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]);
}
if (Options["UCI_AnalyseMode"])
ContemptFactor = VALUE_ZERO;
else
ContemptFactor = Options["Contempt Factor"] * PawnValueMg / 100;
}
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]);
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]);
}
}
void read_evaluation_uci_options(Color us) {
// King safety is asymmetrical. Our king danger level is weighted by
// "Cowardice" UCI parameter, instead the opponent one by "Aggressiveness".
const int kingDangerUs = (us == WHITE ? KingDangerUs : KingDangerThem);
const int kingDangerThem = (us == WHITE ? KingDangerThem : KingDangerUs);
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]);
// 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"].value<bool>())
Weights[kingDangerUs] = Weights[kingDangerThem] = (Weights[kingDangerUs] + Weights[kingDangerThem]) / 2;
init_safety();
}
void init() {
Weights[Mobility] = weight_option("Mobility (Midgame)", "Mobility (Endgame)", WeightsInternal[Mobility]);
Weights[PawnStructure] = weight_option("Pawn Structure (Midgame)", "Pawn Structure (Endgame)", WeightsInternal[PawnStructure]);
Weights[PassedPawns] = weight_option("Passed Pawns (Midgame)", "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]);
const double MaxSlope = 30;
const double Peak = 1280;
for (int t = 0, i = 1; i < 100; ++i)
{
t = int(std::min(Peak, std::min(0.4 * i * i, t + MaxSlope)));
KingDanger[1][i] = apply_weight(make_score(t, 0), Weights[KingDangerUs]);
KingDanger[0][i] = apply_weight(make_score(t, 0), Weights[KingDangerThem]);
}
}