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Introduce notation.h

Browse Source 
And group there all the formatting functions but
uci_pv() that requires access to search.cpp variables.

No functional change.

Signed-off-by: Marco Costalba <mcostalba@gmail.com>
This commit is contained in:
Marco Costalba
2012-07-15 08:14:25 +01:00
parent abc6a0be2f
commit 520e680278
6 changed files with 191 additions and 158 deletions
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190
src/search.cpp
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@@ -21,7 +21,6 @@
#include <cassert>
#include <cmath>
#include <cstring>
#include <iomanip>
#include <iostream>
#include <sstream>
@@ -30,6 +29,7 @@
#include "history.h"
#include "movegen.h"
#include "movepick.h"
#include "notation.h"
#include "search.h"
#include "timeman.h"
#include "thread.h"
@@ -144,8 +144,6 @@ namespace {
bool connected_threat(const Position& pos, Move m, Move threat);
Value refine_eval(const TTEntry* tte, Value ttValue, Value defaultEval);
Move do_skill_level();
string score_to_uci(Value v, Value alpha = -VALUE_INFINITE, Value beta = VALUE_INFINITE);
string pretty_pv(Position& pos, int depth, Value score, int time, Move pv[]);
string uci_pv(const Position& pos, int depth, Value alpha, Value beta);
// MovePickerExt class template extends MovePicker and allows to choose at
@@ -1512,25 +1510,48 @@ split_point_start: // At split points actual search starts from here
}
// score_to_uci() converts a value to a string suitable for use with the UCI
// protocol specifications:
//
// cp <x> The score from the engine's point of view in centipawns.
// mate <y> Mate in y moves, not plies. If the engine is getting mated
// use negative values for y.
// When playing with strength handicap choose best move among the MultiPV set
// using a statistical rule dependent on SkillLevel. Idea by Heinz van Saanen.
string score_to_uci(Value v, Value alpha, Value beta) {
Move do_skill_level() {
std::stringstream s;
assert(MultiPV > 1);
if (abs(v) < VALUE_MATE_IN_MAX_PLY)
s << "cp " << v * 100 / int(PawnValueMidgame);
else
s << "mate " << (v > 0 ? VALUE_MATE - v + 1 : -VALUE_MATE - v) / 2;
static RKISS rk;
s << (v >= beta ? " lowerbound" : v <= alpha ? " upperbound" : "");
// PRNG sequence should be not deterministic
for (int i = Time::current_time().msec() % 50; i > 0; i--)
rk.rand<unsigned>();
return s.str();
// RootMoves are already sorted by score in descending order
size_t size = std::min(MultiPV, RootMoves.size());
int variance = std::min(RootMoves[0].score - RootMoves[size - 1].score, PawnValueMidgame);
int weakness = 120 - 2 * SkillLevel;
int max_s = -VALUE_INFINITE;
Move best = MOVE_NONE;
// Choose best move. For each move score we add two terms both dependent on
// weakness, one deterministic and bigger for weaker moves, and one random,
// then we choose the move with the resulting highest score.
for (size_t i = 0; i < size; i++)
{
int s = RootMoves[i].score;
// Don't allow crazy blunders even at very low skills
if (i > 0 && RootMoves[i-1].score > s + EasyMoveMargin)
break;
// This is our magic formula
s += ( weakness * int(RootMoves[0].score - s)
+ variance * (rk.rand<unsigned>() % weakness)) / 128;
if (s > max_s)
{
max_s = s;
best = RootMoves[i].pv[0];
}
}
return best;
}
@@ -1577,141 +1598,6 @@ split_point_start: // At split points actual search starts from here
return s.str();
}
// pretty_pv() formats human-readable search information, typically to be
// appended to the search log file. It uses the two helpers below to pretty
// format time and score respectively.
string time_to_string(int millisecs) {
const int MSecMinute = 1000 * 60;
const int MSecHour = 1000 * 60 * 60;
int hours = millisecs / MSecHour;
int minutes = (millisecs % MSecHour) / MSecMinute;
int seconds = ((millisecs % MSecHour) % MSecMinute) / 1000;
std::stringstream s;
if (hours)
s << hours << ':';
s << std::setfill('0') << std::setw(2) << minutes << ':'
<< std::setw(2) << seconds;
return s.str();
}
string score_to_string(Value v) {
std::stringstream s;
if (v >= VALUE_MATE_IN_MAX_PLY)
s << "#" << (VALUE_MATE - v + 1) / 2;
else if (v <= VALUE_MATED_IN_MAX_PLY)
s << "-#" << (VALUE_MATE + v) / 2;
else
s << std::setprecision(2) << std::fixed << std::showpos
<< float(v) / PawnValueMidgame;
return s.str();
}
string pretty_pv(Position& pos, int depth, Value value, int time, Move pv[]) {
const int64_t K = 1000;
const int64_t M = 1000000;
StateInfo state[MAX_PLY_PLUS_2], *st = state;
Move* m = pv;
string san, padding;
size_t length;
std::stringstream s;
s << std::setw(2) << depth
<< std::setw(8) << score_to_string(value)
<< std::setw(8) << time_to_string(time);
if (pos.nodes_searched() < M)
s << std::setw(8) << pos.nodes_searched() / 1 << " ";
else if (pos.nodes_searched() < K * M)
s << std::setw(7) << pos.nodes_searched() / K << "K ";
else
s << std::setw(7) << pos.nodes_searched() / M << "M ";
padding = string(s.str().length(), ' ');
length = padding.length();
while (*m != MOVE_NONE)
{
san = move_to_san(pos, *m);
if (length + san.length() > 80)
{
s << "\n" + padding;
length = padding.length();
}
s << san << ' ';
length += san.length() + 1;
pos.do_move(*m++, *st++);
}
while (m != pv)
pos.undo_move(*--m);
return s.str();
}
// When playing with strength handicap choose best move among the MultiPV set
// using a statistical rule dependent on SkillLevel. Idea by Heinz van Saanen.
Move do_skill_level() {
assert(MultiPV > 1);
static RKISS rk;
// PRNG sequence should be not deterministic
for (int i = Time::current_time().msec() % 50; i > 0; i--)
rk.rand<unsigned>();
// RootMoves are already sorted by score in descending order
size_t size = std::min(MultiPV, RootMoves.size());
int variance = std::min(RootMoves[0].score - RootMoves[size - 1].score, PawnValueMidgame);
int weakness = 120 - 2 * SkillLevel;
int max_s = -VALUE_INFINITE;
Move best = MOVE_NONE;
// Choose best move. For each move score we add two terms both dependent on
// weakness, one deterministic and bigger for weaker moves, and one random,
// then we choose the move with the resulting highest score.
for (size_t i = 0; i < size; i++)
{
int s = RootMoves[i].score;
// Don't allow crazy blunders even at very low skills
if (i > 0 && RootMoves[i-1].score > s + EasyMoveMargin)
break;
// This is our magic formula
s += ( weakness * int(RootMoves[0].score - s)
+ variance * (rk.rand<unsigned>() % weakness)) / 128;
if (s > max_s)
{
max_s = s;
best = RootMoves[i].pv[0];
}
}
return best;
}
} // namespace