rv::som:: added our tests
This commit is contained in:
Zeno Rogue
parent
e57f69b936
commit
91faa3faf3
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// analyze the SOM test results
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// Copyright (C) 2011-2022 Tehora and Zeno Rogue, see 'hyper.cpp' for details
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#include "kohonen.h"
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namespace rogueviz {
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namespace kohonen_test {
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extern string cg();
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extern int data_scale, embed_scale;
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extern int subdata_value;
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}
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double UNKNOWN_RESULT = -3;
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using namespace kohonen_test;
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namespace analyzer {
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using measures::manidata;
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using measures::MCOUNT;
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struct maniset {
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vector<string> names;
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map<string, manidata> mdata;
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};
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maniset origs, embs;
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void load_maniset(maniset& m, int scale) {
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FILE *f = fopen((som_test_dir + "edgelists-" + its(scale) + ".txt").c_str(), "r");
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while(true) {
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char buf[200];
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if(fscanf(f, "%s", buf) <= 0) break;
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if(buf[0] != '#')
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m.names.push_back(buf);
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auto& md = m.mdata[buf];
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int N, M;
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fscanf(f, "%d%d", &N, &M);
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println(hlog, "reading ", buf, " of size ", N, " and ", M, " edges");
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md.size = N;
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auto& ed = md.edges;
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for(int i=0; i<M; i++) {
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int a, b;
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fscanf(f, "%d%d", &a, &b);
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ed.emplace_back(a, b);
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}
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md.distances = measures::build_distance_matrix(N, md.edges);
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}
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fclose(f);
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}
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vector<pair<int, int> > vor_edges;
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void analyze_test() {
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println(hlog, "loading original manifolds");
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load_maniset(origs, data_scale);
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println(hlog, "loading embedding manifolds");
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load_maniset(embs, embed_scale);
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map<string, map<int, array<double, MCOUNT>>> results;
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string tablefile = som_test_dir + "table" + cg() + ".csv";
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if(1) {
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fhstream res(tablefile, "rt");
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if(!res.f) { println(hlog, "table ", tablefile, " missing"); }
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else {
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println(hlog, "reading the old table ", tablefile);
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string s = scanline(res);
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while(true) {
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s = scanline(res);
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if(s == "") break;
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int i = 0;
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while(s[i] != ';') i++;
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i++;
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while(s[i] != ';') i++;
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i++;
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int id;
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sscanf(s.c_str()+i, "%d", &id);
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auto& res = results[s.substr(0, i-1)][id];
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for(auto& d: res) d = UNKNOWN_RESULT;
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sscanf(s.c_str()+i, "%d;%lf;%lf;%lf;%lf;%lf;%lf;%lf;%lf;%lf;%lf;%lf;%lf", &id, &res[0], &res[1], &res[2], &res[3], &res[4], &res[5], &res[6], &res[7], &res[8], &res[9], &res[10], &res[11]);
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}
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}
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}
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for(string orig: origs.names) {
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string dir = som_test_dir + "pairs" + cg();
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for(string emb: embs.names) {
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string fname = dir + "/" + orig + "-" + emb + ".txt";
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if(!file_exists(fname)) continue;
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FILE *f = fopen(fname.c_str(), "rt");
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string vorname = dir + "/" + orig + "-" + emb + ".vor";
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if(!file_exists(vorname)) continue;
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FILE *vor = fopen(vorname.c_str(), "rt");
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int No = origs.mdata[orig].size;
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auto& edo = origs.mdata[orig].edges;
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vector<pair<int, int>> edo_recreated;
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int new_results = 0;
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int current_row = -1;
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auto& res1 = results[orig + ";" + emb];
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for(int it=0; it<100; it++) {
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bool know_result = res1.count(it);
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auto& res = res1[it];
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if(!know_result)
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for(int kk=0; kk<MCOUNT; kk++)
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res[kk] = UNKNOWN_RESULT;
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vector<int> mapp(No, -2);
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for(int k=0; k<MCOUNT; k++) {
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bool recompute = false;
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ld energy = 0;
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if(res[k] == UNKNOWN_RESULT || recompute) {
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while(current_row < it) {
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current_row++;
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for(int i=0; i<No; i++) fscanf(f, "%d", &mapp[i]);
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int V = 0; fscanf(vor, "%d", &V);
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vor_edges.resize(V);
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for(int i=0; i<V; i++) fscanf(vor, "%d%d", &vor_edges[i].first, &vor_edges[i].second);
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if(mapp.back() == -2) goto next_pair;
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if(current_row == it)
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edo_recreated = measures::recreate_topology(mapp, edo);
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}
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new_results++;
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energy = evaluate_measure(embs.mdata[emb], origs.mdata[orig], mapp, vor_edges, edo_recreated, k);
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if(recompute && res[k] != UNKNOWN_RESULT) {
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if(abs(res[k] - energy) > 1e-5) {
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println(hlog, "ERROR in ", orig, "->", emb, " in ", cg(), " index ", it, " : was ", res[k], " is ", energy);
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if(subdata_value) res[k] = energy;
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}
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}
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else {
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res[k] = energy;
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}
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}
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}
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}
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next_pair:
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fclose(f);
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if(new_results) println(hlog, "computed ", new_results, " new results in ", cg(), " for ", orig, " -> ", emb);
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}
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}
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fhstream o(som_test_dir + "summary" + cg() + ".html", "wt");
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println(o, "<html><body>\n");
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if(1) {
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println(o, "<table>\n");
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int manis = 0;
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for(string orig: origs.names) {
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print(o, "<tr><th>", orig, "</th>");
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for(string emb: embs.names) print(o, "<th>", emb, "</th>");
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print(o, "</tr>\n");
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for(int k: {0, 2, 4, 7, 8, 10, 11}) {
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print(o, "<tr><td>", measures::catnames[k], "</td>");
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for(string emb: embs.names) {
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ld tenergy = 0;
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int att = 0;
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auto& res1 = results[orig + ";" + emb];
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for(int it=0; it<100; it++) {
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if(!res1.count(it)) continue;
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auto& res = res1[it];
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if(res[k] == UNKNOWN_RESULT) continue;
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att++; tenergy += res[k];
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}
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if(orig == emb)
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print(o, "<td bgcolor=\"#C0FFFF\">");
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else if(manis & 1)
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print(o, "<td bgcolor=\"#FFFFC0\">");
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else
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print(o, "<td>");
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if(att == 100)
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print(o, tenergy * 1. / att);
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else if(att)
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print(o, tenergy * 1. / att, "?");
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else
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print(o, "???");
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print(o, "</td>");
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}
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print(o, "</tr>\n");
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}
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manis++;
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}
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print(o, "</table>\n");
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}
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print(o, "</body></html>\n");
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fhstream res(som_test_dir + "table" + cg() + ".csv", "wt");
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print(res, "orig;emb;index");
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for(int i=0; i<MCOUNT; i++) print(res, ";", measures::catnames[i]); println(res);
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for(auto& p: results) {
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for(auto& p2: p.second) {
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auto &p3 = p2.second;
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print(res, p.first, ";", p2.first);
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for(int i=0; i<MCOUNT; i++) print(res, ";", p3[i]); println(res);
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}
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}
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}
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auto khook = arg::add3("-analyze-test", analyze_test);
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}}
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@ -20,6 +20,8 @@ static const flagtype KS_NEURONS_INI = 16;
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extern flagtype state;
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extern map<int, int> sample_vdata_id;
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extern int tmax;
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extern int samples;
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extern int t, tmax, lpct, cells;
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@ -33,6 +35,7 @@ extern int dispersion_count;
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extern double learning_factor, distmul;
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extern double ttpower;
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extern int min_group, max_group, columns;
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extern bool dispersion_long;
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struct neuron {
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kohvec net;
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@ -58,6 +61,8 @@ extern vector<int> samples_to_show;
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extern vector<neuron> net;
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extern vector<string> colnames;
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extern vector<int> sample_sequence;
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void initialize_neurons();
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void initialize_neurons_initial();
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void initialize_dispersion();
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@ -80,6 +85,8 @@ double vnorm(kohvec& a, kohvec& b);
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namespace embeddings {
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ld gaussian_random();
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using kohonen::columns;
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using kohonen::kohvec;
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using kohonen::alloc;
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@ -90,14 +97,59 @@ void mark_signposts(bool full, const vector<cell*>& ac);
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void mark_signposts_subg(int a, int b, const vector<cell*>& ac);
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void generate_rug(int i, bool close);
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void init_landscape(int dimensions);
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void init_landscape_det(const vector<cell*>& ac);
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extern map<cell*, hyperpoint> rug_coordinates;
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extern void get_coordinates(kohvec& v, cell *c, cell *c0);
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extern vector<cell*> signposts;
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extern map<cellwalker, kohvec> delta_at;
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}
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namespace voronoi {
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struct manifold {
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int N; /* the number of tiles */
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int T; /* the number of triangles */
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/* triangles between three adjacent tiles. triangles[i] are the tiles of triangle i */
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vector<array<int, 3>> triangles;
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/* triangles_of_tile[t] is ids of triangles which contain t */
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vector<vector<int>> triangles_of_tile;
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map<pair<int, int>, vector<int>> triangles_of_edge;
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void generate_data();
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};
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inline string debug_str;
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manifold build_manifold(const vector<cell*>& cells);
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vector<pair<int, int> > compute_voronoi_edges(manifold& m);
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}
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namespace measures {
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struct manidata {
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int size;
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vector<vector<int> > distances;
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vector<pair<int, int> > edges;
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};
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static const int MCOUNT = 12;
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extern vector<string> catnames;
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vector<pair<int, int>> recreate_topology(const vector<int>& mapp, const vector<pair<int, int> >& edges);
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vector<vector<int>> build_distance_matrix(int N, const vector<pair<int,int>>& vedges);
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ld evaluate_measure(manidata& emb, manidata& orig, vector<int>& mapp, vector<pair<int, int> >& vor_edges, vector<pair<int, int>>& edo_recreated, int k);
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}
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static const string som_test_dir = "results/";
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}
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@ -0,0 +1,239 @@
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// test measures
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// Copyright (C) 2011-2022 Tehora and Zeno Rogue, see 'hyper.cpp' for details
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#include "kohonen.h"
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namespace rogueviz {
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namespace measures {
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double kendall(const vector<pair<int, int>>& allp) {
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int maxo = 0, maxe = 0;
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for(const auto& a: allp) maxo = max(maxo, a.first), maxe = max(maxe, a.second);
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maxo++; maxe++;
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if(maxo >= 256 || maxe >= 256) {
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println(hlog, "more than 256!\n");
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exit(1);
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}
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int cnt[256][256];
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for(int a=0; a<maxo; a++)
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for(int b=0; b<maxe; b++)
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cnt[a][b] = 0;
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for(const auto& a: allp) cnt[a.first][a.second]++;
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// int i1 = 0, i2 = 0;
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int K = isize(allp);
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// allp.emplace_back(maxo, maxe);
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vector<int> counts(maxe, 0);
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vector<int> totals(maxe);
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double tau = 0;
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for(int i=0; i<maxo; i++) {
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totals[0] = 0;
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for(int ii=1; ii<maxe; ii++)
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totals[0] -= counts[ii];
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for(int ii=1; ii<maxe; ii++)
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totals[ii] = totals[ii-1] + counts[ii] + counts[ii-1];
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for(int b=0; b<maxe; b++) {
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tau += totals[b] * 1. * cnt[i][b];
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counts[b] += cnt[i][b];
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}
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}
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ld par = (K * (K-1.) / 2);
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return tau / par;
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}
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vector<pair<int, int>> recreate_topology(const vector<int>& mapp, const vector<pair<int, int> >& edges) {
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auto cmapp = mapp;
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for(int i=0; i<isize(cmapp); i++) if(cmapp[i] >= 0) cmapp[i] = i;
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while(true) {
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vector<pair<int, int> > changes;
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for(auto e: edges) {
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if(cmapp[e.first] == -1 && cmapp[e.second] >= 0) changes.emplace_back(e.first, cmapp[e.second]);
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if(cmapp[e.second] == -1 && cmapp[e.first] >= 0) changes.emplace_back(e.second, cmapp[e.first]);
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}
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if(changes.empty()) break;
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for(auto ch: changes) cmapp[ch.first] = ch.second;
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}
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set<pair<int, int>> subedges;
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for(auto e: edges) {
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auto a = cmapp[e.first], b = cmapp[e.second];
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if(a==b) continue;
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if(a<b) swap(a, b);
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subedges.emplace(a, b);
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}
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vector<pair<int, int>> result;
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for(auto sube: subedges)
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result.emplace_back(sube.first, sube.second);
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return result;
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}
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vector<vector<int>> build_distance_matrix(int N, const vector<pair<int,int>>& vedges) {
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vector<vector<int>> res;
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res.resize(N);
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for(auto& r: res) r.resize(N, 1000);
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vector<vector<int>> edges_of(N);
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for(auto [a, b]: vedges) edges_of[a].push_back(b), edges_of[b].push_back(a);
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for(int i=0; i<N; i++) {
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auto& d = res[i];
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queue<int> bfs;
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auto visit = [&] (int id, int dist) {
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if(d[id] <= dist) return;
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d[id] = dist;
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bfs.push(id);
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};
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visit(i, 0);
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while(!bfs.empty()) {
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auto j = bfs.front();
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for(auto e: edges_of[j]) visit(e, d[j]+1);
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bfs.pop();
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}
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}
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return res;
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}
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vector<string> catnames = {"energy", "rips", "kendall", "empty", "emptyx", "subedges", "emptyxx", "villman1", "villman2", "vedges", "maxvill1", "maxvill2"};
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ld evaluate_measure(manidata& emb, manidata& orig, vector<int>& mapp, vector<pair<int, int> >& vor_edges, vector<pair<int, int>>& edo_recreated, int k) {
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int No = orig.size;
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int Ne = emb.size;
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auto& edo = orig.edges;
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auto& ede = emb.edges;
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auto& dise = emb.distances;
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auto& diso = orig.distances;
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ld energy = 0;
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if(k == 2) {
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vector<pair<int, int> > allp;
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allp.reserve(No * No);
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for(int i=0; i<No; i++) if(mapp[i] != -1)
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for(int j=0; j<i; j++) if(mapp[j] != -1)
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allp.emplace_back(diso[i][j], dise[mapp[i]][mapp[j]]);
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energy = kendall(allp);
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}
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else if(k == 3) {
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vector<bool> empty(Ne, true);
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for(int i=0; i<No; i++)
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if(mapp[i] != -1) empty[mapp[i]] = false;
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for(auto b: empty) if(b) energy++;
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}
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else if(k == 4 || k == 6) {
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vector<vector<int>> adj(Ne);
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vector<vector<int>> on(Ne);
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for(int i=0; i<No; i++) if(mapp[i] != -1)
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on[mapp[i]].push_back(i);
|
||||
for(auto [a,b]: ede) adj[a].push_back(b), adj[b].push_back(a);
|
||||
for(auto p: edo_recreated)
|
||||
diso[p.first][p.second] -= 100,
|
||||
diso[p.second][p.first] -= 100;
|
||||
for(int i=0; i<Ne; i++) {
|
||||
bool empty = on[i].empty();
|
||||
if(empty) {
|
||||
for(auto i1: adj[i])
|
||||
for(auto i2: adj[i])
|
||||
for(auto oi1: on[i1])
|
||||
for(auto oi2: on[i2])
|
||||
if(dise[i1][i2] > 1 && diso[oi1][oi2] <= 1)
|
||||
empty = false;
|
||||
}
|
||||
if(empty && k == 6) {
|
||||
for(auto i1: adj[i])
|
||||
for(auto i2: adj[i])
|
||||
for(auto i11: adj[i1]) {
|
||||
for(auto i21: adj[i2])
|
||||
for(auto oi1: on[i11])
|
||||
for(auto oi2: on[i21])
|
||||
if(dise[i11][i21] == dise[i11][i] + dise[i21][i] && diso[oi1][oi2] <= 1)
|
||||
empty = false;
|
||||
|
||||
for(auto oi1: on[i11])
|
||||
for(auto oi2: on[i2])
|
||||
if(dise[i11][i2] == dise[i11][i] + dise[i2][i] && diso[oi1][oi2] <= 1)
|
||||
empty = false;
|
||||
}
|
||||
}
|
||||
if(empty) energy++;
|
||||
}
|
||||
for(auto p: edo_recreated)
|
||||
diso[p.first][p.second] += 100,
|
||||
diso[p.second][p.first] += 100;
|
||||
}
|
||||
else if(k == 5) energy = isize(edo_recreated);
|
||||
else if(k == 1) {
|
||||
for(auto [a,b]: edo_recreated) {
|
||||
if(mapp[a] == -1 || mapp[b] == -1) continue;
|
||||
int d = dise[mapp[a]][mapp[b]];
|
||||
if(k == 9)
|
||||
energy += d * d;
|
||||
else if(k == 1)
|
||||
energy += (d < 2 ? 0 : d == 2 ? 1 : 100);
|
||||
}
|
||||
}
|
||||
else if(k == 0) {
|
||||
for(auto [a,b]: edo) {
|
||||
if(mapp[a] == -1 || mapp[b] == -1) continue;
|
||||
int d = dise[mapp[a]][mapp[b]];
|
||||
energy += d * d;
|
||||
}
|
||||
}
|
||||
else if(k == 7) {
|
||||
for(auto [a,b]: vor_edges) {
|
||||
int d = dise[a][b] - 1;
|
||||
energy += d*d;
|
||||
}
|
||||
}
|
||||
else if(k == 8) {
|
||||
auto disv = build_distance_matrix(Ne, vor_edges);
|
||||
int bugs = 0;
|
||||
for(auto [a,b]: ede) {
|
||||
int d = disv[a][b] - 1;
|
||||
if(d >= 900) bugs++;
|
||||
energy += d*d;
|
||||
}
|
||||
if(bugs) println(hlog, "bugs=", bugs);
|
||||
}
|
||||
else if(k == 10) {
|
||||
for(auto [a,b]: vor_edges)
|
||||
energy = max<ld>(energy, dise[a][b] - 1);
|
||||
}
|
||||
else if(k == 11) {
|
||||
auto disv = build_distance_matrix(Ne, vor_edges);
|
||||
for(auto [a,b]: ede)
|
||||
energy = max<ld>(energy, disv[a][b] - 1);
|
||||
}
|
||||
else if(k == 9)
|
||||
energy = isize(vor_edges);
|
||||
return energy;
|
||||
}
|
||||
|
||||
/*
|
||||
void test_kendall() {
|
||||
for(string orig: origs.names) {
|
||||
int No = origs.mdata[orig].size;
|
||||
vector<pair<int, int> > allp;
|
||||
auto& diso = origs.mdata[orig].distances;
|
||||
|
||||
for(int i=0; i<No; i++)
|
||||
for(int j=0; j<i; j++)
|
||||
allp.emplace_back(diso[i][j], diso[i][j]);
|
||||
|
||||
allp.emplace_back(0, 0);
|
||||
allp.emplace_back(1, 1);
|
||||
allp.emplace_back(2, 2);
|
||||
allp.emplace_back(3, 3);
|
||||
|
||||
println(hlog, orig, " : ", measures::kendall(allp));
|
||||
}
|
||||
}
|
||||
*/
|
||||
|
||||
}
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,258 @@
|
|||
// Voronoi used to measure the quality of the embedding (Villman's measure)
|
||||
// Copyright (C) 2011-2022 Tehora and Zeno Rogue, see 'hyper.cpp' for details
|
||||
|
||||
#include "kohonen.h"
|
||||
|
||||
namespace rogueviz {
|
||||
|
||||
namespace voronoi {
|
||||
|
||||
void manifold::generate_data() {
|
||||
T = isize(triangles);
|
||||
triangles_of_tile.resize(N);
|
||||
|
||||
for(int i=0; i<T; i++) {
|
||||
for(auto v: triangles[i])
|
||||
triangles_of_tile[v].push_back(i);
|
||||
for(int j=0; j<3; j++) {
|
||||
int e0 = triangles[i][j%3];
|
||||
int e1 = triangles[i][(j+1)%3];
|
||||
if(e1<e0) swap(e0, e1);
|
||||
auto p = make_pair(e0, e1);
|
||||
triangles_of_edge[p].push_back(i);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
manifold build_manifold(const vector<cell*>& cells) {
|
||||
map<cell*, int> neuron_id;
|
||||
int N = isize(cells);
|
||||
for(int i=0; i<N; i++)
|
||||
neuron_id[cells[i]] = i;
|
||||
|
||||
set<vector<int> > faces_seen;
|
||||
|
||||
for(auto c: cells) {
|
||||
for(int i=0; i<c->type; i++) {
|
||||
cellwalker cw1(c, i);
|
||||
cellwalker cw2 = cw1;
|
||||
vector<int> tlist;
|
||||
do {
|
||||
cw2 += wstep;
|
||||
cw2++;
|
||||
auto p = at_or_null(neuron_id, cw2.at);
|
||||
if(!p) goto next;
|
||||
tlist.push_back(*p);
|
||||
}
|
||||
while(cw2 != cw1);
|
||||
if(1) {
|
||||
int minv = 0;
|
||||
for(int i=0; i<isize(tlist); i++)
|
||||
if(tlist[i] < tlist[minv])
|
||||
minv = i;
|
||||
vector<int> tlist_sorted;
|
||||
for(int i=minv; i<isize(tlist); i++)
|
||||
tlist_sorted.push_back(tlist[i]);
|
||||
for(int i=0; i<minv; i++)
|
||||
tlist_sorted.push_back(tlist[i]);
|
||||
if(tlist_sorted[1] > tlist_sorted.back())
|
||||
reverse(tlist_sorted.begin()+1, tlist_sorted.end());
|
||||
faces_seen.insert(tlist_sorted);
|
||||
}
|
||||
next: ;
|
||||
}
|
||||
}
|
||||
|
||||
manifold m;
|
||||
m.N = N;
|
||||
for(const auto& v: faces_seen)
|
||||
for(int i=2; i<isize(v); i++)
|
||||
m.triangles.emplace_back(make_array(v[0], v[i-1], v[i]));
|
||||
|
||||
m.generate_data();
|
||||
return m;
|
||||
}
|
||||
|
||||
vector<pair<int, int> > compute_voronoi_edges(manifold& m) {
|
||||
|
||||
using kohonen::net;
|
||||
using kohonen::vnorm;
|
||||
using kohonen::vshift;
|
||||
using kohonen::data;
|
||||
using kohonen::kohvec;
|
||||
using kohonen::samples;
|
||||
|
||||
vector<int> best_tile;
|
||||
/* for every neuron, compute its best tile */
|
||||
int N = isize(net);
|
||||
for(int i=0; i<N; i++) {
|
||||
ld bestval = HUGE_VAL, best_id = -1;
|
||||
for(int j=0; j<samples; j++) {
|
||||
ld val = vnorm(net[i].net, data[j].val);
|
||||
if(val < bestval) bestval = val, best_id = j;
|
||||
}
|
||||
best_tile.push_back(best_id);
|
||||
}
|
||||
|
||||
constexpr int SUBD = 8;
|
||||
using neuron_triangle_pair = pair<int, int>;
|
||||
set< neuron_triangle_pair > visited;
|
||||
queue<neuron_triangle_pair> q;
|
||||
|
||||
vector<kohvec> projected(N);
|
||||
|
||||
auto visit = [&] (neuron_triangle_pair p) {
|
||||
if(visited.count(p)) return;
|
||||
visited.insert(p);
|
||||
q.push(p);
|
||||
};
|
||||
|
||||
kohvec at;
|
||||
kohonen::alloc(at);
|
||||
|
||||
auto project = [&] (kohvec& at, const array<int, 3>& tri, int i, int j) {
|
||||
int k = SUBD-i-j;
|
||||
for(auto& x: at) x = 0;
|
||||
vshift(at, data[tri[0]].val, i * 1. / SUBD);
|
||||
vshift(at, data[tri[1]].val, j * 1. / SUBD);
|
||||
vshift(at, data[tri[2]].val, k * 1. / SUBD);
|
||||
};
|
||||
|
||||
set<kohvec> already_picked;
|
||||
|
||||
map<int, string> which_best;
|
||||
|
||||
/* project all the net[ni].net on the manifold */
|
||||
for(int ni=0; ni<N; ni++) {
|
||||
kohvec best;
|
||||
int best_tri;
|
||||
ld best_dist = HUGE_VAL;
|
||||
reaction_t better = [] {};
|
||||
set<int> triangles_to_visit;
|
||||
queue<int> triangles_queue;
|
||||
|
||||
auto visit1 = [&] (int tri) {
|
||||
if(triangles_to_visit.count(tri)) return;
|
||||
triangles_to_visit.insert(tri);
|
||||
triangles_queue.push(tri);
|
||||
};
|
||||
|
||||
for(int tr: m.triangles_of_tile[best_tile[ni]])
|
||||
visit1(tr);
|
||||
|
||||
auto& bes = which_best[ni];
|
||||
|
||||
while(!triangles_queue.empty()) {
|
||||
int tri = triangles_queue.front();
|
||||
triangles_queue.pop();
|
||||
|
||||
for(int i=0; i<=SUBD; i++)
|
||||
for(int j=0; j<=SUBD-i; j++) {
|
||||
project(at, m.triangles[tri], i, j);
|
||||
ld dist = vnorm(at, net[ni].net);
|
||||
if(dist < best_dist && !already_picked.count(at)) {
|
||||
best_dist = dist, best = at, best_tri = tri;
|
||||
bes = lalign(0, tie(tri, i, j));
|
||||
better = [&tri, i, j, &m, &visit1] () {
|
||||
auto flip_edge = [&] (int t1, int t2) {
|
||||
if(t2 < t1) swap(t1, t2);
|
||||
for(auto tri1: m.triangles_of_edge[{t1, t2}])
|
||||
visit1(tri1);
|
||||
};
|
||||
auto& tria = m.triangles[tri];
|
||||
if(i == 0) flip_edge(tria[1], tria[2]);
|
||||
if(j == 0) flip_edge(tria[0], tria[2]);
|
||||
if(i+j == SUBD) flip_edge(tria[0], tria[1]);
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
better();
|
||||
}
|
||||
projected[ni] = best;
|
||||
already_picked.insert(best);
|
||||
visit({ni, best_tri});
|
||||
}
|
||||
|
||||
struct triangle_data {
|
||||
double dist[SUBD+1][SUBD+1];
|
||||
int which[SUBD+1][SUBD+1];
|
||||
triangle_data() {
|
||||
for(int i=0; i<=SUBD; i++)
|
||||
for(int j=0; j<=SUBD; j++)
|
||||
dist[i][j] = HUGE_VAL, which[i][j] = -1;
|
||||
}
|
||||
};
|
||||
|
||||
vector<triangle_data> tdatas(m.T);
|
||||
|
||||
while(!q.empty()) {
|
||||
auto ntp = q.front();
|
||||
q.pop();
|
||||
auto ni = ntp.first;
|
||||
auto& tri = m.triangles[ntp.second];
|
||||
auto& td = tdatas[ntp.second];
|
||||
|
||||
for(int i=0; i<=SUBD; i++)
|
||||
for(int j=0; j<=SUBD-i; j++) {
|
||||
project(at, tri, i, j);
|
||||
ld dist = vnorm(at, projected[ni]);
|
||||
auto& odist = td.dist[i][j];
|
||||
bool tie = abs(dist - odist) < 1e-6;
|
||||
if(tie ? ni < td.which[i][j] : dist < odist) {
|
||||
td.dist[i][j] = dist,
|
||||
td.which[i][j] = ni;
|
||||
auto flip_edge = [&] (int t1, int t2) {
|
||||
if(t2 < t1) swap(t1, t2);
|
||||
for(auto tr: m.triangles_of_edge[{t1, t2}]) {
|
||||
visit({ni, tr});
|
||||
}
|
||||
};
|
||||
if(i == 0) flip_edge(tri[1], tri[2]);
|
||||
if(j == 0) flip_edge(tri[0], tri[2]);
|
||||
if(i+j == SUBD) flip_edge(tri[0], tri[1]);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
set<pair<int, int> > voronoi_edges;
|
||||
|
||||
auto add_edge = [&] (int i, int j) {
|
||||
if(i>j) swap(i, j);
|
||||
if(i==j) return;
|
||||
voronoi_edges.insert({i, j});
|
||||
};
|
||||
|
||||
for(auto& td: tdatas) {
|
||||
for(int i=0; i<=SUBD; i++)
|
||||
for(int j=0; j<=SUBD-i; j++) {
|
||||
if(i>0) add_edge(td.which[i][j], td.which[i-1][j]);
|
||||
if(j>0) add_edge(td.which[i][j], td.which[i][j-1]);
|
||||
if(j>0) add_edge(td.which[i][j], td.which[i+1][j-1]);
|
||||
}
|
||||
}
|
||||
|
||||
if(1) {
|
||||
vector<int> degs(N, 0);
|
||||
for(auto e: voronoi_edges) degs[e.first]++, degs[e.second]++;
|
||||
for(int v=0; v<N; v++) if(degs[v] == 0) {
|
||||
fhstream vorerr("voronoi-error.txt", "at");
|
||||
println(vorerr, "error: degree 0 vertex ", v, " in ", debug_str);
|
||||
println(vorerr, "best is: ", which_best[v]);
|
||||
int id = 0;
|
||||
for(auto& td: tdatas) {
|
||||
for(int i=0; i<=SUBD; i++)
|
||||
for(int j=0; j<=SUBD-i; j++)
|
||||
if(td.which[i][j] == v) println(vorerr, "Found at ", tie(id, i, j));
|
||||
id++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
vector<pair<int, int> > result;
|
||||
for(auto ve: voronoi_edges) result.push_back(ve);
|
||||
return result;
|
||||
}
|
||||
|
||||
}
|
||||
}
|
||||
Loading…
Reference in New Issue