| 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 | // implementation of the ModelSimil class. |
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| 6 | |
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| 7 | #include "SVD/matrix_tools.h" |
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| 8 | #include "hungarian/hungarian.h" |
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| 9 | #include "simil_model.h" |
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| 10 | #include "simil_match.h" |
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| 11 | #include "frams/model/modelparts.h" |
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| 12 | #include "frams/util/list.h" |
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| 13 | #include "common/nonstd.h" |
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| 14 | #include <frams/vm/classes/genoobj.h> |
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| 15 | #ifdef EMSCRIPTEN |
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| 16 | #include <cstdlib> |
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| 17 | #else |
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| 18 | #include <stdlib.h> |
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| 19 | #endif |
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| 20 | #include <math.h> |
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| 21 | #include <string> |
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| 22 | #include <limits> |
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| 23 | #include <assert.h> |
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| 24 | #include <vector> |
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| 25 | #include <algorithm> |
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| 26 | #include <cstdlib> //required for std::qsort in macos xcode |
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| 27 | |
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| 28 | #define DB(x) //define as x if you want to print debug information |
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| 29 | |
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| 30 | const int ModelSimil::iNOFactors = 4; |
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| 31 | //depth of the fuzzy neighbourhood |
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| 32 | int fuzDepth = 0; |
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| 33 | |
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| 34 | #define FIELDSTRUCT ModelSimil |
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| 35 | |
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| 36 | static ParamEntry MSparam_tab[] = { |
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| 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", }, |
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| 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), "",}, |
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| 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.", }, |
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| 40 | { "simil_partdeg", 0, 0, "Weight of parts' degree", "f 0 100 1", FIELD(m_adFactors[1]), "", }, |
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| 41 | { "simil_neuro", 0, 0, "Weight of neurons count", "f 0 100 0.1", FIELD(m_adFactors[2]), "", }, |
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| 42 | { "simil_partgeom", 0, 0, "Weight of parts' geometric distances", "f 0 100 0", FIELD(m_adFactors[3]), "", }, |
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| 43 | { "simil_fixedZaxis", 0, 0, "Fix 'z' (vertical) axis?", "d 0 1 0", FIELD(fixedZaxis), "", }, |
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| 44 | { "simil_weightedMDS", 0, 0, "Should weighted MDS be used?", "d 0 1 0", FIELD(wMDS), "If activated, weighted MDS with vertex (i.e., Part) degrees as weights is used for 3D alignment of body structure.", }, |
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| 45 | { "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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| 46 | { 0, }, |
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| 47 | }; |
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| 48 | |
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| 49 | #undef FIELDSTRUCT |
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| 50 | |
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| 51 | ////////////////////////////////////////////////////////////////////// |
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| 52 | // Construction/Destruction |
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| 53 | ////////////////////////////////////////////////////////////////////// |
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| 54 | |
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| 55 | /** Constructor. Sets default weights. Initializes other fields with zeros. |
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| 56 | */ |
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| 57 | ModelSimil::ModelSimil() : localpar(MSparam_tab, this), m_iDV(0), m_iDD(0), m_iDN(0), m_dDG(0.0) |
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| 58 | { |
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| 59 | localpar.setDefault(); |
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| 60 | |
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| 61 | m_Gen[0] = NULL; |
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| 62 | m_Gen[1] = NULL; |
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| 63 | m_Mod[0] = NULL; |
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| 64 | m_Mod[1] = NULL; |
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| 65 | m_aDegrees[0] = NULL; |
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| 66 | m_aDegrees[1] = NULL; |
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| 67 | m_aPositions[0] = NULL; |
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| 68 | m_aPositions[1] = NULL; |
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| 69 | m_fuzzyNeighb[0] = NULL; |
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| 70 | m_fuzzyNeighb[1] = NULL; |
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| 71 | m_Neighbours[0] = NULL; |
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| 72 | m_Neighbours[1] = NULL; |
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| 73 | m_pMatching = NULL; |
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| 74 | |
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| 75 | //Determines whether "fuzzy vertex degree" should be used. |
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| 76 | //Currently "fuzzy vertex degree" is inactive. |
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| 77 | isFuzzy = false; |
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| 78 | fuzzyDepth = 10; |
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| 79 | |
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| 80 | //Determines whether weighted MDS should be used. |
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| 81 | wMDS = 0; |
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| 82 | //Determines whether best matching should be saved using hungarian similarity measure. |
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| 83 | saveMatching = false; |
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| 84 | } |
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| 85 | |
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| 86 | double ModelSimil::EvaluateDistanceGreedy(const Geno *G0, const Geno *G1) |
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| 87 | { |
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| 88 | double dResult = 0.0; |
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| 89 | |
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| 90 | m_Gen[0] = G0; |
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| 91 | m_Gen[1] = G1; |
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| 92 | |
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| 93 | // create models of objects to compare |
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| 94 | m_Mod[0] = newModel(m_Gen[0]); |
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| 95 | m_Mod[1] = newModel(m_Gen[1]); |
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| 96 | |
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| 97 | if (m_Mod[0] == NULL || m_Mod[1] == NULL) |
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| 98 | return 0.0; |
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| 99 | |
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| 100 | // difference in the number of vertices (Parts) - positive |
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| 101 | // find object that has less parts (m_iSmaller) |
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| 102 | m_iDV = (m_Mod[0]->getPartCount() - m_Mod[1]->getPartCount()); |
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| 103 | if (m_iDV > 0) |
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| 104 | m_iSmaller = 1; |
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| 105 | else |
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| 106 | { |
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| 107 | m_iSmaller = 0; |
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| 108 | m_iDV = -m_iDV; |
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| 109 | } |
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| 110 | |
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| 111 | // check if index of the smaller organism is a valid index |
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| 112 | assert((m_iSmaller == 0) || (m_iSmaller == 1)); |
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| 113 | // validate difference in the parts number |
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| 114 | assert(m_iDV >= 0); |
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| 115 | |
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| 116 | // create Parts matching object |
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| 117 | m_pMatching = new SimilMatching(m_Mod[0]->getPartCount(), m_Mod[1]->getPartCount()); |
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| 118 | // validate matching object |
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| 119 | assert(m_pMatching != NULL); |
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| 120 | assert(m_pMatching->IsEmpty() == true); |
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| 121 | |
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| 122 | |
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| 123 | // assign matching function |
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| 124 | int (ModelSimil:: * pfMatchingFunction) () = NULL; |
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| 125 | |
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| 126 | pfMatchingFunction = &ModelSimil::MatchPartsGeometry; |
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| 127 | |
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| 128 | // match Parts (vertices of creatures) |
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| 129 | if ((this->*pfMatchingFunction)() == 0) |
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| 130 | { |
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| 131 | logPrintf("ModelSimil", "EvaluateDistanceGreedy", LOG_ERROR, "The matching function returned 0"); |
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| 132 | return 0.0; |
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| 133 | } |
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| 134 | |
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| 135 | // after matching function call we must have full matching |
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| 136 | assert(m_pMatching->IsFull() == true); |
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| 137 | |
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| 138 | DB(SaveIntermediateFiles();) |
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| 139 | |
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| 140 | // count differences in matched parts |
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| 141 | if (CountPartsDistance() == 0) |
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| 142 | { |
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| 143 | logPrintf("ModelSimil", "EvaluateDistanceGreedy", LOG_ERROR, "CountPartDistance()==0"); |
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| 144 | return 0.0; |
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| 145 | } |
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| 146 | |
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| 147 | // delete degree arrays created in CreatePartInfoTables |
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| 148 | SAFEDELETEARRAY(m_aDegrees[0]); |
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| 149 | SAFEDELETEARRAY(m_aDegrees[1]); |
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| 150 | |
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| 151 | // and position arrays |
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| 152 | SAFEDELETEARRAY(m_aPositions[0]); |
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| 153 | SAFEDELETEARRAY(m_aPositions[1]); |
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| 154 | |
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| 155 | // in fuzzy mode delete arrays of neighbourhood and fuzzy neighbourhood |
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| 156 | if (isFuzzy) |
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| 157 | { |
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| 158 | for (int i = 0; i != 2; ++i) |
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| 159 | { |
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| 160 | for (int j = 0; j != m_Mod[i]->getPartCount(); ++j) |
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| 161 | { |
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| 162 | delete[] m_Neighbours[i][j]; |
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| 163 | delete[] m_fuzzyNeighb[i][j]; |
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| 164 | } |
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| 165 | delete[] m_Neighbours[i]; |
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| 166 | delete[] m_fuzzyNeighb[i]; |
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| 167 | } |
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| 168 | |
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| 169 | } |
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| 170 | |
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| 171 | // delete created models |
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| 172 | SAFEDELETE(m_Mod[0]); |
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| 173 | SAFEDELETE(m_Mod[1]); |
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| 174 | |
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| 175 | // delete created matching |
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| 176 | SAFEDELETE(m_pMatching); |
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| 177 | |
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| 178 | dResult = m_adFactors[0] * double(m_iDV) + |
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| 179 | m_adFactors[1] * double(m_iDD) + |
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| 180 | m_adFactors[2] * double(m_iDN) + |
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| 181 | m_adFactors[3] * double(m_dDG); |
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| 182 | |
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| 183 | return dResult; |
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| 184 | } |
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| 185 | |
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| 186 | ModelSimil::~ModelSimil() |
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| 187 | { |
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| 188 | // matching should have been deleted earlier |
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| 189 | assert(m_pMatching == NULL); |
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| 190 | } |
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| 191 | |
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| 192 | /** Creates files matching.txt, org0.txt and org1.txt containing information |
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| 193 | * about the matching and both organisms for visualization purpose. |
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| 194 | */ |
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| 195 | void ModelSimil::SaveIntermediateFiles() |
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| 196 | { |
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| 197 | assert(m_pMatching->IsFull() == true); |
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| 198 | printf("Saving the matching to file 'matching.txt'\n"); |
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| 199 | FILE *pMatchingFile = NULL; |
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| 200 | // try to open the file |
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| 201 | pMatchingFile = fopen("matching.txt", "wt"); |
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| 202 | assert(pMatchingFile != NULL); |
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| 203 | |
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| 204 | int iOrgPart; // original index of a Part |
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| 205 | int nBigger; // index of the larger organism |
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| 206 | |
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| 207 | // check which object is bigger |
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| 208 | if (m_pMatching->GetObjectSize(0) >= m_pMatching->GetObjectSize(1)) |
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| 209 | { |
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| 210 | nBigger = 0; |
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| 211 | } |
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| 212 | else |
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| 213 | { |
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| 214 | nBigger = 1; |
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| 215 | } |
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| 216 | |
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| 217 | // print first line - original indices of Parts of the bigger organism |
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| 218 | fprintf(pMatchingFile, "[ "); |
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| 219 | for (iOrgPart = 0; iOrgPart < m_pMatching->GetObjectSize(nBigger); iOrgPart++) |
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| 220 | { |
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| 221 | fprintf(pMatchingFile, "%2i ", iOrgPart); |
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| 222 | } |
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| 223 | fprintf(pMatchingFile, "] : ORG[%i]\n", nBigger); |
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| 224 | |
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| 225 | // print second line - matched original indices of the second organism |
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| 226 | fprintf(pMatchingFile, "[ "); |
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| 227 | for (iOrgPart = 0; iOrgPart < m_pMatching->GetObjectSize(nBigger); iOrgPart++) |
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| 228 | { |
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| 229 | int iSorted; // index of the iOrgPart after sorting (as used by matching) |
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| 230 | int iSortedMatched; // index of the matched Part (after sorting) |
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| 231 | int iOrginalMatched; // index of the matched Part (the original one) |
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| 232 | |
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| 233 | // find the index of iOrgPart after sorting (in m_aDegrees) |
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| 234 | for (iSorted = 0; iSorted < m_Mod[nBigger]->getPartCount(); iSorted++) |
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| 235 | { |
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| 236 | // for each iSorted, an index in the sorted m_aDegrees array |
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| 237 | if (m_aDegrees[nBigger][iSorted][0] == iOrgPart) |
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| 238 | { |
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| 239 | // if the iSorted Part is the one with iOrgPart as the orginal index |
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| 240 | // remember the index |
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| 241 | break; |
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| 242 | } |
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| 243 | } |
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| 244 | // if the index iSorted was found, then this condition is met |
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| 245 | assert(iSorted < m_Mod[nBigger]->getPartCount()); |
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| 246 | |
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| 247 | // find the matched sorted index |
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| 248 | if (m_pMatching->IsMatched(nBigger, iSorted)) |
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| 249 | { |
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| 250 | // if Part iOrgPart is matched |
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| 251 | // then get the matched Part (sorted) index |
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| 252 | iSortedMatched = m_pMatching->GetMatchedIndex(nBigger, iSorted); |
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| 253 | assert(iSortedMatched >= 0); |
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| 254 | // and find its original index |
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| 255 | iOrginalMatched = m_aDegrees[1 - nBigger][iSortedMatched][0]; |
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| 256 | fprintf(pMatchingFile, "%2i ", iOrginalMatched); |
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| 257 | } |
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| 258 | else |
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| 259 | { |
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| 260 | // if the Part iOrgPart is not matched |
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| 261 | // just print "X" |
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| 262 | fprintf(pMatchingFile, " X "); |
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| 263 | } |
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| 264 | } // for ( iOrgPart ) |
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| 265 | |
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| 266 | // now all matched Part indices are printed out, end the line |
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| 267 | fprintf(pMatchingFile, "] : ORG[%i]\n", 1 - nBigger); |
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| 268 | |
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| 269 | // close the file |
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| 270 | fclose(pMatchingFile); |
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| 271 | // END TEMP |
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| 272 | |
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| 273 | // TEMP |
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| 274 | // print out the 2D positions of Parts of both of the organisms |
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| 275 | // to files "org0.txt" and "org1.txt" using the original indices of Parts |
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| 276 | int iModel; // index of a model (an organism) |
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| 277 | FILE *pModelFile; |
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| 278 | for (iModel = 0; iModel < 2; iModel++) |
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| 279 | { |
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| 280 | // for each iModel, a model of a compared organism |
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| 281 | // write its (only 2D) positions to a file "org<iModel>.txt" |
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| 282 | // construct the model filename "org<iModel>.txt" |
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| 283 | std::string sModelFilename("org"); |
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| 284 | // char *szModelIndex = "0"; // the index of the model (iModel) in the character form |
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| 285 | char szModelIndex[2]; |
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| 286 | sprintf(szModelIndex, "%i", iModel); |
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| 287 | sModelFilename += szModelIndex; |
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| 288 | sModelFilename += ".txt"; |
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| 289 | // open the file for writing |
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| 290 | pModelFile = fopen(sModelFilename.c_str(), "wt"); //FOPEN_WRITE |
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| 291 | assert(pModelFile != NULL); |
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| 292 | // write the 2D positions of iModel to the file |
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| 293 | int iOriginalPart; // an original index of a Part |
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| 294 | for (iOriginalPart = 0; iOriginalPart < m_Mod[iModel]->getPartCount(); iOriginalPart++) |
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| 295 | { |
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| 296 | // for each iOriginalPart, a Part of the organism iModel |
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| 297 | // get the 2D coordinates of the Part |
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| 298 | double dPartX = m_aPositions[iModel][iOriginalPart].x; |
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| 299 | double dPartY = m_aPositions[iModel][iOriginalPart].y; |
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| 300 | // print the line: <iOriginalPart> <dPartX> <dPartY> |
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| 301 | fprintf(pModelFile, "%i %.4lf %.4lf\n", iOriginalPart, dPartX, dPartY); |
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| 302 | } |
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| 303 | // close the file |
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| 304 | fclose(pModelFile); |
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| 305 | } |
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| 306 | } |
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| 307 | |
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| 308 | /** Comparison function required for qsort() call. Used while sorting groups of |
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| 309 | Parts with respect to degree. Compares two TDN structures |
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| 310 | with respect to their [1] field (degree). Highest degree goes first. |
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| 311 | @param pElem1 Pointer to the TDN structure of some Part. |
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| 312 | @param pElem2 Pointer to the TDN structure of some Part. |
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| 313 | @return (-1) - pElem1 should go first, 0 - equal, (1) - pElem2 should go first. |
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| 314 | */ |
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| 315 | int ModelSimil::CompareDegrees(const void *pElem1, const void *pElem2) |
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| 316 | { |
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| 317 | int *tdn1 = (int *)pElem1; |
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| 318 | int *tdn2 = (int *)pElem2; |
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| 319 | |
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| 320 | if (tdn1[1] > tdn2[1]) |
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| 321 | { |
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| 322 | // when degree - tdn1[1] - is BIGGER |
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| 323 | return -1; |
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| 324 | } |
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| 325 | else |
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| 326 | if (tdn1[1] < tdn2[1]) |
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| 327 | { |
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| 328 | // when degree - tdn2[1] - is BIGGER |
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| 329 | return 1; |
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| 330 | } |
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| 331 | else |
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| 332 | { |
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| 333 | return 0; |
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| 334 | } |
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| 335 | } |
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| 336 | |
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| 337 | /** Comparison function required for qsort() call. Used while sorting groups of |
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| 338 | Parts with respect to fuzzy vertex degree. Compares two TDN structures |
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| 339 | with respect to their [4] field ( fuzzy vertex degree). Highest degree goes first. |
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| 340 | @param pElem1 Pointer to the TDN structure of some Part. |
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| 341 | @param pElem2 Pointer to the TDN structure of some Part. |
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| 342 | @return (-1) - pElem1 should go first, 0 - equal, (1) - pElem2 should go first. |
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| 343 | */ |
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| 344 | int ModelSimil::CompareFuzzyDegrees(const void *pElem1, const void *pElem2) |
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| 345 | { |
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| 346 | int *tdn1 = (int *)pElem1; |
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| 347 | int *tdn2 = (int *)pElem2; |
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| 348 | |
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| 349 | if (tdn1[4] > tdn2[4]) |
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| 350 | { |
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| 351 | // when degree - tdn1[4] - is BIGGER |
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| 352 | return -1; |
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| 353 | } |
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| 354 | else |
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| 355 | if (tdn1[4] < tdn2[4]) |
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| 356 | { |
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| 357 | // when degree - tdn2[4] - is BIGGER |
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| 358 | return 1; |
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| 359 | } |
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| 360 | else |
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| 361 | { |
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| 362 | return 0; |
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| 363 | } |
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| 364 | } |
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| 365 | |
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| 366 | /** Comparison function required for qsort() call. Used while sorting groups of Parts with |
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| 367 | the same degree. Firstly, compare NIt. Secondly, compare Neu. If both are equal - |
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| 368 | compare Parts' original index (they are never equal). So this sorting assures |
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| 369 | that the order obtained is deterministic. |
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| 370 | @param pElem1 Pointer to the TDN structure of some Part. |
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| 371 | @param pElem2 Pointer to the TDN structure of some Part. |
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| 372 | @return (-1) - pElem1 should go first, 0 - equal, (1) - pElem2 should go first. |
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| 373 | */ |
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| 374 | int ModelSimil::CompareConnsNo(const void *pElem1, const void *pElem2) |
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| 375 | { |
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| 376 | // pointers to TDN arrays |
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| 377 | int *tdn1, *tdn2; |
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| 378 | // definitions of elements being compared |
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| 379 | tdn1 = (int *)pElem1; |
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| 380 | tdn2 = (int *)pElem2; |
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| 381 | |
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| 382 | // comparison according to Neural Connections (to jest TDN[2]) |
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| 383 | if (tdn1[NEURO_CONNS] > tdn2[NEURO_CONNS]) |
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| 384 | { |
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| 385 | // when number of NConn Elem1 is BIGGER |
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| 386 | return -1; |
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| 387 | } |
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| 388 | else |
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| 389 | if (tdn1[NEURO_CONNS] < tdn2[NEURO_CONNS]) |
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| 390 | { |
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| 391 | // when number of NConn Elem1 is SMALLER |
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| 392 | return 1; |
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| 393 | } |
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| 394 | else |
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| 395 | { |
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| 396 | // when numbers of NConn are EQUAL |
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| 397 | // compare Neu numbers (TDN[3]) |
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| 398 | if (tdn1[NEURONS] > tdn2[NEURONS]) |
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| 399 | { |
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| 400 | // when number of Neu is BIGGER for Elem1 |
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| 401 | return -1; |
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| 402 | } |
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| 403 | else |
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| 404 | if (tdn1[NEURONS] < tdn2[NEURONS]) |
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| 405 | { |
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| 406 | // when number of Neu is SMALLER for Elem1 |
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| 407 | return 1; |
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| 408 | } |
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| 409 | else |
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| 410 | { |
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| 411 | // when numbers of Nconn and Neu are equal we check original indices |
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| 412 | // of Parts being compared |
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| 413 | |
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| 414 | // comparison according to OrgIndex |
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| 415 | if (tdn1[ORIG_IND] > tdn2[ORIG_IND]) |
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| 416 | { |
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| 417 | // when the number of NIt Deg1 id BIGGER |
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| 418 | return -1; |
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| 419 | } |
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| 420 | else |
|---|
| 421 | if (tdn1[ORIG_IND] < tdn2[ORIG_IND]) |
|---|
| 422 | { |
|---|
| 423 | // when the number of NIt Deg1 id SMALLER |
|---|
| 424 | return 1; |
|---|
| 425 | } |
|---|
| 426 | else |
|---|
| 427 | { |
|---|
| 428 | // impossible, indices are alway different |
|---|
| 429 | return 0; |
|---|
| 430 | } |
|---|
| 431 | } |
|---|
| 432 | } |
|---|
| 433 | } |
|---|
| 434 | |
|---|
| 435 | /** Returns number of factors involved in final distance computation. |
|---|
| 436 | These factors include differences in numbers of parts, degrees, |
|---|
| 437 | number of neurons. |
|---|
| 438 | */ |
|---|
| 439 | int ModelSimil::GetNOFactors() |
|---|
| 440 | { |
|---|
| 441 | return ModelSimil::iNOFactors; |
|---|
| 442 | } |
|---|
| 443 | |
|---|
| 444 | /** Prints the array of degrees for the given organism. Debug method. |
|---|
| 445 | */ |
|---|
| 446 | void ModelSimil::_PrintDegrees(int i) |
|---|
| 447 | { |
|---|
| 448 | int j; |
|---|
| 449 | printf("Organizm %i :", i); |
|---|
| 450 | printf("\n "); |
|---|
| 451 | for (j = 0; j < m_Mod[i]->getPartCount(); j++) |
|---|
| 452 | printf("%3i ", j); |
|---|
| 453 | printf("\nInd: "); |
|---|
| 454 | for (j = 0; j < m_Mod[i]->getPartCount(); j++) |
|---|
| 455 | printf("%3i ", (int)m_aDegrees[i][j][0]); |
|---|
| 456 | printf("\nDeg: "); |
|---|
| 457 | for (j = 0; j < m_Mod[i]->getPartCount(); j++) |
|---|
| 458 | printf("%3i ", (int)m_aDegrees[i][j][1]); |
|---|
| 459 | printf("\nNIt: "); |
|---|
| 460 | for (j = 0; j < m_Mod[i]->getPartCount(); j++) |
|---|
| 461 | printf("%3i ", (int)m_aDegrees[i][j][2]); |
|---|
| 462 | printf("\nNeu: "); |
|---|
| 463 | for (j = 0; j < m_Mod[i]->getPartCount(); j++) |
|---|
| 464 | printf("%3i ", (int)m_aDegrees[i][j][3]); |
|---|
| 465 | printf("\n"); |
|---|
| 466 | } |
|---|
| 467 | |
|---|
| 468 | /** Prints one array of ints. Debug method. |
|---|
| 469 | @param array Base pointer of the array. |
|---|
| 470 | @param base First index of the array's element. |
|---|
| 471 | @param size Number of elements to print. |
|---|
| 472 | */ |
|---|
| 473 | void ModelSimil::_PrintArray(int *array, int base, int size) |
|---|
| 474 | { |
|---|
| 475 | int i; |
|---|
| 476 | for (i = base; i < base + size; i++) |
|---|
| 477 | { |
|---|
| 478 | printf("%i ", array[i]); |
|---|
| 479 | } |
|---|
| 480 | printf("\n"); |
|---|
| 481 | } |
|---|
| 482 | |
|---|
| 483 | void ModelSimil::_PrintArrayDouble(double *array, int base, int size) |
|---|
| 484 | { |
|---|
| 485 | int i; |
|---|
| 486 | for (i = base; i < base + size; i++) |
|---|
| 487 | { |
|---|
| 488 | printf("%f ", array[i]); |
|---|
| 489 | } |
|---|
| 490 | printf("\n"); |
|---|
| 491 | } |
|---|
| 492 | |
|---|
| 493 | /** Prints one array of parts neighbourhood. |
|---|
| 494 | @param index of organism |
|---|
| 495 | */ |
|---|
| 496 | void ModelSimil::_PrintNeighbourhood(int o) |
|---|
| 497 | { |
|---|
| 498 | assert(m_Neighbours[o] != 0); |
|---|
| 499 | printf("Neighbourhhod of organism %i\n", o); |
|---|
| 500 | int size = m_Mod[o]->getPartCount(); |
|---|
| 501 | for (int i = 0; i < size; i++) |
|---|
| 502 | { |
|---|
| 503 | for (int j = 0; j < size; j++) |
|---|
| 504 | { |
|---|
| 505 | printf("%i ", m_Neighbours[o][i][j]); |
|---|
| 506 | } |
|---|
| 507 | printf("\n"); |
|---|
| 508 | } |
|---|
| 509 | } |
|---|
| 510 | |
|---|
| 511 | /** Prints one array of parts fuzzy neighbourhood. |
|---|
| 512 | @param index of organism |
|---|
| 513 | */ |
|---|
| 514 | void ModelSimil::_PrintFuzzyNeighbourhood(int o) |
|---|
| 515 | { |
|---|
| 516 | assert(m_fuzzyNeighb[o] != NULL); |
|---|
| 517 | printf("Fuzzy neighbourhhod of organism %i\n", o); |
|---|
| 518 | int size = m_Mod[o]->getPartCount(); |
|---|
| 519 | for (int i = 0; i < size; i++) |
|---|
| 520 | { |
|---|
| 521 | for (int j = 0; j < fuzzyDepth; j++) |
|---|
| 522 | { |
|---|
| 523 | printf("%f ", m_fuzzyNeighb[o][i][j]); |
|---|
| 524 | } |
|---|
| 525 | printf("\n"); |
|---|
| 526 | } |
|---|
| 527 | } |
|---|
| 528 | |
|---|
| 529 | Model* ModelSimil::newModel(const Geno *g) |
|---|
| 530 | { |
|---|
| 531 | if (g == NULL) |
|---|
| 532 | { |
|---|
| 533 | logPrintf("ModelSimil", "newModel", LOG_ERROR, "NULL genotype pointer"); |
|---|
| 534 | return NULL; |
|---|
| 535 | } |
|---|
| 536 | Model *m = new Model(*g, Model::SHAPETYPE_UNKNOWN); |
|---|
| 537 | if (!m->isValid()) |
|---|
| 538 | { |
|---|
| 539 | logPrintf("ModelSimil", "newModel", LOG_ERROR, "Invalid model for the genotype of '%s'", g->getName().c_str()); |
|---|
| 540 | delete m; |
|---|
| 541 | return NULL; |
|---|
| 542 | } |
|---|
| 543 | return m; |
|---|
| 544 | } |
|---|
| 545 | |
|---|
| 546 | |
|---|
| 547 | /** Creates arrays holding information about organisms' Parts (m_aDegrees) andm_Neigh |
|---|
| 548 | fills them with initial data (original indices and zeros). |
|---|
| 549 | Assumptions: |
|---|
| 550 | - Models (m_Mod) are created and available. |
|---|
| 551 | */ |
|---|
| 552 | int ModelSimil::ModelSimil::CreatePartInfoTables() |
|---|
| 553 | { |
|---|
| 554 | // check assumptions about models |
|---|
| 555 | assert((m_Mod[0] != NULL) && (m_Mod[1] != NULL)); |
|---|
| 556 | assert(m_Mod[0]->isValid() && m_Mod[1]->isValid()); |
|---|
| 557 | |
|---|
| 558 | int i, j, partCount; |
|---|
| 559 | // utwórz tablice na informacje o stopniach wierzchołków i liczbie neuroitems |
|---|
| 560 | for (i = 0; i < 2; i++) |
|---|
| 561 | { |
|---|
| 562 | partCount = m_Mod[i]->getPartCount(); |
|---|
| 563 | // utworz i wypelnij tablice dla Parts wartosciami poczatkowymi |
|---|
| 564 | m_aDegrees[i] = new TDN[partCount]; |
|---|
| 565 | |
|---|
| 566 | if (isFuzzy) |
|---|
| 567 | { |
|---|
| 568 | m_Neighbours[i] = new int*[partCount]; |
|---|
| 569 | m_fuzzyNeighb[i] = new float*[partCount]; |
|---|
| 570 | } |
|---|
| 571 | |
|---|
| 572 | if (m_aDegrees[i] != NULL && ((!isFuzzy) || (m_Neighbours[i] != NULL && m_fuzzyNeighb[i] != NULL))) |
|---|
| 573 | { |
|---|
| 574 | // wypelnij tablice zgodnie z sensem TDN[0] - orginalny index |
|---|
| 575 | // TDN[1], TDN[2], TDN[3] - zerami |
|---|
| 576 | DB(printf("m_aDegrees[%i]: %p\n", i, m_aDegrees[i]);) |
|---|
| 577 | for (j = 0; j < partCount; j++) |
|---|
| 578 | { |
|---|
| 579 | m_aDegrees[i][j][0] = j; |
|---|
| 580 | m_aDegrees[i][j][1] = 0; |
|---|
| 581 | m_aDegrees[i][j][2] = 0; |
|---|
| 582 | m_aDegrees[i][j][3] = 0; |
|---|
| 583 | m_aDegrees[i][j][4] = 0; |
|---|
| 584 | |
|---|
| 585 | // sprawdz, czy nie piszemy po jakims szalonym miejscu pamieci |
|---|
| 586 | assert(m_aDegrees[i][j] != NULL); |
|---|
| 587 | |
|---|
| 588 | if (isFuzzy) |
|---|
| 589 | { |
|---|
| 590 | m_Neighbours[i][j] = new int[partCount]; |
|---|
| 591 | for (int k = 0; k < partCount; k++) |
|---|
| 592 | { |
|---|
| 593 | m_Neighbours[i][j][k] = 0; |
|---|
| 594 | } |
|---|
| 595 | |
|---|
| 596 | m_fuzzyNeighb[i][j] = new float[fuzzyDepth]; |
|---|
| 597 | for (int k = 0; k < fuzzyDepth; k++) |
|---|
| 598 | { |
|---|
| 599 | m_fuzzyNeighb[i][j][k] = 0; |
|---|
| 600 | } |
|---|
| 601 | |
|---|
| 602 | assert(m_Neighbours[i][j] != NULL); |
|---|
| 603 | assert(m_fuzzyNeighb[i][j] != NULL); |
|---|
| 604 | } |
|---|
| 605 | |
|---|
| 606 | } |
|---|
| 607 | } |
|---|
| 608 | else |
|---|
| 609 | { |
|---|
| 610 | logPrintf("ModelSimil", "CreatePartInfoTables", LOG_ERROR, "Not enough memory?"); |
|---|
| 611 | return 0; |
|---|
| 612 | } |
|---|
| 613 | // utworz tablice dla pozycji 3D Parts (wielkosc tablicy: liczba Parts organizmu) |
|---|
| 614 | m_aPositions[i] = new Pt3D[m_Mod[i]->getPartCount()]; |
|---|
| 615 | assert(m_aPositions[i] != NULL); |
|---|
| 616 | // wypelnij tablice OnJoints i Anywhere wartościami początkowymi |
|---|
| 617 | // OnJoint |
|---|
| 618 | m_aOnJoint[i][0] = 0; |
|---|
| 619 | m_aOnJoint[i][1] = 0; |
|---|
| 620 | m_aOnJoint[i][2] = 0; |
|---|
| 621 | m_aOnJoint[i][3] = 0; |
|---|
| 622 | // Anywhere |
|---|
| 623 | m_aAnywhere[i][0] = 0; |
|---|
| 624 | m_aAnywhere[i][1] = 0; |
|---|
| 625 | m_aAnywhere[i][2] = 0; |
|---|
| 626 | m_aAnywhere[i][3] = 0; |
|---|
| 627 | } |
|---|
| 628 | return 1; |
|---|
| 629 | } |
|---|
| 630 | |
|---|
| 631 | /** Computes degrees of Parts of both organisms. Fills in the m_aDegrees arrays |
|---|
| 632 | with proper information about degrees. |
|---|
| 633 | Assumptions: |
|---|
| 634 | - Models (m_Mod) are created and available. |
|---|
| 635 | - Arrays m_aDegrees are created. |
|---|
| 636 | */ |
|---|
| 637 | int ModelSimil::CountPartDegrees() |
|---|
| 638 | { |
|---|
| 639 | // sprawdz zalozenie - o modelach |
|---|
| 640 | assert((m_Mod[0] != NULL) && (m_Mod[1] != NULL)); |
|---|
| 641 | assert(m_Mod[0]->isValid() && m_Mod[1]->isValid()); |
|---|
| 642 | |
|---|
| 643 | // sprawdz zalozenie - o tablicach |
|---|
| 644 | assert(m_aDegrees[0] != NULL); |
|---|
| 645 | assert(m_aDegrees[1] != NULL); |
|---|
| 646 | |
|---|
| 647 | Part *P1, *P2; |
|---|
| 648 | int i, j, i1, i2; |
|---|
| 649 | |
|---|
| 650 | // dla obu stworzen oblicz stopnie wierzcholkow |
|---|
| 651 | for (i = 0; i < 2; i++) |
|---|
| 652 | { |
|---|
| 653 | // dla wszystkich jointow |
|---|
| 654 | for (j = 0; j < m_Mod[i]->getJointCount(); j++) |
|---|
| 655 | { |
|---|
| 656 | // pobierz kolejny Joint |
|---|
| 657 | Joint *J = m_Mod[i]->getJoint(j); |
|---|
| 658 | // wez jego konce |
|---|
| 659 | P1 = J->part1; |
|---|
| 660 | P2 = J->part2; |
|---|
| 661 | // znajdz ich indeksy w Modelu (indeksy orginalne) |
|---|
| 662 | i1 = m_Mod[i]->findPart(P1); |
|---|
| 663 | i2 = m_Mod[i]->findPart(P2); |
|---|
| 664 | // zwieksz stopien odpowiednich Parts |
|---|
| 665 | m_aDegrees[i][i1][DEGREE]++; |
|---|
| 666 | m_aDegrees[i][i2][DEGREE]++; |
|---|
| 667 | m_aDegrees[i][i1][FUZZ_DEG]++; |
|---|
| 668 | m_aDegrees[i][i2][FUZZ_DEG]++; |
|---|
| 669 | if (isFuzzy) |
|---|
| 670 | { |
|---|
| 671 | m_Neighbours[i][i1][i2] = 1; |
|---|
| 672 | m_Neighbours[i][i2][i1] = 1; |
|---|
| 673 | } |
|---|
| 674 | } |
|---|
| 675 | // dla elementow nie osadzonych na Parts (OnJoint, Anywhere) - |
|---|
| 676 | // stopnie wierzchołka są już ustalone na zero |
|---|
| 677 | } |
|---|
| 678 | |
|---|
| 679 | if (isFuzzy) |
|---|
| 680 | { |
|---|
| 681 | CountFuzzyNeighb(); |
|---|
| 682 | } |
|---|
| 683 | |
|---|
| 684 | return 1; |
|---|
| 685 | } |
|---|
| 686 | |
|---|
| 687 | void ModelSimil::GetNeighbIndexes(int mod, int partInd, std::vector<int> &indexes) |
|---|
| 688 | { |
|---|
| 689 | indexes.clear(); |
|---|
| 690 | int i, size = m_Mod[mod]->getPartCount(); |
|---|
| 691 | |
|---|
| 692 | for (i = 0; i < size; i++) |
|---|
| 693 | { |
|---|
| 694 | if (m_Neighbours[mod][partInd][i] > 0) |
|---|
| 695 | { |
|---|
| 696 | indexes.push_back(i); |
|---|
| 697 | } |
|---|
| 698 | } |
|---|
| 699 | } |
|---|
| 700 | |
|---|
| 701 | int cmpFuzzyRows(const void *pa, const void *pb) |
|---|
| 702 | { |
|---|
| 703 | float **a = (float**)pa; |
|---|
| 704 | float **b = (float**)pb; |
|---|
| 705 | |
|---|
| 706 | |
|---|
| 707 | for (int i = 1; i < fuzDepth; i++) |
|---|
| 708 | { |
|---|
| 709 | if (a[0][i] > b[0][i]) |
|---|
| 710 | { |
|---|
| 711 | |
|---|
| 712 | return -1; |
|---|
| 713 | } |
|---|
| 714 | if (a[0][i] < b[0][i]) |
|---|
| 715 | { |
|---|
| 716 | |
|---|
| 717 | return 1; |
|---|
| 718 | } |
|---|
| 719 | } |
|---|
| 720 | |
|---|
| 721 | return 0; |
|---|
| 722 | } |
|---|
| 723 | |
|---|
| 724 | void ModelSimil::FuzzyOrder() |
|---|
| 725 | { |
|---|
| 726 | int i, depth, partInd, prevPartInd, partCount; |
|---|
| 727 | for (int mod = 0; mod < 2; mod++) |
|---|
| 728 | { |
|---|
| 729 | partCount = m_Mod[mod]->getPartCount(); |
|---|
| 730 | partInd = m_fuzzyNeighb[mod][partCount - 1][0]; |
|---|
| 731 | m_aDegrees[mod][partInd][FUZZ_DEG] = 0; |
|---|
| 732 | |
|---|
| 733 | for (i = (partCount - 2); i >= 0; i--) |
|---|
| 734 | { |
|---|
| 735 | prevPartInd = partInd; |
|---|
| 736 | partInd = m_fuzzyNeighb[mod][i][0]; |
|---|
| 737 | m_aDegrees[mod][partInd][FUZZ_DEG] = m_aDegrees[mod][prevPartInd][FUZZ_DEG]; |
|---|
| 738 | for (depth = 1; depth < fuzzyDepth; depth++) |
|---|
| 739 | { |
|---|
| 740 | if (m_fuzzyNeighb[mod][i][depth] != m_fuzzyNeighb[mod][i + 1][depth]) |
|---|
| 741 | { |
|---|
| 742 | m_aDegrees[mod][partInd][FUZZ_DEG]++; |
|---|
| 743 | break; |
|---|
| 744 | } |
|---|
| 745 | } |
|---|
| 746 | } |
|---|
| 747 | } |
|---|
| 748 | } |
|---|
| 749 | |
|---|
| 750 | //sort according to fuzzy degree |
|---|
| 751 | void ModelSimil::SortFuzzyNeighb() |
|---|
| 752 | { |
|---|
| 753 | fuzDepth = fuzzyDepth; |
|---|
| 754 | for (int mod = 0; mod < 2; mod++) |
|---|
| 755 | { |
|---|
| 756 | std::qsort(m_fuzzyNeighb[mod], (size_t)m_Mod[mod]->getPartCount(), sizeof(m_fuzzyNeighb[mod][0]), cmpFuzzyRows); |
|---|
| 757 | } |
|---|
| 758 | } |
|---|
| 759 | |
|---|
| 760 | //computes fuzzy vertex degree |
|---|
| 761 | void ModelSimil::CountFuzzyNeighb() |
|---|
| 762 | { |
|---|
| 763 | assert(m_aDegrees[0] != NULL); |
|---|
| 764 | assert(m_aDegrees[1] != NULL); |
|---|
| 765 | |
|---|
| 766 | assert(m_Neighbours[0] != NULL); |
|---|
| 767 | assert(m_Neighbours[1] != NULL); |
|---|
| 768 | |
|---|
| 769 | assert(m_fuzzyNeighb[0] != NULL); |
|---|
| 770 | assert(m_fuzzyNeighb[1] != NULL); |
|---|
| 771 | |
|---|
| 772 | std::vector<int> nIndexes; |
|---|
| 773 | float newDeg = 0; |
|---|
| 774 | |
|---|
| 775 | for (int mod = 0; mod < 2; mod++) |
|---|
| 776 | { |
|---|
| 777 | int partCount = m_Mod[mod]->getPartCount(); |
|---|
| 778 | |
|---|
| 779 | for (int depth = 0; depth < fuzzyDepth; depth++) |
|---|
| 780 | { |
|---|
| 781 | //use first column for storing indices |
|---|
| 782 | for (int partInd = 0; partInd < partCount; partInd++) |
|---|
| 783 | { |
|---|
| 784 | if (depth == 0) |
|---|
| 785 | { |
|---|
| 786 | m_fuzzyNeighb[mod][partInd][depth] = partInd; |
|---|
| 787 | } |
|---|
| 788 | else if (depth == 1) |
|---|
| 789 | { |
|---|
| 790 | m_fuzzyNeighb[mod][partInd][depth] = m_aDegrees[mod][partInd][DEGREE]; |
|---|
| 791 | } |
|---|
| 792 | else |
|---|
| 793 | { |
|---|
| 794 | GetNeighbIndexes(mod, partInd, nIndexes); |
|---|
| 795 | for (unsigned int k = 0; k < nIndexes.size(); k++) |
|---|
| 796 | { |
|---|
| 797 | newDeg += m_fuzzyNeighb[mod][nIndexes.at(k)][depth - 1]; |
|---|
| 798 | } |
|---|
| 799 | newDeg /= nIndexes.size(); |
|---|
| 800 | m_fuzzyNeighb[mod][partInd][depth] = newDeg; |
|---|
| 801 | for (int mod = 0; mod < 2; mod++) |
|---|
| 802 | { |
|---|
| 803 | int partCount = m_Mod[mod]->getPartCount(); |
|---|
| 804 | for (int i = partCount - 1; i >= 0; i--) |
|---|
| 805 | { |
|---|
| 806 | |
|---|
| 807 | } |
|---|
| 808 | } |
|---|
| 809 | newDeg = 0; |
|---|
| 810 | } |
|---|
| 811 | } |
|---|
| 812 | } |
|---|
| 813 | } |
|---|
| 814 | |
|---|
| 815 | SortFuzzyNeighb(); |
|---|
| 816 | FuzzyOrder(); |
|---|
| 817 | } |
|---|
| 818 | |
|---|
| 819 | /** Gets information about Parts' positions in 3D from models into the arrays |
|---|
| 820 | m_aPositions. |
|---|
| 821 | Assumptions: |
|---|
| 822 | - Models (m_Mod) are created and available. |
|---|
| 823 | - Arrays m_aPositions are created. |
|---|
| 824 | @return 1 if success, otherwise 0. |
|---|
| 825 | */ |
|---|
| 826 | int ModelSimil::GetPartPositions() |
|---|
| 827 | { |
|---|
| 828 | // sprawdz zalozenie - o modelach |
|---|
| 829 | assert((m_Mod[0] != NULL) && (m_Mod[1] != NULL)); |
|---|
| 830 | assert(m_Mod[0]->isValid() && m_Mod[1]->isValid()); |
|---|
| 831 | |
|---|
| 832 | // sprawdz zalozenie - o tablicach m_aPositions |
|---|
| 833 | assert(m_aPositions[0] != NULL); |
|---|
| 834 | assert(m_aPositions[1] != NULL); |
|---|
| 835 | |
|---|
| 836 | // dla każdego stworzenia skopiuj informację o polozeniu jego Parts |
|---|
| 837 | // do tablic m_aPositions |
|---|
| 838 | Part *pPart; |
|---|
| 839 | int iMod; // licznik modeli (organizmow) |
|---|
| 840 | int iPart; // licznik Parts |
|---|
| 841 | for (iMod = 0; iMod < 2; iMod++) |
|---|
| 842 | { |
|---|
| 843 | // dla każdego z modeli iMod |
|---|
| 844 | for (iPart = 0; iPart < m_Mod[iMod]->getPartCount(); iPart++) |
|---|
| 845 | { |
|---|
| 846 | // dla każdego iPart organizmu iMod |
|---|
| 847 | // pobierz tego Part |
|---|
| 848 | pPart = m_Mod[iMod]->getPart(iPart); |
|---|
| 849 | // zapamietaj jego pozycje 3D w tablicy m_aPositions |
|---|
| 850 | m_aPositions[iMod][iPart].x = pPart->p.x; |
|---|
| 851 | m_aPositions[iMod][iPart].y = pPart->p.y; |
|---|
| 852 | m_aPositions[iMod][iPart].z = pPart->p.z; |
|---|
| 853 | } |
|---|
| 854 | } |
|---|
| 855 | |
|---|
| 856 | return 1; |
|---|
| 857 | } |
|---|
| 858 | |
|---|
| 859 | /** Computes numbers of neurons and neurons' inputs for each Part of each |
|---|
| 860 | organisms and fills in the m_aDegrees array. |
|---|
| 861 | Assumptions: |
|---|
| 862 | - Models (m_Mod) are created and available. |
|---|
| 863 | - Arrays m_aDegrees are created. |
|---|
| 864 | */ |
|---|
| 865 | int ModelSimil::CountPartNeurons() |
|---|
| 866 | { |
|---|
| 867 | // sprawdz zalozenie - o modelach |
|---|
| 868 | assert((m_Mod[0] != NULL) && (m_Mod[1] != NULL)); |
|---|
| 869 | assert(m_Mod[0]->isValid() && m_Mod[1]->isValid()); |
|---|
| 870 | |
|---|
| 871 | // sprawdz zalozenie - o tablicach |
|---|
| 872 | assert(m_aDegrees[0] != NULL); |
|---|
| 873 | assert(m_aDegrees[1] != NULL); |
|---|
| 874 | |
|---|
| 875 | Part *P1; |
|---|
| 876 | Joint *J1; |
|---|
| 877 | int i, j, i2, neuro_connections; |
|---|
| 878 | |
|---|
| 879 | // dla obu stworzen oblicz liczbe Neurons + connections dla Parts |
|---|
| 880 | // a takze dla OnJoints i Anywhere |
|---|
| 881 | for (i = 0; i < 2; i++) |
|---|
| 882 | { |
|---|
| 883 | for (j = 0; j < m_Mod[i]->getNeuroCount(); j++) |
|---|
| 884 | { |
|---|
| 885 | // pobierz kolejny Neuron |
|---|
| 886 | Neuro *N = m_Mod[i]->getNeuro(j); |
|---|
| 887 | // policz liczbe jego wejść i jego samego tez |
|---|
| 888 | // czy warto w ogole liczyc polaczenia...? co to da/spowoduje? |
|---|
| 889 | neuro_connections = N->getInputCount() + 1; |
|---|
| 890 | // wez Part, na ktorym jest Neuron |
|---|
| 891 | P1 = N->getPart(); |
|---|
| 892 | if (P1) |
|---|
| 893 | { |
|---|
| 894 | // dla neuronow osadzonych na Partach |
|---|
| 895 | i2 = m_Mod[i]->findPart(P1); // znajdz indeks Part w Modelu |
|---|
| 896 | m_aDegrees[i][i2][2] += neuro_connections; // zwieksz liczbe Connections+Neurons dla tego Part (TDN[2]) |
|---|
| 897 | m_aDegrees[i][i2][3]++; // zwieksz liczbe Neurons dla tego Part (TDN[3]) |
|---|
| 898 | } |
|---|
| 899 | else |
|---|
| 900 | { |
|---|
| 901 | // dla neuronow nie osadzonych na partach |
|---|
| 902 | J1 = N->getJoint(); |
|---|
| 903 | if (J1) |
|---|
| 904 | { |
|---|
| 905 | // dla tych na Jointach |
|---|
| 906 | m_aOnJoint[i][2] += neuro_connections; // zwieksz liczbe Connections+Neurons |
|---|
| 907 | m_aOnJoint[i][3]++; // zwieksz liczbe Neurons |
|---|
| 908 | } |
|---|
| 909 | else |
|---|
| 910 | { |
|---|
| 911 | // dla tych "gdziekolwiek" |
|---|
| 912 | m_aAnywhere[i][2] += neuro_connections; // zwieksz liczbe Connections+Neurons |
|---|
| 913 | m_aAnywhere[i][3]++; // zwieksz liczbe Neurons |
|---|
| 914 | } |
|---|
| 915 | } |
|---|
| 916 | } |
|---|
| 917 | } |
|---|
| 918 | return 1; |
|---|
| 919 | } |
|---|
| 920 | |
|---|
| 921 | /** Sorts arrays m_aDegrees (for each organism) by Part's degree, and then by |
|---|
| 922 | number of neural connections and neurons in groups of Parts with the same |
|---|
| 923 | degree. |
|---|
| 924 | Assumptions: |
|---|
| 925 | - Models (m_Mod) are created and available. |
|---|
| 926 | - Arrays m_aDegrees are created. |
|---|
| 927 | @saeDegrees, CompareItemNo |
|---|
| 928 | */ |
|---|
| 929 | int ModelSimil::SortPartInfoTables() |
|---|
| 930 | { |
|---|
| 931 | // sprawdz zalozenie - o modelach |
|---|
| 932 | assert((m_Mod[0] != NULL) && (m_Mod[1] != NULL)); |
|---|
| 933 | assert(m_Mod[0]->isValid() && m_Mod[1]->isValid()); |
|---|
| 934 | |
|---|
| 935 | // sprawdz zalozenie - o tablicach |
|---|
| 936 | assert(m_aDegrees[0] != NULL); |
|---|
| 937 | assert(m_aDegrees[1] != NULL); |
|---|
| 938 | |
|---|
| 939 | int i; |
|---|
| 940 | int(*pfDegreeFunction) (const void*, const void*) = NULL; |
|---|
| 941 | pfDegreeFunction = isFuzzy ? &CompareFuzzyDegrees : &CompareDegrees; |
|---|
| 942 | // sortowanie obu tablic wg stopni punktów - TDN[1] |
|---|
| 943 | for (i = 0; i < 2; i++) |
|---|
| 944 | { |
|---|
| 945 | DB(_PrintDegrees(i)); |
|---|
| 946 | std::qsort(m_aDegrees[i], (size_t)(m_Mod[i]->getPartCount()), |
|---|
| 947 | sizeof(TDN), pfDegreeFunction); |
|---|
| 948 | DB(_PrintDegrees(i)); |
|---|
| 949 | } |
|---|
| 950 | |
|---|
| 951 | // sprawdzenie wartosci parametru |
|---|
| 952 | DB(i = sizeof(TDN);) |
|---|
| 953 | int degreeType = isFuzzy ? FUZZ_DEG : DEGREE; |
|---|
| 954 | |
|---|
| 955 | // sortowanie obu tablic m_aDegrees wedlug liczby neuronów i |
|---|
| 956 | // czesci neuronu - ale w obrebie grup o tym samym stopniu |
|---|
| 957 | for (i = 0; i < 2; i++) |
|---|
| 958 | { |
|---|
| 959 | int iPocz = 0; |
|---|
| 960 | int iDeg, iNewDeg, iPartCount, j; |
|---|
| 961 | // stopien pierwszego punktu w tablicy Degrees odniesienie |
|---|
| 962 | iDeg = m_aDegrees[i][0][degreeType]; |
|---|
| 963 | iPartCount = m_Mod[i]->getPartCount(); |
|---|
| 964 | // po kolei dla kazdego punktu w organizmie |
|---|
| 965 | for (j = 0; j <= iPartCount; j++) |
|---|
| 966 | { |
|---|
| 967 | // sprawdz stopien punktu (lub nadaj 0 - gdy juz koniec tablicy) |
|---|
| 968 | // iNewDeg = (j != iPartCount) ? m_aDegrees[i][j][1] : 0; |
|---|
| 969 | // usunieto stara wersje porownania!!! wprowadzono znak porownania < |
|---|
| 970 | |
|---|
| 971 | iNewDeg = (j < iPartCount) ? m_aDegrees[i][j][degreeType] : 0; |
|---|
| 972 | // skoro tablice sa posortowane wg stopni, to mamy na pewno taka kolejnosc |
|---|
| 973 | assert(iNewDeg <= iDeg); |
|---|
| 974 | if (iNewDeg != iDeg) |
|---|
| 975 | { |
|---|
| 976 | // gdy znaleziono koniec grupy o tym samym stopniu |
|---|
| 977 | // sortuj po liczbie neuronow w obrebie grupy |
|---|
| 978 | DB(_PrintDegrees(i)); |
|---|
| 979 | DB(printf("qsort( poczatek=%i, rozmiar=%i, sizeof(TDN)=%i)\n", iPocz, (j - iPocz), sizeof(TDN));) |
|---|
| 980 | // wyswietlamy z jedna komorka po zakonczeniu tablicy |
|---|
| 981 | DB(_PrintArray(m_aDegrees[i][iPocz], 0, (j - iPocz) * 4);) |
|---|
| 982 | |
|---|
| 983 | std::qsort(m_aDegrees[i][iPocz], (size_t)(j - iPocz), |
|---|
| 984 | sizeof(TDN), ModelSimil::CompareConnsNo); |
|---|
| 985 | DB(_PrintDegrees(i)); |
|---|
| 986 | // wyswietlamy z jedna komorka po zakonczeniu tablicy |
|---|
| 987 | DB(_PrintArray(m_aDegrees[i][iPocz], 0, (j - iPocz) * 4);) |
|---|
| 988 | // rozpocznij nowa grupe |
|---|
| 989 | iPocz = j; |
|---|
| 990 | iDeg = iNewDeg; |
|---|
| 991 | } |
|---|
| 992 | } |
|---|
| 993 | } |
|---|
| 994 | return 1; |
|---|
| 995 | } |
|---|
| 996 | |
|---|
| 997 | |
|---|
| 998 | /** Prints the state of the matching object. Debug method. |
|---|
| 999 | */ |
|---|
| 1000 | void ModelSimil::_PrintPartsMatching() |
|---|
| 1001 | { |
|---|
| 1002 | // assure that matching exists |
|---|
| 1003 | assert(m_pMatching != NULL); |
|---|
| 1004 | |
|---|
| 1005 | printf("Parts matching:\n"); |
|---|
| 1006 | m_pMatching->PrintMatching(); |
|---|
| 1007 | } |
|---|
| 1008 | |
|---|
| 1009 | void ModelSimil::ComputeMatching() |
|---|
| 1010 | { |
|---|
| 1011 | // uniwersalne liczniki |
|---|
| 1012 | int i, j; |
|---|
| 1013 | |
|---|
| 1014 | assert(m_pMatching != NULL); |
|---|
| 1015 | assert(m_pMatching->IsEmpty() == true); |
|---|
| 1016 | |
|---|
| 1017 | // rozpoczynamy etap dopasowywania Parts w organizmach |
|---|
| 1018 | // czy dopasowano już wszystkie Parts? |
|---|
| 1019 | int iCzyDopasowane = 0; |
|---|
| 1020 | // koniec grupy aktualnie dopasowywanej w każdym organizmie |
|---|
| 1021 | int aiKoniecGrupyDopasowania[2] = { 0, 0 }; |
|---|
| 1022 | // koniec grupy już w całości dopasowanej |
|---|
| 1023 | // (Pomiedzy tymi dwoma indeksami znajduja sie Parts w tablicy |
|---|
| 1024 | // m_aDegrees, ktore moga byc dopasowywane (tam nadal moga |
|---|
| 1025 | // byc tez dopasowane - ale nie musi to byc w sposob |
|---|
| 1026 | // ciagly) |
|---|
| 1027 | int aiKoniecPierwszejGrupy[2] = { 0, 0 }; |
|---|
| 1028 | // Tablica przechowująca odległości poszczególnych Parts z aktualnych |
|---|
| 1029 | // grup dopasowania. Rozmiar - prostokąt o bokach równych liczbie elementów w |
|---|
| 1030 | // dopasowywanych aktualnie grupach. Pierwszy wymiar - pierwszy organizm. |
|---|
| 1031 | // Drugi wymiar - drugi organizm (nie zależy to od tego, który jest mniejszy). |
|---|
| 1032 | // Wliczane w rozmiar tablicy są nawet już dopasowane elementy - tablice |
|---|
| 1033 | // paiCzyDopasowany pamiętają stan dopasowania tych elementów. |
|---|
| 1034 | typedef double *TPDouble; |
|---|
| 1035 | double **aadOdleglosciParts; |
|---|
| 1036 | // dwie tablice okreslajace Parts, ktore moga byc do siebie dopasowywane |
|---|
| 1037 | // rozmiary: [0] - aiRozmiarCalychGrup[1] |
|---|
| 1038 | // [1] - aiRozmiarCalychGrup[0] |
|---|
| 1039 | std::vector<bool> *apvbCzyMinimalnaOdleglosc[2]; |
|---|
| 1040 | // rozmiar aktualnie dopasowywanej grupy w odpowiednim organizmie (tylko elementy |
|---|
| 1041 | // jeszcze niedopasowane). |
|---|
| 1042 | int aiRozmiarGrupy[2]; |
|---|
| 1043 | // rozmiar aktualnie dopasowywanych grup w odpowiednim organizmie (włączone są |
|---|
| 1044 | // w to również elementy już dopasowane). |
|---|
| 1045 | int aiRozmiarCalychGrup[2] = { 0, 0 }; |
|---|
| 1046 | |
|---|
| 1047 | // utworzenie tablicy rozmiarow |
|---|
| 1048 | for (i = 0; i < 2; i++) |
|---|
| 1049 | { |
|---|
| 1050 | m_aiPartCount[i] = m_Mod[i]->getPartCount(); |
|---|
| 1051 | } |
|---|
| 1052 | |
|---|
| 1053 | // DOPASOWYWANIE PARTS |
|---|
| 1054 | while (!iCzyDopasowane) |
|---|
| 1055 | { |
|---|
| 1056 | // znajdz konce obu grup aktualnie dopasowywanych w obu organizmach |
|---|
| 1057 | for (i = 0; i < 2; i++) |
|---|
| 1058 | { |
|---|
| 1059 | // czyli poszukaj miejsca zmiany stopnia lub konca tablicy |
|---|
| 1060 | for (j = aiKoniecPierwszejGrupy[i] + 1; j < m_aiPartCount[i]; j++) |
|---|
| 1061 | { |
|---|
| 1062 | if (m_aDegrees[i][j][DEGREE] < m_aDegrees[i][j - 1][DEGREE]) |
|---|
| 1063 | { |
|---|
| 1064 | break; |
|---|
| 1065 | } |
|---|
| 1066 | } |
|---|
| 1067 | aiKoniecGrupyDopasowania[i] = j; |
|---|
| 1068 | |
|---|
| 1069 | // sprawdz poprawnosc tego indeksu |
|---|
| 1070 | assert((aiKoniecGrupyDopasowania[i] > 0) && |
|---|
| 1071 | (aiKoniecGrupyDopasowania[i] <= m_aiPartCount[i])); |
|---|
| 1072 | |
|---|
| 1073 | // oblicz rozmiary całych grup - łącznie z dopasowanymi już elementami |
|---|
| 1074 | aiRozmiarCalychGrup[i] = aiKoniecGrupyDopasowania[i] - |
|---|
| 1075 | aiKoniecPierwszejGrupy[i]; |
|---|
| 1076 | |
|---|
| 1077 | // sprawdz teraz rozmiar tej grupy w sensie liczby niedopasowanzch |
|---|
| 1078 | // nie moze to byc puste! |
|---|
| 1079 | aiRozmiarGrupy[i] = 0; |
|---|
| 1080 | for (j = aiKoniecPierwszejGrupy[i]; j < aiKoniecGrupyDopasowania[i]; j++) |
|---|
| 1081 | { |
|---|
| 1082 | // od poczatku do konca grupy |
|---|
| 1083 | if (!m_pMatching->IsMatched(i, j)) |
|---|
| 1084 | { |
|---|
| 1085 | // jesli niedopasowany, to zwieksz licznik |
|---|
| 1086 | aiRozmiarGrupy[i]++; |
|---|
| 1087 | } |
|---|
| 1088 | } |
|---|
| 1089 | // grupa nie moze byc pusta! |
|---|
| 1090 | assert(aiRozmiarGrupy[i] > 0); |
|---|
| 1091 | } |
|---|
| 1092 | |
|---|
| 1093 | // DOPASOWYWANIE PARTS Z GRUP |
|---|
| 1094 | |
|---|
| 1095 | // stworzenie tablicy odległości lokalnych |
|---|
| 1096 | // stwórz pierwszy wymiar - wg rozmiaru zerowego organizmu |
|---|
| 1097 | aadOdleglosciParts = new TPDouble[aiRozmiarCalychGrup[0]]; |
|---|
| 1098 | assert(aadOdleglosciParts != NULL); |
|---|
| 1099 | // stwórz drugi wymiar - wg rozmiaru drugiego organizmu |
|---|
| 1100 | for (i = 0; i < aiRozmiarCalychGrup[0]; i++) |
|---|
| 1101 | { |
|---|
| 1102 | aadOdleglosciParts[i] = new double[aiRozmiarCalychGrup[1]]; |
|---|
| 1103 | assert(aadOdleglosciParts[i] != NULL); |
|---|
| 1104 | } |
|---|
| 1105 | |
|---|
| 1106 | // stworzenie tablic mozliwosci dopasowania (indykatorow minimalnej odleglosci) |
|---|
| 1107 | apvbCzyMinimalnaOdleglosc[0] = new std::vector<bool>(aiRozmiarCalychGrup[1], false); |
|---|
| 1108 | apvbCzyMinimalnaOdleglosc[1] = new std::vector<bool>(aiRozmiarCalychGrup[0], false); |
|---|
| 1109 | // sprawdz stworzenie tablic |
|---|
| 1110 | assert(apvbCzyMinimalnaOdleglosc[0] != NULL); |
|---|
| 1111 | assert(apvbCzyMinimalnaOdleglosc[1] != NULL); |
|---|
| 1112 | |
|---|
| 1113 | // wypełnienie elementów macierzy (i,j) odległościami pomiędzy |
|---|
| 1114 | // odpowiednimi Parts: (i) w organizmie 0 i (j) w organizmie 1. |
|---|
| 1115 | // UWAGA! Uwzględniamy tylko te Parts, które nie są jeszcze dopasowane |
|---|
| 1116 | // (reszta to byłaby po prostu strata czasu). |
|---|
| 1117 | int iDeg, iNeu; // ilościowe określenie różnic stopnia, liczby neuronów i połączeń Parts |
|---|
| 1118 | //int iNIt; |
|---|
| 1119 | double dGeo; // ilościowe określenie różnic geometrycznych pomiędzy Parts |
|---|
| 1120 | // indeksy konkretnych Parts - indeksy sa ZERO-BASED, choć właściwy dostep |
|---|
| 1121 | // do informacji o Part wymaga dodania aiKoniecPierwszejGrupy[] |
|---|
| 1122 | // tylko aadOdleglosciParts[][] indeksuje sie bezposrednio zawartoscia iIndex[] |
|---|
| 1123 | int iIndex[2]; |
|---|
| 1124 | int iPartIndex[2] = { -1, -1 }; // at [iModel]: original index of a Part for the specified model (iModel) |
|---|
| 1125 | |
|---|
| 1126 | // debug - wypisz zakres dopasowywanych indeksow |
|---|
| 1127 | DB(printf("Organizm 0: grupa: (%2i, %2i)\n", aiKoniecPierwszejGrupy[0], |
|---|
| 1128 | aiKoniecGrupyDopasowania[0]);) |
|---|
| 1129 | DB(printf("Organizm 1: grupa: (%2i, %2i)\n", aiKoniecPierwszejGrupy[1], |
|---|
| 1130 | aiKoniecGrupyDopasowania[1]);) |
|---|
| 1131 | |
|---|
| 1132 | for (i = 0; i < aiRozmiarCalychGrup[0]; i++) |
|---|
| 1133 | { |
|---|
| 1134 | |
|---|
| 1135 | // iterujemy i - Parts organizmu 0 |
|---|
| 1136 | // (indeks podstawowy - aiKoniecPierwszejGrupy[0]) |
|---|
| 1137 | |
|---|
| 1138 | if (!(m_pMatching->IsMatched(0, aiKoniecPierwszejGrupy[0] + i))) |
|---|
| 1139 | { |
|---|
| 1140 | // interesuja nas tylko te niedopasowane jeszcze (i) |
|---|
| 1141 | for (j = 0; j < aiRozmiarCalychGrup[1]; j++) |
|---|
| 1142 | { |
|---|
| 1143 | |
|---|
| 1144 | // iterujemy j - Parts organizmu 1 |
|---|
| 1145 | // (indeks podstawowy - aiKoniecPierwszejGrupy[1]) |
|---|
| 1146 | |
|---|
| 1147 | if (!(m_pMatching->IsMatched(1, aiKoniecPierwszejGrupy[1] + j))) |
|---|
| 1148 | { |
|---|
| 1149 | // interesuja nas tylko te niedopasowane jeszcze (j) |
|---|
| 1150 | // teraz obliczymy lokalne różnice pomiędzy Parts |
|---|
| 1151 | iDeg = abs(m_aDegrees[0][aiKoniecPierwszejGrupy[0] + i][1] |
|---|
| 1152 | - m_aDegrees[1][aiKoniecPierwszejGrupy[1] + j][1]); |
|---|
| 1153 | |
|---|
| 1154 | //iNit currently is not a component of distance measure |
|---|
| 1155 | //iNIt = abs(m_aDegrees[0][ aiKoniecPierwszejGrupy[0] + i ][2] |
|---|
| 1156 | // - m_aDegrees[1][ aiKoniecPierwszejGrupy[1] + j ][2]); |
|---|
| 1157 | |
|---|
| 1158 | iNeu = abs(m_aDegrees[0][aiKoniecPierwszejGrupy[0] + i][3] |
|---|
| 1159 | - m_aDegrees[1][aiKoniecPierwszejGrupy[1] + j][3]); |
|---|
| 1160 | |
|---|
| 1161 | // obliczenie także lokalnych różnic geometrycznych pomiędzy Parts |
|---|
| 1162 | // find original indices of Parts for both of the models |
|---|
| 1163 | iPartIndex[0] = m_aDegrees[0][aiKoniecPierwszejGrupy[0] + i][0]; |
|---|
| 1164 | iPartIndex[1] = m_aDegrees[1][aiKoniecPierwszejGrupy[1] + j][0]; |
|---|
| 1165 | // now compute the geometrical distance of these Parts (use m_aPositions |
|---|
| 1166 | // which should be computed by SVD) |
|---|
| 1167 | Pt3D Part0Pos(m_aPositions[0][iPartIndex[0]]); |
|---|
| 1168 | Pt3D Part1Pos(m_aPositions[1][iPartIndex[1]]); |
|---|
| 1169 | dGeo = m_adFactors[3] == 0 ? 0 : Part0Pos.distanceTo(Part1Pos); //no need to compute distane when m_dDG weight is 0 |
|---|
| 1170 | |
|---|
| 1171 | // tutaj prawdopodobnie należy jeszcze dodać sprawdzanie |
|---|
| 1172 | // identyczności pozostałych własności (oprócz geometrii) |
|---|
| 1173 | // - żeby móc stwierdzić w ogóle identyczność Parts |
|---|
| 1174 | |
|---|
| 1175 | // i ostateczna odleglosc indukowana przez te roznice |
|---|
| 1176 | // (tutaj nie ma różnicy w liczbie wszystkich wierzchołków) |
|---|
| 1177 | aadOdleglosciParts[i][j] = m_adFactors[1] * double(iDeg) + |
|---|
| 1178 | m_adFactors[2] * double(iNeu) + |
|---|
| 1179 | m_adFactors[3] * dGeo; |
|---|
| 1180 | DB(printf("Parts Distance (%2i,%2i) = %.3lf\n", aiKoniecPierwszejGrupy[0] + i, |
|---|
| 1181 | aiKoniecPierwszejGrupy[1] + j, aadOdleglosciParts[i][j]);) |
|---|
| 1182 | DB(printf("Parts geometrical distance = %.20lf\n", dGeo);) |
|---|
| 1183 | DB(printf("Pos0: (%.3lf %.3lf %.3lf)\n", Part0Pos.x, Part0Pos.y, Part0Pos.z);) |
|---|
| 1184 | DB(printf("Pos1: (%.3lf %.3lf %.3lf)\n", Part1Pos.x, Part1Pos.y, Part1Pos.z);) |
|---|
| 1185 | } |
|---|
| 1186 | } |
|---|
| 1187 | } |
|---|
| 1188 | } |
|---|
| 1189 | |
|---|
| 1190 | // tutaj - sprawdzic tylko, czy tablica odleglosci lokalnych jest poprawnie obliczona |
|---|
| 1191 | |
|---|
| 1192 | // WYKORZYSTANIE TABLICY ODLEGLOSCI DO BUDOWY DOPASOWANIA |
|---|
| 1193 | |
|---|
| 1194 | // trzeba raczej iterować aż do zebrania wszystkich możliwych dopasowań w grupie |
|---|
| 1195 | // dlatego wprowadzamy dodatkowa zmienna - czy skonczyla sie juz grupa |
|---|
| 1196 | bool bCzyKoniecGrupy = false; |
|---|
| 1197 | while (!bCzyKoniecGrupy) |
|---|
| 1198 | { |
|---|
| 1199 | for (i = 0; i < 2; i++) |
|---|
| 1200 | { |
|---|
| 1201 | // iterujemy (i) po organizmach |
|---|
| 1202 | // szukamy najpierw jakiegoś niedopasowanego jeszcze Part w organizmach |
|---|
| 1203 | |
|---|
| 1204 | // zakładamy, że nie ma takiego Part |
|---|
| 1205 | iIndex[i] = -1; |
|---|
| 1206 | |
|---|
| 1207 | for (j = 0; j < aiRozmiarCalychGrup[i]; j++) |
|---|
| 1208 | { |
|---|
| 1209 | // iterujemy (j) - Parts organizmu (i) |
|---|
| 1210 | // (indeks podstawowy - aiKoniecPierwszejGrupy[0]) |
|---|
| 1211 | if (!(m_pMatching->IsMatched(i, aiKoniecPierwszejGrupy[i] + j))) |
|---|
| 1212 | { |
|---|
| 1213 | // gdy mamy w tej grupie jakis niedopasowany element, to ustawiamy |
|---|
| 1214 | // iIndex[i] (chcemy w zasadzie pierwszy taki) |
|---|
| 1215 | iIndex[i] = j; |
|---|
| 1216 | break; |
|---|
| 1217 | } |
|---|
| 1218 | } |
|---|
| 1219 | |
|---|
| 1220 | // sprawdzamy, czy w ogole znaleziono taki Part |
|---|
| 1221 | if (iIndex[i] < 0) |
|---|
| 1222 | { |
|---|
| 1223 | // gdy nie znaleziono takiego Part - mamy koniec dopasowywania w |
|---|
| 1224 | // tych grupach |
|---|
| 1225 | bCzyKoniecGrupy = true; |
|---|
| 1226 | } |
|---|
| 1227 | // sprawdz poprawnosc indeksu niedopasowanego Part - musi byc w aktualnej grupie |
|---|
| 1228 | assert((iIndex[i] >= -1) && (iIndex[i] < aiRozmiarCalychGrup[i])); |
|---|
| 1229 | } |
|---|
| 1230 | |
|---|
| 1231 | |
|---|
| 1232 | // teraz mamy sytuacje: |
|---|
| 1233 | // - mamy w iIndex[0] i iIndex[1] indeksy pierwszych niedopasowanych Part |
|---|
| 1234 | // w organizmach, albo |
|---|
| 1235 | // - nie ma w ogóle już czego dopasowywać (należy przejść do innej grupy) |
|---|
| 1236 | if (!bCzyKoniecGrupy) |
|---|
| 1237 | { |
|---|
| 1238 | // gdy nie ma jeszcze końca żadnej z grup - możemy dopasowywać |
|---|
| 1239 | // najpierw wyszukujemy w tablicy minimum odległości od tych |
|---|
| 1240 | // wyznaczonych Parts |
|---|
| 1241 | |
|---|
| 1242 | // najpierw wyczyscimy wektory potencjalnych dopasowan |
|---|
| 1243 | // dla organizmu 1 (o rozmiarze grupy z 0) |
|---|
| 1244 | for (i = 0; i < aiRozmiarCalychGrup[0]; i++) |
|---|
| 1245 | { |
|---|
| 1246 | apvbCzyMinimalnaOdleglosc[1]->operator[](i) = false; |
|---|
| 1247 | } |
|---|
| 1248 | // dla organizmu 0 (o rozmiarze grup z 1) |
|---|
| 1249 | for (i = 0; i < aiRozmiarCalychGrup[1]; i++) |
|---|
| 1250 | { |
|---|
| 1251 | apvbCzyMinimalnaOdleglosc[0]->operator[](i) = false; |
|---|
| 1252 | } |
|---|
| 1253 | |
|---|
| 1254 | // szukanie minimum dla Part o indeksie iIndex[0] w organizmie 0 |
|---|
| 1255 | // wsrod niedopasowanych Parts z organizmu 1 |
|---|
| 1256 | // zakładamy, że nie znaleliśmy jeszcze minimum |
|---|
| 1257 | double dMinimum = HUGE_VAL; |
|---|
| 1258 | for (i = 0; i < aiRozmiarCalychGrup[1]; i++) |
|---|
| 1259 | { |
|---|
| 1260 | if (!(m_pMatching->IsMatched(1, aiKoniecPierwszejGrupy[1] + i))) |
|---|
| 1261 | { |
|---|
| 1262 | |
|---|
| 1263 | // szukamy minimum obliczonej lokalnej odleglosci tylko wsrod |
|---|
| 1264 | // niedopasowanych jeszcze Parts |
|---|
| 1265 | if (aadOdleglosciParts[iIndex[0]][i] < dMinimum) |
|---|
| 1266 | { |
|---|
| 1267 | dMinimum = aadOdleglosciParts[iIndex[0]][i]; |
|---|
| 1268 | } |
|---|
| 1269 | |
|---|
| 1270 | // przy okazji - sprawdz, czy HUGE_VAL jest rzeczywiscie max dla double |
|---|
| 1271 | assert(aadOdleglosciParts[iIndex[0]][i] < HUGE_VAL); |
|---|
| 1272 | } |
|---|
| 1273 | } |
|---|
| 1274 | // sprawdz, czy minimum znaleziono - musi takie byc, bo jest cos niedopasowanego |
|---|
| 1275 | assert((dMinimum >= 0.0) && (dMinimum < HUGE_VAL)); |
|---|
| 1276 | |
|---|
| 1277 | // teraz zaznaczamy w tablicy te wszystkie Parts, ktore maja |
|---|
| 1278 | // rzeczywiscie te minimalna odleglosc do Part iIndex[0] w organizmie 0 |
|---|
| 1279 | for (i = 0; i < aiRozmiarCalychGrup[1]; i++) |
|---|
| 1280 | { |
|---|
| 1281 | if (!(m_pMatching->IsMatched(1, aiKoniecPierwszejGrupy[1] + i))) |
|---|
| 1282 | { |
|---|
| 1283 | if (aadOdleglosciParts[iIndex[0]][i] == dMinimum) |
|---|
| 1284 | { |
|---|
| 1285 | // jesli w danym miejscu tablicy odleglosci jest faktyczne |
|---|
| 1286 | // minimum odleglosci, to mamy potencjalna pare dla iIndex[0] |
|---|
| 1287 | apvbCzyMinimalnaOdleglosc[0]->operator[](i) = true; |
|---|
| 1288 | } |
|---|
| 1289 | |
|---|
| 1290 | // sprawdz poprawnosc znalezionego wczesniej minimum |
|---|
| 1291 | assert(aadOdleglosciParts[iIndex[0]][i] >= dMinimum); |
|---|
| 1292 | } |
|---|
| 1293 | } |
|---|
| 1294 | |
|---|
| 1295 | // podobnie szukamy minimum dla Part o indeksie iIndex[1] w organizmie 1 |
|---|
| 1296 | // wsrod niedopasowanych Parts z organizmu 0 |
|---|
| 1297 | dMinimum = HUGE_VAL; |
|---|
| 1298 | for (i = 0; i < aiRozmiarCalychGrup[0]; i++) |
|---|
| 1299 | { |
|---|
| 1300 | if (!(m_pMatching->IsMatched(0, aiKoniecPierwszejGrupy[0] + i))) |
|---|
| 1301 | { |
|---|
| 1302 | // szukamy minimum obliczonej lokalnej odleglosci tylko wsrod |
|---|
| 1303 | // niedopasowanych jeszcze Parts |
|---|
| 1304 | if (aadOdleglosciParts[i][iIndex[1]] < dMinimum) |
|---|
| 1305 | { |
|---|
| 1306 | dMinimum = aadOdleglosciParts[i][iIndex[1]]; |
|---|
| 1307 | } |
|---|
| 1308 | // przy okazji - sprawdz, czy HUGE_VAL jest rzeczywiscie max dla double |
|---|
| 1309 | assert(aadOdleglosciParts[i][iIndex[1]] < HUGE_VAL); |
|---|
| 1310 | } |
|---|
| 1311 | } |
|---|
| 1312 | // sprawdz, czy minimum znaleziono - musi takie byc, bo jest cos niedopasowanego |
|---|
| 1313 | assert((dMinimum >= 0.0) && (dMinimum < HUGE_VAL)); |
|---|
| 1314 | |
|---|
| 1315 | // teraz zaznaczamy w tablicy te wszystkie Parts, ktore maja |
|---|
| 1316 | // rzeczywiscie te minimalne odleglosci do Part iIndex[1] w organizmie 1 |
|---|
| 1317 | for (i = 0; i < aiRozmiarCalychGrup[0]; i++) |
|---|
| 1318 | { |
|---|
| 1319 | if (!(m_pMatching->IsMatched(0, aiKoniecPierwszejGrupy[0] + i))) |
|---|
| 1320 | { |
|---|
| 1321 | if (aadOdleglosciParts[i][iIndex[1]] == dMinimum) |
|---|
| 1322 | { |
|---|
| 1323 | // jesli w danym miejscu tablicy odleglosci jest faktyczne |
|---|
| 1324 | // minimum odleglosci, to mamy potencjalna pare dla iIndex[1] |
|---|
| 1325 | apvbCzyMinimalnaOdleglosc[1]->operator[](i) = true; |
|---|
| 1326 | } |
|---|
| 1327 | |
|---|
| 1328 | // sprawdz poprawnosc znalezionego wczesniej minimum |
|---|
| 1329 | assert(aadOdleglosciParts[i][iIndex[1]] >= dMinimum); |
|---|
| 1330 | } |
|---|
| 1331 | } |
|---|
| 1332 | |
|---|
| 1333 | // teraz mamy juz poszukane potencjalne grupy dopasowania - musimy |
|---|
| 1334 | // zdecydowac, co do czego dopasujemy! |
|---|
| 1335 | // szukamy Part iIndex[0] posrod mozliwych do dopasowania dla Part iIndex[1] |
|---|
| 1336 | // szukamy takze Part iIndex[1] posrod mozliwych do dopasowania dla Part iIndex[0] |
|---|
| 1337 | bool PartZ1NaLiscie0 = apvbCzyMinimalnaOdleglosc[0]->operator[](iIndex[1]); |
|---|
| 1338 | bool PartZ0NaLiscie1 = apvbCzyMinimalnaOdleglosc[1]->operator[](iIndex[0]); |
|---|
| 1339 | |
|---|
| 1340 | if (PartZ1NaLiscie0 && PartZ0NaLiscie1) |
|---|
| 1341 | { |
|---|
| 1342 | // PRZYPADEK 1. Oba Parts maja sie wzajemnie na listach mozliwych |
|---|
| 1343 | // dopasowan. |
|---|
| 1344 | // AKCJA. Dopasowanie wzajemne do siebie. |
|---|
| 1345 | |
|---|
| 1346 | m_pMatching->Match(0, aiKoniecPierwszejGrupy[0] + iIndex[0], |
|---|
| 1347 | 1, aiKoniecPierwszejGrupy[1] + iIndex[1]); |
|---|
| 1348 | |
|---|
| 1349 | // zmniejsz liczby niedopasowanych elementow w grupach |
|---|
| 1350 | aiRozmiarGrupy[0]--; |
|---|
| 1351 | aiRozmiarGrupy[1]--; |
|---|
| 1352 | // debug - co zostalo dopasowane |
|---|
| 1353 | DB(printf("Przypadek 1.: dopasowane Parts: (%2i, %2i)\n", aiKoniecPierwszejGrupy[0] |
|---|
| 1354 | + iIndex[0], aiKoniecPierwszejGrupy[1] + iIndex[1]);) |
|---|
| 1355 | |
|---|
| 1356 | }// PRZYPADEK 1. |
|---|
| 1357 | else |
|---|
| 1358 | if (PartZ1NaLiscie0 || PartZ0NaLiscie1) |
|---|
| 1359 | { |
|---|
| 1360 | // PRZYPADEK 2. Tylko jeden z Parts ma drugiego na swojej liscie |
|---|
| 1361 | // mozliwych dopasowan |
|---|
| 1362 | // AKCJA. Dopasowanie jednego jest proste (tego, ktory nie ma |
|---|
| 1363 | // na swojej liscie drugiego). Dla tego drugiego nalezy powtorzyc |
|---|
| 1364 | // duza czesc obliczen (znalezc mu nowa mozliwa pare) |
|---|
| 1365 | |
|---|
| 1366 | // indeks organizmu, ktorego Part nie ma dopasowywanego Part |
|---|
| 1367 | // z drugiego organizmu na swojej liscie |
|---|
| 1368 | int iBezDrugiego; |
|---|
| 1369 | |
|---|
| 1370 | // okreslenie indeksu organizmu z dopasowywanym Part |
|---|
| 1371 | if (!PartZ1NaLiscie0) |
|---|
| 1372 | { |
|---|
| 1373 | iBezDrugiego = 0; |
|---|
| 1374 | } |
|---|
| 1375 | else |
|---|
| 1376 | { |
|---|
| 1377 | iBezDrugiego = 1; |
|---|
| 1378 | } |
|---|
| 1379 | // sprawdz indeks organizmu |
|---|
| 1380 | assert((iBezDrugiego == 0) || (iBezDrugiego == 1)); |
|---|
| 1381 | |
|---|
| 1382 | int iDopasowywany = -1; |
|---|
| 1383 | // poszukujemy pierwszego z listy dopasowania |
|---|
| 1384 | for (i = 0; i < aiRozmiarCalychGrup[1 - iBezDrugiego]; i++) |
|---|
| 1385 | { |
|---|
| 1386 | if (apvbCzyMinimalnaOdleglosc[iBezDrugiego]->operator[](i)) |
|---|
| 1387 | { |
|---|
| 1388 | iDopasowywany = i; |
|---|
| 1389 | break; |
|---|
| 1390 | } |
|---|
| 1391 | } |
|---|
| 1392 | // sprawdz poprawnosc indeksu dopasowywanego (musimy cos znalezc!) |
|---|
| 1393 | // nieujemny i w odpowiedniej grupie! |
|---|
| 1394 | assert((iDopasowywany >= 0) && |
|---|
| 1395 | (iDopasowywany < aiRozmiarCalychGrup[1 - iBezDrugiego])); |
|---|
| 1396 | |
|---|
| 1397 | // znalezlismy 1. Part z listy dopasowania - dopasowujemy! |
|---|
| 1398 | m_pMatching->Match( |
|---|
| 1399 | iBezDrugiego, |
|---|
| 1400 | aiKoniecPierwszejGrupy[iBezDrugiego] + iIndex[iBezDrugiego], |
|---|
| 1401 | 1 - iBezDrugiego, |
|---|
| 1402 | aiKoniecPierwszejGrupy[1 - iBezDrugiego] + iDopasowywany); |
|---|
| 1403 | DB(printf("Przypadek 2.1.: dopasowane Parts dopasowanie bez drugiego: (%2i, %2i)\n", aiKoniecPierwszejGrupy[iBezDrugiego] + iIndex[iBezDrugiego], |
|---|
| 1404 | aiKoniecPierwszejGrupy[1 - iBezDrugiego] + iDopasowywany);) |
|---|
| 1405 | |
|---|
| 1406 | // zmniejsz liczby niedopasowanych elementow w grupach |
|---|
| 1407 | aiRozmiarGrupy[0]--; |
|---|
| 1408 | aiRozmiarGrupy[1]--; |
|---|
| 1409 | |
|---|
| 1410 | // sprawdz, czy jest szansa dopasowania tego Part z drugiej strony |
|---|
| 1411 | // (ktora miala mozliwosc dopasowania tego Part z poprzedniego organizmu) |
|---|
| 1412 | if ((aiRozmiarGrupy[0] > 0) && (aiRozmiarGrupy[1] > 0)) |
|---|
| 1413 | { |
|---|
| 1414 | // jesli grupy sie jeszcze nie wyczrpaly |
|---|
| 1415 | // to jest mozliwosc dopasowania w organizmie |
|---|
| 1416 | |
|---|
| 1417 | int iZDrugim = 1 - iBezDrugiego; |
|---|
| 1418 | // sprawdz indeks organizmu |
|---|
| 1419 | assert((iZDrugim == 0) || (iZDrugim == 1)); |
|---|
| 1420 | |
|---|
| 1421 | // bedziemy szukac minimum wsrod niedopasowanych - musimy wykasowac |
|---|
| 1422 | // poprzednie obliczenia minimum |
|---|
| 1423 | // dla organizmu 1 (o rozmiarze grupy z 0) |
|---|
| 1424 | for (i = 0; i < aiRozmiarCalychGrup[0]; i++) |
|---|
| 1425 | { |
|---|
| 1426 | apvbCzyMinimalnaOdleglosc[1]->operator[](i) = false; |
|---|
| 1427 | } |
|---|
| 1428 | // dla organizmu 0 (o rozmiarze grup z 1) |
|---|
| 1429 | for (i = 0; i < aiRozmiarCalychGrup[1]; i++) |
|---|
| 1430 | { |
|---|
| 1431 | apvbCzyMinimalnaOdleglosc[0]->operator[](i) = false; |
|---|
| 1432 | } |
|---|
| 1433 | |
|---|
| 1434 | // szukamy na nowo minimum dla Part o indeksie iIndex[ iZDrugim ] w organizmie iZDrugim |
|---|
| 1435 | // wsrod niedopasowanych Parts z organizmu 1 - iZDrugim |
|---|
| 1436 | dMinimum = HUGE_VAL; |
|---|
| 1437 | for (i = 0; i < aiRozmiarCalychGrup[1 - iZDrugim]; i++) |
|---|
| 1438 | { |
|---|
| 1439 | if (!(m_pMatching->IsMatched( |
|---|
| 1440 | 1 - iZDrugim, |
|---|
| 1441 | aiKoniecPierwszejGrupy[1 - iZDrugim] + i))) |
|---|
| 1442 | { |
|---|
| 1443 | // szukamy minimum obliczonej lokalnej odleglosci tylko wsrod |
|---|
| 1444 | // niedopasowanych jeszcze Parts |
|---|
| 1445 | if (iZDrugim == 0) |
|---|
| 1446 | { |
|---|
| 1447 | // teraz niestety musimy rozpoznac odpowiedni organizm |
|---|
| 1448 | // zeby moc indeksowac niesymetryczna tablice |
|---|
| 1449 | if (aadOdleglosciParts[iIndex[0]][i] < dMinimum) |
|---|
| 1450 | { |
|---|
| 1451 | dMinimum = aadOdleglosciParts[iIndex[0]][i]; |
|---|
| 1452 | } |
|---|
| 1453 | // przy okazji - sprawdz, czy HUGE_VAL jest rzeczywiscie max dla double |
|---|
| 1454 | assert(aadOdleglosciParts[iIndex[0]][i] < HUGE_VAL); |
|---|
| 1455 | |
|---|
| 1456 | } |
|---|
| 1457 | else |
|---|
| 1458 | { |
|---|
| 1459 | if (aadOdleglosciParts[i][iIndex[1]] < dMinimum) |
|---|
| 1460 | { |
|---|
| 1461 | dMinimum = aadOdleglosciParts[i][iIndex[1]]; |
|---|
| 1462 | } |
|---|
| 1463 | // przy okazji - sprawdz, czy HUGE_VAL jest rzeczywiscie max dla double |
|---|
| 1464 | assert(aadOdleglosciParts[i][iIndex[1]] < HUGE_VAL); |
|---|
| 1465 | } |
|---|
| 1466 | } |
|---|
| 1467 | } |
|---|
| 1468 | // sprawdz, czy minimum znaleziono - musi takie byc, bo jest cos niedopasowanego |
|---|
| 1469 | assert((dMinimum >= 0.0) && (dMinimum < HUGE_VAL)); |
|---|
| 1470 | |
|---|
| 1471 | // teraz zaznaczamy w tablicy te wszystkie Parts, ktore maja |
|---|
| 1472 | // rzeczywiscie te minimalne odleglosci do Part w organizmie iZDrugim |
|---|
| 1473 | for (i = 0; i < aiRozmiarCalychGrup[1 - iZDrugim]; i++) |
|---|
| 1474 | { |
|---|
| 1475 | if (!(m_pMatching->IsMatched( |
|---|
| 1476 | 1 - iZDrugim, |
|---|
| 1477 | aiKoniecPierwszejGrupy[1 - iZDrugim] + i))) |
|---|
| 1478 | { |
|---|
| 1479 | if (iZDrugim == 0) |
|---|
| 1480 | { |
|---|
| 1481 | // teraz niestety musimy rozpoznac odpowiedni organizm |
|---|
| 1482 | // zeby moc indeksowac niesymetryczna tablice |
|---|
| 1483 | if (aadOdleglosciParts[iIndex[0]][i] == dMinimum) |
|---|
| 1484 | { |
|---|
| 1485 | // jesli w danym miejscu tablicy odleglosci jest faktyczne |
|---|
| 1486 | // minimum odleglosci, to mamy potencjalna pare dla iIndex[1] |
|---|
| 1487 | apvbCzyMinimalnaOdleglosc[0]->operator[](i) = true; |
|---|
| 1488 | } |
|---|
| 1489 | } |
|---|
| 1490 | else |
|---|
| 1491 | { |
|---|
| 1492 | if (aadOdleglosciParts[i][iIndex[1]] == dMinimum) |
|---|
| 1493 | { |
|---|
| 1494 | apvbCzyMinimalnaOdleglosc[1]->operator[](i) = true; |
|---|
| 1495 | } |
|---|
| 1496 | } |
|---|
| 1497 | } |
|---|
| 1498 | } |
|---|
| 1499 | |
|---|
| 1500 | // a teraz - po znalezieniu potencjalnych elementow do dopasowania |
|---|
| 1501 | // dopasowujemy pierwszy z potencjalnych |
|---|
| 1502 | iDopasowywany = -1; |
|---|
| 1503 | for (i = 0; i < aiRozmiarCalychGrup[1 - iZDrugim]; i++) |
|---|
| 1504 | { |
|---|
| 1505 | if (apvbCzyMinimalnaOdleglosc[iZDrugim]->operator[](i)) |
|---|
| 1506 | { |
|---|
| 1507 | iDopasowywany = i; |
|---|
| 1508 | break; |
|---|
| 1509 | } |
|---|
| 1510 | } |
|---|
| 1511 | // musielismy znalezc jakiegos dopasowywanego |
|---|
| 1512 | assert((iDopasowywany >= 0) && |
|---|
| 1513 | (iDopasowywany < aiRozmiarCalychGrup[1 - iZDrugim])); |
|---|
| 1514 | |
|---|
| 1515 | // no to juz mozemy dopasowac |
|---|
| 1516 | m_pMatching->Match( |
|---|
| 1517 | iZDrugim, |
|---|
| 1518 | aiKoniecPierwszejGrupy[iZDrugim] + iIndex[iZDrugim], |
|---|
| 1519 | 1 - iZDrugim, |
|---|
| 1520 | aiKoniecPierwszejGrupy[1 - iZDrugim] + iDopasowywany); |
|---|
| 1521 | DB(printf("Przypadek 2.1.: dopasowane Parts dopasowaniebz drugim: (%2i, %2i)\n", aiKoniecPierwszejGrupy[iZDrugim] + iIndex[iZDrugim], aiKoniecPierwszejGrupy[1 - iZDrugim] + iDopasowywany);) |
|---|
| 1522 | |
|---|
| 1523 | //aiKoniecPierwszejGrupy[ 1-iBezDrugiego ] + iDopasowywany ;) |
|---|
| 1524 | //aiKoniecPierwszejGrupy[ 1-iBezDrugiego ] + iDopasowywany ;) |
|---|
| 1525 | // zmniejsz liczby niedopasowanych elementow w grupach |
|---|
| 1526 | aiRozmiarGrupy[0]--; |
|---|
| 1527 | aiRozmiarGrupy[1]--; |
|---|
| 1528 | |
|---|
| 1529 | } |
|---|
| 1530 | else |
|---|
| 1531 | { |
|---|
| 1532 | // jedna z grup sie juz wyczerpala |
|---|
| 1533 | // wiec nie ma mozliwosci dopasowania tego drugiego Partu |
|---|
| 1534 | /// i trzeba poczekac na zmiane grupy |
|---|
| 1535 | } |
|---|
| 1536 | |
|---|
| 1537 | DB(printf("Przypadek 2.\n");) |
|---|
| 1538 | |
|---|
| 1539 | }// PRZYPADEK 2. |
|---|
| 1540 | else |
|---|
| 1541 | { |
|---|
| 1542 | // PRZYPADEK 3. Zaden z Parts nie ma na liscie drugiego |
|---|
| 1543 | // AKCJA. Niezalezne dopasowanie obu Parts do pierwszych ze swojej listy |
|---|
| 1544 | |
|---|
| 1545 | // najpierw dopasujemy do iIndex[0] w organizmie 0 |
|---|
| 1546 | int iDopasowywany = -1; |
|---|
| 1547 | // poszukujemy pierwszego z listy dopasowania - w organizmie 1 |
|---|
| 1548 | for (i = 0; i < aiRozmiarCalychGrup[1]; i++) |
|---|
| 1549 | { |
|---|
| 1550 | if (apvbCzyMinimalnaOdleglosc[0]->operator[](i)) |
|---|
| 1551 | { |
|---|
| 1552 | iDopasowywany = i; |
|---|
| 1553 | break; |
|---|
| 1554 | } |
|---|
| 1555 | } |
|---|
| 1556 | // musielismy znalezc jakiegos dopasowywanego |
|---|
| 1557 | assert((iDopasowywany >= 0) && |
|---|
| 1558 | (iDopasowywany < aiRozmiarCalychGrup[1])); |
|---|
| 1559 | |
|---|
| 1560 | // teraz wlasnie dopasowujemy |
|---|
| 1561 | m_pMatching->Match( |
|---|
| 1562 | 0, |
|---|
| 1563 | aiKoniecPierwszejGrupy[0] + iIndex[0], |
|---|
| 1564 | 1, |
|---|
| 1565 | aiKoniecPierwszejGrupy[1] + iDopasowywany); |
|---|
| 1566 | |
|---|
| 1567 | // zmniejszamy liczbe niedopasowanych Parts |
|---|
| 1568 | aiRozmiarGrupy[0]--; |
|---|
| 1569 | aiRozmiarGrupy[1]--; |
|---|
| 1570 | |
|---|
| 1571 | // debug - dopasowanie |
|---|
| 1572 | DB(printf("Przypadek 3.: dopasowane Parts: (%2i, %2i)\n", aiKoniecPierwszejGrupy[0] |
|---|
| 1573 | + iIndex[0], aiKoniecPierwszejGrupy[1] + iDopasowywany);) |
|---|
| 1574 | |
|---|
| 1575 | // teraz dopasowujemy do iIndex[1] w organizmie 1 |
|---|
| 1576 | iDopasowywany = -1; |
|---|
| 1577 | // poszukujemy pierwszego z listy dopasowania - w organizmie 0 |
|---|
| 1578 | for (i = 0; i < aiRozmiarCalychGrup[0]; i++) |
|---|
| 1579 | { |
|---|
| 1580 | if (apvbCzyMinimalnaOdleglosc[1]->operator[](i)) |
|---|
| 1581 | { |
|---|
| 1582 | iDopasowywany = i; |
|---|
| 1583 | break; |
|---|
| 1584 | } |
|---|
| 1585 | } |
|---|
| 1586 | // musielismy znalezc jakiegos dopasowywanego |
|---|
| 1587 | assert((iDopasowywany >= 0) && |
|---|
| 1588 | (iDopasowywany < aiRozmiarCalychGrup[0])); |
|---|
| 1589 | |
|---|
| 1590 | // no i teraz realizujemy dopasowanie |
|---|
| 1591 | m_pMatching->Match( |
|---|
| 1592 | 0, |
|---|
| 1593 | aiKoniecPierwszejGrupy[0] + iDopasowywany, |
|---|
| 1594 | 1, |
|---|
| 1595 | aiKoniecPierwszejGrupy[1] + iIndex[1]); |
|---|
| 1596 | |
|---|
| 1597 | // zmniejszamy liczbe niedopasowanych Parts |
|---|
| 1598 | aiRozmiarGrupy[0]--; |
|---|
| 1599 | aiRozmiarGrupy[1]--; |
|---|
| 1600 | |
|---|
| 1601 | // debug - dopasowanie |
|---|
| 1602 | DB(printf("Przypadek 3.: dopasowane Parts: (%2i, %2i)\n", aiKoniecPierwszejGrupy[0] |
|---|
| 1603 | + iDopasowywany, aiKoniecPierwszejGrupy[1] + iIndex[1]);) |
|---|
| 1604 | |
|---|
| 1605 | |
|---|
| 1606 | } // PRZYPADEK 3. |
|---|
| 1607 | |
|---|
| 1608 | }// if (! bCzyKoniecGrupy) |
|---|
| 1609 | else |
|---|
| 1610 | { |
|---|
| 1611 | // gdy mamy juz koniec grup - musimy zlikwidowac tablice aadOdleglosciParts |
|---|
| 1612 | // bo za chwilke skonczy sie nam petla |
|---|
| 1613 | for (i = 0; i < aiRozmiarCalychGrup[0]; i++) |
|---|
| 1614 | { |
|---|
| 1615 | SAFEDELETEARRAY(aadOdleglosciParts[i]); |
|---|
| 1616 | } |
|---|
| 1617 | SAFEDELETEARRAY(aadOdleglosciParts); |
|---|
| 1618 | |
|---|
| 1619 | // musimy tez usunac tablice (wektory) mozliwosci dopasowania |
|---|
| 1620 | SAFEDELETE(apvbCzyMinimalnaOdleglosc[0]); |
|---|
| 1621 | SAFEDELETE(apvbCzyMinimalnaOdleglosc[1]); |
|---|
| 1622 | } |
|---|
| 1623 | } // while (! bCzyKoniecGrupy) |
|---|
| 1624 | |
|---|
| 1625 | // PO DOPASOWANIU WSZYSTKIEGO Z GRUP (CO NAJMNIEJ JEDNEJ GRUPY W CALOSCI) |
|---|
| 1626 | |
|---|
| 1627 | // gdy rozmiar ktorejkolwiek z grup dopasowania spadl do zera |
|---|
| 1628 | // to musimy przesunac KoniecPierwszejGrupy (wszystkie dopasowane) |
|---|
| 1629 | for (i = 0; i < 2; i++) |
|---|
| 1630 | { |
|---|
| 1631 | // grupy nie moga miec mniejszego niz 0 rozmiaru |
|---|
| 1632 | assert(aiRozmiarGrupy[i] >= 0); |
|---|
| 1633 | if (aiRozmiarGrupy[i] == 0) |
|---|
| 1634 | aiKoniecPierwszejGrupy[i] = aiKoniecGrupyDopasowania[i]; |
|---|
| 1635 | } |
|---|
| 1636 | |
|---|
| 1637 | // sprawdzenie warunku konca dopasowywania - gdy nie |
|---|
| 1638 | // ma juz w jakims organizmie co dopasowywac |
|---|
| 1639 | if (aiKoniecPierwszejGrupy[0] >= m_aiPartCount[0] || |
|---|
| 1640 | aiKoniecPierwszejGrupy[1] >= m_aiPartCount[1]) |
|---|
| 1641 | { |
|---|
| 1642 | iCzyDopasowane = 1; |
|---|
| 1643 | } |
|---|
| 1644 | } // koniec WHILE - petli dopasowania |
|---|
| 1645 | } |
|---|
| 1646 | |
|---|
| 1647 | /** Matches Parts in both organisms so that computation of similarity is possible. |
|---|
| 1648 | New algorithm (assures symmetry of the similarity measure) with geometry |
|---|
| 1649 | taken into consideration. |
|---|
| 1650 | Assumptions: |
|---|
| 1651 | - Models (m_Mod) are created and available. |
|---|
| 1652 | - Matching (m_pMatching) is created, but empty |
|---|
| 1653 | Exit conditions: |
|---|
| 1654 | - Matching (m_pMatching) is full |
|---|
| 1655 | @return 1 if success, 0 otherwise |
|---|
| 1656 | */ |
|---|
| 1657 | int ModelSimil::MatchPartsGeometry() |
|---|
| 1658 | { |
|---|
| 1659 | // zaloz, ze sa modele i sa poprawne |
|---|
| 1660 | assert((m_Mod[0] != NULL) && (m_Mod[1] != NULL)); |
|---|
| 1661 | assert(m_Mod[0]->isValid() && m_Mod[1]->isValid()); |
|---|
| 1662 | |
|---|
| 1663 | if (!CreatePartInfoTables()) |
|---|
| 1664 | return 0; |
|---|
| 1665 | if (!CountPartDegrees()) |
|---|
| 1666 | return 0; |
|---|
| 1667 | if (!GetPartPositions()) |
|---|
| 1668 | { |
|---|
| 1669 | return 0; |
|---|
| 1670 | } |
|---|
| 1671 | if (!CountPartNeurons()) |
|---|
| 1672 | return 0; |
|---|
| 1673 | |
|---|
| 1674 | |
|---|
| 1675 | if (m_adFactors[3] > 0) |
|---|
| 1676 | { |
|---|
| 1677 | if (!ComputePartsPositionsBySVD()) |
|---|
| 1678 | { |
|---|
| 1679 | return 0; |
|---|
| 1680 | } |
|---|
| 1681 | } |
|---|
| 1682 | |
|---|
| 1683 | DB(printf("Przed sortowaniem:\n");) |
|---|
| 1684 | DB(_PrintDegrees(0);) |
|---|
| 1685 | DB(_PrintDegrees(1);) |
|---|
| 1686 | |
|---|
| 1687 | if (!SortPartInfoTables()) |
|---|
| 1688 | return 0; |
|---|
| 1689 | |
|---|
| 1690 | DB(printf("Po sortowaniu:\n");) |
|---|
| 1691 | DB(_PrintDegrees(0);) |
|---|
| 1692 | DB(_PrintDegrees(1);) |
|---|
| 1693 | |
|---|
| 1694 | if (m_adFactors[3] > 0) |
|---|
| 1695 | { |
|---|
| 1696 | // tutaj zacznij pętlę po przekształceniach geometrycznych |
|---|
| 1697 | const int NO_OF_TRANSFORM = 8; // liczba transformacji geometrycznych (na razie tylko ID i O_YZ) |
|---|
| 1698 | // tablice transformacji współrzędnych; nie są to dokładnie tablice tranformacji, ale raczej tablice PRZEJŚĆ |
|---|
| 1699 | // pomiędzy transformacjami; |
|---|
| 1700 | // wartości orginalne transformacji dOrig uzyskuje się przez: |
|---|
| 1701 | // for ( iTrans = 0; iTrans <= TRANS_INDEX; iTrans++ ) dOrig *= dMul[ iTrans ]; |
|---|
| 1702 | //const char *szTransformNames[NO_OF_TRANSFORM] = { "ID", "S_yz", "S_xz", "S_xy", "R180_z", "R180_y", "R180_z", "S_(0,0,0)" }; |
|---|
| 1703 | const int dMulX[NO_OF_TRANSFORM] = { 1, -1, -1, 1, -1, 1, -1, -1 }; |
|---|
| 1704 | const int dMulY[NO_OF_TRANSFORM] = { 1, 1, -1, -1, -1, -1, -1, 1 }; |
|---|
| 1705 | const int dMulZ[NO_OF_TRANSFORM] = { 1, 1, 1, -1, -1, -1, 1, 1 }; |
|---|
| 1706 | |
|---|
| 1707 | #ifdef max |
|---|
| 1708 | #undef max //this macro would conflict with line below |
|---|
| 1709 | #endif |
|---|
| 1710 | double dMinSimValue = std::numeric_limits<double>::max(); // minimum value of similarity |
|---|
| 1711 | int iMinSimTransform = -1; // index of the transformation with the minimum similarity |
|---|
| 1712 | SimilMatching *pMinSimMatching = NULL; // matching with the minimum value of similarity |
|---|
| 1713 | |
|---|
| 1714 | // remember the original positions of model 0 as computed by SVD in order to restore them later, after |
|---|
| 1715 | // all transformations have been computed |
|---|
| 1716 | Pt3D *StoredPositions = NULL; // array of positions of Parts, for one (0th) model |
|---|
| 1717 | // create the stored positions |
|---|
| 1718 | StoredPositions = new Pt3D[m_Mod[0]->getPartCount()]; |
|---|
| 1719 | assert(StoredPositions != NULL); |
|---|
| 1720 | // copy the original positions of model 0 (store them) |
|---|
| 1721 | int iPart; // a counter of Parts |
|---|
| 1722 | for (iPart = 0; iPart < m_Mod[0]->getPartCount(); iPart++) |
|---|
| 1723 | { |
|---|
| 1724 | StoredPositions[iPart].x = m_aPositions[0][iPart].x; |
|---|
| 1725 | StoredPositions[iPart].y = m_aPositions[0][iPart].y; |
|---|
| 1726 | StoredPositions[iPart].z = m_aPositions[0][iPart].z; |
|---|
| 1727 | } |
|---|
| 1728 | // now the original positions of model 0 are stored |
|---|
| 1729 | |
|---|
| 1730 | |
|---|
| 1731 | int iTransform; // a counter of geometric transformations |
|---|
| 1732 | for (iTransform = 0; iTransform < NO_OF_TRANSFORM; iTransform++) |
|---|
| 1733 | { |
|---|
| 1734 | // for each geometric transformation to be done |
|---|
| 1735 | // entry conditions: |
|---|
| 1736 | // - models (m_Mod) exist and are available |
|---|
| 1737 | // - matching (m_pMatching) exists and is empty |
|---|
| 1738 | // - all properties are created and available (m_aDegrees and m_aPositions) |
|---|
| 1739 | |
|---|
| 1740 | // recompute geometric properties according to the transformation iTransform |
|---|
| 1741 | // but only for model 0 |
|---|
| 1742 | for (iPart = 0; iPart < m_Mod[0]->getPartCount(); iPart++) |
|---|
| 1743 | { |
|---|
| 1744 | // for each iPart, a part of the model iMod |
|---|
| 1745 | m_aPositions[0][iPart].x *= dMulX[iTransform]; |
|---|
| 1746 | m_aPositions[0][iPart].y *= dMulY[iTransform]; |
|---|
| 1747 | m_aPositions[0][iPart].z *= dMulZ[iTransform]; |
|---|
| 1748 | } |
|---|
| 1749 | // now the positions are recomputed |
|---|
| 1750 | ComputeMatching(); |
|---|
| 1751 | |
|---|
| 1752 | // teraz m_pMatching istnieje i jest pełne |
|---|
| 1753 | assert(m_pMatching != NULL); |
|---|
| 1754 | assert(m_pMatching->IsFull() == true); |
|---|
| 1755 | |
|---|
| 1756 | // wykorzystaj to dopasowanie i geometrię do obliczenia tymczasowej wartości miary |
|---|
| 1757 | int iTempRes = CountPartsDistance(); |
|---|
| 1758 | // załóż sukces |
|---|
| 1759 | assert(iTempRes == 1); |
|---|
| 1760 | double dCurrentSim = m_adFactors[0] * double(m_iDV) + |
|---|
| 1761 | m_adFactors[1] * double(m_iDD) + |
|---|
| 1762 | m_adFactors[2] * double(m_iDN) + |
|---|
| 1763 | m_adFactors[3] * double(m_dDG); |
|---|
| 1764 | // załóż poprawną wartość podobieństwa |
|---|
| 1765 | assert(dCurrentSim >= 0.0); |
|---|
| 1766 | |
|---|
| 1767 | // porównaj wartość obliczoną z dotychczasowym minimum |
|---|
| 1768 | if (dCurrentSim < dMinSimValue) |
|---|
| 1769 | { |
|---|
| 1770 | // jeśli uzyskano mniejszą wartość dopasowania, |
|---|
| 1771 | // to zapamiętaj to przekształcenie geometryczne i dopasowanie |
|---|
| 1772 | dMinSimValue = dCurrentSim; |
|---|
| 1773 | iMinSimTransform = iTransform; |
|---|
| 1774 | SAFEDELETE(pMinSimMatching); |
|---|
| 1775 | pMinSimMatching = new SimilMatching(*m_pMatching); |
|---|
| 1776 | assert(pMinSimMatching != NULL); |
|---|
| 1777 | } |
|---|
| 1778 | |
|---|
| 1779 | // teraz już można usunąć stare dopasowanie (dla potrzeb następnego przebiegu pętli) |
|---|
| 1780 | m_pMatching->Empty(); |
|---|
| 1781 | } // for ( iTransform ) |
|---|
| 1782 | |
|---|
| 1783 | // po pętli przywróć najlepsze dopasowanie |
|---|
| 1784 | delete m_pMatching; |
|---|
| 1785 | m_pMatching = pMinSimMatching; |
|---|
| 1786 | |
|---|
| 1787 | DB(printf("Matching has been chosen!\n");) |
|---|
| 1788 | // print the name of the chosen transformation: |
|---|
| 1789 | // printf("Chosen transformation: %s\n", szTransformNames[ iMinSimTransform ] ); |
|---|
| 1790 | |
|---|
| 1791 | // i przywróć jednocześnie pozycje Parts modelu 0 dla tego dopasowania |
|---|
| 1792 | // - najpierw przywroc Parts pozycje orginalne, po SVD |
|---|
| 1793 | for (iPart = 0; iPart < m_Mod[0]->getPartCount(); iPart++) |
|---|
| 1794 | { |
|---|
| 1795 | m_aPositions[0][iPart].x = StoredPositions[iPart].x; |
|---|
| 1796 | m_aPositions[0][iPart].y = StoredPositions[iPart].y; |
|---|
| 1797 | m_aPositions[0][iPart].z = StoredPositions[iPart].z; |
|---|
| 1798 | } |
|---|
| 1799 | // - usun teraz zapamietane pozycje Parts |
|---|
| 1800 | delete[] StoredPositions; |
|---|
| 1801 | // - a teraz oblicz na nowo wspolrzedne wlasciwego przeksztalcenia dla model 0 |
|---|
| 1802 | for (iTransform = 0; iTransform <= iMinSimTransform; iTransform++) |
|---|
| 1803 | { |
|---|
| 1804 | // for each transformation before and INCLUDING iMinTransform |
|---|
| 1805 | // do the transformation (only model 0) |
|---|
| 1806 | for (iPart = 0; iPart < m_Mod[0]->getPartCount(); iPart++) |
|---|
| 1807 | { |
|---|
| 1808 | m_aPositions[0][iPart].x *= dMulX[iTransform]; |
|---|
| 1809 | m_aPositions[0][iPart].y *= dMulY[iTransform]; |
|---|
| 1810 | m_aPositions[0][iPart].z *= dMulZ[iTransform]; |
|---|
| 1811 | } |
|---|
| 1812 | } |
|---|
| 1813 | |
|---|
| 1814 | } |
|---|
| 1815 | else |
|---|
| 1816 | { |
|---|
| 1817 | ComputeMatching(); |
|---|
| 1818 | } |
|---|
| 1819 | // teraz dopasowanie musi byc pelne - co najmniej w jednym organizmie musza byc |
|---|
| 1820 | // wszystkie elementy dopasowane |
|---|
| 1821 | assert(m_pMatching->IsFull() == true); |
|---|
| 1822 | |
|---|
| 1823 | // _PrintDegrees(0); |
|---|
| 1824 | // _PrintDegrees(1); |
|---|
| 1825 | |
|---|
| 1826 | DB(_PrintPartsMatching();) |
|---|
| 1827 | |
|---|
| 1828 | return 1; |
|---|
| 1829 | } |
|---|
| 1830 | |
|---|
| 1831 | void ModelSimil::_PrintSeamnessTable(std::vector<int> *pTable, int iCount) |
|---|
| 1832 | { |
|---|
| 1833 | int i; |
|---|
| 1834 | printf(" "); |
|---|
| 1835 | for (i = 0; i < iCount; i++) |
|---|
| 1836 | printf("%3i ", i); |
|---|
| 1837 | printf("\n "); |
|---|
| 1838 | for (i = 0; i < iCount; i++) |
|---|
| 1839 | { |
|---|
| 1840 | |
|---|
| 1841 | printf("%3i ", pTable->operator[](i)); |
|---|
| 1842 | } |
|---|
| 1843 | printf("\n"); |
|---|
| 1844 | } |
|---|
| 1845 | |
|---|
| 1846 | /** Computes elements of similarity (m_iDD, m_iDN, m_dDG) based on underlying matching. |
|---|
| 1847 | Assumptions: |
|---|
| 1848 | - Matching (m_pMatching) exists and is full. |
|---|
| 1849 | - Internal arrays m_aDegrees and m_aPositions exist and are properly filled in |
|---|
| 1850 | Exit conditions: |
|---|
| 1851 | - Elements of similarity are computed (m)iDD, m_iDN, m_dDG). |
|---|
| 1852 | @return 1 if success, otherwise 0. |
|---|
| 1853 | */ |
|---|
| 1854 | int ModelSimil::CountPartsDistance() |
|---|
| 1855 | { |
|---|
| 1856 | int i, temp; |
|---|
| 1857 | |
|---|
| 1858 | // assume existence of m_pMatching |
|---|
| 1859 | assert(m_pMatching != NULL); |
|---|
| 1860 | // musi byc pelne! |
|---|
| 1861 | assert(m_pMatching->IsFull() == true); |
|---|
| 1862 | |
|---|
| 1863 | // roznica w stopniach |
|---|
| 1864 | m_iDD = 0; |
|---|
| 1865 | // roznica w liczbie neuronów |
|---|
| 1866 | m_iDN = 0; |
|---|
| 1867 | // roznica w odleglosci dopasowanych Parts |
|---|
| 1868 | m_dDG = 0.0; |
|---|
| 1869 | |
|---|
| 1870 | int iOrgPart, iOrgMatchedPart; // orginalny indeks Part i jego dopasowanego Part |
|---|
| 1871 | int iMatchedPart; // indeks (wg sortowania) dopasowanego Part |
|---|
| 1872 | |
|---|
| 1873 | // wykorzystanie dopasowania do zliczenia m_iDD - roznicy w stopniach |
|---|
| 1874 | // i m_iDN - roznicy w liczbie neuronow |
|---|
| 1875 | // petla w wiekszej tablicy |
|---|
| 1876 | for (i = 0; i < m_aiPartCount[1 - m_iSmaller]; i++) |
|---|
| 1877 | { |
|---|
| 1878 | // dla kazdego elementu [i] z wiekszego organizmu |
|---|
| 1879 | // pobierz jego orginalny indeks w organizmie z tablicy TDN |
|---|
| 1880 | iOrgPart = m_aDegrees[1 - m_iSmaller][i][0]; |
|---|
| 1881 | if (!(m_pMatching->IsMatched(1 - m_iSmaller, i))) |
|---|
| 1882 | { |
|---|
| 1883 | // gdy nie zostal dopasowany |
|---|
| 1884 | // dodaj jego stopien do DD |
|---|
| 1885 | m_iDD += m_aDegrees[1 - m_iSmaller][i][1]; |
|---|
| 1886 | // dodaj liczbe neuronow do DN |
|---|
| 1887 | m_iDN += m_aDegrees[1 - m_iSmaller][i][3]; |
|---|
| 1888 | // i oblicz odleglosc tego Part od srodka organizmu (0,0,0) |
|---|
| 1889 | // (uzyj orginalnego indeksu) |
|---|
| 1890 | //no need to compute distane when m_dDG weight is 0 |
|---|
| 1891 | m_dDG += m_adFactors[3] == 0 ? 0 : m_aPositions[1 - m_iSmaller][iOrgPart].length(); |
|---|
| 1892 | } |
|---|
| 1893 | else |
|---|
| 1894 | { |
|---|
| 1895 | // gdy byl dopasowany |
|---|
| 1896 | // pobierz indeks (po sortowaniu) tego dopasowanego Part |
|---|
| 1897 | iMatchedPart = m_pMatching->GetMatchedIndex(1 - m_iSmaller, i); |
|---|
| 1898 | // pobierz indeks orginalny tego dopasowanego Part |
|---|
| 1899 | iOrgMatchedPart = m_aDegrees[m_iSmaller][iMatchedPart][0]; |
|---|
| 1900 | // dodaj ABS roznicy stopni do DD |
|---|
| 1901 | temp = m_aDegrees[1 - m_iSmaller][i][1] - |
|---|
| 1902 | m_aDegrees[m_iSmaller][iMatchedPart][1]; |
|---|
| 1903 | m_iDD += abs(temp); |
|---|
| 1904 | // dodaj ABS roznicy neuronow do DN |
|---|
| 1905 | temp = m_aDegrees[1 - m_iSmaller][i][3] - |
|---|
| 1906 | m_aDegrees[m_iSmaller][iMatchedPart][3]; |
|---|
| 1907 | m_iDN += abs(temp); |
|---|
| 1908 | // pobierz polozenie dopasowanego Part |
|---|
| 1909 | Pt3D MatchedPartPos(m_aPositions[m_iSmaller][iOrgMatchedPart]); |
|---|
| 1910 | // dodaj euklidesowa odleglosc Parts do sumy odleglosci |
|---|
| 1911 | //no need to compute distane when m_dDG weight is 0 |
|---|
| 1912 | m_dDG += m_adFactors[3] == 0 ? 0 : m_aPositions[1 - m_iSmaller][iOrgPart].distanceTo(MatchedPartPos); |
|---|
| 1913 | } |
|---|
| 1914 | } |
|---|
| 1915 | |
|---|
| 1916 | // obliczenie i dodanie różnicy w liczbie neuronów OnJoint... |
|---|
| 1917 | temp = m_aOnJoint[0][3] - m_aOnJoint[1][3]; |
|---|
| 1918 | m_iDN += abs(temp); |
|---|
| 1919 | DB(printf("OnJoint DN: %i\n", abs(temp));) |
|---|
| 1920 | // ... i Anywhere |
|---|
| 1921 | temp = m_aAnywhere[0][3] - m_aAnywhere[1][3]; |
|---|
| 1922 | m_iDN += abs(temp); |
|---|
| 1923 | DB(printf("Anywhere DN: %i\n", abs(temp));) |
|---|
| 1924 | |
|---|
| 1925 | return 1; |
|---|
| 1926 | } |
|---|
| 1927 | |
|---|
| 1928 | /** Computes new positions of Parts of both of organisms stored in the object. |
|---|
| 1929 | Assumptions: |
|---|
| 1930 | - models (m_Mod) are created and valid |
|---|
| 1931 | - positions (m_aPositions) are created and filled with original positions of Parts |
|---|
| 1932 | - the sorting algorithm was not yet run on the array m_aDegrees |
|---|
| 1933 | @return true if successful; false otherwise |
|---|
| 1934 | */ |
|---|
| 1935 | bool ModelSimil::ComputePartsPositionsBySVD() |
|---|
| 1936 | { |
|---|
| 1937 | bool bResult = true; // the result; assume a success |
|---|
| 1938 | |
|---|
| 1939 | // check assumptions |
|---|
| 1940 | // the models |
|---|
| 1941 | assert(m_Mod[0] != NULL && m_Mod[0]->isValid()); |
|---|
| 1942 | assert(m_Mod[1] != NULL && m_Mod[1]->isValid()); |
|---|
| 1943 | // the position arrays |
|---|
| 1944 | assert(m_aPositions[0] != NULL); |
|---|
| 1945 | assert(m_aPositions[1] != NULL); |
|---|
| 1946 | |
|---|
| 1947 | int iMod; // a counter of models |
|---|
| 1948 | // use SVD to obtain different point of view on organisms |
|---|
| 1949 | // and store the new positions (currently the original ones are still stored) |
|---|
| 1950 | for (iMod = 0; iMod < 2; iMod++) |
|---|
| 1951 | { |
|---|
| 1952 | // prepare the vector of errors of approximation for the SVD |
|---|
| 1953 | std::vector<double> vEigenvalues; |
|---|
| 1954 | int nSize = m_Mod[iMod]->getPartCount(); |
|---|
| 1955 | |
|---|
| 1956 | double *pDistances = new double[nSize * nSize]; |
|---|
| 1957 | |
|---|
| 1958 | for (int i = 0; i < nSize; i++) |
|---|
| 1959 | { |
|---|
| 1960 | pDistances[i] = 0; |
|---|
| 1961 | } |
|---|
| 1962 | |
|---|
| 1963 | Model *pModel = m_Mod[iMod]; // use the model of the iMod (current) organism |
|---|
| 1964 | int iP1, iP2; // indices of Parts in the model |
|---|
| 1965 | Part *P1, *P2; // pointers to Parts |
|---|
| 1966 | Pt3D P1Pos, P2Pos; // positions of parts |
|---|
| 1967 | double dDistance; // the distance between Parts |
|---|
| 1968 | |
|---|
| 1969 | double *weights = new double[nSize]; |
|---|
| 1970 | for (int i = 0; i < nSize; i++) |
|---|
| 1971 | { |
|---|
| 1972 | if (wMDS == 1) |
|---|
| 1973 | weights[i] = 0; |
|---|
| 1974 | else |
|---|
| 1975 | weights[i] = 1; |
|---|
| 1976 | } |
|---|
| 1977 | |
|---|
| 1978 | if (wMDS == 1) |
|---|
| 1979 | for (int i = 0; i < pModel->getJointCount(); i++) |
|---|
| 1980 | { |
|---|
| 1981 | weights[pModel->getJoint(i)->p1_refno]++; |
|---|
| 1982 | weights[pModel->getJoint(i)->p2_refno]++; |
|---|
| 1983 | } |
|---|
| 1984 | |
|---|
| 1985 | for (iP1 = 0; iP1 < pModel->getPartCount(); iP1++) |
|---|
| 1986 | { |
|---|
| 1987 | // for each iP1, a Part index in the model of organism iMod |
|---|
| 1988 | P1 = pModel->getPart(iP1); |
|---|
| 1989 | // get the position of the Part |
|---|
| 1990 | P1Pos = P1->p; |
|---|
| 1991 | if (fixedZaxis == 1) |
|---|
| 1992 | { |
|---|
| 1993 | P1Pos.z = 0; //fixed vertical axis, so pretend all points are on the xy plane |
|---|
| 1994 | } |
|---|
| 1995 | for (iP2 = 0; iP2 < pModel->getPartCount(); iP2++) |
|---|
| 1996 | { |
|---|
| 1997 | // for each (iP1, iP2), a pair of Parts index in the model |
|---|
| 1998 | P2 = pModel->getPart(iP2); |
|---|
| 1999 | // get the position of the Part |
|---|
| 2000 | P2Pos = P2->p; |
|---|
| 2001 | if (fixedZaxis == 1) |
|---|
| 2002 | { |
|---|
| 2003 | P2Pos.z = 0; //fixed vertical axis, so pretend all points are on the xy plane |
|---|
| 2004 | } |
|---|
| 2005 | // compute the geometric (Euclidean) distance between the Parts |
|---|
| 2006 | dDistance = P1Pos.distanceTo(P2Pos); |
|---|
| 2007 | // store the distance |
|---|
| 2008 | pDistances[iP1 * nSize + iP2] = dDistance; |
|---|
| 2009 | } // for (iP2) |
|---|
| 2010 | } // for (iP1) |
|---|
| 2011 | |
|---|
| 2012 | MatrixTools::weightedMDS(vEigenvalues, nSize, pDistances, m_aPositions[iMod], weights); |
|---|
| 2013 | if (fixedZaxis == 1) //restore the original vertical coordinate of each Part |
|---|
| 2014 | { |
|---|
| 2015 | for (int part = 0; part < pModel->getPartCount(); part++) |
|---|
| 2016 | { |
|---|
| 2017 | m_aPositions[iMod][part].z = pModel->getPart(part)->p.z; |
|---|
| 2018 | } |
|---|
| 2019 | } |
|---|
| 2020 | |
|---|
| 2021 | delete[] pDistances; |
|---|
| 2022 | delete[] weights; |
|---|
| 2023 | } |
|---|
| 2024 | |
|---|
| 2025 | return bResult; |
|---|
| 2026 | } |
|---|
| 2027 | |
|---|
| 2028 | /** Evaluates distance between two given genotypes. The distance depends strongly |
|---|
| 2029 | on weights set and the matching algorithm used. |
|---|
| 2030 | @param G0 Pointer to the first of compared genotypes |
|---|
| 2031 | @param G1 Pointer to the second of compared genotypes. |
|---|
| 2032 | @return Distance between two genotypes. |
|---|
| 2033 | @sa m_adFactors, matching_method |
|---|
| 2034 | */ |
|---|
| 2035 | double ModelSimil::EvaluateDistance(const Geno *G0, const Geno *G1) |
|---|
| 2036 | { |
|---|
| 2037 | return matching_method == 0 ? EvaluateDistanceHungarian(G0, G1) : EvaluateDistanceGreedy(G0, G1); |
|---|
| 2038 | } |
|---|
| 2039 | |
|---|
| 2040 | void ModelSimil::p_evaldistance(ExtValue *args, ExtValue *ret) |
|---|
| 2041 | { |
|---|
| 2042 | Geno *g1 = GenoObj::fromObject(args[1]); |
|---|
| 2043 | Geno *g2 = GenoObj::fromObject(args[0]); |
|---|
| 2044 | if ((!g1) || (!g2)) |
|---|
| 2045 | ret->setEmpty(); |
|---|
| 2046 | else |
|---|
| 2047 | ret->setDouble(EvaluateDistance(g1, g2)); |
|---|
| 2048 | } |
|---|
| 2049 | |
|---|
| 2050 | void ModelSimil::FillPartsDistances(double*& dist, int bigger, int smaller, bool geo) |
|---|
| 2051 | { |
|---|
| 2052 | for (int i = 0; i < bigger; i++) |
|---|
| 2053 | { |
|---|
| 2054 | for (int j = 0; j < bigger; j++) |
|---|
| 2055 | { |
|---|
| 2056 | // assign penalty for unassignment for vertex from bigger model |
|---|
| 2057 | if (j >= smaller) |
|---|
| 2058 | { |
|---|
| 2059 | if (geo) |
|---|
| 2060 | dist[i * bigger + j] += m_adFactors[3] * m_aPositions[1 - m_iSmaller][i].length(); |
|---|
| 2061 | else |
|---|
| 2062 | dist[i * bigger + j] = m_adFactors[1] * m_aDegrees[1 - m_iSmaller][i][DEGREE] + m_adFactors[2] * m_aDegrees[1 - m_iSmaller][i][NEURONS]; |
|---|
| 2063 | } |
|---|
| 2064 | // compute distance between parts |
|---|
| 2065 | else |
|---|
| 2066 | { |
|---|
| 2067 | if (geo) |
|---|
| 2068 | dist[i * bigger + j] += m_adFactors[3] * m_aPositions[1 - m_iSmaller][i].distanceTo(m_aPositions[m_iSmaller][j]); |
|---|
| 2069 | else |
|---|
| 2070 | dist[i * bigger + j] = m_adFactors[1] * abs(m_aDegrees[1 - m_iSmaller][i][DEGREE] - m_aDegrees[m_iSmaller][j][DEGREE]) |
|---|
| 2071 | + m_adFactors[2] * abs(m_aDegrees[1 - m_iSmaller][i][NEURONS] - m_aDegrees[m_iSmaller][j][NEURONS]); |
|---|
| 2072 | } |
|---|
| 2073 | |
|---|
| 2074 | } |
|---|
| 2075 | } |
|---|
| 2076 | } |
|---|
| 2077 | |
|---|
| 2078 | double ModelSimil::EvaluateDistanceHungarian(const Geno *G0, const Geno *G1) |
|---|
| 2079 | { |
|---|
| 2080 | double dResult = 0.0; |
|---|
| 2081 | |
|---|
| 2082 | m_Gen[0] = G0; |
|---|
| 2083 | m_Gen[1] = G1; |
|---|
| 2084 | |
|---|
| 2085 | // create models of objects to compare |
|---|
| 2086 | m_Mod[0] = newModel(m_Gen[0]); |
|---|
| 2087 | m_Mod[1] = newModel(m_Gen[1]); |
|---|
| 2088 | |
|---|
| 2089 | if (m_Mod[0] == NULL || m_Mod[1] == NULL) |
|---|
| 2090 | return 0.0; |
|---|
| 2091 | |
|---|
| 2092 | //Get information about vertex degrees, neurons and 3D location |
|---|
| 2093 | if (!CreatePartInfoTables()) |
|---|
| 2094 | return 0.0; |
|---|
| 2095 | if (!CountPartDegrees()) |
|---|
| 2096 | return 0.0; |
|---|
| 2097 | if (!GetPartPositions()) |
|---|
| 2098 | return 0.0; |
|---|
| 2099 | if (!CountPartNeurons()) |
|---|
| 2100 | return 0.0; |
|---|
| 2101 | |
|---|
| 2102 | m_iSmaller = m_Mod[0]->getPartCount() <= m_Mod[1]->getPartCount() ? 0 : 1; |
|---|
| 2103 | int nSmaller = m_Mod[m_iSmaller]->getPartCount(); |
|---|
| 2104 | int nBigger = m_Mod[1 - m_iSmaller]->getPartCount(); |
|---|
| 2105 | |
|---|
| 2106 | double* partsDistances = new double[nBigger * nBigger](); |
|---|
| 2107 | FillPartsDistances(partsDistances, nBigger, nSmaller, false); |
|---|
| 2108 | int *assignment = new int[nBigger](); |
|---|
| 2109 | |
|---|
| 2110 | HungarianAlgorithm hungarian; |
|---|
| 2111 | |
|---|
| 2112 | if (m_adFactors[3] > 0) |
|---|
| 2113 | { |
|---|
| 2114 | if (!ComputePartsPositionsBySVD()) |
|---|
| 2115 | { |
|---|
| 2116 | return 0.0; |
|---|
| 2117 | } |
|---|
| 2118 | |
|---|
| 2119 | // tutaj zacznij pętlę po przekształceniach geometrycznych |
|---|
| 2120 | const int NO_OF_TRANSFORM = 8; // liczba transformacji geometrycznych (na razie tylko ID i O_YZ) |
|---|
| 2121 | // tablice transformacji współrzędnych; nie są to dokładnie tablice tranformacji, ale raczej tablice PRZEJŚĆ |
|---|
| 2122 | // pomiędzy transformacjami; |
|---|
| 2123 | const int dMulX[NO_OF_TRANSFORM] = { 1, -1, -1, 1, -1, 1, -1, -1 }; |
|---|
| 2124 | const int dMulY[NO_OF_TRANSFORM] = { 1, 1, -1, -1, -1, -1, -1, 1 }; |
|---|
| 2125 | const int dMulZ[NO_OF_TRANSFORM] = { 1, 1, 1, -1, -1, -1, 1, 1 }; |
|---|
| 2126 | |
|---|
| 2127 | std::vector<int> minAssignment(nBigger); |
|---|
| 2128 | #ifdef max |
|---|
| 2129 | #undef max //this macro would conflict with line below |
|---|
| 2130 | #endif |
|---|
| 2131 | double dMinSimValue = std::numeric_limits<double>::max(); // minimum value of similarity |
|---|
| 2132 | |
|---|
| 2133 | int iTransform; // a counter of geometric transformations |
|---|
| 2134 | for (iTransform = 0; iTransform < NO_OF_TRANSFORM; iTransform++) |
|---|
| 2135 | { |
|---|
| 2136 | // for each geometric transformation to be done |
|---|
| 2137 | // entry conditions: |
|---|
| 2138 | // - models (m_Mod) exist and are available |
|---|
| 2139 | // - all properties are created and available (m_aDegrees and m_aPositions) |
|---|
| 2140 | double* tmpPartsDistances = new double[nBigger * nBigger](); |
|---|
| 2141 | std::copy(partsDistances, partsDistances + nBigger * nBigger, tmpPartsDistances); |
|---|
| 2142 | // recompute geometric properties according to the transformation iTransform |
|---|
| 2143 | // but only for model 0 |
|---|
| 2144 | for (int iPart = 0; iPart < m_Mod[m_iSmaller]->getPartCount(); iPart++) |
|---|
| 2145 | { |
|---|
| 2146 | // for each iPart, a part of the model iMod |
|---|
| 2147 | m_aPositions[m_iSmaller][iPart].x *= dMulX[iTransform]; |
|---|
| 2148 | m_aPositions[m_iSmaller][iPart].y *= dMulY[iTransform]; |
|---|
| 2149 | m_aPositions[m_iSmaller][iPart].z *= dMulZ[iTransform]; |
|---|
| 2150 | } |
|---|
| 2151 | // now the positions are recomputed |
|---|
| 2152 | |
|---|
| 2153 | FillPartsDistances(tmpPartsDistances, nBigger, nSmaller, true); |
|---|
| 2154 | std::fill_n(assignment, nBigger, 0); |
|---|
| 2155 | double dCurrentSim = hungarian.Solve(tmpPartsDistances, assignment, nBigger, nBigger); |
|---|
| 2156 | |
|---|
| 2157 | delete[] tmpPartsDistances; |
|---|
| 2158 | // załóż poprawną wartość podobieństwa |
|---|
| 2159 | assert(dCurrentSim >= 0.0); |
|---|
| 2160 | |
|---|
| 2161 | // porównaj wartość obliczoną z dotychczasowym minimum |
|---|
| 2162 | if (dCurrentSim < dMinSimValue) |
|---|
| 2163 | { |
|---|
| 2164 | dMinSimValue = dCurrentSim; |
|---|
| 2165 | if (saveMatching) |
|---|
| 2166 | { |
|---|
| 2167 | minAssignment.clear(); |
|---|
| 2168 | minAssignment.insert(minAssignment.begin(), assignment, assignment + nBigger); |
|---|
| 2169 | } |
|---|
| 2170 | } |
|---|
| 2171 | } |
|---|
| 2172 | |
|---|
| 2173 | dResult = dMinSimValue; |
|---|
| 2174 | if (saveMatching) |
|---|
| 2175 | std::copy(minAssignment.begin(), minAssignment.end(), assignment); |
|---|
| 2176 | } |
|---|
| 2177 | else |
|---|
| 2178 | { |
|---|
| 2179 | dResult = hungarian.Solve(partsDistances, assignment, nBigger, nBigger); |
|---|
| 2180 | } |
|---|
| 2181 | |
|---|
| 2182 | //add difference in anywhere and onJoint neurons |
|---|
| 2183 | dResult += m_adFactors[2] * (abs(m_aOnJoint[0][3] - m_aOnJoint[1][3]) + abs(m_aAnywhere[0][3] - m_aAnywhere[1][3])); |
|---|
| 2184 | //add difference in part numbers |
|---|
| 2185 | dResult += (nBigger - nSmaller) * m_adFactors[0]; |
|---|
| 2186 | |
|---|
| 2187 | // delete degree arrays created in CreatePartInfoTables |
|---|
| 2188 | SAFEDELETEARRAY(m_aDegrees[0]); |
|---|
| 2189 | SAFEDELETEARRAY(m_aDegrees[1]); |
|---|
| 2190 | |
|---|
| 2191 | // and position arrays |
|---|
| 2192 | SAFEDELETEARRAY(m_aPositions[0]); |
|---|
| 2193 | SAFEDELETEARRAY(m_aPositions[1]); |
|---|
| 2194 | |
|---|
| 2195 | // delete created models |
|---|
| 2196 | SAFEDELETE(m_Mod[0]); |
|---|
| 2197 | SAFEDELETE(m_Mod[1]); |
|---|
| 2198 | |
|---|
| 2199 | delete[] assignment; |
|---|
| 2200 | delete[] partsDistances; |
|---|
| 2201 | |
|---|
| 2202 | return dResult; |
|---|
| 2203 | } |
|---|
