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I am trying to plot a single image that contains 35 ggplots. The order of the plots in the single image is fixed and is shown below.
I also want blank grids as shown in the grid image. Each grid should have the plot with a particular drug number. I have a data frame "drug_dctv2" which I am splitting, and making into a list to read data into the for loop.
The problem is: In plot_list[[i]], only the last plot is saved 35 times with i (1 to 35). I am also not sure how to save the plots in the particular order as shown in the grid.
Through my internet search, I found library like "cowplot" and "gridextra" but I couldn't find a proper way to implement these.
I made a plot layout file which contains the drug names in the following order as shown in the grid image and in place of blank spaces, I inserted "tab". But I do not find a way to proceed from there.
I am new to R. Any help and suggestion will be appreciated.
Data set looks like as shown below. Each Drug has 10 data points.
**Drug_name conc viab**
Drug_1 1 1.0265
Drug_1 0.1 1.2365
Drug_1 0.01 0.5896
-- -- --
Drug_2 1 2.0584
Drug_2 0.1 1.0277
Drug_2 0.01 1.5696
-- -- --
#
split <- split(file,rep(1:35,each=10)) #### this will be used in the for loop
plot_list = list()
for(i in 1:length(split))
{
data <- split[[i]]
c <- data$conc
v <- data$viab
p = ggplot(data = data,aes(x=c,y=v))+geom_point()+ylim(0,1.5)+
scale_x_continuous(trans='log10')+
theme(axis.text = element_blank(),axis.title = element_blank()) +
geom_line(data=line_data, aes(x=x,y=y2),color ="red",size=1)
plot_list[[i]] = p
}
Thank you in advance !!
ggplot, as many tidyverse packages, use delayed non standard evaluation. The expression you provide inside aes is not evaluated until the plot is built (e.g. printed or saved).
The expression in your question refers to the vectors c and v defined in the for loop. These vectors change on each iteration, but the aes call only contains an expression to the reference to c and v in the environment where the for loop is running, so the c and v values used in the plot are the ones available when the plot is printed or saved.
You can, as mentioned in the comments, use a column from the data frame directly, since ggplot evaluates the data frame when ggplot() is called.
An alternative if you wanted to keep using c and v, is to make sure each iteration runs in an independent environment, so ggplot references for c and v point to the different c and v on each loop iteration. This can be done for instance replacing the for loop with an lapply call.
plot_list <- lapply(split, function(data_drug) {
c <- data_drug$conc
v <- data_drug$viab
ggplot(data = data_drug,aes(x=c,y=v))+geom_point()+ylim(0,1.5)+
scale_x_continuous(trans='log10')+
theme(axis.text = element_blank(),axis.title = element_blank()) +
geom_line(data=line_data, aes(x=x,y=y2),color ="red",size=1)
})
This is one beautiful example where a for loop and an lapply call produce different results and it's a great learning experience about non standard evaluation and variable environments.
To combine the plots look at cowplot::plot_grid https://wilkelab.org/cowplot/articles/plot_grid.html
Something like this should work
library(cowplot)
plot_grid(
plot_list[[35]], plot_list[[5]], plot_list[[3]], plot_list[[2]],
plot_list[[34]], plot_list[[1]], plot_list[[4]], plot_list[[6]],
plot_list[[32]], plot_list[[8]], NULL, NULL,
plot_list[[30]], plot_list[[7]], plot_list[[33]] , NULL,
labels = "AUTO", ncol = 4
)
You can put all the function arguments in a list and use do.call to call the function with the arguments:
plot_order <- c(
35, 5, 3, 2,
34, 1, 4, 6,
32, 8, NA, NA
)
plot_grid_args <- c(plot_list[plot_order], list(ncol = 4))
do.call(plot_grid, plot_grid_args)
So, Finally I was able to solve this problem.
I made a variable layout with the position of the drugs as they are in the split[i] list. For eg: drug_35 has to come first on the grid and it is on 35th position in split[i] list, so in "layout" variable 35 comes first and so on.
I made a text file with the grid layout as shown above in the image and then read that file in the R script and by some lines of codes I was able to make the layout variable. For the sake of simplicity I am not showing those code lines here. But, I hope the concept is clear.
lay <- read.delim("layout.txt",stringsAsFactors = FALSE,sep = "\t", header = F)
lay1 = c(t(lay))
col_n = ncol(lay)
row_n = nrow(lay)
split <- split(file,rep(1:35,each=10))
## layout = 35 5 3 2 34 1 4 6 32 8 0 0 30 7 33 .....
## 0 means blank spaces
png("PLOT.png", width = 6, height = 10, units = "in", res = 400)
par(mfrow=c(row_n,col_n),mar=c(2,0.7,1.5,0.5)) ## margins: bottom, left, top and right
for(i in layout)
{
if(i== 0) { frame(); next; }
## Here if 0 comes then the for loop will be skipped and frame() will generate a blank in the grid image
data <- split[[i]]
c <- data$conc
v <- data$viab
plot(c,v,xlab = NULL,ylab = NULL, axes = F,log = "x")
}
dev.off()
I was experimenting with the waffle package in r, and was trying to use a for loop to make multiple plots at once but was not able to get my code to work. I have a dataset with values for each year of renewables,and since it is over 40 years of data, was looking for a simple way to plot these with a for loop rather than manyally year by year. What am I doing wrong?
I have it from 1:16 as an experiment to see if it would work, although in reality I would do it for all the years in my dataset.
for(i in 1:16){
renperc<-islren$Value[i]
parts <- c(`Renewable`=(renperc), `Non-Renewable`=100-renperc)
waffle(parts, rows=10, size=1, colors=c("#00CC00", "#A9A9A9"),
title="Iceland Primary Energy Supply",
xlab=islren$TIME)
}
If I get your question correctly you want to plot all the 16 iterations in a same panel? You can parametrise your plot window to be divided into 16 smaller plots using par(mfrow = c(4,4)) (creating a 4 by 4 matrix and plotting into each cells recursively).
## Setting the graphical parameters
par(mfrow = c(4,4))
## Running the loop normally
for(i in 1:16){
renperc<-islren$Value[i]
parts <- c(`Renewable`=(renperc), `Non-Renewable`=100-renperc)
waffle(parts, rows=10, size=1, colors=c("#00CC00", "#A9A9A9"),
title="Iceland Primary Energy Supply",
xlab=islren$TIME)
}
If you need more plots (e.g. 40) you can increase the numbers in the graphical parameters (e.g. par(mfrow = c(6,7))) but that will create really tiny plots. One solution is to do it in multiple loops (for(i in 1:16); for(i in 17:32); etc.)
UPDATE: The code simply wasn't plotting anything when i tried putting in anything above one value (ex. 1:16) or a letter, both in terms of separate plots or many in one plot window (which I think perhaps waffle does not support in the same way as regular plots). In the end, I managed by making it into a function, although I'm still not sure why my original method wouldn't work if this did. See the code that worked below. I also tweaked it a bit, adding ggsave for example.
#function
waffling <- function(x){
renperc<-islren$Value[x]
parts <- c(`Renewable`=(renperc), `Non-Renewable`=100-renperc)
waffle(parts, rows=10, size=1, colors=c("#00CC00", "#A9A9A9"), title="",
xlab=islren$TIME[x])
ggsave(file=paste0("plot_", x,".png"))}
for(i in 1:57){
waffling(i)
}
Let's say I generate 5 sets of random data and want to visualize them using boxplots and save those to a file "boxplots.png". Using the code
png("boxplots.png")
data <- matrix(rnorm(25),5,5)
boxplot(data, names = c("Name1","Name2","Name3","Name4","Name5"))
dev.off()
there are 5 boxplots created as desired in "boxplots.png", however the names for the second ("Name2") and the fourth ("Name4") boxplot are omitted. Even changing the window of my png-view makes no difference. How can I avoid this behavior?
Thank you!
Your offered code does not produce an overlap in my setting, but that point is relatively moot: you want a way to allow more space between words.
One (brute-force-ish) way to fix the symptom is to alternate putting them on separate lines:
set.seed(42)
data <- matrix(rnorm(25),5,5)
nms <- c("Name1","Name2","Name3","Name4","Name5")
oddnums <- which(seq_along(nms) %% 2 == 0)
evennums <- which(seq_along(nms) %% 2 == 1)
(There's got to be a better way to do that, but it works.)
From here:
png("boxplot.png", height = 240)
boxplot(data, names = FALSE)
mtext(nms[oddnums], side = 1, line = 2, at = oddnums)
mtext(nms[evennums], side = 1, line = 1, at = evennums)
dev.off()
(The use of png is not important here, I just used it because of your edit.)
We can plot candle stick chart using chart series function chartSeries(Cl(PSEC)) I have created some custom values (I1,I2 and I3) which I want to plot together(overlay) outside the candle stick pattern. I have used addTA() for this purpose
chartSeries(Cl(PSEC)), TA="addTA(I1,col=2);addTA(I2,col=3);addTA(I3,col=4)")
The problem is that it plots four plots for Cl(PSEC),I1,I2 and I3 separately instead of two plots which I want Cl(PSEC) and (I1,I2,I3)
EDITED
For clarity I am giving a sample code with I1, I2 and I3 variable created for this purpose
library(quantmod)
PSEC=getSymbols("PSEC",auto.assign=F)
price=Cl(PSEC)
I1=SMA(price,3)
I2=SMA(price,10)
I3=SMA(price,15)
chartSeries(price, TA="addTA(I1,col=2);addTA(I2,col=3);addTA(I3,col=4)")
Here is an option which preserves largely your original code.
You can obtain the desired result using the option on=2 for each TA after the first:
library(quantmod)
getSymbols("PSEC")
price <- Cl(PSEC)
I1 <- SMA(price,3)
I2 <- SMA(price,10)
I3 <- SMA(price,15)
chartSeries(price, TA=list("addTA(I1, col=2)", "addTA(I2, col=4, on=2)",
"addTA(I3, col=5, on=2)"), subset = "last 6 months")
If you want to overlay the price and the SMAs in one chart, you can use the option on=1 for each TA.
Thanks to #hvollmeier who made me realize with his answer that I had misunderstood your question in the previous version of my answer.
PS: Note that several options are described in ?addSMA(), including with.col which can be used to select a specific column of the time series (Cl is the default column).
If I understand you correctly you want the 3 SMAs in a SUBPLOT and NOT in your main chart window.You can do the following using newTA.
Using your data:
PSEC=getSymbols("PSEC",auto.assign=F)
price=Cl(PSEC)
Now plotting a 10,30,50 day SMA in a window below the main window:
chartSeries(price['2016'])
newSMA <- newTA(SMA, Cl, on=NA)
newSMA(10)
newSMA(30,on=2)
newSMA(50,on=2)
The key is the argument on. Use on = NA in defining your new TA function, because the default value foron is 1, which is the main window. on = NA plots in a new window. Then plot the remaining SMAs to the same window as the first SMA. Style the colours etc.to your liking :-).
You may want to consider solving this task using plotting with the newer quantmod charts in the quantmod package (chart_Series as opposed to chartSeries).
Pros:
-The plots look cleaner and better (?)
-have more flexibility via editing the pars and themes options to chart_Series (see other examples here on SO for the basics of things you can do with pars and themes)
Cons:
-Not well documented.
PSEC=getSymbols("PSEC",auto.assign=F)
price=Cl(PSEC)
chart_Series(price, subset = '2016')
add_TA(SMA(price, 10))
add_TA(SMA(price, 30), on = 2, col = "green")
add_TA(SMA(price, 50), on = 2, col = "red")
# Make plot all at once (this approach is useful in shiny applications):
print(chart_Series(price, subset = '2016', TA = 'add_TA(SMA(price, 10), yaxis = list(0, 10));
add_TA(SMA(price, 30), on = 2, col = "purple"); add_TA(SMA(price, 50), on = 2, col = "red")'))
I'm trying to plot 6 days of intraday data as 6 charts. Quantmod's experimental chart_Series() function works with par() settings. I've pre-loaded the data into bars (a vector of XTS objects) so my code looks like this:
par(mfrow=c(3,2)) #3 rows, 2 columns
for(d in bars){
print(chart_Series(d, type = "candlesticks") )
}
This works, but each chart has its own different y-axis scale. I wanted to set a y-range that covers all 6 days, but cannot find a way to do this. I tried this:
ylim=c(18000,20000)
print(chart_Series(d, type = "candlesticks",ylim=ylim) )
but it fails with the "unused argument(s)" error. yrange=ylim also fails.
I can use chartSeries(d,yrange=ylim), and it works. But as far as I know I cannot put multiple charts in one display (?).
(It might strictly be off-subject, but suggestions for alternative R packages that can draw nice-looking candlestick charts, allow y-axis control and can draw multiple charts on one image would also be very welcome.)
With chartSeries, you can set the layout argument to NULL to prevent the layout() command from being called: this is what disables the mfrow setting.
library(quantmod)
getSymbols("AA")
op <- par(mfrow=c(3,2))
for(i in 1:6) {
chartSeries(
AA["2011-01"], "candlesticks",
TA=NULL, # No volume plot
layout=NULL,
yrange=c(15,18)
)
}
par(op)
If you want to keep the volume, you can call layout instead of setting mfrow: it does basically the same thing, but allows you to have plots of different sizes and choose the order in which they are plotted.
layout( matrix( c(
1, 3,
2, 4,
5, 7,
6, 8,
9, 11,
10, 12
), nc=2, byrow=TRUE),
heights = rep( c(2,1), 3 )
)
#layout.show(12) # To check that the order is as desired
for(i in 1:6) {
chartSeries(
AA[sprintf("2011-%02d",i)],
"candlesticks", layout=NULL, yrange=c(15,19)
)
}
Googling to understand Vincent's answer led me to the layout() command. It seems incompatible with par(mfrow), but some more experimentation found it can be used as an alternative.
ylim=c(18000,20000)
layout(matrix(1:12,nrow=6,ncol=2), height=c(4,2,4,2,4,2))
for(d in bars){
chartSeries(d,layout=NULL,TA=c(addVo(),addBBands()),yrange=ylim)
}
(You'll notice I added bollinger bands too, to be sure overlays still work too.)