mirror of
https://github.com/msberends/AMR.git
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776 lines
23 KiB
R
776 lines
23 KiB
R
# ==================================================================== #
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# TITLE #
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# Antimicrobial Resistance (AMR) Analysis #
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# #
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# SOURCE #
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# https://gitlab.com/msberends/AMR #
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# #
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# LICENCE #
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# (c) 2018-2020 Berends MS, Luz CF et al. #
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# #
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# This R package is free software; you can freely use and distribute #
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# it for both personal and commercial purposes under the terms of the #
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# GNU General Public License version 2.0 (GNU GPL-2), as published by #
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# the Free Software Foundation. #
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# #
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# We created this package for both routine data analysis and academic #
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# research and it was publicly released in the hope that it will be #
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# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# Visit our website for more info: https://msberends.gitlab.io/AMR. #
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# ==================================================================== #
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# ------------------------------------------------
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# THIS FILE WAS CREATED AUTOMATICALLY!
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# Source file: data-raw/reproduction_of_poorman.R
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# ------------------------------------------------
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# Poorman: a package to replace all dplyr functions with base R so we can lose dependency on dplyr.
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# These functions were downloaded from https://github.com/nathaneastwood/poorman,
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# from this commit: https://github.com/nathaneastwood/poorman/tree/7d76d77f8f7bc663bf30fb5a161abb49801afa17
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#
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# All code below was released under MIT license, that permits 'free of charge, to any person obtaining a
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# copy of the software and associated documentation files (the "Software"), to deal in the Software
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# without restriction, including without limitation the rights to use, copy, modify, merge, publish,
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# distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software
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# is furnished to do so', given that a copyright notice is given in the software.
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#
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# Copyright notice as found on https://github.com/nathaneastwood/poorman/blob/master/LICENSE on 2 May 2020:
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# YEAR: 2020
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# COPYRIGHT HOLDER: Nathan Eastwood
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arrange <- function(.data, ...) {
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check_is_dataframe(.data)
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if ("grouped_data" %in% class(.data)) {
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arrange.grouped_data(.data, ...)
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} else {
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arrange.default(.data, ...)
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}
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}
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arrange.default <- function(.data, ...) {
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rows <- eval.parent(substitute(with(.data, order(...))))
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.data[rows, , drop = FALSE]
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}
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arrange.grouped_data <- function(.data, ...) {
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apply_grouped_function(.data, "arrange", ...)
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}
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between <- function(x, left, right) {
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if (!is.null(attr(x, "class")) && !inherits(x, c("Date", "POSIXct"))) {
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warning("`between()` called on numeric vector with S3 class")
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}
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if (!is.double(x)) x <- as.numeric(x)
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x >= as.numeric(left) & x <= as.numeric(right)
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}
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count <- function(x, ..., wt = NULL, sort = FALSE, name = NULL) {
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groups <- get_groups(x)
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if (!missing(...)) x <- group_by(x, ..., .add = TRUE)
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wt <- deparse_var(wt)
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res <- do.call(tally, list(x, wt, sort, name))
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if (length(groups) > 0L) res <- do.call(group_by, list(res, as.name(groups)))
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res
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}
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tally <- function(x, wt = NULL, sort = FALSE, name = NULL) {
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name <- check_name(x, name)
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wt <- deparse_var(wt)
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res <- do.call(summarise, set_names(list(x, as.name(tally_n(x, wt))), c(".data", name)))
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res <- ungroup(res)
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if (isTRUE(sort)) res <- do.call(arrange, list(res, call("desc", as.name(name))))
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rownames(res) <- NULL
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res
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}
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add_count <- function(x, ..., wt = NULL, sort = FALSE, name = NULL) {
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name <- check_name(x, name)
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row_names <- rownames(x)
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wt <- deparse_var(wt)
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if (!missing(...)) x <- group_by(x, ..., .add = TRUE)
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res <- do.call(add_tally, list(x, wt, sort, name))
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res[row_names, ]
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}
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add_tally <- function(x, wt = NULL, sort = FALSE, name = NULL) {
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wt <- deparse_var(wt)
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n <- tally_n(x, wt)
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name <- check_name(x, name)
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res <- do.call(mutate, set_names(list(x, as.name(n)), c(".data", name)))
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if (isTRUE(sort)) {
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do.call(arrange, list(res, call("desc", as.name(name))))
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} else {
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res
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}
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}
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tally_n <- function(x, wt) {
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if (is.null(wt) && "n" %in% colnames(x)) {
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message("Using `n` as weighting variable")
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wt <- "n"
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}
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context$.data <- x
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on.exit(rm(list = ".data", envir = context))
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if (is.null(wt)) {
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"n()"
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} else {
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paste0("sum(", wt, ", na.rm = TRUE)")
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}
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}
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check_name <- function(df, name) {
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if (is.null(name)) {
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if ("n" %in% colnames(df)) {
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stop(
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"Column 'n' is already present in output\n",
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"* Use `name = \"new_name\"` to pick a new name"
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)
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}
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return("n")
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}
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if (!is.character(name) || length(name) != 1) {
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stop("`name` must be a single string")
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}
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name
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}
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desc <- function(x) -xtfrm(x)
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select_env <- new.env()
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peek_vars <- function() {
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get(".col_names", envir = select_env)
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}
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context <- new.env()
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n <- function() {
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do.call(nrow, list(quote(.data)), envir = context)
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}
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filter <- function(.data, ...) {
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check_is_dataframe(.data)
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if ("grouped_data" %in% class(.data)) {
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filter.grouped_data(.data, ...)
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} else {
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filter.default(.data, ...)
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}
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}
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filter.default <- function(.data, ...) {
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conditions <- paste(deparse_dots(...), collapse = " & ")
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context$.data <- .data
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on.exit(rm(.data, envir = context))
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.data[do.call(with, list(.data, str2lang(unname(conditions)))), ]
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}
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filter.grouped_data <- function(.data, ...) {
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rows <- rownames(.data)
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res <- apply_grouped_function(.data, "filter", ...)
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res[rows[rows %in% rownames(res)], ]
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}
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group_by <- function(.data, ..., .add = FALSE) {
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check_is_dataframe(.data)
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pre_groups <- get_groups(.data)
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groups <- deparse_dots(...)
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if (isTRUE(.add)) groups <- unique(c(pre_groups, groups))
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unknown <- !(groups %in% colnames(.data))
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if (any(unknown)) stop("Invalid groups: ", groups[unknown])
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structure(.data, class = c("grouped_data", class(.data)), groups = groups)
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}
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ungroup <- function(x, ...) {
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check_is_dataframe(x)
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rm_groups <- deparse_dots(...)
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groups <- attr(x, "groups")
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if (length(rm_groups) == 0L) rm_groups <- groups
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attr(x, "groups") <- groups[!(groups %in% rm_groups)]
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if (length(attr(x, "groups")) == 0L) {
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attr(x, "groups") <- NULL
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class(x) <- class(x)[!(class(x) %in% "grouped_data")]
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}
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x
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}
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get_groups <- function(x) {
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attr(x, "groups", exact = TRUE)
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}
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has_groups <- function(x) {
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groups <- get_groups(x)
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if (is.null(groups)) FALSE else TRUE
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}
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set_groups <- function(x, groups) {
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attr(x, "groups") <- groups
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x
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}
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apply_grouped_function <- function(.data, fn, ...) {
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groups <- get_groups(.data)
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grouped <- split_into_groups(.data, groups)
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res <- do.call(rbind, 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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attr(res, "groups") <- groups[groups %in% colnames(res)]
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}
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res
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}
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split_into_groups <- function(.data, groups) {
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class(.data) <- "data.frame"
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group_factors <- lapply(groups, function(x, .data) as.factor(.data[, x]), .data)
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res <- split(x = .data, f = group_factors)
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res
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}
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print.grouped_data <- function(x, ..., digits = NULL, quote = FALSE, right = TRUE, row.names = TRUE, max = NULL) {
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class(x) <- "data.frame"
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print(x, ..., digits = digits, quote = quote, right = right, row.names = row.names, max = max)
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cat("\nGroups: ", paste(attr(x, "groups", exact = TRUE), collapse = ", "), "\n\n")
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}
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if_else <- function(condition, true, false, missing = NULL) {
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if (!is.logical(condition)) stop("`condition` must be a logical vector.")
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cls_true <- class(true)
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cls_false <- class(false)
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cls_missing <- class(missing)
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if (!identical(cls_true, cls_false)) {
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stop("The class of `true` <", class(true), "> is not the same as the class of `false` <", class(false), ">")
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}
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if (!is.null(missing) && !identical(cls_true, cls_missing)) {
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stop("`missing` must be a ", cls_true, " vector, not a ", cls_missing, " vector.")
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}
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res <- ifelse(condition, true, false)
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if (!is.null(missing)) res[is.na(res)] <- missing
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attributes(res) <- attributes(true)
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res
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}
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inner_join <- function(x, y, by = NULL, suffix = c(".x", ".y")) {
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join_worker(x = x, y = y, by = by, suffix = suffix, sort = FALSE)
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}
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left_join <- function(x, y, by = NULL, suffix = c(".x", ".y")) {
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join_worker(x = x, y = y, by = by, suffix = suffix, all.x = TRUE)
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}
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right_join <- function(x, y, by = NULL, suffix = c(".x", ".y")) {
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join_worker(x = x, y = y, by = by, suffix = suffix, all.y = TRUE)
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}
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full_join <- function(x, y, by = NULL, suffix = c(".x", ".y")) {
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join_worker(x = x, y = y, by = by, suffix = suffix, all = TRUE)
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}
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join_worker <- function(x, y, by = NULL, suffix = c(".x", ".y"), ...) {
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x[, ".join_id"] <- seq_len(nrow(x))
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if (is.null(by)) {
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by <- intersect(names(x), names(y))
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join_message(by)
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merged <- merge(x = x, y = y, by = by, suffixes = suffix, ...)[, union(names(x), names(y))]
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} else if (is.null(names(by))) {
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merged <- merge(x = x, y = y, by = by, suffixes = suffix, ...)
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} else {
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merged <- merge(x = x, y = y, by.x = names(by), by.y = by, suffixes = suffix, ...)
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}
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merged <- merged[order(merged[, ".join_id"]), colnames(merged) != ".join_id"]
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rownames(merged) <- NULL
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merged
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}
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join_message <- function(by) {
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if (length(by) > 1L) {
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message("Joining, by = c(\"", paste0(by, collapse = "\", \""), "\")\n", sep = "")
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} else {
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message("Joining, by = \"", by, "\"\n", sep = "")
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}
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}
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anti_join <- function(x, y, by = NULL) {
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filter_join_worker(x, y, by, type = "anti")
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}
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semi_join <- function(x, y, by = NULL) {
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filter_join_worker(x, y, by, type = "semi")
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}
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# filter_join_worker <- function(x, y, by = NULL, type = c("anti", "semi")) {
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# type <- match.arg(type, choices = c("anti", "semi"), several.ok = FALSE)
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# if (is.null(by)) {
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# by <- intersect(names(x), names(y))
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# join_message(by)
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# }
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# rows <- interaction(x[, by]) %in% interaction(y[, by])
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# if (type == "anti") rows <- !rows
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# res <- x[rows, ]
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# rownames(res) <- NULL
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# res
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# }
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lag <- function (x, n = 1L, default = NA) {
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if (inherits(x, "ts")) stop("`x` must be a vector, not a `ts` object, do you want `stats::lag()`?")
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if (length(n) != 1L || !is.numeric(n) || n < 0L) stop("`n` must be a nonnegative integer scalar")
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if (n == 0L) return(x)
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tryCatch(
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storage.mode(default) <- typeof(x),
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warning = function(w) {
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stop("Cannot convert `default` <", typeof(default), "> to `x` <", typeof(x), ">")
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}
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)
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xlen <- length(x)
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n <- pmin(n, xlen)
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res <- c(rep(default, n), x[seq_len(xlen - n)])
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attributes(res) <- attributes(x)
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res
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}
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lead <- function (x, n = 1L, default = NA) {
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if (length(n) != 1L || !is.numeric(n) || n < 0L) stop("n must be a nonnegative integer scalar")
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if (n == 0L) return(x)
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tryCatch(
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storage.mode(default) <- typeof(x),
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warning = function(w) {
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stop("Cannot convert `default` <", typeof(default), "> to `x` <", typeof(x), ">")
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}
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)
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xlen <- length(x)
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n <- pmin(n, xlen)
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res <- c(x[-seq_len(n)], rep(default, n))
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attributes(res) <- attributes(x)
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res
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}
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mutate <- function(.data, ...) {
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check_is_dataframe(.data)
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if ("grouped_data" %in% class(.data)) {
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mutate.grouped_data(.data, ...)
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} else {
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mutate.default(.data, ...)
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}
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}
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mutate.default <- function(.data, ...) {
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conditions <- deparse_dots(...)
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cond_names <- names(conditions)
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unnamed <- which(nchar(cond_names) == 0L)
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if (is.null(cond_names)) {
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names(conditions) <- conditions
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} else if (length(unnamed) > 0L) {
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names(conditions)[unnamed] <- conditions[unnamed]
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}
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not_matched <- names(conditions)[!names(conditions) %in% names(.data)]
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.data[, not_matched] <- NA
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context$.data <- .data
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on.exit(rm(.data, envir = context))
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for (i in seq_along(conditions)) {
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.data[, names(conditions)[i]] <- do.call(with, list(.data, str2lang(unname(conditions)[i])))
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}
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.data
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}
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mutate.grouped_data <- function(.data, ...) {
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rows <- rownames(.data)
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res <- apply_grouped_function(.data, "mutate", ...)
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res[rows, ]
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}
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n_distinct <- function(..., na.rm = FALSE) {
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res <- c(...)
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if (is.list(res)) return(nrow(unique(as.data.frame(res, stringsAsFactors = FALSE))))
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if (isTRUE(na.rm)) res <- res[!is.na(res)]
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length(unique(res))
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}
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`%>%` <- function(lhs, rhs) {
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lhs <- substitute(lhs)
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rhs <- substitute(rhs)
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eval(as.call(c(rhs[[1L]], lhs, as.list(rhs[-1L]))), envir = parent.frame())
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}
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pull <- function(.data, var = -1) {
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var_deparse <- deparse_var(var)
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col_names <- colnames(.data)
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if (!(var_deparse %in% col_names) & grepl("^[[:digit:]]+L|[[:digit:]]", var_deparse)) {
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var <- as.integer(gsub("L", "", var_deparse))
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var <- if_else(var < 1L, rev(col_names)[abs(var)], col_names[var])
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} else if (var_deparse %in% col_names) {
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var <- var_deparse
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}
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.data[, var]
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}
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relocate <- function(.data, ..., .before = NULL, .after = NULL) {
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check_is_dataframe(.data)
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data_names <- colnames(.data)
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col_pos <- select_positions(.data, ...)
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.before <- deparse_var(.before)
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.after <- deparse_var(.after)
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has_before <- !is.null(.before)
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has_after <- !is.null(.after)
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if (has_before && has_after) {
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stop("You must supply only one of `.before` and `.after`")
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} else if (has_before) {
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where <- min(match(.before, data_names))
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col_pos <- c(setdiff(col_pos, where), where)
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} else if (has_after) {
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where <- max(match(.after, data_names))
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col_pos <- c(where, setdiff(col_pos, where))
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} else {
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where <- 1L
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col_pos <- union(col_pos, where)
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}
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lhs <- setdiff(seq(1L, where - 1L), col_pos)
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rhs <- setdiff(seq(where + 1L, ncol(.data)), col_pos)
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col_pos <- unique(c(lhs, col_pos, rhs))
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col_pos <- col_pos[col_pos <= length(data_names)]
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res <- .data[col_pos]
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if (has_groups(.data)) res <- set_groups(res, get_groups(.data))
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res
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}
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rename <- function(.data, ...) {
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check_is_dataframe(.data)
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new_names <- names(deparse_dots(...))
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if (length(new_names) == 0L) {
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warning("You didn't give any new names")
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return(.data)
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}
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col_pos <- select_positions(.data, ...)
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old_names <- colnames(.data)[col_pos]
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new_names_zero <- nchar(new_names) == 0L
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if (any(new_names_zero)) {
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warning("You didn't provide new names for: ", paste0("`", old_names[new_names_zero], collapse = ", "), "`")
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new_names[new_names_zero] <- old_names[new_names_zero]
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}
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colnames(.data)[col_pos] <- new_names
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.data
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}
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rownames_to_column <- function(.data, var = "rowname") {
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check_is_dataframe(.data)
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col_names <- colnames(.data)
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if (var %in% col_names) stop("Column `", var, "` already exists in `.data`")
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.data[, var] <- rownames(.data)
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rownames(.data) <- NULL
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.data[, c(var, setdiff(col_names, var))]
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}
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select <- function(.data, ...) {
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|
map <- names(deparse_dots(...))
|
|
col_pos <- select_positions(.data, ..., group_pos = TRUE)
|
|
res <- .data[, col_pos, drop = FALSE]
|
|
to_map <- nchar(map) > 0L
|
|
colnames(res)[to_map] <- map[to_map]
|
|
if (has_groups(.data)) res <- set_groups(res, get_groups(.data))
|
|
res
|
|
}
|
|
starts_with <- function(match, ignore.case = TRUE, vars = peek_vars()) {
|
|
grep(pattern = paste0("^", paste0(match, collapse = "|^")), x = vars, ignore.case = ignore.case)
|
|
}
|
|
|
|
ends_with <- function(match, ignore.case = TRUE, vars = peek_vars()) {
|
|
grep(pattern = paste0(paste0(match, collapse = "$|"), "$"), x = vars, ignore.case = ignore.case)
|
|
}
|
|
|
|
contains <- function(match, ignore.case = TRUE, vars = peek_vars()) {
|
|
matches <- lapply(
|
|
match,
|
|
function(x) {
|
|
if (isTRUE(ignore.case)) {
|
|
match_u <- toupper(x)
|
|
match_l <- tolower(x)
|
|
pos_u <- grep(pattern = match_u, x = toupper(vars), fixed = TRUE)
|
|
pos_l <- grep(pattern = match_l, x = tolower(vars), fixed = TRUE)
|
|
unique(c(pos_l, pos_u))
|
|
} else {
|
|
grep(pattern = x, x = vars, fixed = TRUE)
|
|
}
|
|
}
|
|
)
|
|
unique(matches)
|
|
}
|
|
|
|
matches <- function(match, ignore.case = TRUE, perl = FALSE, vars = peek_vars()) {
|
|
grep(pattern = match, x = vars, ignore.case = ignore.case, perl = perl)
|
|
}
|
|
|
|
num_range <- function(prefix, range, width = NULL, vars = peek_vars()) {
|
|
if (!is.null(width)) {
|
|
range <- sprintf(paste0("%0", width, "d"), range)
|
|
}
|
|
find <- paste0(prefix, range)
|
|
if (any(duplicated(vars))) {
|
|
stop("Column names must be unique")
|
|
} else {
|
|
x <- match(find, vars)
|
|
x[!is.na(x)]
|
|
}
|
|
}
|
|
|
|
all_of <- function(x, vars = peek_vars()) {
|
|
x_ <- !x %in% vars
|
|
if (any(x_)) {
|
|
which_x_ <- which(x_)
|
|
if (length(which_x_) == 1L) {
|
|
stop("The column ", x[which_x_], " does not exist.")
|
|
} else {
|
|
stop("The columns ", paste(x[which_x_], collapse = ", "), " do not exist.")
|
|
}
|
|
} else {
|
|
which(vars %in% x)
|
|
}
|
|
}
|
|
|
|
any_of <- function(x, vars = peek_vars()) {
|
|
which(vars %in% x)
|
|
}
|
|
|
|
everything <- function(vars = peek_vars()) {
|
|
seq_along(vars)
|
|
}
|
|
|
|
last_col <- function(offset = 0L, vars = peek_vars()) {
|
|
if (!is_wholenumber(offset)) stop("`offset` must be an integer")
|
|
n <- length(vars)
|
|
if (offset && n <= offset) {
|
|
stop("`offset` must be smaller than the number of `vars`")
|
|
} else if (n == 0) {
|
|
stop("Can't select last column when `vars` is empty")
|
|
} else {
|
|
n - offset
|
|
}
|
|
}
|
|
select_positions <- function(.data, ..., group_pos = FALSE) {
|
|
cols <- eval(substitute(alist(...)))
|
|
data_names <- colnames(.data)
|
|
select_env$.col_names <- data_names
|
|
on.exit(rm(list = ".col_names", envir = select_env))
|
|
exec_env <- parent.frame(2L)
|
|
pos <- unlist(lapply(cols, eval_expr, exec_env = exec_env))
|
|
if (isTRUE(group_pos)) {
|
|
groups <- get_groups(.data)
|
|
missing_groups <- !(groups %in% cols)
|
|
if (any(missing_groups)) {
|
|
message("Adding missing grouping variables: `", paste(groups[missing_groups], collapse = "`, `"), "`")
|
|
pos <- c(match(groups[missing_groups], data_names), pos)
|
|
}
|
|
}
|
|
unique(pos)
|
|
}
|
|
|
|
eval_expr <- function(x, exec_env) {
|
|
type <- typeof(x)
|
|
switch(
|
|
type,
|
|
"integer" = x,
|
|
"double" = as.integer(x),
|
|
"character" = select_char(x),
|
|
"symbol" = select_symbol(x, exec_env = exec_env),
|
|
"language" = eval_call(x),
|
|
stop("Expressions of type <", typeof(x), "> cannot be evaluated for use when subsetting.")
|
|
)
|
|
}
|
|
|
|
select_char <- function(expr) {
|
|
pos <- match(expr, select_env$.col_names)
|
|
if (is.na(pos)) stop("Column `", expr, "` does not exist")
|
|
pos
|
|
}
|
|
|
|
select_symbol <- function(expr, exec_env) {
|
|
res <- try(select_char(as.character(expr)), silent = TRUE)
|
|
if (inherits(res, "try-error")) {
|
|
res <- tryCatch(
|
|
select_char(eval(expr, envir = exec_env)),
|
|
error = function(e) stop("Column ", expr, " does not exist.")
|
|
)
|
|
}
|
|
res
|
|
}
|
|
|
|
eval_call <- function(x) {
|
|
type <- as.character(x[[1]])
|
|
switch(
|
|
type,
|
|
`:` = select_seq(x),
|
|
`!` = select_negate(x),
|
|
`-` = select_minus(x),
|
|
`c` = select_c(x),
|
|
`(` = select_bracket(x),
|
|
select_context(x)
|
|
)
|
|
}
|
|
|
|
select_seq <- function(expr) {
|
|
x <- eval_expr(expr[[2]])
|
|
y <- eval_expr(expr[[3]])
|
|
x:y
|
|
}
|
|
|
|
select_negate <- function(expr) {
|
|
x <- if (is_negated_colon(expr)) {
|
|
expr <- call(":", expr[[2]][[2]], expr[[2]][[3]][[2]])
|
|
eval_expr(expr)
|
|
} else {
|
|
eval_expr(expr[[2]])
|
|
}
|
|
x * -1L
|
|
}
|
|
|
|
is_negated_colon <- function(expr) {
|
|
expr[[1]] == "!" && length(expr[[2]]) > 1L && expr[[2]][[1]] == ":" && expr[[2]][[3]][[1]] == "!"
|
|
}
|
|
|
|
select_minus <- function(expr) {
|
|
x <- eval_expr(expr[[2]])
|
|
x * -1L
|
|
}
|
|
|
|
select_c <- function(expr) {
|
|
lst_expr <- as.list(expr)
|
|
lst_expr[[1]] <- NULL
|
|
unlist(lapply(lst_expr, eval_expr))
|
|
}
|
|
|
|
select_bracket <- function(expr) {
|
|
eval_expr(expr[[2]])
|
|
}
|
|
|
|
select_context <- function(expr) {
|
|
eval(expr, envir = context$.data)
|
|
}
|
|
slice <- function(.data, ...) {
|
|
check_is_dataframe(.data)
|
|
if ("grouped_data" %in% class(.data)) {
|
|
slice.grouped_data(.data, ...)
|
|
} else {
|
|
slice.default(.data, ...)
|
|
}
|
|
}
|
|
|
|
slice.default <- function(.data, ...) {
|
|
rows <- c(...)
|
|
stopifnot(is.numeric(rows) | is.integer(rows))
|
|
if (all(rows > 0L)) rows <- rows[rows <= nrow(.data)]
|
|
.data[rows, ]
|
|
}
|
|
|
|
slice.grouped_data <- function(.data, ...) {
|
|
apply_grouped_function(.data, "slice", ...)
|
|
}
|
|
summarise <- function(.data, ...) {
|
|
check_is_dataframe(.data)
|
|
if ("grouped_data" %in% class(.data)) {
|
|
summarise.grouped_data(.data, ...)
|
|
} else {
|
|
summarise.default(.data, ...)
|
|
}
|
|
}
|
|
|
|
summarise.default <- function(.data, ...) {
|
|
fns <- vapply(substitute(...()), deparse, NA_character_)
|
|
context$.data <- .data
|
|
on.exit(rm(.data, envir = context))
|
|
if (has_groups(.data)) {
|
|
group <- unique(.data[, get_groups(.data), drop = FALSE])
|
|
if (nrow(group) == 0L) return(NULL)
|
|
}
|
|
res <- lapply(fns, function(x) do.call(with, list(.data, str2lang(x))))
|
|
res <- as.data.frame(res)
|
|
fn_names <- names(fns)
|
|
colnames(res) <- if (is.null(fn_names)) fns else fn_names
|
|
if (has_groups(.data)) res <- cbind(group, res)
|
|
res
|
|
}
|
|
|
|
summarise.grouped_data <- function(.data, ...) {
|
|
groups <- get_groups(.data)
|
|
res <- apply_grouped_function(.data, "summarise", ...)
|
|
res <- res[do.call(order, lapply(groups, function(x) res[, x])), ]
|
|
rownames(res) <- NULL
|
|
res
|
|
}
|
|
|
|
summarize <- summarise
|
|
summarize.default <- summarise.default
|
|
summarize.grouped_data <- summarise.grouped_data
|
|
transmute <- function(.data, ...) {
|
|
check_is_dataframe(.data)
|
|
if ("grouped_data" %in% class(.data)) {
|
|
transmute.grouped_data(.data, ...)
|
|
} else {
|
|
transmute.default(.data, ...)
|
|
}
|
|
}
|
|
|
|
transmute.default <- function(.data, ...) {
|
|
conditions <- deparse_dots(...)
|
|
mutated <- mutate(.data, ...)
|
|
mutated[, names(conditions), drop = FALSE]
|
|
}
|
|
|
|
transmute.grouped_data <- function(.data, ...) {
|
|
rows <- rownames(.data)
|
|
res <- apply_grouped_function(.data, "transmute", ...)
|
|
res[rows, ]
|
|
}
|
|
deparse_dots <- function(...) {
|
|
vapply(substitute(...()), deparse, NA_character_)
|
|
}
|
|
|
|
deparse_var <- function(var) {
|
|
sub_var <- eval(substitute(substitute(var)), parent.frame())
|
|
if (is.symbol(sub_var)) var <- as.character(sub_var)
|
|
var
|
|
}
|
|
|
|
check_is_dataframe <- function(.data) {
|
|
parent_fn <- all.names(sys.call(-1L), max.names = 1L)
|
|
if (!is.data.frame(.data)) stop(parent_fn, " must be given a data.frame")
|
|
invisible()
|
|
}
|
|
|
|
is_wholenumber <- function(x) {
|
|
x %% 1L == 0L
|
|
}
|
|
|
|
set_names <- function(object = nm, nm) {
|
|
names(object) <- nm
|
|
object
|
|
}
|
|
|
|
cume_dist <- function(x) {
|
|
rank(x, ties.method = "max", na.last = "keep") / sum(!is.na(x))
|
|
}
|
|
|
|
dense_rank <- function(x) {
|
|
match(x, sort(unique(x)))
|
|
}
|
|
|
|
min_rank <- function(x) {
|
|
rank(x, ties.method = "min", na.last = "keep")
|
|
}
|
|
|
|
ntile <- function (x = row_number(), n) {
|
|
if (!missing(x)) x <- row_number(x)
|
|
len <- length(x) - sum(is.na(x))
|
|
n <- as.integer(floor(n))
|
|
if (len == 0L) {
|
|
rep(NA_integer_, length(x))
|
|
} else {
|
|
n_larger <- as.integer(len %% n)
|
|
n_smaller <- as.integer(n - n_larger)
|
|
size <- len / n
|
|
larger_size <- as.integer(ceiling(size))
|
|
smaller_size <- as.integer(floor(size))
|
|
larger_threshold <- larger_size * n_larger
|
|
bins <- if_else(
|
|
x <= larger_threshold,
|
|
(x + (larger_size - 1L)) / larger_size,
|
|
(x + (-larger_threshold + smaller_size - 1L)) / smaller_size + n_larger
|
|
)
|
|
as.integer(floor(bins))
|
|
}
|
|
}
|
|
|
|
percent_rank <- function(x) {
|
|
(min_rank(x) - 1) / (sum(!is.na(x)) - 1)
|
|
}
|
|
|
|
row_number <- function(x) {
|
|
if (missing(x)) seq_len(n()) else rank(x, ties.method = "first", na.last = "keep")
|
|
}
|