Files
PolyWeather/frontend/lib/model-summary.ts
T
2026-06-29 21:17:04 +08:00

206 lines
6.6 KiB
TypeScript

import type { ScanOpportunityRow } from "@/lib/dashboard-types";
import {
REGIONS,
getCityRegion,
} from "@/components/dashboard/scan-terminal/continent-grouping";
export const MODEL_SUMMARY_MODEL_COLUMNS = [
{ key: "ECMWF", label: "ECMWF" },
{ key: "ECMWF AIFS", label: "ECMWF AIFS" },
{ key: "GFS", label: "GFS" },
{ key: "ICON", label: "ICON" },
{ key: "ICON-EU", label: "ICON-EU" },
{ key: "GEM", label: "GEM" },
{ key: "GDPS", label: "GDPS" },
{ key: "JMA", label: "JMA" },
{ key: "AROME HD", label: "AROME HD" },
{ key: "HRRR", label: "HRRR" },
{ key: "NAM", label: "NAM" },
] as const;
export type ModelSummaryColumnKey = (typeof MODEL_SUMMARY_MODEL_COLUMNS)[number]["key"];
export type ModelSummaryRow = {
cityKey: string;
cityName: string;
regionLabel: string;
regionLabelZh: string;
regionSort: number;
tempSymbol: string;
localTime: string;
timezoneOffsetSeconds: number | null;
debPrediction: number | null;
models: Record<ModelSummaryColumnKey, number | null>;
modelMedian: number | null;
modelSpread: number | null;
searchText: string;
};
export type ModelSummaryFilters = {
query: string;
debOnly: boolean;
wideSpreadOnly: boolean;
};
const WIDE_SPREAD_THRESHOLD = 2;
function finiteNumber(value: unknown): number | null {
if (value == null) return null;
if (typeof value === "string" && value.trim() === "") return null;
const numericValue = Number(value);
return Number.isFinite(numericValue) ? numericValue : null;
}
function roundToOneDecimal(value: number) {
return Math.round(value * 10) / 10;
}
function median(values: number[]) {
if (!values.length) return null;
const sorted = [...values].sort((a, b) => a - b);
const mid = Math.floor(sorted.length / 2);
if (sorted.length % 2 === 1) return roundToOneDecimal(sorted[mid]);
return roundToOneDecimal((sorted[mid - 1] + sorted[mid]) / 2);
}
function spread(values: number[]) {
if (!values.length) return null;
return roundToOneDecimal(Math.max(...values) - Math.min(...values));
}
function normalizeCityKey(row: ScanOpportunityRow, index: number) {
const rawKey = row.city || row.city_display_name || row.display_name || `row-${index}`;
return String(rawKey).trim().toLowerCase();
}
function normalizeLocalTime(value: unknown) {
const text = String(value || "").trim();
if (!text) return "";
const match = text.match(/(\d{1,2}):(\d{2})/);
if (!match) return text;
return `${match[1].padStart(2, "0")}:${match[2]}`;
}
function resolveRegion(row: ScanOpportunityRow, isEn: boolean) {
const configuredRegionKey = getCityRegion(row);
const configuredRegion = configuredRegionKey
? REGIONS.find((region) => region.key === configuredRegionKey)
: null;
if (configuredRegion) {
return {
label: isEn ? configuredRegion.labelEn : configuredRegion.labelZh,
labelEn: configuredRegion.labelEn,
labelZh: configuredRegion.labelZh,
sort: configuredRegion.sort,
};
}
const labelEn = row.trading_region_label || row.trading_region_label_zh || "—";
const labelZh = row.trading_region_label_zh || row.trading_region_label || "—";
return {
label: isEn ? labelEn : labelZh,
labelEn,
labelZh,
sort: finiteNumber(row.trading_region_sort) ?? 999,
};
}
export function formatModelSummaryTemp(value: number | null | undefined, symbol = "°C") {
const numericValue = finiteNumber(value);
if (numericValue == null) return "—";
return `${numericValue.toFixed(1)}${symbol || "°C"}`;
}
export function formatModelSummaryLocalTime(
row: Pick<ModelSummaryRow, "localTime" | "timezoneOffsetSeconds">,
nowMs: number | null | undefined = Date.now(),
) {
const offsetSeconds = finiteNumber(row.timezoneOffsetSeconds);
const timestampMs = finiteNumber(nowMs);
if (offsetSeconds == null || timestampMs == null) return row.localTime || "—";
const localDate = new Date(timestampMs + offsetSeconds * 1000);
const hours = String(localDate.getUTCHours()).padStart(2, "0");
const minutes = String(localDate.getUTCMinutes()).padStart(2, "0");
return `${hours}:${minutes}`;
}
export function buildModelSummaryRows(
rows: ScanOpportunityRow[],
isEn: boolean,
): ModelSummaryRow[] {
const byCity = new Map<string, ModelSummaryRow>();
rows.forEach((row, index) => {
const cityKey = normalizeCityKey(row, index);
if (byCity.has(cityKey)) return;
const cityName = row.city_display_name || row.display_name || row.city || "—";
const region = resolveRegion(row, isEn);
const rawModelSources = row.model_cluster_sources || {};
const models = MODEL_SUMMARY_MODEL_COLUMNS.reduce(
(acc, column) => {
acc[column.key] = finiteNumber(rawModelSources[column.key]);
return acc;
},
{} as Record<ModelSummaryColumnKey, number | null>,
);
const modelValues = MODEL_SUMMARY_MODEL_COLUMNS.map((column) => models[column.key]).filter(
(value): value is number => value != null,
);
const modelSearchText = MODEL_SUMMARY_MODEL_COLUMNS.filter(
(column) => models[column.key] != null,
)
.map((column) => column.label)
.join(" ");
byCity.set(cityKey, {
cityKey,
cityName,
regionLabel: region.label,
regionLabelZh: region.labelZh,
regionSort: region.sort,
tempSymbol: row.temp_symbol || "°C",
localTime: normalizeLocalTime(row.local_time),
timezoneOffsetSeconds: finiteNumber(row.tz_offset_seconds),
debPrediction: finiteNumber(row.deb_prediction),
models,
modelMedian: median(modelValues),
modelSpread: spread(modelValues),
searchText: `${cityName} ${row.city || ""} ${region.labelEn} ${region.labelZh} ${modelSearchText}`.toLowerCase(),
});
});
return [...byCity.values()].sort((a, b) => {
if (a.regionSort !== b.regionSort) return a.regionSort - b.regionSort;
return a.cityName.localeCompare(b.cityName, isEn ? "en" : "zh-CN", {
sensitivity: "base",
});
});
}
export function filterModelSummaryRows(
rows: ModelSummaryRow[],
filters: ModelSummaryFilters,
): ModelSummaryRow[] {
const query = filters.query.trim().toLowerCase();
return rows.filter((row) => {
if (query && !row.searchText.includes(query)) return false;
if (filters.debOnly && row.debPrediction == null) return false;
if (
filters.wideSpreadOnly &&
(row.modelSpread == null || row.modelSpread < WIDE_SPREAD_THRESHOLD)
) {
return false;
}
return true;
});
}
export function hasModelSummaryForecastData(rows: ModelSummaryRow[]) {
return rows.some((row) => {
if (row.debPrediction != null) return true;
return MODEL_SUMMARY_MODEL_COLUMNS.some((column) => row.models[column.key] != null);
});
}