Complete Köppen-Geiger filter review with Mixed climate class

Classify each county by area-weighted Köppen class shares: a county is predominantly its top class when that class covers at least 50% of its land and leads the runner-up by at least 5 percentage points; otherwise it is Mixed (133 of 3,143 counties in the 50 states and DC). - Add build_county_koppen_metric.py (writes data/metrics/koppen.csv) and apply_koppen_metric_to_climate_data.py (writes koppenZone plus koppenPrimaryClass/koppenSecondaryClass for Mixed counties). - Move shared helpers into scripts/common/ (county loading, Köppen legend, area-weighted raster shares); fix the 180th-meridian raster window for Aleutians West. - Add check_climate_data.py to validate the app CSV. - Draw Mixed counties in app.js as diagonal stripes of their top two classes, fixed to the ground and following the map at every zoom, with a crossfade only when the stripe size changes. Filtering a class also matches Mixed counties where it is primary or secondary. - Document the rule, display, and pipeline plan in docs/ and update the README and data-source notes. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-09-14 02:54:25 -04:00
parent 92fbbfb2e9
commit 4d2b3e3d44
20 changed files with 6400 additions and 3450 deletions
@@ -0,0 +1,211 @@
+from __future__ import annotations
+
+import csv
+import json
+import sys
+import unittest
+from pathlib import Path
+from tempfile import TemporaryDirectory
+
+SCRIPTS_DIR = Path(__file__).resolve().parents[1] / "scripts"
+sys.path.insert(0, str(SCRIPTS_DIR))
+
+from check_climate_data import (  # noqa: E402
+    CHECK_BLANKS,
+    CHECK_COLUMNS,
+    CHECK_COUNTIES,
+    CHECK_CROSS,
+    CHECK_FORMAT,
+    CHECK_GEOMETRY,
+    CHECK_SOURCES,
+    CHECK_VALUES,
+    DEFAULT_CLIMATE_CSV,
+    DEFAULT_COUNTIES_GEOJSON,
+    DEFAULT_METRIC_SOURCES,
+    EXPECTED_COLUMNS,
+    run_checks,
+)
+
+NOAA_GRID_COLUMNS = (
+    "avgTempF",
+    "avgDiurnalTempRangeF",
+    "annualPrecipIn",
+    "seasonalityIndex",
+    "wettestPrecipMonth",
+    "driestPrecipMonth",
+    "absoluteExtremeDays",
+    "avgSummerSpecificHumidityGKg",
+    "humidHeatDays",
+    "humidHeatSourceFips",
+)
+
+
+def make_row(fips: str, state: str, **overrides: str) -> dict[str, str]:
+    row = {
+        "countyFips": fips,
+        "countyName": "Test",
+        "state": state,
+        "koppenZone": "Cfa",
+        "koppenPrimaryClass": "",
+        "koppenSecondaryClass": "",
+        "avgTempF": "60.0",
+        "avgDiurnalTempRangeF": "20.00",
+        "annualPrecipIn": "40.0",
+        "seasonalityIndex": "20",
+        "wettestPrecipMonth": "May",
+        "driestPrecipMonth": "October",
+        "absoluteExtremeDays": "10.0",
+        "meanDailyGlobalHorizontalRadiationKwhM2Day": "4.5",
+        "clearSkyGhiReductionIndex": "0.25",
+        "avgSummerSpecificHumidityGKg": "12.0",
+        "humidHeatDays": "30.0",
+        "humidHeatSourceFips": fips,
+        "humidHeatFipsAdjustment": "",
+        "source": "test",
+    }
+    row.update(overrides)
+    return row
+
+
+def valid_rows() -> list[dict[str, str]]:
+    alaska = make_row("02013", "AK", koppenZone="Dfc", **{column: "" for column in NOAA_GRID_COLUMNS})
+    return [make_row("01001", "AL"), alaska]
+
+
+class CheckClimateDataTests(unittest.TestCase):
+    def setUp(self) -> None:
+        self._temp_dir = TemporaryDirectory()
+        self.base = Path(self._temp_dir.name)
+        self.csv_path = self.base / "climate-data.csv"
+        self.geojson_path = self.base / "counties.json"
+        self.sources_path = self.base / "metric_sources.json"
+        self.write_geojson(["01001", "02013"])
+        self.sources_path.write_text(json.dumps({"schemaVersion": 1, "metrics": {}}), encoding="utf-8")
+
+    def tearDown(self) -> None:
+        self._temp_dir.cleanup()
+
+    def write_csv(self, rows: list[dict[str, str]], fieldnames: list[str] | None = None, encoding: str = "utf-8") -> None:
+        with self.csv_path.open("w", encoding=encoding, newline="") as handle:
+            writer = csv.DictWriter(handle, fieldnames=fieldnames or list(EXPECTED_COLUMNS))
+            writer.writeheader()
+            writer.writerows(rows)
+
+    def write_geojson(self, fips_codes: list[str]) -> None:
+        features = [
+            {"type": "Feature", "properties": {"id": fips, "STATE": fips[:2]}, "geometry": None}
+            for fips in fips_codes
+        ]
+        self.geojson_path.write_text(json.dumps({"type": "FeatureCollection", "features": features}), encoding="utf-8")
+
+    def run_report(self):
+        return run_checks(self.csv_path, self.geojson_path, self.sources_path)
+
+    def test_valid_file_passes_with_allowed_alaska_blanks(self) -> None:
+        self.write_csv(valid_rows())
+
+        report = self.run_report()
+
+        self.assertTrue(report.ok, report.checks)
+
+    def test_mixed_koppen_county_with_stripe_classes_passes(self) -> None:
+        rows = valid_rows()
+        rows[0].update(koppenZone="Mixed", koppenPrimaryClass="Csb", koppenSecondaryClass="Dsb")
+        self.write_csv(rows)
+
+        self.assertTrue(self.run_report().ok)
+
+    def test_mixed_county_without_stripe_classes_is_reported(self) -> None:
+        rows = valid_rows()
+        rows[0]["koppenZone"] = "Mixed"
+        self.write_csv(rows)
+
+        problems = self.run_report().checks[CHECK_CROSS]
+
+        self.assertEqual(problems, ["01001: Mixed Koppen county needs koppenPrimaryClass and koppenSecondaryClass"])
+
+    def test_stripe_classes_on_predominant_county_are_reported(self) -> None:
+        rows = valid_rows()
+        rows[0].update(koppenPrimaryClass="Csb", koppenSecondaryClass="Dsb")
+        self.write_csv(rows)
+
+        problems = self.run_report().checks[CHECK_CROSS]
+
+        self.assertEqual(problems, ["01001: Koppen stripe classes are set but koppenZone is Cfa, not Mixed"])
+
+    def test_invalid_or_identical_stripe_classes_are_reported(self) -> None:
+        rows = valid_rows()
+        rows[0].update(koppenZone="Mixed", koppenPrimaryClass="Csb", koppenSecondaryClass="Csb")
+        rows[1].update(koppenZone="Mixed", koppenPrimaryClass="Xyz", koppenSecondaryClass="Dfc")
+        self.write_csv(rows)
+
+        problems = self.run_report().checks[CHECK_CROSS]
+
+        self.assertEqual(
+            problems,
+            ["01001: Koppen stripe classes are both Csb", "02013: invalid Koppen stripe classes 'Xyz'/'Dfc'"],
+        )
+
+    def test_bad_values_and_categories_are_reported(self) -> None:
+        rows = valid_rows()
+        rows[0].update(avgTempF="120", koppenZone="cfa", wettestPrecipMonth="Febuary", seasonalityIndex="12.5")
+        self.write_csv(rows)
+
+        problems = self.run_report().checks[CHECK_VALUES]
+
+        self.assertEqual(len(problems), 4, problems)
+        self.assertTrue(any("avgTempF=120 outside" in problem for problem in problems))
+        self.assertTrue(any("'cfa' is not an allowed category" in problem for problem in problems))
+
+    def test_blank_outside_allowed_states_is_reported(self) -> None:
+        rows = valid_rows()
+        rows[0]["avgTempF"] = ""
+        self.write_csv(rows)
+
+        problems = self.run_report().checks[CHECK_BLANKS]
+
+        self.assertEqual(problems, ["01001 (AL): avgTempF is blank"])
+
+    def test_county_missing_from_map_is_reported(self) -> None:
+        self.write_csv(valid_rows())
+        self.write_geojson(["01001"])
+
+        problems = self.run_report().checks[CHECK_GEOMETRY]
+
+        self.assertEqual(problems, ["02013 is in the CSV but has no map polygon"])
+
+    def test_duplicate_fips_and_unexpected_column_are_reported(self) -> None:
+        rows = valid_rows()
+        rows[1] = make_row("01001", "AL", extraMetric="1")
+        self.write_csv(rows, fieldnames=list(EXPECTED_COLUMNS) + ["extraMetric"])
+
+        report = self.run_report()
+
+        self.assertIn("duplicate countyFips 01001", report.checks[CHECK_COUNTIES])
+        self.assertTrue(any("unexpected column 'extraMetric'" in problem for problem in report.checks[CHECK_COLUMNS]))
+
+    def test_byte_order_mark_is_reported(self) -> None:
+        self.write_csv(valid_rows(), encoding="utf-8-sig")
+
+        report = self.run_report()
+
+        self.assertEqual(len(report.checks[CHECK_FORMAT]), 1)
+        self.assertEqual(report.checks[CHECK_COLUMNS], [])
+
+    def test_unknown_metric_in_sources_file_is_reported(self) -> None:
+        self.write_csv(valid_rows())
+        self.sources_path.write_text(json.dumps({"metrics": {"notAMetric": {}}}), encoding="utf-8")
+
+        problems = self.run_report().checks[CHECK_SOURCES]
+
+        self.assertEqual(problems, ["metric_sources.json describes unknown metric 'notAMetric'"])
+
+    @unittest.skipUnless(DEFAULT_CLIMATE_CSV.exists(), "project climate CSV not present")
+    def test_project_climate_csv_passes(self) -> None:
+        report = run_checks(DEFAULT_CLIMATE_CSV, DEFAULT_COUNTIES_GEOJSON, DEFAULT_METRIC_SOURCES)
+
+        self.assertTrue(report.ok, report.checks)
+
+
+if __name__ == "__main__":
+    unittest.main()