2569718930@qq.com
478 lines
17 KiB
TypeScript
478 lines
17 KiB
TypeScript
import { getTemperatureChartData } from "@/lib/chart-utils";
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import type { CityDetail } from "@/lib/dashboard-types";
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import { buildDebBaselinePath } from "@/lib/temperature-chart-paths";
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import {
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buildFullDayChartData,
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mergeHourlyWithLiveObservations,
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mergePatchIntoHourly,
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mergeRowObservationIntoHourly,
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seedHourlyForecastFromRow,
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} from "@/components/dashboard/scan-terminal/temperature-chart-logic";
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function assert(condition: unknown, message: string) {
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if (!condition) throw new Error(message);
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}
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function assertNear(actual: number, expected: number, tolerance: number, message: string) {
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if (Math.abs(actual - expected) > tolerance) {
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throw new Error(`${message}: expected ${expected}±${tolerance}, got ${actual}`);
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}
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}
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export function runTests() {
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const chartData = getTemperatureChartData(
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{
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name: "test-city",
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display_name: "Test City",
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local_date: "2026-05-16",
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local_time: "10:00",
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temp_symbol: "°C",
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hourly: {
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times: [
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"2026-05-16T08:00:00+08:00",
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"2026-05-16T09:00:00+08:00",
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"2026-05-16T10:00:00+08:00",
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"2026-05-16T11:00:00+08:00",
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],
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temps: [20, 22, 24, 26],
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},
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forecast: { today_high: 28 },
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deb: { prediction: 28 },
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} as CityDetail,
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"zh-CN",
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);
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assert(chartData, "temperature chart data should exist for ISO datetime hourly input");
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// hourly max=26, DEB=28 → offset=+2; temps shift from [20,22,24,26] to [22,24,26,28]
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assert(
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chartData?.datasets.debSeries.some((point) => point.labelTime === "08:00" && point.y === 22),
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"temperature chart should normalize ISO hourly times and apply DEB offset based on hourly max",
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);
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assert(
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chartData?.datasets.debSeries.some((point) => point.labelTime === "10:00" && point.y === 26),
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"temperature chart should keep normalized hourly temperatures shifted by offset",
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);
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const correctedHourlyPathChart = buildFullDayChartData(
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{
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city: "shanghai",
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local_date: "2026-05-16",
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local_time: "12:00",
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temp_symbol: "°C",
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deb_prediction: 30,
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tz_offset_seconds: 8 * 3600,
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} as any,
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{
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forecastTodayHigh: 29,
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debPrediction: 30,
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localDate: "2026-05-16",
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localTime: "12:00",
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times: ["10:00", "12:00", "14:00"],
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temps: [24, 29, 25],
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debHourlyPath: {
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source: "deb_hourly_peak_corrected.v1",
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times: ["10:00", "12:00", "14:00"],
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temps: [25.1, 28.0, 26.0],
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},
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} as any,
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true,
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);
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const correctedDebSeries = correctedHourlyPathChart.series.find((item) => item.key === "hourly_forecast");
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const correctedDebValues = correctedHourlyPathChart.data
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.map((item) => item.hourly_forecast)
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.filter((value) => value !== null && value !== undefined);
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assert(correctedDebSeries, "corrected hourly DEB path should still render as DEB Forecast");
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assert(correctedDebValues.includes(28.0), `chart should use backend deb.hourly_path before rebuilding a shifted curve; got ${correctedDebValues.join(",")}`);
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const independentModelTimelineChart = buildFullDayChartData(
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{
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city: "madrid",
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local_date: "2026-06-11",
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local_time: "20:00",
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temp_symbol: "°C",
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tz_offset_seconds: 2 * 3600,
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} as any,
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{
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forecastTodayHigh: 31,
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debPrediction: 31,
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localDate: "2026-06-11",
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localTime: "20:00",
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times: ["08:00", "09:00", "10:00"],
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temps: [20, 25, 22],
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modelTimes: ["15:00", "16:00", "17:00"],
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modelCurves: {
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ECMWF: [24, 32, 25],
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},
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} as any,
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true,
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);
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const independentModelPeak = independentModelTimelineChart.data.find(
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(point) => point.model_curve_ECMWF === 32,
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);
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assert(
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independentModelPeak?.label === "16:00:00",
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`multi-model curves must use models_hourly.times instead of hourly.times; got ${independentModelPeak?.label}`,
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);
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const correctedDetailChart = getTemperatureChartData(
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{
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name: "shanghai",
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display_name: "Shanghai",
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local_date: "2026-05-16",
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local_time: "12:00",
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temp_symbol: "°C",
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hourly: {
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times: ["10:00", "12:00", "14:00"],
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temps: [24, 29, 25],
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},
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forecast: { today_high: 29 },
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deb: {
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prediction: 30,
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hourly_path: {
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source: "deb_hourly_peak_corrected.v1",
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times: ["10:00", "12:00", "14:00"],
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temps: [25.1, 28.0, 26.0],
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},
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},
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} as CityDetail,
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"zh-CN",
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);
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assert(
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correctedDetailChart?.datasets.debSeries.some((point) => point.labelTime === "12:00" && point.y === 28.0),
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"detail temperature chart should use backend deb.hourly_path before fallback baseline",
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);
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const ankaraChartData = getTemperatureChartData(
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{
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name: "ankara",
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display_name: "Ankara",
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local_date: "2026-05-17",
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local_time: "13:00",
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temp_symbol: "°C",
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current: {
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temp: 18,
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obs_time: "2026-05-17T10:50:00Z",
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settlement_source: "mgm",
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},
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forecast: { today_high: null },
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deb: { prediction: 24 },
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mgm: {
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hourly: [
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{ time: "11:00", temp: 19 },
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{ time: "12:00", temp: 21 },
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{ time: "13:00", temp: 22 },
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{ time: "14:00", temp: 23 },
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],
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},
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metar_today_obs: [{ time: "13:00", temp: 22 }],
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} as unknown as CityDetail,
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"zh-CN",
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);
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assert(
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ankaraChartData?.datasets.debSeries.some((point) => point.labelTime === "13:00"),
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"Ankara chart should build the DEB original path from MGM hourly data when Open-Meteo hourly is unavailable",
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);
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assert(
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(ankaraChartData?.datasets.debSeries.length ?? 0) >= 4,
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"Ankara chart should build the DEB original path from MGM hourly data",
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);
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assert(
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ankaraChartData?.datasets.debSeries.some((point) => point.labelTime === "13:00"),
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"Ankara DEB path must include the MGM hourly point at 13:00",
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);
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assert(
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ankaraChartData?.datasets.calibratedFutureSeries.length,
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"Ankara chart should still expose a calibrated path when observation points exist",
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);
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// ── Moscow 场景：forecast.today_high 不可靠 → DEB offset 优先用 hourly 自身 max ──
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const moscowTimes = [
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"00:00", "00:30", "01:00", "01:30", "02:00", "02:30",
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"03:00", "03:30", "04:00", "04:30", "05:00", "05:30",
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"06:00", "06:30", "07:00", "07:30", "08:00", "08:30",
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"09:00", "09:30", "10:00", "10:30", "11:00", "11:30",
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"12:00", "12:30", "13:00", "13:30", "14:00", "14:30",
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"15:00", "15:30", "16:00", "16:30", "17:00", "17:30",
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"18:00", "18:30", "19:00", "19:30", "20:00", "20:30",
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"21:00", "21:30", "22:00", "22:30", "23:00", "23:30",
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];
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const moscowTemps = moscowTimes.map((t) => {
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const h = Number.parseInt(t.split(":")[0], 10);
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// Peak at 15:00 = 24.7, typical diurnal curve
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if (h <= 6) return 12 + h * 1.0;
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if (h <= 12) return 18 + (h - 6) * 0.9;
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if (h <= 15) return 23.4 + (h - 12) * 0.43;
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return 24.7 - (h - 15) * 1.2;
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});
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// Ensure the max is exactly 24.7 at 15:00
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const peakIndex = moscowTimes.indexOf("15:00");
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moscowTemps[peakIndex] = 24.7;
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const moscowBaseline = buildDebBaselinePath(
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moscowTimes,
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moscowTemps,
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24.5, // DEB prediction
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"13:00", // local time
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21.4, // forecast.today_high — unreliable!
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null, // no MGM
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);
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assert(
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Math.abs(moscowBaseline.offset) < 1.0,
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`Moscow: DEB offset should use hourly max (24.7) not forecast.today_high (21.4); got offset=${moscowBaseline.offset}`,
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);
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assertNear(
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moscowBaseline.offset,
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-0.2,
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0.3,
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"Moscow: DEB 24.5 vs hourly max 24.7 → offset ≈ -0.2",
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);
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// 验证后半段曲线没有被整体抬升 +3.1
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const moscowAfternoon = moscowBaseline.debTemps[peakIndex + 6]; // 18:00
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assert(
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moscowAfternoon != null && moscowAfternoon < 22,
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`Moscow 18:00 should not be inflated by unreliable forecast.today_high; got ${moscowAfternoon}`,
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);
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// ── Ankara 部分小时数据：DEB 路径覆盖全天 48 点 ──
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const ankaraPartial = buildDebBaselinePath(
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["11:00", "12:00", "13:00", "14:00"],
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[19, 21, 22, 23],
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24,
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"13:00",
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null,
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null,
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);
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assert(
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ankaraPartial.debTemps.length === 4,
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"Ankara partial: input 4 hours → output 4 points (interpolation handled by fillTemperaturePathForFullDay)",
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);
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// hourly max=23, DEB=24 → offset=+1
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assertNear(ankaraPartial.offset, 1, 0.01, "Ankara partial: hourly max=23, DEB=24 → offset=+1");
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// DEB path should still cover the partial day
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const ankaraValid = ankaraPartial.debTemps.filter((t) => t != null && Number.isFinite(t));
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assert(ankaraValid.length >= 4, "Ankara partial: all input points should be valid");
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// ── 正常城市：完整 hourly → offset 基于 hourly max ──
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const normalHourlyTimes = moscowTimes;
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const normalHourlyTemps = moscowTimes.map((t) => {
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const h = Number.parseInt(t.split(":")[0], 10);
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return 18 + Math.sin(((h - 6) / 12) * Math.PI) * 7; // peak ~25 at 12:00
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});
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const normalBaseline = buildDebBaselinePath(
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normalHourlyTimes,
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normalHourlyTemps,
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27, // DEB 2° above hourly max
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"10:00",
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26, // forecast.today_high close to reality
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null,
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);
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assertNear(
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normalBaseline.offset,
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2.0,
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0.5,
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"Normal city: DEB 27 vs hourly max ~25 → offset ≈ +2",
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);
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// Full 48-point coverage
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assert(
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normalBaseline.debTemps.length === 48,
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"Normal city: full 48-point DEB path",
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);
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assert(
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normalBaseline.debPast.some((t) => t != null) && normalBaseline.debFuture.some((t) => t != null),
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"Normal city: both past and future portions should have data",
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);
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const guangzhouRow = {
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city: "guangzhou",
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local_date: "2026-06-10",
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local_time: "12:45",
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current_temp: 28.4,
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current_max_so_far: 29,
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temp_symbol: "°C",
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tz_offset_seconds: 8 * 3600,
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metar_context: {
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source: "amsc_awos",
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station_label: "AMSC AWOS",
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airport_current_temp: 28.4,
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airport_obs_time: "12:45",
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airport_max_so_far: 29,
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},
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} as any;
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const seededGuangzhou = seedHourlyForecastFromRow(guangzhouRow);
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const guangzhouLiveChart = buildFullDayChartData(guangzhouRow, seededGuangzhou, false);
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const guangzhouSettlementRunway = guangzhouLiveChart.series.find((item) => item.key === "runway_02L_20R");
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assert(
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guangzhouSettlementRunway?.values.some((value) => value === 28.4),
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"row-seeded runway cities must plot the latest scan-row observation immediately instead of waiting for city detail",
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);
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const guangzhouPatched = mergePatchIntoHourly(seededGuangzhou, {
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city: "guangzhou",
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revision: 42,
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changes: {
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temp: 28.8,
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observed_at_local: "12:48",
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obs_time: "12:48",
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source: "amsc_awos",
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runway_points: [{ runway: "02L/20R", temp: 28.8 }],
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},
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});
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const guangzhouPatchedChart = buildFullDayChartData(guangzhouRow, guangzhouPatched, false);
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const patchedRunway = guangzhouPatchedChart.series.find((item) => item.key === "runway_02L_20R");
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assert(
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patchedRunway?.values.some((value) => value === 28.8),
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"SSE runway patches must append directly to the chart series without waiting for a force-refreshed detail payload",
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);
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const guangzhouLaterRow = {
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...guangzhouRow,
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current_temp: 29.1,
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local_time: "12:51",
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sse_revision: 43,
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metar_context: {
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...guangzhouRow.metar_context,
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airport_current_temp: 29.1,
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airport_obs_time: "12:51",
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airport_max_so_far: 29.1,
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},
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} as any;
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const guangzhouRowMerged = mergeRowObservationIntoHourly(seededGuangzhou, guangzhouLaterRow);
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const guangzhouRowMergedChart = buildFullDayChartData(guangzhouLaterRow, guangzhouRowMerged, false);
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const rowMergedRunway = guangzhouRowMergedChart.series.find((item) => item.key === "runway_02L_20R");
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assert(
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rowMergedRunway?.values.some((value) => value === 29.1),
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"same-city scan row observation changes must merge into chart state without requiring an active-slot click",
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);
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const staleDetail = {
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...seededGuangzhou,
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forecastDaily: [{ date: "2026-06-10", max_temp: 31, min_temp: 24 }] as any,
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probabilities: { engine: "legacy", distribution: [{ value: 30, probability: 0.4 }] },
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runwayPlateHistory: {
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"02L/20R": [{ timestamp: "12:45", temp_c: 28.4, value: 28.4 }],
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},
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airportPrimaryTodayObs: [["12:45", 28.4]],
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airportCurrent: { temp: 28.4, obs_time: "12:45", max_so_far: 29 },
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airportPrimary: { temp: 28.4, obs_time: "12:45", max_so_far: 29 },
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} as any;
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const mergedAfterStaleDetail = mergeHourlyWithLiveObservations(staleDetail, guangzhouPatched, guangzhouRow);
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const mergedAfterStaleDetailChart = buildFullDayChartData(guangzhouRow, mergedAfterStaleDetail, false);
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const preservedPatchRunway = mergedAfterStaleDetailChart.series.find((item) => item.key === "runway_02L_20R");
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assert(
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preservedPatchRunway?.values.some((value) => value === 28.8),
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"stale full-detail responses must not overwrite a newer live SSE observation point",
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);
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const olderAutoRefreshDetail = {
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...seededGuangzhou,
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localDate: "2026-06-10",
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localTime: "12:45",
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times: ["12:00", "12:45"],
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temps: [27.8, 28.4],
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probabilities: { engine: "stale", distribution: [{ value: 28, probability: 0.2 }] },
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runwayPlateHistory: {
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"02L/20R": [{ timestamp: "12:45", temp_c: 28.4, value: 28.4 }],
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},
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airportCurrent: { temp: 28.4, obs_time: "12:45", max_so_far: 28.4 },
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airportPrimary: { temp: 28.4, obs_time: "12:45", max_so_far: 28.4 },
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airportPrimaryTodayObs: [["12:45", 28.4]],
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} as any;
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const newerVisibleDetail = {
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...seededGuangzhou,
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localDate: "2026-06-10",
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localTime: "12:55",
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times: ["12:00", "12:55"],
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temps: [27.8, 29.2],
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probabilities: { engine: "fresh", distribution: [{ value: 29, probability: 0.7 }] },
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runwayPlateHistory: {
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"02L/20R": [{ timestamp: "12:55", temp_c: 29.2, value: 29.2 }],
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},
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airportCurrent: { temp: 29.2, obs_time: "12:55", max_so_far: 29.2 },
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airportPrimary: { temp: 29.2, obs_time: "12:55", max_so_far: 29.2 },
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airportPrimaryTodayObs: [["12:55", 29.2]],
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} as any;
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const mergedAfterOlderAutoRefresh = mergeHourlyWithLiveObservations(
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olderAutoRefreshDetail,
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newerVisibleDetail,
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guangzhouRow,
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);
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assert(
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mergedAfterOlderAutoRefresh?.times.includes("12:55") &&
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!mergedAfterOlderAutoRefresh?.times.includes("12:45"),
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"older automatic detail refreshes must not roll a newer visible chart curve back to stale timestamps",
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);
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assert(
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mergedAfterOlderAutoRefresh?.probabilities?.engine === "fresh",
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"older automatic detail refreshes must preserve the newer visible chart probability payload",
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);
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const chengduDetail = {
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forecastTodayHigh: null,
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debPrediction: 31,
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debQuality: null,
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debHourlyPath: null,
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localDate: "2026-06-10",
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localTime: "13:46",
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times: [],
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temps: [],
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modelCurves: undefined,
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runwayPlateHistory: {
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"02L/20R": [
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{ timestamp: "13:35", temp_c: 29.6, value: 29.6 },
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{ timestamp: "13:39", temp_c: 29.8, value: 29.8 },
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{ timestamp: "13:43", temp_c: 30.4, value: 30.4 },
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],
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},
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runwayBandHistory: undefined,
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amos: null,
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current: null,
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airportCurrent: { temp: 28, obs_time: "13:00", max_so_far: 28 },
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airportPrimary: { temp: 28, obs_time: "13:00", max_so_far: 28 },
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forecastDaily: [],
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multiModelDaily: {},
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probabilities: null,
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airportPrimaryTodayObs: [["13:00", 28]],
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} as any;
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|
const staleChengduRow = {
|
|
city: "chengdu",
|
|
local_date: "2026-06-07",
|
|
local_time: "21:37",
|
|
current_temp: 21.0,
|
|
current_max_so_far: 25.0,
|
|
temp_symbol: "°C",
|
|
tz_offset_seconds: 8 * 3600,
|
|
runway_plate_history: {
|
|
"02L/20R": [
|
|
{ time: "2026-06-07T13:20:00+00:00", temp: 21.2 },
|
|
{ time: "2026-06-07T13:30:00+00:00", temp: 21.4 },
|
|
],
|
|
},
|
|
} as any;
|
|
const chengduMerged = mergeRowObservationIntoHourly(chengduDetail, staleChengduRow);
|
|
const chengduChart = buildFullDayChartData(
|
|
{
|
|
city: "chengdu",
|
|
local_date: "2026-06-10",
|
|
local_time: "13:46",
|
|
temp_symbol: "°C",
|
|
tz_offset_seconds: 8 * 3600,
|
|
} as any,
|
|
chengduMerged,
|
|
false,
|
|
);
|
|
const chengduSettlementRunway = chengduChart.series.find((item) => item.key === "runway_02L_20R");
|
|
assert(
|
|
chengduSettlementRunway?.values.some((value) => value === 30.4),
|
|
"current-date Chengdu detail runway history should remain visible after receiving a stale scan row",
|
|
);
|
|
assert(
|
|
!chengduSettlementRunway?.values.some((value) => value !== null && value <= 22),
|
|
"stale previous-day Chengdu scan rows must not append a fake latest runway point to current-date detail",
|
|
);
|
|
assert(
|
|
chengduMerged?.airportCurrent?.temp === 28,
|
|
"stale previous-day scan rows must not replace current-date detail airport conditions",
|
|
);
|
|
}
|