2569718930@qq.com
1470 lines
54 KiB
TypeScript
1470 lines
54 KiB
TypeScript
"use client";
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import clsx from "clsx";
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import { useEffect, useMemo, useState } from "react";
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import {
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Brush,
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CartesianGrid,
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Line,
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LineChart as ReLineChart,
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ReferenceLine,
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ResponsiveContainer,
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Tooltip,
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XAxis,
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YAxis,
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} from "recharts";
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import type {
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AmosData,
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AirportCurrentConditions,
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CityDetail,
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ScanOpportunityRow,
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ForecastDay,
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DailyModelForecast,
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} from "@/lib/dashboard-types";
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import { buildDebBaselinePath } from "@/lib/temperature-chart-paths";
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import { DASHBOARD_REFRESH_POLICY_MS } from "@/lib/refresh-policy";
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import { Panel } from "@/components/dashboard/scan-terminal/Panel";
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import { rowName, temp } from "@/components/dashboard/scan-terminal/utils";
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const ROLLING_WINDOW_BEFORE_MS = 12 * 60 * 60 * 1000;
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const ROLLING_WINDOW_AFTER_LIVE_MS = 2 * 60 * 60 * 1000;
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const ROLLING_WINDOW_AFTER_FORECAST_MS = 8 * 60 * 60 * 1000;
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const SETTLEMENT_RUNWAY_PAIRS: Record<string, Array<[string, string]>> = {
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shanghai: [["17L", "35R"]],
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beijing: [["01", "19"]],
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guangzhou: [["02L", "20R"]],
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chengdu: [["02L", "20R"]],
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chongqing: [["02L", "20R"]],
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wuhan: [["04", "22"]],
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seoul: [["15R", "33L"]],
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};
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function normalizeRunwayLabel(value?: string | null) {
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return String(value || "").trim().toUpperCase().replace(/\s+/g, "");
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}
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function normalizeCityKey(value?: string | null) {
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return String(value || "").trim().toLowerCase().replace(/[\s_-]+/g, "");
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}
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function pairKey(pair: [string, string]) {
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return pair.map(normalizeRunwayLabel).sort().join("/");
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}
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function runwaySeriesKey(rwy: string) {
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return `runway_${String(rwy || "unknown")
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.split("/")
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.map(normalizeRunwayLabel)
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.filter(Boolean)
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.join("_")}`;
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}
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function isTemperatureSeriesVisibleByDefault(city: string, seriesKey: string) {
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if (seriesKey.startsWith("model_curve_")) {
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return normalizeCityKey(city) === "paris" && seriesKey === "model_curve_AROME HD";
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}
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return true;
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}
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function buildRunwayPlates(
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amos: AmosData | null | undefined,
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row: ScanOpportunityRow | null,
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settlementObs?: Array<{ ts: number; value: number }>,
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) {
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if (!amos) return [];
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const runwayObs = amos.runway_obs || {};
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const runwayPairs = runwayObs.runway_pairs || [];
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const runwayTemps = runwayObs.temperatures || [];
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const pointTemps = runwayObs.point_temperatures || [];
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const cityKey = normalizeCityKey(row?.city);
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const settlementPairs = SETTLEMENT_RUNWAY_PAIRS[cityKey] || [];
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const settlementKeys = new Set(settlementPairs.map(pairKey));
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const list: Array<{
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rwy: string;
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isSettlement: boolean;
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tdzTemp: number | null;
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midTemp: number | null;
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endTemp: number | null;
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maxTemp: number | null;
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dailyHigh: number | null;
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trend_15m: number | null;
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}> = [];
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runwayPairs.forEach((rawPair: any, index: number) => {
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const pair = rawPair as [string, string];
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if (!Array.isArray(pair) || pair.length < 2) return;
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const isSettlement = settlementKeys.has(pairKey(pair));
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const tdz = validNumber(pointTemps[index]?.tdz_temp);
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const mid = validNumber(pointTemps[index]?.mid_temp);
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const end = validNumber(pointTemps[index]?.end_temp);
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const historyVals = Array.isArray(runwayTemps[index])
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? (runwayTemps[index] as Array<number | null>).map(validNumber).filter((v): v is number => v !== null)
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: [];
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const tdzVal = tdz !== null ? [tdz] : [];
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const midVal = mid !== null ? [mid] : [];
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const endVal = end !== null ? [end] : [];
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const allVals = [...historyVals, ...tdzVal, ...midVal, ...endVal];
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const maxTemp = allVals.length ? Math.max(...allVals) : null;
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const dailyHigh = historyVals.length ? Math.max(...historyVals) : maxTemp;
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// Calculate 15-minute trend
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const latest = historyVals.length > 0 ? historyVals[historyVals.length - 1] : (tdz ?? mid ?? end ?? null);
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const val15 = historyVals.length > 15 ? historyVals[historyVals.length - 16] : (historyVals.length > 0 ? historyVals[0] : null);
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let trend_15m = (latest !== null && val15 !== null) ? latest - val15 : null;
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if (isSettlement && settlementObs && settlementObs.length >= 2) {
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const latestObs = settlementObs[settlementObs.length - 1];
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const targetTs = latestObs.ts - 15 * 60 * 1000;
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let closestPoint = settlementObs[0];
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let minDiff = Math.abs(closestPoint.ts - targetTs);
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for (let i = 1; i < settlementObs.length; i++) {
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const diff = Math.abs(settlementObs[i].ts - targetTs);
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if (diff < minDiff) {
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minDiff = diff;
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closestPoint = settlementObs[i];
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}
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}
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if (Math.abs(closestPoint.ts - targetTs) < 5 * 60 * 1000) {
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trend_15m = latestObs.value - closestPoint.value;
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}
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}
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list.push({
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rwy: `${normalizeRunwayLabel(pair[0])}/${normalizeRunwayLabel(pair[1])}`,
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isSettlement,
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tdzTemp: tdz,
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midTemp: mid,
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endTemp: end,
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maxTemp,
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dailyHigh,
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trend_15m,
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});
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});
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return list;
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}
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type ObsPoint = { time?: string | null; temp?: number | null };
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type EvidenceSeries = {
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key: string;
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label: string;
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source: string;
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color: string;
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dashed?: boolean;
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featured?: boolean;
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smooth?: boolean;
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curve?: "linear" | "monotone" | "stepAfter";
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connectNulls?: boolean;
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showDot?: boolean;
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values: Array<number | null>;
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};
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type RunwayHistorySeries = {
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key: string;
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label: string;
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rwy: string;
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isSettlement: boolean;
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color: string;
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points: Array<{ ts: number; value: number }>;
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};
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const MAX_OBS_POINTS = 1440;
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const HOURLY_CACHE_TTL_MS = DASHBOARD_REFRESH_POLICY_MS.model;
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const FULL_DAY_SLOT_MINUTES = 30;
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const FULL_DAY_SLOTS = 48;
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const SLOT_INTERVAL_MS = FULL_DAY_SLOT_MINUTES * 60 * 1000;
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const _hourlyCache = new Map<string, { ts: number; data: HourlyForecast }>();
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const RUNWAY_LINE_COLORS = ["#00897b", "#d97706", "#7c3aed", "#0891b2", "#ea580c", "#64748b"];
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function validNumber(value: unknown): number | null {
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return typeof value === "number" && Number.isFinite(value) ? value : null;
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}
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function getCityLocalUtcTimestamp(
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value: string | number | null | undefined,
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tzOffsetSeconds: number,
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referenceLocalDate?: string | null
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): number | null {
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if (value == null) return null;
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if (typeof value === "number") {
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const d = new Date(value + tzOffsetSeconds * 1000);
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return Date.UTC(
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d.getUTCFullYear(),
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d.getUTCMonth(),
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d.getUTCDate(),
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d.getUTCHours(),
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d.getUTCMinutes()
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);
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}
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const raw = String(value).trim();
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if (!raw) return null;
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if (raw.includes("T") || raw.includes("Z") || raw.includes("-")) {
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const d = new Date(raw);
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if (!Number.isNaN(d.getTime())) {
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const localMs = d.getTime() + tzOffsetSeconds * 1000;
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const localDate = new Date(localMs);
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return Date.UTC(
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localDate.getUTCFullYear(),
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localDate.getUTCMonth(),
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localDate.getUTCDate(),
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localDate.getUTCHours(),
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localDate.getUTCMinutes()
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);
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}
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}
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const m = raw.match(/(\d{1,2}):(\d{2})/);
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if (m) {
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const h = +m[1];
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const min = +m[2];
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let year = new Date().getUTCFullYear();
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let month = new Date().getUTCMonth();
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let date = new Date().getUTCDate();
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if (referenceLocalDate) {
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const dateParts = referenceLocalDate.split("-");
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if (dateParts.length === 3) {
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year = parseInt(dateParts[0]);
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month = parseInt(dateParts[1]) - 1;
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date = parseInt(dateParts[2]);
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}
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}
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return Date.UTC(year, month, date, h, min);
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}
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return null;
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}
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function formatTimestamp(ts: number): string {
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const d = new Date(ts);
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return `${String(d.getUTCHours()).padStart(2, "0")}:${String(d.getUTCMinutes()).padStart(2, "0")}`;
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}
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function normObs(points: ObsPoint[] | null | undefined, tzOffsetSeconds: number, limit = MAX_OBS_POINTS) {
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return (points || [])
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.filter((p) => validNumber(p.temp) !== null && p.time)
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.map((p) => ({
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ts: getCityLocalUtcTimestamp(p.time, tzOffsetSeconds)!,
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value: Number(p.temp),
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}))
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.filter((p) => p.ts !== null)
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.slice(-limit);
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}
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function seriesStats(values: Array<number | null>) {
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const nums = values.filter((v): v is number => validNumber(v) !== null);
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const latest = nums.length ? nums[nums.length - 1] : null;
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const high = nums.length ? Math.max(...nums) : null;
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const first15 = nums.length > 1 ? nums[Math.max(0, nums.length - 15)] : null;
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const delta15 = latest !== null && first15 !== null ? latest - first15 : null;
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return { latest, high, delta15 };
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}
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function isSettlementRunway(row: ScanOpportunityRow | null, rwy: string) {
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const cityKey = normalizeCityKey(row?.city);
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const settlementPairs = SETTLEMENT_RUNWAY_PAIRS[cityKey] || [];
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if (!settlementPairs.length) return false;
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const normalized = rwy
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.split("/")
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.map(normalizeRunwayLabel)
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.filter(Boolean)
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.sort()
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.join("/");
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return settlementPairs.some((pair) => pairKey(pair) === normalized);
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}
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function runwayLabelFromPair(rawPair: unknown, index: number) {
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if (Array.isArray(rawPair) && rawPair.length >= 2) {
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return `${normalizeRunwayLabel(rawPair[0])}/${normalizeRunwayLabel(rawPair[1])}`;
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}
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return `RWY ${index + 1}`;
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}
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type HourlyForecast = {
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forecastTodayHigh?: number | null;
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localTime?: string | null;
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times: string[];
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temps: Array<number | null>;
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modelCurves?: Record<string, Array<number | null>>;
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runwayPlateHistory?: Record<string, Array<Record<string, unknown>>>;
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amos?: AmosData | null;
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airportCurrent?: AirportCurrentConditions | null;
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airportPrimary?: AirportCurrentConditions | null;
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forecastDaily?: ForecastDay[];
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multiModelDaily?: Record<string, DailyModelForecast>;
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settlementTodayObs?: ObsPoint[];
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metarTodayObs?: ObsPoint[];
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} | null;
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function parseRunwayHistoryValue(point: Record<string, unknown>) {
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return validNumber(point.max_temp_c) ?? validNumber(point.temp_c) ?? validNumber(point.temp) ?? validNumber(point.value);
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}
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function parseRunwayHistoryTime(
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point: Record<string, unknown>,
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tzOffset: number,
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localDateStr: string,
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) {
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return getCityLocalUtcTimestamp(
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(point.timestamp as string | number | null | undefined) ??
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(point.time as string | number | null | undefined) ??
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(point.observed_at as string | number | null | undefined),
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tzOffset,
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localDateStr,
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);
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}
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function buildRunwayHistorySeries(
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row: ScanOpportunityRow | null,
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hourly: HourlyForecast,
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tzOffset: number,
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localDateStr: string,
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): RunwayHistorySeries[] {
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const directHistory =
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hourly?.runwayPlateHistory ??
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((hourly?.amos as any)?.runway_plate_history as Record<string, Array<Record<string, unknown>>> | undefined) ??
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((row as any)?.runway_plate_history as Record<string, Array<Record<string, unknown>>> | undefined);
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if (directHistory && typeof directHistory === "object") {
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return Object.entries(directHistory)
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.map(([rwy, rawPoints], index) => {
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const normalizedRwy = String(rwy || `RWY ${index + 1}`).trim();
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const points = (Array.isArray(rawPoints) ? rawPoints : [])
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.map((point) => {
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const ts = parseRunwayHistoryTime(point, tzOffset, localDateStr);
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const value = parseRunwayHistoryValue(point);
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return ts !== null && value !== null ? { ts, value } : null;
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})
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.filter((point): point is { ts: number; value: number } => point !== null)
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.sort((a, b) => a.ts - b.ts)
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.slice(-MAX_OBS_POINTS);
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const isSettlement = isSettlementRunway(row, normalizedRwy);
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return {
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key: runwaySeriesKey(normalizedRwy),
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label: `${normalizedRwy}${isSettlement ? (row ? " 结算跑道" : " Settlement") : ""}`,
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rwy: normalizedRwy,
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isSettlement,
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color: isSettlement ? "#009688" : RUNWAY_LINE_COLORS[index % RUNWAY_LINE_COLORS.length],
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points,
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};
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})
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.filter((series) => series.points.length > 1);
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}
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const amos = hourly?.amos;
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const runwayObs = amos?.runway_obs;
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const runwayPairs = runwayObs?.runway_pairs || [];
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const runwayTemps = runwayObs?.temperatures || [];
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const anchor =
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getCityLocalUtcTimestamp(amos?.observation_time_local || amos?.observation_time || hourly?.localTime || row?.local_time, tzOffset, localDateStr) ??
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getCityLocalUtcTimestamp(row?.local_time, tzOffset, localDateStr);
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if (!anchor || !Array.isArray(runwayTemps)) return [];
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return runwayTemps
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.map((rawTemps, index) => {
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if (!Array.isArray(rawTemps) || rawTemps.length <= 2) return null;
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const rwy = runwayLabelFromPair(runwayPairs[index], index);
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const isSettlement = isSettlementRunway(row, rwy);
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const values = rawTemps
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.map(validNumber)
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.map((value, pointIndex) => {
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if (value === null) return null;
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const minutesFromEnd = rawTemps.length - 1 - pointIndex;
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return {
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ts: anchor - minutesFromEnd * 60 * 1000,
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value,
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};
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})
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.filter((point): point is { ts: number; value: number } => point !== null);
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if (values.length <= 1) return null;
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return {
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key: runwaySeriesKey(rwy),
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label: `${rwy}${isSettlement ? " 结算跑道" : ""}`,
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rwy,
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isSettlement,
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color: isSettlement ? "#009688" : RUNWAY_LINE_COLORS[index % RUNWAY_LINE_COLORS.length],
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points: values.slice(-MAX_OBS_POINTS),
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};
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})
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.filter((series): series is RunwayHistorySeries => series !== null);
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}
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function generate3DaySlots(localDateStr: string): number[] {
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const parts = localDateStr.split("-");
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if (parts.length !== 3) return [];
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const year = parseInt(parts[0], 10);
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const month = parseInt(parts[1], 10) - 1;
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const day = parseInt(parts[2], 10);
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const slots: number[] = [];
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// Generate 72 hours starting from local date 00:00
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for (let h = 0; h < 72; h++) {
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slots.push(Date.UTC(year, month, day, h, 0));
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}
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return slots;
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}
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function format3DayTimestamp(ts: number): string {
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const d = new Date(ts);
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const mm = String(d.getUTCMonth() + 1).padStart(2, "0");
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const dd = String(d.getUTCDate()).padStart(2, "0");
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const hh = String(d.getUTCHours()).padStart(2, "0");
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return `${mm}/${dd} ${hh}:00`;
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}
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function build3DayChartData(
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row: ScanOpportunityRow | null,
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hourly: HourlyForecast,
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): { data: Array<Record<string, string | number | null>>; series: EvidenceSeries[] } {
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const tzOffset = row?.tz_offset_seconds ?? 0;
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const localDateStr = row?.local_date || new Date().toISOString().slice(0, 10);
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const slots = generate3DaySlots(localDateStr);
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if (!slots.length) return { data: [], series: [] };
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const n = slots.length;
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const series: EvidenceSeries[] = [];
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const na = (): Array<number | null> => new Array(n).fill(null);
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// DEB forecast curve (from hourly.times & hourly.temps)
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if (hourly?.times?.length && hourly?.temps?.length) {
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const debVals = na();
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hourly.times.forEach((t, i) => {
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const ts = getCityLocalUtcTimestamp(t, tzOffset, localDateStr);
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if (ts === null) return;
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const slotIdx = slots.findIndex((s) => s === ts);
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if (slotIdx >= 0) {
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debVals[slotIdx] = validNumber(hourly.temps[i]);
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}
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});
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if (debVals.some((v) => v !== null)) {
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series.push({
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key: "hourly_forecast",
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label: "DEB Forecast",
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source: "DEB Hourly",
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color: "#f97316",
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featured: true,
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smooth: true,
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values: debVals,
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});
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}
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// Per-model curves
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if (hourly.modelCurves) {
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const modelColors = ["#2563eb", "#7c3aed", "#059669", "#d97706", "#dc2626", "#0891b2"];
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Object.keys(hourly.modelCurves).forEach((model, idx) => {
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const modelTemps = hourly.modelCurves![model];
|
|
if (!modelTemps?.length) return;
|
|
const vals = na();
|
|
hourly.times.forEach((t, i) => {
|
|
const ts = getCityLocalUtcTimestamp(t, tzOffset, localDateStr);
|
|
if (ts === null) return;
|
|
const slotIdx = slots.findIndex((s) => s === ts);
|
|
if (slotIdx >= 0 && i < modelTemps.length) {
|
|
vals[slotIdx] = validNumber(modelTemps[i]);
|
|
}
|
|
});
|
|
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,
|
|
});
|
|
}
|
|
});
|
|
}
|
|
}
|
|
|
|
// Historical METAR observations (past timestamps of the 3 days)
|
|
const metarObs = normObs(
|
|
row?.metar_today_obs || row?.metar_context?.today_obs || row?.metar_recent_obs || row?.metar_context?.recent_obs,
|
|
tzOffset
|
|
);
|
|
if (metarObs.length) {
|
|
const mvals = binObservationsToSlots(slots, metarObs);
|
|
if (mvals.some((v) => v !== null)) {
|
|
series.push({
|
|
key: "metar",
|
|
label: "METAR",
|
|
source: row?.airport || "METAR",
|
|
color: "#0ea5e9",
|
|
dashed: true,
|
|
values: mvals,
|
|
});
|
|
}
|
|
}
|
|
|
|
// Build data rows
|
|
const data = slots.map((ts, i) => {
|
|
const point: Record<string, string | number | null> = {
|
|
label: format3DayTimestamp(ts),
|
|
ts,
|
|
};
|
|
series.forEach((s) => {
|
|
point[s.key] = s.values[i] ?? null;
|
|
});
|
|
return point;
|
|
});
|
|
|
|
return { data, series };
|
|
}
|
|
|
|
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 = row?.local_date || new Date().toISOString().slice(0, 10);
|
|
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(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 buildFullDayChartData(
|
|
row: ScanOpportunityRow | null,
|
|
hourly: HourlyForecast,
|
|
): { data: Array<Record<string, string | number | null>>; series: EvidenceSeries[] } {
|
|
const tzOffset = row?.tz_offset_seconds ?? 0;
|
|
const localDateStr = row?.local_date || new Date().toISOString().slice(0, 10);
|
|
|
|
const settlementObs = normObs(hourly?.settlementTodayObs || row?.settlement_today_obs || row?.metar_context?.settlement_today_obs, tzOffset);
|
|
const metarObs = normObs(hourly?.metarTodayObs || row?.metar_today_obs || row?.metar_context?.today_obs || row?.metar_recent_obs || row?.metar_context?.recent_obs, tzOffset);
|
|
const runwayHistorySeries = buildRunwayHistorySeries(row, hourly, tzOffset, localDateStr);
|
|
|
|
const slots = generateFullDaySlots(localDateStr);
|
|
if (!slots.length) return { data: [], series: [] };
|
|
const slotLabels = slots.map(formatTimestamp);
|
|
const n = slots.length;
|
|
|
|
const series: EvidenceSeries[] = [];
|
|
const na = (): Array<number | null> => new Array(n).fill(null);
|
|
|
|
// ── Runway history series ──
|
|
runwayHistorySeries.forEach((rhs) => {
|
|
const binned = binObservationsToSlots(slots, rhs.points);
|
|
if (!binned.some((v) => v !== null)) return;
|
|
series.push({
|
|
key: rhs.key,
|
|
label: rhs.label,
|
|
source: "AMOS/AMSC",
|
|
color: rhs.color,
|
|
featured: rhs.isSettlement,
|
|
dashed: !rhs.isSettlement,
|
|
values: binned,
|
|
});
|
|
});
|
|
|
|
// ── Settlement observations ──
|
|
if (settlementObs.length) {
|
|
const svals = binObservationsToSlots(slots, settlementObs);
|
|
if (svals.some((v) => v !== null)) {
|
|
series.push({
|
|
key: "settlement",
|
|
label: row?.metar_context?.station_label || row?.metar_context?.station || "Settlement",
|
|
source: row?.metar_context?.station || row?.airport || "Settlement",
|
|
color: "#009688",
|
|
featured: true,
|
|
values: svals,
|
|
});
|
|
}
|
|
}
|
|
|
|
// ── METAR ──
|
|
if (metarObs.length) {
|
|
const mvals = binObservationsToSlots(slots, metarObs);
|
|
if (mvals.some((v) => v !== null)) {
|
|
series.push({
|
|
key: "metar",
|
|
label: row?.metar_context?.station_label || "METAR",
|
|
source: row?.airport || "METAR",
|
|
color: "#0ea5e9",
|
|
dashed: true,
|
|
values: mvals,
|
|
});
|
|
}
|
|
}
|
|
|
|
// ── DEB forecast curve ──
|
|
if (hourly?.times?.length && hourly?.temps?.length) {
|
|
const debPath = buildDebBaselinePath(
|
|
hourly.times,
|
|
hourly.temps,
|
|
row?.deb_prediction,
|
|
hourly.localTime || row?.local_time,
|
|
hourly.forecastTodayHigh,
|
|
);
|
|
const debVals = na();
|
|
hourly.times.forEach((t, i) => {
|
|
const ts = getCityLocalUtcTimestamp(t, tzOffset, localDateStr);
|
|
if (ts === null) return;
|
|
const slotIdx = slots.findIndex((s) => s === ts);
|
|
if (slotIdx >= 0 && i < debPath.debTemps.length) {
|
|
debVals[slotIdx] = validNumber(debPath.debTemps[i]);
|
|
}
|
|
});
|
|
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 = na();
|
|
hourly.times.forEach((t, i) => {
|
|
const ts = getCityLocalUtcTimestamp(t, tzOffset, localDateStr);
|
|
if (ts === null) return;
|
|
const slotIdx = slots.findIndex((s) => s === ts);
|
|
if (slotIdx >= 0 && i < modelTemps.length) vals[slotIdx] = validNumber(modelTemps[i]);
|
|
});
|
|
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 (!series.length) {
|
|
const fb = validNumber(row?.current_temp) ?? 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 = slots.map((ts, i) => {
|
|
const point: Record<string, string | number | null> = {
|
|
label: formatTimestamp(ts),
|
|
ts,
|
|
};
|
|
series.forEach((s) => { point[s.key] = s.values[i] ?? null; });
|
|
return point;
|
|
});
|
|
|
|
return { data, series };
|
|
}
|
|
|
|
// ── 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 buildIntDegreeTicks(series: EvidenceSeries[], data?: Array<Record<string, string | number | 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);
|
|
if (!vals.length) return null;
|
|
const min = Math.floor(Math.min(...vals));
|
|
const max = Math.ceil(Math.max(...vals));
|
|
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>>,
|
|
): [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);
|
|
if (!vals.length) return ["auto", "auto"];
|
|
const min = Math.min(...vals);
|
|
const max = Math.max(...vals);
|
|
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 generateFullDaySlots(localDateStr: string): number[] {
|
|
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 slots: number[] = [];
|
|
for (let h = 0; h < 24; h++) {
|
|
for (let m = 0; m < 60; m += FULL_DAY_SLOT_MINUTES) {
|
|
slots.push(Date.UTC(year, month, day, h, m));
|
|
}
|
|
}
|
|
return slots;
|
|
}
|
|
|
|
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;
|
|
}
|
|
|
|
// ── Main component ─────────────────────────────────────────────────────
|
|
|
|
export function LiveTemperatureThresholdChart({
|
|
isEn,
|
|
row,
|
|
allRows = [],
|
|
compact = false,
|
|
onSearchClick,
|
|
onMaximize,
|
|
onClose,
|
|
isMaximized = false,
|
|
disableClose = false,
|
|
}: {
|
|
isEn: boolean;
|
|
row: ScanOpportunityRow | null;
|
|
allRows?: ScanOpportunityRow[];
|
|
compact?: boolean;
|
|
onSearchClick?: () => void;
|
|
onMaximize?: () => void;
|
|
onClose?: () => void;
|
|
isMaximized?: boolean;
|
|
disableClose?: boolean;
|
|
}) {
|
|
const [hourly, setHourly] = useState<HourlyForecast>(null);
|
|
const city = String(row?.city || "").toLowerCase().trim();
|
|
const [timeframe, setTimeframe] = useState<"1D" | "3D">("1D");
|
|
const [userToggledKeys, setUserToggledKeys] = useState<Record<string, boolean>>({});
|
|
|
|
useEffect(() => {
|
|
setUserToggledKeys({});
|
|
}, [city, timeframe]);
|
|
|
|
useEffect(() => {
|
|
if (!city) return;
|
|
const cached = _hourlyCache.get(city);
|
|
if (cached && Date.now() - cached.ts < HOURLY_CACHE_TTL_MS) {
|
|
setHourly(cached.data);
|
|
return;
|
|
}
|
|
let cancelled = false;
|
|
fetch(`/api/city/${encodeURIComponent(city)}/detail?depth=full&force_refresh=false`, {
|
|
cache: "no-store",
|
|
headers: { Accept: "application/json" },
|
|
})
|
|
.then(async (res) => {
|
|
if (!res.ok) return null;
|
|
return res.json() as Promise<CityDetail>;
|
|
})
|
|
.then((json) => {
|
|
const hourlySource = (json as any)?.hourly ?? (json as any)?.timeseries?.hourly;
|
|
if (cancelled || !json || !hourlySource) return;
|
|
const data: HourlyForecast = {
|
|
forecastTodayHigh: json.forecast?.today_high ?? 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,
|
|
amos: json.amos || null,
|
|
airportCurrent: json.airport_current || null,
|
|
airportPrimary: json.airport_primary || null,
|
|
forecastDaily: json.forecast?.daily || [],
|
|
multiModelDaily: json.multi_model_daily || {},
|
|
settlementTodayObs: (json as any).timeseries?.settlement_today_obs || (json as any)?.settlement_today_obs || undefined,
|
|
metarTodayObs: (json as any).timeseries?.metar_today_obs || (json as any)?.metar_today_obs || undefined,
|
|
};
|
|
_hourlyCache.set(city, { ts: Date.now(), data });
|
|
setHourly(data);
|
|
})
|
|
.catch(() => {});
|
|
return () => { cancelled = true; };
|
|
}, [city]);
|
|
|
|
const { data, series } = useMemo(() => {
|
|
if (timeframe === "3D") {
|
|
return build3DayChartData(row, hourly);
|
|
}
|
|
return buildFullDayChartData(row, hourly);
|
|
}, [row, hourly, timeframe]);
|
|
|
|
const tzOffset = row?.tz_offset_seconds ?? 0;
|
|
const settlementObs = useMemo(() => {
|
|
let obs = normObs(hourly?.settlementTodayObs || row?.settlement_today_obs || row?.metar_context?.settlement_today_obs, tzOffset);
|
|
if (!obs.length && !hourly?.runwayPlateHistory) {
|
|
const mObs = normObs(hourly?.metarTodayObs || row?.metar_today_obs || row?.metar_context?.today_obs, tzOffset);
|
|
if (mObs.length > 0) {
|
|
obs = mObs;
|
|
}
|
|
}
|
|
return obs;
|
|
}, [row, hourly, tzOffset]);
|
|
|
|
const runwayPlates = useMemo(() => buildRunwayPlates(hourly?.amos, row, settlementObs), [hourly?.amos, row, settlementObs]);
|
|
const hasRunwayData = runwayPlates.length > 0;
|
|
const settlementPlate = useMemo(() => runwayPlates.find((p) => p.isSettlement), [runwayPlates]);
|
|
|
|
const chartSeries = useMemo(() => {
|
|
return series;
|
|
}, [series]);
|
|
|
|
const isSeriesVisible = (sKey: string) => {
|
|
if (userToggledKeys[sKey] !== undefined) {
|
|
return userToggledKeys[sKey];
|
|
}
|
|
return isTemperatureSeriesVisibleByDefault(city, sKey);
|
|
};
|
|
|
|
const activeSeries = useMemo(() => {
|
|
return chartSeries.filter((s) => isSeriesVisible(s.key));
|
|
}, [chartSeries, userToggledKeys, city]);
|
|
|
|
const cityKey = String(row?.city || "").toLowerCase().trim();
|
|
const runwaySensorCities = new Set([
|
|
'beijing', 'shanghai', 'guangzhou', 'shenzhen', 'qingdao',
|
|
'chengdu', 'chongqing', 'wuhan', // AMSC runway sensors
|
|
'seoul', 'busan', // AMOS runway sensors
|
|
]);
|
|
const isHKO = cityKey === 'hong kong' || cityKey === 'lau fau shan' || cityKey.includes('hongkong') || cityKey.includes('laufau');
|
|
const isTokyo = cityKey === 'tokyo';
|
|
const isSingapore = cityKey === 'singapore';
|
|
const isParis = cityKey === 'paris';
|
|
const isWeatherStation = !runwaySensorCities.has(cityKey)
|
|
&& !isHKO && !isTokyo && !isSingapore && !isParis;
|
|
|
|
const runwayHeaderLabel = 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)'
|
|
: isWeatherStation ? '气象站实测'
|
|
: '跑道实测 (1分钟)';
|
|
|
|
const metarHeaderLabel = isHKO ? '天文台实测 (10分钟)'
|
|
: 'METAR 结算 (30分钟)';
|
|
|
|
const runwayHighLabel = isHKO ? '参考站点'
|
|
: isTokyo ? '机场气象站'
|
|
: isSingapore ? '航站楼'
|
|
: isParis ? '官方机场观测'
|
|
: isWeatherStation ? '气象站'
|
|
: '跑道实测';
|
|
|
|
const metarHighLabel = isHKO ? '天文台'
|
|
: 'METAR 官方';
|
|
|
|
const currentRunwayTemp = validNumber(hourly?.amos?.temp_c) ?? validNumber(row?.current_temp) ?? settlementPlate?.maxTemp ?? null;
|
|
const observedHighMetar = validNumber(row?.metar_context?.airport_max_so_far ?? row?.metar_context?.max_temp ?? row?.current_max_so_far) ?? null;
|
|
const observedHighRunway = validNumber(row?.current_max_so_far) ?? settlementPlate?.maxTemp ?? currentRunwayTemp ?? null;
|
|
const wundergroundDailyHigh = validNumber(hourly?.airportCurrent?.max_so_far ?? hourly?.airportPrimary?.max_so_far) ?? null;
|
|
|
|
const modelValues = Object.values(row?.model_cluster_sources || {})
|
|
.map(validNumber)
|
|
.filter((v): v is number => v !== null);
|
|
const modelMin = modelValues.length ? Math.min(...modelValues) : (row?.cluster_core_low ?? null);
|
|
const modelMax = modelValues.length ? Math.max(...modelValues) : (row?.cluster_core_high ?? null);
|
|
const debVal = validNumber(row?.deb_prediction) ?? null;
|
|
|
|
const spread = (modelMax !== null && modelMin !== null) ? modelMax - modelMin : null;
|
|
const spreadLabel = spread === null ? "" : (spread <= 2.0 ? "低分歧" : (spread <= 4.0 ? "中等分歧" : "高分歧"));
|
|
const spreadLabelEn = spread === null ? "" : (spread <= 2.0 ? "Low" : (spread <= 4.0 ? "Medium" : "High"));
|
|
|
|
const formattedUpdateTime = useMemo(() => {
|
|
if (row?.local_date && row?.local_time) {
|
|
return `${row.local_date} ${row.local_time.slice(0, 8)}`;
|
|
}
|
|
const d = new Date();
|
|
return d.toISOString().replace('T', ' ').slice(0, 19);
|
|
}, [row]);
|
|
|
|
const cityThresholds = useMemo(() => {
|
|
if (!row || !allRows || !allRows.length) return [];
|
|
const cityKey = String(row.city || "").toLowerCase().trim();
|
|
const sameCityRows = allRows.filter(
|
|
(r) => String(r.city || "").toLowerCase().trim() === cityKey
|
|
);
|
|
|
|
const seen = new Set<number>();
|
|
const list: { threshold: number; label: string; isBreached: boolean; kind: "gte" | "lte" }[] = [];
|
|
sameCityRows.forEach((r) => {
|
|
const t = Number(r.target_threshold ?? r.target_value ?? r.target_lower ?? r.target_upper);
|
|
if (!Number.isFinite(t) || seen.has(t)) return;
|
|
seen.add(t);
|
|
|
|
const maxTemp = Number(r.current_max_so_far ?? r.current_temp ?? 0);
|
|
const q = String(r.market_question || r.target_label || "").toLowerCase();
|
|
const kind: "gte" | "lte" = q.includes("below") || q.includes("under") || q.includes("lte") ? "lte" : "gte";
|
|
const isBreached = kind === "lte" ? maxTemp > t : maxTemp >= t;
|
|
|
|
list.push({
|
|
threshold: t,
|
|
label: r.target_label || `${t}°C`,
|
|
isBreached,
|
|
kind,
|
|
});
|
|
});
|
|
|
|
return list.sort((a, b) => a.threshold - b.threshold);
|
|
}, [row, allRows]);
|
|
|
|
const intDegreeTicks = useMemo(() => buildIntDegreeTicks(series, data), [series, data]);
|
|
const chartDomain = useMemo(
|
|
() => buildChartDomain(series, data),
|
|
[series, data],
|
|
);
|
|
|
|
const subtitle = row
|
|
? isEn
|
|
? timeframe === "1D"
|
|
? "Live & Forecast"
|
|
: `${timeframe} Forecast`
|
|
: timeframe === "1D"
|
|
? "实测与预测"
|
|
: `${timeframe}预报`
|
|
: "";
|
|
|
|
const panelTitle = row ? (
|
|
<div className="flex items-center gap-1">
|
|
<button
|
|
type="button"
|
|
onClick={onSearchClick}
|
|
className={clsx(
|
|
"flex items-center gap-1.5 px-1.5 py-0.5 rounded text-left transition-colors font-bold text-slate-800 outline-none select-none",
|
|
onSearchClick ? "hover:bg-slate-200/80 cursor-pointer" : ""
|
|
)}
|
|
>
|
|
<span>{rowName(row)}</span>
|
|
{onSearchClick && <span className="text-[8px] text-slate-400">▼</span>}
|
|
</button>
|
|
<span className="text-slate-400 font-normal">·</span>
|
|
<span className="text-slate-500 font-normal">{subtitle}</span>
|
|
</div>
|
|
) : isEn ? (
|
|
"Temperature Chart"
|
|
) : (
|
|
"气温图表"
|
|
);
|
|
|
|
const timeframeActions = (
|
|
<div className="flex items-center gap-1.5">
|
|
<div className="flex items-center gap-1 rounded bg-[#eef2f6] p-0.5 border border-slate-200">
|
|
{(["1D", "3D"] as const).map((tf) => (
|
|
<button
|
|
key={tf}
|
|
type="button"
|
|
onClick={() => setTimeframe(tf)}
|
|
className={clsx(
|
|
"px-2 py-0.5 text-[9px] font-bold rounded transition-all",
|
|
timeframe === tf
|
|
? "bg-white text-blue-600 shadow-sm border border-slate-200/50"
|
|
: "text-slate-500 hover:text-slate-800"
|
|
)}
|
|
>
|
|
{tf}
|
|
</button>
|
|
))}
|
|
</div>
|
|
|
|
{(onMaximize || onClose) && (
|
|
<div className="flex items-center gap-1">
|
|
{onMaximize && (
|
|
<button
|
|
type="button"
|
|
onClick={(e) => {
|
|
e.stopPropagation();
|
|
onMaximize();
|
|
}}
|
|
className="grid h-6 w-6 place-items-center rounded bg-white hover:bg-slate-50 border border-slate-200 text-slate-500 hover:text-slate-800 transition-colors shadow-sm"
|
|
title={isMaximized ? (isEn ? "Restore Grid" : "还原网格") : (isEn ? "Maximize" : "最大化")}
|
|
>
|
|
{isMaximized ? "❐" : "⛶"}
|
|
</button>
|
|
)}
|
|
{onClose && (
|
|
<button
|
|
type="button"
|
|
disabled={disableClose}
|
|
onClick={(e) => {
|
|
e.stopPropagation();
|
|
onClose();
|
|
}}
|
|
className={clsx(
|
|
"grid h-6 w-6 place-items-center rounded border transition-colors shadow-sm",
|
|
disableClose
|
|
? "bg-slate-50 text-slate-300 border-slate-100 cursor-not-allowed"
|
|
: "bg-white hover:bg-slate-50 border-slate-200 text-slate-500 hover:text-red-600"
|
|
)}
|
|
title={isEn ? "Clear Slot" : "清除槽位"}
|
|
>
|
|
✕
|
|
</button>
|
|
)}
|
|
</div>
|
|
)}
|
|
</div>
|
|
);
|
|
|
|
return (
|
|
<Panel title={panelTitle} actions={timeframeActions}>
|
|
<div className="flex h-full min-h-[300px] flex-col">
|
|
{/* Compact stats bar */}
|
|
{compact ? (
|
|
<div className="shrink-0 border-b border-slate-200 bg-white px-3 py-1.5 flex items-center justify-between">
|
|
{timeframe === "1D" ? (
|
|
<div className="flex items-center gap-4 text-[11px]">
|
|
<span className="font-semibold text-slate-500">
|
|
{isEn ? "Runway" : runwayHeaderLabel}:{" "}
|
|
<strong className="text-[#009688] font-mono">{temp(currentRunwayTemp)}</strong>
|
|
</span>
|
|
<span className="text-slate-300">|</span>
|
|
<span className="font-semibold text-slate-500">
|
|
{isEn ? "METAR" : metarHeaderLabel}:{" "}
|
|
<strong className="text-blue-600 font-mono">{temp(observedHighMetar)}</strong>
|
|
</span>
|
|
</div>
|
|
) : (
|
|
<div className="flex items-center gap-4 text-[11px]">
|
|
<span className="font-semibold text-slate-500">
|
|
DEB: <strong className="text-orange-600 font-mono">{temp(debVal)}</strong>
|
|
</span>
|
|
{modelMin !== null && modelMax !== null && (
|
|
<>
|
|
<span className="text-slate-300">|</span>
|
|
<span className="font-semibold text-slate-500">
|
|
{isEn ? "Models" : "多模型"}:{" "}
|
|
<strong className="text-slate-700 font-mono">
|
|
{temp(modelMin)} - {temp(modelMax)}
|
|
</strong>
|
|
</span>
|
|
</>
|
|
)}
|
|
</div>
|
|
)}
|
|
<div className="text-[10px] text-slate-400 font-mono">
|
|
{timeframe === "1D" && formattedUpdateTime.includes(" ") ? formattedUpdateTime.split(" ")[1].slice(0, 5) : ""}
|
|
</div>
|
|
</div>
|
|
) : (
|
|
/* Normal detailed stats bar */
|
|
<div className="shrink-0 border-b border-slate-200 bg-white px-4 py-3">
|
|
{/* Top Row: Large temperatures */}
|
|
<div className="flex justify-between items-center gap-6 mb-3">
|
|
{timeframe === "1D" ? (
|
|
<div className="flex items-center gap-12">
|
|
<div className="flex flex-col">
|
|
<span className="text-[11px] font-semibold text-slate-500 uppercase tracking-wider">
|
|
{isEn ? "Runway Live (1m)" : `${runwayHeaderLabel}`}
|
|
</span>
|
|
<span className="text-2xl font-bold font-mono text-[#009688] mt-1">
|
|
{temp(currentRunwayTemp)}
|
|
</span>
|
|
</div>
|
|
<div className="flex flex-col">
|
|
<span className="text-[11px] font-semibold text-slate-500 uppercase tracking-wider">
|
|
{isEn ? "METAR Settlement (30m) · Daily High" : `${metarHeaderLabel} · 当日最高`}
|
|
</span>
|
|
<span className="text-2xl font-bold font-mono text-blue-600 mt-1">
|
|
{temp(observedHighMetar)}
|
|
</span>
|
|
</div>
|
|
</div>
|
|
) : (
|
|
<div className="flex items-center gap-12">
|
|
<div className="flex flex-col">
|
|
<span className="text-[11px] font-semibold text-slate-500 uppercase tracking-wider">
|
|
DEB Max
|
|
</span>
|
|
<span className="text-2xl font-bold font-mono text-orange-600 mt-1">
|
|
{temp(debVal)}
|
|
</span>
|
|
</div>
|
|
<div className="flex flex-col">
|
|
<span className="text-[11px] font-semibold text-slate-500 uppercase tracking-wider">
|
|
{isEn ? "Model Range" : "多模型区间"}
|
|
</span>
|
|
<span className="text-2xl font-bold font-mono text-slate-700 mt-1">
|
|
{modelMin !== null && modelMax !== null ? `${temp(modelMin)} - ${temp(modelMax)}` : "--"}
|
|
</span>
|
|
</div>
|
|
</div>
|
|
)}
|
|
|
|
<div className="hidden sm:flex flex-col items-end text-right">
|
|
<span className="text-[10px] text-slate-400 uppercase font-semibold">
|
|
{isEn ? "Daily Peak" : "当日最高气温"}
|
|
</span>
|
|
<div className="mt-1 flex items-center gap-2 text-xs font-mono text-slate-600">
|
|
<span>{isEn ? "Runway" : runwayHighLabel}: <strong className="text-[#009688]">{temp(observedHighRunway)}</strong></span>
|
|
<span>|</span>
|
|
<span>{isEn ? "METAR" : metarHighLabel}: <strong className="text-blue-600">{temp(observedHighMetar)}</strong></span>
|
|
{wundergroundDailyHigh !== null && (
|
|
<>
|
|
<span>|</span>
|
|
<span>WU: <strong className="text-purple-600">{temp(wundergroundDailyHigh)}</strong></span>
|
|
</>
|
|
)}
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
{/* Bottom Row: Model Range Panel (Only for 1D mode) */}
|
|
{timeframe === "1D" && (
|
|
<div className="grid grid-cols-4 gap-4 border-t border-slate-100 pt-3 text-xs font-mono text-slate-700 bg-slate-50/50 -mx-4 px-4 rounded-b-md">
|
|
<div className="flex flex-col gap-0.5">
|
|
<span className="text-[10px] text-slate-400 uppercase font-semibold">
|
|
{isEn ? "Model Range" : "模型区间"}
|
|
</span>
|
|
<strong className="text-slate-800 font-bold">
|
|
{modelMin !== null && modelMax !== null ? `${temp(modelMin)} - ${temp(modelMax)}` : "--"}
|
|
</strong>
|
|
</div>
|
|
<div className="flex flex-col gap-0.5">
|
|
<span className="text-[10px] text-slate-400 uppercase font-semibold">
|
|
DEB
|
|
</span>
|
|
<strong className="text-blue-600 font-bold">
|
|
{temp(debVal)}
|
|
</strong>
|
|
</div>
|
|
<div className="flex flex-col gap-0.5">
|
|
<span className="text-[10px] text-slate-400 uppercase font-semibold">
|
|
{isEn ? "Spread" : "分歧"}
|
|
</span>
|
|
<strong className={clsx("font-bold", spreadLabel === "高分歧" ? "text-amber-600" : "text-slate-600")}>
|
|
{spread !== null ? `${spread.toFixed(1)}°C` : "--"}
|
|
{spreadLabel && ` · ${isEn ? spreadLabelEn : spreadLabel}`}
|
|
</strong>
|
|
</div>
|
|
<div className="flex flex-col gap-0.5">
|
|
<span className="text-[10px] text-slate-400 uppercase font-semibold">
|
|
{isEn ? "Updated" : "更新时间"}
|
|
</span>
|
|
<strong className="text-slate-800 font-bold">
|
|
{formattedUpdateTime}
|
|
</strong>
|
|
</div>
|
|
</div>
|
|
)}
|
|
</div>
|
|
)}
|
|
|
|
{/* Runway observations (Only for 1D mode and when not compact) */}
|
|
{timeframe === "1D" && !compact && runwayPlates.length > 0 && (
|
|
<div className="shrink-0 border-b border-slate-200 bg-[#f8fafc] px-3 py-2">
|
|
<div className="flex items-center justify-between text-[11px] font-black text-slate-700 mb-1.5 uppercase">
|
|
<span>{isEn ? "Runway Observations" : "跑道观测"}</span>
|
|
{runwayPlates.some((p) => p.trend_15m !== null && p.trend_15m > 0 && !p.isSettlement) && (
|
|
<span className="text-[10px] bg-amber-50 text-amber-700 border border-amber-200 px-1.5 py-0.5 rounded font-sans">
|
|
{isEn ? "Non-settlement Runway Warming Alert" : "非结算跑道升温提醒"}
|
|
</span>
|
|
)}
|
|
</div>
|
|
<div className="grid gap-1">
|
|
{runwayPlates.map((plate) => (
|
|
<div
|
|
key={plate.rwy}
|
|
className={clsx(
|
|
"grid grid-cols-7 gap-2 items-center border rounded px-2.5 py-1 text-[11px] font-mono",
|
|
plate.isSettlement
|
|
? "border-emerald-200 bg-emerald-50/50 text-emerald-950 font-bold"
|
|
: "border-slate-200 bg-white text-slate-600"
|
|
)}
|
|
>
|
|
<div className="flex items-center gap-1.5 font-sans font-bold text-slate-800">
|
|
{plate.isSettlement && <span className="h-1.5 w-1.5 rounded-full bg-emerald-600 animate-pulse" />}
|
|
<span>{plate.rwy}</span>
|
|
{plate.isSettlement && (
|
|
<span className="text-[9px] bg-teal-200 text-teal-800 px-1 rounded font-normal">
|
|
{isEn ? "Settlement" : "结算"}
|
|
</span>
|
|
)}
|
|
</div>
|
|
<div>TDZ: <strong>{plate.tdzTemp !== null ? `${plate.tdzTemp.toFixed(1)}°C` : "--"}</strong></div>
|
|
<div>MID: <strong>{plate.midTemp !== null ? `${plate.midTemp.toFixed(1)}°C` : "--"}</strong></div>
|
|
<div>END: <strong>{plate.endTemp !== null ? `${plate.endTemp.toFixed(1)}°C` : "--"}</strong></div>
|
|
<div>max: <strong>{plate.maxTemp !== null ? `${plate.maxTemp.toFixed(1)}°C` : "--"}</strong></div>
|
|
<div>high: <strong>{plate.dailyHigh !== null ? `${plate.dailyHigh.toFixed(1)}°C` : "--"}</strong></div>
|
|
<div className={clsx(plate.trend_15m !== null && plate.trend_15m > 0 ? "text-orange-600 font-bold" : "text-slate-500")}>
|
|
15m: <strong>{plate.trend_15m !== null ? `${plate.trend_15m >= 0 ? "+" : ""}${plate.trend_15m.toFixed(1)}°C` : "--"}</strong>
|
|
</div>
|
|
</div>
|
|
))}
|
|
</div>
|
|
</div>
|
|
)}
|
|
|
|
{/* Multi-model list (Only in 1D mode and when not compact) */}
|
|
{timeframe === "1D" && !compact && hasRunwayData && series.some((s) => s.key.startsWith("model_curve_")) && (
|
|
<div className="shrink-0 border-b border-slate-200 bg-white px-4 py-2">
|
|
<div className="flex flex-wrap gap-x-6 gap-y-1 text-[11px]">
|
|
<span className="font-black text-slate-500 uppercase mr-2">
|
|
{isEn ? "Models:" : "多模型:"}
|
|
</span>
|
|
{series
|
|
.filter((s) => s.key.startsWith("model_curve_"))
|
|
.map((s) => {
|
|
const stats = seriesStats(s.values);
|
|
return (
|
|
<span key={s.key} className="inline-flex items-center gap-1.5 font-mono">
|
|
<span className="h-2 w-2 rounded-full shrink-0" style={{ backgroundColor: s.color }} />
|
|
<span className="text-slate-700 font-bold">{s.label}</span>
|
|
<span className="text-slate-500">{temp(stats.latest)}</span>
|
|
</span>
|
|
);
|
|
})}
|
|
</div>
|
|
</div>
|
|
)}
|
|
|
|
{/* Chart */}
|
|
<div className="relative min-h-0 flex-1 p-2">
|
|
{/* Interactive legend */}
|
|
<div className="flex flex-wrap gap-x-4 gap-y-1 px-3 py-1.5 text-[11px] border-b border-[#e2e8f0] bg-white">
|
|
{chartSeries.length > 1 && chartSeries.map((s) => (
|
|
<button
|
|
key={s.key}
|
|
type="button"
|
|
onClick={() => {
|
|
setUserToggledKeys((prev) => ({
|
|
...prev,
|
|
[s.key]: !isSeriesVisible(s.key),
|
|
}));
|
|
}}
|
|
className={clsx(
|
|
"inline-flex items-center gap-1.5 font-mono cursor-pointer transition-opacity hover:opacity-80",
|
|
!isSeriesVisible(s.key) && "opacity-40 line-through"
|
|
)}
|
|
>
|
|
<span className="h-2 w-2 rounded-full shrink-0" style={{ backgroundColor: s.color }} />
|
|
<span className="text-slate-700 font-bold">{s.label}</span>
|
|
</button>
|
|
))}
|
|
</div>
|
|
<ResponsiveContainer width="100%" height="100%">
|
|
<ReLineChart data={data} margin={{ top: 16, right: compact ? 20 : 44, left: 4, bottom: 8 }}>
|
|
<CartesianGrid stroke="#dbe6ef" strokeDasharray="2 2" />
|
|
<XAxis
|
|
dataKey="label"
|
|
tick={{ fontSize: 9, fill: "#64748b" }}
|
|
tickLine={false}
|
|
axisLine={{ stroke: "#cbd5e1" }}
|
|
interval={Math.max(1, Math.floor(data.length / (compact ? 6 : 10)))}
|
|
/>
|
|
<YAxis
|
|
orientation="right"
|
|
tick={{ fontSize: 9, fill: "#64748b" }}
|
|
tickFormatter={(v) => `${Number(v).toFixed(0)}°`}
|
|
axisLine={{ stroke: "#cbd5e1" }}
|
|
tickLine={false}
|
|
domain={chartDomain}
|
|
ticks={intDegreeTicks ?? undefined}
|
|
/>
|
|
{timeframe === "1D" && cityThresholds.map((t, idx) => {
|
|
const isSelected = row && (Number(row.target_threshold ?? row.target_value) === t.threshold);
|
|
const labelText = isEn
|
|
? `${t.kind === "gte" ? "≥" : "≤"} ${t.threshold.toFixed(1)}° [${t.isBreached ? "Excluded" : "Active"}]`
|
|
: `${t.kind === "gte" ? "≥" : "≤"} ${t.threshold.toFixed(1)}° [${t.isBreached ? "已排除" : "活跃"}]`;
|
|
|
|
return (
|
|
<ReferenceLine
|
|
key={idx}
|
|
y={t.threshold}
|
|
stroke={isSelected ? "#3b82f6" : t.isBreached ? "#ef4444" : "#f97316"}
|
|
strokeDasharray={isSelected ? undefined : "4 4"}
|
|
strokeWidth={isSelected ? 2 : 1}
|
|
label={{
|
|
value: compact ? undefined : labelText,
|
|
fill: isSelected ? "#3b82f6" : t.isBreached ? "#ef4444" : "#f97316",
|
|
fontSize: 9,
|
|
position: isSelected ? "left" : "insideBottomRight",
|
|
}}
|
|
/>
|
|
);
|
|
})}
|
|
<Tooltip
|
|
contentStyle={{
|
|
border: "1px solid #cbd5e1",
|
|
borderRadius: 4,
|
|
fontSize: 11,
|
|
boxShadow: "0 8px 24px rgba(15,23,42,.12)",
|
|
}}
|
|
formatter={(value: unknown) => `${Number(value).toFixed(2)}°`}
|
|
/>
|
|
{activeSeries.map((item) => (
|
|
<Line
|
|
key={item.key}
|
|
type={item.smooth ? "monotone" : "linear"}
|
|
dataKey={item.key}
|
|
name={item.label}
|
|
stroke={item.color}
|
|
strokeWidth={item.featured ? 2.8 : 1.2}
|
|
strokeDasharray={item.dashed ? "4 3" : undefined}
|
|
dot={false}
|
|
activeDot={{ r: item.featured ? 6 : 4 }}
|
|
connectNulls={true}
|
|
isAnimationActive={false}
|
|
/>
|
|
))}
|
|
{!compact && (timeframe === "1D" || timeframe === "3D") && (
|
|
<Brush
|
|
dataKey="label"
|
|
height={18}
|
|
stroke="#64748b"
|
|
fill="#f8fafc"
|
|
travellerWidth={8}
|
|
startIndex={0}
|
|
endIndex={data.length - 1}
|
|
/>
|
|
)}
|
|
</ReLineChart>
|
|
</ResponsiveContainer>
|
|
</div>
|
|
</div>
|
|
</Panel>
|
|
);
|
|
}
|
|
|
|
export function __buildTemperatureChartDataForTest(
|
|
row: ScanOpportunityRow | null,
|
|
hourly: HourlyForecast,
|
|
timeframe: "1D" | "3D" = "1D",
|
|
) {
|
|
return timeframe === "3D" ? build3DayChartData(row, hourly) : buildFullDayChartData(row, hourly);
|
|
}
|
|
|
|
export const __isTemperatureSeriesVisibleByDefaultForTest = isTemperatureSeriesVisibleByDefault;
|