Changeset 869
- Timestamp:
- 05/02/19 23:50:27 (6 years ago)
- Location:
- cpp/frams
- Files:
-
- 3 added
- 5 edited
Legend:
- Unmodified
- Added
- Removed
-
cpp/frams/Makefile-SDK-files
r864 r869 2 2 3 3 # ALL_DIRS is later expanded by the shell, no spaces/newlines allowed, or it breaks 4 ALL_DIRS={common,PrintFloat,frams,frams/canvas,frams/config,common/loggers,frams/genetics,frams/genetics/f0,frams/genetics/f1,frams/genetics/f2,frams/genetics/f3,frams/genetics/f4,frams/genetics/f5,frams/genetics/f6,frams/genetics/f7,frams/genetics/f8,frams/genetics/f9,frams/genetics/fn,frams/genetics/fF,frams/genetics/fT,frams/genetics/fB,frams/genetics/fH,frams/genetics/fL,frams/model,frams/neuro,frams/neuro/impl,frams/param,frams/test,frams/util,frams/vm/classes,common/virtfile,frams/_demos,frams/model/geometry,frams/_demos/geometry,frams/model/similarity,frams/model/similarity/ SVD}4 ALL_DIRS={common,PrintFloat,frams,frams/canvas,frams/config,common/loggers,frams/genetics,frams/genetics/f0,frams/genetics/f1,frams/genetics/f2,frams/genetics/f3,frams/genetics/f4,frams/genetics/f5,frams/genetics/f6,frams/genetics/f7,frams/genetics/f8,frams/genetics/f9,frams/genetics/fn,frams/genetics/fF,frams/genetics/fT,frams/genetics/fB,frams/genetics/fH,frams/genetics/fL,frams/model,frams/neuro,frams/neuro/impl,frams/param,frams/test,frams/util,frams/vm/classes,common/virtfile,frams/_demos,frams/model/geometry,frams/_demos/geometry,frams/model/similarity,frams/model/similarity/hungarian,frams/model/similarity/SVD} 5 5 6 6 GENMANF4=frams/genetics/f4/f4_oper.o … … 33 33 NEURO_OBJS=frams/neuro/neuroimpl.o frams/neuro/neurofactory.o frams/neuro/impl/neuroimpl-simple.o frams/neuro/impl/neuroimpl-channels.o frams/neuro/impl/neuroimpl-fuzzy.o frams/neuro/impl/neuroimpl-fuzzy-f0.o 34 34 35 SIMILARITY_OBJS=frams/model/similarity/ SVD/lapack.o frams/model/similarity/SVD/matrix_tools.o frams/model/similarity/simil_match.o frams/model/similarity/simil_model.o35 SIMILARITY_OBJS=frams/model/similarity/hungarian/hungarian.o frams/model/similarity/SVD/lapack.o frams/model/similarity/SVD/matrix_tools.o frams/model/similarity/simil_match.o frams/model/similarity/simil_model.o 36 36 37 37 NN_LAYOUT_OBJS=frams/canvas/nn_layout_model.o frams/canvas/nn_simple_layout.o frams/canvas/nn_smart_layout.o -
cpp/frams/model/similarity/simil_match.cpp
r361 r869 1 1 // This file is a part of Framsticks SDK. http://www.framsticks.com/ 2 // Copyright (C) 1999-201 5Maciej Komosinski and Szymon Ulatowski.2 // Copyright (C) 1999-2019 Maciej Komosinski and Szymon Ulatowski. 3 3 // See LICENSE.txt for details. 4 4 … … 8 8 9 9 /** Creates an empty matching for two objects of specified size. 10 11 10 @param Obj0Size Size of the first object. Must be positive. 11 @param Obj1Size Size of the second object. Must be positive. 12 12 */ 13 13 SimilMatching::SimilMatching(int Obj0Size, int Obj1Size) 14 14 { 15 16 17 18 19 20 21 22 23 24 25 26 27 15 // assure that sizes of objects are positive 16 assert(Obj0Size > 0); 17 assert(Obj1Size > 0); 18 19 // create necessary vectors 20 m_apvMatched[0] = new std::vector<int>(Obj0Size); 21 m_apvMatched[1] = new std::vector<int>(Obj1Size); 22 23 // assure that vectors are created 24 assert(m_apvMatched[0] != NULL); 25 assert(m_apvMatched[1] != NULL); 26 27 // fill vectors with "unmatched" indicator 28 28 for (unsigned int i = 0; i < m_apvMatched[0]->size(); i++) 29 30 31 29 { 30 m_apvMatched[0]->operator[](i) = -1; 31 } 32 32 for (unsigned int i = 0; i < m_apvMatched[1]->size(); i++) 33 34 35 33 { 34 m_apvMatched[1]->operator[](i) = -1; 35 } 36 36 } 37 37 38 38 /** A copying constructor. 39 39 @param Source The object to be copied. 40 40 */ 41 41 SimilMatching::SimilMatching(const SimilMatching &Source) 42 42 { 43 44 m_apvMatched[ 0 ] = new std::vector<int>(* (Source.m_apvMatched[ 0]));45 m_apvMatched[ 1 ] = new std::vector<int>(* (Source.m_apvMatched[ 1]));46 47 48 49 43 // copy the vectors of the actual matching 44 m_apvMatched[0] = new std::vector<int>(*(Source.m_apvMatched[0])); 45 m_apvMatched[1] = new std::vector<int>(*(Source.m_apvMatched[1])); 46 47 // assure that vectors are created 48 assert(m_apvMatched[0] != NULL); 49 assert(m_apvMatched[1] != NULL); 50 50 } 51 51 … … 54 54 SimilMatching::~SimilMatching() 55 55 { 56 57 58 56 // delete vectors of matching 57 delete m_apvMatched[0]; 58 delete m_apvMatched[1]; 59 59 } 60 60 61 61 /** Gets size of the specified object. 62 63 62 @param Index of an object (must be 0 or 1). 63 @return Size of the object (in elements). 64 64 */ 65 65 int SimilMatching::GetObjectSize(int Obj) 66 66 { 67 68 69 70 71 return m_apvMatched[ Obj]->size();67 // check parameter 68 assert((Obj == 0) || (Obj == 1)); 69 70 // return the result 71 return m_apvMatched[Obj]->size(); 72 72 } 73 73 74 74 /** Matches elements given by indices in the given objects. 75 76 @param index0 Index of element in the first object. Must be a valid index 77 78 79 @param Index1 index of element in the second object. Must be a valid index 80 75 @param Obj0 Index of the first object. Must be 0 or 1. 76 @param index0 Index of element in the first object. Must be a valid index 77 ( >= 0 and < size of the object). 78 @param Obj1 Index of the second object. Must be 0 or 1 and different from Obj0. 79 @param Index1 index of element in the second object. Must be a valid index 80 ( >= 0 and < size of the object). 81 81 82 82 */ 83 83 void SimilMatching::Match(int Obj0, int Index0, int Obj1, int Index1) 84 84 { 85 86 87 assert((Index0 >= 0) && (Index0 < (int)m_apvMatched[Obj0]->size()));88 89 90 assert((Index1 >= 0) && (Index1 < (int)m_apvMatched[Obj1]->size()));91 92 93 94 m_apvMatched[ Obj0]->operator[](Index0) = Index1;95 96 m_apvMatched[ Obj1]->operator[](Index1) = Index0;85 // check parameters of object 0 86 assert((Obj0 == 0) || (Obj0 == 1)); 87 assert((Index0 >= 0) && (Index0 < (int)m_apvMatched[Obj0]->size())); 88 // check parameters of object 1 89 assert(((Obj1 == 0) || (Obj1 == 1)) && (Obj0 != Obj1)); 90 assert((Index1 >= 0) && (Index1 < (int)m_apvMatched[Obj1]->size())); 91 92 // match given elements 93 // matching_Obj0(Index0) = Index1 94 m_apvMatched[Obj0]->operator[](Index0) = Index1; 95 // matching_Obj1(Index1) = Index0 96 m_apvMatched[Obj1]->operator[](Index1) = Index0; 97 97 } 98 98 99 99 /** Checks if the given element in the given object is already matched. 100 101 @param Index Index of an element in the given object. Must be a valid index 102 103 100 @param Obj Index of an object (must be 0 or 1). 101 @param Index Index of an element in the given object. Must be a valid index 102 ( >=0 and < size of the object). 103 @return true if the given element is matched, false otherwise. 104 104 */ 105 105 bool SimilMatching::IsMatched(int Obj, int Index) 106 106 { 107 108 109 assert((Index >= 0) && (Index < (int) m_apvMatched[ Obj]->size()));110 111 112 if (m_apvMatched[ Obj]->operator[](Index) >= 0)113 114 115 116 117 118 119 107 // check parameters 108 assert((Obj == 0) || (Obj == 1)); 109 assert((Index >= 0) && (Index < (int)m_apvMatched[Obj]->size())); 110 111 // check if the element is matched 112 if (m_apvMatched[Obj]->operator[](Index) >= 0) 113 { 114 return true; 115 } 116 else 117 { 118 return false; 119 } 120 120 } 121 121 122 122 /** Gets index of the element thet is matched in the other object withe the element given 123 124 125 126 127 element. WARNING! If the given element is not matched, the result may be smaller than 0 128 123 by parameters. 124 @param Obj Index of an object (must be 0 or 1). 125 @param Index Index of checked element in the given object. 126 @return Index of the element (in the other organism) that is matched with the given 127 element. WARNING! If the given element is not matched, the result may be smaller than 0 128 (check IsMatched() before using GetMatchedIndex()). 129 129 */ 130 130 int SimilMatching::GetMatchedIndex(int Obj, int Index) 131 131 { 132 133 134 assert((Index >= 0) && (Index < (int) m_apvMatched[ Obj]->size()));135 136 137 return m_apvMatched[ Obj]->operator[](Index);138 } 139 140 /** Checks if the matching is already full, i.e. if the smaller object already has all its 141 elements matched. 142 132 // check parameters 133 assert((Obj == 0) || (Obj == 1)); 134 assert((Index >= 0) && (Index < (int)m_apvMatched[Obj]->size())); 135 136 // return the index of the matched element 137 return m_apvMatched[Obj]->operator[](Index); 138 } 139 140 /** Checks if the matching is already full, i.e. if the smaller object already has all its 141 elements matched. 142 @return true if matching is full, false otherwise. 143 143 */ 144 144 bool SimilMatching::IsFull() 145 145 { 146 147 148 149 150 151 152 if (m_apvMatched[ 0 ]->size() < m_apvMatched[ 1]->size())153 154 155 156 157 158 159 160 161 146 // assume that the matching is full 147 bool bResult = true; 148 // index of the smallest object 149 int nObj; 150 151 // find the smallest object (its index) 152 if (m_apvMatched[0]->size() < m_apvMatched[1]->size()) 153 { 154 nObj = 0; 155 } 156 else 157 { 158 nObj = 1; 159 } 160 161 // check if all elements of the smallest object are matched 162 162 for (unsigned int nElem = 0; nElem < m_apvMatched[nObj]->size(); nElem++) 163 164 if (m_apvMatched[ nObj]->operator[](nElem) < 0)165 166 167 168 169 170 171 172 173 163 { 164 if (m_apvMatched[nObj]->operator[](nElem) < 0) 165 { 166 // if any element is not matched, the result is false 167 bResult = false; 168 break; 169 } 170 } 171 172 // return the result 173 return bResult; 174 174 } 175 175 176 176 /** Checks if the matching is empty (i.e. none of elements is matched). 177 177 @return true if matching is empty, otherwise - false. 178 178 */ 179 179 bool SimilMatching::IsEmpty() 180 180 { 181 182 183 184 185 186 181 // result - assume that matching is empty 182 bool bResult = true; 183 184 // matching is empty if either of objects has only unmatched elements 185 // so it may be first object 186 int nObj = 0; 187 187 for (unsigned int nElem = 0; nElem < m_apvMatched[nObj]->size(); nElem++) 188 189 if (m_apvMatched[ nObj]->operator[](nElem) >= 0)190 191 192 193 194 195 196 197 198 188 { 189 if (m_apvMatched[nObj]->operator[](nElem) >= 0) 190 { 191 // if any element of the object is matched (unmatched objects have (-1)) 192 bResult = false; 193 break; 194 } 195 } 196 197 // return the result from the loop 198 return bResult; 199 199 } 200 200 … … 203 203 void SimilMatching::Empty() 204 204 { 205 206 207 205 for (int iObj = 0; iObj < 2; iObj++) // a counter of objects 206 { 207 // for each object in the matching 208 208 for (unsigned int iElem = 0; iElem < m_apvMatched[iObj]->size(); iElem++) // a counter of objects' elements 209 210 211 212 m_apvMatched[ iObj]->operator[](iElem) = -1;213 214 215 216 217 209 { 210 // for each element iElem for the object iObj 211 // set it as unmatched (marker: -1) 212 m_apvMatched[iObj]->operator[](iElem) = -1; 213 } 214 } 215 216 // the exit condition 217 assert(IsEmpty() == true); 218 218 } 219 219 … … 222 222 void SimilMatching::PrintMatching() 223 223 { 224 225 226 227 if (m_apvMatched[ 0 ]->size() >= m_apvMatched[ 1]->size())228 229 230 231 232 233 234 235 236 237 224 int nBigger; 225 226 // check which object is bigger 227 if (m_apvMatched[0]->size() >= m_apvMatched[1]->size()) 228 { 229 nBigger = 0; 230 } 231 else 232 { 233 nBigger = 1; 234 } 235 236 // print first line - indices of objects 237 printf("[ "); 238 238 for (unsigned int i = 0; i < m_apvMatched[nBigger]->size(); i++) 239 240 241 242 243 244 245 246 247 248 239 { 240 printf("%2d ", i); 241 } 242 printf("]\n"); 243 244 // print second line and third - indices of elements matched with elements of the objects 245 for (int nObj = 0; nObj < 2; nObj++) 246 { 247 // for both objects - print out lines of matched elements 248 printf("[ "); 249 249 for (unsigned int i = 0; i < m_apvMatched[nObj]->size(); i++) 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 } 250 { 251 if (IsMatched(nObj, i)) 252 { 253 // if the element is matched - print the index 254 printf("%2d ", GetMatchedIndex(nObj, i)); 255 } 256 else 257 { 258 // if the element is not matched - print "X" 259 printf(" X "); 260 } 261 } 262 printf("]\n"); 263 } 264 } -
cpp/frams/model/similarity/simil_match.h
r357 r869 1 1 // This file is a part of Framsticks SDK. http://www.framsticks.com/ 2 // Copyright (C) 1999-201 5Maciej Komosinski and Szymon Ulatowski.2 // Copyright (C) 1999-2019 Maciej Komosinski and Szymon Ulatowski. 3 3 // See LICENSE.txt for details. 4 4 … … 8 8 #include <vector> 9 9 10 /** Class describes a mutually single-valued function between two sets of elements11 12 13 This class is used while building a matching function between Parts of two Framsticks' 14 10 /** This class describes a mutually single-valued function between two sets of elements 11 (these sets are called objects). These sets may have different sizes, so this function 12 is mutually single-valued only for some subset of the bigger set. 13 This class is used while building a matching function between Parts of two Framsticks' 14 organisms (similarity measure computation). 15 15 */ 16 16 class SimilMatching 17 17 { 18 18 protected: 19 20 the other object. Value <0 means that an element is not matched yet. Sizes of these 21 22 23 19 /** Array of pointers to two vectors. Each one stores indices of matched elements of 20 the other object. Value <0 means that an element is not matched yet. Sizes of these 21 vectors are sizes of objects themselves. 22 */ 23 std::vector<int> *m_apvMatched[2]; 24 24 public: 25 26 27 28 29 30 31 32 33 34 35 25 SimilMatching(int Obj0Size, int Obj1Size); 26 SimilMatching(const SimilMatching &Source); 27 ~SimilMatching(); 28 int GetObjectSize(int Obj); 29 void Match(int Obj0, int Index0, int Obj1, int Index1); 30 bool IsMatched(int Obj, int Index); 31 int GetMatchedIndex(int Obj, int index); 32 bool IsFull(); 33 bool IsEmpty(); 34 void Empty(); 35 void PrintMatching(); 36 36 }; 37 37 -
cpp/frams/model/similarity/simil_model.cpp
r818 r869 1 1 // This file is a part of Framsticks SDK. http://www.framsticks.com/ 2 // Copyright (C) 1999-201 7Maciej Komosinski and Szymon Ulatowski.2 // Copyright (C) 1999-2019 Maciej Komosinski and Szymon Ulatowski. 3 3 // See LICENSE.txt for details. 4 4 5 // simil_model.cpp: implementation of the ModelSimil class. 6 // 7 ////////////////////////////////////////////////////////////////////// 5 // implementation of the ModelSimil class. 6 8 7 #include "SVD/matrix_tools.h" 8 #include "hungarian/hungarian.h" 9 9 #include "simil_model.h" 10 10 #include "simil_match.h" … … 35 35 36 36 static ParamEntry MSparam_tab[] = { 37 { "Creature: Similarity", 1, 7, "ModelSimilarity", "Evaluates morphological dissimilarity. More information:\nhttp://www.framsticks.com/bib/Komosinski-et-al-2001\nhttp://www.framsticks.com/bib/Komosinski-and-Kubiak-2011\nhttp://www.framsticks.com/bib/Komosinski-2016", }, 37 { "Creature: Similarity", 1, 8, "ModelSimilarity", "Evaluates morphological dissimilarity. More information:\nhttp://www.framsticks.com/bib/Komosinski-et-al-2001\nhttp://www.framsticks.com/bib/Komosinski-and-Kubiak-2011\nhttp://www.framsticks.com/bib/Komosinski-2016\nhttps://doi.org/10.1007/978-3-030-16692-2_8", }, 38 { "simil_method", 0, 0, "Similarity algorithm", "d 0 1 0 ~New (flexible criteria order, optimal matching)~Old (vertex degree order, greedy matching)", FIELD(matching_method), "",}, 38 39 { "simil_parts", 0, 0, "Weight of parts count", "f 0 100 0", FIELD(m_adFactors[0]), "Differing number of parts is also handled by the 'part degree' similarity component.", }, 39 40 { "simil_partdeg", 0, 0, "Weight of parts' degree", "f 0 100 1", FIELD(m_adFactors[1]), "", }, … … 76 77 isFuzzy = 0; 77 78 fuzzyDepth = 10; 78 79 79 80 //Determines whether weighted MDS should be used. 80 81 wMDS = 0; 81 } 82 83 /** Evaluates distance between two given genotypes. The distance depends strongly 84 on weights set. 85 @param G0 Pointer to the first of compared genotypes 86 @param G1 Pointer to the second of compared genotypes. 87 @return Distance between two genotypes. 88 @sa m_adFactors, matching_method 89 */ 90 double ModelSimil::EvaluateDistance(const Geno *G0, const Geno *G1) 82 //Determines whether best matching should be saved using hungarian similarity measure. 83 saveMatching = 0; 84 } 85 86 double ModelSimil::EvaluateDistanceGreedy(const Geno *G0, const Geno *G1) 91 87 { 92 88 double dResult = 0; … … 98 94 if (m_Gen[0] == NULL || m_Gen[1] == NULL) 99 95 { 100 DB(printf("ModelSimil::EvaluateDistance - invalid genotypes pointers\n");) 101 return 0.0; 96 DB(printf("ModelSimil::EvaluateDistanceGreedy - invalid genotype(s) pointers\n");) //TODO convert all such error printfs to legacy error messages, since if's are not in DB(). Example below. 97 logPrintf("ModelSimil", "EvaluateDistanceGreedy", LOG_ERROR, "NULL genotype pointer(s)"); 98 return 0.0; 102 99 } 103 100 // create models of objects to compare … … 108 105 if (m_Mod[0] == NULL || m_Mod[1] == NULL || !(m_Mod[0]->isValid()) || !(m_Mod[1]->isValid())) 109 106 { 110 DB(printf("ModelSimil::EvaluateDistance - invalid modelspointers\n");)107 DB(printf("ModelSimil::EvaluateDistanceGreedy - invalid model(s) pointers\n");) 111 108 return 0.0; 112 109 } … … 143 140 if ((this->*pfMatchingFunction)() == 0) 144 141 { 145 DB(printf("ModelSimil::EvaluateDistance - MatchParts() error\n");)142 DB(printf("ModelSimil::EvaluateDistanceGreedy - MatchParts() error\n");) 146 143 return 0.0; 147 144 } … … 155 152 if (CountPartsDistance() == 0) 156 153 { 157 DB(printf("ModelSimil::EvaluateDistance- CountPartDistance() error\n");)158 return 0.0;154 DB(printf("ModelSimil::EvaluateDistanceGreedy - CountPartDistance() error\n");) 155 return 0.0; 159 156 } 160 157 … … 340 337 if (tdn1[1] < tdn2[1]) 341 338 { 342 // when degree - tdn2[1] - is BIGGER 343 return 1; 339 // when degree - tdn2[1] - is BIGGER 340 return 1; 341 } 342 else 343 { 344 return 0; 345 } 346 } 347 348 /** Comparison function required for qsort() call. Used while sorting groups of 349 Parts with respect to fuzzy vertex degree. Compares two TDN structures 350 with respect to their [4] field ( fuzzy vertex degree). Highest degree goes first. 351 @param pElem1 Pointer to the TDN structure of some Part. 352 @param pElem2 Pointer to the TDN structure of some Part. 353 @return (-1) - pElem1 should go first, 0 - equal, (1) - pElem2 should go first. 354 */ 355 int ModelSimil::CompareFuzzyDegrees(const void *pElem1, const void *pElem2) 356 { 357 int *tdn1 = (int *)pElem1; 358 int *tdn2 = (int *)pElem2; 359 360 if (tdn1[4] > tdn2[4]) 361 { 362 // when degree - tdn1[4] - is BIGGER 363 return -1; 364 } 365 else 366 if (tdn1[4] < tdn2[4]) 367 { 368 // when degree - tdn2[4] - is BIGGER 369 return 1; 344 370 } 345 371 else … … 374 400 if (tdn1[NEURO_CONNS] < tdn2[NEURO_CONNS]) 375 401 { 376 // when number of NConn Elem1 is SMALLER377 return 1;402 // when number of NConn Elem1 is SMALLER 403 return 1; 378 404 } 379 405 else … … 389 415 if (tdn1[NEURONS] < tdn2[NEURONS]) 390 416 { 391 // when number of Neu is SMALLER for Elem1392 return 1;417 // when number of Neu is SMALLER for Elem1 418 return 1; 393 419 } 394 420 else … … 406 432 if (tdn1[ORIG_IND] < tdn2[ORIG_IND]) 407 433 { 408 // when the number of NIt Deg1 id SMALLER409 return 1;434 // when the number of NIt Deg1 id SMALLER 435 return 1; 410 436 } 411 437 else … … 494 520 } 495 521 522 /** Prints one array of parts fuzzy neighbourhood. 523 @param index of organism 524 */ 525 void ModelSimil::_PrintFuzzyNeighbourhood(int o) 526 { 527 assert(m_fuzzyNeighb[o] != NULL); 528 printf("Fuzzy neighbourhhod of organism %i\n", o); 529 int size = m_Mod[o]->getPartCount(); 530 for (int i = 0; i < size; i++) 531 { 532 for (int j = 0; j < fuzzyDepth; j++) 533 { 534 printf("%f ", m_fuzzyNeighb[o][i][j]); 535 } 536 printf("\n"); 537 } 538 } 539 496 540 /** Creates arrays holding information about organisms' Parts (m_aDegrees) andm_Neigh 497 541 fills them with initial data (original indices and zeros). … … 526 570 for (j = 0; j < partCount; j++) 527 571 { 528 m_aDegrees[i][j][0] = j; 529 m_aDegrees[i][j][1] = 0; 530 m_aDegrees[i][j][2] = 0; 531 m_aDegrees[i][j][3] = 0; 532 m_aDegrees[i][j][4] = 0; 533 534 // sprawdz, czy nie piszemy po jakims szalonym miejscu pamieci 535 assert(m_aDegrees[i][j] != NULL); 536 537 if (isFuzzy) 538 { 539 m_Neighbours[i][j] = new int[partCount]; 540 for (int k = 0; k < partCount; k++) 572 m_aDegrees[i][j][0] = j; 573 m_aDegrees[i][j][1] = 0; 574 m_aDegrees[i][j][2] = 0; 575 m_aDegrees[i][j][3] = 0; 576 m_aDegrees[i][j][4] = 0; 577 578 // sprawdz, czy nie piszemy po jakims szalonym miejscu pamieci 579 assert(m_aDegrees[i][j] != NULL); 580 581 if (isFuzzy) 541 582 { 542 m_Neighbours[i][j][k] = 0; 583 m_Neighbours[i][j] = new int[partCount]; 584 for (int k = 0; k < partCount; k++) 585 { 586 m_Neighbours[i][j][k] = 0; 587 } 588 589 m_fuzzyNeighb[i][j] = new float[fuzzyDepth]; 590 for (int k = 0; k < fuzzyDepth; k++) 591 { 592 m_fuzzyNeighb[i][j][k] = 0; 593 } 594 595 assert(m_Neighbours[i][j] != NULL); 596 assert(m_fuzzyNeighb[i][j] != NULL); 543 597 } 544 545 m_fuzzyNeighb[i][j] = new float[fuzzyDepth];546 for (int k = 0; k < fuzzyDepth; k++)547 {548 m_fuzzyNeighb[i][j][k] = 0;549 }550 551 assert(m_Neighbours[i][j] != NULL);552 assert(m_fuzzyNeighb[i][j] != NULL);553 }554 598 555 599 } … … 671 715 } 672 716 673 //store information about identity of parts "fuzzy degrees" in the m_aDegrees[4] 674 void ModelSimil::CheckFuzzyIdentity() 675 { 676 int partCount = 0; 717 void ModelSimil::FuzzyOrder() 718 { 719 int i, depth, partInd, prevPartInd, partCount; 677 720 for (int mod = 0; mod < 2; mod++) 678 721 { 679 //for subsequent pairs of parts680 722 partCount = m_Mod[mod]->getPartCount(); 681 m_aDegrees[mod][partCount - 1][FUZZ_DEG] = 0; 682 for (int partInd = (partCount - 2); partInd >= 0; partInd--) 683 { 684 m_aDegrees[mod][partInd][FUZZ_DEG] = m_aDegrees[mod][partInd + 1][FUZZ_DEG]; 685 for (int depth = 1; depth < fuzzyDepth; depth++) 686 { 687 if (m_fuzzyNeighb[mod][partInd][depth] != m_fuzzyNeighb[mod][partInd + 1][depth]) 688 { 689 m_aDegrees[mod][partInd][FUZZ_DEG] += 1; 723 partInd = m_fuzzyNeighb[mod][partCount - 1][0]; 724 m_aDegrees[mod][partInd][FUZZ_DEG] = 0; 725 726 for (i = (partCount - 2); i >= 0; i--) 727 { 728 prevPartInd = partInd; 729 partInd = m_fuzzyNeighb[mod][i][0]; 730 m_aDegrees[mod][partInd][FUZZ_DEG] = m_aDegrees[mod][prevPartInd][FUZZ_DEG]; 731 for (depth = 1; depth < fuzzyDepth; depth++) 732 { 733 if (m_fuzzyNeighb[mod][i][depth] != m_fuzzyNeighb[mod][i + 1][depth]) 734 { 735 m_aDegrees[mod][partInd][FUZZ_DEG]++; 690 736 break; 691 737 } … … 761 807 762 808 SortFuzzyNeighb(); 809 FuzzyOrder(); 763 810 } 764 811 … … 884 931 885 932 int i; 933 int(*pfDegreeFunction) (const void*, const void*) = NULL; 934 pfDegreeFunction = (isFuzzy == 1) ? &CompareFuzzyDegrees : &CompareDegrees; 886 935 // sortowanie obu tablic wg stopni punktów - TDN[1] 887 if (isFuzzy != 1) 888 { 889 for (i = 0; i < 2; i++) 890 { 891 DB(_PrintDegrees(i)); 892 std::qsort(m_aDegrees[i], (size_t)(m_Mod[i]->getPartCount()), 893 sizeof(TDN), ModelSimil::CompareDegrees); 894 DB(_PrintDegrees(i)); 895 } 896 }//sortowanie wg romzmytego stopnia wierzcholka 897 898 else 899 { 900 SortPartInfoFuzzy(); 901 } 902 936 for (i = 0; i < 2; i++) 937 { 938 DB(_PrintDegrees(i)); 939 std::qsort(m_aDegrees[i], (size_t)(m_Mod[i]->getPartCount()), 940 sizeof(TDN), pfDegreeFunction); 941 DB(_PrintDegrees(i)); 942 } 903 943 904 944 // sprawdzenie wartosci parametru … … 935 975 936 976 std::qsort(m_aDegrees[i][iPocz], (size_t)(j - iPocz), 937 sizeof(TDN), ModelSimil::CompareConnsNo);977 sizeof(TDN), ModelSimil::CompareConnsNo); 938 978 DB(_PrintDegrees(i)); 939 979 // wyswietlamy z jedna komorka po zakonczeniu tablicy … … 948 988 } 949 989 950 int ModelSimil::SortPartInfoFuzzy()951 {952 953 // sprawdz zalozenie - o modelach954 assert((m_Mod[0] != NULL) && (m_Mod[1] != NULL));955 assert(m_Mod[0]->isValid() && m_Mod[1]->isValid());956 957 // sprawdz zalozenie - o tablicach958 assert(m_aDegrees[0] != NULL);959 assert(m_aDegrees[1] != NULL);960 // sprawdz zalozenie - o tablicach961 assert(m_fuzzyNeighb[0] != NULL);962 assert(m_fuzzyNeighb[1] != NULL);963 964 965 TDN * m_aDegreesTmp[2];966 967 for (int i = 0; i < 2; i++)968 {969 int partCount = m_Mod[i]->getPartCount();970 m_aDegreesTmp[i] = new TDN[partCount];971 972 for (int j = 0; j < partCount; j++)973 {974 for (int k = 0; k < TDN_SIZE; k++)975 {976 m_aDegreesTmp[i][j][k] = m_aDegrees[i][j][k];977 }978 }979 }980 981 int newInd = 0;982 for (int i = 0; i < 2; i++)983 {984 int partCount = m_Mod[i]->getPartCount();985 for (int j = 0; j < partCount; j++)986 {987 newInd = (int)m_fuzzyNeighb[i][j][0];988 for (int k = 0; k < TDN_SIZE; k++)989 {990 m_aDegrees[i][j][k] = m_aDegreesTmp[i][newInd][k];991 }992 }993 }994 995 SAFEDELETEARRAY(m_aDegreesTmp[0]);996 SAFEDELETEARRAY(m_aDegreesTmp[1]);997 998 CheckFuzzyIdentity();999 1000 return 1;1001 }1002 1003 /** Checks if given Parts have identical physical and biological properties1004 (except for geometry that might differ).1005 @param P1 Pointer to first Part.1006 @param P2 Pointer to second Part.1007 @return 1 - identical properties, 0 - there are differences.1008 */1009 int ModelSimil::CheckPartsIdentity(Part *P1, Part *P2)1010 {1011 // sprawdz, czy te Parts chociaz sa w sensownym miejscu pamieci1012 assert((P1 != NULL) && (P2 != NULL));1013 1014 if ((P1->assim != P2->assim) ||1015 (P1->friction != P2->friction) ||1016 (P1->ingest != P2->ingest) ||1017 (P1->mass != P2->mass) ||1018 (P1->size != P2->size) ||1019 (P1->density != P2->density))1020 // gdy znaleziono jakas roznice w parametrach fizycznych i1021 // biologicznych1022 return 0;1023 else1024 // gdy nie ma roznic1025 return 1;1026 }1027 990 1028 991 /** Prints the state of the matching object. Debug method. … … 1158 1121 aiKoniecGrupyDopasowania[0]);) 1159 1122 DB(printf("Organizm 1: grupa: (%2i, %2i)\n", aiKoniecPierwszejGrupy[1], 1160 aiKoniecGrupyDopasowania[1]);)1123 aiKoniecGrupyDopasowania[1]);) 1161 1124 1162 1125 for (i = 0; i < aiRozmiarCalychGrup[0]; i++) 1163 1126 { 1164 1127 1165 // iterujemy i - Parts organizmu 0 1166 // (indeks podstawowy - aiKoniecPierwszejGrupy[0]) 1167 1168 if (!(m_pMatching->IsMatched(0, aiKoniecPierwszejGrupy[0] + i))) 1169 { 1170 // interesuja nas tylko te niedopasowane jeszcze (i) 1171 for (j = 0; j < aiRozmiarCalychGrup[1]; j++) 1172 { 1173 1174 // iterujemy j - Parts organizmu 1 1175 // (indeks podstawowy - aiKoniecPierwszejGrupy[1]) 1176 1177 if (!(m_pMatching->IsMatched(1, aiKoniecPierwszejGrupy[1] + j))) 1128 // iterujemy i - Parts organizmu 0 1129 // (indeks podstawowy - aiKoniecPierwszejGrupy[0]) 1130 1131 if (!(m_pMatching->IsMatched(0, aiKoniecPierwszejGrupy[0] + i))) 1132 { 1133 // interesuja nas tylko te niedopasowane jeszcze (i) 1134 for (j = 0; j < aiRozmiarCalychGrup[1]; j++) 1178 1135 { 1179 // interesuja nas tylko te niedopasowane jeszcze (j) 1180 // teraz obliczymy lokalne różnice pomiędzy Parts 1181 iDeg = abs(m_aDegrees[0][aiKoniecPierwszejGrupy[0] + i][1] 1182 - m_aDegrees[1][aiKoniecPierwszejGrupy[1] + j][1]); 1183 1184 //iNit currently is not a component of distance measure 1185 //iNIt = abs(m_aDegrees[0][ aiKoniecPierwszejGrupy[0] + i ][2] 1186 // - m_aDegrees[1][ aiKoniecPierwszejGrupy[1] + j ][2]); 1187 1188 iNeu = abs(m_aDegrees[0][aiKoniecPierwszejGrupy[0] + i][3] 1189 - m_aDegrees[1][aiKoniecPierwszejGrupy[1] + j][3]); 1190 1191 // obliczenie także lokalnych różnic geometrycznych pomiędzy Parts 1192 // find original indices of Parts for both of the models 1193 iPartIndex[0] = m_aDegrees[0][aiKoniecPierwszejGrupy[0] + i][0]; 1194 iPartIndex[1] = m_aDegrees[1][aiKoniecPierwszejGrupy[1] + j][0]; 1195 // now compute the geometrical distance of these Parts (use m_aPositions 1196 // which should be computed by SVD) 1197 Pt3D Part0Pos(m_aPositions[0][iPartIndex[0]]); 1198 Pt3D Part1Pos(m_aPositions[1][iPartIndex[1]]); 1199 dGeo = m_adFactors[3] == 0 ? 0 : Part0Pos.distanceTo(Part1Pos); //no need to compute distane when m_dDG weight is 0 1200 1201 // tutaj prawdopodobnie należy jeszcze dodać sprawdzanie 1202 // identyczności pozostałych własności (oprócz geometrii) 1203 // - żeby móc stwierdzić w ogóle identyczność Parts 1204 1205 // i ostateczna odleglosc indukowana przez te roznice 1206 // (tutaj nie ma różnicy w liczbie wszystkich wierzchołków) 1207 aadOdleglosciParts[i][j] = m_adFactors[1] * double(iDeg) + 1208 m_adFactors[2] * double(iNeu) + 1209 m_adFactors[3] * dGeo; 1210 DB(printf("Parts Distance (%2i,%2i) = %.3lf\n", aiKoniecPierwszejGrupy[0] + i, 1211 aiKoniecPierwszejGrupy[1] + j, aadOdleglosciParts[i][j]);) 1212 DB(printf("Parts geometrical distance = %.20lf\n", dGeo);) 1213 DB(printf("Pos0: (%.3lf %.3lf %.3lf)\n", Part0Pos.x, Part0Pos.y, Part0Pos.z);) 1214 DB(printf("Pos1: (%.3lf %.3lf %.3lf)\n", Part1Pos.x, Part1Pos.y, Part1Pos.z);) 1136 1137 // iterujemy j - Parts organizmu 1 1138 // (indeks podstawowy - aiKoniecPierwszejGrupy[1]) 1139 1140 if (!(m_pMatching->IsMatched(1, aiKoniecPierwszejGrupy[1] + j))) 1141 { 1142 // interesuja nas tylko te niedopasowane jeszcze (j) 1143 // teraz obliczymy lokalne różnice pomiędzy Parts 1144 iDeg = abs(m_aDegrees[0][aiKoniecPierwszejGrupy[0] + i][1] 1145 - m_aDegrees[1][aiKoniecPierwszejGrupy[1] + j][1]); 1146 1147 //iNit currently is not a component of distance measure 1148 //iNIt = abs(m_aDegrees[0][ aiKoniecPierwszejGrupy[0] + i ][2] 1149 // - m_aDegrees[1][ aiKoniecPierwszejGrupy[1] + j ][2]); 1150 1151 iNeu = abs(m_aDegrees[0][aiKoniecPierwszejGrupy[0] + i][3] 1152 - m_aDegrees[1][aiKoniecPierwszejGrupy[1] + j][3]); 1153 1154 // obliczenie także lokalnych różnic geometrycznych pomiędzy Parts 1155 // find original indices of Parts for both of the models 1156 iPartIndex[0] = m_aDegrees[0][aiKoniecPierwszejGrupy[0] + i][0]; 1157 iPartIndex[1] = m_aDegrees[1][aiKoniecPierwszejGrupy[1] + j][0]; 1158 // now compute the geometrical distance of these Parts (use m_aPositions 1159 // which should be computed by SVD) 1160 Pt3D Part0Pos(m_aPositions[0][iPartIndex[0]]); 1161 Pt3D Part1Pos(m_aPositions[1][iPartIndex[1]]); 1162 dGeo = m_adFactors[3] == 0 ? 0 : Part0Pos.distanceTo(Part1Pos); //no need to compute distane when m_dDG weight is 0 1163 1164 // tutaj prawdopodobnie należy jeszcze dodać sprawdzanie 1165 // identyczności pozostałych własności (oprócz geometrii) 1166 // - żeby móc stwierdzić w ogóle identyczność Parts 1167 1168 // i ostateczna odleglosc indukowana przez te roznice 1169 // (tutaj nie ma różnicy w liczbie wszystkich wierzchołków) 1170 aadOdleglosciParts[i][j] = m_adFactors[1] * double(iDeg) + 1171 m_adFactors[2] * double(iNeu) + 1172 m_adFactors[3] * dGeo; 1173 DB(printf("Parts Distance (%2i,%2i) = %.3lf\n", aiKoniecPierwszejGrupy[0] + i, 1174 aiKoniecPierwszejGrupy[1] + j, aadOdleglosciParts[i][j]);) 1175 DB(printf("Parts geometrical distance = %.20lf\n", dGeo);) 1176 DB(printf("Pos0: (%.3lf %.3lf %.3lf)\n", Part0Pos.x, Part0Pos.y, Part0Pos.z);) 1177 DB(printf("Pos1: (%.3lf %.3lf %.3lf)\n", Part1Pos.x, Part1Pos.y, Part1Pos.z);) 1178 } 1215 1179 } 1216 1180 } 1217 }1218 1181 } 1219 1182 … … 1388 1351 if (PartZ1NaLiscie0 || PartZ0NaLiscie1) 1389 1352 { 1390 // PRZYPADEK 2. Tylko jeden z Parts ma drugiego na swojej liscie 1391 // mozliwych dopasowan 1392 // AKCJA. Dopasowanie jednego jest proste (tego, ktory nie ma 1393 // na swojej liscie drugiego). Dla tego drugiego nalezy powtorzyc 1394 // duza czesc obliczen (znalezc mu nowa mozliwa pare) 1395 1396 // indeks organizmu, ktorego Part nie ma dopasowywanego Part 1397 // z drugiego organizmu na swojej liscie 1398 int iBezDrugiego; 1399 1400 // okreslenie indeksu organizmu z dopasowywanym Part 1401 if (!PartZ1NaLiscie0) 1402 { 1403 iBezDrugiego = 0; 1404 } 1405 else 1406 { 1407 iBezDrugiego = 1; 1408 } 1409 // sprawdz indeks organizmu 1410 assert((iBezDrugiego == 0) || (iBezDrugiego == 1)); 1411 1412 int iDopasowywany = -1; 1413 // poszukujemy pierwszego z listy dopasowania 1414 for (i = 0; i < aiRozmiarCalychGrup[1 - iBezDrugiego]; i++) 1415 { 1416 if (apvbCzyMinimalnaOdleglosc[iBezDrugiego]->operator[](i)) 1353 // PRZYPADEK 2. Tylko jeden z Parts ma drugiego na swojej liscie 1354 // mozliwych dopasowan 1355 // AKCJA. Dopasowanie jednego jest proste (tego, ktory nie ma 1356 // na swojej liscie drugiego). Dla tego drugiego nalezy powtorzyc 1357 // duza czesc obliczen (znalezc mu nowa mozliwa pare) 1358 1359 // indeks organizmu, ktorego Part nie ma dopasowywanego Part 1360 // z drugiego organizmu na swojej liscie 1361 int iBezDrugiego; 1362 1363 // okreslenie indeksu organizmu z dopasowywanym Part 1364 if (!PartZ1NaLiscie0) 1417 1365 { 1418 iDopasowywany = i; 1419 break; 1366 iBezDrugiego = 0; 1420 1367 } 1421 } 1422 // sprawdz poprawnosc indeksu dopasowywanego (musimy cos znalezc!) 1423 // nieujemny i w odpowiedniej grupie! 1424 assert((iDopasowywany >= 0) && 1425 (iDopasowywany < aiRozmiarCalychGrup[1 - iBezDrugiego])); 1426 1427 // znalezlismy 1. Part z listy dopasowania - dopasowujemy! 1428 m_pMatching->Match( 1429 iBezDrugiego, 1430 aiKoniecPierwszejGrupy[iBezDrugiego] + iIndex[iBezDrugiego], 1431 1 - iBezDrugiego, 1432 aiKoniecPierwszejGrupy[1 - iBezDrugiego] + iDopasowywany); 1433 DB(printf("Przypadek 2.1.: dopasowane Parts dopasowanie bez drugiego: (%2i, %2i)\n", aiKoniecPierwszejGrupy[iBezDrugiego] + iIndex[iBezDrugiego], 1434 aiKoniecPierwszejGrupy[1 - iBezDrugiego] + iDopasowywany);) 1435 1436 // zmniejsz liczby niedopasowanych elementow w grupach 1437 aiRozmiarGrupy[0]--; 1438 aiRozmiarGrupy[1]--; 1439 1440 // sprawdz, czy jest szansa dopasowania tego Part z drugiej strony 1441 // (ktora miala mozliwosc dopasowania tego Part z poprzedniego organizmu) 1442 if ((aiRozmiarGrupy[0] > 0) && (aiRozmiarGrupy[1] > 0)) 1443 { 1444 // jesli grupy sie jeszcze nie wyczrpaly 1445 // to jest mozliwosc dopasowania w organizmie 1446 1447 int iZDrugim = 1 - iBezDrugiego; 1368 else 1369 { 1370 iBezDrugiego = 1; 1371 } 1448 1372 // sprawdz indeks organizmu 1449 assert((iZDrugim == 0) || (iZDrugim == 1)); 1450 1451 // bedziemy szukac minimum wsrod niedopasowanych - musimy wykasowac 1452 // poprzednie obliczenia minimum 1453 // dla organizmu 1 (o rozmiarze grupy z 0) 1454 for (i = 0; i < aiRozmiarCalychGrup[0]; i++) 1373 assert((iBezDrugiego == 0) || (iBezDrugiego == 1)); 1374 1375 int iDopasowywany = -1; 1376 // poszukujemy pierwszego z listy dopasowania 1377 for (i = 0; i < aiRozmiarCalychGrup[1 - iBezDrugiego]; i++) 1455 1378 { 1456 apvbCzyMinimalnaOdleglosc[1]->operator[](i) = false; 1457 } 1458 // dla organizmu 0 (o rozmiarze grup z 1) 1459 for (i = 0; i < aiRozmiarCalychGrup[1]; i++) 1460 { 1461 apvbCzyMinimalnaOdleglosc[0]->operator[](i) = false; 1462 } 1463 1464 // szukamy na nowo minimum dla Part o indeksie iIndex[ iZDrugim ] w organizmie iZDrugim 1465 // wsrod niedopasowanych Parts z organizmu 1 - iZDrugim 1466 dMinimum = HUGE_VAL; 1467 for (i = 0; i < aiRozmiarCalychGrup[1 - iZDrugim]; i++) 1468 { 1469 if (!(m_pMatching->IsMatched( 1470 1 - iZDrugim, 1471 aiKoniecPierwszejGrupy[1 - iZDrugim] + i))) 1472 { 1473 // szukamy minimum obliczonej lokalnej odleglosci tylko wsrod 1474 // niedopasowanych jeszcze Parts 1475 if (iZDrugim == 0) 1476 { 1477 // teraz niestety musimy rozpoznac odpowiedni organizm 1478 // zeby moc indeksowac niesymetryczna tablice 1479 if (aadOdleglosciParts[iIndex[0]][i] < dMinimum) 1480 { 1481 dMinimum = aadOdleglosciParts[iIndex[0]][i]; 1482 } 1483 // przy okazji - sprawdz, czy HUGE_VAL jest rzeczywiscie max dla double 1484 assert(aadOdleglosciParts[iIndex[0]][i] < HUGE_VAL); 1485 1486 } 1487 else 1488 { 1489 if (aadOdleglosciParts[i][iIndex[1]] < dMinimum) 1490 { 1491 dMinimum = aadOdleglosciParts[i][iIndex[1]]; 1492 } 1493 // przy okazji - sprawdz, czy HUGE_VAL jest rzeczywiscie max dla double 1494 assert(aadOdleglosciParts[i][iIndex[1]] < HUGE_VAL); 1495 } 1496 } 1497 } 1498 // sprawdz, czy minimum znaleziono - musi takie byc, bo jest cos niedopasowanego 1499 assert((dMinimum >= 0.0) && (dMinimum < HUGE_VAL)); 1500 1501 // teraz zaznaczamy w tablicy te wszystkie Parts, ktore maja 1502 // rzeczywiscie te minimalne odleglosci do Part w organizmie iZDrugim 1503 for (i = 0; i < aiRozmiarCalychGrup[1 - iZDrugim]; i++) 1504 { 1505 if (!(m_pMatching->IsMatched( 1506 1 - iZDrugim, 1507 aiKoniecPierwszejGrupy[1 - iZDrugim] + i))) 1508 { 1509 if (iZDrugim == 0) 1510 { 1511 // teraz niestety musimy rozpoznac odpowiedni organizm 1512 // zeby moc indeksowac niesymetryczna tablice 1513 if (aadOdleglosciParts[iIndex[0]][i] == dMinimum) 1514 { 1515 // jesli w danym miejscu tablicy odleglosci jest faktyczne 1516 // minimum odleglosci, to mamy potencjalna pare dla iIndex[1] 1517 apvbCzyMinimalnaOdleglosc[0]->operator[](i) = true; 1518 } 1519 } 1520 else 1521 { 1522 if (aadOdleglosciParts[i][iIndex[1]] == dMinimum) 1523 { 1524 apvbCzyMinimalnaOdleglosc[1]->operator[](i) = true; 1525 } 1526 } 1527 } 1528 } 1529 1530 // a teraz - po znalezieniu potencjalnych elementow do dopasowania 1531 // dopasowujemy pierwszy z potencjalnych 1532 iDopasowywany = -1; 1533 for (i = 0; i < aiRozmiarCalychGrup[1 - iZDrugim]; i++) 1534 { 1535 if (apvbCzyMinimalnaOdleglosc[iZDrugim]->operator[](i)) 1379 if (apvbCzyMinimalnaOdleglosc[iBezDrugiego]->operator[](i)) 1536 1380 { 1537 1381 iDopasowywany = i; … … 1539 1383 } 1540 1384 } 1541 // musielismy znalezc jakiegos dopasowywanego 1385 // sprawdz poprawnosc indeksu dopasowywanego (musimy cos znalezc!) 1386 // nieujemny i w odpowiedniej grupie! 1542 1387 assert((iDopasowywany >= 0) && 1543 (iDopasowywany < aiRozmiarCalychGrup[1 - i ZDrugim]));1544 1545 // no to juz mozemy dopasowac1388 (iDopasowywany < aiRozmiarCalychGrup[1 - iBezDrugiego])); 1389 1390 // znalezlismy 1. Part z listy dopasowania - dopasowujemy! 1546 1391 m_pMatching->Match( 1547 iZDrugim, 1548 aiKoniecPierwszejGrupy[iZDrugim] + iIndex[iZDrugim], 1549 1 - iZDrugim, 1550 aiKoniecPierwszejGrupy[1 - iZDrugim] + iDopasowywany); 1551 DB(printf("Przypadek 2.1.: dopasowane Parts dopasowaniebz drugim: (%2i, %2i)\n", aiKoniecPierwszejGrupy[iZDrugim] + iIndex[iZDrugim], aiKoniecPierwszejGrupy[1 - iZDrugim] + iDopasowywany);) 1552 1553 //aiKoniecPierwszejGrupy[ 1-iBezDrugiego ] + iDopasowywany ;) 1554 //aiKoniecPierwszejGrupy[ 1-iBezDrugiego ] + iDopasowywany ;) 1392 iBezDrugiego, 1393 aiKoniecPierwszejGrupy[iBezDrugiego] + iIndex[iBezDrugiego], 1394 1 - iBezDrugiego, 1395 aiKoniecPierwszejGrupy[1 - iBezDrugiego] + iDopasowywany); 1396 DB(printf("Przypadek 2.1.: dopasowane Parts dopasowanie bez drugiego: (%2i, %2i)\n", aiKoniecPierwszejGrupy[iBezDrugiego] + iIndex[iBezDrugiego], 1397 aiKoniecPierwszejGrupy[1 - iBezDrugiego] + iDopasowywany);) 1398 1555 1399 // zmniejsz liczby niedopasowanych elementow w grupach 1556 1400 aiRozmiarGrupy[0]--; 1557 1401 aiRozmiarGrupy[1]--; 1558 1402 1559 } 1560 else 1561 { 1562 // jedna z grup sie juz wyczerpala 1563 // wiec nie ma mozliwosci dopasowania tego drugiego Partu 1564 /// i trzeba poczekac na zmiane grupy 1565 } 1566 1567 DB(printf("Przypadek 2.\n");) 1403 // sprawdz, czy jest szansa dopasowania tego Part z drugiej strony 1404 // (ktora miala mozliwosc dopasowania tego Part z poprzedniego organizmu) 1405 if ((aiRozmiarGrupy[0] > 0) && (aiRozmiarGrupy[1] > 0)) 1406 { 1407 // jesli grupy sie jeszcze nie wyczrpaly 1408 // to jest mozliwosc dopasowania w organizmie 1409 1410 int iZDrugim = 1 - iBezDrugiego; 1411 // sprawdz indeks organizmu 1412 assert((iZDrugim == 0) || (iZDrugim == 1)); 1413 1414 // bedziemy szukac minimum wsrod niedopasowanych - musimy wykasowac 1415 // poprzednie obliczenia minimum 1416 // dla organizmu 1 (o rozmiarze grupy z 0) 1417 for (i = 0; i < aiRozmiarCalychGrup[0]; i++) 1418 { 1419 apvbCzyMinimalnaOdleglosc[1]->operator[](i) = false; 1420 } 1421 // dla organizmu 0 (o rozmiarze grup z 1) 1422 for (i = 0; i < aiRozmiarCalychGrup[1]; i++) 1423 { 1424 apvbCzyMinimalnaOdleglosc[0]->operator[](i) = false; 1425 } 1426 1427 // szukamy na nowo minimum dla Part o indeksie iIndex[ iZDrugim ] w organizmie iZDrugim 1428 // wsrod niedopasowanych Parts z organizmu 1 - iZDrugim 1429 dMinimum = HUGE_VAL; 1430 for (i = 0; i < aiRozmiarCalychGrup[1 - iZDrugim]; i++) 1431 { 1432 if (!(m_pMatching->IsMatched( 1433 1 - iZDrugim, 1434 aiKoniecPierwszejGrupy[1 - iZDrugim] + i))) 1435 { 1436 // szukamy minimum obliczonej lokalnej odleglosci tylko wsrod 1437 // niedopasowanych jeszcze Parts 1438 if (iZDrugim == 0) 1439 { 1440 // teraz niestety musimy rozpoznac odpowiedni organizm 1441 // zeby moc indeksowac niesymetryczna tablice 1442 if (aadOdleglosciParts[iIndex[0]][i] < dMinimum) 1443 { 1444 dMinimum = aadOdleglosciParts[iIndex[0]][i]; 1445 } 1446 // przy okazji - sprawdz, czy HUGE_VAL jest rzeczywiscie max dla double 1447 assert(aadOdleglosciParts[iIndex[0]][i] < HUGE_VAL); 1448 1449 } 1450 else 1451 { 1452 if (aadOdleglosciParts[i][iIndex[1]] < dMinimum) 1453 { 1454 dMinimum = aadOdleglosciParts[i][iIndex[1]]; 1455 } 1456 // przy okazji - sprawdz, czy HUGE_VAL jest rzeczywiscie max dla double 1457 assert(aadOdleglosciParts[i][iIndex[1]] < HUGE_VAL); 1458 } 1459 } 1460 } 1461 // sprawdz, czy minimum znaleziono - musi takie byc, bo jest cos niedopasowanego 1462 assert((dMinimum >= 0.0) && (dMinimum < HUGE_VAL)); 1463 1464 // teraz zaznaczamy w tablicy te wszystkie Parts, ktore maja 1465 // rzeczywiscie te minimalne odleglosci do Part w organizmie iZDrugim 1466 for (i = 0; i < aiRozmiarCalychGrup[1 - iZDrugim]; i++) 1467 { 1468 if (!(m_pMatching->IsMatched( 1469 1 - iZDrugim, 1470 aiKoniecPierwszejGrupy[1 - iZDrugim] + i))) 1471 { 1472 if (iZDrugim == 0) 1473 { 1474 // teraz niestety musimy rozpoznac odpowiedni organizm 1475 // zeby moc indeksowac niesymetryczna tablice 1476 if (aadOdleglosciParts[iIndex[0]][i] == dMinimum) 1477 { 1478 // jesli w danym miejscu tablicy odleglosci jest faktyczne 1479 // minimum odleglosci, to mamy potencjalna pare dla iIndex[1] 1480 apvbCzyMinimalnaOdleglosc[0]->operator[](i) = true; 1481 } 1482 } 1483 else 1484 { 1485 if (aadOdleglosciParts[i][iIndex[1]] == dMinimum) 1486 { 1487 apvbCzyMinimalnaOdleglosc[1]->operator[](i) = true; 1488 } 1489 } 1490 } 1491 } 1492 1493 // a teraz - po znalezieniu potencjalnych elementow do dopasowania 1494 // dopasowujemy pierwszy z potencjalnych 1495 iDopasowywany = -1; 1496 for (i = 0; i < aiRozmiarCalychGrup[1 - iZDrugim]; i++) 1497 { 1498 if (apvbCzyMinimalnaOdleglosc[iZDrugim]->operator[](i)) 1499 { 1500 iDopasowywany = i; 1501 break; 1502 } 1503 } 1504 // musielismy znalezc jakiegos dopasowywanego 1505 assert((iDopasowywany >= 0) && 1506 (iDopasowywany < aiRozmiarCalychGrup[1 - iZDrugim])); 1507 1508 // no to juz mozemy dopasowac 1509 m_pMatching->Match( 1510 iZDrugim, 1511 aiKoniecPierwszejGrupy[iZDrugim] + iIndex[iZDrugim], 1512 1 - iZDrugim, 1513 aiKoniecPierwszejGrupy[1 - iZDrugim] + iDopasowywany); 1514 DB(printf("Przypadek 2.1.: dopasowane Parts dopasowaniebz drugim: (%2i, %2i)\n", aiKoniecPierwszejGrupy[iZDrugim] + iIndex[iZDrugim], aiKoniecPierwszejGrupy[1 - iZDrugim] + iDopasowywany);) 1515 1516 //aiKoniecPierwszejGrupy[ 1-iBezDrugiego ] + iDopasowywany ;) 1517 //aiKoniecPierwszejGrupy[ 1-iBezDrugiego ] + iDopasowywany ;) 1518 // zmniejsz liczby niedopasowanych elementow w grupach 1519 aiRozmiarGrupy[0]--; 1520 aiRozmiarGrupy[1]--; 1521 1522 } 1523 else 1524 { 1525 // jedna z grup sie juz wyczerpala 1526 // wiec nie ma mozliwosci dopasowania tego drugiego Partu 1527 /// i trzeba poczekac na zmiane grupy 1528 } 1529 1530 DB(printf("Przypadek 2.\n");) 1568 1531 1569 1532 }// PRZYPADEK 2. … … 1724 1687 if (m_adFactors[3] > 0) 1725 1688 { 1726 // tutaj zacznij pętlę po przekształceniach geometrycznych1727 const int NO_OF_TRANSFORM = 8; // liczba transformacji geometrycznych (na razie tylko ID i O_YZ)1728 // tablice transformacji współrzędnych; nie są to dokładnie tablice tranformacji, ale raczej tablice PRZEJŚĆ1729 // pomiędzy transformacjami;1730 // wartości orginalne transformacji dOrig uzyskuje się przez:1731 // for ( iTrans = 0; iTrans <= TRANS_INDEX; iTrans++ ) dOrig *= dMul[ iTrans ];1732 //const char *szTransformNames[NO_OF_TRANSFORM] = { "ID", "S_yz", "S_xz", "S_xy", "R180_z", "R180_y", "R180_z", "S_(0,0,0)" };1733 const int dMulX[NO_OF_TRANSFORM] = { 1, -1, -1, 1, -1, 1, -1, -1 };1734 const int dMulY[NO_OF_TRANSFORM] = { 1, 1, -1, -1, -1, -1, -1, 1 };1735 const int dMulZ[NO_OF_TRANSFORM] = { 1, 1, 1, -1, -1, -1, 1, 1 };1689 // tutaj zacznij pętlę po przekształceniach geometrycznych 1690 const int NO_OF_TRANSFORM = 8; // liczba transformacji geometrycznych (na razie tylko ID i O_YZ) 1691 // tablice transformacji współrzędnych; nie są to dokładnie tablice tranformacji, ale raczej tablice PRZEJŚĆ 1692 // pomiędzy transformacjami; 1693 // wartości orginalne transformacji dOrig uzyskuje się przez: 1694 // for ( iTrans = 0; iTrans <= TRANS_INDEX; iTrans++ ) dOrig *= dMul[ iTrans ]; 1695 //const char *szTransformNames[NO_OF_TRANSFORM] = { "ID", "S_yz", "S_xz", "S_xy", "R180_z", "R180_y", "R180_z", "S_(0,0,0)" }; 1696 const int dMulX[NO_OF_TRANSFORM] = { 1, -1, -1, 1, -1, 1, -1, -1 }; 1697 const int dMulY[NO_OF_TRANSFORM] = { 1, 1, -1, -1, -1, -1, -1, 1 }; 1698 const int dMulZ[NO_OF_TRANSFORM] = { 1, 1, 1, -1, -1, -1, 1, 1 }; 1736 1699 1737 1700 #ifdef max 1738 1701 #undef max //this macro would conflict with line below 1739 1702 #endif 1740 double dMinSimValue = std::numeric_limits<double>::max(); // minimum value of similarity 1741 int iMinSimTransform = -1; // index of the transformation with the minimum similarity 1742 SimilMatching *pMinSimMatching = NULL; // matching with the minimum value of similarity 1743 1744 // remember the original positions of model 0 as computed by SVD in order to restore them later, after 1745 // all transformations have been computed 1746 Pt3D *StoredPositions = NULL; // array of positions of Parts, for one (0th) model 1747 // create the stored positions 1748 StoredPositions = new Pt3D[m_Mod[0]->getPartCount()]; 1749 assert(StoredPositions != NULL); 1750 // copy the original positions of model 0 (store them) 1751 int iPart; // a counter of Parts 1752 for (iPart = 0; iPart < m_Mod[0]->getPartCount(); iPart++) 1753 { 1754 StoredPositions[iPart].x = m_aPositions[0][iPart].x; 1755 StoredPositions[iPart].y = m_aPositions[0][iPart].y; 1756 StoredPositions[iPart].z = m_aPositions[0][iPart].z; 1757 } 1758 // now the original positions of model 0 are stored 1759 1760 1761 int iTransform; // a counter of geometric transformations 1762 for (iTransform = 0; iTransform < NO_OF_TRANSFORM; iTransform++) 1763 { 1764 // for each geometric transformation to be done 1765 // entry conditions: 1766 // - models (m_Mod) exist and are available 1767 // - matching (m_pMatching) exists and is empty 1768 // - all properties are created and available (m_aDegrees and m_aPositions) 1769 1770 // recompute geometric properties according to the transformation iTransform 1771 // but only for model 0 1703 double dMinSimValue = std::numeric_limits<double>::max(); // minimum value of similarity 1704 int iMinSimTransform = -1; // index of the transformation with the minimum similarity 1705 SimilMatching *pMinSimMatching = NULL; // matching with the minimum value of similarity 1706 1707 // remember the original positions of model 0 as computed by SVD in order to restore them later, after 1708 // all transformations have been computed 1709 Pt3D *StoredPositions = NULL; // array of positions of Parts, for one (0th) model 1710 // create the stored positions 1711 StoredPositions = new Pt3D[m_Mod[0]->getPartCount()]; 1712 assert(StoredPositions != NULL); 1713 // copy the original positions of model 0 (store them) 1714 int iPart; // a counter of Parts 1772 1715 for (iPart = 0; iPart < m_Mod[0]->getPartCount(); iPart++) 1773 1716 { 1774 // for each iPart, a part of the model iMod 1775 m_aPositions[0][iPart].x *= dMulX[iTransform]; 1776 m_aPositions[0][iPart].y *= dMulY[iTransform]; 1777 m_aPositions[0][iPart].z *= dMulZ[iTransform]; 1717 StoredPositions[iPart].x = m_aPositions[0][iPart].x; 1718 StoredPositions[iPart].y = m_aPositions[0][iPart].y; 1719 StoredPositions[iPart].z = m_aPositions[0][iPart].z; 1778 1720 } 1779 // now the positions are recomputed 1780 ComputeMatching(); 1781 1782 // teraz m_pMatching istnieje i jest pełne 1783 assert(m_pMatching != NULL); 1784 assert(m_pMatching->IsFull() == true); 1785 1786 // wykorzystaj to dopasowanie i geometrię do obliczenia tymczasowej wartości miary 1787 int iTempRes = CountPartsDistance(); 1788 // załóż sukces 1789 assert(iTempRes == 1); 1790 double dCurrentSim = m_adFactors[0] * double(m_iDV) + 1791 m_adFactors[1] * double(m_iDD) + 1792 m_adFactors[2] * double(m_iDN) + 1793 m_adFactors[3] * double(m_dDG); 1794 // załóż poprawną wartość podobieństwa 1795 assert(dCurrentSim >= 0.0); 1796 1797 // porównaj wartość obliczoną z dotychczasowym minimum 1798 if (dCurrentSim < dMinSimValue) 1799 { 1800 // jeśli uzyskano mniejszą wartość dopasowania, 1801 // to zapamiętaj to przekształcenie geometryczne i dopasowanie 1802 dMinSimValue = dCurrentSim; 1803 iMinSimTransform = iTransform; 1804 SAFEDELETE(pMinSimMatching); 1805 pMinSimMatching = new SimilMatching(*m_pMatching); 1806 assert(pMinSimMatching != NULL); 1721 // now the original positions of model 0 are stored 1722 1723 1724 int iTransform; // a counter of geometric transformations 1725 for (iTransform = 0; iTransform < NO_OF_TRANSFORM; iTransform++) 1726 { 1727 // for each geometric transformation to be done 1728 // entry conditions: 1729 // - models (m_Mod) exist and are available 1730 // - matching (m_pMatching) exists and is empty 1731 // - all properties are created and available (m_aDegrees and m_aPositions) 1732 1733 // recompute geometric properties according to the transformation iTransform 1734 // but only for model 0 1735 for (iPart = 0; iPart < m_Mod[0]->getPartCount(); iPart++) 1736 { 1737 // for each iPart, a part of the model iMod 1738 m_aPositions[0][iPart].x *= dMulX[iTransform]; 1739 m_aPositions[0][iPart].y *= dMulY[iTransform]; 1740 m_aPositions[0][iPart].z *= dMulZ[iTransform]; 1741 } 1742 // now the positions are recomputed 1743 ComputeMatching(); 1744 1745 // teraz m_pMatching istnieje i jest pełne 1746 assert(m_pMatching != NULL); 1747 assert(m_pMatching->IsFull() == true); 1748 1749 // wykorzystaj to dopasowanie i geometrię do obliczenia tymczasowej wartości miary 1750 int iTempRes = CountPartsDistance(); 1751 // załóż sukces 1752 assert(iTempRes == 1); 1753 double dCurrentSim = m_adFactors[0] * double(m_iDV) + 1754 m_adFactors[1] * double(m_iDD) + 1755 m_adFactors[2] * double(m_iDN) + 1756 m_adFactors[3] * double(m_dDG); 1757 // załóż poprawną wartość podobieństwa 1758 assert(dCurrentSim >= 0.0); 1759 1760 // porównaj wartość obliczoną z dotychczasowym minimum 1761 if (dCurrentSim < dMinSimValue) 1762 { 1763 // jeśli uzyskano mniejszą wartość dopasowania, 1764 // to zapamiętaj to przekształcenie geometryczne i dopasowanie 1765 dMinSimValue = dCurrentSim; 1766 iMinSimTransform = iTransform; 1767 SAFEDELETE(pMinSimMatching); 1768 pMinSimMatching = new SimilMatching(*m_pMatching); 1769 assert(pMinSimMatching != NULL); 1770 } 1771 1772 // teraz już można usunąć stare dopasowanie (dla potrzeb następnego przebiegu pętli) 1773 m_pMatching->Empty(); 1774 } // for ( iTransform ) 1775 1776 // po pętli przywróć najlepsze dopasowanie 1777 delete m_pMatching; 1778 m_pMatching = pMinSimMatching; 1779 1780 DB(printf("Matching has been chosen!\n");) 1781 // print the name of the chosen transformation: 1782 // printf("Chosen transformation: %s\n", szTransformNames[ iMinSimTransform ] ); 1783 1784 // i przywróć jednocześnie pozycje Parts modelu 0 dla tego dopasowania 1785 // - najpierw przywroc Parts pozycje orginalne, po SVD 1786 for (iPart = 0; iPart < m_Mod[0]->getPartCount(); iPart++) 1787 { 1788 m_aPositions[0][iPart].x = StoredPositions[iPart].x; 1789 m_aPositions[0][iPart].y = StoredPositions[iPart].y; 1790 m_aPositions[0][iPart].z = StoredPositions[iPart].z; 1791 } 1792 // - usun teraz zapamietane pozycje Parts 1793 delete[] StoredPositions; 1794 // - a teraz oblicz na nowo wspolrzedne wlasciwego przeksztalcenia dla model 0 1795 for (iTransform = 0; iTransform <= iMinSimTransform; iTransform++) 1796 { 1797 // for each transformation before and INCLUDING iMinTransform 1798 // do the transformation (only model 0) 1799 for (iPart = 0; iPart < m_Mod[0]->getPartCount(); iPart++) 1800 { 1801 m_aPositions[0][iPart].x *= dMulX[iTransform]; 1802 m_aPositions[0][iPart].y *= dMulY[iTransform]; 1803 m_aPositions[0][iPart].z *= dMulZ[iTransform]; 1804 } 1807 1805 } 1808 1809 // teraz już można usunąć stare dopasowanie (dla potrzeb następnego przebiegu pętli)1810 m_pMatching->Empty();1811 } // for ( iTransform )1812 1813 // po pętli przywróć najlepsze dopasowanie1814 delete m_pMatching;1815 m_pMatching = pMinSimMatching;1816 1817 DB(printf("Matching has been chosen!\n");)1818 // print the name of the chosen transformation:1819 // printf("Chosen transformation: %s\n", szTransformNames[ iMinSimTransform ] );1820 1821 // i przywróć jednocześnie pozycje Parts modelu 0 dla tego dopasowania1822 // - najpierw przywroc Parts pozycje orginalne, po SVD1823 for (iPart = 0; iPart < m_Mod[0]->getPartCount(); iPart++)1824 {1825 m_aPositions[0][iPart].x = StoredPositions[iPart].x;1826 m_aPositions[0][iPart].y = StoredPositions[iPart].y;1827 m_aPositions[0][iPart].z = StoredPositions[iPart].z;1828 }1829 // - usun teraz zapamietane pozycje Parts1830 delete[] StoredPositions;1831 // - a teraz oblicz na nowo wspolrzedne wlasciwego przeksztalcenia dla model 01832 for (iTransform = 0; iTransform <= iMinSimTransform; iTransform++)1833 {1834 // for each transformation before and INCLUDING iMinTransform1835 // do the transformation (only model 0)1836 for (iPart = 0; iPart < m_Mod[0]->getPartCount(); iPart++)1837 {1838 m_aPositions[0][iPart].x *= dMulX[iTransform];1839 m_aPositions[0][iPart].y *= dMulY[iTransform];1840 m_aPositions[0][iPart].z *= dMulZ[iTransform];1841 }1842 }1843 1806 1844 1807 } … … 1855 1818 1856 1819 DB(_PrintPartsMatching();) 1857 1858 1820 1859 1821 return 1; … … 1985 1947 int nSize = m_Mod[iMod]->getPartCount(); 1986 1948 1987 double *pDistances = 1949 double *pDistances = new double[nSize * nSize]; 1988 1950 1989 1951 for (int i = 0; i < nSize; i++) … … 1997 1959 Pt3D P1Pos, P2Pos; // positions of parts 1998 1960 double dDistance; // the distance between Parts 1999 1961 2000 1962 double *weights = new double[nSize]; 2001 1963 for (int i = 0; i < nSize; i++) 2002 1964 { 2003 if (wMDS ==1)1965 if (wMDS == 1) 2004 1966 weights[i] = 0; 2005 1967 else 2006 1968 weights[i] = 1; 2007 1969 } 2008 2009 if (wMDS ==1)1970 1971 if (wMDS == 1) 2010 1972 for (int i = 0; i < pModel->getJointCount(); i++) 2011 1973 { 2012 1974 weights[pModel->getJoint(i)->p1_refno]++; 2013 weights[pModel->getJoint(i)->p2_refno]++; 1975 weights[pModel->getJoint(i)->p2_refno]++; 2014 1976 } 2015 1977 2016 1978 for (iP1 = 0; iP1 < pModel->getPartCount(); iP1++) 2017 1979 { … … 2057 2019 } 2058 2020 2021 /** Evaluates distance between two given genotypes. The distance depends strongly 2022 on weights set and the matching algorithm used. 2023 @param G0 Pointer to the first of compared genotypes 2024 @param G1 Pointer to the second of compared genotypes. 2025 @return Distance between two genotypes. 2026 @sa m_adFactors, matching_method 2027 */ 2028 double ModelSimil::EvaluateDistance(const Geno *G0, const Geno *G1) 2029 { 2030 return matching_method == 0 ? EvaluateDistanceHungarian(G0, G1) : EvaluateDistanceGreedy(G0, G1); 2031 } 2032 2059 2033 void ModelSimil::p_evaldistance(ExtValue *args, ExtValue *ret) 2060 2034 { … … 2066 2040 ret->setDouble(EvaluateDistance(g1, g2)); 2067 2041 } 2042 2043 void ModelSimil::FillPartsDistances(double*& dist, int bigger, int smaller, bool geo) 2044 { 2045 for (int i = 0; i < bigger; i++) 2046 { 2047 for (int j = 0; j < bigger; j++) 2048 { 2049 // assign penalty for unassignment for vertex from bigger model 2050 if (j >= smaller) 2051 { 2052 if (geo) 2053 dist[i*bigger + j] += m_adFactors[3] * m_aPositions[1 - m_iSmaller][i].length(); 2054 else 2055 dist[i*bigger + j] = m_adFactors[1] * m_aDegrees[1 - m_iSmaller][i][DEGREE] + m_adFactors[2] * m_aDegrees[1 - m_iSmaller][i][NEURONS]; 2056 } 2057 // compute distance between parts 2058 else 2059 { 2060 if (geo) 2061 dist[i*bigger + j] += m_adFactors[3] * m_aPositions[1 - m_iSmaller][i].distanceTo(m_aPositions[m_iSmaller][j]); 2062 else 2063 dist[i*bigger + j] = m_adFactors[1] * abs(m_aDegrees[1 - m_iSmaller][i][DEGREE] - m_aDegrees[m_iSmaller][j][DEGREE]) 2064 + m_adFactors[2] * abs(m_aDegrees[1 - m_iSmaller][i][NEURONS] - m_aDegrees[m_iSmaller][j][NEURONS]); 2065 } 2066 2067 } 2068 } 2069 } 2070 2071 double ModelSimil::EvaluateDistanceHungarian(const Geno *G0, const Geno *G1) 2072 { 2073 double dResult = 0; 2074 2075 m_Gen[0] = G0; 2076 m_Gen[1] = G1; 2077 2078 // check whether pointers are not NULL 2079 if (m_Gen[0] == NULL || m_Gen[1] == NULL) 2080 { 2081 DB(printf("ModelSimil::EvaluateDistanceHungarian - invalid genotypes pointers\n");) 2082 return 0.0; 2083 } 2084 // create models of objects to compare 2085 m_Mod[0] = new Model(*(m_Gen[0])); 2086 m_Mod[1] = new Model(*(m_Gen[1])); 2087 2088 // validate models 2089 if (m_Mod[0] == NULL || m_Mod[1] == NULL || !(m_Mod[0]->isValid()) || !(m_Mod[1]->isValid())) 2090 { 2091 DB(printf("ModelSimil::EvaluateDistanceHungarian - invalid models pointers\n");) 2092 return 0.0; 2093 } 2094 2095 //Get information about vertex degrees, neurons and 3D location 2096 if (!CreatePartInfoTables()) 2097 return 0; 2098 if (!CountPartDegrees()) 2099 return 0; 2100 if (!GetPartPositions()) 2101 return 0; 2102 if (!CountPartNeurons()) 2103 return 0; 2104 2105 m_iSmaller = m_Mod[0]->getPartCount() <= m_Mod[1]->getPartCount() ? 0 : 1; 2106 int nSmaller = m_Mod[m_iSmaller]->getPartCount(); 2107 int nBigger = m_Mod[1 - m_iSmaller]->getPartCount(); 2108 2109 double* partsDistances = new double[nBigger*nBigger](); 2110 FillPartsDistances(partsDistances, nBigger, nSmaller, false); 2111 int *assignment = new int[nBigger](); 2112 2113 HungarianAlgorithm hungarian; 2114 2115 if (m_adFactors[3] > 0) 2116 { 2117 if (!ComputePartsPositionsBySVD()) 2118 { 2119 return 0; 2120 } 2121 2122 // tutaj zacznij pętlę po przekształceniach geometrycznych 2123 const int NO_OF_TRANSFORM = 8; // liczba transformacji geometrycznych (na razie tylko ID i O_YZ) 2124 // tablice transformacji współrzędnych; nie są to dokładnie tablice tranformacji, ale raczej tablice PRZEJŚĆ 2125 // pomiędzy transformacjami; 2126 const int dMulX[NO_OF_TRANSFORM] = { 1, -1, -1, 1, -1, 1, -1, -1 }; 2127 const int dMulY[NO_OF_TRANSFORM] = { 1, 1, -1, -1, -1, -1, -1, 1 }; 2128 const int dMulZ[NO_OF_TRANSFORM] = { 1, 1, 1, -1, -1, -1, 1, 1 }; 2129 2130 std::vector<int> minAssignment(nBigger); 2131 #ifdef max 2132 #undef max //this macro would conflict with line below 2133 #endif 2134 double dMinSimValue = std::numeric_limits<double>::max(); // minimum value of similarity 2135 2136 int iTransform; // a counter of geometric transformations 2137 for (iTransform = 0; iTransform < NO_OF_TRANSFORM; iTransform++) 2138 { 2139 // for each geometric transformation to be done 2140 // entry conditions: 2141 // - models (m_Mod) exist and are available 2142 // - all properties are created and available (m_aDegrees and m_aPositions) 2143 double* tmpPartsDistances = new double[nBigger*nBigger](); 2144 std::copy(partsDistances, partsDistances + nBigger * nBigger, tmpPartsDistances); 2145 // recompute geometric properties according to the transformation iTransform 2146 // but only for model 0 2147 for (int iPart = 0; iPart < m_Mod[m_iSmaller]->getPartCount(); iPart++) 2148 { 2149 // for each iPart, a part of the model iMod 2150 m_aPositions[m_iSmaller][iPart].x *= dMulX[iTransform]; 2151 m_aPositions[m_iSmaller][iPart].y *= dMulY[iTransform]; 2152 m_aPositions[m_iSmaller][iPart].z *= dMulZ[iTransform]; 2153 } 2154 // now the positions are recomputed 2155 2156 FillPartsDistances(tmpPartsDistances, nBigger, nSmaller, true); 2157 std::fill_n(assignment, nBigger, 0); 2158 double dCurrentSim = hungarian.Solve(tmpPartsDistances, assignment, nBigger, nBigger); 2159 2160 delete[] tmpPartsDistances; 2161 // załóż poprawną wartość podobieństwa 2162 assert(dCurrentSim >= 0.0); 2163 2164 // porównaj wartość obliczoną z dotychczasowym minimum 2165 if (dCurrentSim < dMinSimValue) 2166 { 2167 dMinSimValue = dCurrentSim; 2168 if (saveMatching == 1) 2169 { 2170 minAssignment.clear(); 2171 minAssignment.insert(minAssignment.begin(), assignment, assignment + nBigger); 2172 } 2173 } 2174 } 2175 2176 dResult = dMinSimValue; 2177 if (saveMatching == 1) 2178 std::copy(minAssignment.begin(), minAssignment.end(), assignment); 2179 } 2180 2181 else 2182 { 2183 dResult = hungarian.Solve(partsDistances, assignment, nBigger, nBigger); 2184 } 2185 2186 //add difference in anywhere and onJoint neurons 2187 dResult += m_adFactors[2] * (abs(m_aOnJoint[0][3] - m_aOnJoint[1][3]) + abs(m_aAnywhere[0][3] - m_aAnywhere[1][3])); 2188 //add difference in part numbers 2189 dResult += (nBigger - nSmaller) * m_adFactors[0]; 2190 2191 // delete degree arrays created in CreatePartInfoTables 2192 SAFEDELETEARRAY(m_aDegrees[0]); 2193 SAFEDELETEARRAY(m_aDegrees[1]); 2194 2195 // and position arrays 2196 SAFEDELETEARRAY(m_aPositions[0]); 2197 SAFEDELETEARRAY(m_aPositions[1]); 2198 2199 // delete created models 2200 SAFEDELETE(m_Mod[0]); 2201 SAFEDELETE(m_Mod[1]); 2202 2203 delete[] assignment; 2204 delete[] partsDistances; 2205 2206 return dResult; 2207 } -
cpp/frams/model/similarity/simil_model.h
r817 r869 1 1 // This file is a part of Framsticks SDK. http://www.framsticks.com/ 2 // Copyright (C) 1999-201 6Maciej Komosinski and Szymon Ulatowski.2 // Copyright (C) 1999-2019 Maciej Komosinski and Szymon Ulatowski. 3 3 // See LICENSE.txt for details. 4 4 … … 9 9 #include "frams/genetics/geno.h" 10 10 #include "frams/model/model.h" 11 #include "frams/util/3d.h"12 11 #include "simil_match.h" 13 12 … … 27 26 * Marek Kubiak (concept, implementation) 28 27 * Maciej Komosinski (concept, Framsticks interface) 29 * Agnieszka Mensfelt (refactoring )28 * Agnieszka Mensfelt (refactoring, improvements) 30 29 */ 31 30 class ModelSimil … … 34 33 ModelSimil(); 35 34 virtual ~ModelSimil(); 36 double EvaluateDistance(const Geno *G0, const Geno *G1); 35 double EvaluateDistance(const Geno *G0, const Geno *G1); //chooses greedy or hungarian 36 double EvaluateDistanceGreedy(const Geno *G0, const Geno *G1); 37 double EvaluateDistanceHungarian(const Geno *G0, const Geno *G1); 37 38 38 39 static int CompareDegrees(const void *pElem1, const void *pElem2); 40 static int CompareFuzzyDegrees(const void *pElem1, const void *pElem2); 39 41 static int CompareConnsNo(const void *pElem1, const void *pElem2); 40 42 static int GetNOFactors(); … … 48 50 int MatchPartsGeometry(); 49 51 void ComputeMatching(); 52 void FillPartsDistances(double *&dist, int bigger, int smaller, bool geo); 50 53 void _PrintPartsMatching(); 51 54 void SaveIntermediateFiles(); 52 55 53 static int CheckPartsIdentity(Part *P1, Part *P2); 56 static int CheckPartsIdentity(Part *P1, Part *P2); //TODO exists? 54 57 int SortPartInfoTables(); 55 58 int CountPartNeurons(); … … 58 61 int CountPartDegrees(); 59 62 60 int SortPartInfoFuzzy();61 63 void CountFuzzyNeighb(); 62 64 void SortFuzzyNeighb(); 63 65 void GetNeighbIndexes(int mod, int partInd, std::vector<int> &indexes); 64 void CheckFuzzyIdentity();66 void FuzzyOrder(); 65 67 66 68 int CreatePartInfoTables(); … … 68 70 void _PrintArray(int *array, int base, int size); 69 71 void _PrintNeighbourhood(int i); 72 void _PrintFuzzyNeighbourhood(int i); 70 73 void _PrintArrayDouble(double *array, int base, int size); 71 74 int CountPartsDistance(); … … 73 76 74 77 public: 78 /// Currently selected matching algorithm. Allowed values: 0 (more exact, slower), 1 (more greedy, faster). Details in https://doi.org/10.1007/978-3-030-16692-2_8 79 /// @sa EvaluateDistance 80 int matching_method; 81 75 82 /// Table of weights for weighted distance function. 76 83 /// Weights are for factors in the following order: … … 88 95 int fuzzyDepth; 89 96 int isFuzzy; 90 97 91 98 //For wMDS = 1 weighted MDS with vertex degrees as weights is used for the alignment. 92 99 int wMDS; 100 101 //For saveMatching = 1 the best matching found will be saved. 102 int saveMatching; 93 103 94 104 /// Interface to local parameters … … 181 191 }; 182 192 183 184 193 #endif
Note: See TracChangeset
for help on using the changeset viewer.