Document dashboard handoff and dynamic band scoring
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@@ -515,7 +515,7 @@ svg {{ width:100%; height:230px; display:block; }}
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<div class="chips" id="weak"></div>
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</div>
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</section>
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<div class="note">维度得分按同期正常波动区间计算：正向指标高于上沿为 100，低于下沿为 0，区间内线性映射；库存反向。阴影带参数只影响图表展示，总分使用默认 ±15 天、3 倍标准差、去尾 10%。</div>
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<div class="note">维度得分按当前阴影带范围计算：正向指标高于上沿为 100，低于下沿为 0，区间内线性映射；库存反向。顶部阴影带参数同步影响维度分数和总分。</div>
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<main class="rows" id="rows"></main>
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<section class="history-view" id="historyView">
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<div class="history-tools">
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@@ -541,6 +541,7 @@ function yearColor(year, years) {{
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}}
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const dimColors = {json.dumps(DIM_COLORS, ensure_ascii=False)};
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const dims = DATA.dimensions;
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const inverseDims = new Set({json.dumps(list(INVERSE_DIMS), ensure_ascii=False)});
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const search = document.getElementById("search");
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const dimSel = document.getElementById("dim");
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const boardSel = document.getElementById("board");
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@@ -613,13 +614,26 @@ function matches(c) {{
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return hay.includes(q);
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}}
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function activeDims() {{ return includeDemand.checked ? ["利润","产量","库存","需求"] : ["利润","产量","库存"]; }}
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function currentDimScore(dim, v) {{
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const dynamic = scoreFromCurrentBand(v, inverseDims.has(dim));
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if (dynamic != null && Number.isFinite(dynamic)) return dynamic;
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return v?.score;
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}}
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function scoreCommodity(c) {{
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const next = Object.assign({{}}, c);
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next.dims = Object.fromEntries(Object.entries(c.dims).map(([d, v]) => {{
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const score = currentDimScore(d, v);
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return [d, Object.assign({{}}, v, {{score: score == null ? null : score}})];
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}}));
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return Object.assign(next, computeTotal(next));
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}}
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function computeTotal(c) {{
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const keys = activeDims();
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const values = keys.map(d => c.dims[d]?.score).filter(v => v != null && Number.isFinite(Number(v))).map(Number);
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return {{total: values.length ? values.reduce((s,v)=>s+v,0)/values.length : null, valid: values.length, denom: keys.length}};
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}}
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function rankedList(list) {{
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const mapped = list.map(c => Object.assign({{}}, c, computeTotal(c)));
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const mapped = list.map(scoreCommodity);
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const scored = mapped.filter(c => c.total != null).sort((a,b)=>b.total-a.total);
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scored.forEach((c,i)=>c.displayRank=i+1);
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return scored.concat(mapped.filter(c => c.total == null));
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@@ -757,6 +771,64 @@ function robustAnnualSeasonValues(points, useRobust=true) {{
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.map(x=>x.value)
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.sort((a,b)=>a-b);
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}}
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function rawPointsFromYears(years) {{
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const params = chartParams();
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const rawPoints = [];
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Object.entries(years || {{}}).forEach(([year, pts]) => {{
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if (Number(year) < params.startYear) return;
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(pts || []).forEach(p => {{
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const value = Number(p[1]);
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if (Number.isFinite(value)) rawPoints.push({{year:Number(year), md:p[0], day:parseDay(p[0]), value}});
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}});
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}});
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return rawPoints;
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}}
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function buildRawBand(years, rawPoints=null) {{
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const params = chartParams();
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const points = rawPoints || rawPointsFromYears(years);
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const bandUniverse = points.filter(p => Number(p.year) >= params.startYear && Number(p.year) < params.excludeYear);
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const trendLike = trendLikeAnnualLevel(bandUniverse);
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const band = [];
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for (let day=1; day<=366; day++) {{
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const samples = robustAnnualSeasonValues(bandUniverse.filter(p => circularDiff(p.day, day) <= params.window), !trendLike);
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if (samples.length < 3) continue;
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const tail = Math.max(0.02, Math.min(0.45, params.trim || 0.10));
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const mid = quantile(samples, 0.50);
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let low = quantile(samples, tail);
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let high = quantile(samples, 1 - tail);
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const widthScale = Math.max(0.25, Math.min(2.5, params.k / 3));
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low = mid - (mid - low) * widthScale;
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high = mid + (high - mid) * widthScale;
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const date = new Date(2024, 0, day);
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const md = `${{String(date.getMonth()+1).padStart(2,"0")}}-${{String(date.getDate()).padStart(2,"0")}}`;
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band.push([md, low, high, mid]);
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}}
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const smoothRadius = Math.max(3, Math.min(18, Math.round(params.window * 0.75)));
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return smoothBand(band, smoothRadius);
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}}
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function latestRawPoint(years) {{
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const points = rawPointsFromYears(years);
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if (!points.length) return null;
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return points.sort((a,b) => a.year-b.year || a.day-b.day).at(-1);
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}}
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function scoreFromCurrentBand(v, inverse=false) {{
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if (!v || !v.years) return null;
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const latest = latestRawPoint(v.years);
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if (!latest) return null;
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const rawBand = buildRawBand(v.years);
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const row = rawBand.find(p => p[0] === latest.md);
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if (!row) return null;
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let low = Number(row[1]), high = Number(row[2]);
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if (!Number.isFinite(low) || !Number.isFinite(high)) return null;
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if (low > high) {{ const tmp = low; low = high; high = tmp; }}
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let rawScore;
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if (high === low) rawScore = latest.value >= high ? 100 : 0;
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else if (latest.value >= high) rawScore = 100;
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else if (latest.value <= low) rawScore = 0;
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else rawScore = 100 * (latest.value - low) / (high - low);
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const score = inverse ? 100 - rawScore : rawScore;
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return Math.max(0, Math.min(100, score));
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}}
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function smoothBand(band, radius) {{
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if (!band.length || radius <= 0) return band;
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const n = band.length;
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@@ -783,18 +855,9 @@ function smoothBand(band, radius) {{
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}}
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function buildNormalizedChart(years) {{
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const params = chartParams();
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const rawPoints = [];
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Object.entries(years).forEach(([year, pts]) => {{
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if (Number(year) < params.startYear) return;
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pts.forEach(p => {{
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const value = Number(p[1]);
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if (Number.isFinite(value)) rawPoints.push({{year, md:p[0], day:parseDay(p[0]), value}});
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}});
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}});
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const rawPoints = rawPointsFromYears(years);
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const rawValues = rawPoints.map(p=>p.value);
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if (!rawValues.length) return {{years:{{}}, band:[]}};
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const bandUniverse = rawPoints.filter(p => Number(p.year) >= params.startYear && Number(p.year) < params.excludeYear);
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const trendLike = trendLikeAnnualLevel(bandUniverse);
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const m = mean(rawValues);
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let s = std(rawValues);
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if (!Number.isFinite(s) || s === 0) s = 1;
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@@ -804,23 +867,8 @@ function buildNormalizedChart(years) {{
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if (Number(year) < params.startYear) return;
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normYears[year] = pts.map(p => [p[0], z(Number(p[1]))]).filter(p => Number.isFinite(p[1]));
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}});
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const band = [];
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for (let day=1; day<=366; day++) {{
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const samples = robustAnnualSeasonValues(bandUniverse.filter(p => circularDiff(p.day, day) <= params.window), !trendLike);
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if (samples.length < 3) continue;
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const tail = Math.max(0.02, Math.min(0.45, params.trim || 0.10));
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const mid = quantile(samples, 0.50);
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let low = quantile(samples, tail);
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let high = quantile(samples, 1 - tail);
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const widthScale = Math.max(0.25, Math.min(2.5, params.k / 3));
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low = mid - (mid - low) * widthScale;
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high = mid + (high - mid) * widthScale;
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const date = new Date(2024, 0, day);
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const md = `${{String(date.getMonth()+1).padStart(2,"0")}}-${{String(date.getDate()).padStart(2,"0")}}`;
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band.push([md, z(low), z(high), z(mid)]);
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}}
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const smoothRadius = Math.max(3, Math.min(18, Math.round(params.window * 0.75)));
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return {{years:normYears, band:smoothBand(band, smoothRadius)}};
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const band = buildRawBand(years, rawPoints).map(p => [p[0], z(p[1]), z(p[2]), z(p[3])]);
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return {{years:normYears, band}};
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}}
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function drawChart(svg, years) {{
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const normalized = buildNormalizedChart(years);
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