mirrors/hyperrogue
1
0
Fork 0
mirror of https://github.com/zenorogue/hyperrogue.git synced 2024-10-31 19:36:16 +00:00
Code Issues Releases Wiki Activity

rogueviz::kohonen:: precise_placement

Browse Source
This commit is contained in:
Zeno Rogue 2021-03-31 00:42:51 +02:00
parent d781bf538e
commit 5ca009f58b
1 changed files with 105 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

109
rogueviz/kohonen.cpp
View File

@ -75,6 +75,16 @@ void normalize() {
}
}
double vdot(const kohvec& a, const kohvec& b) {
double diff = 0;
for(int k=0; k<columns; k++) diff += a[k] * b[k] * weights[k];
return diff;
}
void vshift(kohvec& a, const kohvec& b, ld i) {
for(int k=0; k<columns; k++) a[k] += b[k] * i;
}
double vnorm(kohvec& a, kohvec& b) {
double diff = 0;
for(int k=0; k<columns; k++) diff += sqr((a[k]-b[k]) * weights[k]);
@ -231,11 +241,93 @@ void coloring() {
if(maxl-minl < 1e-3) maxl = minl+1e-3;
for(int i=0; i<cells; i++)
part(net[i].where->landparam_color, pid) = (255 * (listing[i] - minl)) / (maxl - minl);
part(net[i].where->landparam_color, pid) = 32 + (191 * (listing[i] - minl)) / (maxl - minl);
for(int i=0; i<cells; i++)
net[i].where->wall = waNone;
vid.wallmode = 2;
}
}
}
ld precise_placement = 1.6;
bool triangulate(kohvec d, neuron& w, map<cell*, neuron*>& find, transmatrix& res) {
if(precise_placement < 1) return false;
ld bdiff = HUGE_VAL;
/* find the second neuron */
neuron *second = nullptr;
int dir2 = -1;
forCellIdEx(c2, i, w.where) {
if(!find.count(c2)) continue;
auto w2 = find[c2];
double diff = vnorm(w2->net, d);
if(diff < bdiff) bdiff = diff, second = w2, dir2 = i;
}
if(!second) return false;
/* find the third neuron */
neuron *third = nullptr; bdiff = HUGE_VAL;
int dir3 = -1;
forCellIdEx(c3, i, w.where) {
if(!find.count(c3)) continue;
if(valence() == 3 && !isNeighbor(c3, second->where)) continue;
auto w3 = find[c3];
double diff = vnorm(w3->net, d);
if(diff < bdiff) bdiff = diff, third = w3, dir3 = i;
}
if(!third) return false;
const kohvec& a = w.net;
kohvec b = second->net;
kohvec c = third->net;
/* center at a */
vshift(b, a, -1);
vshift(c, a, -1);
vshift(d, a, -1);
/* orthonormalize */
kohvec c1 = c;
kohvec d1 = d;
ld bd = vdot(b, b);
if(bd < 1e-12) return false;
ld s = vdot(c1, b) / bd;
vshift(c1, b, -s);
ld db = vdot(d1, b) / bd;
ld cd = vdot(c1, c1);
if(cd < 1e-12) return false;
ld dc = vdot(d1, c1) / cd;
// b is: (1,0)
// c is: (s,1)
// d is: (db,dc) = dc * (s,1) + (db-dc*s) * (1,0)
db -= dc * s;
if(db < 0) dc = dc / (1-db), db = 0;
if(dc < 0) db = db / (1-dc), dc = 0;
ld overflow = db + dc - 1;
if(overflow > 0) tie(db,dc) = make_pair(db/(db+dc), dc/(db+dc));
db /= precise_placement, dc /= precise_placement;
hyperpoint h = (1-dc-db) * C0 + db * tC0(currentmap->adj(w.where, dir2)) + dc * tC0(currentmap->adj(w.where, dir3));
h = normalize(h);
res = rgpushxto0(h);
return true;
}
void distribute_neurons() {
whowon.resize(samples);
@ -247,7 +339,11 @@ void distribute_neurons() {
whowon[s] = &w;
w.drawn_samples++;
}
map<cell*, neuron*> find;
if(precise_placement >= 1)
for(auto& w: net) find[w.where] = &w;
ld rad = .25 * cgi.scalefactor;
for(auto p: sample_vdata_id) {
@ -255,9 +351,12 @@ void distribute_neurons() {
int s = p.first;
auto& w = *whowon[s];
vdata[id].m->base = w.where;
vdata[id].m->at =
spin(2*M_PI*w.csample / w.drawn_samples) * xpush(rad * (w.drawn_samples-1) / w.drawn_samples);
if(!triangulate(data[s].val, w, find, vdata[id].m->at))
vdata[id].m->at =
spin(2*M_PI*w.csample / w.drawn_samples) * xpush(rad * (w.drawn_samples-1) / w.drawn_samples);
w.csample++;
for(auto& e: vdata[id].edges) e.second->orig = nullptr;
}
shmup::fixStorage();
@ -1287,6 +1386,8 @@ void showMenu() {
dialog::addItem("level lines", '4');
dialog::add_action_push(levelline::show);
add_edit(precise_placement);
}
void save_compressed(string name) {