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styled, unit test fix

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dr. M.S. (Matthijs) Berends
2022-08-28 10:31:50 +02:00
parent 4cb1db4554
commit 4d050aef7c
147 changed files with 10897 additions and 8169 deletions
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19
vignettes/WHONET.Rmd
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@ -39,9 +39,9 @@ This package comes with an [example data set `WHONET`](https://msberends.github.
First, load the relevant packages if you did not yet did this. I use the tidyverse for all of my analyses. All of them. If you don't know it yet, I suggest you read about it on their website: https://www.tidyverse.org/.
```{r, message = FALSE}
library(dplyr) # part of tidyverse
library(dplyr) # part of tidyverse
library(ggplot2) # part of tidyverse
library(AMR) # this package
library(AMR) # this package
library(cleaner) # to create frequency tables
```
@ -54,7 +54,7 @@ We will have to transform some variables to simplify and automate the analysis:
# transform variables
data <- WHONET %>%
# get microbial ID based on given organism
mutate(mo = as.mo(Organism)) %>%
mutate(mo = as.mo(Organism)) %>%
# transform everything from "AMP_ND10" to "CIP_EE" to the new `rsi` class
mutate_at(vars(AMP_ND10:CIP_EE), as.rsi)
```
@ -83,15 +83,16 @@ An easy `ggplot` will already give a lot of information, using the included `ggp
data %>%
group_by(Country) %>%
select(Country, AMP_ND2, AMC_ED20, CAZ_ED10, CIP_ED5) %>%
ggplot_rsi(translate_ab = 'ab', facet = "Country", datalabels = FALSE)
ggplot_rsi(translate_ab = "ab", facet = "Country", datalabels = FALSE)
```
```{r, echo = FALSE}
# on very old and some new releases of R, this may lead to an error
tryCatch(data %>%
group_by(Country) %>%
select(Country, AMP_ND2, AMC_ED20, CAZ_ED10, CIP_ED5) %>%
ggplot_rsi(translate_ab = 'ab', facet = "Country", datalabels = FALSE) %>%
print(),
error = function(e) base::invisible())
group_by(Country) %>%
select(Country, AMP_ND2, AMC_ED20, CAZ_ED10, CIP_ED5) %>%
ggplot_rsi(translate_ab = "ab", facet = "Country", datalabels = FALSE) %>%
print(),
error = function(e) base::invisible()
)
```