R control structure types

• conditional execution
  • if(condition){expression1} else{expression2}
  • ifelse(condition, expression1, expression2)
• loops
  • repeat{ statements }
  • while(condition){ statements }
  • for(index in object){ statements }
  • (i)break: The keyword break breaks at once and exits from the loop.
  • (ii)next: The keyword next jumps to the start of the next iteration in the loop
• apply family
  • apply(): applying functions on matrices or arrays
  • lapply()
  • sapply()
  • tapply()

apply family

apply

对数组或者矩阵的一个维度使用函数生成值得到列表, 数组或者向量

apply(X, MARGIN, FUN, ...)

  X: an array, including a matrix
  MARGIN: 1 (rows), 2 (columns), c(1, 2) (rows and columns)    
  FUN: Functions

计算按照行(1)或列(2)的方式进行。
如果apply函数命令应用到矩阵的每一个与元素上时，函数的运算顺序为：从第一列第一个数值到第一列最后一个数值，再从第一列到最后一列的顺序。请小伙伴们注意，这是函数的运算顺序。运算之后我们有了对矩阵全部数据的运算结果，结果排序为：当向量值为1的时候，每一列的运算结果变成新的一行，即第一列的运算结果变为第一行，第二列的运算结果变为第二行，以此类推直到最后一列的运算结果变为最后一行。

m <- matrix(1:16, nrow = 4)
apply(m, 1, sqrt)

##          [,1]     [,2]     [,3]     [,4]
## [1,] 1.000000 1.414214 1.732051 2.000000
## [2,] 2.236068 2.449490 2.645751 2.828427
## [3,] 3.000000 3.162278 3.316625 3.464102
## [4,] 3.605551 3.741657 3.872983 4.000000

apply(m, 2, sqrt)

##          [,1]     [,2]     [,3]     [,4]
## [1,] 1.000000 2.236068 3.000000 3.605551
## [2,] 1.414214 2.449490 3.162278 3.741657
## [3,] 1.732051 2.645751 3.316625 3.872983
## [4,] 2.000000 2.828427 3.464102 4.000000

lapply

通过对x的每一个元素运用函数，生成一个与元素个数相同的值列表

sapply

是lapply 函数的包装版, 该函数返回结果是向量或者矩阵, 如果simplify=”array”, 且合适的情况下, 将会通过 simplify2array() 函数转换为阵列

ifelse

ifelse() can be nested in many ways:

ifelse(<condition>, <yes>, <no>)         

ifelse(<condition>, <yes>, ifelse(<condition>, <yes>, <no>))

ifelse(<condition>, ifelse(<condition>, <yes>, <no>), <no>)

ifelse(<condition>, 
       ifelse(<condition>, <yes>, <no>), 
       ifelse(<condition>, <yes>, <no>)
      )

ifelse(<condition>, <yes>, 
       ifelse(<condition>, <yes>, 
              ifelse(<condition>, <yes>, <no>)
             )
       )