2569718930@qq.com
2102 lines
70 KiB
TypeScript
2102 lines
70 KiB
TypeScript
import type {
|
|
AmosData,
|
|
AirportCurrentConditions,
|
|
CityDetail,
|
|
ScanOpportunityRow,
|
|
ForecastDay,
|
|
DailyModelForecast,
|
|
ProbabilityBucket,
|
|
} from "@/lib/dashboard-types";
|
|
import { buildDebBaselinePath } from "@/lib/temperature-chart-paths";
|
|
import { DASHBOARD_REFRESH_POLICY_MS } from "@/lib/refresh-policy";
|
|
import type { CityPatch } from "@/hooks/use-sse-patches";
|
|
const ROLLING_WINDOW_BEFORE_MS = 12 * 60 * 60 * 1000;
|
|
const ROLLING_WINDOW_AFTER_LIVE_MS = 2 * 60 * 60 * 1000;
|
|
const ROLLING_WINDOW_AFTER_FORECAST_MS = 8 * 60 * 60 * 1000;
|
|
const DAY_MS = 24 * 60 * 60 * 1000;
|
|
|
|
const SETTLEMENT_RUNWAY_PAIRS: Record<string, Array<[string, string]>> = {
|
|
shanghai: [["17L", "35R"]],
|
|
beijing: [["19", "01"]],
|
|
guangzhou: [["02L", "20R"]],
|
|
chengdu: [["02L", "20R"]],
|
|
chongqing: [["20R", "02L"]],
|
|
wuhan: [["04", "22"]],
|
|
seoul: [["15R", "33L"]],
|
|
busan: [["SR", "SL"]],
|
|
};
|
|
|
|
function normalizeRunwayLabel(value?: string | null) {
|
|
return String(value || "").trim().toUpperCase().replace(/\s+/g, "");
|
|
}
|
|
|
|
function normalizeCityKey(value?: string | null) {
|
|
return String(value || "").trim().toLowerCase().replace(/[\s_-]+/g, "");
|
|
}
|
|
|
|
function hasRecordEntries(value: unknown) {
|
|
return Boolean(value && typeof value === "object" && Object.keys(value as Record<string, unknown>).length > 0);
|
|
}
|
|
|
|
function pairKey(pair: [string, string]) {
|
|
return pair.map(normalizeRunwayLabel).sort().join("/");
|
|
}
|
|
|
|
function runwaySeriesKey(rwy: string) {
|
|
return `runway_${String(rwy || "unknown")
|
|
.split("/")
|
|
.map(normalizeRunwayLabel)
|
|
.filter(Boolean)
|
|
.join("_")}`;
|
|
}
|
|
|
|
function isTemperatureSeriesVisibleByDefault(city: string, seriesKey: string) {
|
|
if (seriesKey.startsWith("model_curve_")) {
|
|
return normalizeCityKey(city) === "paris" && seriesKey === "model_curve_AROME HD";
|
|
}
|
|
return true;
|
|
}
|
|
|
|
function prefersHighFrequencyRunwayResolution(
|
|
row: ScanOpportunityRow | null,
|
|
hourly: HourlyForecast,
|
|
) {
|
|
const cityKey = normalizeCityKey(row?.city);
|
|
if ((SETTLEMENT_RUNWAY_PAIRS[cityKey] || []).length > 0) return true;
|
|
if (hasRecordEntries((row as any)?.runway_plate_history)) return true;
|
|
if (hasRecordEntries(hourly?.runwayPlateHistory)) return true;
|
|
if ((hourly?.runwayBandHistory || []).length > 0) return true;
|
|
if (((hourly?.amos?.runway_obs as any)?.runway_pairs || []).length > 0) return true;
|
|
return false;
|
|
}
|
|
|
|
function getVisibleTemperatureSeries(
|
|
city: string,
|
|
series: EvidenceSeries[],
|
|
userToggledKeys: Record<string, boolean>,
|
|
) {
|
|
return series.filter((item) => {
|
|
if (userToggledKeys[item.key] !== undefined) {
|
|
return userToggledKeys[item.key];
|
|
}
|
|
return isTemperatureSeriesVisibleByDefault(city, item.key);
|
|
});
|
|
}
|
|
|
|
function getActiveTemperatureSeries(
|
|
city: string,
|
|
chartSeries: EvidenceSeries[],
|
|
userToggledKeys: Record<string, boolean>,
|
|
showRunwayDetails: boolean,
|
|
) {
|
|
const rawVisible = getVisibleTemperatureSeries(city, chartSeries, userToggledKeys);
|
|
const hasRunwayMax = rawVisible.some((item) => item.key === "runway_max");
|
|
|
|
return rawVisible.filter((item) => {
|
|
const isIndividualRunway =
|
|
item.key.startsWith("runway_") && item.key !== "runway_max";
|
|
if (showRunwayDetails) {
|
|
return item.key !== "runway_max";
|
|
}
|
|
if (!hasRunwayMax) {
|
|
return true;
|
|
}
|
|
return !isIndividualRunway;
|
|
});
|
|
}
|
|
|
|
function buildRunwayPlates(
|
|
amos: AmosData | null | undefined,
|
|
row: ScanOpportunityRow | null,
|
|
settlementObs?: Array<{ ts: number; value: number }>,
|
|
) {
|
|
if (!amos) return [];
|
|
const runwayObs = amos.runway_obs || {};
|
|
const runwayPairs = runwayObs.runway_pairs || [];
|
|
const runwayTemps = runwayObs.temperatures || [];
|
|
const pointTemps = runwayObs.point_temperatures || [];
|
|
|
|
const cityKey = normalizeCityKey(row?.city);
|
|
const settlementPairs = SETTLEMENT_RUNWAY_PAIRS[cityKey] || [];
|
|
const settlementKeys = new Set(settlementPairs.map(pairKey));
|
|
|
|
const list: Array<{
|
|
rwy: string;
|
|
isSettlement: boolean;
|
|
tdzTemp: number | null;
|
|
midTemp: number | null;
|
|
endTemp: number | null;
|
|
maxTemp: number | null;
|
|
dailyHigh: number | null;
|
|
trend_15m: number | null;
|
|
}> = [];
|
|
|
|
runwayPairs.forEach((rawPair: any, index: number) => {
|
|
const pair = rawPair as [string, string];
|
|
if (!Array.isArray(pair) || pair.length < 2) return;
|
|
const isSettlement = settlementKeys.has(pairKey(pair));
|
|
|
|
const pointTemp = pointTemps[index] as any;
|
|
const aggregateRunwayTemp = validNumber(pointTemp?.temp) ?? validNumber(pointTemp?.target_runway_max);
|
|
const tdz = validNumber(pointTemp?.tdz_temp);
|
|
const mid = validNumber(pointTemp?.mid_temp);
|
|
const end = validNumber(pointTemp?.end_temp);
|
|
const isAmosTempDewTuple = String(amos.source || "").toLowerCase() === "amos";
|
|
|
|
const historyVals = !isAmosTempDewTuple && Array.isArray(runwayTemps[index])
|
|
? (runwayTemps[index] as Array<number | null>).map(validNumber).filter((v): v is number => v !== null)
|
|
: [];
|
|
|
|
const aggregateVal = aggregateRunwayTemp !== null ? [aggregateRunwayTemp] : [];
|
|
const tdzVal = tdz !== null ? [tdz] : [];
|
|
const midVal = mid !== null ? [mid] : [];
|
|
const endVal = end !== null ? [end] : [];
|
|
const allVals = [...historyVals, ...aggregateVal, ...tdzVal, ...midVal, ...endVal];
|
|
|
|
const maxTemp = allVals.length ? Math.max(...allVals) : null;
|
|
const dailyHigh = historyVals.length ? Math.max(...historyVals) : maxTemp;
|
|
|
|
// Calculate 15-minute trend
|
|
const latest = historyVals.length > 0 ? historyVals[historyVals.length - 1] : (tdz ?? mid ?? end ?? null);
|
|
const val15 = historyVals.length > 15 ? historyVals[historyVals.length - 16] : (historyVals.length > 0 ? historyVals[0] : null);
|
|
let trend_15m = (latest !== null && val15 !== null) ? latest - val15 : null;
|
|
|
|
if (isSettlement && settlementObs && settlementObs.length >= 2) {
|
|
const latestObs = settlementObs[settlementObs.length - 1];
|
|
const targetTs = latestObs.ts - 15 * 60 * 1000;
|
|
let closestPoint = settlementObs[0];
|
|
let minDiff = Math.abs(closestPoint.ts - targetTs);
|
|
for (let i = 1; i < settlementObs.length; i++) {
|
|
const diff = Math.abs(settlementObs[i].ts - targetTs);
|
|
if (diff < minDiff) {
|
|
minDiff = diff;
|
|
closestPoint = settlementObs[i];
|
|
}
|
|
}
|
|
if (Math.abs(closestPoint.ts - targetTs) < 5 * 60 * 1000) {
|
|
trend_15m = latestObs.value - closestPoint.value;
|
|
}
|
|
}
|
|
|
|
list.push({
|
|
rwy: `${normalizeRunwayLabel(pair[0])}/${normalizeRunwayLabel(pair[1])}`,
|
|
isSettlement,
|
|
tdzTemp: tdz,
|
|
midTemp: mid,
|
|
endTemp: end,
|
|
maxTemp,
|
|
dailyHigh,
|
|
trend_15m,
|
|
});
|
|
});
|
|
|
|
return list;
|
|
}
|
|
|
|
type ObsPoint = { time?: string | null; temp?: number | null };
|
|
type RawObsPoint = ObsPoint | [string | number | null, number | null | undefined];
|
|
|
|
type EvidenceSeries = {
|
|
key: string;
|
|
label: string;
|
|
source: string;
|
|
color: string;
|
|
dashed?: boolean;
|
|
featured?: boolean;
|
|
smooth?: boolean;
|
|
curve?: "linear" | "monotone" | "stepAfter";
|
|
connectNulls?: boolean;
|
|
showDot?: boolean;
|
|
values: Array<number | null>;
|
|
};
|
|
|
|
type LegacyGaussianProbabilitySource = {
|
|
mu?: number | null;
|
|
engine?: string | null;
|
|
calibration_mode?: string | null;
|
|
distribution?: ProbabilityBucket[];
|
|
distribution_all?: ProbabilityBucket[];
|
|
};
|
|
|
|
type ProbabilityTemperatureBand = {
|
|
key: string;
|
|
value: number;
|
|
lower: number;
|
|
upper: number;
|
|
probability: number;
|
|
label: string;
|
|
opacity: number;
|
|
};
|
|
|
|
type ProbabilityMuLine = {
|
|
value: number;
|
|
label: string;
|
|
};
|
|
|
|
type ProbabilityOverlay = {
|
|
engine: string | null;
|
|
muLine: ProbabilityMuLine | null;
|
|
bands: ProbabilityTemperatureBand[];
|
|
};
|
|
|
|
type PeakGlowState = "none" | "watch" | "near_peak" | "breakout" | "cooling";
|
|
|
|
type PeakGlowMeta = {
|
|
state: PeakGlowState;
|
|
currentTemp: number | null;
|
|
referenceHigh: number | null;
|
|
distanceToHigh: number | null;
|
|
trend30m: number | null;
|
|
trend60m: number | null;
|
|
observedHigh: number | null;
|
|
};
|
|
|
|
type RunwayHistorySeries = {
|
|
key: string;
|
|
label: string;
|
|
rwy: string;
|
|
isSettlement: boolean;
|
|
color: string;
|
|
points: Array<{ ts: number; value: number }>;
|
|
};
|
|
|
|
type TemperatureBandPoint = { ts: number; high: number; low: number; avg: number };
|
|
type LocalDayBounds = { start: number; end: number };
|
|
|
|
const MAX_OBS_POINTS = 1440;
|
|
const HOURLY_CACHE_TTL_MS = DASHBOARD_REFRESH_POLICY_MS.metar;
|
|
const _hourlyCache = new Map<string, { ts: number; data: HourlyForecast }>();
|
|
const _hourlyRequestCache = new Map<string, Promise<HourlyForecast>>();
|
|
const MAX_HOURLY_DETAIL_CONCURRENT_REQUESTS = 3;
|
|
let _hourlyActiveDetailRequests = 0;
|
|
const _hourlyDetailRequestQueue: Array<() => void> = [];
|
|
const RUNWAY_LINE_COLORS = ["#00897b", "#d97706", "#7c3aed", "#0891b2", "#ea580c", "#64748b"];
|
|
|
|
const SESSION_CACHE_PREFIX = "polyweather_city_detail_v1:";
|
|
const SESSION_CACHE_TTL_MS = DASHBOARD_REFRESH_POLICY_MS.metar;
|
|
|
|
function readSessionCache(city: string): { ts: number; data: HourlyForecast } | null {
|
|
if (typeof window === "undefined") return null;
|
|
try {
|
|
const raw = sessionStorage.getItem(`${SESSION_CACHE_PREFIX}${city}`);
|
|
if (!raw) return null;
|
|
const item = JSON.parse(raw);
|
|
if (item && item.ts && Date.now() - item.ts < SESSION_CACHE_TTL_MS) {
|
|
return item;
|
|
}
|
|
} catch {}
|
|
return null;
|
|
}
|
|
|
|
function writeSessionCache(city: string, data: HourlyForecast) {
|
|
if (typeof window === "undefined" || !data) return;
|
|
try {
|
|
sessionStorage.setItem(
|
|
`${SESSION_CACHE_PREFIX}${city}`,
|
|
JSON.stringify({ ts: Date.now(), data })
|
|
);
|
|
} catch {}
|
|
}
|
|
|
|
function drainHourlyDetailRequestQueue() {
|
|
while (
|
|
_hourlyActiveDetailRequests < MAX_HOURLY_DETAIL_CONCURRENT_REQUESTS &&
|
|
_hourlyDetailRequestQueue.length > 0
|
|
) {
|
|
const start = _hourlyDetailRequestQueue.shift();
|
|
if (start) start();
|
|
}
|
|
}
|
|
|
|
function runQueuedHourlyDetailRequest<T>(task: () => Promise<T>): Promise<T> {
|
|
return new Promise<T>((resolve, reject) => {
|
|
const start = () => {
|
|
_hourlyActiveDetailRequests += 1;
|
|
Promise.resolve()
|
|
.then(task)
|
|
.then(resolve, reject)
|
|
.finally(() => {
|
|
_hourlyActiveDetailRequests = Math.max(0, _hourlyActiveDetailRequests - 1);
|
|
drainHourlyDetailRequestQueue();
|
|
});
|
|
};
|
|
|
|
_hourlyDetailRequestQueue.push(start);
|
|
drainHourlyDetailRequestQueue();
|
|
});
|
|
}
|
|
|
|
export function clearCityDetailCache() {
|
|
_hourlyCache.clear();
|
|
_hourlyRequestCache.clear();
|
|
if (typeof window !== "undefined") {
|
|
try {
|
|
for (let i = sessionStorage.length - 1; i >= 0; i--) {
|
|
const key = sessionStorage.key(i);
|
|
if (key && key.startsWith(SESSION_CACHE_PREFIX)) {
|
|
sessionStorage.removeItem(key);
|
|
}
|
|
}
|
|
} catch {}
|
|
}
|
|
}
|
|
|
|
function __resetHourlyDetailRequestQueueForTest() {
|
|
_hourlyActiveDetailRequests = 0;
|
|
_hourlyDetailRequestQueue.length = 0;
|
|
}
|
|
|
|
const __runQueuedHourlyDetailRequestForTest = runQueuedHourlyDetailRequest;
|
|
|
|
function validNumber(value: unknown): number | null {
|
|
return typeof value === "number" && Number.isFinite(value) ? value : null;
|
|
}
|
|
|
|
function getCityLocalUtcTimestamp(
|
|
value: string | number | null | undefined,
|
|
tzOffsetSeconds: number,
|
|
referenceLocalDate?: string | null
|
|
): number | null {
|
|
if (value == null) return null;
|
|
|
|
if (typeof value === "number") {
|
|
const d = new Date(value + tzOffsetSeconds * 1000);
|
|
return Date.UTC(
|
|
d.getUTCFullYear(),
|
|
d.getUTCMonth(),
|
|
d.getUTCDate(),
|
|
d.getUTCHours(),
|
|
d.getUTCMinutes(),
|
|
d.getUTCSeconds()
|
|
);
|
|
}
|
|
|
|
const raw = String(value).trim();
|
|
if (!raw) return null;
|
|
|
|
if (raw.includes("T") || raw.includes("Z") || raw.includes("-")) {
|
|
const d = new Date(raw);
|
|
if (!Number.isNaN(d.getTime())) {
|
|
const localMs = d.getTime() + tzOffsetSeconds * 1000;
|
|
const localDate = new Date(localMs);
|
|
return Date.UTC(
|
|
localDate.getUTCFullYear(),
|
|
localDate.getUTCMonth(),
|
|
localDate.getUTCDate(),
|
|
localDate.getUTCHours(),
|
|
localDate.getUTCMinutes(),
|
|
localDate.getUTCSeconds()
|
|
);
|
|
}
|
|
}
|
|
|
|
const m = raw.match(/(\d{1,2}):(\d{2})(?::(\d{2}))?/);
|
|
if (m) {
|
|
const h = +m[1];
|
|
const min = +m[2];
|
|
const sec = m[3] ? +m[3] : 0;
|
|
|
|
let year = new Date().getUTCFullYear();
|
|
let month = new Date().getUTCMonth();
|
|
let date = new Date().getUTCDate();
|
|
|
|
if (referenceLocalDate) {
|
|
const dateParts = referenceLocalDate.split("-");
|
|
if (dateParts.length === 3) {
|
|
year = parseInt(dateParts[0]);
|
|
month = parseInt(dateParts[1]) - 1;
|
|
date = parseInt(dateParts[2]);
|
|
}
|
|
}
|
|
|
|
return Date.UTC(year, month, date, h, min, sec);
|
|
}
|
|
|
|
return null;
|
|
}
|
|
|
|
function getLocalDayBounds(localDateStr: string): LocalDayBounds | null {
|
|
const match = /^(\d{4})-(\d{2})-(\d{2})$/.exec(localDateStr);
|
|
if (!match) return null;
|
|
const start = Date.UTC(
|
|
Number(match[1]),
|
|
Number(match[2]) - 1,
|
|
Number(match[3]),
|
|
0,
|
|
0,
|
|
0,
|
|
);
|
|
return Number.isFinite(start) ? { start, end: start + DAY_MS } : null;
|
|
}
|
|
|
|
function dateFromLocalTime(value?: string | null) {
|
|
const match = /^(\d{4})-(\d{2})-(\d{2})/.exec(String(value || "").trim());
|
|
return match ? `${match[1]}-${match[2]}-${match[3]}` : null;
|
|
}
|
|
|
|
function resolveChartLocalDate(row: ScanOpportunityRow | null, hourly: HourlyForecast) {
|
|
return (
|
|
hourly?.localDate ||
|
|
dateFromLocalTime(hourly?.localTime) ||
|
|
row?.local_date ||
|
|
dateFromLocalTime(row?.local_time) ||
|
|
new Date().toISOString().slice(0, 10)
|
|
);
|
|
}
|
|
|
|
function isWithinLocalDay(ts: number | null, bounds: LocalDayBounds | null) {
|
|
return ts !== null && Number.isFinite(ts) && (!bounds || (ts >= bounds.start && ts < bounds.end));
|
|
}
|
|
|
|
function filterTimelinePointsToLocalDay<T extends { ts: number }>(
|
|
points: T[],
|
|
bounds: LocalDayBounds | null,
|
|
) {
|
|
if (!bounds) return points;
|
|
return points.filter((point) => isWithinLocalDay(point.ts, bounds));
|
|
}
|
|
|
|
function filterRunwayHistoryToLocalDay(
|
|
series: RunwayHistorySeries[],
|
|
bounds: LocalDayBounds | null,
|
|
) {
|
|
if (!bounds) return series;
|
|
return series
|
|
.map((item) => ({
|
|
...item,
|
|
points: filterTimelinePointsToLocalDay(item.points, bounds),
|
|
}))
|
|
.filter((item) => item.points.length > 1);
|
|
}
|
|
|
|
function formatTimestamp(ts: number): string {
|
|
const d = new Date(ts);
|
|
return `${String(d.getUTCHours()).padStart(2, "0")}:${String(d.getUTCMinutes()).padStart(2, "0")}:${String(d.getUTCSeconds()).padStart(2, "0")}`;
|
|
}
|
|
|
|
function normalizeRawObsPoint(point: RawObsPoint): ObsPoint | null {
|
|
if (Array.isArray(point)) {
|
|
return { time: point[0] == null ? null : String(point[0]), temp: validNumber(point[1]) };
|
|
}
|
|
return point;
|
|
}
|
|
|
|
function normObs(
|
|
points: RawObsPoint[] | null | undefined,
|
|
tzOffsetSeconds: number,
|
|
limit = MAX_OBS_POINTS,
|
|
referenceLocalDate?: string | null,
|
|
) {
|
|
return (points || [])
|
|
.map(normalizeRawObsPoint)
|
|
.filter((p): p is ObsPoint => p !== null)
|
|
.filter((p) => validNumber(p.temp) !== null && p.time)
|
|
.map((p) => {
|
|
const ts = getCityLocalUtcTimestamp(p.time, tzOffsetSeconds, referenceLocalDate);
|
|
return ts === null ? null : { ts, value: Number(p.temp) };
|
|
})
|
|
.filter((p): p is { ts: number; value: number } => p !== null)
|
|
.slice(-limit);
|
|
}
|
|
|
|
function appendLatestAirportObservation(
|
|
points: RawObsPoint[] | null | undefined,
|
|
...currentSources: Array<AirportCurrentConditions | null | undefined>
|
|
): RawObsPoint[] {
|
|
const merged = [...(points || [])];
|
|
const seen = new Set(
|
|
merged
|
|
.map(normalizeRawObsPoint)
|
|
.filter((point): point is ObsPoint => point !== null)
|
|
.map((point) => `${String(point.time || "")}:${validNumber(point.temp) ?? ""}`),
|
|
);
|
|
|
|
currentSources.forEach((source) => {
|
|
const temp = validNumber(source?.temp);
|
|
const time =
|
|
(source as any)?.obs_time ??
|
|
(source as any)?.observation_time ??
|
|
(source as any)?.timestamp ??
|
|
(source as any)?.time ??
|
|
null;
|
|
if (temp === null || !time) return;
|
|
const key = `${String(time)}:${temp}`;
|
|
if (seen.has(key)) return;
|
|
seen.add(key);
|
|
merged.push({ time: String(time), temp });
|
|
});
|
|
|
|
return merged;
|
|
}
|
|
|
|
function seriesStats(values: Array<number | null>) {
|
|
const nums = values.filter((v): v is number => validNumber(v) !== null);
|
|
const latest = nums.length ? nums[nums.length - 1] : null;
|
|
const high = nums.length ? Math.max(...nums) : null;
|
|
const first15 = nums.length > 1 ? nums[Math.max(0, nums.length - 15)] : null;
|
|
const delta15 = latest !== null && first15 !== null ? latest - first15 : null;
|
|
return { latest, high, delta15 };
|
|
}
|
|
|
|
function latestObservationValue(obs: Array<{ ts: number; value: number }>) {
|
|
if (!obs.length) return null;
|
|
return obs.reduce((latest, point) => (point.ts > latest.ts ? point : latest), obs[0]).value;
|
|
}
|
|
|
|
function maxObservationValue(obs: Array<{ ts: number; value: number }>) {
|
|
if (!obs.length) return null;
|
|
return Math.max(...obs.map((point) => point.value));
|
|
}
|
|
|
|
function getRunwayHistoryObservationMetrics(
|
|
row: ScanOpportunityRow | null,
|
|
hourly: HourlyForecast,
|
|
) {
|
|
const tzOffset = row?.tz_offset_seconds ?? 0;
|
|
const localDateStr = resolveChartLocalDate(row, hourly);
|
|
const localDayBounds = getLocalDayBounds(localDateStr);
|
|
const runwayHistorySeries = buildRunwayHistorySeries(row, hourly, tzOffset, localDateStr, 1)
|
|
.map((item) => ({
|
|
...item,
|
|
points: filterTimelinePointsToLocalDay(item.points, localDayBounds),
|
|
}))
|
|
.filter((item) => item.points.length > 0);
|
|
|
|
const settlementSeries = runwayHistorySeries.filter((item) => item.isSettlement);
|
|
const candidateSeries = settlementSeries.length ? settlementSeries : runwayHistorySeries;
|
|
const points = candidateSeries.flatMap((item) => item.points);
|
|
if (!points.length) return { latest: null, high: null };
|
|
|
|
const latestTs = Math.max(...points.map((point) => point.ts));
|
|
const latestValues = points
|
|
.filter((point) => point.ts === latestTs)
|
|
.map((point) => point.value);
|
|
return {
|
|
latest: latestValues.length ? Math.max(...latestValues) : null,
|
|
high: Math.max(...points.map((point) => point.value)),
|
|
};
|
|
}
|
|
|
|
function hasRenderableLineSeries(series: EvidenceSeries[]) {
|
|
return series.some(
|
|
(item) => item.values.filter((value) => validNumber(value) !== null).length >= 2,
|
|
);
|
|
}
|
|
|
|
function observationSetContains(
|
|
superset: Array<{ ts: number; value: number }>,
|
|
subset: Array<{ ts: number; value: number }>,
|
|
) {
|
|
if (!superset.length || !subset.length) return false;
|
|
return subset.every((point) =>
|
|
superset.some((candidate) => candidate.ts === point.ts && Math.abs(candidate.value - point.value) < 0.01),
|
|
);
|
|
}
|
|
|
|
function getObservationDisplayMetrics(
|
|
row: ScanOpportunityRow | null,
|
|
hourly: HourlyForecast,
|
|
settlementPlate?: { maxTemp: number | null } | null,
|
|
) {
|
|
const tzOffset = row?.tz_offset_seconds ?? 0;
|
|
const localDateStr = resolveChartLocalDate(row, hourly);
|
|
const settlementObs = normObs(hourly?.settlementTodayObs || row?.settlement_today_obs || row?.metar_context?.settlement_today_obs, tzOffset, MAX_OBS_POINTS, localDateStr);
|
|
const metarObs = normObs(hourly?.metarTodayObs || row?.metar_today_obs || row?.metar_context?.today_obs || row?.metar_recent_obs || row?.metar_context?.recent_obs, tzOffset, MAX_OBS_POINTS, localDateStr);
|
|
const madisObs = normObs(
|
|
appendLatestAirportObservation(hourly?.airportPrimaryTodayObs, hourly?.airportPrimary, hourly?.airportCurrent),
|
|
tzOffset,
|
|
MAX_OBS_POINTS,
|
|
localDateStr,
|
|
);
|
|
const latestSettlement = latestObservationValue(settlementObs);
|
|
const latestMetar = latestObservationValue(metarObs);
|
|
const latestMadis = latestObservationValue(madisObs);
|
|
const highSettlement = maxObservationValue(settlementObs);
|
|
const highMetar = maxObservationValue(metarObs);
|
|
const highMadis = maxObservationValue(madisObs);
|
|
const airportCurrentTemp = validNumber(hourly?.airportCurrent?.temp) ?? validNumber(hourly?.airportPrimary?.temp);
|
|
const airportHigh = validNumber(hourly?.airportCurrent?.max_so_far) ?? validNumber(hourly?.airportPrimary?.max_so_far);
|
|
const rowMetarHigh = validNumber(row?.metar_context?.airport_max_so_far ?? row?.metar_context?.max_temp ?? row?.current_max_so_far);
|
|
const runwayHistoryMetrics = getRunwayHistoryObservationMetrics(row, hourly);
|
|
|
|
const settlementCityKey = normalizeCityKey(row?.city);
|
|
const isShenzhen = settlementCityKey === 'shenzhen';
|
|
const isHKO = (settlementCityKey === 'hongkong' || settlementCityKey === 'laufaushan'
|
|
|| (row?.city || '').toLowerCase().includes('hong kong')
|
|
|| (row?.city || '').toLowerCase().includes('lau fau shan')) && !isShenzhen;
|
|
|
|
let currentRunwayTemp: number | null = null;
|
|
let observedHighRunway: number | null = null;
|
|
|
|
if (isHKO) {
|
|
currentRunwayTemp =
|
|
latestMadis ??
|
|
latestSettlement ??
|
|
latestMetar ??
|
|
airportCurrentTemp ??
|
|
validNumber(row?.current_temp) ??
|
|
null;
|
|
observedHighRunway =
|
|
highMadis ??
|
|
highSettlement ??
|
|
airportHigh ??
|
|
highMetar ??
|
|
validNumber(row?.current_max_so_far) ??
|
|
currentRunwayTemp ??
|
|
null;
|
|
} else {
|
|
currentRunwayTemp =
|
|
runwayHistoryMetrics.latest ??
|
|
settlementPlate?.maxTemp ??
|
|
validNumber(hourly?.amos?.temp_c) ??
|
|
latestSettlement ??
|
|
latestMetar ??
|
|
airportCurrentTemp ??
|
|
validNumber(row?.current_temp) ??
|
|
null;
|
|
observedHighRunway =
|
|
runwayHistoryMetrics.high ??
|
|
settlementPlate?.maxTemp ??
|
|
highSettlement ??
|
|
airportHigh ??
|
|
highMetar ??
|
|
validNumber(row?.current_max_so_far) ??
|
|
currentRunwayTemp ??
|
|
null;
|
|
}
|
|
|
|
const observedHighMetar = airportHigh ?? highSettlement ?? highMetar ?? rowMetarHigh ?? null;
|
|
|
|
return { currentRunwayTemp, observedHighMetar, observedHighRunway };
|
|
}
|
|
|
|
function selectDisplayRunwayTemp(
|
|
liveTemp: number | null,
|
|
currentRunwayTemp: number | null,
|
|
hasRunwayData: boolean,
|
|
) {
|
|
if (hasRunwayData && currentRunwayTemp !== null) {
|
|
return currentRunwayTemp;
|
|
}
|
|
return liveTemp ?? currentRunwayTemp;
|
|
}
|
|
|
|
function isSettlementRunway(row: ScanOpportunityRow | null, rwy: string) {
|
|
const cityKey = normalizeCityKey(row?.city);
|
|
const settlementPairs = SETTLEMENT_RUNWAY_PAIRS[cityKey] || [];
|
|
if (!settlementPairs.length) return false;
|
|
const normalized = rwy
|
|
.split("/")
|
|
.map(normalizeRunwayLabel)
|
|
.filter(Boolean)
|
|
.sort()
|
|
.join("/");
|
|
return settlementPairs.some((pair) => pairKey(pair) === normalized);
|
|
}
|
|
|
|
function runwayLabelFromPair(rawPair: unknown, index: number) {
|
|
if (Array.isArray(rawPair) && rawPair.length >= 2) {
|
|
return `${normalizeRunwayLabel(rawPair[0])}/${normalizeRunwayLabel(rawPair[1])}`;
|
|
}
|
|
return `RWY ${index + 1}`;
|
|
}
|
|
|
|
function runwayTemperatureFromPairTuple(rawTemp: unknown) {
|
|
if (Array.isArray(rawTemp)) return validNumber(rawTemp[0]);
|
|
return validNumber(rawTemp);
|
|
}
|
|
|
|
function runwayPatchPointsFromRunwayObs(runwayObs: any) {
|
|
const directPoints = Array.isArray(runwayObs?.point_temperatures)
|
|
? runwayObs.point_temperatures
|
|
: [];
|
|
if (directPoints.length) return directPoints;
|
|
|
|
const runwayPairs = Array.isArray(runwayObs?.runway_pairs)
|
|
? runwayObs.runway_pairs
|
|
: [];
|
|
const temperatures = Array.isArray(runwayObs?.temperatures)
|
|
? runwayObs.temperatures
|
|
: [];
|
|
|
|
return runwayPairs
|
|
.map((pair: unknown, index: number) => {
|
|
const temp = runwayTemperatureFromPairTuple(temperatures[index]);
|
|
if (temp === null) return null;
|
|
return {
|
|
runway: runwayLabelFromPair(pair, index),
|
|
temp,
|
|
target_runway_max: temp,
|
|
};
|
|
})
|
|
.filter((point: any): point is { runway: string; temp: number; target_runway_max: number } => point !== null);
|
|
}
|
|
|
|
type HourlyForecast = {
|
|
forecastTodayHigh?: number | null;
|
|
debPrediction?: number | null;
|
|
localDate?: string | null;
|
|
localTime?: string | null;
|
|
times: string[];
|
|
temps: Array<number | null>;
|
|
modelCurves?: Record<string, Array<number | null>>;
|
|
runwayPlateHistory?: Record<string, Array<Record<string, unknown>>>;
|
|
runwayBandHistory?: Array<{ time: string; high_temp: number; low_temp: number; avg_temp: number }>;
|
|
amos?: AmosData | null;
|
|
airportCurrent?: AirportCurrentConditions | null;
|
|
airportPrimary?: AirportCurrentConditions | null;
|
|
forecastDaily?: ForecastDay[];
|
|
multiModelDaily?: Record<string, DailyModelForecast>;
|
|
probabilities?: LegacyGaussianProbabilitySource | null;
|
|
settlementTodayObs?: ObsPoint[];
|
|
settlementStationLabel?: string | null;
|
|
metarTodayObs?: ObsPoint[];
|
|
airportPrimaryTodayObs?: RawObsPoint[];
|
|
} | null;
|
|
|
|
function seedHourlyForecastFromRow(row: ScanOpportunityRow | null): HourlyForecast {
|
|
if (!row) return null;
|
|
return {
|
|
forecastTodayHigh: null,
|
|
debPrediction: validNumber(row.deb_prediction),
|
|
localDate: row.local_date || null,
|
|
localTime: row.local_time || null,
|
|
times: [],
|
|
temps: [],
|
|
modelCurves: undefined,
|
|
runwayPlateHistory: (row as any)?.runway_plate_history || undefined,
|
|
runwayBandHistory: undefined,
|
|
amos: null,
|
|
airportCurrent: null,
|
|
airportPrimary: null,
|
|
forecastDaily: [],
|
|
multiModelDaily: {},
|
|
probabilities: {
|
|
engine: row.probability_engine || null,
|
|
distribution: row.distribution_preview || [],
|
|
distribution_all: row.distribution_full || row.distribution_preview || [],
|
|
},
|
|
settlementTodayObs: row.settlement_today_obs || row.metar_context?.settlement_today_obs || undefined,
|
|
metarTodayObs: row.metar_today_obs || row.metar_context?.today_obs || row.metar_recent_obs || row.metar_context?.recent_obs || undefined,
|
|
airportPrimaryTodayObs: undefined,
|
|
};
|
|
}
|
|
|
|
type HourlyForecastFetchOptions = {
|
|
ignoreCache?: boolean;
|
|
resolution?: string;
|
|
};
|
|
|
|
function parseHourlyForecastFromCityDetail(json: CityDetail | null): HourlyForecast {
|
|
const hourlySource = (json as any)?.hourly ?? (json as any)?.timeseries?.hourly;
|
|
if (!json || !hourlySource) return null;
|
|
return {
|
|
forecastTodayHigh: json.forecast?.today_high ?? null,
|
|
debPrediction: json.deb?.prediction ?? (json as any)?.overview?.deb_prediction ?? null,
|
|
localDate: json.local_date || (json as any)?.overview?.local_date || null,
|
|
localTime: json.local_time || null,
|
|
times: hourlySource.times || [],
|
|
temps: hourlySource.temps || [],
|
|
modelCurves: (json.models_hourly ?? (json as any)?.timeseries?.models_hourly)?.curves || undefined,
|
|
runwayPlateHistory: (json as any)?.runway_plate_history || (json.amos as any)?.runway_plate_history || undefined,
|
|
runwayBandHistory: (json as any)?.runway_band_history || undefined,
|
|
amos: json.amos || null,
|
|
airportCurrent: json.airport_current || null,
|
|
airportPrimary: json.airport_primary || null,
|
|
forecastDaily: json.forecast?.daily || [],
|
|
multiModelDaily: json.multi_model_daily || {},
|
|
probabilities: json.probabilities || null,
|
|
settlementTodayObs: (json as any).timeseries?.settlement_today_obs || (json as any)?.settlement_today_obs || undefined,
|
|
settlementStationLabel: (json as any)?.settlement_station?.settlement_station_label || null,
|
|
metarTodayObs: (json as any).timeseries?.metar_today_obs || (json as any)?.metar_today_obs || undefined,
|
|
airportPrimaryTodayObs: (json as any)?.official?.airport_primary_today_obs || (json as any)?.airport_primary_today_obs || undefined,
|
|
};
|
|
}
|
|
|
|
async function fetchHourlyForecastForCity(
|
|
city: string,
|
|
options: HourlyForecastFetchOptions = {},
|
|
): Promise<HourlyForecast> {
|
|
const resParam = options.resolution || "10m";
|
|
const cacheKey = `${city}:${resParam}`;
|
|
|
|
if (!options.ignoreCache) {
|
|
const cached = _hourlyCache.get(cacheKey);
|
|
if (cached && Date.now() - cached.ts < HOURLY_CACHE_TTL_MS) {
|
|
return cached.data;
|
|
}
|
|
|
|
const sessionCached = readSessionCache(cacheKey);
|
|
if (sessionCached) {
|
|
_hourlyCache.set(cacheKey, sessionCached);
|
|
return sessionCached.data;
|
|
}
|
|
}
|
|
|
|
const requestKey = options.ignoreCache ? `${city}:${resParam}:live` : `${city}:${resParam}`;
|
|
const pending = _hourlyRequestCache.get(requestKey);
|
|
if (pending) return pending;
|
|
|
|
const request = runQueuedHourlyDetailRequest(() =>
|
|
fetch(`/api/city/${encodeURIComponent(city)}/detail?depth=full&force_refresh=false&resolution=${resParam}`, {
|
|
headers: { Accept: "application/json" },
|
|
})
|
|
.then(async (res) => {
|
|
if (!res.ok) return null;
|
|
return res.json() as Promise<CityDetail>;
|
|
})
|
|
.then((json) => {
|
|
const data = parseHourlyForecastFromCityDetail(json);
|
|
if (!data) return null;
|
|
_hourlyCache.set(cacheKey, { ts: Date.now(), data });
|
|
writeSessionCache(cacheKey, data);
|
|
return data;
|
|
}),
|
|
)
|
|
.finally(() => {
|
|
_hourlyRequestCache.delete(requestKey);
|
|
});
|
|
|
|
_hourlyRequestCache.set(requestKey, request);
|
|
return request;
|
|
}
|
|
|
|
function shouldPollLiveChart({
|
|
city,
|
|
compact,
|
|
isActive,
|
|
isMaximized,
|
|
}: {
|
|
city: string;
|
|
compact: boolean;
|
|
isActive: boolean;
|
|
isMaximized: boolean;
|
|
}) {
|
|
return Boolean(city) && (compact || isActive || isMaximized);
|
|
}
|
|
|
|
function getLiveObservationLabels(
|
|
row: ScanOpportunityRow | null,
|
|
hourly: HourlyForecast,
|
|
) {
|
|
const normalizedKey = normalizeCityKey(row?.city);
|
|
const runwaySensorCities = new Set([
|
|
"beijing", "shanghai", "guangzhou", "qingdao",
|
|
"chengdu", "chongqing", "wuhan",
|
|
"seoul", "busan",
|
|
]);
|
|
const weatherStationCities = new Set(["ankara", "istanbul"]);
|
|
const isShenzhen = normalizedKey === "shenzhen";
|
|
const isHKO = (normalizedKey === "hongkong" || normalizedKey === "laufaushan") && !isShenzhen;
|
|
const isTokyo = normalizedKey === "tokyo";
|
|
const isSingapore = normalizedKey === "singapore";
|
|
const isParis = normalizedKey === "paris";
|
|
const isTaipei = normalizedKey === "taipei";
|
|
const sourceTokens = [
|
|
(hourly?.airportPrimary as any)?.source,
|
|
hourly?.airportPrimary?.source_code,
|
|
hourly?.airportPrimary?.source_label,
|
|
(hourly?.airportCurrent as any)?.source,
|
|
(hourly?.airportCurrent as any)?.source_code,
|
|
(hourly?.airportCurrent as any)?.source_label,
|
|
(row as any)?.station_source_code,
|
|
(row as any)?.network_provider,
|
|
(row as any)?.network_provider_label,
|
|
row?.metar_context?.source,
|
|
row?.metar_context?.station,
|
|
row?.metar_context?.station_label,
|
|
]
|
|
.map((value) => String(value || "").trim().toLowerCase())
|
|
.filter(Boolean)
|
|
.join(" ");
|
|
const hasRealStationNetwork =
|
|
weatherStationCities.has(normalizedKey) ||
|
|
/\b(mgm|turkey_mgm|jma_amedas|fmi|knmi|cowin_obs|ims|ncm|aeroweb|madis_hfmetar|singapore_mss)\b/.test(sourceTokens);
|
|
const isRunwaySensorCity = runwaySensorCities.has(normalizedKey);
|
|
const isWeatherStation = !runwaySensorCities.has(normalizedKey)
|
|
&& !isHKO && !isShenzhen && !isTokyo && !isSingapore && !isParis && !isTaipei
|
|
&& hasRealStationNetwork;
|
|
|
|
const runwayHeaderLabel = isShenzhen ? "天文台实测 (10分钟)"
|
|
: isHKO ? "参考站点 (1分钟)"
|
|
: isTokyo ? "机场气象站 (10分钟)"
|
|
: isSingapore ? "航站楼温度"
|
|
: isParis ? "官方机场观测 (15分钟)"
|
|
: isTaipei ? "CWA (10分钟)"
|
|
: isWeatherStation ? "气象站实测"
|
|
: isRunwaySensorCity ? "跑道实测 (1分钟)"
|
|
: "机场报文";
|
|
|
|
const metarHeaderLabel = (isShenzhen || isHKO) ? "天文台实测 (10分钟)"
|
|
: "METAR 结算 (30分钟)";
|
|
|
|
const runwayHighLabel = isShenzhen ? "天文台实测"
|
|
: isHKO ? "参考站点"
|
|
: isTokyo ? "机场气象站"
|
|
: isSingapore ? "航站楼"
|
|
: isParis ? "官方机场观测"
|
|
: isTaipei ? "CWA"
|
|
: isWeatherStation ? "气象站"
|
|
: isRunwaySensorCity ? "跑道实测"
|
|
: "机场报文";
|
|
|
|
const metarHighLabel = isShenzhen ? "天文台"
|
|
: isHKO ? "天文台"
|
|
: "METAR 官方";
|
|
|
|
return {
|
|
isHKO,
|
|
isParis,
|
|
isShenzhen,
|
|
isTaipei,
|
|
isWeatherStation,
|
|
metarHeaderLabel,
|
|
metarHighLabel,
|
|
runwayHeaderLabel,
|
|
runwayHighLabel,
|
|
};
|
|
}
|
|
|
|
function mergePatchIntoHourly(
|
|
prev: HourlyForecast,
|
|
patch: CityPatch,
|
|
): HourlyForecast {
|
|
const changes = patch.changes || {};
|
|
const tempValue = validNumber(changes.temp);
|
|
const observedAtUtc = typeof changes.observed_at_utc === "string" ? changes.observed_at_utc : null;
|
|
const obsTime = observedAtUtc || (typeof changes.obs_time === "string" ? changes.obs_time : null);
|
|
const source = typeof changes.source === "string" ? changes.source : "";
|
|
const explicitHourlyPatch = changes.hourly && typeof changes.hourly === "object"
|
|
? changes.hourly as Partial<NonNullable<HourlyForecast>>
|
|
: {};
|
|
|
|
const next: NonNullable<HourlyForecast> = {
|
|
...(prev || {
|
|
forecastTodayHigh: null,
|
|
debPrediction: null,
|
|
localDate: null,
|
|
localTime: null,
|
|
times: [],
|
|
temps: [],
|
|
forecastDaily: [],
|
|
multiModelDaily: {},
|
|
probabilities: null,
|
|
}),
|
|
...explicitHourlyPatch,
|
|
};
|
|
|
|
if (typeof (changes as any).local_date === "string") {
|
|
next.localDate = (changes as any).local_date;
|
|
}
|
|
if (typeof (changes as any).city_local_date === "string") {
|
|
next.localDate = (changes as any).city_local_date;
|
|
}
|
|
|
|
if (changes.amos && typeof changes.amos === "object") {
|
|
const oldAmos = prev?.amos || {};
|
|
const newAmos = changes.amos as AmosData;
|
|
next.amos = {
|
|
...oldAmos,
|
|
...newAmos,
|
|
} as any;
|
|
}
|
|
|
|
// Preserve runwayPlateHistory in next state
|
|
if (prev?.runwayPlateHistory) {
|
|
next.runwayPlateHistory = prev.runwayPlateHistory;
|
|
}
|
|
|
|
// Append new runway observations to history if available in the patch
|
|
const amosChanges = changes.amos as Record<string, any> | undefined;
|
|
const obsTimeVal = obsTime || amosChanges?.observation_time || amosChanges?.observation_time_local;
|
|
const runwayObs = amosChanges?.runway_obs;
|
|
const runwayPoints = Array.isArray(changes.runway_points)
|
|
? changes.runway_points
|
|
: runwayObs
|
|
? runwayPatchPointsFromRunwayObs(runwayObs)
|
|
: [];
|
|
if (runwayPoints.length && obsTimeVal) {
|
|
const history: Record<string, Array<Record<string, unknown>>> = {};
|
|
const sourceHistory = next.runwayPlateHistory || (next.amos as any)?.runway_plate_history || {};
|
|
|
|
// Copy existing history points
|
|
Object.entries(sourceHistory).forEach(([rwy, pts]) => {
|
|
if (Array.isArray(pts)) {
|
|
history[rwy] = [...pts];
|
|
}
|
|
});
|
|
|
|
// Append new points from point_temperatures
|
|
runwayPoints.forEach((pt: any) => {
|
|
const rwy = pt.runway || "";
|
|
if (!rwy) return;
|
|
const tempVal = validNumber(pt.temp) ?? validNumber(pt.target_runway_max) ?? validNumber(pt.tdz_temp) ?? validNumber(pt.end_temp);
|
|
if (tempVal === null) return;
|
|
|
|
const rwyHistory = history[rwy] || [];
|
|
const exists = rwyHistory.some((p: any) => p.timestamp === obsTimeVal || p.time === obsTimeVal || p.observed_at === obsTimeVal);
|
|
if (!exists) {
|
|
rwyHistory.push({
|
|
timestamp: obsTimeVal,
|
|
temp_c: tempVal,
|
|
value: tempVal,
|
|
});
|
|
history[rwy] = rwyHistory.slice(-MAX_OBS_POINTS);
|
|
}
|
|
});
|
|
|
|
next.runwayPlateHistory = history;
|
|
next.amos = {
|
|
...(next.amos || {}),
|
|
runway_obs: {
|
|
...((next.amos as any)?.runway_obs || {}),
|
|
point_temperatures: runwayPoints,
|
|
},
|
|
} as any;
|
|
if (next.amos) {
|
|
(next.amos as any).runway_plate_history = history;
|
|
}
|
|
}
|
|
|
|
if (tempValue !== null) {
|
|
next.airportCurrent = {
|
|
...(next.airportCurrent || {}),
|
|
obs_time: obsTime || next.airportCurrent?.obs_time || null,
|
|
temp: tempValue,
|
|
max_so_far: Math.max(
|
|
tempValue,
|
|
validNumber(next.airportCurrent?.max_so_far) ?? tempValue,
|
|
),
|
|
};
|
|
next.airportPrimary = {
|
|
...(next.airportPrimary || {}),
|
|
obs_time: obsTime || next.airportPrimary?.obs_time || null,
|
|
temp: tempValue,
|
|
max_so_far: Math.max(
|
|
tempValue,
|
|
validNumber(next.airportPrimary?.max_so_far) ?? tempValue,
|
|
),
|
|
source_label: next.airportPrimary?.source_label || source || undefined,
|
|
};
|
|
}
|
|
|
|
if (tempValue !== null && obsTime) {
|
|
const obsPoint: RawObsPoint = [obsTime, tempValue];
|
|
const currentObs = Array.isArray(next.airportPrimaryTodayObs)
|
|
? next.airportPrimaryTodayObs
|
|
: [];
|
|
next.airportPrimaryTodayObs = [...currentObs, obsPoint].slice(-MAX_OBS_POINTS);
|
|
}
|
|
|
|
return next;
|
|
}
|
|
|
|
function parseRunwayHistoryValue(point: Record<string, unknown>) {
|
|
return validNumber(point.max_temp_c) ?? validNumber(point.temp_c) ?? validNumber(point.temp) ?? validNumber(point.value);
|
|
}
|
|
|
|
function parseRunwayHistoryTime(
|
|
point: Record<string, unknown>,
|
|
tzOffset: number,
|
|
localDateStr: string,
|
|
) {
|
|
return getCityLocalUtcTimestamp(
|
|
(point.timestamp as string | number | null | undefined) ??
|
|
(point.time as string | number | null | undefined) ??
|
|
(point.observed_at as string | number | null | undefined),
|
|
tzOffset,
|
|
localDateStr,
|
|
);
|
|
}
|
|
|
|
function buildRunwayHistorySeries(
|
|
row: ScanOpportunityRow | null,
|
|
hourly: HourlyForecast,
|
|
tzOffset: number,
|
|
localDateStr: string,
|
|
minPoints = 2,
|
|
): RunwayHistorySeries[] {
|
|
const directHistory =
|
|
hourly?.runwayPlateHistory ??
|
|
((hourly?.amos as any)?.runway_plate_history as Record<string, Array<Record<string, unknown>>> | undefined) ??
|
|
((row as any)?.runway_plate_history as Record<string, Array<Record<string, unknown>>> | undefined);
|
|
|
|
if (directHistory && typeof directHistory === "object") {
|
|
const directSeries = Object.entries(directHistory)
|
|
.map(([rwy, rawPoints], index) => {
|
|
const normalizedRwy = String(rwy || `RWY ${index + 1}`).trim();
|
|
const points = (Array.isArray(rawPoints) ? rawPoints : [])
|
|
.map((point) => {
|
|
const ts = parseRunwayHistoryTime(point, tzOffset, localDateStr);
|
|
const value = parseRunwayHistoryValue(point);
|
|
return ts !== null && value !== null ? { ts, value } : null;
|
|
})
|
|
.filter((point): point is { ts: number; value: number } => point !== null)
|
|
.sort((a, b) => a.ts - b.ts)
|
|
.slice(-MAX_OBS_POINTS);
|
|
const isSettlement = isSettlementRunway(row, normalizedRwy);
|
|
return {
|
|
key: runwaySeriesKey(normalizedRwy),
|
|
label: `${normalizedRwy}${isSettlement ? (row ? " 结算跑道" : " Settlement") : ""}`,
|
|
rwy: normalizedRwy,
|
|
isSettlement,
|
|
color: isSettlement ? "#009688" : RUNWAY_LINE_COLORS[index % RUNWAY_LINE_COLORS.length],
|
|
points,
|
|
};
|
|
})
|
|
.filter((series) => series.points.length >= minPoints);
|
|
if (directSeries.length) return directSeries;
|
|
}
|
|
|
|
const amos = hourly?.amos;
|
|
const runwayObs = amos?.runway_obs;
|
|
const runwayPairs = runwayObs?.runway_pairs || [];
|
|
const runwayTemps = runwayObs?.temperatures || [];
|
|
const pointTemps = runwayObs?.point_temperatures || [];
|
|
const isAmosTempDewTuple = String(amos?.source || "").toLowerCase() === "amos";
|
|
const anchor =
|
|
getCityLocalUtcTimestamp(amos?.observation_time || amos?.observation_time_local || hourly?.localTime || row?.local_time, tzOffset, localDateStr) ??
|
|
getCityLocalUtcTimestamp(row?.local_time, tzOffset, localDateStr);
|
|
|
|
if (!anchor || !Array.isArray(runwayTemps)) return [];
|
|
|
|
return runwayTemps
|
|
.map((rawTemps, index) => {
|
|
if (!Array.isArray(rawTemps)) return null;
|
|
const rwy = runwayLabelFromPair(runwayPairs[index], index);
|
|
const isSettlement = isSettlementRunway(row, rwy);
|
|
const pointTemp = Array.isArray(pointTemps) ? (pointTemps[index] as any) : null;
|
|
const aggregateRunwayTemp =
|
|
validNumber(pointTemp?.temp) ??
|
|
validNumber(pointTemp?.target_runway_max) ??
|
|
(isAmosTempDewTuple ? runwayTemperatureFromPairTuple(rawTemps) : null);
|
|
const snapshotValues = [
|
|
aggregateRunwayTemp,
|
|
validNumber(pointTemp?.tdz_temp),
|
|
validNumber(pointTemp?.mid_temp),
|
|
validNumber(pointTemp?.end_temp),
|
|
].filter((value): value is number => value !== null);
|
|
const samples = isAmosTempDewTuple
|
|
? []
|
|
: rawTemps.map(validNumber).filter((value): value is number => value !== null);
|
|
const valuesForLine = samples.length > 1
|
|
? samples
|
|
: snapshotValues.length > 1
|
|
? snapshotValues
|
|
: samples.length === 1
|
|
? [samples[0], samples[0]]
|
|
: snapshotValues.length === 1
|
|
? [snapshotValues[0], snapshotValues[0]]
|
|
: [];
|
|
const values = valuesForLine
|
|
.map((value, pointIndex) => {
|
|
const minutesFromEnd = (valuesForLine.length - 1 - pointIndex);
|
|
return {
|
|
ts: anchor - minutesFromEnd * 60 * 1000,
|
|
value,
|
|
};
|
|
})
|
|
.filter((point) => validNumber(point.value) !== null);
|
|
if (values.length < minPoints) return null;
|
|
return {
|
|
key: runwaySeriesKey(rwy),
|
|
label: `${rwy}${isSettlement ? " 结算跑道" : ""}`,
|
|
rwy,
|
|
isSettlement,
|
|
color: isSettlement ? "#009688" : RUNWAY_LINE_COLORS[index % RUNWAY_LINE_COLORS.length],
|
|
points: values.slice(-MAX_OBS_POINTS),
|
|
};
|
|
})
|
|
.filter((series): series is RunwayHistorySeries => series !== null);
|
|
}
|
|
|
|
function generateDailySlots(localDateStr: string, daysCount: number): string[] {
|
|
const parts = localDateStr.split("-");
|
|
if (parts.length !== 3) return [];
|
|
const year = parseInt(parts[0], 10);
|
|
const month = parseInt(parts[1], 10) - 1;
|
|
const day = parseInt(parts[2], 10);
|
|
|
|
const dates: string[] = [];
|
|
for (let i = 0; i < daysCount; i++) {
|
|
const d = new Date(Date.UTC(year, month, day + i));
|
|
const yyyy = d.getUTCFullYear();
|
|
const mm = String(d.getUTCMonth() + 1).padStart(2, "0");
|
|
const dd = String(d.getUTCDate()).padStart(2, "0");
|
|
dates.push(`${yyyy}-${mm}-${dd}`);
|
|
}
|
|
return dates;
|
|
}
|
|
|
|
function formatDailyDateLabel(dateStr: string): string {
|
|
const parts = dateStr.split("-");
|
|
if (parts.length !== 3) return dateStr;
|
|
return `${parts[1]}/${parts[2]}`;
|
|
}
|
|
|
|
function buildDailyChartData(
|
|
row: ScanOpportunityRow | null,
|
|
hourly: HourlyForecast,
|
|
daysCount: number,
|
|
): { data: Array<Record<string, string | number | null>>; series: EvidenceSeries[] } {
|
|
const localDateStr = resolveChartLocalDate(row, hourly);
|
|
const slots = generateDailySlots(localDateStr, daysCount);
|
|
|
|
const series: EvidenceSeries[] = [
|
|
{
|
|
key: "deb_prediction",
|
|
label: "DEB Daily Max",
|
|
source: "DEB",
|
|
color: "#f97316", // orange
|
|
featured: true,
|
|
values: [],
|
|
},
|
|
{
|
|
key: "max_temp",
|
|
label: "Model Daily Max",
|
|
source: "Standard Forecast",
|
|
color: "#dc2626", // red
|
|
dashed: true,
|
|
values: [],
|
|
},
|
|
{
|
|
key: "min_temp",
|
|
label: "Model Daily Min",
|
|
source: "Standard Forecast",
|
|
color: "#2563eb", // blue
|
|
dashed: true,
|
|
values: [],
|
|
},
|
|
];
|
|
|
|
const data = slots.map((dateStr) => {
|
|
const dayForecast = hourly?.forecastDaily?.find((d) => d.date === dateStr);
|
|
const dayMultiModel = hourly?.multiModelDaily?.[dateStr];
|
|
|
|
const label = formatDailyDateLabel(dateStr);
|
|
|
|
const debMax = validNumber(dayMultiModel?.deb?.prediction) ??
|
|
(dateStr === localDateStr ? validNumber(hourly?.debPrediction) ?? validNumber(row?.deb_prediction) : null);
|
|
const maxTemp = validNumber(dayForecast?.max_temp);
|
|
const minTemp = validNumber(dayForecast?.min_temp);
|
|
|
|
return {
|
|
label,
|
|
date: dateStr,
|
|
deb_prediction: debMax,
|
|
max_temp: maxTemp,
|
|
min_temp: minTemp,
|
|
};
|
|
});
|
|
|
|
// Populate series values
|
|
series[0].values = data.map((d) => d.deb_prediction);
|
|
series[1].values = data.map((d) => d.max_temp);
|
|
series[2].values = data.map((d) => d.min_temp);
|
|
|
|
// Filter out series that have no valid data points
|
|
const activeSeries = series.filter((s) => s.values.some((v) => v !== null));
|
|
|
|
return { data, series: activeSeries };
|
|
}
|
|
|
|
function binBandObservationsToSlots(
|
|
slots: number[],
|
|
obs: TemperatureBandPoint[],
|
|
): Array<[number, number] | null> {
|
|
const result: Array<[number, number] | null> = new Array(slots.length).fill(null);
|
|
for (const point of obs) {
|
|
for (let i = slots.length - 1; i >= 0; i--) {
|
|
if (point.ts >= slots[i]) {
|
|
result[i] = [point.low, point.high];
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
return result;
|
|
}
|
|
|
|
function sortedTimeline(timestamps: Iterable<number>) {
|
|
return Array.from(new Set(Array.from(timestamps).filter((ts) => Number.isFinite(ts)))).sort((a, b) => a - b);
|
|
}
|
|
|
|
function resolveFullDayFallbackAnchor(
|
|
row: ScanOpportunityRow | null,
|
|
hourly: HourlyForecast,
|
|
tzOffsetSeconds: number,
|
|
localDateStr: string,
|
|
) {
|
|
return (
|
|
getCityLocalUtcTimestamp(hourly?.localTime || row?.local_time, tzOffsetSeconds, localDateStr) ??
|
|
Date.UTC(
|
|
Number(localDateStr.slice(0, 4)) || new Date().getUTCFullYear(),
|
|
(Number(localDateStr.slice(5, 7)) || 1) - 1,
|
|
Number(localDateStr.slice(8, 10)) || new Date().getUTCDate(),
|
|
12,
|
|
0,
|
|
0,
|
|
)
|
|
);
|
|
}
|
|
|
|
function ensureRenderableTimeline(timeline: number[], fallbackAnchor: number) {
|
|
if (timeline.length >= 2) return timeline;
|
|
const anchor = timeline[0] ?? fallbackAnchor;
|
|
return [anchor - 30 * 60 * 1000, anchor];
|
|
}
|
|
|
|
function buildTimelineIndex(timeline: number[]) {
|
|
return new Map(timeline.map((ts, index) => [ts, index]));
|
|
}
|
|
|
|
function valuesAtTimeline(
|
|
size: number,
|
|
indexByTs: Map<number, number>,
|
|
obs: Array<{ ts: number; value: number }>,
|
|
) {
|
|
const result: Array<number | null> = new Array(size).fill(null);
|
|
obs.forEach((point) => {
|
|
const idx = indexByTs.get(point.ts);
|
|
if (idx !== undefined) result[idx] = point.value;
|
|
});
|
|
return result;
|
|
}
|
|
|
|
function bandValuesAtTimeline(
|
|
size: number,
|
|
indexByTs: Map<number, number>,
|
|
obs: TemperatureBandPoint[],
|
|
) {
|
|
const result: Array<[number, number] | null> = new Array(size).fill(null);
|
|
obs.forEach((point) => {
|
|
const idx = indexByTs.get(point.ts);
|
|
if (idx !== undefined) result[idx] = [point.low, point.high];
|
|
});
|
|
return result;
|
|
}
|
|
|
|
function valuesForHourlyTimes(
|
|
size: number,
|
|
indexByTs: Map<number, number>,
|
|
times: string[] | undefined,
|
|
values: Array<number | null | undefined>,
|
|
tzOffsetSeconds: number,
|
|
localDateStr: string,
|
|
bounds: LocalDayBounds | null = null,
|
|
) {
|
|
const result: Array<number | null> = new Array(size).fill(null);
|
|
(times || []).forEach((time, index) => {
|
|
const ts = getCityLocalUtcTimestamp(time, tzOffsetSeconds, localDateStr);
|
|
if (!isWithinLocalDay(ts, bounds)) return;
|
|
if (ts === null) return;
|
|
const value = validNumber(values[index]);
|
|
if (value === null) return;
|
|
const idx = indexByTs.get(ts);
|
|
if (idx !== undefined) result[idx] = value;
|
|
});
|
|
return result;
|
|
}
|
|
|
|
function addHourlyTimesToTimeline(
|
|
timeline: Set<number>,
|
|
times: string[] | undefined,
|
|
values: Array<number | null | undefined> | undefined,
|
|
tzOffsetSeconds: number,
|
|
localDateStr: string,
|
|
bounds: LocalDayBounds | null = null,
|
|
) {
|
|
if (!times?.length || !values?.length) return;
|
|
times.forEach((time, index) => {
|
|
if (validNumber(values[index]) === null) return;
|
|
const ts = getCityLocalUtcTimestamp(time, tzOffsetSeconds, localDateStr);
|
|
if (ts !== null && isWithinLocalDay(ts, bounds)) timeline.add(ts);
|
|
});
|
|
}
|
|
|
|
function probabilityBucketValue(bucket: ProbabilityBucket) {
|
|
return validNumber(bucket.value ?? (bucket as any).temp ?? (bucket as any).temperature);
|
|
}
|
|
|
|
function probabilityBucketProbability(bucket: ProbabilityBucket) {
|
|
const raw = validNumber(bucket.probability ?? (bucket as any).model_probability);
|
|
if (raw === null) return null;
|
|
return raw > 1 ? raw / 100 : raw;
|
|
}
|
|
|
|
function probabilityBucketRange(bucket: ProbabilityBucket, value: number) {
|
|
const rawRange = String(bucket.range || bucket.bucket || "").trim();
|
|
const rangeMatch = rawRange.match(/(-?\d+(?:\.\d+)?)\s*~\s*(-?\d+(?:\.\d+)?)/);
|
|
if (rangeMatch) {
|
|
const lower = Number(rangeMatch[1]);
|
|
const upper = Number(rangeMatch[2]);
|
|
if (Number.isFinite(lower) && Number.isFinite(upper) && upper > lower) {
|
|
return { lower, upper };
|
|
}
|
|
}
|
|
return {
|
|
lower: Number((value - 0.5).toFixed(2)),
|
|
upper: Number((value + 0.5).toFixed(2)),
|
|
};
|
|
}
|
|
|
|
function buildLegacyGaussianProbabilityOverlay(
|
|
row: ScanOpportunityRow | null,
|
|
hourly: HourlyForecast,
|
|
): ProbabilityOverlay | null {
|
|
const source = hourly?.probabilities || null;
|
|
const rowBuckets = ((row as any)?.distribution_full || (row as any)?.distribution_preview || []) as ProbabilityBucket[];
|
|
const buckets = (
|
|
source?.distribution_all?.length
|
|
? source.distribution_all
|
|
: source?.distribution?.length
|
|
? source.distribution
|
|
: rowBuckets
|
|
) || [];
|
|
|
|
const engine = source?.engine || row?.probability_engine || (buckets.length ? "legacy" : null);
|
|
if (engine && String(engine).toLowerCase() !== "legacy") return null;
|
|
|
|
const tempSymbol = row?.temp_symbol || "°C";
|
|
const bands = buckets
|
|
.map((bucket, index) => {
|
|
const value = probabilityBucketValue(bucket);
|
|
const probability = probabilityBucketProbability(bucket);
|
|
if (value === null || probability === null || probability <= 0) return null;
|
|
const { lower, upper } = probabilityBucketRange(bucket, value);
|
|
return {
|
|
key: `legacy_probability_${value}_${index}`,
|
|
value,
|
|
lower,
|
|
upper,
|
|
probability,
|
|
label: `${value}${tempSymbol} ${Math.round(probability * 100)}%`,
|
|
opacity: Number(Math.min(0.16, Math.max(0.035, 0.04 + probability * 0.22)).toFixed(3)),
|
|
};
|
|
})
|
|
.filter((band): band is ProbabilityTemperatureBand => band !== null)
|
|
.sort((a, b) => a.value - b.value);
|
|
|
|
const mu = validNumber(source?.mu);
|
|
const muLine = mu === null
|
|
? null
|
|
: {
|
|
value: mu,
|
|
label: `Gaussian μ ${mu.toFixed(1)}${tempSymbol}`,
|
|
};
|
|
|
|
if (!bands.length && !muLine) return null;
|
|
return {
|
|
engine: engine || "legacy",
|
|
muLine,
|
|
bands,
|
|
};
|
|
}
|
|
|
|
function buildFullDayChartData(
|
|
row: ScanOpportunityRow | null,
|
|
hourly: HourlyForecast,
|
|
isEn: boolean,
|
|
): { data: Array<Record<string, any>>; series: EvidenceSeries[]; probabilityOverlay: ProbabilityOverlay | null } {
|
|
const tzOffset = row?.tz_offset_seconds ?? 0;
|
|
const localDateStr = resolveChartLocalDate(row, hourly);
|
|
const localDayBounds = getLocalDayBounds(localDateStr);
|
|
|
|
const settlementObs = filterTimelinePointsToLocalDay(
|
|
normObs(hourly?.settlementTodayObs || row?.settlement_today_obs || row?.metar_context?.settlement_today_obs, tzOffset, MAX_OBS_POINTS, localDateStr),
|
|
localDayBounds,
|
|
);
|
|
const metarObs = filterTimelinePointsToLocalDay(
|
|
normObs(hourly?.metarTodayObs || row?.metar_today_obs || row?.metar_context?.today_obs || row?.metar_recent_obs || row?.metar_context?.recent_obs, tzOffset, MAX_OBS_POINTS, localDateStr),
|
|
localDayBounds,
|
|
);
|
|
const madisObs = filterTimelinePointsToLocalDay(
|
|
normObs(
|
|
appendLatestAirportObservation(hourly?.airportPrimaryTodayObs, hourly?.airportPrimary, hourly?.airportCurrent),
|
|
tzOffset,
|
|
MAX_OBS_POINTS,
|
|
localDateStr,
|
|
),
|
|
localDayBounds,
|
|
);
|
|
const runwayHistorySeries = filterRunwayHistoryToLocalDay(
|
|
buildRunwayHistorySeries(row, hourly, tzOffset, localDateStr),
|
|
localDayBounds,
|
|
);
|
|
|
|
const settlementCityKey = normalizeCityKey(row?.city);
|
|
const isShenzhen = settlementCityKey === 'shenzhen';
|
|
const isHKO = (settlementCityKey === 'hongkong' || settlementCityKey === 'laufaushan'
|
|
|| (row?.city || '').toLowerCase().includes('hong kong')
|
|
|| (row?.city || '').toLowerCase().includes('lau fau shan')) && !isShenzhen;
|
|
|
|
let finalSettlementObs = settlementObs;
|
|
let finalMadisObs = madisObs;
|
|
if (isHKO) {
|
|
finalSettlementObs = madisObs;
|
|
finalMadisObs = settlementObs;
|
|
} else if (isShenzhen && !settlementObs.length && madisObs.length) {
|
|
finalSettlementObs = madisObs;
|
|
finalMadisObs = [];
|
|
}
|
|
|
|
// ── Runway band & max series ──
|
|
const normBandObs: TemperatureBandPoint[] = (hourly?.runwayBandHistory || []).map((pt) => {
|
|
try {
|
|
const ts = getCityLocalUtcTimestamp(pt.time, tzOffset, localDateStr);
|
|
if (ts === null) return null;
|
|
return {
|
|
ts,
|
|
high: pt.high_temp,
|
|
low: pt.low_temp,
|
|
avg: pt.avg_temp
|
|
};
|
|
} catch {
|
|
return null;
|
|
}
|
|
}).filter((v): v is NonNullable<typeof v> => v !== null && isWithinLocalDay(v.ts, localDayBounds));
|
|
|
|
const isHKOCity = settlementCityKey === 'hongkong' || settlementCityKey === 'laufaushan'
|
|
|| settlementCityKey === 'shenzhen' || (row?.city || '').toLowerCase().includes('hong kong')
|
|
|| (row?.city || '').toLowerCase().includes('lau fau shan');
|
|
const isAmscSource =
|
|
(hourly?.airportPrimary as any)?.source === "amsc_awos" ||
|
|
String(hourly?.airportPrimary?.source_label || "").toLowerCase().includes("amsc");
|
|
const isKoreanAmosSource =
|
|
(settlementCityKey === "seoul" || settlementCityKey === "busan") &&
|
|
(
|
|
String(
|
|
(hourly?.airportPrimary as any)?.source ||
|
|
hourly?.airportPrimary?.source_code ||
|
|
hourly?.airportPrimary?.source_label ||
|
|
hourly?.amos?.source ||
|
|
"",
|
|
).toLowerCase().includes("amos") ||
|
|
Boolean(hourly?.amos?.runway_obs)
|
|
);
|
|
const isRunwaySensorAggregateSource = isAmscSource || isKoreanAmosSource;
|
|
const shouldRenderMetar = metarObs.length > 0 && !observationSetContains(finalMadisObs, metarObs);
|
|
|
|
const timelineSet = new Set<number>();
|
|
runwayHistorySeries.forEach((rhs) => rhs.points.forEach((point) => timelineSet.add(point.ts)));
|
|
normBandObs.forEach((point) => timelineSet.add(point.ts));
|
|
finalSettlementObs.forEach((point) => timelineSet.add(point.ts));
|
|
if (!isRunwaySensorAggregateSource) finalMadisObs.forEach((point) => timelineSet.add(point.ts));
|
|
if (shouldRenderMetar) metarObs.forEach((point) => timelineSet.add(point.ts));
|
|
|
|
let debPath: ReturnType<typeof buildDebBaselinePath> | null = null;
|
|
if (hourly?.times?.length && hourly?.temps?.length) {
|
|
debPath = buildDebBaselinePath(
|
|
hourly.times,
|
|
hourly.temps,
|
|
validNumber(hourly?.debPrediction) ?? row?.deb_prediction,
|
|
hourly.localTime || row?.local_time,
|
|
hourly.forecastTodayHigh,
|
|
);
|
|
addHourlyTimesToTimeline(timelineSet, hourly.times, debPath.debTemps, tzOffset, localDateStr, localDayBounds);
|
|
}
|
|
if (hourly?.times?.length && hourly?.modelCurves) {
|
|
Object.values(hourly.modelCurves).forEach((modelTemps) => {
|
|
addHourlyTimesToTimeline(timelineSet, hourly.times, modelTemps, tzOffset, localDateStr, localDayBounds);
|
|
});
|
|
}
|
|
|
|
const fallbackAnchor = resolveFullDayFallbackAnchor(row, hourly, tzOffset, localDateStr);
|
|
const timeline = ensureRenderableTimeline(sortedTimeline(timelineSet), fallbackAnchor);
|
|
const n = timeline.length;
|
|
const indexByTs = buildTimelineIndex(timeline);
|
|
const series: EvidenceSeries[] = [];
|
|
|
|
// ── Runway history series ──
|
|
runwayHistorySeries.forEach((rhs) => {
|
|
const values = valuesAtTimeline(n, indexByTs, rhs.points);
|
|
if (!values.some((v) => v !== null)) return;
|
|
series.push({
|
|
key: rhs.key,
|
|
label: rhs.label,
|
|
source: "",
|
|
color: rhs.color,
|
|
featured: rhs.isSettlement,
|
|
dashed: !rhs.isSettlement,
|
|
curve: "monotone",
|
|
showDot: rhs.isSettlement,
|
|
values,
|
|
});
|
|
});
|
|
|
|
const bandVals = bandValuesAtTimeline(n, indexByTs, normBandObs);
|
|
const maxVals = bandVals.map((val) => val ? val[1] : null);
|
|
if (maxVals.some((v) => v !== null)) {
|
|
series.push({
|
|
key: "runway_max",
|
|
label: isEn ? "Runway Max" : "跑道最高温",
|
|
source: "Runway Max",
|
|
color: "#009688",
|
|
featured: true,
|
|
values: maxVals,
|
|
});
|
|
}
|
|
|
|
// ── Settlement observations ──
|
|
if (finalSettlementObs.length) {
|
|
const svals = valuesAtTimeline(n, indexByTs, finalSettlementObs);
|
|
if (svals.some((v) => v !== null)) {
|
|
series.push({
|
|
key: "settlement",
|
|
label: isHKO ? "CoWIN 6087" : (isHKOCity ? "HKO" : (hourly?.settlementStationLabel || row?.metar_context?.station_label || row?.metar_context?.station || "Settlement")),
|
|
source: isHKO ? "cowin_obs" : (row?.metar_context?.station || row?.airport || "Settlement"),
|
|
color: "#009688",
|
|
featured: true,
|
|
values: svals,
|
|
});
|
|
}
|
|
}
|
|
|
|
// ── Airport Primary (MADIS / AMSC AWOS) ──
|
|
// Skip this series for AMSC AWOS cities — their data is redundant with
|
|
// runway sensor data and adds a confusing "AMSC AWOS" label to the chart.
|
|
if (finalMadisObs.length && !isRunwaySensorAggregateSource) {
|
|
const madisVals = valuesAtTimeline(n, indexByTs, finalMadisObs);
|
|
if (madisVals.some((v) => v !== null)) {
|
|
series.push({
|
|
key: "madis",
|
|
label: isHKO ? "HKO" : (hourly?.airportPrimary?.source_label || "NOAA MADIS"),
|
|
source: isHKO ? "HKO" : (hourly?.airportPrimary?.station_code || row?.airport || "MADIS"),
|
|
color: "#0284c7",
|
|
dashed: isHKO ? true : false,
|
|
values: madisVals,
|
|
});
|
|
}
|
|
}
|
|
|
|
if (shouldRenderMetar) {
|
|
const mvals = valuesAtTimeline(n, indexByTs, metarObs);
|
|
if (mvals.some((v) => v !== null)) {
|
|
series.push({
|
|
key: "metar",
|
|
label: isHKO ? "VHHH METAR" : (isHKOCity ? "HKO" : (row?.metar_context?.station_label || "METAR")),
|
|
source: row?.airport || "METAR",
|
|
color: "#0ea5e9",
|
|
dashed: true,
|
|
curve: "stepAfter",
|
|
showDot: true,
|
|
values: mvals,
|
|
});
|
|
}
|
|
}
|
|
|
|
// ── DEB forecast curve ──
|
|
if (hourly?.times?.length && debPath?.debTemps.length) {
|
|
const debVals = valuesForHourlyTimes(n, indexByTs, hourly.times, debPath.debTemps, tzOffset, localDateStr, localDayBounds);
|
|
if (debVals.some((v) => v !== null)) {
|
|
series.push({
|
|
key: "hourly_forecast",
|
|
label: "DEB Forecast",
|
|
source: "DEB Hourly",
|
|
color: "#f97316",
|
|
featured: true,
|
|
smooth: true,
|
|
values: debVals,
|
|
});
|
|
}
|
|
|
|
// Per-model curves
|
|
if (hourly.modelCurves) {
|
|
const modelColors = ["#2563eb", "#7c3aed", "#059669", "#d97706", "#dc2626", "#0891b2"];
|
|
Object.keys(hourly.modelCurves).forEach((model, idx) => {
|
|
const modelTemps = hourly.modelCurves![model];
|
|
if (!modelTemps?.length) return;
|
|
const vals = valuesForHourlyTimes(n, indexByTs, hourly.times, modelTemps, tzOffset, localDateStr, localDayBounds);
|
|
if (vals.some((v) => v !== null)) {
|
|
series.push({
|
|
key: `model_curve_${model}`,
|
|
label: model,
|
|
source: "Multi-model hourly",
|
|
color: modelColors[idx % modelColors.length],
|
|
dashed: true,
|
|
smooth: true,
|
|
values: vals,
|
|
});
|
|
}
|
|
});
|
|
}
|
|
}
|
|
|
|
// ── Fallback ──
|
|
if (!hasRenderableLineSeries(series)) {
|
|
const fb =
|
|
validNumber(hourly?.airportCurrent?.temp) ??
|
|
validNumber(hourly?.airportPrimary?.temp) ??
|
|
latestObservationValue(finalMadisObs) ??
|
|
latestObservationValue(finalSettlementObs) ??
|
|
latestObservationValue(metarObs) ??
|
|
validNumber(row?.current_temp) ??
|
|
validNumber(hourly?.debPrediction) ??
|
|
validNumber(row?.deb_prediction) ??
|
|
validNumber(row?.target_threshold);
|
|
if (fb !== null) {
|
|
series.push({
|
|
key: "current",
|
|
label: "Current reference",
|
|
source: row?.metar_context?.source || "Live",
|
|
color: "#009688",
|
|
featured: true,
|
|
values: Array.from({ length: n }, () => fb),
|
|
});
|
|
}
|
|
}
|
|
|
|
// ── Build data rows ──
|
|
const data = timeline.map((ts, i) => {
|
|
const point: Record<string, any> = {
|
|
label: formatTimestamp(ts),
|
|
ts,
|
|
runway_band: bandVals[i] ?? null,
|
|
};
|
|
series.forEach((s) => { point[s.key] = s.values[i] ?? null; });
|
|
return point;
|
|
});
|
|
|
|
const probabilityOverlay = buildLegacyGaussianProbabilityOverlay(row, hourly);
|
|
|
|
return { data, series, probabilityOverlay };
|
|
}
|
|
|
|
// ── Model summary cards (daily high point predictions) ─────────────────
|
|
|
|
function buildModelSummaryCards(row: ScanOpportunityRow | null): EvidenceSeries[] {
|
|
return Object.entries(row?.model_cluster_sources || {})
|
|
.map(([label, value]) => [label, validNumber(value)] as const)
|
|
.filter((entry): entry is readonly [string, number] => entry[1] !== null)
|
|
.slice(0, 4)
|
|
.map(([label, value], index) => ({
|
|
key: `model_summary_${index}`,
|
|
label,
|
|
source: "Multi-model daily high",
|
|
color: ["#2563eb", "#14b8a6", "#7c3aed", "#64748b"][index] || "#64748b",
|
|
dashed: true,
|
|
values: [value],
|
|
}));
|
|
}
|
|
|
|
// ── Integer-degree ticks for Y-axis ──────────────────────────────────
|
|
|
|
function probabilityOverlayValues(probabilityOverlay?: ProbabilityOverlay | null) {
|
|
if (!probabilityOverlay) return [];
|
|
return [
|
|
...(probabilityOverlay.muLine ? [probabilityOverlay.muLine.value] : []),
|
|
...probabilityOverlay.bands.flatMap((band) => [band.lower, band.upper]),
|
|
];
|
|
}
|
|
|
|
function buildIntDegreeTicks(
|
|
series: EvidenceSeries[],
|
|
data?: Array<Record<string, string | number | null>>,
|
|
probabilityOverlay?: ProbabilityOverlay | null,
|
|
): number[] | null {
|
|
const vals = data?.length
|
|
? data.flatMap((point) => series.map((s) => point[s.key])).filter((v): v is number => validNumber(v) !== null)
|
|
: series.flatMap((s) => s.values).filter((v): v is number => validNumber(v) !== null);
|
|
const overlayVals = probabilityOverlayValues(probabilityOverlay);
|
|
const allVals = [...vals, ...overlayVals];
|
|
if (!allVals.length) return null;
|
|
const min = Math.floor(Math.min(...allVals));
|
|
const max = Math.ceil(Math.max(...allVals));
|
|
const ticks: number[] = [];
|
|
for (let d = min; d <= max; d++) ticks.push(d);
|
|
return ticks.length > 0 ? ticks : null;
|
|
}
|
|
|
|
function buildChartDomain(
|
|
series: EvidenceSeries[],
|
|
data?: Array<Record<string, string | number | null>>,
|
|
probabilityOverlay?: ProbabilityOverlay | null,
|
|
): [number, number] | ["auto", "auto"] {
|
|
const vals = data?.length
|
|
? data.flatMap((point) => series.map((s) => point[s.key])).filter((v): v is number => validNumber(v) !== null)
|
|
: series.flatMap((s) => s.values).filter((v): v is number => validNumber(v) !== null);
|
|
const overlayVals = probabilityOverlayValues(probabilityOverlay);
|
|
const allVals = [...vals, ...overlayVals];
|
|
if (!allVals.length) return ["auto", "auto"];
|
|
const min = Math.min(...allVals);
|
|
const max = Math.max(...allVals);
|
|
const span = Math.max(1, max - min);
|
|
const pad = Math.max(0.5, span * 0.08);
|
|
return [Number((min - pad).toFixed(1)), Number((max + pad).toFixed(1))];
|
|
}
|
|
|
|
function isLiveObservationSeries(series: EvidenceSeries) {
|
|
if (series.key === "hourly_forecast") return false;
|
|
if (series.key.startsWith("model_curve_")) return false;
|
|
if (series.key.startsWith("model_summary_")) return false;
|
|
if (["deb_prediction", "max_temp", "min_temp"].includes(series.key)) return false;
|
|
|
|
const source = String(series.source || "").toLowerCase();
|
|
if (source.includes("forecast") || source.includes("multi-model") || source === "deb") return false;
|
|
return true;
|
|
}
|
|
|
|
function latestLiveObservationTimestamp(
|
|
data: Array<Record<string, any>>,
|
|
series: EvidenceSeries[],
|
|
) {
|
|
let latest: number | null = null;
|
|
series.filter(isLiveObservationSeries).forEach((item) => {
|
|
item.values.forEach((value, index) => {
|
|
if (validNumber(value) === null) return;
|
|
const ts = typeof data[index]?.ts === "number" ? data[index].ts : null;
|
|
if (ts === null) return;
|
|
latest = latest === null ? ts : Math.max(latest, ts);
|
|
});
|
|
});
|
|
return latest;
|
|
}
|
|
|
|
function chartDeltaForCelsius(row: ScanOpportunityRow | null, deltaC: number) {
|
|
const symbol = String(row?.temp_symbol || "").toUpperCase();
|
|
return symbol.includes("F") ? deltaC * 1.8 : deltaC;
|
|
}
|
|
|
|
function getLiveObservationPoints(
|
|
data: Array<Record<string, any>>,
|
|
series: EvidenceSeries[],
|
|
) {
|
|
const liveSeries = series.filter(isLiveObservationSeries);
|
|
const points: Array<{ ts: number; temp: number }> = [];
|
|
data.forEach((row, index) => {
|
|
const ts = typeof row?.ts === "number" ? row.ts : null;
|
|
if (ts === null) return;
|
|
const values = liveSeries
|
|
.map((item) => validNumber(item.values[index]))
|
|
.filter((value): value is number => value !== null);
|
|
if (!values.length) return;
|
|
points.push({ ts, temp: Math.max(...values) });
|
|
});
|
|
return points.sort((left, right) => left.ts - right.ts);
|
|
}
|
|
|
|
function pointAtOrBefore(
|
|
points: Array<{ ts: number; temp: number }>,
|
|
targetTs: number,
|
|
): { ts: number; temp: number } | null {
|
|
let match: { ts: number; temp: number } | null = null;
|
|
for (const point of points) {
|
|
if (point.ts <= targetTs) match = point;
|
|
}
|
|
return match;
|
|
}
|
|
|
|
function getPeakGlowState(
|
|
row: ScanOpportunityRow | null,
|
|
data: Array<Record<string, any>>,
|
|
series: EvidenceSeries[],
|
|
): PeakGlowMeta {
|
|
const empty: PeakGlowMeta = {
|
|
state: "none",
|
|
currentTemp: null,
|
|
referenceHigh: null,
|
|
distanceToHigh: null,
|
|
trend30m: null,
|
|
trend60m: null,
|
|
observedHigh: null,
|
|
};
|
|
const livePoints = getLiveObservationPoints(data, series);
|
|
const latest = livePoints[livePoints.length - 1] || null;
|
|
if (!latest) return empty;
|
|
|
|
const previousLivePoints = livePoints.filter((point) => point.ts < latest.ts);
|
|
const previousHigh = previousLivePoints.length
|
|
? Math.max(...previousLivePoints.map((point) => point.temp))
|
|
: null;
|
|
const liveHigh = Math.max(...livePoints.map((point) => point.temp));
|
|
const rowHigh = validNumber(
|
|
row?.current_max_so_far ??
|
|
row?.metar_context?.airport_max_so_far ??
|
|
row?.metar_context?.max_temp,
|
|
);
|
|
const observedHigh = rowHigh !== null ? Math.max(liveHigh, rowHigh) : liveHigh;
|
|
const trend30Base = pointAtOrBefore(livePoints, latest.ts - 30 * 60 * 1000);
|
|
const trend60Base = pointAtOrBefore(livePoints, latest.ts - 60 * 60 * 1000);
|
|
const trend30m = trend30Base ? latest.temp - trend30Base.temp : null;
|
|
const trend60m = trend60Base ? latest.temp - trend60Base.temp : null;
|
|
const distanceToHigh = observedHigh - latest.temp;
|
|
|
|
const metaBase = {
|
|
currentTemp: latest.temp,
|
|
referenceHigh: observedHigh,
|
|
distanceToHigh,
|
|
trend30m,
|
|
trend60m,
|
|
observedHigh,
|
|
};
|
|
|
|
const hotWindowRange = getDebPeakWindowRange(data, series);
|
|
const hotWindowStart =
|
|
hotWindowRange ? validNumber(data[hotWindowRange[0]]?.ts) : null;
|
|
if (hotWindowStart !== null && latest.ts < hotWindowStart) {
|
|
return { state: "none", ...metaBase };
|
|
}
|
|
|
|
const nearThreshold = chartDeltaForCelsius(row, 0.5);
|
|
const watchThreshold = chartDeltaForCelsius(row, 1);
|
|
const flatTrendFloor = -chartDeltaForCelsius(row, 0.2);
|
|
const coolingDrop = -chartDeltaForCelsius(row, 0.5);
|
|
const breakoutStep = chartDeltaForCelsius(row, 0.1);
|
|
const isCooling =
|
|
distanceToHigh >= Math.abs(coolingDrop) &&
|
|
((trend60m !== null && trend60m <= coolingDrop) ||
|
|
(previousHigh !== null && latest.temp <= previousHigh + coolingDrop));
|
|
if (isCooling) return { state: "cooling", ...metaBase };
|
|
|
|
const isBreakout =
|
|
previousHigh !== null &&
|
|
latest.temp > previousHigh + breakoutStep;
|
|
if (isBreakout) return { state: "breakout", ...metaBase };
|
|
|
|
if (
|
|
distanceToHigh <= nearThreshold &&
|
|
(trend30m === null || trend30m >= flatTrendFloor)
|
|
) {
|
|
return { state: "near_peak", ...metaBase };
|
|
}
|
|
|
|
if (distanceToHigh <= watchThreshold) {
|
|
return { state: "watch", ...metaBase };
|
|
}
|
|
|
|
return { state: "none", ...metaBase };
|
|
}
|
|
|
|
function getDebPeakWindowRange(
|
|
data: Array<Record<string, any>>,
|
|
series: EvidenceSeries[],
|
|
): [number, number] | null {
|
|
const debSeries = series.find((item) => item.key === "hourly_forecast");
|
|
if (!debSeries || data.length < 2) return null;
|
|
|
|
const debPoints = debSeries.values
|
|
.map((value, index) => {
|
|
const ts = typeof data[index]?.ts === "number" ? data[index].ts : null;
|
|
const temp = validNumber(value);
|
|
return ts === null || temp === null ? null : { index, ts, temp };
|
|
})
|
|
.filter((point): point is { index: number; ts: number; temp: number } => point !== null);
|
|
|
|
if (debPoints.length < 2) return null;
|
|
|
|
const peak = debPoints.reduce((best, point) => (point.temp > best.temp ? point : best), debPoints[0]);
|
|
const peakPointIndex = debPoints.findIndex((point) => point.index === peak.index);
|
|
if (peakPointIndex < 0) return null;
|
|
|
|
const hotThreshold = peak.temp - 2;
|
|
let hotStartPoint = peakPointIndex;
|
|
let hotEndPoint = peakPointIndex;
|
|
while (hotStartPoint > 0 && debPoints[hotStartPoint - 1].temp >= hotThreshold) {
|
|
hotStartPoint -= 1;
|
|
}
|
|
while (hotEndPoint < debPoints.length - 1 && debPoints[hotEndPoint + 1].temp >= hotThreshold) {
|
|
hotEndPoint += 1;
|
|
}
|
|
|
|
const hour = 60 * 60 * 1000;
|
|
const targetSpan = 8 * hour;
|
|
const minSpan = 6 * hour;
|
|
const maxSpan = 12 * hour;
|
|
const firstTs = data.find((point) => typeof point.ts === "number")?.ts;
|
|
const lastTs = [...data].reverse().find((point) => typeof point.ts === "number")?.ts;
|
|
if (typeof firstTs !== "number" || typeof lastTs !== "number" || lastTs <= firstTs) return null;
|
|
|
|
let startTs = debPoints[hotStartPoint].ts - 1.5 * hour;
|
|
let endTs = debPoints[hotEndPoint].ts + 2 * hour;
|
|
const centerTs = peak.ts;
|
|
const latestObsTs = latestLiveObservationTimestamp(data, series);
|
|
|
|
if (endTs - startTs < targetSpan) {
|
|
startTs = centerTs - targetSpan / 2;
|
|
endTs = centerTs + targetSpan / 2;
|
|
}
|
|
if (endTs - startTs > maxSpan) {
|
|
startTs = centerTs - maxSpan / 2;
|
|
endTs = centerTs + maxSpan / 2;
|
|
}
|
|
if (latestObsTs !== null && latestObsTs > endTs && latestObsTs > debPoints[hotEndPoint].ts) {
|
|
endTs = Math.min(lastTs, latestObsTs);
|
|
if (endTs - startTs > maxSpan) {
|
|
startTs = Math.max(firstTs, endTs - maxSpan);
|
|
}
|
|
}
|
|
|
|
if (startTs < firstTs) {
|
|
endTs = Math.min(lastTs, endTs + firstTs - startTs);
|
|
startTs = firstTs;
|
|
}
|
|
if (endTs > lastTs) {
|
|
startTs = Math.max(firstTs, startTs - (endTs - lastTs));
|
|
endTs = lastTs;
|
|
}
|
|
if (endTs - startTs < minSpan && lastTs - firstTs >= minSpan) {
|
|
const missing = minSpan - (endTs - startTs);
|
|
startTs = Math.max(firstTs, startTs - missing / 2);
|
|
endTs = Math.min(lastTs, endTs + missing / 2);
|
|
}
|
|
|
|
const startIndex = data.findIndex((point) => typeof point.ts === "number" && point.ts >= startTs);
|
|
let endIndex = -1;
|
|
for (let index = data.length - 1; index >= 0; index -= 1) {
|
|
if (typeof data[index]?.ts === "number" && data[index].ts <= endTs) {
|
|
endIndex = index;
|
|
break;
|
|
}
|
|
}
|
|
|
|
return startIndex >= 0 && endIndex > startIndex ? [startIndex, endIndex] : null;
|
|
}
|
|
|
|
function binObservationsToSlots(
|
|
slots: number[],
|
|
obs: Array<{ ts: number; value: number }>,
|
|
): Array<number | null> {
|
|
const result: Array<number | null> = new Array(slots.length).fill(null);
|
|
for (const point of obs) {
|
|
for (let i = slots.length - 1; i >= 0; i--) {
|
|
if (point.ts >= slots[i]) {
|
|
result[i] = point.value;
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
return result;
|
|
}
|
|
|
|
export {
|
|
MAX_HOURLY_DETAIL_CONCURRENT_REQUESTS,
|
|
HOURLY_CACHE_TTL_MS,
|
|
_hourlyCache,
|
|
__resetHourlyDetailRequestQueueForTest,
|
|
__runQueuedHourlyDetailRequestForTest,
|
|
buildChartDomain,
|
|
buildFullDayChartData,
|
|
getDebPeakWindowRange,
|
|
getPeakGlowState,
|
|
buildIntDegreeTicks,
|
|
buildModelSummaryCards,
|
|
buildRunwayPlates,
|
|
fetchHourlyForecastForCity,
|
|
getActiveTemperatureSeries,
|
|
getLiveObservationLabels,
|
|
getObservationDisplayMetrics,
|
|
getVisibleTemperatureSeries,
|
|
isTemperatureSeriesVisibleByDefault,
|
|
mergePatchIntoHourly,
|
|
normObs,
|
|
normalizeCityKey,
|
|
prefersHighFrequencyRunwayResolution,
|
|
readSessionCache,
|
|
selectDisplayRunwayTemp,
|
|
seedHourlyForecastFromRow,
|
|
seriesStats,
|
|
shouldPollLiveChart,
|
|
validNumber,
|
|
};
|
|
|
|
export type { EvidenceSeries, HourlyForecast, PeakGlowMeta, PeakGlowState, ProbabilityOverlay };
|