second

build_distance_matrix.py

@@ -1,8 +1,12 @@
 import math
 from pathlib import Path
+import json
 
 import pandas as pd
 
+# set year
+year = json.load(open('year.json', 'r', encoding='utf-8'))['year']
+filename = f"{year}"
 
 def haversine(lat1, lon1, lat2, lon2):
     R = 6371.0  # Earth radius in km
@@ -41,8 +45,8 @@ def _infer_coords(df, name_col, lat_col, lon_col):
 
 
 def main():
-    demand = _read_csv_flexible("data/DemandLocation.csv")
-    factory = _read_csv_flexible("data/FactoryLocation.csv")
+    demand = _read_csv_flexible(f"data/{filename}/DemandLocation.csv")
+    factory = _read_csv_flexible(f"data/{filename}/FactoryLocation.csv")
 
     # Demand: assume first column name, last two numeric
     demand_coords = _infer_coords(demand, demand.columns[0], demand.columns[-2], demand.columns[-1])
@@ -56,7 +60,7 @@ def main():
             rows.append({"demand_city": drow["name"], "factory": frow["name"], "distance_km": dist})
 
     df = pd.DataFrame(rows)
-    out_path = Path("data") / "distance_matrix.csv"
+    out_path = Path("data") / filename / "distance_matrix.csv"
     df.to_csv(out_path, index=False, encoding="utf-8-sig")
     print(f"Saved {len(df)} rows to {out_path}")