(v1.3.0) skip more CRAN tests

.Rbuildignore

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

DESCRIPTION

@@ -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"), 

R/ab_class_selectors.R

@@ -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 %>% 

R/ab_from_text.R

@@ -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),

R/filter_ab_class.R

@@ -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 @@
 #' 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"))

R/ggplot_pca.R

@@ -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)) %>%

R/resistance_predict.R

@@ -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")) %>%

cran-comments.md

@@ -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.

docs/pkgdown.yml

@@ -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

docs/reference/ab_from_text.html

@@ -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>),

docs/reference/antibiotic_class_selectors.html

@@ -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>

docs/reference/filter_ab_class.html

@@ -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
 <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>))

docs/reference/ggplot_pca.html

@@ -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>

docs/reference/resistance_predict.html

@@ -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>

man/ab_from_text.Rd

@@ -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),

man/antibiotic_class_selectors.Rd

@@ -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 \%>\% 

man/filter_ab_class.Rd

@@ -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 \%>\%
 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"))

man/ggplot_pca.Rd

@@ -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)) \%>\%

man/resistance_predict.Rd

@@ -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")) \%>\%

tests/testthat/test-ab.R

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

tests/testthat/test-ab_from_text.R

@@ -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]],

tests/testthat/test-ab_property.R

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

tests/testthat/test-age.R

@@ -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", {
 })
 
 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))),

tests/testthat/test-availability.R

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

tests/testthat/test-bug_drug_combinations.R

@@ -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))

tests/testthat/test-count.R

@@ -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))

tests/testthat/test-data.R

@@ -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", {
   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", {
 })
 
 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", {
                     "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()))
 })

tests/testthat/test-deprecated.R

@@ -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))

tests/testthat/test-disk.R

@@ -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)))
 

tests/testthat/test-first_isolate.R

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

tests/testthat/test-g.test.R

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

tests/testthat/test-get_locale.R

@@ -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)")
 

tests/testthat/test-ggplot_rsi.R

@@ -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)

tests/testthat/test-guess_ab_col.R

@@ -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")

tests/testthat/test-join_microorganisms.R

@@ -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()

tests/testthat/test-key_antibiotics.R

@@ -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"))

tests/testthat/test-kurtosis.R

@@ -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)

tests/testthat/test-like.R

@@ -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")

tests/testthat/test-mic.R

@@ -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"))

tests/testthat/test-misc.R

@@ -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", {
 })
 
 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", {
 })
 
 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"))

tests/testthat/test-mo_history.R

@@ -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.    #
-# ==================================================================== #

tests/testthat/test-p_symbol.R

@@ -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))
 })

tests/testthat/test-resistance_predict.R

@@ -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",

tests/testthat/test-rsi.R

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

tests/testthat/test-skewness.R

@@ -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)