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(v1.0.1.9001) PCA unit tests

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dr. M.S. (Matthijs) Berends
2020-03-08 09:12:11 +01:00
parent fa0d9c58d9
commit 9fc858f208
15 changed files with 71 additions and 21 deletions
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13
R/ggplot_pca.R
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@ -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,

1
R/pca.R
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@ -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.