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### R BASICS WORKSHOP                                                        ###
### PRESENTATION 8: GRAPHICS                                                 ###
###                                                                          ###
### Center for Conservation and Sustainable Development                      ###
### Missouri Botanical Garden                                                ###
### Website: rbasicsworkshop.weebly.com                                      ###
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### INTRODUCTION ###############################################################

# R offers an incredible variety of options for building graphics. Type this
# into the console to see a few available options:
demo (graphics)


# A better version of the volcano figure (from the help of function *image*):
x <- 10 * (1:nrow(volcano))
y <- 10 * (1:ncol(volcano))
image(x, y, volcano, col = terrain.colors(100), axes = FALSE)
contour(x, y, volcano, levels = seq(90, 200, b = 5), add = TRUE, col = "peru")
axis(1, t = seq (100, 800, b = 100))
axis(2, t = seq (100, 600, b = 100))
box()
title(main = "Maunga Whau Volcano", font.main = 4)


# This part of the workshop is divided into the following sections:

# A. High level functions
# B. Low level functions
# C. Graphic parameters modified by the function *par*
# D. Opening multiple windows and dividing a window into panels
# E. Saving graphics as files



### A. HIGH LEVEL FUNCTIONS ####################################################

# high level graphical functions are used to create figures, while low level
# functions are used to modify or add items to figures

# Here we will look at some examples, but for a slightly longer list of functions
# consult pages 40 and 41 of "R for Beginners" (available at the website)

data(iris)
str(iris)


## *plot* is a generic function used to make many types of graphs.
# A generic function works differently depending on the type of arguments it is
# given. However, this function is most frequently used to create scatter-plots

plot(iris$Sepal.Length ~ iris$Sepal.Width)

plot(iris$Petal.Length ~ iris$Petal.Width)


# There are many arguments that can be used in the function *plot* and
# other functions to modify figures. Some of the most common are:

# type: type of graph

# pch: shape of the symbol
# col: color of the symbol
# bg: background color of the symbol

# main: main title
# xlab and ylab: titles of the axes
# cex.lab: font size of axis titles
# cex.axis: size of text on the axes

# las: controls the orientation of the text on the y axis
# bty: change the type of box around points


plot (iris$Petal.Length ~ iris$Petal.Width, cex = 3)

plot (iris$Petal.Length ~ iris$Petal.Width, cex = 2, pch = 21, col = "black", bg = "gray")

plot (iris$Petal.Length ~ iris$Petal.Width, cex = 3, pch = 21, col = "black",
  bg = "gray", main = "Plot of Petal Petals vs. Width Length", xlab = "Petal Width",
  ylab = "Petal Length", cex.lab = 1.5, cex.axis = 1.5, bty = "l", las = 1)



## These are other common graphics functions ##

# *boxplot* makes boxplots
boxplot(iris$Sepal.Length)

boxplot(iris$Sepal.Length ~ iris$Species)

boxplot(iris$Sepal.Length ~ iris$Species, col = "gold", horizontal = TRUE, las = 1)

boxplot (iris$Sepal.Length ~ iris$Species, names = expression(italic("Iris setosa"),
  italic("Iris versicolor"), italic("Iris virginica")),
  xlab = "Sepal length (cm)", col = "gold", cex.lab = 1.5, cex.axis = 1.5)

? boxplot


# *hist* makes histograms
hist(iris$Sepal.Length)

range(iris$Sepal.Length)

hist(iris$Sepal.Length, breaks = seq(min(iris$Sepal.Length),
  max(iris$Sepal.Length), length.out = 30), col = "darkolivegreen",
  border = "white")

hist(iris$Sepal.Length, breaks = seq(min(iris$Sepal.Length),
  max(iris$Sepal.Length), length.out = 30), col = "darkolivegreen",
  border = "white", xlab = "Sepal Length", freq = FALSE)


# *pie* o *piechart* creates piecharts
table(iris$Species)

pie(x = table(iris$Species))


# *barplot* makes bar charts
barplot(height = table(iris$Species))

rand <- sample(letters, 300, replace = TRUE)

table(rand)

barplot(table(rand))



### B. LOW LEVEL FUNCTIONS #####################################################

# Here, we will use the functions *points*, *lines* and *legend*. To see
# a more extensive list of low-level graphics functions see "R for Beginners"

# *type = "n"* is often used to create an empty graph
plot(iris$Petal.Length ~ iris$Petal.Width, type = "n")

plot (iris$Petal.Length ~ iris$Petal.Width, xlab = "Petal Width",
  ylab = "Petal Length", cex.lab = 1.5, cex.axis = 1.5, bty = "l", las = 1,
  type = "n")

# *points* adds points to a chart created by *plot*
points (iris$Petal.Length[iris$Species == "setosa"] ~
  iris$ Petal.Width[iris$Species == "setosa"])

points(iris$Petal.Length[iris$Species == "setosa"] ~
  iris$Petal.Width[iris$Species == "setosa"], pch = 19, cex = 1.5, col = "lightblue")

points(iris$Petal.Length[iris$Species == "versicolor"] ~
  iris$Petal.Width[iris$Species == "versicolor"], pch = 19, cex = 1.5,
  col = "darkorange")

points(iris$Petal.Length[iris$Species == "virginica"] ~
  iris$Petal.Width[iris$Species == "virginica"], pch = 19, cex = 1.5,
  col = "grey50")


# *lines* adds lines to a graph
lines(x = c(0, 2.5), y = rep(mean(iris$Petal.Length[iris$Species == "setosa"]), times = 2),
  col = "royalblue4", lwd = 3)

lines(x = c(0, 2.5), y = rep(mean(iris$Petal.Length[iris$Species == "versicolor"]), 2),
  col = "orange", lwd = 3)

lines(x = c(0, 2.5), y = rep(mean(iris$Petal.Length[iris$Species == "virginica"]), 2),
  col = "black", lwd = 3)


# *legend* adds a legend
legend(x = "topleft", legend = c(expression(italic("Iris setosa")),
  expression(italic("Iris versicolor")), expression(italic("Iris virginica"))),
  pch = 19, col = c("lightblue", "darkorange", "grey50"), cex = 1.3)


legend(x = 1.3, y = 2.3, legend = c(expression(italic("Iris setosa")),
  expression(italic("Iris versicolor")), expression(italic("Iris virginica"))),
  pch = 19, col = c("lightblue", "darkorange", "grey50"), cex = 1.3)

legend(x = 10.3, y = 20.3, legend = c(expression(italic("Iris setosa")),
  expression(italic("Iris versicolor")), expression(italic("Iris virginica"))),
  pch = 19, col = c("lightblue", "darkorange", "grey50"), cex = 1.3)



### C. GRAPHICAL PARAMETERS  MODIFIED BY FUNCTION *par* ####################

# To have greater control over graphics, it is necessary to know the function
# *par* and its associated arguments.

# Many features of graphics can be specified using the function *par* or inside
# functions like *plot* (e.g. color). Others can be specified only using *par*
# (e.g. size of the margin). The help for function *par* has a lot of useful
# information:
help(par)

# First version:
hist(iris$Sepal.Length, breaks = seq(0, 8, 0.5), col = "gray70", border = "gray40",
  xlab = "", ylab = "", main = "", axes = FALSE, ylim = c(0,40))

hist(iris$Petal.Length, breaks = seq(0, 8, 0.5), density = 10, add = TRUE)

axis(side = 1, t = seq(0, 8, 1), cex.axis = 2, lwd = 2, las = 1)
axis(side = 2, t = seq(0, 40, 5), cex.axis = 1.5, cex.axis = 2, lwd = 2, las = 1)

mtext(text = "Length (cm)", side = 1, line = 3, cex = 2)
mtext(text = "Specimens", side = 2, line = 3, cex = 2)

legend(x = "topright", legend = c("Sepals", "Petals"), fill = c("gray70", "black"),
  density = c(NA, 30), pt.cex = 2, border = c("gray40", "black"), cex = 2)


# In this first version, there is an obvious problem with the title on the
# y axis. To fix this, we can use the argument *mar* in function *par*.

# Second version:
par(mar = c(5, 5, 4, 2), family = "mono") # This is the only line that is different

hist(iris$Sepal.Length, breaks = seq(0, 8, 0.5), col = "gray70", border = "gray40",
  xlab = "", ylab = "", main = "", axes = FALSE, ylim = c(0, 40))

hist(iris$Petal.Length, breaks = seq(0, 8, 0.5), density = 30, add = TRUE)

axis(side = 1, t = seq(0, 8, 1), cex.axis = 2, lwd = 2, las = 1)
axis(side = 2, t = seq(0, 40, 5), cex.axis = 1.5, cex.axis = 2, lwd = 2, las = 1)

mtext(text = "Length (cm)", side = 1, line = 3, cex = 5)
mtext(text = "Specimens", side = 2, line = 3.5, cex = 0.5)

legend(x = "topright", legend = c("Sepals", "Petals"), fill = c("gray70", "black"),
  density = c(NA, 30), pt.cex = 2, border = c("gray40", "black"), cex = 1.5, bty = "n")




### D. OPENING MULTIPLE WINDOWS AND DIVIDING A WINDOW INTO PANELS ##############

## 1. How to open multiple windows ##

# If there is no active window (graphical device), a high level graphical
# function will create a one.
plot(iris$Petal.Length ~ iris$Petal.Width, pch = 19)

# To open more than one viewport can use the *dev.new*
dev.new()
plot(iris$Sepal.Length, iris$Sepal.Width, pch = 19, col = "red")

## Consult the help for *dev.new* to find out about related functions


## 2. Create a window with multiple panels *par* ##

# The argument *mfrow* in *par* needs 2 numbers: the number of rows and columns
# in the used to divide the window:
par(mfrow = c (1,2))
  plot(iris$Petal.Length ~ iris$Petal.Width, pch = 19)
  plot(iris$Sepal.Length, iris$Sepal.Width, pch = 19, col = "red")

par(mfrow = c (2,1))
  plot (iris$Petal.Length ~ iris$Petal.Width, pch = 19)
  plot(iris$Sepal.Length, iris$Sepal.Width, pch = 19, col = "red")


## 3. Create a window with multiple panels *layout* ##

# *layout* is a function that can also split a window into panels, but the
# panels do not have to be the same size or organized in rows and columns

# The main argument for *layout* is a matrix defining how the window will be
# divided:

div <- matrix(1:3, nrow = 3, ncol = 1)
div

layout(mat = div)
layout.show(3)

plot (iris$Sepal.Length, iris$Sepal.Width, pch = 19, cex.lab = 1.5, cex.axis = 1.5,
  xlab = "Sepal length (cm)", ylab = "Sepal width (cm)")
plot (iris$Sepal.Length, iris$Petal.Length, pch = 19, cex.lab = 1.5, cex.axis = 1.5,
  xlab = "Sepal length (cm)", ylab = "Petal length (cm)")
plot (iris$Sepal.Length, iris$Petal.Width, pch = 19, cex.lab = 1.5, cex.axis = 1.5,
  xlab = "Sepal length (cm)", ylab = "Petal width (cm)")


div <- matrix(1:4, nrow = 2, ncol = 2, byrow = TRUE)
div

layout(mat = div)
layout.show(4)

plot (iris$Sepal.Length, iris$Sepal.Width, pch = 19, cex.lab = 1.5, cex.axis = 1.5,
  xlab = "Sepal length (cm)", ylab = "Sepal width (cm)")
plot (iris$Sepal.Length, iris$Petal.Length, pch = 19, cex.lab = 1.5, cex.axis = 1.5,
  xlab = "Sepal length (cm)", ylab = "Petal length (cm)")
plot (iris$Sepal.Length, iris$Petal.Width, pch = 19, cex.lab = 1.5, cex.axis = 1.5,
  xlab = "Sepal length (cm)", ylab = "Petal width (cm)")

plot(iris$Sepal.Length, iris$Petal.Width, pch = 19, type = "n", axes = FALSE,
  bty = "n", xlab = "", ylab = "")

mtext("Sepal length", line = -3, cex = 1.5)
mtext("versus", line = -5, cex = 1.5)
mtext("other variables", line = -7, cex = 1.5)
mtext("in Anderson's Iris", line = -9, cex = 1.5)


# This is a simple graph with two panels
div <- matrix(1:2, nrow = 1, ncol = 2)
layout(mat = div)
layout.show(2)

plot(iris$Sepal.Length, iris$Sepal.Width)
plot(iris$Sepal.Length, iris$Petal.Length)


# What if we want to make one panel to be "inside" the other
div <- matrix(c(1,1,2,1), nrow = 2, ncol = 2)
div

layout(mat = div)
layout.show(2)

plot(iris$Sepal.Length, iris$Sepal.Width)
plot(iris$Sepal.Length, iris$Petal.Length)


# In addition, the arguments * * heights and widths * * We can resize
# The cells in columns or rows
layout(mat = div, widths = c(2, 1), heights = c(1, 2))
layout.show(2)

plot(iris$Sepal.Length, iris$Sepal.Width)
plot(iris$Sepal.Length, iris$Petal.Length)




### E. SAVE GRAPHICS AS FILES ##################################################

# Just like it is possible to send a graphic to an open window, it is possible
# to send a graphic to an open file (both are types of "graphical devices").

# While *new.dev()* opens a window, there are several functions that open
# various types of iles: *jpeg*, *png*, *tiff*, *bmp*, *pdf*, *postscript*


# Example using *png*
help(png)


getwd() # see what the working directory

# Use *setwd* or the menus in R to choose an appropriate working directory


## First version ##
# Step 1. Open the file:
png(filename = "SepalLenght_vs_SepalWidth.png")

# Step 2. Create a figure into the file
plot(iris$Petal.Length ~ iris$Petal.Width, cex = 3, pch = 21, col = "black",
  bg = "gray", main = "Plot of Petal Petals vs. Length Width", xlab = "Petal Width",
  ylab = "Petal Length", cex.lab = 1.5, cex.axis = 1.5, bty = "l", las = 1)

# Step 3. Close the file
dev.off()



## Second Version ##
# In this version we have the figure much larger and better quality
png(filename = "SepalLenght_vs_SepalWidth_2.png", width = 480 * 13, height = 480 * 10,
  pointsize = 12 * 1.5, res = 600)

plot(iris$Petal.Length ~ iris$Petal.Width, cex = 3, pch = 21, col = "black",
  bg = "gray", main = "Plot of Petal Petals vs. Width Length", xlab = "Petal Width",
  ylab = "Petal Length", cex.lab = 1.5, cex.axis = 1.5, bty = "l", las = 1)

dev.off()