Compute a Statistic for the Foreground Phase and the Background Phases

Compute a statistic (for example, a mean) based on all matching comparisons (foreground phase) and the same statistic based on all non-matching comparisons (background phases)

compute_diff_phase(scores_list, FUNC = mean, na.rm = TRUE, both = FALSE)

Arguments

scores_list

a list of all phases

FUNC

a function to be applied to both the foreground phase and the background phases

na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds

both

logical value. If TRUE, return the values of the FUNC for both the foreground phase and the background phases; if FALSE, return their difference

Value

If both = TRUE, return the values of the statistic (calculated by FUNC) for both the foreground phase and the background phases; if both = FALSE, return the difference

Examples

library(tidyverse)
#> ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──
#> ✔ tibble  3.1.6     ✔ dplyr   1.0.8
#> ✔ tidyr   1.2.0     ✔ stringr 1.4.0
#> ✔ readr   2.1.2     ✔ forcats 0.5.1
#> ✔ purrr   0.3.4     
#> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
#> ✖ dplyr::filter() masks stats::filter()
#> ✖ dplyr::lag()    masks stats::lag()

data("bullets")

lands <- unique(bullets$bulletland)

comparisons <- data.frame(expand.grid(land1 = lands[1:6], land2 = lands[7:12]),
                          stringsAsFactors = FALSE)

comparisons <- comparisons %>%
  left_join(bullets %>% select(bulletland, sig1=sigs),
            by = c("land1" = "bulletland")) %>%
  left_join(bullets %>% select(bulletland, sig2=sigs),
            by = c("land2" = "bulletland"))

comparisons <- comparisons %>% mutate(
  cmps = purrr::map2(sig1, sig2, .f = function(x, y) {
    extract_feature_cmps(x$sig, y$sig, include = "full_result")
  })
)

comparisons <- comparisons %>%
  mutate(
    cmps_score = sapply(comparisons$cmps, function(x) x$CMPS_score),
    cmps_nseg = sapply(comparisons$cmps, function(x) x$nseg)
  )
  
cp1 <- comparisons %>% select(land1, land2, cmps_score, cmps_nseg)
cp1 <- cp1 %>% mutate(
  land1idx = land1 %>% str_sub(-1, -1) %>% as.numeric(),
  land2idx = land2 %>% str_sub(-1, -1) %>% as.numeric()
)

phases <- with(cp1, {
  get_all_phases(land1idx, land2idx, cmps_score, addNA = TRUE)
})

compute_diff_phase(phases)
#> [1] 10.96667