hyperrogue/rogueviz/som/kohonen.h

// 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