mirror of https://github.com/msberends/AMR.git
get episode unit tests
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Package: AMR
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Version: 1.8.2.9145
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Version: 1.8.2.9146
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Date: 2023-02-24
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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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@ -1,4 +1,4 @@
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# AMR 1.8.2.9145
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# AMR 1.8.2.9146
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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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133
R/get_episode.R
133
R/get_episode.R
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@ -29,50 +29,52 @@
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#' Determine (Clinical or Epidemic) Episodes
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#'
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#' These functions determine which items in a vector can be considered (the start of) a new episode, based on the argument `episode_days`. This can be used to determine clinical episodes for any epidemiological analysis. The [get_episode()] function returns the index number of the episode per group, while the [is_new_episode()] function returns `TRUE` for every new [get_episode()] index. Both absolute and relative episode determination are supported.
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#' These functions determine which items in a vector can be considered (the start of) a new episode. This can be used to determine clinical episodes for any epidemiological analysis. The [get_episode()] function returns the index number of the episode per group, while the [is_new_episode()] function returns `TRUE` for every new [get_episode()] index. Both absolute and relative episode determination are supported.
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#' @param x vector of dates (class `Date` or `POSIXt`), will be sorted internally to determine episodes
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#' @param episode_days episode length in days, can also be less than a day or `Inf`, see *Details*
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#' @param case_free_days length in days after which new episode will start, can also be less than a day or `Inf`, see *Details*
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#' @param episode_days episode length in days to specify the time period after which a new episode begins, can also be less than a day or `Inf`, see *Details*
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#' @param case_free_days (inter-epidemic) interval length in days after which a new episode will start, can also be less than a day or `Inf`, see *Details*
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#' @param ... ignored, only in place to allow future extensions
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#' @details Episodes can be determined in two ways: absolute and relative.
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#'
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#'
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#' 1. Absolute
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#'
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#'
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#' This method uses `episode_days` to define an episode length in days, after which a new episode will start. A common use case in AMR data analysis is microbial epidemiology: episodes of *S. aureus* bacteraemia in ICU patients for example. The episode length could then be 30 days, so that new *S. aureus* isolates after an ICU episode of 30 days will be considered a different (or new) episode.
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#'
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#'
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#' Thus, this method counts **since the start of the previous episode**.
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#'
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#'
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#' 2. Relative
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#'
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#' This method uses `case_free_days` to quantify the duration of (inter-epidemic) intervals, after which a new episode will start. A common use case is infectious disease epidemiology: episodes of norovirus outbreaks in a hospital for example. The case-free period could then be 14 days, so that new norovirus cases after that time will be considered a different (or new) episode.
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#'
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#'
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#' This method uses `case_free_days` to quantify the duration of case-free days (the inter-epidemic interval), after which a new episode will start. A common use case is infectious disease epidemiology: episodes of norovirus outbreaks in a hospital for example. The case-free period could then be 14 days, so that new norovirus cases after that time will be considered a different (or new) episode.
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#'
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#' Thus, this methods counts **since the last case in the previous episode**.
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#'
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#'
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#' In a table:
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#'
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#'
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#' | Date | Using `episode_days = 7` | Using `case_free_days = 7` |
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#' |:----------:|:------------------------:|:--------------------------:|
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#' | 2023-01-01 | 1 | 1 |
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#' | 2023-01-02 | 1 | 1 |
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#' | 2023-01-05 | 1 | 1 |
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#' | 2023-01-08 | 2\code{*} | 1 |
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#' | 2023-02-21 | 3 | 2\code{**} |
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#' | 2023-01-08 | 2** | 1 |
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#' | 2023-02-21 | 3 | 2*** |
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#' | 2023-02-22 | 3 | 2 |
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#' | 2023-02-23 | 3 | 2 |
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#' | 2023-02-24 | 3 | 2 |
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#' | 2023-03-01 | 4 | 2 |
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#'
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#' \code{*} This marks the start of a new episode, because 8 January 2023 is more than 7 days since the start of the previous episode (1 January 2023). \cr
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#' \code{**} This marks the start of a new episode, because 21 January 2023 is more than 7 days since the last case in the previous episode (8 January 2023).
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#'
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#'
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#' ** This marks the start of a new episode, because 8 January 2023 is more than 7 days since the start of the previous episode (1 January 2023). \cr
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#' *** This marks the start of a new episode, because 21 January 2023 is more than 7 days since the last case in the previous episode (8 January 2023).
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#'
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#' Either `episode_days` or `case_free_days` must be provided in the function.
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#'
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#' ### Difference between `get_episode()` and `is_new_episode()`
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#'
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#' The [get_episode()] function returns the index number of the episode, so all cases/patients/isolates in the first episode will have the number 1, all cases/patients/isolates in the second episode will have the number 2, etc.
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#'
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#'
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#' The [get_episode()] function returns the index number of the episode, so all cases/patients/isolates in the first episode will have the number 1, all cases/patients/isolates in the second episode will have the number 2, etc.
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#'
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#' The [is_new_episode()] function returns `TRUE` for every new [get_episode()] index, and is thus equal to `!duplicated(get_episode(...))`.
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#'
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#'
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#' To specify, when setting `episode_days = 365` (using method 1 as explained above), this is how the two functions differ:
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#'
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#'
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#' | patient | date | `get_episode()` | `is_new_episode()` |
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#' |:---------:|:----------:|:---------------:|:------------------:|
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#' | A | 2019-01-01 | 1 | TRUE |
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@ -83,7 +85,7 @@
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#' | C | 2020-01-01 | 1 | TRUE |
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#'
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#' ### Other
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#'
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#'
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#' The [first_isolate()] function is a wrapper around the [is_new_episode()] function, but is more efficient for data sets containing microorganism codes or names and allows for different isolate selection methods.
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#'
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#' The `dplyr` package is not required for these functions to work, but these episode functions do support [variable grouping][dplyr::group_by()] and work conveniently inside `dplyr` verbs such as [`filter()`][dplyr::filter()], [`mutate()`][dplyr::mutate()] and [`summarise()`][dplyr::summarise()].
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@ -110,8 +112,8 @@
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#' x$absolute <- get_episode(x$dates, episode_days = 7)
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#' x$relative <- get_episode(x$dates, case_free_days = 7)
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#' x
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#'
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#'
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#'
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#'
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#' # `example_isolates` is a data set available in the AMR package.
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#' # See ?example_isolates
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#' df <- example_isolates[sample(seq_len(2000), size = 100), ]
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@ -213,51 +215,54 @@ is_new_episode <- function(x, episode_days = NULL, case_free_days = NULL, ...) {
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exec_episode <- function(x, episode_days, case_free_days, ...) {
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stop_if((is.null(episode_days) && is.null(case_free_days)) || (!is.null(episode_days) && !is.null(case_free_days)),
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"either `episode_days` or `case_free_days` must be set.", call = -2)
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"either `episode_days` or `case_free_days` must be set.",
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call = -2
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)
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x <- as.double(as.POSIXct(x)) # as.POSIXct() required for Date classes
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# running as.double() on a POSIXct object will return its number of seconds since 1970-01-01
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x <- as.double(as.POSIXct(x)) # as.POSIXct() required for Date classes
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# since x is now in seconds, get seconds from episode_days as well
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episode_seconds <- episode_days * 60 * 60 * 24
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case_free_seconds <- case_free_days * 60 * 60 * 24
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# since x is now in seconds, get seconds from episode_days as well
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episode_seconds <- episode_days * 60 * 60 * 24
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case_free_seconds <- case_free_days * 60 * 60 * 24
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if (length(x) == 1) { # this will also match 1 NA, which is fine
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return(1)
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} else if (length(x) == 2 && all(!is.na(x))) {
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if ((length(episode_seconds) > 0 && (max(x) - min(x)) >= episode_seconds) ||
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(length(case_free_seconds) > 0 && (max(x) - min(x)) >= case_free_seconds)) {
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if (x[1] <= x[2]) {
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return(c(1, 2))
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} else {
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return(c(2, 1))
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}
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if (length(x) == 1) { # this will also match 1 NA, which is fine
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return(1)
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} else if (length(x) == 2 && all(!is.na(x))) {
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if ((length(episode_seconds) > 0 && (max(x) - min(x)) >= episode_seconds) ||
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(length(case_free_seconds) > 0 && (max(x) - min(x)) >= case_free_seconds)) {
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if (x[1] <= x[2]) {
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return(c(1, 2))
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} else {
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return(c(1, 1))
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return(c(2, 1))
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}
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} else {
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return(c(1, 1))
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}
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}
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run_episodes <- function(x, episode_seconds, case_free) {
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NAs <- which(is.na(x))
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x[NAs] <- 0
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indices <- integer(length = length(x))
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start <- x[1]
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ind <- 1
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indices[ind] <- 1
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for (i in 2:length(x)) {
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if ((length(episode_seconds) > 0 && (x[i] - start) >= episode_seconds) ||
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(length(case_free_seconds) > 0 && (x[i] - x[i - 1]) >= case_free_seconds)) {
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ind <- ind + 1
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start <- x[i]
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}
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indices[i] <- ind
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run_episodes <- function(x, episode_seconds, case_free) {
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NAs <- which(is.na(x))
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x[NAs] <- 0
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indices <- integer(length = length(x))
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start <- x[1]
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ind <- 1
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indices[ind] <- 1
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for (i in 2:length(x)) {
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if ((length(episode_seconds) > 0 && (x[i] - start) >= episode_seconds) ||
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(length(case_free_seconds) > 0 && (x[i] - x[i - 1]) >= case_free_seconds)) {
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ind <- ind + 1
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start <- x[i]
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}
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indices[NAs] <- NA
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indices
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indices[i] <- ind
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}
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ord <- order(x)
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out <- run_episodes(x[ord], episode_seconds, case_free_seconds)[order(ord)]
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out[is.na(x) & ord != 1] <- NA # every NA expect for the first must remain NA
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out
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indices[NAs] <- NA
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indices
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}
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ord <- order(x)
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out <- run_episodes(x[ord], episode_seconds, case_free_seconds)[order(ord)]
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out[is.na(x) & ord != 1] <- NA # every NA expect for the first must remain NA
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out
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}
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@ -27,6 +27,14 @@
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# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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x <- data.frame(dates = as.Date(c("2021-01-01", "2021-01-02", "2021-01-05", "2021-01-08", "2021-02-21", "2021-02-22", "2021-02-23", "2021-02-24", "2021-03-01", "2021-03-01")))
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x$absolute <- get_episode(x$dates, episode_days = 7)
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x$relative <- get_episode(x$dates, case_free_days = 7)
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expect_equal(x$absolute, c(1, 1, 1, 2, 3, 3, 3, 3, 4, 4))
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expect_equal(x$relative, c(1, 1, 1, 1, 2, 2, 2, 2, 2, 2))
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expect_equal(get_episode(as.Date(c("2022-01-01", "2020-01-01")), 365), c(2, 1))
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expect_equal(get_episode(as.Date(c("2020-01-01", "2022-01-01")), 365), c(1, 2))
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test_df <- rbind(
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data.frame(
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date = as.Date(c("2015-01-01", "2015-10-01", "2016-02-04", "2016-12-31", "2017-01-01", "2017-02-01", "2017-02-05", "2020-01-01")),
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@ -12,9 +12,9 @@ is_new_episode(x, episode_days = NULL, case_free_days = NULL, ...)
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\arguments{
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\item{x}{vector of dates (class \code{Date} or \code{POSIXt}), will be sorted internally to determine episodes}
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\item{episode_days}{episode length in days, can also be less than a day or \code{Inf}, see \emph{Details}}
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\item{episode_days}{episode length in days to specify the time period after which a new episode begins, can also be less than a day or \code{Inf}, see \emph{Details}}
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\item{case_free_days}{length in days after which new episode will start, can also be less than a day or \code{Inf}, see \emph{Details}}
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\item{case_free_days}{(inter-epidemic) interval length in days after which a new episode will start, can also be less than a day or \code{Inf}, see \emph{Details}}
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\item{...}{ignored, only in place to allow future extensions}
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}
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@ -25,7 +25,7 @@ is_new_episode(x, episode_days = NULL, case_free_days = NULL, ...)
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}
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}
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\description{
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These functions determine which items in a vector can be considered (the start of) a new episode, based on the argument \code{episode_days}. This can be used to determine clinical episodes for any epidemiological analysis. The \code{\link[=get_episode]{get_episode()}} function returns the index number of the episode per group, while the \code{\link[=is_new_episode]{is_new_episode()}} function returns \code{TRUE} for every new \code{\link[=get_episode]{get_episode()}} index. Both absolute and relative episode determination are supported.
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These functions determine which items in a vector can be considered (the start of) a new episode. This can be used to determine clinical episodes for any epidemiological analysis. The \code{\link[=get_episode]{get_episode()}} function returns the index number of the episode per group, while the \code{\link[=is_new_episode]{is_new_episode()}} function returns \code{TRUE} for every new \code{\link[=get_episode]{get_episode()}} index. Both absolute and relative episode determination are supported.
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}
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\details{
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Episodes can be determined in two ways: absolute and relative.
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@ -37,7 +37,7 @@ This method uses \code{episode_days} to define an episode length in days, after
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Thus, this method counts \strong{since the start of the previous episode}.
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\item Relative
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This method uses \code{case_free_days} to quantify the duration of (inter-epidemic) intervals, after which a new episode will start. A common use case is infectious disease epidemiology: episodes of norovirus outbreaks in a hospital for example. The case-free period could then be 14 days, so that new norovirus cases after that time will be considered a different (or new) episode.
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This method uses \code{case_free_days} to quantify the duration of case-free days (the inter-epidemic interval), after which a new episode will start. A common use case is infectious disease epidemiology: episodes of norovirus outbreaks in a hospital for example. The case-free period could then be 14 days, so that new norovirus cases after that time will be considered a different (or new) episode.
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Thus, this methods counts \strong{since the last case in the previous episode}.
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}
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@ -47,8 +47,8 @@ In a table:\tabular{ccc}{
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2023-01-01 \tab 1 \tab 1 \cr
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2023-01-02 \tab 1 \tab 1 \cr
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2023-01-05 \tab 1 \tab 1 \cr
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2023-01-08 \tab 2\code{*} \tab 1 \cr
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2023-02-21 \tab 3 \tab 2\code{**} \cr
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2023-01-08 \tab 2** \tab 1 \cr
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2023-02-21 \tab 3 \tab 2*** \cr
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2023-02-22 \tab 3 \tab 2 \cr
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2023-02-23 \tab 3 \tab 2 \cr
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2023-02-24 \tab 3 \tab 2 \cr
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@ -56,8 +56,10 @@ In a table:\tabular{ccc}{
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}
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\code{*} This marks the start of a new episode, because 8 January 2023 is more than 7 days since the start of the previous episode (1 January 2023). \cr
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\code{**} This marks the start of a new episode, because 21 January 2023 is more than 7 days since the last case in the previous episode (8 January 2023).
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** This marks the start of a new episode, because 8 January 2023 is more than 7 days since the start of the previous episode (1 January 2023). \cr
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*** This marks the start of a new episode, because 21 January 2023 is more than 7 days since the last case in the previous episode (8 January 2023).
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Either \code{episode_days} or \code{case_free_days} must be provided in the function.
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\subsection{Difference between \code{get_episode()} and \code{is_new_episode()}}{
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The \code{\link[=get_episode]{get_episode()}} function returns the index number of the episode, so all cases/patients/isolates in the first episode will have the number 1, all cases/patients/isolates in the second episode will have the number 2, etc.
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