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hyperrogue/rogueviz/sag/experiments.cpp
2024-07-24 21:18:13 +02:00

298 lines
7.9 KiB
C++

// RogueViz -- SAG embedder: some experiments
// Copyright (C) 2011-24 Zeno Rogue, see 'hyper.cpp' for details
#include "../rogueviz.h"
namespace rogueviz {
namespace sag {
int recover_from;
vector<pair<dhrg::logistic, ld>> results;
ld bestcost;
int logid;
int lastmethod = 0;
int mul_used;
bool optimized_embedding(int mul, ld bonus = 0) {
if(logid < recover_from) { println(hlog, "skipped ", logid++, " due to recover"); return false; }
println(hlog, "starting, logid = ", logid, " recover_from = ", recover_from, " R = ", best.R+bonus, " T = ", best.T);
int DN = isize(sagid);
mul_used = mul;
lgsag_pre = best;
lgsag_pre.R += bonus;
lgsag = lgsag_pre;
compute_loglik_tab(); compute_cost();
dofullsa_iterations(mul * DN);
optimize_sag_loglik_logistic();
hlog.flush();
while(true) {
int ch = hillclimb();
println(hlog, "changes = ", ch, " cost = ", cost, " R=", lgsag.R, " T=", lgsag.T);
if(!ch) break;
optimize_sag_loglik_logistic();
hlog.flush();
}
bool new_best = cost < bestcost;
if(new_best) best = lgsag, bestcost = cost;
sag::output_stats();
results.emplace_back(lgsag, cost);
return new_best;
}
void sag_new_experiment() {
view_each = 999999;
println(hlog, "SAG new experiment started");
int DN = isize(sagid);
println(hlog, "N = ", DN);
hlog.flush();
twoway = true; allow_doubles = true;
method = smLogistic;
if(recover_from) lgsag = best;
if(!recover_from) lgsag.R = max_sag_dist;
if(!recover_from) lgsag.T = 1;
compute_loglik_tab();
compute_cost();
best = lgsag; bestcost = HUGE_VAL;
for(int i=10; i<=1; i--)
optimized_embedding(15000, i);
for(int i=1; i<=10; i++)
optimized_embedding(15000);
for(int i=1; i<=10; i++)
optimized_embedding(15000, -i);
optimized_embedding(24000);
optimized_embedding(32000);
optimized_embedding(40000);
optimized_embedding(48000);
optimized_embedding(60000);
optimized_embedding(80000);
optimized_embedding(100000);
optimized_embedding(120000);
optimized_embedding(120000);
optimized_embedding(120000);
}
void sag_v5() {
println(hlog, "SAG v5 started");
int DN = isize(sagid);
println(hlog, "N = ", DN);
recost_each = DN; autofix_rt = 2;
hlog.flush();
twoway = true; allow_doubles = true;
method = smLogistic;
lgsag.R = max_sag_dist;
lgsag.T = 1;
compute_loglik_tab();
compute_cost();
best = lgsag; bestcost = HUGE_VAL;
for(int i=0; i<30; i++) optimized_embedding(10000);
}
void sag_v6() {
println(hlog, "SAG v6 started");
int DN = isize(sagid);
println(hlog, "N = ", DN);
recost_each = DN; autofix_rt = 2;
hlog.flush();
twoway = true; allow_doubles = true;
method = smLogistic;
lgsag.R = max_sag_dist;
lgsag.T = 1;
compute_loglik_tab();
compute_cost();
best = lgsag; bestcost = HUGE_VAL;
for(int i=0; i<30; i++) optimized_embedding(100000);
autofix_rt = 1;
for(int i=0; i<30; i++) optimized_embedding(100000);
autofix_rt = 0;
for(int i=0; i<30; i++) optimized_embedding(100000);
}
void sag_test_mul() {
allow_doubles = true; twoway = true;
int DN = isize(sagid);
// lgsag.R=9.19925; lgsag.T=0.587723;
method = smLogistic;
lgsag.R = max_sag_dist;
lgsag.T = 1;
compute_loglik_tab();
compute_cost();
best = lgsag; bestcost = 999999;
recost_each = DN; autofix_rt = 2;
output_fullsa = false;
println(hlog, "sag_test_mul started");
if(1) for(int mul=25;; mul *= 2) for(int af: {3, 2, 1, 0}) {
autofix_rt = af;
ld tcost = 0;
ld tcost2 = 0;
int qty = 100;
vector<ld> costs;
// println(hlog, "R=", best.R, " T=", best.T);
for(int i=0; i<qty; i++) {
println(hlog, tie(mul, af, i));
lgsag = best; compute_loglik_tab(); compute_cost();
sag::dofullsa_iterations(mul * DN);
sag::optimize_sag_loglik_logistic();
checkmark_cost = HUGE_VAL;
while(sag::checkmark_hillclimb()) sag::optimize_sag_loglik_logistic();
tcost += cost;
tcost2 += cost * cost;
costs.push_back(cost);
bool new_best = cost < bestcost;
if(new_best) best = lgsag, bestcost = cost;
// println(hlog, "CSV;", mul, ";", af, ";", i, ";", cost);
}
sort(costs.begin(), costs.end());
println(hlog, "mul=", mul, " AF=", autofix_rt, " ECost=", tcost/qty, " sigma Cost = ", sqrt(tcost2/qty - tcost*tcost/qty/qty), " : ", costs);
}
auto tpair = [&] (int lt, int ht) {
ld tcost = 0;
for(int i=0; i<20; i++) {
sagnode.clear();
sagnode.resize(isize(sagcells), -1);
for(int i=0; i<DN; i++) sagid[i] = i;
for(int i=0; i<DN; i++) sagnode[i] = i;
compute_cost();
lowtemp = 20;
hightemp = 20;
sag::dofullsa_iterations(20 * DN);
lowtemp = lt;
hightemp = ht;
sag::dofullsa_iterations(1000 * DN);
tcost += cost;
}
println(hlog, "lt=", lt, " ht=", ht, " tcost=", tcost);
};
if(false)
for(int lt: {-3, -5, -10, -15, -20, -25})
for(int ht: {-2, -1, 0, 1, 2, 5, 10})
tpair(lt, ht);
}
void write_colors(string s) {
auto_orth(true);
if(s == "-") return;
fhstream f(s, "wt");
for(int i=0; i<isize(vdata); i++) {
println(f, vdata[i].name, ",", format("%8x", vdata[i].cp.color1));
}
}
void sag_new_experiment_viz() {
view_each = 999999;
println(hlog, "SAG new experiment started");
int DN = isize(sagid);
println(hlog, "N = ", DN);
hlog.flush();
twoway = true; allow_doubles = true;
method = smLogistic;
lgsag.R = max_sag_dist;
lgsag.T = 1;
compute_loglik_tab();
compute_cost();
best = lgsag; bestcost = HUGE_VAL;
optimized_embedding(15000, 0);
optimized_embedding(15000, 0);
}
bool report_tempi = false;
string auto_save;
void output_stats() {
if(auto_save != "" && cost < best_cost) {
println(hlog, "cost ", cost, " beats ", best_cost);
best_cost = cost;
sag::save_sag_solution(auto_save);
}
println(hlog, "solution: ", sagid);
int DN = isize(sagid);
auto [mAP, MeanRank] = compute_mAP();
dhrg::iddata routing_result;
if(!known_pairs) { known_pairs = true; dhrg::prepare_pairs(DN, [] (int i) { return edges_yes[i]; }); }
dhrg::greedy_routing(routing_result, [] (int i, int j) { return sagdist[sagid[i]][sagid[j]]; });
print(hlog, "CSV;", logid++, ";", isize(sagnode), ";", DN, ";", isize(sagedges), ";", lgsag_pre.R, ";", lgsag_pre.T, ";", lgsag.R, ";", lgsag.T, ";", cost, ";", mAP, ";", MeanRank, ";", routing_result.suc / routing_result.tot, ";", routing_result.routedist / routing_result.bestdist);
if(lastmethod) print(hlog, ";", lastmethod);
if(mul_used) print(hlog, ";", mul_used);
if(report_tempi) print(hlog, ";", hightemp,";",lowtemp,";",format("%lld", numiter));
println(hlog);
}
int exp_read_args() {
#if CAP_COMMANDLINE
using namespace arg;
if(0) ;
else if(argis("-sag-new")) sag_new_experiment();
else if(argis("-sag-v5")) sag_v5();
else if(argis("-sag-v6")) sag_v6();
else if(argis("-sag-new-viz")) sag_new_experiment_viz();
else if(argis("-sag-test-mul")) sag_test_mul();
else if(argis("-sag-write-colors")) {
shift(); write_colors(args());
}
else if(argis("-sag-recover")) {
shift(); best.R = argf();
shift(); best.T = argf();
shift(); bestcost = argf();
shift(); recover_from = argi();
println(hlog, "set recover_from to ", recover_from);
// 58.6509;7.08961;26492.1
}
else if(argis("-sag-load-solution")) {
PHASE(3); shift(); sag::load_sag_solution_basic(args());
method = smLogistic;
lgsag.R = max_sag_dist;
lgsag.T = 1;
opt_debug = true;
twoway = true; allow_doubles = true;
optimize_sag_loglik_auto();
}
else if(argis("-sagstats-logid")) {
shift(); logid = argi();
}
else if(argis("-sag0")) {
sag::report_tempi = true;
numiter = 0;
}
else if(argis("-sagsave-auto")) {
PHASE(3); shift(); auto_save = args();
}
else if(argis("-sagstats")) {
output_stats();
}
else return 1;
#endif
return 0;
}
int ahexp = addHook(hooks_args, 100, exp_read_args);
}
}