# Multiple plot function # # ggplot objects can be passed in ..., or to plotlist (as a list of ggplot objects) # - cols: Number of columns in layout # - layout: A matrix specifying the layout. If present, 'cols' is ignored. # # If the layout is something like matrix(c(1,2,3,3), nrow=2, byrow=TRUE), # then plot 1 will go in the upper left, 2 will go in the upper right, and # 3 will go all the way across the bottom. # multiplot <- function(..., plotlist=NULL, file, cols=1, layout=NULL) { library(grid) # Make a list from the ... arguments and plotlist plots <- c(list(...), plotlist) numPlots = length(plots) # If layout is NULL, then use 'cols' to determine layout if (is.null(layout)) { # Make the panel # ncol: Number of columns of plots # nrow: Number of rows needed, calculated from # of cols layout <- matrix(seq(1, cols * ceiling(numPlots/cols)), ncol = cols, nrow = ceiling(numPlots/cols)) } if (numPlots==1) { print(plots[[1]]) } else { # Set up the page grid.newpage() pushViewport(viewport(layout = grid.layout(nrow(layout), ncol(layout)))) # Make each plot, in the correct location for (i in 1:numPlots) { # Get the i,j matrix positions of the regions that contain this subplot matchidx <- as.data.frame(which(layout == i, arr.ind = TRUE)) print(plots[[i]], vp = viewport(layout.pos.row = matchidx$row, layout.pos.col = matchidx$col)) } } } # From https://sejohnston.com/2012/08/09/a-quick-and-easy-function-to-plot-lm-results-in-r/ ggplotRegression <- function (fit) { require(ggplot2) ggplot(fit$model, aes_string(x = names(fit$model)[2], y = names(fit$model)[1])) + geom_point() + geom_smooth(method = "lm", col = "red") + labs(title = paste("Adj R2 = ",signif(summary(fit)$adj.r.squared, 5), "Intercept =",signif(fit$coef[[1]],5 ), " Slope =",signif(fit$coef[[2]], 5), " P =",signif(summary(fit)$coef[2,4], 5))) + theme(plot.title = element_text(size=12)) }