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(v1.5.0.9010) MDRO vignette update, get_episode for < day
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@ -46,7 +46,7 @@
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#' @param include_unknown logical to determine whether 'unknown' microorganisms should be included too, i.e. microbial code `"UNKNOWN"`, which defaults to `FALSE`. For WHONET users, this means that all records with organism code `"con"` (*contamination*) will be excluded at default. Isolates with a microbial ID of `NA` will always be excluded as first isolate.
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#' @param ... arguments passed on to [first_isolate()] when using [filter_first_isolate()], or arguments passed on to [key_antibiotics()] when using [filter_first_weighted_isolate()]
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#' @details
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#' These functions are context-aware when used inside `dplyr` verbs, such as `filter()`, `mutate()` and `summarise()`. This means that then the `x` argument can be left blank, see *Examples*.
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#' These functions are context-aware. This means that then the `x` argument can be left blank, see *Examples*.
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#'
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#' The [first_isolate()] function is a wrapper around the [is_new_episode()] function, but more efficient for data sets containing microorganism codes or names.
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#'
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@ -96,7 +96,7 @@
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#' **M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition**, 2014, *Clinical and Laboratory Standards Institute (CLSI)*. <https://clsi.org/standards/products/microbiology/documents/m39/>.
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#' @inheritSection AMR Read more on Our Website!
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#' @examples
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#' # `example_isolates` is a dataset available in the AMR package.
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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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#'
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#' # basic filtering on first isolates
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@ -172,20 +172,20 @@ first_isolate <- function(x,
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col_keyantibiotics <- NULL
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}
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meet_criteria(col_keyantibiotics, allow_class = "character", has_length = 1, allow_NULL = TRUE, is_in = colnames(x))
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meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1)
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meet_criteria(episode_days, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
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meet_criteria(testcodes_exclude, allow_class = "character", allow_NULL = TRUE)
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meet_criteria(icu_exclude, allow_class = "logical", has_length = 1)
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meet_criteria(specimen_group, allow_class = "character", has_length = 1, allow_NULL = TRUE)
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meet_criteria(type, allow_class = "character", has_length = 1)
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meet_criteria(ignore_I, allow_class = "logical", has_length = 1)
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meet_criteria(points_threshold, allow_class = c("numeric", "integer"), has_length = 1)
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meet_criteria(points_threshold, allow_class = c("numeric", "integer"), has_length = 1, is_positive = TRUE, is_finite = TRUE)
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meet_criteria(info, allow_class = "logical", has_length = 1)
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meet_criteria(include_unknown, allow_class = "logical", has_length = 1)
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dots <- unlist(list(...))
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if (length(dots) != 0) {
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# backwards compatibility with old arguments
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dots.names <- dots %pm>% names()
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dots.names <- names(dots)
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if ("filter_specimen" %in% dots.names) {
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specimen_group <- dots[which(dots.names == "filter_specimen")]
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}
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