሓሙም)** = መዓልትታት እቲ ዝለዓለ ሙቐት > 35ºC ዝኸውን [NTx35](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). ከቢድ ሓደጋ = NTx35 > 20 መዓልትታት (ንኹሉ ሓሙም ሓደ እዩ)። - **ሙቐት (ማልሃ)** = መለክዒ ሙቐትን ርጥበትን [THI](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). ከቢድ ሓደጋ ብዓይነት ማልሃ ይፍለል፡ ንሰሌዳ 2 [Thorton et al. 2021](https://doi.org/10.1111/gcb.15825) ርአ። - **ርጥበት** = ብዝሒ መዓልትታት ማይ ምልላፍ [NDWL0](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). ከቢድ ሓደጋ = NDWL0 > 5 መዓልትታት (ንኹሉ ሓሙምን ማልሃን ሓደ እዩ)። ብዝሒ ዝርዝራት ኣብ ሓዘናት ትርጉማትን ደረጃታት ከቢድነት ክፍልታትን ኣብቲ ኣትላስ/ሓዘናት ዊኪ ክርከብ ይከኣል። መጻኢ 2024 ዘምሕይሽ ኣትላስ ንሓሙም ዝተወሰነ ዝለዓለ ሙቐት ደረጃታት ከውስኽ ኮይኑ፡ ሓደ መዘከሪታ ተጠቀምቲ ንሓደጋታት ብዝያዳ ዝርዝር ክዳስስዎ ዘኽእሎም ክፍጠር እዩ። 3. **ሓደጋ**: ነቶም ብዘመናት ወይ ወቅትታት ተሸፊኖም ኣብቲ ሰልፈ-ግዜ ዝርከቡ ዝተመደቡ ሓዘናት ንማእኸላይ ንወስዶም፡ ንሓደጋ ክስተት ንምግማት። 4. **ውሁድ ሓደጋታት**: ነቲ ናይ ውሁድ ሓዘናት ሓደጋ ንምግምጋም፡ ነቶም ምስ ነቃዕ፡ ሙቐት፡ ከምኡውን ርጥበት ኩነታት ዝተተሓሓዙ ሓደጋታት ነባዝዖም። እዚ ምብዛዕ እዚ ብዙሓት ሓዘናት ክራኸቡ ዝኽእሉሉ ከባቢታት ዘርኢ እዩ፡ ነቲ ናይ ሕርሻ ውጽኢት ዝያዳ ሓደጋ ዘምጽኡ። 5. **ምስ ኢኮኖሚያዊ ሓበሬታ ውህደት**: ኣብ መወዳእታ፡ ነቲ ውሁድ ሓደጋ ሓሙም ሓበሬታ ምስ ዋጋ ምርት ሓሙም ሓበሬታ ነባዝዖ። ንኣብነት፡ ሓደ ሓሙም ኣብ 50% ናይቲ ዝዕብለሉ ወቅትታት ንሓደጋ እንተተጋሊጡን ዋጋ ምርቱ ኣመታዊ $2M እንተኾይኑን ሽዑ፡ ብማእኸላይ $1M ካብቲ ምርት ንሓደጋ ተጋሊጡ እዩ። እቲ ተጋሊጡ ዘሎ ዋጋ ምርት ድሕሪኡ ብምምሕዳር ከባቢታት ይውጽእ፡ ኣብ ምርት ሓሙም ክህሉ ዝኽእል ኢኮኖሚያዊ ጽልዋ ንምርኣይ። ### ናይ ምምሕያሽ ክእለት ነቲ ብመሰረት ናይ ምምሕያሽ ክእለት ተባሂሎም ዘለዉ ተባሂሎም ዘለዉ ተለዋዋጥታት ምቅጫፍ ህዝቢ ንምስላጥ፡ ነዚ ዝስዕቡ ስጉምትታት ተኸቲልና፦ 1. **ምደባ ሓበሬታ**: ነቶም ተለዋዋጥታት—ደረጃታት ድኽነት፡ መለክዒ ምሕያል ኣንስተይቲ፡ ከምኡውን ደረጃ ትምህርቲ—ንነፍሲ ወከፍ ኣብ ሰለስተ ክፍልታት ከፊልናዮም። እቲ ናይ መለክዒ ምሕያል ኣንስተይቲን ድኽነትን ምደባ ኣብቲ ሰለስተ ክፋል ምቅጫፍ ናይቲ ስብስብ ሓበሬታ ተመርኲሱ እዩ። ንደረጃ ትምህርቲ፡ ነቲ ሓበሬታ ኣብ ሰለስተ ዓይነት ከፊልናዮ፦ 0-1 ዓመት ትምህርቲ፡ 1-5 ዓመት ትምህርቲ፡ ከምኡውን ልዕሊ 5 ዓመት ትምህርቲ። 2. **ህላዌ ራኽበ-ቦታ**: ድሕሪኡ፡ ነዚኦም ዝተመደቡ ተለዋዋጥታት ምስ ሓበሬታ ህዝቢ ብህላዌ ኣደራረብናዮም። እዚ ስጉምቲ እዚ ንነፍሲ ወከፍ ክፋል ህዝቢ እቲ ፍሉይ ውሕደት ናይቶም ተለዋዋጥታት ክፍልታት ለሊሁ። 3. **ህላዌ ምውጻእ**: ድሕሪኡ ነዚ ኣደራረብ ዝተገብረሎም ሓበሬታ ብምምሕዳር ዶባት ኣውጺእናዮም። እዚ ኣብ ነፍሲ ወከፍ ከባቢ ኣብ ነፍሲ ወከፍ ናይ ምምሕያሽ ክእለት ዓይነት ዝወድቕ ህዝቢ ንምቍጸር ኣኽኢሉና። በዚ ኣገባብ እዚ፡ ነቲ በቶም ሰለስተ ነገራት ምቅጫፍ ህዝቢ ዘርኢ፡ ኣብ ነፍሲ ወከፍ ምምሕዳራዊ ክፍለ-ሃገር ንዅሉ ውሕደታት ዘጠቓልል ምሉእ ስብስብ ሓበሬታ ኣፍሪኡና።`, so: `### Khatarta Cimilada Hab R oo faahfaahsan oo la soo koobi karo oo lagu abuurayo xogta khatarta cimilada ee ceyriinka ah ayaa laga heli karaa [AdaptationAtlas/Hazards](https://github.com/AdaptationAtlas/hazards). U beddelka khataraha cimilada ee ceyriinka ah ee khataro guud iyo kuwo dalag gaar ah waxaa lagu gaadhay iyadoo la adeegsanayo hab R oo kala duwan, laakiin si isku mid ah la soo koobi karo, kaas oo laga heli karo mashruuca GitHub [atlas/hazards_prototype](https://github.com/AdaptationAtlas/hazards_prototype). Habka loo xisaabiyo khatartu waxay ka kooban tahay dhowr tillaabo oo muhiim ah: 1. **Soo koobid Sannadeed ama Xilliyeed**: Xogta khatarta ceyriinka ah waxaa la jaanqaadiyaa [jadwalka dalagga hadhuudhka ee GGCMI Wajiga 3](https://zenodo.org/records/5062513), ka dibna khataraha cimilada waxaa lagu soo koobaa miisaan sannadeed ama xilliyeed. Cusboonaysiinta mustaqbalka ee Atlastu waxay ku dari doontaa jadwal dalag gaar ah. 2. **Dhacdo**: Xilli ama sannad kasta oo ku jira taxanaha wakhtiga, waxaan kala saarnaa khatarta dhacdo khatareed (jirta/ma jirto) saddex heer oo cufnaan ah (dhexdhexaad, daran, aad u daran). Ogow, cufnaanta khatarta waxay ku go'an tahay "daran" buuggan xusuus qorka. Khataraha gaarka ah ee lagu isticmaalay falanqayntan waa: - **Qallayl** = tirada maalmaha cadaadiska biyaha ciidda [NDWS](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Khatar daran = NDWS > 20 maalmood (isku mid dhammaan dalagyada iyo xoolaha). - **Kuleyl (dalagyo)** = maalmaha heerkulka ugu sarreeya > 35ºC [NTx35](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Khatar daran = NTx35 > 20 maalmood (isku mid dhammaan dalagyada). - **Kuleyl (xoolo)** = tusmaha qoyaanka kuleylka [THI](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Khatarta daran waa mid gaar u ah nooca xoolaha, eeg Shaxda 2 ee [Thorton et al. 2021](https://doi.org/10.1111/gcb.15825). - **Qoyaan** = tirada maalmaha biyo-fadhiista [NDWL0](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Khatar daran = NDWL0 > 5 maalmood (isku mid dhammaan dalagyada iyo xoolaha). Faahfaahin dheeraad ah oo ku saabsan qeexitaannada khatarta iyo heerarka loogu talagalay fasallada cufnaanta waxaa laga heli karaa wiki atalas/khataraha. Cusboonaysiinta mustaqbalka 2024 ee Atlastu waxay ku daraysaa heerarka heerkulka ugu sarreeya ee dalag gaar ah waxaana la abuuri doonaa buug xusuus qor ah si ugu oggolaado isticmaalayaashu inay khataraha u sahamiyaan si faahfaahsan. 3. **Khatar**: Waxaan celcelisnaa khataraha kala soocan sannadaha ama xilliyada ay koobayso taxanaha-wakhtiga si aan u helno qiyaas khatarta dhacdo. 4. **Khataraha Isku-dhafan**: Si loo qiimeeyo khatarta khataraha isku-dhafan, waxaan ku dhufannaa khataraha la xidhiidha xaaladaha qallayl, kuleyl, iyo qoyaan. Isku-dhufashadani waxay iftiiminaysaa meelaha ay khataro badan isku iman karaan, taasoo khatar weyn ku ah wax-soosaarka beeraha. 5. **Isku-dhafka Xogta Dhaqaale**: Ugu dambeyntii, waxaan ku dhufannaa xogta khatarta dalagga isku-dhafan ee xogta qiimaha wax-soosaarka dalagga. Tusaale ahaan, haddii dalag uu soo gaadho khatar 50% xilliyada beerashada qiimaha wax-soosaarkuna yahay $2M/sannadka, markaa celcelis ahaan, $1M oo wax-soosaar ah ayaa soo gaadha khatarta. Qiimaha wax-soosaarka ee soo gaadhay ayaa markaa laga soo saaraa aagagga maamulka si loo muujiyo saamaynta dhaqaale ee iman karta ee wax-soosaarka dalagga. ### Awood Laqabsi Si loo xisaabiyo qaybinta dadweynaha marka loo eego doorsoomayaasha awoodda laqabsiga, waxaan raacnay tillaabooyinkan: 1. **Kala-soocidda Xogta**: Waxaan u kala saarnay doorsoomayaasha—heerarka saboolnimada, Tusmaha Awood-siinta Haweenka, iyo heerka waxbarasho—saddex fasalkood midkiiba. Kala-soocidda Tusmaha Awood-siinta Haweenka iyo saboolnimada waxay ku salaysnayd qaybinta saddexaad ee xog-ururinta. Heerka waxbarashada, waxaan u kooxaynnay xogta saddex qaybood: 0-1 sano oo waxbarasho ah, 1-5 sano oo waxbarasho ah, iyo in ka badan 5 sano oo waxbarasho ah. 2. **Isku-dhafka Goobta**: Marka xigta, waxaan goob ahaan isku dul saarnay doorsoomayaashan kala soocan ee xogta dadweynaha. Tallaabadani waxay cadeysay isku-dhafka gaarka ah ee fasallada doorsoomayaasha qayb kasta oo dadweynaha ah. 3. **Soo-saaridda Goobta**: Kadibna waxaan soo saarnay xogtan isku-dul-saaran iyadoo la tixraacayo xuduudaha maamulka. Tani waxay noo oggolaashay inaan tirinno dadka ku nool aag kasta, oo ku dhacaya qayb kasta oo ka mid ah awoodda laqabsiga. Habkani, waxaan soo saarnay xog ururin dhammaystiran oo muujinaysa qaybinta dadweynaha saddexda qaybood, oo koobaysa isku-dhafka kasta oo ka jira gobol maamul kasta dhexdiisa.`, af: `### Khatarta Cimilada Hab R oo faahfaahsan oo la soo koobi karo oo lagu abuurayo xogta khatarta cimilada ee ceyriinka ah ayaa laga heli karaa [AdaptationAtlas/Hazards](https://github.com/AdaptationAtlas/hazards). U beddelka khataraha cimilada ee ceyriinka ah ee khataro guud iyo kuwo dalag gaar ah waxaa lagu gaadhay iyadoo la adeegsanayo hab R oo kala duwan, laakiin si isku mid ah la soo koobi karo, kaas oo laga heli karo mashruuca GitHub [atlas/hazards_prototype](https://github.com/AdaptationAtlas/hazards_prototype). Habka loo xisaabiyo khatartu waxay ka kooban tahay dhowr tillaabo oo muhiim ah: 1. **Soo koobid Sannadeed ama Xilliyeed**: Xogta khatarta ceyriinka ah waxaa la jaanqaadiyaa [jadwalka dalagga hadhuudhka ee GGCMI Wajiga 3](https://zenodo.org/records/5062513), ka dibna khataraha cimilada waxaa lagu soo koobaa miisaan sannadeed ama xilliyeed. Cusboonaysiinta mustaqbalka ee Atlastu waxay ku dari doontaa jadwal dalag gaar ah. 2. **Dhacdo**: Xilli ama sannad kasta oo ku jira taxanaha wakhtiga, waxaan kala saarnaa khatarta dhacdo khatareed (jirta/ma jirto) saddex heer oo cufnaan ah (dhexdhexaad, daran, aad u daran). Ogow, cufnaanta khatarta waxay ku go'an tahay "daran" buuggan xusuus qorka. Khataraha gaarka ah ee lagu isticmaalay falanqayntan waa: - **Qallayl** = tirada maalmaha cadaadiska biyaha ciidda [NDWS](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Khatar daran = NDWS > 20 maalmood (isku mid dhammaan dalagyada iyo xoolaha). - **Kuleyl (dalagyo)** = maalmaha heerkulka ugu sarreeya > 35ºC [NTx35](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Khatar daran = NTx35 > 20 maalmood (isku mid dhammaan dalagyada). - **Kuleyl (xoolo)** = tusmaha qoyaanka kuleylka [THI](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Khatarta daran waa mid gaar u ah nooca xoolaha, eeg Shaxda 2 ee [Thorton et al. 2021](https://doi.org/10.1111/gcb.15825). - **Qoyaan** = tirada maalmaha biyo-fadhiista [NDWL0](https://github.com/AdaptationAtlas/hazards/wiki/Hazards-definitions). Khatar daran = NDWL0 > 5 maalmood (isku mid dhammaan dalagyada iyo xoolaha). Faahfaahin dheeraad ah oo ku saabsan qeexitaannada khatarta iyo heerarka loogu talagalay fasallada cufnaanta waxaa laga heli karaa wiki atalas/khataraha. Cusboonaysiinta mustaqbalka 2024 ee Atlastu waxay ku daraysaa heerarka heerkulka ugu sarreeya ee dalag gaar ah waxaana la abuuri doonaa buug xusuus qor ah si ugu oggolaado isticmaalayaashu inay khataraha u sahamiyaan si faahfaahsan. 3. **Khatar**: Waxaan celcelisnaa khataraha kala soocan sannadaha ama xilliyada ay koobayso taxanaha-wakhtiga si aan u helno qiyaas khatarta dhacdo. 4. **Khataraha Isku-dhafan**: Si loo qiimeeyo khatarta khataraha isku-dhafan, waxaan ku dhufannaa khataraha la xidhiidha xaaladaha qallayl, kuleyl, iyo qoyaan. Isku-dhufashadani waxay iftiiminaysaa meelaha ay khataro badan isku iman karaan, taasoo khatar weyn ku ah wax-soosaarka beeraha. 5. **Isku-dhafka Xogta Dhaqaale**: Ugu dambeyntii, waxaan ku dhufannaa xogta khatarta dalagga isku-dhafan ee xogta qiimaha wax-soosaarka dalagga. Tusaale ahaan, haddii dalag uu soo gaadho khatar 50% xilliyada beerashada qiimaha wax-soosaarkuna yahay $2M/sannadka, markaa celcelis ahaan, $1M oo wax-soosaar ah ayaa soo gaadha khatarta. Qiimaha wax-soosaarka ee soo gaadhay ayaa markaa laga soo saaraa aagagga maamulka si loo muujiyo saamaynta dhaqaale ee iman karta ee wax-soosaarka dalagga. ### Awood Laqabsi Si loo xisaabiyo qaybinta dadweynaha marka loo eego doorsoomayaasha awoodda laqabsiga, waxaan raacnay tillaabooyinkan: 1. **Kala-soocidda Xogta**: Waxaan u kala saarnay doorsoomayaasha—heerarka saboolnimada, Tusmaha Awood-siinta Haweenka, iyo heerka waxbarasho—saddex fasalkood midkiiba. Kala-soocidda Tusmaha Awood-siinta Haweenka iyo saboolnimada waxay ku salaysnayd qaybinta saddexaad ee xog-ururinta. Heerka waxbarashada, waxaan u kooxaynnay xogta saddex qaybood: 0-1 sano oo waxbarasho ah, 1-5 sano oo waxbarasho ah, iyo in ka badan 5 sano oo waxbarasho ah. 2. **Isku-dhafka Goobta**: Marka xigta, waxaan goob ahaan isku dul saarnay doorsoomayaashan kala soocan ee xogta dadweynaha. Tallaabadani waxay cadeysay isku-dhafka gaarka ah ee fasallada doorsoomayaasha qayb kasta oo dadweynaha ah. 3. **Soo-saaridda Goobta**: Kadibna waxaan soo saarnay xogtan isku-dul-saaran iyadoo la tixraacayo xuduudaha maamulka. Tani waxay noo oggolaashay inaan tirinno dadka ku nool aag kasta, oo ku dhacaya qayb kasta oo ka mid ah awoodda laqabsiga. Habkani, waxaan soo saarnay xog ururin dhammaystiran oo muujinaysa qaybinta dadweynaha saddexda qaybood, oo koobaysa isku-dhafka kasta oo ka jira gobol maamul kasta dhexdiisa.` }} } })5d:T11c27,nbText = { // text in the notebook // recommendation: only use objects for better tab-completion return { supportNbText: { ...nbTextSupportNbText.supportNbText }, frontMatter: { heroImage: { url: { en: await FileAttachment("Evaluate-climate-risks.webp").url(), am: await FileAttachment("Evaluate-climate-risks-am.jpg").url(), or: await FileAttachment("Evaluate-climate-risks.webp").url(), ti: await FileAttachment("Evaluate-climate-risks.webp").url(), so: await FileAttachment("Evaluate-climate-risks.webp").url(), af: await FileAttachment("Evaluate-climate-risks.webp").url() } } }, missingMapDataBlurb: { en: `Grey regions signal lack of :::data_label::: data.`, am: `ግራጫ ክልሎች :::data_label::: ውሂብ እጥረትን ያመለክታሉ።`, or: `Maddaawwan diimaa :::data_label::: data hin argamuu agarsiisu.`, ti: `ሕጹጽ ክልላት :::data_label::: ውሂብ ዘይምህላው የምልክት።`, so: `Gobollada cirdan waxay tilmaamaan la'aanta :::data_label::: data.`, af: `Qadaanoo buriitaan :::data_label::: data hin argamuu agarsiisa.` }, export: { chooseFormat: { en: "Choose format...", am: "ቅርጹን ይምረጡ...", or: "Qormaata filadhaa...", ti: "ሓይሊ ምረጹ...", so: "Dooro nooca...", af: "Qormaata filadhaa..." }, png: { en: "PNG (Image)", am: "PNG (ምስል)", or: "PNG (Suura)", ti: "PNG (ምስል)", so: "PNG (Sawir)", af: "PNG (Suura)" }, pngHighQuality: { en: "PNG (High Quality)", am: "PNG (ከፍተኛ ጥራት)", or: "PNG (Qulqullina guddaa)", ti: "PNG (ላቀ ጥራት)", so: "PNG (Tayada sare)", af: "PNG (Qulqullina guddaa)" }, jpeg: { en: "JPEG (Image)", am: "JPEG (ምስል)", or: "JPEG (Suura)", ti: "JPEG (ምስል)", so: "JPEG (Sawir)", af: "JPEG (Suura)" }, jpegSmaller: { en: "JPEG (Smaller File)", am: "JPEG (ትንሽ ፋይል)", or: "JPEG (Faayili xiqqaa)", ti: "JPEG (ንእሽቶ ፋይል)", so: "JPEG (Faylka yar)", af: "JPEG (Faayili xiqqaa)" }, svg: { en: "SVG (Vector)", am: "SVG (ቬክተር)", or: "SVG (Veektora)", ti: "SVG (ቬክተር)", so: "SVG (Vector)", af: "SVG (Veektora)" }, pdf: { en: "PDF (Print to save)", am: "PDF (ለማተም ይታተሙ)", or: "PDF (Maxxansuuf barreessi)", ti: "PDF (ንምትሕታም ምትሕታም)", so: "PDF (Daabac si aad kaydsato)", af: "PDF (Maxxansuuf barreessi)" }, csv: { en: "CSV (Data)", am: "CSV (ውሂብ)", or: "CSV (Daata)", ti: "CSV (ውሂብ)", so: "CSV (Xogta)", af: "CSV (Daata)" }, json: { en: "JSON (Data)", am: "JSON (ውሂብ)", or: "JSON (Daata)", ti: "JSON (ውሂብ)", so: "JSON (Xogta)", af: "JSON (Daata)" }, csvSuccess: { en: "CSV export successful", am: "የCSV ምውጣት ተሳክቷል", or: "Ba'e CSV milkooftee", ti: "ውጻኢ CSV ዓወት ኣለዎ", so: "Dhoofinta CSV waxay ku guulaysatay", af: "Ba'e CSV milkooftee" }, csvFailed: { en: "CSV export failed", am: "የCSV ምውጣት አልተሳካም", or: "Ba'e CSV didde", ti: "ውጻኢ CSV ኣይዓወተን", so: "Dhoofinta CSV way fashilantay", af: "Ba'e CSV didde" }, jsonSuccess: { en: "JSON export successful", am: "የJSON ምውጣት ተሳክቷል", or: "Ba'e JSON milkooftee", ti: "ውጻኢ JSON ዓወት ኣለዎ", so: "Dhoofinta JSON waxay ku guulaysatay", af: "Ba'e JSON milkooftee" }, jsonFailed: { en: "JSON export failed", am: "የJSON ምውጣት አልተሳካም", or: "Ba'e JSON didde", ti: "ውጻኢ JSON ኣይዓወተን", so: "Dhoofinta JSON way fashilantay", af: "Ba'e JSON didde" }, exportSuccess: { en: "Export successful", am: "ምውጣት ተሳክቷል", or: "Ba'e milkooftee", ti: "ውጻኢ ዓወት ኣለዎ", so: "Dhoofinta waxay ku guulaysatay", af: "Ba'e milkooftee" }, exportFailed: { en: "Export failed", am: "ምውጣት አልተሳካም", or: "Ba'e didde", ti: "ውጻኢ ኣይዓወተን", so: "Dhoofinta way fashilantay", af: "Ba'e didde" }, downloadFailed: { en: "Download failed", am: "ማውረድ አልተሳካም", or: "Fe'uu didde", ti: "ውርዲ ኣይዓወተን", so: "Soo dejinta way fashilantay", af: "Fe'uu didde" }, printDialogOpened: { en: "Print dialog opened – use 'Save as PDF' to save", am: "የማተም መስኮት ተከፈተ – ለማስቀጠል 'በPDF አስቀምጥ' ይጠቀሙ", or: "Tuutaa barreessuu baname – 'PDFitti qabi' fayyadamaa", ti: "ዊንዶ ምትሕታም ተኸፊቱ – ንምሕላው 'ከም PDF ኣስቀምጥ' ተጠቐም", so: "Daabacaadda waa la furay – isticmaal 'Kaydi sida PDF' si aad u kaydsato", af: "Tuutaa barreessuu baname – 'PDFitti qabi' fayyadamaa" }, noDataCsv: { en: "No data available for CSV export", am: "ለCSV ምውጣት ውሂብ የለም", or: "Daataan CSV ba'uuuf hin jiru", ti: "ንውጻኢ CSV ውሂብ የለን", so: "Xogta ma jirto dhoofinta CSV", af: "Daataan CSV ba'uuuf hin jiru" }, chartNotFound: { en: "Chart not found. Ensure the chart is rendered above this export cell.", am: "ግራፍ አልተገኘም። ግራፉ ከዚህ የምውጣት ህዋስ በላይ መገናኛ እንደሆነ ያረጋግጡ።", or: "Chaartii hin argamne. Chaartii kutaa ba'aa kana olitti mul'ata jiraachuu hubadhaa.", ti: "ግራፍ ኣይተረኽበን። ግራፉ ኣብ ላይ ናይዚ ውጻኢ ዋንጫ ምስላ ከም ዝወሃብ ኣረጋግጹ።", so: "Shaashaddu ma la helin. Hubi in shaashaddu ka sarreysa xaggan dhoofinta lagu muujiyay.", af: "Chaartii hin argamne. Chaartii kutaa ba'aa kana olitti mul'ata jiraachuu hubadhaa." }, icicleNotFound: { en: "Icicle chart not found. Ensure the chart is rendered above this export cell.", am: "የአይሲክል ግራፍ አልተገኘም። ግራፉ ከዚህ የምውጣት ህዋስ በላይ መገናኛ እንደሆነ ያረጋግጡ።", or: "Chaartii icicle hin argamne. Chaartii kutaa ba'aa kana olitti mul'ata jiraachuu hubadhaa.", ti: "ግራፍ ኣይሲክል ኣይተረኽበን። ግራፉ ኣብ ላይ ናይዚ ውጻኢ ዋንጫ ምስላ ከም ዝወሃብ ኣረጋግጹ።", so: "Shaashada icicle ma la helin. Hubi in shaashaddu ka sarreysa xaggan dhoofinta lagu muujiyay.", af: "Chaartii icicle hin argamne. Chaartii kutaa ba'aa kana olitti mul'ata jiraachuu hubadhaa." }, hazardChartNotFound: { en: "Chart not found. Please make sure the chart is rendered above this export cell.", am: "ግራፍ አልተገኘም። ግራፉ ከዚህ የምውጣት ህዋስ በላይ መገናኛ እንደሆነ ያረጋግጡ።", or: "Chaartii hin argamne. Chaartii kutaa ba'aa kana olitti mul'ata jiraachuu hubadhaa.", ti: "ግራፍ ኣይተረኽበን። ግራፉ ኣብ ላይ ናይዚ ውጻኢ ዋንጫ ምስላ ከም ዝወሃብ ኣረጋግጹ።", so: "Shaashaddu ma la helin. Hubi in shaashaddu ka sarreysa xaggan dhoofinta lagu muujiyay.", af: "Chaartii hin argamne. Chaartii kutaa ba'aa kana olitti mul'ata jiraachuu hubadhaa." }, mapNotFound: { en: "Map not found. Please make sure the map is rendered above this cell.", am: "ካርታ አልተገኘም። ካርታው ከዚህ ህዋስ በላይ መገናኛ እንደሆነ ያረጋግጡ።", or: "Maappii hin argamne. Maappii kutaa kana olitti mul'ata jiraachuu hubadhaa.", ti: "ካርታ ኣይተረኽበን። ካርታ ኣብ ላይ ናይዚ ዋንጫ ምስላ ከም ዝወሃብ ኣረጋግጹ።", so: "Khariidaddu ma la helin. Hubi in khariidaddu ka sarreysa xaggan lagu muujiyay.", af: "Maappii hin argamne. Maappii kutaa kana olitti mul'ata jiraachuu hubadhaa." }, titleHazardVop: { en: "Export Hazard VoP Chart:", am: "የአደጋ VoP ግራፍ ምውጣት:", or: "Chaartii Balaa VoP Ba'aa:", ti: "ውጻኢ ግራፍ ሓደገኛ VoP:", so: "Soo deji Shaashada Khatarta VoP:", af: "Chaartii Balaa VoP Ba'aa:" }, titleCropRisk: { en: "Export Crop Risk Chart:", am: "የዝርያ አደጋ ግራፍ ምውጣት:", or: "Chaartii Balaa Beerii Ba'aa:", ti: "ውጻኢ ግራፍ ሓደገኛ ኣትክልቲ:", so: "Soo deji Shaashada Khatarta Beeraha:", af: "Chaartii Balaa Beerii Ba'aa:" }, titleLivestockRisk: { en: "Export Livestock Risk Chart:", am: "የእንስሳት አደጋ ግራፍ ምውጣት:", or: "Chaartii Balaa Beeyladaa Ba'aa:", ti: "ውጻኢ ግራፍ ሓደገኛ እንስሳ:", so: "Soo deji Shaashada Khatarta Xoolaha:", af: "Chaartii Balaa Beeyladaa Ba'aa:" }, titleIcicle: { en: "Export Adaptive Capacity Icicle:", am: "የመስተካከል አቅም አይሲክል ምውጣት:", or: "Icicle Awwaalii Dabalataa Ba'aa:", ti: "ውጻኢ ኣይሲክል ናይ ምምላስ ክእለት:", so: "Soo deji Icicle Awoodda Isbeddelka:", af: "Icicle Awwaalii Dabalataa Ba'aa:" }, titleMap: { en: "Download Map:", am: "ካርታ አውርድ:", or: "Maappii Fe'aa:", ti: "ካርታ ኣውርድ:", so: "Soo dejinta Khariidadda:", af: "Maappii Fe'aa:" }, titleGeoImpactMap: { en: "Export Geographic Impact Map:", am: "የጂኦግራፊ ተጽእኖ ካርታ ምውጣት:", or: "Maappii Dhiibbaa Geografii Ba'aa:", ti: "ውጻኢ ካርታ ጂኦግራፊያዊ ተጽእኖ:", so: "Soo deji Khariidadda Saameynta Juqraafiyada:", af: "Maappii Dhiibbaa Geografii Ba'aa:" }, titleAdaptiveCapacityMap: { en: "Export Adaptive Capacity Map:", am: "የመስተካከል አቅም ካርታ ምውጣት:", or: "Maappii Awwaalii Dabalataa Ba'aa:", ti: "ውጻኢ ካርታ ናይ ምምላስ ክእለት:", so: "Soo deji Khariidadda Awoodda Isbeddelka:", af: "Maappii Awwaalii Dabalataa Ba'aa:" }, geoImpactMapNotFound: { en: "Geographic Impact map not found. Please make sure the map is rendered and this export cell references plotChoroplethGeoImpact.", am: "የጂኦግራፊ ተጽእኖ ካርታ አልተገኘም። ካርታው መገናኛ እንደሆነ እና ይህ የምውጣት ህዋስ plotChoroplethGeoImpact እንደሚያጣራ ያረጋግጡ።", or: "Maappii dhiibbaa geografii hin argamne. Maappii mul'ata jiraachuu fi kutaa ba'aa kana plotChoroplethGeoImpact qabachuu hubadhaa.", ti: "ካርታ ጂኦግራፊያዊ ተጽእኖ ኣይተረኽበን። ካርታ ምስላ ከም ዝወሃብ እና እዚ ውጻኢ ዋንጫ plotChoroplethGeoImpact ከም ዝጠራጠር ኣረጋግጹ።", so: "Khariidadda saameynta juqraafiyada ma la helin. Hubi in khariidaddu lagu muujiyay oo xaggan dhoofintan plotChoroplethGeoImpact la tixraacayo.", af: "Maappii dhiibbaa geografii hin argamne. Maappii mul'ata jiraachuu fi kutaa ba'aa kana plotChoroplethGeoImpact qabachuu hubadhaa." }, adaptiveCapacityMapNotFound: { en: "Adaptive Capacity visualization not found. Please make sure the visualization is rendered and this export cell references plotChoroplethAdaptiveCapacity1.", am: "የመስተካከል አቅም ምስላ አልተገኘም። ምስላው መገናኛ እንደሆነ እና ይህ የምውጣት ህዋስ plotChoroplethAdaptiveCapacity1 እንደሚያጣራ ያረጋግጡ።", or: "Agarsiisa awwaalii dabalataa hin argamne. Agarsiisa mul'ata jiraachuu fi kutaa ba'aa kana plotChoroplethAdaptiveCapacity1 qabachuu hubadhaa.", ti: "ምስላ ናይ ምምላስ ክእለት ኣይተረኽበን። ምስላ ከም ዝወሃብ እና እዚ ውጻኢ ዋንጫ plotChoroplethAdaptiveCapacity1 ከም ዝጠራጠር ኣረጋግጹ።", so: "Muujinta awoodda isbeddelka ma la helin. Hubi in muujintu lagu muujiyay oo xaggan dhoofintan plotChoroplethAdaptiveCapacity1 la tixraacayo.", af: "Agarsiisa awwaalii dabalataa hin argamne. Agarsiisa mul'ata jiraachuu fi kutaa ba'aa kana plotChoroplethAdaptiveCapacity1 qabachuu hubadhaa." }, geojsonSuccess: { en: "GeoJSON export successful", am: "የGeoJSON ምውጣት ተሳክቷል", or: "Ba'e GeoJSON milkooftee", ti: "ውጻኢ GeoJSON ዓወት ኣለዎ", so: "Dhoofinta GeoJSON waxay ku guulaysatay", af: "Ba'e GeoJSON milkooftee" }, geojsonFailed: { en: "GeoJSON export failed", am: "የGeoJSON ምውጣት አልተሳካም", or: "Ba'e GeoJSON didde", ti: "ውጻኢ GeoJSON ኣይዓወተን", so: "Dhoofinta GeoJSON way fashilantay", af: "Ba'e GeoJSON didde" }, geojsonOption: { en: "GeoJSON (Geographic Data)", am: "GeoJSON (የጂኦግራፊ ውሂብ)", or: "GeoJSON (Daata Geografii)", ti: "GeoJSON (ውሂብ ጂኦግራፊ)", so: "GeoJSON (Xogta Juqraafiyada)", af: "GeoJSON (Daata Geografii)" }, hintGeojson: { en: "GeoJSON: Geographic data with geometry (for GIS)", am: "GeoJSON: የጂኦግራፊ ውሂብ ከጂኦሜትሪ ጋር (ለGIS)", or: "GeoJSON: Daata geografii geomeetirii wajjin (GIS f)", ti: "GeoJSON: ውሂብ ጂኦግራፊ ምስ ጂኦሜትሪ (ንGIS)", so: "GeoJSON: Xogta juqraafiyada leh joomertari (GIS)", af: "GeoJSON: Daata geografii geomeetirii wajjin (GIS f)" }, hintPngJpegSvg: { en: "PNG, JPEG, SVG: Chart image", am: "PNG, JPEG, SVG: የግራፍ ምስል", or: "PNG, JPEG, SVG: Suura chaartii", ti: "PNG, JPEG, SVG: ምስል ግራፍ", so: "PNG, JPEG, SVG: Sawirka shaashada", af: "PNG, JPEG, SVG: Suura chaartii" }, hintPdf: { en: "PDF: Opens print dialog (use Save as PDF)", am: "PDF: የማተም መስኮት ተከፋፍሏል (በPDF አስቀምጥ ይጠቀሙ)", or: "PDF: Tuutaa barreessuu bana (PDFitti qabi fayyadamaa)", ti: "PDF: ዊንዶ ምትሕታም ተኸፊቱ (ከም PDF ኣስቀምጥ ተጠቐም)", so: "PDF: Daabacaadda way furan tahay (isticmaal Kaydi sida PDF)", af: "PDF: Tuutaa barreessuu bana (PDFitti qabi fayyadamaa)" }, hintCsvJson: { en: "CSV, JSON: Tabular data", am: "CSV, JSON: የሠንጠረዥ ውሂብ", or: "CSV, JSON: Daata jedhee", ti: "CSV, JSON: ውሂብ ሰንጠረዥ", so: "CSV, JSON: Xogta jadwalka", af: "CSV, JSON: Daata jedhee" }, hintPng: { en: "PNG: High quality raster image", am: "PNG: ከፍተኛ ጥራት ያለው ራስተር ምስል", or: "PNG: Suura raster qulqullina guddaa", ti: "PNG: ምስል ራስተር ላቀ ጥራት", so: "PNG: Sawirka raster ee tayada sare", af: "PNG: Suura raster qulqullina guddaa" }, hintJpeg: { en: "JPEG: Smaller file size", am: "JPEG: ትንሽ ፋይል መጠን", or: "JPEG: Baay'ina faayilaa xiqqaa", ti: "JPEG: መጠን ፋይል ንእሽቶ", so: "JPEG: Cabbirka faylka yar", af: "JPEG: Baay'ina faayilaa xiqqaa" }, hintSvgVector: { en: "SVG: Vector format (best quality, scalable)", am: "SVG: ቬክተር ቅርጽ (ምርጥ ጥራት፣ ስኬላብል)", or: "SVG: Qormaata veektora (qulqullina gaarii, guddifama)", ti: "SVG: ሓይሊ ቬክተር (ላቀ ጥራት፣ ስኬላብል)", so: "SVG: Nooca vector (tayada ugu fiican, weyni karo)", af: "SVG: Qormaata veektora (qulqullina gaarii, guddifama)" }, hintCsvData: { en: "CSV: Tabular data export", am: "CSV: የሠንጠረዥ ውሂብ ምውጣት", or: "CSV: Ba'e daata jedhee", ti: "CSV: ውጻኢ ውሂብ ሰንጠረዥ", so: "CSV: Dhoofinta xogta jadwalka", af: "CSV: Ba'e daata jedhee" }, hintJsonData: { en: "JSON: Structured data export", am: "JSON: የተዋቀረ ውሂብ ምውጣት", or: "JSON: Ba'e daata qindaa'e", ti: "JSON: ውጻኢ ውሂብ ዝተዋህደ", so: "JSON: Dhoofinta xogta dhismeed", af: "JSON: Ba'e daata qindaa'e" }, hintSvgMap: { en: "SVG: Vector format (best quality)", am: "SVG: ቬክተር ቅርጽ (ምርጥ ጥራት)", or: "SVG: Qormaata veektora (qulqullina gaarii)", ti: "SVG: ሓይሊ ቬክተር (ላቀ ጥራት)", so: "SVG: Nooca vector (tayada ugu fiican)", af: "SVG: Qormaata veektora (qulqullina gaarii)" }, allowPopups: { en: "Please allow popups to export as PDF", am: "በPDF ለማውረድ ፖፕአፖች ይፍቀዱ", or: "PDF ba'uuf popup fayyadamuun nu dhiisaa", ti: "ንምውጻኢ ከም PDF ፖፕአፖች ኣይትርእ", so: "Fadlan ogolaansho pop-up si aad u soo dejiso PDF", af: "PDF ba'uuf popup fayyadamuun nu dhiisaa" }, shapefileOption: { en: "Shapefile (SHP)", am: "ሼፕፋይል (SHP)", or: "Faayilii Shaapii (SHP)", ti: "ሼፕፋይል (SHP)", so: "Shapefile (SHP)", af: "Shapefile (SHP)" }, hintShapefile: { en: "Shapefile for GIS software (ZIP)", am: "ለጂአይኤስ ሶፍትዌር የሚሆን ሼፕፋይል (ZIP)", or: "Faayilii Shaapii softiweerii GIS (ZIP)", ti: "ሼፕፋይል ንሶፍትዌር ጂአይኤስ (ZIP)", so: "Shapefile softiweerka GIS (ZIP)", af: "Shapefile GIS softwareh (ZIP)" }, shapefileSuccess: { en: "Shapefile downloaded successfully", am: "ሼፕፋይል በተሳካ ሁኔታ ወረደ", or: "Faayiliin Shaapii milkaa'inaan buufameera", ti: "ሼፕፋይል ብዕዉት መገዲ ተሓዲሱ", so: "Shapefile si guul leh ayaa loo soo dejiyay", af: "Shapefile taamayah caagitan obsimem" }, shapefileFailed: { en: "Shapefile export failed", am: "ሼፕፋይል ማስወጣት አልተሳካም", or: "Faayilii Shaapii baasuun milkaa'uu baate", ti: "ምፍናት ሼፕፋይል ኣይተሳካን", so: "Shapefile export wuu guul daraystay", af: "Shapefile afak cynno woh tekkek" } }, vopNoteMd: { caption: { en: `Monetary VoP values are represented in 2005 international dollars.`, am: `የገንዘብ VOP እሴቶች በ2005 አለም አቀፍ ዶላር ይወከላሉ።`, or: `Qarshii VoP qabeenyaan 2005 dollars addunyaa irratti kan mul'atudha.`, ti: `ናይ ገንዘብ VOP ዋጋታት ብ2005 ዓለማዊ ዶላር ይውከሉ።`, so: `Qiimaha lacagta ah ee VoP waxaa lagu matalayaa doollaro caalami ah 2005.`, af: `Qarshii VoP qabeenyaan 2005 dollars addunyaa irratti fakkaata.` }, blurb: { en: `VoP, 2005 [international dollars](https://en.wikipedia.org/wiki/International_dollar)`, am: `VOP, 2005 [አለም አቀፍ ዶላር](https://en.wikipedia.org/wiki/International_dollar)`, or: `VoP, 2005 [dollars addunyaa](https://en.wikipedia.org/wiki/International_dollar)`, ti: `VOP, 2005 [ዶላር ዓለማዊ](https://en.wikipedia.org/wiki/International_dollar)`, so: `VoP, 2005 [doollaro caalami ah](https://en.wikipedia.org/wiki/International_dollar)`, af: `VoP, 2005 [dollars addunyaa](https://en.wikipedia.org/wiki/International_dollar)` } }, overview: { header: { en: "Overview", am: "አጠቃላይ እይታ", or: "Irra deebi'iinsa", ti: "ሓፈሻዊ መግለጺ", so: "Dulmarka", af: "Argina guutuu" }, blocks: { opener: { en: "Ethiopian agriculture will be tested by climate change. Rising temperatures, unpredictable rainfall, and flooding will disrupt the growth and production of crops and livestock, jeopardizing food security and livelihoods for millions. This notebook aims to empower users to understand the climate risks facing African agriculture, as well as identify the adaptation barriers in terms of education, women's empowerment, and poverty. You can follow the narrative for the continent as a whole, or select individual countries for geography-specific statistics.", am: "የኢትዮጵያ ሥርዓተ እርሻ በአየር ንብረት ለውጥ ይሞከራል። እየጨመረ ያለው ሙቀት፣ የማይጠበቅ ዝናብ እና ጎርፍ የምርት አይነቶችን እና እንስሳትን እድገት እና ምርት ያበላሻል፣ የምግብ ዋስትና እና የኑሮ መንገድ ለሚሊዮኖች ያስገድዳል። ይህ ኖትቡክ ተጠቃሚዎች የአፍሪካ ሥርዓተ እርሻ የሚያጋጥመውን የአየር ንብረት አደጋ እንዲረዱ እንዲሁም የትምህርት፣ የሴቶች ኃይል እና ድህነት አሰራር ላይ ያሉ የማስተካከያ እንቅፋቶችን እንዲለዩ ያለመ ነው። ለጠቅላላው አህጉር ታሪኩን ሊከተሉ ወይም ለተወሰኑ ጂኦግራፊዎች የተለያዩ ስታቲስቲክስ ለማግኘት የተለያዩ ሀገራትን መምረጥ ይችላሉ።", or: "Qonnaan Bishaan itoophiyaa duumessa haala qilleensaa irratti mokkodha. Ho'inni guddatee, roobni hin eeyyamne, fi gammojjii guddina fi oomishaa mirayaafi beyladaa balleessa, mirga nyaataa fi jireenyaa kumaatamaan tiksu. Barruu kun fayyadamaa duumessa haala qilleensaa qonnaan bishaan Afrikaa qunnamu hubachuuf, akkasumas dhowwii walqixxummaa barumsaa, humna dubartii, fi hiyyummaa keessatti gargaarsa gochuu filatama. Seenaa guutummaa guutuu itti fufuu yookiin lakkoofsa geografii adda addaa argachuuf biyyoota adda addaa filachuu dandeessa.", ti: "ሕርሻ ኢትዮጵያ ብለውጢ ኩነታት ኣየር ክፍትን እዩ። ምውሳኽ ሙቐት፣ ዘይተጠበቐ ዝናብ፣ ማይ ምፍሳስ ንዕቀትን ምምሕያሽን ኣትክልትን እንስሳትን ከተበላሽዎ፣ ንምቁጽጻር ምግብን መንግስትን ንሚልዮናት ዘተግብር እዩ። እዚ ደብዳበ ዚብል ንተጠቃሚታት ምእንቲ ከም ዝገብሩ ሓደገኛ ኩነታት ኣየር ንሕርሻ ኣፍሪቃ ዚገጥም ከምኡውን ኣገዳስነት ትምህርት፣ ስልጣን ኣንስትዮ፣ ምስጢር ድኽነት ኣብ ምርዳእ ከም ዝርድኡ እዩ። ንታሕቲ ኩሉ ኣፍሪቃ ምስ እትኸውን ርእይቶ ክትስዕቡ ወይ ንግዳዊ ሃገራት ንጂኦግራፍያዊ ስታትስቲክስ ክትምርጹ ትኽእሉ ኢኹም።", so: "Beeraha itoobiya waxaa fiiri doona isbeddelka cimilada. Koroorta heerkulka, roobka aan la saadaalin karin, iyo daadadka waxay khalkhalin doonaan koritaanka iyo soo saarida beeraha iyo xoolaha, iyagoo khatar ku hayo nabadgelyada cuntada iyo nolosha malyuunka. Buuggan waxa uu ujeeddo in uu awood u siiyo isticmaalayaasha in ay fahmaan khataraha cimilada ee ku hayo beeraha Afrikaanka, iyo sidoo kale aqoonsiga caqabadaha isbeddelka ee ku saabsan waxbarashada, awood darinta haweenka, iyo faqriga. Waxaad raaci kartaa sheekada qaaradda oo dhan, ama dooro waddamo gaar ah si aad u heshid tirakoobyo ku saabsan juqraafiga gaarka ah.", af: "Qonnaan bishaan Itiyoppiya duumessa qilleensa irratti mokkodha. Ho'inni guddatee, roobni hin eeyyamne, fi gammojjii guddina fi oomishaa mirayaafi beyladaa balleessa, mirga nyaataa fi jireenyaa kumaatamaan tiksu. Kutbata kana fayyadamaa duumessa qilleensa qonnaan bishaan Afrikaa qunnamu hubachuuf, akkasumas dhowwii walqixxummaa barumsaa, humna dubartii, fi hiyyummaa keessatti gargaarsa gochuu filatama. Seenaa guutummaa guutuu itti fufuu yookiin lakkoofsa geografii adda addaa argachuuf biyyoota adda addaa filachuu dandeessa." } } }, africaMap: { blocks: { h1: { en: "What Does Ethiopia Have to Lose?", am: "ኢትዮጵያ ምን ሊጠፋት ይችላል?", or: "Maaltu itoophiyaa Dhiisu?", ti: "ኢትዮጵያ እንታይ ክትጥፍእ ኣለዋ?", so: "Maxay itoobiya waayi doontaa?", af: "Maaltu Itiyoppiya Dhiisu?" }, opener: { en: `Ethiopian agriculture is valuable, both in terms of food production and farmers. Here you can explore how the value of production (:::vop_blurb:::) and size of the rural population differ between specific countries and regions. This context is important for understanding the unique vulnerabilities facing the agricultural sector on the continent, or for specific geographies of interest.`, am: `የኢትዮጵያ ሥርዓተ እርሻ በምግብ ምርት እና በገበሬዎች አንፃር ጠቃሚ ነው። እዚህ የምርት ዋጋ (:::vop_blurb:::) እና የገጠር ሕዝብ መጠን በተለያዩ ሀገራት እና ክልሎች መካከል እንዴት እንደሚለያዩ ማሰስ ይችላሉ። ይህ አውድ ለአህጉሩ የሥርዓተ እርሻ ዘርፍ የሚያጋጥመውን ልዩ የአደጋ ሁኔታ ለመረዳት ወይም ለተወሰኑ ጂኦግራፊዎች አስፈላጊ ነው።`, or: `Qonnaan Bishaan itoophiyaa mi'aawaa dha, kan soorata oomishaa fi qotiyoota keessatti. Asii gatiin oomishaa (:::vop_blurb:::) fi baay'ina ummataa naannoo biyyoota fi naannolee adda addaa akka adda ta'an qo'achuu dandeessa. Kuni hubannoo balaa addaa qonnaan bishaan qarqara Afrikaa qunnatuuf yookiin naannoo barbaachisaa ta'eef barbaachisaa dha.`, ti: `ሕርሻ ኢትዮጵያ ዋጋ ኣለዎ፣ ብኽብረት ምምሕያሽ መግብን ኣቝራኒን። ኣብዚ ከመይ ጌርካ ዋጋ ምምሕያሽ (:::vop_blurb:::) ከምኡውን መጠን ህዝቢ ገጠር ኣብ መንጎ ሓደ ሃገራትን ክልላትን ከም ዚፈላለ ክትፈትሹ ትኽእሉ። እዚ ኸኣ ንርድኢት ሓደገኛ ኩነታት ንሕርሻዊ ወደብ ኣብ ኣፍሪቃ ዚገጥም ወይ ንግዳዊ ጂኦግራፍያዊ ከባቢታት ኣገዳሲ እዩ።`, so: `Beeraha itoobiya waa qiimo leh, labada dhinac ee soo saarista cuntada iyo beeraha. Halkan waxaad ka heli kartaa sida qiimaha soo saarista (:::vop_blurb:::) iyo cabirka dadka reer miyiga uu u kala duwan yahay dalal iyo gobollo gaar ah. Qaabkani waa muhiim ah si loo fahmo khataraha gaarka ah ee ka hor yimaada qaybta beeraha qaaradda, ama juqraafiyada gaarka ah ee la xiiseeyo.`, af: `Qonnaan bishaan Itiyoppiya mi'aawaa dha, kan soorata oomishaa fi qotiyoota keessatti. Asii gatiin oomishaa (:::vop_blurb:::) fi baay'ina ummataa naannoo biyyoota fi naannolee adda addaa akka adda ta'an qo'achuu dandeessa. Kuni hubannoo balaa addaa qonnaan bishaan qarqara Afrikaa qunnatuuf yookiin naannoo barbaachisaa ta'eef barbaachisaa dha.` } }, inputs: { mapLayer: { label: { en: "Map layer", am: "የካርታ ንብርብር", or: "Saala kaartaa", ti: "ሽፋን ካርታ", so: "Dul kaar", af: "Saala kaartaa" }, options: { ruralPop: { label: { en: "Rural population", am: "የገጠር ሕዝብ", or: "Ummata naannoo", ti: "ህዝቢ ገጠር", so: "Dadka reer miyiga", af: "Ummata naannoo" }, labelTip: { en: "Rural population", am: "የገጠር ሕዝብ", or: "Ummata naannoo", ti: "ህዝቢ ገጠር", so: "Dadka reer miyiga", af: "Ummata naannoo" }, labelLegend: { en: "Rural population", am: "የገጠር ሕዝብ", or: "Ummata naannoo", ti: "ህዝቢ ገጠር", so: "Dadka reer miyiga", af: "Ummata naannoo" } }, urbanPop: { label: { en: "Urban population", am: "የከተማ ሕዝብ", or: "Ummata magaalaa", ti: "ህዝቢ ከተማ", so: "Dadka magaalooyinka", af: "Ummata magaalaa" }, labelTip: { en: "Urban population", am: "የከተማ ሕዝብ", or: "Ummata magaalaa", ti: "ህዝቢ ከተማ", so: "Dadka magaalooyinka", af: "Ummata magaalaa" }, labelLegend: { en: "Urban population", am: "የከተማ ሕዝብ", or: "Ummata magaalaa", ti: "ህዝቢ ከተማ", so: "Dadka magaalooyinka", af: "Ummata magaalaa" } }, vop: { label: { en: "Total Value of Production (VoP)", am: "ጠቅላላ የምርት ዋጋ (VOP)", or: "Gatiin Waliigalaa Oomishaa (VoP)", ti: "ጠቕላላ ዋጋ ምምሕያሽ (VOP)", so: "Wadarta Qiimaha Soo Saarista (VoP)", af: "Gatiin Waliigalaa Oomishaa (VoP)" }, labelTip: { en: "VoP", am: "VOP", or: "VoP", ti: "VOP", so: "VoP", af: "VoP" }, labelLegend: { en: `Value of Production (:::unit:::)`, am: `የምርት ዋጋ (:::unit:::)`, or: `Gatiin Oomishaa (:::unit:::)`, ti: `ዋጋ ምምሕያሽ (:::unit:::)`, so: `Qiimaha Soo Saarista (:::unit:::)`, af: `Gatiin Oomishaa (:::unit:::)` } } } } }, insights: { title: { en: `:::insight_string::: for :::admin_selection:::`, am: `:::insight_string::: ለ :::admin_selection:::`, or: `:::insight_string::: :::admin_selection::: irratti`, ti: `:::insight_string::: ን :::admin_selection:::`, so: `:::insight_string::: :::admin_selection::: u`, af: `:::insight_string::: :::admin_selection::: irratti` }, insightOverview: { en: `**:::admin_selection:::**'s total value of crop and livestock production is **:::total_vop:::**.`, am: `የ**:::admin_selection:::** ጠቅላላ የምርት አይነት እና እንስሳት ምርት ዋጋ **:::total_vop:::** ነው።`, or: `Gatiin waliigalaa oomishaa mirayaafi beyladaa **:::admin_selection:::** **:::total_vop:::**.`, ti: `ጠቕላላ ዋጋ ምምሕያሽ ኣትክልትን እንስሳትን **:::admin_selection:::** **:::total_vop:::** እዩ።`, so: `Wadarta qiimaha soo saarista beeraha iyo xoolaha ee **:::admin_selection:::** waa **:::total_vop:::**.`, af: `Gatiin waliigalaa oomishaa mirayaafi beyladaa **:::admin_selection:::** **:::total_vop:::**.` }, insightAreaAndPop: { en: `Its crops are produced over an area of **:::area:::** hectares, with rural areas encompassing a population of **:::population:::** people.`, am: `ምርቶቹ በ**:::area:::** ሄክታር ስፋት ላይ ይመረታሉ፣ የገጠር አካባቢዎቹ ደግሞ **:::population:::** ሰዎችን ያካትታሉ።`, or: `Mirayaan bal'ina **:::area:::** heektaraa irratti oomishaman, naannoon ummata **:::population:::** namootaa qabu.`, ti: `ኣትክልቱ ኣብ ስፍሓት **:::area:::** ሔክታር ይምሕያሽ፣ ከባቢ ገጠር ህዝቢ **:::population:::** ሰባት ዝሓዘ እዩ።`, so: `Beeraha waxaa lagu soo saaraa aagga **:::area:::** hectare, halka deegaanka miyiga ay ku jirto dad **:::population:::** ah.`, af: `Mirayaan bal'ina **:::area:::** heektaraa irratti oomishaman, naannoon ummata **:::population:::** namootaa qabu.` }, insightTopCommodity: { en: `The top :::commodity_word::: by value: :::list_string:::.`, am: `ከፍተኛ ዋጋ ያላቸው :::commodity_word::: :::list_string:::.`, or: `:::commodity_word::: guddaan gatiin: :::list_string:::.`, ti: `ናይ ላዕሊ :::commodity_word::: ብዋጋ: :::list_string:::.`, so: `:::commodity_word::: ugu qiimaha badan: :::list_string:::.`, af: `:::commodity_word::: guddaan gatiin: :::list_string:::.` }, insightTopLivestock: { en: `The top livestock species in terms of population: :::list_string:::.`, am: `ከፍተኛ ቁጥር ያላቸው የእንስሳት ዝርያዎች: :::list_string:::.`, or: `Gosa beyladaa guddaan baay'ina ummataa: :::list_string:::.`, ti: `ናይ ላዕሊ ዓይነት እንስሳት ብብዝሒ ህዝቢ: :::list_string:::.`, so: `Noocyada xoolaha ugu tirada badan: :::list_string:::.`, af: `Gosa beyladaa guddaan baay'ina ummataa: :::list_string:::.` }, titleEt: { en: `:::insight_string::: for Ethiopia`, am: `:::insight_string::: ለ ኢትዮጵያ`, or: `:::insight_string::: Itoophiyaa irratti`, ti: `:::insight_string::: ን ኢትዮጵያ`, so: `:::insight_string::: Itoobiya u`, af: `:::insight_string::: Itoophiyaa irratti` }, insightOverviewEt: { en: `Ethiopia's total value of crop and livestock production is **:::total_vop:::**.`, am: `የኢትዮጵያ ጠቅላላ የምርት አይነት እና እንስሳት ምርት ዋጋ **:::total_vop:::** ነው።`, or: `Gatiin waliigalaa oomishaa mirayaafi beyladaa Itoophiyaa **:::total_vop:::**.`, ti: `ጠቕላላ ዋጋ ምምሕያሽ ኣትክልትን እንስሳትን ኢትዮጵያ **:::total_vop:::** እዩ።`, so: `Wadarta qiimaha soo saarista beeraha iyo xoolaha ee Itoobiya waa **:::total_vop:::**.`, af: `Gatiin waliigalaa oomishaa mirayaafi beyladaa Itoophiyaa **:::total_vop:::**.` }, insightAreaAndPopEt: { en: `Its crops are produced over an area of **:::area:::** hectares, with rural areas encompassing a population of **:::population:::** people.`, am: `ምርቶቹ በ**:::area:::** ሄክታር ስፋት ላይ ይመረታሉ፣ የገጠር አካባቢዎቹ ደግሞ **:::population:::** ሰዎችን ያካትታሉ።`, or: `Mirayaan bal'ina **:::area:::** heektaraa irratti oomishaman, naannoon ummata **:::population:::** namootaa qabu.`, ti: `ኣትክልቱ ኣብ ስፍሓት **:::area:::** ሔክታር ይምሕያሽ፣ ከባቢ ገጠር ህዝቢ **:::population:::** ሰባት ዝሓዘ እዩ።`, so: `Beeraha waxaa lagu soo saaraa aagga **:::area:::** hectare, halka deegaanka miyiga ay ku jirto dad **:::population:::** ah.`, af: `Mirayaan bal'ina **:::area:::** heektaraa irratti oomishaman, naannoon ummata **:::population:::** namootaa qabu.` }, insightTopCommodityEt: { en: `The top :::commodity_word::: by value: :::list_string:::.`, am: `ከፍተኛ ዋጋ ያላቸው :::commodity_word::: :::list_string:::.`, or: `:::commodity_word::: guddaan gatiin: :::list_string:::.`, ti: `ናይ ላዕሊ :::commodity_word::: ብዋጋ: :::list_string:::.`, so: `:::commodity_word::: ugu qiimaha badan: :::list_string:::.`, af: `:::commodity_word::: guddaan gatiin: :::list_string:::.` }, insightTopLivestockEt: { en: `The top livestock species in terms of population: :::list_string:::.`, am: `ከፍተኛ ቁጥር ያላቸው የእንስሳት ዝርያዎች: :::list_string:::.`, or: `Gosa beyladaa guddaan baay'ina ummataa: :::list_string:::.`, ti: `ናይ ላዕሊ ዓይነት እንስሳት ብብዝሒ ህዝቢ: :::list_string:::.`, so: `Noocyada xoolaha ugu tirada badan: :::list_string:::.`, af: `Gosa beyladaa guddaan baay'ina ummataa: :::list_string:::.` } } }, climateRisks: { intro: { h1: { en: "Climate Risks", am: "የአየር ንብረት አደጋዎች", or: "Balaawwan Haala Qilleensaa", ti: "ሓደገኛ ኩነታት ኣየር", so: "Khataraha Cimilada", af: "Balaawwan Haala Qilleensaa" }, opener: { en: `In **:::admin_selection:::**, climate change can impact crops and livestock in diverse ways. The specific risks can vary not only by region but also by the type of crop or livestock. Use the interactive features below to select specific locations and climate change scenarios. This will help you understand the unique hazards each faces and identify the most economically important crops and livestock at risk.`, am: `በ**:::admin_selection:::**፣ አየር ንብረት ለውጥ ምርቶችን እና እንስሳትን በተለያዩ መንገዶች ሊጎዳ ይችላል። የተለያዩ አደጋዎች በክልል ብቻ ሳይሆን በምርት ወይም በእንስሳት አይነትም ሊለያዩ ይችላሉ። ከታች ያሉትን በይነመረብ ባህሪዎች በመጠቀም የተለያዩ ቦታዎችን እና የአየር ንብረት ለውጥ እቅዶችን መምረጥ ይችላሉ። ይህ እያንዳንዳቸው የሚያጋጥሟቸውን ልዩ አደጋዎች እንዲረዱ እና በኢኮኖሚ አስፈላጊ የሆኑ ምርቶችን እና እንስሳትን አደጋ ላይ እንዲለዩ ይረዳዎታል።`, or: `**:::admin_selection:::** keessatti, jijjiirama haala qilleensaa mirayaafi beyladaa karaa adda addaatti dhiibuu danda'a. Balaawwan addaa naannoo hin qofaa miti garuu gosa mirayaafi beyladaa irrattis adda ta'uu danda'u. Asii gulaaltota naannoo fi haala jijjiirama haala qilleensaa adda addaa filachuuf qabiyyee walitti dhufeenyaa gargaarsa. Kun balaa addaa hundaaf qunnamu hubachuuf, akkasumas mirayaafi beyladaa dursaa dhaabbata ekonomii balaa keessa jiran filatamuu keessatti si gargaara.`, ti: `ኣብ **:::admin_selection:::**፣ ለውጢ ኩነታት ኣየር ንኣትክልትን እንስሳትን ብዙሕ ኣገባባት ክጸልዎ ይኽእል እዩ። እቲ ፍሉይ ሓደጋታት ብኸባቢ ጥራይ ዘይኰነስ ብዓይነት ኣትክልትን እንስሳትን እውን ክፈላለ ይኽእል እዩ። ነቲ ኣብ ታሕቲ ዘሎ ተግባራዊ ባህርያት ተጠቒምካ ፍሉያት ቦታታትን ናይ ለውጢ ኩነታት ኣየር ስክራናርዮታትን ምረጽ። እዚ ኸኣ ንፍሉይ ሓደጋታት ነፍሲ ወከፍ ዘጋጥሞም ንኸተረድኡን ነቶም ኣብ ትሕቲ ሓደጋ ዘለዉ ኣገዳሲ ኣትክልትን እንስሳትን ንኸተለዩን ኬገድሰኩም እዩ።`, so: `**:::admin_selection:::**, isbeddelka cimilada waxaa uu saameyn karaa beeraha iyo xoolaha siyo kala duwan. Khataraha gaarka ah waxay kala duwan karaan ma aha oo kaliya gobolka, balse nooca beeraha ama xoolaha. Isticmaal sifooyinka interactive ee hoose si aad u doorato goobo gaar ah iyo muuqaalo isbeddelka cimilada. Tani waxay kaa caawin doontaa in aad fahanto khataraha gaarka ah ee ay kala kulmaan, oo aad u ogaato beeraha iyo xoolaha ugu muhiimsan dhaqaale ahaan ee ku jira khatar.`, af: `**:::admin_selection:::** keessatti, jijjiirama haala qilleensaa mirayaafi beyladaa karaa adda addaatti dhiibuu danda'a. Balaawwan addaa naannoo hin qofaa miti garuu gosa mirayaafi beyladaa irrattis adda ta'uu danda'u. Asii gulaaltota naannoo fi haala jijjiirama haala qilleensaa adda addaa filachuuf qabiyyee walitti dhufeenyaa gargaarsa. Kun balaa addaa hundaaf qunnamu hubachuuf, akkasumas mirayaafi beyladaa dursaa dhaabbata ekonomii balaa keessa jiran filatamuu keessatti si gargaara.` } }, compoundHazards: { h2: { en: "Compound Hazards", am: "የተደራሩ አደጋዎች", or: "Balaawwan Walitti Qabaman", ti: "ሓደጋታት ዝተኣከቡ", so: "Khataraha Isku Darka", af: "Balaawwan Walitti Qabaman" }, opener: { en: `Understand the value of production (:::vop_note:::) at risk from across different hazards alone and in combination. Hover over the bars in the chart below to explore the proportions of agricultural value in **:::admin_selection:::** that will be exposed to different hazard combinations.`, am: `የምርት ዋጋ (:::vop_note:::) ከተለያዩ አደጋዎች ብቻ እና በጥምረት አደጋ ላይ እንዳለ ይረዱ። ከታች ባለው ሰንጠረዥ ላይ ያሉትን አሞሌዎች በማለፍ በ**:::admin_selection:::** ውስጥ ያለው የሥርዓተ እርሻ ዋጋ ከተለያዩ የአደጋ ጥምረቶች ጋር የሚጋለጠውን ሬሾ ያስሱ።`, or: `Gatiin oomishaa (:::vop_note:::) balaa keessa jiru balaa adda addaa tokko tokkooffaa fi walitti qabametti hubadhaa. Saala qabiyyee armaan gadii keessatti baara irratti dhihoo firameshii qonnaan bishaan **:::admin_selection:::** keessaa balaa walitti qabamee adda addaa irratti kan dhiyaatan qo'achuuf.`, ti: `ዋጋ ምምሕያሽ (:::vop_note:::) ካብ ሓደጋታት ንግሆን ከምኡውን ብሓባር ኣብ ሓደጋ ከም ዘሎ ተረድኡ። ኣብቲ ኣብ ታሕቲ ዘሎ ሕብሪ ኣብቲ ኣሞሌታት ምጥዋት ንምእላይ ናይቲ ኣብ **:::admin_selection:::** ዘሎ ዋጋ ሕርሻ ንዝተፈላለዩ ምትእስሳር ሓደጋታት ከም ዚጋለጥ ንኸፈትሩ።`, so: `Faham qiimaha soo saarista (:::vop_note:::) ee ku jira khataraha kala duwan oo keliya iyo isku darka. Ku soo dhawo baararka jaantuska hoose si aad u baadhid qeybaha qiimaha beeraha ee **:::admin_selection:::** ee u saamayn doona isku darka khataraha kala duwan.`, af: `Gatiin oomishaa (:::vop_note:::) balaa keessa jiru balaa adda addaa tokko tokkooffaa fi walitti qabametti hubadhaa. Saala qabiyyee armaan gadii keessatti baara irratti dhihoo firameshii qonnaan bishaan **:::admin_selection:::** keessaa balaa walitti qabamee adda addaa irratti kan dhiyaatan qo'achuuf.` }, inputs: { dropdownScenario: { label: { en: "Scenario", am: "እቅድ", or: "Haala", ti: "ስክራናርዮ", so: "Muuqaal", af: "Haala" }, historic: { en: "Historic", am: "ታሪካዊ", or: "Taariikhawaa", ti: "ታሪኻዊ", so: "Taariikhi", af: "Taariikhawaa" } } }, stackedBar: { xLabel: { en: "Total VoP (%)", am: "ጠቅላላ VOP (%)", or: "VoP Waliigalaa (%)", ti: "ጠቕላላ VOP (%)", so: "Wadarta VoP (%)", af: "VoP Waliigalaa (%)" }, tooltipLabels: { vopRisk: { en: "VoP at risk from hazard", am: "ከአደጋ VOP አደጋ ላይ", or: "VoP balaa irraa balaa keessa", ti: "VOP ካብ ሓደጋ ኣብ ሓደጋ", so: "VoP ku jira khatar ka khatar", af: "VoP balaa irraa balaa keessa" }, hazard: { en: "Hazard", am: "አደጋ", or: "Balaa", ti: "ሓደጋ", so: "Khatar", af: "Balaa" }, totalVop: { en: "Total VoP at risk", am: "ጠቅላላ VOP አደጋ ላይ", or: "VoP Waliigalaa balaa keessa", ti: "ጠቕላላ VOP ኣብ ሓደጋ", so: "Wadarta VoP ku jira khatar", af: "VoP Waliigalaa balaa keessa" } } } }, hazardImpact: { hazards: { wet: { en: "Wet alone", am: "ርጥብ ብቻ", or: "Bishaan qofa", ti: "ርጥብ ጥራይ", so: "Qoyan oo keliya", af: "Bishaan qofa" }, dry: { en: "Dry alone", am: "ደረቅ ብቻ", or: "Gogaa qofa", ti: "ደረቅ ጥራይ", so: "Qalalan oo keliya", af: "Gogaa qofa" }, heat: { en: "Heat alone", am: "ሙቀት ብቻ", or: "Ho'a qofa", ti: "ሙቐት ጥራይ", so: "Kulul oo keliya", af: "Ho'a qofa" }, dry_heat: { en: "Dry and heat", am: "ደረቅ እና ሙቀት", or: "Gogaa fi ho'a", ti: "ደረቅ ከምኡውን ሙቐት", so: "Qalalan iyo kulul", af: "Gogaa fi ho'a" }, dry_wet: { en: "Dry and wet", am: "ደረቅ እና ርጥብ", or: "Gogaa fi bishaan", ti: "ደረቅ ከምኡውን ርጥብ", so: "Qalalan iyo qoyan", af: "Gogaa fi bishaan" }, heat_wet: { en: "Heat and wet", am: "ሙቀት እና ርጥብ", or: "Ho'a fi bishaan", ti: "ሙቐት ከምኡውን ርጥብ", so: "Kulul iyo qoyan", af: "Ho'a fi bishaan" }, dry_heat_wet: { en: "Heat, wet, and dry", am: "ሙቀት, ርጥብ, እና ደረቅ", or: "Ho'a, bishaan, fi gogaa", ti: "ሙቐት, ርጥብ, ከምኡውን ደረቅ", so: "Kulul, qoyan, iyo qalalan", af: "Ho'a, bishaan, fi gogaa" }, no_hazard: { en: "No hazard", am: "አደጋ የለም", or: "Balaa hin jiru", ti: "ሓደጋ የለን", so: "Khatar ma jiro", af: "Balaa hin jiru" } }, h1: { en: "Hazards with the Most Impact", am: "ትልቁን ተጽዕኖ ያላቸው አደጋዎች", or: "Balaawwan Dhiibaa Guddaan Qaban", ti: "ሓደጋታት እተን ዝዓበየ ጸልመት", so: "Khataraha Leexiya Ugu Weyn", af: "Balaawwan Dhiibaa Guddaan Qaban" }, intro: { en: "Select different hazard combinations and see which crops and livestock have the most VoP at risk.", am: "የተለያዩ የአደጋ ጥምረቶችን ይምረጡ እና የትኞቹ ምርቶች እና እንስሳት ትልቁን VOP አደጋ እንዳላቸው ይመልከቱ።", or: "Walitti qabamtoota balaa adda addaa filadhaa fi mirayaafi beyladaa VoP guddan balaa keessa qaban argadhaa.", ti: "ዝተፈላለዩ ምትእስሳር ሓደጋታት ምረጽን ኣየትክልትን እንስሳትን VOP እተን ዝዓበየ ኣብ ሓደጋ ከም ዘለወን ርአ።", so: "Dooro isku darka khataraha kala duwan oo arro beeraha iyo xoolaha ee leh VoP ugu weyn ee ku jira khatar.", af: "Walitti qabamtoota balaa adda addaa filadhaa fi mirayaafi beyladaa VoP guddan balaa keessa qaban argadhaa." }, inputs: { dropdownHazard: { label: { en: "Hazard", am: "አደጋ", or: "Balaa", ti: "ሓደጋ", so: "Khatar", af: "Balaa" } } }, plots: { general: { noPlotMessage: { en: "No VoP exposure", am: "VOP መጋለጥ የለም", or: "VoP dhiyaachuu hin jiru", ti: "VOP ምጋለጽ የለን", so: "Ma jiro saameyn VoP", af: "VoP dhiyaachuu hin jiru" }, vopLabel: { en: "VoP at risk", am: "VOP አደጋ ላይ", or: "VoP balaa keessa", ti: "VOP ኣብ ሓደጋ", so: "VoP ku jira khatar", af: "VoP balaa keessa" } }, crops: { header: { en: `Crops most at risk under :::hazard_string:::`, am: `በ:::hazard_string::: ትልቁን አደጋ ያጋጠማቸው ምርቶች`, or: `Mirayaan balaa guddan :::hazard_string::: jala`, ti: `ኣትክልቲ እተን ዝዓበየ ሓደጋ :::hazard_string::: ትሕቲ`, so: `Beeraha ugu khatarta badan :::hazard_string::: hoosteeda`, af: `Mirayaan balaa guddan :::hazard_string::: jala` } }, livestock: { header: { en: `Livestock most at risk under :::hazard_string:::`, am: `በ:::hazard_string::: ትልቁን አደጋ ያጋጠማቸው እንስሳት`, or: `Beyladaan balaa guddan :::hazard_string::: jala`, ti: `እንስሳት እተን ዝዓበየ ሓደጋ :::hazard_string::: ትሕቲ`, so: `Xoolaha ugu khatarta badan :::hazard_string::: hoosteeda`, af: `Beyladaan balaa guddan :::hazard_string::: jala` } } }, insights: { title: { en: `:::insight_string::: for :::admin_selection::: (:::scenario:::)`, am: `:::insight_string::: ለ :::admin_selection::: (:::scenario:::)`, or: `:::insight_string::: :::admin_selection::: irratti (:::scenario:::)`, ti: `:::insight_string::: ን :::admin_selection::: (:::scenario:::)`, so: `:::insight_string::: :::admin_selection::: u (:::scenario:::)`, af: `:::insight_string::: :::admin_selection::: irratti (:::scenario:::)` }, hazardBlurb: { en: `For hazard: **:::hazard_string:::**`, am: `ለአደጋ: **:::hazard_string:::**`, or: `Balaa: **:::hazard_string:::**`, ti: `ሓደጋ: **:::hazard_string:::**`, so: `Khatar: **:::hazard_string:::**`, af: `Balaa: **:::hazard_string:::**` }, labels: { totalVopCrop: { en: "Total Exposed VoP, Crop", am: "ጠቅላላ የተጋለጠ VOP, ምርት", or: "VoP Waliigalaa Dhiyaate, Miraa", ti: "ጠቕላላ VOP ዝተጋለጸ, ኣትክልቲ", so: "Wadarta VoP ee La Saameeyay, Beer", af: "VoP Waliigalaa Dhiyaate, Miraa" }, totalVopLivestock: { en: "Total Exposed VoP, Livestock", am: "ጠቅላላ የተጋለጠ VOP, እንስሳት", or: "VoP Waliigalaa Dhiyaate, Beyladaa", ti: "ጠቕላላ VOP ዝተጋለጸ, እንስሳት", so: "Wadarta VoP ee La Saameeyay, Xoolo", af: "VoP Waliigalaa Dhiyaate, Beyladaa" }, exposureCrop: { en: "Crop, greatest exposure", am: "ምርት, ትልቁ መጋለጥ", or: "Miraa, dhiyaachaa guddaa", ti: "ኣትክልቲ, ዝዓበየ ምጋለጽ", so: "Beer, saameyn ugu weyn", af: "Miraa, dhiyaachaa guddaa" }, exposureLivestock: { en: "Livestock, greatest exposure", am: "እንስሳት, ትልቁ መጋለጥ", or: "Beyladaa, dhiyaachaa guddaa", ti: "እንስሳት, ዝዓበየ ምጋለጽ", so: "Xoolo, saameyn ugu weyn", af: "Beyladaa, dhiyaachaa guddaa" } }, blurbBiggestHazard: { en: "The biggest hazards for selection and scenario/timeframe are:", am: "ለተመረጠው እና እቅድ/ጊዜ ክልል ትልቁ አደጋዎች:", or: "Balaawwan guddaan filannoo fi haala/yeroo irratti:", ti: "እተን ዝዓበየ ሓደጋታት ንምርጫን ስክራናርዮ/ግዜ ክልልን:", so: "Khataraha ugu weyn ee doorashada iyo muuqaal/waqtiga waa:", af: "Balaawwan guddaan filannoo fi haala/yeroo irratti:" } } } }, adaptiveCapacities: { h1: { en: "Adaptive Capacities", am: "የማስተካከያ አቅም", or: "Dandeettii Walqixxummaa", ti: "መጠን ምምሕያሽ", so: "Awoodaha Isbeddelka", af: "Dandeettii Walqixxummaa" }, intro: { en: `Farmers ability to adapt to climate change in **:::admin_selection:::** hinges on several key socio-economic factors. These include poverty, education, and gender inequality, which significantly influence their vulnerability and their capacity to respond effectively. Explore the map and indexes below to gain a deeper understanding of the geographic distribution of these variables across the region. Each of the three indexes are scored between 0 and 100. For the poverty index, lower values indicate lower levels of poverty. For Education and Female Empowerment, a higher score indicates increased levels of educational attainment and female decision making power.`, am: `የ**:::admin_selection:::** ገበሬዎች ወደ አየር ንብረት ለውጥ የማስተካከል ችሎታ በበርካታ ቁልፍ ማህበራዊ-ኢኮኖሚያዊ ምክንያቶች ላይ የተመሰረተ ነው። እነዚህም ድህነት፣ ትምህርት እና የጾታ እኩልነት ሲሆኑ እነዚህም የእነሱን የአደጋ ሁኔታ እና በተሳካ ሁኔታ የመልስ አቅምን በከፍተኛ ሁኔታ ይጎድላሉ። በክልሉ ውስጥ የእነዚህ ተለዋዋጮች ጂኦግራፊያዊ ስርጭት የበለጠ ለመረዳት ከታች ያለውን ካርታ እና መረጃ ጠቋሚዎች ያስሱ። ሦስቱም መረጃ ጠቋሚዎች ከ0 እስከ 100 ይለካሉ። ለድህነት መረጃ ጠቋሚ፣ ዝቅተኛ እሴቶች ዝቅተኛ የድህነት ደረጃን ያመለክታሉ። ለትምህርት እና ለሴቶች ኃይል፣ ከፍተኛ ነጥብ ከፍተኛ የትምህርት ደረጃ እና የሴቶች የመወሰን ኃይልን ያመለክታል።`, or: `Dandeettii qotiyootaa **:::admin_selection:::** jijjiirama haala qilleensaa irratti walqixxummaa gochuuf haala hawaasa-dhaabbataa gurguddaa hedduu irratti hirkata. Kuni hiyyummaa, barumsaa, fi walqixxummaa saalaa dabalata, kan dandeettii isaanii balaa qunnamuu fi deebii gaarii kennuu ciminaan dhiibuu. Kaartaa fi indeeksota armaan gadii qo'achuun naannoo keessatti jijjiirama geografii kanneenii hubannoo gadi fagoo argachuuf. Indeeksota sadiin hunduu 0 fi 100 gidduutti qoratama. Indeeksa hiyyummaa, gatii gadi aanaa sadarkaa hiyyummaa gadi aanaa agarsiisa. Barumsaa fi Humna Dubartii, qorannoo ol aanaa sadarkaa barumsaa fi humna murteessaa dubartii guddataa agarsiisa.`, ti: `ናይ ሓታቲ **:::admin_selection:::** ንለውጢ ኩነታት ኣየር ንምምሕያሽ ዘለዎም ክእለት ኣብ ሓያሎ ቁልፊ ማሕበራዊ-ቁጠባዊ ረቛሒታት ይወጽእ። እዚኦም ድኽነት፣ ትምህርት፣ ከምኡውን እኩልነት ጾታ የጠቃልል፣ እቶም ንስስነቶም ሓደጋን ንግቡእ መልሲ ክእለቶምን ብኸባይ ዚጸልዉ። ነቲ ኣብ ታሕቲ ዘሎ ካርታን መርበብን ተጠቒምካ ንጂኦግራፍያዊ ስርጭት ናይዞም ተለዋዋጥታት ኣብ ከባቢኡ ዝበለጸ ርድኢት ምእንቲ ኽትረክብ ፈልጥ። ካልኦት ሰለስተ መርበብታት ካብ 0 ክሳዕ 100 ይውሰኑ። ንመርበብ ድኽነት፣ ንእሽቶ ዋጋታት ንእሽቶ ደረጃ ድኽነት የምልክት። ንትምህርትን ስልጣን ኣንስትዮን፣ ልዑል ደረጃ ልዑል ደረጃ ትምህርትን ስልጣን ኣንስትዮ ንመወሰንን የምልክት።`, so: `Awoodda beeraha loogu adeegsado isbeddelka cimilada ee **:::admin_selection:::** waxay ku xirantahay dhowr arrimood oo muhiim ah oo bulsho-dhaqaale. Kuwaas waxaa ka mid ah faqriga, waxbarashada, iyo sinaanta jinsiga, kuwaas oo si weyn u saameeya khatarta ay kala kulmaan iyo awooddooda in ay si wax ku ool ah uga jawaabaan. Baadh khariidadda iyo indeksiyada hoose si aad u heshid faham dheeraad ah oo ku saabsan qaybinta juqraafiyadeed ee doorsoomayaashan gobolka. Mid kasta oo saddexda indeks waxaa lagu qiimeeyaa inta u dhexeysa 0 ilaa 100. Indeksiga faqriga, qiimayaasha hoose waxay tilmaamaan heerar hoose oo faqri. Waxbarashada iyo Awooddarinta Haweenka, qiimeyn sare wuxuu tilmaamayaa heerar korodhay oo waxbarasho iyo awood go 'aan qaadashada haweenka.`, af: `Dandeettii qotiyootaa **:::admin_selection:::** jijjiirama haala qilleensaa irratti walqixxummaa gochuuf haala hawaasa-dhaabbataa gurguddaa hedduu irratti hirkata. Kuni hiyyummaa, barumsaa, fi walqixxummaa saalaa dabalata, kan dandeettii isaanii balaa qunnamuu fi deebii gaarii kennuu ciminaan dhiibuu. Kaartaa fi indeeksota armaan gadii qo'achuun naannoo keessatti jijjiirama geografii kanneenii hubannoo gadi fagoo argachuuf. Indeeksota sadiin hunduu 0 fi 100 gidduutti qoratama. Indeeksa hiyyummaa, gatii gadi aanaa sadarkaa hiyyummaa gadi aanaa agarsiisa. Barumsaa fi Humna Dubartii, qorannoo ol aanaa sadarkaa barumsaa fi humna murteessaa dubartii guddataa agarsiisa.` }, inputs: { mapLayer: { label: { en: "Map layer", am: "የካርታ ንብርብር", or: "Saala kaartaa", ti: "ሽፋን ካርታ", so: "Dul kaar", af: "Saala kaartaa" }, options: { general: { labels: { population: { en: "Population", am: "ሕዝብ", or: "Ummata", ti: "ህዝቢ", so: "Dad", af: "Ummata" } } }, pov: { label: { en: "Poverty Rate", am: "የድህነት መጠን", or: "Saffisa Hiyyummaa", ti: "ስፍሓት ድኽነት", so: "Heerka Faqriga", af: "Saffisa Hiyyummaa" }, labelLegend: { en: "Poverty Rate (% of population under $3.65 per day)", am: "የድህነት መጠን (% ሕዝብ በቀን ከ$3.65 በታች)", or: "Saffisa Hiyyummaa (% ummataa guyyaa $3.65 gadi)", ti: "ስፍሓት ድኽነት (% ህዝቢ ብመዓልቲ $3.65 ትሕቲ)", so: "Heerka Faqriga (% dadka maalinta $3.65 ka hooseeya)", af: "Saffisa Hiyyummaa (% ummataa guyyaa $3.65 gadi)" } }, edu: { label: { en: "Education Attainment", am: "የትምህርት ደረጃ", or: "Qabiyyee Barumsaa", ti: "ደረጃ ትምህርት", so: "Heerka Waxbarashada", af: "Qabiyyee Barumsaa" }, labelLegend: { en: "Education Attainment (Years of schooling)", am: "የትምህርት ደረጃ (የትምህርት ዓመታት)", or: "Qabiyyee Barumsaa (Waggaa Mana Barumsaa)", ti: "ደረጃ ትምህርት (ዓመታት ትምህርቲ)", so: "Heerka Waxbarashada (Sanooyinka Dugsiyeed)", af: "Qabiyyee Barumsaa (Waggaa Mana Barumsaa)" } }, fem: { label: { en: "Female empowerment index", am: "የሴቶች ኃይል መረጃ ጠቋሚ", or: "Indeeksa Humna Dubartii", ti: "መርበብ ስልጣን ኣንስትዮ", so: "Indeksiga Awooddarinta Haweenka", af: "Indeeksa Humna Dubartii" }, labelLegend: { en: "Female empowerment index (higher is better)", am: "የሴቶች ኃይል መረጃ ጠቋሚ (ከፍ ያለ የተሻለ ነው)", or: "Indeeksa Humna Dubartii (olfaan caala)", ti: "መርበብ ስልጣን ኣንስትዮ (ልዑል ዝበለጸ እዩ)", so: "Indeksiga Awooddarinta Haweenka (kor uu ka fiican yahay)", af: "Indeeksa Humna Dubartii (olfaan caala)" } } } } }, insights: { title: { en: `:::insight_string::: for :::admin_selection:::`, am: `:::insight_string::: ለ :::admin_selection:::`, or: `:::insight_string::: :::admin_selection::: irratti`, ti: `:::insight_string::: ን :::admin_selection:::`, so: `:::insight_string::: :::admin_selection::: u`, af: `:::insight_string::: :::admin_selection::: irratti` }, madLib: { en: `**:::admin:::**: the education index is **:::index_edu:::**, the female empowerment index is **:::index_fem:::**, and the poverty index is **:::index_pov:::**.`, am: `**:::admin:::**: የትምህርት መረጃ ጠቋሚ **:::index_edu:::** ነው, የሴቶች ኃይል መረጃ ጠቋሚ **:::index_fem:::** ነው, እና የድህነት መረጃ ጠቋሚ **:::index_pov:::** ነው።`, or: `**:::admin:::**: indeeksi barumsaa **:::index_edu:::**, indeeksi humna dubartii **:::index_fem:::**, fi indeeksi hiyyummaa **:::index_pov:::**.`, ti: `**:::admin:::**: መርበብ ትምህርት **:::index_edu:::**, መርበብ ስልጣን ኣንስትዮ **:::index_fem:::**, ከምኡውን መርበብ ድኽነት **:::index_pov:::**.`, so: `**:::admin:::**: indeksiga waxbarashadu waa **:::index_edu:::**, indeksiga awooddarinta haweenku waa **:::index_fem:::**, iyo indeksiga faqrigu waa **:::index_pov:::**.`, af: `**:::admin:::**: indeeksi barumsaa **:::index_edu:::**, indeeksi humna dubartii **:::index_fem:::**, fi indeeksi hiyyummaa **:::index_pov:::**.` }, nestedLocationBlurb: { en: `**:::admin_inner:::** is located within **:::admin_outer:::**.`, am: `**:::admin_inner:::** በ**:::admin_outer:::** ውስጥ ይገኛል።`, or: `**:::admin_inner:::** **:::admin_outer:::** keessatti argama.`, ti: `**:::admin_inner:::** ኣብ **:::admin_outer:::** ውሽጢ ይርከብ።`, so: `**:::admin_inner:::** waxaa ku yaala **:::admin_outer:::**.`, af: `**:::admin_inner:::** **:::admin_outer:::** keessatti argama.` } }, delvingDeeper: { h2: { en: "Delving Deeper", am: "ወደ ጥልቀት መሄድ", or: "Gadi Fagoo Seenuu", ti: "ናብ ዕምቆት ምኻድ", so: "Ku Dhufasho Qoto Dheer", af: "Gadi Fagoo Seenuu" }, intro: { en: "By analyzing overlays of poverty levels, education attainment, and female empowerment, you can gain additional insights into the diverse challenges and opportunities faced by communities. This deeper understanding of barriers to adaptation can help you to identify the localized context in which climate risk needs to be addressed.", am: "የድህነት ደረጃ፣ የትምህርት ደረጃ እና የሴቶች ኃይል ንብርብሮችን በመተንተን ማህበረሰቦች የሚያጋጥሟቸውን የተለያዩ ፈተናዎች እና እድሎች ላይ ተጨማሪ ግንዛቤ ማግኘት ይችላሉ። ይህ ለማስተካከያ እንቅፋቶች ጥልቀት ያለው ግንዛቤ የአየር ንብረት አደጋ መፍትሄ የሚገኝበትን የአካባቢ አውድ ለመለየት ይረዳዎታል።", or: "Sadarkaa hiyyummaa, qabiyyee barumsaa, fi humna dubartii dhiyaannoo firamuun, dursaa fi carraawwan adda addaa ummatni qunnatan irratti hubannoo dabalataa argachuu dandeessa. Kana hubannoo gadi fagoo dhowwii walqixxummaa gochuu keessatti naannoo adda addaa balaa haala qilleensaa itti gaafatamuu qabu filatamuu keessatti si gargaara.", ti: `ብምዕራፍ ደረጃ ድኽነት፣ ደረጃ ትምህርት፣ ከምኡውን ስልጣን ኣንስትዮ ተጠቒምካ፣ ንዝተፈላለዩ ሸገራትን ኣጋጣሚታትን ማሕበረሰብታት ዚጋጥሞም ተወሳኺ ርድኢት ክትረክብ ትኽእል ኢኻ። እዚ ዝበለጸ ርድኢት ናይ እንቅፋት ምምሕያሽ ንኸተርእ ኣብ ዝተፈላለየ ከባቢታት ሓደጋ ኩነታት ኣየር ንምፍታሽ ክትረድእ ይሕግዘካ።`, so: `Markaad falanqeeyo heerarka faqriga, heerka waxbarashada, iyo awooddarinta haweenka, waxaad ka heli kartaa fahamo dheeraad ah oo ku saabsan caqabadaha kala duwan iyo fursadaha ay wajahaan bulshada. Fahamkan qoto dheer ee caqabadaha isbeddelka waxay kaa caawin kartaa in aad u ogaato xaaladaha gobollada ee ay tahay in la xalliyo khatarka cimilada.`, af: "Sadarkaa hiyyummaa, qabiyyee barumsaa, fi humna dubartii dhiyaannoo firamuun, dursaa fi carraawwan adda addaa ummatni qunnatan irratti hubannoo dabalataa argachuu dandeessa. Kana hubannoo gadi fagoo dhowwii walqixxummaa gochuu keessatti naannoo adda addaa balaa haala qilleensaa itti gaafatamuu qabu filatamuu keessatti si gargaara." }, plot: { legend: { domain: { en: ["Better", "Moderate", "Worse"], am: ["የተሻለ", "መካከለኛ", "የተጣለ"], or: ["Caala", "Giddu galeessa", "Hammaate"], ti: ["ዝበለጸ", "መንጎመንጎ", "ዝገደደ"], so: ["Fiican", "Dhexdhexaad", "Xun"], af: ["Caala", "Giddu galeessa", "Hammaate"] } }, nameMap: { population: { en: "Total Population", am: "ጠቅላላ ሕዝብ", or: "Ummata Waliigalaa", ti: "ጠቕላላ ህዝቢ", so: "Wadarta Dadweynaha", af: "Ummata Waliigalaa" }, poverty0: { en: "Low Poverty", am: "ዝቅተኛ ድህነት", or: "Hiyyummaa Gadi aanaa", ti: "ንእሽቶ ድኽነት", so: "Faqri Hooseeya", af: "Hiyyummaa Gadi aanaa" }, poverty1: { en: "Moderate Poverty", am: "መካከለኛ ድህነት", or: "Hiyyummaa Giddu galeessa", ti: "መንጎመንጎ ድኽነት", so: "Faqri Dhexdhexaad", af: "Hiyyummaa Giddu galeessa" }, poverty2: { en: "High Poverty", am: "ከፍተኛ ድህነት", or: "Hiyyummaa Ol aanaa", ti: "ልዑል ድኽነት", so: "Faqri Sare", af: "Hiyyummaa Ol aanaa" }, education0: { en: "0-1 Years of Education", am: "0-1 ዓመት ትምህርት", or: "0-1 Waggaa Barumsaa", ti: "0-1 ዓመት ትምህርቲ", so: "0-1 Sano Waxbarasho", af: "0-1 Waggaa Barumsaa" }, education1: { en: "1-5 Years of Education", am: "1-5 ዓመት ትምህርት", or: "1-5 Waggaa Barumsaa", ti: "1-5 ዓመት ትምህርቲ", so: "1-5 Sano Waxbarasho", af: "1-5 Waggaa Barumsaa" }, education2: { en: "5+ Years of Education", am: "5+ ዓመት ትምህርት", or: "5+ Waggaa Barumsaa", ti: "5+ ዓመት ትምህርቲ", so: "5+ Sano Waxbarasho", af: "5+ Waggaa Barumsaa" }, gender0: { en: "Low Female Empowerment", am: "ዝቅተኛ የሴቶች ኃይል", or: "Humna Dubartii Gadi aanaa", ti: "ንእሽቶ ስልጣን ኣንስትዮ", so: "Awooddarinta Hooseeya Haweenka", af: "Humna Dubartii Gadi aanaa" }, gender1: { en: "Moderate Female Empowerment", am: "መካከለኛ የሴቶች ኃይል", or: "Humna Dubartii Giddu galeessa", ti: "መንጎመንጎ ስልጣን ኣንስትዮ", so: "Awooddarinta Dhexdhexaad Haweenka", af: "Humna Dubartii Giddu galeessa" }, gender2: { en: "High Female Empowerment", am: "ከፍተኛ የሴቶች ኃይል", or: "Humna Dubartii Ol aanaa", ti: "ልዑል ስልጣን ኣንስትዮ", so: "Awooddarinta Sare Haweenka", af: "Humna Dubartii Ol aanaa" } } } } }, summary: { h1: { en: "Summary", am: "ማጠቃለያ", or: "Xumura", ti: "ጽማቝ", so: "Soo koobid", af: "Xumura" }, blocks: { dynamicSummary: { intro: { en: `The people of **:::admin0:::** need to be ready with strategies to make crops and livestock more resilient to combat the changing climate.`, am: `የ**:::admin0:::** ሕዝብ ምርቶችን እና እንስሳትን ከሚቀየረው አየር ንብረት ለመከላከል የበለጠ የሚቋቋሙ ለማድረግ በስትራቴጂዎች መዘጋጀት አለባቸው።`, or: `Ummata **:::admin0:::** stratejiiwwan mirayaafi beyladaa haala qilleensaa jijjiiramaa irratti tolfachuuf dandeettii ol aanaa qabuuf qophaa'uu qaba.`, ti: `ህዝቢ **:::admin0:::** ኣትክልትን እንስሳትን ንለውጢ ኩነታት ኣየር ንምክላኽ ዝያዳ ዚቋቋሙ ንምግባር ብስትራተጂታት ክዳግሙ ኣለዎም።`, so: `Dadka **:::admin0:::** waxay u baahan yihiin in ay diyaar u yihiin siyaabado loo sameeyo beeraha iyo xoolaha in ay awood ugu yeeshaan in ay la tacaalaan cimilada isbeddesha.`, af: `Ummata **:::admin0:::** stratejiiwwan mirayaafi beyladaa haala qilleensaa jijjiiramaa irratti tolfachuuf dandeettii ol aanaa qabuuf qophaa'uu qaba.` } }, closer: { en: "This work aims to enhance crop variety and livestocks breed, reduce emissions, promote sustainable land management, and educate and train populations on climate-smart agriculture practices.", am: "ይህ ሥራ የምርት ዓይነት እና የእንስሳት ዝርያ ማሻሻል፣ የማምረቻ መጠን መቀነስ፣ ዘላቂ የመሬት አስተዳደር ማስተዋወቅ እና ሕዝቡን በአየር ንብረት-የሚስተካከል የሥርዓተ እርሻ ተግባራት ማሰልጠን ያለመ ነው።", or: "Hojii kana kaayyoo gosa mirayaafi beyladaa fooyyessuu, ba'aa hir'isuu, bulchiinsa lafa dhaabbataa daddaaqsiisuu, fi ummata qonnaan bishaan haala qilleensaa irratti hojjetu barsiisuu fi o'achuu dha.", ti: "እዚ ስራሕ እዚ ዓይነት ኣትክልትን ዝርያ እንስሳትን ንምህዳእ፣ ምትላል ንምንካይ፣ ምምሕያሽ መሬት ዘለዎ ዘለኣለማዊ ምምሕያሽ ንምድጋፍ፣ ከምኡውን ህዝቢ ኣብ ሕርሻ ብማዕረ ኩነታት ኣየር ንምምሕያሽ ንምትምህርትን ምድላን ይውከል።", so: "Hawshani waxay ujeeddo in ay horumariyo kala duwanaanta beeraha iyo noocyada xoolaha, yareeyo dhaca, kor u qaado maareynta dhulka oo aan dhimanayn, oo waxbaro oo tababaro dadweynaha hababka beerista cimilada ee cilmiga ah.", af: "Hojii kana kaayyoo gosa mirayaafi beyladaa fooyyessuu, ba'aa hir'isuu, bulchiinsa lafa dhaabbataa daddaaqsiisuu, fi ummata qonnaan bishaan haala qilleensaa irratti hojjetu barsiisuu fi o'achuu dha." } }, dynamicSummarylist: { en: `A range of strategies and policies can be implemented in support of researching and addressing the impact of climate change on agriculture, including: :::markdownList:::`, am: `የአየር ንብረት ለውጥ በሥርዓተ እርሻ ላይ ያለውን ተጽዕኖ ለማጥናት እና ለመፍታት የሚደግፉ በርካታ ስትራቴጂዎች እና ፖሊሲዎች ሊተገበሩ ይችላሉ፣ ከነዚህም መካከል: :::markdownList:::` } }, methods: { ...nbTextMethods.methods } }; }5e:T2920,dataGeoImpact = { let admin_query; console.log("DEBUG: dataGeoImpact - Current selections:", { admin0: adminSelections.selectAdmin0?.value, admin1: adminSelections.selectAdmin1?.value, admin2: adminSelections.selectAdmin2?.value, admin3: adminSelections.selectAdmin3?.value }); if (adminSelections.selectAdmin2.value && adminSelections.selectAdmin0.value !== "Ethiopia") { admin_query = `WHERE admin0_name = '${adminSelections.selectAdmin0.value}' AND admin1_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin1.value)}' AND admin2_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin2.value)}'`; } else if (adminSelections.selectAdmin1.value) { if (adminSelections.selectAdmin0.value === "Ethiopia") { admin_query = `WHERE admin0_name = '${adminSelections.selectAdmin0.value}' AND admin1_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin1.value)}' AND admin2_name IS NOT NULL`; console.log("DEBUG: Using Ethiopia-specific query (admin2_name IS NOT NULL)"); } else { admin_query = `WHERE admin0_name = '${adminSelections.selectAdmin0.value}' AND admin1_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin1.value)}' AND admin2_name IS NOT NULL`; console.log("DEBUG: Using normal country query (admin2_name IS NOT NULL)"); } } else if (adminSelections.selectAdmin0.value) { admin_query = `WHERE admin0_name = '${adminSelections.selectAdmin0.value}' AND admin1_name IS NOT NULL AND admin2_name IS NULL`; } else { admin_query = `WHERE admin1_name IS NULL`; } console.log("DEBUG: dataGeoImpact - Final SQL query:", admin_query); // Get data for choropleth map based on choice, unless admin3 for Ethiopia let dataSource; if (adminSelections.selectAdmin2.value && !adminSelections.selectAdmin3.value && adminSelections.selectAdmin0.value === "Ethiopia") { const dataColumn = selectGeoDataType.dataColumn; // rural_pop or vop_total const a2_name = adminSelections.selectAdmin2.value; const a1_name = adminSelections.selectAdmin1.value; console.log("DEBUG: Using mock admin3 data for:", a2_name); // Use mockWoredaData directly for admin3 data dataSource = mockWoredaData .filter(d => d.admin0_name === adminSelections.selectAdmin0.value && d.admin1_name === a1_name && d.admin2_name === a2_name && d.admin3_name // Only admin3 rows have admin3_name populated ) .map(d => ({ admin0_name: d.admin0_name, admin1_name: d.admin1_name, admin2_name: d.admin2_name, admin3_name: d.admin3_name, [dataColumn]: d[dataColumn] || 0, rural_pop: d.rural_pop || 0, urban_pop: d.urban_pop || 0, vop_total: d.vop_total || 0, a3_a2_a1_a0: [d.admin3_name, d.admin2_name, d.admin1_name, d.admin0_name].join("_"), gender_men: d.gender_men || 0.5, gender_women: d.gender_women || 0.5 })); if (dataSource.length === 0) { console.warn("No mock data found for selected admin2:", a2_name); dataSource = []; } else { console.log("DEBUG: Loaded mock admin3 data rows from table:", dataSource.length); } } else if (selectGeoDataType.key == "urban_population") { // Urban population uses mock data at all admin levels console.log("DEBUG: Using mock data for urban population at all levels"); // Filter mock data based on admin selections let filteredMock = mockWoredaData; if (adminSelections.selectAdmin0.value) { filteredMock = filteredMock.filter(d => d.admin0_name === adminSelections.selectAdmin0.value ); } if (adminSelections.selectAdmin1.value) { filteredMock = filteredMock.filter(d => d.admin1_name === adminSelections.selectAdmin1.value ); } if (adminSelections.selectAdmin2.value) { filteredMock = filteredMock.filter(d => d.admin2_name === adminSelections.selectAdmin2.value ); } if (adminSelections.selectAdmin3.value) { filteredMock = filteredMock.filter(d => d.admin3_name === adminSelections.selectAdmin3.value ); } // Determine which admin level we're displaying if (!adminSelections.selectAdmin0.value) { // Admin0 level - aggregate by country const aggregated = {}; filteredMock.forEach(d => { if (!d.admin1_name && d.admin0_name) { const key = d.admin0_name; if (!aggregated[key]) { aggregated[key] = { admin0_name: d.admin0_name, admin1_name: null, admin2_name: null, admin3_name: null, urban_pop: 0, rural_pop: 0, vop_total: 0 }; } aggregated[key].urban_pop += (d.urban_pop || 0); } }); dataSource = Object.values(aggregated); } else if (!adminSelections.selectAdmin1.value) { // Admin1 level - aggregate by region const aggregated = {}; filteredMock.forEach(d => { if (d.admin1_name && !d.admin2_name && d.admin0_name === adminSelections.selectAdmin0.value) { const key = `${d.admin1_name}_${d.admin0_name}`; if (!aggregated[key]) { aggregated[key] = { admin0_name: d.admin0_name, admin1_name: d.admin1_name, admin2_name: null, admin3_name: null, urban_pop: 0, rural_pop: 0, vop_total: 0 }; } aggregated[key].urban_pop += (d.urban_pop || 0); } }); dataSource = Object.values(aggregated); } else if (!adminSelections.selectAdmin2.value) { // Admin2 level - aggregate by subregion const aggregated = {}; filteredMock.forEach(d => { if (d.admin2_name && !d.admin3_name && d.admin1_name === adminSelections.selectAdmin1.value && d.admin0_name === adminSelections.selectAdmin0.value) { const key = `${d.admin2_name}_${d.admin1_name}_${d.admin0_name}`; if (!aggregated[key]) { aggregated[key] = { admin0_name: d.admin0_name, admin1_name: d.admin1_name, admin2_name: d.admin2_name, admin3_name: null, urban_pop: 0, rural_pop: 0, vop_total: 0 }; } aggregated[key].urban_pop += (d.urban_pop || 0); } }); dataSource = Object.values(aggregated); } else if (!adminSelections.selectAdmin3.value) { // Admin3 level - show individual woredas dataSource = filteredMock .filter(d => d.admin3_name && d.admin2_name === adminSelections.selectAdmin2.value && d.admin1_name === adminSelections.selectAdmin1.value && d.admin0_name === adminSelections.selectAdmin0.value) .map(d => ({ admin0_name: d.admin0_name, admin1_name: d.admin1_name, admin2_name: d.admin2_name, admin3_name: d.admin3_name, urban_pop: d.urban_pop || 0, rural_pop: d.rural_pop || 0, vop_total: d.vop_total || 0, gender_men: d.gender_men || 0.5, gender_women: d.gender_women || 0.5 })); } else { // Specific admin3 selected dataSource = filteredMock .filter(d => d.admin3_name === adminSelections.selectAdmin3.value && d.admin2_name === adminSelections.selectAdmin2.value && d.admin1_name === adminSelections.selectAdmin1.value && d.admin0_name === adminSelections.selectAdmin0.value) .map(d => ({ admin0_name: d.admin0_name, admin1_name: d.admin1_name, admin2_name: d.admin2_name, admin3_name: d.admin3_name, urban_pop: d.urban_pop || 0, rural_pop: d.rural_pop || 0, vop_total: d.vop_total || 0, gender_men: d.gender_men || 0.5, gender_women: d.gender_women || 0.5 })); } // Add gender data from mock for aggregated levels dataSource = dataSource.map(d => { const mockRow = mockWoredaData.find(m => (m.admin0_name?.trim().toLowerCase() || '') === (d.admin0_name?.trim().toLowerCase() || '') && (m.admin1_name?.trim().toLowerCase() || '') === (d.admin1_name?.trim().toLowerCase() || '') && (m.admin2_name?.trim().toLowerCase() || '') === (d.admin2_name?.trim().toLowerCase() || '') && (m.admin3_name?.trim().toLowerCase() || '') === (d.admin3_name?.trim().toLowerCase() || '') ); return { ...d, gender_men: mockRow ? mockRow.gender_men : 0.5, gender_women: mockRow ? mockRow.gender_women : 0.5 }; }); console.log("DEBUG: dataGeoImpact - Mock urban population rows:", dataSource.length); } else { dataSource = selectGeoDataType.key == "population" ? await dataPopulation(admin_query) : await dataTotalVoP(admin_query); console.log("DEBUG: dataGeoImpact - Query result rows:", dataSource.length); // Apply gender from mock for non-admin3 levels dataSource = dataSource.map(d => { const mockRow = mockWoredaData.find(m => (m.admin0_name?.trim().toLowerCase() || '') === (d.admin0_name?.trim().toLowerCase() || '') && (m.admin1_name?.trim().toLowerCase() || '') === (d.admin1_name?.trim().toLowerCase() || '') && (m.admin2_name?.trim().toLowerCase() || '') === (d.admin2_name?.trim().toLowerCase() || '') && (m.admin3_name?.trim().toLowerCase() || '') === (d.admin3_name?.trim().toLowerCase() || '') ); return { ...d, rural_pop: d.rural_pop || 0, vop_total: d.vop_total || 0, gender_men: mockRow ? mockRow.gender_men : 0.5, gender_women: mockRow ? mockRow.gender_women : 0.5 }; }); } // Log final result for debugging if (dataSource.length > 0) { console.log("DEBUG: dataGeoImpact - Final data sample:", { admin0: dataSource[0].admin0_name, admin1: dataSource[0].admin1_name, admin2: dataSource[0].admin2_name, admin3: dataSource[0].admin3_name, rural_pop: dataSource[0].rural_pop, urban_pop: dataSource[0].urban_pop, vop_total: dataSource[0].vop_total, hasVop: !!dataSource[0].vop_total }); } return dataSource; } 5f:T447,function getAdminSelection(selections=adminSelections) { // get the most granular admin selection made const a0 = selections.selectAdmin0 const a1 = selections.selectAdmin1 const a2 = selections.selectAdmin2 const a3 = selections.selectAdmin3 const global = globalSelection // Check if admin3 is selected (value is not null and not undefined) if (a3 && a3.value !== null && a3.value !== undefined) { // If a3 doesn't have a label property, use the value as the label // (since dataAdmin3 uses woreda name for both label and value) if (!a3.hasOwnProperty('label') || a3.label === undefined) { return { ...a3, label: a3.value } } return a3 } // Check if admin2 is selected if (a2 && a2.value !== null && a2.value !== undefined) { return a2 } // Check if admin1 is selected if (a1 && a1.value !== null && a1.value !== undefined) { return a1 } // Check if admin0 is selected if (a0 && a0.value !== null && a0.value !== undefined) { return a0 } // Return global selection as fallback return global }60:T8c2,function generateMockWoredaData(selections, realData) { if (!selections.selectAdmin2.value) return []; // Find the parent admin2 data to base our mock data on const parentAdmin2Data = realData.find(d => d.admin0_name === selections.selectAdmin0.value && d.admin1_name === selections.selectAdmin1.value && d.admin2_name === selections.selectAdmin2.value && !d.admin3_name // This should be the admin2-level row ); if (!parentAdmin2Data) { console.warn("No parent admin2 data found for mock woreda generation"); return []; } // Get all woredas for this admin2 const woredas = boundaries.admin3.features.filter(d => d.properties.admin0_name === selections.selectAdmin0.value && d.properties.admin1_name === selections.selectAdmin1.value && d.properties.admin2_name === selections.selectAdmin2.value ); const dataColumn = selectGeoDataType.dataColumn; // "rural_pop", "urban_pop", or "vop_total" const parentValue = parentAdmin2Data[dataColumn]; // Distribute the parent value randomly among woredas return woredas.map(woreda => { // Create random distribution (60-140% of average) const randomFactor = 0.6 + Math.random() * 0.8; const woredaValue = (parentValue / woredas.length) * randomFactor; return { admin0_name: selections.selectAdmin0.value, admin1_name: selections.selectAdmin1.value, admin2_name: selections.selectAdmin2.value, admin3_name: woreda.properties.admin3_name, [dataColumn]: woredaValue, // Include other columns that might be needed ...(dataColumn === "vop_total" ? { rural_pop: parentAdmin2Data.rural_pop / woredas.length * randomFactor, urban_pop: parentAdmin2Data.urban_pop / woredas.length * randomFactor } : {}), ...(dataColumn === "rural_pop" ? { vop_total: parentAdmin2Data.vop_total / woredas.length * randomFactor, urban_pop: parentAdmin2Data.urban_pop / woredas.length * randomFactor } : {}), ...(dataColumn === "urban_pop" ? { rural_pop: parentAdmin2Data.rural_pop / woredas.length * randomFactor, vop_total: parentAdmin2Data.vop_total / woredas.length * randomFactor } : {}) }; }); }61:Ta34,admin3_with_vop = { void admin3_cleaned; // Make it reactive if (!admin3_cleaned || !admin3_cleaned.features) { return { type: "FeatureCollection", features: [] }; } console.log("Creating enhanced admin3 data with", admin3_cleaned.features.length, "features"); // Create a proper deep copy const enhancedData = { type: "FeatureCollection", features: admin3_cleaned.features.map(feature => { const newFeature = JSON.parse(JSON.stringify(feature)); // Find matching mock data row with normalized matching, only for admin3 const mockRow = mockWoredaData.find(d => // Only match rows with non-empty admin3_name d.admin3_name && (d.admin0_name?.trim().toLowerCase() || '') === (newFeature.properties.admin0_name?.trim().toLowerCase() || '') && (d.admin1_name?.trim().toLowerCase() || '') === (newFeature.properties.admin1_name?.trim().toLowerCase() || '') && (d.admin2_name?.trim().toLowerCase() || '') === (newFeature.properties.admin2_name?.trim().toLowerCase() || '') && (d.admin3_name?.trim().toLowerCase() || '') === (newFeature.properties.admin3_name?.trim().toLowerCase() || '') ); // Initialize properties.data if not present if (!newFeature.properties.data) { newFeature.properties.data = {}; } if (mockRow) { // Use mock data values newFeature.properties.data.rural_pop = mockRow.rural_pop || 10000; newFeature.properties.data.vop_total = mockRow.vop_total || 0; newFeature.properties.data.gender_men = mockRow.gender_men || 0.5; newFeature.properties.data.gender_women = mockRow.gender_women || 0.5; // Log first few for verification if (admin3_cleaned.features.indexOf(feature) < 3) { console.log(`Enhanced: ${newFeature.properties.admin3_name}`, { rural_pop: newFeature.properties.data.rural_pop, vop_total: newFeature.properties.data.vop_total, gender_men: newFeature.properties.data.gender_men, gender_women: newFeature.properties.data.gender_women }); } } else { console.warn(`No mock data found for woreda: ${newFeature.properties.admin3_name}`); newFeature.properties.data.rural_pop = 10000; // Fallback newFeature.properties.data.vop_total = 0; // Fallback newFeature.properties.data.gender_men = 0.5; // Fallback newFeature.properties.data.gender_women = 0.5; // Fallback } return newFeature; }) }; return enhancedData; }62:T22fe,mapDataGeoImpact = { const selections = adminSelections; console.log("=== MAP DATA GEOIMPACT - FULL DEBUG ==="); console.log("All selections:", adminSelections); console.log("Is Ethiopia?", adminSelections.selectAdmin0.value === "Ethiopia"); console.log("Has region?", !!adminSelections.selectAdmin1.value); console.log("Has subregion?", !!adminSelections.selectAdmin2.value); console.log("DEBUG: Current selections:", { admin0: selections.selectAdmin0.value, admin1: selections.selectAdmin1.value, admin2: selections.selectAdmin2.value, admin3: selections.selectAdmin3.value }); // no selections - admin0 level if (!selections.selectAdmin0.value) { const geoData = { ...boundaries.admin0, features: boundaries.admin0.features.map(f => ({ ...f, properties: { ...f.properties, admin0_name: f.properties.admin0_name } })) }; const result = bindTabularToGeo({ data: dataGeoImpact, dataBindColumn: "admin0_name", geoData: geoData, geoDataBindColumn: "admin0_name", defaultData: { rural_pop: 0, urban_pop: 0, vop_total: 0, gender_men: 0.5, gender_women: 0.5 } }); console.log("DEBUG: Admin0 level - Features:", result.features.length); return result; } // admin0 selected only - admin1 level else if (!selections.selectAdmin1.value) { const data = T.tidy( dataGeoImpact, T.mutate({ a1_a0: (d) => [d.admin1_name || '', d.admin0_name].join("_") }) ); const geoData = { ...boundaries.admin1, features: boundaries.admin1.features.filter( (d) => d.properties.admin0_name == selections.selectAdmin0.value ).map(f => ({ ...f, properties: { ...f.properties, a1_a0: [f.properties.admin1_name, f.properties.admin0_name].join("_") } })) }; console.log("DEBUG: Admin1 level - Filtered features:", geoData.features.length); console.log("DEBUG: Admin1 level - Data rows:", data.length); console.log("DEBUG: Admin1 level - Sample data:", data.slice(0, 2)); const result = bindTabularToGeo({ data: data, dataBindColumn: "a1_a0", geoData: geoData, geoDataBindColumn: "a1_a0", defaultData: { rural_pop: 0, urban_pop: 0, vop_total: 0, gender_men: 0.5, gender_women: 0.5 } }); console.log("DEBUG: Admin1 level - Result features:", result.features.length); if (result.features.length > 0) { console.log("DEBUG: Admin1 level - Sample feature data:", result.features[0].properties.data); } return result; } // admin1 selected - admin2 level else if (!selections.selectAdmin2.value || selections.selectAdmin2.value === null) { const data = T.tidy( dataGeoImpact, T.mutate({ a2_a1_a0: (d) => [d.admin2_name || '', d.admin1_name, d.admin0_name].join("_") }) ); const geoData = { ...boundaries.admin2, features: boundaries.admin2.features.filter((d) => { return ( d.properties.admin1_name == selections.selectAdmin1.value && d.properties.admin0_name == selections.selectAdmin0.value ); }).map(f => ({ ...f, properties: { ...f.properties, a2_a1_a0: [f.properties.admin2_name, f.properties.admin1_name, f.properties.admin0_name].join("_") } })) }; console.log("DEBUG: Admin2 level - Filtered features:", geoData.features.length); console.log("DEBUG: Admin2 level - Data rows:", data.length); console.log("DEBUG: Admin2 level - Sample data:", data.slice(0, 2)); const result = bindTabularToGeo({ data: data, dataBindColumn: "a2_a1_a0", geoData: geoData, geoDataBindColumn: "a2_a1_a0", defaultData: { rural_pop: 0, urban_pop: 0, vop_total: 0, gender_men: 0.5, gender_women: 0.5 } }); console.log("DEBUG: Admin2 level - Result features:", result.features.length); if (result.features.length > 0) { console.log("DEBUG: Admin2 level - Sample feature data:", result.features[0].properties.data); } return result; } // admin2 selected - admin3 level (Ethiopia only) else if (!selections.selectAdmin3.value && selections.selectAdmin0.value === "Ethiopia") { console.log("DEBUG: Ethiopia - Showing admin3 woredas for selected subregion"); const geoData = { ...boundaries.admin3, features: boundaries.admin3.features.filter((d) => { return ( d.properties.admin2_name == selections.selectAdmin2.value && d.properties.admin1_name == selections.selectAdmin1.value && d.properties.admin0_name == selections.selectAdmin0.value ); }).map(f => ({ ...f, properties: { ...f.properties, a3_a2_a1_a0: [f.properties.admin3_name, f.properties.admin2_name, f.properties.admin1_name, f.properties.admin0_name].join("_") } })) }; console.log("DEBUG: Ethiopia Admin3 level - Filtered features:", geoData.features.length); if (geoData.features.length === 0) { console.warn("No admin3 features found for the selected subregion"); return { type: "FeatureCollection", features: [] }; } // Use mock data for admin3 const enhancedFeatures = geoData.features.map(feature => { const enhanced = JSON.parse(JSON.stringify(feature)); const mockRow = mockWoredaData.find(d => d.admin3_name === feature.properties.admin3_name && d.admin2_name === selections.selectAdmin2.value && d.admin1_name === selections.selectAdmin1.value ); if (mockRow) { enhanced.properties.data = { ...enhanced.properties.data, rural_pop: mockRow.rural_pop || 0, urban_pop: mockRow.urban_pop || 0, vop_total: mockRow.vop_total || 0, gender_men: mockRow.gender_men || 0.5, gender_women: mockRow.gender_women || 0.5 }; } else { console.warn("No mock data for woreda:", feature.properties.admin3_name); enhanced.properties.data = { ...enhanced.properties.data, rural_pop: 0, urban_pop: 0, vop_total: 0, gender_men: 0.5, gender_women: 0.5 }; } return enhanced; }); return { ...geoData, features: enhancedFeatures }; } // admin3 selected - show specific woreda (Ethiopia only) else { if (selections.selectAdmin0.value !== "Ethiopia") { console.warn("Admin3 data only available for Ethiopia"); return { type: "FeatureCollection", features: [] }; } console.log("DEBUG: Ethiopia - Showing specific woreda"); const geoData = { ...boundaries.admin3, features: boundaries.admin3.features.filter((d) => { return ( d.properties.admin3_name == selections.selectAdmin3.value && d.properties.admin2_name == selections.selectAdmin2.value && d.properties.admin1_name == selections.selectAdmin1.value && d.properties.admin0_name == selections.selectAdmin0.value ); }).map(f => ({ ...f, properties: { ...f.properties, a3_a2_a1_a0: [f.properties.admin3_name, f.properties.admin2_name, f.properties.admin1_name, f.properties.admin0_name].join("_") } })) }; console.log("DEBUG: Ethiopia Admin3 level (single woreda) - Filtered features:", geoData.features.length); if (geoData.features.length === 0) { console.warn("No specific woreda found"); return { type: "FeatureCollection", features: [] }; } // Enhance with mock data const enhancedFeatures = geoData.features.map(feature => { const enhanced = JSON.parse(JSON.stringify(feature)); const mockRow = mockWoredaData.find(d => d.admin3_name === feature.properties.admin3_name && d.admin2_name === selections.selectAdmin2.value && d.admin1_name === selections.selectAdmin1.value ); if (mockRow) { enhanced.properties.data = { ...enhanced.properties.data, rural_pop: mockRow.rural_pop || 0, vop_total: mockRow.vop_total || 0, gender_men: mockRow.gender_men || 0.5, gender_women: mockRow.gender_women || 0.5 }; } else { console.warn("No mock data for selected woreda:", feature.properties.admin3_name); enhanced.properties.data = { ...enhanced.properties.data, rural_pop: 0, vop_total: 0, gender_men: 0.5, gender_women: 0.5 }; } return enhanced; }); return { ...geoData, features: enhancedFeatures }; } } 63:T23db,dynamicInsights_geoImpact = { // --- START OF CURRENCY CONVERSION LOGIC --- // Birr (no year) and Dollar (with year) for text insights - same as tooltips const formatBirrAndDollar = (dollarValue) => { if (dollarValue === null || dollarValue === undefined || isNaN(dollarValue)) return "---"; const birrStr = formatCurrencyToBirr(dollarValue, { year: intDollarYear, includeCurrency: true, missingValue: "---" }).replace("2005 ", ""); const dollarStr = "2005 Int$" + formatUSD({locale: language.locale})(dollarValue).replace("$", ""); return `${birrStr} | ${dollarStr}`; }; const _formatTopNVop = formatBirrAndDollar; // --- END OF CURRENCY CONVERSION LOGIC --- let admin2_null = !selectAdmin2.value let admin3_selected = selectAdmin3?.value && adminSelections.selectAdmin0.value === "Ethiopia" // format functions const locale = language.locale; const _formatNumber = formatNumCompactLong({locale: locale}); function getTopValue({ d, i } = {}) { // If d is empty or undefined, return "---" for both value and label if (!d || d.length === 0 || !d[i]) { return { data: undefined, value: "---", label: "---" }; } return { data: d?.[i]?.vop_total, value: formatWithDefault({ value: d?.[i]?.vop_total, format: _formatTopNVop }), label: formatWithDefault({ value: d?.[i]?.crop }) }; } // If admin3 is selected, use woreda tables (mock_exposure_woreda) if (admin3_selected) { const mockRow = mockWoredaData.find(m => m.admin0_name === adminSelections.selectAdmin0.value && m.admin1_name === adminSelections.selectAdmin1.value && m.admin2_name === adminSelections.selectAdmin2.value && m.admin3_name === selectAdmin3.value ); // Debug: Check what's in the table const debugTable = await db.query(` SELECT crop, value FROM vop_crop_woreda WHERE admin0_name = '${adminSelections.selectAdmin0.value}' AND admin1_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin1.value)}' AND admin2_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin2.value)}' AND admin3_name = '${cleanAdminInput_SQL(selectAdmin3.value)}' ORDER BY crop `); console.log("🔵 [Woreda Insights] Raw table data:", JSON.stringify(debugTable, null, 2)); // Query woreda-level data from woreda tables const [woredaVopTotals, woredaHaTotals, rawCropData, woredaRankedAnimals] = await Promise.all([ db.query(` SELECT SUM(CAST(value AS DOUBLE)) AS vop_total FROM vop_woreda WHERE admin0_name = '${adminSelections.selectAdmin0.value}' AND admin1_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin1.value)}' AND admin2_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin2.value)}' AND admin3_name = '${cleanAdminInput_SQL(selectAdmin3.value)}' `), db.query(` SELECT SUM(CAST(value AS DOUBLE)) AS ha_total FROM ha_woreda WHERE admin0_name = '${adminSelections.selectAdmin0.value}' AND admin1_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin1.value)}' AND admin2_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin2.value)}' AND admin3_name = '${cleanAdminInput_SQL(selectAdmin3.value)}' `), db.query(` -- Get all crop data - we'll aggregate in JavaScript SELECT crop, CAST(value AS DOUBLE) AS value FROM vop_crop_woreda WHERE admin0_name = '${adminSelections.selectAdmin0.value}' AND admin1_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin1.value)}' AND admin2_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin2.value)}' AND admin3_name = '${cleanAdminInput_SQL(selectAdmin3.value)}' ORDER BY crop `), db.query(` -- Normalize and aggregate livestock types WITH livestock_normalized AS ( SELECT CASE WHEN crop LIKE 'cattle%' THEN 'cattle' WHEN crop LIKE 'goat%' OR crop = 'goats' THEN 'goats' WHEN crop LIKE 'pig%' OR crop = 'pigs' THEN 'pigs' WHEN crop LIKE 'poultry%' THEN 'poultry' WHEN crop LIKE 'sheep%' THEN 'sheep' WHEN crop LIKE 'donkey%' OR LOWER(crop) LIKE '%donkey%' THEN 'donkey' WHEN crop LIKE 'camel%' THEN 'camel' ELSE crop END AS crop_normalized, CAST(value AS DOUBLE) AS vop_total FROM vop_animal_woreda WHERE admin0_name = '${adminSelections.selectAdmin0.value}' AND admin1_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin1.value)}' AND admin2_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin2.value)}' AND admin3_name = '${cleanAdminInput_SQL(selectAdmin3.value)}' ), livestock_aggregated AS ( SELECT crop_normalized AS crop, SUM(CAST(vop_total AS DOUBLE)) AS vop_total FROM livestock_normalized GROUP BY crop_normalized ) SELECT crop, vop_total FROM livestock_aggregated ORDER BY vop_total DESC LIMIT 3 `) ]); // Aggregate crop varieties in JavaScript (since SQL aggregation wasn't working correctly) const aggregated = {}; for (const row of rawCropData) { const baseCrop = row.crop && row.crop.includes('_') ? row.crop.split('_')[0] : row.crop; if (baseCrop) { if (!aggregated[baseCrop]) { aggregated[baseCrop] = 0; } aggregated[baseCrop] += row.value || 0; } } // Convert to array and sort const woredaRankedNonAnimals = Object.entries(aggregated) .map(([crop, vop_total]) => ({ crop, vop_total })) .sort((a, b) => b.vop_total - a.vop_total) .slice(0, 3); console.log("🔵 [Woreda Insights] Aggregated crops:", JSON.stringify(woredaRankedNonAnimals, null, 2)); // Format the data to match expected structure // Note: woreda data values are now in USD (matching original vop_ha structure) const totalVopValue = woredaVopTotals[0]?.vop_total || (mockRow ? mockRow.vop_total : NaN); const totalHaValue = woredaHaTotals[0]?.ha_total || NaN; // Format ranked data with ranks const formattedTopCommodities = (woredaRankedNonAnimals || []).map((item, index) => { return { crop: item.crop, vop_total: item.vop_total, rank: index + 1 }; }); const formattedTopLivestock = woredaRankedAnimals.map((item, index) => ({ ...item, rank: index + 1 })); return { data: { totalVop: [{ vop_total: totalVopValue }], totalHa: [{ ha_total: totalHaValue }], population: mockRow ? [{ rural_pop: mockRow.rural_pop, total_pop: (mockRow.rural_pop || 0) + (mockRow.urban_pop || 0) }] : [{ rural_pop: NaN, total_pop: NaN }], topCommodities: formattedTopCommodities, topLivestock: formattedTopLivestock }, insight: { totalVop: formatWithDefault({ value: totalVopValue, format: _formatTopNVop }), totalHa: formatWithDefault({ value: totalHaValue, format: _formatNumber }), totalPop: formatWithDefault({ value: mockRow ? ((mockRow.rural_pop || 0) + (mockRow.urban_pop || 0)) : NaN, format: _formatNumber }), topCommodities: [0, 1, 2].map((x) => getTopValue({ d: formattedTopCommodities, i: x }) ), topLivestock: [0, 1, 2].map((x) => getTopValue({ d: formattedTopLivestock, i: x }) ), } }; } // define data for admin0/admin1/admin2 levels const totalVop = admin2_null ? dynInsightGeo_vopTotals : filterByAdminNames(dynInsightGeo_vopTotals); const totalHa = admin2_null ? dynInsightGeo_haTotals: filterByAdminNames(dynInsightGeo_haTotals); const population = admin2_null ? dynInsightGeo_population : filterByAdminNames(dynInsightGeo_population); const topCommodities = admin2_null ? dynInsightGeo_rankedNonAnimals: filterByAdminNames(dynInsightGeo_rankedNonAnimals); const topLivestock = admin2_null ? dynInsightGeo_rankedAnimals : filterByAdminNames(dynInsightGeo_rankedAnimals); // make insights ------------------------------------ return { data: { totalVop, totalHa, population, topCommodities, topLivestock }, insight: { totalVop: formatWithDefault({ value: totalVop?.[0]?.vop_total, format: _formatTopNVop }), totalHa: formatWithDefault({ value: totalHa?.[0]?.ha_total, format: _formatNumber }), totalPop: formatWithDefault({ value: population?.[0]?.rural_pop, format: _formatNumber }), topCommodities: [0, 1, 2].map((x) => getTopValue({ d: topCommodities, i: x }) ), topLivestock: [0, 1, 2].map((x) => getTopValue({ d: topLivestock, i: x }) ), } }; } 64:T493,insight_adminQuery = { let admin_query // If admin3 is selected, we'll use mock data, so return a query that won't match anything // (admin3 data comes from mockWoredaData, not database) if (adminSelections.selectAdmin3?.value && adminSelections.selectAdmin0.value === "Ethiopia") { admin_query = `WHERE 1=0` // Return empty result, mock data will be used instead } else if (adminSelections.selectAdmin2?.value) { admin_query = `WHERE admin0_name = '${adminSelections.selectAdmin0.value}' AND admin1_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin1.value)}' AND admin2_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin2.value)}'` } else if (adminSelections.selectAdmin1.value) { admin_query = `WHERE admin0_name = '${adminSelections.selectAdmin0.value}' AND admin1_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin1.value)}' AND admin2_name IS NOT NULL` } else if (adminSelections.selectAdmin0.value) { admin_query = `WHERE admin0_name = '${adminSelections.selectAdmin0.value}' AND admin1_name IS NOT NULL AND admin2_name IS NULL` } else { admin_query = `WHERE admin1_name IS NULL` } return admin_query } 65:T50f,dynInsightGeo_rankedNonAnimals = { let admin_query = insight_adminQuery let data = await db.query(` -- Combine global totals with regional data WITH tbl_vop AS ( -- Fetch the base data for NON-animals SELECT admin0_name, admin1_name, admin2_name, crop, value AS vop_total FROM vop_crop ${admin_query} ), -- Calculate global totals (where admin names are null) global_total_crop AS ( SELECT NULL AS admin0_name, NULL AS admin1_name, NULL AS admin2_name, crop, SUM(vop_total) AS vop_total FROM tbl_vop GROUP BY crop ) -- Combine global totals with regional data SELECT * FROM global_total_crop UNION ALL SELECT * FROM tbl_vop ORDER BY admin0_name, admin1_name, admin2_name, vop_total DESC `) const groupedData = data.reduce((acc, item) => { const key = `${item.admin0_name}-${item.admin1_name}-${item.admin2_name}`; if (!acc[key]) acc[key] = []; acc[key].push(item); return acc; }, {}); // Rank within each group const rankedData = Object.values(groupedData).flatMap(group => { return group.sort((a, b) => b.vop_total - a.vop_total).slice(0, 3).map((item, index) => ({ ...item, rank: index + 1 })); }); return rankedData }66:T788,dynInsightGeo_rankedAnimals = { let admin_query = insight_adminQuery let data = await db.query(` -- Simplified SQL query to fetch animal data, including global totals WITH tbl_base AS ( -- Base animal data grouped by crop type SELECT admin0_name, admin1_name, admin2_name, CASE WHEN crop LIKE 'cattle\_%' ESCAPE '\\' THEN 'cattle' WHEN crop LIKE 'goats\_%' ESCAPE '\\' THEN 'goats' WHEN crop LIKE 'pigs\_%' ESCAPE '\\' THEN 'pigs' WHEN crop LIKE 'poultry\_%' ESCAPE '\\' THEN 'poultry' WHEN crop LIKE 'sheep\_%' ESCAPE '\\' THEN 'sheep' ELSE 'other' END AS crop, SUM(value) AS vop_total FROM vop_animal ${admin_query} GROUP BY admin0_name, admin1_name, admin2_name, crop ), -- Global totals where admin names are null global_total_animal AS ( SELECT NULL AS admin0_name, NULL AS admin1_name, NULL AS admin2_name, crop, SUM(vop_total) AS vop_total FROM tbl_base GROUP BY crop ) -- Combine global totals with the base data SELECT * FROM global_total_animal UNION ALL SELECT * FROM tbl_base ORDER BY admin0_name, admin1_name, admin2_name, vop_total DESC `); const groupedData = data.reduce((acc, item) => { const key = `${item.admin0_name || 'TOTAL'}-${item.admin1_name || 'TOTAL'}-${item.admin2_name || 'TOTAL'}`; if (!acc[key]) acc[key] = []; acc[key].push(item); return acc; }, {}); // Rank within each group const rankedData = Object.entries(groupedData).flatMap(([key, group]) => { // Sort by value within the group const sortedGroup = group.sort((a, b) => b.value - a.value); // Take the top 3 crops for each region const top3 = sortedGroup.slice(0, 3).map((item, index) => ({ ...item, rank: index + 1 })); return top3; }); return rankedData }67:Tdae,makeTopCropBarChart = {return( function makeTopCropBarChart(data, {marginLeft=100}={}) { // --- START OF CURRENCY CONVERSION LOGIC --- const DOLLAR_TO_BIRR_RATE = usdToEtbExchangeRate; // Function to convert a numerical dollar value to a Birr-formatted string for tooltips const formatBirr = (dollarValue) => { if (dollarValue === null || dollarValue === undefined || isNaN(dollarValue)) return "---"; const birrValue = dollarValue * DOLLAR_TO_BIRR_RATE; let birrOutput; let newMagnitudeLabel = ''; if (birrValue >= 1000000000000) { newMagnitudeLabel = 'T'; birrOutput = (birrValue / 1000000000000).toFixed(1); } else if (birrValue >= 1000000000) { newMagnitudeLabel = 'B'; birrOutput = (birrValue / 1000000000).toFixed(1); } else if (birrValue >= 1000000) { newMagnitudeLabel = 'M'; birrOutput = (birrValue / 1000000).toFixed(1); } else { birrOutput = Math.round(birrValue).toLocaleString(language.locale); } return `2005 ETB${birrOutput}${newMagnitudeLabel}`; }; // Function to show both Birr and Dollar in tooltips (bar chart) - Birr without year, Dollar with year const formatBirrAndDollar = (dollarValue) => { if (dollarValue === null || dollarValue === undefined || isNaN(dollarValue)) return "---"; const birrStr = formatBirr(dollarValue).replace("2005 ", ""); const dollarStr = "2005 Int$" + formatUSD({locale: language.locale})(dollarValue).replace("$", ""); return `${birrStr} | ${dollarStr}`; }; // Function to format Birr for axis ticks (converts USD value to ETB and formats) const formatBirrAxis = (dollarValue) => { if (dollarValue === null || dollarValue === undefined || isNaN(dollarValue)) return ""; const birrValue = dollarValue * DOLLAR_TO_BIRR_RATE; // Format the number using the same formatter as formatUSD but without the dollar sign // The axis label already indicates the currency is ETB const formatter = formatUSD({locale: language.locale}); const formatted = formatter(birrValue); // Replace $ with ETB or just remove it (since label already says ETB) return formatted.replace('$', 'ETB'); }; // --- END OF CURRENCY CONVERSION LOGIC --- const vopCaption = _lang(nbText.vopNoteMd.caption); const vopLabel = _lang( nbText.climateRisks.hazardImpact.plots.general.vopLabel ); const noDataMessage = _lang(nbText.climateRisks.hazardImpact.plots.general.noPlotMessage) // if no data is available for selected hazard, show a message if (data.length == 0) { return md`*${noDataMessage}*`; } const topN = 10; return Plot.plot({ width, marginLeft, caption: vopCaption, x: { tickFormat: formatBirrAxis, label: `${vopLabel} (2005 ETB)`, grid: true }, y: { label: null, tickSize: 0 }, color: { domain: hazardPlotLookup.color.domain, range: hazardPlotLookup.color.range }, marks: [ Plot.barX(data, { x: "vop", y: (d) => hazardPlotLookup.crops[d.crop], fill: (d) => hazardPlotLookup.names[d.hazard], sort: { y: "x", reverse: true, limit: 10 }, channels: { vop: { label: vopLabel, value: "vop" } }, tip: { format: { x: false, y: false, fill: false, vop: (d) => formatBirrAndDollar(d) } } }) ] }); } )} 68:T627,// formatting crop names cropNames = { const raw = T.tidy( hazardCrops, T.distinct("crop"), T.select("crop"), T.mutate({ type: (d) => { // Check if crop is in livestock list if (riskDataTypes.crop.livestock.includes(d.crop)) { return "livestock"; } // Check if crop is in crop list (including subspecies) if (riskDataTypes.crop.crop.includes(d.crop)) { return "crop"; } // Fallback to underscore pattern for legacy livestock (only if not in either list) return (/_/.test(d.crop) ? "livestock" : "crop"); } }), T.arrange(["type", "cropName"]) ); let data = raw; // translation const translateCrop = (crop) => td.crop.values?.[crop]; data = data.map((d) => { // Fallback to crop name if translation is missing const translation = translateCrop(d.crop); const translatedText = translation ? _lang(translation) : d.crop; const raw = translation ? _lang(translation) : d.crop; // Force it to a string, or fall back to the crop key const safeText = typeof raw === "string" ? raw : raw == null ? d.crop : String(raw); const arr = Lang.toSentenceCase(safeText).split("_"); const mainHalf = arr.slice(0, 1); const backHalf = arr .slice(1) .filter((d) => d !== "de") .join(" "); const paren = backHalf.length > 0 ? `(${backHalf})` : ""; const formatted = [...mainHalf, paren].join(" ").trimEnd(); return { ...d, cropName: formatted }; }); return data; }69:T59b,// lookups for hazard plot hazardPlotLookup = { const hazards = { wet: _lang(nbText.climateRisks.hazardImpact.hazards.wet), dry: _lang(nbText.climateRisks.hazardImpact.hazards.dry), heat: _lang(nbText.climateRisks.hazardImpact.hazards.heat), dry_heat: _lang(nbText.climateRisks.hazardImpact.hazards.dry_heat), dry_wet: _lang(nbText.climateRisks.hazardImpact.hazards.dry_wet), heat_wet: _lang(nbText.climateRisks.hazardImpact.hazards.heat_wet), dry_heat_wet: _lang(nbText.climateRisks.hazardImpact.hazards.dry_heat_wet), no_hazard: _lang(nbText.climateRisks.hazardImpact.hazards.no_hazard) }; return { names: { wet: hazards.wet, dry: hazards.dry, heat: hazards.heat, "dry+heat": hazards.dry_heat, "dry+wet": hazards.dry_wet, "heat+wet": hazards.heat_wet, "dry+heat+wet": hazards.dry_heat_wet, "no hazard": hazards.no_hazard }, color: { domain: [ hazards.wet, hazards.dry, hazards.heat, hazards.dry_heat, hazards.dry_wet, hazards.heat_wet, hazards.dry_heat_wet, hazards.no_hazard ], range: [ "#4FB5B7", "#FCC42C", "#FC8A34", "#EE624F", "#B34E65", "#8C3E5F", "#523D4E", "#EFEFEF" ] }, crops: cropNames.reduce((acc, obj) => { acc[obj.crop] = obj.cropName; return acc; }, {}) }; }6a:T54a,dataHazardAdminAll = await db.query(` -- Admin0 total for Sub-Saharan Africa (SSA) regions WITH HazardRiskBase AS ( -- Filter by chosen scenario and timeframe, focusing on severe hazards SELECT admin0_name, admin1_name, admin2_name, scenario, timeframe, crop, severity, hazard, value AS vop FROM haz_risk_vop_int_combined WHERE severity = 'severe' and timeframe = '${selectScenarioAndTimeframe.timeframe}' and scenario = '${selectScenarioAndTimeframe.scenario}' ), -- Data for SSA regions only, where admin1_name is NULL (Admin0 level) Admin0SSAData AS ( SELECT * FROM HazardRiskBase WHERE admin1_name IS NULL ), -- Aggregate VoP for each crop by hazard type across Admin0 regions AggregatedCropData AS ( SELECT severity, scenario, timeframe, hazard, crop, SUM(vop) AS vop FROM Admin0SSAData GROUP BY severity, scenario, timeframe, hazard, crop ) -- Output: Admin0 level crop data with null admin names for SSA SELECT NULL AS admin0_name, NULL AS admin1_name, NULL AS admin2_name, severity, scenario, timeframe, hazard, crop, vop FROM AggregatedCropData `);6b:T481,// map layer options dataLayerOptionsAdaptiveCapacities = [ { key: "pov", // lookup id for data option dataColumn: "ac_pov", // data column (decimal of AC) label: _lang(nbText.adaptiveCapacities.inputs.mapLayer.options.pov.label), // label labelLegend: _lang( nbText.adaptiveCapacities.inputs.mapLayer.options.pov.labelLegend ) // label for color legend }, { key: "edu", dataColumn: "ac_edu", label: _lang(nbText.adaptiveCapacities.inputs.mapLayer.options.edu.label), labelLegend: _lang( nbText.adaptiveCapacities.inputs.mapLayer.options.edu.labelLegend ) }, { key: "fem", dataColumn: "ac_fem", label: _lang(nbText.adaptiveCapacities.inputs.mapLayer.options.fem.label), labelLegend: _lang( nbText.adaptiveCapacities.inputs.mapLayer.options.fem.labelLegend ) } ].map((d) => ({ // apply common values across all options ...d, labelPop: "Population", // tooltip label for population affected popColumn: "total_pop", // population column colorDomain: colorScales.range.orangeRed, // color domain colorUnknown: colorScales.unknown // unknown fill color }))6c:Tafd,mapFeaturesAdaptiveCapacity = { if (!adminSelections.selectAdmin0.value) return mapDataAdaptiveCapacityAdmin0.features // admin0 selected - return admin2 level (zones) else if (!adminSelections.selectAdmin1.value) { return mapDataAdaptiveCapacityAdmin2.features.filter((d) => { return d.properties.admin0_name === adminSelections.selectAdmin0.value; }); } // admin1 selected - return admin2 level (zones in region) else if (!adminSelections.selectAdmin2.value) { return mapDataAdaptiveCapacityAdmin2.features.filter((d) => { return ( d.properties.admin0_name === adminSelections.selectAdmin0.value && d.properties.admin1_name === adminSelections.selectAdmin1.value ); }); } // admin2 selected - return admin3 level (woredas in zone) else if (!adminSelections.selectAdmin3.value && adminSelections.selectAdmin0.value === "Ethiopia") { const boundFeatures = mapDataAdaptiveCapacityAdmin3.features; // Get all woreda features for the selected zone const allWoredaFeatures = boundaries.admin3.features.filter((d) => { return ( d.properties.admin0_name === adminSelections.selectAdmin0.value && d.properties.admin1_name === adminSelections.selectAdmin1.value && d.properties.admin2_name === adminSelections.selectAdmin2.value ); }); console.log("DEBUG: mapFeaturesAdaptiveCapacity - Bound admin3 features:", boundFeatures.length); console.log("DEBUG: mapFeaturesAdaptiveCapacity - All woreda features:", allWoredaFeatures.length); // Merge: use bound features if available, otherwise use all woreda features with default data if (boundFeatures.length > 0) { return boundFeatures; } else { // Return all woreda features with default data const featuresWithDefaultData = allWoredaFeatures.map(f => ({ ...f, properties: { ...f.properties, data: { ac_pov: 0, ac_edu: 0, ac_fem: 0, rural_pop: 0, total_pop: 0, gender_men: 0.5, gender_women: 0.5, poverty_men_ratio: 0.5, poverty_women_ratio: 0.5, edu_men_ratio: 0.5, edu_women_ratio: 0.5 } } })); console.log("DEBUG: mapFeaturesAdaptiveCapacity - Admin3 features with defaults:", featuresWithDefaultData.length); return featuresWithDefaultData; } } // admin3 selected - return single woreda else { const features = mapDataAdaptiveCapacityAdmin3.features.filter((d) => { return d.properties.admin3_name === adminSelections.selectAdmin3.value; }); console.log("DEBUG: mapFeaturesAdaptiveCapacity - Single Woreda features:", features.length); return features; } }6d:T4b2,{ console.log("DEBUG: adminSelections:", { admin0: adminSelections.selectAdmin0.value, admin1: adminSelections.selectAdmin1.value, admin2: adminSelections.selectAdmin2.value, admin3: adminSelections.selectAdmin3.value }); console.log("DEBUG: dataAdaptiveCapacity sample:", dataAdaptiveCapacity.slice(0, 2)); console.log("DEBUG: mapDataAdaptiveCapacityAdmin0 features:", mapDataAdaptiveCapacityAdmin0.features.length); console.log("DEBUG: mapDataAdaptiveCapacityAdmin2 features:", mapDataAdaptiveCapacityAdmin2.features.length); console.log("DEBUG: mapDataAdaptiveCapacityAdmin3 features:", mapDataAdaptiveCapacityAdmin3.features.length); console.log("DEBUG: mapFeaturesAdaptiveCapacity sample:", mapFeaturesAdaptiveCapacity.slice(0, 2).map(f => ({ admin0_name: f.properties.admin0_name, admin1_name: f.properties.admin1_name, admin2_name: f.properties.admin2_name, admin3_name: f.properties.admin3_name, data: f.properties.data }))); return { dataAdaptiveCapacity, mapDataAdmin0: mapDataAdaptiveCapacityAdmin0, mapDataAdmin2: mapDataAdaptiveCapacityAdmin2, mapDataAdmin3: mapDataAdaptiveCapacityAdmin3, mapFeatures: mapFeaturesAdaptiveCapacity }; }6e:T560,mapDataAdaptiveCapacityAdmin3 = { const { selectAdmin0, selectAdmin1, selectAdmin2 } = adminSelections; const data = T.tidy( dataAdaptiveCapacity, T.mutate({ a3_a2_a1_a0: (d) => [d.admin3_name, d.admin2_name, d.admin1_name, d.admin0_name].join("_") }) ); const geoData = { ...boundaries.admin3, features: boundaries.admin3.features.filter((d) => { return d.properties.admin0_name === selectAdmin0.value && d.properties.admin1_name === selectAdmin1.value && d.properties.admin2_name === selectAdmin2.value; }).map(f => ({ ...f, properties: { ...f.properties, a3_a2_a1_a0: [f.properties.admin3_name, f.properties.admin2_name, f.properties.admin1_name, f.properties.admin0_name].join("_") } })) }; console.log("DEBUG: mapDataAdaptiveCapacityAdmin3 - Filtered geo features for zone:", geoData.features.length); console.log("DEBUG: mapDataAdaptiveCapacityAdmin3 - Data rows:", data.length); const result = bindTabularToGeo({ data: data, dataBindColumn: "a3_a2_a1_a0", geoData: geoData, geoDataBindColumn: "a3_a2_a1_a0" }); console.log("DEBUG: mapDataAdaptiveCapacityAdmin3 - Bound features:", result.features.length); console.log("DEBUG: mapDataAdaptiveCapacityAdmin3 - Sample bound feature:", result.features[0]?.properties); return result; }6f:T1940,dataAdaptiveCapacity = { const country = adminSelections.selectAdmin0.value; const admin1 = adminSelections.selectAdmin1.value || null; const admin2 = adminSelections.selectAdmin2.value || null; const admin3 = adminSelections.selectAdmin3.value || null; let adminQuery = `WHERE admin0_name ${country ? `= '${country}'` : 'IS NOT NULL'}`; adminQuery += !country ? ` AND admin1_name IS NULL` : ` AND admin2_name IS NOT NULL`; console.log("DEBUG: dataAdaptiveCapacity - Query:", adminQuery); let dataSource = await db.query(` WITH filtered_ac AS ( SELECT admin0_name, admin1_name, admin2_name, "GenderEquity_1995.2015" AS ac_fem, "IHME_edu.years_2014" AS ac_edu, "GASP_poor365_2017" AS ac_pov FROM vul_ac2 ${adminQuery} ), filtered_pop AS ( SELECT admin0_name, admin1_name, admin2_name, total_pop, rural_pop FROM population ${adminQuery} ) SELECT v.*, p.total_pop, p.rural_pop FROM filtered_ac v JOIN filtered_pop p ON v.admin0_name = p.admin0_name AND (v.admin1_name = p.admin1_name OR (v.admin1_name IS NULL AND p.admin1_name IS NULL)) AND (v.admin2_name = p.admin2_name OR (v.admin2_name IS NULL AND p.admin2_name IS NULL)); `); console.log("DEBUG: dataAdaptiveCapacity - Query result rows:", dataSource.length); console.log("DEBUG: dataAdaptiveCapacity - Ethiopia sample:", dataSource.find(d => d.admin0_name === "Ethiopia") || "No Ethiopia data"); // Apply gender-related fields from mock data for all levels let mappedDataSource = dataSource.map(d => { const mockRow = mockAdaptiveCapacityData.find(m => (m.admin0_name?.trim().toLowerCase() || '') === (d.admin0_name?.trim().toLowerCase() || '') && (m.admin1_name?.trim().toLowerCase() || '') === (d.admin1_name?.trim().toLowerCase() || '') && (m.admin2_name?.trim().toLowerCase() || '') === (d.admin2_name?.trim().toLowerCase() || '') && (m.admin3_name?.trim().toLowerCase() || '') === (d.admin3_name?.trim().toLowerCase() || '') ); return { ...d, gender_men: mockRow ? mockRow.gender_men : 0.5, gender_women: mockRow ? mockRow.gender_women : 0.5, poverty_men_ratio: mockRow ? mockRow.poverty_men_ratio : 0.5, poverty_women_ratio: mockRow ? mockRow.poverty_women_ratio : 0.5, edu_men_ratio: mockRow ? mockRow.edu_men_ratio : 0.5, edu_women_ratio: mockRow ? mockRow.edu_women_ratio : 0.5 }; }); // Mock data for admin3 level (only for Ethiopia) // When admin2 is selected but admin3 is not, add mock woreda data for the map // but keep the real admin2 aggregate data for insights if (admin2 && !admin3 && country === "Ethiopia") { console.log("DEBUG: Adding mock admin3 data for map, keeping admin2 aggregate for insights"); const mockWoredaData = mockAdaptiveCapacityData .filter(d => d.admin0_name === country && d.admin1_name === admin1 && d.admin2_name === admin2 && d.admin3_name ) .map(d => ({ admin0_name: d.admin0_name, admin1_name: d.admin1_name, admin2_name: d.admin2_name, admin3_name: d.admin3_name, ac_pov: d.ac_pov, ac_edu: d.ac_edu, ac_fem: d.ac_fem, rural_pop: d.rural_pop, total_pop: d.total_pop, a3_a2_a1_a0: [d.admin3_name, d.admin2_name, d.admin1_name, d.admin0_name].join("_"), gender_men: d.gender_men || 0.5, gender_women: d.gender_women || 0.5, poverty_men_ratio: d.poverty_men_ratio || 0.5, poverty_women_ratio: d.poverty_women_ratio || 0.5, edu_men_ratio: d.edu_men_ratio || 0.5, edu_women_ratio: d.edu_women_ratio || 0.5 })); // Add mock woreda data to the existing data (for map), but keep admin2 aggregate (for insights) if (mockWoredaData.length > 0) { mappedDataSource = [...mappedDataSource, ...mockWoredaData]; console.log("DEBUG: Added mock admin3 data rows for map:", mockWoredaData.length); } } // When admin3 is actually selected, use only mock woreda data if (admin3 && admin2 && country === "Ethiopia") { console.log("DEBUG: Using mock admin3 data for specific woreda:", admin3); const mockData = mockAdaptiveCapacityData .filter(d => d.admin0_name === country && d.admin1_name === admin1 && d.admin2_name === admin2 && d.admin3_name === admin3 ) .map(d => ({ admin0_name: d.admin0_name, admin1_name: d.admin1_name, admin2_name: d.admin2_name, admin3_name: d.admin3_name, ac_pov: d.ac_pov, ac_edu: d.ac_edu, ac_fem: d.ac_fem, rural_pop: d.rural_pop, total_pop: d.total_pop, a3_a2_a1_a0: [d.admin3_name, d.admin2_name, d.admin1_name, d.admin0_name].join("_"), gender_men: d.gender_men || 0.5, gender_women: d.gender_women || 0.5, poverty_men_ratio: d.poverty_men_ratio || 0.5, poverty_women_ratio: d.poverty_women_ratio || 0.5, edu_men_ratio: d.edu_men_ratio || 0.5, edu_women_ratio: d.edu_women_ratio || 0.5 })); if (mockData.length === 0) { console.warn("No mock data found for selected admin3:", admin3); mappedDataSource = []; } else { mappedDataSource = mockData; console.log("DEBUG: Loaded mock admin3 data for specific woreda:", mockData.length); } } if (mappedDataSource.length > 0) { console.log("DEBUG: dataAdaptiveCapacity - Final data sample:", { admin0: mappedDataSource[0].admin0_name, admin1: mappedDataSource[0].admin1_name, admin2: mappedDataSource[0].admin2_name, admin3: mappedDataSource[0].admin3_name, ac_pov: mappedDataSource[0].ac_pov, ac_edu: mappedDataSource[0].ac_edu, ac_fem: mappedDataSource[0].ac_fem, total_pop: mappedDataSource[0].total_pop, gender_men: mappedDataSource[0].gender_men }); } return mappedDataSource; }70:T4b2,{ console.log("DEBUG: adminSelections:", { admin0: adminSelections.selectAdmin0.value, admin1: adminSelections.selectAdmin1.value, admin2: adminSelections.selectAdmin2.value, admin3: adminSelections.selectAdmin3.value }); console.log("DEBUG: dataAdaptiveCapacity sample:", dataAdaptiveCapacity.slice(0, 2)); console.log("DEBUG: mapDataAdaptiveCapacityAdmin0 features:", mapDataAdaptiveCapacityAdmin0.features.length); console.log("DEBUG: mapDataAdaptiveCapacityAdmin2 features:", mapDataAdaptiveCapacityAdmin2.features.length); console.log("DEBUG: mapDataAdaptiveCapacityAdmin3 features:", mapDataAdaptiveCapacityAdmin3.features.length); console.log("DEBUG: mapFeaturesAdaptiveCapacity sample:", mapFeaturesAdaptiveCapacity.slice(0, 2).map(f => ({ admin0_name: f.properties.admin0_name, admin1_name: f.properties.admin1_name, admin2_name: f.properties.admin2_name, admin3_name: f.properties.admin3_name, data: f.properties.data }))); return { dataAdaptiveCapacity, mapDataAdmin0: mapDataAdaptiveCapacityAdmin0, mapDataAdmin2: mapDataAdaptiveCapacityAdmin2, mapDataAdmin3: mapDataAdaptiveCapacityAdmin3, mapFeatures: mapFeaturesAdaptiveCapacity }; }71:T230d,// data and insights for dynamicInsights_adaptiveCapacity = { const data = dataAdaptiveCapacity; const admin3_selected = selectAdmin3?.value && adminSelections.selectAdmin0.value === "Ethiopia"; // format functions const _formatNumber = formatNumCompactLong; // source data ------------------------------- let exportData = { admin0: data, admin1: undefined, admin2: undefined, admin3: undefined }; // If admin3 is selected, use mock data if (admin3_selected) { const mockRow = mockAdaptiveCapacityData.find(m => m.admin0_name === adminSelections.selectAdmin0.value && m.admin1_name === adminSelections.selectAdmin1.value && m.admin2_name === adminSelections.selectAdmin2.value && m.admin3_name === selectAdmin3.value ); if (mockRow) { // Create a single-row dataset for the woreda const woredaData = [{ admin0_name: mockRow.admin0_name, admin1_name: mockRow.admin1_name, admin2_name: mockRow.admin2_name, admin3_name: mockRow.admin3_name, ac_pov: mockRow.ac_pov ?? NaN, ac_edu: mockRow.ac_edu ?? NaN, ac_fem: mockRow.ac_fem ?? NaN, rural_pop: mockRow.rural_pop ?? NaN, total_pop: mockRow.total_pop ?? NaN, gender_men: mockRow.gender_men ?? 0.5, gender_women: mockRow.gender_women ?? 0.5, poverty_men_ratio: mockRow.poverty_men_ratio ?? NaN, poverty_women_ratio: mockRow.poverty_women_ratio ?? NaN, edu_men_ratio: mockRow.edu_men_ratio ?? NaN, edu_women_ratio: mockRow.edu_women_ratio ?? NaN }]; exportData = { admin0: woredaData, admin1: woredaData, admin2: woredaData, admin3: woredaData }; } else { // No mock data found - return NaN values const emptyData = [{ admin0_name: adminSelections.selectAdmin0.value, admin1_name: adminSelections.selectAdmin1.value, admin2_name: adminSelections.selectAdmin2.value, admin3_name: selectAdmin3.value, ac_pov: NaN, ac_edu: NaN, ac_fem: NaN, rural_pop: NaN, total_pop: NaN, gender_men: NaN, gender_women: NaN, poverty_men_ratio: NaN, poverty_women_ratio: NaN, edu_men_ratio: NaN, edu_women_ratio: NaN }]; exportData = { admin0: emptyData, admin1: emptyData, admin2: emptyData, admin3: emptyData }; } } else if (!Object.values(adminSelections).every((d) => d.value === null)) { // selected admin0 data const filteredData0 = adminSelections.selectAdmin0.value ? data.filter((d) => { return ( d.admin0_name === (adminSelections.selectAdmin0.value || d.admin0_name) ); }) : undefined; // selected admin1 data const filteredData1 = adminSelections.selectAdmin1.value ? data.filter((d) => { return ( d.admin0_name === (adminSelections.selectAdmin0.value || d.admin0_name) && d.admin1_name === (adminSelections.selectAdmin1.value || d.admin1_name) ); }) : undefined; // selected admin2 data const filteredData2 = adminSelections.selectAdmin2.value ? data.filter((d) => { return ( d.admin0_name === (adminSelections.selectAdmin0.value || d.admin0_name) && d.admin1_name === (adminSelections.selectAdmin1.value || d.admin1_name) && d.admin2_name === (adminSelections.selectAdmin2.value || d.admin2_name) && !d.admin3_name // Exclude woreda-level data to get admin2 aggregate ); }) : undefined; exportData = { admin0: filteredData0, admin1: filteredData1, admin2: filteredData2, admin3: undefined }; } // insights from source ------------------------------- function findAdmin2ACStats(data) { // admin2 stats // - find the counts for each AC // - find majorities // - find regions that have all and none for binary ACs return T.tidy( data, T.mutate({ ac_edu_pop: (d) => { if (d.ac_edu === null || isNaN(d.ac_edu) || d.total_pop === null || isNaN(d.total_pop)) return NaN; return d.ac_edu * d.total_pop; }, ac_fem_pop: (d) => { if (d.ac_fem === null || isNaN(d.ac_fem) || d.total_pop === null || isNaN(d.total_pop)) return NaN; return d.ac_fem * d.total_pop; }, ac_pov_pop: (d) => { if (d.ac_pov === null || isNaN(d.ac_pov) || d.total_pop === null || isNaN(d.total_pop)) return NaN; return d.ac_pov * d.total_pop; } }), T.summarize({ total_pop: T.sum("total_pop"), ac_edu_pop: T.sum("ac_edu_pop"), ac_fem_pop: T.sum("ac_fem_pop"), ac_pov_pop: T.sum("ac_pov_pop") }), T.mutate({ ac_edu_maj: (d) => { if (isNaN(d.ac_edu_pop) || isNaN(d.total_pop) || d.total_pop === 0) return false; return d.ac_edu_pop > (0.5 * d.total_pop); }, ac_fem_maj: (d) => { if (isNaN(d.ac_fem_pop) || isNaN(d.total_pop) || d.total_pop === 0) return false; return d.ac_fem_pop > (0.5 * d.total_pop); }, ac_pov_maj: (d) => { if (isNaN(d.ac_pov_pop) || isNaN(d.total_pop) || d.total_pop === 0) return false; return d.ac_pov_pop > (0.5 * d.total_pop); }, }), T.mutate({ ac_edu_perc: (d) => { if (isNaN(d.ac_edu_pop) || isNaN(d.total_pop) || d.total_pop === 0) return NaN; return d.ac_edu_pop / d.total_pop; }, ac_fem_perc: (d) => { if (isNaN(d.ac_fem_pop) || isNaN(d.total_pop) || d.total_pop === 0) return NaN; return d.ac_fem_pop / d.total_pop; }, ac_pov_perc: (d) => { if (isNaN(d.ac_pov_pop) || isNaN(d.total_pop) || d.total_pop === 0) return NaN; return d.ac_pov_pop / d.total_pop; }, }) ); } const insights0 = exportData.admin0 ? findAdmin2ACStats(exportData.admin0) : null; const insights1 = exportData.admin1 ? findAdmin2ACStats(exportData.admin1) : null; const insights2 = exportData.admin2 ? findAdmin2ACStats(exportData.admin2) : null; const insights3 = exportData.admin3 ? findAdmin2ACStats(exportData.admin3) : null; const insights = { admin0: insights0?.[0], admin1: insights1?.[0], admin2: insights2?.[0], admin3: insights3?.[0] }; // admin selection total --------------------------------- // - sum the admin2 population values for given admin selection function sumPopulations(data) { return T.tidy( data, T.summarize({ total_pop: T.sum("total_pop"), rural_pop: T.sum("rural_pop") }) ); } // get total based on admin selection // overwrite total if more granular data is non-null let totalPopulations; totalPopulations = exportData.admin0 ? sumPopulations(exportData.admin0) : totalPopulations; totalPopulations = exportData.admin1 ? sumPopulations(exportData.admin1) : totalPopulations; totalPopulations = exportData.admin2 ? sumPopulations(exportData.admin2) : totalPopulations; totalPopulations = exportData.admin3 ? sumPopulations(exportData.admin3) : totalPopulations; totalPopulations = totalPopulations?.[0]; totalPopulations["total_pop_format"] = _formatNumber( totalPopulations["total_pop"] ); totalPopulations["rural_pop_format"] = _formatNumber( totalPopulations["rural_pop"] ); // all/none admin2's within admin0 --------------------------------- // the admin2's within the selected admin0 that are all/none AC function findAdmin2ACStatsAdmin0(data) { // admin2 stats // - find regions that have all and none for binary ACs return T.tidy( data, // all or none of ACs T.mutate({ admin0_ac_all: (d) => // include all admin2's if showing all regions (adminSelections.selectAdmin0.value ? d.admin0_name == adminSelections.selectAdmin0.value : true) && d.ac_edu > 0.5 && d.ac_fem > 0.5 && d.ac_pov <= 0.5, // reversed admin0_ac_none: (d) => (adminSelections.selectAdmin0.value ? d.admin0_name == adminSelections.selectAdmin0.value : true) && d.ac_edu <= 0.5 && d.ac_fem <= 0.5 && d.ac_pov > 0.5 }), T.summarize({ admin2_count: T.n(), admin0_ac_all_count: T.sum("admin0_ac_all"), admin0_ac_none_count: T.sum("admin0_ac_none") }) ); } const extremeAC2Stats = findAdmin2ACStatsAdmin0(exportData.admin0)?.[0]; return { data: exportData, insights: insights, population_sums: totalPopulations, admin0LevelA2AllNone: extremeAC2Stats }; } 72:T466,// define the mad lib for adaptive capacity admin1 and admin 0 levels function adaptiveCapacityInsightMadLib(data, adminName) { const madLib = Lang.reduceReplaceTemplateItems( _lang(nbText.adaptiveCapacities.insights.madLib), [ { name: "admin", value: adminName }, { name: "index_edu", value: formatPercentNoSymbol(transformPercent(data?.ac_edu_perc)) }, { name: "index_fem", value: formatPercentNoSymbol(transformPercent(data?.ac_fem_perc)) }, { name: "index_pov", value: formatPercentNoSymbol(transformPercent(data?.ac_pov_perc)) } ] ); return `${madLib}`; } // // define the mad lib for adaptive capacity admin1 and admin 0 levels // function adaptiveCapacityInsightMadLib(data, adminName) { // return `In **${adminName}**, the education index is **${formatPercentNoSymbol(transformPercent(data?.ac_edu_perc))}**, the female empowerment index is **${formatPercentNoSymbol(transformPercent(data?.ac_fem_perc))}**, and the poverty index is **${formatPercentNoSymbol(transformPercent(data?.ac_pov_perc))}**.` // }73:T6be,textDynamicInsights_adaptiveCapacities1 = { // return md`TODO: based on icicle data` // dynamic insight based on selected region const admin2 = adminSelections.selectAdmin2.value; const admin2MadLib = adaptiveCapacityInsightMadLib( dynamicInsights_adaptiveCapacity.insights.admin2, admin2 ); const admin1 = adminSelections.selectAdmin1.value; const admin1MadLib = adaptiveCapacityInsightMadLib( dynamicInsights_adaptiveCapacity.insights.admin1, admin1 ); const admin0 = adminSelections.selectAdmin0.label ?? globalSelection.label; const admin0Insights = dynamicInsights_adaptiveCapacity.insights.admin0; const admin0MadLib = adaptiveCapacityInsightMadLib( admin0Insights, admin0 ); const langWithinAdmin1 = Lang.reduceReplaceTemplateItems( _lang(nbText.adaptiveCapacities.insights.nestedLocationBlurb), [ { name: "admin_inner", value: admin2 }, { name: "admin_outer", value: admin1 } ] ); const withinAdmin1 = admin2 ? `${langWithinAdmin1}` : ``; const langWithinAdmin0 = Lang.reduceReplaceTemplateItems( _lang(nbText.adaptiveCapacities.insights.nestedLocationBlurb), [ { name: "admin_inner", value: admin1 }, { name: "admin_outer", value: admin0 } ] ); const withinAdmin0 = admin1 ? `${langWithinAdmin0}` : ``; // Text sections ------------------------------ const admin2Text = md`${admin2MadLib}`; const admin1Text = md`${withinAdmin1} ${admin1MadLib}`; const admin0Text = md`${withinAdmin0} ${admin0MadLib}`; // Final text ------------------------------ return md` #### Old Insight: ${admin2 ? admin2Text : ""} ${admin1 ? admin1Text : ""} ${admin0Insights ? admin0Text : ""} `; }74:T4c7,function buildHierarchy(csv) { // Helper function that transforms the given CSV into a hierarchical format. const root = { name: "root", children: [] }; for (let i = 0; i < csv.length; i++) { const sequence = csv[i]["path"]; const size = +csv[i]['value']; if (isNaN(size)) { // e.g. if this is a header row continue; } const parts = sequence.split("_"); let currentNode = root; for (let j = 0; j < parts.length; j++) { const children = currentNode["children"]; const nodeName = parts[j]; let childNode = null; let foundChild = false; // Search for existing child with the same name for (let k = 0; k < children.length; k++) { if (children[k]["name"] === nodeName) { childNode = children[k]; foundChild = true; break; } } // If not found, create a new child node if (!foundChild) { childNode = { name: nodeName, children: [] }; children.push(childNode); } currentNode = childNode; // If it's the last part of the sequence, create a leaf node if (j === parts.length - 1) { childNode.value = size; } } } return root; }75:T13eb,db = { document.body.style.cursor = "wait"; let db = await DuckDBClient.of({ haz_risk_vop_int: FileAttachment("haz_risk_vop_int_reduced_clean@1.parquet"), mock_local_haz_risk: FileAttachment("mock_local_haz_risk@2.csv"), population: FileAttachment("population_long@1.parquet"), vop_ha: FileAttachment("exposure_adm_sum_sorted (3).parquet"), mock_exposure_woreda: FileAttachment("mock_exposure_woreda@1.csv"), vul_ac: FileAttachment("vulnerability_RawIndex_adminALL@2.parquet"), vul_ac2: FileAttachment("AC_adminALL (1).parquet"), icicle_data: FileAttachment("All-adm_ssa_icicle_data_3class.parquet"), icicle_data_admin3: FileAttachment("icicle_data_admin3_ethiopia.csv") }); // Merge mock local data with main haz_risk_vop_int table await db.query(` CREATE VIEW haz_risk_vop_int_combined AS SELECT admin0_name, admin1_name, admin2_name, NULL as admin3_name, crop, scenario, timeframe, severity, hazard, value, total_value FROM haz_risk_vop_int UNION ALL SELECT admin0_name, admin1_name, admin2_name, CASE WHEN admin3_name = '' THEN NULL ELSE admin3_name END as admin3_name, crop, scenario, timeframe, severity, hazard, CAST(value AS DOUBLE) as value, CAST(total_value AS DOUBLE) as total_value FROM mock_local_haz_risk `); await db.query(`CREATE TABLE vop AS SELECT * FROM vop_ha WHERE "exposure" = 'vop'`) await db.query(`CREATE TABLE ha AS SELECT * FROM vop_ha WHERE "exposure" = 'ha'`) await db.query(` CREATE TABLE vop_crop AS SELECT * FROM vop_ha WHERE NOT ( crop LIKE 'cattle\_%' ESCAPE '\\' OR crop LIKE 'goats\_%' ESCAPE '\\' OR crop LIKE 'pigs\_%' ESCAPE '\\' OR crop LIKE 'poultry\_%' ESCAPE '\\' OR crop LIKE 'sheep\_%' ESCAPE '\\' ) AND crop NOT LIKE 'total_%' ESCAPE '\\' AND exposure = 'vop'`) await db.query(` CREATE TABLE vop_animal AS SELECT * FROM vop_ha WHERE ( crop LIKE 'cattle\_%' ESCAPE '\\' OR crop LIKE 'goats\_%' ESCAPE '\\' OR crop LIKE 'pigs\_%' ESCAPE '\\' OR crop LIKE 'poultry\_%' ESCAPE '\\' OR crop LIKE 'sheep\_%' ESCAPE '\\' ) AND crop NOT LIKE 'total_%' ESCAPE '\\' -- remove total lines AND exposure = 'vop'`) // Create woreda-level tables from mock_exposure_woreda // Cast value to DOUBLE to ensure proper numeric type await db.query(`CREATE TABLE vop_woreda AS SELECT admin0_name, admin1_name, admin2_name, admin3_name, crop, CAST(value AS DOUBLE) AS value FROM mock_exposure_woreda WHERE exposure = 'vop'`) await db.query(`CREATE TABLE ha_woreda AS SELECT admin0_name, admin1_name, admin2_name, admin3_name, crop, CAST(value AS DOUBLE) AS value FROM mock_exposure_woreda WHERE exposure = 'ha'`) await db.query(` CREATE TABLE vop_crop_woreda AS SELECT admin0_name, admin1_name, admin2_name, admin3_name, crop, CAST(value AS DOUBLE) AS value FROM mock_exposure_woreda WHERE exposure = 'vop' AND crop NOT IN ( 'donkey', 'Donkey (highland)', 'camel' ) AND crop NOT LIKE 'cattle\_%' ESCAPE '\\' AND crop NOT LIKE 'goats\_%' ESCAPE '\\' AND crop NOT LIKE 'pigs\_%' ESCAPE '\\' AND crop NOT LIKE 'poultry\_%' ESCAPE '\\' AND crop NOT LIKE 'sheep\_%' ESCAPE '\\' AND crop NOT LIKE 'total_%' ESCAPE '\\'`) await db.query(` CREATE TABLE vop_animal_woreda AS SELECT admin0_name, admin1_name, admin2_name, admin3_name, crop, CAST(value AS DOUBLE) AS value FROM mock_exposure_woreda WHERE ( crop LIKE 'cattle\_%' ESCAPE '\\' OR crop LIKE 'goats\_%' ESCAPE '\\' OR crop LIKE 'pigs\_%' ESCAPE '\\' OR crop LIKE 'poultry\_%' ESCAPE '\\' OR crop LIKE 'sheep\_%' ESCAPE '\\' OR crop = 'donkey' OR crop = 'Donkey (highland)' OR crop = 'camel' ) AND crop NOT LIKE 'total_%' ESCAPE '\\' AND exposure = 'vop'`) // Merge admin3 icicle data with existing icicle_data // First create a combined table with both original and admin3 data await db.query(` CREATE TABLE icicle_data_combined AS SELECT admin0_name, admin1_name, admin2_name, NULL AS admin3_name, path, value FROM icicle_data UNION ALL SELECT admin0_name, admin1_name, admin2_name, admin3_name, path, value FROM icicle_data_admin3`) // Drop the original icicle_data view (it's a view, not a table) await db.query(`DROP VIEW IF EXISTS icicle_data`) // Create the final icicle_data table from the combined data await db.query(` CREATE TABLE icicle_data AS SELECT * FROM icicle_data_combined`) // Drop the temporary combined table await db.query(`DROP TABLE icicle_data_combined`) document.body.style.cursor = "default"; return db } 76:T597,get_admin1 = async () => { let country = adminSelections.selectAdmin0.value let admin1 = adminSelections.selectAdmin1.value if (country) { document.body.style.cursor = "wait"; let admin1_query = `WHERE admin0_name = '${country}'` // let response = await geo_db.query(` // SELECT * // FROM admin1_geom // ${admin1_query}`) let response = await geo_db.query(` SELECT * FROM "${resolveWindowsCacheIssue( partitioned_boundries + "/admin0=" + admin_iso + "/admin_level=1/" + admin_iso + ".parquet" )}" `) let wkb_list = response.map((d) => d.geometry); let data = await response.map(({ geometry, ...rest }) => rest); const features = []; for (let i = 0; i < wkb_list.length; i++) { const pointer = GEOS.geosGeomFromWKB(wkb_list[i]); let geojson = await GEOS.geosGeomToGeojson(pointer, GEOS.geos); geojson = turfRewind(geojson, { reverse: true }); const feature = { type: "Feature", geometry: geojson, properties: data[i] }; features.push(feature); GEOS.geos.GEOSGeom_destroy(pointer); } const geojson = { type: "FeatureCollection", features: features }; // return { names: ["Full Country"].concat(a1_names), GEOJSON: geojson }; document.body.style.cursor = "default"; return geojson; } }77:T6d9,get_admin2 = async () => { let country = adminSelections.selectAdmin0.value let admin1 = adminSelections.selectAdmin1.value if (country) { document.body.style.cursor = "wait"; // let admin2_query = `WHERE admin0_name = '${country}'` // admin2_query += !admin1? "":` AND admin1_name = '${cleanAdminInput_SQL(admin1)}'` // let response = await geo_db.query(` // SELECT * // FROM admin2_geom // ${admin2_query}`) // let response = await geo_db.query(` // SELECT * // FROM "${partitioned_boundries}/admin0=${admin_iso}/admin_level=2/${admin_iso}.parquet" // `) console.log( "a2_path:", resolveWindowsCacheIssue( partitioned_boundries + "/admin0=" + admin_iso + "/admin_level=2/" + admin_iso + ".parquet" ) ) let response = await geo_db.query(` SELECT * FROM "${resolveWindowsCacheIssue(partitioned_boundries + "/admin0=" + admin_iso + "/admin_level=2/" + admin_iso + ".parquet")}" `) let wkb_list = response.map((d) => d.geometry); let data = await response.map(({ geometry, ...rest }) => rest) const features = []; for (let i = 0; i < wkb_list.length; i++) { const pointer = GEOS.geosGeomFromWKB(wkb_list[i]); let geojson = await GEOS.geosGeomToGeojson(pointer, GEOS.geos); geojson = turfRewind(geojson, { reverse: true }); const feature = { type: "Feature", geometry: geojson, properties: data[i] }; features.push(feature); GEOS.geos.GEOSGeom_destroy(pointer); } const geojson = { type: "FeatureCollection", features: features }; document.body.style.cursor = "default"; return geojson; } }78:T472,// lookup for risk data type groupings // used by inputs and for grouping up data riskDataTypes = ({ crop: { crop: [ "arabica coffee", "banana", "barley", "bean", "cassava", "chickpea", "cocoa", "coconut", "cotton", "cowpea", "enset", "generic", "groundnut", "lentil", "maize", "maize_001", "maize_002", "oilpalm", "pearl millet", "pigeonpea", "plantain", "potato", "rice", "robusta coffee", "sesameseed", "small millet", "sorghum", "soybean", "sugarcane", "sunflower", "sweet potato", "tea", "tobacco", "wheat", "yams", "teff", "teff_001", "teff_002", "enset" ], livestock: [ "cattle_highland", "cattle_tropical", "goats_highland", "goats_tropical", "pigs_highland", "pigs_tropical", "poultry_highland", "poultry_tropical", "sheep_highland", "sheep_tropical", "Donkey (highland)", "donkey", "camel" ] } })79:T762,{ const text = `### v1.2.0: adding language conversion - language toggle ### v1.1.2: Adaptive capacity formatting - Update adaptive capacity data - AC data for map are indices and should be describes as such, not as rates - Update insights to be about selected indexes rather than population affected ### v1.1.1 Map fix (2024-03-26) Looking at map with multiple regions shown for choropleth - Fix binding when you've selected admin1: - Bind data by BOTH admin1 and admin0, not just admin1 ### v1.1 Data Update (2024-03-19) - Hazard field is now 'no hazard' (all lowercase) - VoP values are the total across all severities, not just hard-coded to 'moderate' ### v1.0.1 (2024-03-15) - Adding cover image ### v1.0 (2024-03-15) - Updating hazard data - Included 'No hazard' as option, so updated how data is extracted (no longer joining up totals) - Using new option as definition of distribution - Update removal from component bar charts - Not using the explicit 'any' column, instead defining using sum of component values (to avoid any rounding errors) - Cleanup - Remove unused hazard helpers - Clean up documentation for data sources ### v0.6 (2024-03-11) - Collapse y-axis for percent chart when crop hazards are zero (preserve order for crops and livestock) - Remove 'no hazard' from hazard bar chart dropdown - Update perc chart tooltip - Total VoP at risk is now in terms of colored bars only (using any hazard data) - Format to match percent and money with hazard exposure - Fix bar ordering - Update adaptive capacity icicle - includes SSA and updated colors - Update adaptive capacity map data `; const newestVersion = text.split('###') .filter(d => d) .map(d => d.trim()) ?.[0] .split('\n') ?.[0] return makeDevNotes({ text: md`${text}`, title: newestVersion ?? "Dev notes", emojis: "🪵✏️" }) }7a:T556,formatCurrencyToBirr = { return function formatCurrencyToBirr(dollarValue, options = {}) { const { includeYear = true, // Whether to include "2005" prefix includeCurrency = true, // Whether to include "ETB" prefix locale = language?.locale || "en-US" } = options; if (dollarValue === null || dollarValue === undefined || isNaN(dollarValue)) { return options.missingValue || "---"; } const birrValue = dollarValue * usdToEtbExchangeRate; let birrOutput; let newMagnitudeLabel = ''; // Determine the new magnitude based on the converted value if (birrValue >= 1000000000000) { newMagnitudeLabel = 'T'; // Trillion birrOutput = (birrValue / 1000000000000).toFixed(1); } else if (birrValue >= 1000000000) { newMagnitudeLabel = 'B'; // Billion birrOutput = (birrValue / 1000000000).toFixed(1); } else if (birrValue >= 1000000) { newMagnitudeLabel = 'M'; // Million birrOutput = (birrValue / 1000000).toFixed(1); } else { birrOutput = Math.round(birrValue).toLocaleString(locale); } // Construct the final string let result = ''; if (includeYear) { result += '2005 '; } if (includeCurrency) { result += 'ETB'; } result += birrOutput + newMagnitudeLabel; return result; }; }7b:T859, // Shared TLU (Tropical Livestock Unit) conversion function // TLU is a standardized unit for measuring livestock (1 TLU = 250 kg live weight) // This function converts livestock counts to TLU based on animal convertToTLU = { // Standard TLU conversion factors (can be customized per region/animal type) const TLU_FACTORS = { // Cattle 'cattle': 0.7, // Average: 0.7-1.0 TLU per head 'cattle_highland': 0.8, // Highland cattle are typically larger 'cattle_tropical': 0.6, // Tropical cattle are typically smaller // Small ruminants 'sheep': 0.1, // Average: 0.1-0.15 TLU per head 'sheep_highland': 0.12, 'sheep_tropical': 0.08, 'goats': 0.1, // Average: 0.1-0.2 TLU per head 'goats_highland': 0.12, 'goats_tropical': 0.08, // Other animals 'camels': 1.2, // Average: 1.0-1.4 TLU per head 'horses': 0.8, 'donkeys': 0.5, 'mules': 0.6, 'poultry': 0.01, // Very small contribution 'pigs': 0.2, // Default fallback 'default': 0.5 }; return function convertToTLU(animalCount, animalType, options = {}) { const { locale = "en-US", includeUnit = true, precision = 2 } = options; if (animalCount === null || animalCount === undefined || isNaN(animalCount)) { return options.missingValue || "---"; } // Normalize animal type to lowercase for lookup const normalizedType = String(animalType || 'default').toLowerCase().trim(); // Get TLU factor for the animal type const tluFactor = TLU_FACTORS[normalizedType] || TLU_FACTORS['default']; // Calculate TLU const tluValue = animalCount * tluFactor; // Format the result let formattedValue; if (tluValue >= 1000000) { formattedValue = (tluValue / 1000000).toFixed(precision) + 'M'; } else if (tluValue >= 1000) { formattedValue = (tluValue / 1000).toFixed(precision) + 'K'; } else { formattedValue = tluValue.toFixed(precision); } return includeUnit ? `${formattedValue} TLU` : formattedValue; }; 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_lang(download_translation), \"CropClimateHazards.csv\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2665,"value":"{\n const text = _lang(nbText.climateRisks.hazardImpact.h1)\n return md`## ${text}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2664,"value":"{\n const text = _lang(nbText.climateRisks.hazardImpact.intro)\n return md`${text}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2259,"value":"// picking hazard\nviewof selectHazard = {\n const data = new Map(\n Object.keys(hazardPlotLookup.names)\n .filter(d => d !== 'no hazard') // remove no hazard option\n .map(d => [hazardPlotLookup.names[d], d])\n );\n return Inputs.select(data, {\n value: 'dry',\n label: _lang(nbText.climateRisks.hazardImpact.inputs.dropdownHazard.label)\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2662,"value":"{\n const template = _lang(nbText.climateRisks.hazardImpact.plots.crops.header)\n const items = [{name: \"hazard_string\", value: hazardPlotLookup.names[selectHazard].toLowerCase()}]\n const format = Lang.reduceReplaceTemplateItems(template, items)\n return md`### ${format}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2257,"value":"chart_35 = {\n const data = data_hazardVoP.filter((d) => {\n return (\n d.hazard == selectHazard &&\n d.vop !== 0 &&\n riskDataTypes.crop.crop.includes(d.crop)\n ); // lookup crop type\n });\n const marginLeft = _lang({en: 110, fr: 120});\n return makeTopCropBarChart(data, {marginLeft});\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4587,"value":"$4f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2808,"value":"buildInlineDownloadButton(\n data_hazardVoP.filter((d) => {\n return (\n d.hazard == selectHazard &&\n d.vop !== 0 &&\n riskDataTypes.crop.crop.includes(d.crop)\n );\n }), _lang(download_translation), `CropRisk_${selectHazard}.csv`)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2660,"value":"{\n const template = _lang(nbText.climateRisks.hazardImpact.plots.livestock.header)\n const items = [{name: \"hazard_string\", value: hazardPlotLookup.names[selectHazard].toLowerCase()}]\n const format = Lang.reduceReplaceTemplateItems(template, items)\n return md`### ${format}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2255,"value":"chart_38 = {\n const data = data_hazardVoP.filter((d) => {\n return (\n d.hazard == selectHazard &&\n d.vop !== 0 &&\n riskDataTypes.crop.livestock.includes(d.crop)\n ); // lookup crop type\n });\n const marginLeft = _lang({en: 110, fr: 150});\n return makeTopCropBarChart(data, {marginLeft});\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4596,"value":"$50","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2818,"value":"buildInlineDownloadButton(\n data_hazardVoP.filter((d) => {\n return (\n d.hazard == selectHazard &&\n d.vop !== 0 &&\n riskDataTypes.crop.livestock.includes(d.crop)\n );\n }), _lang(download_translation), `LivestockRisk_${selectHazard}.csv`)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2658,"value":"{\n const format = Lang.reduceReplaceTemplateItems(\n _lang(nbText.climateRisks.hazardImpact.insights.title),\n [\n { name: \"insight_string\", value: _lang(nbText.supportNbText.labels.quickInsights) },\n { name: \"admin_selection\", value: getAdminSelection().label },\n { name: \"scenario\", value: selectScenarioAndTimeframe.label }\n ]\n );\n return md`### ${format}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2251,"value":"$51","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2250,"value":"$52","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1363,"value":"{\n const text = _lang(nbText.adaptiveCapacities.h1)\n return md`# ${text}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2654,"value":"{\n const adminSelection = getAdminSelectionLabelWithParen({\n admin0Label: _lang(\n td.admin0_name.values?.[getAdminSelectionAdmin0().value ?? \"SSA\"][\"article3\"]\n ),\n adminSublabel: getAdminSelection().label\n });\n const format = Lang.reduceReplaceTemplateItems(\n _lang(nbText.adaptiveCapacities.intro),\n [{name: \"admin_selection\", value: adminSelection}]\n )\n return md`${format}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1996,"value":"// format admin selections\n// bind to appendix inputs, add template to format\nInputs.form(\n [\n Inputs.bind(\n Inputs.select(dataAdmin0, { label: adminRegions.labels.admin0, format: x => x.label }),\n viewof selectAdmin0\n ),\n Inputs.bind(\n Inputs.select(dataAdmin1, { label: adminRegions.labels.admin1, format: x => x.label }),\n viewof selectAdmin1\n ),\n Inputs.bind(\n Inputs.select(dataAdmin2, { label: adminRegions.labels.admin2, format: x => x.label }),\n viewof selectAdmin2\n ),\n Inputs.bind(\n Inputs.select(dataAdmin3, { label: adminRegions.labels.admin3, format: x => x.label }),\n viewof selectAdmin3\n )\n ],\n {\n template: adminFormTemplate\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1821,"value":"// define choices for the data value\nviewof selectAcDataTypeNew = {\n const options = dataLayerOptionsAdaptiveCapacities;\n \n return Inputs.radio(options, {\n width: 300,\n label: _lang(nbText.adaptiveCapacities.inputs.mapLayer.label),\n format: (x) => x.label,\n value: options.find((t) => t.key === \"pov\"),\n sort: true\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4083,"value":"viewof genderFilter = Inputs.select([\"All\", \"Men\", \"Women\"], {label: \"Gender Disaggregation (for Poverty and Education)\", value: \"All\"});","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4429,"value":"viewof plotChoroplethAdaptiveCapacity1ChartType = {return(\n Inputs.radio(\n [\"map\", \"bar\"],\n {\n label: \"Chart Type\",\n format: (d) => d === \"map\" ? \"Map\" : \"Bar Chart\",\n value: \"map\"\n }\n )\n)}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1817,"value":"$53","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4532,"value":"$54","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2787,"value":"buildInlineDownloadButton(dataAdaptiveCapacity, _lang(download_translation), \"AdaptiveCapacityMap\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2651,"value":"{\n const format = Lang.reduceReplaceTemplateItems(\n _lang(nbText.adaptiveCapacities.insights.title),\n [\n { name: \"insight_string\", value: _lang(nbText.supportNbText.labels.quickInsights) },\n { name: \"admin_selection\", value: getAdminSelection().label },\n ]\n );\n return md`## ${format}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2748,"value":"$55","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2649,"value":"{\n const text = _lang(nbText.adaptiveCapacities.delvingDeeper.h2)\n return md`## ${text}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2322,"value":"{\n const text = _lang(nbText.adaptiveCapacities.delvingDeeper.intro)\n return md`${text}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2247,"value":"// format admin selections\n// bind to appendix inputs, add template to format\nInputs.form(\n [\n Inputs.bind(\n Inputs.select(dataAdmin0, { label: adminRegions.labels.admin0, format: x => x.label }),\n viewof selectAdmin0\n ),\n Inputs.bind(\n Inputs.select(dataAdmin1, { label: adminRegions.labels.admin1, format: x => x.label }),\n viewof selectAdmin1\n ),\n Inputs.bind(\n Inputs.select(dataAdmin2, { label: adminRegions.labels.admin2, format: x => x.label }),\n viewof selectAdmin2\n ),\n Inputs.bind(\n Inputs.select(dataAdmin3, { label: adminRegions.labels.admin3, format: x => x.label }),\n viewof selectAdmin3\n )\n ],\n {\n template: adminFormTemplate\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2246,"value":"$56","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2382,"value":"$57","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4605,"value":"$58","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2776,"value":"buildInlineDownloadButton(icicle_raw, _lang(download_translation), \"AdaptiveCapacityIcicle\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1358,"value":"{\n const text = _lang(nbText.summary.h1)\n return md`# ${text}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1356,"value":"dynamicSummaryCell = {\n let dynamicSummary = \"\";\n // add filter to do nothing in case where no admin0 is selected\n if (adminSelections.selectAdmin0.value !== null) {\n dynamicSummary = Lang.reduceReplaceTemplateItems(\n _lang(nbText.summary.dynamicSummarylist),\n [{ name: \"markdownList\", value: dynamicSummaryMarkdown }]\n );\n }\n const admin0 = _lang(\n td.admin0_name.values?.[getAdminSelectionAdmin0().value ?? 'SSA'][\"article3\"]\n );\n const intro = Lang.reduceReplaceTemplateItems(\n _lang(nbText.summary.blocks.dynamicSummary.intro),\n [{ name: \"admin0\", value: admin0 }]\n );\n\n return md`${intro} ${dynamicSummary}`;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1634,"value":"{\n const text = _lang(nbText.summary.blocks.closer)\n return md`${text}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2642,"value":"{\n const text = _lang(nbText.methods.h1)\n return md`# ${text}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2641,"value":"{\n const text = _lang(nbText.methods.section1)\n return md`## ${text}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2640,"value":"{\n const text = _lang(nbText.methods.section1.subsections);\n return md`${text}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2639,"value":"{\n const text = _lang(nbText.methods.section2)\n return md`## ${text}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2638,"value":"{\n const text = _lang(nbText.methods.section2.subsections)\n return md`${text}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":49,"value":"***\n# Appendix\nThis large section includes all the cells that power the notebook.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2244,"value":"toc()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1258,"value":"---\n## Work by Topic\n*Cells that power different sections*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1750,"value":"---\n### Support notebook\n[Support Notebook](https://observablehq.com/@periscopic/ab-atlas-spotlight-support): used for imports across spotlights.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1747,"value":"---\n### Notebook Variables\n_Main variables across notebook_","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1746,"value":"// main title of the notebook\nnotebookTitle = \"Evaluate Climate Risks\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1745,"value":"// info for the admin selectors - UPDATED\nadminRegions = {\n return {\n labels: {\n admin0: Lang.toSentenceCase(\n _lang(nbText.supportNbText.words.country.singular)\n ),\n admin1: Lang.toSentenceCase(\n _lang(nbText.supportNbText.words.region.singular)\n ),\n admin2: Lang.toSentenceCase(\n _lang(nbText.supportNbText.words.subregion.singular)\n ),\n admin3: Lang.toSentenceCase(\n _lang(nbText.supportNbText.words.woreda.singular)\n ),\n },\n allLabels: {\n admin1: _lang(nbText.supportNbText.labels.allRegions),\n admin2: _lang(nbText.supportNbText.labels.allSubregions),\n admin3: _lang(nbText.supportNbText.labels.allWoredas)\n }\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2110,"value":"function getLowerLevelAdminLabel(selections=adminSelections) {\n // based on admin selection, get the lower level label \n if (selections.selectAdmin3.value) return adminRegions.labels.admin3\n if (selections.selectAdmin2.value) return adminRegions.labels.admin3\n if (selections.selectAdmin1.value) return adminRegions.labels.admin2\n if (selections.selectAdmin0.value) return adminRegions.labels.admin1\n else return adminRegions.labels.admin0\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2180,"value":"// width of the maps\nmapWidth = 625","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2634,"value":"**Language and notebook text**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2633,"value":"import { Lang } from \"7d46679f7d0d917e\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2632,"value":"Lang ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2631,"value":"languages = [\n { key: \"en\", label: \"English\", locale: 'en-US' },\n { key: \"am\", label: \"አማርኛ\", locale: 'am-ET' },\n {key: \"or\", label: \"Afaan Oromoo\", locale: 'or-ET'},\n {key: \"ti\", label: \"ትግርኛ\", locale: 'ti-ET'},\n {key: \"so\", label: \"Soomaali\", locale: 'so-ET'},\n {key: \"af\", label: \"Qafar af\", locale: 'af-ET'}\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2630,"value":"// get the default language key from parameter, or use default\ndefaultLangKey = {\n const name = \"lang\";\n const list = languages.map((d) => d.key);\n const defaultKey = \"en\";\n\n const queryParam = await Lang.getParamFromList({ name, list });\n\n return queryParam ?? defaultKey;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2629,"value":"// helper shorthand for Lang text-getting\n_lang = Lang.lg(language.key)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2628,"value":"// main toggle of language key\nviewof language = Inputs.radio(languages, {\n label: \"Main language toggle\",\n format: (d) => d.key,\n value: languages.find((x) => x.key === defaultLangKey),\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2626,"value":"// data translation values\ntd = {\n let data = await FileAttachment(\"abAtlas-td-translation-data-v3 (4)-2 (3)@1.json\").json()\n\n // // update SSA default\n // data.admin0_name.values.SSA.en = \"Sub-Saharan Africa\"\n // // cote d'ivoire, comma version duplicate\n // data.admin0_name.values[\"Côte d’Ivoire\"] = data.admin0_name.values[\"Côte d'Ivoire\"]\n \n return data\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1644,"value":"---\n### Notebook Styling\n*styling helpers*\nStylesheet is a named cell, which is necessary to include for embeds.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1813,"value":"**CSS styling**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1643,"value":"viewof toggleCustomStyling = Inputs.toggle({label: \"Use custom styling\", value: true})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1642,"value":"$59","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2779,"value":"downloadButtonCSS = htl.html`\nDownload Button CSS\n\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2175,"value":"**Table of Contents**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2174,"value":"$5a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1812,"value":"**Color Scales**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":4621,"value":"$5b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4676,"value":"$5c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2627,"value":"$5d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3046,"value":"// get admin3 options based on admin2 selection - ETHIOPIA ONLY\ndataAdmin3 = {\n if (!selectAdmin2.value || !selectAdmin0.value || selectAdmin0.value !== \"Ethiopia\") {\n return [{ label: \"All Woredas\", value: null }];\n }\n \n // Only get woredas for Ethiopia\n const data = admin3_cleaned.features\n .filter(d => \n d.properties.admin0_name === \"Ethiopia\" &&\n d.properties.admin1_name === selectAdmin1.value &&\n d.properties.admin2_name === selectAdmin2.value\n )\n .map(d => d.properties.admin3_name);\n \n const allLabel = {\n label: adminRegions.allLabels.admin3,\n value: null\n }\n \n const uniqueWoredas = [...new Set(data)].sort();\n \n return [allLabel, ...uniqueWoredas.map(d => {\n return {\n label: d,\n value: d,\n }\n })];\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1811,"value":"// color scale info\ncolorScales = {\n return {\n range: {\n green: ['#E4F5D0', '#015023'],\n blue: ['#E8F2FF', '#003E6B'],\n brown: ['#FFFDE5', '#A87B00'],\n yellowGreen: ['#F7D732', '#216729'],\n orangeRed: ['#F4BB21', '#EC5A47'],\n },\n unknown: \"#ccc\"\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1257,"value":"---\n### Admin Selection\n*Global admin selector using dropdowns*\n\nThis is the global selector for the selected region\n- The completed data is contained within `adminSelections` to be used in queries\n- Dropdowns are defined below then bound for each section\n - Defined as separate cells since they dynamically respond to different values\n - In narrative, they are simply views of the data \n - Dropdowns are dynamic based on higher-level choices\n - Options are defined from the geographic data\n - `null` value means unselected region\n- Dropdowns are added to each section, using `Inputs.bind` to create synchronized inputs (see `viewof` for input definitions). A form input is used to consolidate and apply a template to format.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1256,"value":"// get admin0 options from geo\ndataAdmin0 = {\n const data = admin0.features.map((d) => d.properties);\n // add a blank value\n return [null, ...data.map((d) => d.admin_name)].map((d) => {\n return {\n label:\n d == null ? globalSelection.label : _lang(td.admin0_name.values?.[d]?.general),\n value: d\n };\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1255,"value":"// get admin1 options based on admin0 selection\n// (the admin1 regions within selected admin0)\ndataAdmin1 = {\n // admin 1, filter by 0 \n // const data = boundaries.admin1.features.map(d => d.properties)\n // .filter(d => d.admin0_name == selectAdmin0.value)\n const data = await geo_db.query(`SELECT DISTINCT admin1_name FROM admin1_geom WHERE admin0_name = '${selectAdmin0.value}'`)\n // add blank value\n const allLabel = {\n label: adminRegions.allLabels.admin1,\n value: null\n }\n return [allLabel, ...data.map(d => {\n return {\n label: d.admin1_name,\n value: d.admin1_name,\n }\n })].map(d => {\n return {label: d.label, value: d.value}\n })\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1251,"value":"$5e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1254,"value":"// get admin2 options based on admin1 selection\n// (the admin2 regions within selected admin1)\ndataAdmin2 = {\n // const data = boundaries.admin2.features.map(d => d.properties)\n // .filter(d => d.admin0_name == selectAdmin0.value && d.admin1_name == selectAdmin1.value)\n const data = await geo_db.query(`SELECT DISTINCT admin2_name FROM admin2_geom WHERE admin0_name = '${selectAdmin0.value}' AND admin1_name = '${cleanAdminInput_SQL(selectAdmin1.value)}'`)\n // add blank value\n const allLabel = {\n label: adminRegions.allLabels.admin2,\n value: null\n }\n return [allLabel, ...data.map(d => {\n return {\n label: d.admin2_name,\n value: d.admin2_name,\n }\n })].map(d => {\n return {label: d.label, value: d.value}\n })\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1265,"value":"viewof selectAdmin0 = Inputs.select(dataAdmin0, {\n label: adminRegions.labels.admin0,\n format: x => x.label,\n value: dataAdmin0.find(x => x.label === \"Ethiopia\") // Set default to Ethiopia\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1264,"value":"viewof selectAdmin1 = Inputs.select(dataAdmin1, {label: adminRegions.labels.admin1, format: x => x.label})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1263,"value":"viewof selectAdmin2 = Inputs.select(dataAdmin2, {label: adminRegions.labels.admin2, format: x => x.label})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3090,"value":"viewof selectAdmin3 = Inputs.select(dataAdmin3, {label: adminRegions.labels.admin3, format: x => x.label})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1253,"value":"adminSelections = ({\n selectAdmin0: selectAdmin0,\n selectAdmin1: selectAdmin1,\n selectAdmin2: selectAdmin2,\n selectAdmin3: selectAdmin3\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1955,"value":"// template to format admin selection form\nadminFormTemplate = (inputs) => htl.html`

${inputs}

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2620,"value":"getAdminSelectionLabelWithParen = ({\n selections = adminSelections,\n admin0Label,\n adminSublabel\n} = {}) => {\n // return admin0 selection and admin1/admin2 selection if chosen (in parentheses)\n if (selections.selectAdmin1.value === null) {\n return admin0Label;\n } else {\n return `${admin0Label} (${adminSublabel})`;\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3188,"value":"// A helper to get all existing admin3_name units for a given admin2_name\nadmin3NamesByAdmin2 = {\n // Add dependency to make it reactive\n void boundaries;\n \n const map = new Map();\n if (boundaries.admin3 && boundaries.admin3.features) {\n for (const f of boundaries.admin3.features) {\n const a2_name = f.properties.admin2_name;\n const a3_name = f.properties.admin3_name;\n \n if (a2_name && a3_name) {\n if (!map.has(a2_name)) {\n map.set(a2_name, new Set());\n }\n map.get(a2_name).add(a3_name);\n }\n }\n }\n return map;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1339,"value":"---\n### Admin Selection - Display\n*Showing admin selections*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1338,"value":"// options for the global admin selection\n// used when no admin selection is made\nglobalSelection = {\n return {\n label: _lang(td.admin0_name.values.SSA.general),\n value: null\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1336,"value":"$5f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1629,"value":"function getAdminSelectionAdmin0(selections=adminSelections) {\n // get the selected admin0 or global value\n const a0 = selections.selectAdmin0\n const global = globalSelection.label\n\n return a0\n ? a0\n : global\n} ","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1335,"value":"function getAdminSelectionMarkdownPath(selections=adminSelections) {\n // function to show selected admin region\n // return path showing nested admin selection\n \n const delim = ' → '\n const path = [\n selections.selectAdmin0,\n selections.selectAdmin1,\n selections.selectAdmin2\n ].filter(d => d)\n \n const formatted = path\n .filter((d) => d)\n .map((d, i) => {\n return (i == path.length - 1)\n ? `**${d}**`\n : `*${d}*`\n })\n \n return formatted.length == 0\n ? `**${globalSelection.label}**` // no selection, all of Africa\n : `${formatted.join(delim)}`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1252,"value":"---\n### Choropleth map - Geographic Impact\n*Showing context for admin selection*\n\nThere is some hoop-jumping to get the right data based on the Admin Selection. The tabular data is then bound to the applicable geojson, and visualized with Plot.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2743,"value":"dataPopulation = async (admin_query) => {\n return await db.query(`\nselect * \nfrom population\n${admin_query}\n`)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1292,"value":"// // total VoP data\ndataTotalVoP = async (admin_query) => {\nreturn await db.query(`\nselect admin0_name\n , admin1_name\n , admin2_name\n , SUM(value) as vop_total\n from vop\n ${admin_query}\n group by admin0_name, admin1_name, admin2_name\n order by admin0_name, admin1_name, admin2_name\n`)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3792,"value":"mockWoredaData = {\n return await FileAttachment(\"mock_woreda_data@7.csv\").csv({ typed: true });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4077,"value":"mockAdaptiveCapacityData = {\n return await FileAttachment(\"mock_adaptive_capacity_data@1.csv\").csv({ typed: true });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3233,"value":"$60","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3519,"value":"// Add mock VOP data to admin3 features\nfunction addMockVopDataToAdmin3(admin3Data) {\n if (!admin3Data || !admin3Data.features) return admin3Data;\n \n // Create a copy to avoid modifying the original\n const enhancedData = JSON.parse(JSON.stringify(admin3Data));\n \n enhancedData.features.forEach(feature => {\n if (feature.properties.data) {\n // Generate mock VOP data based on rural population\n const ruralPop = feature.properties.data.rural_pop || 0;\n const totalPop = feature.properties.data.total_pop || ruralPop;\n \n // VOP is roughly proportional to population with some variation\n // Using a reasonable per-capita VOP estimate for Ethiopia\n const vopPerCapita = 150 + (Math.random() * 100); // $150-250 per capita\n const vopTotal = totalPop * vopPerCapita;\n \n // Add mock VOP data to the embedded data\n feature.properties.data.vop_total = vopTotal;\n }\n });\n \n return enhancedData;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3581,"value":"// Alternative: Simple scale calculation\nfunction calculateOptimalScale(bounds, width, height) {\n const [[minLon, minLat], [maxLon, maxLat]] = bounds;\n const lonRange = maxLon - minLon;\n \n // Simple heuristic: for Ethiopia regions, these scales usually work well\n if (lonRange < 0.5) return 50000; // Very small area\n if (lonRange < 1.0) return 30000; // Small area \n if (lonRange < 2.0) return 20000; // Medium area\n return 15000; // Larger area\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3522,"value":"$61","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3834,"value":"{\n const vulSample = await db.query(\"SELECT * FROM vul_ac2 LIMIT 5\");\n const popSample = await db.query(\"SELECT * FROM population LIMIT 5\");\n return { vulSample, popSample };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1250,"value":"$62","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1334,"value":"---\n### Dynamic Insights - Geographic Impact\n*quick insights for given admin selection*\n\n- Sql cells add a row that is the combined value for all admin regions, where all admin names are `null`.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1453,"value":"Here are the combined data and insights for creating the dynamic narrative. Data tables are below.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1333,"value":"$63","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1332,"value":"---\n#### Data cells for insights","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2739,"value":"$64","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1452,"value":"// total harvested area\ndynInsightGeo_haTotals = {\n let admin_query = insight_adminQuery\n \n return await db.query(`\nwith tblHA as (\n -- total VoP and harvested area\n SELECT admin0_name, admin1_name, admin2_name, SUM(value) AS ha_total\n FROM ha\n ${admin_query}\n AND exposure = 'ha'\n GROUP BY 1, 2, 3\n)\n\n-- QUERY ------------------------------------------\n(\n -- total for all regions\n select null as admin0_name\n , null as admin1_name\n , null as admin2_name\n , ha_total\n from (\n select sum(ha_total) as ha_total\n from tblHA\n )\n \n union\n \n select * \n from tblHA\n \n order by 1, 2, 3\n)\n`)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1451,"value":"dynInsightGeo_vopTotals = {\n let admin_query = insight_adminQuery\n\n \n return db.query(`\n-- total value of production\nwith tbl as (\n -- total VoP and harvested area\n SELECT admin0_name, admin1_name, admin2_name, SUM(value) AS vop_total\n FROM vop\n ${admin_query}\n GROUP BY 1, 2, 3\n ORDER BY 1, 2, 3\n)\n\n-- QUERY ------------------------------------------\n(\n -- total for all regions\n select null as admin0_name\n , null as admin1_name\n , null as admin2_name\n , vop_total\n from (\n select sum(vop_total) as vop_total\n from tbl\n )\n \n union\n \n select * \n from tbl\n \n order by 1, 2, 3\n)\n`)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1450,"value":"dynInsightGeo_population = {\n let admin_query = insight_adminQuery\nreturn await db.query(`\nwith tbl as (\n -- population data\n select admin0_name\n , admin1_name\n , admin2_name\n , total_pop\n , rural_pop\n from population\n ${admin_query}\n order by admin0_name\n , admin1_name\n , admin2_name\n)\n\n-- QUERY ------------------------------------------\n(\n -- total for all regions\n select null as admin0_name\n , null as admin1_name\n , null as admin2_name\n , *\n from (\n select sum(total_pop) as total_pop\n , sum(rural_pop) as rural_pop\n from tbl\n )\n \n union\n \n select *\n from tbl\n \n order by 1, 2, 3\n)\n`)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2735,"value":"$65","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2734,"value":"$66","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1694,"value":"---\n### Bar Charts - Hazards and Exposures\n*getting data based on admin selection and hazard options*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2243,"value":"#### Plot Function\nMaking the top VoP bar charts","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2242,"value":"$67","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2241,"value":"#### Hazard Data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2240,"value":"➡️ The hazard data includes a `generic` crop, which is a large value that dwarfs other crop values. We exclude this from the chart.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2239,"value":"Below is a table of the explanations of every hazard component. The `any` hazard is the combination of all of the below hazards.\n\n| hazard | description |\n| --- | --- |\n| dry | risk of dry hazard occurring alone |\n| heat | risk of heat hazard occurring alone |\n| wet | risk of wet hazard occurring alone |\n| dry+heat | risk of dry and heat hazard occurring together |\n| dry+wet | risk of dry and wet hazard occurring together |\n| heat+wet | risk of heat and wet hazard occurring together |\n| dry+heat+wet | risk of dry and heat and wet hazard occurring together |\n| No hazard | no hazard applied\n\n*If there are zeros for individual hazards then it means it always occurs in combination with another hazard and does not occur alone.*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2414,"value":"// data for selected hazard scenario, with total vop\ndata_hazardVoP = T.tidy(\n dataHazardSelected,\n T.leftJoin(dataHazardVoPTotalSelected, {by: ['admin0_name', 'admin1_name', 'admin2_name', 'admin3_name', 'crop']}),\n T.filter((d) => d.crop !== 'generic') // remove generic \n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2413,"value":"dataHazardVoPTotalSelected = T.tidy(\n dataHazardSelected,\n T.filter((d) => d.hazard !== 'any'),\n T.groupBy(\n [\n \"admin0_name\",\n \"admin1_name\",\n \"admin2_name\",\n \"admin3_name\",\n \"severity\",\n \"scenario\",\n \"timeframe\",\n \"crop\"\n ],\n [\n T.summarize({\n vop_total: T.sum(\"vop\")\n })\n ]\n )\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2412,"value":"#### Lookups","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2236,"value":"// unique crops in the hazard data\nhazardCrops = {\n const query = await db.query(`select crop\n , count(*) as count\n from haz_risk_vop_int_combined\n group by 1\n order by 1`);\n\n return query\n }","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2233,"value":"$68","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2234,"value":"$69","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1691,"value":"#### Selecting VoP data by scenario\n- The data is queried as separate components for each admin region to reduce query size and allow for dynamic null handling. A table is chosen based on the selected admin region.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1690,"value":"// pick the admin dataset based on admin selection\ndataHazardSelected = {\n if (adminSelections.selectAdmin3?.value) return dataHazardAdmin3\n else if (adminSelections.selectAdmin2.value) return dataHazardAdmin2\n else if (adminSelections.selectAdmin1.value) return dataHazardAdmin1\n else if (adminSelections.selectAdmin0.value) return dataHazardAdmin0\n else return dataHazardAdminAll\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2733,"value":"$6a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2732,"value":"dataHazardAdmin0 = db.query(`\n select admin0_name\n , admin1_name\n , admin2_name\n , scenario\n , timeframe\n , crop\n , severity\n , hazard\n , value as vop\n from haz_risk_vop_int_combined\n where severity = 'severe' -- hard-coded\n -- and hazard in ('heat', 'wet', 'dry') -- single hazards alone\n and timeframe = '${selectScenarioAndTimeframe.timeframe}'\n and scenario = '${selectScenarioAndTimeframe.scenario}'\n and admin1_name is null\n and admin0_name = '${adminSelections.selectAdmin0.value}'`)\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2731,"value":"dataHazardAdmin1 = db.query(`-- admin1 level hazard data\n -- chosen scenario and timeframe VoP\n select admin0_name\n , admin1_name\n , admin2_name\n , scenario\n , timeframe\n , crop\n , severity\n , hazard\n , value as vop\n from haz_risk_vop_int_combined\n where severity = 'severe' -- hard-coded\n -- and hazard in ('heat', 'wet', 'dry') -- single hazards alone\n and timeframe = '${selectScenarioAndTimeframe.timeframe}'\n and scenario = '${selectScenarioAndTimeframe.scenario}'\n and admin0_name = '${adminSelections.selectAdmin0.value}'\n and admin1_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin1.value)}'\n and admin2_name is null\n`)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2730,"value":"dataHazardAdmin2 = db.query(`-- admin2 level hazard data\n -- chosen scenario and timeframe VoP\n select admin0_name\n , admin1_name\n , admin2_name\n , scenario\n , timeframe\n , crop\n , severity\n , hazard\n , value as vop\n from haz_risk_vop_int_combined\n where severity = 'severe' -- hard-coded\n -- and hazard in ('heat', 'wet', 'dry') -- single hazards alone\n and timeframe = '${selectScenarioAndTimeframe.timeframe}'\n and scenario = '${selectScenarioAndTimeframe.scenario}'\n and admin0_name = '${adminSelections.selectAdmin0.value}'\n and admin1_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin1.value)}'\n and admin2_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin2.value)}'\n and admin3_name IS NULL -- Only subregion-level data, not woreda-level\n`)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4388,"value":"dataHazardAdmin3 = db.query(`-- admin3 level (woreda) hazard data\n -- chosen scenario and timeframe VoP\n select admin0_name\n , admin1_name\n , admin2_name\n , admin3_name\n , scenario\n , timeframe\n , crop\n , severity\n , hazard\n , value as vop\n from haz_risk_vop_int_combined\n where severity = 'severe' -- hard-coded\n and timeframe = '${selectScenarioAndTimeframe.timeframe}'\n and scenario = '${selectScenarioAndTimeframe.scenario}'\n and admin0_name = '${adminSelections.selectAdmin0.value}'\n and admin1_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin1.value)}'\n and admin2_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin2.value)}'\n and admin3_name = '${cleanAdminInput_SQL(adminSelections.selectAdmin3.value)}'\n`)\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2923,"value":"db.query(`SELECT DISTINCT admin0_name from haz_risk_vop_int_combined\n where severity = 'severe' and hazard = 'dry+heat+wet' and value > 0 and admin1_name is null`)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2231,"value":"---\n### Dynamic Insights - Hazards and exposures","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2230,"value":"// get selected hazard for insights, define crop type\ndata_selectedHazardCropType = T.tidy(\n data_hazardVoP,\n T.filter(d => d.hazard == selectHazard),\n T.mutate({\n cropType: d => {\n if (riskDataTypes.crop.crop.includes(d.crop)) return 'crop'\n if (riskDataTypes.crop.livestock.includes(d.crop)) return 'livestock'\n return 'other'\n }\n }),\n T.arrange(['cropType', T.desc('vop')])\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2229,"value":"// combined crop and livestock exposed for selection\ninsight_totalExposedVop = T.tidy(\n data_selectedHazardCropType,\n T.groupBy(['cropType'], [\n T.summarize({\n totalExposedVop: T.sum('vop')\n })\n ])\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2228,"value":"// top crop and livestock for selection\ninsight_topCrops = {\n const topCrop = T.tidy(\n data_selectedHazardCropType,\n T.select([\"cropType\", \"crop\", \"vop\"]),\n T.filter((d) => d.cropType == \"crop\"),\n T.sliceMax(1, \"vop\")\n );\n const topLivestock = T.tidy(\n data_selectedHazardCropType,\n T.select([\"cropType\", \"crop\", \"vop\"]),\n T.filter((d) => d.cropType == \"livestock\"),\n T.sliceMax(1, \"vop\")\n );\n return [\n ...topCrop,\n ...topLivestock\n ]\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2227,"value":"// total vop exposed by each hazard\ninsight_rankedHazardVopTotals = T.tidy(\n data_hazardVoP,\n T.groupBy(['hazard'], [\n T.summarize({\n totalVop: T.sum('vop')\n })\n ]),\n T.filter((d) => !['any', 'no hazard'].includes(d.hazard)), // remove combined and no hazard\n T.arrange(T.desc('totalVop'))\n \n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1381,"value":"---\n### Choropleth map - Adaptive Capacities\n*Population affected by admin region*\n- Fetch the data separately for the different admin levels and generate map data for each\n- Serve different data based on admin selection","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2606,"value":"$6b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1809,"value":"$6c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4157,"value":"$6d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4144,"value":"{\n console.log(\"DEBUG: adminSelections:\", {\n admin0: adminSelections.selectAdmin0.value,\n admin1: adminSelections.selectAdmin1.value,\n admin2: adminSelections.selectAdmin2.value,\n admin3: adminSelections.selectAdmin3.value\n });\n console.log(\"DEBUG: dataAdaptiveCapacity sample:\", dataAdaptiveCapacity.slice(0, 2));\n console.log(\"DEBUG: mapDataAdaptiveCapacityAdmin0 features:\", mapDataAdaptiveCapacityAdmin0.features.length);\n console.log(\"DEBUG: mapDataAdaptiveCapacityAdmin2 features:\", mapDataAdaptiveCapacityAdmin2.features.length);\n console.log(\"DEBUG: mapDataAdaptiveCapacityAdmin3 features:\", mapDataAdaptiveCapacityAdmin3.features.length);\n console.log(\"DEBUG: mapFeaturesAdaptiveCapacity sample:\", mapFeaturesAdaptiveCapacity.slice(0, 2).map(f => f.properties));\n return { dataAdaptiveCapacity, mapDataAdmin0: mapDataAdaptiveCapacityAdmin0, mapDataAdmin2: mapDataAdaptiveCapacityAdmin2, mapDataAdmin3: mapDataAdaptiveCapacityAdmin3, mapFeatures: mapFeaturesAdaptiveCapacity };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1808,"value":"mapDataAdaptiveCapacityAdmin2 = {\n const data = T.tidy(\n dataAdaptiveCapacity,\n T.mutate({ a2_a1_a0: (d) => [d.admin2_name || '', d.admin1_name || '', d.admin0_name].join(\"_\") })\n );\n const geoData = boundaries.admin2;\n \n console.log(\"DEBUG: mapDataAdaptiveCapacityAdmin2 - Data rows:\", data.length);\n console.log(\"DEBUG: mapDataAdaptiveCapacityAdmin2 - Geo features:\", geoData?.features?.length || 0);\n \n const result = bindTabularToGeo({\n data: data,\n dataBindColumn: \"a2_a1_a0\",\n geoData: geoData,\n geoDataBindColumn: \"a2_a1_a0\"\n });\n \n console.log(\"DEBUG: mapDataAdaptiveCapacityAdmin2 - Bound features:\", result.features.length);\n console.log(\"DEBUG: mapDataAdaptiveCapacityAdmin2 - Sample bound feature:\", result.features[0]?.properties);\n \n return result;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1807,"value":"mapDataAdaptiveCapacityAdmin0 = {\n const data = T.tidy(\n dataAdaptiveCapacity,\n T.mutate({ admin0_name: (d) => d.admin0_name })\n );\n const geoData = boundaries.admin0;\n\n return bindTabularToGeo({\n data: data,\n dataBindColumn: \"admin0_name\",\n geoData: geoData,\n geoDataBindColumn: \"admin0_name\"\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3086,"value":"$6e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4123,"value":"{\n console.log(\"DEBUG: adminSelections:\", {\n admin0: adminSelections.selectAdmin0.value,\n admin1: adminSelections.selectAdmin1.value,\n admin2: adminSelections.selectAdmin2.value,\n admin3: adminSelections.selectAdmin3.value\n });\n console.log(\"DEBUG: dataAdaptiveCapacity sample:\", dataAdaptiveCapacity.slice(0, 2));\n console.log(\"DEBUG: boundaries.admin3_with_vop features:\", boundaries.admin3_with_vop?.features?.length || 0);\n console.log(\"DEBUG: mapDataAdaptiveCapacityAdmin3 features:\", mapDataAdaptiveCapacityAdmin3.features.length);\n console.log(\"DEBUG: mapFeaturesAdaptiveCapacity features:\", mapFeaturesAdaptiveCapacity.length);\n console.log(\"admin 3\",boundaries?.admin3)\n return { dataAdaptiveCapacity, mapDataAdmin3: mapDataAdaptiveCapacityAdmin3, mapFeatures: mapFeaturesAdaptiveCapacity };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2727,"value":"$6f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":4171,"value":"$70","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1498,"value":"---\n### Dynamic Insights - Adapative Capacities\n*insights and helpers*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2172,"value":"$71","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1496,"value":"#### Helpers","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2171,"value":"$72","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2725,"value":"// define the mad lib for adaptive capacity admin1 and admin 0 levels\nfunction adaptiveCapacityInsightMadLib2(data, adminName) {\n // Handle NaN values\n const education_years = (data?.ac_edu_perc != null && !isNaN(data.ac_edu_perc)) \n ? data.ac_edu_perc.toFixed(2) \n : \"NaN\";\n const female_empowerment = (data?.ac_fem_perc != null && !isNaN(data.ac_fem_perc)) \n ? (data.ac_fem_perc * 100).toFixed(0) \n : \"NaN\";\n const poverty_rate = (data?.ac_pov_perc != null && !isNaN(data.ac_pov_perc)) \n ? formatPercentWhole(data.ac_pov_perc) \n : \"NaN\";\n\n \n return `In **${adminName}**, the average educational attainment is **${education_years}** years, the female empowerment index is **${female_empowerment}**, and **${poverty_rate}** live in poverty.`\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2724,"value":"$73","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2226,"value":"---\n### Adaptive Capacity Icicle - Adaptive Capacities\nNote: data uses `SSA` for combined admin region (see `icicle_csv`)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2723,"value":"icicle_raw = {\n const country = adminSelections.selectAdmin0.value || \"SSA\";\n const admin1 = adminSelections.selectAdmin1.value || null;\n const admin2 = adminSelections.selectAdmin2.value || null;\n const admin3 = adminSelections.selectAdmin3?.value || null;\n \n let adminQuery = `WHERE admin0_name = '${country}' AND admin1_name`\n adminQuery += !admin1 ? ` IS NULL` : ` = '${cleanAdminInput_SQL(admin1)}'`\n adminQuery += ` AND admin2_name`\n adminQuery += !admin2 ? ` IS NULL` : ` = '${cleanAdminInput_SQL(admin2)}'`\n adminQuery += ` AND admin3_name`\n adminQuery += !admin3 ? ` IS NULL` : ` = '${cleanAdminInput_SQL(admin3)}'`\n // let adminQuery = `WHERE admin0_name = 'Angola' AND admin1_name IS NULL`\n // return adminQuery\n return db.query(`SELECT path, value FROM icicle_data ${adminQuery}`)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2722,"value":"icicle_data = buildHierarchy(icicle_raw)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2221,"value":"icicle_alias = {\n const base = nbText.adaptiveCapacities.delvingDeeper.plot.nameMap\n const nameMap = {\n population: _lang(base.population),\n poverty0: _lang(base.poverty0),\n poverty1: _lang(base.poverty1),\n poverty2: _lang(base.poverty2),\n education0: _lang(base.education0),\n education1: _lang(base.education1),\n education2: _lang(base.education2),\n gender0: _lang(base.gender0),\n gender1: _lang(base.gender1),\n gender2: _lang(base.gender2)\n };\n return nameMap;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2220,"value":"partition = (data) =>\n d3\n .partition()\n .padding(1)\n .size(narrow ? [height, width] : [width, height])(\n d3\n .hierarchy(data)\n .sum((d) => d.value)\n .sort((a, b) => b.value - a.value)\n )","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2219,"value":"icicle_color = d3\n .scaleOrdinal()\n .domain([\n \"population\",\n \"poverty2\",\n \"poverty1\",\n \"poverty0\",\n \"education2\",\n \"education1\",\n \"education0\",\n \"gender2\",\n \"gender1\",\n \"gender0\"\n ])\n .range([\n \"#a4a4a4\",\n \"#ec5a47\",\n \"#fc8a34\",\n \"#f4bb21\",\n \"#f4bb21\",\n \"#fc8a34\",\n \"#ec5a47\",\n \"#f4bb21\",\n \"#fc8a34\",\n \"#ec5a47\"\n ])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2218,"value":"targetHeight = 350","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2217,"value":"narrowHeight = 600","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2216,"value":"height = narrow ? narrowHeight : targetHeight","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2215,"value":"narrow = width <= 0","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2214,"value":"segmentX = d => (narrow ? d.y0 : d.x0)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2213,"value":"segmentY = d => (narrow ? d.x0 : d.y0)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2212,"value":"segmentWidth = d => (narrow ? d.y1 - d.y0 : d.x1 - d.x0)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2211,"value":"segmentHeight = d => (narrow ? d.x1 - d.x0 : d.y1 - d.y0)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2210,"value":"$74","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2209,"value":"breadcrumbWidth = 200","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2208,"value":"breadcrumbHeight = 35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2207,"value":"// Generate a string that describes the points of a breadcrumb SVG polygon.\nfunction breadcrumbPoints(d, i) {\n const tipWidth = 10;\n const points = [];\n points.push(\"0,0\");\n points.push(`${breadcrumbWidth},0`);\n points.push(`${breadcrumbWidth + tipWidth},${breadcrumbHeight / 2}`);\n points.push(`${breadcrumbWidth},${breadcrumbHeight}`);\n points.push(`0,${breadcrumbHeight}`);\n if (i > 0) {\n // Leftmost breadcrumb; don't include 6th vertex.\n points.push(`${tipWidth},${breadcrumbHeight / 2}`);\n }\n return points.join(\" \");\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2206,"value":"This notebook reuses much of the `buildHierarchy` function from the original [Sequences sunburst](https://gist.github.com/kerryrodden/7090426) gist, which was published with the following [license](https://gist.github.com/kerryrodden/7090426#file-license):\n\n> Copyright 2013 Google Inc. All Rights Reserved.\n> \n> Licensed under the Apache License, Version 2.0 (the \"License\");\n> you may not use this file except in compliance with the License.\n> You may obtain a copy of the License at\n> \n> http://www.apache.org/licenses/LICENSE-2.0\n> \n> Unless required by applicable law or agreed to in writing, software\n> distributed under the License is distributed on an \"AS IS\" BASIS,\n> WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n> See the License for the specific language governing permissions and\n> limitations under the License.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":33,"value":"---\n## Data\n*Data sources*\n- Data is from local files downloaded from S3, uploaded as a file attachments\n- Data is then wrapped as a duckDB database table (separate tables for each parquet file)\n- We are using some simplified data sources, suffixed with `reduced.parquet` in the S3 bucket","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1282,"value":"### Tabular data\n- **haz_risk_vop_int**: risk data showing effect hazards have on crops. Interactions are independent.\n - `risk_prototype/data/hazard_risk_vop_ac/annual/haz_risk_vop_int_ac_reduced.parquet` \n- **population**: population data by admin levels\n - `population/population_long.parquet`\n- **vop_ha**: Value of Production (VoP) and hectare data (Ha) exposures by admin level. No hazards applied.\n - `risk_prototype/data/exposure/exposure_adm_sum.parquet`\n- **vul_ac**: adaptive capacity data (update)\n - `vulnerability/vulnerability_RawIndex_adminALL.parquet`","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":8,"value":"$75","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":548,"value":"### Geographic data\nGeo files were converted to TopoJSON and reduced in complexity before uploading to the notebook, see [Simplify large spatial files](https://observablehq.com/d/258c68ee969e8ed5?collection=@periscopic/ab-atlas) notebook for method.\n- **admin0**: broadest level, country boundaries\n - `boundaries/atlas-region_admin0_harmonized.geojson`\n- **admin1**: one level down from `admin0`, regions within each `admin0` region\n - `boundaries/atlas-region_admin1_harmonized.geojson`\n- **admin2**: lowest level, subregions of every `admin1` region\n - `boundaries/atlas-region_admin2_harmonized.geojson`","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2719,"value":"boundaries = {\n let admin1Data, admin2Data;\n \n // Only fetch admin1 and admin2 data if a country is selected\n if (adminSelections.selectAdmin0.value) {\n admin1Data = await get_admin1();\n admin2Data = await get_admin2();\n } else {\n admin1Data = { type: \"FeatureCollection\", features: [] };\n admin2Data = { type: \"FeatureCollection\", features: [] };\n }\n \n return {\n admin0: admin0,\n admin1: admin1Data,\n admin2: admin2Data,\n admin3: admin3_with_vop,// Use the enhanced version\n admin32: admin3_cleaned\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3500,"value":"// Refresh boundaries when country changes\nrefreshBoundaries = {\n void adminSelections.selectAdmin0.value;\n return boundaries; // This will trigger boundaries to recalculate\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2718,"value":"geo_db = {\n let db = await DuckDBClient.of({\n // admin0_geom: FileAttachment(\"atlas-region_admin0_simplified.parquet\"),\n admin1_geom: FileAttachment(\"atlas-region_admin1_simplified@1.parquet\")\n });\n await db.query(`\n CREATE VIEW admin2_geom AS\n SELECT *\n FROM read_parquet(\"${resolveWindowsCacheIssue(\n \"https://digital-atlas.s3.amazonaws.com/boundaries/atlas-region_admin2_simplified.parquet\"\n )}\")`);\n return db;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2841,"value":"partitioned_boundries = \"https://digital-atlas.s3.amazonaws.com/boundaries/subnational-boundaries_simplified\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2851,"value":"iso3_list = new Object({\n \"Nigeria\": \"NGA\",\n \"Sudan\": \"SDN\",\n \"Cameroon\": \"CMR\",\n \"Ethiopia\": \"ETH\",\n \"Mauritania\": \"MRT\",\n \"Côte d’Ivoire\": \"CIV\",\n \"Ghana\": \"GHA\",\n \"Madagascar\": \"MDG\",\n \"Djibouti\": \"DJI\",\n \"Benin\": \"BEN\",\n \"Equatorial Guinea\": \"GNQ\",\n \"Eritrea\": \"ERI\",\n \"Tanzania\": \"TZA\",\n \"Somalia\": \"SOM\",\n \"Guinea-Bissau\": \"GNB\",\n \"Mali\": \"MLI\",\n \"Central African Republic\": \"CAF\",\n \"Gambia\": \"GMB\",\n \"Chad\": \"TCD\",\n \"Kenya\": \"KEN\",\n \"Congo - Kinshasa\": \"COD\",\n \"Angola\": \"AGO\",\n \"Lesotho\": \"LSO\",\n \"Guinea\": \"GIN\",\n \"Liberia\": \"LBR\",\n \"Burkina Faso\": \"BFA\",\n \"Congo - Brazzaville\": \"COG\",\n \"Burundi\": \"BDI\",\n \"Zimbabwe\": \"ZWE\",\n \"Mozambique\": \"MOZ\",\n \"Botswana\": \"BWA\",\n \"Malawi\": \"MWI\",\n \"Uganda\": \"UGA\",\n \"Zambia\": \"ZMB\",\n \"South Sudan\": \"SSD\",\n \"Togo\": \"TGO\",\n \"Senegal\": \"SEN\",\n \"Niger\": \"NER\",\n \"Sierra Leone\": \"SLE\",\n \"South Africa\": \"ZAF\",\n \"Rwanda\": \"RWA\",\n \"Namibia\": \"NAM\",\n \"Gabon\": \"GAB\",\n \"Eswatini\": \"SWZ\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2855,"value":"admin_iso = iso3_list[selectAdmin0.value]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2717,"value":"admin0 = {\n let admin0 = await FileAttachment(\"atlas-region_admin0_harmonized@1.json\").json()\n return topojson.feature(admin0, admin0.objects[\"atlas-region_admin0_harmonized\"])\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3067,"value":"admin3 = {\n const admin3 = FileAttachment(\"eth_admbnda_adm3_csa_bofedb_2021_simplified.json\").json();\n return admin3; // already GeoJSON\n}\n\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":3079,"value":"admin3_cleaned = {\n const renamed = admin3.features.map(f => ({\n ...f,\n properties: {\n admin3_name: f.properties.ADM31_EN,\n admin3_pcode: f.properties.ADM3_PCODE,\n admin2_name: f.properties.ADM2_EN,\n admin2_pcode: f.properties.ADM2_PCODE,\n admin1_name: f.properties.ADM1_EN,\n admin1_pcode: f.properties.ADM1_PCODE,\n admin0_name: f.properties.ADM0_EN,\n admin0_pcode: f.properties.ADM0_PCODE,\n ...f.properties // keep everything else\n }\n }));\n\n return { type: \"FeatureCollection\", features: renamed };\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2716,"value":"$76","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2715,"value":"$77","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2109,"value":"### Dynamic summary links\nCSV of links to include for different admin0 selections\n- `Local Drive Google Sheet`","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2108,"value":"// dynamic bulleted list data\ndynamicSummaryData = {\n const raw = await FileAttachment(\"dynamic-summary-links@1.csv\").csv()\n\n return raw.filter((d) => d.admin0_name.length > 0)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2107,"value":"dynamicSummarySelectedLinks = {\n // filter and check link number\n const data = dynamicSummaryData\n const admin0Selection = adminSelections.selectAdmin0.value ?? \"DEFAULT\"\n \n const numLinks = data.filter(d => d.admin0_name == admin0Selection).length\n return numLinks == 0\n ? data.filter(d => d.admin0_name == 'DEFAULT')\n : data.filter(d => d.admin0_name == admin0Selection)\n\n \n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2106,"value":"dynamicSummaryMarkdown = {\n const linkArr = dynamicSummarySelectedLinks.map(d => `- [${d.link_text}](${d.link_url})${d.description.length > 0 ? `: ${d.description}`: \"\"}`)\n return linkArr.join(\"\\n\")\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":448,"value":"***\n## Helpers\n*Functions and other good stuff*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1476,"value":"---\n### Risk data grouping\n*Lookups for risk data binning, such as hazards and crop types*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1475,"value":"$78","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1327,"value":"---\n### Dynamic insights\n*functions for formatting results*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1326,"value":"function filterByAdminNames(data) {\n // filter down data by combined selected admin0/admin1/admin2/admin3 Admin Selections\n // pass data from query, use tidyjs to filter by admin selection\n const result = T.tidy(\n data,\n T.filter((d) => {\n const matchAdmin0 = d.admin0_name == adminSelections.selectAdmin0.value;\n const matchAdmin1 = d.admin1_name == adminSelections.selectAdmin1.value;\n const matchAdmin2 = d.admin2_name == adminSelections.selectAdmin2.value;\n // If admin3 is selected, also filter by admin3 (though most queries don't have admin3_name)\n const matchAdmin3 = adminSelections.selectAdmin3?.value \n ? (d.admin3_name == adminSelections.selectAdmin3.value || !d.hasOwnProperty('admin3_name'))\n : true;\n return matchAdmin0 && matchAdmin1 && matchAdmin2 && matchAdmin3;\n })\n )\n return result\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1325,"value":"function formatWithDefault({\n value=1000, \n format=d=>d, \n defaultValue=\"---\", \n debug=false\n}={}) {\n // apply a formatting function to a value\n // return default value if undefined, null, or NaN\n if (value === null || value === undefined || (typeof value === 'number' && isNaN(value))) {\n return defaultValue\n } else {\n return format(value)\n }\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1324,"value":"---\n### Data functions: format and transform\n*apply formatting to/transform a value*\n\n- Reference: [Intl.NumberFormat()](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Intl/NumberFormat/NumberFormat)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1799,"value":"**Transforms**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1798,"value":"// transform non-number to percent value\ntransformPercent = (d) => {\n if (d === undefined || d === null) return d\n else return d * 100\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1797,"value":"**Formatting**","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":1796,"value":"// format non-number as percent\nformatPercentTenth = (d) => {\n if (d === undefined || d === null) return d\n else return d3.format('.1%')(d)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2167,"value":"// format non-number as percent\nformatPercentWhole = (d) => {\n if (d === undefined || d === null) return d\n else return d3.format('.0%')(d)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2543,"value":"// format non-number with no floating point \n// for index values\nformatPercentNoSymbol = (d) => {\n if (d === undefined || d === null) return d\n else return d3.format('.0f')(d)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2562,"value":"function formatUSD({ locale = \"en-US\" } = {}) {\n const formatter = formatNumCompactShort({ locale });\n\n return (number) => {\n const formattedNum = formatter(number)\n return \"$\" + formattedNum;\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2561,"value":"intDollarYear = 2005 // year of international year data","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2560,"value":"intDollarUnit = `${intDollarYear} Int$` // full unit for international dollars","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":449,"value":"// format US currency\nfunction formatIntDollar({ locale = \"en-US\" } = {}) {\n return (number, unit = intDollarUnit.replace(\"$\", \"\")) => {\n let formattedNumber = formatUSD({ locale })(number);\n let intDollar = unit + formattedNumber;\n return intDollar;\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1322,"value":"// format number, long notation\nformatNumCompactLong = function ({ locale = \"en-US\" } = {}) {\n return function (number) {\n return new Intl.NumberFormat(locale, {\n notation: \"compact\",\n compactDisplay: \"long\",\n unitDisplay: \"long\"\n }).format(number);\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1794,"value":"// format number, short notation\nformatNumCompactShort = ({ locale = \"en-US\" } = {}) =>\n new Intl.NumberFormat(locale, {\n notation: \"compact\",\n compactDisplay: \"short\"\n }).format","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1321,"value":"---\n### Querying data\n*functions for querying data*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":693,"value":"function getUniqueValues(col, tbl, db) {\n // return unique values of from db tbl as a list\n return db.query(`select distinct ${col} from ${tbl}`).then(x => x.map(d => d[col]))\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1242,"value":"function bindTabularToGeo({\n data = [],\n dataBindColumn = 'dataBindColumn',\n geoData = [],\n geoDataBindColumn = 'geoDataBindColumn'\n}) {\n if (!data.length || !geoData.features || !geoData.features.length) {\n return {\n type: \"FeatureCollection\",\n features: []\n };\n }\n // bind data to geojson\n const index = new Map(data.map(d => [d[dataBindColumn], d])) // map data by dataBindColumn\n const geojson = JSON.parse(JSON.stringify(geoData)); // do a copy, rather than mutate\n // join up data to geojson\n for (const f of geojson.features) {\n f.properties.data = index.get(f.properties[geoDataBindColumn]);\n }\n return geojson;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":98,"value":"***\n## Testing Queries\n*Test queries of the tabular data*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2371,"value":"{\n const debugString = md`**Query hidden: Debug: non-zero hazard data counts**\n\n_(update boolean within this cell to run)_ \n - this checks the number of results for every combination of hazard data \n - ~3% of choices have no data across all crops`\n \n const hideQuery = true;\n\n return hideQuery\n ? debugString\n : db.query(`\nwith tbl as (\n select admin0_name\n , admin1_name\n , admin2_name\n , scenario\n , timeframe\n , count(*) as total_count\n , count(case when value <> 0 then 1 end) as non_zero_count\n from haz_risk_vop_int_combined\n -- where admin0_name = 'Angola'\n where severity = 'moderate' -- hard-coded\n and hazard != 'any'\n group by admin0_name\n , admin1_name\n , admin2_name\n , scenario\n , timeframe\n order by non_zero_count\n)\n\nselect * \n from tbl\n -- where non_zero_count = 0\n`);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":264,"value":"***\n## Imports\n*External imports*","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":265,"value":"import {toc} from \"@nebrius/indented-toc\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1240,"value":"import {T} from \"@pbeshai/tidyjs\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2713,"value":"import {cleanAdminInput_SQL, resolveWindowsCacheIssue} from \"cbd32f92c155bf5b\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2711,"value":"GEOS = {\n const initgeosJs = (await import(\"https://cdn.skypack.dev/geos-wasm@2.0.0\"))\n .default;\n const geos = await initgeosJs();\n\n function geosGeomFromWKB(wkb) {\n const wkbPtr = geos.Module._malloc(wkb.length); //Allocate memory for the geom\n geos.Module.HEAPU8.set(wkb, wkbPtr);\n const geomPtr = geos.GEOSGeomFromWKB_buf(wkbPtr, wkb.length);\n geos.Module._free(wkbPtr);\n return geomPtr;\n }\n \n const geosGeomToGeojson = (\n await import(\"https://cdn.skypack.dev/geos-wasm/helpers\")\n ).geosGeomToGeojson;\n\n return { geosGeomToGeojson, geosGeomFromWKB, geos };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2710,"value":"turfRewind = require(\"@turf/turf\").then((t) => t.rewind)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2772,"value":"import {buildInlineDownloadButton} from \"1bda5f9b60c64223\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2783,"value":"download_translation = new Object({en: \"Download Data\", fr: \"Télécharger les Données\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":2370,"value":"---\n\n## Other","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":2369,"value":"function makeDevNotes({\n // adding dev notes as a html summary (collapsible)\n title = \"Plot dev notes\",\n emojis = \"👆🛠\",\n text = md`Update this text using the \\`text\\` field.`\n} = {}) {\n return htl.html`

${title} ${emojis}

${text}