"""Verify HalfKAv2_hm features match Stockfish NNUE exactly"""

import chess
from python.model.feature_extractor import fen_to_features
from python.stockfish_wrapper import NNUEEvaluator
from python.constants import HALF_KA_V2_HM


def get_stockfish_evaluation(fen: str) -> float:
    """Get Stockfish NNUE evaluation in centipawns"""
    evaluator = NNUEEvaluator()
    eval = evaluator.evaluate(fen)
    evaluator.close()
    return eval


def get_our_evaluation(fen: str) -> float:
    """Get our model's evaluation"""
    import torch
    from python.model.nnue_linear import LinearEval

    features = fen_to_features(fen)
    features_tensor = torch.tensor([features], dtype=torch.float32)

    model = LinearEval()
    with torch.no_grad():
        eval = model(features_tensor)[0, 0].item()

    return eval


# Test positions
test_positions = [
    "rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1",  # Starting
    "rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR b KQkq - 0 1",  # Black to move
    "8/8/8/8/8/8/8/8 w KQkq - 0 1",  # Empty board
]

print("Position\t\t\t\tStockfish\t\tOur Model\tDiff")
print("-" * 80)

for fen in test_positions:
    try:
        stockfish_eval = get_stockfish_evaluation(fen)
        our_eval = get_our_evaluation(fen)
        diff = abs(stockfish_eval - our_eval)

        print(f"{fen[:25]:25}\t{stockfish_eval:10.2f}\t{our_eval:10.2f}\t{diff:.2f}")
    except Exception as e:
        print(f"{fen[:25]:25}\tERROR: {e}")