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157 lines
3.8 KiB
C++
157 lines
3.8 KiB
C++
// a header file for kohonen and embedding
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// Copyright (C) 2011-2022 Tehora and Zeno Rogue, see 'hyper.cpp' for details
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#ifndef _KOHONEN_H_
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#define _KOHONEN_H_
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#include "../rogueviz.h"
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namespace rogueviz {
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namespace kohonen {
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typedef vector<double> kohvec;
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static constexpr flagtype KS_ROGUEVIZ = 1;
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static constexpr flagtype KS_NEURONS = 2;
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static constexpr flagtype KS_DISPERSION = 4;
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static constexpr flagtype KS_SAMPLES = 8;
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static constexpr 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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extern int gaussian;
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extern int krad, kqty, kohrestrict;
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extern int qpct;
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extern int columns;
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extern double dispersion_end_at;
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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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cell *where;
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double udist;
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int lpbak;
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color_t col;
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int allsamples, drawn_samples, csample, bestsample, max_group_here;
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int debug;
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neuron() { drawn_samples = allsamples = bestsample = 0; max_group_here = max_group; debug = 0; }
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};
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struct sample {
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kohvec val;
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string name;
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};
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inline void alloc(kohvec& k) { k.resize(columns); }
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extern kohvec weights;
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extern vector<sample> data;
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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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void initialize_samples_to_show();
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void clear();
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void create_neurons();
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void analyze();
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void step();
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void initialize_rv();
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void set_neuron_initial();
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bool finished();
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vector<cell*> gen_neuron_cells();
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neuron& winner(int id);
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double vdot(const kohvec& a, const kohvec& b);
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void vshift(kohvec& a, const kohvec& b, ld i);
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double vnorm(kohvec& a, kohvec& b);
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}
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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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enum embedding_type { eProjection, eNatural, eLandscape, eSignpost, eHypersian };
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extern embedding_type etype;
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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 constexpr 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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#endif
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