[976] | 1 | /*! |
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| 2 | \file |
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| 3 | \brief Robust Bayesian auto-regression model |
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| 4 | \author Jan Sindelar. |
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| 5 | */ |
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| 6 | |
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| 7 | #ifndef ROBUST_H |
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| 8 | #define ROBUST_H |
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| 9 | |
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| 10 | #include <stat/exp_family.h> |
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[1171] | 11 | #include <limits> |
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[1172] | 12 | #include <vector> |
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[1213] | 13 | #include <list> |
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[1220] | 14 | #include <set> |
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[1172] | 15 | #include <algorithm> |
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[976] | 16 | |
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| 17 | using namespace bdm; |
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| 18 | using namespace std; |
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[1204] | 19 | using namespace itpp; |
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[976] | 20 | |
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[1254] | 21 | const double max_range = 1000.0;//numeric_limits<double>::max()/10e-10; |
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[1171] | 22 | |
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[1208] | 23 | enum actions {MERGE, SPLIT}; |
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| 24 | |
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[1171] | 25 | class polyhedron; |
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| 26 | class vertex; |
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[1254] | 27 | class toprow; |
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[1171] | 28 | |
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[1234] | 29 | /* |
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| 30 | class t_simplex |
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| 31 | { |
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| 32 | public: |
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| 33 | set<vertex*> minima; |
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| 34 | |
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| 35 | set<vertex*> simplex; |
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| 36 | |
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| 37 | t_simplex(vertex* origin_vertex) |
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| 38 | { |
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| 39 | simplex.insert(origin_vertex); |
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| 40 | minima.insert(origin_vertex); |
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| 41 | } |
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| 42 | };*/ |
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| 43 | |
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[1172] | 44 | /// A class describing a single polyhedron of the split complex. From a collection of such classes a Hasse diagram |
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| 45 | /// of the structure in the exponent of a Laplace-Inverse-Gamma density will be created. |
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[1171] | 46 | class polyhedron |
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[976] | 47 | { |
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[1172] | 48 | /// A property having a value of 1 usually, with higher value only if the polyhedron arises as a coincidence of |
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| 49 | /// more than just the necessary number of conditions. For example if a newly created line passes through an already |
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| 50 | /// existing point, the points multiplicity will rise by 1. |
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| 51 | int multiplicity; |
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[976] | 52 | |
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[1204] | 53 | int split_state; |
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| 54 | |
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| 55 | int merge_state; |
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| 56 | |
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| 57 | |
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| 58 | |
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[1172] | 59 | public: |
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| 60 | /// A list of polyhedrons parents within the Hasse diagram. |
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[1213] | 61 | list<polyhedron*> parents; |
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[1171] | 62 | |
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[1172] | 63 | /// A list of polyhedrons children withing the Hasse diagram. |
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[1213] | 64 | list<polyhedron*> children; |
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[1171] | 65 | |
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[1172] | 66 | /// All the vertices of the given polyhedron |
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[1220] | 67 | set<vertex*> vertices; |
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[1171] | 68 | |
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[1172] | 69 | /// A list used for storing children that lie in the positive region related to a certain condition |
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[1213] | 70 | list<polyhedron*> positivechildren; |
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[1171] | 71 | |
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[1172] | 72 | /// A list used for storing children that lie in the negative region related to a certain condition |
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[1213] | 73 | list<polyhedron*> negativechildren; |
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[1171] | 74 | |
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[1172] | 75 | /// Children intersecting the condition |
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[1213] | 76 | list<polyhedron*> neutralchildren; |
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[1171] | 77 | |
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[1213] | 78 | list<polyhedron*> totallyneutralgrandchildren; |
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[1211] | 79 | |
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[1213] | 80 | list<polyhedron*> totallyneutralchildren; |
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[1211] | 81 | |
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[1220] | 82 | set<vertex*> positiveneutralvertices; |
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| 83 | |
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| 84 | set<vertex*> negativeneutralvertices; |
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| 85 | |
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[1208] | 86 | bool totally_neutral; |
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| 87 | |
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[1213] | 88 | list<polyhedron*> mergechildren; |
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[1204] | 89 | |
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| 90 | polyhedron* positiveparent; |
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| 91 | |
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| 92 | polyhedron* negativeparent; |
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| 93 | |
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[1214] | 94 | polyhedron* next_poly; |
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| 95 | |
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| 96 | polyhedron* prev_poly; |
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| 97 | |
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[1204] | 98 | int message_counter; |
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| 99 | |
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[1172] | 100 | /// List of triangulation polyhedrons of the polyhedron given by their relative vertices. |
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[1234] | 101 | list<set<vertex*>> triangulation; |
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[1171] | 102 | |
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[1172] | 103 | /// A list of relative addresses serving for Hasse diagram construction. |
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[1213] | 104 | list<int> kids_rel_addresses; |
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[1171] | 105 | |
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[1172] | 106 | /// Default constructor |
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[1171] | 107 | polyhedron() |
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| 108 | { |
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[1204] | 109 | multiplicity = 1; |
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| 110 | |
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| 111 | message_counter = 0; |
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[1208] | 112 | |
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| 113 | totally_neutral = NULL; |
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[1171] | 114 | } |
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| 115 | |
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[1172] | 116 | /// Setter for raising multiplicity |
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[1204] | 117 | void raise_multiplicity() |
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[1171] | 118 | { |
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| 119 | multiplicity++; |
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| 120 | } |
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| 121 | |
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[1172] | 122 | /// Setter for lowering multiplicity |
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[1204] | 123 | void lower_multiplicity() |
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[1171] | 124 | { |
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| 125 | multiplicity--; |
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| 126 | } |
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| 127 | |
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[1172] | 128 | /// An obligatory operator, when the class is used within a C++ STL structure like a vector |
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| 129 | int operator==(polyhedron polyhedron2) |
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| 130 | { |
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| 131 | return true; |
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| 132 | } |
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| 133 | |
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| 134 | /// An obligatory operator, when the class is used within a C++ STL structure like a vector |
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| 135 | int operator<(polyhedron polyhedron2) |
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| 136 | { |
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| 137 | return false; |
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| 138 | } |
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[1204] | 139 | |
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[1208] | 140 | |
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| 141 | |
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[1204] | 142 | void set_state(double state_indicator, actions action) |
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| 143 | { |
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| 144 | switch(action) |
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| 145 | { |
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| 146 | case MERGE: |
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| 147 | merge_state = (int)sign(state_indicator); |
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| 148 | break; |
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| 149 | case SPLIT: |
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| 150 | split_state = (int)sign(state_indicator); |
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| 151 | break; |
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| 152 | } |
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| 153 | } |
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| 154 | |
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| 155 | int get_state(actions action) |
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| 156 | { |
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| 157 | switch(action) |
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| 158 | { |
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| 159 | case MERGE: |
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| 160 | return merge_state; |
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| 161 | break; |
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| 162 | case SPLIT: |
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| 163 | return split_state; |
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| 164 | break; |
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| 165 | } |
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| 166 | } |
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| 167 | |
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| 168 | int number_of_children() |
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| 169 | { |
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[1207] | 170 | return children.size(); |
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[1204] | 171 | } |
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| 172 | |
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[1254] | 173 | void triangulate(bool should_integrate); |
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| 174 | |
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[1234] | 175 | |
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[1207] | 176 | |
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[976] | 177 | }; |
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| 178 | |
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[1186] | 179 | /// A class for representing 0-dimensional polyhedron - a vertex. It will be located in the bottom row of the Hasse |
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| 180 | /// diagram representing a complex of polyhedrons. It has its coordinates in the parameter space. |
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[1172] | 181 | class vertex : public polyhedron |
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[976] | 182 | { |
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[1186] | 183 | /// A dynamic array representing coordinates of the vertex |
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[1204] | 184 | vec coordinates; |
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[976] | 185 | |
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[1208] | 186 | |
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[1204] | 187 | |
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[976] | 188 | public: |
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[1171] | 189 | |
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[1204] | 190 | |
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| 191 | |
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[1186] | 192 | /// Default constructor |
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[1171] | 193 | vertex(); |
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| 194 | |
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[1186] | 195 | /// Constructor of a vertex from a set of coordinates |
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[1204] | 196 | vertex(vec coordinates) |
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[1171] | 197 | { |
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[1172] | 198 | this->coordinates = coordinates; |
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[1234] | 199 | |
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| 200 | vertices.insert(this); |
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| 201 | |
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| 202 | set<vertex*> vert_simplex; |
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| 203 | |
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| 204 | vert_simplex.insert(this); |
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| 205 | |
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| 206 | triangulation.push_back(vert_simplex); |
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[1171] | 207 | } |
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| 208 | |
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[1186] | 209 | /// A method that widens the set of coordinates of given vertex. It is used when a complex in a parameter |
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| 210 | /// space of certain dimension is established, but the dimension is not known when the vertex is created. |
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[1171] | 211 | void push_coordinate(double coordinate) |
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| 212 | { |
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[1204] | 213 | coordinates = concat(coordinates,coordinate); |
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[1171] | 214 | } |
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| 215 | |
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[1186] | 216 | /// A method obtaining the set of coordinates of a vertex. These coordinates are not obtained as a pointer |
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| 217 | /// (not given by reference), but a new copy is created (they are given by value). |
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[1204] | 218 | vec get_coordinates() |
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| 219 | { |
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| 220 | return coordinates; |
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| 221 | } |
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[1172] | 222 | |
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[1204] | 223 | |
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[1172] | 224 | }; |
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[976] | 225 | |
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[1186] | 226 | /// A class representing a polyhedron in a top row of the complex. Such polyhedron has a condition that differitiates |
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| 227 | /// it from polyhedrons in other rows. |
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[1172] | 228 | class toprow : public polyhedron |
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[1171] | 229 | { |
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[1204] | 230 | |
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| 231 | public: |
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[1242] | 232 | double probability; |
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| 233 | |
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[1186] | 234 | /// A condition used for determining the function of a Laplace-Inverse-Gamma density resulting from Bayesian estimation |
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[1204] | 235 | vec condition; |
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[976] | 236 | |
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[1242] | 237 | int condition_order; |
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| 238 | |
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[1186] | 239 | /// Default constructor |
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[1213] | 240 | toprow(){}; |
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[976] | 241 | |
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[1186] | 242 | /// Constructor creating a toprow from the condition |
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[1242] | 243 | toprow(vec condition, int condition_order) |
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[1171] | 244 | { |
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[1242] | 245 | this->condition = condition; |
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| 246 | this->condition_order = condition_order; |
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| 247 | } |
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[1171] | 248 | |
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[1172] | 249 | }; |
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[1171] | 250 | |
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[1204] | 251 | class condition |
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| 252 | { |
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| 253 | public: |
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| 254 | vec value; |
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[1171] | 255 | |
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[1204] | 256 | int multiplicity; |
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[1171] | 257 | |
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[1204] | 258 | condition(vec value) |
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| 259 | { |
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| 260 | this->value = value; |
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| 261 | multiplicity = 1; |
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| 262 | } |
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[1208] | 263 | }; |
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[1171] | 264 | |
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[1214] | 265 | class c_statistic |
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| 266 | { |
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| 267 | polyhedron* end_poly; |
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| 268 | polyhedron* start_poly; |
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[1204] | 269 | |
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[1214] | 270 | public: |
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| 271 | vector<polyhedron*> rows; |
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| 272 | |
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| 273 | vector<polyhedron*> row_ends; |
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| 274 | |
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| 275 | c_statistic() |
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| 276 | { |
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| 277 | end_poly = new polyhedron(); |
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| 278 | start_poly = new polyhedron(); |
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| 279 | }; |
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| 280 | |
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| 281 | void append_polyhedron(int row, polyhedron* appended_start, polyhedron* appended_end) |
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| 282 | { |
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| 283 | if(row>((int)rows.size())-1) |
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| 284 | { |
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| 285 | if(row>rows.size()) |
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| 286 | { |
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| 287 | throw new exception("You are trying to append a polyhedron whose children are not in the statistic yet!"); |
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| 288 | return; |
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| 289 | } |
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| 290 | |
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| 291 | rows.push_back(end_poly); |
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| 292 | row_ends.push_back(end_poly); |
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| 293 | } |
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| 294 | |
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| 295 | // POSSIBLE FAILURE: the function is not checking if start and end are connected |
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| 296 | |
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| 297 | if(rows[row] != end_poly) |
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| 298 | { |
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| 299 | appended_start->prev_poly = row_ends[row]; |
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| 300 | row_ends[row]->next_poly = appended_start; |
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| 301 | |
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| 302 | } |
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| 303 | else if((row>0 && rows[row-1]!=end_poly)||row==0) |
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| 304 | { |
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| 305 | appended_start->prev_poly = start_poly; |
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| 306 | rows[row]= appended_start; |
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| 307 | } |
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| 308 | else |
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| 309 | { |
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| 310 | throw new exception("Wrong polyhedron insertion into statistic: missing intermediary polyhedron!"); |
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| 311 | } |
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| 312 | |
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| 313 | appended_end->next_poly = end_poly; |
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| 314 | row_ends[row] = appended_end; |
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| 315 | } |
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| 316 | |
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| 317 | void append_polyhedron(int row, polyhedron* appended_poly) |
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| 318 | { |
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| 319 | append_polyhedron(row,appended_poly,appended_poly); |
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| 320 | } |
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| 321 | |
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| 322 | void insert_polyhedron(int row, polyhedron* inserted_poly, polyhedron* following_poly) |
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| 323 | { |
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| 324 | if(following_poly != end_poly) |
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| 325 | { |
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| 326 | inserted_poly->next_poly = following_poly; |
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| 327 | inserted_poly->prev_poly = following_poly->prev_poly; |
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| 328 | |
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| 329 | if(following_poly->prev_poly == start_poly) |
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| 330 | { |
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| 331 | rows[row] = inserted_poly; |
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| 332 | } |
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| 333 | else |
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| 334 | { |
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| 335 | inserted_poly->prev_poly->next_poly = inserted_poly; |
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| 336 | } |
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| 337 | |
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| 338 | following_poly->prev_poly = inserted_poly; |
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| 339 | } |
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| 340 | else |
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| 341 | { |
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| 342 | this->append_polyhedron(row, inserted_poly); |
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| 343 | } |
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| 344 | |
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| 345 | } |
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| 346 | |
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| 347 | |
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| 348 | |
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| 349 | |
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| 350 | void delete_polyhedron(int row, polyhedron* deleted_poly) |
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| 351 | { |
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| 352 | if(deleted_poly->prev_poly != start_poly) |
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| 353 | { |
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| 354 | deleted_poly->prev_poly->next_poly = deleted_poly->next_poly; |
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| 355 | } |
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| 356 | else |
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| 357 | { |
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| 358 | rows[row] = deleted_poly->next_poly; |
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| 359 | } |
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| 360 | |
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| 361 | if(deleted_poly->next_poly!=end_poly) |
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| 362 | { |
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| 363 | deleted_poly->next_poly->prev_poly = deleted_poly->prev_poly; |
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| 364 | } |
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| 365 | else |
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| 366 | { |
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| 367 | row_ends[row] = deleted_poly->prev_poly; |
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| 368 | } |
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| 369 | |
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| 370 | |
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| 371 | |
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| 372 | deleted_poly->next_poly = NULL; |
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| 373 | deleted_poly->prev_poly = NULL; |
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| 374 | } |
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| 375 | |
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| 376 | int size() |
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| 377 | { |
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| 378 | return rows.size(); |
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| 379 | } |
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| 380 | |
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| 381 | polyhedron* get_end() |
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| 382 | { |
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| 383 | return end_poly; |
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| 384 | } |
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| 385 | |
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| 386 | polyhedron* get_start() |
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| 387 | { |
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| 388 | return start_poly; |
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| 389 | } |
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| 390 | |
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| 391 | int row_size(int row) |
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| 392 | { |
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| 393 | if(this->size()>row && row>=0) |
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| 394 | { |
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| 395 | int row_size = 0; |
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| 396 | |
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| 397 | for(polyhedron* row_poly = rows[row]; row_poly!=end_poly; row_poly=row_poly->next_poly) |
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| 398 | { |
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| 399 | row_size++; |
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| 400 | } |
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| 401 | |
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| 402 | return row_size; |
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| 403 | } |
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| 404 | else |
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| 405 | { |
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| 406 | throw new exception("There is no row to obtain size from!"); |
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| 407 | } |
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| 408 | } |
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| 409 | }; |
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| 410 | |
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| 411 | |
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[976] | 412 | //! Conditional(e) Multicriteria-Laplace-Inverse-Gamma distribution density |
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[1186] | 413 | class emlig // : eEF |
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[1172] | 414 | { |
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[976] | 415 | |
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[1186] | 416 | /// A statistic in a form of a Hasse diagram representing a complex of convex polyhedrons obtained as a result |
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| 417 | /// of data update from Bayesian estimation or set by the user if this emlig is a prior density |
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[1214] | 418 | c_statistic statistic; |
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[1204] | 419 | |
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[1213] | 420 | vector<list<polyhedron*>> for_splitting; |
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[1207] | 421 | |
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[1213] | 422 | vector<list<polyhedron*>> for_merging; |
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[1207] | 423 | |
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[1213] | 424 | list<condition*> conditions; |
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[1204] | 425 | |
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| 426 | double normalization_factor; |
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| 427 | |
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| 428 | void alter_toprow_conditions(vec condition, bool should_be_added) |
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| 429 | { |
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[1214] | 430 | for(polyhedron* horiz_ref = statistic.rows[statistic.size()-1];horiz_ref!=statistic.get_end();horiz_ref=horiz_ref->next_poly) |
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[1204] | 431 | { |
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| 432 | double product = 0; |
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| 433 | |
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[1220] | 434 | set<vertex*>::iterator vertex_ref = horiz_ref->vertices.begin(); |
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[1204] | 435 | |
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| 436 | do |
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| 437 | { |
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[1208] | 438 | product = (*vertex_ref)->get_coordinates()*condition; |
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[1204] | 439 | } |
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[1208] | 440 | while(product == 0); |
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[1204] | 441 | |
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| 442 | if((product>0 && should_be_added)||(product<0 && !should_be_added)) |
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| 443 | { |
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[1214] | 444 | ((toprow*) horiz_ref)->condition += condition; |
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[1204] | 445 | } |
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| 446 | else |
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| 447 | { |
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[1214] | 448 | ((toprow*) horiz_ref)->condition -= condition; |
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| 449 | } |
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[1204] | 450 | } |
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| 451 | } |
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[1207] | 452 | |
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| 453 | |
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[1216] | 454 | |
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[1212] | 455 | void send_state_message(polyhedron* sender, vec toadd, vec toremove, int level) |
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[1211] | 456 | { |
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| 457 | |
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[1213] | 458 | bool shouldmerge = (toremove.size() != 0); |
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| 459 | bool shouldsplit = (toadd.size() != 0); |
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[1212] | 460 | |
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[1207] | 461 | if(shouldsplit||shouldmerge) |
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| 462 | { |
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[1213] | 463 | for(list<polyhedron*>::iterator parent_iterator = sender->parents.begin();parent_iterator!=sender->parents.end();parent_iterator++) |
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[1207] | 464 | { |
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| 465 | polyhedron* current_parent = *parent_iterator; |
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| 466 | |
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| 467 | current_parent->message_counter++; |
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| 468 | |
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| 469 | bool is_last = (current_parent->message_counter == current_parent->number_of_children()); |
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| 470 | |
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| 471 | if(shouldmerge) |
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| 472 | { |
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| 473 | int child_state = sender->get_state(MERGE); |
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| 474 | int parent_state = current_parent->get_state(MERGE); |
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| 475 | |
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| 476 | if(parent_state == 0) |
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| 477 | { |
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| 478 | current_parent->set_state(child_state, MERGE); |
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| 479 | |
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| 480 | if(child_state == 0) |
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| 481 | { |
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| 482 | current_parent->mergechildren.push_back(sender); |
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| 483 | } |
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| 484 | } |
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| 485 | else |
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| 486 | { |
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| 487 | if(child_state == 0) |
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| 488 | { |
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| 489 | if(parent_state > 0) |
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| 490 | { |
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| 491 | sender->positiveparent = current_parent; |
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| 492 | } |
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| 493 | else |
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| 494 | { |
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| 495 | sender->negativeparent = current_parent; |
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| 496 | } |
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| 497 | } |
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| 498 | } |
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| 499 | |
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| 500 | if(is_last) |
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| 501 | { |
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| 502 | if(parent_state > 0) |
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| 503 | { |
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[1213] | 504 | for(list<polyhedron*>::iterator merge_child = current_parent->mergechildren.begin(); merge_child != current_parent->mergechildren.end();merge_child++) |
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[1207] | 505 | { |
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| 506 | (*merge_child)->positiveparent = current_parent; |
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| 507 | } |
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| 508 | } |
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| 509 | |
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| 510 | if(parent_state < 0) |
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| 511 | { |
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[1213] | 512 | for(list<polyhedron*>::iterator merge_child = current_parent->mergechildren.begin(); merge_child != current_parent->mergechildren.end();merge_child++) |
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[1207] | 513 | { |
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| 514 | (*merge_child)->negativeparent = current_parent; |
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| 515 | } |
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| 516 | } |
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| 517 | |
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| 518 | if(parent_state == 0) |
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| 519 | { |
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| 520 | for_merging[level+1].push_back(current_parent); |
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| 521 | } |
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| 522 | |
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| 523 | current_parent->mergechildren.clear(); |
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| 524 | } |
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| 525 | |
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[1208] | 526 | |
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| 527 | } |
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| 528 | |
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| 529 | if(shouldsplit) |
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[1207] | 530 | { |
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[1211] | 531 | current_parent->totallyneutralgrandchildren.insert(current_parent->totallyneutralgrandchildren.end(),sender->totallyneutralchildren.begin(),sender->totallyneutralchildren.end()); |
---|
| 532 | |
---|
[1207] | 533 | switch(sender->get_state(SPLIT)) |
---|
| 534 | { |
---|
| 535 | case 1: |
---|
[1220] | 536 | current_parent->positivechildren.push_back(sender); |
---|
| 537 | current_parent->positiveneutralvertices.insert(sender->vertices.begin(),sender->vertices.end()); |
---|
[1207] | 538 | break; |
---|
| 539 | case 0: |
---|
[1220] | 540 | current_parent->neutralchildren.push_back(sender); |
---|
| 541 | current_parent->positiveneutralvertices.insert(sender->positiveneutralvertices.begin(),sender->positiveneutralvertices.end()); |
---|
| 542 | current_parent->negativeneutralvertices.insert(sender->negativeneutralvertices.begin(),sender->negativeneutralvertices.end()); |
---|
[1208] | 543 | |
---|
| 544 | if(current_parent->totally_neutral == NULL) |
---|
| 545 | { |
---|
| 546 | current_parent->totally_neutral = sender->totally_neutral; |
---|
| 547 | } |
---|
| 548 | else |
---|
| 549 | { |
---|
| 550 | current_parent->totally_neutral = current_parent->totally_neutral && sender->totally_neutral; |
---|
| 551 | } |
---|
[1211] | 552 | |
---|
| 553 | if(sender->totally_neutral) |
---|
| 554 | { |
---|
| 555 | current_parent->totallyneutralchildren.push_back(sender); |
---|
| 556 | } |
---|
[1208] | 557 | |
---|
[1207] | 558 | break; |
---|
| 559 | case -1: |
---|
[1220] | 560 | current_parent->negativechildren.push_back(sender); |
---|
| 561 | current_parent->negativeneutralvertices.insert(sender->vertices.begin(),sender->vertices.end()); |
---|
[1207] | 562 | break; |
---|
| 563 | } |
---|
| 564 | |
---|
| 565 | if(is_last) |
---|
| 566 | { |
---|
[1211] | 567 | unique(current_parent->totallyneutralgrandchildren.begin(),current_parent->totallyneutralgrandchildren.end()); |
---|
| 568 | |
---|
[1208] | 569 | if((current_parent->negativechildren.size()>0&¤t_parent->positivechildren.size()>0)|| |
---|
| 570 | (current_parent->neutralchildren.size()>0&¤t_parent->totally_neutral==false)) |
---|
[1207] | 571 | { |
---|
[1208] | 572 | |
---|
[1207] | 573 | for_splitting[level+1].push_back(current_parent); |
---|
| 574 | |
---|
| 575 | current_parent->set_state(0, SPLIT); |
---|
[1208] | 576 | } |
---|
[1211] | 577 | else |
---|
[1208] | 578 | { |
---|
[1242] | 579 | ((toprow*)current_parent)->condition_order++; |
---|
| 580 | |
---|
[1211] | 581 | if(current_parent->negativechildren.size()>0) |
---|
| 582 | { |
---|
| 583 | current_parent->set_state(-1, SPLIT); |
---|
[1212] | 584 | |
---|
[1242] | 585 | ((toprow*)current_parent)->condition-=toadd; |
---|
| 586 | |
---|
[1211] | 587 | } |
---|
| 588 | else if(current_parent->positivechildren.size()>0) |
---|
| 589 | { |
---|
[1212] | 590 | current_parent->set_state(1, SPLIT); |
---|
| 591 | |
---|
[1242] | 592 | ((toprow*)current_parent)->condition+=toadd; |
---|
[1211] | 593 | } |
---|
| 594 | else |
---|
| 595 | { |
---|
| 596 | current_parent->raise_multiplicity(); |
---|
| 597 | } |
---|
[1207] | 598 | |
---|
| 599 | current_parent->positivechildren.clear(); |
---|
[1211] | 600 | current_parent->negativechildren.clear(); |
---|
[1207] | 601 | current_parent->neutralchildren.clear(); |
---|
[1211] | 602 | current_parent->totallyneutralchildren.clear(); |
---|
| 603 | current_parent->totallyneutralgrandchildren.clear(); |
---|
[1220] | 604 | current_parent->positiveneutralvertices.clear(); |
---|
| 605 | current_parent->negativeneutralvertices.clear(); |
---|
[1216] | 606 | current_parent->totally_neutral = NULL; |
---|
| 607 | current_parent->kids_rel_addresses.clear(); |
---|
[1219] | 608 | current_parent->message_counter = 0; |
---|
[1207] | 609 | } |
---|
| 610 | } |
---|
| 611 | } |
---|
| 612 | |
---|
| 613 | if(is_last) |
---|
| 614 | { |
---|
[1213] | 615 | send_state_message(current_parent,toadd,toremove,level+1); |
---|
[1207] | 616 | } |
---|
| 617 | |
---|
| 618 | } |
---|
| 619 | |
---|
| 620 | } |
---|
| 621 | } |
---|
[1171] | 622 | |
---|
| 623 | public: |
---|
[976] | 624 | |
---|
[1216] | 625 | int number_of_parameters; |
---|
| 626 | |
---|
[1186] | 627 | /// A default constructor creates an emlig with predefined statistic representing only the range of the given |
---|
| 628 | /// parametric space, where the number of parameters of the needed model is given as a parameter to the constructor. |
---|
[1171] | 629 | emlig(int number_of_parameters) |
---|
[1214] | 630 | { |
---|
[1216] | 631 | this->number_of_parameters = number_of_parameters; |
---|
[1214] | 632 | |
---|
[1216] | 633 | create_statistic(number_of_parameters); |
---|
[1171] | 634 | } |
---|
| 635 | |
---|
[1186] | 636 | /// A constructor for creating an emlig when the user wants to create the statistic by himself. The creation of a |
---|
| 637 | /// statistic is needed outside the constructor. Used for a user defined prior distribution on the parameters. |
---|
[1214] | 638 | emlig(c_statistic statistic) |
---|
[1171] | 639 | { |
---|
[1172] | 640 | this->statistic = statistic; |
---|
[1171] | 641 | } |
---|
| 642 | |
---|
[1219] | 643 | void step_me(int marker) |
---|
[1216] | 644 | { |
---|
| 645 | for(int i = 0;i<statistic.size();i++) |
---|
| 646 | { |
---|
| 647 | for(polyhedron* horiz_ref = statistic.rows[i];horiz_ref!=statistic.get_end();horiz_ref=horiz_ref->next_poly) |
---|
| 648 | { |
---|
| 649 | char* string = "Checkpoint"; |
---|
| 650 | } |
---|
| 651 | } |
---|
| 652 | } |
---|
| 653 | |
---|
| 654 | int statistic_rowsize(int row) |
---|
| 655 | { |
---|
| 656 | return statistic.row_size(row); |
---|
| 657 | } |
---|
| 658 | |
---|
[1208] | 659 | void add_condition(vec toadd) |
---|
[1204] | 660 | { |
---|
[1208] | 661 | vec null_vector = ""; |
---|
| 662 | |
---|
| 663 | add_and_remove_condition(toadd, null_vector); |
---|
| 664 | } |
---|
| 665 | |
---|
[1216] | 666 | |
---|
[1208] | 667 | void remove_condition(vec toremove) |
---|
[1242] | 668 | { |
---|
[1208] | 669 | vec null_vector = ""; |
---|
| 670 | |
---|
| 671 | add_and_remove_condition(null_vector, toremove); |
---|
| 672 | |
---|
| 673 | } |
---|
| 674 | |
---|
[1216] | 675 | |
---|
[1208] | 676 | void add_and_remove_condition(vec toadd, vec toremove) |
---|
| 677 | { |
---|
| 678 | bool should_remove = (toremove.size() != 0); |
---|
| 679 | bool should_add = (toadd.size() != 0); |
---|
| 680 | |
---|
[1216] | 681 | for_splitting.clear(); |
---|
| 682 | for_merging.clear(); |
---|
| 683 | |
---|
| 684 | for(int i = 0;i<statistic.size();i++) |
---|
| 685 | { |
---|
| 686 | list<polyhedron*> empty_split; |
---|
| 687 | list<polyhedron*> empty_merge; |
---|
| 688 | |
---|
| 689 | for_splitting.push_back(empty_split); |
---|
| 690 | for_merging.push_back(empty_merge); |
---|
| 691 | } |
---|
| 692 | |
---|
[1213] | 693 | list<condition*>::iterator toremove_ref = conditions.end(); |
---|
[1204] | 694 | bool condition_should_be_added = false; |
---|
| 695 | |
---|
[1213] | 696 | for(list<condition*>::iterator ref = conditions.begin();ref!=conditions.end();ref++) |
---|
[1204] | 697 | { |
---|
[1208] | 698 | if(should_remove) |
---|
[1204] | 699 | { |
---|
| 700 | if((*ref)->value == toremove) |
---|
| 701 | { |
---|
[1208] | 702 | if((*ref)->multiplicity>1) |
---|
[1204] | 703 | { |
---|
[1208] | 704 | (*ref)->multiplicity--; |
---|
[1204] | 705 | |
---|
| 706 | alter_toprow_conditions(toremove,false); |
---|
| 707 | |
---|
[1208] | 708 | should_remove = false; |
---|
[1204] | 709 | } |
---|
| 710 | else |
---|
| 711 | { |
---|
| 712 | toremove_ref = ref; |
---|
| 713 | } |
---|
| 714 | } |
---|
| 715 | } |
---|
| 716 | |
---|
[1208] | 717 | if(should_add) |
---|
[1204] | 718 | { |
---|
[1208] | 719 | if((*ref)->value == toadd) |
---|
[1204] | 720 | { |
---|
[1208] | 721 | (*ref)->multiplicity++; |
---|
[1204] | 722 | |
---|
| 723 | alter_toprow_conditions(toadd,true); |
---|
| 724 | |
---|
[1208] | 725 | should_add = false; |
---|
[1204] | 726 | } |
---|
| 727 | else |
---|
| 728 | { |
---|
| 729 | condition_should_be_added = true; |
---|
| 730 | } |
---|
| 731 | } |
---|
| 732 | } |
---|
| 733 | |
---|
| 734 | if(toremove_ref!=conditions.end()) |
---|
| 735 | { |
---|
| 736 | conditions.erase(toremove_ref); |
---|
| 737 | } |
---|
| 738 | |
---|
| 739 | if(condition_should_be_added) |
---|
| 740 | { |
---|
| 741 | conditions.push_back(new condition(toadd)); |
---|
| 742 | } |
---|
| 743 | |
---|
[1207] | 744 | |
---|
[1214] | 745 | |
---|
| 746 | for(polyhedron* horizontal_position = statistic.rows[0];horizontal_position!=statistic.get_end();horizontal_position=horizontal_position->next_poly) |
---|
[1204] | 747 | { |
---|
[1214] | 748 | vertex* current_vertex = (vertex*)horizontal_position; |
---|
[1204] | 749 | |
---|
[1208] | 750 | if(should_add||should_remove) |
---|
[1204] | 751 | { |
---|
[1208] | 752 | vec appended_vec = current_vertex->get_coordinates(); |
---|
[1212] | 753 | appended_vec.ins(0,-1.0); |
---|
[1208] | 754 | |
---|
| 755 | if(should_add) |
---|
| 756 | { |
---|
[1211] | 757 | double local_condition = toadd*appended_vec; |
---|
| 758 | |
---|
| 759 | current_vertex->set_state(local_condition,SPLIT); |
---|
| 760 | |
---|
| 761 | if(local_condition == 0) |
---|
| 762 | { |
---|
| 763 | current_vertex->totally_neutral = true; |
---|
| 764 | |
---|
[1213] | 765 | current_vertex->raise_multiplicity(); |
---|
[1220] | 766 | |
---|
| 767 | current_vertex->negativeneutralvertices.insert(current_vertex); |
---|
| 768 | current_vertex->positiveneutralvertices.insert(current_vertex); |
---|
[1211] | 769 | } |
---|
[1208] | 770 | } |
---|
[1204] | 771 | |
---|
[1208] | 772 | if(should_remove) |
---|
| 773 | { |
---|
[1211] | 774 | double local_condition = toremove*appended_vec; |
---|
[1207] | 775 | |
---|
[1211] | 776 | current_vertex->set_state(local_condition,MERGE); |
---|
| 777 | |
---|
| 778 | if(local_condition == 0) |
---|
| 779 | { |
---|
| 780 | for_merging[0].push_back(current_vertex); |
---|
| 781 | } |
---|
| 782 | } |
---|
[1204] | 783 | } |
---|
| 784 | |
---|
[1214] | 785 | send_state_message(current_vertex, toadd, toremove, 0); |
---|
| 786 | |
---|
[1208] | 787 | } |
---|
[1207] | 788 | |
---|
[1212] | 789 | if(should_add) |
---|
[1208] | 790 | { |
---|
[1214] | 791 | int k = 1; |
---|
| 792 | |
---|
| 793 | vector<list<polyhedron*>>::iterator beginning_ref = ++for_splitting.begin(); |
---|
| 794 | |
---|
| 795 | for(vector<list<polyhedron*>>::iterator vert_ref = beginning_ref;vert_ref<for_splitting.end();vert_ref++) |
---|
[1213] | 796 | { |
---|
[1208] | 797 | |
---|
[1213] | 798 | for(list<polyhedron*>::reverse_iterator split_ref = vert_ref->rbegin();split_ref != vert_ref->rend();split_ref++) |
---|
[1212] | 799 | { |
---|
[1213] | 800 | polyhedron* new_totally_neutral_child; |
---|
[1212] | 801 | |
---|
[1213] | 802 | polyhedron* current_polyhedron = (*split_ref); |
---|
[1212] | 803 | |
---|
[1214] | 804 | if(vert_ref == beginning_ref) |
---|
[1212] | 805 | { |
---|
[1213] | 806 | vec coordinates1 = ((vertex*)(*(current_polyhedron->children.begin())))->get_coordinates(); |
---|
| 807 | vec coordinates2 = ((vertex*)(*(current_polyhedron->children.begin()++)))->get_coordinates(); |
---|
[1212] | 808 | coordinates2.ins(0,-1.0); |
---|
| 809 | |
---|
| 810 | double t = (-toadd*coordinates2)/(toadd(1,toadd.size()-1)*coordinates1)+1; |
---|
| 811 | |
---|
| 812 | vec new_coordinates = coordinates1*t+(coordinates2(1,coordinates2.size()-1)-coordinates1); |
---|
| 813 | |
---|
| 814 | vertex* neutral_vertex = new vertex(new_coordinates); |
---|
| 815 | |
---|
| 816 | new_totally_neutral_child = neutral_vertex; |
---|
| 817 | } |
---|
| 818 | else |
---|
| 819 | { |
---|
| 820 | toprow* neutral_toprow = new toprow(); |
---|
| 821 | |
---|
| 822 | new_totally_neutral_child = neutral_toprow; |
---|
| 823 | } |
---|
| 824 | |
---|
| 825 | new_totally_neutral_child->children.insert(new_totally_neutral_child->children.end(), |
---|
| 826 | current_polyhedron->totallyneutralgrandchildren.begin(), |
---|
| 827 | current_polyhedron->totallyneutralgrandchildren.end()); |
---|
| 828 | |
---|
[1219] | 829 | for(list<polyhedron*>::iterator grand_ref = current_polyhedron->totallyneutralgrandchildren.begin(); grand_ref != current_polyhedron->totallyneutralgrandchildren.end();grand_ref++) |
---|
| 830 | { |
---|
| 831 | (*grand_ref)->parents.push_back(new_totally_neutral_child); |
---|
[1220] | 832 | |
---|
| 833 | new_totally_neutral_child->vertices.insert((*grand_ref)->vertices.begin(),(*grand_ref)->vertices.end()); |
---|
[1219] | 834 | } |
---|
| 835 | |
---|
[1242] | 836 | toprow* positive_poly = new toprow(((toprow*)current_polyhedron)->condition+toadd, ((toprow*)current_polyhedron)->condition_order+1); |
---|
| 837 | toprow* negative_poly = new toprow(((toprow*)current_polyhedron)->condition-toadd, ((toprow*)current_polyhedron)->condition_order+1); |
---|
[1212] | 838 | |
---|
[1216] | 839 | for(list<polyhedron*>::iterator parent_ref = current_polyhedron->parents.begin();parent_ref!=current_polyhedron->parents.end();parent_ref++) |
---|
| 840 | { |
---|
| 841 | (*parent_ref)->totallyneutralgrandchildren.push_back(new_totally_neutral_child); |
---|
[1212] | 842 | |
---|
[1216] | 843 | (*parent_ref)->neutralchildren.remove(current_polyhedron); |
---|
[1219] | 844 | (*parent_ref)->children.remove(current_polyhedron); |
---|
| 845 | |
---|
| 846 | (*parent_ref)->children.push_back(positive_poly); |
---|
| 847 | (*parent_ref)->children.push_back(negative_poly); |
---|
[1216] | 848 | (*parent_ref)->positivechildren.push_back(positive_poly); |
---|
| 849 | (*parent_ref)->negativechildren.push_back(negative_poly); |
---|
| 850 | } |
---|
| 851 | |
---|
[1212] | 852 | positive_poly->parents.insert(positive_poly->parents.end(), |
---|
| 853 | current_polyhedron->parents.begin(), |
---|
| 854 | current_polyhedron->parents.end()); |
---|
| 855 | |
---|
| 856 | negative_poly->parents.insert(negative_poly->parents.end(), |
---|
| 857 | current_polyhedron->parents.begin(), |
---|
| 858 | current_polyhedron->parents.end()); |
---|
| 859 | |
---|
[1216] | 860 | positive_poly->children.push_back(new_totally_neutral_child); |
---|
| 861 | negative_poly->children.push_back(new_totally_neutral_child); |
---|
| 862 | |
---|
| 863 | new_totally_neutral_child->parents.push_back(positive_poly); |
---|
| 864 | new_totally_neutral_child->parents.push_back(negative_poly); |
---|
| 865 | |
---|
| 866 | for(list<polyhedron*>::iterator child_ref = current_polyhedron->positivechildren.begin();child_ref!=current_polyhedron->positivechildren.end();child_ref++) |
---|
| 867 | { |
---|
| 868 | (*child_ref)->parents.remove(current_polyhedron); |
---|
[1220] | 869 | (*child_ref)->parents.push_back(positive_poly); |
---|
[1216] | 870 | } |
---|
| 871 | |
---|
[1212] | 872 | positive_poly->children.insert(positive_poly->children.end(), |
---|
| 873 | current_polyhedron->positivechildren.begin(), |
---|
| 874 | current_polyhedron->positivechildren.end()); |
---|
| 875 | |
---|
[1216] | 876 | for(list<polyhedron*>::iterator child_ref = current_polyhedron->negativechildren.begin();child_ref!=current_polyhedron->negativechildren.end();child_ref++) |
---|
| 877 | { |
---|
| 878 | (*child_ref)->parents.remove(current_polyhedron); |
---|
| 879 | (*child_ref)->parents.push_back(negative_poly); |
---|
| 880 | } |
---|
| 881 | |
---|
[1212] | 882 | negative_poly->children.insert(negative_poly->children.end(), |
---|
| 883 | current_polyhedron->negativechildren.begin(), |
---|
| 884 | current_polyhedron->negativechildren.end()); |
---|
| 885 | |
---|
[1220] | 886 | positive_poly->vertices.insert(current_polyhedron->positiveneutralvertices.begin(),current_polyhedron->positiveneutralvertices.end()); |
---|
| 887 | positive_poly->vertices.insert(new_totally_neutral_child->vertices.begin(),new_totally_neutral_child->vertices.end()); |
---|
| 888 | |
---|
| 889 | negative_poly->vertices.insert(current_polyhedron->negativeneutralvertices.begin(),current_polyhedron->negativeneutralvertices.end()); |
---|
| 890 | negative_poly->vertices.insert(new_totally_neutral_child->vertices.begin(),new_totally_neutral_child->vertices.end()); |
---|
| 891 | |
---|
[1242] | 892 | new_totally_neutral_child->triangulate(false); |
---|
[1234] | 893 | |
---|
[1242] | 894 | positive_poly->triangulate(k==for_splitting.size()-1); |
---|
| 895 | negative_poly->triangulate(k==for_splitting.size()-1); |
---|
[1234] | 896 | |
---|
[1214] | 897 | statistic.append_polyhedron(k-1, new_totally_neutral_child); |
---|
[1212] | 898 | |
---|
[1214] | 899 | statistic.insert_polyhedron(k, positive_poly, current_polyhedron); |
---|
| 900 | statistic.insert_polyhedron(k, negative_poly, current_polyhedron); |
---|
[1212] | 901 | |
---|
[1216] | 902 | statistic.delete_polyhedron(k, current_polyhedron); |
---|
| 903 | |
---|
| 904 | delete current_polyhedron; |
---|
[1214] | 905 | } |
---|
[1212] | 906 | |
---|
[1214] | 907 | k++; |
---|
[1208] | 908 | } |
---|
[1204] | 909 | } |
---|
[1208] | 910 | |
---|
[1216] | 911 | /* |
---|
[1214] | 912 | vector<int> sizevector; |
---|
| 913 | for(int s = 0;s<statistic.size();s++) |
---|
| 914 | { |
---|
| 915 | sizevector.push_back(statistic.row_size(s)); |
---|
[1216] | 916 | }*/ |
---|
[1204] | 917 | } |
---|
| 918 | |
---|
[1171] | 919 | protected: |
---|
| 920 | |
---|
[1186] | 921 | /// A method for creating plain default statistic representing only the range of the parameter space. |
---|
[1172] | 922 | void create_statistic(int number_of_parameters) |
---|
[1171] | 923 | { |
---|
[1224] | 924 | for(int i = 0;i<number_of_parameters;i++) |
---|
| 925 | { |
---|
| 926 | vec condition_vec = zeros(number_of_parameters+1); |
---|
| 927 | condition_vec[i+1] = 1; |
---|
| 928 | |
---|
| 929 | condition* new_condition = new condition(condition_vec); |
---|
| 930 | |
---|
| 931 | conditions.push_back(new_condition); |
---|
| 932 | } |
---|
| 933 | |
---|
[1186] | 934 | // An empty vector of coordinates. |
---|
[1204] | 935 | vec origin_coord; |
---|
[1171] | 936 | |
---|
[1186] | 937 | // We create an origin - this point will have all the coordinates zero, but now it has an empty vector of coords. |
---|
[1172] | 938 | vertex *origin = new vertex(origin_coord); |
---|
[1234] | 939 | |
---|
[1214] | 940 | /* |
---|
[1186] | 941 | // As a statistic, we have to create a vector of vectors of polyhedron pointers. It will then represent the Hasse |
---|
| 942 | // diagram. First we create a vector of polyhedrons.. |
---|
[1213] | 943 | list<polyhedron*> origin_vec; |
---|
[1171] | 944 | |
---|
[1186] | 945 | // ..we fill it with the origin.. |
---|
[1172] | 946 | origin_vec.push_back(origin); |
---|
| 947 | |
---|
[1186] | 948 | // ..and we fill the statistic with the created vector. |
---|
[1171] | 949 | statistic.push_back(origin_vec); |
---|
[1214] | 950 | */ |
---|
[1171] | 951 | |
---|
[1214] | 952 | statistic = *(new c_statistic()); |
---|
| 953 | |
---|
| 954 | statistic.append_polyhedron(0, origin); |
---|
| 955 | |
---|
[1186] | 956 | // Now we have a statistic for a zero dimensional space. Regarding to how many dimensional space we need to |
---|
| 957 | // describe, we have to widen the descriptional default statistic. We use an iterative procedure as follows: |
---|
[1172] | 958 | for(int i=0;i<number_of_parameters;i++) |
---|
[1171] | 959 | { |
---|
[1186] | 960 | // We first will create two new vertices. These will be the borders of the parameter space in the dimension |
---|
| 961 | // of newly added parameter. Therefore they will have all coordinates except the last one zero. We get the |
---|
| 962 | // right amount of zero cooridnates by reading them from the origin |
---|
[1204] | 963 | vec origin_coord = origin->get_coordinates(); |
---|
[1171] | 964 | |
---|
[1186] | 965 | // And we incorporate the nonzero coordinates into the new cooordinate vectors |
---|
[1216] | 966 | vec origin_coord1 = concat(origin_coord,-max_range); |
---|
| 967 | vec origin_coord2 = concat(origin_coord,max_range); |
---|
| 968 | |
---|
[1172] | 969 | |
---|
[1186] | 970 | // Now we create the points |
---|
[1234] | 971 | vertex* new_point1 = new vertex(origin_coord1); |
---|
| 972 | vertex* new_point2 = new vertex(origin_coord2); |
---|
[1186] | 973 | |
---|
| 974 | //********************************************************************************************************* |
---|
| 975 | // The algorithm for recursive build of a new Hasse diagram representing the space structure from the old |
---|
| 976 | // diagram works so that you create two copies of the old Hasse diagram, you shift them up one level (points |
---|
| 977 | // will be segments, segments will be areas etc.) and you connect each one of the original copied polyhedrons |
---|
| 978 | // with its offspring by a parent-child relation. Also each of the segments in the first (second) copy is |
---|
| 979 | // connected to the first (second) newly created vertex by a parent-child relation. |
---|
| 980 | //********************************************************************************************************* |
---|
[1172] | 981 | |
---|
[1186] | 982 | |
---|
[1214] | 983 | /* |
---|
[1186] | 984 | // Create the vectors of vectors of pointers to polyhedrons to hold the copies of the old Hasse diagram |
---|
[1172] | 985 | vector<vector<polyhedron*>> new_statistic1; |
---|
| 986 | vector<vector<polyhedron*>> new_statistic2; |
---|
[1214] | 987 | */ |
---|
[1172] | 988 | |
---|
[1214] | 989 | c_statistic* new_statistic1 = new c_statistic(); |
---|
| 990 | c_statistic* new_statistic2 = new c_statistic(); |
---|
| 991 | |
---|
[1213] | 992 | |
---|
| 993 | // Copy the statistic by rows |
---|
[1172] | 994 | for(int j=0;j<statistic.size();j++) |
---|
[1171] | 995 | { |
---|
[1213] | 996 | |
---|
| 997 | |
---|
[1186] | 998 | // an element counter |
---|
[1171] | 999 | int element_number = 0; |
---|
| 1000 | |
---|
[1214] | 1001 | /* |
---|
[1186] | 1002 | vector<polyhedron*> supportnew_1; |
---|
| 1003 | vector<polyhedron*> supportnew_2; |
---|
| 1004 | |
---|
| 1005 | new_statistic1.push_back(supportnew_1); |
---|
| 1006 | new_statistic2.push_back(supportnew_2); |
---|
[1214] | 1007 | */ |
---|
[1186] | 1008 | |
---|
| 1009 | // for each polyhedron in the given row |
---|
[1214] | 1010 | for(polyhedron* horiz_ref = statistic.rows[j];horiz_ref!=statistic.get_end();horiz_ref=horiz_ref->next_poly) |
---|
[1171] | 1011 | { |
---|
[1186] | 1012 | // Append an extra zero coordinate to each of the vertices for the new dimension |
---|
[1213] | 1013 | // If vert_ref is at the first index => we loop through vertices |
---|
[1186] | 1014 | if(j == 0) |
---|
| 1015 | { |
---|
| 1016 | // cast the polyhedron pointer to a vertex pointer and push a zero to its vector of coordinates |
---|
[1214] | 1017 | ((vertex*) horiz_ref)->push_coordinate(0); |
---|
[1186] | 1018 | } |
---|
[1213] | 1019 | /* |
---|
| 1020 | else |
---|
| 1021 | { |
---|
| 1022 | ((toprow*) (*horiz_ref))->condition.ins(0,0); |
---|
| 1023 | }*/ |
---|
[1186] | 1024 | |
---|
| 1025 | // if it has parents |
---|
[1214] | 1026 | if(!horiz_ref->parents.empty()) |
---|
[1171] | 1027 | { |
---|
[1186] | 1028 | // save the relative address of this child in a vector kids_rel_addresses of all its parents. |
---|
| 1029 | // This information will later be used for copying the whole Hasse diagram with each of the |
---|
| 1030 | // relations contained within. |
---|
[1214] | 1031 | for(list<polyhedron*>::iterator parent_ref = horiz_ref->parents.begin();parent_ref != horiz_ref->parents.end();parent_ref++) |
---|
[1171] | 1032 | { |
---|
[1172] | 1033 | (*parent_ref)->kids_rel_addresses.push_back(element_number); |
---|
| 1034 | } |
---|
[1171] | 1035 | } |
---|
| 1036 | |
---|
[1186] | 1037 | // ************************************************************************************************** |
---|
| 1038 | // Here we begin creating a new polyhedron, which will be a copy of the old one. Each such polyhedron |
---|
| 1039 | // will be created as a toprow, but this information will be later forgotten and only the polyhedrons |
---|
| 1040 | // in the top row of the Hasse diagram will be considered toprow for later use. |
---|
| 1041 | // ************************************************************************************************** |
---|
| 1042 | |
---|
| 1043 | // First we create vectors specifying a toprow condition. In the case of a preconstructed statistic |
---|
| 1044 | // this condition will be a vector of zeros. There are two vectors, because we need two copies of |
---|
| 1045 | // the original Hasse diagram. |
---|
[1213] | 1046 | vec vec1(number_of_parameters+1); |
---|
[1204] | 1047 | vec1.zeros(); |
---|
[1171] | 1048 | |
---|
[1213] | 1049 | vec vec2(number_of_parameters+1); |
---|
[1204] | 1050 | vec2.zeros(); |
---|
| 1051 | |
---|
[1186] | 1052 | // We create a new toprow with the previously specified condition. |
---|
[1242] | 1053 | toprow* current_copy1 = new toprow(vec1, 0); |
---|
| 1054 | toprow* current_copy2 = new toprow(vec2, 0); |
---|
[1171] | 1055 | |
---|
[1186] | 1056 | // The vertices of the copies will be inherited, because there will be a parent/child relation |
---|
| 1057 | // between each polyhedron and its offspring (comming from the copy) and a parent has all the |
---|
| 1058 | // vertices of its child plus more. |
---|
[1220] | 1059 | for(set<vertex*>::iterator vertex_ref = horiz_ref->vertices.begin();vertex_ref!=horiz_ref->vertices.end();vertex_ref++) |
---|
[1171] | 1060 | { |
---|
[1220] | 1061 | current_copy1->vertices.insert(*vertex_ref); |
---|
| 1062 | current_copy2->vertices.insert(*vertex_ref); |
---|
[1171] | 1063 | } |
---|
[1172] | 1064 | |
---|
[1186] | 1065 | // The only new vertex of the offspring should be the newly created point. |
---|
[1220] | 1066 | current_copy1->vertices.insert(new_point1); |
---|
[1234] | 1067 | current_copy2->vertices.insert(new_point2); |
---|
[1186] | 1068 | |
---|
| 1069 | // This method guarantees that each polyhedron is already triangulated, therefore its triangulation |
---|
| 1070 | // is only one set of vertices and it is the set of all its vertices. |
---|
[1234] | 1071 | set<vertex*> t_simplex1; |
---|
| 1072 | set<vertex*> t_simplex2; |
---|
[1220] | 1073 | |
---|
[1234] | 1074 | t_simplex1.insert(current_copy1->vertices.begin(),current_copy1->vertices.end()); |
---|
| 1075 | t_simplex2.insert(current_copy2->vertices.begin(),current_copy2->vertices.end()); |
---|
[1172] | 1076 | |
---|
[1234] | 1077 | current_copy1->triangulation.push_back(t_simplex1); |
---|
| 1078 | current_copy2->triangulation.push_back(t_simplex2); |
---|
| 1079 | |
---|
[1186] | 1080 | // Now we have copied the polyhedron and we have to copy all of its relations. Because we are copying |
---|
| 1081 | // in the Hasse diagram from bottom up, we always have to copy the parent/child relations to all the |
---|
| 1082 | // kids and when we do that and know the child, in the child we will remember the parent we came from. |
---|
| 1083 | // This way all the parents/children relations are saved in both the parent and the child. |
---|
[1214] | 1084 | if(!horiz_ref->kids_rel_addresses.empty()) |
---|
[1171] | 1085 | { |
---|
[1214] | 1086 | for(list<int>::iterator kid_ref = horiz_ref->kids_rel_addresses.begin();kid_ref!=horiz_ref->kids_rel_addresses.end();kid_ref++) |
---|
[1186] | 1087 | { |
---|
[1214] | 1088 | polyhedron* new_kid1 = new_statistic1->rows[j-1]; |
---|
| 1089 | polyhedron* new_kid2 = new_statistic2->rows[j-1]; |
---|
| 1090 | |
---|
| 1091 | // THIS IS NOT EFFECTIVE: It could be improved by having the list indexed for new_statistic, but |
---|
| 1092 | // not indexed for statistic. Hopefully this will not cause a big slowdown - happens only offline. |
---|
| 1093 | if(*kid_ref) |
---|
| 1094 | { |
---|
| 1095 | for(int k = 1;k<=(*kid_ref);k++) |
---|
| 1096 | { |
---|
| 1097 | new_kid1=new_kid1->next_poly; |
---|
| 1098 | new_kid2=new_kid2->next_poly; |
---|
| 1099 | } |
---|
| 1100 | } |
---|
| 1101 | |
---|
[1186] | 1102 | // find the child and save the relation to the parent |
---|
[1214] | 1103 | current_copy1->children.push_back(new_kid1); |
---|
| 1104 | current_copy2->children.push_back(new_kid2); |
---|
[1171] | 1105 | |
---|
[1186] | 1106 | // in the child save the parents' address |
---|
[1214] | 1107 | new_kid1->parents.push_back(current_copy1); |
---|
| 1108 | new_kid2->parents.push_back(current_copy2); |
---|
[1172] | 1109 | } |
---|
[1171] | 1110 | |
---|
[1186] | 1111 | // Here we clear the parents kids_rel_addresses vector for later use (when we need to widen the |
---|
| 1112 | // Hasse diagram again) |
---|
[1214] | 1113 | horiz_ref->kids_rel_addresses.clear(); |
---|
[1171] | 1114 | } |
---|
[1186] | 1115 | // If there were no children previously, we are copying a polyhedron that has been a vertex before. |
---|
| 1116 | // In this case it is a segment now and it will have a relation to its mother (copywise) and to the |
---|
| 1117 | // newly created point. Here we create the connection to the new point, again from both sides. |
---|
[1171] | 1118 | else |
---|
| 1119 | { |
---|
[1186] | 1120 | // Add the address of the new point in the former vertex |
---|
[1172] | 1121 | current_copy1->children.push_back(new_point1); |
---|
| 1122 | current_copy2->children.push_back(new_point2); |
---|
[1171] | 1123 | |
---|
[1186] | 1124 | // Add the address of the former vertex in the new point |
---|
[1172] | 1125 | new_point1->parents.push_back(current_copy1); |
---|
| 1126 | new_point2->parents.push_back(current_copy2); |
---|
[1171] | 1127 | } |
---|
| 1128 | |
---|
[1186] | 1129 | // Save the mother in its offspring |
---|
[1214] | 1130 | current_copy1->children.push_back(horiz_ref); |
---|
| 1131 | current_copy2->children.push_back(horiz_ref); |
---|
[1171] | 1132 | |
---|
[1186] | 1133 | // Save the offspring in its mother |
---|
[1214] | 1134 | horiz_ref->parents.push_back(current_copy1); |
---|
| 1135 | horiz_ref->parents.push_back(current_copy2); |
---|
[1186] | 1136 | |
---|
[1171] | 1137 | |
---|
[1186] | 1138 | // Add the copies into the relevant statistic. The statistic will later be appended to the previous |
---|
| 1139 | // Hasse diagram |
---|
[1214] | 1140 | new_statistic1->append_polyhedron(j,current_copy1); |
---|
| 1141 | new_statistic2->append_polyhedron(j,current_copy2); |
---|
[1186] | 1142 | |
---|
| 1143 | // Raise the count in the vector of polyhedrons |
---|
[1214] | 1144 | element_number++; |
---|
[1186] | 1145 | |
---|
[1213] | 1146 | } |
---|
| 1147 | |
---|
[1186] | 1148 | } |
---|
| 1149 | |
---|
[1214] | 1150 | /* |
---|
[1213] | 1151 | statistic.begin()->push_back(new_point1); |
---|
| 1152 | statistic.begin()->push_back(new_point2); |
---|
[1214] | 1153 | */ |
---|
[1186] | 1154 | |
---|
[1214] | 1155 | statistic.append_polyhedron(0, new_point1); |
---|
| 1156 | statistic.append_polyhedron(0, new_point2); |
---|
| 1157 | |
---|
[1186] | 1158 | // Merge the new statistics into the old one. This will either be the final statistic or we will |
---|
| 1159 | // reenter the widening loop. |
---|
[1214] | 1160 | for(int j=0;j<new_statistic1->size();j++) |
---|
[1186] | 1161 | { |
---|
[1214] | 1162 | /* |
---|
[1186] | 1163 | if(j+1==statistic.size()) |
---|
| 1164 | { |
---|
[1213] | 1165 | list<polyhedron*> support; |
---|
[1186] | 1166 | statistic.push_back(support); |
---|
| 1167 | } |
---|
| 1168 | |
---|
[1213] | 1169 | (statistic.begin()+j+1)->insert((statistic.begin()+j+1)->end(),new_statistic1[j].begin(),new_statistic1[j].end()); |
---|
| 1170 | (statistic.begin()+j+1)->insert((statistic.begin()+j+1)->end(),new_statistic2[j].begin(),new_statistic2[j].end()); |
---|
[1214] | 1171 | */ |
---|
| 1172 | statistic.append_polyhedron(j+1,new_statistic1->rows[j],new_statistic1->row_ends[j]); |
---|
| 1173 | statistic.append_polyhedron(j+1,new_statistic2->rows[j],new_statistic2->row_ends[j]); |
---|
[1186] | 1174 | } |
---|
[1213] | 1175 | |
---|
| 1176 | |
---|
[1171] | 1177 | } |
---|
[1213] | 1178 | |
---|
[1214] | 1179 | /* |
---|
[1213] | 1180 | vector<list<toprow*>> toprow_statistic; |
---|
| 1181 | int line_count = 0; |
---|
| 1182 | |
---|
| 1183 | for(vector<list<polyhedron*>>::iterator polyhedron_ref = ++statistic.begin(); polyhedron_ref!=statistic.end();polyhedron_ref++) |
---|
| 1184 | { |
---|
| 1185 | list<toprow*> support_list; |
---|
| 1186 | toprow_statistic.push_back(support_list); |
---|
| 1187 | |
---|
| 1188 | for(list<polyhedron*>::iterator polyhedron_ref2 = polyhedron_ref->begin(); polyhedron_ref2 != polyhedron_ref->end(); polyhedron_ref2++) |
---|
| 1189 | { |
---|
| 1190 | toprow* support_top = (toprow*)(*polyhedron_ref2); |
---|
| 1191 | |
---|
| 1192 | toprow_statistic[line_count].push_back(support_top); |
---|
| 1193 | } |
---|
| 1194 | |
---|
| 1195 | line_count++; |
---|
[1214] | 1196 | }*/ |
---|
| 1197 | |
---|
[1216] | 1198 | /* |
---|
[1214] | 1199 | vector<int> sizevector; |
---|
| 1200 | for(int s = 0;s<statistic.size();s++) |
---|
| 1201 | { |
---|
| 1202 | sizevector.push_back(statistic.row_size(s)); |
---|
[1213] | 1203 | } |
---|
[1216] | 1204 | */ |
---|
[1214] | 1205 | |
---|
[1171] | 1206 | } |
---|
| 1207 | |
---|
| 1208 | |
---|
[976] | 1209 | |
---|
[1171] | 1210 | |
---|
[976] | 1211 | }; |
---|
| 1212 | |
---|
[1208] | 1213 | /* |
---|
| 1214 | |
---|
[976] | 1215 | //! Robust Bayesian AR model for Multicriteria-Laplace-Inverse-Gamma density |
---|
[1204] | 1216 | class RARX : public BM |
---|
| 1217 | { |
---|
| 1218 | private: |
---|
| 1219 | |
---|
| 1220 | emlig posterior; |
---|
| 1221 | |
---|
| 1222 | public: |
---|
| 1223 | RARX():BM() |
---|
| 1224 | { |
---|
| 1225 | }; |
---|
| 1226 | |
---|
| 1227 | void bayes(const itpp::vec &yt, const itpp::vec &cond = empty_vec) |
---|
| 1228 | { |
---|
| 1229 | |
---|
| 1230 | } |
---|
| 1231 | |
---|
[1208] | 1232 | };*/ |
---|
[976] | 1233 | |
---|
| 1234 | |
---|
[1208] | 1235 | |
---|
[976] | 1236 | #endif //TRAGE_H |
---|