rtnorm:抽样截断的单正态分布

# rtnorm Sampling truncated univ normal distribution. This repos contains python and matlab package for simulation of truncated normal random variables based upon the codes: [Vincent Mazet](http://miv.u-strasbg.fr/mazet/rtnorm/), and it built from the article [Fast simulation of trunacted Gaussian distributions](http://link.springer.com/article/10.1007%2Fs11222-009-9168-1) of [Niclos Chopin](https://sites.google.com/site/nicolaschopinstatistician/software). ## Python For python the requirements are: * scipy (will be removed) * NumPy * Cython * openmp (option can be turned off in setupy.py) pip -e 'git+https://git@github.com/JonasWallin/rtnorm.git#egg=rtnorm&subdirectory=python/rtnorm' To use the sampler: import rtnorm sampler = rtnorm.rtnorm() X = sampler(a = 1, b = 2, mu = 3, sigma = 4) Or with vectors: import rtnorm import numpy as np X = sampler( a = np.zeros((4,)), b = np.random.rand(4) ) ## Matlab For matlab: make should install the make mex files link to the directory with addpath. Run matlab code with: x = rtnorm(a, b, mu, sigma); where a,b,mu, and sigma are vectors ###TODO: 1. setup test case in python (done) 2. setup speed test in python (done) 3. modify the code so it sutiable for vector versions (done) 4. Write the probability so we can test more advanced 5. Matlab version (done) 7. test on the amzaon cluster (done)