2569718930@qq.com
ce667ba1b6
city_payloads 新增 models_hourly 包含 per-model hourly_forecasts。LiveTemperatureThresholdChart 渲染多模型曲线替代点预测卡片。CityDetail 类型新增 models_hourly。
534 lines
20 KiB
TypeScript
534 lines
20 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 Link from "next/link";
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import { ExternalLink } from "lucide-react";
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import {
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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 { CityDetail, ScanOpportunityRow } from "@/lib/dashboard-types";
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import { buildDebBaselinePath } from "@/lib/temperature-chart-paths";
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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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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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values: Array<number | null>;
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};
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type RunwayObsPayload = {
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runway_pairs?: Array<[string, string] | string[] | null> | null;
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temperatures?: Array<[number | null, number | null] | Array<number | null> | null> | null;
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point_temperatures?: Array<{
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runway?: string | null;
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tdz_temp?: number | null;
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mid_temp?: number | null;
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end_temp?: number | null;
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} | null> | null;
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};
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// Semi-hourly buckets for the 24-hour day — gives the chart enough resolution
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// without making the x-axis unreadable when showing a 12 hour window.
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const HALF_HOUR_SLOTS = Array.from({ length: 48 }, (_, i) => {
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const h = Math.floor(i / 2);
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const m = i % 2 === 0 ? "00" : "30";
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return `${String(h).padStart(2, "0")}:${m}`;
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});
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const VISIBLE_WINDOW_HOURS = 12;
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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 normalizeObs(points?: ObsPoint[] | null, limit = 88) {
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return (points || [])
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.filter((point) => validNumber(point.temp) !== null)
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.slice(-limit)
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.map((point, index) => ({
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label: point.time || String(index + 1),
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value: Number(point.temp),
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}));
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}
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function parseTimeSlot(value?: string | null) {
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const raw = String(value || "").trim();
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if (!raw) return null;
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// Try ISO / full date first
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const parsed = new Date(raw);
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if (!Number.isNaN(parsed.getTime())) {
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const h = parsed.getHours();
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const m = parsed.getMinutes();
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return h * 2 + (m >= 30 ? 1 : 0);
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}
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// Parse "HH:MM" or "HH：MM" or "HH:MM:SS"
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const match = raw.match(/(?:^|\D)([01]?\d|2[0-3])[:：]([0-5]\d)/);
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if (match?.[1] !== undefined && match?.[2] !== undefined) {
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const h = Number(match[1]);
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const m = Number(match[2]);
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if (h >= 0 && h < 24) return h * 2 + (m >= 30 ? 1 : 0);
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}
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return null;
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}
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function seriesStats(values: Array<number | null>) {
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const nums = values.filter((value): value is number => validNumber(value) !== 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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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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} | null;
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function buildModelCurves(row: ScanOpportunityRow | null, length: number, hourly: HourlyForecast) {
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const result: EvidenceSeries[] = [];
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// Use hourly forecast data if available. Daily model highs are not plotted
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// as curves because they are single terminal values, not a time series.
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if (hourly?.times?.length && hourly?.temps?.length) {
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const debPath = buildDebBaselinePath(
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hourly.times,
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hourly.temps,
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row?.deb_prediction,
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hourly.localTime || row?.local_time,
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hourly.forecastTodayHigh,
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);
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const values = Array.from({ length }, (): number | null => null);
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hourly.times.forEach((t, i) => {
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const slot = parseTimeSlot(t);
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if (slot !== null && slot >= 0 && slot < length && i < hourly.temps.length) {
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values[slot] = validNumber(debPath.debTemps[i]);
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}
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});
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if (values.some((v) => v !== null)) {
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result.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,
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});
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}
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// Per-model hourly curves from Open-Meteo multi-model API
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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];
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if (!modelTemps?.length) return;
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const values = Array.from({ length }, (): number | null => null);
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hourly.times.forEach((t, i) => {
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const slot = parseTimeSlot(t);
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if (slot !== null && slot >= 0 && slot < length && i < modelTemps.length) {
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values[slot] = validNumber(modelTemps[i]);
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}
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});
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if (values.some((v) => v !== null)) {
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result.push({
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key: `model_curve_${model}`,
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label: model,
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source: "Multi-model hourly",
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color: modelColors[idx % modelColors.length],
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dashed: true,
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smooth: true,
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values,
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});
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}
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});
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}
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}
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return result;
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}
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function buildModelSummaryCards(row: ScanOpportunityRow | null): EvidenceSeries[] {
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return Object.entries(row?.model_cluster_sources || {})
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.map(([label, value]) => [label, validNumber(value)] as const)
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.filter((entry): entry is readonly [string, number] => entry[1] !== null)
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.slice(0, 4)
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.map(([label, value], index) => ({
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key: `model_summary_${index}`,
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label,
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source: "Multi-model daily high",
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color: ["#2563eb", "#14b8a6", "#7c3aed", "#64748b"][index] || "#64748b",
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dashed: true,
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values: [value],
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}));
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}
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function extractRunwayPointSeries(row: ScanOpportunityRow | null, length: number): EvidenceSeries[] {
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const payload = row as
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| (ScanOpportunityRow & {
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amos?: { runway_obs?: RunwayObsPayload | null; source_label?: string | null; source?: string | null } | null;
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runway_obs?: RunwayObsPayload | null;
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})
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| null;
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const runwayObs = payload?.amos?.runway_obs || payload?.runway_obs;
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if (!runwayObs) return [];
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const pairs = 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 source = payload?.amos?.source_label || payload?.amos?.source || "Runway";
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const series: EvidenceSeries[] = [];
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pairs.forEach((pair, index) => {
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const pairLabel = Array.isArray(pair) && pair.length
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? pair.filter(Boolean).join("/")
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: pointTemps[index]?.runway || `RWY ${index + 1}`;
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const values = [
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...(Array.isArray(runwayTemps[index]) ? runwayTemps[index] || [] : []),
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pointTemps[index]?.tdz_temp,
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pointTemps[index]?.mid_temp,
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pointTemps[index]?.end_temp,
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]
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.map(validNumber)
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.filter((value): value is number => value !== null);
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if (!values.length) return;
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const maxTemp = Math.max(...values);
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series.push({
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key: `runway_${index}`,
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label: `${pairLabel} runway`,
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source,
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color: ["#009688", "#f97316", "#0ea5e9", "#ef4444"][index] || "#64748b",
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featured: index === 0,
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dashed: index !== 0,
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values: Array.from({ length }, () => maxTemp),
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});
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});
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return series.slice(0, 4);
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}
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function buildEvidenceChart(row: ScanOpportunityRow | null, hourly: HourlyForecast) {
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const settlement = normalizeObs(row?.settlement_today_obs || row?.metar_context?.settlement_today_obs);
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const metar = normalizeObs(row?.metar_today_obs || row?.metar_context?.today_obs || row?.metar_recent_obs || row?.metar_context?.recent_obs);
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const labels = HALF_HOUR_SLOTS;
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const length = labels.length;
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const align = (points: Array<{ label: string; value: number }>) => {
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if (!points.length) return Array.from({ length }, (): number | null => null);
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const values = Array.from({ length }, (): number | null => null);
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points.forEach((point, index) => {
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const slot = parseTimeSlot(point.label);
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const bucket = slot ?? Math.min(index, length - 1);
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values[bucket] = point.value;
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});
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return values;
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};
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const series: EvidenceSeries[] = [];
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series.push(...extractRunwayPointSeries(row, length));
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if (settlement.length) {
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series.push({
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key: "settlement",
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label: row?.metar_context?.station_label || row?.metar_context?.station || "Settlement station",
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source: row?.metar_context?.station_label || row?.metar_context?.station || row?.airport || "Settlement",
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color: "#009688",
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featured: true,
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values: align(settlement),
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});
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}
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if (metar.length) {
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series.push({
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key: "metar",
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label: "METAR official",
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source: row?.airport || row?.metar_context?.source || "METAR",
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color: "#0ea5e9",
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dashed: true,
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values: align(metar),
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});
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}
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series.push(...buildModelCurves(row, length, hourly));
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const fallbackValue =
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validNumber(row?.current_temp) ??
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validNumber(row?.current_max_so_far) ??
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validNumber(row?.deb_prediction) ??
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validNumber(row?.target_value) ??
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validNumber(row?.target_threshold);
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if (!series.length && fallbackValue !== null) {
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series.push({
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key: "current",
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label: "Current reference",
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source: row?.metar_context?.source || "Live",
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color: "#009688",
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featured: true,
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values: Array.from({ length }, () => fallbackValue),
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});
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}
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const data = labels.map((label, index) => {
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const point: Record<string, string | number | null> = { label };
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series.forEach((item) => {
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point[item.key] = item.values[index] ?? null;
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});
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return point;
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});
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return { data, series };
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}
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function currentSlotForWindow(row: ScanOpportunityRow | null, hourly: HourlyForecast) {
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const slot = parseTimeSlot(hourly?.localTime || row?.local_time);
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if (slot !== null) return slot;
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const now = new Date();
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return now.getHours() * 2 + (now.getMinutes() >= 30 ? 1 : 0);
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}
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function buildMovingWindowData(
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data: Array<Record<string, string | number | null>>,
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row: ScanOpportunityRow | null,
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hourly: HourlyForecast,
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) {
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if (!data.length) return data;
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const totalHalfHours = 48;
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const windowSlots = VISIBLE_WINDOW_HOURS * 2; // 24 half-hour slots = 12 hours
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const currentSlot = currentSlotForWindow(row, hourly);
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const endSlot = Math.min(totalHalfHours - 1, Math.max(windowSlots - 1, currentSlot + 8));
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const startSlot = Math.max(0, endSlot - windowSlots + 1);
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return data.slice(startSlot, endSlot + 1);
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}
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function parseTemperatureOptionsFromText(value?: string | null) {
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const raw = String(value || "");
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const matches = raw.match(/-?\d+(?:\.\d+)?/g) || [];
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return matches
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.map((item) => Number(item))
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.filter((item) => Number.isFinite(item) && item > -80 && item < 80);
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}
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function buildMarketTemperatureOptions(row: ScanOpportunityRow | null) {
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const buckets = row?.distribution_full?.length
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? row.distribution_full
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: row?.distribution_preview;
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const values = new Set<number>();
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(buckets || []).forEach((bucket) => {
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const value = validNumber(bucket.value);
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if (value !== null) values.add(value);
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parseTemperatureOptionsFromText(bucket.label).forEach((item) => values.add(item));
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});
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[
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row?.target_lower,
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row?.target_upper,
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row?.target_value,
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row?.target_threshold,
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].forEach((value) => {
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const numeric = validNumber(value);
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if (numeric !== null) values.add(numeric);
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});
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parseTemperatureOptionsFromText(row?.target_label).forEach((item) => values.add(item));
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parseTemperatureOptionsFromText(row?.market_question).forEach((item) => values.add(item));
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const sorted = [...values].sort((a, b) => a - b);
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if (sorted.length) return sorted;
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const threshold = validNumber(row?.target_threshold) ?? validNumber(row?.target_value);
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if (threshold === null) return null;
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return [threshold - 2, threshold - 1, threshold, threshold + 1, threshold + 2];
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}
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function buildChartDomain(
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marketTicks: number[] | null,
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series: EvidenceSeries[],
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): [number, number] | ["auto", "auto"] {
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const values = series
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.flatMap((item) => item.values)
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.filter((value): value is number => validNumber(value) !== null);
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const domainValues = [...(marketTicks || []), ...values];
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if (!domainValues.length) return ["auto", "auto"];
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const min = Math.min(...domainValues);
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const max = Math.max(...domainValues);
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const span = Math.max(1, max - min);
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const padding = Math.max(0.5, span * 0.08);
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return [Number((min - padding).toFixed(1)), Number((max + padding).toFixed(1))];
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}
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export function LiveTemperatureThresholdChart({
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isEn,
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row,
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}: {
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isEn: boolean;
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row: ScanOpportunityRow | null;
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}) {
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const [hourly, setHourly] = useState<HourlyForecast>(null);
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const city = String(row?.city || "").toLowerCase().trim();
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useEffect(() => {
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setHourly(null);
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if (!city) return;
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let cancelled = false;
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fetch(`/api/city/${encodeURIComponent(city)}/detail?depth=panel&force_refresh=false`, {
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cache: "no-store",
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headers: { Accept: "application/json" },
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})
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.then(async (res) => {
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if (!res.ok) return null;
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return res.json() as Promise<CityDetail>;
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})
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.then((json) => {
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if (cancelled || !json?.hourly) return;
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setHourly({
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forecastTodayHigh: json.forecast?.today_high ?? null,
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localTime: json.local_time || null,
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times: json.hourly.times || [],
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temps: json.hourly.temps || [],
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modelCurves: json.models_hourly?.curves || undefined,
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});
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})
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.catch(() => {});
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return () => { cancelled = true; };
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}, [city]);
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const { data, series } = useMemo(() => buildEvidenceChart(row, hourly), [row, hourly]);
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const visibleData = useMemo(() => buildMovingWindowData(data, row, hourly), [data, row, hourly]);
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const threshold = validNumber(row?.target_threshold) ?? validNumber(row?.target_value);
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const modelSummaryCards = useMemo(() => {
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const cards = buildModelSummaryCards(row);
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// Exclude models that already show as hourly curves (from buildModelCurves)
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if (!hourly?.modelCurves) return cards;
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const curveKeys = new Set(Object.keys(hourly.modelCurves));
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return cards.filter((card) => !curveKeys.has(card.label));
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}, [row, hourly]);
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const tableRows = [...series, ...modelSummaryCards]
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.slice(0, 5)
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.map((item) => ({ ...item, ...seriesStats(item.values) }));
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const marketTemperatureTicks = useMemo(() => buildMarketTemperatureOptions(row), [row]);
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const chartDomain = useMemo(
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() => buildChartDomain(marketTemperatureTicks, series),
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[marketTemperatureTicks, series],
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);
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return (
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<Panel title={isEn ? "Live Temperature Trend & Option Threshold Lines" : "实时气温走势与期权阈值线"}>
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<div className="flex h-full min-h-[420px] flex-col">
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<div className="shrink-0 border-b border-slate-200 bg-white px-3 py-2">
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<div className="mb-2 flex items-end justify-between gap-3 text-[10px]">
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<div className="space-y-0.5">
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<div className="font-mono font-black text-teal-700">
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{isEn ? "Settlement live" : "跑道实测"} {temp(validNumber(row?.current_temp))}
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</div>
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<div className="font-mono font-black text-blue-600">
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METAR {temp(validNumber(row?.metar_context?.airport_current_temp ?? row?.metar_context?.last_temp))}
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</div>
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</div>
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<div className="text-right font-mono font-black text-slate-800">
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{isEn ? "Threshold" : "当日阈值"} {temp(threshold)}
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</div>
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</div>
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<div className="grid grid-cols-5 gap-1.5 text-[10px]">
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{tableRows.map((item) => (
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<div
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key={item.key}
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className={clsx(
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"rounded border px-2 py-1.5",
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item.featured ? "border-teal-200 bg-teal-50" : "border-slate-200 bg-slate-50",
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)}
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>
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<div className="flex items-center gap-1">
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<span className="h-1.5 w-4 rounded-full" style={{ backgroundColor: item.color }} />
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<span className="truncate font-black text-slate-700">{item.label}</span>
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</div>
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<div className="mt-1 font-mono text-[10px] text-slate-600">
|
||
{item.key.startsWith("model_summary_") ? (
|
||
<span>{temp(item.latest)}</span>
|
||
) : (
|
||
<div className="grid grid-cols-3 gap-1">
|
||
<span>now: {temp(item.latest)}</span>
|
||
<span>max: {temp(item.high)}</span>
|
||
<span>15m: {item.delta15 === null ? "--" : `${item.delta15 >= 0 ? "+" : ""}${item.delta15.toFixed(1)}°`}</span>
|
||
</div>
|
||
)}
|
||
</div>
|
||
</div>
|
||
))}
|
||
</div>
|
||
</div>
|
||
<div className="relative min-h-0 flex-1 p-2">
|
||
<div className="absolute left-3 top-3 z-10 rounded border border-slate-200 bg-white px-2 py-1 text-[10px] font-black text-slate-800 shadow-sm">
|
||
{rowName(row)} <span className="ml-1 text-teal-600">{row?.target_label || row?.market_direction || ""}</span>
|
||
</div>
|
||
<ResponsiveContainer width="100%" height="100%">
|
||
<ReLineChart data={visibleData} margin={{ top: 16, right: 28, left: 8, bottom: 8 }}>
|
||
<CartesianGrid stroke="#dbe6ef" strokeDasharray="2 2" />
|
||
<XAxis dataKey="label" tick={{ fontSize: 10, fill: "#64748b" }} tickLine={false} axisLine={{ stroke: "#cbd5e1" }} interval={0} />
|
||
<YAxis
|
||
tick={{ fontSize: 10, fill: "#64748b" }}
|
||
tickFormatter={(v) => `${Number(v).toFixed(1)}°`}
|
||
axisLine={{ stroke: "#cbd5e1" }}
|
||
tickLine={false}
|
||
domain={chartDomain}
|
||
ticks={marketTemperatureTicks || undefined}
|
||
/>
|
||
{threshold !== null && (
|
||
<ReferenceLine
|
||
y={threshold}
|
||
stroke="#f97316"
|
||
strokeDasharray="4 3"
|
||
strokeWidth={2}
|
||
label={{ value: `UMA ${threshold.toFixed(1)}°`, fill: "#f97316", fontSize: 10, position: "left" }}
|
||
/>
|
||
)}
|
||
<Tooltip
|
||
contentStyle={{
|
||
border: "1px solid #cbd5e1",
|
||
borderRadius: 4,
|
||
fontSize: 11,
|
||
boxShadow: "0 8px 24px rgba(15,23,42,.12)",
|
||
}}
|
||
formatter={(value: unknown) => `${Number(value).toFixed(2)}°`}
|
||
/>
|
||
{series.map((item) => (
|
||
<Line
|
||
key={item.key}
|
||
dataKey={item.key}
|
||
stroke={item.color}
|
||
strokeWidth={item.featured ? 2.4 : 1.4}
|
||
strokeDasharray={item.dashed ? "4 3" : undefined}
|
||
dot={false}
|
||
isAnimationActive={false}
|
||
name={item.label}
|
||
type={item.smooth ? "monotone" : "stepAfter"}
|
||
/>
|
||
))}
|
||
</ReLineChart>
|
||
</ResponsiveContainer>
|
||
</div>
|
||
{row?.market_slug ? (
|
||
<div className="shrink-0 border-t border-slate-200 px-3 py-2">
|
||
<Link
|
||
href={`https://polymarket.com/event/${row.market_slug.replace(/-?\d+(?:-?\d+)*[cf](?:or\w+)?(?:for\w+)?$/i, "")}`}
|
||
target="_blank"
|
||
rel="noopener noreferrer"
|
||
className="inline-flex items-center gap-1.5 text-[11px] font-bold text-blue-600 hover:text-blue-800 transition-colors"
|
||
>
|
||
<ExternalLink size={12} />
|
||
{isEn ? "View on Polymarket" : "在 Polymarket 查看"}
|
||
</Link>
|
||
</div>
|
||
) : null}
|
||
</div>
|
||
</Panel>
|
||
);
|
||
}
|