1 | // Copyright David Abrahams 2002. |
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2 | // Distributed under the Boost Software License, Version 1.0. (See |
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3 | // accompanying file LICENSE_1_0.txt or copy at |
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4 | // http://www.boost.org/LICENSE_1_0.txt) |
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5 | #include <boost/python/object/inheritance.hpp> |
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6 | #include <boost/python/type_id.hpp> |
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7 | #include <boost/graph/breadth_first_search.hpp> |
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8 | #if _MSC_FULL_VER >= 13102171 && _MSC_FULL_VER <= 13102179 |
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9 | # include <boost/graph/reverse_graph.hpp> |
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10 | #endif |
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11 | #include <boost/graph/adjacency_list.hpp> |
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12 | #include <boost/graph/reverse_graph.hpp> |
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13 | #include <boost/property_map.hpp> |
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14 | #include <boost/bind.hpp> |
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15 | #include <boost/integer_traits.hpp> |
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16 | #include <boost/tuple/tuple.hpp> |
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17 | #include <boost/tuple/tuple_comparison.hpp> |
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18 | #include <queue> |
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19 | #include <vector> |
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20 | #include <functional> |
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21 | |
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22 | // |
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23 | // Procedure: |
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24 | // |
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25 | // The search is a BFS over the space of (type,address) pairs |
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26 | // guided by the edges of the casting graph whose nodes |
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27 | // correspond to classes, and whose edges are traversed by |
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28 | // applying associated cast functions to an address. We use |
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29 | // vertex distance to the goal node in the cast_graph to rate the |
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30 | // paths. The vertex distance to any goal node is calculated on |
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31 | // demand and outdated by the addition of edges to the graph. |
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32 | |
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33 | namespace boost { |
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34 | namespace |
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35 | { |
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36 | enum edge_cast_t { edge_cast = 8010 }; |
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37 | template <class T> inline void unused_variable(const T&) { } |
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38 | } |
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39 | |
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40 | // Install properties |
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41 | BOOST_INSTALL_PROPERTY(edge, cast); |
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42 | |
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43 | namespace |
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44 | { |
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45 | typedef void*(*cast_function)(void*); |
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46 | |
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47 | // |
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48 | // Here we put together the low-level data structures of the |
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49 | // casting graph representation. |
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50 | // |
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51 | typedef python::type_info class_id; |
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52 | |
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53 | // represents a graph of available casts |
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54 | |
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55 | #if 0 |
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56 | struct cast_graph |
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57 | : |
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58 | #else |
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59 | typedef |
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60 | #endif |
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61 | adjacency_list<vecS,vecS, bidirectionalS, no_property |
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62 | |
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63 | // edge index property allows us to look up edges in the connectivity matrix |
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64 | , property<edge_index_t,std::size_t |
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65 | |
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66 | // The function which casts a void* from the edge's source type |
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67 | // to its destination type. |
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68 | , property<edge_cast_t,cast_function> > > |
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69 | #if 0 |
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70 | {}; |
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71 | #else |
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72 | cast_graph; |
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73 | #endif |
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74 | |
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75 | typedef cast_graph::vertex_descriptor vertex_t; |
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76 | typedef cast_graph::edge_descriptor edge_t; |
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77 | |
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78 | struct smart_graph |
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79 | { |
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80 | typedef std::vector<std::size_t>::const_iterator node_distance_map; |
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81 | |
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82 | typedef std::pair<cast_graph::out_edge_iterator |
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83 | , cast_graph::out_edge_iterator> out_edges_t; |
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84 | |
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85 | // Return a map of the distances from any node to the given |
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86 | // target node |
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87 | node_distance_map distances_to(vertex_t target) const |
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88 | { |
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89 | std::size_t n = num_vertices(m_topology); |
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90 | if (m_distances.size() != n * n) |
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91 | { |
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92 | m_distances.clear(); |
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93 | m_distances.resize(n * n, (std::numeric_limits<std::size_t>::max)()); |
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94 | m_known_vertices = n; |
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95 | } |
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96 | |
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97 | std::vector<std::size_t>::iterator to_target = m_distances.begin() + n * target; |
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98 | |
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99 | // this node hasn't been used as a target yet |
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100 | if (to_target[target] != 0) |
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101 | { |
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102 | typedef reverse_graph<cast_graph> reverse_cast_graph; |
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103 | reverse_cast_graph reverse_topology(m_topology); |
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104 | |
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105 | to_target[target] = 0; |
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106 | |
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107 | breadth_first_search( |
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108 | reverse_topology, target |
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109 | , visitor( |
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110 | make_bfs_visitor( |
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111 | record_distances( |
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112 | make_iterator_property_map( |
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113 | to_target |
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114 | , get(vertex_index, reverse_topology) |
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115 | # ifdef BOOST_NO_STD_ITERATOR_TRAITS |
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116 | , *to_target |
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117 | # endif |
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118 | ) |
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119 | , on_tree_edge() |
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120 | )))); |
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121 | } |
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122 | |
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123 | return to_target; |
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124 | } |
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125 | |
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126 | cast_graph& topology() { return m_topology; } |
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127 | cast_graph const& topology() const { return m_topology; } |
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128 | |
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129 | smart_graph() |
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130 | : m_known_vertices(0) |
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131 | {} |
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132 | |
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133 | private: |
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134 | cast_graph m_topology; |
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135 | mutable std::vector<std::size_t> m_distances; |
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136 | mutable std::size_t m_known_vertices; |
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137 | }; |
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138 | |
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139 | smart_graph& full_graph() |
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140 | { |
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141 | static smart_graph x; |
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142 | return x; |
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143 | } |
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144 | |
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145 | smart_graph& up_graph() |
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146 | { |
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147 | static smart_graph x; |
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148 | return x; |
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149 | } |
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150 | |
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151 | // |
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152 | // Our index of class types |
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153 | // |
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154 | using boost::python::objects::dynamic_id_function; |
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155 | typedef tuples::tuple< |
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156 | class_id // static type |
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157 | , vertex_t // corresponding vertex |
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158 | , dynamic_id_function // dynamic_id if polymorphic, or 0 |
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159 | > |
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160 | index_entry_interface; |
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161 | typedef index_entry_interface::inherited index_entry; |
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162 | enum { ksrc_static_t, kvertex, kdynamic_id }; |
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163 | |
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164 | typedef std::vector<index_entry> type_index_t; |
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165 | |
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166 | |
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167 | type_index_t& type_index() |
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168 | { |
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169 | static type_index_t x; |
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170 | return x; |
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171 | } |
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172 | |
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173 | template <class Tuple> |
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174 | struct select1st |
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175 | { |
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176 | typedef typename tuples::element<0, Tuple>::type result_type; |
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177 | |
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178 | result_type const& operator()(Tuple const& x) const |
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179 | { |
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180 | return tuples::get<0>(x); |
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181 | } |
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182 | }; |
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183 | |
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184 | // map a type to a position in the index |
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185 | inline type_index_t::iterator type_position(class_id type) |
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186 | { |
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187 | typedef index_entry entry; |
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188 | |
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189 | return std::lower_bound( |
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190 | type_index().begin(), type_index().end() |
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191 | , boost::make_tuple(type, vertex_t(), dynamic_id_function(0)) |
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192 | , boost::bind<bool>(std::less<class_id>() |
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193 | , boost::bind<class_id>(select1st<entry>(), _1) |
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194 | , boost::bind<class_id>(select1st<entry>(), _2))); |
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195 | } |
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196 | |
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197 | inline index_entry* seek_type(class_id type) |
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198 | { |
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199 | type_index_t::iterator p = type_position(type); |
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200 | if (p == type_index().end() || tuples::get<ksrc_static_t>(*p) != type) |
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201 | return 0; |
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202 | else |
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203 | return &*p; |
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204 | } |
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205 | |
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206 | // Get the entry for a type, inserting if necessary |
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207 | inline type_index_t::iterator demand_type(class_id type) |
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208 | { |
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209 | type_index_t::iterator p = type_position(type); |
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210 | |
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211 | if (p != type_index().end() && tuples::get<ksrc_static_t>(*p) == type) |
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212 | return p; |
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213 | |
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214 | vertex_t v = add_vertex(full_graph().topology()); |
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215 | vertex_t v2 = add_vertex(up_graph().topology()); |
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216 | unused_variable(v2); |
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217 | assert(v == v2); |
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218 | return type_index().insert(p, boost::make_tuple(type, v, dynamic_id_function(0))); |
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219 | } |
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220 | |
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221 | // Map a two types to a vertex in the graph, inserting if necessary |
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222 | typedef std::pair<type_index_t::iterator, type_index_t::iterator> |
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223 | type_index_iterator_pair; |
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224 | |
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225 | inline type_index_iterator_pair |
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226 | demand_types(class_id t1, class_id t2) |
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227 | { |
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228 | // be sure there will be no reallocation |
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229 | type_index().reserve(type_index().size() + 2); |
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230 | type_index_t::iterator first = demand_type(t1); |
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231 | type_index_t::iterator second = demand_type(t2); |
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232 | if (first == second) |
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233 | ++first; |
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234 | return std::make_pair(first, second); |
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235 | } |
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236 | |
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237 | struct q_elt |
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238 | { |
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239 | q_elt(std::size_t distance |
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240 | , void* src_address |
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241 | , vertex_t target |
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242 | , cast_function cast |
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243 | ) |
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244 | : distance(distance) |
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245 | , src_address(src_address) |
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246 | , target(target) |
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247 | , cast(cast) |
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248 | {} |
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249 | |
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250 | std::size_t distance; |
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251 | void* src_address; |
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252 | vertex_t target; |
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253 | cast_function cast; |
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254 | |
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255 | bool operator<(q_elt const& rhs) const |
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256 | { |
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257 | return distance < rhs.distance; |
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258 | } |
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259 | }; |
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260 | |
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261 | // Optimization: |
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262 | // |
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263 | // Given p, src_t, dst_t |
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264 | // |
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265 | // Get a pointer pd to the most-derived object |
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266 | // if it's polymorphic, dynamic_cast to void* |
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267 | // otherwise pd = p |
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268 | // |
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269 | // Get the most-derived typeid src_td |
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270 | // |
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271 | // ptrdiff_t offset = p - pd |
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272 | // |
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273 | // Now we can keep a cache, for [src_t, offset, src_td, dst_t] of |
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274 | // the cast transformation function to use on p and the next src_t |
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275 | // in the chain. src_td, dst_t don't change throughout this |
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276 | // process. In order to represent unreachability, when a pair is |
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277 | // found to be unreachable, we stick a 0-returning "dead-cast" |
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278 | // function in the cache. |
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279 | |
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280 | // This is needed in a few places below |
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281 | inline void* identity_cast(void* p) |
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282 | { |
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283 | return p; |
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284 | } |
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285 | |
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286 | void* search(smart_graph const& g, void* p, vertex_t src, vertex_t dst) |
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287 | { |
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288 | // I think this test was thoroughly bogus -- dwa |
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289 | // If we know there's no path; bail now. |
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290 | // if (src > g.known_vertices() || dst > g.known_vertices()) |
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291 | // return 0; |
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292 | |
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293 | smart_graph::node_distance_map d(g.distances_to(dst)); |
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294 | |
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295 | if (d[src] == (std::numeric_limits<std::size_t>::max)()) |
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296 | return 0; |
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297 | |
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298 | typedef property_map<cast_graph,edge_cast_t>::const_type cast_map; |
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299 | cast_map casts = get(edge_cast, g.topology()); |
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300 | |
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301 | typedef std::pair<vertex_t,void*> search_state; |
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302 | typedef std::vector<search_state> visited_t; |
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303 | visited_t visited; |
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304 | std::priority_queue<q_elt> q; |
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305 | |
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306 | q.push(q_elt(d[src], p, src, identity_cast)); |
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307 | while (!q.empty()) |
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308 | { |
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309 | q_elt top = q.top(); |
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310 | q.pop(); |
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311 | |
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312 | // Check to see if we have a real state |
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313 | void* dst_address = top.cast(top.src_address); |
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314 | if (dst_address == 0) |
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315 | continue; |
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316 | |
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317 | if (top.target == dst) |
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318 | return dst_address; |
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319 | |
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320 | search_state s(top.target,dst_address); |
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321 | |
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322 | visited_t::iterator pos = std::lower_bound( |
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323 | visited.begin(), visited.end(), s); |
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324 | |
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325 | // If already visited, continue |
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326 | if (pos != visited.end() && *pos == s) |
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327 | continue; |
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328 | |
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329 | visited.insert(pos, s); // mark it |
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330 | |
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331 | // expand it: |
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332 | smart_graph::out_edges_t edges = out_edges(s.first, g.topology()); |
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333 | for (cast_graph::out_edge_iterator p = edges.first |
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334 | , finish = edges.second |
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335 | ; p != finish |
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336 | ; ++p |
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337 | ) |
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338 | { |
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339 | edge_t e = *p; |
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340 | q.push(q_elt( |
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341 | d[target(e, g.topology())] |
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342 | , dst_address |
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343 | , target(e, g.topology()) |
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344 | , boost::get(casts, e))); |
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345 | } |
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346 | } |
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347 | return 0; |
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348 | } |
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349 | |
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350 | struct cache_element |
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351 | { |
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352 | typedef tuples::tuple< |
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353 | class_id // source static type |
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354 | , class_id // target type |
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355 | , std::ptrdiff_t // offset within source object |
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356 | , class_id // source dynamic type |
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357 | >::inherited key_type; |
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358 | |
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359 | cache_element(key_type const& k) |
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360 | : key(k) |
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361 | , offset(0) |
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362 | {} |
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363 | |
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364 | key_type key; |
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365 | std::ptrdiff_t offset; |
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366 | |
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367 | BOOST_STATIC_CONSTANT( |
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368 | std::ptrdiff_t, not_found = integer_traits<std::ptrdiff_t>::const_min); |
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369 | |
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370 | bool operator<(cache_element const& rhs) const |
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371 | { |
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372 | return this->key < rhs.key; |
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373 | } |
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374 | |
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375 | bool unreachable() const |
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376 | { |
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377 | return offset == not_found; |
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378 | } |
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379 | }; |
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380 | |
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381 | enum { kdst_t = ksrc_static_t + 1, koffset, ksrc_dynamic_t }; |
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382 | typedef std::vector<cache_element> cache_t; |
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383 | |
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384 | cache_t& cache() |
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385 | { |
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386 | static cache_t x; |
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387 | return x; |
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388 | } |
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389 | |
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390 | inline void* convert_type(void* const p, class_id src_t, class_id dst_t, bool polymorphic) |
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391 | { |
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392 | // Quickly rule out unregistered types |
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393 | index_entry* src_p = seek_type(src_t); |
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394 | if (src_p == 0) |
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395 | return 0; |
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396 | |
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397 | index_entry* dst_p = seek_type(dst_t); |
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398 | if (dst_p == 0) |
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399 | return 0; |
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400 | |
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401 | // Look up the dynamic_id function and call it to get the dynamic |
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402 | // info |
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403 | boost::python::objects::dynamic_id_t dynamic_id = polymorphic |
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404 | ? tuples::get<kdynamic_id>(*src_p)(p) |
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405 | : std::make_pair(p, src_t); |
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406 | |
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407 | // Look in the cache first for a quickie address translation |
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408 | std::ptrdiff_t offset = (char*)p - (char*)dynamic_id.first; |
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409 | |
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410 | cache_element seek(boost::make_tuple(src_t, dst_t, offset, dynamic_id.second)); |
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411 | cache_t& c = cache(); |
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412 | cache_t::iterator const cache_pos |
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413 | = std::lower_bound(c.begin(), c.end(), seek); |
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414 | |
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415 | |
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416 | // if found in the cache, we're done |
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417 | if (cache_pos != c.end() && cache_pos->key == seek.key) |
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418 | { |
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419 | return cache_pos->offset == cache_element::not_found |
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420 | ? 0 : (char*)p + cache_pos->offset; |
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421 | } |
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422 | |
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423 | // If we are starting at the most-derived type, only look in the up graph |
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424 | smart_graph const& g = polymorphic && dynamic_id.second != src_t |
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425 | ? full_graph() : up_graph(); |
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426 | |
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427 | void* result = search( |
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428 | g, p, tuples::get<kvertex>(*src_p) |
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429 | , tuples::get<kvertex>(*dst_p)); |
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430 | |
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431 | // update the cache |
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432 | c.insert(cache_pos, seek)->offset |
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433 | = (result == 0) ? cache_element::not_found : (char*)result - (char*)p; |
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434 | |
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435 | return result; |
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436 | } |
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437 | } |
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438 | |
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439 | namespace python { namespace objects { |
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440 | |
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441 | BOOST_PYTHON_DECL void* find_dynamic_type(void* p, class_id src_t, class_id dst_t) |
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442 | { |
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443 | return convert_type(p, src_t, dst_t, true); |
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444 | } |
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445 | |
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446 | BOOST_PYTHON_DECL void* find_static_type(void* p, class_id src_t, class_id dst_t) |
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447 | { |
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448 | return convert_type(p, src_t, dst_t, false); |
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449 | } |
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450 | |
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451 | BOOST_PYTHON_DECL void add_cast( |
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452 | class_id src_t, class_id dst_t, cast_function cast, bool is_downcast) |
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453 | { |
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454 | // adding an edge will invalidate any record of unreachability in |
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455 | // the cache. |
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456 | static std::size_t expected_cache_len = 0; |
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457 | cache_t& c = cache(); |
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458 | if (c.size() > expected_cache_len) |
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459 | { |
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460 | c.erase(std::remove_if( |
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461 | c.begin(), c.end(), |
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462 | mem_fn(&cache_element::unreachable)) |
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463 | , c.end()); |
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464 | |
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465 | // If any new cache entries get added, we'll have to do this |
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466 | // again when the next edge is added |
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467 | expected_cache_len = c.size(); |
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468 | } |
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469 | |
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470 | type_index_iterator_pair types = demand_types(src_t, dst_t); |
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471 | vertex_t src = tuples::get<kvertex>(*types.first); |
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472 | vertex_t dst = tuples::get<kvertex>(*types.second); |
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473 | |
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474 | cast_graph* const g[2] = { &up_graph().topology(), &full_graph().topology() }; |
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475 | |
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476 | for (cast_graph*const* p = g + (is_downcast ? 1 : 0); p < g + 2; ++p) |
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477 | { |
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478 | edge_t e; |
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479 | bool added; |
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480 | |
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481 | tie(e, added) = add_edge(src, dst, **p); |
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482 | assert(added); |
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483 | |
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484 | put(get(edge_cast, **p), e, cast); |
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485 | put(get(edge_index, **p), e, num_edges(full_graph().topology()) - 1); |
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486 | } |
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487 | } |
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488 | |
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489 | BOOST_PYTHON_DECL void register_dynamic_id_aux( |
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490 | class_id static_id, dynamic_id_function get_dynamic_id) |
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491 | { |
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492 | tuples::get<kdynamic_id>(*demand_type(static_id)) = get_dynamic_id; |
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493 | } |
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494 | |
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495 | }}} // namespace boost::python::objects |
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