I am trying to fit in 13 plots in one image but the plots in the image seem to be stretched and is not clear.
This is currently my coding progress:
par(mfrow=c(4,4))
plot(johordata,series = "male", main = "Johor")
plot(kedahdata,series = "male", main = "Kedah")
plot(kelantandata,series = "male", main = "Kelantan")
plot(melakadata,series = "male",main = "Melaka" )
plot(nsembilandata,series = "male",main = "Negeri Sembilan")
plot(pahangdata,series = "male",main = "Pahang")
plot(perakdata,series = "male",main = "Perak")
plot(perlisdata,series = "male",main = "Perlis")
plot(ppinangdata,series = "male",main = "Pulau Pinang")
plot(sabahdata,series = "male",main = "Sabah")
plot(sarawakdata,series = "male",main = "Sarawak")
plot(selangordata,series = "male",main = "Selangor")
plot(terengganudata,series = "male",main = "Terengganu")
Thus, I'm trying to figure out the right way for the 13 plots to look like this:
As #zx8754 said in the comments, you should use the png or pdf device, to make the result independent of the current scaling of your plots window. See this Q&A. In addition you may want to screw a little more on the par options, e.g. using mar=. Just read ?par help file. Example:
png("X:/plot1.png", width=480, height=480)
op <- par(mfrow=c(4, 4), mar=c(4, 4, 2.5, 1.5)) ## set pars and store defaults
replicate(16, plot(mpg ~ hp, mtcars, col=4))
par(op) ## reset par defaults
dev.off()
Related
I tried to plot star plots with individual label in R but could not achieve it.
This is a picture of what I want my starplots to look like:
This is what I got after running the code below:
# loading package
library(fmsb)
# loading data
dac<- read_excel("Mean_data_ESS.xlsx")#reading from the .xlsx fil
daks<-select(dac, Pollinators,Flower_abundance,
Climate_regulation,Crop_area,
Plant_diversity,Nitrogen_balance,
Phosphorus_balance,Habitat_provision,
Recreation_covid,Aesthetic_appreciation,
Reconnection_nature,Mental_health,
Physical_health)
process <- preProcess(as.data.frame(daks), method=c("range"))
norm_datas <- predict(process, as.data.frame(daks))
stars(norm_datas[, 1:12], full = TRUE,radius = TRUE,len = 1.0,
key.loc = c(14,1),
labels = abbreviate(case.names(norm_datas)),
main = "Provision of Ecosystem services", draw.segments = TRUE,
lwd = 0.25, lty = par("lty"), xpd = TRUE)
I want to skip a empty panel using lattice package in R.
set.seed(1)
df1 <- data.frame("treatment" = c(rep("A",16),rep("B",16),rep("C",16)),
"disease_type" = c(rep("1",8),rep("2",8)),
"days_after_application" = rep(c(rep("10-24",4),rep("24-48",4)),6),
"severity" = rnorm(48, mean = 80, sd = 5))
df1[(df1$disease_type == "2" & df1$days_after_application == "24-48"),"severity"] <- NA
library(lattice)
figure1 <- bwplot(treatment~severity|days_after_application+disease_type,
data = df1,layout = c(2,2),
strip = strip.custom(strip.names = TRUE))
jpeg("figure1.jpeg")
print(figure1)
dev.off()
Here is what I get
My question is how I can remove/skip empty panel in the top right WITHOUT changing layout?
I have tried following code. However, it doesn't work.
figure2 <- bwplot(treatment~severity|days_after_application+disease_type,
data = df1,layout = c(2,2),
strip = strip.custom(strip.names = TRUE),
skip = c(FALSE,FALSE,FALSE,TRUE))
jpeg("figure2.jpeg")
print(figure2)
dev.off()
Here is what I got
I also tried following codes. But it is not what I want since I do want 2 levels strips.
df1[(df1$disease_type == "2" & df1$days_after_application == "24-48"),] <- NA
bwplot(treatment~severity|interaction(days_after_application,disease_type),
data = df1,layout = c(2,2),
strip = strip.custom(strip.names = TRUE))
Thank you!
Get help from a Professor in Temple University.
Here is his solution:
figure4 <- bwplot(treatment~severity|days_after_application+disease_type,
data = df1,layout = c(2,2),
strip = strip.custom(strip.names = TRUE),
skip = c(FALSE,FALSE,FALSE,TRUE),
scales=list(alternating=FALSE), ## keep x-scale on bottom
between=list(x=1, y=1)) ## space between panels
pdf("figure4%03d.pdf",onefile = FALSE) ## force two pages in file.
print(figure4)
dev.off()
so I am in dire need of help. I have finally managed to construct my R-INLA model and get it to graph as needed. via the code below:
First I create the stacks (note this is the very end of my INLA process, the mesh etc has already been done)
stk.abdu = inla.stack(data = list(y = 1, e = 0), A = list(abdu.mat, 1),tag = 'abdu', effects = list(list(i = 1:sc.mesh.5$n), data.frame(Intercept = 1,dwater=winter.abdu$dwater,elev=winter.abdu$elev,forest=winter.abdu$forest,developed=winter.abdu$developed,openwater=winter.abdu$OpenWater,barren=winter.abdu$barren,shrubland=winter.abdu$shrubland,herb=winter.abdu$herb,planted=winter.abdu$planted,wetland=winter.abdu$wetland,dist=winter.abdu$dwater)))
stk.quad = inla.stack(data = list(y = 0, e = 0.1), A = list(quad.mat, 1),tag = 'quad', effects = list(list(i = 1:sc.mesh.5$n), data.frame(Intercept = 1,dwater=dummy$dwater,elev=dummy$elev,forest=dummy$forest,developed=dummy$developed,openwater=dummy$openwater,barren=dummy$barren,shrubland=dummy$shrubland,herb=dummy$herb,planted=dummy$planted,wetland=dummy$wetland,dist=dummy$dwater)))
stk.prd<-inla.stack(data = list(y = NA), A = list(Aprd, 1),tag = 'prd', effects = list(list(i = 1:sc.mesh.5$n), data.frame(Intercept = 1,dwater=prddf2$dwater,elev=prddf2$elev,forest=prddf2$forest,developed=prddf2$developed,openwater=prddf2$openwater,barren=prddf2$barren,shrubland=prddf2$shrubland,herb=prddf2$herb,planted=prddf2$planted,wetland=prddf2$wetland,dist=prddf2$dwater)))
stk.all.prd = inla.stack(stk.abdu,stk.quad,stk.prd)
Next I fit my model
ft.inla.prd<-inla(y ~ 0 + Intercept + elev + dwater + forest+ developed + f(inla.group(dist,n=50,method="quantile"),model="rw1",scale.model=TRUE)+f(i,model=sc.spde),family="binomial",data=inla.stack.data(stk.all.prd),control.predictor = list(A = inla.stack.A(stk.all.prd),compute=TRUE),E=inla.stack.data(stk.all.prd)$e,control.compute=list(dic = TRUE),control.fixed=list(expand.factor.strategy="INLA"))
Then I change the predicted values from logit to probabilities
ft.inla.prd$newfield <- exp(ft.inla.prd$summary.random$i$mean)/(1 + exp(ft.inla.prd$summary.random$i$mean))
And finally I use inla.mesh.project and levelplot to create my image
xmean <- inla.mesh.project(projgrid,ft.inla.prd$newfield)
levelplot(xmean, col.regions=topo.colors(99), main='Probability of Presence',xlab='', ylab='', scales=list(draw=FALSE))
So my problem is that I now want to export this data (what is projected as the graph) as a raster so that I can work with it in ArcGIS. However, I have not been able to find a way to do so.
Any input is greatly appreciated
I am plotting a time series with the timePlot function of the open air package of R. The graph has grey grid lines in the background that I would like to turn off but I do not find a way to do it. I would expect something simple such as grid = FALSE, but that is not the case. It appears to be rather complex, requiring the use of extra arguments which are passed to xyplot of the library lattice. I believe the answer lies some where in the par.settings function but all attempts have failed. Does anyone have any suggestions to this issue?
Here is by script:
timeozone <- import(i, date="date", date.format = "%m/%d/%Y", header=TRUE, na.strings="")
ROMO = timePlot(timeozone, pollutant = c("C7", "C9", "C10"), group = TRUE, stack = FALSE,y.relation = "same", date.breaks = 9, lty = c(1,2,3), lwd = c(2, 3, 3), fontsize = 15, cols = c("black", "black"), ylab = "Ozone (ppbv)")
panel = function(x, y) {
panel.grid(h = 0, v = 0)
panel.xyplot(x,y)
}
I have a question about the par function in R.
I want to change the color and/or width of a line in a graph with par function. (I am using par function because the gaps.plot command below does not allow "col" option to be included. The gaps.plot command is used after the synth command).
So, I used the following command. But I noticed that the lines of the BOX are changed rather than the lines of the GRAPHS.
synth1<-read.csv(file="C:\\Users\\Research\\R\\synthinR_v4.csv",header=TRUE)
attach(synth1)
library("Synth")
dataprep.out34 <- dataprep(foo = synth1, predictors = c("lncdsales", "md1", "md2","md3", "md4", "md5", "md6", "md7", "md8", "md9", "md10", "md11", "yd1", "yd2", "yd3", "yd4", "yd5", "yd6", "yd7", "yd8"), predictors.op = "mean", time.predictors.prior = -13:1, dependent = "lndigital", unit.variable = "artistalbumcode", time.variable = "release", treatment.identifier = 34, controls.identifier = c(1:33, 35:49), time.optimize.ssr = -13:1, time.plot = -13:25)
synth.out34 <- synth(data.prep.obj = dataprep.out34, method = "BFGS")
par(lwd = 2, col="#cccccc")
gaps.plot(synth.res = synth.out34, dataprep.res = dataprep.out34, Ylab = " Log Digital Sales ", Xlab = "Release", Ylim = c(-7, 7) , Main = NA)
Does anyone know how to fix this problem??
Thank you in advance for your willingness to help. I greatly appreciate it!
The col argument to par sets the default plotting colour (i.e. when col is not explicitly specified in plotting calls), but unfortunately col = "black" is hard-coded into the source of gaps.plot.
You can make a modified copy of the function by either (1) viewing the source (F2 in RStudio, or just executing gaps.plot), editing it and assigning it to a new object, or (2) doing something like the following:
gaps.plot2 <- eval(parse(text=gsub('col = "black"', 'col = "red"',
deparse(Synth:::gaps.plot))))
and then using gaps.plot2 as you would use gaps.plot:
gaps.plot2(synth.res = synth.out34, dataprep.res = dataprep.out34,
Ylab = " Log Digital Sales ", Xlab = "Release", Ylim = c(-7, 7) ,
Main = NA)
Alter the lwd similarly. For example to make lines red and have width of 3, use nested gsub calls like this:
gaps.plot2 <- eval(parse(text=gsub('lwd = 2', 'lwd = 3',
gsub('col = "black"', 'col = "red"',
deparse(Synth:::gaps.plot)))))