first commit

backend/app/analysis/likert.py

@@ -0,0 +1,54 @@
+"""Likert scale scoring storage and aggregation."""
+
+from typing import Dict, List
+
+from sqlalchemy.orm import Session
+
+from app.models import Result
+
+
+def save_likert_score(db: Session, run_id: str, score: int) -> Result:
+    if not 1 <= score <= 5:
+        raise ValueError("Likert score must be between 1 and 5")
+    result = db.query(Result).filter_by(run_id=run_id).first()
+    if not result:
+        raise ValueError(f"Result not found for run {run_id}")
+    result.likert_score = score
+    db.commit()
+    db.refresh(result)
+    return result
+
+
+def aggregate_likert_by_model_and_level(db: Session) -> Dict[str, Dict[str, Dict[str, float]]]:
+    """Aggregate Likert scores by model_id and level.
+
+    Returns mean and frequency distribution per (model, level).
+    """
+    rows = (
+        db.query(Result, ExperimentRun)
+        .join(ExperimentRun, Result.run_id == ExperimentRun.id)
+        .all()
+    )
+
+    grouped: Dict[str, Dict[str, List[int]]] = {}
+    for result, run in rows:
+        if result.likert_score is None:
+            continue
+        key_model = run.model_id
+        key_level = run.template_version.template.level
+        grouped.setdefault(key_model, {}).setdefault(key_level, []).append(result.likert_score)
+
+    output = {}
+    for model, levels in grouped.items():
+        output[model] = {}
+        for level, scores in levels.items():
+            total = len(scores)
+            output[model][level] = {
+                "mean": round(sum(scores) / total, 2) if total else 0.0,
+                "count": total,
+                "distribution": {i: scores.count(i) for i in range(1, 6)},
+            }
+    return output
+
+
+from app.models import ExperimentRun  # noqa: E402