1 | // -*- c++ -*- |
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2 | #include <iostream> |
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3 | #include <fstream> |
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4 | #include <vector> |
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5 | #include <cstdlib> |
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6 | |
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7 | #include <LEDA/graph.h> |
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8 | #include <LEDA/mcb_matching.h> |
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9 | #include <LEDA/list.h> |
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10 | #include <LEDA/graph_gen.h> |
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11 | |
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12 | #include <leda_graph_wrapper.h> |
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13 | #include <sage_graph.h> |
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14 | //#include <smart_graph.h> |
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15 | //#include <dimacs.h> |
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16 | #include <hugo/time_measure.h> |
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17 | #include <hugo/for_each_macros.h> |
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18 | #include <hugo/graph_wrapper.h> |
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19 | #include <bipartite_graph_wrapper.h> |
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20 | #include <hugo/maps.h> |
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21 | #include <max_flow.h> |
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22 | |
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23 | /** |
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24 | * Inicializalja a veletlenszamgeneratort. |
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25 | * Figyelem, ez nem jo igazi random szamokhoz, |
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26 | * erre ne bizzad a titkaidat! |
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27 | */ |
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28 | void random_init() |
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29 | { |
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30 | unsigned int seed = getpid(); |
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31 | seed |= seed << 15; |
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32 | seed ^= time(0); |
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33 | |
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34 | srand(seed); |
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35 | } |
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36 | |
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37 | /** |
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38 | * Egy veletlen int-et ad vissza 0 es m-1 kozott. |
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39 | */ |
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40 | int random(int m) |
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41 | { |
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42 | return int( double(m) * rand() / (RAND_MAX + 1.0) ); |
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43 | } |
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44 | |
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45 | using namespace hugo; |
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46 | |
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47 | int main() { |
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48 | //for leda graph |
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49 | leda::graph lg; |
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50 | //lg.make_undirected(); |
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51 | typedef LedaGraphWrapper<leda::graph> Graph; |
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52 | Graph g(lg); |
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53 | |
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54 | //for UndirSageGraph |
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55 | //typedef UndirSageGraph Graph; |
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56 | //Graph g; |
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57 | |
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58 | typedef Graph::Node Node; |
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59 | typedef Graph::NodeIt NodeIt; |
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60 | typedef Graph::Edge Edge; |
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61 | typedef Graph::EdgeIt EdgeIt; |
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62 | typedef Graph::OutEdgeIt OutEdgeIt; |
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63 | |
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64 | std::vector<Graph::Node> s_nodes; |
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65 | std::vector<Graph::Node> t_nodes; |
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66 | |
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67 | int a; |
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68 | std::cout << "number of nodes in the first color class="; |
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69 | std::cin >> a; |
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70 | int b; |
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71 | std::cout << "number of nodes in the second color class="; |
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72 | std::cin >> b; |
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73 | int m; |
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74 | std::cout << "number of edges="; |
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75 | std::cin >> m; |
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76 | int k; |
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77 | std::cout << "A bipartite graph is a random group graph if the color classes \nA and B are partitiones to A_0, A_1, ..., A_{k-1} and B_0, B_1, ..., B_{k-1} \nas equally as possible \nand the edges from A_i goes to A_{i-1 mod k} and A_{i+1 mod k}.\n"; |
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78 | std::cout << "number of groups in LEDA random group graph="; |
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79 | std::cin >> k; |
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80 | std::cout << std::endl; |
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81 | |
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82 | leda_list<leda_node> lS; |
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83 | leda_list<leda_node> lT; |
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84 | random_bigraph(lg, a, b, m, lS, lT, k); |
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85 | |
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86 | Graph::NodeMap<int> ref_map(g, -1); |
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87 | IterableBoolMap< Graph::NodeMap<int> > bipartite_map(ref_map); |
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88 | |
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89 | //generating leda random group graph |
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90 | leda_node ln; |
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91 | forall(ln, lS) bipartite_map.insert(ln, false); |
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92 | forall(ln, lT) bipartite_map.insert(ln, true); |
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93 | |
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94 | //making bipartite graph |
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95 | typedef BipartiteGraphWrapper<Graph> BGW; |
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96 | BGW bgw(g, bipartite_map); |
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97 | |
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98 | |
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99 | //st-wrapper |
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100 | typedef stGraphWrapper<BGW> stGW; |
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101 | stGW stgw(bgw); |
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102 | ConstMap<stGW::Edge, int> const1map(1); |
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103 | stGW::EdgeMap<int> flow(stgw); |
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104 | |
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105 | Timer ts; |
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106 | |
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107 | ts.reset(); |
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108 | FOR_EACH_LOC(stGW::EdgeIt, e, stgw) flow.set(e, 0); |
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109 | MaxFlow<stGW, int, ConstMap<stGW::Edge, int>, stGW::EdgeMap<int> > |
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110 | max_flow_test(stgw, stgw.S_NODE, stgw.T_NODE, const1map, flow/*, true*/); |
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111 | max_flow_test.run(); |
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112 | std::cout << "HUGO max matching algorithm based on preflow." << std::endl |
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113 | << "Size of matching: " |
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114 | << max_flow_test.flowValue() << std::endl; |
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115 | std::cout << "elapsed time: " << ts << std::endl << std::endl; |
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116 | |
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117 | ts.reset(); |
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118 | leda_list<leda_edge> ml=MAX_CARD_BIPARTITE_MATCHING(lg); |
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119 | std::cout << "LEDA max matching algorithm." << std::endl |
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120 | << "Size of matching: " |
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121 | << ml.size() << std::endl; |
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122 | std::cout << "elapsed time: " << ts << std::endl; |
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123 | std::cout << "\n"; |
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124 | |
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125 | ts.reset(); |
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126 | FOR_EACH_LOC(stGW::EdgeIt, e, stgw) flow.set(e, 0); |
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127 | typedef SageGraph MutableGraph; |
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128 | while (max_flow_test.augmentOnBlockingFlow<MutableGraph>()) { } |
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129 | std::cout << "HUGO max matching algorithm based on blocking flow augmentation." |
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130 | << std::endl << "Matching size: " |
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131 | << max_flow_test.flowValue() << std::endl; |
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132 | std::cout << "elapsed time: " << ts << std::endl; |
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133 | |
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134 | return 0; |
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135 | } |
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