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2007c3eef3
Author | SHA1 | Date | |
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2007c3eef3 | |||
03294c7901 |
@ -1,5 +1,5 @@
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Package: AMR
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Version: 1.8.2.9114
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Version: 1.8.2.9116
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Date: 2023-02-10
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Title: Antimicrobial Resistance Data Analysis
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Description: Functions to simplify and standardise antimicrobial resistance (AMR)
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2
NEWS.md
2
NEWS.md
@ -1,4 +1,4 @@
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# AMR 1.8.2.9114
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# AMR 1.8.2.9116
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*(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)*
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@ -94,7 +94,9 @@ TAXONOMY_VERSION <- list(
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)
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globalVariables(c(
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".mo",
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".rowid",
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".syndromic_group",
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"ab",
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"ab_txt",
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"affect_ab_name",
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@ -105,8 +107,9 @@ globalVariables(c(
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"atc_group1",
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"atc_group2",
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"base_ab",
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"ci_min",
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"ci_max",
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"ci_min",
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"clinical_breakpoints",
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"code",
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"cols",
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"count",
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@ -130,14 +133,15 @@ globalVariables(c(
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"language",
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"lookup",
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"method",
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"mic",
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"mic ",
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"mic",
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"microorganism",
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"microorganisms",
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"microorganisms.codes",
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"mo",
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"name",
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"new",
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"numerator",
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"observations",
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"old",
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"old_name",
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@ -149,13 +153,14 @@ globalVariables(c(
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"reference.rule_group",
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"reference.version",
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"rowid",
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"sir",
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"clinical_breakpoints",
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"rule_group",
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"rule_name",
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"se_max",
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"se_min",
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"SI",
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"sir",
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"species",
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"syndromic_group",
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"total",
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"txt",
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"type",
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@ -64,20 +64,26 @@ pm_left_join <- function(x, y, by = NULL, suffix = c(".x", ".y")) {
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}
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# support where() like tidyverse:
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# adapted from https://github.com/nathaneastwood/poorman/blob/52eb6947e0b4430cd588976ed8820013eddf955f/R/where.R#L17-L32
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where <- function(fn) {
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# adapted from https://github.com/nathaneastwood/poorman/blob/52eb6947e0b4430cd588976ed8820013eddf955f/R/where.R#L17-L32
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if (!is.function(fn)) {
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stop(pm_deparse_var(fn), " is not a valid predicate function.")
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stop_("`", deparse(substitute(fn)), "()` is not a valid predicate function.")
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}
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df <- pm_select_env$.data
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cols <- pm_select_env$get_colnames()
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if (is.null(df)) {
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df <- get_current_data("where", call = FALSE)
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cols <- colnames(df)
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}
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preds <- unlist(lapply(
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pm_select_env$.data,
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df,
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function(x, fn) {
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do.call("fn", list(x))
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},
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fn
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))
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if (!is.logical(preds)) stop("`where()` must be used with functions that return `TRUE` or `FALSE`.")
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data_cols <- pm_select_env$get_colnames()
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if (!is.logical(preds)) stop_("`where()` must be used with functions that return `TRUE` or `FALSE`.")
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data_cols <- cols
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cols <- data_cols[preds]
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which(data_cols %in% cols)
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}
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@ -156,6 +162,20 @@ quick_case_when <- function(...) {
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out
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}
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bind_rows2 <- function(..., fill = NA) {
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# this AMAZING code is from ChatGPT: when I asked for a base R dplyr::bind_rows alternative
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dfs <- list(...)
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all_cols <- unique(unlist(lapply(dfs, colnames)))
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mat_list <- lapply(dfs, function(x) {
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mat <- matrix(NA, nrow = nrow(x), ncol = length(all_cols))
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colnames(mat) <- all_cols
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mat[, colnames(x)] <- as.matrix(x)
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mat
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})
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mat <- do.call(rbind, mat_list)
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as.data.frame(mat, stringsAsFactors = FALSE)
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}
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# No export, no Rd
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addin_insert_in <- function() {
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import_fn("insertText", "rstudioapi")(" %in% ")
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2
R/ab.R
2
R/ab.R
@ -495,7 +495,7 @@ as.ab <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
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# save to package env to save time for next time
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if (isTRUE(initial_search)) {
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AMR_env$ab_previously_coerced <- AMR_env$ab_previously_coerced[which(!AMR_env$ab_previously_coerced$x %in% x), , drop = FALSE]
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AMR_env$ab_previously_coerced <- unique(rbind(AMR_env$ab_previously_coerced,
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AMR_env$ab_previously_coerced <- unique(bind_rows2(AMR_env$ab_previously_coerced,
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data.frame(
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x = x,
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ab = x_new,
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@ -404,8 +404,8 @@ antibiogram <- function(x,
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if (i == 1) {
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new_df <- long_to_wide(out[which(out$syndromic_group == grp), , drop = FALSE], digs = digits)
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} else {
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new_df <- bind_rows(new_df,
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long_to_wide(out[which(out$syndromic_group == grp), , drop = FALSE], digs = digits))
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new_df <- bind_rows2(new_df,
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long_to_wide(out[which(out$syndromic_group == grp), , drop = FALSE], digs = digits))
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}
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}
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# sort rows
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2
R/av.R
2
R/av.R
@ -461,7 +461,7 @@ as.av <- function(x, flag_multiple_results = TRUE, info = interactive(), ...) {
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# save to package env to save time for next time
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if (isTRUE(initial_search)) {
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AMR_env$av_previously_coerced <- AMR_env$av_previously_coerced[which(!AMR_env$av_previously_coerced$x %in% x), , drop = FALSE]
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AMR_env$av_previously_coerced <- unique(rbind(AMR_env$av_previously_coerced,
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AMR_env$av_previously_coerced <- unique(bind_rows2(AMR_env$av_previously_coerced,
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data.frame(
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x = x,
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av = x_new,
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@ -124,7 +124,7 @@ bug_drug_combinations <- function(x,
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m <- as.matrix(table(x))
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data.frame(S = m["S", ], I = m["I", ], R = m["R", ], stringsAsFactors = FALSE)
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})
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merged <- do.call(rbind, pivot)
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merged <- do.call(bind_rows2, pivot)
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out_group <- data.frame(
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mo = rep(unique_mo[i], NROW(merged)),
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ab = rownames(merged),
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@ -144,14 +144,14 @@ bug_drug_combinations <- function(x,
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}
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out_group <- cbind(group_values, out_group)
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}
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out <- rbind(out, out_group, stringsAsFactors = FALSE)
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out <- bind_rows2(out, out_group)
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}
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out
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}
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# based on pm_apply_grouped_function
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apply_group <- function(.data, fn, groups, drop = FALSE, ...) {
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grouped <- pm_split_into_groups(.data, groups, drop)
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res <- do.call(rbind, unname(lapply(grouped, fn, ...)))
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res <- do.call(bind_rows2, unname(lapply(grouped, fn, ...)))
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if (any(groups %in% colnames(res))) {
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class(res) <- c("grouped_data", class(res))
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res <- pm_set_groups(res, groups[groups %in% colnames(res)])
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@ -165,7 +165,7 @@ bug_drug_combinations <- function(x,
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out <- run_it(x)
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}
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rownames(out) <- NULL
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out <- out %>% pm_arrange(mo, ab)
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out <- out %pm>% pm_arrange(mo, ab)
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out <- as_original_data_class(out, class(x.bak)) # will remove tibble groups
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structure(out, class = c("bug_drug_combinations", ifelse(data_has_groups, "grouped", character(0)), class(out)))
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}
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@ -153,7 +153,7 @@ add_custom_antimicrobials <- function(x) {
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# assign new values
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new_df[, col] <- x[, col, drop = TRUE]
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}
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AMR_env$AB_lookup <- unique(rbind(AMR_env$AB_lookup, new_df))
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AMR_env$AB_lookup <- unique(bind_rows2(AMR_env$AB_lookup, new_df))
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AMR_env$ab_previously_coerced <- AMR_env$ab_previously_coerced[which(!AMR_env$ab_previously_coerced$ab %in% x$ab), , drop = FALSE]
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class(AMR_env$AB_lookup$ab) <- c("ab", "character")
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@ -279,7 +279,7 @@ add_custom_microorganisms <- function(x) {
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# clear previous coercions
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suppressMessages(mo_reset_session())
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AMR_env$MO_lookup <- unique(rbind(AMR_env$MO_lookup, new_df))
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AMR_env$MO_lookup <- unique(bind_rows2(AMR_env$MO_lookup, new_df))
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class(AMR_env$MO_lookup$mo) <- c("mo", "character")
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if (nrow(x) <= 3) {
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message_("Added ", vector_and(italicise(x$fullname), quotes = FALSE), " to the internal `microorganisms` data set.")
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@ -475,7 +475,7 @@ eucast_rules <- function(x,
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amox$base_ab <- "AMX"
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amox$base_name <- ab_name("AMX", language = NULL)
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# merge and sort
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ab_enzyme <- rbind(ab_enzyme, ampi, amox)
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ab_enzyme <- bind_rows2(ab_enzyme, ampi, amox)
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ab_enzyme <- ab_enzyme[order(ab_enzyme$enzyme_name), , drop = FALSE]
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for (i in seq_len(nrow(ab_enzyme))) {
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@ -1161,10 +1161,8 @@ edit_sir <- function(x,
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)
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verbose_new <- verbose_new %pm>% pm_filter(old != new | is.na(old) | is.na(new) & !is.na(old))
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# save changes to data set 'verbose_info'
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track_changes$verbose_info <- rbind(track_changes$verbose_info,
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verbose_new,
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stringsAsFactors = FALSE
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)
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track_changes$verbose_info <- bind_rows2(track_changes$verbose_info,
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verbose_new)
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# count adds and changes
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track_changes$added <- track_changes$added + verbose_new %pm>%
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pm_filter(is.na(old)) %pm>%
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@ -1215,7 +1213,7 @@ eucast_dosage <- function(ab, administration = "iv", version_breakpoints = 12.0)
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)
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)
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}
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out <- do.call("rbind", lapply(lst, as.data.frame, stringsAsFactors = FALSE))
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out <- do.call("bind_rows2", lapply(lst, as.data.frame, stringsAsFactors = FALSE))
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rownames(out) <- NULL
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out$ab <- ab
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out$name <- ab_name(ab, language = NULL)
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12
R/mo.R
12
R/mo.R
@ -325,7 +325,7 @@ as.mo <- function(x,
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result_mo <- NA_character_
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} else {
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result_mo <- AMR_env$MO_lookup$mo[match(top_hits[1], AMR_env$MO_lookup$fullname)]
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AMR_env$mo_uncertainties <- rbind(AMR_env$mo_uncertainties,
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AMR_env$mo_uncertainties <- bind_rows2(AMR_env$mo_uncertainties,
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data.frame(
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original_input = x_search,
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input = x_search_cleaned,
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@ -339,7 +339,7 @@ as.mo <- function(x,
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stringsAsFactors = FALSE
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)
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# save to package env to save time for next time
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AMR_env$mo_previously_coerced <- unique(rbind(AMR_env$mo_previously_coerced,
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AMR_env$mo_previously_coerced <- unique(bind_rows2(AMR_env$mo_previously_coerced,
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data.frame(
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x = paste(x_search, minimum_matching_score),
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mo = result_mo,
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@ -966,14 +966,14 @@ convert_colloquial_input <- function(x) {
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out[x %like_case% "(viridans.* (strepto|^s).*|^vgs[^a-z]*$)"] <- "B_STRPT_VIRI"
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# Salmonella in different languages, like "Salmonella grupo B"
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out[x %like_case% "salmonella.* [bcd]$"] <- gsub(".*salmonella.* ([bcd])$",
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out[x %like_case% "salmonella.* [abcd]$"] <- gsub(".*salmonella.* ([abcd])$",
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"B_SLMNL_GRP\\U\\1",
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x[x %like_case% "salmonella.* [bcd]$"],
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x[x %like_case% "salmonella.* [abcd]$"],
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perl = TRUE
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)
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out[x %like_case% "group [bcd] salmonella"] <- gsub(".*group ([bcd]) salmonella*",
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out[x %like_case% "group [abcd] salmonella"] <- gsub(".*group ([abcd]) salmonella*",
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"B_SLMNL_GRP\\U\\1",
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x[x %like_case% "group [bcd] salmonella"],
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x[x %like_case% "group [abcd] salmonella"],
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perl = TRUE
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)
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|
@ -69,9 +69,8 @@
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#' @return
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#' - An [integer] in case of [mo_year()]
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#' - An [ordered factor][factor] in case of [mo_pathogenicity()]
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#' - A [list] in case of [mo_taxonomy()], [mo_synonyms()] and [mo_info()]
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#' - A [list] in case of [mo_taxonomy()], [mo_synonyms()], [mo_snomed()] and [mo_info()]
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#' - A named [character] in case of [mo_url()]
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#' - A [numeric] in case of [mo_snomed()]
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#' - A [character] in all other cases
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#' @export
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#' @seealso Data set [microorganisms]
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|
6
R/plot.R
6
R/plot.R
@ -585,17 +585,17 @@ plot.sir <- function(x,
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data$s <- round((data$n / sum(data$n)) * 100, 1)
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if (!"S" %in% data$x) {
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data <- rbind(data, data.frame(x = "S", n = 0, s = 0, stringsAsFactors = FALSE),
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data <- bind_rows2(data, data.frame(x = "S", n = 0, s = 0, stringsAsFactors = FALSE),
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stringsAsFactors = FALSE
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)
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}
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if (!"I" %in% data$x) {
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data <- rbind(data, data.frame(x = "I", n = 0, s = 0, stringsAsFactors = FALSE),
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data <- bind_rows2(data, data.frame(x = "I", n = 0, s = 0, stringsAsFactors = FALSE),
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stringsAsFactors = FALSE
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)
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}
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if (!"R" %in% data$x) {
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data <- rbind(data, data.frame(x = "R", n = 0, s = 0, stringsAsFactors = FALSE),
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data <- bind_rows2(data, data.frame(x = "R", n = 0, s = 0, stringsAsFactors = FALSE),
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stringsAsFactors = FALSE
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)
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}
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|
2
R/sir.R
2
R/sir.R
@ -998,7 +998,7 @@ as_sir_method <- function(method_short,
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}
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# write to verbose output
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AMR_env$sir_interpretation_history <- rbind(
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AMR_env$sir_interpretation_history <- bind_rows2(
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AMR_env$sir_interpretation_history,
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# recycling 1 to 2 rows does not seem to work, which is why rep() was added
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data.frame(
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|
@ -322,7 +322,7 @@ sir_calc_df <- function(type, # "proportion", "count" or "both"
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}
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out_new <- cbind(group_values, out_new)
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}
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out <- rbind(out, out_new, stringsAsFactors = FALSE)
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out <- bind_rows2(out, out_new)
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}
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}
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out
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@ -331,7 +331,7 @@ sir_calc_df <- function(type, # "proportion", "count" or "both"
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# based on pm_apply_grouped_function
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apply_group <- function(.data, fn, groups, drop = FALSE, ...) {
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grouped <- pm_split_into_groups(.data, groups, drop)
|
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res <- do.call(rbind, unname(lapply(grouped, fn, ...)))
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res <- do.call(bind_rows2, unname(lapply(grouped, fn, ...)))
|
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if (any(groups %in% colnames(res))) {
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class(res) <- c("grouped_data", class(res))
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res <- pm_set_groups(res, groups[groups %in% colnames(res)])
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||||
|
@ -163,7 +163,7 @@ expect_identical(mo_current(c("Escherichia blattae", "Escherichia coli")),
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expect_identical(mo_ref("Chlamydia psittaci"), "Garcia-Lopez et al., 2019")
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expect_identical(mo_ref("Chlamydophila psittaci", keep_synonyms = TRUE), "Everett et al., 1999")
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expect_true(112283007 %in% mo_snomed("Escherichia coli"))
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expect_true(112283007 %in% mo_snomed("Escherichia coli")[[1]])
|
||||
# old codes must throw a warning in mo_* family
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expect_warning(mo_name(c("B_ESCHR_COL", "B_STPHY_AUR")))
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||||
# outcome of mo_fullname must always return the fullname from the data set
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||||
|
@ -284,9 +284,8 @@ mo_property(
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\itemize{
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\item An \link{integer} in case of \code{\link[=mo_year]{mo_year()}}
|
||||
\item An \link[=factor]{ordered factor} in case of \code{\link[=mo_pathogenicity]{mo_pathogenicity()}}
|
||||
\item A \link{list} in case of \code{\link[=mo_taxonomy]{mo_taxonomy()}}, \code{\link[=mo_synonyms]{mo_synonyms()}} and \code{\link[=mo_info]{mo_info()}}
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\item A \link{list} in case of \code{\link[=mo_taxonomy]{mo_taxonomy()}}, \code{\link[=mo_synonyms]{mo_synonyms()}}, \code{\link[=mo_snomed]{mo_snomed()}} and \code{\link[=mo_info]{mo_info()}}
|
||||
\item A named \link{character} in case of \code{\link[=mo_url]{mo_url()}}
|
||||
\item A \link{numeric} in case of \code{\link[=mo_snomed]{mo_snomed()}}
|
||||
\item A \link{character} in all other cases
|
||||
}
|
||||
}
|
||||
|
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Reference in New Issue
Block a user