Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
pkgload::load_all()
## ----setup--------------------------------------------------------------------
library(scrutiny)
## -----------------------------------------------------------------------------
schlim_scalar <- function(y, n) {
y <- as.numeric(y)
n <- as.numeric(n)
all(y / 3 > n)
}
schlim_scalar(y = 30, n = 4)
schlim_scalar(y = 2, n = 7)
## -----------------------------------------------------------------------------
schlim <- Vectorize(schlim_scalar)
schlim(y = 10:15, n = 4)
## -----------------------------------------------------------------------------
schlim_map <- function_map(
.fun = schlim_scalar,
.reported = c("y", "n"),
.name_test = "SCHLIM"
)
# Example data:
df1 <- tibble::tibble(y = 16:25, n = 3:12)
schlim_map(df1)
## -----------------------------------------------------------------------------
audit.scr_schlim_map <- function(data) {
audit_cols_minimal(data, name_test = "SCHLIM")
}
df1 %>%
schlim_map() %>%
audit()
## -----------------------------------------------------------------------------
schlim_map_seq <- function_map_seq(
.fun = schlim_map,
.reported = c("y", "n"),
.name_test = "SCHLIM"
)
df1 %>%
schlim_map_seq()
## -----------------------------------------------------------------------------
df1 %>%
schlim_map_seq() %>%
audit_seq()
## -----------------------------------------------------------------------------
df2 <- tibble::tribble(
~y1, ~y2, ~n,
84, 37, 29,
61, 55, 26
)
## -----------------------------------------------------------------------------
schlim_map_total_n <- function_map_total_n(
.fun = schlim_map,
.reported = "y",
.name_test = "SCHLIM"
)
df2 %>%
schlim_map_total_n()
## -----------------------------------------------------------------------------
df2 %>%
schlim_map_total_n() %>%
audit_total_n()
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