May 2014 - Boost-users - lists.preview.boost.org

[interprocess] Determine size of managed_shared_memory
by Kai Benndorf 12 Oct '19

12 Oct '19

Hi all, I want to create a managed_shared_memory in exactly the size I needed. Therefore I do something like this: size = sizeof( common_managed_shared_memory ); size += sizeof( MyClassInSharedMem ); managed_shared_memory segment(create_only, "name", size ); MyClassInSharedMem allocates itself some memory by segment->allocate(). I added this also to the size, but get a boost::interprocess::bad_alloc exception on allocating this additional memory. Are there some magic bytes I forgot to add? Many thanks in advance Kai

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[Range, Phoenix] What am I missing...
by Robert Jones 25 Apr '17

25 Apr '17

Hi Folks Can anyone explain the output of this program... #include <iostream> #include <boost/range/algorithm/copy.hpp> #include <boost/range/counting_range.hpp> #include <boost/range/adaptor/reversed.hpp> #include <boost/range/adaptor/transformed.hpp> #include <boost/phoenix/bind/bind_function.hpp> #include <boost/phoenix/core/argument.hpp> int f( int i ) { return i * 2; } int main( ) { using boost::adaptors::reversed; using boost::adaptors::transformed; using boost::counting_range; using boost::copy; using boost::phoenix::arg_names::_1; copy( counting_range( 1, 5 ) | reversed | transformed( f ), std::ostream_iterator<int>( std::cout, " " ) ); std::cout << std::endl; copy( counting_range( 1, 5 ) | reversed | transformed( bind( f, _1 ) ), std::ostream_iterator<int>( std::cout, " " ) ); std::cout << std::endl; } Which is... 8 6 4 2 1768406272 1768406272 1768406272 1768406272 I'm using Gcc 4.6.2 & Boost 1.53 Thx All.

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[statechart] Passing parameters from event to State Local Storage
by Christophe Bourez 16 Nov '16

16 Nov '16

I need to maintain a parameter into the state local storage. This parameter is initially contained in the event that causes the transition to the target state. I give hereafter a small illustrative example. typename sc = boost::statechart; class EvTest : public sc::event<EvTest> { public: EvTest(std::size_t val) : value(val) {} std::size_t getValue() const { return this->value; } private: std::size_t value; }; class MyStateMachine; class StSource; class StTarget; class StSource : public sc::simple_state<StSource, MyStateMachine> { public: typedef sc::custom_reaction<EvTest> reactions; sc::result react(const EvTest &event) { // How to pass event.getValue() to the target state ? transit<StTarget>(); } }; class StTarget : public sc::simple_state<StTarget, MyStateMachine> { public: StTarget(std::size_t val) : val(value) {} private: std::size_t value; }; Thanks, Christophe

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Re: [Boost-users] lexical_cast between double and string slow in Visual Studio 2013
by David Roberts 07 May '15

07 May '15

> That issue is unknown. I'd really appreciate the investigation. I have done some more investigation, and there are two factors that only cause the slowness when they both occur together. > Try excluding the lexical_cast from test, I have a feeling that this is only MSVC related issue: > > #include <sstream> > #include <string> > > int main (int, char **) > { > for (double count = 0.0; count < 1000000.0; count += 1.41) > { > std::stringstream ss; > ss << count; > std::string result = std::move(ss.str()); > ss.str(std::string()); > > ss << result; > ss >> count; > } > > return 0; > } > Running your test program does not exhibit the problem. It runs in around 3 seconds on my machine when built with either Visual Studio 2010 or Visual Studio 2013. However, changing it very slightly to match more closely what lexical_cast does internally does recreate the problem: #include <sstream> #include <string> int main (int, char **) { for (double count = 0.0; count < 1000000.0; count += 1.41) { std::stringstream ss; ss.unsetf(std::ios::skipws); ss.precision(17); ss << count; std::string result = std::move(ss.str()); ss.str(std::string()); ss << result; ss >> count; } return 0; } The effect of setting the precision to 17 is that lots of 9s appear in the string representations. (The number 17 is what boost::detail::lcast_get_precision(double*) chooses.) Without the precision call the contents of the string called result start off like this: 0 1.41 2.82 4.23 5.64 7.05 8.46 9.87 11.28 12.69 With precision set to 17 they start off like this: 0 1.4099999999999999 2.8199999999999998 4.2299999999999995 5.6399999999999997 7.0499999999999998 8.4599999999999991 9.8699999999999992 11.279999999999999 12.69 This happens for both Visual Studio 2010 and Visual Studio 2013. Then the next difference is that Visual Studio 2013 spends a lot longer handling all the extra 9s. Changing the program so that the double is converted to a string using std::stringstream without a precision call and then back to double using lexical_cast takes about 3 seconds for both Visual Studio 2010 and Visual Studio 2013. It is the combination of having all the extra 9s to parse and using Visual Studio 2013 that makes the test using lexical_cast to go both ways slow. Both Visual Studio 2010 and Visual Studio 2013 do the conversion by calling std::num_get<char,std::istreambuf_iterator<char,std::char_traits<char> > >::do_get() which then calls a function called _Stodx() which is implemented in xstod.c. This function is very different for the two versions. In Visual Studio 2010 it's a relatively thin wrapper around the C function strtod(). In Visual Studio 2013 _Stodx() has got a completely new implementation that's generated by #including xxstod.h with some macros defined. The original C function strtod() is much faster than the new _Stodx() when there are lots of 9s at the end of the strings being parsed. This modification to the program: #include <sstream> #include <string> #include <stdlib.h> int main (int, char **) { for (double count = 0.0; count < 1000000.0; count += 1.41) { std::stringstream ss; ss.unsetf(std::ios::skipws); ss.precision(17); ss << count; std::string result = std::move(ss.str()); ss.str(std::string()); ss << result; char *endptr; count = strtod(ss.str().c_str(), &endptr); } return 0; } has a runtime of about 3 seconds even though it's got to cope with all the 9s. I guess only someone from Microsoft or Dinkumware could comment on why _Stodx() was reimplemented. But the other thing is that by setting precision to 17 lexical_cast is bloating the string representations of the doubles with lots of 9s in both Visual Studio 2010 and Visual Studio 2013. Setting precision to 15 instead prevents this, and makes the original test run faster even with Visual Studio 2013 (about 4 seconds rather than 10). Regards, David

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Statechart serialization
by mbrodeur65 04 Mar '15

04 Mar '15

Hi, I'm looking for a solution to serialize boost::statechart objects. I'm aware that this feature is on the statechart library todo list but was wondering if there are any workaround to achieve this with the latest boost release (1.34) ? thanks for your help ! mbrodeur65 -- View this message in context: http://www.nabble.com/Statechart-serialization-tf4131326.html#a11749139 Sent from the Boost - Users mailing list archive at Nabble.com.

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NT² 3.0 and Boost.SIMD - Stable release
by Joel Falcou 21 Nov '14

21 Nov '14

The first stable release of the 3.x series of MetaScale’s open-source software is available: NT² 3.0. It also includes its spin-off project, Boost.SIMD (not yet a Boost library). Many Issues have been closed since last beta. The main focus of this release cycle was to fix performances issues and to stabilize some parts of the API. Next step will be to separate NT2 and Boost.SIMD into separate repositories, thus making one more step toward Boost.SIMD submission into review. [ http://www.metascale.org/nt%C2%B2-3-0-and-boost-simd ] *Changes & Bug Fixes:* - Major performance improvements in both libraries - Added experimental support for the HPX runtime for parallelization on shared memory systems - Optimizations of many elemental functions, in particuler log/ex, frexp/ldexp and cbrt - More advanced shuffle pattern recognition for SIMD - Fixed issues with Visual Studio 2013 - More functions are force-inlined to ensure good performance - New functions for conversion between types and mixing of vectors of different sizes - Demo applications usable as benchmarks - Better handling of errors when an unsupported function is called - New API for custom memory allocators Full changelog is available at https://github.com/MetaScale/nt2/releases/tag/3.0.0. *How to get it ?* - Source and binary packages can be downloaded here: http://nt2.metascale.org/downloads - The release is also available on Github : https://github.com/MetaScale/nt2/releases - The main master branch is still under development : https://github.com/MetaScale/nt2

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[Thread] Read-write locks
by lfrfly＠icqmail.com 18 Sep '14

18 Sep '14

I'm trying to create a standard read/write lock using Boost Threads, and I'm having a bit of difficulty mapping the Boost concepts onto the usual ones. A read/write lock should have several states: Locked for reading (multiple threads may lock at once), locked for writing (only one thread may lock, and no threads may be locked for reading at the same time), and unlocked. Ideally it would be nice if an RWL which is locked for reading may temporarily upgrade to locked for writing, then return to the locked for reading state. Boost supports several relevant notions of locking: shared locking, upgrade locking, and exclusive locking. This to me is a confusing distinction. In particular, a shared_mutex seems appropriate as the basis for a RWL, but is lock_upgrade() the equivalent of a write lock and lock_shared the equivalent of a read lock? This is unclear. If "upgrade locking" is not the same as "exclusive locking", then is an upgrade lock actually exclusive? Could someone please clarify this.

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[Statechart] How to decide between post_event and process_event atrun time ?
by Philippe DAVID 22 Jul '14

22 Jul '14

Hi, I have a method in which I want to post/process an event. The thing is, this method can be called from outside the state machine (so I need to call process_event), or indirectly by a reaction of the state machine (in this case I must call post_event since process_event is not reentrant). I don't want to write 2 distinct methods to do this (one that calls post, and the other process), I would much rather prefer adding a 'if' in my method that tells me if I have to call process_event or post_event (if I'm being called indirectly by the state machine or not). Is there a way to do this with statechart ? regards, Philippe

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[Log] Extract severity value
by Olivier Tournaire 17 Jul '14

17 Jul '14

Hi all, I am trying to extract severity level from a log record, but i seems that I am doing it the wrong way. Here is the code I use: void LogDockWidget::receiveLog(boost::log::record_view const& rec, const std::string& log) { logging::value_ref< logging::trivial::severity_level > level = logging::extract< logging::trivial::severity_level >("Severity", rec); // ... } Here level.get() always returns "info". All my logs are done with the BOOST_LOG_TRIVIAL(...) macro. The formatter whereas displays correctly the severity level. Here is how it is defined: void LogDockWidget::init_logging() { boost::shared_ptr< logging::core > core = logging::core::get(); typedef sinks::synchronous_sink< QTextEditFormattedSinkBackend > sink_t; boost::shared_ptr< sink_t > sink(new sink_t); // ... logging::add_file_log( keywords::file_name = logFilename, keywords::auto_flush = true, keywords::format = ( BUILD_LOG_FORMATTER() ) ); sink->set_formatter( BUILD_LOG_FORMATTER() ); core->add_sink(sink); // Add attributes that we will use logging::add_common_attributes(); core->add_global_attribute( "ThreadID", attrs::current_thread_id()); } #define BUILD_LOG_FORMATTER() \ expr::stream \ << "[" << expr::format_date_time< boost::posix_time::ptime >("TimeStamp", "%Y-%m-%d %H:%M:%S") << "] " \ << expr::attr<unsigned int>("LineID") << " " \ << ": <" << logging::trivial::severity << "> " \ << " [" << expr::attr<attrs::current_thread_id::value_type>("ThreadID") << "] " \ << expr::if_(expr::has_attr(scope_attribute)) \ [ \ expr::stream << "[" << scope_attribute << "] " \ ] \ << expr::message Could you please let me know what I am doing wrong? Regards, Olivier

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[Graph] Newbie on A*
by Sensei 04 Jul '14

04 Jul '14

Dear all, I am fiddling with the A* example on cities in order to learn how to use the A* search. Obviously, I cannot make it work :) The main goal is this, but I'm way too far from this: make A* fail when the path is longer, **not costlier**, than a constant. But right now I'd just like to have A* working on a graph. :) In order to see the different results, I've paired it with a Dijkstra search, and my A* heuristics is quite simple: constant. Dijkstra works fine, but A* stops at the first node, and the target isn't reached (but a path is available). What am I doing wrong? Forgive me if I'm making a stupid mistake bu I'm completely a newbie! If you need the graph, here's the link: https://dl.dropboxusercontent.com/u/15635416/g.txt Thanks! #include <cstdio> #include <cstdlib> #include <iostream> #include <utility> #include <algorithm> #include <numeric> #include <deque> #include <unordered_set> #include <vector> #include <fstream> #include <list> #include <boost/graph/graph_traits.hpp> #include <boost/graph/compressed_sparse_row_graph.hpp> #include <boost/graph/dijkstra_shortest_paths.hpp> #include <boost/graph/breadth_first_search.hpp> #include <boost/graph/depth_first_search.hpp> #include <boost/pending/indirect_cmp.hpp> #include <boost/range/irange.hpp> #include <boost/property_map/property_map.hpp> #include <boost/graph/astar_search.hpp> // Properties: weights are int typedef boost::property<boost::edge_weight_t, int> edge_weight; // The graph itself as a compressed sparse row matrix typedef boost::compressed_sparse_row_graph<boost::bidirectionalS, boost::no_property, edge_weight> boost_graph; // Vertex iterator typedef boost::graph_traits<boost_graph>::vertex_iterator vertex_iterator; // Edge iterator typedef boost::graph_traits<boost_graph>::edge_iterator edge_iterator; // Adjacent nodes iterator typedef boost::graph_traits<boost_graph>::adjacency_iterator adjacency_iterator; typedef boost::graph_traits<boost_graph>::out_edge_iterator outward_iterator; typedef boost::graph_traits<boost_graph>::in_edge_iterator inward_iterator; // Property maps typedef boost::property_map<boost_graph, boost::vertex_index_t>::type index_map; //typedef boost::property_map<boost_graph, boost::vertex_name_t> name_map; // Property iterators typedef boost::iterator_property_map<std::size_t*, index_map, std::size_t, std::size_t&> predecessor_map; typedef boost::iterator_property_map<std::size_t*, index_map, std::size_t, std::size_t&> distance_map; bool isValid(std::size_t index) { return (index >= 0) && (index <= 12); } // **************************************************************************** // A* heuristics template <class graph_type> class astar_heuristic : public boost::astar_heuristic<graph_type, std::size_t> { public: typedef typename boost::graph_traits<graph_type>::vertex_descriptor vertex_type; astar_heuristic(vertex_type goal) : goal_(goal) { }; std::size_t operator()(vertex_type u) { return 3; } private: vertex_type goal_; }; // Class to be used to terminate the A* algorithm class exit_astar { public: exit_astar(bool found) { }; }; // A* visitor that terminates when we find the goal template <class vertex_type> class astar_visitor : public boost::default_astar_visitor { public: astar_visitor(vertex_type goal) : goal_(goal) { }; template <class Graph> void examine_vertex(vertex_type u, Graph& g) { //std::cout << "EXAM: " << u << std::endl; if (u == goal_) throw exit_astar(true); } private: vertex_type goal_; }; // **************************************************************************** int main(int argc, const char * argv[]) { std::vector<std::pair<std::size_t, std::size_t>> graph_edges; std::vector<int> edge_weight; int n_nodes; int read_a, read_b, read_w; n_nodes = -1; std::ifstream igraph("/Users/senseiwa/Documents/Projects/scratch/tbb/g.txt"); while(igraph >> read_a >> read_b >> read_w) { if (read_a > n_nodes) n_nodes = read_a; if (read_b > n_nodes) n_nodes = read_b; read_a--; read_b--; graph_edges.push_back(std::make_pair(read_a, read_b)); edge_weight.push_back(read_w); } std::cout << "+++ READ # NODES: " << n_nodes << std::endl; // Create the graph boost_graph graph(boost::edges_are_unsorted_multi_pass, graph_edges.begin(), graph_edges.end(), edge_weight.data(), n_nodes); std::cout << "Graph statistics: " << std::endl; std::cout << "Nodes: " << boost::num_vertices(graph) << std::endl; std::cout << "Edges: " << graph_edges.size() << std::endl; edge_iterator ei, ee; std::size_t source_node = std::stoul(argv[1]); std::size_t destination_node = std::stoul(argv[2]); std::cout << ">> SOURCE NODE " << source_node << std::endl; std::cout << "Degrees in/out: " << source_node << std::endl; std::cout << boost::in_degree(boost::vertex(source_node, graph), graph) << std::endl; std::cout << boost::out_degree(boost::vertex(source_node, graph), graph) << std::endl; std::cout << "Degrees in/out: " << destination_node << std::endl; std::cout << boost::in_degree(boost::vertex(destination_node, graph), graph) << std::endl; std::cout << boost::out_degree(boost::vertex(destination_node, graph), graph) << std::endl; std::vector<std::size_t> preds(boost::num_vertices(graph)); std::vector<std::size_t> dists(boost::num_vertices(graph)); index_map idx_map = boost::get(boost::vertex_index, graph); predecessor_map pred_map(preds.data(), idx_map); distance_map dist_map(dists.data(), idx_map); boost::dijkstra_shortest_paths(graph, source_node, boost::distance_map(dist_map).predecessor_map(pred_map)); typedef std::vector<boost_graph::edge_descriptor> path_type; path_type spath; std::cout << ">> SOURCE NODE " << source_node << std::endl; std::cout << ">> DESTINATION NODE " << destination_node << std::endl; // ******* DIJKSTRA ******************************************************** std::size_t v = destination_node; // We want to start at the destination and work our way back to the source for(std::size_t u = pred_map[v]; // Start by setting 'u' to the destintaion node's predecessor u != v; // Keep tracking the path until we get to the source v = u, u = pred_map[v]) // Set the current vertex to the current predecessor, and the predecessor to one level up { std::pair<boost_graph::edge_descriptor, bool> edgePair = boost::edge(u, v, graph); boost_graph::edge_descriptor edge = edgePair.first; spath.push_back(edge); } // Write shortest path int totalDistance = 0; for(path_type::reverse_iterator pathIterator = spath.rbegin(); pathIterator != spath.rend(); ++pathIterator) { std::cout << boost::source(*pathIterator, graph) << " - " << boost::target(*pathIterator, graph) << " = " << boost::get(boost::edge_weight, graph, *pathIterator) << std::endl; totalDistance += boost::get(boost::edge_weight, graph, *pathIterator); } std::cout << "Shortest Dijkstra path from " << source_node << " to " << destination_node << " cost " << totalDistance << std::endl; // ******* A* ************************************************************** // A* search predecessor and cost std::vector<std::size_t> p(boost::num_vertices(graph)); std::vector<std::size_t> d(boost::num_vertices(graph)); try { // A* parameter interface astar_search(graph, source_node, astar_heuristic<boost_graph>(destination_node), boost::predecessor_map(&p[0]).distance_map(&d[0]).visitor(astar_visitor<std::size_t>(destination_node))); } catch(exit_astar fg) { std::list<std::size_t> shortest_path; for(std::size_t v = source_node; ; v = p[v]) { shortest_path.push_front(v); if(p[v] == v) break; } auto spi = shortest_path.begin(); std::cout << "node " << source_node << std::endl; for(++spi; spi != shortest_path.end(); ++spi) std::cout << "node " << *spi << std::endl; std::cout << "Shortest A* path from " << source_node << " to " << destination_node << " cost " << d[destination_node] << std::endl; std::cout << shortest_path.size() << std::endl; return 0; } std::cout << "Didn't find a path from " << source_node << "to" << destination_node << "!" << std::endl; return 0; } +++ READ # NODES: 200 Graph statistics: Nodes: 200 Edges: 4000 >> SOURCE NODE 1 Degrees in/out: 1 0 35 Degrees in/out: 192 39 1 >> SOURCE NODE 1 >> DESTINATION NODE 192 1 - 47 = 2 47 - 91 = 3 91 - 120 = 1 120 - 175 = 1 175 - 192 = 10 Shortest Dijkstra path from 1 to 192 cost 17 node 1 Shortest A* path from 1 to 192 cost 17 1

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