Add EMOS auto retraining and gating

tests/test_auto_retrain_probability_calibration.py

@@ -0,0 +1,42 @@
+from scripts.auto_retrain_probability_calibration import judge_candidate
+
+
+def _report(sample_count=80, crps=-0.1, mae=0.0, hit=0.0):
+    return {
+        "summary": {
+            "sample_count": sample_count,
+            "delta": {
+                "crps": crps,
+                "mae": mae,
+                "bucket_hit_rate": hit,
+            },
+        }
+    }
+
+
+def test_candidate_gate_promotes_when_metrics_pass():
+    decision = judge_candidate(
+        _report(),
+        min_samples=50,
+        max_delta_crps=0.0,
+        max_delta_mae=0.05,
+        min_delta_bucket_hit_rate=-0.05,
+    )
+
+    assert decision["decision"] == "promote"
+    assert decision["ready_for_promotion"] is True
+    assert decision["blocking_reasons"] == []
+
+
+def test_candidate_gate_holds_when_metrics_regress():
+    decision = judge_candidate(
+        _report(sample_count=40, crps=0.1, mae=0.2, hit=-0.2),
+        min_samples=50,
+        max_delta_crps=0.0,
+        max_delta_mae=0.05,
+        min_delta_bucket_hit_rate=-0.05,
+    )
+
+    assert decision["decision"] == "hold"
+    assert decision["ready_for_promotion"] is False
+    assert len(decision["blocking_reasons"]) == 4