autoplot.funData: Visualize functional data objects using ggplot

Description

This function allows to plot funData objects based on the ggplot2 package. The function provides a wrapper that rearranges the data in a funData object on a one- or two-dimensional domain and provides a basic ggplot object, which can be customized using all functionalities of the ggplot2 package.

Usage

autoplot.funData(object, obs = seq_len(nObs(object)), geom = "line",
  plotNA = FALSE, ...)
autolayer.funData(object, obs = seq_len(nObs(object)), geom = "line",
  plotNA = FALSE, ...)

Arguments

object

A funData object on a one- or two-dimensional domain.

obs

A vector of numerics giving the observations to plot. Defaults to all observations in object. For two-dimensional functions (images) obs must have length 1.

geom

A character string describing the geometric object to use. Defaults to "line". See ggplot2 for details.

plotNA

Logical. If TRUE, missing values are interpolated using the approxNA function (only for one-dimensional functions). Defaults to FALSE. See Details.

...

Further parameters passed to geom_line (for one dimensional domains, e.g. alpha, color, fill, linetype, size) or to geom_raster (for two-dimensional domains, e.g. hjust, vjust, interpolate).

Value

A ggplot object that can be customized using all functionalities of the ggplot2 package.

Details

If some observations contain missing values (coded via NA), the functions can be interpolated using the option plotNA = TRUE. This option relies on the na.approx function in package zoo and is currently implemented for one-dimensional functions only in the function approxNA.

Examples

Run this code

# NOT RUN {
# Install / load package ggplot2 before running the examples
library("ggplot2")

# One-dimensional
argvals <- seq(0,2*pi,0.01)
object <- funData(argvals,
                   outer(seq(0.75, 1.25, length.out = 11), sin(argvals)))

g <- autoplot(object) # returns ggplot object
g # plot the object

# add the mean function in red
g + autolayer(meanFunction(object),  col = 2)

# Two-dimensional
X <- array(0, dim = c(2, length(argvals), length(argvals)))
X[1,,] <- outer(argvals, argvals, function(x,y){sin((x-pi)^2 + (y-pi)^2)})
X[2,,] <- outer(argvals, argvals, function(x,y){sin(2*x*pi) * cos(2*y*pi)})
object2D <- funData(list(argvals, argvals), X)

# }
# NOT RUN {
autoplot(object2D, obs = 1)
autoplot(object2D, obs = 2)
# }
# NOT RUN {
autoplot(object2D)
# }
# NOT RUN {
 # must specify obs!

### More examples ###
# }
# NOT RUN {
par(mfrow = c(1,1))

# using plotNA (needs packages zoo and gridExtra)
requireNamespace("zoo", quietly = TRUE)
requireNamespace("gridExtra", quietly = TRUE)
objectMissing <- funData(1:5, rbind(c(1, NA, 5, 4, 3), c(10, 9, NA, NA, 6)))
g1 <- autoplot(objectMissing) # the default
g2 <- autoplot(objectMissing, plotNA = TRUE) # requires zoo

gridExtra::grid.arrange(g1 + ggtitle("plotNA = FALSE (default)"),
                        g2 + ggtitle("plotNA = TRUE")) # requires gridExtra

# Customizing plots (see ggplot2 documentation for more details)
# parameters passed to geom_line are passed via the ... argument
gFancy <- autoplot(object, color = "red", linetype = 2) 
gFancy

# new layers can be added directly to the ggplot object
gFancy + theme_bw() # add new layers to the ggplot object
gFancy + ggtitle("Fancy Plot with Title and Axis Legends") + 
         xlab("The x-Axis") + ylab("The y-Axis")

autoplot(object2D, obs = 1) + ggtitle("Customized 2D plot") + theme_minimal() +
          scale_fill_gradient(high = "green", low = "blue", name = "Legend here")
# }