I need to put two plots side by side. As such, not a hard exercise, except that:
I want and need to use basic graphics
the plots should be placed seamlessly next to each other.
Here is an example how I solve it
x2 <- seq(1.9, 7.3, length.out=10)
x1 <- seq(0.2, 5.8, length.out=10)
y1 <- rnorm(10)
par(mfrow=c(1,2))
par(mar=c(5,4,4,0))
plot(x1, y1, type="l", bty="n", xlim=range(x1), ylim=c(-2, 2))
par(mar=c(5,0,4,2))
plot(x2, y1, type="l", bty="n", xlim=rev(range(x2)), ylim=c(-2, 2), yaxt="n")
Here is the problem: I would like the two lines to touch or almost touch. If the axes are separated, that is OK; but the distance between these two plots should be minimal. Optimally, I will want to have fat red vertical line showing where the two parts of the plot meet.
None of the answers I have found so far allow me to do that.
Context: I am plotting a genomic rearrangement in which two distant parts of some chromosomes were fused together, one of them reversed (hence the different scaling).
Add xaxs = "i" into the fist par(), i.e.
par(mfrow = c(1, 2), xaxs = "i")
and run the entire code again.
xaxs indicates the style of axis interval calculation to be used for the x-axis. The default is "r"(regular) which extends the data range by 4 percent at each end. Revising it to "i" will make the x-axis fit within the original data range.
While #DarrenTsai's answer is absolutely correct, you'll find that the x-axis scales take up different values per pixel when they have different mar parameters. I suggest you consider plotting them together and then adding a custom axis.
x2 <- seq(1.9, 7.3, length.out=10)
x1 <- seq(0.2, 5.8, length.out=10)
y1 <- rnorm(10)
ValueTable <- data.frame(Foward = c(x1,max(x1) + (x2-min(x2))), Join = c(x1,rev(x2)))
plot(ValueTable$Foward,c(y1,rev(y1)),type = "l",xaxt="n",xlab = "",ylab = "Value")
axis(1, ValueTable$Foward[seq(1,nrow(ValueTable),by = 2)], labels=formatC(ValueTable$Join[seq(1,nrow(ValueTable),by = 2)],format = "f", digits = 2))
abline(v=max(x1))
Related
I have a data frame with the first column named "Date." It has values like "2016-01-01, 2016-01-02 ..." etc. The second column is named "precipBulk," and it just has decimal values (ex. 3.36, 1.57, etc.). The third column is named "abundance," and it also has decimal values. I want to graph both "abundance" and "precipBulk" on one graph(Like the image), but I want the x-axis to have intervals with every month instead of every other month like it is now. I know there's a way to do it in ggplot2 using "scale_x_date()" but I can't graph both of the y values in one graph with ggplot2 for some reason. Is there a way to do it without using ggplot2? if not, any tips on how I would graph dual y-axis to achieve this with ggplot2?
Graph link https://i.stack.imgur.com/SZXgT.png `
Small portion of data frame https://i.stack.imgur.com/PvTED.png
To make the graph, I did:
x = frame$Date
y1 = frame$precipBulk
y2 = frame$abundance
plot(x,y1, type = "l",ylab="Bulk Precipitation",xlab="Month",col="blue", main = "Precipitation vs Mosquito Abundance (OSBS 2016)", cex.main = 1)
par(new = TRUE)
plot(x, y2, type = "l",yaxt="n",xaxt="n",ylab="",col="red")
axis(side = 4)
legend('topleft', c("Precipitation", "Mosquito Abundance"), col= c("blue", "Red"),lty=c(1,1), adj = c(0,0.6), cex= 0.75)
You need to turn the x-axis off (as you did) and then add it manually, perhaps reducing the size if necessary so that the axis tick labels fit, otherwise, R will decide for you.
x <- seq(as.Date("2017-01-01"), as.Date("2018-01-01"), "day")
plot(x, rnorm(length(x)), xaxt="n")
at <- seq(min(x), max(x), "month")
axis(side=1, at=at, labels=format(at, "%b"), cex.axis=0.7)
The problem is that I managed to graph this:
by writing this:
par(mar=c(0,4,2,1)+.1)
shap <- shapiro.test(as.numeric(residuals.arima))$p.value
qqnorm(residuals.arima, main=c("Normal Q-Q Plot", paste("Shapiro p=", prettyNum(shap, digits = 2))))
qqline(residuals.arima)
op <- par(fig=c(.02,.5,.5,.98), new=TRUE)
hist(residuals.arima, breaks=22, probability=T,
col="grey", xlab="", ylab="", main="", axes=F)
lines(a,dnorm(a,mean(residuals.arima), sd(residuals.arima)), lty=1, col="darkblue", lwd=2)
box()
par(op)
Now, this is exactly the way I'd like the two plots to be visualized together. I do not want to split them up.
However I'd like to put everything in the right panel (2) of a structure like the following, so that I can add another plot on panel (1) without everything messing up:
layout(matrix(c(1,2), nr=1, byrow = TRUE))
How can I do this?
If I understand you correctly you want to simply do this:
par(mfrow=c(1,2))
qqplot(...)
qqline(...)
hist(...)
lines(...)
Alternative interpretation of what you are after is to put everything you have on that second side and leave the first side blank (to be used for something else). If that is the case you can use screen:
figs <- rbind(c(0, 0.5, 0, 1), # Screen1
c(0.5, 1, 0, 1), # Screen2
)
colnames(figs) <- c("W", "E", "S", "N")
rownames(figs) <- c("Screen1", "Screen2")
screenIDs <- split.screen(figs)
names(screenIDs) <- rownames(figs)
screen(screenIDs["Screen1"])
# Everything that should go on the left side goes here
screen(screenIDs["Screen2"])
# The current plots you have go here
I'm trying to add color to specific points in my circular data based on group membership (I have two groups: one with individuals with a certain medical condition and another group of just healthy controls). I've converted their data from degrees to radians and put it on the plot, but I haven't managed to be able to selectively change the color of the points based on the factor variable I have).
Know that I've loaded library (circular), which doesn't allow me to use ggplot. Here's the syntax I've been working with:
plot(bcirc, stack=FALSE, bins=60, shrink= 1, col=w$dx, axes=FALSE, xlab ="Basal sCORT", ylab = "Basal sAA")
If you've noticed, I specified the factor variable (which has two levels) in the color section, but it just keeps putting everything in one color. Any suggestions?
Seems plot.circular does not like to assign multiple colours. Here's one potential work-around:
library(circular)
## simulate circular data
bcirc1 <- rvonmises(100, circular(90), 10, control.circular=list(units="degrees"))
bcirc2 <- rvonmises(100, circular(0), 10, control.circular=list(units="degrees"))
bcirc <- c(bcirc1, bcirc2)
dx <- c(rep(1,100),rep(2,100))
## start with blank plot, then add group-specific points
plot(bcirc, stack=FALSE, bins=60, shrink= 1, col=NA,
axes=FALSE, xlab ="Basal sCORT", ylab = "Basal sAA")
points(bcirc[dx==1], col=rgb(1,0,0,0.1), cex=2) # note: a loop would be cleaner if dealing with >2 levels
points(bcirc[dx==2], col=rgb(0,0,1,0.1), cex=2)
Inspired by Paul Regular's example, here is a version using the same data where one condition is plotted stacking inwards and the other is plotted stacking outwards.
library(circular)
## simulate circular data
bcirc1 <- rvonmises(100, circular(90, units = 'degrees'), 10, control.circular=list(units="degrees"))
bcirc2 <- rvonmises(100, circular(0, units = 'degrees'), 10, control.circular=list(units="degrees"))
bcirc <- data.frame(condition = c(
rep(1,length(bcirc1)),
rep(2,length(bcirc2)) ),
angles = c(bcirc1,
bcirc2) )
## start with blank plot, then add group-specific points
dev.new(); par(mai = c(1, 1, 0.1,0.1))
plot(circular(subset(bcirc, condition == 1)$angles, units = 'degrees'), stack=T, bins=60, shrink= 1, col=1,sep = 0.005, tcl.text = -0.073,#text outside
axes=T, xlab ="Basal sCORT", ylab = "Basal sAA")
par(new = T)
plot(circular(subset(bcirc, condition == 2)$angles, units = 'degrees'), stack=T, bins=60, shrink= 1.05, col=2,
sep = -0.005, axes=F)#inner circle, no axes, stacks inwards
I used this code to make this plot:
plot(p, cv2,col=rgb(0,100,0,50,maxColorValue=255),pch=16,
panel.last=abline(h=67,v=1.89, lty=1,lwd=3))
My plot looks like this:
1.) How can I plot the value of the ablines in a simple plot?
2.) How can I scale my plot so that both lines appear in the middle?
to change scale of plot so lines are in the middle change the axes i.e.
x<-1:10
y<-1:10
plot(x,y)
abline(a=1,b=0,v=1)
changed to:
x<-1:10
y<-1:10
plot(x,y,xlim=c(-30,30))
abline(a=1,b=0,v=1)
by "value" I am assuming you mean where the line cuts the x-axis? Something like text? i.e.:
text((0), min(y), "number", pos=2)
if you want the label on the x axis then try:
abline(a=1,b=0,v=1)
axis(1, at=1,labels=1)
to prevent overlap between labels you could remove the zero i.e.:
plot(x,y,xlim=c(-30,30),yaxt="n")
axis(2, at=c(1.77,5,10,15,20,25))
or before you plot extend the margins and add the labels further from the axis
par(mar = c(6.5, 6.5, 6.5, 6.5))
plot(x,y,xlim=c(-30,30))
abline(a=1,b=0,v=1)
axis(2, at=1.77,labels=1.77,mgp = c(10, 2, 0))
Similar in spirit to the answer proposed by #user1317221, here is my suggestion
# generate some fake points
x <- rnorm(100)
y <- rnorm(100)
# positions of the lines
vert = 0.5
horiz = 1.3
To display the lines at the center of the plot, first compute the horizontal and vertical distances between the data points and the lines, then adjust the limits adequately.
# compute the limits, in order for the lines to be centered
# REM we add a small fraction (here 10%) to leave some empty space,
# available to plot the values inside the frame (useful for one the solutions, see below)
xlim = vert + c(-1.1, 1.1) * max(abs(x-vert))
ylim = horiz + c(-1.1, 1.1) * max(abs(y-horiz))
# do the main plotting
plot(x, y, xlim=xlim, ylim=ylim)
abline(h=horiz, v=vert)
Now, you could plot the 'values of the lines', either on the axes (the lineparameter allows you to control for possible overlapping):
mtext(c(vert, horiz), side=c(1,2))
or alternatively within the plotting frame:
text(x=vert, y=ylim[1], labels=vert, adj=c(1.1,1), col='blue')
text(x=xlim[1], y=horiz, labels=horiz, adj=c(0.9,-0.1), col='blue')
HTH
This is a follow-up of this question.
I wanted to plot multiple curves on the same graph but so that my new curves respect the same y-axis scale generated by the first curve.
Notice the following example:
y1 <- c(100, 200, 300, 400, 500)
y2 <- c(1, 2, 3, 4, 5)
x <- c(1, 2, 3, 4, 5)
# first plot
plot(x, y1)
# second plot
par(new = TRUE)
plot(x, y2, axes = FALSE, xlab = "", ylab = "")
That actually plots both sets of values on the same coordinates of the graph (because I'm hiding the new y-axis that would be created with the second plot).
My question then is how to maintain the same y-axis scale when plotting the second graph.
(The typical method would be to use plot just once to set up the limits, possibly to include the range of all series combined, and then to use points and lines to add the separate series.) To use plot multiple times with par(new=TRUE) you need to make sure that your first plot has a proper ylim to accept the all series (and in another situation, you may need to also use the same strategy for xlim):
# first plot
plot(x, y1, ylim=range(c(y1,y2)))
# second plot EDIT: needs to have same ylim
par(new = TRUE)
plot(x, y2, ylim=range(c(y1,y2)), axes = FALSE, xlab = "", ylab = "")
This next code will do the task more compactly, by default you get numbers as points but the second one gives you typical R-type-"points":
matplot(x, cbind(y1,y2))
matplot(x, cbind(y1,y2), pch=1)
points or lines comes handy if
y2 is generated later, or
the new data does not have the same x but still should go into the same coordinate system.
As your ys share the same x, you can also use matplot:
matplot (x, cbind (y1, y2), pch = 19)
(without the pch matplopt will plot the column numbers of the y matrix instead of dots).
You aren't being very clear about what you want here, since I think #DWin's is technically correct, given your example code. I think what you really want is this:
y1 <- c(100, 200, 300, 400, 500)
y2 <- c(1, 2, 3, 4, 5)
x <- c(1, 2, 3, 4, 5)
# first plot
plot(x, y1,ylim = range(c(y1,y2)))
# Add points
points(x, y2)
DWin's solution was operating under the implicit assumption (based on your example code) that you wanted to plot the second set of points overlayed on the original scale. That's why his image looks like the points are plotted at 1, 101, etc. Calling plot a second time isn't what you want, you want to add to the plot using points. So the above code on my machine produces this:
But DWin's main point about using ylim is correct.
My solution is to use ggplot2. It takes care of these types of things automatically. The biggest thing is to arrange the data appropriately.
y1 <- c(100, 200, 300, 400, 500)
y2 <- c(1, 2, 3, 4, 5)
x <- c(1, 2, 3, 4, 5)
df <- data.frame(x=rep(x,2), y=c(y1, y2), class=c(rep("y1", 5), rep("y2", 5)))
Then use ggplot2 to plot it
library(ggplot2)
ggplot(df, aes(x=x, y=y, color=class)) + geom_point()
This is saying plot the data in df, and separate the points by class.
The plot generated is
I'm not sure what you want, but i'll use lattice.
x = rep(x,2)
y = c(y1,y2)
fac.data = as.factor(rep(1:2,each=5))
df = data.frame(x=x,y=y,z=fac.data)
# this create a data frame where I have a factor variable, z, that tells me which data I have (y1 or y2)
Then, just plot
xyplot(y ~x|z, df)
# or maybe
xyplot(x ~y|z, df)