Question

这是上一个问题的延续： Apply function over every entry one table to every entry of another

我有下表loss.tib和bandstib以及函数bandedlossfn：

library(tidyverse)
set.seed(1)
n <- 5
loss.tib <- tibble(lossid = seq(n),
                   loss = rbeta(n, 1, 10) * 100)

bandstib <- tibble(bandid = seq(4),
                   start = seq(0, 75, by = 25),
                    end = seq(25, 100, by = 25))

bandedlossfn <- function(loss, start, end) {
  pmin(end - start, pmax(0, loss - start))
}

可以使用loss.tib作为参数在bandstib上应用此功能：

loss.tib %>% 
mutate(
  result = map(
    loss, ~ tibble(result = bandedlossfn(.x, bandstib$start, 
bandstib$end))
    )
    ) %>% unnest

但是，我想在地图内添加索引，如下所示：

loss.tib %>% 
mutate(
  result = map(
    loss, ~ tibble(result = bandedlossfn(.x, bandstib$start, 
bandstib$end)) %>% 
    mutate(bandid2 = row_number())
    )
    ) %>% unnest

但是它似乎没有按预期工作。我也想在map函数中添加filter(!near(result,0))以便有效地进行内存管理。

我期望的结果是：

lossid  loss    bandid  result
1   21.6691088  1   21.6691088  
2   6.9390647   1   6.9390647   
3   0.5822383   1   0.5822383   
4   5.5671643   1   5.5671643   
5   27.8237244  1   25.0000000  
5   27.8237244  2   2.8237244

谢谢。

Answer 1

这里是一种可能性：您首先嵌套bandstib，然后将其添加到loss.tib。这样，id便会坚持您的计算：

bandstib <- tibble(bandid = seq(4),
                   start = seq(0, 75, by = 25),
                   end = seq(25, 100, by = 25)) %>% 
  nest(.key = "data")

set.seed(1)
n <- 5
result <- tibble(loss = rbeta(n, 1, 10) * 100) %>% 
  bind_cols(., slice(bandstib, rep(1, n))) %>%
  mutate(result = map2(loss, data, ~bandedlossfn(.x, .y$start, .y$end))) %>% 
  unnest()

地图功能中的索引列表

1 个答案: