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// Copyright David Abrahams 2002.
// Distributed under the Boost Software License, Version 1.0. (See
// accompanying file LICENSE_1_0.txt or copy at
// http://www.boost.org/LICENSE_1_0.txt)
#include <boost/python/object/inheritance.hpp>
#include <boost/python/type_id.hpp>
#include <boost/graph/breadth_first_search.hpp>
#if _MSC_FULL_VER >= 13102171 && _MSC_FULL_VER <= 13102179
# include <boost/graph/reverse_graph.hpp>
#endif
#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/reverse_graph.hpp>
#include <boost/property_map/property_map.hpp>
#include <boost/bind.hpp>
#include <boost/integer_traits.hpp>
#include <boost/tuple/tuple.hpp>
#include <boost/tuple/tuple_comparison.hpp>
#include <queue>
#include <vector>
#include <functional>
//
// Procedure:
//
// The search is a BFS over the space of (type,address) pairs
// guided by the edges of the casting graph whose nodes
// correspond to classes, and whose edges are traversed by
// applying associated cast functions to an address. We use
// vertex distance to the goal node in the cast_graph to rate the
// paths. The vertex distance to any goal node is calculated on
// demand and outdated by the addition of edges to the graph.
namespace boost {
namespace
{
enum edge_cast_t { edge_cast = 8010 };
template <class T> inline void unused_variable(const T&) { }
}
// Install properties
BOOST_INSTALL_PROPERTY(edge, cast);
namespace
{
typedef void*(*cast_function)(void*);
//
// Here we put together the low-level data structures of the
// casting graph representation.
//
typedef python::type_info class_id;
// represents a graph of available casts
#if 0
struct cast_graph
:
#else
typedef
#endif
adjacency_list<vecS,vecS, bidirectionalS, no_property
// edge index property allows us to look up edges in the connectivity matrix
, property<edge_index_t,std::size_t
// The function which casts a void* from the edge's source type
// to its destination type.
, property<edge_cast_t,cast_function> > >
#if 0
{};
#else
cast_graph;
#endif
typedef cast_graph::vertex_descriptor vertex_t;
typedef cast_graph::edge_descriptor edge_t;
struct smart_graph
{
typedef std::vector<std::size_t>::const_iterator node_distance_map;
typedef std::pair<cast_graph::out_edge_iterator
, cast_graph::out_edge_iterator> out_edges_t;
// Return a map of the distances from any node to the given
// target node
node_distance_map distances_to(vertex_t target) const
{
std::size_t n = num_vertices(m_topology);
if (m_distances.size() != n * n)
{
m_distances.clear();
m_distances.resize(n * n, (std::numeric_limits<std::size_t>::max)());
m_known_vertices = n;
}
std::vector<std::size_t>::iterator to_target = m_distances.begin() + n * target;
// this node hasn't been used as a target yet
if (to_target[target] != 0)
{
typedef reverse_graph<cast_graph> reverse_cast_graph;
reverse_cast_graph reverse_topology(m_topology);
to_target[target] = 0;
breadth_first_search(
reverse_topology, target
, visitor(
make_bfs_visitor(
record_distances(
make_iterator_property_map(
to_target
, get(vertex_index, reverse_topology)
# ifdef BOOST_NO_STD_ITERATOR_TRAITS
, *to_target
# endif
)
, on_tree_edge()
))));
}
return to_target;
}
cast_graph& topology() { return m_topology; }
cast_graph const& topology() const { return m_topology; }
smart_graph()
: m_known_vertices(0)
{}
private:
cast_graph m_topology;
mutable std::vector<std::size_t> m_distances;
mutable std::size_t m_known_vertices;
};
smart_graph& full_graph()
{
static smart_graph x;
return x;
}
smart_graph& up_graph()
{
static smart_graph x;
return x;
}
//
// Our index of class types
//
using boost::python::objects::dynamic_id_function;
typedef tuples::tuple<
class_id // static type
, vertex_t // corresponding vertex
, dynamic_id_function // dynamic_id if polymorphic, or 0
>
index_entry_interface;
typedef index_entry_interface::inherited index_entry;
enum { ksrc_static_t, kvertex, kdynamic_id };
typedef std::vector<index_entry> type_index_t;
type_index_t& type_index()
{
static type_index_t x;
return x;
}
template <class Tuple>
struct select1st
{
typedef typename tuples::element<0, Tuple>::type result_type;
result_type const& operator()(Tuple const& x) const
{
return tuples::get<0>(x);
}
};
// map a type to a position in the index
inline type_index_t::iterator type_position(class_id type)
{
typedef index_entry entry;
return std::lower_bound(
type_index().begin(), type_index().end()
, boost::make_tuple(type, vertex_t(), dynamic_id_function(0))
, boost::bind<bool>(std::less<class_id>()
, boost::bind<class_id>(select1st<entry>(), _1)
, boost::bind<class_id>(select1st<entry>(), _2)));
}
inline index_entry* seek_type(class_id type)
{
type_index_t::iterator p = type_position(type);
if (p == type_index().end() || tuples::get<ksrc_static_t>(*p) != type)
return 0;
else
return &*p;
}
// Get the entry for a type, inserting if necessary
inline type_index_t::iterator demand_type(class_id type)
{
type_index_t::iterator p = type_position(type);
if (p != type_index().end() && tuples::get<ksrc_static_t>(*p) == type)
return p;
vertex_t v = add_vertex(full_graph().topology());
vertex_t v2 = add_vertex(up_graph().topology());
unused_variable(v2);
assert(v == v2);
return type_index().insert(p, boost::make_tuple(type, v, dynamic_id_function(0)));
}
// Map a two types to a vertex in the graph, inserting if necessary
typedef std::pair<type_index_t::iterator, type_index_t::iterator>
type_index_iterator_pair;
inline type_index_iterator_pair
demand_types(class_id t1, class_id t2)
{
// be sure there will be no reallocation
type_index().reserve(type_index().size() + 2);
type_index_t::iterator first = demand_type(t1);
type_index_t::iterator second = demand_type(t2);
if (first == second)
++first;
return std::make_pair(first, second);
}
struct q_elt
{
q_elt(std::size_t distance
, void* src_address
, vertex_t target
, cast_function cast
)
: distance(distance)
, src_address(src_address)
, target(target)
, cast(cast)
{}
std::size_t distance;
void* src_address;
vertex_t target;
cast_function cast;
bool operator<(q_elt const& rhs) const
{
return distance < rhs.distance;
}
};
// Optimization:
//
// Given p, src_t, dst_t
//
// Get a pointer pd to the most-derived object
// if it's polymorphic, dynamic_cast to void*
// otherwise pd = p
//
// Get the most-derived typeid src_td
//
// ptrdiff_t offset = p - pd
//
// Now we can keep a cache, for [src_t, offset, src_td, dst_t] of
// the cast transformation function to use on p and the next src_t
// in the chain. src_td, dst_t don't change throughout this
// process. In order to represent unreachability, when a pair is
// found to be unreachable, we stick a 0-returning "dead-cast"
// function in the cache.
// This is needed in a few places below
inline void* identity_cast(void* p)
{
return p;
}
void* search(smart_graph const& g, void* p, vertex_t src, vertex_t dst)
{
// I think this test was thoroughly bogus -- dwa
// If we know there's no path; bail now.
// if (src > g.known_vertices() || dst > g.known_vertices())
// return 0;
smart_graph::node_distance_map d(g.distances_to(dst));
if (d[src] == (std::numeric_limits<std::size_t>::max)())
return 0;
typedef property_map<cast_graph,edge_cast_t>::const_type cast_map;
cast_map casts = get(edge_cast, g.topology());
typedef std::pair<vertex_t,void*> search_state;
typedef std::vector<search_state> visited_t;
visited_t visited;
std::priority_queue<q_elt> q;
q.push(q_elt(d[src], p, src, identity_cast));
while (!q.empty())
{
q_elt top = q.top();
q.pop();
// Check to see if we have a real state
void* dst_address = top.cast(top.src_address);
if (dst_address == 0)
continue;
if (top.target == dst)
return dst_address;
search_state s(top.target,dst_address);
visited_t::iterator pos = std::lower_bound(
visited.begin(), visited.end(), s);
// If already visited, continue
if (pos != visited.end() && *pos == s)
continue;
visited.insert(pos, s); // mark it
// expand it:
smart_graph::out_edges_t edges = out_edges(s.first, g.topology());
for (cast_graph::out_edge_iterator p = edges.first
, finish = edges.second
; p != finish
; ++p
)
{
edge_t e = *p;
q.push(q_elt(
d[target(e, g.topology())]
, dst_address
, target(e, g.topology())
, boost::get(casts, e)));
}
}
return 0;
}
struct cache_element
{
typedef tuples::tuple<
class_id // source static type
, class_id // target type
, std::ptrdiff_t // offset within source object
, class_id // source dynamic type
>::inherited key_type;
cache_element(key_type const& k)
: key(k)
, offset(0)
{}
key_type key;
std::ptrdiff_t offset;
BOOST_STATIC_CONSTANT(
std::ptrdiff_t, not_found = integer_traits<std::ptrdiff_t>::const_min);
bool operator<(cache_element const& rhs) const
{
return this->key < rhs.key;
}
bool unreachable() const
{
return offset == not_found;
}
};
enum { kdst_t = ksrc_static_t + 1, koffset, ksrc_dynamic_t };
typedef std::vector<cache_element> cache_t;
cache_t& cache()
{
static cache_t x;
return x;
}
inline void* convert_type(void* const p, class_id src_t, class_id dst_t, bool polymorphic)
{
// Quickly rule out unregistered types
index_entry* src_p = seek_type(src_t);
if (src_p == 0)
return 0;
index_entry* dst_p = seek_type(dst_t);
if (dst_p == 0)
return 0;
// Look up the dynamic_id function and call it to get the dynamic
// info
boost::python::objects::dynamic_id_t dynamic_id = polymorphic
? tuples::get<kdynamic_id>(*src_p)(p)
: std::make_pair(p, src_t);
// Look in the cache first for a quickie address translation
std::ptrdiff_t offset = (char*)p - (char*)dynamic_id.first;
cache_element seek(boost::make_tuple(src_t, dst_t, offset, dynamic_id.second));
cache_t& c = cache();
cache_t::iterator const cache_pos
= std::lower_bound(c.begin(), c.end(), seek);
// if found in the cache, we're done
if (cache_pos != c.end() && cache_pos->key == seek.key)
{
return cache_pos->offset == cache_element::not_found
? 0 : (char*)p + cache_pos->offset;
}
// If we are starting at the most-derived type, only look in the up graph
smart_graph const& g = polymorphic && dynamic_id.second != src_t
? full_graph() : up_graph();
void* result = search(
g, p, tuples::get<kvertex>(*src_p)
, tuples::get<kvertex>(*dst_p));
// update the cache
c.insert(cache_pos, seek)->offset
= (result == 0) ? cache_element::not_found : (char*)result - (char*)p;
return result;
}
}
namespace python { namespace objects {
BOOST_PYTHON_DECL void* find_dynamic_type(void* p, class_id src_t, class_id dst_t)
{
return convert_type(p, src_t, dst_t, true);
}
BOOST_PYTHON_DECL void* find_static_type(void* p, class_id src_t, class_id dst_t)
{
return convert_type(p, src_t, dst_t, false);
}
BOOST_PYTHON_DECL void add_cast(
class_id src_t, class_id dst_t, cast_function cast, bool is_downcast)
{
// adding an edge will invalidate any record of unreachability in
// the cache.
static std::size_t expected_cache_len = 0;
cache_t& c = cache();
if (c.size() > expected_cache_len)
{
c.erase(std::remove_if(
c.begin(), c.end(),
mem_fn(&cache_element::unreachable))
, c.end());
// If any new cache entries get added, we'll have to do this
// again when the next edge is added
expected_cache_len = c.size();
}
type_index_iterator_pair types = demand_types(src_t, dst_t);
vertex_t src = tuples::get<kvertex>(*types.first);
vertex_t dst = tuples::get<kvertex>(*types.second);
cast_graph* const g[2] = { &up_graph().topology(), &full_graph().topology() };
for (cast_graph*const* p = g + (is_downcast ? 1 : 0); p < g + 2; ++p)
{
edge_t e;
bool added;
tie(e, added) = add_edge(src, dst, **p);
assert(added);
put(get(edge_cast, **p), e, cast);
put(get(edge_index, **p), e, num_edges(full_graph().topology()) - 1);
}
}
BOOST_PYTHON_DECL void register_dynamic_id_aux(
class_id static_id, dynamic_id_function get_dynamic_id)
{
tuples::get<kdynamic_id>(*demand_type(static_id)) = get_dynamic_id;
}
}}} // namespace boost::python::objects
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