R语言中dim函数_R语言函数使用总结

R语言函数使用总结​www.bioinfo.online

固定参数函数

f1 <- function(a,b=2){
    message(a,b)
    return(a+b) # 没有return返回最后一条语句
}
b <- f1(5) # 52
b # 7
f1(2,5) # 25
f1(b=2,a=5) # 52
f1(b=5,2) # 25

可变参数的函数

r自带函数 c(..., recursive = FALSE, use.names = TRUE)

f2 <- function(...){
  cat(..2) # 2
  dot_args = list(...)
  print(dot_args)
}
f2(1,2,3,4,5)

一切都是对象

操作符也是函数类型对象

1+2 # 3
"+"(1,2) # 3
`+`(1,2) # 3
'+'(1+2) # 3

'<-'(new_var,5)
new_var # 5

':'(1,5) # 1 2 3 4 5

'['(1:10,2) # 2

自定义运算符

'%ab2c%' <- function(a,b){
  sqrt(sum(a^2,b^2))
}
ab2c(3,4)
3 %ab2c% 4

'ab2c' <- function(a,b){
  sqrt(sum(a^2,b^2))
}
ab2c(3,4)
3 %ab2c% 4

ab2c <- function(a,b){
  sqrt(sum(a^2,b^2))
}
ab2c(3,4)
3 %ab2c% 4

---

5+2 # 7
"+" <- function(x,y){
  x*y
}
5+2 # 10

rm(`+`)
5+2 # 7

对于%>%的理解

library(purrr)
x <- c(1,1,2,2,8,5,9)
x %>% 
  unique() %>% 
  sort() 

# > 1 2 8 5 9

x <- unique(x)
x <- sort(x)

# > 1 2 8 5 9

泛型和多态

函数接受不同的对象有不同的结果‘

x <- seq(1,100,by=10)
y <- 2*x + 10
xy <- cbind(x,y)
class(xy) # matrix
plot(xy,
     xlim = c(1,100),
     ylim = c(0,230),
     type = "o",col="red") # figure 1

---

x <- seq(1,100,by=10)
y <- 2*x + 10
xy <- cbind(x,y)
my_model <- lm(y~x)
class(my_model) # lm
op <- par(mfrow = c(2,2))
plot(my_model) # figure 2
par(op)

figure 1

figure 2

自定义泛型函数

my_function <- function(x,y){
  message("I am interface")
  UseMethod("my_function",x) # 通过x标签类型确定执行函数
}
my_function.addXY <- function(x,y){
  return(x+y)
}
my_function.multiplyXY <- function(x,y){
  return(x*y)
}
my_function.default <- function(x,y){
  return(x-y)
}
x<-9
y<-5
my_function(x,y) # default 4
class(x) <- "addXY"
my_function(x,y) # addXY 14
class(x) <- "multiplyXY"
my_function(x,y) # multiplyXY 45

对于泛型函数"+"的理解

"+" 是有两个参数函数的操作

"+.onlyFirst" <- function(a,b){
  return(a[1]+b[1])
}
a <- 1:5
b <- 6:10
a+b # 7  9 11 13 15
"+"(a,b) # 7  9 11 13 15

class(a) <- "onlyFirst"
a+b # 7  
"+"(a,b) # 7

class(a) <- NULL
class(b) <- "onlyFirst"
a+b # 7  
"+"(a,b) # 7

class(a) <- "onlyFirst"
class(b) <- "onlyFirst"
a+b # 7  
"+"(a,b) # 7

R递归

fun1 <- function(s){
    message("before",s)
    if(s>0){
     fun1(s-1)
    }
    message("after",s)
}
fun1(5)

---

before5
  before4
    before3
      before2
        before1
          before0
          after0
        after1
      after2
    after3
  after4
after5

递归Fibonacci

fib <- function(n){
  if(n==1){
    return(1)
  }else{
    return(c(fib(n-1),sum(fib(n-1),n=2)))
  }
}
fib(10)

# > 1   3   6  12  24  48  96 192 384 768