| 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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| 11 | #include <itpp/itbase.h> |
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| 12 | #include <itpp/base/random.h> |
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| 13 | #include <map> |
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| 14 | #include <limits> |
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| 15 | #include <vector> |
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| 16 | #include <list> |
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| 17 | #include <set> |
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| 18 | #include <algorithm> |
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| 19 | |
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| 20 | using namespace bdm; |
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| 21 | using namespace std; |
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| 22 | using namespace itpp; |
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| 23 | |
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| 24 | const double max_range = 5;//numeric_limits<double>::max()/10e-10; |
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| 25 | |
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| 26 | /// An enumeration of possible actions performed on the polyhedrons. We can merge them or split them. |
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| 27 | enum actions {MERGE, SPLIT}; |
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| 28 | |
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| 29 | // Forward declaration of polyhedron, vertex and emlig |
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| 30 | class polyhedron; |
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| 31 | class vertex; |
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| 32 | class emlig; |
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| 33 | |
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| 34 | /* |
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| 35 | class t_simplex |
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| 36 | { |
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| 37 | public: |
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| 38 | set<vertex*> minima; |
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| 39 | |
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| 40 | set<vertex*> simplex; |
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| 41 | |
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| 42 | t_simplex(vertex* origin_vertex) |
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| 43 | { |
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| 44 | simplex.insert(origin_vertex); |
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| 45 | minima.insert(origin_vertex); |
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| 46 | } |
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| 47 | };*/ |
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| 48 | |
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| 49 | /// A class representing a single condition that can be added to the emlig. A condition represents data entries in a statistical model. |
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| 50 | class condition |
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| 51 | { |
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| 52 | public: |
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| 53 | /// Value of the condition representing the data |
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| 54 | vec value; |
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| 55 | |
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| 56 | /// Mulitplicity of the given condition may represent multiple occurences of same data entry. |
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| 57 | int multiplicity; |
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| 58 | |
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| 59 | /// Default constructor of condition class takes the value of data entry and creates a condition with multiplicity 1 (first occurence of the data). |
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| 60 | condition(vec value) |
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| 61 | { |
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| 62 | this->value = value; |
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| 63 | multiplicity = 1; |
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| 64 | } |
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| 65 | }; |
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| 66 | |
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| 67 | class simplex |
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| 68 | { |
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| 69 | |
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| 70 | |
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| 71 | public: |
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| 72 | |
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| 73 | set<vertex*> vertices; |
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| 74 | |
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| 75 | double probability; |
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| 76 | |
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| 77 | vector<multimap<double,double>> positive_gamma_parameters; |
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| 78 | |
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| 79 | vector<multimap<double,double>> negative_gamma_parameters; |
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| 80 | |
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| 81 | double positive_gamma_sum; |
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| 82 | |
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| 83 | double negative_gamma_sum; |
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| 84 | |
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| 85 | double min_beta; |
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| 86 | |
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| 87 | |
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| 88 | simplex(set<vertex*> vertices) |
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| 89 | { |
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| 90 | this->vertices.insert(vertices.begin(),vertices.end()); |
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| 91 | probability = 0; |
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| 92 | } |
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| 93 | |
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| 94 | simplex(vertex* vertex) |
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| 95 | { |
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| 96 | this->vertices.insert(vertex); |
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| 97 | probability = 0; |
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| 98 | } |
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| 99 | |
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| 100 | void clear_gammas() |
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| 101 | { |
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| 102 | positive_gamma_parameters.clear(); |
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| 103 | negative_gamma_parameters.clear(); |
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| 104 | |
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| 105 | positive_gamma_sum = 0; |
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| 106 | negative_gamma_sum = 0; |
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| 107 | |
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| 108 | min_beta = numeric_limits<double>::max(); |
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| 109 | } |
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| 110 | |
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| 111 | void insert_gamma(int order, double weight, double beta) |
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| 112 | { |
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| 113 | if(weight>=0) |
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| 114 | { |
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| 115 | while(positive_gamma_parameters.size()<order+1) |
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| 116 | { |
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| 117 | multimap<double,double> map; |
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| 118 | positive_gamma_parameters.push_back(map); |
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| 119 | } |
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| 120 | |
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| 121 | positive_gamma_sum += weight; |
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| 122 | |
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| 123 | positive_gamma_parameters[order].insert(pair<double,double>(weight,beta)); |
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| 124 | } |
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| 125 | else |
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| 126 | { |
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| 127 | while(negative_gamma_parameters.size()<order+1) |
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| 128 | { |
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| 129 | multimap<double,double> map; |
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| 130 | negative_gamma_parameters.push_back(map); |
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| 131 | } |
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| 132 | |
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| 133 | negative_gamma_sum -= weight; |
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| 134 | |
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| 135 | negative_gamma_parameters[order].insert(pair<double,double>(-weight,beta)); |
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| 136 | } |
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| 137 | |
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| 138 | if(beta < min_beta) |
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| 139 | { |
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| 140 | min_beta = beta; |
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| 141 | } |
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| 142 | } |
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| 143 | }; |
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| 144 | |
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| 145 | |
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| 146 | /// A class describing a single polyhedron of the split complex. From a collection of such classes a Hasse diagram |
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| 147 | /// of the structure in the exponent of a Laplace-Inverse-Gamma density will be created. |
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| 148 | class polyhedron |
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| 149 | { |
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| 150 | /// A property having a value of 1 usually, with higher value only if the polyhedron arises as a coincidence of |
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| 151 | /// more than just the necessary number of conditions. For example if a newly created line passes through an already |
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| 152 | /// existing point, the points multiplicity will rise by 1. |
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| 153 | int multiplicity; |
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| 154 | |
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| 155 | /// A property representing the position of the polyhedron related to current condition with relation to which we |
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| 156 | /// are splitting the parameter space (new data has arrived). This property is setup within a classification procedure and |
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| 157 | /// is only valid while the new condition is being added. It has to be reset when new condition is added and new classification |
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| 158 | /// has to be performed. |
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| 159 | int split_state; |
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| 160 | |
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| 161 | /// A property representing the position of the polyhedron related to current condition with relation to which we |
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| 162 | /// are merging the parameter space (data is being deleted usually due to a moving window model which is more adaptive and |
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| 163 | /// steps in for the forgetting in a classical Gaussian AR model). This property is setup within a classification procedure and |
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| 164 | /// is only valid while the new condition is being removed. It has to be reset when new condition is removed and new classification |
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| 165 | /// has to be performed. |
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| 166 | int merge_state; |
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| 167 | |
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| 168 | |
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| 169 | |
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| 170 | public: |
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| 171 | /// A pointer to the multi-Laplace inverse gamma distribution this polyhedron belongs to. |
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| 172 | emlig* my_emlig; |
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| 173 | |
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| 174 | /// A list of polyhedrons parents within the Hasse diagram. |
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| 175 | list<polyhedron*> parents; |
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| 176 | |
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| 177 | /// A list of polyhedrons children withing the Hasse diagram. |
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| 178 | list<polyhedron*> children; |
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| 179 | |
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| 180 | /// All the vertices of the given polyhedron |
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| 181 | set<vertex*> vertices; |
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| 182 | |
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| 183 | /// The conditions that gave birth to the polyhedron. If some of them is removed, the polyhedron ceases to exist. |
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| 184 | set<condition*> parentconditions; |
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| 185 | |
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| 186 | /// A list used for storing children that lie in the positive region related to a certain condition |
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| 187 | list<polyhedron*> positivechildren; |
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| 188 | |
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| 189 | /// A list used for storing children that lie in the negative region related to a certain condition |
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| 190 | list<polyhedron*> negativechildren; |
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| 191 | |
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| 192 | /// Children intersecting the condition |
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| 193 | list<polyhedron*> neutralchildren; |
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| 194 | |
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| 195 | /// A set of grandchildren of the polyhedron that when new condition is added lie exactly on the condition hyperplane. These grandchildren |
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| 196 | /// behave differently from other grandchildren, when the polyhedron is split. New grandchild is not necessarily created on the crossection of |
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| 197 | /// the polyhedron and new condition. |
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| 198 | set<polyhedron*> totallyneutralgrandchildren; |
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| 199 | |
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| 200 | /// A set of children of the polyhedron that when new condition is added lie exactly on the condition hyperplane. These children |
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| 201 | /// behave differently from other children, when the polyhedron is split. New child is not necessarily created on the crossection of |
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| 202 | /// the polyhedron and new condition. |
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| 203 | set<polyhedron*> totallyneutralchildren; |
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| 204 | |
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| 205 | /// Reverse relation to the totallyneutralgrandchildren set is needed for merging of already existing polyhedrons to keep |
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| 206 | /// totallyneutralgrandchildren list up to date. |
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| 207 | set<polyhedron*> grandparents; |
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| 208 | |
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| 209 | /// Vertices of the polyhedron classified as positive related to an added condition. When the polyhderon is split by the new condition, |
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| 210 | /// these vertices will belong to the positive part of the splitted polyhedron. |
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| 211 | set<vertex*> positiveneutralvertices; |
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| 212 | |
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| 213 | /// Vertices of the polyhedron classified as negative related to an added condition. When the polyhderon is split by the new condition, |
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| 214 | /// these vertices will belong to the negative part of the splitted polyhedron. |
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| 215 | set<vertex*> negativeneutralvertices; |
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| 216 | |
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| 217 | /// A bool specifying if the polyhedron lies exactly on the newly added condition or not. |
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| 218 | bool totally_neutral; |
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| 219 | |
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| 220 | /// When two polyhedrons are merged, there always exists a child lying on the former border of the polyhedrons. This child manages the merge |
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| 221 | /// of the two polyhedrons. This property gives us the address of the mediator child. |
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| 222 | polyhedron* mergechild; |
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| 223 | |
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| 224 | /// If the polyhedron serves as a mergechild for two of its parents, we need to have the address of the parents to access them. This |
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| 225 | /// is the pointer to the positive parent being merged. |
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| 226 | polyhedron* positiveparent; |
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| 227 | |
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| 228 | /// If the polyhedron serves as a mergechild for two of its parents, we need to have the address of the parents to access them. This |
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| 229 | /// is the pointer to the negative parent being merged. |
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| 230 | polyhedron* negativeparent; |
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| 231 | |
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| 232 | /// Adressing withing the statistic. Next_poly is a pointer to the next polyhedron in the statistic on the same level (if this is a point, |
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| 233 | /// next_poly will be a point etc.). |
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| 234 | polyhedron* next_poly; |
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| 235 | |
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| 236 | /// Adressing withing the statistic. Prev_poly is a pointer to the previous polyhedron in the statistic on the same level (if this is a point, |
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| 237 | /// next_poly will be a point etc.). |
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| 238 | polyhedron* prev_poly; |
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| 239 | |
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| 240 | /// A property counting the number of messages obtained from children within a classification procedure of position of the polyhedron related |
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| 241 | /// an added/removed condition. If the message counter reaches the number of children, we know the polyhedrons' position has been fully classified. |
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| 242 | int message_counter; |
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| 243 | |
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| 244 | /// List of triangulation polyhedrons of the polyhedron given by their relative vertices. |
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| 245 | set<simplex*> triangulation; |
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| 246 | |
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| 247 | /// A list of relative addresses serving for Hasse diagram construction. |
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| 248 | list<int> kids_rel_addresses; |
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| 249 | |
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| 250 | /// Default constructor |
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| 251 | polyhedron() |
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| 252 | { |
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| 253 | multiplicity = 1; |
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| 254 | |
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| 255 | message_counter = 0; |
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| 256 | |
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| 257 | totally_neutral = NULL; |
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| 258 | |
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| 259 | mergechild = NULL; |
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| 260 | } |
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| 261 | |
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| 262 | /// Setter for raising multiplicity |
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| 263 | void raise_multiplicity() |
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| 264 | { |
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| 265 | multiplicity++; |
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| 266 | } |
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| 267 | |
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| 268 | /// Setter for lowering multiplicity |
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| 269 | void lower_multiplicity() |
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| 270 | { |
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| 271 | multiplicity--; |
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| 272 | } |
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| 273 | |
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| 274 | int get_multiplicity() |
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| 275 | { |
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| 276 | return multiplicity; |
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| 277 | } |
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| 278 | |
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| 279 | /// An obligatory operator, when the class is used within a C++ STL structure like a vector |
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| 280 | int operator==(polyhedron polyhedron2) |
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| 281 | { |
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| 282 | return true; |
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| 283 | } |
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| 284 | |
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| 285 | /// An obligatory operator, when the class is used within a C++ STL structure like a vector |
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| 286 | int operator<(polyhedron polyhedron2) |
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| 287 | { |
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| 288 | return false; |
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| 289 | } |
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| 290 | |
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| 291 | |
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| 292 | /// A setter of state of current polyhedron relative to the action specified in the argument. The three possible states of the |
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| 293 | /// polyhedron are -1 - NEGATIVE, 0 - NEUTRAL, 1 - POSITIVE. Neutral state means that either the state has been reset or the polyhedron is |
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| 294 | /// ready to be split/merged. |
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| 295 | int set_state(double state_indicator, actions action) |
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| 296 | { |
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| 297 | switch(action) |
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| 298 | { |
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| 299 | case MERGE: |
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| 300 | merge_state = (int)sign(state_indicator); |
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| 301 | return merge_state; |
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| 302 | case SPLIT: |
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| 303 | split_state = (int)sign(state_indicator); |
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| 304 | return split_state; |
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| 305 | } |
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| 306 | } |
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| 307 | |
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| 308 | /// A getter of state of current polyhedron relative to the action specified in the argument. The three possible states of the |
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| 309 | /// polyhedron are -1 - NEGATIVE, 0 - NEUTRAL, 1 - POSITIVE. Neutral state means that either the state has been reset or the polyhedron is |
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| 310 | /// ready to be split/merged. |
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| 311 | int get_state(actions action) |
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| 312 | { |
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| 313 | switch(action) |
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| 314 | { |
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| 315 | case MERGE: |
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| 316 | return merge_state; |
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| 317 | break; |
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| 318 | case SPLIT: |
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| 319 | return split_state; |
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| 320 | break; |
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| 321 | } |
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| 322 | } |
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| 323 | |
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| 324 | /// Method for obtaining the number of children of given polyhedron. |
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| 325 | int number_of_children() |
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| 326 | { |
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| 327 | return children.size(); |
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| 328 | } |
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| 329 | |
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| 330 | /// A method for triangulation of given polyhedron. |
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| 331 | double triangulate(bool should_integrate); |
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| 332 | }; |
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| 333 | |
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| 334 | |
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| 335 | /// A class for representing 0-dimensional polyhedron - a vertex. It will be located in the bottom row of the Hasse |
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| 336 | /// diagram representing a complex of polyhedrons. It has its coordinates in the parameter space. |
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| 337 | class vertex : public polyhedron |
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| 338 | { |
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| 339 | /// A dynamic array representing coordinates of the vertex |
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| 340 | vec coordinates; |
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| 341 | |
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| 342 | public: |
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| 343 | /// A property specifying the value of the density (ted nevim, jestli je to jakoby log nebo ne) above the vertex. |
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| 344 | double function_value; |
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| 345 | |
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| 346 | /// Default constructor |
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| 347 | vertex(); |
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| 348 | |
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| 349 | /// Constructor of a vertex from a set of coordinates |
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| 350 | vertex(vec coordinates) |
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| 351 | { |
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| 352 | this->coordinates = coordinates; |
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| 353 | |
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| 354 | vertices.insert(this); |
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| 355 | |
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| 356 | simplex* vert_simplex = new simplex(vertices); |
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| 357 | |
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| 358 | triangulation.insert(vert_simplex); |
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| 359 | } |
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| 360 | |
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| 361 | /// A method that widens the set of coordinates of given vertex. It is used when a complex in a parameter |
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| 362 | /// space of certain dimension is established, but the dimension is not known when the vertex is created. |
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| 363 | void push_coordinate(double coordinate) |
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| 364 | { |
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| 365 | coordinates = concat(coordinates,coordinate); |
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| 366 | } |
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| 367 | |
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| 368 | /// A method obtaining the set of coordinates of a vertex. These coordinates are not obtained as a pointer |
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| 369 | /// (not given by reference), but a new copy is created (they are given by value). |
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| 370 | vec get_coordinates() |
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| 371 | { |
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| 372 | return coordinates; |
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| 373 | } |
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| 374 | |
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| 375 | }; |
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| 376 | |
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| 377 | |
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| 378 | /// A class representing a polyhedron in a top row of the complex. Such polyhedron has a condition that differen tiates |
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| 379 | /// it from polyhedrons in other rows. |
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| 380 | class toprow : public polyhedron |
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| 381 | { |
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| 382 | |
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| 383 | public: |
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| 384 | double probability; |
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| 385 | |
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| 386 | vertex* minimal_vertex; |
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| 387 | |
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| 388 | /// A condition used for determining the function of a Laplace-Inverse-Gamma density resulting from Bayesian estimation |
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| 389 | vec condition_sum; |
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| 390 | |
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| 391 | int condition_order; |
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| 392 | |
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| 393 | /// Default constructor |
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| 394 | toprow(){}; |
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| 395 | |
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| 396 | /// Constructor creating a toprow from the condition |
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| 397 | toprow(condition *condition, int condition_order) |
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| 398 | { |
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| 399 | this->condition_sum = condition->value; |
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| 400 | this->condition_order = condition_order; |
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| 401 | } |
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| 402 | |
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| 403 | toprow(vec condition_sum, int condition_order) |
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| 404 | { |
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| 405 | this->condition_sum = condition_sum; |
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| 406 | this->condition_order = condition_order; |
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| 407 | } |
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| 408 | |
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| 409 | double integrate_simplex(simplex* simplex, char c); |
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| 410 | |
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| 411 | }; |
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| 412 | |
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| 413 | |
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| 414 | |
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| 415 | |
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| 416 | |
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| 417 | |
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| 418 | |
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| 419 | class c_statistic |
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| 420 | { |
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| 421 | |
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| 422 | public: |
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| 423 | polyhedron* end_poly; |
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| 424 | polyhedron* start_poly; |
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| 425 | |
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| 426 | vector<polyhedron*> rows; |
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| 427 | |
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| 428 | vector<polyhedron*> row_ends; |
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| 429 | |
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| 430 | c_statistic() |
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| 431 | { |
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| 432 | end_poly = new polyhedron(); |
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| 433 | start_poly = new polyhedron(); |
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| 434 | }; |
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| 435 | |
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| 436 | ~c_statistic() |
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| 437 | { |
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| 438 | delete end_poly; |
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| 439 | delete start_poly; |
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| 440 | } |
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| 441 | |
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| 442 | void append_polyhedron(int row, polyhedron* appended_start, polyhedron* appended_end) |
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| 443 | { |
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| 444 | if(row>((int)rows.size())-1) |
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| 445 | { |
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| 446 | if(row>rows.size()) |
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| 447 | { |
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| 448 | throw new exception("You are trying to append a polyhedron whose children are not in the statistic yet!"); |
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| 449 | return; |
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| 450 | } |
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| 451 | |
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| 452 | rows.push_back(end_poly); |
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| 453 | row_ends.push_back(end_poly); |
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| 454 | } |
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| 455 | |
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| 456 | // POSSIBLE FAILURE: the function is not checking if start and end are connected |
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| 457 | |
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| 458 | if(rows[row] != end_poly) |
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| 459 | { |
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| 460 | appended_start->prev_poly = row_ends[row]; |
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| 461 | row_ends[row]->next_poly = appended_start; |
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| 462 | |
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| 463 | } |
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| 464 | else if((row>0 && rows[row-1]!=end_poly)||row==0) |
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| 465 | { |
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| 466 | appended_start->prev_poly = start_poly; |
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| 467 | rows[row]= appended_start; |
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| 468 | } |
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| 469 | else |
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| 470 | { |
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| 471 | throw new exception("Wrong polyhedron insertion into statistic: missing intermediary polyhedron!"); |
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| 472 | } |
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| 473 | |
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| 474 | appended_end->next_poly = end_poly; |
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| 475 | row_ends[row] = appended_end; |
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| 476 | } |
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| 477 | |
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| 478 | void append_polyhedron(int row, polyhedron* appended_poly) |
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| 479 | { |
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| 480 | append_polyhedron(row,appended_poly,appended_poly); |
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| 481 | } |
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| 482 | |
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| 483 | void insert_polyhedron(int row, polyhedron* inserted_poly, polyhedron* following_poly) |
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| 484 | { |
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| 485 | if(following_poly != end_poly) |
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| 486 | { |
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| 487 | inserted_poly->next_poly = following_poly; |
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| 488 | inserted_poly->prev_poly = following_poly->prev_poly; |
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| 489 | |
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| 490 | if(following_poly->prev_poly == start_poly) |
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| 491 | { |
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| 492 | rows[row] = inserted_poly; |
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| 493 | } |
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| 494 | else |
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| 495 | { |
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| 496 | inserted_poly->prev_poly->next_poly = inserted_poly; |
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| 497 | } |
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| 498 | |
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| 499 | following_poly->prev_poly = inserted_poly; |
|---|
| 500 | } |
|---|
| 501 | else |
|---|
| 502 | { |
|---|
| 503 | this->append_polyhedron(row, inserted_poly); |
|---|
| 504 | } |
|---|
| 505 | |
|---|
| 506 | } |
|---|
| 507 | |
|---|
| 508 | |
|---|
| 509 | |
|---|
| 510 | |
|---|
| 511 | void delete_polyhedron(int row, polyhedron* deleted_poly) |
|---|
| 512 | { |
|---|
| 513 | if(deleted_poly->prev_poly != start_poly) |
|---|
| 514 | { |
|---|
| 515 | deleted_poly->prev_poly->next_poly = deleted_poly->next_poly; |
|---|
| 516 | } |
|---|
| 517 | else |
|---|
| 518 | { |
|---|
| 519 | rows[row] = deleted_poly->next_poly; |
|---|
| 520 | } |
|---|
| 521 | |
|---|
| 522 | if(deleted_poly->next_poly!=end_poly) |
|---|
| 523 | { |
|---|
| 524 | deleted_poly->next_poly->prev_poly = deleted_poly->prev_poly; |
|---|
| 525 | } |
|---|
| 526 | else |
|---|
| 527 | { |
|---|
| 528 | row_ends[row] = deleted_poly->prev_poly; |
|---|
| 529 | } |
|---|
| 530 | |
|---|
| 531 | |
|---|
| 532 | |
|---|
| 533 | deleted_poly->next_poly = NULL; |
|---|
| 534 | deleted_poly->prev_poly = NULL; |
|---|
| 535 | } |
|---|
| 536 | |
|---|
| 537 | int size() |
|---|
| 538 | { |
|---|
| 539 | return rows.size(); |
|---|
| 540 | } |
|---|
| 541 | |
|---|
| 542 | polyhedron* get_end() |
|---|
| 543 | { |
|---|
| 544 | return end_poly; |
|---|
| 545 | } |
|---|
| 546 | |
|---|
| 547 | polyhedron* get_start() |
|---|
| 548 | { |
|---|
| 549 | return start_poly; |
|---|
| 550 | } |
|---|
| 551 | |
|---|
| 552 | int row_size(int row) |
|---|
| 553 | { |
|---|
| 554 | if(this->size()>row && row>=0) |
|---|
| 555 | { |
|---|
| 556 | int row_size = 0; |
|---|
| 557 | |
|---|
| 558 | for(polyhedron* row_poly = rows[row]; row_poly!=end_poly; row_poly=row_poly->next_poly) |
|---|
| 559 | { |
|---|
| 560 | row_size++; |
|---|
| 561 | } |
|---|
| 562 | |
|---|
| 563 | return row_size; |
|---|
| 564 | } |
|---|
| 565 | else |
|---|
| 566 | { |
|---|
| 567 | throw new exception("There is no row to obtain size from!"); |
|---|
| 568 | } |
|---|
| 569 | } |
|---|
| 570 | }; |
|---|
| 571 | |
|---|
| 572 | |
|---|
| 573 | class my_ivec : public ivec |
|---|
| 574 | { |
|---|
| 575 | public: |
|---|
| 576 | my_ivec():ivec(){}; |
|---|
| 577 | |
|---|
| 578 | my_ivec(ivec origin):ivec() |
|---|
| 579 | { |
|---|
| 580 | this->ins(0,origin); |
|---|
| 581 | } |
|---|
| 582 | |
|---|
| 583 | bool operator>(const my_ivec &second) const |
|---|
| 584 | { |
|---|
| 585 | return max(*this)>max(second); |
|---|
| 586 | |
|---|
| 587 | /* |
|---|
| 588 | int size1 = this->size(); |
|---|
| 589 | int size2 = second.size(); |
|---|
| 590 | |
|---|
| 591 | int counter1 = 0; |
|---|
| 592 | while(0==0) |
|---|
| 593 | { |
|---|
| 594 | if((*this)[counter1]==0) |
|---|
| 595 | { |
|---|
| 596 | size1--; |
|---|
| 597 | } |
|---|
| 598 | |
|---|
| 599 | if((*this)[counter1]!=0) |
|---|
| 600 | break; |
|---|
| 601 | |
|---|
| 602 | counter1++; |
|---|
| 603 | } |
|---|
| 604 | |
|---|
| 605 | int counter2 = 0; |
|---|
| 606 | while(0==0) |
|---|
| 607 | { |
|---|
| 608 | if(second[counter2]==0) |
|---|
| 609 | { |
|---|
| 610 | size2--; |
|---|
| 611 | } |
|---|
| 612 | |
|---|
| 613 | if(second[counter2]!=0) |
|---|
| 614 | break; |
|---|
| 615 | |
|---|
| 616 | counter2++; |
|---|
| 617 | } |
|---|
| 618 | |
|---|
| 619 | if(size1!=size2) |
|---|
| 620 | { |
|---|
| 621 | return size1>size2; |
|---|
| 622 | } |
|---|
| 623 | else |
|---|
| 624 | { |
|---|
| 625 | for(int i = 0;i<size1;i++) |
|---|
| 626 | { |
|---|
| 627 | if((*this)[counter1+i]!=second[counter2+i]) |
|---|
| 628 | { |
|---|
| 629 | return (*this)[counter1+i]>second[counter2+i]; |
|---|
| 630 | } |
|---|
| 631 | } |
|---|
| 632 | |
|---|
| 633 | return false; |
|---|
| 634 | }*/ |
|---|
| 635 | } |
|---|
| 636 | |
|---|
| 637 | |
|---|
| 638 | bool operator==(const my_ivec &second) const |
|---|
| 639 | { |
|---|
| 640 | return max(*this)==max(second); |
|---|
| 641 | |
|---|
| 642 | /* |
|---|
| 643 | int size1 = this->size(); |
|---|
| 644 | int size2 = second.size(); |
|---|
| 645 | |
|---|
| 646 | int counter = 0; |
|---|
| 647 | while(0==0) |
|---|
| 648 | { |
|---|
| 649 | if((*this)[counter]==0) |
|---|
| 650 | { |
|---|
| 651 | size1--; |
|---|
| 652 | } |
|---|
| 653 | |
|---|
| 654 | if((*this)[counter]!=0) |
|---|
| 655 | break; |
|---|
| 656 | |
|---|
| 657 | counter++; |
|---|
| 658 | } |
|---|
| 659 | |
|---|
| 660 | counter = 0; |
|---|
| 661 | while(0==0) |
|---|
| 662 | { |
|---|
| 663 | if(second[counter]==0) |
|---|
| 664 | { |
|---|
| 665 | size2--; |
|---|
| 666 | } |
|---|
| 667 | |
|---|
| 668 | if(second[counter]!=0) |
|---|
| 669 | break; |
|---|
| 670 | |
|---|
| 671 | counter++; |
|---|
| 672 | } |
|---|
| 673 | |
|---|
| 674 | if(size1!=size2) |
|---|
| 675 | { |
|---|
| 676 | return false; |
|---|
| 677 | } |
|---|
| 678 | else |
|---|
| 679 | { |
|---|
| 680 | for(int i=0;i<size1;i++) |
|---|
| 681 | { |
|---|
| 682 | if((*this)[size()-1-i]!=second[second.size()-1-i]) |
|---|
| 683 | { |
|---|
| 684 | return false; |
|---|
| 685 | } |
|---|
| 686 | } |
|---|
| 687 | |
|---|
| 688 | return true; |
|---|
| 689 | }*/ |
|---|
| 690 | } |
|---|
| 691 | |
|---|
| 692 | bool operator<(const my_ivec &second) const |
|---|
| 693 | { |
|---|
| 694 | return !(((*this)>second)||((*this)==second)); |
|---|
| 695 | } |
|---|
| 696 | |
|---|
| 697 | bool operator!=(const my_ivec &second) const |
|---|
| 698 | { |
|---|
| 699 | return !((*this)==second); |
|---|
| 700 | } |
|---|
| 701 | |
|---|
| 702 | bool operator<=(const my_ivec &second) const |
|---|
| 703 | { |
|---|
| 704 | return !((*this)>second); |
|---|
| 705 | } |
|---|
| 706 | |
|---|
| 707 | bool operator>=(const my_ivec &second) const |
|---|
| 708 | { |
|---|
| 709 | return !((*this)<second); |
|---|
| 710 | } |
|---|
| 711 | |
|---|
| 712 | my_ivec right(my_ivec original) |
|---|
| 713 | { |
|---|
| 714 | |
|---|
| 715 | } |
|---|
| 716 | }; |
|---|
| 717 | |
|---|
| 718 | |
|---|
| 719 | |
|---|
| 720 | |
|---|
| 721 | |
|---|
| 722 | |
|---|
| 723 | |
|---|
| 724 | //! Conditional(e) Multicriteria-Laplace-Inverse-Gamma distribution density |
|---|
| 725 | class emlig // : eEF |
|---|
| 726 | { |
|---|
| 727 | |
|---|
| 728 | /// A statistic in a form of a Hasse diagram representing a complex of convex polyhedrons obtained as a result |
|---|
| 729 | /// of data update from Bayesian estimation or set by the user if this emlig is a prior density |
|---|
| 730 | |
|---|
| 731 | |
|---|
| 732 | vector<list<polyhedron*>> for_splitting; |
|---|
| 733 | |
|---|
| 734 | vector<list<polyhedron*>> for_merging; |
|---|
| 735 | |
|---|
| 736 | list<condition*> conditions; |
|---|
| 737 | |
|---|
| 738 | double normalization_factor; |
|---|
| 739 | |
|---|
| 740 | int condition_order; |
|---|
| 741 | |
|---|
| 742 | double last_log_nc; |
|---|
| 743 | |
|---|
| 744 | |
|---|
| 745 | |
|---|
| 746 | void alter_toprow_conditions(condition *condition, bool should_be_added) |
|---|
| 747 | { |
|---|
| 748 | for(polyhedron* horiz_ref = statistic.rows[statistic.size()-1];horiz_ref!=statistic.get_end();horiz_ref=horiz_ref->next_poly) |
|---|
| 749 | { |
|---|
| 750 | set<vertex*>::iterator vertex_ref = horiz_ref->vertices.begin(); |
|---|
| 751 | |
|---|
| 752 | do |
|---|
| 753 | { |
|---|
| 754 | vertex_ref++; |
|---|
| 755 | } |
|---|
| 756 | while((*vertex_ref)->parentconditions.find(condition)==(*vertex_ref)->parentconditions.end()); |
|---|
| 757 | |
|---|
| 758 | double product = (*vertex_ref)->get_coordinates()*condition->value; |
|---|
| 759 | |
|---|
| 760 | if(should_be_added) |
|---|
| 761 | { |
|---|
| 762 | ((toprow*) horiz_ref)->condition_order++; |
|---|
| 763 | |
|---|
| 764 | if(product>0) |
|---|
| 765 | { |
|---|
| 766 | ((toprow*) horiz_ref)->condition_sum += condition->value; |
|---|
| 767 | } |
|---|
| 768 | else |
|---|
| 769 | { |
|---|
| 770 | ((toprow*) horiz_ref)->condition_sum -= condition->value; |
|---|
| 771 | } |
|---|
| 772 | } |
|---|
| 773 | else |
|---|
| 774 | { |
|---|
| 775 | ((toprow*) horiz_ref)->condition_order--; |
|---|
| 776 | |
|---|
| 777 | if(product<0) |
|---|
| 778 | { |
|---|
| 779 | ((toprow*) horiz_ref)->condition_sum += condition->value; |
|---|
| 780 | } |
|---|
| 781 | else |
|---|
| 782 | { |
|---|
| 783 | ((toprow*) horiz_ref)->condition_sum -= condition->value; |
|---|
| 784 | } |
|---|
| 785 | } |
|---|
| 786 | } |
|---|
| 787 | } |
|---|
| 788 | |
|---|
| 789 | |
|---|
| 790 | |
|---|
| 791 | void send_state_message(polyhedron* sender, condition *toadd, condition *toremove, int level) |
|---|
| 792 | { |
|---|
| 793 | |
|---|
| 794 | bool shouldmerge = (toremove != NULL); |
|---|
| 795 | bool shouldsplit = (toadd != NULL); |
|---|
| 796 | |
|---|
| 797 | if(shouldsplit||shouldmerge) |
|---|
| 798 | { |
|---|
| 799 | for(list<polyhedron*>::iterator parent_iterator = sender->parents.begin();parent_iterator!=sender->parents.end();parent_iterator++) |
|---|
| 800 | { |
|---|
| 801 | polyhedron* current_parent = *parent_iterator; |
|---|
| 802 | |
|---|
| 803 | current_parent->message_counter++; |
|---|
| 804 | |
|---|
| 805 | bool is_last = (current_parent->message_counter == current_parent->number_of_children()); |
|---|
| 806 | bool is_first = (current_parent->message_counter == 1); |
|---|
| 807 | |
|---|
| 808 | bool out_of_the_game = true; |
|---|
| 809 | |
|---|
| 810 | if(shouldmerge) |
|---|
| 811 | { |
|---|
| 812 | int child_state = sender->get_state(MERGE); |
|---|
| 813 | int parent_state = current_parent->get_state(MERGE); |
|---|
| 814 | |
|---|
| 815 | if(parent_state == 0||is_first) |
|---|
| 816 | { |
|---|
| 817 | parent_state = current_parent->set_state(child_state, MERGE); |
|---|
| 818 | } |
|---|
| 819 | |
|---|
| 820 | if(child_state == 0) |
|---|
| 821 | { |
|---|
| 822 | if(current_parent->mergechild == NULL) |
|---|
| 823 | { |
|---|
| 824 | current_parent->mergechild = sender; |
|---|
| 825 | } |
|---|
| 826 | } |
|---|
| 827 | |
|---|
| 828 | if(is_last) |
|---|
| 829 | { |
|---|
| 830 | if(level == number_of_parameters-1) |
|---|
| 831 | { |
|---|
| 832 | if(parent_state == 1) |
|---|
| 833 | { |
|---|
| 834 | ((toprow*)current_parent)->condition_sum-=toremove->value; |
|---|
| 835 | } |
|---|
| 836 | |
|---|
| 837 | if(parent_state == -1) |
|---|
| 838 | { |
|---|
| 839 | ((toprow*)current_parent)->condition_sum+=toremove->value; |
|---|
| 840 | } |
|---|
| 841 | } |
|---|
| 842 | |
|---|
| 843 | ((toprow*)current_parent)->condition_order--; |
|---|
| 844 | |
|---|
| 845 | |
|---|
| 846 | if(current_parent->mergechild != NULL) |
|---|
| 847 | { |
|---|
| 848 | out_of_the_game = false; |
|---|
| 849 | |
|---|
| 850 | if(current_parent->mergechild->get_multiplicity()==1) |
|---|
| 851 | { |
|---|
| 852 | if(parent_state > 0) |
|---|
| 853 | { |
|---|
| 854 | current_parent->mergechild->positiveparent = current_parent; |
|---|
| 855 | } |
|---|
| 856 | |
|---|
| 857 | if(parent_state < 0) |
|---|
| 858 | { |
|---|
| 859 | current_parent->mergechild->negativeparent = current_parent; |
|---|
| 860 | } |
|---|
| 861 | } |
|---|
| 862 | else |
|---|
| 863 | { |
|---|
| 864 | out_of_the_game = true; |
|---|
| 865 | } |
|---|
| 866 | } |
|---|
| 867 | |
|---|
| 868 | if(out_of_the_game) |
|---|
| 869 | { |
|---|
| 870 | //current_parent->set_state(0,MERGE); |
|---|
| 871 | |
|---|
| 872 | if((level == number_of_parameters - 1) && (!shouldsplit)) |
|---|
| 873 | { |
|---|
| 874 | toprow* cur_par_toprow = ((toprow*)current_parent); |
|---|
| 875 | cur_par_toprow->probability = 0.0; |
|---|
| 876 | |
|---|
| 877 | //set<simplex*> new_triangulation; |
|---|
| 878 | |
|---|
| 879 | for(set<simplex*>::iterator s_ref = current_parent->triangulation.begin();s_ref!=current_parent->triangulation.end();s_ref++) |
|---|
| 880 | { |
|---|
| 881 | double cur_prob = cur_par_toprow->integrate_simplex((*s_ref),'C'); |
|---|
| 882 | |
|---|
| 883 | cur_par_toprow->probability += cur_prob; |
|---|
| 884 | |
|---|
| 885 | //new_triangulation.insert(pair<double,set<vertex*>>(cur_prob,(*t_ref).second)); |
|---|
| 886 | } |
|---|
| 887 | |
|---|
| 888 | normalization_factor += cur_par_toprow->probability; |
|---|
| 889 | |
|---|
| 890 | //current_parent->triangulation.clear(); |
|---|
| 891 | //current_parent->triangulation.insert(new_triangulation.begin(),new_triangulation.end()); |
|---|
| 892 | } |
|---|
| 893 | } |
|---|
| 894 | |
|---|
| 895 | if(parent_state == 0) |
|---|
| 896 | { |
|---|
| 897 | for_merging[level+1].push_back(current_parent); |
|---|
| 898 | //current_parent->parentconditions.erase(toremove); |
|---|
| 899 | } |
|---|
| 900 | |
|---|
| 901 | |
|---|
| 902 | } |
|---|
| 903 | } |
|---|
| 904 | |
|---|
| 905 | if(shouldsplit) |
|---|
| 906 | { |
|---|
| 907 | current_parent->totallyneutralgrandchildren.insert(sender->totallyneutralchildren.begin(),sender->totallyneutralchildren.end()); |
|---|
| 908 | |
|---|
| 909 | for(set<polyhedron*>::iterator tot_child_ref = sender->totallyneutralchildren.begin();tot_child_ref!=sender->totallyneutralchildren.end();tot_child_ref++) |
|---|
| 910 | { |
|---|
| 911 | (*tot_child_ref)->grandparents.insert(current_parent); |
|---|
| 912 | } |
|---|
| 913 | |
|---|
| 914 | if(current_parent->totally_neutral == NULL) |
|---|
| 915 | { |
|---|
| 916 | current_parent->totally_neutral = sender->totally_neutral; |
|---|
| 917 | } |
|---|
| 918 | else |
|---|
| 919 | { |
|---|
| 920 | current_parent->totally_neutral = current_parent->totally_neutral && sender->totally_neutral; |
|---|
| 921 | } |
|---|
| 922 | |
|---|
| 923 | switch(sender->get_state(SPLIT)) |
|---|
| 924 | { |
|---|
| 925 | case 1: |
|---|
| 926 | current_parent->positivechildren.push_back(sender); |
|---|
| 927 | current_parent->positiveneutralvertices.insert(sender->vertices.begin(),sender->vertices.end()); |
|---|
| 928 | break; |
|---|
| 929 | case 0: |
|---|
| 930 | current_parent->neutralchildren.push_back(sender); |
|---|
| 931 | |
|---|
| 932 | if(level!=0) |
|---|
| 933 | { |
|---|
| 934 | current_parent->positiveneutralvertices.insert(sender->positiveneutralvertices.begin(),sender->positiveneutralvertices.end()); |
|---|
| 935 | current_parent->negativeneutralvertices.insert(sender->negativeneutralvertices.begin(),sender->negativeneutralvertices.end()); |
|---|
| 936 | } |
|---|
| 937 | else |
|---|
| 938 | { |
|---|
| 939 | current_parent->positiveneutralvertices.insert(*sender->vertices.begin()); |
|---|
| 940 | current_parent->negativeneutralvertices.insert(*sender->vertices.begin()); |
|---|
| 941 | } |
|---|
| 942 | |
|---|
| 943 | if(sender->totally_neutral) |
|---|
| 944 | { |
|---|
| 945 | current_parent->totallyneutralchildren.insert(sender); |
|---|
| 946 | } |
|---|
| 947 | |
|---|
| 948 | break; |
|---|
| 949 | case -1: |
|---|
| 950 | current_parent->negativechildren.push_back(sender); |
|---|
| 951 | current_parent->negativeneutralvertices.insert(sender->vertices.begin(),sender->vertices.end()); |
|---|
| 952 | break; |
|---|
| 953 | } |
|---|
| 954 | |
|---|
| 955 | if(is_last) |
|---|
| 956 | { |
|---|
| 957 | |
|---|
| 958 | if((current_parent->negativechildren.size()>0&¤t_parent->positivechildren.size()>0) |
|---|
| 959 | ||(current_parent->neutralchildren.size()>0&¤t_parent->totallyneutralchildren.empty())) |
|---|
| 960 | { |
|---|
| 961 | for_splitting[level+1].push_back(current_parent); |
|---|
| 962 | |
|---|
| 963 | current_parent->set_state(0, SPLIT); |
|---|
| 964 | } |
|---|
| 965 | else |
|---|
| 966 | { |
|---|
| 967 | if(current_parent->negativechildren.size()>0) |
|---|
| 968 | { |
|---|
| 969 | current_parent->set_state(-1, SPLIT); |
|---|
| 970 | |
|---|
| 971 | if(level == number_of_parameters-1) |
|---|
| 972 | { |
|---|
| 973 | ((toprow*)current_parent)->condition_sum-=toadd->value; |
|---|
| 974 | } |
|---|
| 975 | |
|---|
| 976 | } |
|---|
| 977 | else if(current_parent->positivechildren.size()>0) |
|---|
| 978 | { |
|---|
| 979 | current_parent->set_state(1, SPLIT); |
|---|
| 980 | |
|---|
| 981 | if(level == number_of_parameters-1) |
|---|
| 982 | { |
|---|
| 983 | ((toprow*)current_parent)->condition_sum+=toadd->value; |
|---|
| 984 | } |
|---|
| 985 | } |
|---|
| 986 | else |
|---|
| 987 | { |
|---|
| 988 | current_parent->raise_multiplicity(); |
|---|
| 989 | current_parent->totally_neutral = true; |
|---|
| 990 | current_parent->parentconditions.insert(toadd); |
|---|
| 991 | } |
|---|
| 992 | |
|---|
| 993 | ((toprow*)current_parent)->condition_order++; |
|---|
| 994 | |
|---|
| 995 | if(level == number_of_parameters - 1 && current_parent->mergechild == NULL) |
|---|
| 996 | { |
|---|
| 997 | toprow* cur_par_toprow = ((toprow*)current_parent); |
|---|
| 998 | cur_par_toprow->probability = 0.0; |
|---|
| 999 | |
|---|
| 1000 | //map<double,set<vertex*>> new_triangulation; |
|---|
| 1001 | |
|---|
| 1002 | for(set<simplex*>::iterator s_ref = current_parent->triangulation.begin();s_ref!=current_parent->triangulation.end();s_ref++) |
|---|
| 1003 | { |
|---|
| 1004 | double cur_prob = cur_par_toprow->integrate_simplex((*s_ref),'C'); |
|---|
| 1005 | |
|---|
| 1006 | cur_par_toprow->probability += cur_prob; |
|---|
| 1007 | |
|---|
| 1008 | //new_triangulation.insert(pair<double,set<vertex*>>(cur_prob,(*t_ref).second)); |
|---|
| 1009 | } |
|---|
| 1010 | |
|---|
| 1011 | normalization_factor += cur_par_toprow->probability; |
|---|
| 1012 | |
|---|
| 1013 | //current_parent->triangulation.clear(); |
|---|
| 1014 | //current_parent->triangulation.insert(new_triangulation.begin(),new_triangulation.end()); |
|---|
| 1015 | } |
|---|
| 1016 | |
|---|
| 1017 | if(out_of_the_game) |
|---|
| 1018 | { |
|---|
| 1019 | current_parent->positivechildren.clear(); |
|---|
| 1020 | current_parent->negativechildren.clear(); |
|---|
| 1021 | current_parent->neutralchildren.clear(); |
|---|
| 1022 | //current_parent->totallyneutralchildren.clear(); |
|---|
| 1023 | current_parent->totallyneutralgrandchildren.clear(); |
|---|
| 1024 | // current_parent->grandparents.clear(); |
|---|
| 1025 | current_parent->positiveneutralvertices.clear(); |
|---|
| 1026 | current_parent->negativeneutralvertices.clear(); |
|---|
| 1027 | current_parent->totally_neutral = NULL; |
|---|
| 1028 | current_parent->kids_rel_addresses.clear(); |
|---|
| 1029 | } |
|---|
| 1030 | } |
|---|
| 1031 | } |
|---|
| 1032 | } |
|---|
| 1033 | |
|---|
| 1034 | if(is_last) |
|---|
| 1035 | { |
|---|
| 1036 | current_parent->mergechild = NULL; |
|---|
| 1037 | current_parent->message_counter = 0; |
|---|
| 1038 | |
|---|
| 1039 | send_state_message(current_parent,toadd,toremove,level+1); |
|---|
| 1040 | } |
|---|
| 1041 | |
|---|
| 1042 | } |
|---|
| 1043 | |
|---|
| 1044 | sender->totallyneutralchildren.clear(); |
|---|
| 1045 | } |
|---|
| 1046 | } |
|---|
| 1047 | |
|---|
| 1048 | public: |
|---|
| 1049 | c_statistic statistic; |
|---|
| 1050 | |
|---|
| 1051 | vertex* minimal_vertex; |
|---|
| 1052 | |
|---|
| 1053 | double min_ll; |
|---|
| 1054 | |
|---|
| 1055 | double log_nc; |
|---|
| 1056 | |
|---|
| 1057 | |
|---|
| 1058 | |
|---|
| 1059 | vector<multiset<my_ivec>> correction_factors; |
|---|
| 1060 | |
|---|
| 1061 | int number_of_parameters; |
|---|
| 1062 | |
|---|
| 1063 | /// A default constructor creates an emlig with predefined statistic representing only the range of the given |
|---|
| 1064 | /// parametric space, where the number of parameters of the needed model is given as a parameter to the constructor. |
|---|
| 1065 | emlig(int number_of_parameters, bool is_proper, double soft_prior_parameter) |
|---|
| 1066 | { |
|---|
| 1067 | this->number_of_parameters = number_of_parameters; |
|---|
| 1068 | |
|---|
| 1069 | condition_order = number_of_parameters+2; |
|---|
| 1070 | |
|---|
| 1071 | if(is_proper) |
|---|
| 1072 | condition_order++; |
|---|
| 1073 | |
|---|
| 1074 | create_statistic(number_of_parameters, soft_prior_parameter); |
|---|
| 1075 | |
|---|
| 1076 | //step_me(10); |
|---|
| 1077 | |
|---|
| 1078 | min_ll = numeric_limits<double>::max(); |
|---|
| 1079 | |
|---|
| 1080 | if(is_proper) |
|---|
| 1081 | { |
|---|
| 1082 | double normalization_factor = 0; |
|---|
| 1083 | int counter = 0; |
|---|
| 1084 | for(polyhedron* top_ref = statistic.rows[number_of_parameters];top_ref!=statistic.get_end();top_ref=top_ref->next_poly) |
|---|
| 1085 | { |
|---|
| 1086 | counter++; |
|---|
| 1087 | toprow* cur_toprow = (toprow*)top_ref; |
|---|
| 1088 | |
|---|
| 1089 | set<simplex*>::iterator cur_simplex = cur_toprow->triangulation.begin(); |
|---|
| 1090 | normalization_factor += cur_toprow->integrate_simplex(*cur_simplex,'X'); |
|---|
| 1091 | } |
|---|
| 1092 | |
|---|
| 1093 | log_nc = log(normalization_factor) + logfact(condition_order-number_of_parameters-2); |
|---|
| 1094 | |
|---|
| 1095 | /* |
|---|
| 1096 | cout << "part1: " << log(normalization_factor) << endl; |
|---|
| 1097 | cout << "part2: " << logfact(condition_order-number_of_parameters-2) << endl; |
|---|
| 1098 | pause(1); |
|---|
| 1099 | */ |
|---|
| 1100 | } |
|---|
| 1101 | |
|---|
| 1102 | } |
|---|
| 1103 | |
|---|
| 1104 | /// A constructor for creating an emlig when the user wants to create the statistic by himself. The creation of a |
|---|
| 1105 | /// statistic is needed outside the constructor. Used for a user defined prior distribution on the parameters. |
|---|
| 1106 | emlig(c_statistic statistic, int condition_order) |
|---|
| 1107 | { |
|---|
| 1108 | this->statistic = statistic; |
|---|
| 1109 | |
|---|
| 1110 | min_ll = numeric_limits<double>::max(); |
|---|
| 1111 | |
|---|
| 1112 | this->condition_order = condition_order; |
|---|
| 1113 | } |
|---|
| 1114 | |
|---|
| 1115 | |
|---|
| 1116 | void step_me(int marker) |
|---|
| 1117 | { |
|---|
| 1118 | |
|---|
| 1119 | for(int i = 0;i<statistic.size();i++) |
|---|
| 1120 | { |
|---|
| 1121 | //int zero = 0; |
|---|
| 1122 | //int one = 0; |
|---|
| 1123 | //int two = 0; |
|---|
| 1124 | |
|---|
| 1125 | for(polyhedron* horiz_ref = statistic.rows[i];horiz_ref!=statistic.get_end();horiz_ref=horiz_ref->next_poly) |
|---|
| 1126 | { |
|---|
| 1127 | |
|---|
| 1128 | |
|---|
| 1129 | if(i==statistic.size()-1) |
|---|
| 1130 | { |
|---|
| 1131 | cout << ((toprow*)horiz_ref)->condition_sum << " " << ((toprow*)horiz_ref)->probability << endl; |
|---|
| 1132 | cout << "Condition: " << ((toprow*)horiz_ref)->condition_sum << endl; |
|---|
| 1133 | cout << "Order:" << ((toprow*)horiz_ref)->condition_order << endl; |
|---|
| 1134 | } |
|---|
| 1135 | |
|---|
| 1136 | |
|---|
| 1137 | // cout << "Stepped." << endl; |
|---|
| 1138 | |
|---|
| 1139 | if(marker==101) |
|---|
| 1140 | { |
|---|
| 1141 | if(!(*horiz_ref).negativechildren.empty()||!(*horiz_ref).positivechildren.empty()||!(*horiz_ref).neutralchildren.empty()||!(*horiz_ref).kids_rel_addresses.empty()||!(*horiz_ref).mergechild==NULL||!(*horiz_ref).negativeneutralvertices.empty()) |
|---|
| 1142 | { |
|---|
| 1143 | cout << "Cleaning error!" << endl; |
|---|
| 1144 | } |
|---|
| 1145 | |
|---|
| 1146 | } |
|---|
| 1147 | |
|---|
| 1148 | for(set<simplex*>::iterator sim_ref = (*horiz_ref).triangulation.begin();sim_ref!=(*horiz_ref).triangulation.end();sim_ref++) |
|---|
| 1149 | { |
|---|
| 1150 | if((*sim_ref)->vertices.size()!=i+1) |
|---|
| 1151 | { |
|---|
| 1152 | cout << "Something is wrong." << endl; |
|---|
| 1153 | } |
|---|
| 1154 | } |
|---|
| 1155 | |
|---|
| 1156 | /* |
|---|
| 1157 | if(i==0) |
|---|
| 1158 | { |
|---|
| 1159 | cout << ((vertex*)horiz_ref)->get_coordinates() << endl; |
|---|
| 1160 | } |
|---|
| 1161 | */ |
|---|
| 1162 | |
|---|
| 1163 | /* |
|---|
| 1164 | char* string = "Checkpoint"; |
|---|
| 1165 | |
|---|
| 1166 | |
|---|
| 1167 | if((*horiz_ref).parentconditions.size()==0) |
|---|
| 1168 | { |
|---|
| 1169 | zero++; |
|---|
| 1170 | } |
|---|
| 1171 | else if((*horiz_ref).parentconditions.size()==1) |
|---|
| 1172 | { |
|---|
| 1173 | one++; |
|---|
| 1174 | } |
|---|
| 1175 | else |
|---|
| 1176 | { |
|---|
| 1177 | two++; |
|---|
| 1178 | } |
|---|
| 1179 | */ |
|---|
| 1180 | |
|---|
| 1181 | } |
|---|
| 1182 | } |
|---|
| 1183 | |
|---|
| 1184 | |
|---|
| 1185 | /* |
|---|
| 1186 | list<vec> table_entries; |
|---|
| 1187 | for(polyhedron* horiz_ref = statistic.rows[statistic.size()-1];horiz_ref!=statistic.row_ends[statistic.size()-1];horiz_ref=horiz_ref->next_poly) |
|---|
| 1188 | { |
|---|
| 1189 | toprow *current_toprow = (toprow*)(horiz_ref); |
|---|
| 1190 | for(list<set<vertex*>>::iterator tri_ref = current_toprow->triangulation.begin();tri_ref!=current_toprow->triangulation.end();tri_ref++) |
|---|
| 1191 | { |
|---|
| 1192 | for(set<vertex*>::iterator vert_ref = (*tri_ref).begin();vert_ref!=(*tri_ref).end();vert_ref++) |
|---|
| 1193 | { |
|---|
| 1194 | vec table_entry = vec(); |
|---|
| 1195 | |
|---|
| 1196 | table_entry.ins(0,(*vert_ref)->get_coordinates()*current_toprow->condition.get(1,current_toprow->condition.size()-1)-current_toprow->condition.get(0,0)); |
|---|
| 1197 | |
|---|
| 1198 | table_entry.ins(0,(*vert_ref)->get_coordinates()); |
|---|
| 1199 | |
|---|
| 1200 | table_entries.push_back(table_entry); |
|---|
| 1201 | } |
|---|
| 1202 | } |
|---|
| 1203 | } |
|---|
| 1204 | |
|---|
| 1205 | unique(table_entries.begin(),table_entries.end()); |
|---|
| 1206 | |
|---|
| 1207 | |
|---|
| 1208 | |
|---|
| 1209 | for(list<vec>::iterator entry_ref = table_entries.begin();entry_ref!=table_entries.end();entry_ref++) |
|---|
| 1210 | { |
|---|
| 1211 | ofstream myfile; |
|---|
| 1212 | myfile.open("robust_data.txt", ios::out | ios::app); |
|---|
| 1213 | if (myfile.is_open()) |
|---|
| 1214 | { |
|---|
| 1215 | for(int i = 0;i<(*entry_ref).size();i++) |
|---|
| 1216 | { |
|---|
| 1217 | myfile << (*entry_ref)[i] << ";"; |
|---|
| 1218 | } |
|---|
| 1219 | myfile << endl; |
|---|
| 1220 | |
|---|
| 1221 | myfile.close(); |
|---|
| 1222 | } |
|---|
| 1223 | else |
|---|
| 1224 | { |
|---|
| 1225 | cout << "File problem." << endl; |
|---|
| 1226 | } |
|---|
| 1227 | } |
|---|
| 1228 | */ |
|---|
| 1229 | |
|---|
| 1230 | |
|---|
| 1231 | return; |
|---|
| 1232 | } |
|---|
| 1233 | |
|---|
| 1234 | int statistic_rowsize(int row) |
|---|
| 1235 | { |
|---|
| 1236 | return statistic.row_size(row); |
|---|
| 1237 | } |
|---|
| 1238 | |
|---|
| 1239 | void add_condition(vec toadd) |
|---|
| 1240 | { |
|---|
| 1241 | vec null_vector = ""; |
|---|
| 1242 | |
|---|
| 1243 | add_and_remove_condition(toadd, null_vector); |
|---|
| 1244 | } |
|---|
| 1245 | |
|---|
| 1246 | |
|---|
| 1247 | void remove_condition(vec toremove) |
|---|
| 1248 | { |
|---|
| 1249 | vec null_vector = ""; |
|---|
| 1250 | |
|---|
| 1251 | add_and_remove_condition(null_vector, toremove); |
|---|
| 1252 | } |
|---|
| 1253 | |
|---|
| 1254 | void add_and_remove_condition(vec toadd, vec toremove) |
|---|
| 1255 | { |
|---|
| 1256 | |
|---|
| 1257 | //step_me(0); |
|---|
| 1258 | normalization_factor = 0; |
|---|
| 1259 | min_ll = numeric_limits<double>::max(); |
|---|
| 1260 | |
|---|
| 1261 | bool should_remove = (toremove.size() != 0); |
|---|
| 1262 | bool should_add = (toadd.size() != 0); |
|---|
| 1263 | |
|---|
| 1264 | if(should_remove) |
|---|
| 1265 | { |
|---|
| 1266 | condition_order--; |
|---|
| 1267 | } |
|---|
| 1268 | |
|---|
| 1269 | if(should_add) |
|---|
| 1270 | { |
|---|
| 1271 | condition_order++; |
|---|
| 1272 | } |
|---|
| 1273 | |
|---|
| 1274 | for_splitting.clear(); |
|---|
| 1275 | for_merging.clear(); |
|---|
| 1276 | |
|---|
| 1277 | for(int i = 0;i<statistic.size();i++) |
|---|
| 1278 | { |
|---|
| 1279 | list<polyhedron*> empty_split; |
|---|
| 1280 | list<polyhedron*> empty_merge; |
|---|
| 1281 | |
|---|
| 1282 | for_splitting.push_back(empty_split); |
|---|
| 1283 | for_merging.push_back(empty_merge); |
|---|
| 1284 | } |
|---|
| 1285 | |
|---|
| 1286 | list<condition*>::iterator toremove_ref = conditions.end(); |
|---|
| 1287 | bool condition_should_be_added = should_add; |
|---|
| 1288 | |
|---|
| 1289 | for(list<condition*>::iterator ref = conditions.begin();ref!=conditions.end();ref++) |
|---|
| 1290 | { |
|---|
| 1291 | if(should_remove) |
|---|
| 1292 | { |
|---|
| 1293 | if((*ref)->value == toremove) |
|---|
| 1294 | { |
|---|
| 1295 | if((*ref)->multiplicity>1) |
|---|
| 1296 | { |
|---|
| 1297 | (*ref)->multiplicity--; |
|---|
| 1298 | |
|---|
| 1299 | alter_toprow_conditions(*ref,false); |
|---|
| 1300 | |
|---|
| 1301 | should_remove = false; |
|---|
| 1302 | } |
|---|
| 1303 | else |
|---|
| 1304 | { |
|---|
| 1305 | toremove_ref = ref; |
|---|
| 1306 | } |
|---|
| 1307 | } |
|---|
| 1308 | } |
|---|
| 1309 | |
|---|
| 1310 | if(should_add) |
|---|
| 1311 | { |
|---|
| 1312 | if((*ref)->value == toadd) |
|---|
| 1313 | { |
|---|
| 1314 | (*ref)->multiplicity++; |
|---|
| 1315 | |
|---|
| 1316 | alter_toprow_conditions(*ref,true); |
|---|
| 1317 | |
|---|
| 1318 | should_add = false; |
|---|
| 1319 | |
|---|
| 1320 | condition_should_be_added = false; |
|---|
| 1321 | } |
|---|
| 1322 | } |
|---|
| 1323 | } |
|---|
| 1324 | |
|---|
| 1325 | condition* condition_to_remove = NULL; |
|---|
| 1326 | |
|---|
| 1327 | if(toremove_ref!=conditions.end()) |
|---|
| 1328 | { |
|---|
| 1329 | condition_to_remove = *toremove_ref; |
|---|
| 1330 | conditions.erase(toremove_ref); |
|---|
| 1331 | } |
|---|
| 1332 | |
|---|
| 1333 | condition* condition_to_add = NULL; |
|---|
| 1334 | |
|---|
| 1335 | if(condition_should_be_added) |
|---|
| 1336 | { |
|---|
| 1337 | condition* new_condition = new condition(toadd); |
|---|
| 1338 | |
|---|
| 1339 | conditions.push_back(new_condition); |
|---|
| 1340 | condition_to_add = new_condition; |
|---|
| 1341 | } |
|---|
| 1342 | |
|---|
| 1343 | for(polyhedron* horizontal_position = statistic.rows[0];horizontal_position!=statistic.get_end();horizontal_position=horizontal_position->next_poly) |
|---|
| 1344 | { |
|---|
| 1345 | vertex* current_vertex = (vertex*)horizontal_position; |
|---|
| 1346 | |
|---|
| 1347 | if(should_add||should_remove) |
|---|
| 1348 | { |
|---|
| 1349 | vec appended_coords = current_vertex->get_coordinates(); |
|---|
| 1350 | appended_coords.ins(0,-1.0); |
|---|
| 1351 | |
|---|
| 1352 | if(should_add) |
|---|
| 1353 | { |
|---|
| 1354 | double local_condition = 0;// = toadd*(appended_coords.first/=appended_coords.second); |
|---|
| 1355 | |
|---|
| 1356 | local_condition = appended_coords*toadd; |
|---|
| 1357 | |
|---|
| 1358 | // cout << "Vertex multiplicity: "<< current_vertex->get_multiplicity() << endl; |
|---|
| 1359 | |
|---|
| 1360 | current_vertex->set_state(local_condition,SPLIT); |
|---|
| 1361 | |
|---|
| 1362 | /// \TODO There should be a rounding error tolerance used here to insure we are not having too many points because of rounding error. |
|---|
| 1363 | if(local_condition == 0) |
|---|
| 1364 | { |
|---|
| 1365 | cout << "Condition to add: " << toadd << endl; |
|---|
| 1366 | cout << "Vertex coords: " << appended_coords << endl; |
|---|
| 1367 | |
|---|
| 1368 | current_vertex->totally_neutral = true; |
|---|
| 1369 | |
|---|
| 1370 | current_vertex->raise_multiplicity(); |
|---|
| 1371 | current_vertex->parentconditions.insert(condition_to_add); |
|---|
| 1372 | } |
|---|
| 1373 | else |
|---|
| 1374 | { |
|---|
| 1375 | current_vertex->totally_neutral = false; |
|---|
| 1376 | } |
|---|
| 1377 | } |
|---|
| 1378 | |
|---|
| 1379 | if(should_remove) |
|---|
| 1380 | { |
|---|
| 1381 | set<condition*>::iterator cond_ref; |
|---|
| 1382 | |
|---|
| 1383 | for(cond_ref = current_vertex->parentconditions.begin();cond_ref!=current_vertex->parentconditions.end();cond_ref++) |
|---|
| 1384 | { |
|---|
| 1385 | if(*cond_ref == condition_to_remove) |
|---|
| 1386 | { |
|---|
| 1387 | break; |
|---|
| 1388 | } |
|---|
| 1389 | } |
|---|
| 1390 | |
|---|
| 1391 | if(cond_ref!=current_vertex->parentconditions.end()) |
|---|
| 1392 | { |
|---|
| 1393 | current_vertex->parentconditions.erase(cond_ref); |
|---|
| 1394 | current_vertex->set_state(0,MERGE); |
|---|
| 1395 | for_merging[0].push_back(current_vertex); |
|---|
| 1396 | } |
|---|
| 1397 | else |
|---|
| 1398 | { |
|---|
| 1399 | double local_condition = toremove*appended_coords; |
|---|
| 1400 | current_vertex->set_state(local_condition,MERGE); |
|---|
| 1401 | } |
|---|
| 1402 | } |
|---|
| 1403 | } |
|---|
| 1404 | |
|---|
| 1405 | send_state_message(current_vertex, condition_to_add, condition_to_remove, 0); |
|---|
| 1406 | |
|---|
| 1407 | } |
|---|
| 1408 | |
|---|
| 1409 | // step_me(1); |
|---|
| 1410 | |
|---|
| 1411 | if(should_remove) |
|---|
| 1412 | { |
|---|
| 1413 | /* |
|---|
| 1414 | for(int i = 0;i<for_merging.size();i++) |
|---|
| 1415 | { |
|---|
| 1416 | for(list<polyhedron*>::iterator merge_ref = for_merging[i].begin();merge_ref!=for_merging[i].end();merge_ref++) |
|---|
| 1417 | { |
|---|
| 1418 | |
|---|
| 1419 | for(list<polyhedron*>::iterator par_ref = (*merge_ref)->children.begin();par_ref!=(*merge_ref)->children.end();par_ref++) |
|---|
| 1420 | { |
|---|
| 1421 | if(find((*par_ref)->parents.begin(),(*par_ref)->parents.end(),(*merge_ref))==(*par_ref)->parents.end()) |
|---|
| 1422 | { |
|---|
| 1423 | cout << "Parent/child relations are not matched!" << endl; |
|---|
| 1424 | } |
|---|
| 1425 | } |
|---|
| 1426 | |
|---|
| 1427 | //cout << (*merge_ref)->get_state(MERGE) << ","; |
|---|
| 1428 | } |
|---|
| 1429 | |
|---|
| 1430 | // cout << endl; |
|---|
| 1431 | } |
|---|
| 1432 | */ |
|---|
| 1433 | |
|---|
| 1434 | |
|---|
| 1435 | |
|---|
| 1436 | cout << "Merging." << endl; |
|---|
| 1437 | |
|---|
| 1438 | set<vertex*> vertices_to_be_reduced; |
|---|
| 1439 | |
|---|
| 1440 | int k = 1; |
|---|
| 1441 | |
|---|
| 1442 | for(vector<list<polyhedron*>>::iterator vert_ref = for_merging.begin();vert_ref<for_merging.end();vert_ref++) |
|---|
| 1443 | { |
|---|
| 1444 | for(list<polyhedron*>::reverse_iterator merge_ref = vert_ref->rbegin();merge_ref!=vert_ref->rend();merge_ref++) |
|---|
| 1445 | { |
|---|
| 1446 | if((*merge_ref)->get_multiplicity()>1) |
|---|
| 1447 | { |
|---|
| 1448 | (*merge_ref)->parentconditions.erase(condition_to_remove); |
|---|
| 1449 | |
|---|
| 1450 | if(k==1) |
|---|
| 1451 | { |
|---|
| 1452 | vertices_to_be_reduced.insert((vertex*)(*merge_ref)); |
|---|
| 1453 | } |
|---|
| 1454 | else |
|---|
| 1455 | { |
|---|
| 1456 | (*merge_ref)->lower_multiplicity(); |
|---|
| 1457 | } |
|---|
| 1458 | |
|---|
| 1459 | if((*merge_ref)->get_state(SPLIT)!=0||(*merge_ref)->totally_neutral) |
|---|
| 1460 | { |
|---|
| 1461 | (*merge_ref)->positivechildren.clear(); |
|---|
| 1462 | (*merge_ref)->negativechildren.clear(); |
|---|
| 1463 | (*merge_ref)->neutralchildren.clear(); |
|---|
| 1464 | (*merge_ref)->totallyneutralgrandchildren.clear(); |
|---|
| 1465 | (*merge_ref)->positiveneutralvertices.clear(); |
|---|
| 1466 | (*merge_ref)->negativeneutralvertices.clear(); |
|---|
| 1467 | (*merge_ref)->totally_neutral = NULL; |
|---|
| 1468 | (*merge_ref)->kids_rel_addresses.clear(); |
|---|
| 1469 | } |
|---|
| 1470 | } |
|---|
| 1471 | else |
|---|
| 1472 | { |
|---|
| 1473 | bool will_be_split = false; |
|---|
| 1474 | |
|---|
| 1475 | toprow* current_positive = (toprow*)(*merge_ref)->positiveparent; |
|---|
| 1476 | toprow* current_negative = (toprow*)(*merge_ref)->negativeparent; |
|---|
| 1477 | |
|---|
| 1478 | if(current_positive->totally_neutral!=current_negative->totally_neutral) |
|---|
| 1479 | { |
|---|
| 1480 | throw new exception("Both polyhedrons must be totally neutral if they should be merged!"); |
|---|
| 1481 | } |
|---|
| 1482 | |
|---|
| 1483 | //current_positive->condition_sum -= toremove; |
|---|
| 1484 | //current_positive->condition_order--; |
|---|
| 1485 | |
|---|
| 1486 | current_positive->parentconditions.erase(condition_to_remove); |
|---|
| 1487 | |
|---|
| 1488 | current_positive->children.insert(current_positive->children.end(),current_negative->children.begin(),current_negative->children.end()); |
|---|
| 1489 | current_positive->children.remove(*merge_ref); |
|---|
| 1490 | |
|---|
| 1491 | for(list<polyhedron*>::iterator child_ref = current_negative->children.begin();child_ref!=current_negative->children.end();child_ref++) |
|---|
| 1492 | { |
|---|
| 1493 | (*child_ref)->parents.remove(current_negative); |
|---|
| 1494 | (*child_ref)->parents.push_back(current_positive); |
|---|
| 1495 | } |
|---|
| 1496 | |
|---|
| 1497 | // current_positive->parents.insert(current_positive->parents.begin(),current_negative->parents.begin(),current_negative->parents.end()); |
|---|
| 1498 | // unique(current_positive->parents.begin(),current_positive->parents.end()); |
|---|
| 1499 | |
|---|
| 1500 | for(list<polyhedron*>::iterator parent_ref = current_negative->parents.begin();parent_ref!=current_negative->parents.end();parent_ref++) |
|---|
| 1501 | { |
|---|
| 1502 | (*parent_ref)->children.remove(current_negative); |
|---|
| 1503 | |
|---|
| 1504 | switch(current_negative->get_state(SPLIT)) |
|---|
| 1505 | { |
|---|
| 1506 | case -1: |
|---|
| 1507 | (*parent_ref)->negativechildren.remove(current_negative); |
|---|
| 1508 | break; |
|---|
| 1509 | case 0: |
|---|
| 1510 | (*parent_ref)->neutralchildren.remove(current_negative); |
|---|
| 1511 | break; |
|---|
| 1512 | case 1: |
|---|
| 1513 | (*parent_ref)->positivechildren.remove(current_negative); |
|---|
| 1514 | break; |
|---|
| 1515 | } |
|---|
| 1516 | //(*parent_ref)->children.push_back(current_positive); |
|---|
| 1517 | } |
|---|
| 1518 | |
|---|
| 1519 | if(current_positive->get_state(SPLIT)!=0&¤t_negative->get_state(SPLIT)==0) |
|---|
| 1520 | { |
|---|
| 1521 | for(list<polyhedron*>::iterator parent_ref = current_positive->parents.begin();parent_ref!=current_positive->parents.end();parent_ref++) |
|---|
| 1522 | { |
|---|
| 1523 | if(current_positive->get_state(SPLIT)==1) |
|---|
| 1524 | { |
|---|
| 1525 | (*parent_ref)->positivechildren.remove(current_positive); |
|---|
| 1526 | } |
|---|
| 1527 | else |
|---|
| 1528 | { |
|---|
| 1529 | (*parent_ref)->negativechildren.remove(current_positive); |
|---|
| 1530 | } |
|---|
| 1531 | |
|---|
| 1532 | (*parent_ref)->neutralchildren.push_back(current_positive); |
|---|
| 1533 | } |
|---|
| 1534 | |
|---|
| 1535 | current_positive->set_state(0,SPLIT); |
|---|
| 1536 | for_splitting[k].push_back(current_positive); |
|---|
| 1537 | |
|---|
| 1538 | will_be_split = true; |
|---|
| 1539 | } |
|---|
| 1540 | |
|---|
| 1541 | if((current_positive->get_state(SPLIT)==0&&!current_positive->totally_neutral)||(current_negative->get_state(SPLIT)==0&&!current_negative->totally_neutral)) |
|---|
| 1542 | { |
|---|
| 1543 | current_positive->negativechildren.insert(current_positive->negativechildren.end(),current_negative->negativechildren.begin(),current_negative->negativechildren.end()); |
|---|
| 1544 | |
|---|
| 1545 | current_positive->positivechildren.insert(current_positive->positivechildren.end(),current_negative->positivechildren.begin(),current_negative->positivechildren.end()); |
|---|
| 1546 | |
|---|
| 1547 | current_positive->neutralchildren.insert(current_positive->neutralchildren.end(),current_negative->neutralchildren.begin(),current_negative->neutralchildren.end()); |
|---|
| 1548 | |
|---|
| 1549 | switch((*merge_ref)->get_state(SPLIT)) |
|---|
| 1550 | { |
|---|
| 1551 | case -1: |
|---|
| 1552 | current_positive->negativechildren.remove(*merge_ref); |
|---|
| 1553 | break; |
|---|
| 1554 | case 0: |
|---|
| 1555 | current_positive->neutralchildren.remove(*merge_ref); |
|---|
| 1556 | break; |
|---|
| 1557 | case 1: |
|---|
| 1558 | current_positive->positivechildren.remove(*merge_ref); |
|---|
| 1559 | break; |
|---|
| 1560 | } |
|---|
| 1561 | |
|---|
| 1562 | /* |
|---|
| 1563 | current_positive->totallyneutralchildren.insert(current_negative->totallyneutralchildren.begin(),current_negative->totallyneutralchildren.end()); |
|---|
| 1564 | |
|---|
| 1565 | current_positive->totallyneutralchildren.erase(*merge_ref); |
|---|
| 1566 | */ |
|---|
| 1567 | |
|---|
| 1568 | current_positive->totallyneutralgrandchildren.insert(current_negative->totallyneutralgrandchildren.begin(),current_negative->totallyneutralgrandchildren.end()); |
|---|
| 1569 | |
|---|
| 1570 | current_positive->negativeneutralvertices.insert(current_negative->negativeneutralvertices.begin(),current_negative->negativeneutralvertices.end()); |
|---|
| 1571 | current_positive->positiveneutralvertices.insert(current_negative->positiveneutralvertices.begin(),current_negative->positiveneutralvertices.end()); |
|---|
| 1572 | |
|---|
| 1573 | will_be_split = true; |
|---|
| 1574 | } |
|---|
| 1575 | else |
|---|
| 1576 | { |
|---|
| 1577 | current_positive->positivechildren.clear(); |
|---|
| 1578 | current_positive->negativechildren.clear(); |
|---|
| 1579 | current_positive->neutralchildren.clear(); |
|---|
| 1580 | // current_positive->totallyneutralchildren.clear(); |
|---|
| 1581 | current_positive->totallyneutralgrandchildren.clear(); |
|---|
| 1582 | current_positive->positiveneutralvertices.clear(); |
|---|
| 1583 | current_positive->negativeneutralvertices.clear(); |
|---|
| 1584 | current_positive->totally_neutral = NULL; |
|---|
| 1585 | current_positive->kids_rel_addresses.clear(); |
|---|
| 1586 | } |
|---|
| 1587 | |
|---|
| 1588 | current_positive->vertices.insert(current_negative->vertices.begin(),current_negative->vertices.end()); |
|---|
| 1589 | |
|---|
| 1590 | |
|---|
| 1591 | for(set<vertex*>::iterator vert_ref = (*merge_ref)->vertices.begin();vert_ref!=(*merge_ref)->vertices.end();vert_ref++) |
|---|
| 1592 | { |
|---|
| 1593 | if((*vert_ref)->get_multiplicity()==1) |
|---|
| 1594 | { |
|---|
| 1595 | current_positive->vertices.erase(*vert_ref); |
|---|
| 1596 | |
|---|
| 1597 | if(will_be_split) |
|---|
| 1598 | { |
|---|
| 1599 | current_positive->negativeneutralvertices.erase(*vert_ref); |
|---|
| 1600 | current_positive->positiveneutralvertices.erase(*vert_ref); |
|---|
| 1601 | } |
|---|
| 1602 | } |
|---|
| 1603 | } |
|---|
| 1604 | |
|---|
| 1605 | if(current_negative->get_state(SPLIT)==0&&!current_negative->totally_neutral) |
|---|
| 1606 | { |
|---|
| 1607 | for_splitting[k].remove(current_negative); |
|---|
| 1608 | } |
|---|
| 1609 | |
|---|
| 1610 | |
|---|
| 1611 | |
|---|
| 1612 | if(current_positive->totally_neutral) |
|---|
| 1613 | { |
|---|
| 1614 | for(set<polyhedron*>::iterator grand_ref = current_negative->grandparents.begin();grand_ref!=current_negative->grandparents.end();grand_ref++) |
|---|
| 1615 | { |
|---|
| 1616 | (*grand_ref)->totallyneutralgrandchildren.erase(current_negative); |
|---|
| 1617 | (*grand_ref)->totallyneutralgrandchildren.insert(current_positive); |
|---|
| 1618 | } |
|---|
| 1619 | } |
|---|
| 1620 | |
|---|
| 1621 | current_positive->grandparents.clear(); |
|---|
| 1622 | |
|---|
| 1623 | normalization_factor += current_positive->triangulate(k==for_splitting.size()-1 && !will_be_split); |
|---|
| 1624 | |
|---|
| 1625 | statistic.delete_polyhedron(k,current_negative); |
|---|
| 1626 | |
|---|
| 1627 | delete current_negative; |
|---|
| 1628 | |
|---|
| 1629 | for(list<polyhedron*>::iterator child_ref = (*merge_ref)->children.begin();child_ref!=(*merge_ref)->children.end();child_ref++) |
|---|
| 1630 | { |
|---|
| 1631 | (*child_ref)->parents.remove(*merge_ref); |
|---|
| 1632 | } |
|---|
| 1633 | |
|---|
| 1634 | /* |
|---|
| 1635 | for(list<polyhedron*>::iterator parent_ref = (*merge_ref)->parents.begin();parent_ref!=(*merge_ref)->parents.end();parent_ref++) |
|---|
| 1636 | { |
|---|
| 1637 | (*parent_ref)->positivechildren.remove(*merge_ref); |
|---|
| 1638 | (*parent_ref)->negativechildren.remove(*merge_ref); |
|---|
| 1639 | (*parent_ref)->neutralchildren.remove(*merge_ref); |
|---|
| 1640 | (*parent_ref)->children.remove(*merge_ref); |
|---|
| 1641 | } |
|---|
| 1642 | */ |
|---|
| 1643 | |
|---|
| 1644 | for(set<polyhedron*>::iterator grand_ch_ref = (*merge_ref)->totallyneutralgrandchildren.begin();grand_ch_ref!=(*merge_ref)->totallyneutralgrandchildren.end();grand_ch_ref++) |
|---|
| 1645 | { |
|---|
| 1646 | (*grand_ch_ref)->grandparents.erase(*merge_ref); |
|---|
| 1647 | } |
|---|
| 1648 | |
|---|
| 1649 | |
|---|
| 1650 | for(set<polyhedron*>::iterator grand_p_ref = (*merge_ref)->grandparents.begin();grand_p_ref!=(*merge_ref)->grandparents.end();grand_p_ref++) |
|---|
| 1651 | { |
|---|
| 1652 | (*grand_p_ref)->totallyneutralgrandchildren.erase(*merge_ref); |
|---|
| 1653 | } |
|---|
| 1654 | |
|---|
| 1655 | statistic.delete_polyhedron(k-1,*merge_ref); |
|---|
| 1656 | |
|---|
| 1657 | |
|---|
| 1658 | |
|---|
| 1659 | if(k==1) |
|---|
| 1660 | { |
|---|
| 1661 | vertices_to_be_reduced.insert((vertex*)(*merge_ref)); |
|---|
| 1662 | for_splitting[k-1].remove(*merge_ref); |
|---|
| 1663 | } |
|---|
| 1664 | else |
|---|
| 1665 | { |
|---|
| 1666 | delete (*merge_ref); |
|---|
| 1667 | for_splitting[k-1].remove(*merge_ref); |
|---|
| 1668 | } |
|---|
| 1669 | } |
|---|
| 1670 | } |
|---|
| 1671 | |
|---|
| 1672 | k++; |
|---|
| 1673 | |
|---|
| 1674 | } |
|---|
| 1675 | |
|---|
| 1676 | for(set<vertex*>::iterator vert_ref = vertices_to_be_reduced.begin();vert_ref!=vertices_to_be_reduced.end();vert_ref++) |
|---|
| 1677 | { |
|---|
| 1678 | if((*vert_ref)->get_multiplicity()>1) |
|---|
| 1679 | { |
|---|
| 1680 | (*vert_ref)->lower_multiplicity(); |
|---|
| 1681 | } |
|---|
| 1682 | else |
|---|
| 1683 | { |
|---|
| 1684 | delete (*vert_ref); |
|---|
| 1685 | } |
|---|
| 1686 | } |
|---|
| 1687 | |
|---|
| 1688 | delete condition_to_remove; |
|---|
| 1689 | } |
|---|
| 1690 | |
|---|
| 1691 | |
|---|
| 1692 | vector<int> sizevector; |
|---|
| 1693 | for(int s = 0;s<statistic.size();s++) |
|---|
| 1694 | { |
|---|
| 1695 | sizevector.push_back(statistic.row_size(s)); |
|---|
| 1696 | cout << statistic.row_size(s) << ", "; |
|---|
| 1697 | } |
|---|
| 1698 | |
|---|
| 1699 | |
|---|
| 1700 | cout << endl; |
|---|
| 1701 | |
|---|
| 1702 | if(should_add) |
|---|
| 1703 | { |
|---|
| 1704 | cout << "Splitting." << endl; |
|---|
| 1705 | |
|---|
| 1706 | int k = 1; |
|---|
| 1707 | int counter = 0; |
|---|
| 1708 | |
|---|
| 1709 | vector<list<polyhedron*>>::iterator beginning_ref = ++for_splitting.begin(); |
|---|
| 1710 | |
|---|
| 1711 | for(vector<list<polyhedron*>>::iterator vert_ref = beginning_ref;vert_ref<for_splitting.end();vert_ref++) |
|---|
| 1712 | { |
|---|
| 1713 | |
|---|
| 1714 | for(list<polyhedron*>::reverse_iterator split_ref = vert_ref->rbegin();split_ref != vert_ref->rend();split_ref++) |
|---|
| 1715 | { |
|---|
| 1716 | counter++; |
|---|
| 1717 | |
|---|
| 1718 | polyhedron* new_totally_neutral_child; |
|---|
| 1719 | |
|---|
| 1720 | polyhedron* current_polyhedron = (*split_ref); |
|---|
| 1721 | |
|---|
| 1722 | if(vert_ref == beginning_ref) |
|---|
| 1723 | { |
|---|
| 1724 | vec coordinates1 = ((vertex*)(*(current_polyhedron->children.begin())))->get_coordinates(); |
|---|
| 1725 | vec coordinates2 = ((vertex*)(*(++current_polyhedron->children.begin())))->get_coordinates(); |
|---|
| 1726 | |
|---|
| 1727 | vec extended_coord2 = coordinates2; |
|---|
| 1728 | extended_coord2.ins(0,-1.0); |
|---|
| 1729 | |
|---|
| 1730 | double t = (-toadd*extended_coord2)/(toadd(1,toadd.size()-1)*(coordinates1-coordinates2)); |
|---|
| 1731 | |
|---|
| 1732 | vec new_coordinates = (1-t)*coordinates2+t*coordinates1; |
|---|
| 1733 | |
|---|
| 1734 | // cout << "c1:" << coordinates1 << endl << "c2:" << coordinates2 << endl << "nc:" << new_coordinates << endl; |
|---|
| 1735 | |
|---|
| 1736 | vertex* neutral_vertex = new vertex(new_coordinates); |
|---|
| 1737 | |
|---|
| 1738 | new_totally_neutral_child = neutral_vertex; |
|---|
| 1739 | } |
|---|
| 1740 | else |
|---|
| 1741 | { |
|---|
| 1742 | toprow* neutral_toprow = new toprow(); |
|---|
| 1743 | |
|---|
| 1744 | neutral_toprow->condition_sum = ((toprow*)current_polyhedron)->condition_sum; // tohle tu bylo driv: zeros(number_of_parameters+1); |
|---|
| 1745 | neutral_toprow->condition_order = ((toprow*)current_polyhedron)->condition_order+1; |
|---|
| 1746 | |
|---|
| 1747 | new_totally_neutral_child = neutral_toprow; |
|---|
| 1748 | } |
|---|
| 1749 | |
|---|
| 1750 | new_totally_neutral_child->parentconditions.insert(current_polyhedron->parentconditions.begin(),current_polyhedron->parentconditions.end()); |
|---|
| 1751 | new_totally_neutral_child->parentconditions.insert(condition_to_add); |
|---|
| 1752 | |
|---|
| 1753 | new_totally_neutral_child->my_emlig = this; |
|---|
| 1754 | |
|---|
| 1755 | new_totally_neutral_child->children.insert(new_totally_neutral_child->children.end(), |
|---|
| 1756 | current_polyhedron->totallyneutralgrandchildren.begin(), |
|---|
| 1757 | current_polyhedron->totallyneutralgrandchildren.end()); |
|---|
| 1758 | |
|---|
| 1759 | |
|---|
| 1760 | |
|---|
| 1761 | // cout << ((toprow*)current_polyhedron)->condition << endl << toadd << endl; |
|---|
| 1762 | vec cur_pos_condition = ((toprow*)current_polyhedron)->condition_sum; |
|---|
| 1763 | vec cur_neg_condition = ((toprow*)current_polyhedron)->condition_sum; |
|---|
| 1764 | |
|---|
| 1765 | if(k == number_of_parameters) |
|---|
| 1766 | { |
|---|
| 1767 | cur_pos_condition = cur_pos_condition + toadd; |
|---|
| 1768 | cur_neg_condition = cur_neg_condition - toadd; |
|---|
| 1769 | } |
|---|
| 1770 | |
|---|
| 1771 | toprow* positive_poly = new toprow(cur_pos_condition, ((toprow*)current_polyhedron)->condition_order+1); |
|---|
| 1772 | toprow* negative_poly = new toprow(cur_neg_condition, ((toprow*)current_polyhedron)->condition_order+1); |
|---|
| 1773 | |
|---|
| 1774 | positive_poly->my_emlig = this; |
|---|
| 1775 | negative_poly->my_emlig = this; |
|---|
| 1776 | |
|---|
| 1777 | positive_poly->parentconditions.insert(current_polyhedron->parentconditions.begin(),current_polyhedron->parentconditions.end()); |
|---|
| 1778 | negative_poly->parentconditions.insert(current_polyhedron->parentconditions.begin(),current_polyhedron->parentconditions.end()); |
|---|
| 1779 | |
|---|
| 1780 | for(set<polyhedron*>::iterator grand_ref = current_polyhedron->totallyneutralgrandchildren.begin(); grand_ref != current_polyhedron->totallyneutralgrandchildren.end();grand_ref++) |
|---|
| 1781 | { |
|---|
| 1782 | (*grand_ref)->parents.push_back(new_totally_neutral_child); |
|---|
| 1783 | |
|---|
| 1784 | // tohle tu nebylo. ma to tu byt? |
|---|
| 1785 | //positive_poly->totallyneutralgrandchildren.insert(*grand_ref); |
|---|
| 1786 | //negative_poly->totallyneutralgrandchildren.insert(*grand_ref); |
|---|
| 1787 | |
|---|
| 1788 | //(*grand_ref)->grandparents.insert(positive_poly); |
|---|
| 1789 | //(*grand_ref)->grandparents.insert(negative_poly); |
|---|
| 1790 | |
|---|
| 1791 | new_totally_neutral_child->vertices.insert((*grand_ref)->vertices.begin(),(*grand_ref)->vertices.end()); |
|---|
| 1792 | } |
|---|
| 1793 | |
|---|
| 1794 | positive_poly->children.push_back(new_totally_neutral_child); |
|---|
| 1795 | negative_poly->children.push_back(new_totally_neutral_child); |
|---|
| 1796 | |
|---|
| 1797 | |
|---|
| 1798 | for(list<polyhedron*>::iterator parent_ref = current_polyhedron->parents.begin();parent_ref!=current_polyhedron->parents.end();parent_ref++) |
|---|
| 1799 | { |
|---|
| 1800 | (*parent_ref)->totallyneutralgrandchildren.insert(new_totally_neutral_child); |
|---|
| 1801 | // new_totally_neutral_child->grandparents.insert(*parent_ref); |
|---|
| 1802 | |
|---|
| 1803 | (*parent_ref)->neutralchildren.remove(current_polyhedron); |
|---|
| 1804 | (*parent_ref)->children.remove(current_polyhedron); |
|---|
| 1805 | |
|---|
| 1806 | (*parent_ref)->children.push_back(positive_poly); |
|---|
| 1807 | (*parent_ref)->children.push_back(negative_poly); |
|---|
| 1808 | (*parent_ref)->positivechildren.push_back(positive_poly); |
|---|
| 1809 | (*parent_ref)->negativechildren.push_back(negative_poly); |
|---|
| 1810 | } |
|---|
| 1811 | |
|---|
| 1812 | positive_poly->parents.insert(positive_poly->parents.end(), |
|---|
| 1813 | current_polyhedron->parents.begin(), |
|---|
| 1814 | current_polyhedron->parents.end()); |
|---|
| 1815 | |
|---|
| 1816 | negative_poly->parents.insert(negative_poly->parents.end(), |
|---|
| 1817 | current_polyhedron->parents.begin(), |
|---|
| 1818 | current_polyhedron->parents.end()); |
|---|
| 1819 | |
|---|
| 1820 | |
|---|
| 1821 | |
|---|
| 1822 | new_totally_neutral_child->parents.push_back(positive_poly); |
|---|
| 1823 | new_totally_neutral_child->parents.push_back(negative_poly); |
|---|
| 1824 | |
|---|
| 1825 | for(list<polyhedron*>::iterator child_ref = current_polyhedron->positivechildren.begin();child_ref!=current_polyhedron->positivechildren.end();child_ref++) |
|---|
| 1826 | { |
|---|
| 1827 | (*child_ref)->parents.remove(current_polyhedron); |
|---|
| 1828 | (*child_ref)->parents.push_back(positive_poly); |
|---|
| 1829 | } |
|---|
| 1830 | |
|---|
| 1831 | positive_poly->children.insert(positive_poly->children.end(), |
|---|
| 1832 | current_polyhedron->positivechildren.begin(), |
|---|
| 1833 | current_polyhedron->positivechildren.end()); |
|---|
| 1834 | |
|---|
| 1835 | for(list<polyhedron*>::iterator child_ref = current_polyhedron->negativechildren.begin();child_ref!=current_polyhedron->negativechildren.end();child_ref++) |
|---|
| 1836 | { |
|---|
| 1837 | (*child_ref)->parents.remove(current_polyhedron); |
|---|
| 1838 | (*child_ref)->parents.push_back(negative_poly); |
|---|
| 1839 | } |
|---|
| 1840 | |
|---|
| 1841 | negative_poly->children.insert(negative_poly->children.end(), |
|---|
| 1842 | current_polyhedron->negativechildren.begin(), |
|---|
| 1843 | current_polyhedron->negativechildren.end()); |
|---|
| 1844 | |
|---|
| 1845 | positive_poly->vertices.insert(current_polyhedron->positiveneutralvertices.begin(),current_polyhedron->positiveneutralvertices.end()); |
|---|
| 1846 | positive_poly->vertices.insert(new_totally_neutral_child->vertices.begin(),new_totally_neutral_child->vertices.end()); |
|---|
| 1847 | |
|---|
| 1848 | negative_poly->vertices.insert(current_polyhedron->negativeneutralvertices.begin(),current_polyhedron->negativeneutralvertices.end()); |
|---|
| 1849 | negative_poly->vertices.insert(new_totally_neutral_child->vertices.begin(),new_totally_neutral_child->vertices.end()); |
|---|
| 1850 | |
|---|
| 1851 | new_totally_neutral_child->triangulate(false); |
|---|
| 1852 | |
|---|
| 1853 | normalization_factor += positive_poly->triangulate(k==for_splitting.size()-1); |
|---|
| 1854 | normalization_factor += negative_poly->triangulate(k==for_splitting.size()-1); |
|---|
| 1855 | |
|---|
| 1856 | statistic.append_polyhedron(k-1, new_totally_neutral_child); |
|---|
| 1857 | |
|---|
| 1858 | |
|---|
| 1859 | |
|---|
| 1860 | statistic.insert_polyhedron(k, positive_poly, current_polyhedron); |
|---|
| 1861 | statistic.insert_polyhedron(k, negative_poly, current_polyhedron); |
|---|
| 1862 | |
|---|
| 1863 | statistic.delete_polyhedron(k, current_polyhedron); |
|---|
| 1864 | |
|---|
| 1865 | delete current_polyhedron; |
|---|
| 1866 | } |
|---|
| 1867 | |
|---|
| 1868 | k++; |
|---|
| 1869 | } |
|---|
| 1870 | } |
|---|
| 1871 | |
|---|
| 1872 | /* |
|---|
| 1873 | vector<int> sizevector; |
|---|
| 1874 | //sizevector.clear(); |
|---|
| 1875 | for(int s = 0;s<statistic.size();s++) |
|---|
| 1876 | { |
|---|
| 1877 | sizevector.push_back(statistic.row_size(s)); |
|---|
| 1878 | cout << statistic.row_size(s) << ", "; |
|---|
| 1879 | } |
|---|
| 1880 | |
|---|
| 1881 | cout << endl; |
|---|
| 1882 | */ |
|---|
| 1883 | |
|---|
| 1884 | // cout << "Normalization factor: " << normalization_factor << endl; |
|---|
| 1885 | |
|---|
| 1886 | log_nc = log(normalization_factor) + logfact(condition_order-number_of_parameters-2); |
|---|
| 1887 | |
|---|
| 1888 | |
|---|
| 1889 | cout << "part1: " << log(normalization_factor) << endl; |
|---|
| 1890 | cout << "part2: " << logfact(condition_order-number_of_parameters-2) << endl; |
|---|
| 1891 | pause(1); |
|---|
| 1892 | |
|---|
| 1893 | |
|---|
| 1894 | /* |
|---|
| 1895 | for(polyhedron* topr_ref = statistic.rows[statistic.size()-1];topr_ref!=statistic.row_ends[statistic.size()-1]->next_poly;topr_ref=topr_ref->next_poly) |
|---|
| 1896 | { |
|---|
| 1897 | cout << ((toprow*)topr_ref)->condition << endl; |
|---|
| 1898 | } |
|---|
| 1899 | */ |
|---|
| 1900 | |
|---|
| 1901 | // step_me(101); |
|---|
| 1902 | |
|---|
| 1903 | } |
|---|
| 1904 | |
|---|
| 1905 | void set_correction_factors(int order) |
|---|
| 1906 | { |
|---|
| 1907 | for(int remaining_order = correction_factors.size();remaining_order<order;remaining_order++) |
|---|
| 1908 | { |
|---|
| 1909 | multiset<my_ivec> factor_templates; |
|---|
| 1910 | multiset<my_ivec> final_factors; |
|---|
| 1911 | |
|---|
| 1912 | my_ivec orig_template = my_ivec(); |
|---|
| 1913 | |
|---|
| 1914 | for(int i = 1;i<number_of_parameters-remaining_order+1;i++) |
|---|
| 1915 | { |
|---|
| 1916 | bool in_cycle = false; |
|---|
| 1917 | for(int j = 0;j<=remaining_order;j++) { |
|---|
| 1918 | |
|---|
| 1919 | multiset<my_ivec>::iterator fac_ref = factor_templates.begin(); |
|---|
| 1920 | |
|---|
| 1921 | do |
|---|
| 1922 | { |
|---|
| 1923 | my_ivec current_template; |
|---|
| 1924 | if(!in_cycle) |
|---|
| 1925 | { |
|---|
| 1926 | current_template = orig_template; |
|---|
| 1927 | in_cycle = true; |
|---|
| 1928 | } |
|---|
| 1929 | else |
|---|
| 1930 | { |
|---|
| 1931 | current_template = (*fac_ref); |
|---|
| 1932 | fac_ref++; |
|---|
| 1933 | } |
|---|
| 1934 | |
|---|
| 1935 | current_template.ins(current_template.size(),i); |
|---|
| 1936 | |
|---|
| 1937 | // cout << "template:" << current_template << endl; |
|---|
| 1938 | |
|---|
| 1939 | if(current_template.size()==remaining_order+1) |
|---|
| 1940 | { |
|---|
| 1941 | final_factors.insert(current_template); |
|---|
| 1942 | } |
|---|
| 1943 | else |
|---|
| 1944 | { |
|---|
| 1945 | factor_templates.insert(current_template); |
|---|
| 1946 | } |
|---|
| 1947 | } |
|---|
| 1948 | while(fac_ref!=factor_templates.end()); |
|---|
| 1949 | } |
|---|
| 1950 | } |
|---|
| 1951 | |
|---|
| 1952 | correction_factors.push_back(final_factors); |
|---|
| 1953 | |
|---|
| 1954 | } |
|---|
| 1955 | } |
|---|
| 1956 | |
|---|
| 1957 | pair<vec,simplex*> choose_simplex() |
|---|
| 1958 | { |
|---|
| 1959 | double rnumber = randu(); |
|---|
| 1960 | |
|---|
| 1961 | // cout << "RND:" << rnumber << endl; |
|---|
| 1962 | |
|---|
| 1963 | // This could be more efficient (log n), but map::upper_bound() doesn't let me dereference returned iterator |
|---|
| 1964 | double prob_sum = 0; |
|---|
| 1965 | toprow* sampled_toprow; |
|---|
| 1966 | for(polyhedron* top_ref = statistic.rows[number_of_parameters];top_ref!=statistic.end_poly;top_ref=top_ref->next_poly) |
|---|
| 1967 | { |
|---|
| 1968 | // cout << "CDF:"<< (*top_ref).first << endl; |
|---|
| 1969 | |
|---|
| 1970 | toprow* current_toprow = ((toprow*)top_ref); |
|---|
| 1971 | |
|---|
| 1972 | prob_sum += current_toprow->probability; |
|---|
| 1973 | |
|---|
| 1974 | if(prob_sum >= rnumber*normalization_factor) |
|---|
| 1975 | { |
|---|
| 1976 | sampled_toprow = (toprow*)top_ref; |
|---|
| 1977 | break; |
|---|
| 1978 | } |
|---|
| 1979 | else |
|---|
| 1980 | { |
|---|
| 1981 | if(top_ref->next_poly==statistic.end_poly) |
|---|
| 1982 | { |
|---|
| 1983 | cout << "Error."; |
|---|
| 1984 | } |
|---|
| 1985 | } |
|---|
| 1986 | } |
|---|
| 1987 | |
|---|
| 1988 | //// cout << "Toprow/Count: " << toprow_count << "/" << ordered_toprows.size() << endl; |
|---|
| 1989 | // cout << &sampled_toprow << ";"; |
|---|
| 1990 | |
|---|
| 1991 | rnumber = randu(); |
|---|
| 1992 | |
|---|
| 1993 | set<simplex*>::iterator s_ref; |
|---|
| 1994 | prob_sum = 0; |
|---|
| 1995 | for(s_ref = sampled_toprow->triangulation.begin();s_ref!=sampled_toprow->triangulation.end();s_ref++) |
|---|
| 1996 | { |
|---|
| 1997 | prob_sum += (*s_ref)->probability; |
|---|
| 1998 | |
|---|
| 1999 | if(prob_sum/sampled_toprow->probability >= rnumber) |
|---|
| 2000 | break; |
|---|
| 2001 | } |
|---|
| 2002 | |
|---|
| 2003 | return pair<vec,simplex*>(sampled_toprow->condition_sum,*s_ref); |
|---|
| 2004 | } |
|---|
| 2005 | |
|---|
| 2006 | pair<double,double> choose_sigma(simplex* sampled_simplex) |
|---|
| 2007 | { |
|---|
| 2008 | double sigma = 0; |
|---|
| 2009 | double pg_sum; |
|---|
| 2010 | double ng_sum; |
|---|
| 2011 | do |
|---|
| 2012 | { |
|---|
| 2013 | double rnumber = randu(); |
|---|
| 2014 | |
|---|
| 2015 | |
|---|
| 2016 | double sum_g = 0; |
|---|
| 2017 | for(int i = 0;i<sampled_simplex->positive_gamma_parameters.size();i++) |
|---|
| 2018 | { |
|---|
| 2019 | for(multimap<double,double>::iterator g_ref = sampled_simplex->positive_gamma_parameters[i].begin();g_ref != sampled_simplex->positive_gamma_parameters[i].end();g_ref++) |
|---|
| 2020 | { |
|---|
| 2021 | sum_g += (*g_ref).first/sampled_simplex->positive_gamma_sum; |
|---|
| 2022 | |
|---|
| 2023 | |
|---|
| 2024 | if(sum_g>rnumber) |
|---|
| 2025 | { |
|---|
| 2026 | //itpp::Gamma_RNG* gamma = new itpp::Gamma_RNG(conditions.size()-number_of_parameters,1/(*g_ref).second); |
|---|
| 2027 | //sigma = 1/(*gamma)(); |
|---|
| 2028 | |
|---|
| 2029 | GamRNG.setup(conditions.size()-number_of_parameters,(*g_ref).second); |
|---|
| 2030 | |
|---|
| 2031 | sigma = 1/GamRNG(); |
|---|
| 2032 | |
|---|
| 2033 | // cout << "Sigma mean: " << (*g_ref).second/(conditions.size()-number_of_parameters-1) << endl; |
|---|
| 2034 | break; |
|---|
| 2035 | } |
|---|
| 2036 | } |
|---|
| 2037 | |
|---|
| 2038 | if(sigma!=0) |
|---|
| 2039 | { |
|---|
| 2040 | break; |
|---|
| 2041 | } |
|---|
| 2042 | } |
|---|
| 2043 | |
|---|
| 2044 | rnumber = randu(); |
|---|
| 2045 | |
|---|
| 2046 | pg_sum = 0; |
|---|
| 2047 | for(vector<multimap<double,double>>::iterator v_ref = sampled_simplex->positive_gamma_parameters.begin();v_ref!=sampled_simplex->positive_gamma_parameters.end();v_ref++) |
|---|
| 2048 | { |
|---|
| 2049 | for(multimap<double,double>::iterator pg_ref = (*v_ref).begin();pg_ref!=(*v_ref).end();pg_ref++) |
|---|
| 2050 | { |
|---|
| 2051 | pg_sum += exp((sampled_simplex->min_beta-(*pg_ref).second)/sigma)*pow((*pg_ref).second/sigma,(int)conditions.size()-number_of_parameters-1)*(*pg_ref).second/fact(conditions.size()-number_of_parameters-1)*(*pg_ref).first; |
|---|
| 2052 | } |
|---|
| 2053 | } |
|---|
| 2054 | |
|---|
| 2055 | ng_sum = 0; |
|---|
| 2056 | for(vector<multimap<double,double>>::iterator v_ref = sampled_simplex->negative_gamma_parameters.begin();v_ref!=sampled_simplex->negative_gamma_parameters.end();v_ref++) |
|---|
| 2057 | { |
|---|
| 2058 | for(multimap<double,double>::iterator ng_ref = (*v_ref).begin();ng_ref!=(*v_ref).end();ng_ref++) |
|---|
| 2059 | { |
|---|
| 2060 | ng_sum += exp((sampled_simplex->min_beta-(*ng_ref).second)/sigma)*pow((*ng_ref).second/sigma,(int)conditions.size()-number_of_parameters-1)*(*ng_ref).second/fact(conditions.size()-number_of_parameters-1)*(*ng_ref).first; |
|---|
| 2061 | } |
|---|
| 2062 | } |
|---|
| 2063 | } |
|---|
| 2064 | while(pg_sum-ng_sum<0); |
|---|
| 2065 | |
|---|
| 2066 | return pair<double,double>((pg_sum-ng_sum)/pg_sum,sigma); |
|---|
| 2067 | } |
|---|
| 2068 | |
|---|
| 2069 | mat sample_mat(int n) |
|---|
| 2070 | { |
|---|
| 2071 | |
|---|
| 2072 | /// \TODO tady je to spatne, tady nesmi byt conditions.size(), viz RARX.bayes() |
|---|
| 2073 | if(conditions.size()-2-number_of_parameters>=0) |
|---|
| 2074 | { |
|---|
| 2075 | mat sample_mat; |
|---|
| 2076 | map<double,toprow*> ordered_toprows; |
|---|
| 2077 | double sum_a = 0; |
|---|
| 2078 | |
|---|
| 2079 | //cout << "Likelihoods of toprows:" << endl; |
|---|
| 2080 | |
|---|
| 2081 | for(polyhedron* top_ref = statistic.rows[number_of_parameters];top_ref!=statistic.end_poly;top_ref=top_ref->next_poly) |
|---|
| 2082 | { |
|---|
| 2083 | toprow* current_top = (toprow*)top_ref; |
|---|
| 2084 | |
|---|
| 2085 | sum_a+=current_top->probability; |
|---|
| 2086 | /* |
|---|
| 2087 | cout << current_top->probability << " "; |
|---|
| 2088 | |
|---|
| 2089 | for(set<vertex*>::iterator vert_ref = (*top_ref).vertices.begin();vert_ref!=(*top_ref).vertices.end();vert_ref++) |
|---|
| 2090 | { |
|---|
| 2091 | cout << round(100*(*vert_ref)->get_coordinates())/100 << " ; "; |
|---|
| 2092 | } |
|---|
| 2093 | */ |
|---|
| 2094 | |
|---|
| 2095 | // cout << endl; |
|---|
| 2096 | ordered_toprows.insert(pair<double,toprow*>(sum_a,current_top)); |
|---|
| 2097 | } |
|---|
| 2098 | |
|---|
| 2099 | // cout << "Sum N: " << normalization_factor << endl; |
|---|
| 2100 | |
|---|
| 2101 | while(sample_mat.cols()<n) |
|---|
| 2102 | { |
|---|
| 2103 | //// cout << "*************************************" << endl; |
|---|
| 2104 | |
|---|
| 2105 | |
|---|
| 2106 | |
|---|
| 2107 | double rnumber = randu()*sum_a; |
|---|
| 2108 | |
|---|
| 2109 | // cout << "RND:" << rnumber << endl; |
|---|
| 2110 | |
|---|
| 2111 | // This could be more efficient (log n), but map::upper_bound() doesn't let me dereference returned iterator |
|---|
| 2112 | int toprow_count = 0; |
|---|
| 2113 | toprow* sampled_toprow; |
|---|
| 2114 | for(map<double,toprow*>::iterator top_ref = ordered_toprows.begin();top_ref!=ordered_toprows.end();top_ref++) |
|---|
| 2115 | { |
|---|
| 2116 | // cout << "CDF:"<< (*top_ref).first << endl; |
|---|
| 2117 | toprow_count++; |
|---|
| 2118 | |
|---|
| 2119 | if((*top_ref).first >= rnumber) |
|---|
| 2120 | { |
|---|
| 2121 | sampled_toprow = (*top_ref).second; |
|---|
| 2122 | break; |
|---|
| 2123 | } |
|---|
| 2124 | } |
|---|
| 2125 | |
|---|
| 2126 | //// cout << "Toprow/Count: " << toprow_count << "/" << ordered_toprows.size() << endl; |
|---|
| 2127 | // cout << &sampled_toprow << ";"; |
|---|
| 2128 | |
|---|
| 2129 | rnumber = randu(); |
|---|
| 2130 | |
|---|
| 2131 | set<simplex*>::iterator s_ref; |
|---|
| 2132 | double sum_b = 0; |
|---|
| 2133 | int simplex_count = 0; |
|---|
| 2134 | for(s_ref = sampled_toprow->triangulation.begin();s_ref!=sampled_toprow->triangulation.end();s_ref++) |
|---|
| 2135 | { |
|---|
| 2136 | simplex_count++; |
|---|
| 2137 | |
|---|
| 2138 | sum_b += (*s_ref)->probability; |
|---|
| 2139 | |
|---|
| 2140 | if(sum_b/sampled_toprow->probability >= rnumber) |
|---|
| 2141 | break; |
|---|
| 2142 | } |
|---|
| 2143 | |
|---|
| 2144 | //// cout << "Simplex/Count: " << simplex_count << "/" << sampled_toprow->triangulation.size() << endl; |
|---|
| 2145 | //// cout << "Simplex factor: " << (*s_ref)->probability << endl; |
|---|
| 2146 | //// cout << "Toprow factor: " << sampled_toprow->probability << endl; |
|---|
| 2147 | //// cout << "Emlig factor: " << normalization_factor << endl; |
|---|
| 2148 | // cout << &(*tri_ref) << endl; |
|---|
| 2149 | |
|---|
| 2150 | int number_of_runs = 0; |
|---|
| 2151 | bool have_sigma = false; |
|---|
| 2152 | double sigma = 0; |
|---|
| 2153 | do |
|---|
| 2154 | { |
|---|
| 2155 | rnumber = randu(); |
|---|
| 2156 | |
|---|
| 2157 | double sum_g = 0; |
|---|
| 2158 | for(int i = 0;i<(*s_ref)->positive_gamma_parameters.size();i++) |
|---|
| 2159 | { |
|---|
| 2160 | for(multimap<double,double>::iterator g_ref = (*s_ref)->positive_gamma_parameters[i].begin();g_ref != (*s_ref)->positive_gamma_parameters[i].end();g_ref++) |
|---|
| 2161 | { |
|---|
| 2162 | sum_g += (*g_ref).first/(*s_ref)->positive_gamma_sum; |
|---|
| 2163 | |
|---|
| 2164 | |
|---|
| 2165 | if(sum_g>rnumber) |
|---|
| 2166 | { |
|---|
| 2167 | //itpp::Gamma_RNG* gamma = new itpp::Gamma_RNG(conditions.size()-number_of_parameters,1/(*g_ref).second); |
|---|
| 2168 | //sigma = 1/(*gamma)(); |
|---|
| 2169 | |
|---|
| 2170 | GamRNG.setup(conditions.size()-number_of_parameters,(*g_ref).second); |
|---|
| 2171 | |
|---|
| 2172 | sigma = 1/GamRNG(); |
|---|
| 2173 | |
|---|
| 2174 | // cout << "Sigma mean: " << (*g_ref).second/(conditions.size()-number_of_parameters-1) << endl; |
|---|
| 2175 | break; |
|---|
| 2176 | } |
|---|
| 2177 | } |
|---|
| 2178 | |
|---|
| 2179 | if(sigma!=0) |
|---|
| 2180 | { |
|---|
| 2181 | break; |
|---|
| 2182 | } |
|---|
| 2183 | } |
|---|
| 2184 | |
|---|
| 2185 | rnumber = randu(); |
|---|
| 2186 | |
|---|
| 2187 | double pg_sum = 0; |
|---|
| 2188 | for(vector<multimap<double,double>>::iterator v_ref = (*s_ref)->positive_gamma_parameters.begin();v_ref!=(*s_ref)->positive_gamma_parameters.end();v_ref++) |
|---|
| 2189 | { |
|---|
| 2190 | for(multimap<double,double>::iterator pg_ref = (*v_ref).begin();pg_ref!=(*v_ref).end();pg_ref++) |
|---|
| 2191 | { |
|---|
| 2192 | pg_sum += exp(((*s_ref)->min_beta-(*pg_ref).second)/sigma)*pow((*pg_ref).second/sigma,(int)conditions.size()-number_of_parameters-1)*(*pg_ref).second/fact(conditions.size()-number_of_parameters-1)*(*pg_ref).first; |
|---|
| 2193 | } |
|---|
| 2194 | } |
|---|
| 2195 | |
|---|
| 2196 | double ng_sum = 0; |
|---|
| 2197 | for(vector<multimap<double,double>>::iterator v_ref = (*s_ref)->negative_gamma_parameters.begin();v_ref!=(*s_ref)->negative_gamma_parameters.end();v_ref++) |
|---|
| 2198 | { |
|---|
| 2199 | for(multimap<double,double>::iterator ng_ref = (*v_ref).begin();ng_ref!=(*v_ref).end();ng_ref++) |
|---|
| 2200 | { |
|---|
| 2201 | ng_sum += exp(((*s_ref)->min_beta-(*ng_ref).second)/sigma)*pow((*ng_ref).second/sigma,(int)conditions.size()-number_of_parameters-1)*(*ng_ref).second/fact(conditions.size()-number_of_parameters-1)*(*ng_ref).first; |
|---|
| 2202 | } |
|---|
| 2203 | } |
|---|
| 2204 | |
|---|
| 2205 | if((pg_sum-ng_sum)/pg_sum>rnumber) |
|---|
| 2206 | { |
|---|
| 2207 | have_sigma = true; |
|---|
| 2208 | } |
|---|
| 2209 | |
|---|
| 2210 | number_of_runs++; |
|---|
| 2211 | } |
|---|
| 2212 | while(!have_sigma); |
|---|
| 2213 | |
|---|
| 2214 | //// cout << "Sigma: " << sigma << endl; |
|---|
| 2215 | //// cout << "Nr. of sigma runs: " << number_of_runs << endl; |
|---|
| 2216 | |
|---|
| 2217 | int dimension = (*s_ref)->vertices.size()-1; |
|---|
| 2218 | |
|---|
| 2219 | mat jacobian(dimension,dimension); |
|---|
| 2220 | vec gradient = sampled_toprow->condition_sum.right(dimension); |
|---|
| 2221 | |
|---|
| 2222 | vertex* base_vert = *(*s_ref)->vertices.begin(); |
|---|
| 2223 | |
|---|
| 2224 | //// cout << "Base vertex coords(should be close to est. param.): " << base_vert->get_coordinates() << endl; |
|---|
| 2225 | |
|---|
| 2226 | int row_count = 0; |
|---|
| 2227 | |
|---|
| 2228 | for(set<vertex*>::iterator vert_ref = ++(*s_ref)->vertices.begin();vert_ref!=(*s_ref)->vertices.end();vert_ref++) |
|---|
| 2229 | { |
|---|
| 2230 | vec current_coords = (*vert_ref)->get_coordinates(); |
|---|
| 2231 | |
|---|
| 2232 | //// cout << "Coords of vertex[" << row_count << "]: " << current_coords << endl; |
|---|
| 2233 | |
|---|
| 2234 | vec relative_coords = current_coords-base_vert->get_coordinates(); |
|---|
| 2235 | |
|---|
| 2236 | jacobian.set_row(row_count,relative_coords); |
|---|
| 2237 | |
|---|
| 2238 | row_count++; |
|---|
| 2239 | } |
|---|
| 2240 | |
|---|
| 2241 | //// cout << "Jacobian: " << jacobian << endl; |
|---|
| 2242 | |
|---|
| 2243 | //// cout << "Gradient before trafo:" << gradient << endl; |
|---|
| 2244 | |
|---|
| 2245 | gradient = jacobian*gradient; |
|---|
| 2246 | |
|---|
| 2247 | //// cout << "Gradient after trafo:" << gradient << endl; |
|---|
| 2248 | |
|---|
| 2249 | // vec normal_gradient = gradient/sqrt(gradient*gradient); |
|---|
| 2250 | // cout << gradient << endl; |
|---|
| 2251 | // cout << normal_gradient << endl; |
|---|
| 2252 | // cout << sqrt(gradient*gradient) << endl; |
|---|
| 2253 | |
|---|
| 2254 | mat rotation_matrix = eye(dimension); |
|---|
| 2255 | |
|---|
| 2256 | |
|---|
| 2257 | |
|---|
| 2258 | for(int i = 1;i<dimension;i++) |
|---|
| 2259 | { |
|---|
| 2260 | vec x_axis = zeros(dimension); |
|---|
| 2261 | x_axis.set(0,1); |
|---|
| 2262 | |
|---|
| 2263 | x_axis = rotation_matrix*x_axis; |
|---|
| 2264 | |
|---|
| 2265 | double t = abs(gradient[i]/gradient*x_axis); |
|---|
| 2266 | |
|---|
| 2267 | double sin_theta = sign(gradient[i])*t/sqrt(1+pow(t,2)); |
|---|
| 2268 | double cos_theta = sign(gradient*x_axis)/sqrt(1+pow(t,2)); |
|---|
| 2269 | |
|---|
| 2270 | mat partial_rotation = eye(dimension); |
|---|
| 2271 | |
|---|
| 2272 | partial_rotation.set(0,0,cos_theta); |
|---|
| 2273 | partial_rotation.set(i,i,cos_theta); |
|---|
| 2274 | |
|---|
| 2275 | partial_rotation.set(0,i,sin_theta); |
|---|
| 2276 | partial_rotation.set(i,0,-sin_theta); |
|---|
| 2277 | |
|---|
| 2278 | rotation_matrix = rotation_matrix*partial_rotation; |
|---|
| 2279 | |
|---|
| 2280 | } |
|---|
| 2281 | |
|---|
| 2282 | // cout << rotation_matrix << endl; |
|---|
| 2283 | |
|---|
| 2284 | mat extended_rotation = rotation_matrix; |
|---|
| 2285 | extended_rotation.ins_col(0,zeros(extended_rotation.rows())); |
|---|
| 2286 | |
|---|
| 2287 | //// cout << "Extended rotation: " << extended_rotation << endl; |
|---|
| 2288 | |
|---|
| 2289 | vec minima = itpp::min(extended_rotation,2); |
|---|
| 2290 | vec maxima = itpp::max(extended_rotation,2); |
|---|
| 2291 | |
|---|
| 2292 | //// cout << "Minima: " << minima << endl; |
|---|
| 2293 | //// cout << "Maxima: " << maxima << endl; |
|---|
| 2294 | |
|---|
| 2295 | vec sample_coordinates; |
|---|
| 2296 | bool is_inside = true; |
|---|
| 2297 | |
|---|
| 2298 | vec new_sample; |
|---|
| 2299 | sample_coordinates = new_sample; |
|---|
| 2300 | |
|---|
| 2301 | for(int j = 0;j<number_of_parameters;j++) |
|---|
| 2302 | { |
|---|
| 2303 | rnumber = randu(); |
|---|
| 2304 | |
|---|
| 2305 | double coordinate; |
|---|
| 2306 | |
|---|
| 2307 | if(j==0) |
|---|
| 2308 | { |
|---|
| 2309 | vec new_gradient = rotation_matrix*gradient; |
|---|
| 2310 | |
|---|
| 2311 | //// cout << "New gradient(should have only first component nonzero):" << new_gradient << endl; |
|---|
| 2312 | |
|---|
| 2313 | // cout << "Max: " << maxima[0] << " Min: " << minima[0] << " Grad:" << new_gradient[0] << endl; |
|---|
| 2314 | |
|---|
| 2315 | double log_bracket = 1-rnumber*(1-exp(new_gradient[0]/sigma*(minima[0]-maxima[0]))); |
|---|
| 2316 | |
|---|
| 2317 | coordinate = minima[0]-sigma/new_gradient[0]*log(log_bracket); |
|---|
| 2318 | } |
|---|
| 2319 | else |
|---|
| 2320 | { |
|---|
| 2321 | coordinate = minima[j]+rnumber*(maxima[j]-minima[j]); |
|---|
| 2322 | } |
|---|
| 2323 | |
|---|
| 2324 | sample_coordinates.ins(j,coordinate); |
|---|
| 2325 | } |
|---|
| 2326 | |
|---|
| 2327 | //// cout << "Sampled coordinates(gradient direction): " << sample_coordinates << endl; |
|---|
| 2328 | |
|---|
| 2329 | sample_coordinates = rotation_matrix.T()*sample_coordinates; |
|---|
| 2330 | |
|---|
| 2331 | //// cout << "Sampled coordinates(backrotated direction):" << sample_coordinates << endl; |
|---|
| 2332 | |
|---|
| 2333 | |
|---|
| 2334 | for(int j = 0;j<sample_coordinates.size();j++) |
|---|
| 2335 | { |
|---|
| 2336 | if(sample_coordinates[j]<0) |
|---|
| 2337 | { |
|---|
| 2338 | is_inside = false; |
|---|
| 2339 | } |
|---|
| 2340 | } |
|---|
| 2341 | |
|---|
| 2342 | double above_criterion = ones(sample_coordinates.size())*sample_coordinates; |
|---|
| 2343 | |
|---|
| 2344 | if(above_criterion>1) |
|---|
| 2345 | { |
|---|
| 2346 | is_inside = false; |
|---|
| 2347 | } |
|---|
| 2348 | |
|---|
| 2349 | if(is_inside) |
|---|
| 2350 | { |
|---|
| 2351 | sample_coordinates = jacobian.T()*sample_coordinates+(*base_vert).get_coordinates(); |
|---|
| 2352 | |
|---|
| 2353 | sample_coordinates.ins(0,sigma); |
|---|
| 2354 | |
|---|
| 2355 | //// cout << "Sampled coordinates(parameter space):" << sample_coordinates << endl; |
|---|
| 2356 | |
|---|
| 2357 | sample_mat.ins_col(0,sample_coordinates); |
|---|
| 2358 | |
|---|
| 2359 | // cout << sample_mat.cols() << ","; |
|---|
| 2360 | } |
|---|
| 2361 | |
|---|
| 2362 | // cout << sampled_toprow->condition_sum.right(sampled_toprow->condition_sum.size()-1)*min_grad->get_coordinates()-sampled_toprow->condition_sum[0] << endl; |
|---|
| 2363 | // cout << sampled_toprow->condition_sum.right(sampled_toprow->condition_sum.size()-1)*max_grad->get_coordinates()-sampled_toprow->condition_sum[0] << endl; |
|---|
| 2364 | |
|---|
| 2365 | |
|---|
| 2366 | } |
|---|
| 2367 | |
|---|
| 2368 | cout << endl; |
|---|
| 2369 | return sample_mat; |
|---|
| 2370 | } |
|---|
| 2371 | else |
|---|
| 2372 | { |
|---|
| 2373 | throw new exception("You are trying to sample from density that is not determined (parameters can't be integrated out)!"); |
|---|
| 2374 | |
|---|
| 2375 | return 0; |
|---|
| 2376 | } |
|---|
| 2377 | |
|---|
| 2378 | |
|---|
| 2379 | } |
|---|
| 2380 | |
|---|
| 2381 | pair<vec,mat> importance_sample(int n) |
|---|
| 2382 | { |
|---|
| 2383 | vec probabilities; |
|---|
| 2384 | mat samples; |
|---|
| 2385 | |
|---|
| 2386 | for(int i = 0;i<n;i++) |
|---|
| 2387 | { |
|---|
| 2388 | pair<vec,simplex*> condition_and_simplex = choose_simplex(); |
|---|
| 2389 | |
|---|
| 2390 | pair<double,double> probability_and_sigma = choose_sigma(condition_and_simplex.second); |
|---|
| 2391 | |
|---|
| 2392 | int dimension = condition_and_simplex.second->vertices.size()-1; |
|---|
| 2393 | |
|---|
| 2394 | mat jacobian(dimension,dimension); |
|---|
| 2395 | vec gradient = condition_and_simplex.first.right(dimension); |
|---|
| 2396 | |
|---|
| 2397 | vertex* base_vert = *condition_and_simplex.second->vertices.begin(); |
|---|
| 2398 | |
|---|
| 2399 | //// cout << "Base vertex coords(should be close to est. param.): " << base_vert->get_coordinates() << endl; |
|---|
| 2400 | |
|---|
| 2401 | int row_count = 0; |
|---|
| 2402 | |
|---|
| 2403 | for(set<vertex*>::iterator vert_ref = ++condition_and_simplex.second->vertices.begin();vert_ref!=condition_and_simplex.second->vertices.end();vert_ref++) |
|---|
| 2404 | { |
|---|
| 2405 | vec current_coords = (*vert_ref)->get_coordinates(); |
|---|
| 2406 | |
|---|
| 2407 | //// cout << "Coords of vertex[" << row_count << "]: " << current_coords << endl; |
|---|
| 2408 | |
|---|
| 2409 | vec relative_coords = current_coords-base_vert->get_coordinates(); |
|---|
| 2410 | |
|---|
| 2411 | jacobian.set_row(row_count,relative_coords); |
|---|
| 2412 | |
|---|
| 2413 | row_count++; |
|---|
| 2414 | } |
|---|
| 2415 | |
|---|
| 2416 | //// cout << "Jacobian: " << jacobian << endl; |
|---|
| 2417 | |
|---|
| 2418 | /// \todo Is this correct? Are the random coordinates really jointly uniform? I don't know. |
|---|
| 2419 | vec sample_coords; |
|---|
| 2420 | double sampling_diff = 1; |
|---|
| 2421 | for(int j = 0;j<number_of_parameters;j++) |
|---|
| 2422 | { |
|---|
| 2423 | double rnumber = randu()*sampling_diff; |
|---|
| 2424 | |
|---|
| 2425 | sample_coords.ins(0,rnumber); |
|---|
| 2426 | |
|---|
| 2427 | sampling_diff -= rnumber; |
|---|
| 2428 | } |
|---|
| 2429 | |
|---|
| 2430 | sample_coords = jacobian.T()*sample_coords+(*base_vert).get_coordinates(); |
|---|
| 2431 | |
|---|
| 2432 | vec extended_coords = sample_coords; |
|---|
| 2433 | extended_coords.ins(0,-1.0); |
|---|
| 2434 | |
|---|
| 2435 | double exponent = extended_coords*condition_and_simplex.first; |
|---|
| 2436 | double sample_prob = 1/condition_and_simplex.second->probability/pow(probability_and_sigma.second,(int)conditions.size()-number_of_parameters)*exp((-1)/probability_and_sigma.second*exponent); |
|---|
| 2437 | sample_prob *= probability_and_sigma.first; |
|---|
| 2438 | |
|---|
| 2439 | sample_coords.ins(0,probability_and_sigma.second); |
|---|
| 2440 | |
|---|
| 2441 | samples.ins_col(0,sample_coords); |
|---|
| 2442 | probabilities.ins(0,sample_prob); |
|---|
| 2443 | } |
|---|
| 2444 | |
|---|
| 2445 | return pair<vec,mat>(probabilities,samples); |
|---|
| 2446 | } |
|---|
| 2447 | |
|---|
| 2448 | int logfact(int factor) |
|---|
| 2449 | { |
|---|
| 2450 | if(factor>0) |
|---|
| 2451 | { |
|---|
| 2452 | return factor+logfact(factor-1); |
|---|
| 2453 | } |
|---|
| 2454 | else |
|---|
| 2455 | { |
|---|
| 2456 | return 0; |
|---|
| 2457 | } |
|---|
| 2458 | } |
|---|
| 2459 | protected: |
|---|
| 2460 | |
|---|
| 2461 | /// A method for creating plain default statistic representing only the range of the parameter space. |
|---|
| 2462 | void create_statistic(int number_of_parameters, double soft_prior_parameter) |
|---|
| 2463 | { |
|---|
| 2464 | /* |
|---|
| 2465 | for(int i = 0;i<number_of_parameters;i++) |
|---|
| 2466 | { |
|---|
| 2467 | vec condition_vec = zeros(number_of_parameters+1); |
|---|
| 2468 | condition_vec[i+1] = 1; |
|---|
| 2469 | |
|---|
| 2470 | condition* new_condition = new condition(condition_vec); |
|---|
| 2471 | |
|---|
| 2472 | conditions.push_back(new_condition); |
|---|
| 2473 | } |
|---|
| 2474 | */ |
|---|
| 2475 | |
|---|
| 2476 | // An empty vector of coordinates. |
|---|
| 2477 | vec origin_coord; |
|---|
| 2478 | |
|---|
| 2479 | // We create an origin - this point will have all the coordinates zero, but now it has an empty vector of coords. |
|---|
| 2480 | vertex *origin = new vertex(origin_coord); |
|---|
| 2481 | |
|---|
| 2482 | origin->my_emlig = this; |
|---|
| 2483 | |
|---|
| 2484 | /* |
|---|
| 2485 | // As a statistic, we have to create a vector of vectors of polyhedron pointers. It will then represent the Hasse |
|---|
| 2486 | // diagram. First we create a vector of polyhedrons.. |
|---|
| 2487 | list<polyhedron*> origin_vec; |
|---|
| 2488 | |
|---|
| 2489 | // ..we fill it with the origin.. |
|---|
| 2490 | origin_vec.push_back(origin); |
|---|
| 2491 | |
|---|
| 2492 | // ..and we fill the statistic with the created vector. |
|---|
| 2493 | statistic.push_back(origin_vec); |
|---|
| 2494 | */ |
|---|
| 2495 | |
|---|
| 2496 | statistic = *(new c_statistic()); |
|---|
| 2497 | |
|---|
| 2498 | statistic.append_polyhedron(0, origin); |
|---|
| 2499 | |
|---|
| 2500 | // Now we have a statistic for a zero dimensional space. Regarding to how many dimensional space we need to |
|---|
| 2501 | // describe, we have to widen the descriptional default statistic. We use an iterative procedure as follows: |
|---|
| 2502 | for(int i=0;i<number_of_parameters;i++) |
|---|
| 2503 | { |
|---|
| 2504 | // We first will create two new vertices. These will be the borders of the parameter space in the dimension |
|---|
| 2505 | // of newly added parameter. Therefore they will have all coordinates except the last one zero. We get the |
|---|
| 2506 | // right amount of zero cooridnates by reading them from the origin |
|---|
| 2507 | vec origin_coord = origin->get_coordinates(); |
|---|
| 2508 | |
|---|
| 2509 | |
|---|
| 2510 | |
|---|
| 2511 | // And we incorporate the nonzero coordinates into the new cooordinate vectors |
|---|
| 2512 | vec origin_coord1 = concat(origin_coord,-max_range); |
|---|
| 2513 | vec origin_coord2 = concat(origin_coord,max_range); |
|---|
| 2514 | |
|---|
| 2515 | |
|---|
| 2516 | // Now we create the points |
|---|
| 2517 | vertex* new_point1 = new vertex(origin_coord1); |
|---|
| 2518 | vertex* new_point2 = new vertex(origin_coord2); |
|---|
| 2519 | |
|---|
| 2520 | new_point1->my_emlig = this; |
|---|
| 2521 | new_point2->my_emlig = this; |
|---|
| 2522 | |
|---|
| 2523 | //********************************************************************************************************* |
|---|
| 2524 | // The algorithm for recursive build of a new Hasse diagram representing the space structure from the old |
|---|
| 2525 | // diagram works so that you create two copies of the old Hasse diagram, you shift them up one level (points |
|---|
| 2526 | // will be segments, segments will be areas etc.) and you connect each one of the original copied polyhedrons |
|---|
| 2527 | // with its offspring by a parent-child relation. Also each of the segments in the first (second) copy is |
|---|
| 2528 | // connected to the first (second) newly created vertex by a parent-child relation. |
|---|
| 2529 | //********************************************************************************************************* |
|---|
| 2530 | |
|---|
| 2531 | |
|---|
| 2532 | /* |
|---|
| 2533 | // Create the vectors of vectors of pointers to polyhedrons to hold the copies of the old Hasse diagram |
|---|
| 2534 | vector<vector<polyhedron*>> new_statistic1; |
|---|
| 2535 | vector<vector<polyhedron*>> new_statistic2; |
|---|
| 2536 | */ |
|---|
| 2537 | |
|---|
| 2538 | c_statistic* new_statistic1 = new c_statistic(); |
|---|
| 2539 | c_statistic* new_statistic2 = new c_statistic(); |
|---|
| 2540 | |
|---|
| 2541 | |
|---|
| 2542 | // Copy the statistic by rows |
|---|
| 2543 | for(int j=0;j<statistic.size();j++) |
|---|
| 2544 | { |
|---|
| 2545 | |
|---|
| 2546 | |
|---|
| 2547 | // an element counter |
|---|
| 2548 | int element_number = 0; |
|---|
| 2549 | |
|---|
| 2550 | /* |
|---|
| 2551 | vector<polyhedron*> supportnew_1; |
|---|
| 2552 | vector<polyhedron*> supportnew_2; |
|---|
| 2553 | |
|---|
| 2554 | new_statistic1.push_back(supportnew_1); |
|---|
| 2555 | new_statistic2.push_back(supportnew_2); |
|---|
| 2556 | */ |
|---|
| 2557 | |
|---|
| 2558 | // for each polyhedron in the given row |
|---|
| 2559 | for(polyhedron* horiz_ref = statistic.rows[j];horiz_ref!=statistic.get_end();horiz_ref=horiz_ref->next_poly) |
|---|
| 2560 | { |
|---|
| 2561 | // Append an extra zero coordinate to each of the vertices for the new dimension |
|---|
| 2562 | // If vert_ref is at the first index => we loop through vertices |
|---|
| 2563 | if(j == 0) |
|---|
| 2564 | { |
|---|
| 2565 | // cast the polyhedron pointer to a vertex pointer and push a zero to its vector of coordinates |
|---|
| 2566 | ((vertex*) horiz_ref)->push_coordinate(0); |
|---|
| 2567 | } |
|---|
| 2568 | /* |
|---|
| 2569 | else |
|---|
| 2570 | { |
|---|
| 2571 | ((toprow*) (*horiz_ref))->condition.ins(0,0); |
|---|
| 2572 | }*/ |
|---|
| 2573 | |
|---|
| 2574 | // if it has parents |
|---|
| 2575 | if(!horiz_ref->parents.empty()) |
|---|
| 2576 | { |
|---|
| 2577 | // save the relative address of this child in a vector kids_rel_addresses of all its parents. |
|---|
| 2578 | // This information will later be used for copying the whole Hasse diagram with each of the |
|---|
| 2579 | // relations contained within. |
|---|
| 2580 | for(list<polyhedron*>::iterator parent_ref = horiz_ref->parents.begin();parent_ref != horiz_ref->parents.end();parent_ref++) |
|---|
| 2581 | { |
|---|
| 2582 | (*parent_ref)->kids_rel_addresses.push_back(element_number); |
|---|
| 2583 | } |
|---|
| 2584 | } |
|---|
| 2585 | |
|---|
| 2586 | // ************************************************************************************************** |
|---|
| 2587 | // Here we begin creating a new polyhedron, which will be a copy of the old one. Each such polyhedron |
|---|
| 2588 | // will be created as a toprow, but this information will be later forgotten and only the polyhedrons |
|---|
| 2589 | // in the top row of the Hasse diagram will be considered toprow for later use. |
|---|
| 2590 | // ************************************************************************************************** |
|---|
| 2591 | |
|---|
| 2592 | // First we create vectors specifying a toprow condition. In the case of a preconstructed statistic |
|---|
| 2593 | // this condition will be a vector of zeros. There are two vectors, because we need two copies of |
|---|
| 2594 | // the original Hasse diagram. |
|---|
| 2595 | vec vec1; |
|---|
| 2596 | vec vec2; |
|---|
| 2597 | if(!horiz_ref->kids_rel_addresses.empty()) |
|---|
| 2598 | { |
|---|
| 2599 | vec1 = ((toprow*)horiz_ref)->condition_sum; |
|---|
| 2600 | vec1.ins(vec1.size(),-soft_prior_parameter); |
|---|
| 2601 | |
|---|
| 2602 | vec2 = ((toprow*)horiz_ref)->condition_sum; |
|---|
| 2603 | vec2.ins(vec2.size(),soft_prior_parameter); |
|---|
| 2604 | } |
|---|
| 2605 | else |
|---|
| 2606 | { |
|---|
| 2607 | vec1.ins(0,-soft_prior_parameter); |
|---|
| 2608 | vec2.ins(0,soft_prior_parameter); |
|---|
| 2609 | |
|---|
| 2610 | vec1.ins(0,-1); |
|---|
| 2611 | vec2.ins(0,-1); |
|---|
| 2612 | } |
|---|
| 2613 | |
|---|
| 2614 | cout << vec1 << endl; |
|---|
| 2615 | cout << vec2 << endl; |
|---|
| 2616 | |
|---|
| 2617 | |
|---|
| 2618 | // We create a new toprow with the previously specified condition. |
|---|
| 2619 | toprow* current_copy1 = new toprow(vec1, this->condition_order); |
|---|
| 2620 | toprow* current_copy2 = new toprow(vec2, this->condition_order); |
|---|
| 2621 | |
|---|
| 2622 | current_copy1->my_emlig = this; |
|---|
| 2623 | current_copy2->my_emlig = this; |
|---|
| 2624 | |
|---|
| 2625 | // The vertices of the copies will be inherited, because there will be a parent/child relation |
|---|
| 2626 | // between each polyhedron and its offspring (comming from the copy) and a parent has all the |
|---|
| 2627 | // vertices of its child plus more. |
|---|
| 2628 | for(set<vertex*>::iterator vertex_ref = horiz_ref->vertices.begin();vertex_ref!=horiz_ref->vertices.end();vertex_ref++) |
|---|
| 2629 | { |
|---|
| 2630 | current_copy1->vertices.insert(*vertex_ref); |
|---|
| 2631 | current_copy2->vertices.insert(*vertex_ref); |
|---|
| 2632 | } |
|---|
| 2633 | |
|---|
| 2634 | // The only new vertex of the offspring should be the newly created point. |
|---|
| 2635 | current_copy1->vertices.insert(new_point1); |
|---|
| 2636 | current_copy2->vertices.insert(new_point2); |
|---|
| 2637 | |
|---|
| 2638 | // This method guarantees that each polyhedron is already triangulated, therefore its triangulation |
|---|
| 2639 | // is only one set of vertices and it is the set of all its vertices. |
|---|
| 2640 | simplex* t_simplex1 = new simplex(current_copy1->vertices); |
|---|
| 2641 | simplex* t_simplex2 = new simplex(current_copy2->vertices); |
|---|
| 2642 | |
|---|
| 2643 | current_copy1->triangulation.insert(t_simplex1); |
|---|
| 2644 | current_copy2->triangulation.insert(t_simplex2); |
|---|
| 2645 | |
|---|
| 2646 | // Now we have copied the polyhedron and we have to copy all of its relations. Because we are copying |
|---|
| 2647 | // in the Hasse diagram from bottom up, we always have to copy the parent/child relations to all the |
|---|
| 2648 | // kids and when we do that and know the child, in the child we will remember the parent we came from. |
|---|
| 2649 | // This way all the parents/children relations are saved in both the parent and the child. |
|---|
| 2650 | if(!horiz_ref->kids_rel_addresses.empty()) |
|---|
| 2651 | { |
|---|
| 2652 | for(list<int>::iterator kid_ref = horiz_ref->kids_rel_addresses.begin();kid_ref!=horiz_ref->kids_rel_addresses.end();kid_ref++) |
|---|
| 2653 | { |
|---|
| 2654 | polyhedron* new_kid1 = new_statistic1->rows[j-1]; |
|---|
| 2655 | polyhedron* new_kid2 = new_statistic2->rows[j-1]; |
|---|
| 2656 | |
|---|
| 2657 | // THIS IS NOT EFFECTIVE: It could be improved by having the list indexed for new_statistic, but |
|---|
| 2658 | // not indexed for statistic. Hopefully this will not cause a big slowdown - happens only offline. |
|---|
| 2659 | if(*kid_ref) |
|---|
| 2660 | { |
|---|
| 2661 | for(int k = 1;k<=(*kid_ref);k++) |
|---|
| 2662 | { |
|---|
| 2663 | new_kid1=new_kid1->next_poly; |
|---|
| 2664 | new_kid2=new_kid2->next_poly; |
|---|
| 2665 | } |
|---|
| 2666 | } |
|---|
| 2667 | |
|---|
| 2668 | // find the child and save the relation to the parent |
|---|
| 2669 | current_copy1->children.push_back(new_kid1); |
|---|
| 2670 | current_copy2->children.push_back(new_kid2); |
|---|
| 2671 | |
|---|
| 2672 | // in the child save the parents' address |
|---|
| 2673 | new_kid1->parents.push_back(current_copy1); |
|---|
| 2674 | new_kid2->parents.push_back(current_copy2); |
|---|
| 2675 | } |
|---|
| 2676 | |
|---|
| 2677 | // Here we clear the parents kids_rel_addresses vector for later use (when we need to widen the |
|---|
| 2678 | // Hasse diagram again) |
|---|
| 2679 | horiz_ref->kids_rel_addresses.clear(); |
|---|
| 2680 | } |
|---|
| 2681 | // If there were no children previously, we are copying a polyhedron that has been a vertex before. |
|---|
| 2682 | // In this case it is a segment now and it will have a relation to its mother (copywise) and to the |
|---|
| 2683 | // newly created point. Here we create the connection to the new point, again from both sides. |
|---|
| 2684 | else |
|---|
| 2685 | { |
|---|
| 2686 | // Add the address of the new point in the former vertex |
|---|
| 2687 | current_copy1->children.push_back(new_point1); |
|---|
| 2688 | current_copy2->children.push_back(new_point2); |
|---|
| 2689 | |
|---|
| 2690 | // Add the address of the former vertex in the new point |
|---|
| 2691 | new_point1->parents.push_back(current_copy1); |
|---|
| 2692 | new_point2->parents.push_back(current_copy2); |
|---|
| 2693 | } |
|---|
| 2694 | |
|---|
| 2695 | // Save the mother in its offspring |
|---|
| 2696 | current_copy1->children.push_back(horiz_ref); |
|---|
| 2697 | current_copy2->children.push_back(horiz_ref); |
|---|
| 2698 | |
|---|
| 2699 | // Save the offspring in its mother |
|---|
| 2700 | horiz_ref->parents.push_back(current_copy1); |
|---|
| 2701 | horiz_ref->parents.push_back(current_copy2); |
|---|
| 2702 | |
|---|
| 2703 | |
|---|
| 2704 | // Add the copies into the relevant statistic. The statistic will later be appended to the previous |
|---|
| 2705 | // Hasse diagram |
|---|
| 2706 | new_statistic1->append_polyhedron(j,current_copy1); |
|---|
| 2707 | new_statistic2->append_polyhedron(j,current_copy2); |
|---|
| 2708 | |
|---|
| 2709 | // Raise the count in the vector of polyhedrons |
|---|
| 2710 | element_number++; |
|---|
| 2711 | |
|---|
| 2712 | } |
|---|
| 2713 | |
|---|
| 2714 | } |
|---|
| 2715 | |
|---|
| 2716 | /* |
|---|
| 2717 | statistic.begin()->push_back(new_point1); |
|---|
| 2718 | statistic.begin()->push_back(new_point2); |
|---|
| 2719 | */ |
|---|
| 2720 | |
|---|
| 2721 | statistic.append_polyhedron(0, new_point1); |
|---|
| 2722 | statistic.append_polyhedron(0, new_point2); |
|---|
| 2723 | |
|---|
| 2724 | // Merge the new statistics into the old one. This will either be the final statistic or we will |
|---|
| 2725 | // reenter the widening loop. |
|---|
| 2726 | for(int j=0;j<new_statistic1->size();j++) |
|---|
| 2727 | { |
|---|
| 2728 | /* |
|---|
| 2729 | if(j+1==statistic.size()) |
|---|
| 2730 | { |
|---|
| 2731 | list<polyhedron*> support; |
|---|
| 2732 | statistic.push_back(support); |
|---|
| 2733 | } |
|---|
| 2734 | |
|---|
| 2735 | (statistic.begin()+j+1)->insert((statistic.begin()+j+1)->end(),new_statistic1[j].begin(),new_statistic1[j].end()); |
|---|
| 2736 | (statistic.begin()+j+1)->insert((statistic.begin()+j+1)->end(),new_statistic2[j].begin(),new_statistic2[j].end()); |
|---|
| 2737 | */ |
|---|
| 2738 | statistic.append_polyhedron(j+1,new_statistic1->rows[j],new_statistic1->row_ends[j]); |
|---|
| 2739 | statistic.append_polyhedron(j+1,new_statistic2->rows[j],new_statistic2->row_ends[j]); |
|---|
| 2740 | } |
|---|
| 2741 | } |
|---|
| 2742 | |
|---|
| 2743 | /* |
|---|
| 2744 | vector<list<toprow*>> toprow_statistic; |
|---|
| 2745 | int line_count = 0; |
|---|
| 2746 | |
|---|
| 2747 | for(vector<list<polyhedron*>>::iterator polyhedron_ref = ++statistic.begin(); polyhedron_ref!=statistic.end();polyhedron_ref++) |
|---|
| 2748 | { |
|---|
| 2749 | list<toprow*> support_list; |
|---|
| 2750 | toprow_statistic.push_back(support_list); |
|---|
| 2751 | |
|---|
| 2752 | for(list<polyhedron*>::iterator polyhedron_ref2 = polyhedron_ref->begin(); polyhedron_ref2 != polyhedron_ref->end(); polyhedron_ref2++) |
|---|
| 2753 | { |
|---|
| 2754 | toprow* support_top = (toprow*)(*polyhedron_ref2); |
|---|
| 2755 | |
|---|
| 2756 | toprow_statistic[line_count].push_back(support_top); |
|---|
| 2757 | } |
|---|
| 2758 | |
|---|
| 2759 | line_count++; |
|---|
| 2760 | }*/ |
|---|
| 2761 | |
|---|
| 2762 | /* |
|---|
| 2763 | vector<int> sizevector; |
|---|
| 2764 | for(int s = 0;s<statistic.size();s++) |
|---|
| 2765 | { |
|---|
| 2766 | sizevector.push_back(statistic.row_size(s)); |
|---|
| 2767 | } |
|---|
| 2768 | */ |
|---|
| 2769 | |
|---|
| 2770 | } |
|---|
| 2771 | |
|---|
| 2772 | }; |
|---|
| 2773 | |
|---|
| 2774 | |
|---|
| 2775 | |
|---|
| 2776 | //! Robust Bayesian AR model for Multicriteria-Laplace-Inverse-Gamma density |
|---|
| 2777 | class RARX //: public BM |
|---|
| 2778 | { |
|---|
| 2779 | private: |
|---|
| 2780 | bool has_constant; |
|---|
| 2781 | |
|---|
| 2782 | int window_size; |
|---|
| 2783 | |
|---|
| 2784 | list<vec> conditions; |
|---|
| 2785 | |
|---|
| 2786 | public: |
|---|
| 2787 | emlig* posterior; |
|---|
| 2788 | |
|---|
| 2789 | RARX(int number_of_parameters, const int window_size, bool has_constant)//:BM() |
|---|
| 2790 | { |
|---|
| 2791 | this->has_constant = has_constant; |
|---|
| 2792 | |
|---|
| 2793 | posterior = new emlig(number_of_parameters,true,0.001); |
|---|
| 2794 | |
|---|
| 2795 | this->window_size = window_size; |
|---|
| 2796 | }; |
|---|
| 2797 | |
|---|
| 2798 | void bayes(itpp::vec yt) |
|---|
| 2799 | { |
|---|
| 2800 | if(has_constant) |
|---|
| 2801 | { |
|---|
| 2802 | int c_size = yt.size(); |
|---|
| 2803 | |
|---|
| 2804 | yt.ins(c_size,1.0); |
|---|
| 2805 | } |
|---|
| 2806 | |
|---|
| 2807 | if(yt.size() == posterior->number_of_parameters+1) |
|---|
| 2808 | { |
|---|
| 2809 | conditions.push_back(yt); |
|---|
| 2810 | } |
|---|
| 2811 | else |
|---|
| 2812 | { |
|---|
| 2813 | throw new exception("Wrong condition size for bayesian data update!"); |
|---|
| 2814 | } |
|---|
| 2815 | |
|---|
| 2816 | //posterior->step_me(0); |
|---|
| 2817 | |
|---|
| 2818 | /// \TODO tohle je spatne, tady musi byt jiny vypocet poctu podminek, kdyby nejaka byla multiplicitni, tak tohle bude spatne |
|---|
| 2819 | if(conditions.size()>window_size && window_size!=0) |
|---|
| 2820 | { |
|---|
| 2821 | posterior->add_and_remove_condition(yt,conditions.front()); |
|---|
| 2822 | conditions.pop_front(); |
|---|
| 2823 | |
|---|
| 2824 | //posterior->step_me(1); |
|---|
| 2825 | } |
|---|
| 2826 | else |
|---|
| 2827 | { |
|---|
| 2828 | posterior->add_condition(yt); |
|---|
| 2829 | } |
|---|
| 2830 | |
|---|
| 2831 | |
|---|
| 2832 | |
|---|
| 2833 | } |
|---|
| 2834 | |
|---|
| 2835 | }; |
|---|
| 2836 | |
|---|
| 2837 | |
|---|
| 2838 | |
|---|
| 2839 | #endif //TRAGE_H |
|---|