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  • Why does my finite state machine take so long to execute?

    - by BillyONeal
    Hello all :) I'm working on a state machine which is supposed to extract function calls of the form /* I am a comment */ //I am a comment perf("this.is.a.string.which\"can have QUOTES\"", 123456); where the extracted data would be perf("this.is.a.string.which\"can have QUOTES\"", 123456); from a file. Currently, to process a 41kb file, this process is taking close to a minute and a half. Is there something I'm seriously misunderstanding here about this finite state machine? #include <boost/algorithm/string.hpp> std::vector<std::string> Foo() { std::string fileData; //Fill filedata with the contents of a file std::vector<std::string> results; std::string::iterator begin = fileData.begin(); std::string::iterator end = fileData.end(); std::string::iterator stateZeroFoundLocation = fileData.begin(); std::size_t state = 0; for(; begin < end; begin++) { switch (state) { case 0: if (boost::starts_with(boost::make_iterator_range(begin, end), "pref(")) { stateZeroFoundLocation = begin; begin += 4; state = 2; } else if (*begin == '/') state = 1; break; case 1: state = 0; switch (*begin) { case '*': begin = boost::find_first(boost::make_iterator_range(begin, end), "*/").end(); break; case '/': begin = std::find(begin, end, L'\n'); } break; case 2: if (*begin == '"') state = 3; break; case 3: switch(*begin) { case '\\': state = 4; break; case '"': state = 5; } break; case 4: state = 3; break; case 5: if (*begin == ',') state = 6; break; case 6: if (*begin != ' ') state = 7; break; case 7: switch(*begin) { case '"': state = 8; break; default: state = 10; break; } break; case 8: switch(*begin) { case '\\': state = 9; break; case '"': state = 10; } break; case 9: state = 8; break; case 10: if (*begin == ')') state = 11; break; case 11: if (*begin == ';') state = 12; break; case 12: state = 0; results.push_back(std::string(stateZeroFoundLocation, begin)); }; } return results; } Billy3

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  • Complex error handling

    - by Caspin
    I've got a particularly ornery piece of network code. I'm using asio but that really doesn't matter for this question. I assume there is no way to unbind a socket other than closing it. The problem is that open(), bind(), and listen() can all throw a system_error. So I handled the code with a simple try/catch. The code as written in broken. using namespace boost::asio; class Thing { public: ip::tcp::endpoint m_address; ip::tcp::acceptor m_acceptor; /// connect should handle all of its exceptions internally. bool connect() { try { m_acceptor.open( m_address.protocol() ); m_acceptor.set_option( tcp::acceptor::reuse_address(true) ); m_acceptor.bind( m_address ); m_acceptor.listen(); m_acceptor.async_accept( /*stuff*/ ); } catch( const boost::system::system_error& error ) { assert(acceptor.is_open()); m_acceptor.close(); return false; } return true; } /// don't call disconnect unless connect previously succeeded. void disconnect() { // other stuff needed to disconnect is ommited m_acceptor.close(); } }; The error is if the socket fails to connect it will try to close it in the catch block and throw another system_error about closing an acceptor that has never been opened. One solution is to add an if( acceptor.is_open() ) in the catch block but that tastes wrong. Kinda like mixing C-style error checking with c++ exceptions. If I where to go that route, I may as well use the non-throwing version of open(). boost::system::error_code error; acceptor.open( address.protocol, error ); if( ! error ) { try { acceptor.set_option( tcp::acceptor::reuse_address(true) ); acceptor.bind( address ); acceptor.listen(); acceptor.async_accept( /*stuff*/ ); } catch( const boost::system::system_error& error ) { assert(acceptor.is_open()); acceptor.close(); return false; } } return !error; Is there an elegant way to handle these possible exceptions using RAII and try/catch blocks? Am I just wrong headed in trying to avoid if( error condition ) style error handling when using exceptions?

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  • Portability of pthreads-win32 over various compilers.

    - by Artyom
    Hello, I'm using pthreads-win32 for portable threading support for windows. At least, according to the documentation pthreads-win32 should work with MSVC and even MSVC builds provided. But I don't know if the library is tested with latest MSVC compilers like MSVC-2008 and if it is supported under 64bit windows. Does anybody aware of any issues with this library? Note: Do not even try to recommend using Boost.Thread, I'm not interested in. And I'm familiar with Boost.Thread library

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  • Parallelism in Python

    - by fmark
    What are the options for achieving parallelism in Python? I want to perform a bunch of CPU bound calculations over some very large rasters, and would like to parallelise them. Coming from a C background, I am familiar with three approaches to parallelism: Message passing processes, possibly distributed across a cluster, e.g. MPI. Explicit shared memory parallelism, either using pthreads or fork(), pipe(), et. al Implicit shared memory parallelism, using OpenMP. Deciding on an approach to use is an exercise in trade-offs. In Python, what approaches are available and what are their characteristics? Is there a clusterable MPI clone? What are the preferred ways of achieving shared memory parallelism? I have heard reference to problems with the GIL, as well as references to tasklets. In short, what do I need to know about the different parallelization strategies in Python before choosing between them?

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  • Is this an idiomatic way to pass mocks into objects?

    - by Billy ONeal
    I'm a bit confused about passing in this mock class into an implementation class. It feels wrong to have all this explicitly managed memory flying around. I'd just pass the class by value but that runs into the slicing problem. Am I missing something here? Implementation: namespace detail { struct FileApi { virtual HANDLE CreateFileW( __in LPCWSTR lpFileName, __in DWORD dwDesiredAccess, __in DWORD dwShareMode, __in_opt LPSECURITY_ATTRIBUTES lpSecurityAttributes, __in DWORD dwCreationDisposition, __in DWORD dwFlagsAndAttributes, __in_opt HANDLE hTemplateFile ) { return ::CreateFileW(lpFileName, dwDesiredAccess, dwShareMode, lpSecurityAttributes, dwCreationDisposition, dwFlagsAndAttributes, hTemplateFile); } virtual void CloseHandle(HANDLE handleToClose) { ::CloseHandle(handleToClose); } }; } class File : boost::noncopyable { HANDLE hWin32; boost::scoped_ptr<detail::FileApi> fileApi; public: File( __in LPCWSTR lpFileName, __in DWORD dwDesiredAccess, __in DWORD dwShareMode, __in_opt LPSECURITY_ATTRIBUTES lpSecurityAttributes, __in DWORD dwCreationDisposition, __in DWORD dwFlagsAndAttributes, __in_opt HANDLE hTemplateFile, __in detail::FileApi * method = new detail::FileApi() ) { fileApi.reset(method); hWin32 = fileApi->CreateFileW(lpFileName, dwDesiredAccess, dwShareMode, lpSecurityAttributes, dwCreationDisposition, dwFlagsAndAttributes, hTemplateFile); } }; namespace detail { struct FileApi { virtual HANDLE CreateFileW( __in LPCWSTR lpFileName, __in DWORD dwDesiredAccess, __in DWORD dwShareMode, __in_opt LPSECURITY_ATTRIBUTES lpSecurityAttributes, __in DWORD dwCreationDisposition, __in DWORD dwFlagsAndAttributes, __in_opt HANDLE hTemplateFile ) { return ::CreateFileW(lpFileName, dwDesiredAccess, dwShareMode, lpSecurityAttributes, dwCreationDisposition, dwFlagsAndAttributes, hTemplateFile); } virtual void CloseHandle(HANDLE handleToClose) { ::CloseHandle(handleToClose); } }; } class File : boost::noncopyable { HANDLE hWin32; boost::scoped_ptr<detail::FileApi> fileApi; public: File( __in LPCWSTR lpFileName, __in DWORD dwDesiredAccess, __in DWORD dwShareMode, __in_opt LPSECURITY_ATTRIBUTES lpSecurityAttributes, __in DWORD dwCreationDisposition, __in DWORD dwFlagsAndAttributes, __in_opt HANDLE hTemplateFile, __in detail::FileApi * method = new detail::FileApi() ) { fileApi.reset(method); hWin32 = fileApi->CreateFileW(lpFileName, dwDesiredAccess, dwShareMode, lpSecurityAttributes, dwCreationDisposition, dwFlagsAndAttributes, hTemplateFile); } ~File() { fileApi->CloseHandle(hWin32); } }; Tests: namespace detail { struct MockFileApi : public FileApi { MOCK_METHOD7(CreateFileW, HANDLE(LPCWSTR, DWORD, DWORD, LPSECURITY_ATTRIBUTES, DWORD, DWORD, HANDLE)); MOCK_METHOD1(CloseHandle, void(HANDLE)); }; } using namespace detail; using namespace testing; TEST(Test_File, OpenPassesArguments) { MockFileApi * api = new MockFileApi; EXPECT_CALL(*api, CreateFileW(Eq(L"BozoFile"), Eq(56), Eq(72), Eq(reinterpret_cast<LPSECURITY_ATTRIBUTES>(67)), Eq(98), Eq(102), Eq(reinterpret_cast<HANDLE>(98)))) .Times(1).WillOnce(Return(reinterpret_cast<HANDLE>(42))); File test(L"BozoFile", 56, 72, reinterpret_cast<LPSECURITY_ATTRIBUTES>(67), 98, 102, reinterpret_cast<HANDLE>(98), api); }

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  • Running OpenMPI on Windows XP

    - by iamweird
    Hi there. I'm trying to build a simple cluster based on Windows XP. I compiled OpenMPI-1.4.2 successfully, and tools like mpicc and ompi_info work too, but I can't get my mpirun working properly. The only output I can see is Z:\orterun --hostfile z:\hosts.txt -np 2 hostname [host0:04728] Failed to initialize COM library. Error code = -2147417850 [host0:04728] [[8946,0],0] ORTE_ERROR_LOG: Error in file ..\..\openmpi-1.4.2 \orte\mca\ess\hnp\ess_hnp_module.c at line 218 -------------------------------------------------------------------------- It looks like orte_init failed for some reason; your parallel process is likely to abort. There are many reasons that a parallel process can fail during orte_init; some of which are due to configuration or environment problems. This failure appears to be an internal failure; here's some additional information (which may only be relevant to an Open MPI developer): orte_plm_init failed -- Returned value Error (-1) instead of ORTE_SUCCESS -------------------------------------------------------------------------- [host0:04728] [[8946,0],0] ORTE_ERROR_LOG: Error in file ..\..\openmpi-1.4.2 \orte\runtime\orte_init.c at line 132 -------------------------------------------------------------------------- It looks like orte_init failed for some reason; your parallel process is likely to abort. There are many reasons that a parallel process can fail during orte_init; some of which are due to configuration or environment problems. This failure appears to be an internal failure; here's some additional information (which may only be relevant to an Open MPI developer): orte_ess_set_name failed -- Returned value Error (-1) instead of ORTE_SUCCESS -------------------------------------------------------------------------- [host0:04728] [[8946,0],0] ORTE_ERROR_LOG: Error in file ..\..\..\..\openmpi -1.4.2\orte\tools\orterun\orterun.c at line 543 Where z:\hosts.txt appears as follows: host0 host1 Z: is a shared network drive available to both host0 and host1. What my problem is and how do I fix it? Upd: Ok, this problem seems to be fixed. It seems to me that WideCap driver and/or software components causes this error to appear. A "clean" machine runs local task successfully. Anyway, I still cannot run a task within at least 2 machines, I'm getting following message: Z:\mpirun --hostfile z:\hosts.txt -np 2 hostname connecting to host1 username:cluster password:******** Save Credential?(Y/N) y [host0:04728] This feature hasn't been implemented yet. [host0:04728] Could not connect to namespace cimv2 on node host1. Error code =-2147024891 -------------------------------------------------------------------------- mpirun was unable to start the specified application as it encountered an error. More information may be available above. -------------------------------------------------------------------------- I googled a little and did all the things as described here: http://www.open-mpi.org/community/lists/users/2010/03/12355.php but I'm still getting the same error. Can anyone help me? Upd2: Error code -2147024891 might be WMI error WBEM_E_INVALID_PARAMETER (0x80041008) which occures when one of the parameters passed to the WMI call is not correct. Does this mean that the problem is in OpenMPI source code itself? Or maybe it's because of wrong/outdated wincred.h and credui.lib I used while building OpenMPI from the source code?

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  • Why is overloading operator&() prohibited for classes stored in STL containers?

    - by sharptooth
    Suddenly in this article ("problem 2") I see a statement that C++ Standard prohibits using STL containers for storing elemants of class if that class has an overloaded operator&(). Having overloaded operator&() can indeed be problematic, but looks like a default "address-of" operator can be used easily through a set of dirty-looking casts that are used in boost::addressof() and are believed to be portable and standard-compilant. Why is having an overloaded operator&() prohibited for classes stored in STL containers while the boost::addressof() workaround exists?

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  • conditionally enabling constructor

    - by MK
    Here is how I can conditionally enable a constructor of a class : struct Foo { template<class T> Foo( T* ptr, boost::enable_if<is_arithmetic<T> >::type* = NULL ) {} }; I would like to know why I need to do the enabling via a dummy parameter. Why can I not just write : struct Foo { template<class T> Foo( boost::enable_if<is_arithmetic<T>, T>::type* = NULL ) {} };

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  • C++, what does this syntax mean?

    - by aaa
    i found this in this file: http://www.boost.org/doc/libs/1_43_0/boost/spirit/home/phoenix/core/actor.hpp What does this syntax means? struct actor ... { ... template <typename T0, typename T1> typename result<actor(T0&,T1&)>::type // this line thank you

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  • Considerations when porting a MS VC++ program (single machine) to a rocks cluster

    - by Mel
    I am trying to port a MS VC++ program to run on a rocks cluster! I am not very good with linux but I am eager to learn and I imagine porting it wouldn't be an impossible task for me. However, I do not understand how to take advantage of the cluster nodes. because it seems that the code execute only runs on the front end server (obviously). I have read a little about MPI and its seems like I should use MPI to comminicate between nodes. The program is currently written such that I have a main thread that synchronizes all worker threads. The main thread also recieves commands to manipulate the simulation or query its state. If the simulation is properly setup, communication between executing threads can be significantly minimized. What I don't understand is how do I start the process on the compute nodes and how do I handle failures in nodes? And maybe there should be other things I should also consider when porting my program to run in a cluster?

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  • Windows Azure Recipe: High Performance Computing

    - by Clint Edmonson
    One of the most attractive ways to use a cloud platform is for parallel processing. Commonly known as high-performance computing (HPC), this approach relies on executing code on many machines at the same time. On Windows Azure, this means running many role instances simultaneously, all working in parallel to solve some problem. Doing this requires some way to schedule applications, which means distributing their work across these instances. To allow this, Windows Azure provides the HPC Scheduler. This service can work with HPC applications built to use the industry-standard Message Passing Interface (MPI). Software that does finite element analysis, such as car crash simulations, is one example of this type of application, and there are many others. The HPC Scheduler can also be used with so-called embarrassingly parallel applications, such as Monte Carlo simulations. Whatever problem is addressed, the value this component provides is the same: It handles the complex problem of scheduling parallel computing work across many Windows Azure worker role instances. Drivers Elastic compute and storage resources Cost avoidance Solution Here’s a sketch of a solution using our Windows Azure HPC SDK: Ingredients Web Role – this hosts a HPC scheduler web portal to allow web based job submission and management. It also exposes an HTTP web service API to allow other tools (including Visual Studio) to post jobs as well. Worker Role – typically multiple worker roles are enlisted, including at least one head node that schedules jobs to be run among the remaining compute nodes. Database – stores state information about the job queue and resource configuration for the solution. Blobs, Tables, Queues, Caching (optional) – many parallel algorithms persist intermediate and/or permanent data as a result of their processing. These fast, highly reliable, parallelizable storage options are all available to all the jobs being processed. Training Here is a link to online Windows Azure training labs where you can learn more about the individual ingredients described above. (Note: The entire Windows Azure Training Kit can also be downloaded for offline use.) Windows Azure HPC Scheduler (3 labs)  The Windows Azure HPC Scheduler includes modules and features that enable you to launch and manage high-performance computing (HPC) applications and other parallel workloads within a Windows Azure service. The scheduler supports parallel computational tasks such as parametric sweeps, Message Passing Interface (MPI) processes, and service-oriented architecture (SOA) requests across your computing resources in Windows Azure. With the Windows Azure HPC Scheduler SDK, developers can create Windows Azure deployments that support scalable, compute-intensive, parallel applications. See my Windows Azure Resource Guide for more guidance on how to get started, including links web portals, training kits, samples, and blogs related to Windows Azure.

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  • How to have many Ubuntu workstations centrally managed?

    - by Richard Zak
    I have about a dozen Alienware workstations that are used for CUDA development and for execution of MPI jobs. What is the best way to manage them? I'd like to have something like an apt-get but for several systems, and a way to reimage a system simply and centrally. It seems that a combination of Landscape and Canonical's MAAS would be a good fit, but I need an open source solution. Any thoughts?

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  • Use of for_each on map elements

    - by Antonio
    I have a map where I'd like to perform a call on every data type object member function. I yet know how to do this on any sequence but, is it possible to do it on an associative container? The closest answer I could find was this: Boost.Bind to access std::map elements in std::for_each. But I cannot use boost in my project so, is there an STL alternative that I'm missing to boost::bind? If not possible, I thought on creating a temporary sequence for pointers to the data objects and then, call for_each on it, something like this: class MyClass { public: void Method() const; } std::map<int, MyClass> Map; //... std::vector<MyClass*> Vector; std::transform(Map.begin(), Map.end(), std::back_inserter(Vector), std::mem_fun_ref(&std::map<int, MyClass>::value_type::second)); std::for_each(Vector.begin(), Vector.end(), std::mem_fun(&MyClass::Method)); It looks too obfuscated and I don't really like it. Any suggestions?

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  • Find max integer size that a floating point type can handle without loss of precision

    - by Checkers
    Double has range more than a 64-bit integer, but its precision is less dues to its representation (since double is 64-bit as well, it can't fit more actual values). So, when representing larger integers, you start to lose precision in the integer part. #include <boost/cstdint.hpp> #include <limits> template<typename T, typename TFloat> void maxint_to_double() { T i = std::numeric_limits<T>::max(); TFloat d = i; std::cout << std::fixed << i << std::endl << d << std::endl; } int main() { maxint_to_double<int, double>(); maxint_to_double<boost::intmax_t, double>(); maxint_to_double<int, float>(); return 0; } This prints: 2147483647 2147483647.000000 9223372036854775807 9223372036854775800.000000 2147483647 2147483648.000000 Note how max int can fit into a double without loss of precision and boost::intmax_t (64-bit in this case) cannot. float can't even hold an int. Now, the question: is there a way in C++ to check if the entire range of a given integer type can fit into a loating point type without loss of precision? Preferably, it would be a compile-time check that can be used in a static assertion, and would not involve enumerating the constants the compiler should know or can compute.

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  • What would be the safest way to store objects of classes derived from a common interface in a common

    - by Svenstaro
    I'd like to manage a bunch of objects of classes derived from a shared interface class in a common container. To illustrate the problem, let's say I'm building a game which will contain different actors. Let's call the interface IActor and derive Enemy and Civilian from it. Now, the idea is to have my game main loop be able to do this: // somewhere during init std::vector<IActor> ActorList; Enemy EvilGuy; Civilian CoolGuy; ActorList.push_back(EvilGuy); ActorList.push_back(CoolGuy); and // main loop while(!done) { BOOST_FOREACH(IActor CurrentActor, ActorList) { CurrentActor.Update(); CurrentActor.Draw(); } } ... or something along those lines. This example obviously won't work but that is pretty much the reason I'm asking here. I'd like to know: What would be the best, safest, highest-level way to manage those objects in a common heterogeneous container? I know about a variety of approaches (Boost::Any, void*, handler class with boost::shared_ptr, Boost.Pointer Container, dynamic_cast) but I can't decide which would be the way to go here. Also I'd like to emphasize that I want to stay away as far as possible from manual memory management or nested pointers. Help much appreciated :).

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  • What is the rationale to non allow overloading of C++ conversions operator with non-member functio

    - by Vicente Botet Escriba
    C++0x has added explicit conversion operators, but they must always be defined as members of the Source class. The same applies to the assignment operator, it must be defined on the Target class. When the Source and Target classes of the needed conversion are independent of each other, neither the Source can define a conversion operator, neither the Target can define a constructor from a Source. Usually we get it by defining a specific function such as Target ConvertToTarget(Source& v); If C++0x allowed to overload conversion operator by non member functions we could for example define the conversion implicitly or explicitly between unrelated types. template < typename To, typename From operator To(const From& val); For example we could specialize the conversion from chrono::time_point to posix_time::ptime as follows template < class Clock, class Duration operator boost::posix_time::ptime( const boost::chrono::time_point& from) { using namespace boost; typedef chrono::time_point time_point_t; typedef chrono::nanoseconds duration_t; typedef duration_t::rep rep_t; rep_t d = chrono::duration_cast( from.time_since_epoch()).count(); rep_t sec = d/1000000000; rep_t nsec = d%1000000000; return posix_time::from_time_t(0)+ posix_time::seconds(static_cast(sec))+ posix_time::nanoseconds(nsec); } And use the conversion as any other conversion. So the question is: What is the rationale to non allow overloading of C++ conversions operator with non-member functions?

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  • Lucene setboost doesn't work

    - by Keven
    Hi all, OUr team just upgrade lucene from 2.3 to 3.0 and we are confused about the setboost and getboost of document. What we want is just set a boost for each document when add them into index, then when search it the documents in the response should have different order according to the boost I set. But it seems the order is not changed at all, even the boost of each document in the search response is still 1.0. Could some one give me some hit? Following is our code: String[] a = new String[] { "schindler", "spielberg", "shawshank", "solace", "sorcerer", "stone", "soap", "salesman", "save" }; List strings = Arrays.asList(a); AutoCompleteIndex index = new Index(); IndexWriter writer = new IndexWriter(index.getDirectory(), AnalyzerFactory.createAnalyzer("en_US"), true, MaxFieldLength.LIMITED); float i = 1f; for (String string : strings) { Document doc = new Document(); Field f = new Field(AutoCompleteIndexFactory.QUERYTEXTFIELD, string, Field.Store.YES, Field.Index.NOT_ANALYZED); doc.setBoost(i); doc.add(f); writer.addDocument(doc); i += 2f; } writer.close(); IndexReader reader2 = IndexReader.open(index.getDirectory()); for (int j = 0; j < reader2.maxDoc(); j++) { if (reader2.isDeleted(j)) { continue; } Document doc = reader2.document(j); Field f = doc.getField(AutoCompleteIndexFactory.QUERYTEXTFIELD); System.out.println(f.stringValue() + ":" + f.getBoost() + ", docBoost:" + doc.getBoost()); doc.setBoost(j); }

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  • noncopyable static const member class in template class

    - by Dukales
    I have a non-copyable (inherited from boost::noncopyable) class that I use as a custom namespace. Also, I have another class, that uses previous one, as shown here: #include <boost/utility.hpp> #include <cmath> template< typename F > struct custom_namespace : boost::noncopyable { F sqrt_of_half(F const & x) const { using std::sqrt; return sqrt(x / F(2.0L)); } // ... maybe others are not so dummy const/constexpr methods }; template< typename F > class custom_namespace_user { static ::custom_namespace< F > const custom_namespace_; public : F poisson() const { return custom_namespace_.sqrt_of_half(M_PI); } static F square_diagonal(F const & a) { return a * custom_namespace_.sqrt_of_half(1.0L); } }; template< typename F > ::custom_namespace< F > const custom_namespace_user< F >::custom_namespace_(); this code leads to the next error (even without instantiation): error: no 'const custom_namespace custom_namespace_user::custom_namespace_()' member function declared in class 'custom_namespace_user' The next way is not legitimate: template< typename F ::custom_namespace< F const custom_namespace_user< F ::custom_namespace_ = ::custom_namespace< F (); What should I do to declare this two classes (first as noncopyable static const member class of second)? Is this feaseble?

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  • What is the difference between Inversion of Control and Dependency injection in C++?

    - by rlbond
    I've been reading recently about DI and IoC in C++. I am a little confused (even after reading related questions here on SO) and was hoping for some clarification. It seems to me that being familiar with the STL and Boost leads to use of dependency injection quite a bit. For example, let's say I made a function that found the mean of a range of numbers: template <typename Iter> double mean(Iter first, Iter last) { double sum = 0; size_t number = 0; while (first != last) { sum += *(first++); ++number; } return sum/number; }; Is this dependency injection? Inversion of control? Neither? Let's look at another example. We have a class: class Dice { public: typedef boost::mt19937 Engine; Dice(int num_dice, Engine& rng) : n_(num_dice), eng_(rng) {} int roll() { int sum = 0; for (int i = 0; i < num_dice; ++i) sum += boost::uniform_int<>(1,6)(eng_); return sum; } private: Engine& eng_; int n_; }; This seems like dependency injection. But is it inversion of control? Also, if I'm missing something, can someone help me out?

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  • How do I enforce the order of qmake library dependencies?

    - by James Oltmans
    I'm getting a lot of errors because qmake is improperly ordering the boost libraries I'm using. Here's what .pro file looks like QT += core gui TARGET = MyTarget TEMPLATE = app CONFIG += no_keywords \ link_pkgconfig SOURCES += file1.cpp \ file2.cpp \ file3.cpp PKGCONFIG += my_package \ sqlite3 LIBS += -lsqlite3 \ -lboost_signals \ -lboost_date_time HEADERS += file1.h\ file2.h\ file3.h FORMS += mainwindow.ui RESOURCES += Resources/resources.qrc This produces the following command: g++ -Wl,-O1 -o MyTarget file1.o file2.o file3.o moc_mainwindow.o -L/usr/lib/x86_64-linux-gnu -lboost_signals -lboost_date_time -L/usr/local/lib -lmylib1 -lmylib2 -lsqlite3 -lQtGui -lQtCore Note: mylib1 and mylib2 are statically compiled by another project, placed in /usr/local/lib with an appropriate pkg-config .pc file pointing there. The .pro file references them via my_package in PKGCONFIG. The problem is not with pkg-config's output but with Qt's ordering. Here's the .pc file: prefix=/usr/local exec_prefix=${prefix} libdir=${exec_prefix}/lib includedir=${prefix}/include Name: my_package Description: My component package Version: 0.1 URL: http://example.com Libs: -L${libdir} -lmylib1 -lmylib2 Cflags: -I${includedir}/my_package/ The linking stage fails spectacularly as mylib1 and mylib2 come up with a lot of undefined references to boost libraries that both the app and mylib1 and mylib2 are using. We have another build method using scons and it properly orders things for the linker. It's build command order is below. g++ -o MyTarget file1.o file2.o file3.o moc_mainwindow.o -L/usr/local/lib -lmylib1 -lmylib2 -lsqlite3 -lboost_signals -lboost_date_time -lQtGui -lQtCore Note that the principle difference is the order of the boost libs. Scons puts them at the end just before QtGui and QtCore while qmake puts them first. The other differences in the compile commands are unimportant as I have hand modified the qmake produced make file and the simple reordering fixed the problem. So my question is, how do I enforce the right order in my .pro file despite what qmake thinks they should be?

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  • Why do you need "extern C" for in C++ callbacks to C functions?

    - by Artyom
    Hello, I find such examples in Boost code. namespace boost { namespace { extern "C" void *thread_proxy(void *f) { .... } } // anonymous void thread::thread_start(...) { ... pthread_create(something,0,&thread_proxy,something_else); ... } } // boost Why do you actually need this extern "C"? It is clear that thread_proxy function is private internal and I do not expect that it would be mangled as "thread_proxy" because I actually do not need it mangled at all. In fact in all my code that I had written and that runs on may platforms I never used extern "C" and this had worked as-as with normal functions. Why extern "C" is added? My problem is that extern "C" function pollute global name-space and they do not actually hidden as author expects. This is not duplicate! I'm not talking about mangling and external linkage. It is obvious in this code that external linkage is unwanted!

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