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| author | Loïc Guégan <loic.guegan@mailbox.org> | 2025-09-22 11:06:18 +0200 |
|---|---|---|
| committer | Loïc Guégan <loic.guegan@mailbox.org> | 2025-09-22 11:06:18 +0200 |
| commit | cd162cfa8ffa96758017a5ac05fc3744a7d1929c (patch) | |
| tree | 06b546ac422e3fc7307d5e393257052a03d8b599 /analysis | |
| parent | d06f583dc59c6317e16370aa29b96bacaeaaa770 (diff) | |
Clean in-situ code
Diffstat (limited to 'analysis')
| -rw-r--r-- | analysis/in-situ.R | 8 |
1 files changed, 3 insertions, 5 deletions
diff --git a/analysis/in-situ.R b/analysis/in-situ.R index 2d57666..8df51e0 100644 --- a/analysis/in-situ.R +++ b/analysis/in-situ.R @@ -27,8 +27,6 @@ library("latex2exp") ## energy [0,+inf) ## nDataRcv [0,+inf) -## WARNING: Goto line 138 first and set the boolean to T (populate the R environment with accuracy results) afterwhich you can set it to FALSE (save time) - nseed=200 nwakeupfor=2 nwireless=2 @@ -59,7 +57,7 @@ reduce_days=function(data,every=6){data%>%filter(((days/4) %% every) == 0)} ## GGPlot Theme th = function(option="D") {list(theme_bw(), - theme(legend.box.background = element_rect(fill = "white", color = "black",size=0.9), + theme(legend.box.background = element_rect(fill = "white", color = "black",linewidth=0.9), strip.background =element_rect(fill="#F5F5F5")), scale_color_viridis(discrete=TRUE,option=option,end=0.95), scale_fill_viridis(discrete=TRUE,option=option,end=0.95))} @@ -136,7 +134,7 @@ generate_accuracy_energy = function(wireless,wakeupfor,steps=1, accuracy=10,igno ########## Generate accuracy, energy, F1-Score and coverage data ########## -if(F){ # Toggle to train +if(!exists("accuracy")){ # Perform the inital training (do it only one time) lora180=generate_accuracy_energy("lora",180) lora60=generate_accuracy_energy("lora",60) nbiot60=generate_accuracy_energy("nbiot",60) @@ -217,7 +215,7 @@ data_seed_energy=data_seed_energy%>%filter(days %in% !!energy$days) ## Compute the delta data energy_coverage_delta=data_seed_energy%>% full_join(energy,by=c("days","wireless","wakeupfor"),suffix=c("","_training")) -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)/npolicies,coverage=coverage/npolicies,coverage_training=coverage_training/npolicies) # delta_coverage divide by $npolicies because we want the average per day (coverage is measure every $npolicies days (round-robin of $npolicies policies)) +energy_coverage_delta=energy_coverage_delta%>%group_by(wireless,wakeupfor)%>%reframe(delta_energy=energy-energy_training,simkey=simkey,days=days,delta_coverage=(coverage-coverage_training)/npolicies,coverage=coverage/npolicies,coverage_training=coverage_training/npolicies) # delta_coverage divide by $npolicies because we want the average per day (coverage is measure every $npolicies days (round-robin of $npolicies policies)) write("wireless,wakeupfor,policy,slope,intercept,delta_coverage,coverage,coverage_training,latex","figures/delta_energy_coverage.csv") |