A plot of a simple relationship between control variables and measurable outputs

relationshipplot.R

library(ggplot2)
library(reshape2)
parm.table<-expand.grid(Temperature=seq(20,80,length.out=20),Gene=c(1,2,3),pH=seq(3,6,length.out=10))
rf<-function(amplitude=0.1) runif(nrow(parm.table),min=1/(1+amplitude),max=1+amplitude)
parm.table$Thickness<-with(parm.table,10^(pH+as.numeric(Gene))-10*Temperature)*rf(.1)
parm.table$Count<-with(parm.table,10^(as.numeric(Gene))+100*Temperature)*rf(0.01)
parm.table$Connections<-with(parm.table,2^(as.numeric(Gene))-5*as.numeric(Gene)+12)*rf(0.2)
parm.table$GrowthRate<-with(parm.table,log(Thickness/Count)*Gene)*rf(0.2)
parm.table$Strength<-with(parm.table,Count/Connections)*rf(0.1)
parm.table$Viability<-with(parm.table,10^(10-Connections))*rf(0.2)

parm.melt<-melt(parm.table,measure.vars = c("Temperature","Gene","pH"),variable.name="Controlled",value.name="CValue")
strt.melt<-melt(parm.melt,measure.vars = c("Thickness","Count","Connections"),variable.name="Measured",value.name="MValue")
all.melt<-melt(strt.melt,measure.vars = c("GrowthRate","Strength","Viability"),variable.name="Desired",value.name="DValue")

ggplot(all.melt,aes(x=CValue,y=MValue))+
  geom_jitter()+
  facet_grid(Measured~Controlled,scales="free")+
  labs(x="Controlled Value",y="Measured Value")+
  theme_bw(25)

ggplot(all.melt,aes(x=CValue,y=DValue))+
  geom_jitter()+
  facet_grid(Desired~Controlled,scales="free")+
  labs(x="Controlled Value",y="Desired Value")+
  theme_bw(25)

ggplot(all.melt,aes(x=MValue,y=DValue))+
  geom_jitter()+
  facet_grid(Desired~Measured,scales="free")+
  labs(y="Desired Value",x="Measured Value")+
  theme_bw(25)