# NOT RUN {
ex.CIG <- CIG("9-4.2")
## play around with the dynamic graph until it looks right
## look up its id number in the title bar of the graph window and use it for id
par(xpd=TRUE)
CIGstatic(ex.CIG, id=1)
# }
# NOT RUN {
graph1 <- CIG("9-4.2", plot=FALSE) ### create graph object from design name
### calculate graph properties
require(igraph)
degree(graph1)
clique.number(graph1)
independence.number(graph1)
largest.cliques(graph1)
graph2 <- gen2CIG(32, c(7,11,14,29)) ### create graph object from generator columns
### check isomorphism to graph1
graph.isomorphic(graph1,graph2)
# }
# NOT RUN {
## use a CIG for manual design search
## requirement set:
estim <- compromise(17,15:17)$requirement ## all interactions of factors 15 to 17 (P,Q,R)
## graph the requirement set CIG
CIG(estim)
FrF2(128, 17, estimable=estim) ## will run for a very long time
## interrupt with ESC key, after a short period of waiting
FrF2.currentlychecked() ## displays the design that is currently checked
## should be 17-10.2407
CIG("17-10.2407")
## clearly, using columns 1, 8 and 9 for factors 15:17 does the job
## sometimes, the design where the algorithm got stuck, does not provide a solution
## in that case, option select.catlg can be used for restricting the search designs
## to designs further down in the catalogue, in order to find the next candidate
## until final success is reached
## e.g.
which(names(catlg)=="17-10.2407")
FrF2(128, 17, estimable=estim, select.catlg=catlg[2375:length(catlg)])
## will run for a very long time
## interrupting after short waiting time yields
FrF2.currentlychecked() ## displays the design that is currently checked
## should be 17-10.4177
## note: in this example, option sort="high" would make the automatic search fast
## so that manual treatment is not needed!
# }
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