Clarify calibrated probability read with LGBM context

2026-04-17 20:53:37 +08:00
parent bc09a3753c
commit f5e61e96ff
6 changed files with 154 additions and 71 deletions
@@ -923,6 +923,49 @@
  gap: 8px;
 }

+.root :global(.prob-calibration-head) {
+  display: grid;
+  gap: 6px;
+  margin-bottom: 4px;
+  padding: 10px;
+  border: 1px solid rgba(34, 211, 238, 0.16);
+  border-radius: 8px;
+  background: rgba(15, 23, 42, 0.26);
+}
+
+.root :global(.prob-calibration-head > div) {
+  display: flex;
+  align-items: center;
+  flex-wrap: wrap;
+  gap: 8px;
+}
+
+.root :global(.prob-calibration-head strong) {
+  color: var(--text-primary);
+  font-size: 13px;
+  font-weight: 800;
+}
+
+.root :global(.prob-calibration-head p) {
+  margin: 0;
+  color: var(--text-muted);
+  font-size: 11px;
+  line-height: 1.45;
+}
+
+.root :global(.prob-source-chip) {
+  display: inline-flex;
+  align-items: center;
+  min-height: 22px;
+  padding: 3px 8px;
+  border: 1px solid rgba(34, 211, 238, 0.28);
+  border-radius: 8px;
+  color: #67e8f9;
+  background: rgba(34, 211, 238, 0.08);
+  font-size: 11px;
+  font-weight: 900;
+}
+
 .root :global(.prob-row) {
  display: flex;
  align-items: center;
@@ -742,6 +742,13 @@ export function FutureForecastModal() {
    [dateStr, detail],
  );
  const modelView = useMemo(() => getModelView(detail, dateStr), [dateStr, detail]);
+  const hasLgbmProbability = useMemo(
+    () =>
+      Object.keys(modelView?.models || {}).some((name) =>
+        String(name || "").toLowerCase().replace(/[\s_/-]/g, "").includes("lgbm"),
+      ),
+    [modelView],
+  );
  const topProbabilityBucket = useMemo(() => {
    const buckets = Array.isArray(probabilityView?.probabilities)
      ? probabilityView.probabilities
@@ -914,9 +921,14 @@ export function FutureForecastModal() {
    }
    const bucketLabel = formatBucketLabel(topProbabilityBucket);
    const bucketProb = formatMarketPercent(topProbabilityBucket.probability);
+    if (hasLgbmProbability) {
+      return locale === "en-US"
+        ? `LGBM-calibrated read puts the leading bucket at ${bucketLabel} (${bucketProb}). Treat this as the base case, not the final settlement.`
+        : `LGBM 校准后领先温度桶为 ${bucketLabel}（${bucketProb}）。可作为基准情形，但不要直接等同于最终结算。`;
+    }
    return locale === "en-US"
-      ? `Highest current hit probability is ${bucketLabel} at ${bucketProb}. Treat this as the base case, not the final settlement.`
-      : `当前命中概率最高的是 ${bucketLabel}（${bucketProb}），可把它当作基准情形，但不要直接等同于最终结算。`;
+      ? `Calibrated model probability puts the leading bucket at ${bucketLabel} (${bucketProb}). Treat this as the base case, not the final settlement.`
+      : `校准模型概率显示领先温度桶为 ${bucketLabel}（${bucketProb}）。可作为基准情形，但不要直接等同于最终结算。`;
  })();
  const modelSummary = (() => {
    if (!modelSpreadView) {
@@ -1823,10 +1835,16 @@ export function FutureForecastModal() {
                    <section className="future-modal-section">
                      <div className="modal-section-heading">
                        <div className="modal-section-kicker">
-                          {locale === "en-US" ? "Auxiliary probability" : "辅助概率"}
+                          {locale === "en-US" ? "Probability read" : "概率判断"}
                        </div>
                        <h3>
-                          {locale === "en-US" ? "Model & Market Reference" : "模型与市场参考"}
+                          {hasLgbmProbability
+                            ? locale === "en-US"
+                              ? "LGBM-Calibrated Probability"
+                              : "LGBM 校准概率"
+                            : locale === "en-US"
+                              ? "Calibrated Model Probability"
+                              : "校准模型概率"}
                        </h3>
                      </div>
                      <div className="future-text-block" style={{ marginBottom: "12px" }}>
@@ -310,6 +310,31 @@ function getMarketTopBucketKey(bucket: MarketTopBucket) {
  return `s:${String(bucket?.slug || bucket?.question || bucket?.label || "")}`;
 }

+function hasLgbmModel(detail: CityDetail, targetDate?: string | null) {
+  const view = getModelView(detail, targetDate);
+  return Object.keys(view.models || {}).some((name) =>
+    normalizeModelNameForVote(name).includes("lgbm"),
+  );
+}
+
+function formatProbabilityEngineLabel(
+  detail: CityDetail,
+  targetDate: string | null | undefined,
+  locale: string,
+) {
+  const view = getProbabilityView(detail, targetDate);
+  if (hasLgbmModel(detail, targetDate)) {
+    return locale === "en-US"
+      ? "LGBM-calibrated probability"
+      : "LGBM 校准概率";
+  }
+  const engine = String(view.engine || "").trim().toLowerCase();
+  if (engine === "emos") {
+    return locale === "en-US" ? "EMOS-calibrated probability" : "EMOS 校准概率";
+  }
+  return locale === "en-US" ? "Model probability" : "模型概率";
+}
+
 export function HeroSummary() {
  const { data } = useCityData();
  const { locale } = useI18n();
@@ -580,6 +605,12 @@ export function ProbabilityDistribution({
  const marketYesText = toPercent(marketYesPrice);
  const marketNoText = toPercent(marketNoPrice);
  const isToday = !targetDate || targetDate === detail.local_date;
+  const probabilityEngineLabel = formatProbabilityEngineLabel(
+    detail,
+    targetDate,
+    locale,
+  );
+  const hasLgbmProbability = hasLgbmModel(detail, targetDate);
  const modelVoteView = useMemo(
    () => getRoundedModelVoteDistribution(detail, targetDate),
    [detail, targetDate],
@@ -610,11 +641,41 @@ export function ProbabilityDistribution({
  const useMarketTopBuckets =
    marketScan?.available && sortedMarketTopBuckets.length >= 2;
  const topMarketBucketText = toPercent(sortedMarketTopBuckets[0]?.probability);
+  const topProbability = [...(view.probabilities || [])].sort(
+    (a, b) => Number(b.probability || 0) - Number(a.probability || 0),
+  )[0];
+  const topProbabilityText = toPercent(topProbability?.probability);
+  const topProbabilityLabel = topProbability
+    ? topProbability.label || `${topProbability.value}${detail.temp_symbol}`
+    : null;

  return (
    <section className="prob-section">
      {!hideTitle && <h3>{t("section.probability")}</h3>}
      <div className="prob-bars">
+        <div className="prob-calibration-head">
+          <div>
+            <span className="prob-source-chip">{probabilityEngineLabel}</span>
+            <strong>
+              {topProbability && topProbabilityText
+                ? locale === "en-US"
+                  ? `${topProbabilityLabel} leads at ${topProbabilityText}`
+                  : `${topProbabilityLabel} 当前最高，${topProbabilityText}`
+                : locale === "en-US"
+                  ? "Awaiting calibrated buckets"
+                  : "等待校准概率桶"}
+            </strong>
+          </div>
+          <p>
+            {hasLgbmProbability
+              ? locale === "en-US"
+                ? "LGBM is the learned intraday adjustment; model consensus below remains an explanation layer."
+                : "LGBM 作为日内学习校准项；下方模型共识只保留为解释层。"
+              : locale === "en-US"
+                ? "Using the calibrated model distribution; model consensus below is for explanation only."
+                : "使用校准后的模型分布；下方模型共识仅用于解释。"}
+          </p>
+        </div>
        {view.mu != null && (
          <div
            style={{
@@ -639,82 +700,27 @@ export function ProbabilityDistribution({
          >
            {useMarketTopBuckets
              ? locale === "en-US"
-                ? `Market top-4 buckets (top): ${topMarketBucketText}`
-                : `市场概率（前4温度桶）：最高 ${topMarketBucketText}`
+                ? `Market reference only: top traded bucket ${topMarketBucketText}`
+                : `市场仅作参考：最高交易温度桶 ${topMarketBucketText}`
              : locale === "en-US"
-                ? `Market probability (this bucket): ${marketYesText}`
-                : `市场概率（该温度桶）: ${marketYesText}`}
+                ? `Market reference only: this bucket ${marketYesText}`
+                : `市场仅作参考：该温度桶 ${marketYesText}`}
          </div>
        )}
        {modelVoteHint && (
          <div className="prob-model-hint">
            <span>
-              {locale === "en-US" ? "Model vote reference" : "模型投票参考"}
+              {locale === "en-US" ? "Model consensus" : "模型共识参考"}
            </span>
            <strong>{modelVoteHint}</strong>
            <em>
              {locale === "en-US"
-                ? "shown for explanation only"
-                : "仅用于解释，不作为结算概率"}
+                ? "explains clustering, not calibrated probability"
+                : "解释模型聚集，不等同于校准概率"}
            </em>
          </div>
        )}
-        {useMarketTopBuckets ? (
-          sortedMarketTopBuckets.map((bucket, index) => {
-            const probability = Math.round(
-              Number(bucket.probability || 0) * 100,
-            );
-            let bucketLabel =
-              bucket.label ||
-              (bucket.value != null
-                ? `${bucket.value}${detail.temp_symbol}`
-                : `${bucket.temp ?? "--"}${detail.temp_symbol}`);
-
-            if (bucketLabel) {
-              let str = String(bucketLabel).toUpperCase().replace(/\s+/g, "");
-              str = str.replace(/°?C($|\+|-)/g, "℃$1");
-              if (!str.includes("℃") && /[0-9]/.test(str)) {
-                str += "℃";
-              }
-              bucketLabel = str;
-            }
-            const buyYesText = toPriceCents(
-              bucket.yes_buy ?? bucket.market_price ?? bucket.probability,
-            );
-            const buyNoText = toPriceCents(bucket.no_buy);
-            const marketTag = buyYesText
-              ? locale === "en-US"
-                ? `Market ref: ${buyYesText}`
-                : `市场参考: ${buyYesText}`
-              : buyNoText
-                ? locale === "en-US"
-                  ? `Market hedge: ${buyNoText}`
-                  : `市场反向: ${buyNoText}`
-                : null;
-
-            return (
-              <div
-                key={`${bucket.slug || bucket.label || index}`}
-                className="prob-row"
-              >
-                <div className="prob-label">{bucketLabel}</div>
-                <div className="prob-bar-track">
-                  <div
-                    className={clsx("prob-bar-fill", `rank-${index}`)}
-                    style={{ width: `${Math.max(probability, 8)}%` }}
-                  >
-                    {probability}%
-                  </div>
-                </div>
-                {marketTag && (
-                  <div className={clsx("prob-market-inline", "yes")}>
-                    {marketTag}
-                  </div>
-                )}
-              </div>
-            );
-          })
-        ) : view.probabilities.length === 0 ? (
+        {view.probabilities.length === 0 ? (
          <EmptyState text={t("section.noProb")} />
        ) : (
          view.probabilities.slice(0, 6).map((bucket, index) => {
@@ -429,6 +429,14 @@ export interface CityDetail {
  probabilities?: {
    mu?: number | null;
    distribution?: ProbabilityBucket[];
+    engine?: string | null;
+    calibration_mode?: string | null;
+    calibration_version?: string | null;
+    raw_mu?: number | null;
+    raw_sigma?: number | null;
+    calibrated_mu?: number | null;
+    calibrated_sigma?: number | null;
+    shadow_distribution?: ProbabilityBucket[];
  };
  hourly?: {
    times?: string[];
@@ -1195,15 +1195,23 @@ export function getProbabilityView(detail: CityDetail, targetDate?: string | nul
  const date = targetDate || detail.local_date;
  if (date === detail.local_date) {
    return {
+      calibrationMode: detail.probabilities?.calibration_mode ?? null,
+      calibrationVersion: detail.probabilities?.calibration_version ?? null,
+      engine: detail.probabilities?.engine ?? null,
      mu: detail.probabilities?.mu ?? null,
      probabilities: detail.probabilities?.distribution || [],
+      shadowProbabilities: detail.probabilities?.shadow_distribution || [],
    };
  }

  const daily = detail.multi_model_daily?.[date];
  return {
+    calibrationMode: null,
+    calibrationVersion: null,
+    engine: null,
    mu: daily?.deb?.prediction ?? null,
    probabilities: daily?.probabilities || [],
+    shadowProbabilities: [],
  };
 }

@@ -88,7 +88,7 @@ const MESSAGES: Record<Locale, Record<string, string>> = {
    "future.score": "趋势评分",
    "future.todayTempTrend": "今日温度走势",
    "future.targetTempTrend": "目标日小时走势",
-    "future.probability": "模型结算概率分布",
+    "future.probability": "校准模型概率",
    "future.models": "多模型预报",
    "future.structureToday": "今日日内结构信号",
    "future.structureDate": "未来 6-48 小时趋势",
@@ -108,7 +108,7 @@ const MESSAGES: Record<Locale, Record<string, string>> = {

    "section.todayTempTrend": "今日温度走势",
    "section.chartEmpty": "暂无小时级数据",
-    "section.probability": "模型结算概率分布",
+    "section.probability": "校准模型概率",
    "section.mu": "动态分布中心 μ = {value}{unit}",
    "section.noProb": "暂无概率数据",
    "section.models": "多模型预报",
@@ -253,7 +253,7 @@ const MESSAGES: Record<Locale, Record<string, string>> = {
    "future.score": "Trend Score",
    "future.todayTempTrend": "Today's Temperature Trend",
    "future.targetTempTrend": "Target-day Hourly Trend",
-    "future.probability": "Model Settlement Probabilities",
+    "future.probability": "Calibrated Model Probability",
    "future.models": "Multi-model Forecast",
    "future.structureToday": "Intraday Structural Signal",
    "future.structureDate": "6-48h Structural Trend",
@@ -275,7 +275,7 @@ const MESSAGES: Record<Locale, Record<string, string>> = {

    "section.todayTempTrend": "Today's Temperature Trend",
    "section.chartEmpty": "No hourly data available",
-    "section.probability": "Model Settlement Probabilities",
+    "section.probability": "Calibrated Model Probability",
    "section.mu": "Dynamic center μ = {value}{unit}",
    "section.noProb": "No probability data available",
    "section.models": "Multi-model Forecast",