Re run a specific region of the code in R

Question

I'm working in R and I need to re-run a region of the code that is written above the line where I 'm working at. I mean, just a specific part of the code, a few lines. For example :

1   x <- c(0:10)
2
3   #Start of region to rerun ----------------------
4 
5   y <- c(0,1,0,0,2,2,3,3,4,4,5)
6   z <- c(rep(100,3), rep(200, 3), rep(300,5))
7   table <- cbind(x,y,z)
8 
9   #End of region to rerun ------------------------
10 
11 
12   plot(table, type = "o") #plot numer1
13 
14   #Modification of one variable
15   x <- x*1.5
16 
17   # I would like tu rerun the region above, form line 3 to line 9
18
19   
20   plot(table, type = "o") #plot numer2

Thank you for your help!

You can copy and paste the respective lines into the R shell. — cdalitz, Apr 12 '22 at 08:31

score 0 · Answer 1 · answered Apr 12 '22 at 08:30

Just use a for loop:

nplot <- 3   # number of plot you want
x <- c(0:10) # x, y and z will not be different at this time
y <- c(0,1,0,0,2,2,3,3,4,4,5)
z <- c(rep(100,3), rep(200, 3), rep(300,5))
table <- cbind(x,y,z) # keep going in a table

for (i in 1:nplot){ # how many plots do you want?
  if (i==1){ # if is the first case...
    plot(table, type = "o") # do the plot
  }
  else{ # if is the second plot, third plot, ...
    x <- x*1.5 # now x takes other values but y and z remains constant
    table <- cbind(x,y,z) # make a new table with updated x values
    plot(table, type = "o") # just plot that new values
  }
}

You can save the plots with png("path/filename.png") before every plot. After a plot is done, you must write dev.off() just to close the png file:

nplot <- 3   # number of plot you want
x <- c(0:10) # x, y and z will not be different at this time
y <- c(0,1,0,0,2,2,3,3,4,4,5)
z <- c(rep(100,3), rep(200, 3), rep(300,5))
table <- cbind(x,y,z) # keep going in a table

for (i in 1:nplot){ # how many plots do you want?
  if (i==1){ # if is the first case...
    png(paste("yourpath/filename_",i,".png",sep=""))
    plot(table, type = "o") # do the plot
    dev.off()
  }
  else{ # if is the second plot, third plot, ...
    x <- x*1.5 # now x takes other values but y and z remains constant
    table <- cbind(x,y,z) # make a new table with updated x values
    png(paste("yourpath/filename_",i,".png",sep=""))
    plot(table, type = "o") # just plot that new values
    dev.off()
  }
}

Note that "i" in png is written to record the number of plot you're saving in order to not confuse in a future work.

Thanks for your answer. I needed to play a little with x after changing its values. That's why the "function" resulted the better soution fto ma request. But I'll have your advise in mind for another time! thanks! — user18780359, Apr 12 '22 at 12:50

score 0 · Accepted Answer · answered Apr 12 '22 at 08:41

I assume you want to rerun the code because you changed the value of x, right?

also you do not seem to need the variables of x and y further.

Therefore a function might be ideal for you:

make_my_table <- function(x){
  y <- c(0,1,0,0,2,2,3,3,4,4,5)
  z <- c(rep(100,3), rep(200, 3), rep(300,5))
  table <- cbind(x,y,z)
  # return says to return this variable, if the function is called
  return(table)
}

x <- c(0:10)
# first Plot
# make_my_table(x) will execute the function with the value for x and return the table
plot(make_my_table(x), type = "o") 

# change of x
x <- 1.5*x

# second plot

plot(make_my_table(x), type = "o")

I dont know how often you want to repeat the plot, but if there is a defined series of x values, you can execute the plot function within a for-loop or a lapply-loop, as the other answer suggest. I just wanted to explain how one can actively rerun a certain piece of code.

The advantage of a function is that except for the return variable, all variables within the function are deleted, so they do not clog your environment and confuse you.

yes that's right, I changed the x value, so I needed to "rerun" a part of the code just once to get somme subsets and make many plots. Thanks for you answer! it worked perfectly ! — user18780359, Apr 12 '22 at 12:47

Re run a specific region of the code in R

2 Answers2