I'm plotting the vertex degree (# of incident edges) of the graph g.
deg <- degree(g, v=V(g), mode = c("in"), loops = TRUE)
histdata <- hist( deg, breaks=1000, plot=FALSE )
plot(histdata$count, log="xy", type="p", col="blue", bg = "blue", pch=20,
xlim=c(1,max(deg)),
ylim=c(1,max(histdata$count)),
ylab="Frequency", xlab="Degree")
This code plots this scatterplot,
which is very close to what I need but has a few issues:
1) the x labels are wrong, as they don't represent the degrees but the histogram breaks.
2) the axis bars are messy. How can I remove the empty ones?
3) how can I plot a regression line? I tried with abline and lm(histdata$mids~histdata$count) but nothing gets plotted.
Thanks for any hint!
UPDATE: this plot is probably plain wrong. See http://www.hpl.hp.com/research/idl/papers/ranking/ranking.html
Related
The goal is to reproduce this Bid-Rent graph in R:
The challenge is to draw the projected circles. So far I got:
The 2D part is created by the R code below with the traditional graphic system in base R:
#Distance
X <- seq(0,7,1)
#Bid Rent Curves: Commercial, Industrial, Residential
com <- -5*X + 10
ind <- -2*X + 7
res <- -0.75*X + 4
graph <- plot(X, com, type="l", col="green", ylim=c(0,10), xlab="", ylab="", axes=FALSE)
lines(X, ind, col="red")
lines(X, res, col="blue")
abline(v=0, h=0)
segments(1,0, 1,5, lty=2)
segments(2.5,0, 2.5,2, lty=2)
title(main="Bid Rent Curves", sub="Alonso Model",
xlab="Distance from CBD", ylab="Rent per m2")
text(2.5,7.5, "Commercial", col="green")
text(3.5,4, "Industrial", col="red")
text(5.5,2, "Residential", col="blue")
(Detail: Why the curves do not respect the ylim = 0 ?)
How make the projection and draw the semi-circles?
It is not exactly a 3D plot. I have looked into plot3D and rgl. I am not sure which packages or strategy to use from here.
I'm taking you at your word that you want circles, so you need to push the plot area into the upper right corner:
outHalfCirc <- function(r,colr) {opar=par(xpd=TRUE, new=TRUE) #plot ouside plot area
polygon(x=seq(r,-r,by=-0.1),
y= -sqrt(r^2 - seq(r,-r,by=-0.1)^2) , # solve r^2 = x^2 +y^2 for y
xlim =c(0,7 ), ylim=c(0,10), col=colr, # need xlim and ylim to match base plot ranges
yaxs="i", yaxt="n", xaxs="i") # yaxis off; x and y axes meet at origin
par(opar)}
Then push plot up and to the right: This will draw a colored half-circles (largest first so they overlap) below the y=0 line.
png() # send to image file; not needed for testing
opar <- par(mar=c(15, 15, 2,2) ) # default units are in widths of text-"line".
# the margins start at lower, then clockwise
# run your code
outHalfCirc(5.5, "blue")
outHalfCirc(2.5, "red")
outHalfCirc(1, "green")
dev.off() # complete image production
par(opar) # different than the 'opar' inside the function
Voila! Although not really circles because the aspect ratio is not 1. That can be fixed (or you could set the xlim and ylim to be equal.
I have 7 different categories per each value in X. I am using barplot to plot these categories. Such graph looks fine in colors printer, but what if I want it to be fine in black & white. You can check the graph below. I want to have different colors texture, so the graph looks good in color and black & white printer.
I used densities = c(10,30,40,50,100,60,80) for density parameter in barplot function. Are there any other ways to do different texture in barplot?
Note: I tried the angle value in barplot. However, it isn't a good solution in that case, since not all bars have high values (i.e height of the bar).
Along the lines of my comment, you might find the following helpful:
# data generation ---------------------------------------------------------
set.seed(1)
mat <- matrix(runif(4*7, min=0, max=10), 7, 4)
rownames(mat) <- 1:7
colnames(mat) <- LETTERS[1:4]
# plotting settings -------------------------------------------------------
ylim <- range(mat)*c(1,1.5)
angle1 <- rep(c(45,45,135), length.out=7)
angle2 <- rep(c(45,135,135), length.out=7)
density1 <- seq(5,35,length.out=7)
density2 <- seq(5,35,length.out=7)
col <- 1 # rainbow(7)
# plot --------------------------------------------------------------------
op <- par(mar=c(3,3,1,1))
barplot(mat, beside=TRUE, ylim=ylim, col=col, angle=angle1, density=density1)
barplot(mat, add=TRUE, beside=TRUE, ylim=ylim, col=col, angle=angle2, density=density2)
legend("top", legend=1:7, ncol=7, fill=TRUE, col=col, angle=angle1, density=density1)
par(bg="transparent")
legend("top", legend=1:7, ncol=7, fill=TRUE, col=col, angle=angle2, density=density2)
par(op)
I want to make a histogram for multiple variables.
I used the following code :
set.seed(2)
dataOne <- runif(10)
dataTwo <- runif(10)
dataThree <- runif(10)
one <- hist(dataOne, plot=FALSE)
two <- hist(dataTwo, plot=FALSE)
three <- hist(dataThree, plot=FALSE)
plot(one, xlab="Beta Values", ylab="Frequency",
labels=TRUE, col="blue", xlim=c(0,1))
plot(two, col='green', add=TRUE)
plot(three, col='red', add=TRUE)
But the problem is that they cover each other, as shown below.
I just want them to be added to each other (showing the bars over each other) i.e. not overlapping/ not covering each other.
How can I do this ?
Try replacing your last three lines by:
plot(One, xlab = "Beta Values", ylab = "Frequency", col = "blue")
points(Two, col = 'green')
points(Three, col = 'red')
The first time you need to call plot. But the next time you call plot it will start a new plot which means you lose the first data. Instead you want to add more data to it either with scatter chart using points, or with a line chart using lines.
It's not quite clear what you are looking for here.
One approach is to place the plots in separate plotting spaces:
par("mfcol"=c(3, 1))
hist(dataOne, col="blue")
hist(dataTwo, col="green")
hist(dataThree, col="red")
par("mfcol"=c(1, 1))
Is this what you're after?
I want to plot a distribution and a single value (with abline) which is very smaller than the minimum value in my distribution, so the abline won't appear in the plot. How can I plot them in the same plot manipulating the x-axis scale or maybe inserting breaks?
data <- rnorm(1000, -3500, 27)
estimate <- -80000
plot(density(data))
abline(v = estimate)
Here's a rough solution, it's not particularly pretty:
library(plotrix)
d <- density(data)
gap.plot(c(-8000,d$x), c(0,d$y), gap=range(c(-7990,-3620)),
gap.axis="x", type="l", xlab="x", ylab="Density",
xtics=c(-8000,seq(-3600,-3300,by=100)))
abline(v=-8000, col="red", lwd=2)
Not exactly clear what is needed but this might be progress:
plot(density(data), xlim=range(c(data, estimate+10) ) )
abline(v = estimate, col='red')
In package:plotrix there are broken axis plotting functions.
I'm generating numerous plots with xlim and ylim values that I'm calculating on a per-plot basis. I want to put my legend outside the plot area (just above the box around the actual plot), but I can't figure out how to get the maximum y-value of the box around my plot area.
Is there a method for even doing this? I can move the legend where I want it by manually changing the legend() x and y values, but this takes a LONG time for the amount of graphs I'm creating.
Thanks!
-JM
Here's a basic example illustrating what I think you're looking for using one of the code examples from ?legend.
#Construct some data and start the plot
x <- 0:64/64
y <- sin(3*pi*x)
plot(x, y, type="l", col="blue")
points(x, y, pch=21, bg="white")
#Grab the plotting region dimensions
rng <- par("usr")
#Call your legend with plot = FALSE to get its dimensions
lg <- legend(rng[1],rng[2], "sin(c x)", pch=21,
pt.bg="white", lty=1, col = "blue",plot = FALSE)
#Once you have the dimensions in lg, use them to adjust
# the legend position
#Note the use of xpd = NA to allow plotting outside plotting region
legend(rng[1],rng[4] + lg$rect$h, "sin(c x)", pch=21,
pt.bg="white", lty=1, col = "blue",plot = TRUE, xpd = NA)
The command par('usr') will return the coordinates of the bounding box, but you can also use the grconvertX and grconvertY functions. A simple example:
plot(1:10)
par(xpd=NA)
legend(par('usr')[1], par('usr')[4], yjust=0, legend='anything', pch=1)
legend( grconvertX(1, from='npc'), grconvertY(1, from='npc'), yjust=0,
xjust=1, legend='something', lty=1)
The oma, omd, and omi arguments of par() control boundaries and margins of plots - they can be queried using par()$omd (etc). and set (if needed) using par(oma=c()) (where the vector can have up to 4 values - see ?par)