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(v1.1.0.9009) lose dependencies

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dr. M.S. (Matthijs) Berends
2020-05-18 10:30:53 +02:00
parent 071bdc5a9e
commit bf0402a653
29 changed files with 405 additions and 374 deletions
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2
R/atc_online.R
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@ -132,7 +132,7 @@ atc_online_property <- function(atc_code,
for (i in seq_len(length(atc_code))) {
progress$tick()$print()
progress$tick()
atc_url <- sub("%s", atc_code[i], url, fixed = TRUE)

41
R/first_isolate.R
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@ -46,12 +46,9 @@
#'
#' All isolates with a microbial ID of `NA` will be excluded as first isolate.
#'
#' The functions [filter_first_isolate()] and [filter_first_weighted_isolate()] are helper functions to quickly filter on first isolates. The function [filter_first_isolate()] is essentially equal to:
#' The functions [filter_first_isolate()] and [filter_first_weighted_isolate()] are helper functions to quickly filter on first isolates. The function [filter_first_isolate()] is essentially equal to one of:
#' ```
#' x %>%
#' mutate(only_firsts = first_isolate(x, ...)) %>%
#' filter(only_firsts == TRUE) %>%
#' select(-only_firsts)
#' x %>% filter(first_isolate(., ...))
#' ```
#' The function [filter_first_weighted_isolate()] is essentially equal to:
#' ```
@ -60,7 +57,7 @@
#' mutate(only_weighted_firsts = first_isolate(x,
#' col_keyantibiotics = "keyab", ...)) %>%
#' filter(only_weighted_firsts == TRUE) %>%
#' select(-only_weighted_firsts)
#' select(-only_weighted_firsts, -keyab)
#' ```
#' @section Key antibiotics:
#' There are two ways to determine whether isolates can be included as first *weighted* isolates which will give generally the same results:
@ -451,7 +448,7 @@ filter_first_isolate <- function(x,
col_patient_id = NULL,
col_mo = NULL,
...) {
filter(x, first_isolate(x = x,
subset(x, first_isolate(x = x,
col_date = col_date,
col_patient_id = col_patient_id,
col_mo = col_mo,
@ -466,15 +463,23 @@ filter_first_weighted_isolate <- function(x,
col_mo = NULL,
col_keyantibiotics = NULL,
...) {
tbl_keyab <- x %>%
mutate(keyab = suppressMessages(key_antibiotics(.,
col_mo = col_mo,
...))) %>%
mutate(firsts = first_isolate(.,
col_date = col_date,
col_patient_id = col_patient_id,
col_mo = col_mo,
col_keyantibiotics = "keyab",
...))
x[which(tbl_keyab$firsts == TRUE), ]
y <- x
if (is.null(col_keyantibiotics)) {
# first try to look for it
col_keyantibiotics <- search_type_in_df(x = x, type = "keyantibiotics")
# still NULL? Then create it since we are calling filter_first_WEIGHTED_isolate()
if (is.null(col_keyantibiotics)) {
y$keyab <- suppressMessages(key_antibiotics(x,
col_mo = col_mo,
...))
col_keyantibiotics <- "keyab"
}
}
subset(x, first_isolate(x = y,
col_date = col_date,
col_patient_id = col_patient_id,
col_mo = col_mo,
col_keyantibiotics = col_keyantibiotics,
...))
}

4
R/key_antibiotics.R
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@ -214,11 +214,9 @@ key_antibiotics <- function(x,
warning("only using ", length(gram_negative), " different antibiotics as key antibiotics for Gram-negatives. See ?key_antibiotics.", call. = FALSE)
}
# join to microorganisms data set
x <- x %>% as.data.frame(stringsAsFactors = FALSE)
x <- as.data.frame(x, stringsAsFactors = FALSE)
x[, col_mo] <- as.mo(x[, col_mo, drop = TRUE])
x$gramstain <- mo_gramstain(x[, col_mo, drop = TRUE], language = NULL)
x$key_ab <- NA_character_
# Gram +