AMR/R/join_microorganisms.R

193 lines
8.3 KiB
R
Raw Normal View History

# ==================================================================== #
# TITLE #
2022-10-05 09:12:22 +02:00
# AMR: An R Package for Working with Antimicrobial Resistance Data #
# #
2019-01-02 23:24:07 +01:00
# SOURCE #
2020-07-08 14:48:06 +02:00
# https://github.com/msberends/AMR #
# #
2022-10-05 09:12:22 +02:00
# CITE AS #
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
# Data. Journal of Statistical Software, 104(3), 1-31. #
# doi:10.18637/jss.v104.i03 #
# #
2022-12-27 15:16:15 +01:00
# Developed at the University of Groningen and the University Medical #
# Center Groningen in The Netherlands, in collaboration with many #
# colleagues from around the world, see our website. #
# #
2019-01-02 23:24:07 +01:00
# This R package is free software; you can freely use and distribute #
# it for both personal and commercial purposes under the terms of the #
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
# the Free Software Foundation. #
# We created this package for both routine data analysis and academic #
# research and it was publicly released in the hope that it will be #
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
2020-10-08 11:16:03 +02:00
# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Join [microorganisms] to a Data Set
2018-02-21 11:52:31 +01:00
#'
2021-05-12 18:15:03 +02:00
#' Join the data set [microorganisms] easily to an existing data set or to a [character] vector.
2018-02-21 11:52:31 +01:00
#' @rdname join
#' @name join
#' @aliases join inner_join
2021-05-12 18:15:03 +02:00
#' @param x existing data set to join, or [character] vector. In case of a [character] vector, the resulting [data.frame] will contain a column 'x' with these values.
2020-12-17 16:22:25 +01:00
#' @param by a variable to join by - if left empty will search for a column with class [`mo`] (created with [as.mo()]) or will be `"mo"` if that column name exists in `x`, could otherwise be a column name of `x` with values that exist in `microorganisms$mo` (such as `by = "bacteria_id"`), or another column in [microorganisms] (but then it should be named, like `by = c("bacteria_id" = "fullname")`)
2021-05-12 18:15:03 +02:00
#' @param suffix if there are non-joined duplicate variables in `x` and `y`, these suffixes will be added to the output to disambiguate them. Should be a [character] vector of length 2.
2021-04-29 17:16:30 +02:00
#' @param ... ignored, only in place to allow future extensions
2022-08-28 10:31:50 +02:00
#' @details **Note:** As opposed to the `join()` functions of `dplyr`, [character] vectors are supported and at default existing columns will get a suffix `"2"` and the newly joined columns will not get a suffix.
#'
#' If the `dplyr` package is installed, their join functions will be used. Otherwise, the much slower [merge()] and [interaction()] functions from base \R will be used.
2021-05-12 18:15:03 +02:00
#' @return a [data.frame]
2018-02-21 11:52:31 +01:00
#' @export
2018-04-02 11:11:21 +02:00
#' @examples
2018-10-12 16:35:18 +02:00
#' left_join_microorganisms(as.mo("K. pneumoniae"))
2021-05-12 18:15:03 +02:00
#' left_join_microorganisms("B_KLBSL_PNMN")
2018-04-02 11:11:21 +02:00
#'
2022-08-28 10:31:50 +02:00
#' df <- data.frame(
#' date = seq(
#' from = as.Date("2018-01-01"),
#' to = as.Date("2018-01-07"),
#' by = 1
#' ),
#' bacteria = as.mo(c(
#' "S. aureus", "MRSA", "MSSA", "STAAUR",
#' "E. coli", "E. coli", "E. coli"
#' )),
#' stringsAsFactors = FALSE
#' )
2022-08-27 20:49:37 +02:00
#' colnames(df)
2022-08-28 10:31:50 +02:00
#'
2022-08-27 20:49:37 +02:00
#' df_joined <- left_join_microorganisms(df, "bacteria")
#' colnames(df_joined)
2022-08-28 10:31:50 +02:00
#'
#' \donttest{
#' if (require("dplyr")) {
#' example_isolates %>%
2022-08-28 10:31:50 +02:00
#' left_join_microorganisms() %>%
#' colnames()
#' }
2020-05-16 13:05:47 +02:00
#' }
2018-10-12 16:35:18 +02:00
inner_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
meet_criteria(x, allow_class = c("data.frame", "character"))
meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
meet_criteria(suffix, allow_class = "character", has_length = 2)
2022-08-28 10:31:50 +02:00
2021-05-12 18:15:03 +02:00
join_microorganisms(type = "inner_join", x = x, by = by, suffix = suffix, ...)
2018-02-21 11:52:31 +01:00
}
#' @rdname join
#' @export
2018-10-12 16:35:18 +02:00
left_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
meet_criteria(x, allow_class = c("data.frame", "character"))
meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
meet_criteria(suffix, allow_class = "character", has_length = 2)
2022-08-28 10:31:50 +02:00
2021-05-12 18:15:03 +02:00
join_microorganisms(type = "left_join", x = x, by = by, suffix = suffix, ...)
2018-02-21 11:52:31 +01:00
}
#' @rdname join
#' @export
2018-10-12 16:35:18 +02:00
right_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
meet_criteria(x, allow_class = c("data.frame", "character"))
meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
meet_criteria(suffix, allow_class = "character", has_length = 2)
2022-08-28 10:31:50 +02:00
2021-05-12 18:15:03 +02:00
join_microorganisms(type = "right_join", x = x, by = by, suffix = suffix, ...)
2018-02-21 11:52:31 +01:00
}
#' @rdname join
#' @export
2018-10-12 16:35:18 +02:00
full_join_microorganisms <- function(x, by = NULL, suffix = c("2", ""), ...) {
meet_criteria(x, allow_class = c("data.frame", "character"))
meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
meet_criteria(suffix, allow_class = "character", has_length = 2)
2022-08-28 10:31:50 +02:00
2021-05-12 18:15:03 +02:00
join_microorganisms(type = "full_join", x = x, by = by, suffix = suffix, ...)
2018-02-21 11:52:31 +01:00
}
#' @rdname join
#' @export
2018-10-12 16:35:18 +02:00
semi_join_microorganisms <- function(x, by = NULL, ...) {
meet_criteria(x, allow_class = c("data.frame", "character"))
meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
2022-08-28 10:31:50 +02:00
2021-05-13 15:56:12 +02:00
join_microorganisms(type = "semi_join", x = x, by = by, ...)
2018-02-21 11:52:31 +01:00
}
#' @rdname join
#' @export
2018-10-12 16:35:18 +02:00
anti_join_microorganisms <- function(x, by = NULL, ...) {
meet_criteria(x, allow_class = c("data.frame", "character"))
meet_criteria(by, allow_class = "character", allow_NULL = TRUE)
2022-08-28 10:31:50 +02:00
2021-05-13 15:56:12 +02:00
join_microorganisms(type = "anti_join", x = x, by = by, ...)
2018-10-12 16:35:18 +02:00
}
2021-05-12 18:15:03 +02:00
join_microorganisms <- function(type, x, by, suffix, ...) {
2023-01-21 23:47:20 +01:00
add_MO_lookup_to_AMR_env()
2023-01-23 15:01:21 +01:00
2021-05-12 18:15:03 +02:00
if (!is.data.frame(x)) {
2022-08-27 20:49:37 +02:00
if (pkg_is_available("tibble", also_load = FALSE)) {
x <- import_fn("tibble", "tibble")(mo = x)
} else {
x <- data.frame(mo = x, stringsAsFactors = FALSE)
}
2021-05-12 18:15:03 +02:00
by <- "mo"
2018-10-12 16:35:18 +02:00
}
2022-08-27 20:49:37 +02:00
x.bak <- x
2018-10-12 16:35:18 +02:00
if (is.null(by)) {
2021-05-12 18:15:03 +02:00
by <- search_type_in_df(x, "mo", info = FALSE)
2021-05-13 15:56:12 +02:00
if (is.null(by) && NCOL(x) == 1) {
by <- colnames(x)[1L]
} else {
stop_if(is.null(by), "no column with microorganism names or codes found, set this column with `by`", call = -2)
}
message_('Joining, by = "', by, '"', add_fn = font_black, as_note = FALSE) # message same as dplyr::join functions
2021-05-12 18:15:03 +02:00
}
2022-10-14 13:02:50 +02:00
if (!all(x[, by, drop = TRUE] %in% AMR_env$MO_lookup$mo, na.rm = TRUE)) {
2021-05-12 18:15:03 +02:00
x$join.mo <- as.mo(x[, by, drop = TRUE])
by <- c("join.mo" = "mo")
} else {
x[, by] <- as.mo(x[, by, drop = TRUE])
}
2022-08-28 10:31:50 +02:00
2018-02-21 11:52:31 +01:00
if (is.null(names(by))) {
2021-05-12 18:15:03 +02:00
# will always be joined to microorganisms$mo, so add name to that
by <- stats::setNames("mo", by)
}
2022-08-28 10:31:50 +02:00
2023-02-09 13:07:39 +01:00
# use dplyr if available - it's much faster than poorman alternatives
dplyr_join <- import_fn(name = type, pkg = "dplyr", error_on_fail = FALSE)
if (!is.null(dplyr_join)) {
join_fn <- dplyr_join
} else {
# otherwise use poorman, see R/aa_helper_pm_functions.R
join_fn <- get(paste0("pm_", type), envir = asNamespace("AMR"))
}
2023-01-06 19:21:04 +01:00
MO_df <- AMR_env$MO_lookup[, colnames(AMR::microorganisms), drop = FALSE]
2021-05-12 18:15:03 +02:00
if (type %like% "full|left|right|inner") {
2023-01-06 19:21:04 +01:00
joined <- join_fn(x = x, y = MO_df, by = by, suffix = suffix, ...)
2020-06-03 14:33:55 +02:00
} else {
2023-01-06 19:21:04 +01:00
joined <- join_fn(x = x, y = MO_df, by = by, ...)
2020-06-03 14:33:55 +02:00
}
2022-08-28 10:31:50 +02:00
2021-05-12 18:15:03 +02:00
if ("join.mo" %in% colnames(joined)) {
if ("mo" %in% colnames(joined)) {
ind_mo <- which(colnames(joined) %in% c("mo", "join.mo"))
colnames(joined)[ind_mo[1L]] <- paste0("mo", suffix[1L])
colnames(joined)[ind_mo[2L]] <- paste0("mo", suffix[2L])
} else {
colnames(joined)[colnames(joined) == "join.mo"] <- "mo"
}
2020-06-03 11:48:00 +02:00
}
2022-08-28 10:31:50 +02:00
2021-05-12 18:15:03 +02:00
if (type %like% "full|left|right|inner" && NROW(joined) > NROW(x)) {
2022-12-12 00:14:56 +01:00
warning_("in `", type, "_microorganisms()`: the newly joined data set contains ", nrow(joined) - nrow(x), " rows more than the number of rows of `x`.")
2021-05-12 18:15:03 +02:00
}
2022-08-28 10:31:50 +02:00
2023-01-06 19:21:04 +01:00
as_original_data_class(joined, class(x.bak)) # will remove tibble groups
2020-06-03 11:48:00 +02:00
}