ggmatplot: ggplot Columns of Matrices

In luca-scr/smef: Statistical Methods for Economy and Finance

Description

ggplot2 version of matplot base graphic

Usage

ggmatplot(x, y, type = "p", pch, lty, col, legend = FALSE, add = FALSE, ...)

Arguments

x	vector for the x-axis variable
y	a matrix or a data.frame for the y-axis variables
type	character string indicating the type of plot for each column of y. Possible values are "p" for points, "l" for lines, "b" for both points and lines
pch	character string or vector of 1-characters or integers for plotting characters
lty	vector of line types
col	vector of colors
legend	boolean specifying if a legend should be added or not
...	additional arguments
plot	boolean specifying if the graph should be added to an existing plot. If TRUE it is added to the last ggplot graph, but a specific ggplot object can also be provided

See Also

matplot

Examples

x <- 0:50/50
sines <- outer(x, 1:4, function(x, y) sin(y*pi*x))
ggmatplot(x, sines)
ggmatplot(x, sines, type = "l")
ggmatplot(x, sines, type = "b", lty = 1)


# parallel coordinate plot
x = t(apply(iris[,1:4], 2, function(x) (x-min(x))/(max(x)-min(x))))
ggmatplot(x, type = "l", lty = 1, col = 1) +
  scale_x_continuous(labels = rownames(x))
ggmatplot(x, type = "l", lty = 1, 
          col = as.numeric(iris$Species)+1) +
          scale_x_continuous(labels = rownames(x))

# add to an existing ggplot graph
mod1 = lm(Ozone ~ Temp, data = airquality)
mod2 = lm(Ozone ~ poly(Temp,2), data = airquality)
mod3 = lm(Ozone ~ poly(Temp,3), data = airquality)
df = data.frame(Temp = seq(56, 97, by = 0.1))
df = cbind(df, pred1 = predict(mod1, df),
               pred2 = predict(mod2, df),
               pred3 = predict(mod3, df))
ggplot(data = airquality, aes(x = Temp, y = Ozone)) +
  geom_point()
ggmatplot(df$Temp, df[,-1], type = "l", lty = 1, col = 2:4, 
          add = TRUE, legend = TRUE)

luca-scr/smef documentation built on Feb. 22, 2022, 8:32 p.m.