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get episode unit tests

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dr. M.S. (Matthijs) Berends 2023-02-24 19:54:56 +01:00
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2
DESCRIPTION
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@ -1,5 +1,5 @@
Package: AMR Package: AMR
Version: 1.8.2.9145 Version: 1.8.2.9146
Date: 2023-02-24 Date: 2023-02-24
Title: Antimicrobial Resistance Data Analysis Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR) Description: Functions to simplify and standardise antimicrobial resistance (AMR)

2
NEWS.md
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@ -1,4 +1,4 @@
# AMR 1.8.2.9145 # AMR 1.8.2.9146
*(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)* *(this beta version will eventually become v2.0! We're happy to reach a new major milestone soon!)*

133
R/get_episode.R
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@ -29,50 +29,52 @@
#' Determine (Clinical or Epidemic) Episodes #' Determine (Clinical or Epidemic) Episodes
#' #'
#' 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. #' 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.
#' @param x vector of dates (class `Date` or `POSIXt`), will be sorted internally to determine episodes #' @param x vector of dates (class `Date` or `POSIXt`), will be sorted internally to determine episodes
#' @param episode_days episode length in days, can also be less than a day or `Inf`, see *Details* #' @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*
#' @param case_free_days length in days after which new episode will start, can also be less than a day or `Inf`, see *Details* #' @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*
#' @param ... ignored, only in place to allow future extensions #' @param ... ignored, only in place to allow future extensions
#' @details Episodes can be determined in two ways: absolute and relative. #' @details Episodes can be determined in two ways: absolute and relative.
#' #'
#' 1. Absolute #' 1. Absolute
#' #'
#' 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. #' 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.
#' #'
#' Thus, this method counts **since the start of the previous episode**. #' Thus, this method counts **since the start of the previous episode**.
#' #'
#' 2. Relative #' 2. Relative
#' #'
#' 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. #' 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.
#' #'
#' Thus, this methods counts **since the last case in the previous episode**. #' Thus, this methods counts **since the last case in the previous episode**.
#' #'
#' In a table: #' In a table:
#' #'
#' | Date | Using `episode_days = 7` | Using `case_free_days = 7` | #' | Date | Using `episode_days = 7` | Using `case_free_days = 7` |
#' |:----------:|:------------------------:|:--------------------------:| #' |:----------:|:------------------------:|:--------------------------:|
#' | 2023-01-01 | 1 | 1 | #' | 2023-01-01 | 1 | 1 |
#' | 2023-01-02 | 1 | 1 | #' | 2023-01-02 | 1 | 1 |
#' | 2023-01-05 | 1 | 1 | #' | 2023-01-05 | 1 | 1 |
#' | 2023-01-08 | 2\code{*} | 1 | #' | 2023-01-08 | 2** | 1 |
#' | 2023-02-21 | 3 | 2\code{**} | #' | 2023-02-21 | 3 | 2*** |
#' | 2023-02-22 | 3 | 2 | #' | 2023-02-22 | 3 | 2 |
#' | 2023-02-23 | 3 | 2 | #' | 2023-02-23 | 3 | 2 |
#' | 2023-02-24 | 3 | 2 | #' | 2023-02-24 | 3 | 2 |
#' | 2023-03-01 | 4 | 2 | #' | 2023-03-01 | 4 | 2 |
#' #'
#' \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 #' ** 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
#' \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). #' *** 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).
#' #'
#' Either `episode_days` or `case_free_days` must be provided in the function.
#'
#' ### Difference between `get_episode()` and `is_new_episode()` #' ### Difference between `get_episode()` and `is_new_episode()`
#' #'
#' 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. #' 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.
#' #'
#' The [is_new_episode()] function returns `TRUE` for every new [get_episode()] index, and is thus equal to `!duplicated(get_episode(...))`. #' The [is_new_episode()] function returns `TRUE` for every new [get_episode()] index, and is thus equal to `!duplicated(get_episode(...))`.
#' #'
#' To specify, when setting `episode_days = 365` (using method 1 as explained above), this is how the two functions differ: #' To specify, when setting `episode_days = 365` (using method 1 as explained above), this is how the two functions differ:
#' #'
#' | patient | date | `get_episode()` | `is_new_episode()` | #' | patient | date | `get_episode()` | `is_new_episode()` |
#' |:---------:|:----------:|:---------------:|:------------------:| #' |:---------:|:----------:|:---------------:|:------------------:|
#' | A | 2019-01-01 | 1 | TRUE | #' | A | 2019-01-01 | 1 | TRUE |
@ -83,7 +85,7 @@
#' | C | 2020-01-01 | 1 | TRUE | #' | C | 2020-01-01 | 1 | TRUE |
#' #'
#' ### Other #' ### Other
#' #'
#' 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. #' 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.
#' #'
#' 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()]. #' 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()].
@ -110,8 +112,8 @@
#' x$absolute <- get_episode(x$dates, episode_days = 7) #' x$absolute <- get_episode(x$dates, episode_days = 7)
#' x$relative <- get_episode(x$dates, case_free_days = 7) #' x$relative <- get_episode(x$dates, case_free_days = 7)
#' x #' x
#' #'
#' #'
#' # `example_isolates` is a data set available in the AMR package. #' # `example_isolates` is a data set available in the AMR package.
#' # See ?example_isolates #' # See ?example_isolates
#' df <- example_isolates[sample(seq_len(2000), size = 100), ] #' df <- example_isolates[sample(seq_len(2000), size = 100), ]
@ -213,51 +215,54 @@ is_new_episode <- function(x, episode_days = NULL, case_free_days = NULL, ...) {
exec_episode <- function(x, episode_days, case_free_days, ...) { exec_episode <- function(x, episode_days, case_free_days, ...) {
stop_if((is.null(episode_days) && is.null(case_free_days)) || (!is.null(episode_days) && !is.null(case_free_days)), stop_if((is.null(episode_days) && is.null(case_free_days)) || (!is.null(episode_days) && !is.null(case_free_days)),
"either `episode_days` or `case_free_days` must be set.", call = -2) "either `episode_days` or `case_free_days` must be set.",
call = -2
)
x <- as.double(as.POSIXct(x)) # as.POSIXct() required for Date classes # running as.double() on a POSIXct object will return its number of seconds since 1970-01-01
x <- as.double(as.POSIXct(x)) # as.POSIXct() required for Date classes
# since x is now in seconds, get seconds from episode_days as well # since x is now in seconds, get seconds from episode_days as well
episode_seconds <- episode_days * 60 * 60 * 24 episode_seconds <- episode_days * 60 * 60 * 24
case_free_seconds <- case_free_days * 60 * 60 * 24 case_free_seconds <- case_free_days * 60 * 60 * 24
if (length(x) == 1) { # this will also match 1 NA, which is fine if (length(x) == 1) { # this will also match 1 NA, which is fine
return(1) return(1)
} else if (length(x) == 2 && all(!is.na(x))) { } else if (length(x) == 2 && all(!is.na(x))) {
if ((length(episode_seconds) > 0 && (max(x) - min(x)) >= episode_seconds) || if ((length(episode_seconds) > 0 && (max(x) - min(x)) >= episode_seconds) ||
(length(case_free_seconds) > 0 && (max(x) - min(x)) >= case_free_seconds)) { (length(case_free_seconds) > 0 && (max(x) - min(x)) >= case_free_seconds)) {
if (x[1] <= x[2]) { if (x[1] <= x[2]) {
return(c(1, 2)) return(c(1, 2))
} else {
return(c(2, 1))
}
} else { } else {
return(c(1, 1)) return(c(2, 1))
} }
} else {
return(c(1, 1))
} }
}
run_episodes <- function(x, episode_seconds, case_free) { run_episodes <- function(x, episode_seconds, case_free) {
NAs <- which(is.na(x)) NAs <- which(is.na(x))
x[NAs] <- 0 x[NAs] <- 0
indices <- integer(length = length(x)) indices <- integer(length = length(x))
start <- x[1] start <- x[1]
ind <- 1 ind <- 1
indices[ind] <- 1 indices[ind] <- 1
for (i in 2:length(x)) { for (i in 2:length(x)) {
if ((length(episode_seconds) > 0 && (x[i] - start) >= episode_seconds) || if ((length(episode_seconds) > 0 && (x[i] - start) >= episode_seconds) ||
(length(case_free_seconds) > 0 && (x[i] - x[i - 1]) >= case_free_seconds)) { (length(case_free_seconds) > 0 && (x[i] - x[i - 1]) >= case_free_seconds)) {
ind <- ind + 1 ind <- ind + 1
start <- x[i] start <- x[i]
}
indices[i] <- ind
} }
indices[NAs] <- NA indices[i] <- ind
indices
} }
indices[NAs] <- NA
ord <- order(x) indices
out <- run_episodes(x[ord], episode_seconds, case_free_seconds)[order(ord)] }
out[is.na(x) & ord != 1] <- NA # every NA expect for the first must remain NA
out ord <- order(x)
out <- run_episodes(x[ord], episode_seconds, case_free_seconds)[order(ord)]
out[is.na(x) & ord != 1] <- NA # every NA expect for the first must remain NA
out
} }

8
inst/tinytest/test-episode.R → inst/tinytest/test-get_episode.R
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@ -27,6 +27,14 @@
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ # # how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== # # ==================================================================== #
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")))
x$absolute <- get_episode(x$dates, episode_days = 7)
x$relative <- get_episode(x$dates, case_free_days = 7)
expect_equal(x$absolute, c(1, 1, 1, 2, 3, 3, 3, 3, 4, 4))
expect_equal(x$relative, c(1, 1, 1, 1, 2, 2, 2, 2, 2, 2))
expect_equal(get_episode(as.Date(c("2022-01-01", "2020-01-01")), 365), c(2, 1))
expect_equal(get_episode(as.Date(c("2020-01-01", "2022-01-01")), 365), c(1, 2))
test_df <- rbind( test_df <- rbind(
data.frame( data.frame(
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")), 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")),

18
man/get_episode.Rd
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@ -12,9 +12,9 @@ is_new_episode(x, episode_days = NULL, case_free_days = NULL, ...)
\arguments{ \arguments{
\item{x}{vector of dates (class \code{Date} or \code{POSIXt}), will be sorted internally to determine episodes} \item{x}{vector of dates (class \code{Date} or \code{POSIXt}), will be sorted internally to determine episodes}
\item{episode_days}{episode length in days, can also be less than a day or \code{Inf}, see \emph{Details}} \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}}
\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}} \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}}
\item{...}{ignored, only in place to allow future extensions} \item{...}{ignored, only in place to allow future extensions}
} }
@ -25,7 +25,7 @@ is_new_episode(x, episode_days = NULL, case_free_days = NULL, ...)
} }
} }
\description{ \description{
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. 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.
} }
\details{ \details{
Episodes can be determined in two ways: absolute and relative. Episodes can be determined in two ways: absolute and relative.
@ -37,7 +37,7 @@ This method uses \code{episode_days} to define an episode length in days, after
Thus, this method counts \strong{since the start of the previous episode}. Thus, this method counts \strong{since the start of the previous episode}.
\item Relative \item Relative
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. 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.
Thus, this methods counts \strong{since the last case in the previous episode}. Thus, this methods counts \strong{since the last case in the previous episode}.
} }
@ -47,8 +47,8 @@ In a table:\tabular{ccc}{
2023-01-01 \tab 1 \tab 1 \cr 2023-01-01 \tab 1 \tab 1 \cr
2023-01-02 \tab 1 \tab 1 \cr 2023-01-02 \tab 1 \tab 1 \cr
2023-01-05 \tab 1 \tab 1 \cr 2023-01-05 \tab 1 \tab 1 \cr
2023-01-08 \tab 2\code{*} \tab 1 \cr 2023-01-08 \tab 2** \tab 1 \cr
2023-02-21 \tab 3 \tab 2\code{**} \cr 2023-02-21 \tab 3 \tab 2*** \cr
2023-02-22 \tab 3 \tab 2 \cr 2023-02-22 \tab 3 \tab 2 \cr
2023-02-23 \tab 3 \tab 2 \cr 2023-02-23 \tab 3 \tab 2 \cr
2023-02-24 \tab 3 \tab 2 \cr 2023-02-24 \tab 3 \tab 2 \cr
@ -56,8 +56,10 @@ In a table:\tabular{ccc}{
} }
\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 ** 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
\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). *** 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).
Either \code{episode_days} or \code{case_free_days} must be provided in the function.
\subsection{Difference between \code{get_episode()} and \code{is_new_episode()}}{ \subsection{Difference between \code{get_episode()} and \code{is_new_episode()}}{
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. 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.