audit_seq() and audit_total_n() summarize the results of
functions that end on _seq and _total_n, respectively.
See below for a record of such functions. Go to the documentation of any of
them to learn about the way its output is processed by audit_seq() or
audit_total_n().
Details
All functions named below that end on _seq were made by
function_map_seq(). All that end on _total_n were made by
function_map_total_n().
Before audit_seq()
| Function | Class |
grim_map_seq() | "scr_grim_map_seq" |
grimmer_map_seq() | "scr_grimmer_map_seq" |
debit_map_seq() | "scr_debit_map_seq" |
Before audit_total_n()
| Function | Class |
grim_map_total_n() | "scr_grim_map_total_n" |
grimmer_map_total_n() | "scr_grimmer_map_total_n" |
debit_map_total_n() | "scr_debit_map_total_n" |
Examples
# For GRIM-testing with dispersed inputs:
out <- pigs1 %>%
grim_map_seq() %>%
audit_seq()
out
#> # A tibble: 8 × 12
#> x n consistency hits_total hits_x hits_n diff_x diff_x_up diff_x_down
#> <chr> <int> <lgl> <int> <int> <int> <int> <int> <int>
#> 1 4.74 25 FALSE 4 2 2 2 2 -2
#> 2 5.23 29 FALSE 6 3 3 1 1 -2
#> 3 2.57 24 FALSE 6 3 3 1 1 -3
#> 4 6.77 27 FALSE 7 3 4 1 1 -3
#> 5 7.01 29 FALSE 3 3 0 1 2 -1
#> 6 3.14 27 FALSE 6 3 3 1 1 -3
#> 7 6.89 31 FALSE 8 4 4 1 1 -2
#> 8 0.24 28 FALSE 6 3 3 1 1 -3
#> # ℹ 3 more variables: diff_n <int>, diff_n_up <int>, diff_n_down <int>
# Follow up on `audit_seq()` or
# `audit_total_n()` with `audit()`:
audit(out)
#> # A tibble: 9 × 8
#> term mean sd median min max na_count na_rate
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 hits_total 5.75 1.58 6 3 8 0 0
#> 2 hits_x 3 0.535 3 2 4 0 0
#> 3 hits_n 2.75 1.28 3 0 4 0 0
#> 4 diff_x 1.12 0.354 1 1 2 0 0
#> 5 diff_x_up 1.25 0.463 1 1 2 0 0
#> 6 diff_x_down -2.38 0.744 -2.5 -3 -1 0 0
#> 7 diff_n 1.43 0.787 1 1 3 1 0.125
#> 8 diff_n_up 2.29 1.38 2 1 4 1 0.125
#> 9 diff_n_down -2.57 1.40 -3 -5 -1 1 0.125