Visualize Principal Component Analysis

Usage

mgrastPlotPCA(file_in, file_out = "my_pca", num_PCs = 2, produce_fig = FALSE, PC1 = "PC1", PC2 = "PC2", image_out = "my_pca", image_title = image_out, figure_width = 950, figure_height = 950, points_color = "red", figure_res = NA, lab_cex = 1, axis_cex = 1, points_text_cex = 0.8)

Arguments

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (file_in, file_out = "my_pca", num_PCs = 2, produce_fig = FALSE, 
    PC1 = "PC1", PC2 = "PC2", image_out = "my_pca", image_title = image_out, 
    figure_width = 950, figure_height = 950, points_color = "red", 
    figure_res = NA, lab_cex = 1, axis_cex = 1, points_text_cex = 0.8) 
{
    suppressPackageStartupMessages(library(Cairo))
    suppressPackageStartupMessages(library(pcaMethods))
  }