ggplot2 (version 0.9.1)

opts: Set options/theme elements for a single plot

Description

Use this function if you want to modify a few theme settings for a single plot.

Usage

opts(...)

Arguments

...

a list of element name, element pairings that modify the existing theme.

Theme elements

The individual theme elements are:

ll{ axis.line line along axis axis.title.x x axis label axis.title.y y axis label axis.ticks axis tick marks axis.ticks.length tick mark length axis.ticks.margin tick mark margin spacing axis.text.x horizontal tick labels axis.text.y vertical tick labels legend.background background of legend legend.margin extra space added around legend (both width or height depending on orientation of legend) legend.key background underneath legend keys legend.key.size key background size legend.key.height key background height legend.key.width key background width legend.text legend labels legend.text.align alignment of legend labels legend.title legend name legend.title.align alignment of legend title legend.position A string or numeric vector specifying the position of guides (legends). Possible values are: "left", "right", "bottom", "top", and two-element numeric vector. legend.justification alignment of legend legend.direction horizontal or vertical legend.box A string specifying the direction of multiple guides. Possible string values are: "horizontal" and "vertical". panel.background background of panel panel.border border around panel panel.margin margin around facet panels panel.grid.major major grid lines panel.grid.minor minor grid lines plot.background background of the entire plot plot.title plot title plot.margin plot margins strip.background background of facet labels strip.text.x text for horizontal strips strip.text.y text for vertical strips }

Examples

p <- qplot(mpg, wt, data = mtcars)
p
p + opts(panel_background = theme_rect(colour = "pink"))
p + theme_bw()

# Scatter plot of gas mileage by vehicle weight
p <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_point()
# Calculate slope and intercept of line of best fit
coef(lm(mpg ~ wt, data = mtcars))
p + geom_abline(intercept = 37, slope = -5)
# Calculate correlation coefficient
with(mtcars, cor(wt, mpg, use = "everything", method = "pearson"))
#annotate the plot
p + geom_abline(intercept = 37, slope = -5) +
geom_text(data = data.frame(), aes(4.5, 30, label = "Pearson-R = -.87"))

# Change the axis labels
# Original plot
p
p + xlab("Vehicle Weight") + ylab("Miles per Gallon")
# Or
p + labs(x = "Vehicle Weight", y = "Miles per Gallon")

# Add a title to the plot
p + opts(title = "Vehicle Weight-Gas Mileage Relationship")
# Change title appearance
p <- p + opts(title = "Vehicle Weight-Gas Mileage Relationship")
p + opts(plot.title = theme_text(size = 20))
p + opts(plot.title = theme_text(size = 20, colour = "Blue"))

# Changing plot look with themes
DF <- data.frame(x = rnorm(400))
m <- ggplot(DF, aes(x = x)) + geom_histogram()
#default is theme_grey()
m
# Compare with
m + theme_bw()

# Manipulate Axis Attributes
library(grid) # for unit
m + opts(axis.line = theme_segment())
m + opts(axis.line = theme_segment(colour = "red", linetype = "dotted"))
m + opts(axis.text.x = theme_text(colour = "blue"))
m + opts(axis.text.y = theme_blank())
m + opts(axis.ticks = theme_segment(size = 2))
m + opts(axis.title.y = theme_text(size = 20, angle = 90))
m + opts(axis.title.x = theme_blank())
m + opts(axis.ticks.length = unit(.85, "cm"))

# Legend Attributes
z <- ggplot(mtcars, aes(wt, mpg, colour = factor(cyl))) + geom_point()
z
z + opts(legend.position = "none")
z + opts(legend.position = "bottom")
# Or use relative coordinates between 0 and 1
z + opts(legend.position = c(.5, .5))
z + opts(legend.background = theme_rect())
# Legend margin controls extra space around outside of legend:
z + opts(legend.background = theme_rect(), legend.margin = unit(1, "cm"))
z + opts(legend.background = theme_rect(), legend.margin = unit(0, "cm"))
# Or to just the keys
z + opts(legend.key = theme_rect())
z + opts(legend.key = theme_rect(fill = "yellow"))
z + opts(legend.key.size = unit(2.5, "cm"))
z + opts(legend.text = theme_text(size = 20, colour = "red", angle = 45))
z + opts(legend.title = theme_text(face = "italic"))

# To change the title of the legend use the name argument
# in one of the scale options
z + scale_colour_brewer(name = "My Legend")
z + scale_colour_grey(name = "Number of \nCylinders")

# Panel and Plot Attributes
z + opts(panel.background = theme_rect())
z + opts(panel.background = theme_rect(fill = "black"))
z + opts(panel.border = theme_rect(linetype = "dashed"))
z + opts(panel.grid.major = theme_line(colour = "blue"))
z + opts(panel.grid.minor = theme_line(colour = "red", linetype = "dotted"))
z + opts(panel.grid.major = theme_line(size = 2))
z + opts(plot.background = theme_rect())
z + opts(plot.background = theme_rect(fill = "grey"))

# Faceting Attributes
set.seed(4940)
dsmall <- diamonds[sample(nrow(diamonds), 1000), ]
k <- ggplot(dsmall, aes(carat, ..density..)) +  geom_histogram(binwidth = 0.2) +
facet_grid(. ~ cut)
k + opts(strip.background = theme_rect(colour = "purple", fill = "pink", size = 3, linetype = "dashed"))
k + opts(strip.text.x = theme_text(colour = "red", angle = 45, size = 10, hjust = 0.5, vjust = 0.5))
k + opts(panel.margin = unit(5, "lines"))
k + opts(panel.margin = unit(0, "lines"))