I have 4 maps to plot and would like to plot them in a single plot area so I use the code
par(mfrow=c(2,2), bty="n")
However, the result is lots of useless blank space around my maps (which become also too small).
The image below shows how much space is taken up by each map (blue rectangle) relative to the plot area.
Is it possible to go from the current situation (cf. 2 x 2 plot fit) to the desired situation (cf. Desired better fit)?
I tried changing width and height parameters (dev.new(width=x, height=y)) but with no luck.
I would suggest using the layout function, though using par is fine too. I give a simple example below, in which you can adjust par(mar=c()) settings for each individual plot, bringing them closer together. layout allows you to adjust relative heights of plots with the height parameter, which might be useful when trying to get panel plots to be all the same height, when you have the x-axis only for the lower tier plots.
y=runif(100)
x=runif(100)
layout(matrix(c(1,2,3,4), byrow=TRUE, ncol=2,nrow=2))
par(mar=c(3,3,0.5,0.5))
plot(y,x, xaxt='n')
par(mar=c(3,3,0.5,0.5))
plot(y,x, xaxt='n')
par(mar=c(3,3,0.5,0.5))
plot(y,x)
par(mar=c(3,3,0.5,0.5))
plot(y,x, yaxt='n')
Related
So I've been running a DCA analysis on a species/site count spreadsheet (DCA file made using Vegan and decorana command). I'm having a bit of overlap with my points, so I'm trying to extend DCA 1 axis. I keep trying to use the xlim value to narrow it down to -2,2, but it just won't do it. For some reason, it seems tied to the ylim value. If I drop the ylim to -1,1, that will force the xlim to -2,2, but I can't actually have the ylim that small.
> plot(DCA, type = "n", xlim = c(-2,2))1
First plot shows result of this command. Trying to include a ylim of (-2,2) didn't change it either. Second plot shows result of this command:
> plot(DCA, type = "n", xlim = c(-2,2)), ylim = c(-2,2)2
I'm not exactly an expert at this, and I feel like I might be making a stupid mistake. Anyone got any ideas?
The plot is enforcing equal aspect ratio, and if you insist on having full range on y-axis (you do not set ylim), the x-axis will be set to accommodate the range you want to show on y-axis. You must either change the shape of your graphics display for a shorter x-axis, or then you also must set the range on y-axis with ylim Your choice. If you draw on square graphics window, the output will be square and it will be taken care that both the x and y scale (xlim, ylim) will fit the square. Changing the shape of the graphics window or setting both limits will help. Function locator() can be used to query coordinates in an existing plot, and these can be used to set up the new limits.
It is better to start again from a clean table. My intention was not to be rude, but trying to complement the answer in comments leads into terse messages where details and special cases are hard to handle. So I try to explain here how you can control the display and the axis limits in vegan ordination graphics. This answer has two main parts: (1) why we insist on equal aspect ratio, and (2) how to survive with equal aspect ratio. The latter can indeed be tricky, but we have not made it tricky because we are evil, but it is necessarily tricky.
First about the equal aspect ratio. This means that the numeric scales is equal on vertical (y) and horizontal (x) axes. In ordination the "importance" of an axis is normally reflected by its length: important axes are long, minor axes are short. In eigenvector methods this is determined by eigenvalues (which actually define the scatter of points along axes). In DCA (decorana) it should be the SD scaling so that one unit is equal to average width of species responses. We pay great attention in scaling axes accordingly, and we want to show this in the plot so that long x axis remains long and short y axis remains short even when the graph is designed for a portrait printer page shape. In this way the axis scaling (tic values) are equally spaced on both axes, and distances in the graph are equal horizontally, vertically or diagonally. Also if you draw a circle in the plot, it will remain a circle and not flattened or elongated to an ellipse. So this is something that we insist as a necessary feature of an ordination graph.
Insistence on equal scaling of equal axes comes with a price. One obvious price is that the ordination plot may not fill the graph area, but there can be a plenty of empty space in the graph for shorter axes. You can get rid of this adjusting graph shape – typically making it flatter. Another price that must be paid is the one that bit you: setting axis limits is tricky. However, this is not a vegan invention, but we use base R plot command with option asp = 1 for equal aspect ratio of axes.
To see how we can set axis limits with equal ratio, let us generate a regular rectangular grid and plot it:
x <- seq(-2, 2, by=0.2)
xy <- expand.grid(x, x)
plot(xy, asp=1)
This is a square grid on a square plot and nothing very special. However, if we plot the same grid on rectangle the aspect ratio remains equal, numeric scales are equal and the points remain equidistant on a square, but there is a lot of empty space and x-axis has longer numeric scale (but the points have unchanged numeric scale). If we try reduce only the x-scale, we face a disappointment:
plot(xy, asp=1, xlim=c(-1,1), main="xlim=c(-1,1)")
The graph is essentially similar as the first unlimited case with unchanged x. Setting xlim does not remove any points, but it only tells plot that do not reserve space but for that range on x-axis. However, y-scale is still longer and with equal aspect ratio it will also set the scale for x-axis and since there is empty space in the graph, the points are plotted there (this is analogous to having empty space even when there is nothing to plot there). To really limit the x-axis, you must simultaneously limit the y-axis accordingly:
plot(xy, asp=1, xlim=c(-1,1), ylim=c(-1,1), main="xlim=c(-1,1), ylim=c(-1,1)")
This give the desired x-limits .
Like I wrote, we did not invent that nastiness, but this is base R plot(..., asp=1) behaviour. I know this can be tricky (I have used that myself and sometimes I get irritated). I have been thinking could we be more user-friendly and by-pass base R. It is pretty easy to do this in a way that works in many normal use cases, but it is much harder to do this so that it works in most cases, and I don't know how to do this in all possible cases. If anybody knows, pull requests are welcome in vegan.
Finally, there is one tool that may help: vegan has an interactive dynamic plotting tool orditkplot where you can zoom into a plot by selecting a rectangle with left mouse button. However, this function may not work in all R systems, but if it works it gives an easy way of studying details of the plot (but if you have Mac with one-button mouse, don't ask me how it works: I don't know). You can start this with
orditkplot(mod, display="sites") # or "species", but only one
Even without orditkplot you can use base R function locator(): click the diagonally opposite corners of the rectangle you want to focus on, and this give you the xlim and ylim you need to set to zoom into this rectangle.
I have a plot with 50 categories(states) that show on my X axis, but in my output they are on top of each other. I want my plot to be spread out engough/large enough that there is no overlap and you could determine the state value from the next.
NOTE: i used the coord_flip command, so I know that my X-axis is actually my Y in image and vice versa. I am just wondering what function I would use to fix problem.
You can always change the size of the text via themes(axis.text.x=element_text(size=...))...
But the easy answer here is that your plot will change appearance based on the aspect ratio. When you view in Rstudio, you can adjust the size of your plot and you'll see the rearrangement. Additionally, when you save, the plot, play around in particular to the height and width to get the ratio you want. ggsave('filename.png', width=??, height=??).
When I use corrplot::corrplot() to plot a correlation matrix, the bottom label (1) on the y-axis is half cut off, because the bottom of the plot is at the very bottom of the plotting area, and the 1 is centered on the bottom axis. I'd like to use the plot for publication. How do I give a bit more space at the bottom so that this bottom y-axis label is not cut off?
Thanks in advance for the plot and for help with the above. This is a very nice plot except for the above issue.
Larry Hunsicker
Although no reproducible example was provided, we can show here a generic example of how to deal with this. Here a corrplot, in which the bottom label on the color scale is cut off:
M = cor(mtcars)
corrplot(M)
We can solve this by increasing the margin size using mar parameter in corrplot, to give enough space around the figure for labels. We also need to specify par(xpd=TRUE) to allow labels to be printed within the margin areas. Note that the behaviour of corrplot with respect to graphical parameters is somewhat inconsistent. Some parameters need to be specified in a par statement preceding corrplot, otherwise they are not respected if specified within the corrplot statement itself. Other parameters only work if they are specified within the corrplot statement. ?corrplot will tell you which graphical parameters get over-ridden by default values if not specified in corrplot - these are the ones that will have to be specified inside corrplot.
par(xpd=TRUE)
corrplot(M, mar = c(2, 0, 1, 0))
I am plotting polygon in R and saving it.Problem, I am facing is that the whole plot is saved as png file but I want to save only the filled area in the polygon.
Is there a way for that ?
x<-c(0.000000000,0.010986328,0.006351471,-0.004634857)
y<-c(0.000000000,0.007232612,0.012841203,0.006199415)
file_name = paste("~/Downloads/Plot", ".png", sep="")
png(file_name,width=1280,height = 720,units="px",res=200)
plot(x,y,axes=FALSE,ylab='',xlab='')+polygon(x,y,col="#FF0000FF")
dev.off()
If you're drawing a monofigure plot (which is the default), then I believe there are three possible sources of spacing that can cause a plot element to not extend to the edges of the graphics device:
1: data coordinate limits that are larger than the extent of the plot element.
2: "internal spacing", which is best thought of as an expansion of the plot area that sits inside the margins.
3: margins. This is normally where axes, ticks, tick labels, axis labels, titles, and sometimes legends are drawn.
All of these sources of spacing can be eliminated with the following customizations:
1: set the xlim and ylim graphics parameters to perfectly fit the target plot element.
2: set xaxs='i',yaxs='i', which can be done with either a preemptive par() call or on the initial plot() call.
3: zero the margins with mar=c(0,0,0,0). This must be done with par() prior to the initial plot() call.
Example:
## generate data
pts <- data.frame(x=c(0.2,0.4,0.9,0.7),y=c(0.5,0.4,0.5,0.6));
## precompute plot parameters
xlim <- range(pts$x);
ylim <- range(pts$y);
## draw plot
par(mar=c(0,0,0,0));
plot(NA,xlim=xlim,ylim=ylim,xaxs='i',yaxs='i',axes=F,ann=F);
points(pts$x,pts$y,pch=21L);
polygon(pts$x,pts$y,col='red',pch=21L);
Multifigure plots can incur one additional source of spacing, namely outer margins, but it looks like that doesn't concern you for this problem. In any case, I'm pretty sure outer margins always default to zero anyway.
See par() for the relevant documentation.
It looks like I misunderstood the question. What you want is a transparent background, which is different from simply fitting the image size to the plot element.
You can use the png() function to set the background to be transparent by passing bg='transparent', as explained on the documentation page.
For example, here's my fitted image saved with a transparent background:
Note that not all image viewers will correctly detect and/or clearly depict the transparency of the background. I would highly recommend GIMP, which is basically a free Photoshop knockoff, albeit markedly lighter in features. GIMP depicts transparent regions as a kind of checkerboard of grey squares, which looks like this:
I am trying to include two plot in a single window using mfrowin par().
something like this
x=1:10
y=seq(10,100,10)
z=seq(100,1000,100)
par(mfrow=c(2,1))
par(mar=c(0.2,4.1,4.1,2.1))
plot(x,y,xaxt="n",xlab=NA)
par(mar=c(4.1,4.1,0.2,2.1))
plot(x,z)
which gives
Now let's say I want to adjust the height of second plot as small as half the height of the first plot. How can I do it? I was trying with many par() parameters. But I couldn't find a way.