Browse Source

(v1.3.0) skip more CRAN tests

new-mo-algorithm
parent
commit
c5f7294381
  1. 6
      .Rbuildignore
  2. 2
      DESCRIPTION
  3. 3
      R/ab_class_selectors.R
  4. 2
      R/ab_from_text.R
  5. 5
      R/filter_ab_class.R
  6. 3
      R/ggplot_pca.R
  7. 4
      R/resistance_predict.R
  8. 2
      cran-comments.md
  9. 2
      docs/pkgdown.yml
  10. 2
      docs/reference/ab_from_text.html
  11. 3
      docs/reference/antibiotic_class_selectors.html
  12. 5
      docs/reference/filter_ab_class.html
  13. 3
      docs/reference/ggplot_pca.html
  14. 4
      docs/reference/resistance_predict.html
  15. 2
      man/ab_from_text.Rd
  16. 3
      man/antibiotic_class_selectors.Rd
  17. 5
      man/filter_ab_class.Rd
  18. 3
      man/ggplot_pca.Rd
  19. 4
      man/resistance_predict.Rd
  20. 1
      tests/testthat/test-ab.R
  21. 1
      tests/testthat/test-ab_from_text.R
  22. 1
      tests/testthat/test-ab_property.R
  23. 2
      tests/testthat/test-age.R
  24. 1
      tests/testthat/test-availability.R
  25. 1
      tests/testthat/test-bug_drug_combinations.R
  26. 1
      tests/testthat/test-count.R
  27. 20
      tests/testthat/test-data.R
  28. 1
      tests/testthat/test-deprecated.R
  29. 1
      tests/testthat/test-disk.R
  30. 1
      tests/testthat/test-first_isolate.R
  31. 1
      tests/testthat/test-g.test.R
  32. 1
      tests/testthat/test-get_locale.R
  33. 2
      tests/testthat/test-ggplot_rsi.R
  34. 1
      tests/testthat/test-guess_ab_col.R
  35. 1
      tests/testthat/test-join_microorganisms.R
  36. 1
      tests/testthat/test-key_antibiotics.R
  37. 1
      tests/testthat/test-kurtosis.R
  38. 1
      tests/testthat/test-like.R
  39. 1
      tests/testthat/test-mic.R
  40. 3
      tests/testthat/test-misc.R
  41. 20
      tests/testthat/test-mo_history.R
  42. 1
      tests/testthat/test-p_symbol.R
  43. 1
      tests/testthat/test-resistance_predict.R
  44. 1
      tests/testthat/test-rsi.R
  45. 1
      tests/testthat/test-skewness.R

6
.Rbuildignore

@ -1,6 +1,4 @@ @@ -1,6 +1,4 @@
^.*\.Rproj$
^\.gitlab-ci\.R$
^\.gitlab-ci\.yml$
^\.Renviron$
^\.Rprofile$
^\.Rproj\.user$
@ -23,6 +21,4 @@ @@ -23,6 +21,4 @@
^public$
^data-raw$
^\.lintr$
^vignettes/benchmark.*
^vignettes/SPSS.*
^tests/appveyor$
^vignettes$

2
DESCRIPTION

@ -1,6 +1,6 @@ @@ -1,6 +1,6 @@
Package: AMR
Version: 1.3.0
Date: 2020-07-30
Date: 2020-07-31
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),

3
R/ab_class_selectors.R

@ -31,7 +31,8 @@ @@ -31,7 +31,8 @@
#' @name antibiotic_class_selectors
#' @export
#' @examples
#' if (require("dplyr")) {
#' \dontrun{
#' library(dplyr)
#'
#' # this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
#' example_isolates %>%

2
R/ab_from_text.R

@ -64,7 +64,7 @@ @@ -64,7 +64,7 @@
#' abx <- ab_from_text("500 mg amoxi po and 400mg cipro iv")
#' ab_group(abx[[1]])
#'
#' if (require(dplyr)) {
#' if (require("dplyr")) {
#' tibble(clinical_text = c("given 400mg cipro and 500 mg amox",
#' "started on doxy iv today")) %>%
#' mutate(abx_codes = ab_from_text(clinical_text),

5
R/filter_ab_class.R

@ -33,7 +33,8 @@ @@ -33,7 +33,8 @@
#' @seealso [antibiotic_class_selectors()] for the `select()` equivalent.
#' @export
#' @examples
#' if (require(dplyr)) {
#' \dontrun{
#' library(dplyr)
#'
#' # filter on isolates that have any result for any aminoglycoside
#' example_isolates %>% filter_ab_class("aminoglycoside")
@ -62,9 +63,7 @@ @@ -62,9 +63,7 @@
#' example_isolates %>%
#' filter_aminoglycosides("R", "all") %>%
#' filter_fluoroquinolones("R", "all")
#' }
#'
#' \dontrun{
#' # with dplyr 1.0.0 and higher (that adds 'across()'), this is equal:
#' example_isolates %>% filter_carbapenems("R", "all")
#' example_isolates %>% filter(across(carbapenems(), ~. == "R"))

3
R/ggplot_pca.R

@ -60,7 +60,8 @@ @@ -60,7 +60,8 @@
#' # See ?example_isolates.
#'
#' # See ?pca for more info about Principal Component Analysis (PCA).
#' if (require("dplyr")) {
#' \dontrun{
#' library(dplyr)
#' pca_model <- example_isolates %>%
#' filter(mo_genus(mo) == "Staphylococcus") %>%
#' group_by(species = mo_shortname(mo)) %>%

4
R/resistance_predict.R

@ -84,7 +84,9 @@ @@ -84,7 +84,9 @@
#' }
#'
#' # create nice plots with ggplot2 yourself
#' if (require(ggplot2) & require("dplyr")) {
#' \dontrun{
#' library(dplyr)
#' library(ggplot2)
#'
#' data <- example_isolates %>%
#' filter(mo == as.mo("E. coli")) %>%

2
cran-comments.md

@ -1,3 +1,3 @@ @@ -1,3 +1,3 @@
* For this specific version, nothing to mention.
* Edited the unit tests, so they will run under 10 minutes on CRAN (using testthat::skip_on_cran() on some tests).
* Since version 0.3.0 (2018-08-14), CHECK returns a NOTE for having a data directory over 3 MB. This is needed to offer users reference data for the complete taxonomy of microorganisms - one of the most important features of this package.

2
docs/pkgdown.yml

@ -10,7 +10,7 @@ articles: @@ -10,7 +10,7 @@ articles:
WHONET: WHONET.html
benchmarks: benchmarks.html
resistance_predict: resistance_predict.html
last_built: 2020-07-30T13:15Z
last_built: 2020-07-31T08:49Z
urls:
reference: https://msberends.github.io/AMR/reference
article: https://msberends.github.io/AMR/articles

2
docs/reference/ab_from_text.html

@ -321,7 +321,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing< @@ -321,7 +321,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing<
<span class='no'>abx</span> <span class='kw'>&lt;-</span> <span class='fu'>ab_from_text</span>(<span class='st'>"500 mg amoxi po and 400mg cipro iv"</span>)
<span class='fu'><a href='ab_property.html'>ab_group</a></span>(<span class='no'>abx</span><span class='kw'>[[</span><span class='fl'>1</span>]])
<span class='kw'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='no'>dplyr</span>)) {
<span class='kw'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'>"dplyr"</span>)) {
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/reexports.html'>tibble</a></span>(<span class='kw'>clinical_text</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"given 400mg cipro and 500 mg amox"</span>,
<span class='st'>"started on doxy iv today"</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>abx_codes</span> <span class='kw'>=</span> <span class='fu'>ab_from_text</span>(<span class='no'>clinical_text</span>),

3
docs/reference/antibiotic_class_selectors.html

@ -281,7 +281,8 @@ @@ -281,7 +281,8 @@
<div class='dont-index'><p><code><a href='filter_ab_class.html'>filter_ab_class()</a></code> for the <code><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter()</a></code> equivalent.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='kw'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'>"dplyr"</span>)) {
<pre class="examples"><span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>dplyr</span>)
<span class='co'># this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):</span>
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>

5
docs/reference/filter_ab_class.html

@ -303,7 +303,8 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s @@ -303,7 +303,8 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<div class='dont-index'><p><code><a href='antibiotic_class_selectors.html'>antibiotic_class_selectors()</a></code> for the <code><a href='https://dplyr.tidyverse.org/reference/select.html'>select()</a></code> equivalent.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='kw'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='no'>dplyr</span>)) {
<pre class="examples"><span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>dplyr</span>)
<span class='co'># filter on isolates that have any result for any aminoglycoside</span>
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span> <span class='fu'>filter_ab_class</span>(<span class='st'>"aminoglycoside"</span>)
@ -332,9 +333,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s @@ -332,9 +333,7 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
<span class='fu'>filter_aminoglycosides</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>filter_fluoroquinolones</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
}
<span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
<span class='co'># with dplyr 1.0.0 and higher (that adds 'across()'), this is equal:</span>
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span> <span class='fu'>filter_carbapenems</span>(<span class='st'>"R"</span>, <span class='st'>"all"</span>)
<span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='fu'><a href='https://dplyr.tidyverse.org/reference/across.html'>across</a></span>(<span class='fu'><a href='antibiotic_class_selectors.html'>carbapenems</a></span>(), ~<span class='no'>.</span> <span class='kw'>==</span> <span class='st'>"R"</span>))

3
docs/reference/ggplot_pca.html

@ -388,7 +388,8 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing< @@ -388,7 +388,8 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>maturing<
<span class='co'># See ?example_isolates.</span>
<span class='co'># See ?pca for more info about Principal Component Analysis (PCA).</span>
<span class='kw'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'>"dplyr"</span>)) {
<span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>pca_model</span> <span class='kw'>&lt;-</span> <span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='fu'><a href='mo_property.html'>mo_genus</a></span>(<span class='no'>mo</span>) <span class='kw'>==</span> <span class='st'>"Staphylococcus"</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='kw'>species</span> <span class='kw'>=</span> <span class='fu'><a href='mo_property.html'>mo_shortname</a></span>(<span class='no'>mo</span>)) <span class='kw'>%&gt;%</span>

4
docs/reference/resistance_predict.html

@ -411,7 +411,9 @@ A microorganism is categorised as <em>Susceptible, Increased exposure</em> when @@ -411,7 +411,9 @@ A microorganism is categorised as <em>Susceptible, Increased exposure</em> when
}
<span class='co'># create nice plots with ggplot2 yourself</span>
<span class='kw'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='no'>ggplot2</span>) <span class='kw'>&amp;</span> <span class='fu'><a href='https://rdrr.io/r/base/library.html'>require</a></span>(<span class='st'>"dplyr"</span>)) {
<span class='kw'>if</span> (<span class='fl'>FALSE</span>) {
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>dplyr</span>)
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>ggplot2</span>)
<span class='no'>data</span> <span class='kw'>&lt;-</span> <span class='no'>example_isolates</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>mo</span> <span class='kw'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"E. coli"</span>)) <span class='kw'>%&gt;%</span>

2
man/ab_from_text.Rd

@ -80,7 +80,7 @@ ab_from_text("500 mg amoxi po and 400mg cipro iv", collapse = ", ") @@ -80,7 +80,7 @@ ab_from_text("500 mg amoxi po and 400mg cipro iv", collapse = ", ")
abx <- ab_from_text("500 mg amoxi po and 400mg cipro iv")
ab_group(abx[[1]])
if (require(dplyr)) {
if (require("dplyr")) {
tibble(clinical_text = c("given 400mg cipro and 500 mg amox",
"started on doxy iv today")) \%>\%
mutate(abx_codes = ab_from_text(clinical_text),

3
man/antibiotic_class_selectors.Rd

@ -58,7 +58,8 @@ All columns will be searched for known antibiotic names, abbreviations, brand na @@ -58,7 +58,8 @@ All columns will be searched for known antibiotic names, abbreviations, brand na
These functions only work if the \code{tidyselect} package is installed, that comes with the \code{dplyr} package. An error will be thrown if \code{tidyselect} package is not installed, or if the functions are used outside a function that allows Tidyverse selections like \code{select()} or \code{pivot_longer()}.
}
\examples{
if (require("dplyr")) {
\dontrun{
library(dplyr)
# this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
example_isolates \%>\%

5
man/filter_ab_class.Rd

@ -71,7 +71,8 @@ If the unlying code needs breaking changes, they will occur gradually. For examp @@ -71,7 +71,8 @@ If the unlying code needs breaking changes, they will occur gradually. For examp
}
\examples{
if (require(dplyr)) {
\dontrun{
library(dplyr)
# filter on isolates that have any result for any aminoglycoside
example_isolates \%>\% filter_ab_class("aminoglycoside")
@ -100,9 +101,7 @@ example_isolates \%>\% @@ -100,9 +101,7 @@ example_isolates \%>\%
example_isolates \%>\%
filter_aminoglycosides("R", "all") \%>\%
filter_fluoroquinolones("R", "all")
}
\dontrun{
# with dplyr 1.0.0 and higher (that adds 'across()'), this is equal:
example_isolates \%>\% filter_carbapenems("R", "all")
example_isolates \%>\% filter(across(carbapenems(), ~. == "R"))

3
man/ggplot_pca.Rd

@ -118,7 +118,8 @@ The \link[=lifecycle]{lifecycle} of this function is \strong{maturing}. The unly @@ -118,7 +118,8 @@ The \link[=lifecycle]{lifecycle} of this function is \strong{maturing}. The unly
# See ?example_isolates.
# See ?pca for more info about Principal Component Analysis (PCA).
if (require("dplyr")) {
\dontrun{
library(dplyr)
pca_model <- example_isolates \%>\%
filter(mo_genus(mo) == "Staphylococcus") \%>\%
group_by(species = mo_shortname(mo)) \%>\%

4
man/resistance_predict.Rd

@ -150,7 +150,9 @@ if (require("dplyr")) { @@ -150,7 +150,9 @@ if (require("dplyr")) {
}
# create nice plots with ggplot2 yourself
if (require(ggplot2) & require("dplyr")) {
\dontrun{
library(dplyr)
library(ggplot2)
data <- example_isolates \%>\%
filter(mo == as.mo("E. coli")) \%>\%

1
tests/testthat/test-ab.R

@ -22,7 +22,6 @@ @@ -22,7 +22,6 @@
context("ab.R")
test_that("as.ab works", {
skip_on_cran()
expect_equal(as.character(as.ab(c("J01FA01",

1
tests/testthat/test-ab_from_text.R

@ -22,7 +22,6 @@ @@ -22,7 +22,6 @@
context("ab_from_text.R")
test_that("ab_from_text works", {
skip_on_cran()
expect_identical(ab_from_text("28/03/2020 regular amoxicilliin 500mg po tds")[[1]],

1
tests/testthat/test-ab_property.R

@ -22,7 +22,6 @@ @@ -22,7 +22,6 @@
context("ab_property.R")
test_that("ab_property works", {
skip_on_cran()
expect_identical(ab_name("AMX"), "Amoxicillin")

2
tests/testthat/test-age.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("age.R")
test_that("age works", {
skip_on_cran()
expect_equal(age(x = c("1980-01-01", "1985-01-01", "1990-01-01"),
reference = "2019-01-01"),
c(39, 34, 29))
@ -47,6 +48,7 @@ test_that("age works", { @@ -47,6 +48,7 @@ test_that("age works", {
})
test_that("age_groups works", {
skip_on_cran()
ages <- c(3, 8, 16, 54, 31, 76, 101, 43, 21)
expect_equal(length(unique(age_groups(ages, 50))),

1
tests/testthat/test-availability.R

@ -22,5 +22,6 @@ @@ -22,5 +22,6 @@
context("availability.R")
test_that("availability works", {
skip_on_cran()
expect_equal(class(availability(example_isolates)), "data.frame")
})

1
tests/testthat/test-bug_drug_combinations.R

@ -22,7 +22,6 @@ @@ -22,7 +22,6 @@
context("bug_drug_combinations.R")
test_that("bug_drug_combinations works", {
skip_on_cran()
b <- suppressWarnings(bug_drug_combinations(example_isolates))

1
tests/testthat/test-count.R

@ -22,7 +22,6 @@ @@ -22,7 +22,6 @@
context("count.R")
test_that("counts work", {
skip_on_cran()
expect_equal(count_resistant(example_isolates$AMX), count_R(example_isolates$AMX))

20
tests/testthat/test-data.R

@ -22,7 +22,7 @@ @@ -22,7 +22,7 @@
context("data.R")
test_that("data sets are valid", {
skip_on_cran()
expect_true(check_dataset_integrity()) # in misc.R
# IDs should always be unique
@ -39,10 +39,10 @@ test_that("data sets are valid", { @@ -39,10 +39,10 @@ test_that("data sets are valid", {
expect_false(any(is.na(microorganisms.codes$code)))
expect_false(any(is.na(microorganisms.codes$mo)))
expect_false(any(microorganisms.translation$mo_old %in% microorganisms$mo))
# antibiotic names must always be coercible to their original AB code
expect_identical(antibiotics$ab, as.ab(antibiotics$name))
# there should be no diacritics (i.e. non ASCII) characters in the datasets (CRAN policy)
datasets <- data(package = "AMR", envir = asNamespace("AMR"))$results[, "Item"]
for (i in seq_len(length(datasets))) {
@ -52,6 +52,8 @@ test_that("data sets are valid", { @@ -52,6 +52,8 @@ test_that("data sets are valid", {
})
test_that("creation of data sets is valid", {
skip_on_cran()
df <- create_MO_lookup()
expect_lt(nrow(df[which(df$prevalence == 1), ]), nrow(df[which(df$prevalence == 2), ]))
expect_lt(nrow(df[which(df$prevalence == 2), ]), nrow(df[which(df$prevalence == 3), ]))
@ -59,16 +61,18 @@ test_that("creation of data sets is valid", { @@ -59,16 +61,18 @@ test_that("creation of data sets is valid", {
"kingdom", "phylum", "class", "order", "family", "genus", "species", "subspecies",
"rank", "ref", "species_id", "source", "prevalence", "snomed",
"kingdom_index", "fullname_lower", "g_species") %in% colnames(df)))
olddf <- create_MO.old_lookup()
expect_true(all(c("fullname", "fullname_new", "ref", "prevalence",
"fullname_lower", "g_species") %in% colnames(olddf)))
})
test_that("CoL version info works", {
expect_identical(class(catalogue_of_life_version()),
c("catalogue_of_life_version", "list"))
skip_on_cran()
expect_identical(class(catalogue_of_life_version()),
c("catalogue_of_life_version", "list"))
expect_output(print(catalogue_of_life_version()))
})

1
tests/testthat/test-deprecated.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("deprecated.R")
test_that("deprecated functions work", {
skip_on_cran()
expect_equal(suppressWarnings(portion_S(example_isolates$AMX)), proportion_S(example_isolates$AMX))
expect_equal(suppressWarnings(portion_SI(example_isolates$AMX)), proportion_SI(example_isolates$AMX))
expect_equal(suppressWarnings(portion_I(example_isolates$AMX)), proportion_I(example_isolates$AMX))

1
tests/testthat/test-disk.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("disk.R")
test_that("disk works", {
skip_on_cran()
expect_true(as.disk(8) == as.disk("8"))
expect_true(is.disk(as.disk(8)))

1
tests/testthat/test-first_isolate.R

@ -22,7 +22,6 @@ @@ -22,7 +22,6 @@
context("first_isolate.R")
test_that("first isolates work", {
skip_on_cran()
# first isolates

1
tests/testthat/test-g.test.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("g.test.R")
test_that("G-test works", {
skip_on_cran()
# GOODNESS-OF-FIT

1
tests/testthat/test-get_locale.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("get_locale.R")
test_that("get_locale works", {
skip_on_cran()
expect_identical(mo_genus("B_GRAMP", language = "pt"),
"(Gram positivos desconhecidos)")

2
tests/testthat/test-ggplot_rsi.R

@ -25,7 +25,7 @@ test_that("ggplot_rsi works", { @@ -25,7 +25,7 @@ test_that("ggplot_rsi works", {
skip_on_cran()
skip_if_not("ggplot2" %in% rownames(installed.packages()))
skip_if_not_installed("ggplot2")
library(dplyr)
library(ggplot2)

1
tests/testthat/test-guess_ab_col.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("guess_ab_col.R")
test_that("guess_ab_col works", {
skip_on_cran()
expect_equal(guess_ab_col(example_isolates, "amox"),
"AMX")

1
tests/testthat/test-join_microorganisms.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("join_microorganisms.R")
test_that("joins work", {
skip_on_cran()
unjoined <- example_isolates
inner <- example_isolates %>% inner_join_microorganisms()
left <- example_isolates %>% left_join_microorganisms()

1
tests/testthat/test-key_antibiotics.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("key_antibiotics.R")
test_that("keyantibiotics work", {
skip_on_cran()
expect_equal(length(key_antibiotics(example_isolates, warnings = FALSE)), nrow(example_isolates))
expect_false(all(is.na(key_antibiotics(example_isolates))))
expect_true(key_antibiotics_equal("SSS", "SSS"))

1
tests/testthat/test-kurtosis.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("kurtosis.R")
test_that("kurtosis works", {
skip_on_cran()
expect_equal(kurtosis(example_isolates$age),
3.549319,
tolerance = 0.00001)

1
tests/testthat/test-like.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("like.R")
test_that("`like` works", {
skip_on_cran()
expect_true(sum("test" %like% c("^t", "^s")) == 1)
expect_true("test" %like% "test")
expect_true("test" %like% "TEST")

1
tests/testthat/test-mic.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("mic.R")
test_that("mic works", {
skip_on_cran()
expect_true(as.mic(8) == as.mic("8"))
expect_true(as.mic("1") > as.mic("<=0.0625"))
expect_true(as.mic("1") < as.mic(">=32"))

3
tests/testthat/test-misc.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("misc.R")
test_that("percentages works", {
skip_on_cran()
expect_equal(percentage(0.25), "25%")
expect_equal(percentage(0.5), "50%")
expect_equal(percentage(0.500, digits = 1), "50.0%")
@ -32,6 +33,7 @@ test_that("percentages works", { @@ -32,6 +33,7 @@ test_that("percentages works", {
})
test_that("functions missing in older R versions work", {
skip_on_cran()
expect_equal(strrep("A", 5), "AAAAA")
expect_equal(strrep(c("A", "B"), c(5, 2)), c("AAAAA", "BB"))
expect_equal(trimws(" test "), "test")
@ -40,6 +42,7 @@ test_that("functions missing in older R versions work", { @@ -40,6 +42,7 @@ test_that("functions missing in older R versions work", {
})
test_that("looking up ab columns works", {
skip_on_cran()
expect_warning(generate_warning_abs_missing(c("AMP", "AMX")))
expect_warning(generate_warning_abs_missing(c("AMP", "AMX"), any = TRUE))
expect_warning(get_column_abx(example_isolates, hard_dependencies = "FUS"))

20
tests/testthat/test-mo_history.R

@ -1,20 +0,0 @@ @@ -1,20 +0,0 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# LICENCE #
# (c) 2018-2020 Berends MS, Luz CF et al. #
# #
# This R package is free software; you can freely use and distribute #
# it for both personal and commercial purposes under the terms of the #
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
# the Free Software Foundation. #
# #
# We created this package for both routine data analysis and academic #
# research and it was publicly released in the hope that it will be #
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
# Visit our website for more info: https://msberends.github.io/AMR. #
# ==================================================================== #

1
tests/testthat/test-p_symbol.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("p_symbol.R")
test_that("P symbol works", {
skip_on_cran()
expect_identical(p_symbol(c(0.001, 0.01, 0.05, 0.1, 1, NA, 3)),
c("***", "**", "*", ".", " ", NA, NA))
})

1
tests/testthat/test-resistance_predict.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("resistance_predict.R")
test_that("prediction of rsi works", {
skip_on_cran()
AMX_R <- example_isolates %>%
filter(mo == "B_ESCHR_COLI") %>%
rsi_predict(col_ab = "AMX",

1
tests/testthat/test-rsi.R

@ -22,7 +22,6 @@ @@ -22,7 +22,6 @@
context("rsi.R")
test_that("rsi works", {
skip_on_cran()
expect_true(as.rsi("S") < as.rsi("I"))

1
tests/testthat/test-skewness.R

@ -22,6 +22,7 @@ @@ -22,6 +22,7 @@
context("skewness.R")
test_that("skewness works", {
skip_on_cran()
expect_equal(skewness(example_isolates$age),
-0.8958019,
tolerance = 0.00001)

Loading…
Cancel
Save