How to write function that takes uses the single ouput from another function as starting point for new analysis? - r

Question

I'm having trouble writing a function that calls another function and uses the output as the basis for running new analysis in a loop (or equivalent). For example, let's say function 1 creates this output: 10. The second function would take that as a starting point to run new analysis. The single data point from the second output would then be the basis for the next round of analysis, and so on.
Here's a simple example. The question is how to create a for loop for this. Or perhaps there's a more efficient way using lapply. In any case, the first function might be as follows:
f.1 <-function(x) {
x
a <-seq(x,by=1,length.out=5)
a.1 <-tail(a,1)
}
The second function, which calls the first function, could run as follows:
f.2 <-function(x) {
f.1 <-function(x) {
a <-seq(x,by=1,length.out=5)
a.1 <-tail(a,1)
}
z <-f.1(x)
y=z+1
seq(y,by=1,length.out=5)
}
How can I modify f.2() so that it re-runs that computation using the previous output as the basis for the next round of analysis. To be precise, f.1(10) outputs:
[1] 14
In turn, f.2(10) results in:
[1] 15 16 17 18 19
How can I re-write f.2() so that it automatically computes f.2(19) on the next iteration, and continually do so for several loops. In the process, I'd like to collect the outputs in a separate file for review. Thanks much!

Answer 1

The magrittr library (which is used most notably by dplyr) makes this type of chaining somewhat simple. First, define the functions,
f.1 <-function(x) {
x
a <- seq(x, by=1, length.out=5)
a.1 <- tail(a,1)
}
f.2 <-function(x) {
y <- x+1
seq(y, by=1, length.out=5)
}
then
library(magrittr)
f.1(10) %>% f.2
# [1] 15 16 17 18 19
As #BondedDust mentioned, you could use Reduce although normally it expects to use the same function over and over so you just need to flip the most common use case
Reduce(function(x,f) f(x), list(f.1, f.2), init=10)
# [1] 15 16 17 18 19

Answer 2

You can try this with two arguments for f.2. The first argument is the x value that you need to initialize x with and n is the number of iterations that you want to do. The output of the function will be a matrix containing n rows and 5 columns.
f.2 <-function(x, n) {
c <- matrix(nrow=n, ncol=5)
for (i in 1:nrow(c))
{
z <-f.1(x) ##if you have already defined your f.1(x) beforehand, there is no need to define it again in f.2. you can simply use z <- f.1(x) like it is done here
y=z+1
c[i,] = seq(y, by=1, length.out=5)
x = c[i,5]
}
return(c)
}
The output of
f <- f.2(10, 10) ##initialising x with 10 and running 10 loops
f
[,1] [,2] [,3] [,4] [,5]
[1,] 15 16 17 18 19
[2,] 24 25 26 27 28
[3,] 33 34 35 36 37
[4,] 42 43 44 45 46
[5,] 51 52 53 54 55
[6,] 60 61 62 63 64
[7,] 69 70 71 72 73
[8,] 78 79 80 81 82
[9,] 87 88 89 90 91
[10,] 96 97 98 99 100