timecat 1.52.0

A NNUE-based chess engine that implements the Negamax algorithm and can be integrated into any project as a library. It features move generation, advanced position evaluation through NNUE, and move searching capabilities.
Documentation 
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#[cfg(feature = "extras")]
mod model_update_test {
    use timecat::*;

    fn check_evaluation(
        board: &mut Board,
        depth: u8,
    ) -> std::result::Result<(), Vec<ValidOrNullMove>> {
        if depth == 0 {
            return Ok(());
        }
        for valid_or_null_move in board.generate_legal_moves() {
            unsafe { board.push_unchecked(valid_or_null_move) };
            let position = board.get_position().to_owned();
            if board
                .get_evaluator_mut()
                .get_model_mut()
                .update_model_and_evaluate(&position)
                != EvaluatorNNUE::slow_evaluate_nnue_raw(&position)
            {
                return Err(board.get_all_stack_moves().collect_vec());
            }
            check_evaluation(board, depth - 1)?;
            board.pop().unwrap();
        }
        Ok(())
    }

    macro_rules! test_model_updated_correctly {
        ($func_name: ident, $fen: expr, $depth: expr) => {
            #[test]
            fn $func_name() {
                let mut board = Board::from_fen($fen).unwrap();
                if let Err(variation) = check_evaluation(&mut board, $depth) {
                    panic!(
                        "Incorrect evaluation at position {} with starting fen {} and moves {}",
                        board.get_fen(),
                        $fen,
                        Board::variation_san(
                            &mut Board::from_fen($fen).unwrap(),
                            variation.into_iter()
                        )
                        .unwrap()
                    );
                }
            }
        };
    }

    test_model_updated_correctly!(model_accumulator_update_test_1, STARTING_POSITION_FEN, 4);
    test_model_updated_correctly!(
        model_accumulator_update_test_2,
        "2kr3r/pp1bbppp/2np1n2/2P1p1q1/2B1P3/2N2N2/PBPP1PPP/R2QR1K1 w - - 8 10",
        3
    );
    test_model_updated_correctly!(
        model_accumulator_update_test_3,
        "2kr3r/pp2nppp/3pB3/2P1p1b1/4R3/8/PBPP1PPP/R2Q2K1 b - - 0 14",
        4
    );
    test_model_updated_correctly!(
        model_accumulator_update_test_4,
        "2k3r1/pp4Bp/4R3/2Pr2b1/8/8/P1P2PPP/6K1 b - - 0 21",
        3
    );
    test_model_updated_correctly!(
        model_accumulator_update_test_5,
        "8/5bk1/8/2Pp4/8/1K6/8/8 w - d6 0 1",
        4
    );
    test_model_updated_correctly!(
        model_accumulator_update_test_6,
        "8/8/1k6/8/2pP4/8/5BK1/8 b - d3 0 1",
        4
    );
    test_model_updated_correctly!(
        model_accumulator_update_test_7,
        "8/8/1k6/2b5/2pP4/8/5K2/8 b - d3 0 1",
        4
    );
    test_model_updated_correctly!(
        model_accumulator_update_test_8,
        "8/5k2/8/2Pp4/2B5/1K6/8/8 w - d6 0 1",
        4
    );
    test_model_updated_correctly!(
        model_accumulator_update_test_9,
        "5k2/8/8/8/8/8/8/4K2R w K - 0 1",
        4
    );
    test_model_updated_correctly!(
        model_accumulator_update_test_10,
        "r3k3/8/8/8/8/8/8/3K4 b q - 0 1",
        4
    );
    test_model_updated_correctly!(
        model_accumulator_update_test_11,
        "3K4/8/8/8/8/8/4p3/2k2R2 b - - 0 1",
        4
    );
    test_model_updated_correctly!(
        model_accumulator_update_test_12,
        "5K2/8/1Q6/2N5/8/1p2k3/8/8 w - - 0 1",
        4
    );
    test_model_updated_correctly!(
        model_accumulator_update_test_13,
        "8/8/8/8/8/k7/p1K5/8 b - - 0 1",
        4
    );
    test_model_updated_correctly!(
        model_accumulator_update_test_14,
        "8/8/2k5/5q2/5n2/8/5K2/8 b - - 0 1",
        4
    );
    test_model_updated_correctly!(
        model_accumulator_update_test_kiwipete,
        "r3k2r/p1ppqpb1/bn2pnp1/3PN3/1p2P3/2N2Q1p/PPPBBPPP/R3K2R w KQkq - 0 1",
        3
    );
}