C++11下的<random>与<cmath>

注：最近搞数据挖掘跟各种分布拟合、采样打交道，Matlab用着非常的爽，不过商业软件你懂得~~~本想C++调用.m未果，就只好.m调用.exe了，虽然实验挺顺的，但是想着这样不适合搞应用啊，就想找些第三方C++库来搞统计分布之类的东西，可搜“C++各大有名科学计算库”似乎GNU Scientific Library (linux)-GSL就够用的了，Boost中的math方法也不是很全，感觉与C++11中比较增加不是很多，以后的策略就是先看C++11中<cmath>及<random>中有没有，没有的话再调用GSL库。

安装g++ 4.7

g++ 4.7以上才支持C++11.
g++ 4.7要用-std=c++11来开启对C++11的支持，如

$$ g++ -std=c++11 hello.cpp -o hello

Ubuntu

Ubuntu 12.04 LTS默认g++版本是4.6（Ubuntu 13.04默认4.7）
以下方法来自这里,还有这个方法，但没试过

  • You can add the repository using

      $ sudo add-apt-repository ppa:ubuntu-toolchain-r/test

  • Then, to install it use

      $ sudo apt-get update
  $ sudo apt-get install g++-4.7

  • To change the default compiler use update-alternatives

      $ sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-4.6 60 --slave /usr/bin/g++ g++ /usr/bin/g++-4.6
  $ sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-4.7 40 --slave /usr/bin/g++ g++ /usr/bin/g++-4.7
  $ sudo update-alternatives --config gcc

Win7

下载MinGW最新版安装即可，可自行google之

C++11中的随机数及各种分布

首先要包含头文件 #include <random>

  • 均匀分布：
    • uniform_int_distribution 整数均匀分布
    • uniform_real_distribution 浮点数均匀分布
  • 伯努利类型分布：（仅有yes/no两种结果，概率一个p，一个1-p）
    • bernoulli_distribution 伯努利分布
    • binomial_distribution 二项分布
    • geometry_distribution 几何分布
    • negative_biomial_distribution 负二项分布
  • Rate-based distributions:
    • poisson_distribution 泊松分布
    • exponential_distribution 指数分布
    • gamma_distribution 伽马分布
    • weibull_distribution 威布尔分布
    • extreme_value_distribution 极值分布
  • 正态分布相关：
    • normal_distribution 正态分布
    • lognormal_distribution 对数正态分布
    • chi_squared_distribution 卡方分布
    • cauchy_distribution 柯西分布
    • fisher_f_distribution 费歇尔F分布
    • student_t_distribution t分布
  • 分段分布相关：
    • discrete_distribution 离散分布
    • piecewise_constant_distribution 分段常数分布
    • piecewise_linear_distribution 分段线性分布

<cmath>

<cmath>中包含计算Gamma函数的tgamma()与计算log-gamma的lgamma()（在C++11中添加的函数）

GSL

GSL Reference Manual

  • Introduction:
  • Using the library:
  • Error Handling:
  • Mathematical Functions:
  • Complex Numbers:
  • Polynomials:
  • Special Functions:
  • Vectors and Matrices:
  • Permutations:
  • Combinations:
  • Multisets:
  • Sorting:
  • BLAS Support:
  • Linear Algebra:
  • Eigensystems:
  • Fast Fourier Transforms:
  • Numerical Integration:
  • Random Number Generation:
  • Quasi-Random Sequences:
  • Random Number Distributions:
  • Statistics:
  • Histograms:
  • N-tuples:
  • Monte Carlo Integration:
  • Simulated Annealing:
  • Ordinary Differential Equations:
  • Interpolation:
  • Numerical Differentiation:
  • Chebyshev Approximations:
  • Series Acceleration:
  • Wavelet Transforms:
  • Discrete Hankel Transforms:
  • One dimensional Root-Finding:
  • One dimensional Minimization:
  • Multidimensional Root-Finding:
  • Multidimensional Minimization:
  • Least-Squares Fitting:
  • Nonlinear Least-Squares Fitting:
  • Basis Splines:
  • Physical Constants:
  • IEEE floating-point arithmetic:
  • Debugging Numerical Programs:
  • Contributors to GSL:
  • Autoconf Macros:
  • GSL CBLAS Library:
  • GNU General Public License:
  • GNU Free Documentation License:
  • Function Index:
  • Variable Index:
  • Type Index:
  • Concept Index:

Special Functions

  • Special Function Usage:
  • The gsl_sf_result struct:
  • Special Function Modes:
  • Airy Functions and Derivatives:
  • Bessel Functions:
  • Clausen Functions:
  • Coulomb Functions:
  • Coupling Coefficients:
  • Dawson Function:
  • Debye Functions:
  • Dilogarithm:
  • Elementary Operations:
  • Elliptic Integrals:
  • Elliptic Functions (Jacobi):
  • Error Functions:
  • Exponential Functions:
  • Exponential Integrals:
  • Fermi-Dirac Function:
  • Gamma and Beta Functions:
  • Gegenbauer Functions:
  • Hypergeometric Functions:
  • Laguerre Functions:
  • Lambert W Functions:
  • Legendre Functions and Spherical Harmonics:
  • Logarithm and Related Functions:
  • Mathieu Functions:
  • Power Function:
  • Psi (Digamma) Function:
  • Synchrotron Functions:
  • Transport Functions:
  • Trigonometric Functions:
  • Zeta Functions:
  • Special Functions Examples:
  • Special Functions References and Further Reading:

Random Number Distributions

  • Random Number Distribution Introduction:
  • The Gaussian Distribution:
  • The Gaussian Tail Distribution:
  • The Bivariate Gaussian Distribution:
  • The Exponential Distribution:
  • The Laplace Distribution:
  • The Exponential Power Distribution:
  • The Cauchy Distribution:
  • The Rayleigh Distribution:
  • The Rayleigh Tail Distribution:
  • The Landau Distribution:
  • The Levy alpha-Stable Distributions:
  • The Levy skew alpha-Stable Distribution:
  • The Gamma Distribution:
  • The Flat (Uniform) Distribution:
  • The Lognormal Distribution:
  • The Chi-squared Distribution:
  • The F-distribution:
  • The t-distribution:
  • The Beta Distribution:
  • The Logistic Distribution:
  • The Pareto Distribution:
  • Spherical Vector Distributions:
  • The Weibull Distribution:
  • The Type-1 Gumbel Distribution:
  • The Type-2 Gumbel Distribution:
  • The Dirichlet Distribution:
  • General Discrete Distributions:
  • The Poisson Distribution:
  • The Bernoulli Distribution:
  • The Binomial Distribution:
  • The Multinomial Distribution:
  • The Negative Binomial Distribution:
  • The Pascal Distribution:
  • The Geometric Distribution:
  • The Hypergeometric Distribution:
  • The Logarithmic Distribution:
  • Shuffling and Sampling:
  • Random Number Distribution Examples:
  • Random Number Distribution References and Further Reading:

References

[1] GNU Scientific Library – Reference Manual

[2] [C++11]随机数函数库random

[3] C++11 <random>

[4] C++11 <cmath>

Leequangang /
Published under (CC) BY-NC-SA

Categories :   tech  ·   Tags :   C++  ·   分布  ·   MinGW  ·   随机数  ·   math  ·  

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