29:null 2a:["$","title",null,{"children":"Joint Progression Modeling (JPM): A Probabilistic Framework for Mixed-Pathology Progression | Hongtao Hao | Observable"}] 30:T1e42,viewof chart_simplified = { const metricName = selectedMetric; const width = 280, height = 180, margin = { top: 30, right: 10, bottom: 40, left: 50 }; // ======= Extract data ======= const experiments = [...grouped.keys()].sort((a, b) => a.localeCompare(b, undefined, { numeric: true, sensitivity: "base" }) ); const firstExp = grouped.get(experiments[0]); const Js = [...firstExp.keys()].map(Number).sort((a, b) => a - b); const Rs = [...Js.flatMap(j => [...firstExp.get(j).keys()].map(Number))] .filter((v, i, self) => self.indexOf(v) === i) .sort((a, b) => a - b); const algos = new Set(); for (const [E, jMap] of grouped) { for (const [J, rMap] of jMap) { for (const [R, algoMap] of rMap) { for (const [algo] of algoMap) algos.add(algo); } } } const uniqueAlgos = [...algos]; // ======= Shapes ======= const shapeGenerators = { circle: (g, cx, cy, size, fill, stroke) => g.append("circle").attr("cx", cx).attr("cy", cy).attr("r", size) .attr("fill", fill).attr("stroke", stroke).attr("stroke-width", 0.6), triangle: (g, cx, cy, size, fill, stroke) => g.append("polygon").attr("points", `${cx},${cy - size} ${cx + size},${cy + size} ${cx - size},${cy + size}`) .attr("fill", fill).attr("stroke", stroke).attr("stroke-width", 0.6), star: (g, cx, cy, size, fill, stroke) => { const R = size * 1.2, r = size * 0.6; let path = ""; for (let i = 0; i < 10; i++) { const angle = Math.PI / 5 * i; const radius = i % 2 === 0 ? R : r; const x = cx + radius * Math.sin(angle); const y = cy - radius * Math.cos(angle); path += i === 0 ? `M${x},${y}` : `L${x},${y}`; } return g.append("path").attr("d", path + "Z") .attr("fill", fill).attr("stroke", stroke).attr("stroke-width", 0.6); } }; const algoToShape = { "Mallows_Tau": "triangle", "Mallows_RMJ": "star", "EBM": "circle", "BT": "triangle", "Pairwise": "circle", "PL": "star", }; // ======= Aggregate data ======= const aggregatedData = []; for (const [E, jMap] of grouped) { for (const [J, rMap] of jMap) { for (const [R, algoMap] of rMap) { for (const [algo, stats] of algoMap) { aggregatedData.push({ E, J: +J, R: +R, algo, ...stats }); } } } } // ======= Algo stats ======= const algoStats = {}; uniqueAlgos.forEach(algo => { const vals = aggregatedData.filter(d => d.algo === algo).map(d => d[metricName]); const mean = d3.mean(vals); let ciLow = null, ciHigh = null; if (vals.length > 1) { const n = vals.length; const sd = Math.sqrt(d3.sum(vals.map(x => Math.pow(x - mean, 2))) / (n - 1)); const se = sd / Math.sqrt(n); const t = 1.96; ciLow = mean - t * se; ciHigh = mean + t * se; } algoStats[algo] = { mean, ciLow, ciHigh }; }); const sortedAlgos = [...uniqueAlgos].sort((a, b) => algoStats[a].mean - algoStats[b].mean); const color = d3.scaleOrdinal(d3.schemeTableau10).domain(sortedAlgos); const xGroup = d3.scaleBand().domain(Js).range([margin.left, width - margin.right]).padding(0.1); const xInner = d3.scalePoint().domain(Rs).range([0, xGroup.bandwidth()]).padding(0.5); // ======= Layout: 2 columns ======= const cols = 3; const outerContainer = d3.create("div").style("width", "100%"); const svgWidth = width * cols; const svgHeight = height * Math.ceil(experiments.length / cols) + 120; const masterSVG = outerContainer.append("svg") .attr("width", svgWidth) .attr("height", svgHeight) // .style("background", "#fafafa") .style("font-family", "sans-serif"); // ======= Draw charts ======= experiments.forEach((E, index) => { const row = Math.floor(index / cols); const col = index % cols; const chartG = masterSVG.append("g") .attr("transform", `translate(${col * width}, ${row * height})`); const expData = aggregatedData.filter(d => d.E === E); const yDomain = metricName === "kendalls_tau" ? [0.3, 0] : metricName === "energy" ? [500, 0] : [1.5, 0]; const y = d3.scaleLinear().domain(yDomain).nice() .range([height - margin.bottom, margin.top]); // Y-axis with gridlines chartG.append("g") .attr("transform", `translate(${margin.left},0)`) .call(d3.axisLeft(y).ticks(5)) .style("font-size", "11px"); // chartG.append("g") // .attr("transform", `translate(${margin.left},0)`) // .call(d3.axisLeft(y).ticks(5).tickSize(-width + margin.left + margin.right)) // .call(g => g.selectAll(".tick line").attr("stroke", "#ddd")) // .call(g => g.select(".domain").remove()) // .style("font-size", "11px"); // X-axis chartG.append("g") .attr("transform", `translate(0,${height - margin.bottom})`) .call(d3.axisBottom(xGroup)) .selectAll("text").text(d => `J=${d}`) .style("font-size", "11px") // Title chartG.append("text") .attr("x", width / 2).attr("y", margin.top - 10) .attr("text-anchor", "middle") .style("font-size", "11px").style("font-weight", "bold") .text(E); // Y-axis label on first chart only if (index === 0) { chartG.append("text") .attr("transform", "rotate(-90)") .attr("x", -(height / 2)) .attr("y", 15) .attr("text-anchor", "middle") .style("font-size", "12px") .text(metricName === "kendalls_tau" ? "Kendall's Tau" : metricName === "mae" ? "MAE" : "Energy"); } // Lines + markers sortedAlgos.forEach(algo => { Js.forEach(J => { const pts = expData.filter(d => d.algo === algo && d.J === J).sort((a, b) => a.R - b.R); if (pts.length < 2) return; const line = d3.line() .x(d => xGroup(d.J) + xInner(d.R)) .y(d => y(d[metricName])) .curve(d3.curveMonotoneX); chartG.append("path").datum(pts) .attr("fill", "none").attr("stroke", color(algo)) .attr("stroke-width", 2.5).attr("opacity", 0.9) .attr("d", line); pts.forEach(d => { const shapeFn = shapeGenerators[algoToShape[algo]]; if (shapeFn) shapeFn(chartG, xGroup(d.J) + xInner(d.R), y(d[metricName]), 3.5, color(algo), "white"); }); }); }); }); // ======= Legend (2 columns) ======= const legendG = masterSVG.append("g") .attr("transform", `translate(0, ${height * Math.ceil(experiments.length / cols)})`); const itemsPerRow = 3; const itemWidth = (svgWidth / itemsPerRow) * 0.8; const itemHeight = 22; legendG.append("text") .attr("x", svgWidth / 2) .attr("y", 15) .attr("text-anchor", "middle") .style("font-size", "11px").style("font-weight", "bold") .text(`Algorithms (Avg. ${ metricName === "kendalls_tau" ? "Kendall's Tau" : metricName === "mae" ? "MAE" : "Energy" } ± 95% CI)`); sortedAlgos.forEach((algo, i) => { const row = Math.floor(i / itemsPerRow); const col = i % itemsPerRow; const g = legendG.append("g") .attr("transform", `translate(${col * itemWidth + 40}, ${row * itemHeight + 40})`); const shapeFn = shapeGenerators[algoToShape[algo]]; if (shapeFn) shapeFn(g, 0, 0, 5, color(algo), "black"); const { mean, ciLow, ciHigh } = algoStats[algo]; const statText = (ciLow != null && ciHigh != null) ? `${algo} (${mean.toFixed(2)} ± ${((ciHigh - ciLow) / 2).toFixed(2)})` : `${algo} (${mean.toFixed(2)})`; g.append("text").attr("x", 12).attr("y", 0).attr("dy", "0.32em") .style("font-size", "11px").style("fill", "#333").text(statText); }); return outerContainer.node(); } 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Progression","pinned":false,"hidden":false,"mode":"md"},{"id":80,"value":"compare_mpebm_saebm = await FileAttachment(\"all_results@110.csv\").csv({typed: \"auto\"})","pinned":true,"hidden":false,"mode":"ojs"},{"id":6,"value":"processed = compare_mpebm_saebm\n .filter(d => d.data_framework === Data_Framework)\n .map(d => ({\n E: d.E,\n J: +d.J,\n R: +d.R,\n algo: d.algo,\n kendalls_tau: +d.kendalls_tau,\n mae: +d.mae,\n energy: +d.energy,\n }))","pinned":false,"hidden":false,"mode":"ojs"},{"id":8,"value":"grouped = d3.rollup(\n processed,\n values => ({\n kendalls_tau: d3.mean(values, d => d.kendalls_tau),\n mae: d3.mean(values, d => d.mae),\n energy: d3.mean(values, d => d.energy),\n mae_diseased: d3.mean(values, d => d.mae_diseased),\n count: values.length\n }),\n d => d.E,\n d => d.J,\n d => d.R,\n d => d.algo\n);\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":193,"value":"viewof Data_Framework = Inputs.select(['Pairwise', 'Random', 'BT', 'PL', 'Mallows_Tau_T1.0', 'Mallows_Tau_T10.0'], {value: 'Pairwise', label: \"Select Data Framework\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":14,"value":"viewof selectedMetric = {\n const form = html``;\n \n form.value = form.querySelector(\"select\").value;\n form.querySelector(\"select\").addEventListener(\"input\", () => {\n form.value = form.querySelector(\"select\").value;\n form.dispatchEvent(new Event(\"input\"));\n });\n \n return form;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":199,"value":"Data_Framework","pinned":false,"hidden":false,"mode":"ojs"},{"id":12,"value":"$30","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W31","stdlib":"1","titling":"auto"}} 2e:"$2d:body"