Upload 2 files

runtime.py

@@ -1410,6 +1410,91 @@ def save_live_accuracy(data: dict[str, Any]) -> None:
     LIVE_ACCURACY_PATH.write_text(json.dumps(data, indent=2), encoding="utf-8")
 
 
+def seed_live_accuracy_from_backtest() -> dict[str, Any]:
+    """Seed the live accuracy ledger from backtest test predictions.
+    
+    This creates the baseline entries from the test set so that
+    accuracy starts at the backtest level and moves smoothly.
+    """
+    ledger = {
+        "tomorrow": {"entries": [], "accuracy": None, "total": 0, "correct_count": 0, "live_count": 0},
+        "t5": {"entries": [], "accuracy": None, "total": 0, "correct_count": 0, "live_count": 0},
+        "tplus1": {"entries": [], "accuracy": None, "total": 0, "correct_count": 0, "live_count": 0},
+    }
+    
+    # Seed T+5
+    t5_test = load_test_predictions()
+    if not t5_test.empty and "correct" in t5_test.columns:
+        for _, row in t5_test.iterrows():
+            day = pd.to_datetime(row.get("date")).date().isoformat()
+            pred = str(row.get("prediction", "")).upper()
+            correct = bool(row.get("correct"))
+            actual = pred if correct else ("DOWN" if pred == "UP" else "UP")
+            ledger["t5"]["entries"].append({
+                "date": day, "prediction": pred,
+                "actual": actual, "correct": correct,
+                "source": "backtest",
+            })
+
+    # Seed Tomorrow
+    tom_test = load_tomorrow_test_predictions()
+    if not tom_test.empty:
+        if "pred" in tom_test.columns and "prediction" not in tom_test.columns:
+            tom_test["prediction"] = np.where(pd.to_numeric(tom_test["pred"], errors="coerce") == 1, "UP", "DOWN")
+        if "correct" not in tom_test.columns and {"target", "pred"}.issubset(tom_test.columns):
+            tom_test["correct"] = pd.to_numeric(tom_test["target"], errors="coerce") == pd.to_numeric(tom_test["pred"], errors="coerce")
+        if "correct" in tom_test.columns:
+            for _, row in tom_test.iterrows():
+                target_date = row.get("target_date")
+                if pd.isna(target_date):
+                    continue
+                day = pd.to_datetime(target_date).date().isoformat()
+                pred = str(row.get("prediction", "")).upper()
+                correct = bool(row.get("correct"))
+                actual = pred if correct else ("DOWN" if pred == "UP" else "UP")
+                ledger["tomorrow"]["entries"].append({
+                    "date": day, "prediction": pred,
+                    "actual": actual, "correct": correct,
+                    "source": "backtest",
+                })
+
+    # Seed T+1
+    t1_test = load_tplus1_test_predictions()
+    if not t1_test.empty:
+        for _, row in t1_test.iterrows():
+            target_date = row.get("target_date")
+            if pd.isna(target_date):
+                continue
+            day = pd.to_datetime(target_date).date().isoformat()
+            pred = str(row.get("prediction", "")).upper()
+            if "correct" in t1_test.columns:
+                correct = bool(row.get("correct"))
+                actual = pred if correct else ("DOWN" if pred == "UP" else "UP")
+            elif {"target", "prediction"}.issubset(t1_test.columns):
+                target_val = pd.to_numeric(row.get("target"), errors="coerce")
+                actual = "UP" if target_val == 1 else "DOWN"
+                correct = pred == actual
+            else:
+                continue
+            ledger["tplus1"]["entries"].append({
+                "date": day, "prediction": pred,
+                "actual": actual, "correct": correct,
+                "source": "backtest",
+            })
+
+    for model_id in ("t5", "tomorrow", "tplus1"):
+        entries = ledger[model_id]["entries"]
+        total = len(entries)
+        correct = sum(1 for e in entries if e.get("correct"))
+        ledger[model_id]["total"] = total
+        ledger[model_id]["correct_count"] = correct
+        ledger[model_id]["accuracy"] = correct / total if total > 0 else None
+        ledger[model_id]["live_count"] = 0
+
+    save_live_accuracy(ledger)
+    return ledger
+
+
 def update_live_accuracy(session_date: date) -> dict[str, Any]:
     """Score today's predictions against actual outcomes and update the ledger.
 
@@ -1419,6 +1504,11 @@ def update_live_accuracy(session_date: date) -> dict[str, Any]:
     we want to score).
     """
     ledger = load_live_accuracy()
+    
+    # If ledger is empty/unseeded, seed from backtest first
+    if not any(ledger[m].get("entries") for m in ("t5", "tomorrow", "tplus1")):
+        ledger = seed_live_accuracy_from_backtest()
+
     daily = pd.read_parquet(NIFTY_1D_PATH)
     daily["_date"] = pd.to_datetime(daily["date"], errors="coerce").dt.normalize()
     today_rows = daily[daily["_date"].dt.date == session_date]
@@ -1445,6 +1535,7 @@ def update_live_accuracy(session_date: date) -> dict[str, Any]:
                         "prediction": pred,
                         "actual": actual_close_gt_open,
                         "correct": pred == actual_close_gt_open,
+                        "source": "live",
                     })
         except Exception:
             pass
@@ -1462,6 +1553,7 @@ def update_live_accuracy(session_date: date) -> dict[str, Any]:
                         "prediction": pred,
                         "actual": actual_close_gt_open,
                         "correct": pred == actual_close_gt_open,
+                        "source": "live",
                     })
         except Exception:
             pass
@@ -1495,6 +1587,7 @@ def update_live_accuracy(session_date: date) -> dict[str, Any]:
                         "prediction": pred,
                         "actual": t1_actual,
                         "correct": pred == t1_actual,
+                        "source": "live",
                     })
         except Exception:
             pass
@@ -1503,8 +1596,10 @@ def update_live_accuracy(session_date: date) -> dict[str, Any]:
     for model_id in ("t5", "tomorrow", "tplus1"):
         entries = ledger[model_id]["entries"]
         total = len(entries)
+        live_count = sum(1 for e in entries if e.get("source") == "live")
         correct = sum(1 for e in entries if e.get("correct"))
         ledger[model_id]["total"] = total
+        ledger[model_id]["live_count"] = live_count
         ledger[model_id]["correct_count"] = correct
         ledger[model_id]["accuracy"] = correct / total if total > 0 else None
 

test.py

@@ -0,0 +1,12 @@
+import sys
+sys.path.append('backend')
+from nifty_backend.runtime import update_live_accuracy, load_live_accuracy, dashboard_payload
+from datetime import datetime
+
+print('Seeding live accuracy...')
+update_live_accuracy(datetime.now().date())
+ledger = load_live_accuracy()
+for m in ('t5', 'tomorrow', 'tplus1'):
+    print(f'{m}: total={ledger[m].get("total")}, accuracy={ledger[m].get("accuracy")}')
+
+print('\nDone')