#plotting results 08-23-12 #load mode comparison workspace load(file.choose()) #final files #figure3 - rInf, trc windowsFonts(Arial=windowsFont("TT Arial")) tiff(filename="figure3.tif",height=4.5,width=6.5,units="in",res=300) par(mar=c(5,19,2.5,1)) boxplot(rInf_trc_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1), xlab="",cex.axis=1,font=1) mtext(side=3,line=0.2,cex=1,c("Complete Sampling"),font=1) mtext(side=3,line=1.3,cex=1,c("Clade-Constant Protocol"),font=1) mtext(side=1,line=2.2,cex=1,c("Intrinsically Resolvable"),font=1) mtext(side=1,line=3.3,cex=1,c("Proportion of Clades"),font=1) graphics.off() #figure4 - r0.1, trc windowsFonts(Arial=windowsFont("TT Arial")) tiff(filename="figure4.tif",height=4.5,width=6.5,units="in",res=300) par(mar=c(5,19,2.5,1)) boxplot(r0.1_trc_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1), xlab="",cex.axis=1,font=1) mtext(side=3,line=0.2,cex=1,c("Incomplete Sampling (0.1 per Ltu)"),font=1) mtext(side=3,line=1.3,cex=1,c("Clade-Constant Protocol"),font=1) mtext(side=1,line=2.2,cex=1,c("Intrinsically Resolvable"),font=1) mtext(side=1,line=3.3,cex=1,c("Proportion of Clades"),font=1) graphics.off() #figure5 - r0.01, trc windowsFonts(Arial=windowsFont("TT Arial")) tiff(filename="figure5.tif",height=4.5,width=6.5,units="in",res=300) par(mar=c(5,19,2.5,1)) boxplot(r0.01_trc_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1), xlab="",cex.axis=1,font=1) mtext(side=3,line=0.2,cex=1,c("Incomplete Sampling (0.01 per Ltu)"),font=1) mtext(side=3,line=1.3,cex=1,c("Clade-Constant Protocol"),font=1) mtext(side=1,line=2.2,cex=1,c("Intrinsically Resolvable"),font=1) mtext(side=1,line=3.3,cex=1,c("Proportion of Clades"),font=1) graphics.off() #figure6 - extant only windowsFonts(Arial=windowsFont("TT Arial")) tiff(filename="figure6.tif",height=4.5,width=6.5,units="in",res=300,family="Arial") par(mar=c(5,19,1.3,1)) boxplot(extant_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1), xlab="",cex.axis=1) mtext(side=3,line=0.2,cex=1,c("Extant Only Sampling"),font=1) mtext(side=1,line=2.2,cex=1,c("Intrinsically Resolvable"),font=1) mtext(side=1,line=3.3,cex=1,c("Proportion of Clades"),font=1) graphics.off() #Fig 8 - propDur at r0.01 windowsFonts(Arial=windowsFont("TT Arial")) tiff(filename="figure8.tif",height=4.5,width=6.5,units="in",res=300) par(mar=c(5,19,1.3,1)) boxplot(propDur_r0.01,names=names,horizontal=TRUE,las=1,ylim=c(0,0.3), xlab="",cex.axis=1,font=1) mtext(side=3,line=0.2,cex=1,c("Incomplete Sampling (0.01 per Ltu)"),font=1) mtext(side=1,line=2.2,cex=1,c("Proportion of Sampled Taxa"),font=1) mtext(side=1,line=3.3,cex=1,c("with Observed Durations"),font=1) graphics.off() #figureS1 - rInf, ntc windowsFonts(Arial=windowsFont("TT Arial")) tiff(filename="figureS1.tif",height=4.5,width=6.5,units="in",res=300) par(mar=c(5,19,2.5,1)) boxplot(rInf_ntc_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1), xlab="",cex.axis=1,font=1) mtext(side=3,line=0.2,cex=1,c("Complete Sampling"),font=1) mtext(side=3,line=1.3,cex=1,c("Size-Constant Protocol"),font=1) mtext(side=1,line=2.2,cex=1,c("Intrinsically Resolvable"),font=1) mtext(side=1,line=3.3,cex=1,c("Proportion of Clades"),font=1) graphics.off() #figureS2 - r0.1, ntc windowsFonts(Arial=windowsFont("TT Arial")) tiff(filename="figureS2.tif",height=4.5,width=6.5,units="in",res=300) par(mar=c(5,19,2.5,1)) boxplot(r0.1_ntc_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1), xlab="",cex.axis=1,font=1) mtext(side=3,line=0.2,cex=1,c("Incomplete Sampling (0.1 per Ltu)"),font=1) mtext(side=3,line=1.3,cex=1,c("Size-Constant Protocol"),font=1) mtext(side=1,line=2.2,cex=1,c("Intrinsically Resolvable"),font=1) mtext(side=1,line=3.3,cex=1,c("Proportion of Clades"),font=1) graphics.off() #figureS3 - r0.01, ntc windowsFonts(Arial=windowsFont("TT Arial")) tiff(filename="figureS3.tif",height=4.5,width=6.5,units="in",res=300) par(mar=c(5,19,2.5,1)) boxplot(r0.01_ntc_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1), xlab="",cex.axis=1,font=1) mtext(side=3,line=0.2,cex=1,c("Incomplete Sampling (0.01 per Ltu)"),font=1) mtext(side=3,line=1.3,cex=1,c("Size-Constant Protocol"),font=1) mtext(side=1,line=2.2,cex=1,c("Intrinsically Resolvable"),font=1) mtext(side=1,line=3.3,cex=1,c("Proportion of Clades"),font=1) graphics.off() ######################################## #propD1 at r0.01 windowsFonts(Arial=windowsFont("TT Arial")) tiff(filename="figure8_alt.tif",height=4.5,width=6.5,units="in",res=300) par(mar=c(5,19,1,1)) boxplot(propDur_r0.01,names=names,horizontal=TRUE,las=1,ylim=c(0,0.3), xlab="",cex.axis=1,font=1) mtext(side=1,line=2.2,cex=1,c("Proportion of Sampled Taxa"),font=1) mtext(side=1,line=3.3,cex=1,c("with Obs. Durations >1"),font=1) graphics.off() #################################### #testing emily's idea about binomial dist #is the variance of prop res statistic dist as under binomial? #i.e. variance should be = np(1-p) ntaxa<-r0.1_trc_ntaxa propRes<-r0.1_trc_pR ntaxa<-r0.01_trc_ntaxa propRes<-r0.01_trc_pR binomVarR2<-function(ntaxa,propRes){ obsVar<-sapply(propRes,var) obsMean<-sapply(propRes,median) expVar<-sapply(1:length(propRes),function(x) mean(sapply(1:length(propRes[[x]]),function(y) (obsMean[[x]])*(1-obsMean[[x]])/(ntaxa[[x]][[y]]-2)))) plot(expVar,obsVar, ylab="Observed Variances of Resolvable Proportion in Simulations", xlab="Expected Variance Under Binomial Distribution" );abline(0,1) R2<-(cor.test(expVar,obsVar)$est^2) names(R2)<-NULL return(R2) } #all simulation sets binomVarR2(c(rInf_trc_ntaxa,r0.1_trc_ntaxa,r0.01_trc_ntaxa,extant_ntaxa), c(rInf_trc_pR,r0.1_trc_pR,r0.01_trc_pR,extant_pR)) ######################################### #plot largest proportion of cladogram in polytomy size pdf(file="polySize_prop.pdf",width=11,height=5) par(mar=c(5,18,2,1)) rInf_trc_propNode<-lapply(1:length(rInf_trc_maxNode),function(x) rInf_trc_maxNode[[x]]/rInf_trc_ntaxa[[x]]) rInf_ntc_propNode<-lapply(1:length(rInf_ntc_maxNode),function(x) rInf_ntc_maxNode[[x]]/rInf_ntc_ntaxa[[x]]) r0.1_trc_propNode<-lapply(1:length(r0.1_trc_maxNode),function(x) r0.1_trc_maxNode[[x]]/r0.1_trc_ntaxa[[x]]) r0.1_ntc_propNode<-lapply(1:length(r0.1_ntc_maxNode),function(x) r0.1_ntc_maxNode[[x]]/r0.1_ntc_ntaxa[[x]]) r0.01_trc_propNode<-lapply(1:length(r0.01_trc_maxNode),function(x) r0.01_trc_maxNode[[x]]/r0.01_trc_ntaxa[[x]]) r0.01_ntc_propNode<-lapply(1:length(r0.01_ntc_maxNode),function(x) r0.01_ntc_maxNode[[x]]/r0.01_ntc_ntaxa[[x]]) extant_propNode<-lapply(1:length(extant_maxNode),function(x) extant_maxNode[[x]]/extant_ntaxa[[x]]) boxplot(rInf_trc_propNode,names=names,horizontal=TRUE,las=1,ylim=c(0,0.4),xlab="Ratio of Max Obs Polytomy Size to Tree Size") mtext(side=3,line=0.3,cex=1.5,"tree constant, rInf") boxplot(rInf_ntc_propNode,names=names,horizontal=TRUE,las=1,ylim=c(0,0.4),xlab="Ratio of Max Obs Polytomy Size to Tree Size") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, rInf") boxplot(r0.1_trc_propNode,names=names,horizontal=TRUE,las=1,ylim=c(0,0.4),xlab="Ratio of Max Obs Polytomy Size to Tree Size") mtext(side=3,line=0.3,cex=1.5,"tree constant, r0.1") boxplot(r0.1_ntc_propNode,names=names,horizontal=TRUE,las=1,ylim=c(0,0.4),xlab="Ratio of Max Obs Polytomy Size to Tree Size") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, r0.1") boxplot(r0.01_trc_propNode,names=names,horizontal=TRUE,las=1,ylim=c(0,0.4),xlab="Ratio of Max Obs Polytomy Size to Tree Size") mtext(side=3,line=0.3,cex=1.5,"tree constant, r0.01") boxplot(r0.01_ntc_propNode,names=names,horizontal=TRUE,las=1,ylim=c(0,0.4),xlab="Ratio of Max Obs Polytomy Size to Tree Size") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, r0.01") boxplot(extant_propNode,names=names,horizontal=TRUE,las=1,ylim=c(0,0.4),xlab="Ratio of Max Obs Polytomy Size to Tree Size") mtext(side=3,line=0.3,cex=1.5,"extant-only") graphics.off() ######################################## pdf(file="modeComparison.pdf",width=11,height=5) par(mar=c(5,18,2,1)) #plot ntaxa boxplot(rInf_trc_ntaxa,names=names,horizontal=TRUE,las=1,ylim=c(1,6500),log="x",xlab="Number of Taxa Sampled (log-scale)") mtext(side=3,line=0.3,cex=1.5,"tree constant, rInf") boxplot(rInf_ntc_ntaxa,names=names,horizontal=TRUE,las=1,ylim=c(1,6500),log="x",xlab="Number of Taxa Sampled (log-scale)") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, rInf") boxplot(r0.1_trc_ntaxa,names=names,horizontal=TRUE,las=1,ylim=c(1,6500),log="x",xlab="Number of Taxa Sampled (log-scale)") mtext(side=3,line=0.3,cex=1.5,"tree constant, r0.1") boxplot(r0.1_ntc_ntaxa,names=names,horizontal=TRUE,las=1,ylim=c(1,6500),log="x",xlab="Number of Taxa Sampled (log-scale)") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, r0.1") boxplot(r0.01_trc_ntaxa,names=names,horizontal=TRUE,las=1,ylim=c(1,6500),log="x",xlab="Number of Taxa Sampled (log-scale)") mtext(side=3,line=0.3,cex=1.5,"tree constant, r0.01") boxplot(r0.01_ntc_ntaxa,names=names,horizontal=TRUE,las=1,ylim=c(1,6500),log="x",xlab="Number of Taxa Sampled (log-scale)") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, r0.01") boxplot(extant_ntaxa,names=names,horizontal=TRUE,las=1,ylim=c(1,6500),log="x",xlab="Number of Taxa Sampled (log-scale)") mtext(side=3,line=0.3,cex=1.5,"extant-only") #plot propres boxplot(rInf_trc_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1),xlab="Proportion of Clades Resolvable") mtext(side=3,line=0.3,cex=1.5,"tree constant, rInf") boxplot(rInf_ntc_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1),xlab="Proportion of Clades Resolvable") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, rInf") boxplot(r0.1_trc_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1),xlab="Proportion of Clades Resolvable") mtext(side=3,line=0.3,cex=1.5,"tree constant, r0.1") boxplot(r0.1_ntc_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1),xlab="Proportion of Clades Resolvable") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, r0.1") boxplot(r0.01_trc_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1),xlab="Proportion of Clades Resolvable") mtext(side=3,line=0.3,cex=1.5,"tree constant, r0.01") boxplot(r0.01_ntc_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1),xlab="Proportion of Clades Resolvable") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, r0.01") boxplot(extant_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1),xlab="Proportion of Clades Resolvable") mtext(side=3,line=0.3,cex=1.5,"extant-only") #plot polydepth boxplot(rInf_trc_pD,names=names,horizontal=TRUE,las=1,ylim=c(0,1),xlab="ChiSq p-value for Evenness of Polytomy Depth") mtext(side=3,line=0.3,cex=1.5,"tree constant, rInf") boxplot(rInf_ntc_pD,names=names,horizontal=TRUE,las=1,ylim=c(0,1),xlab="ChiSq p-value for Evenness of Polytomy Depth") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, rInf") boxplot(r0.1_trc_pD,names=names,horizontal=TRUE,las=1,ylim=c(0,1),xlab="ChiSq p-value for Evenness of Polytomy Depth") mtext(side=3,line=0.3,cex=1.5,"tree constant, r0.1") boxplot(r0.1_ntc_pD,names=names,horizontal=TRUE,las=1,ylim=c(0,1),xlab="ChiSq p-value for Evenness of Polytomy Depth") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, r0.1") boxplot(r0.01_trc_pD,names=names,horizontal=TRUE,las=1,ylim=c(0,1),xlab="ChiSq p-value for Evenness of Polytomy Depth") mtext(side=3,line=0.3,cex=1.5,"tree constant, r0.01") boxplot(r0.01_ntc_pD,names=names,horizontal=TRUE,las=1,ylim=c(0,1),xlab="ChiSq p-value for Evenness of Polytomy Depth") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, r0.01") boxplot(extant_pD,names=names,horizontal=TRUE,las=1,ylim=c(0,1),xlab="ChiSq p-value for Evenness of Polytomy Depth") mtext(side=3,line=0.3,cex=1.5,"extant-only") #plot max polytomy size boxplot(rInf_trc_maxNode,names=names,horizontal=TRUE,las=1,ylim=c(1,41),xlab="Maximum Size of Observed Polytomies") mtext(side=3,line=0.3,cex=1.5,"tree constant, rInf") boxplot(rInf_ntc_maxNode,names=names,horizontal=TRUE,las=1,ylim=c(1,41),xlab="Maximum Size of Observed Polytomies") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, rInf") boxplot(r0.1_trc_maxNode,names=names,horizontal=TRUE,las=1,ylim=c(1,41),xlab="Maximum Size of Observed Polytomies") mtext(side=3,line=0.3,cex=1.5,"tree constant, r0.1") boxplot(r0.1_ntc_maxNode,names=names,horizontal=TRUE,las=1,ylim=c(1,41),xlab="Maximum Size of Observed Polytomies") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, r0.1") boxplot(r0.01_trc_maxNode,names=names,horizontal=TRUE,las=1,ylim=c(1,41),xlab="Maximum Size of Observed Polytomies") mtext(side=3,line=0.3,cex=1.5,"tree constant, r0.01") boxplot(r0.01_ntc_maxNode,names=names,horizontal=TRUE,las=1,ylim=c(1,41),xlab="Maximum Size of Observed Polytomies") mtext(side=3,line=0.3,cex=1.5,"ntaxa constant, r0.01") boxplot(extant_maxNode,names=names,horizontal=TRUE,las=1,ylim=c(1,41),xlab="Maximum Size of Observed Polytomies") mtext(side=3,line=0.3,cex=1.5,"extant-only") graphics.off() ############################### #JUST WHAT NUMBER OF SIMS DO HAVE A P-VALUE less than 0.05? res_mat<-matrix(,7,length(names)) colnames(res_mat)<-names rownames(res_mat)<-c("rInf_trc_pD","rInf_ntc_pD","r0.1_trc_pD","r0.1_ntc_pD","r0.01_trc_pD","r0.01_ntc_pD","extant_pD") res_mat[1,]<-sapply(rInf_trc_pD,function(x) sum(x<0.05,na.rm=TRUE)/length(x[!is.na(x)])) res_mat[2,]<-sapply(rInf_ntc_pD,function(x) sum(x<0.05,na.rm=TRUE)/length(x[!is.na(x)])) res_mat[3,]<-sapply(r0.1_trc_pD,function(x) sum(x<0.05,na.rm=TRUE)/length(x[!is.na(x)])) res_mat[4,]<-sapply(r0.1_ntc_pD,function(x) sum(x<0.05,na.rm=TRUE)/length(x[!is.na(x)])) res_mat[5,]<-sapply(r0.01_trc_pD,function(x) sum(x<0.05,na.rm=TRUE)/length(x[!is.na(x)])) res_mat[6,]<-sapply(r0.01_ntc_pD,function(x) sum(x<0.05,na.rm=TRUE)/length(x[!is.na(x)])) res_mat[7,]<-sapply(extant_pD,function(x) sum(x<0.05,na.rm=TRUE)/length(x[!is.na(x)])) res_mat<-res_mat[,rev(colnames(res_mat))] res_mat #bonferroni corrected res_mat<-matrix(,7,length(names)) colnames(res_mat)<-names rownames(res_mat)<-c("rInf_trc_pD","rInf_ntc_pD","r0.1_trc_pD","r0.1_ntc_pD","r0.01_trc_pD","r0.01_ntc_pD","extant_pD") res_mat[1,]<-sapply(rInf_trc_pD,function(x) sum(x<(0.05/length(x[!is.na(x)])),na.rm=TRUE)/length(x[!is.na(x)])) res_mat[2,]<-sapply(rInf_ntc_pD,function(x) sum(x<(0.05/length(x[!is.na(x)])),na.rm=TRUE)/length(x[!is.na(x)])) res_mat[3,]<-sapply(r0.1_trc_pD,function(x) sum(x<(0.05/length(x[!is.na(x)])),na.rm=TRUE)/length(x[!is.na(x)])) res_mat[4,]<-sapply(r0.1_ntc_pD,function(x) sum(x<(0.05/length(x[!is.na(x)])),na.rm=TRUE)/length(x[!is.na(x)])) res_mat[5,]<-sapply(r0.01_trc_pD,function(x) sum(x<(0.05/length(x[!is.na(x)])),na.rm=TRUE)/length(x[!is.na(x)])) res_mat[6,]<-sapply(r0.01_ntc_pD,function(x) sum(x<(0.05/length(x[!is.na(x)])),na.rm=TRUE)/length(x[!is.na(x)])) res_mat[7,]<-sapply(extant_pD,function(x) sum(x<(0.05/length(x[!is.na(x)])),na.rm=TRUE)/length(x[!is.na(x)])) res_mat<-res_mat[,rev(colnames(res_mat))] res_mat ############################# #OLD #plot rInf results par(mar=c(5,18,1,1)) boxplot(rInf_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1),xlab="Proportion of Clades Resolvable") #plot r0.1 results par(mar=c(5,18,1,1)) boxplot(r0.1_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1),xlab="Proportion of Clades Resolvable") #plot r0.01 results par(mar=c(5,18,1,1)) boxplot(r0.01_pR,names=names,horizontal=TRUE,las=1,ylim=c(0.3,1),xlab="Proportion of Clades Resolvable") #################################### #TO LOAD DATA (unneccessary once you have workspace as a saved Rdata file) #extant only extant_pR<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] extant_pD<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] extant_ntaxa<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] extant_maxNode<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] #for tree constant r0.01_trc_pR<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] r0.1_trc_pR<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] rInf_trc_pR<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] r0.01_trc_pD<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] r0.1_trc_pD<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] rInf_trc_pD<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] r0.01_trc_ntaxa<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] r0.1_trc_ntaxa<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] rInf_trc_ntaxa<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] r0.01_trc_maxNode<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] r0.1_trc_maxNode<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] rInf_trc_maxNode<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] #for ntaxa constant r0.01_ntc_pR<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] r0.1_ntc_pR<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] rInf_ntc_pR<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] r0.01_ntc_pD<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] r0.1_ntc_pD<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] rInf_ntc_pD<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] r0.01_ntc_ntaxa<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] r0.1_ntc_ntaxa<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] rInf_ntc_ntaxa<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] r0.01_ntc_maxNode<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] r0.1_ntc_maxNode<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] rInf_ntc_maxNode<-dget(file.choose())[rev(c(1:2,4,8:10,5:7,3,11:13))] #names names<-list("budding","bifurcation", "cryptic & anagenesis", "budding & bifurcation","budding & anagenesis", "bifurcation & anagenesis","budding & bifurcation & anagenesis", "budding & cryptic","bifurcation & cryptic","budding & bifurcation & cryptic", "budding & cryptic & anagenesis","bifurcation & cryptic & anagenesis", "budding & bifurcation & cryptic & anagenesis")[rev(c(1:2,4,8:10,5:7,3,11:13))] save.image(file.choose())