I've created a script for calculating several model for regression. I made a triple loop to save the results of the model in a list and then I can call whatever I need for plotting etc. I've then created other three loop for plotting my data. Everything seems to work but the last loop of the cycle create a pdf file for the plots it gets hang and corrupted. I can, of course, add dummy data in order to have the correct plot that I need but I cannot understand what it is.
I've tried all the options for graphics.off() and dev.off() but it seems I get something wrong. my R 3.3.2 version Any help appreciated
Plot DSC thermograms of isothermal crysallization
for (intK in 1:nrow(sample_levels)) #the levels of my sample
{ for (intJ in 1:nrow(conc_levels)) #concentration levels of my samples
{
plot(0,0,type='n', xlim=c(0,lim_Max_Time) ,ylim=c(0,lim_Max_exo_up),xlab=expression(paste("Time(s)")),ylab=expression(paste("Heat flow (J/g) -exo up")) ) #create null plot
for (intL in 1:nrow(Temperatures_levels))
{
if (!is.null(matrix_Avrami[[intK,intJ,intL]] ))
{
data_plot <-matrix_Avrami[[intK,intJ,intL]] #recall my data from previous part in the script
Time_p=data_plot[5] #choose the x I need
Time_p<-as.matrix(Time_p) #to avoid Error in xy.coords(x, y) : 'x' and 'y' lengths differ
Heat_flow_exo_up<-data_plot[4] #my y
Heat_flow_exo_up<-as.matrix(Heat_flow_exo_up) #same as before for avoiding erro
points(Time_p,Heat_flow_exo_up,pch=intL) #create correctly the plot I need
}
}
title(main=paste("Conc",as.character(conc_levels[intJ,]),"% GO",as.character(sample_levels[intK,]), sep = " " ) )
legend ("topright", paste(as.character(Temperatures_levels[,]),"°C",sep = ""),pch=1:nrow(Temperatures_levels))
mypath <- file.path("C:","R","SAVEHERE",paste("Heat_flow_vs_Time", as.character(intK),as.character(intJ),".pdf", sep = ""))
pdf(file=mypath)
}
dev.off()
} #the last plot of the loop correctly visualized in my console
Related
I'm trying to trouble shoot why Drake plots are not showing up with readd() - the rest of the pipeline seem's to have worked though.
Not sure if this is caused by minfi::densityPlot or some other reason; my thoughts are the later as it's also not working for the barplot function which is base R.
In the RMarkdown report I have readd(dplot1) etc. in the chunks but the output is NULL
This is the code I have in my R/setup.R file:
library(drake)
library(tidyverse)
library(magrittr)
library(minfi)
library(DNAmArray)
library(methylumi)
library(RColorBrewer)
library(minfiData)
pkgconfig::set_config("drake::strings_in_dots" = "literals") # New file API
# Your custom code is a bunch of functions.
make_beta <- function(rgSet){
rgSet_betas = minfi::getBeta(rgSet)
}
make_filter <- function(rgSet){
rgSet_filtered = DNAmArray::probeFiltering(rgSet)
}
This is my R/plan.R file:
# The workflow plan data frame outlines what you are going to do
plan <- drake_plan(
baseDir = system.file("extdata", package = "minfiData"),
targets = read.metharray.sheet(baseDir),
rgSet = read.metharray.exp(targets = targets),
mSetSq = preprocessQuantile(rgSet),
detP = detectionP(rgSet),
dplot1 = densityPlot(rgSet, sampGroups=targets$Sample_Group,main="Raw", legend=FALSE),
dplot2 = densityPlot (getBeta (mSetSq), sampGroups=targets$Sample_Group, main="Normalized", legend=FALSE),
pal = RColorBrewer::brewer.pal (8,"Dark2"),
dplot3 = barplot (colMeans (detP[,1:6]), col=pal[ factor (targets$Sample_Group[1:6])], las=2, cex.names=0.8, ylab="Mean detection p-values"),
report = rmarkdown::render(
knitr_in("report.Rmd"),
output_file = file_out("report.html"),
quiet = TRUE
)
)
After using make(plan) it looks like everything ran smoothly:
config <- drake_config(plan)
vis_drake_graph(config)
I am able to use loadd() to load the objects needed for one of these plots and then make the plots, like this:
loadd(rgSet)
loadd(targets)
densityPlot(rgSet, sampGroups=targets$Sample_Group,main="Raw", legend=FALSE)
But the readd() command doesn't work?
The output in the .html for dplot3 looks weird...
Fortunately, this is expected behavior. drake targets are return values of commands, and so the value of dplot3 is supposed to be the return value of barplot(). The return value of barplot() is actually not a plot. The "Value" section of the help file (?barplot) explains the return value.
A numeric vector (or matrix, when beside = TRUE), say mp, giving the coordinates of all the bar midpoints drawn, useful for adding to the graph.
If beside is true, use colMeans(mp) for the midpoints of each group of bars, see example.
So what is going on? As with most base graphics functions, the plot from barplot() is actually a side effect. barplot() sends the plot to a graphics device and then returns something else to the user.
Have you considered ggplot2? The return value of ggplot() is actually a plot object, which is more intuitive. If you want to stick with base graphics, maybe you could save the plot to an output file.
plan <- drake_plan(
...,
dplot3 = {
pdf(file_out("dplot3.pdf"))
barplot(...)
dev.off()
}
)
I am trying to write R codes for the histogram plot and save each histogram separate file using the following command.
I have a data set "Dummy" and i want to plot each histogram by a column name and there will be 100 histogram plots in total...
I have the following R codes that draws the each Histogram...
library(ggplot2)
i<-1
for(i in 1:100)
{
jpeg(file="d:/R Data/hist.jpeg", sep=",")
hist(Dummy$colnames<-1, ylab= "Score",ylim=c(0,3),col=c("blue"));
dev.off()
i++
if(i>100)
break()
}
As a start, let's get your for loop into R a little better by taking out the lines trying to change i, your for loop will do that for you.
We'll also include a file= value that changes with each loop run.
for(i in 1:100)
{
jpeg(file = paste0("d:/R Data/hist", i, ".jpeg"))
hist(Dummy[[i]], ylab = "Score", ylim = c(0, 3), col = "blue")
dev.off()
}
Now we just need to decide what you want to plot. Will each plot be different? How will each plot extract the data it needs?
EDIT: I've taken a stab at what you're trying to do. Are you trying to take each of 100 columns from the Dummy dataset? If so, Dummy[[i]] should achieve that (or Dummy[,i] if Dummy is a matrix).
I'm attempting to step through a dataset and create a histogram and summary table for each factor and save the output as a .svg . The histogram is created using ggplot2 and the summary table using summary().
I have successfully used the code below to save the output to a single .pdf with each page containing the relevant histogram/table. However, when I attempt to save each histogram/table combo into a set of .svg images using ggsave only the ggplot histogram is showing up in the .svg. The table is just white space.
I've tried using dev.copy Cairo and svg but all end up with the same result: Histogram renders, but table does not. If I save the image as a .png the table shows up.
I'm using the iris data as a reproducible dataset. I'm not using R-Studio which I saw was causing some "empty plot" grief for others.
#packages used
library(ggplot2)
library(gridExtra)
library(gtable)
library(Cairo)
#Create iris histogram plot
iris.hp<-ggplot(data=iris, aes(x=Sepal.Length)) +
geom_histogram(binwidth =.25,origin=-0.125,
right = TRUE,col="white", fill="steelblue4",alpha=1) +
labs(title = "Iris Sepal Length")+
labs(x="Sepal Length", y="Count")
iris.list<-by(data = iris, INDICES = iris$Species, simplify = TRUE,FUN = function(x)
{iris.hp %+% x + ggtitle(unique(x$Species))})
#Generate list of data to create summary statistics table
sum.str<-aggregate(Sepal.Length~Species,iris,summary)
spec<-sum.str[,1]
spec.stats<-sum.str[,2]
sum.data<-data.frame(spec,spec.stats)
sum.table<-tableGrob(sum.data)
colnames(sum.data) <-c("species","sep.len.min","sep.len.1stQ","sep.len.med",
"sep.len.mean","sep. len.3rdQ","sep.len.max")
table.list<-by(data = sum.data, INDICES = sum.data$"species", simplify = TRUE,
FUN = function(x) {tableGrob(x)})
#Combined histogram and summary table across multiple plots
multi.plots<-marrangeGrob(grobs=(c(rbind(iris.list,table.list))),
nrow=2, ncol=1, top = quote(paste(iris$labels$Species,'\nPage', g, 'of',pages)))
#bypass the class check per #baptiste
ggsave <- ggplot2::ggsave; body(ggsave) <- body(ggplot2::ggsave)[-2]
#
for(i in 1:3){
multi.plots<-marrangeGrob(grobs=(c(rbind(iris.list[i],table.list[i]))),
nrow=2, ncol=1,heights=c(1.65,.35),
top = quote(paste(iris$labels$Species,'\nPage', g, 'of',pages)))
prefix<-unique(iris$Species)
prefix<-prefix[i]
filename<-paste(prefix,".svg",sep="")
ggsave(filename,multi.plots)
#dev.off()
}
Edit removed theme tt3 that #rawr referenced. It was accidentally left in example code. It was not causing the problem, just in case anyone was curious.
Edit: Removing previous answer regarding it working under 32bit install and not x64 install because that was not the problem. Still unsure what was causing the issue, but it is working now. Leaving the info about grid.export as it may be a useful alternative for someone else.
Below is the loop for saving the .svg's using grid.export(), although I was having some text formatting issues with this (different dataset).
for(i in 1:3){
multi.plots<-marrangeGrob(grobs=(c(rbind(iris.list[i],table.list[i]))),
nrow=2, ncol=1,heights=c(1.65,.35), top =quote(paste(iris$labels$Species,'\nPage', g,
'of',pages)))
prefix<-unique(iris$Species)
prefix<-prefix[i]
filename<-paste(prefix,".svg",sep="")
grid.draw(multi.plots)
grid.export(filename)
grid.newpage()
}
EDIT: As for using arrangeGrob per #baptiste's comment. Below is the updated code. I was incorrectly using the single brackets [] for the returned by list, so I switched to the correct double brackets [[]] and used grid.draw to on the ggsave call.
for(i in 1:3){
prefix<-unique(iris$Species)
prefix<-prefix[i]
multi.plots<-grid.arrange(arrangeGrob(iris.list[[i]],table.list[[i]],
nrow=2,ncol=1,top = quote(paste(iris$labels$Species))))
filename<-paste(prefix,".svg",sep="")
ggsave(filename,grid.draw(multi.plots))
}
In the following reproducible example I try to create a function for a ggplot distribution plot and saving it as an R object, with the intention of displaying two plots in a grid.
ggplothist<- function(dat,var1)
{
if (is.character(var1)) {
var1 <- which(names(dat) == var1)
}
distribution <- ggplot(data=dat, aes(dat[,var1]))
distribution <- distribution + geom_histogram(aes(y=..density..),binwidth=0.1,colour="black", fill="white")
output<-list(distribution,var1,dat)
return(output)
}
Call to function:
set.seed(100)
df <- data.frame(x = rnorm(100, mean=10),y =rep(1,100))
output1 <- ggplothist(dat=df,var1='x')
output1[1]
All fine untill now.
Then i want to make a second plot, (of note mean=100 instead of previous 10)
df2 <- data.frame(x = rep(1,1000),y = rnorm(1000, mean=100))
output2 <- ggplothist(dat=df2,var1='y')
output2[1]
Then i try to replot first distribution with mean 10.
output1[1]
I get the same distibution as before?
If however i use the information contained inside the function, return it back and reset it as a global variable it works.
var1=as.numeric(output1[2]);dat=as.data.frame(output1[3]);p1 <- output1[1]
p1
If anyone can explain why this happens I would like to know. It seems that in order to to draw the intended distribution I have to reset the data.frame and variable to what was used to draw the plot. Is there a way to save the plot as an object without having to this. luckly I can replot the first distribution.
but i can't plot them both at the same time
var1=as.numeric(output2[2]);dat=as.data.frame(output2[3]);p2 <- output2[1]
grid.arrange(p1,p2)
ERROR: Error in gList(list(list(data = list(x = c(9.66707664902549, 11.3631137069225, :
only 'grobs' allowed in "gList"
In this" Grid of multiple ggplot2 plots which have been made in a for loop " answer is suggested to use a list for containing the plots
ggplothist<- function(dat,var1)
{
if (is.character(var1)) {
var1 <- which(names(dat) == var1)
}
distribution <- ggplot(data=dat, aes(dat[,var1]))
distribution <- distribution + geom_histogram(aes(y=..density..),binwidth=0.1,colour="black", fill="white")
plot(distribution)
pltlist <- list()
pltlist[["plot"]] <- distribution
output<-list(pltlist,var1,dat)
return(output)
}
output1 <- ggplothist(dat=df,var1='x')
p1<-output1[1]
output2 <- ggplothist(dat=df2,var1='y')
p2<-output2[1]
output1[1]
Will produce the distribution with mean=100 again instead of mean=10
and:
grid.arrange(p1,p2)
will produce the same Error
Error in gList(list(list(plot = list(data = list(x = c(9.66707664902549, :
only 'grobs' allowed in "gList"
As a last attempt i try to use recordPlot() to record everything about the plot into an object. The following is now inside the function.
ggplothist<- function(dat,var1)
{
if (is.character(var1)) {
var1 <- which(names(dat) == var1)
}
distribution <- ggplot(data=dat, aes(dat[,var1]))
distribution <- distribution + geom_histogram(aes(y=..density..),binwidth=0.1,colour="black", fill="white")
plot(distribution)
distribution<-recordPlot()
output<-list(distribution,var1,dat)
return(output)
}
This function will produce the same errors as before, dependent on resetting the dat, and var1 variables to what is needed for drawing the distribution. and similarly can't be put inside a grid.
I've tried similar things like arrangeGrob() in this question "R saving multiple ggplot2 plots as R-object in list and re-displaying in grid " but with no luck.
I would really like a solution that creates an R object containing the plot, that can be redrawn by itself and can be used inside a grid without having to reset the variables used to draw the plot each time it is done. I would also like to understand wht this is happening as I don't consider it intuitive at all.
The only solution I can think of is to draw the plot as a png file, saved somewhere and then have the function return the path such that i can be reused - is that what other people are doing?.
Thanks for reading, and sorry for the long question.
Found a solution
How can I reference the local environment within a function, in R?
by inserting
localenv <- environment()
And referencing that in the ggplot
distribution <- ggplot(data=dat, aes(dat[,var1]),environment = localenv)
made it all work! even with grid arrange!
I would like to plot data in parallel using foreach in R but I didn't find any way to get all my plots in the same pdf file. I thought of using recordPlot to save my plots in a list and then print them in a pdf device but it doesn't work.
I have the following error :
Error in replayPlot(x) : loading snapshot from a different session
I tried as well with ggplot but this is to slow with my large dataset.
Here is a piece of code showing my problem :
# Creating a dataframe : df
df=as.data.frame(matrix(nrow=1, ncol=10))
df=apply(df, 2, function(x) runif(100))
# Plotting function
par.plot=function(dat){
plot(dat)
p=recordPlot()
return(p)}
#Applying the function in parallel
library("parallel")
library("foreach")
library("doParallel")
cl <- makeCluster(detectCores())
registerDoParallel(cl, cores = detectCores())
plot.lst = foreach(i = 1:nrow(df)) %dopar% {
par.plot(df[i,])
}
# Trying to get 1st plot
plot.lst[[1]]
Error in replayPlot(x) : loading snapshot from a different session
Replacing %dopar% by %do% is working when I try to get my plots, because they seems to have been generated in the same environment.
I know I can call a pdf device inside the loop to generate a file for each iteration, but I would like to know if there is a way to get one file for all my plots at the output of my function.
Or do you know an easy way to merge my pdf files afterwards ?
Thanks for your help.
Charles
In my opinion your question can be devided into two distinctive parts:
1. Using the replayPlot function in th%dopar% without getting the weird error
2. Somehow getting 1 file at the end
The first question is easy to answer. The reason you get this error is that the R somehow remembers where (in OS level) the plots has been generated. You can get the same effect by using Rstudio server and trying to replay some of the recorded plots after couple of hours of closing the browser tab. In brief, the issue is that R remembers the PID of the process that generated the plot (Don't know why though!):
# generate a plot
plot(iris[, 1:2]
# record the plot
myplot <- recordPlot()
# check the PID
attr(x = myplot, which = "pid")
the good thing is you can overwrite this by assigning your current PID:
attr(x = myplot, which = "pid") <- Sys.getpid()
so you should only change the last line of your code to the following:
pdf(file = "plot.lst.pdf"))
graphics.off()
lapply(plot.lst, function(x){
attr(x = x, which = "pid") <- Sys.getpid()
replayPlot(x)})
graphics.off()
The part above entirely solves your problem, but in case you are interested in merging PDF files, follow this discussion:
Merging existing PDF files using R