This function creates a visualization of the results of the PCA applied on a sample of QTS and returns the corresponding ggplot2::ggplot object which enable further customization of the plot.
An object of class
prcomp_qtsas produced by the
A string specifying what kind of visualization the user wants to perform. Choices are words starting with
PCand ending with a PC number (in which case the mean QTS is displayed along with its perturbations due to the required PC) or
scores(in which case individuals are projected on the required plane). Defaults to
what = "PC?", the user can specify whether to plot the QTS in the tangent space or in the original space by providing a boolean argument
original_spacewhich defaults to
what = "scores", the user can specify the plane onto which the individuals will be projected by providing a length-2 integer vector argument
planewhich defaults to
A ggplot2::ggplot object.
df <- as_qts_sample(vespa64$igp[1:16]) res_pca <- prcomp(df) #> ℹ The maximum number of principal component is 15. # Plot the data points in a PC plane # And color points according to a categorical variable p <- ggplot2::autoplot(res_pca, what = "scores") #> The `plane` length-2 integer vector argument is not specified. Defaulting to #> 1:2. p + ggplot2::geom_point(ggplot2::aes(color = vespa64$V[1:16]))