2569718930@qq.com
534 lines
22 KiB
Python
534 lines
22 KiB
Python
"""
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Unit tests for trend_engine core logic.
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Tests: μ/σ calculation, dead market detection, forecast bust grading.
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"""
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import sys
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import os
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# Ensure project root is in path
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from unittest.mock import patch
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from src.analysis.trend_engine import analyze_weather_trend, _sf
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# ─── Helpers ───
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def _make_weather_data(
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cur_temp=25.0,
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max_so_far=28.0,
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om_today_high=30.0,
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ens_median=29.0,
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ens_p10=27.0,
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ens_p90=31.0,
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local_time="2026-03-04 14:30",
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recent_temps=None,
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multi_model=None,
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multi_model_hourly=None,
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recent_obs=None,
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):
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"""Build a minimal weather_data dict for testing."""
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data = {
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"metar": {
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"current": {
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"temp": cur_temp,
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"max_temp_so_far": max_so_far,
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"max_temp_time": "14:00",
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"wind_speed_kt": 5,
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"wind_dir": 180,
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"humidity": 50,
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"clouds": [{"cover": "SCT", "base": 5000}],
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},
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"recent_temps": recent_temps or [("14:00", 27.0), ("13:00", 26.0), ("12:00", 25.0)],
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"recent_obs": recent_obs or [],
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},
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"open-meteo": {
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"current": {"local_time": local_time},
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"daily": {
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"temperature_2m_max": [om_today_high],
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"sunrise": ["06:30"],
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"sunset": ["18:30"],
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},
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"hourly": {
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"time": [f"2026-03-04T{h:02d}:00" for h in range(24)],
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"temperature_2m": [15 + (h - 6) * 1.5 if 6 <= h <= 14 else 20 - (h - 14) * 0.5 for h in range(24)],
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"shortwave_radiation": [0 if h < 6 or h > 18 else 200 + h * 20 for h in range(24)],
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},
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},
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"ensemble": {
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"median": ens_median,
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"p10": ens_p10,
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"p90": ens_p90,
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},
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"multi_model": {"forecasts": multi_model or {}, **(multi_model_hourly or {})},
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"nws": {},
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}
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return data
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# ─── Tests: _sf ───
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class TestSafeFloat:
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def test_none(self):
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assert _sf(None) is None
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def test_int(self):
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assert _sf(5) == 5.0
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def test_str_number(self):
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assert _sf("3.14") == 3.14
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def test_invalid_str(self):
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assert _sf("abc") is None
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# ─── Tests: μ Calculation ───
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class TestMuCalculation:
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@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
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@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
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@patch("src.analysis.trend_engine.update_daily_record")
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def test_normal_mu_blends_forecast_and_ensemble(self, _udr, _deb_acc, _dw):
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"""Normal case: μ = forecast_median * 0.7 + ens_median * 0.3"""
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data = _make_weather_data(
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cur_temp=25.0, max_so_far=26.0,
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om_today_high=30.0, ens_median=29.0,
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local_time="2026-03-04 10:00" # Before peak window to prevent early bust override
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)
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_, _, sd = analyze_weather_trend(data, "°C", "test_city")
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mu = sd["mu"]
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# forecast_median = 30.0, ens_median = 29.0 → 30*0.7 + 29*0.3 = 29.7
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assert mu is not None
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assert 29.0 <= mu <= 31.0 # Reasonable range
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@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
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@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
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@patch("src.analysis.trend_engine.update_daily_record")
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def test_reality_anchored_mu_on_forecast_bust(self, _udr, _deb_acc, _dw):
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"""When past peak and actual << forecasts, μ anchors on actual max."""
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data = _make_weather_data(
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cur_temp=22.0, max_so_far=23.0,
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om_today_high=30.0, ens_median=29.0,
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local_time="2026-03-04 17:00", # Past peak
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recent_temps=[("17:00", 22.0), ("16:00", 23.0), ("15:00", 23.0)],
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)
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_, _, sd = analyze_weather_trend(data, "°C", "test_city")
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mu = sd["mu"]
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# max_so_far=23 vs forecast_median=30 → bust → μ ≈ 23
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assert mu is not None
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assert mu <= 24.0, f"μ should anchor on actual max (23°C), got {mu}"
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@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
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@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
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@patch("src.analysis.trend_engine.update_daily_record")
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def test_mu_rises_when_actual_exceeds_forecast(self, _udr, _deb_acc, _dw):
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"""When actual max exceeds μ, μ adjusts upward."""
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data = _make_weather_data(
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cur_temp=32.0, max_so_far=33.0,
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om_today_high=30.0, ens_median=29.0,
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local_time="2026-03-04 14:00",
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recent_temps=[("14:00", 32.0), ("13:00", 31.0), ("12:00", 30.0)],
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)
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_, _, sd = analyze_weather_trend(data, "°C", "test_city")
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mu = sd["mu"]
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assert mu is not None
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assert mu >= 33.0, f"μ should be >= actual max (33°C), got {mu}"
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@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
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@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
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@patch("src.analysis.trend_engine.update_daily_record")
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def test_mu_uses_city_local_date_daily_high(self, _udr, _deb_acc, _dw):
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"""Cached daily arrays may include yesterday first; μ must use the city-local target date."""
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data = _make_weather_data(
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cur_temp=25.0,
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max_so_far=25.0,
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om_today_high=24.0,
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ens_median=None,
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ens_p10=None,
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ens_p90=None,
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local_time="2026-05-28 09:30",
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recent_temps=[("09:00", 25.0), ("08:00", 24.0), ("07:00", 23.0)],
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multi_model={},
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)
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data["open-meteo"]["daily"]["time"] = ["2026-05-27", "2026-05-28"]
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data["open-meteo"]["daily"]["temperature_2m_max"] = [24.0, 31.0]
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data["open-meteo"]["hourly"]["time"] = [f"2026-05-28T{h:02d}:00" for h in range(24)]
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_, _, sd = analyze_weather_trend(data, "°C", "test_city")
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assert sd["current_forecasts"]["Open-Meteo"] == 31.0
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assert sd["mu"] is not None and sd["mu"] >= 30.0
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@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
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@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
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@patch("src.analysis.trend_engine.update_daily_record")
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def test_multi_model_peak_window_prevents_early_open_meteo_bust(
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self, _udr, _deb_acc, _dw
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):
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"""If Open-Meteo peaks early but multi-models peak later, μ must not anchor to morning actuals."""
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hourly_times = [f"2026-03-04T{h:02d}:00" for h in range(24)]
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data = _make_weather_data(
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cur_temp=25.0,
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max_so_far=25.0,
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om_today_high=31.5,
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ens_median=None,
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ens_p10=None,
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ens_p90=None,
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local_time="2026-03-04 09:50",
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recent_temps=[("09:00", 25.0), ("08:00", 24.5), ("07:00", 24.0)],
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multi_model={
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"ECMWF": 30.8,
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"GFS": 32.0,
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"ICON": 28.8,
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"GEM": 29.8,
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},
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multi_model_hourly={
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"hourly_times": hourly_times,
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"hourly_forecasts": {
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"ECMWF": [24, 24, 24, 24, 24, 24, 24, 25, 26, 27, 28, 29, 30, 30.5, 30.8, 30.8, 30.4, 29, 28, 27, 26, 25, 24, 24],
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"GFS": [24, 24, 24, 24, 24, 24, 24, 25, 26, 27, 29, 30, 31, 31.5, 32.0, 32.0, 31.2, 30, 28, 27, 26, 25, 24, 24],
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"ICON": [23, 23, 23, 23, 23, 23, 23, 24, 25, 26, 27, 28, 28.5, 28.8, 28.8, 28.8, 28.4, 28, 27, 26, 25, 24, 23, 23],
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"GEM": [24, 24, 24, 24, 24, 24, 24, 25, 26, 27, 28, 29, 29.5, 29.8, 29.8, 29.8, 29.4, 29, 28, 27, 26, 25, 24, 24],
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},
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},
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)
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data["open-meteo"]["hourly"]["time"] = hourly_times
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data["open-meteo"]["hourly"]["temperature_2m"] = [
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23, 23, 23, 23, 23, 24, 25, 27, 30, 31.5, 29, 28, 27, 26, 25, 24, 24, 23, 23, 22, 22, 22, 22, 22
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]
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_, _, sd = analyze_weather_trend(data, "°C", "test_city")
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assert sd["peak_status"] == "before"
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assert sd["mu"] is not None and sd["mu"] >= 29.0
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@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
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@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
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@patch("src.analysis.trend_engine.update_daily_record")
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def test_deb_hourly_consensus_takes_priority_for_peak_window(
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self, _udr, _deb_acc, _dw
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):
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"""The peak window should follow the independent DEB hourly path before raw model medians."""
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data = _make_weather_data(
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cur_temp=25.0,
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max_so_far=25.0,
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om_today_high=31.0,
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ens_median=None,
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ens_p10=None,
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ens_p90=None,
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local_time="2026-03-04 10:00",
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multi_model_hourly={
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"hourly_times": [f"2026-03-04T{h:02d}:00" for h in range(24)],
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"hourly_forecasts": {
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"ECMWF": [24.0 if h != 12 else 31.0 for h in range(24)],
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"GFS": [24.0 if h != 12 else 31.0 for h in range(24)],
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},
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},
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)
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data["deb"] = {
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"hourly_consensus": {
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"times": ["09:00", "15:00", "16:00"],
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"temps": [24.0, 30.0, 30.0],
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}
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}
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_, _, sd = analyze_weather_trend(data, "°C", "test_city")
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assert sd["peak_hours"] == ["15:00", "16:00"]
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assert sd["peak_status"] == "before"
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@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
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@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
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@patch("src.analysis.trend_engine.update_daily_record")
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def test_weathernext2_probability_replaces_legacy_distribution(
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self, _udr, _deb_acc, _dw
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):
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data = _make_weather_data(
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cur_temp=30.0,
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max_so_far=31.0,
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om_today_high=33.0,
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ens_median=32.0,
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local_time="2026-03-04 11:00",
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)
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data["weathernext2"] = {
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"summary": {"median": 33.1},
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"buckets": [
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{
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"label": "32°C",
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"value": 32.1,
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"lower": 31.5,
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"upper": 32.5,
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"probability": 0.41,
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},
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{
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"label": "33°C",
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"value": 33.0,
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"lower": 32.5,
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"upper": 33.5,
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"probability": 0.56,
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},
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],
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}
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_, ai_context, sd = analyze_weather_trend(data, "°C", "test_city")
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assert sd["probability_engine"] == "weathernext2"
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assert sd["probabilities_all"] == data["weathernext2"]["buckets"]
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assert sd["mu"] == 33.1
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assert "WeatherNext 2 概率分布" in ai_context
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@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
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@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
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@patch("src.analysis.trend_engine.update_daily_record")
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def test_weathernext2_median_enters_current_forecasts(
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self, _udr, _deb_acc, _dw
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):
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data = _make_weather_data(local_time="2026-03-04 11:00")
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data["weathernext2"] = {
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"summary": {"median": 33.1},
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"buckets": [
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{"label": "33°C", "value": 33.0, "probability": 0.56},
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],
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}
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_, _, sd = analyze_weather_trend(data, "°C", "test_city")
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assert sd["current_forecasts"]["WeatherNext 2"] == 33.1
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class TestDebEnsembleSignal:
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@patch(
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"src.analysis.trend_engine.calculate_deb_prediction",
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return_value={
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"prediction": 30.1,
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"raw_prediction": 30.1,
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"weights_info": "test weights",
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},
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)
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@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
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@patch("src.analysis.trend_engine.update_daily_record")
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def test_narrow_ensemble_supports_aligned_deb(self, _udr, _deb_acc, _deb):
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data = _make_weather_data(
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cur_temp=25.0,
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max_so_far=25.2,
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om_today_high=30.0,
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ens_median=30.0,
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ens_p10=29.4,
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ens_p90=30.6,
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local_time="2026-03-04 10:00",
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multi_model={"ECMWF": 30.2, "GFS": 30.0},
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)
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_, ai_context, sd = analyze_weather_trend(data, "°C", "test_city")
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signal = sd["deb_ensemble_signal"]
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assert signal["available"] is True
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assert signal["stance"] == "supporting"
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assert signal["confidence_delta"] > 0
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assert signal["spread"] == 1.2
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assert "集合支撑" in ai_context
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assert "GEFS" not in sd["current_forecasts"]
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assert not any("ensemble" in name.lower() for name in sd["current_forecasts"])
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@patch(
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"src.analysis.trend_engine.calculate_deb_prediction",
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return_value={
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"prediction": 31.0,
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"raw_prediction": 31.0,
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"weights_info": "test weights",
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},
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)
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@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
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@patch("src.analysis.trend_engine.update_daily_record")
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def test_wide_ensemble_marks_deb_as_caution(self, _udr, _deb_acc, _deb):
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data = _make_weather_data(
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cur_temp=25.0,
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max_so_far=25.2,
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om_today_high=30.0,
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ens_median=29.0,
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ens_p10=24.0,
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ens_p90=34.0,
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local_time="2026-03-04 10:00",
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multi_model={"ECMWF": 30.2, "GFS": 31.0},
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)
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_, ai_context, sd = analyze_weather_trend(data, "°C", "test_city")
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signal = sd["deb_ensemble_signal"]
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assert signal["available"] is True
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assert signal["stance"] == "caution"
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assert signal["confidence_delta"] < 0
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assert signal["spread"] == 10.0
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assert "集合分歧" in ai_context
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# ─── Tests: Dead Market ───
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class TestDeadMarket:
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@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
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@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
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@patch("src.analysis.trend_engine.update_daily_record")
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def test_dead_market_after_peak_with_cooling(self, _udr, _deb_acc, _dw):
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"""Past peak + 1.5°C drop → dead market."""
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data = _make_weather_data(
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cur_temp=26.0, max_so_far=28.0,
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local_time="2026-03-04 17:00",
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recent_temps=[("17:00", 26.0), ("16:00", 27.0), ("15:00", 28.0)],
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)
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_, _, sd = analyze_weather_trend(data, "°C", "test_city")
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ti = sd["trend_info"]
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assert ti["is_dead_market"] is True
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@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
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@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
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@patch("src.analysis.trend_engine.update_daily_record")
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def test_not_dead_market_during_peak_warming(self, _udr, _deb_acc, _dw):
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"""During peak window while still warming → NOT dead market."""
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data = _make_weather_data(
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cur_temp=28.0, max_so_far=28.0,
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local_time="2026-03-04 14:00",
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recent_temps=[("14:00", 28.0), ("13:00", 27.0), ("12:00", 26.0)],
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)
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_, _, sd = analyze_weather_trend(data, "°C", "test_city")
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ti = sd["trend_info"]
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assert ti["is_dead_market"] is False
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@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
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@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
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@patch("src.analysis.trend_engine.update_daily_record")
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def test_dead_market_probability_is_100_percent(self, _udr, _deb_acc, _dw):
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"""When dead market, probabilities collapse to 100% at settled value."""
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data = _make_weather_data(
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cur_temp=25.0, max_so_far=28.0,
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local_time="2026-03-04 22:00", # Late night
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recent_temps=[("22:00", 25.0), ("21:00", 26.0), ("20:00", 27.0)],
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)
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_, _, sd = analyze_weather_trend(data, "°C", "test_city")
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||
assert sd["trend_info"]["is_dead_market"] is True
|
||
probs = sd["probabilities"]
|
||
assert len(probs) == 1
|
||
assert probs[0]["value"] == 28 # round(28.0)
|
||
assert probs[0]["probability"] == 1.0
|
||
|
||
|
||
# ─── Tests: Forecast Bust Detection ───
|
||
|
||
class TestForecastBust:
|
||
@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
|
||
@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
|
||
@patch("src.analysis.trend_engine.update_daily_record")
|
||
def test_heavy_forecast_bust_detected(self, _udr, _deb_acc, _dw):
|
||
"""Heavy bust: forecast_median - max_so_far > 5.0"""
|
||
data = _make_weather_data(
|
||
cur_temp=22.0, max_so_far=23.0,
|
||
om_today_high=30.0, ens_median=29.0,
|
||
local_time="2026-03-04 16:00",
|
||
recent_temps=[("16:00", 22.0), ("15:00", 23.0), ("14:00", 23.0)],
|
||
)
|
||
_, ai_context, sd = analyze_weather_trend(data, "°C", "test_city")
|
||
|
||
# forecast_median=30, max_so_far=23 → miss = 7°C → heavy
|
||
assert "预报崩盘" in ai_context
|
||
assert "重" in ai_context or "级失准" in ai_context
|
||
|
||
@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
|
||
@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
|
||
@patch("src.analysis.trend_engine.update_daily_record")
|
||
def test_no_bust_when_on_track(self, _udr, _deb_acc, _dw):
|
||
"""No bust when actual is close to forecast."""
|
||
data = _make_weather_data(
|
||
cur_temp=29.0, max_so_far=29.5,
|
||
om_today_high=30.0, ens_median=29.5,
|
||
local_time="2026-03-04 14:00",
|
||
recent_temps=[("14:00", 29.0), ("13:00", 28.5), ("12:00", 28.0)],
|
||
)
|
||
_, ai_context, _ = analyze_weather_trend(data, "°C", "test_city")
|
||
|
||
assert "预报崩盘" not in ai_context
|
||
|
||
|
||
# ─── Tests: Trend Direction ───
|
||
|
||
class TestTrendDirection:
|
||
@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
|
||
@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
|
||
@patch("src.analysis.trend_engine.update_daily_record")
|
||
def test_rising_trend(self, _udr, _deb_acc, _dw):
|
||
data = _make_weather_data(
|
||
recent_temps=[("14:00", 28.0), ("13:00", 27.0), ("12:00", 26.0)],
|
||
)
|
||
_, _, sd = analyze_weather_trend(data, "°C", "test_city")
|
||
assert sd["trend_info"]["direction"] == "rising"
|
||
|
||
@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
|
||
@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
|
||
@patch("src.analysis.trend_engine.update_daily_record")
|
||
def test_falling_trend(self, _udr, _deb_acc, _dw):
|
||
data = _make_weather_data(
|
||
recent_temps=[("16:00", 25.0), ("15:00", 26.0), ("14:00", 27.0)],
|
||
)
|
||
_, _, sd = analyze_weather_trend(data, "°C", "test_city")
|
||
assert sd["trend_info"]["direction"] == "falling"
|
||
|
||
@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
|
||
@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
|
||
@patch("src.analysis.trend_engine.update_daily_record")
|
||
def test_stagnant_trend(self, _udr, _deb_acc, _dw):
|
||
data = _make_weather_data(
|
||
recent_temps=[("14:00", 27.0), ("13:00", 27.0), ("12:00", 27.0)],
|
||
)
|
||
_, _, sd = analyze_weather_trend(data, "°C", "test_city")
|
||
assert sd["trend_info"]["direction"] == "stagnant"
|
||
|
||
|
||
class TestDynamicCommentary:
|
||
@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
|
||
@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
|
||
@patch("src.analysis.trend_engine.update_daily_record")
|
||
def test_dynamic_commentary_detects_cloud_build_without_cooling(
|
||
self, _udr, _deb_acc, _dw
|
||
):
|
||
data = _make_weather_data(
|
||
cur_temp=28.0,
|
||
max_so_far=28.2,
|
||
local_time="2026-03-04 14:00",
|
||
recent_temps=[("14:00", 28.0), ("13:00", 27.6), ("12:00", 27.0)],
|
||
recent_obs=[
|
||
{"temp": 28.0, "wdir": 185, "wspd": 8, "cloud_rank": 3, "altim": 1009.2},
|
||
{"temp": 27.6, "wdir": 170, "wspd": 7, "cloud_rank": 2, "altim": 1010.0},
|
||
{"temp": 27.2, "wdir": 155, "wspd": 6, "cloud_rank": 1, "altim": 1010.8},
|
||
],
|
||
)
|
||
|
||
display_str, ai_context, sd = analyze_weather_trend(data, "°C", "test_city")
|
||
|
||
summary = sd["dynamic_commentary"]["summary"]
|
||
notes = sd["dynamic_commentary"]["notes"]
|
||
assert summary
|
||
assert "云层明显增厚" in summary
|
||
assert "结构解读" in display_str
|
||
assert any("云层明显增厚" in note for note in notes)
|
||
assert "结构解读" in ai_context
|
||
|
||
@patch("src.analysis.trend_engine.calculate_dynamic_weights", return_value=(None, ""))
|
||
@patch("src.analysis.trend_engine.get_deb_accuracy", return_value=None)
|
||
@patch("src.analysis.trend_engine.update_daily_record")
|
||
def test_dynamic_commentary_falls_back_when_recent_obs_missing(
|
||
self, _udr, _deb_acc, _dw
|
||
):
|
||
data = _make_weather_data(recent_obs=[])
|
||
|
||
display_str, ai_context, sd = analyze_weather_trend(data, "°C", "test_city")
|
||
|
||
assert sd["dynamic_commentary"]["summary"] == ""
|
||
assert sd["dynamic_commentary"]["notes"] == []
|
||
assert "结构解读" not in display_str
|
||
assert "结构解读" not in ai_context
|