activeChromosomeSet.BigBang {galgo} | R Documentation |
Swaps the "active" chromosomes for analysis. All the plots and methods compute the information from the variable $bestChromosomes
, $bestFitness
and $count
.
When callEnhancerFunc
has been used it could be needed to use the same plots with different sets of chromosomes. activeChromosomeSet
swaps the information between different chromosomes sets to concentrate the analysis on that set.
## S3 method for class 'BigBang': activeChromosomeSet(.O, set=c("evolved", "default", "custom"), count=TRUE, chromosomes=NULL, fitness=NULL, ...)
set |
"evolved" specify to analyse original chromosomes that were evolved insted of the enhanced (see evolvedChromosomes and evolvedFitness parameters). "default" restore the original chromosomes. "custom" is for user-specified chromosomes and fitness. |
count |
Instruct to re-build the count matrix used for some plots. Recommended to be TRUE always. |
chromosomes |
The chromosome set to analyse. The default is to use the variable $evolvedChromosomes from the BigBang object. |
fitness |
The fitness of the chromosomes to analyse. The default is to use the variable $evolvedFitness from the BigBang object. |
Returns nothing.
Victor Trevino. Francesco Falciani Group. University of Birmingham, U.K. http://www.bip.bham.ac.uk/bioinf
Goldberg, David E. 1989 Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Pub. Co. ISBN: 0201157675
For more information see BigBang
.
# bb was created activeChromosomeSet(bb, set="evolved") plot(bb) activeChromosomeSet(bb, set="default") plot(bb)