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reference/as.disk.md

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+# Transform Input to Disk Diffusion Diameters
+
+This transforms a vector to a new class `disk`, which is a disk
+diffusion growth zone size (around an antibiotic disk) in millimetres
+between 0 and 50.
+
+## Usage
+
+``` r
+as.disk(x, na.rm = FALSE)
+
+NA_disk_
+
+is.disk(x)
+```
+
+## Format
+
+An object of class `disk` (inherits from `integer`) of length 1.
+
+## Arguments
+
+- x:
+
+  Vector.
+
+- na.rm:
+
+  A [logical](https://rdrr.io/r/base/logical.html) indicating whether
+  missing values should be removed.
+
+## Value
+
+An [integer](https://rdrr.io/r/base/integer.html) with additional class
+`disk`
+
+## Details
+
+Interpret disk values as SIR values with
+[`as.sir()`](https://amr-for-r.org/reference/as.sir.md). It supports
+guidelines from EUCAST and CLSI.
+
+Disk diffusion growth zone sizes must be between 0 and 50 millimetres.
+Values higher than 50 but lower than 100 will be maximised to 50. All
+others input values outside the 0-50 range will return `NA`.
+
+`NA_disk_` is a missing value of the new `disk` class.
+
+## See also
+
+[`as.sir()`](https://amr-for-r.org/reference/as.sir.md)
+
+## Examples
+
+``` r
+# transform existing disk zones to the `disk` class (using base R)
+df <- data.frame(
+  microorganism = "Escherichia coli",
+  AMP = 20,
+  CIP = 14,
+  GEN = 18,
+  TOB = 16
+)
+df[, 2:5] <- lapply(df[, 2:5], as.disk)
+str(df)
+#> 'data.frame':    1 obs. of  5 variables:
+#>  $ microorganism: chr "Escherichia coli"
+#>  $ AMP          : 'disk' int 20
+#>  $ CIP          : 'disk' int 14
+#>  $ GEN          : 'disk' int 18
+#>  $ TOB          : 'disk' int 16
+
+# \donttest{
+# transforming is easier with dplyr:
+if (require("dplyr")) {
+  df %>% mutate(across(AMP:TOB, as.disk))
+}
+#>      microorganism AMP CIP GEN TOB
+#> 1 Escherichia coli  20  14  18  16
+# }
+
+# interpret disk values, see ?as.sir
+as.sir(
+  x = as.disk(18),
+  mo = "Strep pneu", # `mo` will be coerced with as.mo()
+  ab = "ampicillin", # and `ab` with as.ab()
+  guideline = "EUCAST"
+)
+#> Class 'sir'
+#> [1] R
+
+# interpret whole data set, pretend to be all from urinary tract infections:
+as.sir(df, uti = TRUE)
+#>      microorganism AMP  CIP GEN TOB
+#> 1 Escherichia coli   S <NA>   S   S
+```