Tweaked to have separate script for boilerplate

[ou-jupyter-r-demo.git] / plot_extensions.R

diff --git a/plot_extensions.R b/plot_extensions.R
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+++ b/plot_extensions.R
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+# 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$model)[1])) + 
+    geom_point() +
+    stat_smooth(method = "lm", col = "red") +
+    labs(title = paste("Adj R2 = ",signif(summary(fit)$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))
+}