Create baseline/generate_baseline_predictions.py

baseline/generate_baseline_predictions.py

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+import csv
+import os
+from typing import Dict, List
+
+K = 1.0
+
+
+def compute_surfaces(pressure: float, buffer: float, lag: float, coupling: float) -> Dict[str, float]:
+    s1 = buffer - (pressure * coupling) - (K * lag)
+    s2 = buffer - (pressure * (coupling ** 2)) - (K * lag)
+    s3 = buffer - (pressure * coupling) - (K * (lag ** 2))
+    return {
+        "baseline_surface": s1,
+        "coupling_surface": s2,
+        "lag_surface": s3,
+    }
+
+
+def compute_manifold_margin(pressure: float, buffer: float, lag: float, coupling: float) -> float:
+    return min(compute_surfaces(pressure, buffer, lag, coupling).values())
+
+
+def load_rows(path: str) -> List[Dict[str, str]]:
+    with open(path, newline="", encoding="utf-8") as f:
+        return list(csv.DictReader(f))
+
+
+def write_predictions(rows: List[Dict[str, str]], output_path: str) -> None:
+    with open(output_path, "w", newline="", encoding="utf-8") as f:
+        writer = csv.writer(f)
+        writer.writerow(["scenario_id", "prediction"])
+
+        for row in rows:
+            pressure = float(row["pressure"])
+            buffer = float(row["buffer"])
+            lag = float(row["lag"])
+            coupling = float(row["coupling"])
+
+            margin = compute_manifold_margin(pressure, buffer, lag, coupling)
+            prediction = 1 if margin >= 0 else 0
+
+            writer.writerow([row["scenario_id"], prediction])
+
+
+def run_split(input_file: str, output_file: str) -> None:
+    rows = load_rows(input_file)
+    write_predictions(rows, output_file)
+    print(f"Predictions written: {output_file}")
+
+
+def main() -> None:
+    os.makedirs("baseline_predictions", exist_ok=True)
+
+    splits = {
+        "in_domain_test": "data/in_domain_test.csv",
+        "distribution_shift": "data/distribution_shift.csv",
+        "boundary_trap": "data/boundary_trap.csv",
+    }
+
+    for split_name, input_path in splits.items():
+        output_path = f"baseline_predictions/{split_name}_baseline_predictions.csv"
+        run_split(input_path, output_path)
+
+
+if __name__ == "__main__":
+    main()