diff options
Diffstat (limited to 'analysis/days.R')
| -rw-r--r-- | analysis/days.R | 41 |
1 files changed, 19 insertions, 22 deletions
diff --git a/analysis/days.R b/analysis/days.R index 8747bc3..dd9a819 100644 --- a/analysis/days.R +++ b/analysis/days.R @@ -156,11 +156,11 @@ learning_curves=accuracy%>%group_by(wireless,wakeupfor,days,model)%>% ggplot(data=learning_curves%>%mutate(model=ifelse(model=="knn","KNN","DT")),aes(linetype=model))+ - geom_line(aes(days,mean_f1_baseline,color="Baseline"),size=1.2)+ - geom_line(aes(days,mean_f1_extended,color="Extended"),size=1.2)+ - geom_line(aes(days,mean_f1_hintandextended,color="Hintandextended"),size=1.2)+labs(color="Classes",linetype="Model")+ + geom_line(aes(days/30,mean_f1_baseline,color="Baseline"),size=1.2)+ + geom_line(aes(days/30,mean_f1_extended,color="Extended"),size=1.2)+ + geom_line(aes(days/30,mean_f1_hintandextended,color="Hintandextended"),size=1.2)+labs(color="Classes",linetype="Model")+ facet_wrap(~wireless+wakeupfor)+ - scale_x_continuous(breaks = seq(0, 15, by = 1))+ + scale_x_continuous(breaks = seq(0, max(learning_curves$days/30)))+ scale_y_continuous(breaks = seq(0, 1, by = 0.1))+ theme_bw()+ theme(panel.grid.minor = element_blank(), @@ -169,16 +169,16 @@ ggplot(data=learning_curves%>%mutate(model=ifelse(model=="knn","KNN","DT")),aes( legend.spacing=unit(-0.2,"cm"), legend.box.margin=margin(1,1,1,1), legend.box.background = element_rect(fill = "white", color = "black",size=0.8))+ - xlab("Training days")+ylab("Classes F1-Score")+ + xlab("Training months")+ylab("Classes F1-Score")+ scale_color_viridis(discrete=TRUE,end=0.7) ggsave("figures/days_f1-score.pdf",width=8.5,height=6) ## Plot Merge Accuracy ggplot(data=learning_curves%>%mutate(model=ifelse(model=="knn","KNN","DT"))%>%reduce_days(3), - aes(days,mean_accuracy))+ - geom_line(aes(linetype=model),size=1.2)+xlab("Training days")+ylab("Model accuracy")+labs(linetype="Models")+ - scale_x_continuous(breaks = seq(0, max(learning_curves$days), by = 40))+ + aes(days/30,mean_accuracy))+ + geom_line(aes(linetype=model),size=1.2)+xlab("Training months")+ylab("Model accuracy")+labs(linetype="Models")+ + scale_x_continuous(breaks = seq(0, max(learning_curves$days/30)))+ scale_y_continuous(breaks = seq(0, 1, by = 0.1))+ facet_wrap(~wireless+wakeupfor)+ theme_bw()+ @@ -205,8 +205,6 @@ energy_coverage_delta=data_seed_energy%>% energy_coverage_delta=energy_coverage_delta%>%group_by(wireless,wakeupfor)%>%summarize(delta_energy=energy-energy_training,simkey=simkey,days=days,delta_coverage=coverage-coverage_training) - - write("wireless,wakeupfor,policy,slope,intercept,delta_coverage","figures/delta_energy_coverage.csv") energy_coverage_delta%>%group_by(wireless,wakeupfor,simkey)%>%group_walk(function(data,grp){ grp=as.list(grp) @@ -218,28 +216,27 @@ energy_coverage_delta%>%group_by(wireless,wakeupfor,simkey)%>%group_walk(functio write(paste(grp$wireless,grp$wakeupfor,grp$simkey,slope,intercept,mean_delta_coverage,sep=","),"figures/delta_energy_coverage.csv",append=T) }) -ggplot(energy_coverage_delta,aes(days,delta_energy/1e3,color=simkey,shape=simkey))+ - geom_line(size=1.2)+ylab("Delta in energy (kJ)")+xlab("Training days")+ +ggplot(energy_coverage_delta,aes(days/30,delta_energy/1e3,color=simkey,shape=simkey))+ + geom_line(size=1.2)+ylab("Delta in energy (kJ)")+xlab("Training months")+ facet_wrap(~wireless+wakeupfor,scale="free")+ scale_color_viridis(discrete=TRUE,option="H",end=0.95)+labs(color="Class")+ - theme_bw()+theme(legend.position=c(0.58,0.9), - legend.box.background = element_rect(fill = "white", color = "black",size=0.8)) + theme_bw()+theme(legend.position="top", + legend.box.spacing=margin(0,0,0,0)) ggsave("figures/delta_energy_training.pdf") -ggplot(energy_coverage_delta,aes(days,delta_coverage,color=simkey))+ - geom_line(size=1.2)+ylab("Delta in coverage")+xlab("Training days")+ +ggplot(energy_coverage_delta,aes(days/30,delta_coverage,color=simkey))+ + geom_line(size=1.2)+ylab("Delta in coverage")+xlab("Training months")+ facet_wrap(~wireless+wakeupfor,scale="free")+ scale_color_viridis(discrete=TRUE,end=0.9)+labs(color="Class")+ - theme_bw()+theme(legend.position=c(0.45,0.94), - legend.box.background = element_rect(fill = "white", color = "black",size=0.8)) -ggsave("figures/delta_coverage_training.pdf") + theme_bw()+theme(legend.position="top",legend.box.spacing=margin(0,0,0,0)) +ggsave("figures/delta_coverage_training.pdf",width=9) -ggplot(data=energy%>%reduce_days(6),aes(days,energy/1e6,group=setup,fill=setup))+ +ggplot(data=energy%>%reduce_days(6),aes(days/30,energy/1e6,group=setup,fill=setup))+ geom_bar(stat="identity",position="dodge")+ scale_fill_viridis(discrete=TRUE,option="D")+ labs(fill="Nodes wireless technology and uptime")+theme(legend.position=c(0.2,0.75))+ - scale_x_continuous(breaks = seq(0, max(energy$days), by = 15))+ - xlab("Number of days")+ylab("Energy consumption (MJ)") + scale_x_continuous(breaks = seq(0, max(energy$days/30)))+ + xlab("Number of months")+ylab("Energy consumption (MJ)") ggsave("figures/days_energy.pdf",width=8.5,height=4) |