"use client"; import clsx from "clsx"; import { useEffect, useMemo, useState } from "react"; import Link from "next/link"; import { ExternalLink } from "lucide-react"; import { CartesianGrid, Line, LineChart as ReLineChart, ReferenceLine, ResponsiveContainer, Tooltip, XAxis, YAxis, } from "recharts"; import type { CityDetail, ScanOpportunityRow } from "@/lib/dashboard-types"; import { buildDebBaselinePath } from "@/lib/temperature-chart-paths"; import { Panel } from "@/components/dashboard/scan-terminal/Panel"; import { rowName, temp } from "@/components/dashboard/scan-terminal/utils"; type ObsPoint = { time?: string | null; temp?: number | null }; type EvidenceSeries = { key: string; label: string; source: string; color: string; dashed?: boolean; featured?: boolean; smooth?: boolean; values: Array; }; type RunwayObsPayload = { runway_pairs?: Array<[string, string] | string[] | null> | null; temperatures?: Array<[number | null, number | null] | Array | null> | null; point_temperatures?: Array<{ runway?: string | null; tdz_temp?: number | null; mid_temp?: number | null; end_temp?: number | null; } | null> | null; }; // Semi-hourly buckets for the 24-hour day — gives the chart enough resolution // without making the x-axis unreadable when showing a 12 hour window. const HALF_HOUR_SLOTS = Array.from({ length: 48 }, (_, i) => { const h = Math.floor(i / 2); const m = i % 2 === 0 ? "00" : "30"; return `${String(h).padStart(2, "0")}:${m}`; }); const VISIBLE_WINDOW_HOURS = 12; function validNumber(value: unknown): number | null { return typeof value === "number" && Number.isFinite(value) ? value : null; } function normalizeObs(points?: ObsPoint[] | null, limit = 88) { return (points || []) .filter((point) => validNumber(point.temp) !== null) .slice(-limit) .map((point, index) => ({ label: point.time || String(index + 1), value: Number(point.temp), })); } function parseTimeSlot(value?: string | null) { const raw = String(value || "").trim(); if (!raw) return null; // Try ISO / full date first const parsed = new Date(raw); if (!Number.isNaN(parsed.getTime())) { const h = parsed.getHours(); const m = parsed.getMinutes(); return h * 2 + (m >= 30 ? 1 : 0); } // Parse "HH:MM" or "HH:MM" or "HH:MM:SS" const match = raw.match(/(?:^|\D)([01]?\d|2[0-3])[::]([0-5]\d)/); if (match?.[1] !== undefined && match?.[2] !== undefined) { const h = Number(match[1]); const m = Number(match[2]); if (h >= 0 && h < 24) return h * 2 + (m >= 30 ? 1 : 0); } return null; } function seriesStats(values: Array) { const nums = values.filter((value): value is number => validNumber(value) !== 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 }; } type HourlyForecast = { forecastTodayHigh?: number | null; localTime?: string | null; times: string[]; temps: Array; modelCurves?: Record>; } | null; function buildModelCurves(row: ScanOpportunityRow | null, length: number, hourly: HourlyForecast) { const result: EvidenceSeries[] = []; // Use hourly forecast data if available. Daily model highs are not plotted // as curves because they are single terminal values, not a time series. 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 values = Array.from({ length }, (): number | null => null); hourly.times.forEach((t, i) => { const slot = parseTimeSlot(t); if (slot !== null && slot >= 0 && slot < length && i < hourly.temps.length) { values[slot] = validNumber(debPath.debTemps[i]); } }); if (values.some((v) => v !== null)) { result.push({ key: "hourly_forecast", label: "DEB Forecast", source: "DEB Hourly", color: "#f97316", featured: true, smooth: true, values, }); } // Per-model hourly curves from Open-Meteo multi-model API 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 values = Array.from({ length }, (): number | null => null); hourly.times.forEach((t, i) => { const slot = parseTimeSlot(t); if (slot !== null && slot >= 0 && slot < length && i < modelTemps.length) { values[slot] = validNumber(modelTemps[i]); } }); if (values.some((v) => v !== null)) { result.push({ key: `model_curve_${model}`, label: model, source: "Multi-model hourly", color: modelColors[idx % modelColors.length], dashed: true, smooth: true, values, }); } }); } } return result; } function buildModelSummaryCards(row: ScanOpportunityRow | null): EvidenceSeries[] { return Object.entries(row?.model_cluster_sources || {}) .map(([label, value]) => [label, validNumber(value)] as const) .filter((entry): entry is readonly [string, number] => entry[1] !== null) .slice(0, 4) .map(([label, value], index) => ({ key: `model_summary_${index}`, label, source: "Multi-model daily high", color: ["#2563eb", "#14b8a6", "#7c3aed", "#64748b"][index] || "#64748b", dashed: true, values: [value], })); } function extractRunwayPointSeries(row: ScanOpportunityRow | null, length: number): EvidenceSeries[] { const payload = row as | (ScanOpportunityRow & { amos?: { runway_obs?: RunwayObsPayload | null; source_label?: string | null; source?: string | null } | null; runway_obs?: RunwayObsPayload | null; }) | null; const runwayObs = payload?.amos?.runway_obs || payload?.runway_obs; if (!runwayObs) return []; const pairs = runwayObs.runway_pairs || []; const runwayTemps = runwayObs.temperatures || []; const pointTemps = runwayObs.point_temperatures || []; const source = payload?.amos?.source_label || payload?.amos?.source || "Runway"; const series: EvidenceSeries[] = []; pairs.forEach((pair, index) => { const pairLabel = Array.isArray(pair) && pair.length ? pair.filter(Boolean).join("/") : pointTemps[index]?.runway || `RWY ${index + 1}`; const values = [ ...(Array.isArray(runwayTemps[index]) ? runwayTemps[index] || [] : []), pointTemps[index]?.tdz_temp, pointTemps[index]?.mid_temp, pointTemps[index]?.end_temp, ] .map(validNumber) .filter((value): value is number => value !== null); if (!values.length) return; const maxTemp = Math.max(...values); series.push({ key: `runway_${index}`, label: `${pairLabel} runway`, source, color: ["#009688", "#f97316", "#0ea5e9", "#ef4444"][index] || "#64748b", featured: index === 0, dashed: index !== 0, values: Array.from({ length }, () => maxTemp), }); }); return series.slice(0, 4); } function buildEvidenceChart(row: ScanOpportunityRow | null, hourly: HourlyForecast) { const settlement = normalizeObs(row?.settlement_today_obs || row?.metar_context?.settlement_today_obs); const metar = normalizeObs(row?.metar_today_obs || row?.metar_context?.today_obs || row?.metar_recent_obs || row?.metar_context?.recent_obs); const labels = HALF_HOUR_SLOTS; const length = labels.length; const align = (points: Array<{ label: string; value: number }>) => { if (!points.length) return Array.from({ length }, (): number | null => null); const values = Array.from({ length }, (): number | null => null); points.forEach((point, index) => { const slot = parseTimeSlot(point.label); const bucket = slot ?? Math.min(index, length - 1); values[bucket] = point.value; }); return values; }; const series: EvidenceSeries[] = []; series.push(...extractRunwayPointSeries(row, length)); if (settlement.length) { series.push({ key: "settlement", label: row?.metar_context?.station_label || row?.metar_context?.station || "Settlement station", source: row?.metar_context?.station_label || row?.metar_context?.station || row?.airport || "Settlement", color: "#009688", featured: true, values: align(settlement), }); } if (metar.length) { series.push({ key: "metar", label: "METAR official", source: row?.airport || row?.metar_context?.source || "METAR", color: "#0ea5e9", dashed: true, values: align(metar), }); } series.push(...buildModelCurves(row, length, hourly)); const fallbackValue = validNumber(row?.current_temp) ?? validNumber(row?.current_max_so_far) ?? validNumber(row?.deb_prediction) ?? validNumber(row?.target_value) ?? validNumber(row?.target_threshold); if (!series.length && fallbackValue !== null) { series.push({ key: "current", label: "Current reference", source: row?.metar_context?.source || "Live", color: "#009688", featured: true, values: Array.from({ length }, () => fallbackValue), }); } const data = labels.map((label, index) => { const point: Record = { label }; series.forEach((item) => { point[item.key] = item.values[index] ?? null; }); return point; }); return { data, series }; } function currentSlotForWindow(row: ScanOpportunityRow | null, hourly: HourlyForecast) { const slot = parseTimeSlot(hourly?.localTime || row?.local_time); if (slot !== null) return slot; const now = new Date(); return now.getHours() * 2 + (now.getMinutes() >= 30 ? 1 : 0); } function buildMovingWindowData( data: Array>, row: ScanOpportunityRow | null, hourly: HourlyForecast, ) { if (!data.length) return data; const totalHalfHours = 48; const windowSlots = VISIBLE_WINDOW_HOURS * 2; // 24 half-hour slots = 12 hours const currentSlot = currentSlotForWindow(row, hourly); const endSlot = Math.min(totalHalfHours - 1, Math.max(windowSlots - 1, currentSlot + 8)); const startSlot = Math.max(0, endSlot - windowSlots + 1); return data.slice(startSlot, endSlot + 1); } function parseTemperatureOptionsFromText(value?: string | null) { const raw = String(value || ""); const matches = raw.match(/-?\d+(?:\.\d+)?/g) || []; return matches .map((item) => Number(item)) .filter((item) => Number.isFinite(item) && item > -80 && item < 80); } function buildMarketTemperatureOptions(row: ScanOpportunityRow | null) { const buckets = row?.distribution_full?.length ? row.distribution_full : row?.distribution_preview; const values = new Set(); (buckets || []).forEach((bucket) => { const value = validNumber(bucket.value); if (value !== null) values.add(value); parseTemperatureOptionsFromText(bucket.label).forEach((item) => values.add(item)); }); [ row?.target_lower, row?.target_upper, row?.target_value, row?.target_threshold, ].forEach((value) => { const numeric = validNumber(value); if (numeric !== null) values.add(numeric); }); parseTemperatureOptionsFromText(row?.target_label).forEach((item) => values.add(item)); parseTemperatureOptionsFromText(row?.market_question).forEach((item) => values.add(item)); const sorted = [...values].sort((a, b) => a - b); if (sorted.length) return sorted; const threshold = validNumber(row?.target_threshold) ?? validNumber(row?.target_value); if (threshold === null) return null; return [threshold - 2, threshold - 1, threshold, threshold + 1, threshold + 2]; } function buildChartDomain( marketTicks: number[] | null, series: EvidenceSeries[], ): [number, number] | ["auto", "auto"] { const values = series .flatMap((item) => item.values) .filter((value): value is number => validNumber(value) !== null); const domainValues = [...(marketTicks || []), ...values]; if (!domainValues.length) return ["auto", "auto"]; const min = Math.min(...domainValues); const max = Math.max(...domainValues); const span = Math.max(1, max - min); const padding = Math.max(0.5, span * 0.08); return [Number((min - padding).toFixed(1)), Number((max + padding).toFixed(1))]; } export function LiveTemperatureThresholdChart({ isEn, row, }: { isEn: boolean; row: ScanOpportunityRow | null; }) { const [hourly, setHourly] = useState(null); const city = String(row?.city || "").toLowerCase().trim(); useEffect(() => { setHourly(null); if (!city) return; let cancelled = false; fetch(`/api/city/${encodeURIComponent(city)}/detail?depth=panel&force_refresh=false`, { cache: "no-store", headers: { Accept: "application/json" }, }) .then(async (res) => { if (!res.ok) return null; return res.json() as Promise; }) .then((json) => { if (cancelled || !json?.hourly) return; setHourly({ forecastTodayHigh: json.forecast?.today_high ?? null, localTime: json.local_time || null, times: json.hourly.times || [], temps: json.hourly.temps || [], modelCurves: json.models_hourly?.curves || undefined, }); }) .catch(() => {}); return () => { cancelled = true; }; }, [city]); const { data, series } = useMemo(() => buildEvidenceChart(row, hourly), [row, hourly]); const visibleData = useMemo(() => buildMovingWindowData(data, row, hourly), [data, row, hourly]); const threshold = validNumber(row?.target_threshold) ?? validNumber(row?.target_value); const modelSummaryCards = useMemo(() => { const cards = buildModelSummaryCards(row); // Exclude models that already show as hourly curves (from buildModelCurves) if (!hourly?.modelCurves) return cards; const curveKeys = new Set(Object.keys(hourly.modelCurves)); return cards.filter((card) => !curveKeys.has(card.label)); }, [row, hourly]); const tableRows = [...series, ...modelSummaryCards] .slice(0, 5) .map((item) => ({ ...item, ...seriesStats(item.values) })); const marketTemperatureTicks = useMemo(() => buildMarketTemperatureOptions(row), [row]); const chartDomain = useMemo( () => buildChartDomain(marketTemperatureTicks, series), [marketTemperatureTicks, series], ); return (
{isEn ? "Settlement live" : "跑道实测"} {temp(validNumber(row?.current_temp))}
METAR {temp(validNumber(row?.metar_context?.airport_current_temp ?? row?.metar_context?.last_temp))}
{isEn ? "Threshold" : "当日阈值"} {temp(threshold)}
{tableRows.map((item) => (
{item.label}
{item.key.startsWith("model_summary_") ? ( {temp(item.latest)} ) : (
now: {temp(item.latest)} max: {temp(item.high)} 15m: {item.delta15 === null ? "--" : `${item.delta15 >= 0 ? "+" : ""}${item.delta15.toFixed(1)}°`}
)}
))}
{rowName(row)} {row?.target_label || row?.market_direction || ""}
`${Number(v).toFixed(1)}°`} axisLine={{ stroke: "#cbd5e1" }} tickLine={false} domain={chartDomain} ticks={marketTemperatureTicks || undefined} /> {threshold !== null && ( )} `${Number(value).toFixed(2)}°`} /> {series.map((item) => ( ))}
{row?.market_slug ? (
{isEn ? "View on Polymarket" : "在 Polymarket 查看"}
) : null}
); }