Keep bot operational when forecast model is unavailable

tests/test_calibrate_thresholds.py

@@ -1,13 +1,18 @@
 from __future__ import annotations
 
+from types import SimpleNamespace
+
 from tools.calibrate_torch_thresholds import (
     CalibrationResult,
     ForecastRecord,
+    _average_selected_predictions,
     _apply_platt_calibration,
     _choose_recommendation,
+    _full_backtest,
     _fit_platt_calibration,
     _entry_validation_skill,
 )
+from tools.train_torch_recurrent_forecaster import _ensemble_candidate
 
 
 def _result(*, trades: int, average: float, total: float, profit_factor: float) -> CalibrationResult:
@@ -85,3 +90,81 @@ def test_entry_quality_never_falls_back_to_holdout_skill() -> None:
 
     assert _entry_validation_skill(entry) == 0.12
     assert _entry_validation_skill({"skill": 0.99, "holdout_skill": 0.99}) == 0.0
+
+
+def test_batched_ensemble_averages_decoded_predictions() -> None:
+    averaged = _average_selected_predictions(
+        [
+            {"expected_return": 0.01, "q50": 0.02, "probability_up": 0.6},
+            {"expected_return": 0.03, "q50": 0.04, "probability_up": 0.8},
+        ]
+    )
+
+    assert averaged == {
+        "expected_return": 0.02,
+        "q50": 0.03,
+        "probability_up": 0.7,
+    }
+
+
+def test_multi_seed_export_does_not_duplicate_first_member_weights() -> None:
+    members = [
+        {
+            "validation_mae": 0.1,
+            "state_dict": {"weight": [seed]},
+            "head_weight": [[seed]],
+            "head_bias": [seed],
+        }
+        for seed in (7, 19)
+    ]
+
+    exported = _ensemble_candidate(members, [7, 19])
+
+    assert exported["ensemble_size"] == 2
+    assert exported["ensemble_seeds"] == [7, 19]
+    assert len(exported["ensemble_members"]) == 2
+    assert "state_dict" not in exported
+    assert "head_weight" not in exported
+
+
+def test_single_seed_export_keeps_only_top_level_weights() -> None:
+    exported = _ensemble_candidate(
+        [
+            {
+                "validation_mae": 0.1,
+                "state_dict": {"weight": [7]},
+                "head_weight": [[7]],
+                "head_bias": [7],
+            }
+        ],
+        [7],
+    )
+
+    assert exported["ensemble_size"] == 1
+    assert exported["state_dict"] == {"weight": [7]}
+    assert "ensemble_members" not in exported
+
+
+def test_full_backtest_never_uses_global_threshold_for_ineligible_symbol() -> None:
+    btc = [_record(index, 0.8, 1.0) for index in range(3)]
+    eth = [_record(index, 0.8, 1.0) for index in range(3)]
+    for record in eth:
+        record.symbol = "ETHUSDT"
+    thresholds = _result(trades=3, average=1.0, total=3.0, profit_factor=999.0)
+
+    replay = _full_backtest(
+        btc + eth,
+        thresholds,
+        horizon=3,
+        round_trip_cost=0.0,
+        settings=SimpleNamespace(
+            stop_loss_percent=0.04,
+            take_profit_percent=0.035,
+            stop_loss_exit_enabled=True,
+            atr_trailing_multiplier=2.2,
+        ),
+        symbol_thresholds={"BTCUSDT": thresholds},
+        require_symbol_thresholds=True,
+    )
+
+    assert {row["symbol"] for row in replay["symbol_breakdown"]} == {"BTCUSDT"}