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