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从a使用 map 创建的多个目标 ( ) 中，我有 2 个其他目标 (b和d) 迭代第一个目标。现在我想在另一个目标中使用这些目标的结果。此外，我想与另一个变量 ( model) 交叉。

我在下面粘贴了一个代表，但在我的情况下，对于某些上下文，a描述数据集的不同子集，b并d预先计算一些东西，e使用预先计算的数据在每个子集上应用不同的模型。

我尝试了不同的组合map cross（如下e所示）但没有成功。我试图在 fn4 中添加我想要使用的所有目标名称，但它会创建不必要的交叉。

library(drake)
drake_plan(
  a = target(
    fn1(arg1, arg2),
    transform = map(
      arg1 = !!c("arg11", "arg12"),
      arg2 = !!c("arg21", "arg22")
    )
  ),
  b = target(
    fn2(arg1),
    transform = map(arg1)
  ),
  d = target(
    fn3(arg1),
    transform = map(arg1)
  ),
  e = target(
    fn4(b, d, model, arg1),
    transform = cross(
      b,
      d,
      model = !!c("x", "y", "z"),
      .by = arg1,
      .id = c(arg1, model)
    )
  ),
  trace = TRUE
)
#> # A tibble: 18 x 10
#>    target   command     arg1    arg2   a      b     d     model .by   e    
#>    <chr>    <expr>      <chr>   <chr>  <chr>  <chr> <chr> <chr> <chr> <chr>
#>  1 a_arg11… fn1("arg11… "\"arg… "\"ar… a_arg… <NA>  <NA>  <NA>  <NA>  <NA> 
#>  2 a_arg12… fn1("arg12… "\"arg… "\"ar… a_arg… <NA>  <NA>  <NA>  <NA>  <NA> 
#>  3 b_arg11  fn2("arg11… "\"arg… "\"ar… a_arg… b_ar… <NA>  <NA>  <NA>  <NA> 
#>  4 b_arg12  fn2("arg12… "\"arg… "\"ar… a_arg… b_ar… <NA>  <NA>  <NA>  <NA> 
#>  5 d_arg11  fn3("arg11… "\"arg… "\"ar… a_arg… <NA>  d_ar… <NA>  <NA>  <NA> 
#>  6 d_arg12  fn3("arg12… "\"arg… "\"ar… a_arg… <NA>  d_ar… <NA>  <NA>  <NA> 
#>  7 e_NA_x   fn4(b_arg1… <NA>    <NA>   <NA>   b_ar… d_ar… "\"x… arg1  e_NA…
#>  8 e_NA_y   fn4(b_arg1… <NA>    <NA>   <NA>   b_ar… d_ar… "\"y… arg1  e_NA…
#>  9 e_NA_z   fn4(b_arg1… <NA>    <NA>   <NA>   b_ar… d_ar… "\"z… arg1  e_NA…
#> 10 e_NA_x_2 fn4(b_arg1… <NA>    <NA>   <NA>   b_ar… d_ar… "\"x… arg1  e_NA…
#> 11 e_NA_y_2 fn4(b_arg1… <NA>    <NA>   <NA>   b_ar… d_ar… "\"y… arg1  e_NA…
#> 12 e_NA_z_2 fn4(b_arg1… <NA>    <NA>   <NA>   b_ar… d_ar… "\"z… arg1  e_NA…
#> 13 e_NA_x_3 fn4(b_arg1… <NA>    <NA>   <NA>   b_ar… d_ar… "\"x… arg1  e_NA…
#> 14 e_NA_y_3 fn4(b_arg1… <NA>    <NA>   <NA>   b_ar… d_ar… "\"y… arg1  e_NA…
#> 15 e_NA_z_3 fn4(b_arg1… <NA>    <NA>   <NA>   b_ar… d_ar… "\"z… arg1  e_NA…
#> 16 e_NA_x_4 fn4(b_arg1… <NA>    <NA>   <NA>   b_ar… d_ar… "\"x… arg1  e_NA…
#> 17 e_NA_y_4 fn4(b_arg1… <NA>    <NA>   <NA>   b_ar… d_ar… "\"y… arg1  e_NA…
#> 18 e_NA_z_4 fn4(b_arg1… <NA>    <NA>   <NA>   b_ar… d_ar… "\"z… arg1  e_NA…

由reprex 包（v0.3.0）于 2019-07-15 创建

它似乎有效，但arg1andarg2没有被延续，并且不能用于fn4和跟随目标。我应该把这一步分成两步吗，如果是的话怎么做？（map然后cross，cross然后map？）我尝试过早点，之后a，但我不会重新计算相同b和d多次，这可能需要大量时间和内存。

编辑：一个更现实的例子

因为许多目标使用需要保存为run函数文件的相同数据（调用外部二进制文件），所以为了防止多次重新计算相同的东西并将相同的东西多次保存在不同的文件中（taht 可以是巨大的）我在德雷克分离了所有这些任务。


library(drake)
library(tibble)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

path_data <- c("path/data_1.csv", "path/data_2.csv")
countries <- c("1", "2")
analysis_dir <- "path"
substudies_1 <- tribble(
  ~substudy, ~adjust, ~sex,
  "sub1", "no", "male/female",
  "sub2", "yes", "male/female"
)
models <- c("x", "y")

plan <- drake_plan(
  data = target(
    get_data(file_in(path)),
    transform = map(path = !!path_data, country = !!countries, .id = country)
  ),
  SNP = target(
    get_SNP_data_country(SNP_gene, data),
    transform = map(data, .id = country)
  ),
  map = target(
    # actually write file and save path
    write_snp_map(SNP, file.path(analysis_dir, country, "SNP_map.txt")),
    transform = map(SNP, .id = country)
  ),
  ref = target(
    # actually write file and save path
    write_snp_ref(SNP, file.path(analysis_dir, country, "SNP_ref.txt")),
    transform = map(SNP, .id = country)
  ),
  # data_2 is managed in another target because it has a different set of substudies,
  # this maybe can be tidied up, a problem for another day...
  population_1 = target(
    extract_population(data, sex, adjust),
    transform = map(
      data = data_1,
      country = "1",
      .data = !!substudies_1,
      .id = c(substudy)
    ),
  ),
  pedigree_1 = target(
    extract_pedigree(data_1, population_1),
    transform = map(
      population_1,
      .id = substudy
    )
  ),
  covariable_1 = target(
    extract_covariable(data_1, population_1, adjust, sex),
    transform = map(
      population_1,
      .id = substudy
    )
  ),
  # run_1 = target(
  #   run_fn(map_1, ref_1, pedigree_1, covariable_1, substudy, model, adjust, sex),
  #   transform = cross(population_1, model = !!models)
  # ),
  trace = TRUE
)

# the desired plan for the run target
run_plan <- tibble(
  target = c("run_1_x_population_1_sub1", "run_1_y_population_1_sub1", "run_1_x_population_1_sub2", "run_1_y_population_1_sub2"),
  command = list(
    expr(run(map_1, ref_1, pedigree_1_sub1, covariable_1_sub1, "x", "sub1", "no")),
    expr(run(map_1, ref_1, pedigree_1_sub1, covariable_1_sub1, "y", "sub1", "no")),
    expr(run(map_1, ref_1, pedigree_1_sub2, covariable_1_sub2, "x", "sub2", "yes")),
    expr(run(map_1, ref_1, pedigree_1_sub2, covariable_1_sub2, "y", "sub2", "yes"))
  ),
  path = NA_character_,
  country = "1",
  population_1 = c(rep("population_1_sub1", 2), rep("population_1_sub2", 2)),
  substudy = c(rep("sub1", 2), rep("sub2", 2)),
  adjust = c(rep("no", 2), rep("yes", 2)),
  sex = c(rep("male/female", 4)),
  pedigree_1 = c(rep("pedigree_1_sub1", 2), rep("pedigree_1_sub2", 2)),
  covariable_1 =  c(rep("covariable_1_sub1", 2), rep("covariable_1_sub2", 2)),
  model = c("x", "y", "x", "y"),
  SNP = "SNP_1",
  map = "map_1",
  ref = "ref_1"
)

config <- drake_config(bind_rows(plan, run_plan))
vis_drake_graph(config, targets_only = TRUE)

由reprex 包（v0.3.0）于 2019-07-15 创建

计划：i.imgur.com/MyqoKJi.png

编辑2：

我现在使用.data具有先前目标名称的数据框（使用rlang::syms）在地图转换中使用该参数，它工作正常，但它不适用于drake::drake_plan'smax_expand参数。这个解决方案也不是最优的，因为制作一个网格.data非常冗长。

4

1 回答 1

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您介意在没有任何转换的情况下明确发布您想要的计划吗？drake_plan_source()能够帮助。

一注：combine()只懂.by。也许另一种方法是使用transform = map(.data = !!your_grid_of_combinations)：https ://ropenscilabs.github.io/drake-manual/plans.html#map 。

你想要的计划看起来像这样吗？

library(drake)
plan <- drake_plan(
  a = target(
    fn1(arg1, arg2),
    transform = map(
      arg1 = !!c("arg11", "arg12"),
      arg2 = !!c("arg21", "arg22")
    )
  ),
  b = target(
    fn2(arg1),
    transform = map(arg1)
  ),
  d = target(
    fn3(arg1),
    transform = map(arg1)
  ),
  e = target(
    fn4(b, d, model, arg1),
    transform = cross(
      b,
      d,
      model = c("x", "y", "z"),
      arg1,
      .id = c(arg1, model)
    )
  )
)

config <- drake_config(plan)
vis_drake_graph(config)

由reprex 包（v0.3.0）于 2019-07-15 创建

于 2019-07-15T13:37:24.080 回答