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2026-03-22 19:55:49 +00:00
parent 3560dfd611
commit c95646d39c
120 changed files with 617 additions and 675 deletions
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16
reference/as.mic.md
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@@ -96,7 +96,7 @@ operation it acts as decimal numbers:
x <- random_mic(10)
x
#> Class 'mic'
#> Class <mic>
#> [1] 16 1 8 8 64 >=128 0.0625 32 32 16
is.factor(x)
@@ -114,7 +114,7 @@ values, such "\>=" and "\<=", even when filtering using
e.g.:
x[x > 4]
#> Class 'mic'
#> Class <mic>
#> [1] 16 8 8 64 >=128 32 32 16
df <- data.frame(x, hospital = "A")
@@ -187,14 +187,14 @@ MIC values. They return 'normal'
``` r
mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16"))
mic_data
#> Class 'mic'
#> Class <mic>
#> [1] >=32 1 1 1 8 <=0.128 8 16 16
is.mic(mic_data)
#> [1] TRUE
# this can also coerce combined MIC/SIR values:
as.mic("<=0.002; S")
#> Class 'mic'
#> Class <mic>
#> [1] <=0.002
# mathematical processing treats MICs as, and returns, numeric values
@@ -208,14 +208,14 @@ all(mic_data < 512)
# rescale MICs using rescale_mic()
rescale_mic(mic_data, mic_range = c(4, 16))
#> Class 'mic'
#> Class <mic>
#> [1] >=16 <=4 <=4 <=4 8 <=4 8 >=16 >=16
# round up to nearest log2 level, e.g. for CLSI breakpoint interpretation:
c(1:8)
#> [1] 1 2 3 4 5 6 7 8
as.mic(c(1:8), round_to_next_log2 = TRUE)
#> Class 'mic'
#> Class <mic>
#> [1] 1 2 4 4 8 8 8 8
# interpret MIC values
@@ -225,7 +225,7 @@ as.sir(
ab = "AMX",
guideline = "EUCAST"
)
#> Class 'sir'
#> Class <sir>
#> [1] R
as.sir(
x = as.mic(c(0.01, 2, 4, 8)),
@@ -233,7 +233,7 @@ as.sir(
ab = "AMX",
guideline = "EUCAST"
)
#> Class 'sir'
#> Class <sir>
#> [1] S R R R
# plot MIC values, see ?plot