plot.Galgo: Plots information about the Galgo object

In galgo: Genetic Algorithms for Multivariate Statistical Models from Large-Scale Functional Genomics Data

Description

. See arguments for details.

Usage

## S3 method for class 'Galgo'
plot(x,
	type=c("all", "populations", "fitness", "maxchromosomes"),
	...)

Arguments

type	The type of plot. "populations" will plots all chromosomes in one axis and the genes in the other axis. The maximum chromosome in each population is drawn with "M" whereas the best chromosome is drawn with "B". The best chromosome from Galgo object is drawn with "x". This plot give an overview of the population coverage. "fitness" plots the evolution of the maximum fitness in vertical axis against generation in horizontal. maxChromosomes plots the evolution of the maximum chromosomes in horizontal and the generation in vertical. all plots altogether.
main,xlab, ylab,col,pch	World defaults for common plot parameters. Their usage overwrite the default value. col controls the color for chromosomes
...	Other user named values to include in the object.

Value

Returns nothing.

Author(s)

Victor Trevino. Francesco Falciani Group. University of Birmingham, U.K. http://www.bip.bham.ac.uk/bioinf

References

Goldberg, David E. 1989 Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Pub. Co. ISBN: 0201157675

See Also

For more information see Galgo.

Examples

  wo <- World(niches=newRandomCollection(Niche(chromosomes=
                     newRandomCollection(Chromosome(genes=
                     newCollection(Gene(shape1=1, shape2=100),5)),
                     10),2),2))
  ga <- Galgo(populations=newRandomCollection(wo,1), goalFitness = 0.75,
              callBackFunc=plot,
              fitnessFunc=function(chr, parent) 5/sd(as.numeric(chr)))
  evolve(ga) 
  best(ga)
  bestFitness(ga)
  plot(ga)

  reInit(ga)
  generateRandom(ga)
  evolve(ga)
  best(ga)
  bestFitness(ga)
  plot(ga)

galgo documentation built on May 2, 2019, 4:20 a.m.