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Refresh sparse model detail caches in forecast views

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This commit is contained in:
2569718930@qq.com
2026-04-08 15:23:34 +08:00
parent 0af5a84449
commit 7b1f34db27
5 changed files with 69 additions and 1 deletions
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data/probability_training_snapshots.jsonl
+1
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@@ -123,3 +123,4 @@
{"city": "shenzhen", "timestamp": "2026-03-25T10:02:35+00:00", "date": "2026-03-25", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.15911458333333342, "deb_prediction": 28.2, "ensemble": {"p10": 30.5, "median": 31.4, "p90": 31.8}, "multi_model": {"Open-Meteo": 26.5, "ECMWF": 28.8, "GFS": 30.3, "ICON": 26.5, "GEM": 30.7, "JMA": 26.2}, "max_so_far": 28.9, "peak_status": "past", "prob_snapshot": [{"v": 28, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
{"city": "shanghai", "timestamp": "2026-03-29T15:00:00.000Z", "date": "2026-03-29", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.23736458333333335, "deb_prediction": 18.4, "ensemble": {"p10": 16.1, "median": 16.5, "p90": 16.9}, "multi_model": {"Open-Meteo": 17.0, "ECMWF": 19.2, "GFS": 19.1, "ICON": 17.0, "GEM": 17.6, "JMA": 15.8}, "max_so_far": 18.0, "observation": {"current_temp": 14.0, "humidity": null, "wind_speed_kt": 4.0, "visibility_mi": 3.11, "local_hour": 23.25}, "peak_status": "past", "prob_snapshot": [{"v": 18, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
{"city": "ankara", "timestamp": "2026-03-29T15:01:00.000Z", "date": "2026-03-29", "temp_symbol": "°C", "raw_mu": null, "raw_sigma": 0.25176666666666664, "deb_prediction": 9.7, "ensemble": {"p10": 9.2, "median": 9.5, "p90": 10.2}, "multi_model": {"Open-Meteo": 9.2, "ECMWF": 9.5, "GFS": 10.1, "ICON": 9.2, "GEM": 11.0, "JMA": 10.0}, "max_so_far": 10.0, "observation": {"current_temp": 7.0, "humidity": null, "wind_speed_kt": 12.0, "visibility_mi": null, "local_hour": 18.25}, "peak_status": "past", "prob_snapshot": [{"v": 10, "p": 1.0}], "shadow_prob_snapshot": [], "probability_engine": "legacy", "probability_mode": "legacy", "calibration_version": null, "calibration_source": null, "calibrated_mu": null, "calibrated_sigma": null}
{"city": "chengdu", "timestamp": "2026-04-08T07:00:00.000Z", "date": "2026-04-08", "temp_symbol": "°C", "raw_mu": 24.3, "raw_sigma": 1.1821289062499998, "deb_prediction": 23.1, "ensemble": {"p10": 21.8, "median": 23.0, "p90": 24.5}, "multi_model": {"Open-Meteo": 22.5, "ECMWF": 23.9, "GFS": 23.0, "ICON": 22.5, "GEM": 23.7, "JMA": 23.2}, "max_so_far": 24.0, "observation": {"current_temp": 24.0, "humidity": null, "wind_speed_kt": 4.0, "visibility_mi": null, "local_hour": 15.183333333333334}, "peak_status": "before", "prob_snapshot": [{"v": 24, "p": 0.442}, {"v": 25, "p": 0.386}, {"v": 26, "p": 0.172}], "shadow_prob_snapshot": [{"v": 24, "p": 0.394}, {"v": 25, "p": 0.355}, {"v": 26, "p": 0.19}, {"v": 27, "p": 0.06}], "probability_engine": "legacy", "probability_mode": "emos_shadow", "calibration_version": "emos-20260402162744", "calibration_source": "artifacts\\probability_calibration\\default.json", "calibrated_mu": 24.3, "calibrated_sigma": 1.354078466151897}
frontend/components/dashboard/FutureForecastModal.tsx
+10
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@@ -609,6 +609,7 @@ export function FutureForecastModal() {
const max = Math.max(...values);
const spread = max - min;
return {
count: values.length,
max,
min,
spread,
@@ -790,6 +791,15 @@ export function FutureForecastModal() {
? "Model spread is unavailable right now."
: "当前拿不到可用的模型分歧。";
}
const modelEntries = Object.entries(modelView?.models || {}).filter(
([, value]) => value !== null && value !== undefined && Number.isFinite(Number(value)),
);
if (modelEntries.length === 1) {
const [singleModelName, singleModelValue] = modelEntries[0];
return locale === "en-US"
? `Only ${singleModelName} is available right now at ${Number(singleModelValue).toFixed(1)}${detail.temp_symbol}; multi-model spread is temporarily unavailable.`
: `当前只收到 ${singleModelName} ${Number(singleModelValue).toFixed(1)}${detail.temp_symbol}，其他多模型暂未回传，所以这里先不判断模型分歧。`;
}
return locale === "en-US"
? `Model range runs from ${modelSpreadView.min.toFixed(1)}${detail.temp_symbol} to ${modelSpreadView.max.toFixed(1)}${detail.temp_symbol}; spread ${modelSpreadView.spread.toFixed(1)}${detail.temp_symbol}.`
: `当前模型区间在 ${modelSpreadView.min.toFixed(1)}${detail.temp_symbol} 到 ${modelSpreadView.max.toFixed(1)}${detail.temp_symbol}，分歧 ${modelSpreadView.spread.toFixed(1)}${detail.temp_symbol}。`;
frontend/components/dashboard/PanelSections.tsx
+14
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@@ -609,6 +609,7 @@ export function ModelForecast({
([, value]) =>
value !== null && value !== undefined && Number.isFinite(Number(value)),
);
const hasSingleModelOnly = modelEntries.length === 1;
// 如果没有任何数值，给出提示
if (modelEntries.length === 0) {
@@ -637,6 +638,19 @@ export function ModelForecast({
<section className="models-section">
{!hideTitle && <h3>{t("section.models")}</h3>}
<div className="model-bars">
{hasSingleModelOnly && (
<div
style={{
color: "var(--text-secondary)",
fontSize: "11px",
marginBottom: "8px",
}}
>
{locale === "en-US"
? "Single-model fallback: waiting for the rest of the model cluster."
: "当前处于单模型回退，其他模型结果还没回传。"}
</div>
)}
{modelEntries
.sort((a, b) => Number(b[1] || 0) - Number(a[1] || 0))
.map(([name, value]) => {
frontend/hooks/useDashboardStore.tsx
+31 -1
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@@ -91,6 +91,28 @@ const BACKGROUND_SUMMARY_REFRESH_MS = 30_000;
const EAGER_CITY_SUMMARIES_ENABLED =
process.env.NEXT_PUBLIC_POLYWEATHER_EAGER_CITY_SUMMARIES === "true";
function countAvailableModels(
detail?: CityDetail | null,
targetDate?: string | null,
): number {
if (!detail) return 0;
const date = String(targetDate || detail.local_date || "").trim();
const dailyModels = detail.multi_model_daily?.[date]?.models;
const models = dailyModels && typeof dailyModels === "object"
? dailyModels
: detail.multi_model || {};
return Object.values(models).filter((value) =>
Number.isFinite(Number(value)),
).length;
}
function hasSparseModelCoverage(
detail?: CityDetail | null,
targetDate?: string | null,
): boolean {
return countAvailableModels(detail, targetDate) <= 1;
}
export function DashboardStoreProvider({
children,
}: {
@@ -598,6 +620,12 @@ export function DashboardStoreProvider({
mapStopMotionRef.current();
setFutureModalDate(dateStr);
if (!selectedCity || !proAccess.subscriptionActive) return;
const cachedDetail = cityDetailsByName[selectedCity];
const needsModelRefresh =
!forceRefresh && hasSparseModelCoverage(cachedDetail, dateStr);
if (needsModelRefresh) {
void ensureCityDetail(selectedCity, true).catch(() => {});
}
const cacheKey = getMarketScanCacheKey(selectedCity, dateStr);
setLoadingState((current) => ({ ...current, marketScan: true }));
void ensureCityMarketScan(
@@ -624,6 +652,8 @@ export function DashboardStoreProvider({
setFutureModalDate(cachedDetail.local_date);
}
if (!proAccess.subscriptionActive) return;
const needsModelRefresh =
!forceRefresh && hasSparseModelCoverage(cachedDetail, cachedDetail?.local_date);
setLoadingState((current) => ({
...current,
@@ -634,7 +664,7 @@ export function DashboardStoreProvider({
try {
const detail = await ensureCityDetail(
selectedCity,
Boolean(forceRefresh),
Boolean(forceRefresh || needsModelRefresh),
);
setSelectedForecastDate(detail.local_date);
setFutureModalDate(detail.local_date);
frontend/lib/dashboard-client.ts
+13
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@@ -52,11 +52,24 @@ function normalizeRevisionPart(value: unknown) {
export function getCityRevision(source?: CityDetail | CitySummary | null) {
if (!source) return "";
const modelDaily =
"multi_model_daily" in source && source.multi_model_daily
? source.multi_model_daily?.[source.local_date || ""]
: null;
const modelFootprint = modelDaily?.models || ("multi_model" in source ? source.multi_model : null);
return [
normalizeRevisionPart(source.updated_at),
normalizeRevisionPart(source.current?.obs_time),
normalizeRevisionPart(source.current?.temp),
normalizeRevisionPart(source.deb?.prediction),
normalizeRevisionPart(
modelFootprint && typeof modelFootprint === "object"
? Object.keys(modelFootprint)
.sort()
.map((key) => `${key}:${normalizeRevisionPart(modelFootprint[key])}`)
.join("|")
: "",
),
].join("|");
}