c++ - 在 .h 文件中声明正态分布生成器-6ren

c++ - 在 .h 文件中声明正态分布生成器

转载作者：塔克拉玛干更新时间：2023-11-03 07:42:32

我有一个成员函数，我想生成大量高斯分布的随机数，但我不想在每次调用该函数时都初始化随机数生成器，认为这样会更慢。我想我可以在 .h 文件中声明随机数生成器并在构造函数中对其进行初始化，但我不确定执行此操作的语法，甚至不确定它是否有效。另外，我不确定这是否确实有必要节省计算时间。

换句话说，我想在 .h 文件中创建一个 std::normal_distribution 生成器，而不指定参数。声明它的标准方法是

std::default_random_engine generator;

std::normal_distribution<double> distribution1(mu, sigma);

但是，我不确定这是否适用于 .h 文件，因为这实际上实例化了类。我在想也许我应该声明一个指向正态分布对象的指针，或者类似的东西，但我不确定这个的正确语法。我想要某种形式的东西

class my_rand{
   my_rand(double, double);
   std::default_random_engine generator;
   std::normal_distribution<double> distribution;
   double return_rand();
}

my_rand::my_rand(double mu, double sigma){
   distribution.param(mu,sigma);
}

double my_rand::return_rand(){
   return distribution(generator);
}

最佳答案

几年前，我编写了几个类来封装标准的随机生成器和分布类。这是我的类(class)的样子:有几种方法可以为生成器和不同的生成器提供种子；类 RandomEngine 和 RandomDistribution 无缝地一起工作，因为它们只是包装类中的静态方法。在类之后还有 typedefs 以减少输入量:分别是 RE 和 RD。

随机生成器.h

#ifndef RANDOM_GENERATOR_H
#define RANDOM_GENERATOR_H

#include <limits>
#include <chrono>
#include <random>

class RandomEngine {
public:
    using Clock = std::conditional_t<std::chrono::high_resolution_clock::is_steady,
        std::chrono::high_resolution_clock,
        std::chrono::steady_clock>;

    // Used To Determine Which Seeding Process To Use
    enum SeedType {
        USE_CHRONO_CLOCK,
        USE_RANDOM_DEVICE,
        USE_SEED_VALUE, 
        USE_SEED_SEQ,
    }; // SeedType

    // This Enum Is Not In Use - It Is A Visual Reference Only; But If User Wants To
    // Use It For Their Own Pupose They Are Free To Do So.
    enum EngineType {
        // Default Random Engine
        DEFAULT_RANDOM_ENGINE,

        // Linear Congruential Engines
        MINSTD_RAND0,
        MINSTD_RAND,

        // Mersenne Twister Engines 
        MT19937,
        MT19937_64,

        // Subtract With Carry Engines 
        RANLUX24_BASE,
        RANLUX48_BASE,

        // Discard Block Engines 
        RANLUX24,
        RANLUX48,

        // Shuffle Order Engines
        KNUTH_B,

    }; // EngineType

protected:
    RandomEngine(){}

    // Internal Helper Function  
    // ---------------------------------------------------------------------------
    // getRandomDevice()
    static std::random_device& getRandomDevice() {
        static std::random_device device{};
        return device;
    } // getRandomDevice

public:
    // ---------------------------------------------------------------------------
    // getTimeNow()
    static unsigned int getTimeNow() {
        unsigned int now = static_cast<unsigned int>(Clock::now().time_since_epoch().count());
        return now;
    } // getTimeNow

    // ---------------------------------------------------------------------------
    // getDefaultRandomEngine()
    static std::default_random_engine& getDefaultRandomEngine( SeedType type, unsigned seedValue = 0, std::seed_seq& seq = std::seed_seq{} ) {
        static std::default_random_engine engine{};

        switch ( type ) {
            case USE_CHRONO_CLOCK: {
                engine.seed( getTimeNow() );
                break;
            }
            case USE_SEED_VALUE: {
                engine.seed( seedValue );
                break;
            }
            case USE_SEED_SEQ: {
                engine.seed( seq );
                break;
            }
            default: {
                engine.seed( getRandomDevice()() );
                break;
            }
        }

        return engine;
    } // getDefaultRandomEngine

    // ---------------------------------------------------------------------------
    // getMinStd_Rand0()
    static std::minstd_rand0& getMinStd_Rand0( SeedType type, unsigned seedValue = 0, std::seed_seq& seq = std::seed_seq{} ) {
        static std::minstd_rand0 engine{};

        switch ( type ) {
            case USE_CHRONO_CLOCK: {
                engine.seed( getTimeNow() );
                break;
            }
            case USE_SEED_VALUE: {
                engine.seed( seedValue );
                break;
            }
            case USE_SEED_SEQ: {
                engine.seed( seq );
                break;
            }
            default: {
                engine.seed( getRandomDevice()() );
                break;
            }
        }

        return engine;
    } // getMinStd_Rand0

    // ---------------------------------------------------------------------------
    // getMinStd_Rand()
    static std::minstd_rand& getMinStd_Rand( SeedType type, unsigned seedValue = 0, std::seed_seq& seq = std::seed_seq{} ) {
        static std::minstd_rand engine{};

        switch( type ) {
            case USE_CHRONO_CLOCK: {
                engine.seed( getTimeNow() );
                break;
            }
            case USE_SEED_VALUE: {
                engine.seed( seedValue );
                break;
            }
            case USE_SEED_SEQ: {
                engine.seed(seq);
                break;
            }
            default: {
                engine.seed( getRandomDevice()() );
                break;
            }
        }

        return engine;
    } // getMinStd_Rand

    // ---------------------------------------------------------------------------
    // getMt19937()
    static std::mt19937& getMt19937( SeedType type, unsigned seedValue = 0, std::seed_seq& seq = std::seed_seq{} ) {
        static std::mt19937 engine{};

        switch ( type ) {
            case USE_CHRONO_CLOCK: {
                engine.seed( getTimeNow() );
                break;
            }
            case USE_SEED_VALUE: {
                engine.seed( seedValue );
                break;
            }
            case USE_SEED_SEQ: {
                engine.seed( seq );
                break;
            }
            default: {
                engine.seed( getRandomDevice()() );
                break;
            }
        }

        return engine;
    } //getMt19937

    // ---------------------------------------------------------------------------
    // getMt19937_64()
    static std::mt19937_64& getMt19937_64( SeedType type, unsigned seedValue = 0, std::seed_seq& seq = std::seed_seq{} ) {
        static std::mt19937_64 engine{};

        switch ( type ) {
            case USE_CHRONO_CLOCK: {
                engine.seed( getTimeNow() );
                break;
            }
            case USE_SEED_VALUE: {
                engine.seed( seedValue );
                break;
            }
            case USE_SEED_SEQ: {
                engine.seed( seq );
                break;
            }
            default: {
                engine.seed( getRandomDevice()() );
                break;
            }
        }

        return engine;
    } // getMt19937_64

    // ---------------------------------------------------------------------------
    // getRanLux24_base()
    static std::ranlux24_base& getRanLux24_base( SeedType type, unsigned seedValue = 0, std::seed_seq& seq = std::seed_seq{} ) {
        static std::ranlux24_base engine{};

        switch ( type ) {
            case USE_CHRONO_CLOCK: {
                engine.seed( getTimeNow() );
                break;
            }
            case USE_SEED_VALUE: {
                engine.seed( seedValue );
                break;
            }
            case USE_SEED_SEQ: {
                engine.seed( seq );
                break;
            }
            default: {
                engine.seed( getRandomDevice()() );
                break;
            }
        }

        return engine;
    } // getRanLux24_base

    // ---------------------------------------------------------------------------
    // getRanLux48_base()
    static std::ranlux48_base& getRanLux48_base( SeedType type, unsigned seedValue = 0, std::seed_seq& seq = std::seed_seq{} ) {
        static std::ranlux48_base engine{};

        switch ( type ) {
            case USE_CHRONO_CLOCK: {
                engine.seed( getTimeNow() );
                break;
            }
            case USE_SEED_VALUE: {
                engine.seed( seedValue );
                break;
            }
            case USE_SEED_SEQ: {
                engine.seed( seq );
                break;
            }
            default: {
                engine.seed( getRandomDevice()() );
                break;
            }
        }

        return engine;
    } // getRanLux48_base

    // ---------------------------------------------------------------------------
    // getRanLux24()
    static std::ranlux24& getRanLux24( SeedType type, unsigned seedValue = 0, std::seed_seq& seq = std::seed_seq{} ) {
        static std::ranlux24 engine{};

        switch ( type ) {
            case USE_CHRONO_CLOCK: {
                engine.seed( getTimeNow() );
                break;
            }
            case USE_SEED_VALUE: {
                engine.seed( seedValue );
                break;
            }
            case USE_SEED_SEQ: {
                engine.seed( seq );
                break;
            }
            default: {
                engine.seed( getRandomDevice()() );
                break;
            }
        }

        return engine;
    } // getRanLux24

    // ---------------------------------------------------------------------------
    // getRanLux48()
    static std::ranlux48& getRanLux48( SeedType type, unsigned seedValue = 0, std::seed_seq& seq = std::seed_seq{} ) {
        static std::ranlux48 engine{};

        switch ( type ) {
            case USE_CHRONO_CLOCK: {
                engine.seed( getTimeNow() );
                break;
            }
            case USE_SEED_VALUE: {
                engine.seed( seedValue );
                break;
            }
            case USE_SEED_SEQ: {
                engine.seed( seq );
                break;
            }
            default: {
                engine.seed( getRandomDevice()() );
                break;
            }
        }

        return engine;
    } //getRanLux48

}; // RandomEngine

class RandomDistribution {
public:
    // This Enum Is Not In Use - It Is A Visual Reference Only; But If User Wants To
    // Use It For Their Own Pupose They Are Free To Do So.
    enum DistributionType {
        // Uniform Distributions
        UNIFORM_INT,
        UNIFORM_INT_DISTRIBUTION,
        UNIFORM_REAL,
        UNIFORM_REAL_DISTRIBUTION,
        // GENERATE_CANONICAL, - This is a function template and not a class template use it directly form std:: <random> c++11

        // Bernoulli Distributions
        BERNOULLI_DISTRIBUTION,
        BINOMAIL_DISTRIBUTION,
        NEGATIVE_BINOMIAL_DISTRIBUTION,
        GEOMETRIC_DISTRIBUTION,

        // Poisson Distributions
        POISSON_DISTRIBUTION,
        EXPONENTIAL_DISTRIBUTION,
        GAMMA_DISTRIBUTION,
        WEIBULL_DISTRIBUTION,
        EXTREME_VALUE_DISTRIBUTION,

        // Normal Distributions
        NORMAL_DISTRIBUTION,
        LOGNORMAL_DISTRIBUTION,
        CHI_SQUARED_DISTRIBUTION,
        CAUCHY_DISTRIBUTION,
        FISHER_F_DISTRIBUTION,
        STUDENT_T_DISTRIBUTION,

        // Sampling Distributions
        DISCRETE_DISTRIBUTION,
        PIECEWISE_CONSTANT_DISTRIBUTION,
        PIECEWISE_LINEAR_DISTRIBUTION
    }; // DistributionType

protected:
    RandomDistribution(){}

public:

    // UNIFORM DISTRIBUTIONS

    // ---------------------------------------------------------------------------
    // getUniformIntDistribution()
    template<class IntType = int>
    static std::uniform_int_distribution<IntType>& getUniformIntDistribution( IntType lowerBound = 0, IntType upperBound = (std::numeric_limits<IntType>::max)() ) {
        static std::uniform_int_distribution<IntType> dist( lowerBound, upperBound );
        return dist;
    } // getUniformIntDistribution

    // ---------------------------------------------------------------------------
    // getUniformRealDistribution()
    template<class RealType = double>
    static std::uniform_real_distribution<RealType>& getUniformRealDistribution( RealType lowerBound = 0.0, RealType upperBound = 1.0 ) {
        static std::uniform_real_distribution<RealType> dist( lowerBound, upperBound );
        return dist;
    } // getUniformRealDistribution



    // BERNOULLI DISTRIBUTIONS

    // ---------------------------------------------------------------------------
    // getBernoulliDistribution()
    static std::bernoulli_distribution& getBernoulliDistribution( double probability = 0.5 ) {
        static std::bernoulli_distribution dist( probability );
        return dist;
    } // getBernoulliDistribution

    // ---------------------------------------------------------------------------
    // getBinomialDistribution()
    template<class IntType = int>
    static std::binomial_distribution<IntType>& getBinomialDistribution( IntType numTrials = 1, double probability = 0.5 ) {
        static std::binomial_distribution<IntType> dist( numTrials, probability );
        return dist;
    } // getBinomialDistribution

    // ---------------------------------------------------------------------------
    // getNegativeBinomialDistribution()
    template<class IntType = int>
    static std::negative_binomial_distribution<IntType>& getNegativeBinomialDistribution( IntType numTrialFailures = 1, double probability = 0.5 ) {
        static std::negative_binomial_distribution<IntType> dist( numTrialFailures, probability );
        return dist;
    } // getNegativeBinomialDistribution

    // ---------------------------------------------------------------------------
    // getGeometricDistribution()
    template<class IntType = int>
    static std::geometric_distribution<IntType>& getGeometricDistribution( double probability = 0.5 ) {
        static std::geometric_distribution<IntType> dist( probability ); 
        return dist;
    } // getGeometricDistribution



    // POISSON DISTRIBUTIONS

    // ---------------------------------------------------------------------------
    // getPoissonDistribution()
    template<class IntType = int>
    static std::poisson_distribution<IntType>& getPoissonDistribution( double mean = 1.0 ) {
        static std::poisson_distribution<IntType> dist( mean );
        return dist;
    } // getPoissonDistribution

    // ---------------------------------------------------------------------------
    // getExponentialDistribution()
    template<class RealType = double>
    static std::exponential_distribution<RealType>& getExponentialDistribution( RealType rate = 1.0 ) {
        static std::exponential_distribution<RealType> dist( rate );
        return dist;
    } // getExponentialDistribution

    // ---------------------------------------------------------------------------
    // getGammDistribution()
    template<class RealType = double>
    static std::gamma_distribution<RealType>& getGammaDistribution( RealType alpha_shape = 1.0, RealType beta_scale = 1.0 ) {
        static std::gamma_distribution<RealType> dist( alpha_shape, beta_scale );
        return dist;
    } // getGammaDistribution

    // ---------------------------------------------------------------------------
    // getWeibullDistribution()
    template<class RealType = double>
    static std::weibull_distribution<RealType>& getWeibullDistribution( RealType alpha_shape = 1.0, RealType beta_scale = 1.0 ) {
        static std::weibull_distribution<RealType> dist( alpha_shape, beta_scale );
        return dist;
    } // getWeibullDistribution

    // ---------------------------------------------------------------------------
    // getExtremeValueDistribution()
    template<class RealType = double>
    static std::extreme_value_distribution<RealType>& getExtremeValueDistribution( RealType location = 0.0, RealType scale = 1.0 ) {
        static std::extreme_value_distribution<RealType> dist( location, scale );
        return dist;
    } // getExtremeValueDistribution


    // NORMAL DISTRIBUTIONS

    // ---------------------------------------------------------------------------
    // getNormalDistribution()
    template<class RealType = double>
    static std::normal_distribution<RealType>& getNormalDistribution( RealType mean = 0.0, RealType stddev = 1.0 ) {
        static std::normal_distribution<RealType> dist( mean, stddev );
        return dist;
    } // getNormaDistribution

    // ---------------------------------------------------------------------------
    // getLogNormalDistribution()
    template<class RealType = double>
    static std::lognormal_distribution<RealType>& getLogNormalDistribution( RealType logScale = 0.0, RealType shape = 1.0 ) {
        static std::lognormal_distribution<RealType> dist( logScale, shape );
        return dist;
    } // getLogNormalDistribution

    // ---------------------------------------------------------------------------
    // getChiSquaredDistribution()
    template<class RealType = double>
    static std::chi_squared_distribution<RealType>& getChiSquaredDistribution( RealType degreesOfFreedom = 1.0 ) {
        static std::chi_squared_distribution<RealType> dist( degreesOfFreedom );
        return dist;
    } // getChiSquaredDistribution

    // ---------------------------------------------------------------------------
    // getCauchyDistribution()
    template<class RealType = double>
    static std::cauchy_distribution<RealType>& getCauchyDistribution( RealType location = 0.0, RealType scale = 1.0 ) {
        static std::cauchy_distribution<RealType> dist( location, scale );
        return dist;
    } // getCauchyDistribution

    // ---------------------------------------------------------------------------
    // getFisherFDistribution() Both m,n are degress of freedom
    template<class RealType = double>
    static std::fisher_f_distribution<RealType>& getFisherFDistribution( RealType m = 1.0, RealType n = 1.0 ) {
        static std::fisher_f_distribution<RealType> dist( m, n );
        return dist;
    } // getFisherFDistribution

    // ---------------------------------------------------------------------------
    // getStudentTDistribution()
    template<class RealType = double>
    static std::student_t_distribution<RealType>& getStudentTDistribution( RealType degreesOfFreedom = 1.0 ) {
        static std::student_t_distribution<RealType> dist( degreesOfFreedom );
        return dist;
    } // getStudentTDistribution


    // SAMPLING DISTRIBUTIONS

    // ---------------------------------------------------------------------------
    //  getDiscreteDistribution()
    template<class IntType = int>
    static std::discrete_distribution<IntType>& getDiscreteDistribution() {
        static std::discrete_distribution<IntType> dist;
        return dist;
    } // getDiscreteDistribution

    // ---------------------------------------------------------------------------
    //  getDiscreteDistribution()
    template<class IntType = int, class InputIt>
    static std::discrete_distribution<IntType>& getDiscreteDistribution( InputIt first, InputIt last ) {
        static std::discrete_distribution<IntType> dist( first, last );
        return dist;
    } // getDiscreteDistribution

    // ---------------------------------------------------------------------------
    //  getDiscreteDistribution()
    template<class IntType = int>
    static std::discrete_distribution<IntType>& getDiscreteDistribution( std::initializer_list<double> weights ) {
        static std::discrete_distribution<IntType> dist( weights );
        return dist;
    } // getDiscreteDistribution

    // ---------------------------------------------------------------------------
    //  getDiscreteDistribution()
    template<class IntType = int, class UnaryOperation>
    static std::discrete_distribution<IntType>& getDiscreteDistribution( std::size_t count, double xmin, double xmax, UnaryOperation unary_op ) {
        static std::discrete_distribution<IntType> dist( count, xmin, xmax, unary_op );
        return dist;
    } // getDiscreteDistribution

    // ---------------------------------------------------------------------------
    // getPiecewiseConstantDistribution()
    template<class RealType = double>
    static std::piecewise_constant_distribution<RealType>& getPiecewiseConstantDistribution() {
        static std::piecewise_constant_distribution<RealType> dist;
        return dist;
    } // getPiecewiseConstantDistribution

    // ---------------------------------------------------------------------------
    // getPiecewiseConstantDistribution()
    template<class RealType = double, class InputIt1, class InputIt2>
    static std::piecewise_constant_distribution<RealType>& getPiecewiseConstantDistribution( InputIt1 first_i, InputIt1 last_i, InputIt2 first_w ) {
        static std::piecewise_constant_distribution<RealType> dist( first_i, last_i, first_w );
        return dist;
    } // getPiecewiseConstantDistribution

    // ---------------------------------------------------------------------------
    // getPiecewiseConstantDistribution()
    template<class RealType = double, class UnaryOperation>
    static std::piecewise_constant_distribution<RealType>& getPiecewiseConstantDistribution( std::initializer_list<RealType> bl, UnaryOperation fw ) {
        static std::piecewise_constant_distribution<RealType> dist( bl, fw );
        return dist;
    } // getPiecewiseConstantDistribution

    // ---------------------------------------------------------------------------
    // getPiecewiseConstantDistribution()
    template<class RealType = double, class UnaryOperation>
    static std::piecewise_constant_distribution<RealType>& getPiecewiseConstantDistribution( std::size_t nw, RealType xmin, RealType xmax, UnaryOperation fw ) {
        static std::piecewise_constant_distribution<RealType> dist( nw, xmin, xmax, fw );
        return dist;
    } // getPiecewiseConstantDistribution

    // ---------------------------------------------------------------------------
    // getPiecewiseLinearDistribution()
    template<class RealType = double>
    static std::piecewise_linear_distribution<RealType>& getPiecewiseLinearDistribution() {
        static std::piecewise_linear_distribution<RealType> dist;
        return dist;
    } // getPiecewiseLinearDistribution

    // ---------------------------------------------------------------------------
    // getPiecewiseLinearDistribution()
    template<class RealType = double, class InputIt1, class InputIt2>
    static std::piecewise_linear_distribution<RealType>& getPiecewiseLinearDistribution( InputIt1 first_i, InputIt1 last_i, InputIt2 first_w ) {
        static std::piecewise_linear_distribution<RealType> dist( first_i, last_i, first_w );
        return dist;
    } // getPiecewiseLinearDistribution

    // ---------------------------------------------------------------------------
    // getPiecewiseLinearDistribution()
    template<class RealType = double, class UnaryOperation>
    static std::piecewise_linear_distribution<RealType>& getPiecewiseLinearDistribution( std::initializer_list<RealType> bl, UnaryOperation fw ) {
        static std::piecewise_linear_distribution<RealType> dist( bl, fw );
        return dist;
    } // getPiecewiseLinearDistribution

    // ---------------------------------------------------------------------------
    // getPiecewiseLinearDistribution()
    template<class RealType = double, class UnaryOperation>
    static std::piecewise_linear_distribution<RealType>& getPiecewiseLinearDistribution( std::size_t nw, RealType xmin, RealType xmax, UnaryOperation fw ) {
        static std::piecewise_linear_distribution<RealType> dist( nw, xmin, xmax, fw );
        return dist;
    } // getPiecewiseLinearDistribution

}; // RandomDistribution

typedef RandomEngine RE;
typedef RandomDistribution RD;

#endif // RANDOM_GENERATOR_H

这是我上面的类的一次使用。如何使用它们也有多种选择。

main.cpp

// #include "Logger.h"
#include "RandomGenerator.h"
#include <isotream>
#include <sstream>

// ----------------------------------------------------------------------------
// main()
int main() {    
    // Logger log( "log.txt" );

    std::ostringstream strStream;
    strStream << "Random number generated Between [1,9] using default random engine & uniform int distribution is: " << std::endl;
    //Logger::log( strStream, Logger::TYPE_CONSOLE );
    std::cout << strStream.str();

    std::uniform_int_distribution<unsigned> uid = RD::getUniformIntDistribution<unsigned>(1, 9);
    // std::uniform_int_distribution<unsigned> uid( 1, 9 );
    for ( unsigned int i = 1; i < 101; i++ ) {
        std::ostringstream strStream;
        unsigned val = uid( RE::getDefaultRandomEngine( RE::SeedType::USE_CHRONO_CLOCK, 14 ) );

        strStream << i << " : " << val << std::endl;
        //Logger::log( strStream, Logger::TYPE_CONSOLE );
        std::cout << strStream.str();
    }

    std::cout << "\n";

    for ( unsigned int i = 1; i < 101; i++ ) {
        std::ostringstream strStream;
        // Using the same distribution above but reseeding it with a different type of seeding method.
        unsigned val = uid( RE::getDefaultRandomEngine( RE::SeedType::USE_RANDOM_DEVICE ) );

        strStream << i << " : " << val << std::endl;
        // Logger::log( strStream, Logger::TYPE_CONSOLE );
        std::cout << strStream.str();
    }

    return 0;
} // main

我注释掉了属于我的记录器类的代码行，并将其替换为一个简单的 std::cout 调用。目前的设计方式是您只需创建一个分布类型的本地实例或成员实例，因为不需要创建实际随机引擎的本地实例code> 或 Seeding 对象，因为这一切都在静态存储中工作。我希望这对您有所帮助，因为它相当有效。

编辑 -- 这是另一个使用 Mersenne Twister 的示例，其真实分布在 [0,1] 之间，其中 50 个示例使用计时时钟播种:

int main() {

    std::ostringstream strStream;
    strStream << "Random number generated between [0.0, 1.0] \nusing mersenne & chrono clock for seeding:\n";
    std::cout << strStream.str();

    std::uniform_real_distribution<double> urd = RD::getUniformRealDistribution<double>( 0.0, 1.0 );
    for ( unsigned i = 1; i <= 50; i++ ) {
        std::ostringstream strStream;
        double val = urd( RE::getMt19937( RE::SeedType::USE_CHRONO_CLOCK, 12 ) );
        strStream << i << " : " << val << "\n";
        std::cout << strStream.str();
    }

    return 0;
}

关于c++ - 在 .h 文件中声明正态分布生成器，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/46799778/

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c# - 通过网络在 C/C++ 服务器、C/C++ 和 C# 客户端之间发送数据结构
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我在 C# 中有以下函数: public Matrix ConcatDescriptors(IList> descriptors) { int cols = descriptors[0].Co
c++ - C/C++ - 对其他人隐藏 C 或 C++ 函数代码
我有一个项目要编写一个函数来对某些数据执行某些操作。我可以用 C/C++ 编写代码，但我不想与雇主共享该函数的代码。相反，我只想让他有权在他自己的代码中调用该函数。是否可以？我想到了这两种方法 - 在
c# - 在托管代码(C++、C、C++/CLI、C#)中使用非托管代码时处理错误
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c# - C#、C/C++ 或 Objective-C 中的眼动追踪库
关闭。这个问题不符合Stack Overflow guidelines .它目前不接受答案。我们不允许提问寻求书籍、工具、软件库等的推荐。您可以编辑问题，以便用事实和引用来回答。关闭 7 年前。
c++ - C/C++/Objective-C 文本识别库
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c# - 将 C/C++ 函数导入 C#
我有一些 C 代码，将使用 P/Invoke 从 C# 调用。我正在尝试为这个 C 函数定义一个 C# 等效项。 SomeData* DoSomething(); struct SomeData {
c - C语言中 "c -= --c - c++;"的结果应该是什么？
这个问题已经有答案了: Why are these constructs using pre and post-increment undefined behavior? (14 个回答) 已关闭 6

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c++ - 在 .h 文件中声明正态分布生成器