2569718930@qq.com
720 lines
26 KiB
Python
720 lines
26 KiB
Python
import threading
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from datetime import datetime, timedelta, timezone
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from pathlib import Path
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from typing import Any
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import pytest
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import yaml
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from src.data_collection.country_networks import build_country_network_snapshot
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from src.data_collection.city_registry import ALIASES, CITY_REGISTRY
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from src.data_collection.city_time import CITY_TIME_ZONES, get_city_utc_offset_seconds
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from src.data_collection import metar_sources
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from src.data_collection.metar_sources import MetarSourceMixin
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from web.analysis_service import (
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_build_city_detail_payload,
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_build_intraday_meteorology,
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_should_build_country_network_snapshot,
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)
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from web.core import CITIES
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class _DummyMetarSource(MetarSourceMixin):
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CITY_REGISTRY = CITY_REGISTRY
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CITY_TO_ICAO = {key: value["icao"] for key, value in CITY_REGISTRY.items() if value.get("icao")}
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metar_cache_ttl_sec = 600
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metar_fast_cache_ttl_sec = 60
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def __init__(self):
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self._metar_cache = {}
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self._metar_cache_lock = threading.Lock()
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self.metar_timeout_sec = 0.0
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self.metar_latest_timeout_sec = 0.0
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self.timeout = 0.0
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self._http_get: Any = None
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def test_new_city_registry_entries_are_wired():
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assert CITY_REGISTRY["manila"]["settlement_source"] == "wunderground"
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assert CITY_REGISTRY["manila"]["settlement_station_code"] == "RPLL"
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assert CITY_REGISTRY["karachi"]["settlement_source"] == "wunderground"
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assert CITY_REGISTRY["karachi"]["settlement_station_code"] == "OPKC"
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assert CITY_REGISTRY["qingdao"]["settlement_source"] == "wunderground"
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assert CITY_REGISTRY["qingdao"]["settlement_station_code"] == "ZSQD"
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assert ALIASES["rpll"] == "manila"
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assert ALIASES["opkc"] == "karachi"
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assert ALIASES["zsqd"] == "qingdao"
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assert CITIES["manila"]["lat"] == CITY_REGISTRY["manila"]["lat"]
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assert CITIES["karachi"]["lon"] == CITY_REGISTRY["karachi"]["lon"]
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assert CITIES["qingdao"]["lat"] == CITY_REGISTRY["qingdao"]["lat"]
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def test_city_time_zone_mapping_covers_every_city_and_dst_offsets():
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missing = sorted(set(CITY_REGISTRY) - set(CITY_TIME_ZONES))
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assert missing == []
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april = datetime(2026, 4, 19, 6, 30, tzinfo=timezone.utc)
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assert get_city_utc_offset_seconds("guangzhou", april) == 28800
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assert get_city_utc_offset_seconds("qingdao", april) == 28800
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assert get_city_utc_offset_seconds("ankara", april) == 10800
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assert get_city_utc_offset_seconds("london", april) == 3600
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assert get_city_utc_offset_seconds("paris", april) == 7200
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assert get_city_utc_offset_seconds("new york", april) == -14400
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assert get_city_utc_offset_seconds("chicago", april) == -18000
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assert get_city_utc_offset_seconds("los angeles", april) == -25200
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assert get_city_utc_offset_seconds("wellington", april) == 43200
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def test_paris_registry_uses_le_bourget_anchor():
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paris = CITY_REGISTRY["paris"]
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assert paris["icao"] == "LFPB"
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assert paris["settlement_source"] == "aeroweb"
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assert paris["settlement_station_code"] == "LFPB"
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settlement_url = paris.get("settlement_url")
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assert isinstance(settlement_url, str)
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assert "bonneuil-en-france/LFPB" in settlement_url
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assert CITIES["paris"]["lat"] == paris["lat"]
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assert CITIES["paris"]["settlement_source"] == "aeroweb"
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assert _DummyMetarSource.CITY_TO_ICAO["paris"] == "LFPB"
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def test_new_york_config_uses_registry_airport_anchor():
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config_path = Path(__file__).resolve().parents[1] / "config" / "config.yaml"
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config = yaml.safe_load(config_path.read_text(encoding="utf-8"))
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city_config = next(city for city in config["cities"] if city["id"] == "new_york")
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registry = CITY_REGISTRY["new york"]
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assert city_config["latitude"] == pytest.approx(registry["lat"])
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assert city_config["longitude"] == pytest.approx(registry["lon"])
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def test_turkey_metar_uses_fast_cache_ttl():
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source = _DummyMetarSource()
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assert source._metar_cache_ttl_for_city("ankara", "LTAC") == 60
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assert source._metar_cache_ttl_for_city("istanbul", "LTFM") == 60
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assert source._metar_cache_ttl_for_city("karachi", "OPKC") == 600
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def test_metar_marks_previous_local_day_report_stale(monkeypatch):
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class FixedDateTime(datetime):
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@classmethod
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def now(cls, tz=None): # type: ignore
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value = datetime(2026, 4, 21, 12, 0, tzinfo=timezone.utc)
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return value if tz is None else value.astimezone(tz)
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@classmethod
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def utcnow(cls): # type: ignore
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return datetime(2026, 4, 21, 12, 0)
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class FakeResponse:
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def raise_for_status(self):
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return None
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def json(self):
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return [
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{
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"rawOb": "METAR OPKC 200600Z 00000KT 9999 SCT015 26/25 Q1012",
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"reportTime": "2026-04-20T06:00:00Z",
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"receiptTime": "2026-04-20T06:12:07Z",
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"temp": 26,
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"dewp": 25,
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"name": "Jinnah International Airport",
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}
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]
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source = _DummyMetarSource()
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source._metar_cache = {}
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source._metar_cache_lock = threading.Lock()
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source.metar_timeout_sec = 1
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source.metar_latest_timeout_sec = 1
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source.timeout = 1
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source._http_get = lambda *args, **kwargs: FakeResponse()
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monkeypatch.setattr(metar_sources, "datetime", FixedDateTime)
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result = source.fetch_metar("karachi", utc_offset=18000)
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assert result is not None
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assert result["stale_for_today"] is True
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assert result["observation_local_date"] == "2026-04-20"
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assert result["current_local_date"] == "2026-04-21"
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assert result["today_obs"] == []
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def test_turkey_mgm_provider_returns_official_nearby_rows():
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anchor_time = datetime.now(timezone.utc).replace(microsecond=0)
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station_time = anchor_time + timedelta(minutes=8)
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raw = {
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"metar": {
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"observation_time": anchor_time.isoformat().replace("+00:00", "Z"),
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"current": {"temp": 16.0},
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},
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"mgm_nearby": [
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{
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"name": "Airport (MGM/17128)",
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"istNo": "17128",
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"lat": 40.1,
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"lon": 32.9,
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"temp": 17.1,
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"obs_time": station_time.isoformat().replace("+00:00", "Z"),
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}
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],
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}
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snapshot = build_country_network_snapshot("ankara", raw)
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assert snapshot["provider_code"] == "turkey_mgm"
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assert snapshot["official_network_status"]["available"] is True
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assert snapshot["official_nearby"][0]["source_code"] == "mgm"
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assert snapshot["official_nearby"][0]["is_official"] is True
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assert snapshot["official_nearby"][0]["time_delta_vs_anchor_minutes"] == 8
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assert snapshot["official_nearby"][0]["sync_status"] == "synced"
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assert snapshot["official_nearby"][0]["usable_for_intraday"] is True
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assert snapshot["official_network_status"]["usable_row_count"] == 1
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def test_turkey_mgm_primary_today_obs_uses_mgm_airport_history_not_metar():
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raw = {
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"metar": {
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"observation_time": "2026-05-29T11:50:00Z",
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"today_obs": [{"time": "14:50", "temp": 17.0}],
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"current": {"temp": 17.0},
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},
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"mgm": {
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"obs_time": "2026-05-29T11:56:00Z",
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"current": {"temp": 17.3},
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},
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"mgm_today_obs": [{"time": "14:56", "temp": 17.3}],
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}
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snapshot = build_country_network_snapshot("ankara", raw)
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assert snapshot["airport_primary_current"]["source_code"] == "mgm"
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assert snapshot["airport_primary_today_obs"] == [{"time": "14:56", "temp": 17.3}]
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def test_panel_mode_still_builds_turkey_mgm_airport_snapshot():
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raw = {
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"mgm": {
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"obs_time": "2026-05-29T11:56:00Z",
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"current": {"temp": 17.3},
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}
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}
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assert (
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_should_build_country_network_snapshot(
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"ankara", raw, is_panel_mode=True, is_market_mode=False
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)
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is True
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)
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assert (
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_should_build_country_network_snapshot(
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"istanbul", raw, is_panel_mode=True, is_market_mode=False
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)
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is True
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)
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assert (
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_should_build_country_network_snapshot(
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"guangzhou", raw, is_panel_mode=True, is_market_mode=False
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)
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is False
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)
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assert (
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_should_build_country_network_snapshot(
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"ankara", raw, is_panel_mode=False, is_market_mode=False
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)
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is True
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)
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assert (
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_should_build_country_network_snapshot(
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"ankara", raw, is_panel_mode=True, is_market_mode=True
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)
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is False
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)
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def test_nearby_station_timing_marks_stale_rows_unusable_for_network_signal():
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anchor_time = datetime.now(timezone.utc).replace(microsecond=0)
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fresh_time = anchor_time + timedelta(minutes=20)
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stale_time = anchor_time - timedelta(minutes=90)
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raw = {
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"metar": {
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"observation_time": anchor_time.isoformat().replace("+00:00", "Z"),
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"current": {"temp": 20.0},
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},
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"mgm_nearby": [
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{
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"name": "Fresh",
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"istNo": "100",
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"lat": 40.1,
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"lon": 32.9,
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"temp": 21.0,
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"obs_time": fresh_time.isoformat().replace("+00:00", "Z"),
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},
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{
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"name": "Stale Hot",
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"istNo": "101",
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"lat": 40.2,
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"lon": 33.0,
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"temp": 26.0,
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"obs_time": stale_time.isoformat().replace("+00:00", "Z"),
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},
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],
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}
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snapshot = build_country_network_snapshot("ankara", raw)
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stale = next(row for row in snapshot["official_nearby"] if row["station_label"] == "Stale Hot")
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assert stale["sync_status"] == "stale"
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assert stale["usable_for_intraday"] is False
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assert snapshot["official_network_status"]["stale_row_count"] == 1
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assert snapshot["network_lead_signal"]["leader_station_label"] == "Fresh"
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assert snapshot["airport_vs_network_delta"] == 1.0
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def test_china_provider_falls_back_to_metar_cluster_without_replacing_airport_anchor():
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raw = {
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"metar": {
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"observation_time": "2026-04-06T10:00:00.000Z",
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"current": {"temp": 22.5},
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},
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"mgm_nearby": [
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{
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"name": "Hongqiao",
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"icao": "ZSSS",
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"lat": 31.2,
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"lon": 121.3,
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"temp": 23.1,
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}
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],
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}
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snapshot = build_country_network_snapshot("shanghai", raw)
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assert snapshot["provider_code"] == "china_cma"
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assert snapshot["airport_primary_current"]["source_code"] == "metar"
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assert snapshot["airport_primary_current"]["is_airport_station"] is True
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assert snapshot["official_nearby"][0]["source_code"] == "metar_cluster"
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assert snapshot["official_nearby"][0]["is_official"] is False
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def test_metar_cluster_obs_time_label_uses_city_local_time():
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raw = {
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"metar": {
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"observation_time": "2026-04-19T06:30:00.000Z",
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"current": {"temp": 32.0},
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},
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"mgm_nearby": [
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{
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"name": "Guangzhou/Baiyun",
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"icao": "ZGGG",
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"lat": 23.39,
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"lon": 113.30,
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"temp": 32.0,
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"obs_time": "2026-04-19T06:30:00.000Z",
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}
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],
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}
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snapshot = build_country_network_snapshot("guangzhou", raw)
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row = snapshot["official_nearby"][0]
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assert row["source_code"] == "metar_cluster"
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assert row["obs_time_label"] == "14:30"
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assert row["obs_time_display_tz"] == "city_local"
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def test_metar_cluster_obs_time_label_uses_dst_aware_city_time():
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raw = {
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"metar": {
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"observation_time": "2026-04-19T06:30:00.000Z",
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"current": {"temp": 12.0},
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},
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"mgm_nearby": [
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{
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"name": "London test",
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"icao": "EGLC",
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"lat": 51.50,
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"lon": -0.05,
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"temp": 12.0,
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"obs_time": "2026-04-19T06:30:00.000Z",
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}
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],
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}
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snapshot = build_country_network_snapshot("london", raw)
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row = snapshot["official_nearby"][0]
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assert row["source_code"] == "metar_cluster"
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assert row["obs_time_label"] == "07:30"
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def test_metar_cluster_naive_obs_time_is_interpreted_as_utc_before_city_display():
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raw = {
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"metar": {
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"observation_time": "2026-04-19 08:00",
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"current": {"temp": 4.0},
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},
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"mgm_nearby": [
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{
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"name": "Moscow/Vnukovo",
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"icao": "UUWW",
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"lat": 55.59,
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"lon": 37.26,
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"temp": 4.0,
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"obs_time": "2026-04-19 08:00",
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}
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],
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}
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snapshot = build_country_network_snapshot("moscow", raw)
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row = snapshot["official_nearby"][0]
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assert row["source_code"] == "metar_cluster"
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assert row["obs_time_label"] == "11:00"
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assert row["obs_time_display_tz"] == "city_local"
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def test_hko_provider_marks_explicit_official_station_as_anchor():
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raw = {
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"settlement_current": {
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"station_code": "LFS",
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"station_name": "shenzhen",
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"observation_time": "2026-04-06T10:00:00+08:00",
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"current": {"temp": 25.0},
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}
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}
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snapshot = build_country_network_snapshot("shenzhen", raw)
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assert snapshot["provider_code"] == "hongkong_hko"
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assert snapshot["settlement_station"]["is_official_station_anchor"] is True
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assert snapshot["official_nearby"][0]["is_settlement_anchor"] is True
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assert snapshot["official_nearby"][0]["station_code"] == "LFS"
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def test_hong_kong_cowin_primary_uses_station_6087_history(monkeypatch):
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from src.database import runtime_state
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requested = {}
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class FakeOfficialIntradayObservationRepository:
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def load_points(self, *, source_code, station_code, target_date):
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requested["source_code"] = source_code
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requested["station_code"] = station_code
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requested["target_date"] = target_date
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if source_code == "cowin_obs" and station_code == "6087":
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return [
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{"time": "10:40", "temp": 31.1},
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{"time": "10:41", "temp": 31.3},
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]
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return []
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monkeypatch.setattr(
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runtime_state,
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"OfficialIntradayObservationRepository",
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FakeOfficialIntradayObservationRepository,
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)
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snapshot = build_country_network_snapshot(
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"hong kong",
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{
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"cowin_current": {
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"temp": 31.3,
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"obs_time": "2026-05-27T02:41:00Z",
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"istNo": "6087",
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"icao": "COWIN6087",
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"station_label": "保良局陳守仁小學 1min (CoWIN)",
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},
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"settlement_current": {
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"station_code": "HKO",
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"station_name": "HK Observatory",
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"observation_time": "2026-05-27T10:40:00+08:00",
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"current": {"temp": 31.2},
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},
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},
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)
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assert snapshot["airport_primary_current"]["source_code"] == "cowin_obs"
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assert snapshot["airport_primary_current"]["station_code"] == "6087"
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assert "陳守仁" in snapshot["airport_primary_current"]["station_label"]
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assert requested["station_code"] == "6087"
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assert snapshot["airport_primary_today_obs"] == [
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{"time": "10:40", "temp": 31.1},
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{"time": "10:41", "temp": 31.3},
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]
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def test_hong_kong_cowin_primary_prefers_live_intraday_series(monkeypatch):
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from src.database import runtime_state
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class FakeOfficialIntradayObservationRepository:
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def load_points(self, *, source_code, station_code, target_date):
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return [{"time": "09:00", "temp": 30.0}]
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monkeypatch.setattr(
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runtime_state,
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"OfficialIntradayObservationRepository",
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FakeOfficialIntradayObservationRepository,
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)
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snapshot = build_country_network_snapshot(
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"hong kong",
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{
|
|
"cowin_current": {
|
|
"temp": 31.3,
|
|
"obs_time": "2026-05-27T02:41:00Z",
|
|
"istNo": "6087",
|
|
"icao": "COWIN6087",
|
|
"station_label": "保良局陳守仁小學 1min (CoWIN)",
|
|
},
|
|
"cowin_today_obs": [
|
|
{"time": "10:40", "temp": 31.1},
|
|
{"time": "10:41", "temp": 31.3},
|
|
],
|
|
"settlement_current": {
|
|
"station_code": "HKO",
|
|
"station_name": "HK Observatory",
|
|
"observation_time": "2026-05-27T10:40:00+08:00",
|
|
"current": {"temp": 31.2},
|
|
},
|
|
},
|
|
)
|
|
|
|
assert snapshot["airport_primary_current"]["source_code"] == "cowin_obs"
|
|
assert snapshot["airport_primary_today_obs"] == [
|
|
{"time": "10:40", "temp": 31.1},
|
|
{"time": "10:41", "temp": 31.3},
|
|
]
|
|
|
|
|
|
def test_moscow_provider_uses_realtime_metar_cluster_not_station_archive_rows():
|
|
raw = {
|
|
"metar": {
|
|
"observation_time": "2026-04-06T10:00:00.000Z",
|
|
"current": {"temp": 11.0},
|
|
},
|
|
"ru_official_nearby": [
|
|
{
|
|
"station_code": "27524",
|
|
"station_label": "Vnukovo",
|
|
"lat": 55.5870,
|
|
"lon": 37.2500,
|
|
"temp": 12.3,
|
|
"obs_time": "2026-04-06T09:00:00+00:00",
|
|
"is_airport_station": True,
|
|
"page_url": "https://www.pogodaiklimat.ru/weather.php?id=27524",
|
|
}
|
|
],
|
|
"mgm_nearby": [
|
|
{
|
|
"name": "Sheremetyevo",
|
|
"icao": "UUEE",
|
|
"lat": 55.97,
|
|
"lon": 37.41,
|
|
"temp": 12.0,
|
|
}
|
|
],
|
|
}
|
|
|
|
snapshot = build_country_network_snapshot("moscow", raw)
|
|
|
|
assert snapshot["provider_code"] == "global_metar"
|
|
assert snapshot["official_network_status"]["available"] is True
|
|
assert snapshot["official_network_status"]["mode"] == "fallback_metar_cluster"
|
|
assert snapshot["official_nearby"][0]["source_code"] == "metar_cluster"
|
|
assert snapshot["official_nearby"][0]["is_airport_station"] is True
|
|
|
|
|
|
def test_us_madis_airport_primary_uses_city_display_unit():
|
|
raw = {
|
|
"madis_hfmetar_current": {
|
|
"icao": "KHOU",
|
|
"temp_c": 19.4,
|
|
"temp": 66.9,
|
|
"obs_time": "2026-05-27T17:00:00+00:00",
|
|
"wind_kt": 8.0,
|
|
},
|
|
"metar": {
|
|
"observation_time": "2026-05-27T17:00:00+00:00",
|
|
"current": {
|
|
"temp": 66.9,
|
|
"max_temp_so_far": 84.9,
|
|
},
|
|
},
|
|
}
|
|
|
|
snapshot = build_country_network_snapshot("houston", raw)
|
|
airport_primary = snapshot["airport_primary_current"]
|
|
|
|
assert airport_primary["source_code"] == "madis_hfmetar"
|
|
assert airport_primary["source_label"] == "NOAA MADIS"
|
|
assert airport_primary["temp"] == 66.9
|
|
assert airport_primary["temp_c"] == 19.4
|
|
|
|
|
|
def test_city_detail_payload_exposes_airport_and_official_network_layers():
|
|
payload = _build_city_detail_payload(
|
|
{
|
|
"name": "ankara",
|
|
"display_name": "Ankara",
|
|
"local_time": "12:00",
|
|
"local_date": "2026-04-06",
|
|
"temp_symbol": "°C",
|
|
"updated_at": "2026-04-06T04:00:00Z",
|
|
"current": {
|
|
"temp": 16.0,
|
|
"settlement_source": "metar",
|
|
"settlement_source_label": "METAR",
|
|
},
|
|
"risk": {"icao": "LTAC", "airport": "Esenboga", "level": "medium", "warning": ""},
|
|
"airport_primary": {"temp": 16.0, "source_code": "metar"},
|
|
"airport_primary_today_obs": [{"time": "10:00", "temp": 16.0}],
|
|
"official_nearby": [{"station_code": "17128", "temp": 17.2, "source_code": "mgm"}],
|
|
"official_network_source": "turkey_mgm",
|
|
"official_network_status": {"provider_code": "turkey_mgm", "available": True},
|
|
"network_lead_signal": {"available": True, "delta": 1.2},
|
|
"network_spread_signal": {"available": True, "spread": 2.1},
|
|
"center_station_candidate": {"station_code": "17128", "temp": 17.2},
|
|
"airport_vs_network_delta": 1.2,
|
|
"settlement_station": {
|
|
"settlement_station_code": "LTAC",
|
|
"settlement_station_label": "Ankara Esenboga Airport",
|
|
"is_airport_anchor": True,
|
|
},
|
|
"probabilities": {"distribution": []},
|
|
"multi_model": {},
|
|
"multi_model_daily": {},
|
|
"dynamic_commentary": {"summary": "", "notes": []},
|
|
"taf": {},
|
|
}
|
|
)
|
|
|
|
assert payload["official"]["airport_primary"]["source_code"] == "metar"
|
|
assert payload["official"]["official_nearby"][0]["source_code"] == "mgm"
|
|
assert payload["settlement_station"]["settlement_station_code"] == "LTAC"
|
|
|
|
|
|
def test_intraday_meteorology_supportive_heating_case():
|
|
payload = _build_intraday_meteorology(
|
|
{
|
|
"local_time": "12:04",
|
|
"temp_symbol": "°C",
|
|
"current": {"temp": 38.2, "max_so_far": 38.2},
|
|
"deb": {"prediction": 40.4},
|
|
"probabilities": {"distribution": [{"value": 40, "probability": 0.42}]},
|
|
"peak": {"first_h": 14, "last_h": 15, "status": "before"},
|
|
"deviation_monitor": {"direction": "hot", "severity": "strong", "current_delta": 1.9},
|
|
"vertical_profile_signal": {
|
|
"heating_setup": "supportive",
|
|
"summary_zh": "混合层偏深，仍支持午后继续升温。",
|
|
},
|
|
"taf": {"signal": {"available": True, "suppression_level": "low", "summary_zh": "TAF 暂未提示强云雨压温。"}},
|
|
}
|
|
)
|
|
|
|
assert "上修空间" in payload["headline"]
|
|
assert "upside" in payload["headline_en"].lower()
|
|
assert payload["confidence"] == "high"
|
|
assert payload["base_case_bucket"] == "40°C"
|
|
assert payload["next_observation_time"] == "12:30"
|
|
assert any(item["direction"] == "support" for item in payload["signal_contributions"])
|
|
assert all(item.get("summary_en") for item in payload["signal_contributions"])
|
|
|
|
|
|
def test_intraday_meteorology_suppressed_cloud_rain_case():
|
|
payload = _build_intraday_meteorology(
|
|
{
|
|
"local_time": "13:10",
|
|
"temp_symbol": "°C",
|
|
"current": {"temp": 36.0, "max_so_far": 36.5},
|
|
"deb": {"prediction": 40.2},
|
|
"probabilities": {"distribution": [{"value": 40, "probability": 0.35}]},
|
|
"peak": {"first_h": 14, "last_h": 15, "status": "before"},
|
|
"deviation_monitor": {"direction": "cold", "severity": "strong", "current_delta": -2.0},
|
|
"vertical_profile_signal": {"heating_setup": "suppressed", "suppression_risk": "high"},
|
|
"taf": {"signal": {"available": True, "suppression_level": "high", "disruption_level": "high"}},
|
|
}
|
|
)
|
|
|
|
assert "压制" in payload["headline"]
|
|
assert "capping" in payload["headline_en"].lower()
|
|
assert payload["confidence"] == "high"
|
|
assert any("云雨" in rule for rule in payload["invalidation_rules"])
|
|
assert any("cloud" in rule.lower() for rule in payload["invalidation_rules_en"])
|
|
assert any(item["direction"] == "suppress" for item in payload["signal_contributions"])
|
|
|
|
|
|
def test_intraday_meteorology_structural_cap_does_not_claim_taf_cloud_rain():
|
|
payload = _build_intraday_meteorology(
|
|
{
|
|
"local_time": "11:30",
|
|
"temp_symbol": "°C",
|
|
"current": {"temp": 39.0, "max_so_far": 39.0},
|
|
"deb": {"prediction": 40.4},
|
|
"probabilities": {"distribution": [{"value": 42, "probability": 0.35}]},
|
|
"peak": {"first_h": 12, "last_h": 16, "status": "before"},
|
|
"deviation_monitor": {"direction": "cold", "severity": "strong", "current_delta": -1.4},
|
|
"vertical_profile_signal": {
|
|
"heating_setup": "suppressed",
|
|
"suppression_risk": "medium",
|
|
"summary_zh": "边界层混合偏弱，午后上修需要后续观测确认。",
|
|
},
|
|
"taf": {
|
|
"signal": {
|
|
"available": True,
|
|
"suppression_level": "low",
|
|
"disruption_level": "low",
|
|
"summary_zh": "TAF 在峰值窗口暂未提示明显云雨压温。",
|
|
}
|
|
},
|
|
}
|
|
)
|
|
|
|
assert "结构信号压制" in payload["headline"]
|
|
assert "TAF 云雨层暂未构成主压温理由" in payload["headline"]
|
|
assert "存在云雨或结构压制" not in payload["headline"]
|
|
assert any(item["label"] == "TAF 云雨扰动" and item["direction"] == "support" for item in payload["signal_contributions"])
|
|
|
|
|
|
def test_intraday_meteorology_handles_sparse_observations():
|
|
payload = _build_intraday_meteorology(
|
|
{
|
|
"local_time": "08:00",
|
|
"temp_symbol": "°C",
|
|
"current": {},
|
|
"probabilities": {"distribution": []},
|
|
"peak": {},
|
|
"taf": {},
|
|
"vertical_profile_signal": {},
|
|
}
|
|
)
|
|
|
|
assert payload["confidence"] == "low"
|
|
assert payload["next_observation_time"] == "08:30"
|
|
assert payload["signal_contributions"][0]["label"] == "数据完整性"
|
|
assert payload["signal_contributions"][0]["label_en"] == "Data completeness"
|
|
|
|
|
|
def test_intraday_meteorology_past_peak_case():
|
|
payload = _build_intraday_meteorology(
|
|
{
|
|
"local_time": "17:20",
|
|
"temp_symbol": "°C",
|
|
"current": {"temp": 33.0, "max_so_far": 39.0},
|
|
"probabilities": {"distribution": [{"value": 39, "probability": 0.5}]},
|
|
"peak": {"first_h": 13, "last_h": 15, "status": "past"},
|
|
"deviation_monitor": {"direction": "normal", "severity": "normal", "current_delta": 0.1},
|
|
}
|
|
)
|
|
|
|
assert "峰值窗口已过" in payload["headline"]
|
|
assert "passed" in payload["headline_en"].lower()
|
|
assert payload["base_case_bucket"] == "39°C"
|
|
assert any("最终高点" in rule for rule in payload["invalidation_rules"])
|
|
assert any("final" in rule.lower() for rule in payload["invalidation_rules_en"])
|