feat: add baseline range to NO2 and Nightlights chart data

Store per-year baseline values during API queries and expose
baseline_range_mean/min/max in chart_data for both indicators when
>=2 baseline years are available. Tests cover range inclusion, the
single-year guard, and the None/fallback paths.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

app/indicators/nightlights.py

@@ -52,7 +52,7 @@ class NightlightsIndicator(BaseIndicator):
         status = self._classify(ratio)
         trend = self._compute_trend(ratio)
         confidence = self._compute_confidence(spatial)
-        chart_data = self._build_chart_data(current_radiance, baseline_radiance, time_range)
+        chart_data = self._build_chart_data(current_radiance, baseline_radiance, time_range, getattr(self, '_baseline_yearly_vals', None))
 
         if ratio >= 0.9:
             headline = f"Nighttime light intensity at {pct:.0f}% of baseline — normal activity"
@@ -213,6 +213,7 @@ class NightlightsIndicator(BaseIndicator):
             return None
 
         baseline_mean = float(np.mean(baseline_vals))
+        self._baseline_yearly_vals = baseline_vals
 
         # Build spatial data from whichever year we read
         spatial = None
@@ -338,6 +339,7 @@ class NightlightsIndicator(BaseIndicator):
             return None
 
         baseline_mean = float(np.mean(baseline_vals))
+        self._baseline_yearly_vals = baseline_vals
         # NASA source provides scalar means only (no 2D spatial data due to sinusoidal tiling)
         return current_mean, baseline_mean, None
 
@@ -379,10 +381,18 @@ class NightlightsIndicator(BaseIndicator):
 
     @staticmethod
     def _build_chart_data(
-        current: float, baseline: float, time_range: TimeRange
+        current: float,
+        baseline: float,
+        time_range: TimeRange,
+        baseline_yearly_vals: list[float] | None = None,
     ) -> dict[str, Any]:
-        return {
+        result: dict[str, Any] = {
             "dates": [str(time_range.start.year - 1), str(time_range.end.year)],
             "values": [round(baseline, 4), round(current, 4)],
             "label": "Mean VIIRS DNB radiance (nW·cm⁻²·sr⁻¹)",
         }
+        if baseline_yearly_vals and len(baseline_yearly_vals) >= 2:
+            result["baseline_range_mean"] = round(float(np.mean(baseline_yearly_vals)), 4)
+            result["baseline_range_min"] = round(float(min(baseline_yearly_vals)), 4)
+            result["baseline_range_max"] = round(float(max(baseline_yearly_vals)), 4)
+        return result

app/indicators/no2.py

@@ -39,7 +39,7 @@ class NO2Indicator(BaseIndicator):
         status = self._classify(abs(z_score))
         trend = self._compute_trend(z_score)
         confidence = ConfidenceLevel.MODERATE
-        chart_data = self._build_chart_data(current_no2, baseline_mean, baseline_std, time_range)
+        chart_data = self._build_chart_data(current_no2, baseline_mean, baseline_std, time_range, getattr(self, '_baseline_yearly_means', None))
 
         direction = "above" if z_score >= 0 else "below"
         abs_z = abs(z_score)
@@ -142,6 +142,7 @@ class NO2Indicator(BaseIndicator):
             self._is_placeholder = True
             return self._synthetic_no2()
 
+        self._baseline_yearly_means = baseline_yearly_means
         return (
             float(np.mean(current_vals)),
             float(np.mean(baseline_yearly_means)),
@@ -178,10 +179,16 @@ class NO2Indicator(BaseIndicator):
         baseline_mean: float,
         baseline_std: float,
         time_range: TimeRange,
+        baseline_yearly_means: list[float] | None = None,
     ) -> dict[str, Any]:
-        return {
+        result: dict[str, Any] = {
             "dates": ["baseline", str(time_range.end.year)],
             "values": [round(baseline_mean, 1), round(current, 1)],
             "baseline_std": round(baseline_std, 1),
             "label": "NO2 concentration (µg/m³)",
         }
+        if baseline_yearly_means and len(baseline_yearly_means) >= 2:
+            result["baseline_range_mean"] = round(float(np.mean(baseline_yearly_means)), 1)
+            result["baseline_range_min"] = round(float(min(baseline_yearly_means)), 1)
+            result["baseline_range_max"] = round(float(max(baseline_yearly_means)), 1)
+        return result

tests/test_indicator_nightlights.py

@@ -0,0 +1,51 @@
+def test_build_chart_data_includes_baseline_range():
+    from app.indicators.nightlights import NightlightsIndicator
+    from datetime import date
+    from app.models import TimeRange
+    tr = TimeRange(start=date(2025, 1, 1), end=date(2025, 12, 31))
+    result = NightlightsIndicator._build_chart_data(
+        current=2.8, baseline=3.2, time_range=tr,
+        baseline_yearly_vals=[3.0, 3.2, 3.4],
+    )
+    assert "baseline_range_mean" in result
+    assert result["baseline_range_min"] == 3.0
+    assert result["baseline_range_max"] == 3.4
+
+
+def test_build_chart_data_no_range_when_single_year():
+    from app.indicators.nightlights import NightlightsIndicator
+    from datetime import date
+    from app.models import TimeRange
+    tr = TimeRange(start=date(2025, 1, 1), end=date(2025, 12, 31))
+    result = NightlightsIndicator._build_chart_data(
+        current=2.8, baseline=3.2, time_range=tr,
+        baseline_yearly_vals=[3.2],
+    )
+    assert "baseline_range_mean" not in result
+
+
+def test_build_chart_data_no_range_when_none():
+    from app.indicators.nightlights import NightlightsIndicator
+    from datetime import date
+    from app.models import TimeRange
+    tr = TimeRange(start=date(2025, 1, 1), end=date(2025, 12, 31))
+    result = NightlightsIndicator._build_chart_data(
+        current=2.8, baseline=3.2, time_range=tr,
+    )
+    assert "baseline_range_mean" not in result
+    assert result["values"] == [3.2, 2.8]
+
+
+def test_build_chart_data_uses_four_decimal_places():
+    from app.indicators.nightlights import NightlightsIndicator
+    from datetime import date
+    from app.models import TimeRange
+    tr = TimeRange(start=date(2025, 1, 1), end=date(2025, 12, 31))
+    result = NightlightsIndicator._build_chart_data(
+        current=2.8, baseline=3.2, time_range=tr,
+        baseline_yearly_vals=[3.0, 3.2, 3.4],
+    )
+    # mean of [3.0, 3.2, 3.4] = 3.2, check rounding to 4 dp
+    assert result["baseline_range_mean"] == 3.2
+    assert result["baseline_range_min"] == 3.0
+    assert result["baseline_range_max"] == 3.4

tests/test_indicator_no2.py

@@ -0,0 +1,36 @@
+def test_build_chart_data_includes_baseline_range():
+    from app.indicators.no2 import NO2Indicator
+    from datetime import date
+    from app.models import TimeRange
+    tr = TimeRange(start=date(2025, 1, 1), end=date(2025, 12, 31))
+    result = NO2Indicator._build_chart_data(
+        current=16.5, baseline_mean=15.0, baseline_std=4.0, time_range=tr,
+        baseline_yearly_means=[12.0, 15.0, 18.0],
+    )
+    assert "baseline_range_mean" in result
+    assert result["baseline_range_min"] == 12.0
+    assert result["baseline_range_max"] == 18.0
+
+
+def test_build_chart_data_no_range_when_single_year():
+    from app.indicators.no2 import NO2Indicator
+    from datetime import date
+    from app.models import TimeRange
+    tr = TimeRange(start=date(2025, 1, 1), end=date(2025, 12, 31))
+    result = NO2Indicator._build_chart_data(
+        current=16.5, baseline_mean=15.0, baseline_std=4.0, time_range=tr,
+        baseline_yearly_means=[15.0],
+    )
+    assert "baseline_range_mean" not in result
+
+
+def test_build_chart_data_no_range_when_none():
+    from app.indicators.no2 import NO2Indicator
+    from datetime import date
+    from app.models import TimeRange
+    tr = TimeRange(start=date(2025, 1, 1), end=date(2025, 12, 31))
+    result = NO2Indicator._build_chart_data(
+        current=16.5, baseline_mean=15.0, baseline_std=4.0, time_range=tr,
+    )
+    assert "baseline_range_mean" not in result
+    assert result["baseline_std"] == 4.0