Dear all,
I'm working with a code that consists of two parts: In Part 1 I'm generating
a random graph using the igraph library (which represents the relationships
between different nodes) and a vector (which represents a certain
characteristic for each node):
library(igraph)
g <- watts.strogatz.game(1,100,5,0.05)
z <- rlnorm(100,0,1)
In Part 2 I'm iteratively changing the elements of z in order to reach a
certain value of a certain target variable. I'm doing this using a while
statement:
while (target_variable < threshold) {## adapt z}
The problem is that in some rare cases this iterative procedure can take
very long (a couple of million of iterations), depending on the specific
structure of the graph generated in Part 1. I therefore would like to change
Part 2 of my code in the sense that once a certain threshold number of
iterations has been achieved, the iterative process in Part 2 stops and goes
back to Part 1 to generate a new graph structure. So my idea is as follows:
- Run Part 1 and generate g and z
- Run Part 2 and iteratively modify z to maximize the target variable
- If Part 2 can be obtained in less than X steps, then go to Part 3
- If Part 2 takes more than X steps then go back to Part 1 and start again
I think that R does not have a function like "go-to" or "go-back".
Does anybody know of a convenient way of doing this?
Thanks very much for your help,
Michael
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