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(v1.5.0.9016) only_rsi_columns update, documentation

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dr. M.S. (Matthijs) Berends
2021-02-08 14:18:42 +01:00
parent 8fda473e49
commit 4a84894f79
88 changed files with 654 additions and 375 deletions
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56
R/first_isolate.R
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@ -27,7 +27,7 @@
#'
#' Determine first (weighted) isolates of all microorganisms of every patient per episode and (if needed) per specimen type. To determine patient episodes not necessarily based on microorganisms, use [is_new_episode()] that also supports grouping with the `dplyr` package.
#' @inheritSection lifecycle Stable Lifecycle
#' @param x a [data.frame] containing isolates. Can be left blank for automatic determination.
#' @param x a [data.frame] containing isolates. Can be left blank for automatic determination, see *Examples*.
#' @param col_date column name of the result date (or date that is was received on the lab), defaults to the first column with a date class
#' @param col_patient_id column name of the unique IDs of the patients, defaults to the first column that starts with 'patient' or 'patid' (case insensitive)
#' @param col_mo column name of the IDs of the microorganisms (see [as.mo()]), defaults to the first column of class [`mo`]. Values will be coerced using [as.mo()].
@ -86,7 +86,7 @@
#'
#' 2. Using `type = "points"` and argument `points_threshold`
#'
#' A difference from I to S|R (or vice versa) means 0.5 points, a difference from S to R (or vice versa) means 1 point. When the sum of points exceeds `points_threshold`, which default to `2`, an isolate will be (re)selected as a first weighted isolate.
#' A difference from I to S|R (or vice versa) means 0.5 points, a difference from S to R (or vice versa) means 1 point. When the sum of points exceeds `points_threshold`, which defaults to `2`, an isolate will be (re)selected as a first weighted isolate.
#' @rdname first_isolate
#' @seealso [key_antibiotics()]
#' @export
@ -99,10 +99,12 @@
#' # `example_isolates` is a data set available in the AMR package.
#' # See ?example_isolates.
#'
#' # basic filtering on first isolates
#' example_isolates[first_isolate(), ]
#' example_isolates[first_isolate(example_isolates), ]
#'
#' \donttest{
#' # faster way, only works in R 3.2 and later:
#' example_isolates[first_isolate(), ]
#'
#' # get all first Gram-negatives
#' example_isolates[which(first_isolate() & mo_is_gram_negative()), ]
#'
@ -140,7 +142,7 @@
#' # when you (erroneously) would have used all isolates for analysis.
#' }
#' }
first_isolate <- function(x,
first_isolate <- function(x = NULL,
col_date = NULL,
col_patient_id = NULL,
col_mo = NULL,
@ -158,10 +160,7 @@ first_isolate <- function(x,
info = interactive(),
include_unknown = FALSE,
...) {
if (missing(x)) {
x <- get_current_data(arg_name = "x", call = -2)
}
meet_criteria(x, allow_class = "data.frame") # also checks dimensions to be >0
meet_criteria(x, allow_class = "data.frame", allow_NULL = TRUE) # also checks dimensions to be >0
meet_criteria(col_date, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
meet_criteria(col_patient_id, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
@ -185,6 +184,14 @@ first_isolate <- function(x,
meet_criteria(info, allow_class = "logical", has_length = 1)
meet_criteria(include_unknown, allow_class = "logical", has_length = 1)
if (is_null_or_grouped_tbl(x)) {
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
# is also fix for using a grouped df as input (a dot as first argument)
x <- get_current_data(arg_name = "x", call = -2)
}
# remove data.table, grouping from tibbles, etc.
x <- as.data.frame(x, stringsAsFactors = FALSE)
dots <- unlist(list(...))
if (length(dots) != 0) {
# backwards compatibility with old arguments
@ -197,18 +204,7 @@ first_isolate <- function(x,
}
}
# fix for using a grouped df as input (a dot as first argument)
# such as example_isolates %>% group_by(hospital_id) %>% mutate(first_isolate = first_isolate(.))
if (inherits(x, "grouped_df")) {
# get_current_data() contains dplyr::cur_data_all()
x <- tryCatch(get_current_data(arg_name = "x", 0),
error = function(e) x)
}
# remove data.table, grouping from tibbles, etc.
x <- as.data.frame(x, stringsAsFactors = FALSE)
# try to find columns based on type
# try to find columns based on type
# -- mo
if (is.null(col_mo)) {
col_mo <- search_type_in_df(x = x, type = "mo")
@ -510,15 +506,20 @@ first_isolate <- function(x,
#' @rdname first_isolate
#' @export
filter_first_isolate <- function(x,
filter_first_isolate <- function(x = NULL,
col_date = NULL,
col_patient_id = NULL,
col_mo = NULL,
...) {
meet_criteria(x, allow_class = "data.frame")
meet_criteria(x, allow_class = "data.frame", allow_NULL = TRUE)
meet_criteria(col_date, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
meet_criteria(col_patient_id, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
if (is_null_or_grouped_tbl(x)) {
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
# is also fix for using a grouped df as input (a dot as first argument)
x <- get_current_data(arg_name = "x", call = -2)
}
subset(x, first_isolate(x = x,
col_date = col_date,
col_patient_id = col_patient_id,
@ -528,17 +529,22 @@ filter_first_isolate <- function(x,
#' @rdname first_isolate
#' @export
filter_first_weighted_isolate <- function(x,
filter_first_weighted_isolate <- function(x = NULL,
col_date = NULL,
col_patient_id = NULL,
col_mo = NULL,
col_keyantibiotics = NULL,
...) {
meet_criteria(x, allow_class = "data.frame")
meet_criteria(x, allow_class = "data.frame", allow_NULL = TRUE)
meet_criteria(col_date, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
meet_criteria(col_patient_id, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
meet_criteria(col_mo, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
meet_criteria(col_keyantibiotics, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
if (is_null_or_grouped_tbl(x)) {
# when `x` is left blank, auto determine it (get_current_data() also contains dplyr::cur_data_all())
# is also fix for using a grouped df as input (a dot as first argument)
x <- get_current_data(arg_name = "x", call = -2)
}
y <- x
if (is.null(col_keyantibiotics)) {
# first try to look for it