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In the following example, the last x-axis label ("4.0") is omitted.
df <- data.frame(x = c(1, 2, 3.8), y = c(1, 2, 3))
#png(filename = "cutoff.png")
plot(df$x, df$y, xaxt = "n")
axis(side = 1, at = seq(0, 4, 0.5), labels = seq(0, 4, 0.5))
#dev.off()
How to prevent this behaviour?
You axis limit does not include 4; you need to overwrite the default limits of the plot (which it derives from the data) using xlim:
plot(df$x, df$y, xaxt = "n", xlim = c(1, 4))
Note that when using axis your specification of at will become your labels unless you overwrite that, so your script doesn't need to specify labels; your script can become:
axis(side = 1, at = seq(0, 4, 0.5))
As #griffinevo answered (+1), If you want the axis limits to go to 4, you must specify that using xlim. However, it is probably worth explaining how the default limits are computed. This is explained in the documentation, but in a slightly obscure place. On the help page ?par search for xaxs. There you will see
Style "r" (regular) first extends the data range by 4 percent at each
end and then finds an axis with pretty labels that fits within the
extended range.
In your case, the data ranges from 1 to 3.8. So plot will look for pretty labels inside the range
1 - 0.04*(3.8-1) = 0.888
to
3.8 + 0.04*(3.8-1) = 3.912
4 is outside of this range and so will not appear as an axis label. For completeness, it is worth noting that "pretty" sounds like just a word, but actually has a technical meaning here - related to the pretty function. If you look at the help page ?pretty You will see the description:
Compute a sequence of about n+1 equally spaced ‘round’ values which
cover the range of the values in x. The values are chosen so that they
are 1, 2 or 5 times a power of 10.
There is additional detail on the help page.
I am having extreme difficulty in making my axes logarithmic/have custom tick marks in plot3d using the rgl package. I've tried using the "log='xy'" command in my code just like you would in the basic plot function, and I have tried to create custom tick marks using rgl.bbox. My y axis is plotting fine but my x and z are not cooperating. I cannot get anything to work. Any ideas? Below is my data, code, and a picture of the result I'm getting. I should also add that I'm basically plotting multiple 2d scatterplots in 3d using an arbitrary z value to separate the individual 2d plots.
https://www.dropbox.com/s/wv24rmnyalm3vvc/scattertest.csv?dl=0
#!/usr/bin/env Rscript
library("rgl")
data <- read.csv("~/Desktop/scattertest.csv", header=TRUE, fill=TRUE, sep=',')
x <- names(data[2])
y <- names(data[3])
z <- names(data[4])
plot3d(data[[x]], data[[z]], data[[y]], type="s", size=0.75, lit=FALSE, axes=FALSE,
xlab="rpmn", ylab="round", zlab="rpmt", log="xz",
xmin=c(0.1, 10^6), ymin=c(1,4), zmin=c(0.1, 10^6))
rgl.bbox(color="grey50", emission="grey50",
xat = c(0.1, 1, 10, 100, 10^3, 10^4, 10^5, 10^6), yat = c(1, 2, 3, 4), zat = c(0.1, 1, 10, 100, 10^3, 10^4, 10^5, 10^6),
xlen=8, ylen=4, zlen=8)
There's no support for log="xy" in plot3d(), you'll need to do the transformation yourself.
Your code asks for logarithmic labels, but you aren't doing the logarithmic transformation, so it's not working. You need to rescale the data as well.
You didn't post a reproducible example, but it's easy to create one:
x <- rlnorm(20, 2, 6)
y <- runif(20, 1, 4)
z <- rlnorm(20, 2, 6)
xyz <- cbind(log(x), y, log(z))
plot3d(xyz, axes = FALSE)
ticks <- 10^((-1):6)
bbox3d(xat = log(ticks), xlab = ticks, yat = pretty(1:4),
zat = log(ticks), zlab = ticks,
color="grey50", emission="grey50")
I'm using plot() to create a map with a legend and because of the shape of the map, it overlaps with the legend. I'm still learning R, but how can I move the map slightly to the left to reduce overlap? I'm sure there's a simple fix, but I was not able to find the right parameter.
Thanks for your help! I'm new to R (and stackoverflow) so I cannot post an image unfortunately.
EDIT: Here's the code that I'm running:
plot(spdfCounties, bg="gray90", col=findColours(ciFisher, colRamp))
title("Fisher-Jenks")
strLegend = paste(
"$", format(round(ciFisher$brks[-(intClasses + 1)]), big.mark=","), " - ",
"$", format(round(ciFisher$brks[-1]), big.mark=","), sep=""
)
legMain = legend(
"topright", legend=strLegend,
title="Median Income, 2010", bg="gray", inset=0.02, cex=0.6,
fill=colRamp
)
Use the mar (for margin) options in par. From ?par
mar A numerical vector of the form c(bottom, left, top, right) which
gives the number of lines of margin to be specified on the four sides
of the plot. The default is c(5, 4, 4, 2) + 0.1.
So, if your legend is on the right, make your right margin bigger by entering
par(mar = c(5, 4, 4, 8) + 0.1)
Some trial and error should be able to get it right.
This question about resetting par values may also be helpful. In general, you can always do dev.off() to close the device, and a new device will start with the default par settings.
EDIT: Adapting #Hugh's example
x <- runif(1000)
y <- runif(1000)
plot(x, y)
legend('topright', legend = "points") # overlaps points
par(mar = c(5, 4, 4, 8) + 0.2)
plot(x, y)
legend('right', legend = "points", inset = -.3, xpd = T)
# The correct right margin and inset value will depend
# on the size of your graphic device.
Adjusting the margins results in
Adding white space to the graph, as in #Hugh's answer, looks like this:
Edit 2
Trying to adapt new code from question. You're still using base graphics' plot function, so nothing should be special about having a map. However, we don't have your data, so we can't really test anything. (If this doesn't work---and regardless before posting another question---you should look at tips for making reproducible examples.)
dev.off() # to reset par
par(mar = c(5, 4, 4, 8))
plot(spdfCounties, bg="gray90", col=findColours(ciFisher, colRamp))
# the margins are set as soon as you call plot()
title("Fisher-Jenks")
strLegend = paste(
"$", format(round(ciFisher$brks[-(intClasses + 1)]), big.mark=","), " - ",
"$", format(round(ciFisher$brks[-1]), big.mark=","), sep=""
)
legMain = legend(
"right", # changed the legend to right
legend=strLegend,
title="Median Income, 2010",
bg="gray",
inset= -0.3, # negative inset to put it outside of the plotting region
xpd = T, # xpd set to allow plotting outside of the plot region
cex=0.6,
fill=colRamp
)
As a one off, you can change the lim arguments of plot to create more space.
x <- runif(1000)
y <- runif(1000)
plot(x,y)
legend('topright', legend = "points") # overlaps points
plot(x,y, xlim = c(0, 1.5), ylim = c(0, 1.5) # adds white space
legend('topright', legend = "points")
I am embarrassed to ask this simple question, but has been in kicking my mind for several days whenever I create a plot:
plot (x = 1:10, y = rnorm (10, 5, 2))
grid (10,10, lty = 6, col = "cornsilk2")
I want to position the grids right at where axis are labelled, i.e. at 2, 4, 6, 8, 10 in x axis and similarly 3, 4, 5, 6, 7, 8 in y axis.
I want to automate the process as whenever the plot size changes the default label behaviour changes. See the following plot:
From ?grid description of the nx and ny arguments:
When NULL, as per default, the grid aligns with the tick marks on the
corresponding default axis (i.e., tickmarks as computed by axTicks)
plot (x = 1:10, y = rnorm (10, 5, 2))
grid (NULL,NULL, lty = 6, col = "cornsilk2")
For reference, there is a way to control the grid and axes parameters directly from the plot() command, if we are not defining a custom tick interval:
plot(x = 1:10, y = rnorm(10, 5, 2), xlim=c(1, 10), ylim=c(1, 10), panel.first=grid())
The plot.default() documentation gives more information about these parameters.
When using a custom ticks interval, the easiest is to draw the grid using abline:
plot(x = 1:10, y = rnorm(10, 5, 2), xaxp=c(1, 10, 10), yaxp=c(1, 10, 10), axes=FALSE)
axis(1, 1:10)
axis(2, 1:10)
abline(h=1:10, v=1:10, col="gray", lty=3)
More information about custom tick intervals in this thread and here for grid alignment.
For posterity, here is the long-winded way of doing it manually:
plot (x = 1:10, y = rnorm (10, 5, 2))
grid (lty = 6, col = "cornsilk2")
xaxp <- par("xaxp")
yaxp <- par("yaxp")
abline(v=seq(xaxp[1], xaxp[2], (xaxp[2]-xaxp[1])/xaxp[3]), lty=6, col = "cornsilk2")
abline(h=seq(yaxp[1], yaxp[2], (yaxp[2]-yaxp[1])/yaxp[3]), lty=6, col = "cornsilk2")
The answer provided here is much more straightforward, although you may dislike the lack of "free space" at each end of the axes. In brief,
The problem is that grid is putting nx grid lines in the user space,
but plot is adding 4% extra space on each side. You can take control
of this. Adding xaxs="i", yaxs="i" to your plot will turn off the
extra space. But then your upper right point will be cut off, so you
need to change the xlim and ylim values and change nx to match
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)