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use dplyr where available, new antibiogram() for WISCA, fixed Salmonella Typhi/Paratyphi

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dr. M.S. (Matthijs) Berends
2023-02-06 11:57:22 +01:00
parent 4b133d4c96
commit 9e99e66f01
69 changed files with 1670 additions and 650 deletions
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22
R/mo.R
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@ -561,10 +561,10 @@ pillar_shaft.mo <- function(x, ...) {
# markup NA and UNKNOWN
out[is.na(x)] <- font_na(" NA")
out[x == "UNKNOWN"] <- font_na(" UNKNOWN")
# markup manual codes
out[x %in% AMR_env$MO_lookup$mo & !x %in% AMR::microorganisms$mo] <- font_blue(out[x %in% AMR_env$MO_lookup$mo & !x %in% AMR::microorganisms$mo], collapse = NULL)
df <- tryCatch(get_current_data(arg_name = "x", call = 0),
error = function(e) NULL
)
@ -579,7 +579,7 @@ pillar_shaft.mo <- function(x, ...) {
(!is.null(df) && !all(unlist(df[, which(mo_cols), drop = FALSE]) %in% all_mos))) {
# markup old mo codes
out[!x %in% all_mos] <- font_italic(
font_na(x[!x %in% all_mos],
font_na(font_stripstyle(out[!x %in% all_mos]),
collapse = NULL
),
collapse = NULL
@ -627,7 +627,7 @@ freq.mo <- function(x, ...) {
.add_header = list(
`Gram-negative` = paste0(
format(sum(grams == "Gram-negative", na.rm = TRUE),
big.mark = ",",
big.mark = " ",
decimal.mark = "."
),
" (", percentage(sum(grams == "Gram-negative", na.rm = TRUE) / length(grams),
@ -637,7 +637,7 @@ freq.mo <- function(x, ...) {
),
`Gram-positive` = paste0(
format(sum(grams == "Gram-positive", na.rm = TRUE),
big.mark = ",",
big.mark = " ",
decimal.mark = "."
),
" (", percentage(sum(grams == "Gram-positive", na.rm = TRUE) / length(grams),
@ -645,8 +645,8 @@ freq.mo <- function(x, ...) {
),
")"
),
`Nr. of genera` = pm_n_distinct(mo_genus(x_noNA, language = NULL)),
`Nr. of species` = pm_n_distinct(paste(
`Nr. of genera` = n_distinct(mo_genus(x_noNA, language = NULL)),
`Nr. of species` = n_distinct(paste(
mo_genus(x_noNA, language = NULL),
mo_species(x_noNA, language = NULL)
))
@ -1155,14 +1155,14 @@ repair_reference_df <- function(reference_df) {
return(NULL)
}
# has valid own reference_df
reference_df <- reference_df %pm>%
pm_filter(!is.na(mo))
reference_df <- reference_df %>%
filter(!is.na(mo))
# keep only first two columns, second must be mo
if (colnames(reference_df)[1] == "mo") {
reference_df <- reference_df %pm>% pm_select(2, "mo")
reference_df <- reference_df %>% select(2, "mo")
} else {
reference_df <- reference_df %pm>% pm_select(1, "mo")
reference_df <- reference_df %>% select(1, "mo")
}
# remove factors, just keep characters