PE.ends: A sample final-timepoint dataset from a Pheno-Evo experiment
In jessicaaudreylee/PhenoEvoR: Tools for analysis of NetLogo Pheno-Evo model results
Description
Usage
Format
Examples
Description
This is an example Pheno-Evo dataset containing the final timepoints from each of 9 runs in a BehaviorSpace parameter sweep. It is useful for testing any functions for analyzing or visualizing data from the final timepoints. It was generated from the main example dataset PhenoEvoData (available online with our tutorial) with the following commands:
PE.ends<-extract.endpoint(PhenoEvoData, run.numbers)
pop.level.traits<-c('degrade.rate','switch.rate','response.error','generation')
PE.ends<-summarize.endpoint(PE.ends, pop.level.traits)
dr.fundiv<-calc.fun.div(PE.ends, 'degrade.rate')
PE.ends<-merge(PE.ends, dr.fundiv, by='run.number')
Usage
1
data("PE.ends")
Format
A data frame with 9 observations on the following 20 variables.
run.numbera numeric vector
toxin.conca numeric vector
env.noisea numeric vector
stepa numeric vector
count.turtlesa numeric vector
mean.toxina numeric vector
degrade.ratea character vector
switch.ratea character vector
response.errora character vector
barcodea character vector
generationa character vector
xydra character vector
mean.degrade.ratea numeric vector
mean.switch.ratea numeric vector
mean.response.errora numeric vector
mean.generationa numeric vector
nbspa numeric vector
FRica numeric vector
FEvea numeric vector
FDisa numeric vector
Examples
1
2
3
data(PE.ends)
generation.heatmap(PE.ends, toxin.conc, env.noise)
phenotype.histogram(PE.ends, xvar=env.noise, yvar=toxin.conc)
jessicaaudreylee/PhenoEvoR documentation built on Sept. 7, 2020, 3:50 a.m.
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Description Usage Format Examples
Description
This is an example Pheno-Evo dataset containing the final timepoints from each of 9 runs in a BehaviorSpace parameter sweep. It is useful for testing any functions for analyzing or visualizing data from the final timepoints. It was generated from the main example dataset PhenoEvoData (available online with our tutorial) with the following commands: PE.ends<-extract.endpoint(PhenoEvoData, run.numbers) pop.level.traits<-c('degrade.rate','switch.rate','response.error','generation') PE.ends<-summarize.endpoint(PE.ends, pop.level.traits) dr.fundiv<-calc.fun.div(PE.ends, 'degrade.rate') PE.ends<-merge(PE.ends, dr.fundiv, by='run.number')
Usage
1 | data("PE.ends")
|
Format
A data frame with 9 observations on the following 20 variables.
run.numbera numeric vector
toxin.conca numeric vector
env.noisea numeric vector
stepa numeric vector
count.turtlesa numeric vector
mean.toxina numeric vector
degrade.ratea character vector
switch.ratea character vector
response.errora character vector
barcodea character vector
generationa character vector
xydra character vector
mean.degrade.ratea numeric vector
mean.switch.ratea numeric vector
mean.response.errora numeric vector
mean.generationa numeric vector
nbspa numeric vector
FRica numeric vector
FEvea numeric vector
FDisa numeric vector
Examples
1 2 3 | data(PE.ends)
generation.heatmap(PE.ends, toxin.conc, env.noise)
phenotype.histogram(PE.ends, xvar=env.noise, yvar=toxin.conc)
|
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