KnouandClaude Opus 5
4d2b3e3d44
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>
65 lines
1.4 KiB
Python
65 lines
1.4 KiB
Python
"""Koppen-Geiger raster codes and the Beck et al. legend loader."""
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from __future__ import annotations
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import re
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from pathlib import Path
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from typing import Dict
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# Beck et al legend key is expected as text file, but this default handles common codes.
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DEFAULT_KOPPEN_CODE_MAP = {
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1: "Af",
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2: "Am",
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3: "Aw",
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4: "BWh",
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5: "BWk",
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6: "BSh",
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7: "BSk",
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8: "Csa",
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9: "Csb",
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10: "Csc",
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11: "Cwa",
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12: "Cwb",
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13: "Cwc",
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14: "Cfa",
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15: "Cfb",
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16: "Cfc",
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17: "Dsa",
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18: "Dsb",
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19: "Dsc",
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20: "Dsd",
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21: "Dwa",
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22: "Dwb",
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23: "Dwc",
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24: "Dwd",
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25: "Dfa",
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26: "Dfb",
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27: "Dfc",
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28: "Dfd",
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29: "ET",
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30: "EF",
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}
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def load_koppen_legend(legend_path: Path | None) -> Dict[int, str]:
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"""Load Koppen raster codes, using defaults when no legend exists."""
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if legend_path is None:
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return DEFAULT_KOPPEN_CODE_MAP
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mapping: Dict[int, str] = {}
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for line in legend_path.read_text(encoding="utf-8").splitlines():
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text = line.strip()
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if not text or text.startswith("#"):
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continue
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# Handles patterns like:
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# "1: Af ..." or "1 = Af" or "1 Af"
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match = re.match(r"^(\d+)\s*[:=]?\s*([A-Za-z]{2,3})\b", text)
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if not match:
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continue
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key = int(match.group(1))
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value = match.group(2)
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mapping[key] = value
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return mapping if mapping else DEFAULT_KOPPEN_CODE_MAP
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