Eliminate configuration drift: unify direction/inference defaults to single source of truth

cli/commands.py

@@ -21,6 +21,7 @@
 from cli.tf_config import _configure_tf_metal
 
 from src.utils import load_config
+from src.core.constants import DIRECTION_DEFAULTS
 
 logger = logging.getLogger(__name__)
 
@@ -2699,8 +2700,8 @@ def _buddy_test_modular_ensemble(
     model_meta = json.loads(model_meta_path.read_text()) if model_meta_path.exists() else {}
     model_cfg = model_meta.get("config", {})
 
-    threshold_pct = model_cfg.get("direction_threshold", 0.0015)  # Default matches training
-    lookahead = model_cfg.get("direction_lookahead", 24)
+    threshold_pct = model_cfg.get("direction_threshold", DIRECTION_DEFAULTS['threshold'])
+    lookahead = model_cfg.get("direction_lookahead", DIRECTION_DEFAULTS['lookahead'])
 
     console.print(f"[dim]Using MODEL training settings: threshold={threshold_pct*100:.2f}%, lookahead={lookahead}[/dim]")
 

cli/training.py

@@ -29,6 +29,7 @@
 
 from src.utils import load_config
 from src.utils.seed_manager import set_global_seed, get_global_seed
+from src.core.constants import DIRECTION_DEFAULTS
 
 # ── String constants (SonarQube duplicate-literal fix) ──────────────
 _STYLE_HEADER = "bold cyan"
@@ -817,8 +818,8 @@ def _train_ensemble_models(
     transformer_cfg = cfg.get("transformer", {})
     use_transformer = transformer_cfg.get("use_transformer", True)
     use_regime = transformer_cfg.get("use_regime", False)
-    direction_threshold = cfg.get("direction_threshold", 0.005)
-    direction_lookahead = cfg.get("direction_lookahead", 12)
+    direction_threshold = cfg.get("direction_threshold", DIRECTION_DEFAULTS['threshold'])
+    direction_lookahead = cfg.get("direction_lookahead", DIRECTION_DEFAULTS['lookahead'])
     regime_lookback = transformer_cfg.get("regime_lookback", 20)
     regime_lookahead = transformer_cfg.get("regime_lookahead", 12)
 

src/core/constants.py

@@ -0,0 +1,36 @@
+"""
+Shared constants for ML Engine configuration.
+
+This module defines authoritative defaults that match config/config_improved_H1.yaml
+to prevent configuration drift across the codebase.
+"""
+
+# =============================================================================
+# DIRECTION LABELING DEFAULTS (H1 TIMEFRAME)
+# =============================================================================
+# These values match config/config_improved_H1.yaml:
+#   direction_threshold: 0.003  # Min 0.3% move for clear signal
+#   direction_lookahead: 24     # 24 hours lookahead
+#
+# Used by:
+# - cli/training.py (training orchestration)
+# - src/core/modular_data_loaders.py (data loading functions)
+# - cli/commands.py (backtest evaluation)
+
+DIRECTION_DEFAULTS = {
+    'threshold': 0.003,  # 0.3% minimum price move for clear signal
+    'lookahead': 24,     # 24 H1 bars = 24 hours lookahead
+}
+
+
+# =============================================================================
+# INFERENCE GATE DEFAULTS
+# =============================================================================
+# These values match config/config_improved_H1.yaml inference section
+
+INFERENCE_DEFAULTS = {
+    'min_tcn_probability': 0.60,  # 60% minimum confidence (not coin-flip)
+    'min_confidence': 50.0,       # ADX-based trend strength threshold
+    'min_momentum': 0.20,         # Momentum percentile threshold
+    'max_drawdown_pct': 0.025,    # 2.5% max expected drawdown
+}

src/core/modular_data_loaders.py

@@ -30,6 +30,8 @@
 import numpy as np
 import pandas as pd
 
+from src.core.constants import DIRECTION_DEFAULTS
+
 logger = logging.getLogger(__name__)
 
 
@@ -1682,8 +1684,8 @@ def load_regime_data(
 def load_direction_data(
     df: pd.DataFrame,
     split: Tuple[float, float, float] = (0.7, 0.2, 0.1),
-    lookahead: int = 6,
-    threshold: float = 0.001,  # 0.1% minimum move (reduced from 0.5% to include more samples)
+    lookahead: int = DIRECTION_DEFAULTS['lookahead'],
+    threshold: float = DIRECTION_DEFAULTS['threshold'],
     locked_feature_names: Optional[List[str]] = None,
     gap: int = 0,  # Gap between train/val and val/test splits (default 0 for backward compatibility)
 ) -> Dict[str, np.ndarray]:
@@ -3688,8 +3690,8 @@ def validate_no_leakage(
 def load_all_modular_data(
     df: pd.DataFrame,
     split: Tuple[float, float, float] = (0.7, 0.2, 0.1),
-    direction_threshold: float = 0.005,
-    direction_lookahead: int = 6,
+    direction_threshold: float = DIRECTION_DEFAULTS['threshold'],
+    direction_lookahead: int = DIRECTION_DEFAULTS['lookahead'],
     use_regime: bool = False,
     regime_lookback: int = 20,
     regime_lookahead: int = 12,

src/core/modular_inference.py

@@ -45,6 +45,8 @@
 import numpy as np
 import pandas as pd
 
+from .constants import INFERENCE_DEFAULTS
+
 # Import normalized feature computation from data loaders
 from .modular_data_loaders import (
     compute_normalized_features,
@@ -416,8 +418,8 @@ class InferenceConfig:
     min_confidence: float = 50.0  # 0-100 scale (tightened from 45)
 
     # Direction-confidence gate (Transformer/primary direction model)
-    # 0.55 means require >=55% (or <=45%) to consider the direction actionable.
-    min_tcn_probability: float = 0.55
+    # 0.60 means require >=60% (or <=40%) to consider the direction actionable.
+    min_tcn_probability: float = INFERENCE_DEFAULTS['min_tcn_probability']
 
     # Momentum gate - median momentum is 0.3, so 0.20 catches bottom 40%
     min_momentum: float = 0.20  # 0-1 scale (tightened from 0.15)
@@ -3884,8 +3886,8 @@ def predict(
         # === TRANSFORMER CONFIDENCE GATE (direction confidence) ===
         # Require reasonable confidence in direction prediction.
         # Prefer config-driven threshold so this can be tuned without code changes.
-        # Example: min_tcn_probability=0.55 means require >=55% (or <=45%).
-        min_dir_prob = float(getattr(self.config, 'min_tcn_probability', 0.55))
+        # Example: min_tcn_probability=0.60 means require >=60% (or <=40%).
+        min_dir_prob = float(getattr(self.config, 'min_tcn_probability', INFERENCE_DEFAULTS['min_tcn_probability']))
         min_dir_prob = max(0.5, min(0.99, min_dir_prob))
         direction_confidence_gate_passed = (
             tcn_probability >= min_dir_prob or tcn_probability <= (1.0 - min_dir_prob)
@@ -4082,7 +4084,7 @@ def predict(
                 else:
                     reasons.append(f"low_volatility_regime({volatility_regime_name or 'N/A'})")
             if not direction_confidence_gate_passed:
-                min_dir_prob = float(getattr(self.config, 'min_tcn_probability', 0.55))
+                min_dir_prob = float(getattr(self.config, 'min_tcn_probability', INFERENCE_DEFAULTS['min_tcn_probability']))
                 min_dir_prob = max(0.5, min(0.99, min_dir_prob))
                 reasons.append(f"weak_direction_conf({tcn_probability:.2f}<{min_dir_prob:.2f})")
             if self.use_regime:

tests/test_unified_defaults.py

@@ -0,0 +1,97 @@
+"""
+Test suite for unified configuration defaults.
+
+Verifies that:
+1. Constants module defines correct values
+2. All code locations use the shared constants
+3. Values match config/config_improved_H1.yaml
+"""
+
+import pytest
+import yaml
+from pathlib import Path
+
+
+def test_direction_defaults_exist():
+    """Test that DIRECTION_DEFAULTS constant is defined correctly."""
+    from src.core.constants import DIRECTION_DEFAULTS
+
+    assert 'threshold' in DIRECTION_DEFAULTS
+    assert 'lookahead' in DIRECTION_DEFAULTS
+    assert DIRECTION_DEFAULTS['threshold'] == 0.003
+    assert DIRECTION_DEFAULTS['lookahead'] == 24
+
+
+def test_inference_defaults_exist():
+    """Test that INFERENCE_DEFAULTS constant is defined correctly."""
+    from src.core.constants import INFERENCE_DEFAULTS
+
+    assert 'min_tcn_probability' in INFERENCE_DEFAULTS
+    assert 'min_confidence' in INFERENCE_DEFAULTS
+    assert 'min_momentum' in INFERENCE_DEFAULTS
+    assert 'max_drawdown_pct' in INFERENCE_DEFAULTS
+
+    assert INFERENCE_DEFAULTS['min_tcn_probability'] == 0.60
+    assert INFERENCE_DEFAULTS['min_confidence'] == 50.0
+    assert INFERENCE_DEFAULTS['min_momentum'] == 0.20
+    assert INFERENCE_DEFAULTS['max_drawdown_pct'] == 0.025
+
+
+def test_constants_match_yaml_config():
+    """Test that constants match config/config_improved_H1.yaml."""
+    from src.core.constants import DIRECTION_DEFAULTS, INFERENCE_DEFAULTS
+
+    config_path = Path(__file__).parent.parent / 'config' / 'config_improved_H1.yaml'
+    with open(config_path, 'r') as f:
+        config = yaml.safe_load(f)
+
+    # Check direction defaults
+    assert DIRECTION_DEFAULTS['threshold'] == config['direction_threshold']
+    assert DIRECTION_DEFAULTS['lookahead'] == config['direction_lookahead']
+
+    # Check inference defaults
+    inference_config = config.get('inference', {})
+    assert INFERENCE_DEFAULTS['min_tcn_probability'] == inference_config.get('min_tcn_probability')
+    assert INFERENCE_DEFAULTS['min_confidence'] == inference_config.get('min_confidence')
+    assert INFERENCE_DEFAULTS['min_momentum'] == inference_config.get('min_momentum')
+    assert INFERENCE_DEFAULTS['max_drawdown_pct'] == inference_config.get('max_drawdown_pct')
+
+
+def test_inference_config_uses_constant():
+    """Test that InferenceConfig uses INFERENCE_DEFAULTS for min_tcn_probability."""
+    from src.core.modular_inference import InferenceConfig
+    from src.core.constants import INFERENCE_DEFAULTS
+
+    config = InferenceConfig()
+    assert config.min_tcn_probability == INFERENCE_DEFAULTS['min_tcn_probability']
+    assert config.min_tcn_probability == 0.60
+
+
+def test_load_direction_data_signature():
+    """Test that load_direction_data function signature uses constants."""
+    from src.core.modular_data_loaders import load_direction_data
+    from src.core.constants import DIRECTION_DEFAULTS
+    import inspect
+
+    sig = inspect.signature(load_direction_data)
+
+    # Check default values in signature
+    assert sig.parameters['lookahead'].default == DIRECTION_DEFAULTS['lookahead']
+    assert sig.parameters['threshold'].default == DIRECTION_DEFAULTS['threshold']
+
+
+def test_load_all_modular_data_signature():
+    """Test that load_all_modular_data function signature uses constants."""
+    from src.core.modular_data_loaders import load_all_modular_data
+    from src.core.constants import DIRECTION_DEFAULTS
+    import inspect
+
+    sig = inspect.signature(load_all_modular_data)
+
+    # Check default values in signature
+    assert sig.parameters['direction_threshold'].default == DIRECTION_DEFAULTS['threshold']
+    assert sig.parameters['direction_lookahead'].default == DIRECTION_DEFAULTS['lookahead']
+
+
+if __name__ == '__main__':
+    pytest.main([__file__, '-v'])