- /// init() computes evaluation weights from the corresponding UCI parameters
- /// and setup king tables.
-
- void init() {
-
- Weights[Mobility] = weight_option("Mobility (Middle Game)", "Mobility (Endgame)", WeightsInternal[Mobility]);
- Weights[PassedPawns] = weight_option("Passed Pawns (Middle Game)", "Passed Pawns (Endgame)", WeightsInternal[PassedPawns]);
- Weights[Space] = weight_option("Space", "Space", WeightsInternal[Space]);
- Weights[KingDangerUs] = weight_option("Cowardice", "Cowardice", WeightsInternal[KingDangerUs]);
- Weights[KingDangerThem] = weight_option("Aggressiveness", "Aggressiveness", WeightsInternal[KingDangerThem]);
-
- // King safety is asymmetrical. Our king danger level is weighted by
- // "Cowardice" UCI parameter, instead the opponent one by "Aggressiveness".
- // If running in analysis mode, make sure we use symmetrical king safety. We
- // do this by replacing both Weights[kingDangerUs] and Weights[kingDangerThem]
- // by their average.
- if (Options["UCI_AnalyseMode"])
- Weights[KingDangerUs] = Weights[KingDangerThem] = (Weights[KingDangerUs] + Weights[KingDangerThem]) / 2;
-
- const int MaxSlope = 30;
- const int Peak = 1280;
-
- for (int t = 0, i = 1; i < 100; i++)
- {
- t = std::min(Peak, std::min(int(0.4 * i * i), t + MaxSlope));
-
- KingDangerTable[1][i] = apply_weight(make_score(t, 0), Weights[KingDangerUs]);
- KingDangerTable[0][i] = apply_weight(make_score(t, 0), Weights[KingDangerThem]);
- }
- }
-
-
- /// trace() is like evaluate() but instead of a value returns a string suitable
- /// to be print on stdout with the detailed descriptions and values of each
- /// evaluation term. Used mainly for debugging.
-
- std::string trace(const Position& pos) {
-
- Value margin;
- std::string totals;
-
- Search::RootColor = pos.side_to_move();
-
- TraceStream.str("");
- TraceStream << std::showpoint << std::showpos << std::fixed << std::setprecision(2);
- memset(TracedScores, 0, 2 * 16 * sizeof(Score));
-
- do_evaluate<true>(pos, margin);
-
- totals = TraceStream.str();
- TraceStream.str("");
-
- TraceStream << std::setw(21) << "Eval term " << "| White | Black | Total \n"
- << " | MG EG | MG EG | MG EG \n"
- << "---------------------+-------------+-------------+---------------\n";
-
- trace_row("Material, PST, Tempo", PST);
- trace_row("Material imbalance", IMBALANCE);
- trace_row("Pawns", PAWN);
- trace_row("Knights", KNIGHT);
- trace_row("Bishops", BISHOP);
- trace_row("Rooks", ROOK);
- trace_row("Queens", QUEEN);
- trace_row("Mobility", MOBILITY);
- trace_row("King safety", KING);
- trace_row("Threats", THREAT);
- trace_row("Passed pawns", PASSED);
- trace_row("Unstoppable pawns", UNSTOPPABLE);
- trace_row("Space", SPACE);
-
- TraceStream << "---------------------+-------------+-------------+---------------\n";
- trace_row("Total", TOTAL);
- TraceStream << totals;
-
- return TraceStream.str();
- }
-
-} // namespace Eval
-
-
-namespace {
-
-template<bool Trace>
-Value do_evaluate(const Position& pos, Value& margin) {
-
- assert(!pos.in_check());
-
- EvalInfo ei;
- Score score, mobilityWhite, mobilityBlack;
-
- Key key = pos.key();
- Thread* th = pos.this_thread();
- Eval::Entry* e = th->evalTable[key];
-
- // If e->key matches the position's hash key, it means that we have analysed
- // this node before, and we can simply return the information we found the last
- // time instead of recomputing it.
- if (e->key == key)
- {
- margin = Value(e->margins[pos.side_to_move()]);
- return e->value;
- }
-
- // Otherwise we overwrite current content with this node info.
- e->key = key;
-
- // margins[] store the uncertainty estimation of position's evaluation
- // that typically is used by the search for pruning decisions.
- e->margins[WHITE] = e->margins[BLACK] = VALUE_ZERO;
-
- // Initialize score by reading the incrementally updated scores included
- // in the position object (material + piece square tables) and adding
- // Tempo bonus. Score is computed from the point of view of white.
- score = pos.psq_score() + (pos.side_to_move() == WHITE ? Tempo : -Tempo);