plot_extensions.R

   1 # Multiple plot function
   2 #
   3 # ggplot objects can be passed in ..., or to plotlist (as a list of ggplot objects)
   4 # - cols:   Number of columns in layout
   5 # - layout: A matrix specifying the layout. If present, 'cols' is ignored.
   6 #
   7 # If the layout is something like matrix(c(1,2,3,3), nrow=2, byrow=TRUE),
   8 # then plot 1 will go in the upper left, 2 will go in the upper right, and
   9 # 3 will go all the way across the bottom.
  10 #
  11 multiplot <- function(..., plotlist=NULL, file, cols=1, layout=NULL) {
  12   library(grid)
  13
  14   # Make a list from the ... arguments and plotlist
  15   plots <- c(list(...), plotlist)
  16
  17   numPlots = length(plots)
  18
  19   # If layout is NULL, then use 'cols' to determine layout
  20   if (is.null(layout)) {
  21     # Make the panel
  22     # ncol: Number of columns of plots
  23     # nrow: Number of rows needed, calculated from # of cols
  24     layout <- matrix(seq(1, cols * ceiling(numPlots/cols)),
  25                     ncol = cols, nrow = ceiling(numPlots/cols))
  26   }
  27
  28  if (numPlots==1) {
  29     print(plots[[1]])
  30
  31   } else {
  32     # Set up the page
  33     grid.newpage()
  34     pushViewport(viewport(layout = grid.layout(nrow(layout), ncol(layout))))
  35
  36     # Make each plot, in the correct location
  37     for (i in 1:numPlots) {
  38       # Get the i,j matrix positions of the regions that contain this subplot
  39       matchidx <- as.data.frame(which(layout == i, arr.ind = TRUE))
  40
  41       print(plots[[i]], vp = viewport(layout.pos.row = matchidx$row,
  42                                       layout.pos.col = matchidx$col))
  43     }
  44   }
  45 }
  46
  47 # From https://sejohnston.com/2012/08/09/a-quick-and-easy-function-to-plot-lm-results-in-r/
  48 ggplotRegression <- function (fit) {
  49
  50 require(ggplot2)
  51
  52 ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) +
  53     geom_point() +
  54     geom_smooth(method = "lm", col = "red") +
  55     labs(title = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 5),
  56                      "Intercept =",signif(fit$coef[[1]],5 ),
  57                      " Slope =",signif(fit$coef[[2]], 5),
  58                      " P =",signif(summary(fit)$coef[2,4], 5))) +
  59     theme(plot.title = element_text(size=12))
  60 }