Merge pull request 'Promote dev to main: MET forecast coverage gate' (#64) from dev into main

backend/data/climate.py

@@ -626,7 +626,9 @@ def _metno_to_frame(props: dict) -> pl.DataFrame:
         day = step["time"][:10]
         data = step.get("data", {})
         inst = data.get("instant", {}).get("details", {})
-        a = agg.setdefault(day, {"t": [], "rh": [], "wind": [], "precip": None})
+        a = agg.setdefault(day, {"t": [], "rh": [], "wind": [], "precip": None,
+                                 "hours": []})
+        a["hours"].append(int(step["time"][11:13]))
         if (t := inst.get("air_temperature")) is not None:
             a["t"].append(t)
         if (rh := inst.get("relative_humidity")) is not None:
@@ -642,7 +644,17 @@ def _metno_to_frame(props: dict) -> pl.DataFrame:
         if p is not None:
             a["precip"] = (a["precip"] or 0.0) + p
 
-    dates = sorted(agg)
+    # Coverage gate: a day's min/max are only real if its samples span most of
+    # the day. MET's series starts mid-today and thins to 6-hourly then sparser
+    # in the tail, so without this the current day is built from the remaining
+    # afternoon hours (seen live: a served "overnight low" of 114.8°F graded at
+    # the ~100th percentile) and the final day can collapse to one sample with
+    # tmin == tmax. 18h keeps full hourly days and the 0/6/12/18 6-hourly shape;
+    # it drops partial today and the degenerate tail rather than grading them.
+    MIN_SPAN_HOURS = 18
+    dates = [d for d in sorted(agg)
+             if agg[d]["hours"]
+             and max(agg[d]["hours"]) - min(agg[d]["hours"]) >= MIN_SPAN_HOURS]
     c2f = lambda c: c * 9.0 / 5.0 + 32.0
     df = pl.DataFrame({
         "date": dates,

backend/tests/data/test_climate.py

@@ -117,13 +117,17 @@ def _metno_step(time, t, rh, wind, p1=None, p6=None):
 
 def test_metno_to_frame_aggregates_daily_and_converts_units():
     props = {"timeseries": [
-        # Day 1: two hourly steps. The first also carries a next_6_hours block, which
-        # must be IGNORED (next_1_hours wins) so precip isn't double-counted.
+        # Day 1: hourly steps spanning the day (the coverage gate needs >= 18h).
+        # The first also carries a next_6_hours block, which must be IGNORED
+        # (next_1_hours wins) so precip isn't double-counted.
         _metno_step("2026-07-16T00:00:00Z", 20.0, 50.0, 2.0, p1=0.5, p6=3.0),
         _metno_step("2026-07-16T01:00:00Z", 25.0, 60.0, 4.0, p1=0.5),
-        # Day 2: a 6-hourly step (only next_6_hours) + an instant-only tail step.
+        _metno_step("2026-07-16T18:00:00Z", 22.0, 55.0, 1.0),
+        # Day 2: the far-term 6-hourly shape (0/6/12/18) with one next_6_hours block.
         _metno_step("2026-07-17T00:00:00Z", 10.0, 80.0, 10.0, p6=6.0),
         _metno_step("2026-07-17T06:00:00Z", 12.0, 70.0, 8.0),
+        _metno_step("2026-07-17T12:00:00Z", 14.0, 60.0, 6.0),
+        _metno_step("2026-07-17T18:00:00Z", 11.0, 75.0, 7.0),
     ]}
     df = climate._metno_to_frame(props)
     assert len(df) == 2
@@ -137,6 +141,30 @@ def test_metno_to_frame_aggregates_daily_and_converts_units():
     assert round(d2["precip"], 4) == round(6.0 / 25.4, 4)     # only the 6-hour block
 
 
+def test_metno_to_frame_drops_days_without_diurnal_coverage():
+    """Partial days must not be graded: MET's series starts mid-today (the
+    remaining afternoon hours would masquerade as the day's extremes — seen
+    live as a ~100th-percentile 'overnight low') and its final day can be a
+    single sample with tmin == tmax. Both shapes are dropped; the 6-hourly
+    0/6/12/18 far-term shape (18h span) survives."""
+    props = {"timeseries": [
+        # "Today", started at 21:00 — only evening remains: dropped.
+        _metno_step("2026-07-20T21:00:00Z", 46.0, 20.0, 2.0),
+        _metno_step("2026-07-20T22:00:00Z", 45.0, 22.0, 2.0),
+        # Full 6-hourly day: kept.
+        _metno_step("2026-07-21T00:00:00Z", 30.0, 40.0, 3.0),
+        _metno_step("2026-07-21T06:00:00Z", 28.0, 50.0, 3.0),
+        _metno_step("2026-07-21T12:00:00Z", 38.0, 30.0, 4.0),
+        _metno_step("2026-07-21T18:00:00Z", 34.0, 35.0, 3.0),
+        # Degenerate tail day, one sample: dropped (would grade tmin == tmax).
+        _metno_step("2026-07-22T00:00:00Z", 29.0, 45.0, 3.0),
+    ]}
+    df = climate._metno_to_frame(props)
+    assert df["date"].to_list() == [datetime.date(2026, 7, 21)]
+    row = df.row(0, named=True)
+    assert row["tmax"] != row["tmin"]
+
+
 def test_recent_forecast_merges_nasa_past_and_metno_forward(monkeypatch, tmp_path):
     """The recent/forecast bundle is built from a NASA POWER recent-past range plus the
     MET Norway forward forecast, merged by date (Open-Meteo not consulted)."""