Minor changes

20 files changed, 102 insertions, 78 deletions

diff --git a/analysis/analysis.R b/analysis/analysis.R
index 1a323a2..f2343a7 100644
--- a/analysis/analysis.R
+++ b/analysis/analysis.R
@@ -36,6 +36,8 @@ sim=sim%>%group_by(simkey,wireless,wakeupfor,seed,energy_constraint,coverage_con
 sim=sim%>%mutate(energy_delta=energy-energy_constraint,coverage_delta=coverage-coverage_constraint)
 sim=sim%>%group_by(simkey,wireless,wakeupfor,energy_constraint,coverage_constraint,model)%>%summarize(mean_energy_delta=mean(energy_delta),mean_coverage_delta=mean(coverage_delta),sd_energy_delta=sd(energy_delta),sd_coverage_delta=sd(coverage_delta))
 sim=sim%>%arrange(energy_constraint,coverage_constraint)%>%group_by(wireless,wakeupfor,model)%>%mutate(id=row_number())%>%ungroup() # Create id for each experiment
+rand_id=sample(seq(1,NROW(sim)/8))
+sim=sim%>%mutate(id_rand=rand_id[id])
 
 ## Perform various plots to understand the data
 GG_VARIOUS=function(){
@@ -73,31 +75,43 @@ GG_VARIOUS=function(){
 }
 
 ## Plot to generate:
-#GG_VARIOUS()
+GG_VARIOUS()
 
 
-GG_SIMULATIONS = function() {
+GG_SIMULATIONS = function(file,key="NOKEY") {
+    ## Load simulation results
+    sim=read_csv(file)
+    sim=sim%>%group_by(simkey,wireless,wakeupfor,seed,energy_constraint,coverage_constraint,model)%>%summarize(energy=sum(energy),coverage=sum(nDataRcv))
+    sim=sim%>%mutate(energy_delta=energy-energy_constraint,coverage_delta=coverage-coverage_constraint)
+    sim=sim%>%group_by(simkey,wireless,wakeupfor,energy_constraint,coverage_constraint,model)%>%summarize(mean_energy_delta=mean(energy_delta),mean_coverage_delta=mean(coverage_delta),sd_energy_delta=sd(energy_delta),sd_coverage_delta=sd(coverage_delta))
+    sim=sim%>%arrange(energy_constraint,coverage_constraint)%>%group_by(wireless,wakeupfor,model)%>%mutate(id=row_number())%>%ungroup() # Create id for each experiment
+    rand_id=sample(seq(1,NROW(sim)/8))
+    sim=sim%>%mutate(id_rand=rand_id[id])
+
     sim_means=sim%>%group_by(wireless,wakeupfor,model)%>%summarize(mean_energy=mean(mean_energy_delta),mean_coverage=mean(mean_coverage_delta))
     ## Dimension Energy
-    ggplot(sim,aes(id,mean_energy_delta,color=model))+
+    ggplot(sim,aes(id_rand,mean_energy_delta,color=model))+
         geom_hline(data=sim_means,aes(yintercept=mean_energy,color=model),linetype="dashed")+
         geom_ribbon(aes(ymin=mean_energy_delta-sd_energy_delta,ymax=mean_energy_delta+sd_energy_delta,fill=model),alpha=0.2,color=NA)+
-        geom_point(aes(shape=simkey),size=2)+geom_line()+facet_wrap(~wireless+wakeupfor,scale="free")+ggtitle("Simulation Dimension Energy")+ylab("Energy Relative Absolute Error (J)")+
+        geom_point(aes(shape=simkey),size=2)+geom_line()+facet_wrap(~wireless+wakeupfor,scale="free")+ggtitle(paste0("Simulation Dimension Energy (",key,")"))+ylab("Energy Relative Absolute Error (J)")+
         scale_x_continuous("Experiments id",breaks=seq(1,max(sim$id)))+theme(panel.grid.minor = element_blank())+labs(shape="Predictions")+
-        guides(fill=guide_legend(title="Models"),color=guide_legend(title="Models"))
-    ggsave("figures/sim_dimension_energy.pdf",width=11)
+        guides(fill=guide_legend(title="Models"),color=guide_legend(title="Models"))+
+        theme(axis.text.x=element_blank(),axis.ticks.x=element_blank())
+    ggsave(paste0("figures/sim_dimension_energy_",key,".pdf"),width=20)
     ## Dimension Coverage
-    ggplot(sim,aes(id,mean_coverage_delta,color=model))+
+    ggplot(sim,aes(id_rand,mean_coverage_delta,color=model))+
         geom_hline(data=sim_means,aes(yintercept=mean_coverage,color=model),linetype="dashed")+
         geom_ribbon(aes(ymin=mean_coverage_delta-sd_coverage_delta,ymax=mean_coverage_delta+sd_coverage_delta,fill=model),alpha=0.2,color=NA)+
-        geom_point(aes(shape=simkey),size=2)+geom_line()+facet_wrap(~wireless+wakeupfor,scale="free")+ggtitle("Simulation Dimension Coverage")+ylab("Coverage Relative Absolute Error")+
+        geom_point(aes(shape=simkey),size=2)+geom_line()+facet_wrap(~wireless+wakeupfor,scale="free")+ggtitle(paste0("Simulation Dimension Coverage (",key,")"))+ylab("Coverage Relative Absolute Error")+
         scale_x_continuous("Experiments id",breaks=seq(1,max(sim$id)))+theme(panel.grid.minor = element_blank())+labs(shape="Predictions")+
-        guides(fill=guide_legend(title="Models"),color=guide_legend(title="Models"))
-    ggsave("figures/sim_dimension_coverage.pdf",width=11)
+        guides(fill=guide_legend(title="Models"),color=guide_legend(title="Models"))+
+        theme(axis.text.x=element_blank(),axis.ticks.x=element_blank())
+    ggsave(paste0("figures/sim_dimension_coverage_",key,".pdf"),width=20)
 
 }
 
-GG_SIMULATIONS()
+GG_SIMULATIONS("../simulations/results/results_NoHintIsFALSE.csv",key="WITH_HINT")
+GG_SIMULATIONS("../simulations/results/results_NoHintIsTRUE.csv",key="NO_HINT")
 
 system("rm -f figures/combined.pdf")
 system("pdfunite figures/*.pdf figures/combined.pdf")
diff --git a/analysis/figures/combined.pdf b/analysis/figures/combined.pdf
index 9658dbd..162ff49 100644
--- a/analysis/figures/combined.pdf
+++ b/analysis/figures/combined.pdf
diff --git a/analysis/figures/combined2.pdf b/analysis/figures/combined2.pdf
deleted file mode 100644
index 969dd8c..0000000
--- a/analysis/figures/combined2.pdf
+++ /dev/null
diff --git a/analysis/figures/dimension_coverage.pdf b/analysis/figures/dimension_coverage.pdf
index 4520271..f77bee9 100644
--- a/analysis/figures/dimension_coverage.pdf
+++ b/analysis/figures/dimension_coverage.pdf
diff --git a/analysis/figures/dimension_efficiency.pdf b/analysis/figures/dimension_efficiency.pdf
index 685e519..06d53cb 100644
--- a/analysis/figures/dimension_efficiency.pdf
+++ b/analysis/figures/dimension_efficiency.pdf
diff --git a/analysis/figures/dimension_energy-coverage-policy.pdf b/analysis/figures/dimension_energy-coverage-policy.pdf
index 36af3df..bb6c27e 100644
--- a/analysis/figures/dimension_energy-coverage-policy.pdf
+++ b/analysis/figures/dimension_energy-coverage-policy.pdf
diff --git a/analysis/figures/dimension_energy-coverage-wakeupfor.pdf b/analysis/figures/dimension_energy-coverage-wakeupfor.pdf
index d4b5732..52de042 100644
--- a/analysis/figures/dimension_energy-coverage-wakeupfor.pdf
+++ b/analysis/figures/dimension_energy-coverage-wakeupfor.pdf
diff --git a/analysis/figures/dimension_energy-coverage.pdf b/analysis/figures/dimension_energy-coverage.pdf
index 5301d93..977adf6 100644
--- a/analysis/figures/dimension_energy-coverage.pdf
+++ b/analysis/figures/dimension_energy-coverage.pdf
diff --git a/analysis/figures/dimension_energy.pdf b/analysis/figures/dimension_energy.pdf
index 0aee6e7..bf4d1b9 100644
--- a/analysis/figures/dimension_energy.pdf
+++ b/analysis/figures/dimension_energy.pdf
diff --git a/analysis/figures/random_inputs.pdf b/analysis/figures/random_inputs.pdf
deleted file mode 100644
index 14e48fa..0000000
--- a/analysis/figures/random_inputs.pdf
+++ /dev/null
diff --git a/analysis/figures/random_inputs_NoHintIsFALSE.pdf b/analysis/figures/random_inputs_NoHintIsFALSE.pdf
new file mode 100644
index 0000000..c48174c
--- /dev/null
+++ b/analysis/figures/random_inputs_NoHintIsFALSE.pdf
diff --git a/analysis/figures/random_inputs_NoHintIsTRUE.pdf b/analysis/figures/random_inputs_NoHintIsTRUE.pdf
new file mode 100644
index 0000000..1153418
--- /dev/null
+++ b/analysis/figures/random_inputs_NoHintIsTRUE.pdf
diff --git a/analysis/figures/sim_dimension_coverage.pdf b/analysis/figures/sim_dimension_coverage.pdf
deleted file mode 100644
index dc40733..0000000
--- a/analysis/figures/sim_dimension_coverage.pdf
+++ /dev/null
diff --git a/analysis/figures/sim_dimension_coverage_NO_HINT.pdf b/analysis/figures/sim_dimension_coverage_NO_HINT.pdf
new file mode 100644
index 0000000..7f45e6b
--- /dev/null
+++ b/analysis/figures/sim_dimension_coverage_NO_HINT.pdf
diff --git a/analysis/figures/sim_dimension_coverage_WITH_HINT.pdf b/analysis/figures/sim_dimension_coverage_WITH_HINT.pdf
new file mode 100644
index 0000000..9081c60
--- /dev/null
+++ b/analysis/figures/sim_dimension_coverage_WITH_HINT.pdf
diff --git a/analysis/figures/sim_dimension_energy.pdf b/analysis/figures/sim_dimension_energy.pdf
deleted file mode 100644
index 83ecb0e..0000000
--- a/analysis/figures/sim_dimension_energy.pdf
+++ /dev/null
diff --git a/analysis/figures/sim_dimension_energy_NO_HINT.pdf b/analysis/figures/sim_dimension_energy_NO_HINT.pdf
new file mode 100644
index 0000000..efcf376
--- /dev/null
+++ b/analysis/figures/sim_dimension_energy_NO_HINT.pdf
diff --git a/analysis/figures/sim_dimension_energy_WITH_HINT.pdf b/analysis/figures/sim_dimension_energy_WITH_HINT.pdf
new file mode 100644
index 0000000..937e413
--- /dev/null
+++ b/analysis/figures/sim_dimension_energy_WITH_HINT.pdf
diff --git a/analysis/figures/tree.pdf b/analysis/figures/tree.pdf
index 0478306..097ad26 100644
--- a/analysis/figures/tree.pdf
+++ b/analysis/figures/tree.pdf
diff --git a/analysis/learning.R b/analysis/learning.R
index cb8a3b4..b3798e6 100644
--- a/analysis/learning.R
+++ b/analysis/learning.R
@@ -34,74 +34,84 @@ data_seed=data%>%group_by(simkey,wireless,wakeupfor,seed)%>%summarize(energy=sum
     mutate(efficiency=energy/coverage)%>%
     ungroup()
 
-## Prepare data for traning
-set.seed(1) # Reproducibility
-wireless_map=c("lora"=1,"nbiot"=2)
-data_ml=data_seed%>%select(-efficiency,-seed)%>%mutate(wireless=wireless_map[data_seed$wireless])#%>%filter(simkey!="hint")
-train_set=data_ml%>%sample_frac(0.8)     # 80% of the data
-test_set=data_ml%>%anti_join(train_set)  # 20% of the data
+generate_inputs=function(ignore_hint=FALSE) {
+    ## Prepare data for traning
+    set.seed(1) # Reproducibility
+    wireless_map=c("lora"=1,"nbiot"=2)
+    data_ml=data_seed%>%select(-efficiency,-seed)%>%mutate(wireless=wireless_map[data_seed$wireless])
+    if(ignore_hint){
+        data_ml=data_ml%>%filter(simkey!="hint")
+    }
+    train_set=data_ml%>%sample_frac(0.8)     # 80% of the data
+    test_set=data_ml%>%anti_join(train_set)  # 20% of the data
 
-## KNN training
-knn_predictions=knn(train=train_set%>%select(-simkey),test=test_set%>%select(-simkey),cl=train_set$simkey,k=10)
-## KNN analysis
-knn_cont_table=table(knn_predictions,test_set$simkey)
-knn_accuracy=round((sum(diag(knn_cont_table)/sum(rowSums(knn_cont_table))))*100)
-knn_prop_table=round(prop.table(knn_cont_table),digits=2)
+    ## KNN training
+    knn_predictions=knn(train=train_set%>%select(-simkey),test=test_set%>%select(-simkey),cl=train_set$simkey,k=10)
+    ## KNN analysis
+    knn_cont_table=table(knn_predictions,test_set$simkey)
+    knn_accuracy=round((sum(diag(knn_cont_table)/sum(rowSums(knn_cont_table))))*100)
+    knn_prop_table=round(prop.table(knn_cont_table),digits=2)
 
-## Decision tree
-tree=rpart(
-    simkey ~ wireless + wakeupfor + energy + coverage,
-    data=train_set,
-    method="class",
-    minsplit=60,
-    minbucket=1)
-tree_predictions=predict(tree,newdata=test_set%>%select(-simkey),type="class")
-tree_cont_table=table(tree_predictions,test_set$simkey)
-tree_accuracy=round((sum(diag(tree_cont_table)/sum(rowSums(tree_cont_table))))*100)
-tree_prop_table=round(prop.table(tree_cont_table),digits=2)
+    ## Decision tree
+    tree=rpart(
+        simkey ~ wireless + wakeupfor + energy + coverage,
+        data=train_set,
+        method="class",
+        minsplit=60,
+        minbucket=1)
+    tree_predictions=predict(tree,newdata=test_set%>%select(-simkey),type="class")
+    tree_cont_table=table(tree_predictions,test_set$simkey)
+    tree_accuracy=round((sum(diag(tree_cont_table)/sum(rowSums(tree_cont_table))))*100)
+    tree_prop_table=round(prop.table(tree_cont_table),digits=2)
 
-## Prints
-print(paste0("Accuracy: KNN=",knn_accuracy,"% CART=",tree_accuracy,"%"))
-pdf("figures/tree.pdf")
-tree_plot=rpart.plot(tree,box.palette=as.list(viridis::viridis(4,begin=0.48)))
-silent_call=dev.off()
-## Notes: KNN accuracy jump to 76% and CART to 80% accuracy without the hint policy
+    ## Prints
+    print(paste0("Accuracy: KNN=",knn_accuracy,"% CART=",tree_accuracy,"%"))
+    pdf(paste0("figures/tree_",as.character(ignore_hint),".pdf"))
+    tree_plot=rpart.plot(tree,box.palette=as.list(viridis::viridis(4,begin=0.48)))
+    silent_call=dev.off()
+    ## Notes: KNN accuracy jump to 76% and CART to 80% accuracy without the hint policy
 
-## Generate simulation inputs
-inputs=tibble(
-wakeupfor = c(60,180,60,180),
-wireless  = c("lora", "lora", "nbiot", "nbiot"))
-constraints=apply(inputs,1,function(row){
-    wi=row["wireless"]
-    wa=as.numeric(row["wakeupfor"])
-    ## First extract energy/coverage boundaries
-    min_energy=min((data_seed%>%filter(wireless==wi,wakeupfor==wa))$energy)
-    max_energy=max((data_seed%>%filter(wireless==wi,wakeupfor==wa))$energy)
-    min_coverage=min((data_seed%>%filter(wireless==wi,wakeupfor==wa))$coverage)
-    max_coverage=max((data_seed%>%filter(wireless==wi,wakeupfor==wa))$coverage)
-    ## Generate random points (10 per scenarios)
-    n=20
-    current_inputs=tibble(
-        wireless=rep(wi,n),
-        wakeupfor=rep(wa,n),
-        energy_constraint=runif(n,min_energy,max_energy),
-        coverage_constraint=round(runif(n,min_coverage,max_coverage)))
-    predictions_knn=knn(train=train_set%>%select(-simkey),test=current_inputs%>%
-                                              rename(energy=energy_constraint,coverage=coverage_constraint)%>%
-                                              mutate(wireless=wireless_map[wireless]),cl=train_set$simkey,k=10)
-    predictions_tree=predict(tree,newdata=current_inputs%>%
-                                              rename(energy=energy_constraint,coverage=coverage_constraint)%>%
-                                              mutate(wireless=wireless_map[wireless]),type="class")
-    knn_final=tibble(cbind(current_inputs,tibble(simkey=predictions_knn,model="knn")))
-    tree_final=tibble(cbind(current_inputs,tibble(simkey=predictions_tree,model="tree")))
-    rbind(knn_final,tree_final)
-})
-inputs=do.call("rbind",constraints)%>%distinct()
-## Dimension Energy/Coverage
-ggplot(data_seed%>%mutate(wakeupfor=as.character(wakeupfor)),
-       aes(coverage,energy,color=simkey))+geom_point()+
-    geom_point(data=inputs%>%mutate(wakeupfor=as.character(wakeupfor)),aes(coverage_constraint,energy_constraint),size=3,pch=5)+
-    ggtitle("Dimension Energy/Coverage")+xlab("Coverage")+ylab("Sum of nodes energy consumption (J)")+
-    facet_wrap(~wakeupfor+wireless,scale="free")
-ggsave("figures/random_inputs.pdf")
-write.csv(inputs,"../inputs.csv",row.names=FALSE, quote=FALSE)
+    ## Generate simulation inputs
+    inputs=tibble(
+        wakeupfor = c(60,180,60,180),
+        wireless  = c("lora", "lora", "nbiot", "nbiot"))
+    constraints=apply(inputs,1,function(row){
+        wi=row["wireless"]
+        wa=as.numeric(row["wakeupfor"])
+        ## First extract energy/coverage boundaries
+        min_energy=min((data_seed%>%filter(wireless==wi,wakeupfor==wa))$energy)
+        max_energy=max((data_seed%>%filter(wireless==wi,wakeupfor==wa))$energy)
+        min_coverage=min((data_seed%>%filter(wireless==wi,wakeupfor==wa))$coverage)
+        max_coverage=max((data_seed%>%filter(wireless==wi,wakeupfor==wa))$coverage)
+        ## Generate random points (10 per scenarios)
+        n=100
+        current_inputs=tibble(
+            wireless=rep(wi,n),
+            wakeupfor=rep(wa,n),
+            energy_constraint=runif(n,min_energy,max_energy),
+            coverage_constraint=round(runif(n,min_coverage,max_coverage)))
+        predictions_knn=knn(train=train_set%>%select(-simkey),test=current_inputs%>%
+                                                                  rename(energy=energy_constraint,coverage=coverage_constraint)%>%
+                                                                  mutate(wireless=wireless_map[wireless]),cl=train_set$simkey,k=10)
+        predictions_tree=predict(tree,newdata=current_inputs%>%
+                                          rename(energy=energy_constraint,coverage=coverage_constraint)%>%
+                                          mutate(wireless=wireless_map[wireless]),type="class")
+        knn_final=tibble(cbind(current_inputs,tibble(simkey=predictions_knn,model="knn")))
+        tree_final=tibble(cbind(current_inputs,tibble(simkey=predictions_tree,model="tree")))
+        rbind(knn_final,tree_final)
+    })
+    inputs=do.call("rbind",constraints)%>%distinct()
+    ## Dimension Energy/Coverage
+    ggplot(data_seed%>%mutate(wakeupfor=as.character(wakeupfor)),
+           aes(coverage,energy,color=simkey))+geom_point()+
+        geom_point(data=inputs%>%mutate(wakeupfor=as.character(wakeupfor)),aes(coverage_constraint,energy_constraint),size=3,pch=5)+
+        ggtitle("Dimension Energy/Coverage")+xlab("Coverage")+ylab("Sum of nodes energy consumption (J)")+
+        facet_wrap(~wakeupfor+wireless,scale="free")
+    ggsave(paste0("figures/random_inputs_NoHintIs",as.character(ignore_hint),".pdf"),width=15)
+    write.csv(inputs,paste0("../inputs_NoHintIs",as.character(ignore_hint),".csv"),row.names=FALSE, quote=FALSE)
+
+}
+
+## Generate inputs
+generate_inputs(FALSE)
+generate_inputs(TRUE)