(v1.0.1.9001) PCA unit tests

v1.8.2
parent fa0d9c58d9
commit 9fc858f208
  1. 4
      DESCRIPTION
  2. 1
      NAMESPACE
  3. 2
      NEWS.md
  4. 13
      R/ggplot_pca.R
  5. 1
      R/pca.R
  6. 2
      docs/404.html
  7. 2
      docs/LICENSE-text.html
  8. 2
      docs/articles/index.html
  9. 2
      docs/authors.html
  10. 2
      docs/index.html
  11. 8
      docs/news/index.html
  12. 10
      docs/reference/ggplot_pca.html
  13. 2
      docs/reference/index.html
  14. 4
      man/ggplot_pca.Rd
  15. 37
      tests/testthat/test-pca.R

@ -1,6 +1,6 @@
Package: AMR
Version: 1.0.1.9000
Date: 2020-03-07
Version: 1.0.1.9001
Date: 2020-03-08
Title: Antimicrobial Resistance Analysis
Authors@R: c(
person(role = c("aut", "cre"),

@ -327,6 +327,7 @@ importFrom(stats,complete.cases)
importFrom(stats,glm)
importFrom(stats,lm)
importFrom(stats,pchisq)
importFrom(stats,prcomp)
importFrom(stats,predict)
importFrom(tidyr,pivot_longer)
importFrom(tidyr,pivot_wider)

@ -1,4 +1,4 @@
# AMR 1.0.1.9000
# AMR 1.0.1.9001
### New
* Support for easy principal component analysis for AMR, using the new `pca()` function

@ -33,6 +33,7 @@
#' @param ellipse_prob statistical size of the ellipse in normal probability
#' @param ellipse_size the size of the ellipse line
#' @param ellipse_alpha the alpha (transparency) of the ellipse line
#' @param points_size the size of the points
#' @param points_alpha the alpha (transparency) of the points
#' @param arrows a logical to indicate whether arrows should be drawn
#' @param arrows_textsize the size of the text for variable names
@ -42,7 +43,7 @@
#' @param arrows_alpha the alpha (transparency) of the arrows and their text
#' @param base_textsize the text size for all plot elements except the labels and arrows
#' @param ... Parameters passed on to functions
#' @source The [ggplot_pca()] function is based on the [ggbiplot()] function from the `ggbiplot` package by Vince Vu, as found on GitHub: <https://github.com/vqv/ggbiplot> (retrieved: 2 March 2020, their latest commit: [`7325e88`](https://github.com/vqv/ggbiplot/commit/7325e880485bea4c07465a0304c470608fffb5d9); 12 February 2015).
#' @source The [ggplot_pca()] function is based on the `ggbiplot()` function from the `ggbiplot` package by Vince Vu, as found on GitHub: <https://github.com/vqv/ggbiplot> (retrieved: 2 March 2020, their latest commit: [`7325e88`](https://github.com/vqv/ggbiplot/commit/7325e880485bea4c07465a0304c470608fffb5d9); 12 February 2015).
#'
#' As per their GPL-2 licence that demands documentation of code changes, the changes made based on the source code were:
#' 1. Rewritten code to remove the dependency on packages `plyr`, `scales` and `grid`
@ -324,14 +325,18 @@ pca_calculations <- function(pca_model,
sigma <- var(cbind(x$xvar, x$yvar))
mu <- c(mean(x$xvar), mean(x$yvar))
ed <- sqrt(qchisq(ellipse_prob, df = 2))
data.frame(sweep(circle %*% chol(sigma) * ed, 2, mu, FUN = "+"),
el <- data.frame(sweep(circle %*% chol(sigma) * ed, 2, mu, FUN = "+"),
groups = x$groups[1])
names(el)[1:2] <- c("xvar", "yvar")
el
}))
names(ell)[1:2] <- c("xvar", "yvar")
if (NROW(ell) == 0) {
ell <- NULL
}
} else {
ell <- NULL
}
list(nobs.factor = nobs.factor,
d = d,
u = u,

@ -31,6 +31,7 @@
#' The result of the [pca()] function is a [`prcomp`] object, with an additional attribute `non_numeric_cols` which is a vector with the column names of all columns that do not contain numeric values. These are probably the groups and labels, and will be used by [ggplot_pca()].
#' @rdname pca
#' @exportMethod prcomp.data.frame
#' @importFrom stats prcomp
#' @export
#' @examples
#' # `example_isolates` is a dataset available in the AMR package.

@ -78,7 +78,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="https://msberends.gitlab.io/AMR/index.html">AMR (for R)</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.0.1.9000</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.0.1.9001</span>
</span>
</div>

@ -78,7 +78,7 @@
</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">1.0.1.9000</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.0.1.9001</span>
</span>
</div>

@ -78,7 +78,7 @@
</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">1.0.1.9000</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.0.1.9001</span>
</span>
</div>

@ -78,7 +78,7 @@
</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">1.0.1.9000</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.0.1.9001</span>
</span>
</div>

@ -43,7 +43,7 @@
</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">1.0.1.9000</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.0.1.9001</span>
</span>
</div>

@ -78,7 +78,7 @@
</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">1.0.1.9000</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.0.1.9001</span>
</span>
</div>
@ -226,9 +226,9 @@
</div>
<div id="amr-1019000" class="section level1">
<div id="amr-1019001" class="section level1">
<h1 class="page-header">
<a href="#amr-1019000" class="anchor"></a>AMR 1.0.1.9000<small> Unreleased </small>
<a href="#amr-1019001" class="anchor"></a>AMR 1.0.1.9001<small> Unreleased </small>
</h1>
<div id="new" class="section level3">
<h3 class="hasAnchor">
@ -1489,7 +1489,7 @@
<div id="tocnav">
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#amr-1019000">1.0.1.9000</a></li>
<li><a href="#amr-1019001">1.0.1.9001</a></li>
<li><a href="#amr-101">1.0.1</a></li>
<li><a href="#amr-100">1.0.0</a></li>
<li><a href="#amr-090">0.9.0</a></li>

@ -79,7 +79,7 @@
</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">1.0.1.9000</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.0.1.9001</span>
</span>
</div>
@ -117,9 +117,9 @@
</li>
<li>
<a href="../articles/PCA.html">
<span class="fa fa-compress-alt"></span>
<span class="fa fa-compress"></span>
Conduct Principal Component Analysis for AMR
Conduct principal component analysis for AMR
</a>
</li>
<li>
@ -307,6 +307,10 @@
<th>ellipse_alpha</th>
<td><p>the alpha (transparency) of the ellipse line</p></td>
</tr>
<tr>
<th>points_size</th>
<td><p>the size of the points</p></td>
</tr>
<tr>
<th>points_alpha</th>
<td><p>the alpha (transparency) of the points</p></td>

@ -78,7 +78,7 @@
</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">1.0.1.9000</span>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Latest development version">1.0.1.9001</span>
</span>
</div>

@ -4,7 +4,7 @@
\alias{ggplot_pca}
\title{PCA biplot with \code{ggplot2}}
\source{
The \code{\link[=ggplot_pca]{ggplot_pca()}} function is based on the \code{\link[=ggbiplot]{ggbiplot()}} function from the \code{ggbiplot} package by Vince Vu, as found on GitHub: \url{https://github.com/vqv/ggbiplot} (retrieved: 2 March 2020, their latest commit: \href{https://github.com/vqv/ggbiplot/commit/7325e880485bea4c07465a0304c470608fffb5d9}{\code{7325e88}}; 12 February 2015).
The \code{\link[=ggplot_pca]{ggplot_pca()}} function is based on the \code{ggbiplot()} function from the \code{ggbiplot} package by Vince Vu, as found on GitHub: \url{https://github.com/vqv/ggbiplot} (retrieved: 2 March 2020, their latest commit: \href{https://github.com/vqv/ggbiplot/commit/7325e880485bea4c07465a0304c470608fffb5d9}{\code{7325e88}}; 12 February 2015).
As per their GPL-2 licence that demands documentation of code changes, the changes made based on the source code were:
\enumerate{
@ -71,6 +71,8 @@ ggplot_pca(
\item{ellipse_alpha}{the alpha (transparency) of the ellipse line}
\item{points_size}{the size of the points}
\item{points_alpha}{the alpha (transparency) of the points}
\item{arrows}{a logical to indicate whether arrows should be drawn}

@ -0,0 +1,37 @@
# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Analysis #
# #
# SOURCE #
# https://gitlab.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.gitlab.io/AMR. #
# ==================================================================== #
context("pca.R")
test_that("PCA works", {
library(dplyr)
resistance_data <- example_isolates %>%
filter(mo %in% as.mo(c("E. coli", "K. pneumoniae", "S. aureus"))) %>%
select(mo, AMC, CXM, CTX, TOB, TMP) %>%
group_by(order = mo_order(mo), # group on anything, like order
genus = mo_genus(mo)) %>% # and genus as we do here
summarise_if(is.rsi, resistance, minimum = 0)
expect_s3_class(pca(resistance_data), "prcomp")
expect_s3_class(prcomp(resistance_data), "prcomp")
ggplot_pca(pca(resistance_data), ellipse = TRUE)
})
Loading…
Cancel
Save