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#' @keywords internal
.get_model_info <- function(model, model_info = NULL, ...) {
if (is.null(model_info)) model_info <- insight::model_info(model)
model_info
}
#' Print a message saying that an argument is deprecated and that the user
#' should use its replacement instead.
#'
#' @param arg Argument that is deprecated
#' @param replacement Argument that replaces the deprecated argument
#' @keywords internal
.is_deprecated <- function(arg, replacement) {
insight::format_warning(
paste0("Argument `", arg, "` is deprecated. Please use `", replacement, "` instead.")
)
}
#' `NULL` coalescing operator
#'
#' @keywords internal
#' @noRd
`%||%` <- function(x, y) {
if (is.null(x)) y else x
}
#' Try to convert object to a dataframe
#'
#' @keywords internal
#' @noRd
.coerce_to_dataframe <- function(data) {
if (!is.data.frame(data)) {
data <- tryCatch(
as.data.frame(data, stringsAsFactors = FALSE),
error = function(e) {
insight::format_error(
"`data` must be a data frame, or an object that can be coerced to a data frame."
)
}
)
}
data
}
#' Fuzzy grep, matches pattern that are close, but not identical
#' Example:
#' colnames(iris)
#' p <- sprintf("(%s){~%i}", "Spela", 2)
#' grep(pattern = p, x = colnames(iris), ignore.case = FALSE)
#' @keywords internal
#' @noRd
.fuzzy_grep <- function(x, pattern, precision = NULL) {
if (is.null(precision)) {
precision <- round(nchar(pattern) / 3)
}
if (precision > nchar(pattern)) {
return(NULL)
}
p <- sprintf("(%s){~%i}", pattern, precision)
grep(pattern = p, x = x, ignore.case = FALSE)
}
#' create a message string to tell user about matches that could possibly
#' be the string they were looking for
#'
#' @keywords internal
#' @noRd
.misspelled_string <- function(source, searchterm, default_message = NULL) {
if (is.null(searchterm) || length(searchterm) < 1) {
return(default_message)
}
# used for many matches
more_found <- ""
# init default
msg <- ""
# guess the misspelled string
possible_strings <- unlist(lapply(searchterm, function(s) {
source[.fuzzy_grep(source, s)]
}))
if (length(possible_strings)) {
msg <- "Did you mean "
if (length(possible_strings) > 1) {
# make sure we don't print dozens of alternatives for larger data frames
if (length(possible_strings) > 5) {
more_found <- sprintf(
" We even found %i more possible matches, not shown here.",
length(possible_strings) - 5
)
possible_strings <- possible_strings[1:5]
}
msg <- paste0(msg, "one of ", text_concatenate(possible_strings, enclose = "\"", last = " or "))
} else {
msg <- paste0(msg, "\"", possible_strings, "\"")
}
msg <- paste0(msg, "?", more_found)
} else {
msg <- default_message
}
# no double white space
insight::trim_ws(msg)
}
#' Check that a vector is sorted
#' @noRd
.is_sorted <- Negate(is.unsorted)
#' Replace only custom attributes
#'
#' Using "attributes(out) <- attributes(data)" or similar doesn't work so well
#' for big datasets because it takes some time to attribute the row names.
#'
#' This function gives only custom attributes to the new dataset.
#' @noRd
.replace_attrs <- function(data, custom_attr) {
for (nm in setdiff(names(custom_attr), names(attributes(data.frame())))) {
attr(data, which = nm) <- custom_attr[[nm]]
}
return(data)
}
.is_date <- function(x) {
inherits(x, "Date")
}
#' Taken from https://github.com/coolbutuseless/gluestick [licence: MIT]
#' Same functionality as `{glue}`
#'
#' @noRd
.gluestick <- function(fmt, src = parent.frame(), open = "{", close = "}", eval = TRUE) {
nchar_open <- nchar(open)
nchar_close <- nchar(close)
# Sanity checks
stopifnot(exprs = {
is.character(fmt)
length(fmt) == 1L
is.character(open)
length(open) == 1L
nchar_open > 0L
is.character(close)
length(close) == 1
nchar_close > 0
})
# Brute force the open/close characters into a regular expression for
# extracting the expressions from the format string
open <- gsub("(.)", "\\\\\\1", open) # Escape everything!!
close <- gsub("(.)", "\\\\\\1", close) # Escape everything!!
re <- paste0(open, ".*?", close)
# Extract the delimited expressions
matches <- gregexpr(re, fmt)
exprs <- regmatches(fmt, matches)[[1]]
# Remove the delimiters
exprs <- substr(exprs, nchar_open + 1L, nchar(exprs) - nchar_close)
# create a valid sprintf fmt string.
# - replace all "{expr}" strings with "%s"
# - escape any '%' so sprintf() doesn't try and use them for formatting
# but only if the '%' is NOT followed by an 's'
#
# gluestick() doesn't deal with any pathological cases
fmt_sprintf <- gsub(re, "%s", fmt)
fmt_sprintf <- gsub("%(?!s)", "%%", fmt_sprintf, perl = TRUE)
# Evaluate
if (eval) {
args <- lapply(exprs, function(expr) {
eval(parse(text = expr), envir = src)
})
} else {
args <- unname(mget(exprs, envir = as.environment(src)))
}
# Create the string(s)
do.call(sprintf, c(list(fmt_sprintf), args))
}
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