使用 purrr::partial() 创建函数工厂时如何打印函数的输入

Question

我正在玩 purrr 的

map()

和

partial()

并想尝试创建一个具有预配置输入的函数列表，当我使用这些函数时，它将返回函数输出 AND 打印出函数的配置（也作为验证检查，以确保我已正确配置该功能）

我已经使用预配置的输入设置了每个功能，没有任何问题，但我无法让它向输入发送消息。

library(tidyverse)

#arbitrary sequence

n_vec <- seq(5,100,5)
mean_vec <- seq(50,1000,50)

# create list of functions that are pre-configured with various inputs

rnorm_lst <- map2(
  .x=n_vec
  ,.y=mean_vec
  ,.f=\(.x,.y){

# When I use a function, I want it to message its input assumptions

    print(.x)
    print(.y)
    
# this is the underlying function that I want to create with partial
   out <-  partial(rnorm,n=.x,mean=.y)
   
   return(out)
   
  }
)

# create a name based on its configuration
names_lst <- paste0("n",n_vec,"_","mean",mean_vec)

# assign a name to each function

names(rnorm_lst) <- names_lst

# call a function to see if it works

rnorm_lst$n50_mean500()

此功能的

rnorm()

方面有效，但它不会打印或发送其输入消息。

我认为这与环境有关？但我不确定。

Answer 1

print(.x)

和

print(.y)

是在定义

rnorm_list

期间执行的，而不是在函数执行期间执行的。

我将

print()

移入新函数的定义中，然后将其输入到

partial()

:

library(purrr)
#> 
#> Attaching package: 'purrr'
#> The following object is masked from 'package:base':
#> 
#>     %||%

n_vec <- seq(5,100,5)
mean_vec <- seq(50,1000,50)

# create list of functions that are pre-configured with various inputs

rnorm_lst <- map2(
                  .x=n_vec
                  ,.y=mean_vec
                  ,.f=\(.x,.y){

                      # this is the underlying function that I want to create with partial
                      new <-  function(...) {
                          # When I use a function, I want it to message its input assumptions

                          print(.x)
                          print(.y)

                          rnorm(...) 
                      }

                      return(partial(new, n = .x, mean = .y))
                  }
)

# create a name based on its configuration
names_lst <- paste0("n",n_vec,"_","mean",mean_vec)

# assign a name to each function

names(rnorm_lst) <- names_lst

# call a function to see if it works

rnorm_lst$n50_mean500()
#> [1] 50
#> [1] 500
#>  [1] 499.7868 500.5834 500.0835 500.7119 500.0949 498.2750 498.4815 498.7130
#>  [9] 499.7779 500.8300 500.8086 498.2535 500.4854 498.6614 501.3506 501.5732
#> [17] 500.3742 500.5254 499.3777 498.4927 499.7738 500.9925 499.4880 499.0919
#> [25] 500.4387 499.7716 500.7130 498.2386 500.1190 499.8829 499.2836 499.4103
#> [33] 499.5191 499.9471 499.8817 500.2749 499.9995 499.4147 500.4018 498.9776
#> [41] 499.6448 500.0447 500.4869 500.0282 499.4247 500.2372 500.5241 500.1198
#> [49] 500.4847 500.1996

^{创建于 2024-05-19，使用 reprex v2.1.0}