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(v3.0.1.9014) try-again fix

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dr. M.S. (Matthijs) Berends
2026-01-07 15:10:21 +01:00
parent 85e8e814e8
commit 7b9c151241
3 changed files with 26 additions and 22 deletions
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2
DESCRIPTION
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@@ -1,5 +1,5 @@
Package: AMR Package: AMR
Version: 3.0.1.9013 Version: 3.0.1.9014
Date: 2026-01-07 Date: 2026-01-07
Title: Antimicrobial Resistance Data Analysis Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR) Description: Functions to simplify and standardise antimicrobial resistance (AMR)

2
NEWS.md
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@@ -1,4 +1,4 @@
# AMR 3.0.1.9013 # AMR 3.0.1.9014
### New ### New
* Integration with the **tidymodels** framework to allow seamless use of SIR, MIC and disk data in modelling pipelines via `recipes` * Integration with the **tidymodels** framework to allow seamless use of SIR, MIC and disk data in modelling pipelines via `recipes`

44
R/translate.R
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@@ -263,6 +263,30 @@ translate_into_language <- function(from,
df_trans$pattern[df_trans$regular_expr == TRUE] <- gsub("$$", "$", df_trans$pattern[df_trans$regular_expr == TRUE], fixed = TRUE) df_trans$pattern[df_trans$regular_expr == TRUE] <- gsub("$$", "$", df_trans$pattern[df_trans$regular_expr == TRUE], fixed = TRUE)
} }
# non-regex part
translate_tokens <- function(tokens) {
patterns <- df_trans$pattern[df_trans$regular_expr == FALSE]
replacements <- df_trans[[lang]][df_trans$regular_expr == FALSE]
matches <- match(tokens, patterns)
tokens[!is.na(matches)] <- replacements[matches[!is.na(matches)]]
tokens
}
from_unique_translated[order(nchar(from_unique_translated), decreasing = TRUE)] <- vapply(
FUN.VALUE = character(1),
USE.NAMES = FALSE,
from_unique_translated[order(nchar(from_unique_translated), decreasing = TRUE)],
function(x) {
delimiters <- "[ /()]"
split_regex <- paste0("(?<=", delimiters, ")|(?=", delimiters, ")")
tokens <- strsplit(x, split_regex, perl = TRUE)[[1]]
tokens <- translate_tokens(tokens)
out <- paste(tokens, collapse = "")
# also try with those tokens
out <- translate_tokens(out)
out
}
)
df_trans_regex <- df_trans[which(df_trans$regular_expr == TRUE), ] df_trans_regex <- df_trans[which(df_trans$regular_expr == TRUE), ]
# regex part # regex part
lapply( lapply(
@@ -279,26 +303,6 @@ translate_into_language <- function(from,
) )
} }
) )
# non-regex part
translate_tokens <- function(tokens) {
patterns <- df_trans$pattern[df_trans$regular_expr == FALSE]
replacements <- df_trans[[lang]][df_trans$regular_expr == FALSE]
matches <- match(tokens, patterns)
tokens[!is.na(matches)] <- replacements[matches[!is.na(matches)]]
tokens
}
from_unique_translated <- vapply(
FUN.VALUE = character(1),
USE.NAMES = FALSE,
from_unique_translated,
function(x) {
delimiters <- "[ /()]"
split_regex <- paste0("(?<=", delimiters, ")|(?=", delimiters, ")")
tokens <- strsplit(x, split_regex, perl = TRUE)[[1]]
tokens <- translate_tokens(tokens)
paste(tokens, collapse = "")
}
)
# force UTF-8 for diacritics # force UTF-8 for diacritics
from_unique_translated <- enc2utf8(from_unique_translated) from_unique_translated <- enc2utf8(from_unique_translated)