1 | // This file is a part of Framsticks SDK. http://www.framsticks.com/ |
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2 | // Copyright (C) 1999-2020 Maciej Komosinski and Szymon Ulatowski. |
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3 | // See LICENSE.txt for details. |
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4 | |
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5 | #include "measure-distribution.h" |
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6 | #include <common/nonstd_math.h> |
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7 | #include <limits> |
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8 | #include "EMD/emd.c" |
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9 | #include <iostream> |
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10 | |
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11 | #define FIELDSTRUCT SimilMeasureDistribution |
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12 | |
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13 | static ParamEntry simil_distribution_paramtab[] = { |
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14 | { "Creature: Similarity: Descriptor distribution", 1, 4, "SimilMeasureDistribution", "Evaluates morphological dissimilarity using distribution measure.", }, |
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15 | { "simil_density", 0, 0, "Density of surface sampling", "f 1 100 10", FIELD(density), "", }, |
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16 | { "simil_bin_num", 0, 0, "Number of bins", "d 1 1000 128", FIELD(bin_num), "", }, |
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17 | { "simil_samples_num", 0, 0, "Number of samples", "d 1 1048576 1048576", FIELD(samples_num), "", }, |
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18 | { "evaluateDistance", 0, PARAM_DONTSAVE | PARAM_USERHIDDEN, "Evaluate model dissimilarity", "p f(oGeno,oGeno)", PROCEDURE(p_evaldistance), "Calculates dissimilarity between two models created from Geno objects.", }, |
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19 | { 0, }, |
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20 | }; |
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21 | |
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22 | #undef FIELDSTRUCT |
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23 | |
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24 | SimilMeasureDistribution::SimilMeasureDistribution() : localpar(simil_distribution_paramtab, this) |
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25 | { |
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26 | localpar.setDefault(); |
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27 | SimilMeasureDistribution::distribution_fun = &SimilMeasureDistribution::D2; //D1 and D2 are the best descriptors |
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28 | } |
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29 | |
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30 | double SimilMeasureDistribution::getDistance() |
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31 | { |
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32 | double dist = 0; |
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33 | for (int i = 0; i < 2; i++) |
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34 | { |
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35 | funs[i] = new std::pair<double, float>[bin_num](); |
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36 | for (int j = 0; j < bin_num; j++) |
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37 | funs[i][j] = std::make_pair(0, 0); |
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38 | } |
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39 | |
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40 | for (int i = 0; i < 2; i++) |
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41 | sst_models[i] = new SolidsShapeTypeModel((*models[i])); |
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42 | |
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43 | SimilMeasureDistribution::calculateFuns(); |
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44 | dist = SimilMeasureDistribution::compareFuns(); |
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45 | |
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46 | for (int i = 0; i < 2; i++) |
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47 | { |
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48 | SAFEDELETE(sst_models[i]); |
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49 | SAFEDELETEARRAY(funs[i]); |
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50 | } |
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51 | return dist; |
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52 | } |
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53 | |
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54 | int SimilMeasureDistribution::setParams(std::vector<double> params) |
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55 | { |
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56 | for (unsigned int i = 0; i < params.size(); i++) |
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57 | if (params.at(i) <= 0) |
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58 | { |
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59 | logPrintf("SimilDistributionMeasure", "setParams", LOG_ERROR, "Param values should be larger than 0."); |
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60 | return -1; |
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61 | } |
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62 | |
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63 | density = params.at(0); |
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64 | bin_num = params.at(1); |
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65 | samples_num = params.at(2); |
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66 | |
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67 | return 0; |
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68 | } |
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69 | |
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70 | void SimilMeasureDistribution::calculateFun(std::pair<double, float> *fun, Model &sampled) |
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71 | { |
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72 | int size = sampled.getPartCount(); |
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73 | int samples_taken = samples_num; |
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74 | |
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75 | //Check if total number of points pairs is smaller than samples number |
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76 | //but first, prevent exceeding int limits |
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77 | if (size < (int) sqrt((double) std::numeric_limits<int>::max())) |
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78 | samples_taken = min(samples_num, size*size); |
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79 | |
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80 | //Get sampled distribution |
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81 | std::vector<double> dist_vect = (this->*SimilMeasureDistribution::distribution_fun)(samples_taken, &sampled); |
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82 | |
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83 | auto result = std::minmax_element(dist_vect.begin(), dist_vect.end()); |
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84 | double min = *result.first; |
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85 | double max = *result.second; |
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86 | |
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87 | //Create histogram |
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88 | vector<float> hist(bin_num); |
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89 | int ind = 0; |
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90 | |
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91 | for (unsigned int j = 0; j < dist_vect.size(); j++) |
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92 | { |
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93 | ind = (int) std::floor((dist_vect.at(j)-min)*1/(max-min)*bin_num); |
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94 | if (ind <= (bin_num-1)) |
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95 | hist[ind] += 1; |
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96 | else if (ind == bin_num) |
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97 | hist[bin_num-1] += 1; |
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98 | } |
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99 | |
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100 | //Create pairs |
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101 | for (int j = 0; j < bin_num; j++) |
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102 | { |
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103 | fun[j] = std::make_pair(min+(max-min)/bin_num*(j+0.5), hist[j]); |
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104 | } |
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105 | |
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106 | //Normalize |
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107 | float total_mass = 0; |
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108 | for (int j = 0; j < bin_num; j++) |
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109 | { |
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110 | total_mass += fun[j].second; |
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111 | } |
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112 | |
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113 | for (int j = 0; j < bin_num; j++) |
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114 | fun[j].second /= total_mass; |
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115 | } |
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116 | |
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117 | void SimilMeasureDistribution::calculateFuns() |
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118 | { |
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119 | for (int i = 0; i < 2; i++) |
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120 | { |
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121 | Model sampled = SimilMeasureDistribution::sampleSurface(&sst_models[i]->getModel(), density); |
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122 | SimilMeasureDistribution::calculateFun(funs[i], sampled); |
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123 | } |
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124 | } |
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125 | |
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126 | double SimilMeasureDistribution::compareFuns() |
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127 | { |
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128 | return SimilMeasureDistribution::EMD(funs[0], funs[1]); |
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129 | } |
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130 | |
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131 | vector<double> SimilMeasureDistribution::D1(int samples_taken, Model *sampled) |
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132 | { |
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133 | vector<double> dist_vect; |
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134 | int size = sampled->getPartCount(); |
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135 | double x = 0; |
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136 | double y = 0; |
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137 | double z = 0; |
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138 | |
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139 | for (int i = 0; i < size; i++) |
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140 | { |
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141 | Pt3D pos = sampled->getPart(i)->p; |
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142 | x += pos.x; |
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143 | y += pos.y; |
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144 | z += pos.z; |
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145 | } |
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146 | |
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147 | x = x/size; |
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148 | y = y/size; |
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149 | z = z/size; |
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150 | |
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151 | Pt3D centroid = {x, y, z}; |
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152 | |
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153 | for (int i = 0; i < samples_taken; i++) |
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154 | { |
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155 | int p1 = rndUint(size); |
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156 | double dist = sampled->getPart(p1)->p.distanceTo(centroid); |
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157 | if (dist > 0) |
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158 | dist_vect.push_back(dist); |
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159 | } |
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160 | |
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161 | return dist_vect; |
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162 | } |
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163 | |
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164 | vector<double> SimilMeasureDistribution::D2(int samples_taken, Model *sampled) |
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165 | { |
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166 | vector<double> dist_vect; |
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167 | int size = sampled->getPartCount(); |
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168 | for (int i = 0; i < samples_taken; i++) |
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169 | { |
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170 | int p1 = rndUint(size); |
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171 | int p2 = rndUint(size); |
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172 | double dist = sampled->getPart(p1)->p.distanceTo(sampled->getPart(p2)->p); |
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173 | if (dist > 0) |
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174 | dist_vect.push_back(dist); |
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175 | } |
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176 | |
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177 | return dist_vect; |
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178 | } |
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179 | |
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180 | vector<double> SimilMeasureDistribution::D3(int samples_taken, Model *sampled) |
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181 | { |
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182 | vector<double> dist_vect; |
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183 | int size = sampled->getPartCount(); |
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184 | for (int i = 0; i < samples_taken; i++) |
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185 | { |
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186 | int p1 = rndUint(size); |
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187 | int p2 = rndUint(size); |
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188 | int p3 = rndUint(size); |
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189 | |
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190 | Pt3D v(sampled->getPart(p2)->p); |
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191 | Pt3D w(sampled->getPart(p3)->p); |
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192 | v -= sampled->getPart(p1)->p; |
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193 | w -= sampled->getPart(p1)->p; |
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194 | Pt3D cross_prod(0); |
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195 | cross_prod.vectorProduct(v, w); |
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196 | |
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197 | double dist = 0.5 * cross_prod.length(); |
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198 | if (dist > 0) |
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199 | dist_vect.push_back(dist); |
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200 | } |
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201 | |
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202 | return dist_vect; |
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203 | } |
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204 | |
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205 | vector<double> SimilMeasureDistribution::D4(int samples_taken, Model *sampled) |
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206 | { |
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207 | vector<double> dist_vect; |
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208 | int size = sampled->getPartCount(); |
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209 | for (int i = 0; i < samples_taken; i++) |
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210 | { |
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211 | int a = rndUint(size); |
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212 | int b = rndUint(size); |
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213 | int c = rndUint(size); |
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214 | int d = rndUint(size); |
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215 | |
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216 | Pt3D ad(sampled->getPart(a)->p); |
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217 | Pt3D bd(sampled->getPart(b)->p); |
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218 | Pt3D cd(sampled->getPart(c)->p); |
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219 | |
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220 | ad -= sampled->getPart(d)->p; |
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221 | bd -= sampled->getPart(d)->p; |
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222 | cd -= sampled->getPart(d)->p; |
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223 | |
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224 | Pt3D cross_prod(0); |
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225 | cross_prod.vectorProduct(bd, cd); |
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226 | cross_prod.entrywiseProduct(ad); |
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227 | |
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228 | double dist = cross_prod.length()/6; |
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229 | if (dist > 0) |
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230 | dist_vect.push_back(dist); |
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231 | } |
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232 | |
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233 | return dist_vect; |
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234 | } |
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235 | |
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236 | vector<double> SimilMeasureDistribution::A3(int samples_taken, Model *sampled) |
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237 | { |
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238 | vector<double> dist_vect; |
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239 | int size = sampled->getPartCount(); |
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240 | for (int i = 0; i < samples_taken; i++) |
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241 | { |
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242 | int p1 = rndUint(size); |
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243 | int p2 = rndUint(size); |
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244 | int p3 = rndUint(size); |
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245 | double a = sampled->getPart(p1)->p.distanceTo(sampled->getPart(p3)->p); |
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246 | double b = sampled->getPart(p3)->p.distanceTo(sampled->getPart(p2)->p); |
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247 | double c = sampled->getPart(p1)->p.distanceTo(sampled->getPart(p2)->p); |
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248 | double beta = acos((a*a + b*b - c*c)/(2*a*b)); |
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249 | |
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250 | if (!std::isnan(beta)) |
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251 | dist_vect.push_back(beta); |
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252 | } |
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253 | |
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254 | return dist_vect; |
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255 | } |
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256 | |
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257 | |
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258 | float dist(feature_t* F1, feature_t* F2) |
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259 | { |
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260 | return abs((*F1)-(*F2)); |
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261 | } |
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262 | |
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263 | |
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264 | void SimilMeasureDistribution::fillPointsWeights(std::pair<double, float> *fun, feature_t *points, float *weights) |
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265 | { |
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266 | for (int j = 0; j < bin_num; j++) |
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267 | { |
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268 | points[j] = {fun[j].first}; |
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269 | weights[j] = fun[j].second; |
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270 | } |
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271 | } |
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272 | |
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273 | double SimilMeasureDistribution::EMD(std::pair<double, float> *fun1, std::pair<double, float> *fun2) |
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274 | { |
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275 | feature_t *points[2]; |
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276 | float *weights[2]; |
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277 | |
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278 | for (int i = 0; i < 2; i++) |
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279 | { |
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280 | points[i] = new feature_t[bin_num]; |
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281 | weights[i] = new float[bin_num](); |
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282 | } |
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283 | SimilMeasureDistribution::fillPointsWeights(fun1, points[0], weights[0]); |
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284 | SimilMeasureDistribution::fillPointsWeights(fun2, points[1], weights[1]); |
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285 | |
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286 | signature_t sig1 = {bin_num, points[0], weights[0]}, |
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287 | sig2 = {bin_num, points[1], weights[1]}; |
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288 | |
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289 | float e = emd(&sig1, &sig2, dist, 0, 0); |
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290 | |
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291 | for (int i = 0; i < 2; i++) |
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292 | { |
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293 | delete[] points[i]; |
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294 | delete[] weights[i]; |
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295 | } |
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296 | |
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297 | return e; |
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298 | } |
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