Question

以下源代码来自一本书。我写评论是为了更好地理解代码。

describe('window.foo', () => {
  afterEach(() => {
    delete global.foo // make sure you clean your global object after each test
  })

  it('should be called twice', () => {
    const fooSpy = jest.fn();
    const barSpy = jest.fn();
    Object.defineProperty(global, 'foo', {
      configurable: true, // very important or else you can't delete
      get() {
        fooSpy(); //we manually call our spy so we can assert later

        // and we return an object with another spy for our bar function
        return { bar: barSpy};
      }
    });

    if (global.foo) {
      global.foo.bar()
    }


    expect(fooSpy).toHaveBeenCalledTimes(2);
    expect(barSpy).toHaveBeenCalledTimes(1);
  });

  it('should be called once', () => {
    const fooSpy = jest.fn();
    Object.defineProperty(global, 'foo', {
      writconfigurableable: true,
      get() {
        fooSpy(); // we trigger the spy manually

        // we return undefined
        return undefined;
      }
    });

    if (global.foo) {
      global.foo.bar()
    }


    expect(fooSpy).toHaveBeenCalledTimes(1);
  });
});

我对这个源代码有些困惑。

为什么#================================================================== # markov(init,mat,n,states) = Simulates n steps of a Markov chain #------------------------------------------------------------------ # init = initial distribution # mat = transition matrix # labels = a character vector of states used as label of data-frame; # default is 1, .... k #------------------------------------------------------------------- markov <- function(init,mat,n,labels) { if (missing(labels)) # check if 'labels' argument is missing { labels <- 1:length(init) # obtain the length of init-vecor, and number them accordingly. } simlist <- numeric(n+1) # create an empty vector of 0's states <- 1:length(init)# ???? use the length of initial distribution to generate states. simlist[1] <- sample(states,1,prob=init) # sample function returns a random permutation of a vector. # select one value from the 'states' based on 'init' probabilities. for (i in 2:(n+1)) { simlist[i] <- sample(states, 1, prob = mat[simlist[i-1],]) # simlist is a vector. # so, it is selecting all the columns # of a specific row from 'mat' } labels[simlist] } #==================================================================用于生成状态？如果状态如 S = {-1，0，1，2，...} 该怎么办？

Answer 1

S的确切标签由输入标签表示。

状态用作索引，在最后一行中，从1到states <- 1:length(init)的状态的simlist被用作索引以提取正确的标签。

了解R中的马尔可夫链源代码

1 个答案: