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fix for using dplyr::select()
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Package: AMR
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Version: 1.8.2.9130
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Version: 1.8.2.9131
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Date: 2023-02-15
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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
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# AMR 1.8.2.9130
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# AMR 1.8.2.9131
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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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@ -890,11 +890,12 @@ get_current_data <- function(arg_name, call) {
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!is.null(x) && is.data.frame(x)
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}
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# try a manual (base R) method, by going over all underlying environments with sys.frames()
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for (env in sys.frames()) {
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# dplyr support ----
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if (!is.null(env$mask) && is.function(env$mask$current_rows) && (valid_df(env$data) || valid_df(env$`.data`))) {
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frms <- sys.frames()
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# check dplyr environments to support dplyr groups
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with_mask <- vapply(FUN.VALUE = logical(1), frms, function(e) !is.null(e$mask))
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for (env in frms[which(with_mask)]) {
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if (is.function(env$mask$current_rows) && (valid_df(env$data) || valid_df(env$`.data`))) {
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# an element `.data` or `data` (containing all data) and `mask` (containing functions) will be in the environment when using dplyr verbs
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# we use their mask$current_rows() to get the group rows, since dplyr::cur_data_all() is deprecated and will be removed in the future
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# e.g. for `example_isolates %>% group_by(ward) %>% mutate(first = first_isolate(.))`
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@ -907,21 +908,28 @@ get_current_data <- function(arg_name, call) {
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}
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rows <- tryCatch(env$mask$current_rows(), error = function(e) seq_len(NROW(df)))
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return(df[rows, , drop = FALSE])
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# base R support ----
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} else if (!is.null(env$`.Generic`)) {
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# don't check `".Generic" %in% names(env)`, because in R < 3.2, `names(env)` is always NULL
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}
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}
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if (valid_df(env$xx)) {
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# an element `xx` will be in the environment for rows + cols in base R, e.g. `example_isolates[c(1:3), carbapenems()]`
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return(env$xx)
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} else if (valid_df(env$x)) {
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# an element `x` will be in the environment for only cols in base R, e.g. `example_isolates[, carbapenems()]`
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return(env$x)
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}
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# scoped dplyr support ----
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} else if (!is.null(names(env)) && all(c(".tbl", ".vars", ".cols") %in% names(env), na.rm = TRUE) && valid_df(env$`.tbl`)) {
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# now go over all underlying environments looking for other dplyr and base R selection environments
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with_generic <- vapply(FUN.VALUE = logical(1), frms, function(e) !is.null(e$`.Generic`))
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for (env in frms[which(with_generic)]) {
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if (valid_df(env$`.data`)) {
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# an element `.data` will be in the environment when using dplyr::select()
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return(env$`.data`)
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} else if (valid_df(env$xx)) {
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# an element `xx` will be in the environment for rows + cols in base R, e.g. `example_isolates[c(1:3), carbapenems()]`
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return(env$xx)
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} else if (valid_df(env$x)) {
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# an element `x` will be in the environment for only cols in base R, e.g. `example_isolates[, carbapenems()]`
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return(env$x)
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}
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}
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# now a special case for dplyr's 'scoped' variants
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with_tbl <- vapply(FUN.VALUE = logical(1), frms, function(e) valid_df(e$`.tbl`))
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for (env in frms[which(with_tbl)]) {
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if (!is.null(names(env)) && all(c(".tbl", ".vars", ".cols") %in% names(env), na.rm = TRUE)) {
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# an element `.tbl` will be in the environment when using scoped dplyr variants, with or without `dplyr::vars()`
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# (e.g. `dplyr::summarise_at()` or `dplyr::mutate_at()`)
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return(env$`.tbl`)
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