mirror of
https://github.com/zenorogue/hyperrogue.git
synced 2024-11-14 01:14:48 +00:00
157 lines
3.8 KiB
C++
157 lines
3.8 KiB
C++
// a header file for kohonen and embedding
|
|
// Copyright (C) 2011-2022 Tehora and Zeno Rogue, see 'hyper.cpp' for details
|
|
|
|
#ifndef _KOHONEN_H_
|
|
#define _KOHONEN_H_
|
|
|
|
#include "../rogueviz.h"
|
|
|
|
namespace rogueviz {
|
|
|
|
namespace kohonen {
|
|
|
|
typedef vector<double> kohvec;
|
|
|
|
static const flagtype KS_ROGUEVIZ = 1;
|
|
static const flagtype KS_NEURONS = 2;
|
|
static const flagtype KS_DISPERSION = 4;
|
|
static const flagtype KS_SAMPLES = 8;
|
|
static const flagtype KS_NEURONS_INI = 16;
|
|
|
|
extern flagtype state;
|
|
|
|
extern map<int, int> sample_vdata_id;
|
|
|
|
extern int tmax;
|
|
extern int samples;
|
|
extern int t, tmax, lpct, cells;
|
|
extern int gaussian;
|
|
|
|
extern int krad, kqty, kohrestrict;
|
|
extern int qpct;
|
|
extern int columns;
|
|
extern double dispersion_end_at;
|
|
extern int dispersion_count;
|
|
extern double learning_factor, distmul;
|
|
extern double ttpower;
|
|
extern int min_group, max_group, columns;
|
|
extern bool dispersion_long;
|
|
|
|
struct neuron {
|
|
kohvec net;
|
|
cell *where;
|
|
double udist;
|
|
int lpbak;
|
|
color_t col;
|
|
int allsamples, drawn_samples, csample, bestsample, max_group_here;
|
|
int debug;
|
|
neuron() { drawn_samples = allsamples = bestsample = 0; max_group_here = max_group; debug = 0; }
|
|
};
|
|
|
|
struct sample {
|
|
kohvec val;
|
|
string name;
|
|
};
|
|
|
|
inline void alloc(kohvec& k) { k.resize(columns); }
|
|
|
|
extern kohvec weights;
|
|
extern vector<sample> data;
|
|
extern vector<int> samples_to_show;
|
|
extern vector<neuron> net;
|
|
extern vector<string> colnames;
|
|
|
|
extern vector<int> sample_sequence;
|
|
|
|
void initialize_neurons();
|
|
void initialize_neurons_initial();
|
|
void initialize_dispersion();
|
|
void initialize_samples_to_show();
|
|
void clear();
|
|
void create_neurons();
|
|
void analyze();
|
|
void step();
|
|
void initialize_rv();
|
|
void set_neuron_initial();
|
|
bool finished();
|
|
|
|
vector<cell*> gen_neuron_cells();
|
|
neuron& winner(int id);
|
|
|
|
double vdot(const kohvec& a, const kohvec& b);
|
|
void vshift(kohvec& a, const kohvec& b, ld i);
|
|
double vnorm(kohvec& a, kohvec& b);
|
|
}
|
|
|
|
namespace embeddings {
|
|
|
|
ld gaussian_random();
|
|
|
|
using kohonen::columns;
|
|
using kohonen::kohvec;
|
|
using kohonen::alloc;
|
|
|
|
enum embedding_type { eProjection, eNatural, eLandscape, eSignpost, eHypersian };
|
|
extern embedding_type etype;
|
|
void mark_signposts(bool full, const vector<cell*>& ac);
|
|
void mark_signposts_subg(int a, int b, const vector<cell*>& ac);
|
|
void generate_rug(int i, bool close);
|
|
void init_landscape(int dimensions);
|
|
void init_landscape_det(const vector<cell*>& ac);
|
|
|
|
extern map<cell*, hyperpoint> rug_coordinates;
|
|
extern void get_coordinates(kohvec& v, cell *c, cell *c0);
|
|
|
|
extern vector<cell*> signposts;
|
|
|
|
extern map<cellwalker, kohvec> delta_at;
|
|
|
|
}
|
|
|
|
namespace voronoi {
|
|
|
|
struct manifold {
|
|
|
|
int N; /* the number of tiles */
|
|
int T; /* the number of triangles */
|
|
|
|
/* triangles between three adjacent tiles. triangles[i] are the tiles of triangle i */
|
|
vector<array<int, 3>> triangles;
|
|
|
|
/* triangles_of_tile[t] is ids of triangles which contain t */
|
|
vector<vector<int>> triangles_of_tile;
|
|
|
|
map<pair<int, int>, vector<int>> triangles_of_edge;
|
|
|
|
void generate_data();
|
|
};
|
|
|
|
inline string debug_str;
|
|
manifold build_manifold(const vector<cell*>& cells);
|
|
vector<pair<int, int> > compute_voronoi_edges(manifold& m);
|
|
}
|
|
|
|
namespace measures {
|
|
|
|
struct manidata {
|
|
int size;
|
|
vector<vector<int> > distances;
|
|
vector<pair<int, int> > edges;
|
|
};
|
|
|
|
static const int MCOUNT = 12;
|
|
|
|
extern vector<string> catnames;
|
|
|
|
vector<pair<int, int>> recreate_topology(const vector<int>& mapp, const vector<pair<int, int> >& edges);
|
|
vector<vector<int>> build_distance_matrix(int N, const vector<pair<int,int>>& vedges);
|
|
ld evaluate_measure(manidata& emb, manidata& orig, vector<int>& mapp, vector<pair<int, int> >& vor_edges, vector<pair<int, int>>& edo_recreated, int k);
|
|
|
|
}
|
|
|
|
static const string som_test_dir = "results/";
|
|
}
|
|
|
|
|
|
#endif
|