Improve Trader V4 training pipeline

Align entry labels with max future edge, tune direction labeling, and harden regression evaluation.

Add training diagnostics, price-plan search, feature screening, and nonlinear benchmark scripts.

training/trader_training/onnx_export.py

@@ -5,6 +5,8 @@ from pathlib import Path
 
 import numpy as np
 
+from trader_training.schemas import FEATURE_ORDER
+
 
 @dataclass(frozen=True)
 class LinearHead:
@@ -23,7 +25,7 @@ def require_onnx():
     return onnx, TensorProto, helper, numpy_helper
 
 
-def export_heads(path: Path, heads: list[LinearHead], feature_count: int = 39, opset: int = 17) -> None:
+def export_heads(path: Path, heads: list[LinearHead], feature_count: int = len(FEATURE_ORDER), opset: int = 17) -> None:
     onnx, TensorProto, helper, numpy_helper = require_onnx()
     nodes = []
     initializers = []