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/*

  Stockfish, a UCI chess playing engine derived from Glaurung 2.1

  Copyright (C) 2004-2008 Tord Romstad (Glaurung author)

  Copyright (C) 2008-2015 Marco Costalba, Joona Kiiski, Tord Romstad

  Copyright (C) 2015-2018 Marco Costalba, Joona Kiiski, Gary Linscott, Tord Romstad

  Stockfish is free software: you can redistribute it and/or modify

  it under the terms of the GNU General Public License as published by

  the Free Software Foundation, either version 3 of the License, or

  (at your option) any later version.

  Stockfish is distributed in the hope that it will be useful,

  but WITHOUT ANY WARRANTY; without even the implied warranty of

  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the

  GNU General Public License for more details.

  You should have received a copy of the GNU General Public License

  along with this program.  If not, see <http://www.gnu.org/licenses/>.

*/

#include <algorithm>

#include <cfloat>

#include <cmath>

#include "search.h"

#include "timeman.h"

#include "uci.h"

TimeManagement Time; // Our global time management object

namespace {

  enum TimeType { OptimumTime, MaxTime };

  const int MoveHorizon   = 50;   // Plan time management at most this many moves ahead

  const double MaxRatio   = 7.09; // When in trouble, we can step over reserved time with this ratio

  const double StealRatio = 0.35; // However we must not steal time from remaining moves over this ratio

  // move_importance() is a skew-logistic function based on naive statistical

  // analysis of "how many games are still undecided after n half-moves". Game

  // is considered "undecided" as long as neither side has >275cp advantage.

  // Data was extracted from the CCRL game database with some simple filtering criteria.

  double move_importance(int ply) {

    const double XScale = 7.64;

    const double XShift = 58.4;

    const double Skew   = 0.183;

    return pow((1 + exp((ply - XShift) / XScale)), -Skew) + DBL_MIN; // Ensure non-zero

  }

  template<TimeType T>

  int remaining(int myTime, int movesToGo, int ply, int slowMover) {

    const double TMaxRatio   = (T == OptimumTime ? 1 : MaxRatio);

    const double TStealRatio = (T == OptimumTime ? 0 : StealRatio);

    double moveImportance = (move_importance(ply) * slowMover) / 100;

    double otherMovesImportance = 0;

    for (int i = 1; i < movesToGo; ++i)

        otherMovesImportance += move_importance(ply + 2 * i);

    double ratio1 = (TMaxRatio * moveImportance) / (TMaxRatio * moveImportance + otherMovesImportance);

    double ratio2 = (moveImportance + TStealRatio * otherMovesImportance) / (moveImportance + otherMovesImportance);

    return int(myTime * std::min(ratio1, ratio2)); // Intel C++ asks for an explicit cast

  }

} // namespace

/// init() is called at the beginning of the search and calculates the allowed

/// thinking time out of the time control and current game ply. We support four

/// different kinds of time controls, passed in 'limits':

///

///  inc == 0 && movestogo == 0 means: x basetime  [sudden death!]

///  inc == 0 && movestogo != 0 means: x moves in y minutes

///  inc >  0 && movestogo == 0 means: x basetime + z increment

///  inc >  0 && movestogo != 0 means: x moves in y minutes + z increment

void TimeManagement::init(Search::LimitsType& limits, Color us, int ply) {

  int minThinkingTime = Options["Minimum Thinking Time"];

  int moveOverhead    = Options["Move Overhead"];

  int slowMover       = Options["Slow Mover"];

  int npmsec          = Options["nodestime"];

  // If we have to play in 'nodes as time' mode, then convert from time

  // to nodes, and use resulting values in time management formulas.

  // WARNING: Given npms (nodes per millisecond) must be much lower then

  // the real engine speed to avoid time losses.

  if (npmsec)

  {

      if (!availableNodes) // Only once at game start

          availableNodes = npmsec * limits.time[us]; // Time is in msec

      // Convert from millisecs to nodes

      limits.time[us] = (int)availableNodes;

      limits.inc[us] *= npmsec;

      limits.npmsec = npmsec;

  }

  startTime = limits.startTime;

  optimumTime = maximumTime = std::max(limits.time[us], minThinkingTime);

  const int MaxMTG = limits.movestogo ? std::min(limits.movestogo, MoveHorizon) : MoveHorizon;

  // We calculate optimum time usage for different hypothetical "moves to go"-values

  // and choose the minimum of calculated search time values. Usually the greatest

  // hypMTG gives the minimum values.

  for (int hypMTG = 1; hypMTG <= MaxMTG; ++hypMTG)

  {

      // Calculate thinking time for hypothetical "moves to go"-value

      int hypMyTime =  limits.time[us]

                     + limits.inc[us] * (hypMTG - 1)

                     - moveOverhead * (2 + std::min(hypMTG, 40));

      hypMyTime = std::max(hypMyTime, 0);

      int t1 = minThinkingTime + remaining<OptimumTime>(hypMyTime, hypMTG, ply, slowMover);

      int t2 = minThinkingTime + remaining<MaxTime    >(hypMyTime, hypMTG, ply, slowMover);

      optimumTime = std::min(t1, optimumTime);

      maximumTime = std::min(t2, maximumTime);

  }

  if (Options["Ponder"])

      optimumTime += optimumTime / 4;

}