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00002
00003 #include "osl/rating/bradleyTerry.h"
00004 #include "osl/rating/group.h"
00005 #include "osl/checkmate/immediateCheckmate.h"
00006 #include "osl/move_generator/legalMoves.h"
00007 #include "osl/apply_move/applyMove.h"
00008 #include "osl/record/kisen.h"
00009 #include "osl/container/moveVector.h"
00010
00011 #include <boost/thread/thread.hpp>
00012 #include <iostream>
00013 #include <iomanip>
00014
00015 #ifndef MINIMAL
00016 osl::rating::
00017 BradleyTerry::BradleyTerry(FeatureSet& f, const std::string& kisen_file, int kisen_start)
00018 : features(f), kisen_filename(kisen_file), kisen_start(kisen_start), num_cpus(1), num_records(200),
00019 verbose(1), fix_group(-1), min_rating(0)
00020 {
00021 }
00022
00023 osl::rating::BradleyTerry::~BradleyTerry()
00024 {
00025 }
00026
00027 bool osl::rating::
00028 BradleyTerry::addPosition(size_t g, const NumEffectState& state,
00029 const RatingEnv& env, Move selected,
00030 valarray_t& wins, std::valarray<long double>& denominator) const
00031 {
00032 MoveVector moves;
00033 LegalMoves::generate(state, moves);
00034 if (! moves.isMember(selected))
00035 return false;
00036 const range_t range = features.range(g);
00037 #ifdef SPEEDUP_TEST
00038 const bool in_check = EffectUtil::isKingInCheck(state.getTurn(), state);
00039 if (! in_check || features.effectiveInCheck(g))
00040 #endif
00041 {
00042 int found = features.group(g).findMatch(state, selected, env);
00043 if (found >= 0)
00044 ++wins[found+range.first];
00045 }
00046 valarray_t sum_c(0.0, range.second-range.first);
00047 long double sum_e = 0.0;
00048 for (size_t i=0; i<moves.size(); ++i) {
00049 Move m = moves[i];
00050 double product = 1.0;
00051 int count = 0;
00052 int match_id = -1;
00053 for (size_t j=0; j<features.groupSize(); ++j) {
00054 #ifdef SPEEDUP_TEST
00055 if (in_check && ! features.effectiveInCheck(j))
00056 continue;
00057 #endif
00058 int found = features.group(j).findMatch(state, m, env);
00059 if (found < 0)
00060 continue;
00061 found += features.range(j).first;
00062 product *= features.weight(found);
00063 ++count;
00064 if (j == g) {
00065 assert(range.first <= found && found < range.second);
00066 match_id = found;
00067 }
00068 }
00069 assert(count);
00070 sum_e += product;
00071 if (match_id >= 0)
00072 sum_c[match_id-range.first] += product / features.weight(match_id);
00073 }
00074 assert(sum_e > 0);
00075 for (int f=range.first; f<range.second; ++f)
00076 denominator[f] += sum_c[f-range.first]/sum_e;
00077 return true;
00078 }
00079
00080 struct osl::rating::
00081 BradleyTerry::Thread
00082 {
00083 const BradleyTerry *features;
00084 size_t target;
00085 size_t first, last;
00086 valarray_t *wins;
00087 std::valarray<long double> *denominator;
00088 size_t *skip;
00089 Thread(const BradleyTerry *a, size_t t, size_t f, size_t l, valarray_t *w, std::valarray<long double> *d,
00090 size_t *s)
00091 : features(a), target(t), first(f), last(l), wins(w), denominator(d), skip(s)
00092 {
00093 }
00094 void operator()()
00095 {
00096 *skip = features->accumulate(target, first, last, *wins, *denominator);
00097 }
00098 };
00099
00100 size_t osl::rating::
00101 BradleyTerry::accumulate(size_t g, size_t first, size_t last, valarray_t& wins, std::valarray<long double>& denominator) const
00102 {
00103 assert(wins.size() == features.featureSize());
00104 KisenFile kisen_file(kisen_filename.c_str());
00105 KisenIpxFile ipx(KisenFile::ipxFileName(kisen_filename));
00106 size_t skip = 0;
00107 for (size_t i=first; i<last; i++) {
00108 if ((i % 4000) == 0)
00109 std::cerr << ".";
00110 if (ipx.getRating(i, BLACK) < min_rating
00111 || ipx.getRating(i, WHITE) < min_rating) {
00112 ++skip;
00113 continue;
00114 }
00115 NumEffectState state(kisen_file.getInitialState());
00116 RatingEnv env;
00117 env.make(state);
00118 const vector<Move> moves=kisen_file.getMoves(i+kisen_start);
00119 for (size_t j=0; j<moves.size(); j++) {
00120 if (j<2)
00121 goto next;
00122 {
00123 const Player turn = state.getTurn();
00124 if (! state.inCheck()
00125 && ImmediateCheckmate::hasCheckmateMove(turn, state))
00126 break;
00127 }
00128 if (! addPosition(g, state, env, moves[j], wins, denominator))
00129 break;
00130 next:
00131 ApplyMoveOfTurn::doMove(state, moves[j]);
00132 env.update(state, moves[j]);
00133 }
00134 }
00135 return skip;
00136 }
00137
00138 void osl::rating::
00139 BradleyTerry::update(size_t g)
00140 {
00141 std::valarray<valarray_t> wins(valarray_t(0.0, features.featureSize()), num_cpus);
00142 std::valarray<std::valarray<long double> > denominator(std::valarray<long double>(0.0, features.featureSize()), num_cpus);
00143 assert(wins.size() == num_cpus);
00144
00145 KisenFile kisen_file(kisen_filename.c_str());
00146 if (num_records==0)
00147 num_records=kisen_file.size();
00148 if (num_cpus == 1) {
00149 accumulate(g, 0, num_records, wins[0], denominator[0]);
00150 }
00151 else {
00152 size_t cur = 0;
00153 size_t last = num_records, step = (last - cur)/num_cpus;
00154 boost::ptr_vector<boost::thread> threads;
00155 std::valarray<size_t> skip((size_t)0, num_cpus);
00156 for (size_t i=0; i<num_cpus; ++i, cur += step) {
00157 size_t next = (i+1 == num_cpus) ? last : cur + step;
00158 threads.push_back(new boost::thread(Thread(this, g, cur, next, &wins[i], &denominator[i], &skip[i])));
00159 }
00160 for (size_t i=0; i<num_cpus; ++i)
00161 threads[i].join();
00162 if (g == 0)
00163 std::cerr << "skip " << skip.sum() << " / " << num_records << "\n";
00164 }
00165 const range_t range = features.range(g);
00166 for (int f=range.first; f<range.second; ++f) {
00167 const int NPRIOR = 10;
00168 double sum_win = NPRIOR;
00169 long double sum_denom = (1.0 / (features.weight(f) + 1.0)) * 2 * NPRIOR;
00170 for (size_t i=0; i<num_cpus; ++i) {
00171 sum_win += wins[i][f];
00172 sum_denom += denominator[i][f];
00173 }
00174 #ifdef DEBUG
00175 std::cerr << " " << std::setw(14) << features.feature(f).name()
00176 << " " << features.weight(f) << " => " << sum_win/sum_denom
00177 << " " << sum_win << " / " << sum_denom
00178 << " " << 400*log10(sum_win/sum_denom) << "\n";
00179 #endif
00180
00181 if (sum_denom)
00182 features.setWeight(f, sum_win/sum_denom);
00183 assert(! std::isinf(features.weight(f)));
00184 assert(! std::isnan(features.weight(f)));
00185 }
00186
00187 features.showGroup(std::cerr, g);
00188 }
00189
00190 void osl::rating::
00191 BradleyTerry::iterate()
00192 {
00193 for (int j=0; j<16; ++j) {
00194 std::cerr << "\nnew iteration " << j << "\n";
00195 for (size_t i=0; i<features.groupSize(); ++i) {
00196 update(i);
00197 features.save(output_directory, i);
00198 if ((int)(i+1) == fix_group)
00199 break;
00200 }
00201 }
00202 }
00203 #endif
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