I am using vegan library to make some plots, with this code:
raremax <- min(colSums(mydata))
col <- palette()
lty <- c("solid", "dashed", "longdash", "dotdash")
pars <- expand.grid(col = col, lty = lty, stringsAsFactors = FALSE)
out <- with(pars[1:18, ], rarecurve(mydata, step = 100, sample = raremax,
cex =0.6, ylab="OTUs", label=F, col=col, lty=lty, lwd=2))
Then I add a legend using this code:
legend("bottomright", names(mydata), col=pars[1:18,1], lty= pars[1:18,2],
lwd=2, cex=0.5, xjust=1, ncol=2, x.intersp=0.5, y.intersp=0.5, bg="white")
The resulting graph looks like this:
I would like to reduce the space between legend columns, also reducing the size of the legend box, but I can't find a way to do that.
Anyone could provide me some help?
A combination of the legend() parameters "x.intersp" and "text.width" should be helpful.
Decreasing "x.intersp" (default value = 1, for me 0.25 looked good) should move your the legend labels closer to their respective points. Decreasing "text.width" (default value=NULL, for me 0.045 looked good) moves the columns closer together.
Related
Just a minor question. I am trying to make a legend for the following plot.
# fitting the linear model
iris_lm = lm(Petal.Length ~ Sepal.Length, data = iris)
summary(iris_lm)
# calculating the confidence interval for the fitted line
preds = predict(iris_lm, newdata = data.frame(Sepal.Length = seq(4,8,0.1)),
interval = "confidence")
# making the initial plot
par(family = "serif")
plot(Petal.Length ~ Sepal.Length, data = iris, col = "darkgrey",
family = "serif", las = 1, xlab = "Sepal Length", ylab = "Pedal Length")
# shading in the confidence interval
polygon(
c(seq(8,4,-0.1), seq(4,8,0.1)), # all of the necessary x values
c(rev(preds[,3]), preds[,2]), # all of the necessary y values
col = rgb(0.2745098, 0.5098039, 0.7058824, 0.4), # the color of the interval
border = NA # turning off the border
)
# adding the regression line
abline(iris_lm, col = "SteelBlue")
# adding a legend
legend("bottomright", legend = c("Fitted Values", "Confidence Interval"),
lty = c(1,0))
Here's the output so far:
My goal is to put a box in the legend next to the "Confidence Interval" tab, and color it in the same shade that it is in the picture. Naturally, I thought to use the pch parameter. However, when I re-run my code with the additional legend option pch = c(NA, 25), I get the following:
It is not super noticeable, but if you look closely at the padding on the left margin of the legend, it actually has decreased, and the edge of the border is now closer to the line than I would like. Is there any way to work around this?
That's a curious behavior in legend(). I'm sure someone will suggest a ggplot2 alternative. However, legend() does offer a solution. This solution calls the function without plotting anything to capture the dimensions of the desired rectangle. The legend is then plotted with the elements you really want but no enclosing box (bty = "n"). The desired rectangle is added explicitly. I assume you mean pch = 22 to get the filled box symbol. I added pt.cex = 2 to make it a bit larger.
# Capture the confidence interval color, reusable variables
myCol <- rgb(0.2745098, 0.5098039, 0.7058824, 0.4)
legText <- c("Fitted Values", "Confidence Interval")
# Picking it up from 'adding a legend'
ans <- legend("bottomright", lty = c(1,0), legend = legText, plot = F)
r <- ans$rect
legend("bottomright", lty = c(1,0), legend = legText, pch = c(NA,22),
pt.bg = myCol, col = c(1, 0), pt.cex = 2, bty = "n")
# Draw the desired box
rect(r$left, r$top - r$h, r$left + r$w, r$top)
By the way, I don't think this will work without further tweaking if you place the legend on the left side.
I want to make a legend on my graph, which is generated by plot() function. The original legend() function will generate a list which has only 1 column. How can I make a legend which has 2 columns?
I could not find a way to do that within a single call to legend for standard plots.
Here's an option, drawing two separate legends: one with lines and points, one with labels. x.intersp can be used to tweak distance between labels and lines.
plot(cumsum(runif(n = 100)))
# draw legend with lines and point but without labels and box. x.intersp controls horizontal distance between lines
L = legend(x = 'bottom', legend = rep(NA,4), col=1:2, lty=c(1,1,2,2), ncol=2, bty='n', x.intersp=0.5, pch=c(1,2,1,2), inset=0.02)
# use position data of previous legend to draw legend with invisble lines and points but with labels and box. x.intersp controls distance between lines and labels
legend(x = L$rect$left, y = L$rect$top, legend = c('Group A', 'Group B'), col=rep(NA,2), lty=c(1,1), ncol=1, x.intersp = 3, bg = NA)
Check this:
library(lattice)
myPCH <- 15:17
Data <- rnorm(50)
Index <- seq(length(Data))
xyplot(Data ~ Index,
pch = myPCH, col=1:2,
key = list(space = "right", adj=1,
text = list(c("a", "b", "c"), cex=1.5),
points = list(pch = myPCH),
points = list(pch = myPCH,col=2)))
It looks like Victorp answered this in the comments of the original post. The ncol argument in the legend function works for me:
legend(locator(1), legend=c("name1","name2", "name3", "name4"), lty=2, col=c("black", "blue", "dark green", "orange"), ncol=2)
enter image description here
I have multiple time series data plots and I need an horizontal line in each plot but with different horizontal values (es. 1st plot: h=50, 2nd plot: h=48...).
I tried abline(h=50... and I get the horizontal line in each plot.
I tried abline(h=c(50,48... and I get multilple horizontal lines in each plot.
I can't figure out how to get the plot.zoo index in order to plot h=50 in the 1st plot, h=48 in the 2nd plot and so on.
library(xts)
data(sample_matrix)
x <- as.xts(sample_matrix)
# plot with single line
my.panel <- function(x, ...) {
lines(x, ...)
abline(h=50, col = "red", lty="solid", lwd=1.5 )
}
plot.zoo(x, main="title",
plot.type="multiple", type="o", lwd=1.5, col="blue",
panel=my.panel)
# plot multiple lines in all plots
my.panel <- function(x, ...) {
lines(x, ...)
abline(h=c(50,50,48,50), col = "red", lty="solid", lwd=1.5 )}
plot.zoo(x, main="title",
plot.type="multiple", type="o", lwd=1.5, col="blue",
panel=my.panel)
To customize single panels in a multipanel plot is not thoroughly described in the actual ?plot.zoo text. In the 'Details' section you find:
"In the case of a custom panel the panel can reference parent.frame$panel.number in order to determine which frame the panel is being called from. See examples.". And there are quite a few examples. Using them as template, I found that this could be a way to call separate panels, and draw a separate hline in each.
Update. Thanks to #G. Grothendieck for an edit that made the code much cleaner!
# create values for hline, one for each panel
hlines <- c(50, 50, 48, 50)
# panel function that loops over panels
my.panel <- function(x, ...) {
lines(x, ...)
panel.number <- parent.frame()$panel.number
abline(h = hlines[panel.number], col = "red", lty = "solid", lwd = 1.5)
}
plot.zoo(x, main = "title", type = "o", lwd = 1.5, col = "blue", panel = my.panel)
I am trying to come up with a solution that doesn't involve using other packages such as ggplot. While plotting multiple lines is pretty straightforward, I haven't figured out a way to apply different values of an argument - e.g., different colors - to different lines. The code below (with the resulting plot) was my attempt, which obviously didn't do what I would like it to do. I also don't want to use a loop because I am trying to make my script as simple as possible.
df = cbind(sort(rnorm(10)), sort(rnorm(10,-2)), sort(rlnorm(10)))
plot(0, xlim = c(1,10), ylim=range(df), type="n")
apply(df, 2, lines, type="b", col = c("red", "blue", "black"))
What I really want is a plot like below:
plot(0, xlim = c(1,10), ylim=range(df), type="n")
color = c("red","blue","black")
for(i in 1:3){
lines(1:10, df[,i], type = "b", col=color[i])
}
Thank you in advance!
Try matplot():
df <- cbind(sort(rnorm(10)), sort(rnorm(10,-2)), sort(rlnorm(10)))
matplot(df, type="b", lty=1, pch=1, col=c("blue", "red", "black"))
Context and Question:
I want to add a legend to a lattice plot in R that shows the density of two groups.
I've changed the default colours to black and gray. However, the legend has not updated the colours.
How can I get the lattice plot to use my updated colours in the legend?
How can I control the position of the legend (I'd like to be able to place it inside the plot area)?
Working example:
set.seed(4444)
x1 <- rep("Group A", 50)
x2 <- rep("Group B", 50)
y1 <- rnorm(50, 0, 2)
y2 <- rnorm(50, 1, 2)
dtf <- data.frame(x=c(x1, x2), y =c(y1, y2))
print(densityplot(~y, groups=x, data=dtf,
pch=".",
cex=2,
col=c("black", "gray"),
auto.key=TRUE,
xlab="Y"))
The legend color is a well-known annoyance in lattice. It looks like it is difficult to correct, because Deepayan recommends simpleTheme as a solution. For positioning, see Josh's answer.
print(densityplot(~y, groups=x, data=dtf,
pch=".",
cex=2,
par.settings=simpleTheme(col=c("gray","black")),
auto.key=TRUE,
xlab="Y"))
There might be a more elegant solution, but this works well enough. Notice that the corner= argument can be used to place the legend anywhere inside the plot.
densityplot(~y, groups = x, data = dtf,
pch = ".",
cex = 2,
col = c("black", "gray"),
par.settings = list(superpose.line = list(col=c("black", "grey"))),
auto.key = list(corner = c(0.95, 0.95)),
xlab = "Y")