将一个列表的列表转换为不同排列的列表，以供pmap使用。

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英文:

Transform a list of lists into a differently arranged list of lists to use for pmap

问题

Sure, here's the translated content:

我一直在努力使pmap()正常工作，并误解了我应该提供给它的列表的结构。

基本上，我最终得到了一个列表的列表，名为before，但它的排列方式不正确，无法用于pmap。

以下是一个最小化的可重现示例：

  1. before <- list(
  2.   list(
  3.     tibble(a = c(10:13), b = c(13:16), c = c(17:20)),
  4.     tibble(d = c(10:13), e = c(13:16)),
  5.     tibble(f = c(10:13))
  6.   ),
  7.   list(
  8.     tibble(a = c(10:13), b = c(13:16), c = c(17:20)),
  9.     tibble(d = c(21:24), e = c(25:28)),
  10.     tibble(f = c(21:24))
  11.   ),
  12.   list(
  13.     tibble(a = c(31:34), b = c(35:38), c = c(20:23)),
  14.     tibble(d = c(31:34), e = c(35:38)),
  15.     tibble(f = c(31:34))
  16.   ),
  17.   list(
  18.     tibble(a = c(40:43), b = c(43:46), c = c(47:50)),
  19.     tibble(d = c(40:43), e = c(43:46)),
  20.     tibble(f = c(40:43))
  21.   )
  22. )

然而，这对于在pmap()的.l参数中使用是错误的。

我认为我想要将它转换成像下面的列表的列表，名为after。

  1. after <- list(
  2.   list(
  3.     tibble(a = c(10:13), b = c(13:16), c = c(17:20)),
  4.     tibble(a = c(10:13), b = c(13:16), c = c(17:20)),
  5.     tibble(a = c(31:34), b = c(35:38), c = c(20:23)),
  6.     tibble(a = c(40:43), b = c(43:46), c = c(47:50))
  7.   ),
  8.   list(
  9.     tibble(d = c(10:13), e = c(13:16)),
  10.     tibble(d = c(21:24), e = c(25:28)),
  11.     tibble(d = c(31:34), e = c(35:38)),
  12.     tibble(d = c(40:43), e = c(43:46))
  13.   ),
  14.   list(
  15.     tibble(f = c(10:13)),
  16.     tibble(f = c(21:24)),
  17.     tibble(f = c(31:34)),
  18.     tibble(f = c(40:43))
  19.   )
  20. )

这样，我就可以执行以下操作...

  1. x <- pmap(after, my_func)

其中my_func是一个接受3个不同tibbles作为参数的函数。实际上，它是一个创建复杂ggplots的函数。

问题是：

  • 如何将before转换成after？
  • after的形式是否正确，可以用于将其映射到一个接受3个tibble作为参数的函数中？
英文:

I've been struggling really hard to get pmap() to work and misunderstood the structure of the list that I am supposed to feed it.

Basically, I ended up with a list of lists, before, but it's not in the correct arrangement for pmap.

Here's a minimum repro of what it's like:

  1. before &lt;- list(
  2.   list(
  3.     tibble(a = c(10:13), b = c(13:16), c = c(17:20)),
  4.     tibble(d = c(10:13), e = c(13:16)),
  5.     tibble(f = c(10:13))
  6.   ),
  7.   list(
  8.     tibble(a = c(10:13), b = c(13:16), c = c(17:20)),
  9.     tibble(d = c(21:24), e = c(25:28)),
  10.     tibble(f = c(21:24))
  11.   ),
  12.   list(
  13.     tibble(a = c(31:34), b = c(35:38), c = c(20:23)),
  14.     tibble(d = c(31:34), e = c(35:38)),
  15.     tibble(f = c(31:34))
  16.   ),
  17.   list(
  18.     tibble(a = c(40:43), b = c(43:46), c = c(47:50)),
  19.     tibble(d = c(40:43), e = c(43:46)),
  20.     tibble(f = c(40:43))
  21.   )
  22. )

However, that's wrong for what to use as the .l argument in pmap().

I think would like to transform it into a list of lists like below, after.

  1. after &lt;- list(
  2.   list(
  3.     tibble(a = c(10:13), b = c(13:16), c = c(17:20)),
  4.     tibble(a = c(10:13), b = c(13:16), c = c(17:20)),
  5.     tibble(a = c(31:34), b = c(35:38), c = c(20:23)),
  6.     tibble(a = c(40:43), b = c(43:46), c = c(47:50))
  7.   ),
  8.   list(
  9.     tibble(d = c(10:13), e = c(13:16)),
  10.     tibble(d = c(21:24), e = c(25:28)),
  11.     tibble(d = c(31:34), e = c(35:38)),
  12.     tibble(d = c(40:43), e = c(43:46))
  13.   ),
  14.   list(
  15.     tibble(f = c(10:13)),
  16.     tibble(f = c(21:24)),
  17.     tibble(f = c(31:34)),
  18.     tibble(f = c(40:43))
  19.   )
  20. )

That way, I could perform this...

  1. x &lt;- pmap(after, my_func)

Where my_func is a function that takes 3 different tibbles as arguments. It's actually a function that creates complicated ggplots.

The questions are:

  • How can I transform before to after?
  • Is after in the right form to use pmap to map to a function that takes 3 tibbles as arguments?

答案1

得分: 2

Using lapply:

  1. out &lt;- lapply(1:3, \(i) lapply(before, &quot;[[&quot;, i))
  3. #check
  4. identical(out, after)
  5. # [1] TRUE
英文:

Using lapply:

  1. out &lt;- lapply(1:3, \(i) lapply(before, &quot;[[&quot;, i))
  3. #check
  4. identical(out, after)
  5. # [1] TRUE

答案2

得分: 2

使用purrr中的transpose函数：

  1. library(purrr)
  3. after2 <- transpose(before)
  5. identical(after, after2)
  6. ## [1] TRUE
英文:

Use tranpose from purrr:

  1. library(purrr)
  3. after2 &lt;- tranpose(before)
  5. identical(after, after2)
  6. ## [1] TRUE

答案3

得分: 1

使用 pmap 时，使用适合列表内容的参数。

  1. before %>% purrr::pmap(\(x, y, z, k) list(x, y, z, k))
  2. [[1]]
  3. [[1]][[1]]
  4. # A tibble: 4 × 3
  5.       a     b     c
  6.   <int> <int> <int>
  7. 1    10    13    17
  8. 2    11    14    18
  9. 3    12    15    19
  10. 4    13    16    20
  12. [[1]][[2]]
  13. # A tibble: 4 × 3
  14.       a     b     c
  15.   <int> <int> <int>
  16. 1    10    13    17
  17. 2    11    14    18
  18. 3    12    15    19
  19. 4    13    16    20
  20. ...

在 after 上进行测试：

  1. identical(after, before %>% purrr::pmap(\(x, y, z, k) list(x, y, z, k)))
  2. [1] TRUE
英文:

With pmap use arguments that fit the list content

  1. before %&gt;% purrr::pmap(\(x, y, z, k) list(x, y, z, k))
  2. [[1]]
  3. [[1]][[1]]
  4. # A tibble: 4 &#215; 3
  5.       a     b     c
  6.   &lt;int&gt; &lt;int&gt; &lt;int&gt;
  7. 1    10    13    17
  8. 2    11    14    18
  9. 3    12    15    19
  10. 4    13    16    20
  12. [[1]][[2]]
  13. # A tibble: 4 &#215; 3
  14.       a     b     c
  15.   &lt;int&gt; &lt;int&gt; &lt;int&gt;
  16. 1    10    13    17
  17. 2    11    14    18
  18. 3    12    15    19
  19. 4    13    16    20
  20. ...

Test on after

  1. identical(after, before %&gt;% purrr::pmap(\(x, y, z, k) list(x, y, z, k)))
  2. [1] TRUE

huangapple
  • 本文由 发表于 2023年5月24日 20:48:40
  • 转载请务必保留本文链接：https://go.coder-hub.com/76323717.html
  • pmap
  • purrr
  • r
  • tidyverse
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