further improvements to Kohonen
This commit is contained in:
Zeno Rogue
parent
b0489b7312
commit
951566399e
1
hyper.h
1
hyper.h
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@ -1524,6 +1524,7 @@ void addauraspecial(const hyperpoint& h, int col, int dir);
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void drawBug(const cellwalker& cw, int col);
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void mainloop();
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void mainloopiter();
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extern bool showstartmenu;
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void selectLanguageScreen();
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357
kohonen.cpp
357
kohonen.cpp
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@ -30,6 +30,8 @@ struct neuron {
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int samples, csample, bestsample;
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};
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vector<string> colnames;
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kohvec weights;
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vector<neuron> net;
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@ -94,10 +96,12 @@ void loadsamples(const char *fname) {
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bigbreak:
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fclose(f);
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samples = size(data);
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normalize();
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normalize();
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colnames.resize(cols);
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for(int i=0; i<cols; i++) colnames[i] = "Column " + its(i);
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uninit(0); sominit(1);
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}
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int tmax = 30000;
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double distmul = 1;
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double learning_factor = .1;
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@ -178,7 +182,7 @@ void coloring() {
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vector<double> listing;
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for(neuron& n: net) switch(c) {
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case -4:
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listing.push_back(n.samples);
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listing.push_back(log(5+n.samples));
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break;
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case -3:
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@ -477,6 +481,42 @@ void uninit(int initto) {
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if(inited > initto) inited = initto;
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}
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void showsample(int id) {
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for(int ii: samples_shown)
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if(ii == id)
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return;
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int i = vdata.size();
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samples_shown.push_back(id);
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vdata.emplace_back();
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auto& v = vdata.back();
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v.name = data[id].name;
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v.cp = dftcolor;
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createViz(i, cwt.c, Id);
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v.m->store();
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}
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void showsample(string s) {
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if(s == "") return;
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for(int i=0; i<samples; i++) {
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if(s[0] != '*' && data[i].name == s)
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showsample(i);
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if(s[0] == '*' && data[i].name.find(s.substr(1)) != string::npos)
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showsample(i);
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}
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}
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void showbestsamples() {
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vector<int> samplesbak;
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for(auto& n: net)
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if(n.samples)
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showsample(n.bestsample);
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analyze();
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for(auto& n: net) n.samples = 0;
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for(int i=0; i<samples; i++)
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if(whowon[i])
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whowon[i]->samples++;
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}
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void sominit(int initto) {
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if(inited < 1 && initto >= 1) {
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@ -563,19 +603,151 @@ void describe(cell *c) {
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if(cmode & sm::HELP) return;
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neuron *n = getNeuronSlow(c);
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if(!n) return;
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help += "cell number: " + its(neuronId(*n)) + "\n";
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help += "cell number: " + its(neuronId(*n)) + " (" + its(n->samples) + ")\n";
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help += "parameters:"; for(int k=0; k<cols; k++) help += " " + fts(n->net[k]);
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help += ", u-matrix = " + fts(n->udist);
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help += "\n";
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int qty = 0;
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for(int s=0; s<samples; s++) if(whowon[s] == n) {
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vector<pair<double, int>> v;
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for(int s=0; s<samples; s++) if(whowon[s] == n) v.emplace_back(vnorm(n->net, data[s].val), s);
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random_shuffle(v.begin(), v.end());
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sort(v.begin(), v.end(), [] (auto a, auto b) { return a.first < b.first; });
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for(int i=0; i<size(v) && i<20; i++) {
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int s = v[i].second;
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help += "sample "+its(s)+":";
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for(int k=0; k<cols; k++) help += " " + fts(data[s].val[k]);
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help += " "; help += data[s].name; help += "\n";
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qty++; if(qty >= 20) break;
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}
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}
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namespace levelline {
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struct levelline {
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int column, qty;
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unsigned int color;
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vector<double> values;
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bool modified;
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};
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vector<levelline> levellines;
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bool on;
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void create() {
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int xlalpha = int(pow(ld(.5), ggamma) * 255);
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for(int i=0; i<cols; i++) {
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levellines.emplace_back();
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levelline& lv = levellines.back();
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lv.column = i;
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lv.color = ((hrandpos() & 0xFFFFFF) << 8) | xlalpha;
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lv.qty = 0;
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}
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}
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void build() {
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if(levellines.size() == 0) create();
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on = false;
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for(auto& lv: levellines) {
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if(!lv.qty) { lv.values.clear(); continue; }
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on = true;
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if(!lv.modified) continue;
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lv.modified = false;
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vector<double> sample;
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for(int j=0; j<=1024; j++) sample.push_back(data[hrand(samples)].val[lv.column]);
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sort(sample.begin(), sample.end());
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lv.values.clear();
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lv.values.push_back(-1e10);
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for(int j=0; j<=1024; j+=1024 >> (lv.qty)) lv.values.push_back(sample[j]);
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lv.values.push_back(1e10);
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}
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}
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void draw() {
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if(!on) return;
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for(auto& g: gmatrix) {
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cell *c1 = g.first;
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transmatrix T = g.second;
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neuron *n1 = getNeuron(c1);
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if(!n1) continue;
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for(int i=0; i<c1->type; i++) {
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cell *c2 = c1->mov[i];
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if(!c2) continue;
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cell *c3 = c1->mov[i ? i-1 : c1->type-1];
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if(!c3) continue;
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if(!gmatrix.count(c2)) continue;
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if(!gmatrix.count(c3)) continue;
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double d2 = hdist(tC0(T), tC0(gmatrix[c2]));
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double d3 = hdist(tC0(T), tC0(gmatrix[c3]));
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neuron *n2 = getNeuron(c2);
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if(!n2) continue;
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neuron *n3 = getNeuron(c3);
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if(!n3) continue;
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for(auto& l: levellines) {
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auto val1 = n1->net[l.column];
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auto val2 = n2->net[l.column];
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auto val3 = n3->net[l.column];
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auto v1 = lower_bound(l.values.begin(), l.values.end(), val1);
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auto v2 = lower_bound(l.values.begin(), l.values.end(), val2);
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auto v3 = lower_bound(l.values.begin(), l.values.end(), val3);
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auto draw = [&] () {
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auto vmid = *v1;
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queueline(
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tC0(T * ddspin(c1,i) * xpush(d2 * (vmid-val1) / (val2-val1))),
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tC0(T * ddspin(c1,i-1) * xpush(d3 * (vmid-val1) / (val3-val1))),
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l.color);
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};
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while(v1 < v2 && v1 < v3) {
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draw();
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v1++;
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}
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while(v1 > v2 && v1 > v3) {
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v1--;
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draw();
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}
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}
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}
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}
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setindex(false);
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}
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void show() {
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if(levellines.size() == 0) create();
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gamescreen(0);
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cmode = vid.xres > vid.yres * 1.4 ? sm::SIDE : 0;
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dialog::init("level lines");
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char nx = 'a';
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for(auto &l : levellines) {
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dialog::addSelItem(colnames[l.column], its(l.qty), nx++);
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dialog::lastItem().colorv = l.color >> 8;
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}
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dialog::addItem("exit menu", '0');
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dialog::addItem("shift+letter to change color", 0);
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dialog::display();
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keyhandler = [] (int sym, int uni) {
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dialog::handleNavigation(sym, uni);
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if(uni >= 'a' && uni - 'a' + size(levellines)) {
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auto& l = levellines[uni - 'a'];
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dialog::editNumber(l.qty, 0, 10, 1, 0, colnames[l.column],
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XLAT("Controls the number of level lines."));
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dialog::reaction = [&l] () {
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l.modified = true;
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build();
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};
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}
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else if(uni >= 'A' && uni - 'A' + size(levellines)) {
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auto& l = levellines[uni - 'A'];
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dialog::openColorDialog(l.color, NULL);
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}
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else if(doexiton(sym, uni)) popScreen();
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};
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}
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}
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void ksave(const char *fname) {
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sominit(1);
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FILE *f = fopen(fname, "wt");
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@ -586,7 +758,7 @@ void ksave(const char *fname) {
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fprintf(f, "%d %d\n", cells, t);
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for(neuron& n: net) {
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for(int k=0; k<cols; k++)
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fprintf(f, "%.4lf ", n.net[k]);
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fprintf(f, "%.9lf ", n.net[k]);
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fprintf(f, "\n");
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}
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fclose(f);
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@ -612,26 +784,64 @@ void kload(const char *fname) {
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analyze();
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}
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void kclassify(const char *fname) {
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void ksavew(const char *fname) {
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sominit(1);
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for(neuron& n: net) n.samples = 0;
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FILE *f = fopen(fname, "wt");
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FILE *f = fopen(fname, "wt");
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if(!f) {
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fprintf(stderr, "Could not save classification\n");
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fprintf(stderr, "Could not save the weights\n");
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return;
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}
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for(int id=0; id<samples; id++) {
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auto& w = winner(id);
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w.samples++;
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if(id % 100000 == 0) printf("%d/%d\n", id, size(data));
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fprintf(f, "%s;%d\n", data[id].name.c_str(), neuronId(w));
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}
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for(int i=0; i<cols; i++)
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fprintf(f, "%s=%.9lf\n", colnames[i].c_str(), weights[i]);
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fclose(f);
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coloring();
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}
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void kclassify2(const char *fname_classify, const char *fname_samples) {
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void kloadw(const char *fname) {
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sominit(1);
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FILE *f = fopen(fname, "rt");
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if(!f) {
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fprintf(stderr, "Could not load the weights\n");
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return;
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}
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for(int i=0; i<cols; i++) {
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string s1, s2;
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char kind = 0;
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while(true) {
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int c = fgetc(f);
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if(c == 10 || c == 13 || c == -1) {
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if(s1 == "" && !kind && c != -1) continue;
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if(s1 != "") colnames[i] = s1;
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if(kind == '=') weights[i] = atof(s2.c_str());
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if(kind == '*') weights[i] *= atof(s2.c_str());
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if(kind == '/') weights[i] /= atof(s2.c_str());
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if(c == -1) break;
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goto nexti;
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}
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else if(c == '=' || c == '/' || c == '*') kind = c;
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else (kind?s2:s1) += c;
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}
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nexti: ;
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}
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fclose(f);
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analyze();
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}
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unsigned lastprogress;
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void progress(string s) {
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if(SDL_GetTicks() >= lastprogress + (noGUI ? 500 : 100)) {
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if(noGUI)
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printf("%s\n", s.c_str());
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else {
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clearMessages();
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addMessage(s);
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mainloopiter();
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}
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lastprogress = SDL_GetTicks();
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}
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}
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void kclassify(const char *fname_classify) {
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sominit(1);
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vector<double> bdiffs(samples, 1e20);
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@ -646,9 +856,10 @@ void kclassify2(const char *fname_classify, const char *fname_samples) {
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double diff = vnorm(net[n].net, data[s].val);
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if(diff < bdiffs[s]) bdiffs[s] = diff, bids[s] = n, whowon[s] = &net[n];
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}
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if(s % 1000000 == 999999) printf("%d/%d\n", s, samples);
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if(!(s % 128))
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progress("Classifying: " + its(s) + "/" + its(samples));
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}
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vector<double> bdiffn(cells, 1e20);
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printf("Finding samples...\n");
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@ -673,30 +884,55 @@ void kclassify2(const char *fname_classify, const char *fname_samples) {
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fclose(f);
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}
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}
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coloring();
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}
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void klistsamples(const char *fname_samples, bool best, bool colorformat) {
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if(fname_samples != NULL) {
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printf("Listing best samples...\n");
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printf("Listing samples...\n");
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FILE *f = fopen(fname_samples, "wt");
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if(!f) {
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printf("Failed to open file\n");
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}
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else {
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fprintf(f, "%d\n", cols);
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for(int n=0; n<cells; n++) {
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fflush(f);
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if(!net[n].samples) { fprintf(f, "\n"); continue; }
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int s = net[n].bestsample;
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for(int k=0; k<cols; k++)
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fprintf(f, "%.4lf ", data[s].val[k]);
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fflush(f);
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fprintf(f, "!%s\n", data[s].name.c_str());
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fflush(f);
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}
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auto klistsample = [f, colorformat] (int id, int neu) {
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if(colorformat) {
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fprintf(f, "%s;+#%d\n", data[id].name.c_str(), neu);
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}
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else {
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for(int k=0; k<cols; k++)
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fprintf(f, "%.4lf ", data[id].val[k]);
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fprintf(f, "!%s\n", data[id].name.c_str());
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}
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};
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if(!colorformat) fprintf(f, "%d\n", cols);
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if(best)
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for(int n=0; n<cells; n++) {
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if(!net[n].samples) { if(!colorformat) fprintf(f, "\n"); continue; }
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klistsample(net[n].bestsample, n);
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}
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else
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for(int i=0; i<size(samples_shown); i++)
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klistsample(samples_shown[i], neuronId(*(whowon[i])));
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fclose(f);
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}
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}
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}
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coloring();
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void neurondisttable(const char *fname) {
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FILE *f = fopen(fname, "wt");
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if(!f) {
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printf("Could not open file: %s\n", fname);
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return;
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}
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int neurons = size(net);
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fprintf(f, "%d\n", neurons);
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for(int i=0; i<neurons; i++) {
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for(int j=0; j<neurons; j++) fprintf(f, "%3d", celldistance(net[i].where, net[j].where));
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// todo: build the table correctly for gaussian=2
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fprintf(f, "\n");
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}
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fclose(f);
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}
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void steps() {
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@ -717,9 +953,11 @@ void showMenu() {
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else if(whattodraw[i] == -4) c = "number of samples";
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else if(whattodraw[i] == -5) c = "best sample's color";
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else if(whattodraw[i] == -6) c = "sample names to colors";
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else c = "column " + its(whattodraw[i]);
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else c = colnames[whattodraw[i]];
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dialog::addSelItem(XLAT("coloring (%1)", parts[i]), c, '1'+i);
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}
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dialog::addItem("coloring (all)", '0');
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dialog::addItem("level lines", '4');
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}
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bool handleMenu(int sym, int uni) {
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@ -734,6 +972,10 @@ bool handleMenu(int sym, int uni) {
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for(char x: {'1','2','3'}) handleMenu(x, x);
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return true;
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}
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if(uni == '4') {
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pushScreen(levelline::show);
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return true;
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}
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return false;
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}
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@ -800,7 +1042,10 @@ int readArgs() {
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// #4: run, stop etc.
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else if(argis("-somrunto")) {
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int i = argi();
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shift(); while(t > i) kohonen::step();
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shift(); while(t > i) {
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if(t % 128 == 0) progress("Steps left: " + its(t));
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kohonen::step();
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}
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}
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else if(argis("-somstop")) {
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t = 0;
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@ -809,7 +1054,10 @@ int readArgs() {
|
|||
noshow = true;
|
||||
}
|
||||
else if(argis("-somfinish")) {
|
||||
while(!finished()) kohonen::step();
|
||||
while(!finished()) {
|
||||
kohonen::step();
|
||||
if(t % 128 == 0) progress("Steps left: " + its(t));
|
||||
}
|
||||
}
|
||||
|
||||
// #5 save data, classify etc.
|
||||
|
|
@ -817,22 +1065,43 @@ int readArgs() {
|
|||
PHASE(3);
|
||||
shift(); kohonen::ksave(args());
|
||||
}
|
||||
else if(argis("-somsavew")) {
|
||||
PHASE(3);
|
||||
shift(); kohonen::ksavew(args());
|
||||
}
|
||||
else if(argis("-somloadw")) {
|
||||
PHASE(3);
|
||||
shift(); kohonen::kloadw(args());
|
||||
}
|
||||
else if(argis("-somclassify")) {
|
||||
PHASE(3);
|
||||
shift(); kohonen::kclassify(args());
|
||||
}
|
||||
else if(argis("-somclassify2")) {
|
||||
else if(argis("-somlistshown")) {
|
||||
PHASE(3);
|
||||
shift(); const char *f1 = args();
|
||||
shift(); const char *f2 = args();
|
||||
kohonen::kclassify2(f1, f2);
|
||||
shift(); kohonen::klistsamples(args(), false, false);
|
||||
}
|
||||
else if(argis("-somlistbest")) {
|
||||
PHASE(3);
|
||||
shift(); kohonen::klistsamples(args(), true, false);
|
||||
}
|
||||
else if(argis("-somlistbestc")) {
|
||||
PHASE(3);
|
||||
shift(); kohonen::klistsamples(args(), true, true);
|
||||
}
|
||||
else if(argis("-somndist")) {
|
||||
PHASE(3);
|
||||
shift(); kohonen::neurondisttable(args());
|
||||
}
|
||||
else if(argis("-somshowbest")) {
|
||||
showbestsamples();
|
||||
}
|
||||
|
||||
else return 1;
|
||||
return 0;
|
||||
}
|
||||
|
||||
auto hooks = addHook(hooks_args, 100, readArgs);
|
||||
auto hooks = addHook(hooks_args, 100, readArgs) + addHook(hooks_frame, 50, levelline::draw);
|
||||
}
|
||||
|
||||
void mark(cell *c) {
|
||||
|
|
|
|||
21
rogueviz.cpp
21
rogueviz.cpp
|
|
@ -29,6 +29,8 @@ bool specialmark = false;
|
|||
|
||||
bool rog3 = false;
|
||||
|
||||
ld ggamma = .5;
|
||||
|
||||
string fname;
|
||||
|
||||
// const char *fname;
|
||||
|
|
@ -1027,8 +1029,6 @@ void queuedisk(const transmatrix& V, const colorpair& cp, bool legend) {
|
|||
if(cp.shade == 'm') queuepoly(V, shDiskM, cp.color2);
|
||||
}
|
||||
|
||||
ld ggamma = .5;
|
||||
|
||||
void drawVertex(const transmatrix &V, cell *c, shmup::monster *m) {
|
||||
if(m->dead) return;
|
||||
int i = m->pid;
|
||||
|
|
@ -1292,7 +1292,16 @@ void readcolor(const char *cfname) {
|
|||
|
||||
colorpair x;
|
||||
int c2 = fgetc(f);
|
||||
if(c2 == '=') {
|
||||
if(kohonen::samples && c2 == '+') {
|
||||
kohonen::showsample(lab);
|
||||
c2 = fgetc(f);
|
||||
if(c2 == 10 || c2 == 13) continue;
|
||||
}
|
||||
if(c2 == '#') {
|
||||
while(c2 != 10 && c2 != 13 && c2 != -1) c2 = fgetc(f);
|
||||
continue;
|
||||
}
|
||||
else if(c2 == '=') {
|
||||
string lab2 = "";
|
||||
while(true) {
|
||||
int c = fgetc(f);
|
||||
|
|
@ -1326,6 +1335,12 @@ void readcolor(const char *cfname) {
|
|||
vdata[i].cp = x;
|
||||
}
|
||||
}
|
||||
else if(kohonen::samples) {
|
||||
for(int i=0; i<size(vdata); i++)
|
||||
if(vdata[i].name == lab) {
|
||||
vdata[i].cp = x;
|
||||
}
|
||||
}
|
||||
else {
|
||||
int i = getid(lab);
|
||||
again: vdata[i].cp = x;
|
||||
|
|
|
|||
Loading…
Reference in New Issue