(v1.6.0.9065) unit tests

This commit is contained in:
dr. M.S. (Matthijs) Berends 2021-05-24 11:01:32 +02:00
parent 4fbf9e1720
commit e5599bc694
22 changed files with 126 additions and 133 deletions

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@ -121,6 +121,7 @@ jobs:
# - name: Only keep vignettes on release version
- name: Remove vignettes
# if: matrix.config.r != 'release'
if: always()
# writing to DESCRIPTION2 and then moving to DESCRIPTION is required for R < 3.3 as writeLines() cannot overwrite
run: |
rm -rf AMR/vignettes

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@ -1,5 +1,5 @@
Package: AMR
Version: 1.6.0.9064
Version: 1.6.0.9065
Date: 2021-05-24
Title: Antimicrobial Resistance Data Analysis
Authors@R: c(

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@ -1,4 +1,4 @@
# `AMR` 1.6.0.9064
# `AMR` 1.6.0.9065
## <small>Last updated: 24 May 2021</small>
### Breaking change

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@ -864,8 +864,13 @@ unique_call_id <- function(entire_session = FALSE) {
} else {
# combination of environment ID (like "0x7fed4ee8c848")
# and highest system call
call <- paste0(deparse(sys.calls()[[1]]), collapse = "")
if (call %like% "run_test_dir|test_all|tinytest|test_package|testthat") {
# unit tests will keep the same call and environment - give them a unique ID
call <- paste0(sample(c(c(0:9), letters[1:6]), size = 64, replace = TRUE), collapse = "")
}
c(envir = gsub("<environment: (.*)>", "\\1", utils::capture.output(sys.frames()[[1]])),
call = paste0(deparse(sys.calls()[[1]]), collapse = ""))
call = call)
}
}
@ -881,14 +886,6 @@ message_not_thrown_before <- function(fn, entire_session = FALSE) {
is.null(pkg_env[[paste0("thrown_msg.", fn)]]) || !identical(pkg_env[[paste0("thrown_msg.", fn)]], unique_call_id(entire_session))
}
reset_all_thrown_messages <- function() {
# for unit tests, where the environment and highest system call do not change
# can be found in tests/testthat/*.R
pkg_env_contents <- ls(envir = pkg_env)
rm(list = pkg_env_contents[pkg_env_contents %like% "^thrown_msg."],
envir = pkg_env)
}
has_colour <- function() {
# this is a base R version of crayon::has_color, but disables colours on emacs

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@ -115,35 +115,35 @@
#' ggplot() +
#' geom_col(aes(x = x, y = y, fill = z)) +
#' scale_rsi_colours(Value4 = "S", Value5 = "I", Value6 = "R")
#'
#' # resistance of ciprofloxacine per age group
#' example_isolates %>%
#' mutate(first_isolate = first_isolate()) %>%
#' filter(first_isolate == TRUE,
#' mo == as.mo("E. coli")) %>%
#' # age_groups() is also a function in this AMR package:
#' group_by(age_group = age_groups(age)) %>%
#' select(age_group,
#' CIP) %>%
#' ggplot_rsi(x = "age_group")
#'
#' # a shorter version which also adjusts data label colours:
#' example_isolates %>%
#' select(AMX, NIT, FOS, TMP, CIP) %>%
#' ggplot_rsi(colours = FALSE)
#'
#'
#' # it also supports groups (don't forget to use the group var on `x` or `facet`):
#' example_isolates %>%
#' select(hospital_id, AMX, NIT, FOS, TMP, CIP) %>%
#' group_by(hospital_id) %>%
#' ggplot_rsi(x = "hospital_id",
#' facet = "antibiotic",
#' nrow = 1,
#' title = "AMR of Anti-UTI Drugs Per Hospital",
#' x.title = "Hospital",
#' datalabels = FALSE)
#' }
#'
#' # resistance of ciprofloxacine per age group
#' example_isolates %>%
#' mutate(first_isolate = first_isolate(.)) %>%
#' filter(first_isolate == TRUE,
#' mo == as.mo("E. coli")) %>%
#' # age_groups() is also a function in this AMR package:
#' group_by(age_group = age_groups(age)) %>%
#' select(age_group,
#' CIP) %>%
#' ggplot_rsi(x = "age_group")
#'
#' # a shorter version which also adjusts data label colours:
#' example_isolates %>%
#' select(AMX, NIT, FOS, TMP, CIP) %>%
#' ggplot_rsi(colours = FALSE)
#'
#'
#' # it also supports groups (don't forget to use the group var on `x` or `facet`):
#' example_isolates %>%
#' select(hospital_id, AMX, NIT, FOS, TMP, CIP) %>%
#' group_by(hospital_id) %>%
#' ggplot_rsi(x = "hospital_id",
#' facet = "antibiotic",
#' nrow = 1,
#' title = "AMR of Anti-UTI Drugs Per Hospital",
#' x.title = "Hospital",
#' datalabels = FALSE)
#' }
ggplot_rsi <- function(data,
position = NULL,

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@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="https://msberends.github.io/AMR//index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9064</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9065</span>
</span>
</div>

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@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9064</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9065</span>
</span>
</div>

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@ -39,7 +39,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9064</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9065</span>
</span>
</div>

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@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9064</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9065</span>
</span>
</div>

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@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9064</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9065</span>
</span>
</div>

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@ -42,7 +42,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9064</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9065</span>
</span>
</div>

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@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9064</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9065</span>
</span>
</div>
@ -236,9 +236,9 @@
<small>Source: <a href='https://github.com/msberends/AMR/blob/master/NEWS.md'><code>NEWS.md</code></a></small>
</div>
<div id="amr-1609064" class="section level1">
<h1 class="page-header" data-toc-text="1.6.0.9064">
<a href="#amr-1609064" class="anchor"></a><small> Unreleased </small><code>AMR</code> 1.6.0.9064</h1>
<div id="amr-1609065" class="section level1">
<h1 class="page-header" data-toc-text="1.6.0.9065">
<a href="#amr-1609065" class="anchor"></a><small> Unreleased </small><code>AMR</code> 1.6.0.9065</h1>
<div id="last-updated-24-may-2021" class="section level2">
<h2 class="hasAnchor">
<a href="#last-updated-24-may-2021" class="anchor"></a><small>Last updated: 24 May 2021</small>
@ -288,7 +288,7 @@
</ul>
</li>
<li>Function <code><a href="../reference/antibiotic_class_selectors.html">betalactams()</a></code> as additional antbiotic column selector and function <code><a href="../reference/AMR-deprecated.html">filter_betalactams()</a></code> as additional antbiotic column filter. The group of betalactams consists of all carbapenems, cephalosporins and penicillins.</li>
<li>A <code>ggplot()</code> method for <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>
<li>A <code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot()</a></code> method for <code><a href="../reference/resistance_predict.html">resistance_predict()</a></code>
</li>
</ul>
</div>
@ -387,7 +387,7 @@
<span class="co">#&gt; Filtering on oxazolidinones: value in column `LNZ` (linezolid) is either "R", "S" or "I"</span></code></pre></div>
</li>
<li><p>Support for custom MDRO guidelines, using the new <code><a href="../reference/mdro.html">custom_mdro_guideline()</a></code> function, please see <code><a href="../reference/mdro.html">mdro()</a></code> for additional info</p></li>
<li><p><code>ggplot()</code> generics for classes <code>&lt;mic&gt;</code> and <code>&lt;disk&gt;</code></p></li>
<li><p><code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot()</a></code> generics for classes <code>&lt;mic&gt;</code> and <code>&lt;disk&gt;</code></p></li>
<li>
<p>Function <code><a href="../reference/mo_property.html">mo_is_yeast()</a></code>, which determines whether a microorganism is a member of the taxonomic class Saccharomycetes or the taxonomic order Saccharomycetales:</p>
<div class="sourceCode" id="cb4"><pre class="downlit sourceCode r">
@ -444,7 +444,7 @@
<li>Plotting of MIC and disk diffusion values now support interpretation colouring if you supply the microorganism and antimicrobial agent</li>
<li>All colours were updated to colour-blind friendly versions for values R, S and I for all plot methods (also applies to tibble printing)</li>
<li>Interpretation of MIC and disk diffusion values to R/SI will now be translated if the system language is German, Dutch or Spanish (see <code>translate</code>)</li>
<li>Plotting is now possible with base R using <code><a href="../reference/plot.html">plot()</a></code> and with ggplot2 using <code>ggplot()</code> on any vector of MIC and disk diffusion values</li>
<li>Plotting is now possible with base R using <code><a href="../reference/plot.html">plot()</a></code> and with ggplot2 using <code><a href="https://ggplot2.tidyverse.org/reference/ggplot.html">ggplot()</a></code> on any vector of MIC and disk diffusion values</li>
</ul>
</li>
<li>Updated SNOMED codes to US Edition of SNOMED CT from 1 September 2020 and added the source to the help page of the <code>microorganisms</code> data set</li>

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@ -12,7 +12,7 @@ articles:
datasets: datasets.html
resistance_predict: resistance_predict.html
welcome_to_AMR: welcome_to_AMR.html
last_built: 2021-05-24T07:33Z
last_built: 2021-05-24T09:00Z
urls:
reference: https://msberends.github.io/AMR//reference
article: https://msberends.github.io/AMR//articles

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@ -82,7 +82,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9063</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9065</span>
</span>
</div>
@ -477,35 +477,35 @@ The <a href='lifecycle.html'>lifecycle</a> of this function is <strong>stable</s
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></span><span class='op'>(</span><span class='op'>)</span> <span class='op'>+</span>
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/geom_bar.html'>geom_col</a></span><span class='op'>(</span><span class='fu'><a href='https://ggplot2.tidyverse.org/reference/aes.html'>aes</a></span><span class='op'>(</span>x <span class='op'>=</span> <span class='va'>x</span>, y <span class='op'>=</span> <span class='va'>y</span>, fill <span class='op'>=</span> <span class='va'>z</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>+</span>
<span class='fu'>scale_rsi_colours</span><span class='op'>(</span>Value4 <span class='op'>=</span> <span class='st'>"S"</span>, Value5 <span class='op'>=</span> <span class='st'>"I"</span>, Value6 <span class='op'>=</span> <span class='st'>"R"</span><span class='op'>)</span>
<span class='co'># resistance of ciprofloxacine per age group</span>
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span><span class='op'>(</span>first_isolate <span class='op'>=</span> <span class='fu'><a href='first_isolate.html'>first_isolate</a></span><span class='op'>(</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span><span class='op'>(</span><span class='va'>first_isolate</span> <span class='op'>==</span> <span class='cn'>TRUE</span>,
<span class='va'>mo</span> <span class='op'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span><span class='op'>(</span><span class='st'>"E. coli"</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='co'># age_groups() is also a function in this AMR package:</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span><span class='op'>(</span>age_group <span class='op'>=</span> <span class='fu'><a href='age_groups.html'>age_groups</a></span><span class='op'>(</span><span class='va'>age</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span><span class='op'>(</span><span class='va'>age_group</span>,
<span class='va'>CIP</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'>ggplot_rsi</span><span class='op'>(</span>x <span class='op'>=</span> <span class='st'>"age_group"</span><span class='op'>)</span>
<span class='co'># a shorter version which also adjusts data label colours:</span>
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span><span class='op'>(</span><span class='va'>AMX</span>, <span class='va'>NIT</span>, <span class='va'>FOS</span>, <span class='va'>TMP</span>, <span class='va'>CIP</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'>ggplot_rsi</span><span class='op'>(</span>colours <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span>
<span class='co'># it also supports groups (don't forget to use the group var on `x` or `facet`):</span>
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span><span class='op'>(</span><span class='va'>hospital_id</span>, <span class='va'>AMX</span>, <span class='va'>NIT</span>, <span class='va'>FOS</span>, <span class='va'>TMP</span>, <span class='va'>CIP</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span><span class='op'>(</span><span class='va'>hospital_id</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'>ggplot_rsi</span><span class='op'>(</span>x <span class='op'>=</span> <span class='st'>"hospital_id"</span>,
facet <span class='op'>=</span> <span class='st'>"antibiotic"</span>,
nrow <span class='op'>=</span> <span class='fl'>1</span>,
title <span class='op'>=</span> <span class='st'>"AMR of Anti-UTI Drugs Per Hospital"</span>,
x.title <span class='op'>=</span> <span class='st'>"Hospital"</span>,
datalabels <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span>
<span class='op'>}</span>
<span class='co'># resistance of ciprofloxacine per age group</span>
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span><span class='op'>(</span>first_isolate <span class='op'>=</span> <span class='fu'><a href='first_isolate.html'>first_isolate</a></span><span class='op'>(</span><span class='va'>.</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/filter.html'>filter</a></span><span class='op'>(</span><span class='va'>first_isolate</span> <span class='op'>==</span> <span class='cn'>TRUE</span>,
<span class='va'>mo</span> <span class='op'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span><span class='op'>(</span><span class='st'>"E. coli"</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='co'># age_groups() is also a function in this AMR package:</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span><span class='op'>(</span>age_group <span class='op'>=</span> <span class='fu'><a href='age_groups.html'>age_groups</a></span><span class='op'>(</span><span class='va'>age</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span><span class='op'>(</span><span class='va'>age_group</span>,
<span class='va'>CIP</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'>ggplot_rsi</span><span class='op'>(</span>x <span class='op'>=</span> <span class='st'>"age_group"</span><span class='op'>)</span>
<span class='co'># a shorter version which also adjusts data label colours:</span>
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span><span class='op'>(</span><span class='va'>AMX</span>, <span class='va'>NIT</span>, <span class='va'>FOS</span>, <span class='va'>TMP</span>, <span class='va'>CIP</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'>ggplot_rsi</span><span class='op'>(</span>colours <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span>
<span class='co'># it also supports groups (don't forget to use the group var on `x` or `facet`):</span>
<span class='va'>example_isolates</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/select.html'>select</a></span><span class='op'>(</span><span class='va'>hospital_id</span>, <span class='va'>AMX</span>, <span class='va'>NIT</span>, <span class='va'>FOS</span>, <span class='va'>TMP</span>, <span class='va'>CIP</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'><a href='https://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span><span class='op'>(</span><span class='va'>hospital_id</span><span class='op'>)</span> <span class='op'>%&gt;%</span>
<span class='fu'>ggplot_rsi</span><span class='op'>(</span>x <span class='op'>=</span> <span class='st'>"hospital_id"</span>,
facet <span class='op'>=</span> <span class='st'>"antibiotic"</span>,
nrow <span class='op'>=</span> <span class='fl'>1</span>,
title <span class='op'>=</span> <span class='st'>"AMR of Anti-UTI Drugs Per Hospital"</span>,
x.title <span class='op'>=</span> <span class='st'>"Hospital"</span>,
datalabels <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span>
<span class='co'># }</span>
</pre>
</div>

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@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9064</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9065</span>
</span>
</div>

View File

@ -81,7 +81,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9064</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.6.0.9065</span>
</span>
</div>

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@ -22,34 +22,32 @@
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
expect_equal(AMR:::percentage(0.25), "25%")
expect_equal(AMR:::percentage(0.5), "50%")
expect_equal(AMR:::percentage(0.500, digits = 1), "50.0%")
expect_equal(AMR:::percentage(0.1234), "12.3%")
# round up 0.5
# round up 0.5
expect_equal(AMR:::percentage(0.0054), "0.5%")
expect_equal(AMR:::percentage(0.0055), "0.6%")
expect_equal(AMR:::strrep("A", 5), "AAAAA")
expect_equal(AMR:::strrep(c("A", "B"), c(5, 2)), c("AAAAA", "BB"))
expect_equal(AMR:::trimws(" test "), "test")
expect_equal(AMR:::trimws(" test ", "l"), "test ")
expect_equal(AMR:::trimws(" test ", "r"), " test")
expect_warning(AMR:::generate_warning_abs_missing(c("AMP", "AMX")))
expect_warning(AMR:::generate_warning_abs_missing(c("AMP", "AMX"), any = TRUE))
expect_warning(AMR:::get_column_abx(example_isolates, hard_dependencies = "FUS"))
expect_message(AMR:::get_column_abx(example_isolates, soft_dependencies = "FUS"))
if (AMR:::pkg_is_available("dplyr")) {
if (AMR:::pkg_is_available("dplyr")) {
expect_warning(AMR:::get_column_abx(rename(example_isolates, thisone = AMX), amox = "thisone", tmp = "thisone", verbose = TRUE))
expect_warning(AMR:::get_column_abx(rename(example_isolates, thisone = AMX), amox = "thisone", tmp = "thisone", verbose = FALSE))
}
# we rely on "grouped_tbl" being a class of grouped tibbles, so implement a test that checks for this:
if (AMR:::pkg_is_available("dplyr")) {
expect_true(AMR:::is_null_or_grouped_tbl(example_isolates %>% group_by(hospital_id)))
}
}
# we rely on "grouped_tbl" being a class of grouped tibbles, so implement a test that checks for this:
if (AMR:::pkg_is_available("dplyr")) {
expect_true(AMR:::is_null_or_grouped_tbl(example_isolates %>% group_by(hospital_id)))
}

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@ -36,11 +36,9 @@ expect_equal(count_R(example_isolates$AMX) + count_I(example_isolates$AMX),
expect_equal(suppressWarnings(count_S(example_isolates$AMX)) + count_I(example_isolates$AMX),
count_SI(example_isolates$AMX))
# warning for speed loss
AMR:::reset_all_thrown_messages()
expect_warning(count_resistant(as.character(example_isolates$AMC)))
AMR:::reset_all_thrown_messages()
expect_warning(count_resistant(example_isolates$AMC,
as.character(example_isolates$GEN)))

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@ -45,6 +45,7 @@ expect_warning(eucast_rules(data.frame(mo = "Escherichia coli", vancomycin = "S"
expect_identical(colnames(example_isolates),
colnames(suppressWarnings(eucast_rules(example_isolates, info = FALSE))))
expect_stdout(suppressMessages(eucast_rules(example_isolates, info = TRUE)))
a <- data.frame(mo = c("Klebsiella pneumoniae",
@ -84,7 +85,7 @@ if (AMR:::pkg_is_available("dplyr")) {
"R")
}
# Azithromycin and Clarythromycin must be equal to Erythromycin
# azithromycin and clarythromycin must be equal to Erythromycin
a <- suppressWarnings(as.rsi(eucast_rules(data.frame(mo = example_isolates$mo,
ERY = example_isolates$ERY,
AZM = as.rsi("R"),
@ -117,18 +118,21 @@ if (AMR:::pkg_is_available("dplyr")) {
expect_stdout(suppressWarnings(eucast_rules(example_isolates, verbose = TRUE, rules = "all", info = TRUE)))
# AmpC de-repressed cephalo mutants
expect_identical(
eucast_rules(data.frame(mo = c("Escherichia coli", "Enterobacter cloacae"),
cefotax = as.rsi(c("S", "S"))),
ampc_cephalosporin_resistance = TRUE,
info = FALSE)$cefotax,
as.rsi(c("S", "R")))
expect_identical(
eucast_rules(data.frame(mo = c("Escherichia coli", "Enterobacter cloacae"),
cefotax = as.rsi(c("S", "S"))),
ampc_cephalosporin_resistance = NA,
info = FALSE)$cefotax,
as.rsi(c("S", NA)))
expect_identical(
eucast_rules(data.frame(mo = c("Escherichia coli", "Enterobacter cloacae"),
cefotax = as.rsi(c("S", "S"))),

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@ -88,14 +88,12 @@ if (AMR:::pkg_is_available("dplyr")) {
example_isolates$AMX %>% proportion_R())
)
}
AMR:::reset_all_thrown_messages()
expect_warning(proportion_R(as.character(example_isolates$AMC)))
AMR:::reset_all_thrown_messages()
expect_warning(proportion_S(as.character(example_isolates$AMC)))
AMR:::reset_all_thrown_messages()
expect_warning(proportion_S(as.character(example_isolates$AMC,
example_isolates$GEN)))
AMR:::reset_all_thrown_messages()
expect_warning(n_rsi(as.character(example_isolates$AMC,
example_isolates$GEN)))
expect_equal(suppressWarnings(n_rsi(as.character(example_isolates$AMC,
@ -120,11 +118,8 @@ expect_identical(suppressWarnings(proportion_S(example_isolates$AMX, minimum = n
NA_real_)
# warning for speed loss
AMR:::reset_all_thrown_messages()
expect_warning(proportion_R(as.character(example_isolates$GEN)))
AMR:::reset_all_thrown_messages()
expect_warning(proportion_I(as.character(example_isolates$GEN)))
AMR:::reset_all_thrown_messages()
expect_warning(proportion_S(example_isolates$AMC, as.character(example_isolates$GEN)))
expect_error(proportion_df(c("A", "B", "C")))
expect_error(proportion_df(example_isolates[, "date"]))

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@ -202,34 +202,34 @@ if (require("ggplot2") & require("dplyr")) {
ggplot() +
geom_col(aes(x = x, y = y, fill = z)) +
scale_rsi_colours(Value4 = "S", Value5 = "I", Value6 = "R")
}
# resistance of ciprofloxacine per age group
example_isolates \%>\%
mutate(first_isolate = first_isolate(.)) \%>\%
filter(first_isolate == TRUE,
mo == as.mo("E. coli")) \%>\%
# age_groups() is also a function in this AMR package:
group_by(age_group = age_groups(age)) \%>\%
select(age_group,
CIP) \%>\%
ggplot_rsi(x = "age_group")
# resistance of ciprofloxacine per age group
example_isolates \%>\%
mutate(first_isolate = first_isolate()) \%>\%
filter(first_isolate == TRUE,
mo == as.mo("E. coli")) \%>\%
# age_groups() is also a function in this AMR package:
group_by(age_group = age_groups(age)) \%>\%
select(age_group,
CIP) \%>\%
ggplot_rsi(x = "age_group")
# a shorter version which also adjusts data label colours:
example_isolates \%>\%
select(AMX, NIT, FOS, TMP, CIP) \%>\%
ggplot_rsi(colours = FALSE)
# a shorter version which also adjusts data label colours:
example_isolates \%>\%
select(AMX, NIT, FOS, TMP, CIP) \%>\%
ggplot_rsi(colours = FALSE)
# it also supports groups (don't forget to use the group var on `x` or `facet`):
example_isolates \%>\%
select(hospital_id, AMX, NIT, FOS, TMP, CIP) \%>\%
group_by(hospital_id) \%>\%
ggplot_rsi(x = "hospital_id",
facet = "antibiotic",
nrow = 1,
title = "AMR of Anti-UTI Drugs Per Hospital",
x.title = "Hospital",
datalabels = FALSE)
# it also supports groups (don't forget to use the group var on `x` or `facet`):
example_isolates \%>\%
select(hospital_id, AMX, NIT, FOS, TMP, CIP) \%>\%
group_by(hospital_id) \%>\%
ggplot_rsi(x = "hospital_id",
facet = "antibiotic",
nrow = 1,
title = "AMR of Anti-UTI Drugs Per Hospital",
x.title = "Hospital",
datalabels = FALSE)
}
}
}