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expose-helpers.R
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expose-helpers.R
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# General expose helpers --------------------------------------------------
guess_pack_type <- function(.pack_out, .rule_sep = inside_punct("\\._\\.")) {
all_logical <- all(vapply(.pack_out, is.logical, TRUE))
n_rows_one <- nrow(.pack_out) == 1
all_contain_sep <- all(grepl(pattern = .rule_sep, x = colnames(.pack_out)))
if (!all_logical) {
return("group_pack")
}
if (n_rows_one) {
if (all_contain_sep) {
return("col_pack")
} else {
return("data_pack")
}
} else {
if (all_contain_sep) {
return("cell_pack")
} else {
return("row_pack")
}
}
}
remove_obeyers <- function(.report, .do_remove) {
if (!.do_remove) {
return(.report)
} else {
.report %>% filter(!is_obeyer(.data[["value"]]))
}
}
impute_exposure_pack_names <- function(.single_exposures, .exposure_ref) {
pack_names <- rlang::names2(.single_exposures)
is_empty_pack_names <- pack_names == ""
if (sum(is_empty_pack_names) == 0) {
return(.single_exposures)
}
# Collect data about imputed pack types
pack_types <- vapply(.single_exposures, function(cur_single_exposure) {
cur_single_exposure[["pack_info"]][["type"]][1]
}, "chr")
pack_types_table <- table(pack_types)
unique_pack_types <- names(pack_types_table)
start_ind_vec <- rep(1, length(unique_pack_types))
names(start_ind_vec) <- unique_pack_types
# Account for reference pack types
if (!identical(.exposure_ref, NULL)) {
ref_pack_types <- .exposure_ref[["packs_info"]][["type"]]
ref_pack_types_table <- table(ref_pack_types)
common_pack_types <- intersect(
unique_pack_types,
names(ref_pack_types_table)
)
start_ind_vec[common_pack_types] <-
ref_pack_types_table[common_pack_types] + 1
}
# Impute
def_names <- mapply(
compute_def_names,
.n = pack_types_table, .root = unique_pack_types,
.start_ind = start_ind_vec,
SIMPLIFY = FALSE
) %>%
unsplit(f = pack_types)
names(.single_exposures)[is_empty_pack_names] <-
def_names[is_empty_pack_names]
.single_exposures
}
#' Add pack names to single exposures
#'
#' Function to add pack names to single exposures. Converts list of
#' [single exposures][single_exposure] to list of [exposures][exposure] without
#' validating.
#'
#' @param .single_exposures List of [single exposures][single_exposure].
#'
#' @keywords internal
add_pack_names <- function(.single_exposures) {
pack_names <- names(.single_exposures)
lapply(pack_names, function(pack_name) {
single_exposure <- .single_exposures[[pack_name]]
# Add pack name to report
report <- single_exposure[["report"]]
new_report <- report
new_report[["pack"]] <- rep(pack_name, nrow(report))
new_report <- new_report[, c("pack", colnames(report))] %>%
as_report(.validate = FALSE)
# Add pack name to pack info and convert to `packs_info`
packs_info <- single_exposure[["pack_info"]]
packs_info[["name"]] <- rep(pack_name, nrow(packs_info))
packs_info <-
packs_info[, c("name", colnames(single_exposure[["pack_info"]]))] %>%
as_packs_info(.validate = FALSE)
new_exposure(packs_info, new_report, .validate = FALSE)
}) %>%
rlang::set_names(pack_names)
}
# Binder ------------------------------------------------------------------
#' Bind exposures
#'
#' Function to bind several exposures into one.
#'
#' @param ... Exposures to bind.
#' @param .validate_output Whether to validate with [is_exposure()] if the
#' output is exposure.
#'
#' @details __Note__ that the output might not have names in list-column `fun`
#' in [packs info][packs_info], which depends on version of
#' [dplyr][dplyr::dplyr-package] package.
#'
#' @examples
#' my_data_packs <- data_packs(
#' data_dims = . %>% dplyr::summarise(nrow_low = nrow(.) < 10),
#' data_sum = . %>% dplyr::summarise(sum = sum(.) < 1000)
#' )
#'
#' ref_exposure <- mtcars %>%
#' expose(my_data_packs) %>%
#' get_exposure()
#'
#' exposure_1 <- mtcars %>%
#' expose(my_data_packs[1]) %>%
#' get_exposure()
#' exposure_2 <- mtcars %>%
#' expose(my_data_packs[2]) %>%
#' get_exposure()
#' exposure_binded <- bind_exposures(exposure_1, exposure_2)
#'
#' exposure_pipe <- mtcars %>%
#' expose(my_data_packs[1]) %>%
#' expose(my_data_packs[2]) %>%
#' get_exposure()
#'
#' identical(exposure_binded, ref_exposure)
#'
#' identical(exposure_pipe, ref_exposure)
#' @export
bind_exposures <- function(..., .validate_output = TRUE) {
exposures <- rlang::dots_list(...) %>%
squash() %>%
filter_not_null()
if (length(exposures) == 0) {
return(NULL)
}
binded_packs_info <- lapply(exposures, `[[`, "packs_info") %>%
bind_rows() %>%
as_packs_info(.validate = FALSE)
row.names(binded_packs_info) <- NULL
binded_report <- lapply(exposures, `[[`, "report") %>%
bind_rows() %>%
as_report(.validate = FALSE)
row.names(binded_report) <- NULL
new_exposure(binded_packs_info, binded_report, .validate = .validate_output)
}
filter_not_null <- function(.x) {
is_null_x <- vapply(.x, identical, FUN.VALUE = TRUE, y = NULL)
.x[!is_null_x]
}
# Assertions for pack outputs ---------------------------------------------
assert_pack_out_one_row <- function(.pack_out, .pack_type) {
if (nrow(.pack_out) != 1) {
stop(paste0("Some ", .pack_type, " has output with not 1 row."))
}
TRUE
}
assert_pack_out_all_logical <- function(.pack_out, .pack_type) {
is_lgl_col <- vapply(.pack_out, is.logical, TRUE)
if (all(is_lgl_col)) {
return(TRUE)
} else {
stop(paste0("Some ", .pack_type, " has not logical output column"))
}
}
assert_pack_out_all_have_separator <-
function(.pack_out, .pack_type, .rule_sep) {
has_sep <- grepl(pattern = .rule_sep, x = colnames(.pack_out))
if (all(has_sep)) {
return(TRUE)
} else {
stop(paste0(
"In some ", .pack_type, " not all columns contain rule separator"
))
}
}