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=??).
In R,
is it possible to get the barplot (or whatever the name of this type plot is), that the size of each bar area = value of x axis * value of y axis.
Thanks.
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updated:
Actually I am trying to make a chart to show the performance (speed+accuracy) of the tools I was testing. There are 7 small plot in a panel. That gives some sort of overview, of course there are more detailed plots just for speed and accuracy for each tool.
In the plot, some symbols (15 symbols in total) overlapped each other, so it could be hard for the reader to find out which are the symbols behind the others.
And that was the reason I am seeking other ways of doing this.
A also did a bubble plot for the performance (green: accuracy, red: speed), this is only a initial version of it, but still, it doesn't look OK.
I've produced a pareto.chart using the QCC package in R. In the default plot, the Y axis is scaled too large & for that reason the bars are too small. Most of the plot is wasted to empty white space. I assume this is a result of the long tail (right-skew) in the data ?
How is it possible to re-scale the Y-Axis so that the bars of the chart will be taller and more prominent (and differences between the bars more visible) ?
This is my first question and I can't post images yet. Please follow the link to an illustration of the problem:
https://www.dropbox.com/s/t8bwhmoxmwl1aic/pareto-axis.png
Thanks!
Keith
If you type help(pareto.chart) you will see there is an option ylim to specify the limits if the y-axis. If you provide some sample data I could try it out.
Otherwise, try including in your function call
pareto.chart(..., ylim=c(0,10000))
and see if that rescales your y-axis.
I'm working on visualizing a matrix in R (almost exactly like http://reference.wolfram.com/mathematica/ref/MatrixPlot.html), and I've been using
image(<matrix>,axes=FALSE)
to draw the picture. However, I noticed that with the y-axis turned off, the plot isn't centered--the space is still there for the axis ticks + label. I can finagle some centering with
par(oma=c(0,0,0,2.5))
but this seems inefficient and error-prone (if my matrix were to change dimensions/become non-square). Is there a better way to force the graphic to center?
Reference image http://img694.imageshack.us/img694/9891/metropolis.png
The right hand margin is significantly smaller than the left.
Does
par(mar=c(5,2,4,2))+0.1
help?