Sync main.py from blood-brain-omics repo

main.py

@@ -288,7 +288,9 @@ def shutdown():
 # Helpers
 # =============================================================================
 
-VALID_METRICS = {"r2", "pearson", "mse", "mae"}
+VALID_METRICS = {"r2", "pearson", "mse", "mae", "accuracy", "f1"}
+# Metrics where lower is better (used by every endpoint that compares values).
+ASCENDING_METRICS = {"mse", "mae"}
 
 
 def q(sql: str, params=None):
@@ -398,11 +400,12 @@ def maxn_detail(
     phase = covariate_phase("maxn", covariates)
 
     rows = q("""
-        SELECT target, n_samples, r2, pearson, mse, mae
+        SELECT target, task_type, n_samples, r2, pearson, mse, mae,
+               accuracy, f1
         FROM results
         WHERE phase = ? AND blood_platform = ? AND brain_target = ?
               AND model = ?
-        ORDER BY r2 DESC
+        ORDER BY COALESCE(r2, accuracy) DESC
     """, [phase, blood, brain, model]).fetchall()
 
     return {
@@ -411,8 +414,9 @@ def maxn_detail(
         "covariates": covariates,
         "model": model,
         "targets": [
-            {"target": r[0], "n_samples": r[1], "r2": r[2],
-             "pearson": r[3], "mse": r[4], "mae": r[5]}
+            {"target": r[0], "task_type": r[1], "n_samples": r[2],
+             "r2": r[3], "pearson": r[4], "mse": r[5], "mae": r[6],
+             "accuracy": r[7], "f1": r[8]}
             for r in rows
         ],
     }
@@ -502,7 +506,7 @@ def h2h_blood_summary(
                 platforms = list(buffer.keys())
                 v0, v1 = buffer[platforms[0]], buffer[platforms[1]]
                 if v0 is not None and v1 is not None:
-                    asc = metric in ("mse", "mae")
+                    asc = metric in ASCENDING_METRICS
                     winner = platforms[0] if (v0 < v1 if asc else v0 > v1) else platforms[1]
                     pair_wins[pair_key][winner] = pair_wins[pair_key].get(winner, 0) + 1
             current = key
@@ -517,7 +521,7 @@ def h2h_blood_summary(
         platforms = list(buffer.keys())
         v0, v1 = buffer[platforms[0]], buffer[platforms[1]]
         if v0 is not None and v1 is not None:
-            asc = metric in ("mse", "mae")
+            asc = metric in ASCENDING_METRICS
             winner = platforms[0] if (v0 < v1 if asc else v0 > v1) else platforms[1]
             pair_wins[pair_key][winner] = pair_wins[pair_key].get(winner, 0) + 1
 
@@ -578,7 +582,7 @@ def h2h_blood_per_outcome(
                 "platforms": sorted(platforms_seen), "outcomes": []}
 
     p_a, p_b = sorted(platforms_seen)
-    asc = metric in ("mse", "mae")
+    asc = metric in ASCENDING_METRICS
 
     # Aggregate per brain_target
     by_outcome: dict[str, dict] = {}