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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/python/detail/pymutex.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/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demand and outdated by the addition of edges to the graph.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)
{
using
namespace
boost
::placeholders
;
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)
{
BOOST_PYTHON_LOCK_STATE
();
//
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)
{
BOOST_PYTHON_LOCK_STATE
();
//
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)
{
BOOST_PYTHON_LOCK_STATE
();
tuples::get<kdynamic_id>(*
demand_type
(static_id)) = get_dynamic_id;
}
}}}
//
namespace boost::python::objects
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