Automated_Rotating_Beam_Analysis/R_scripts/statistical_analysis.R

library(moments)
library(readxl)
library(car)
library(irr)

addcol<-function(Table, cols=50){
  while(ncol(Table)<cols){
    extracol<-rep(NA,21)
    Table=cbind(Table, extracol)
  }
  return(Table)
}

Fredi="/home/user/owncloud/Manual_Rotating_Beam_Analyse/Manual_RotatingBeam_ Analyse_ Fredi.xlsx"
Markus="/home/user/owncloud/Manual_Rotating_Beam_Analyse/Manual_RotatingBeam_ Analyse_ Markus.xlsx"
Sebastian="/home/user/owncloud/Manual_Rotating_Beam_Analyse/Manual_RotatingBeam_ Analyse_ Sebastian.xlsx"

TM=read_xlsx(Markus, col_names = T)
TF=read_xlsx(Fredi, col_names = T)
TS=read_xlsx(Sebastian, col_names = T)

StartM=data.frame()
StartF=data.frame()
StartS=data.frame()
StartTDLC1=data.frame()
EndM=data.frame()
EndF=data.frame()
EndS=data.frame()
EndDLC=data.frame()
SpeedM=data.frame()
SpeedF=data.frame()
SpeedS=data.frame()
SpeedDLC=data.frame()
ICCStart<-data.frame()
ICCEnd<-data.frame()
ICCSpeed<-data.frame()
ICCHLD<-data.frame()

cols<-c(ncol(TM), ncol(TF), ncol(TS), ncol(TDLC1))
TM=addcol(TM, max(cols))
TF=addcol(TF, max(cols))
TS=addcol(TS, max(cols))
TDLC1=addcol(TDLC1, max(cols))


for(i in 1:(nrow(TM)-1)){
  StartM[i,1]<-as.numeric(TM$Start[i+1])
  StartM[i,2]<-"M"
}
for(i in 1:(nrow(TF)-1)){
  StartF[i,1]<-as.numeric(TF$Start[i+1])
  StartF[i,2]<-"F"
}
for(i in 1:(nrow(TS)-1)){
  StartS[i,1]<-as.numeric(TS$Start[i+1])
  StartS[i,2]<-"S"
}
for(i in 1:(nrow(TDLC1)-1)){
  StartTDLC1[i,1]<-as.numeric(TDLC1$Start[i+1])
  StartTDLC1[i,2]<-"DLC"
}
for(i in 1:(nrow(TM)-1)){
  EndM[i,1]<-as.numeric(TM$End[i+1])
  EndM[i,2]<-"M"
}
for(i in 1:(nrow(TF)-1)){
  EndF[i,1]<-as.numeric(TF$End[i+1])
  EndF[i,2]<-"F"
}
for(i in 1:(nrow(TS)-1)){
  EndS[i,1]<-as.numeric(TS$End[i+1])
  EndS[i,2]<-"S"
}
for(i in 1:(nrow(TS)-1)){
  EndDLC[i,1]<-as.numeric(TDLC1$End[i+1])
  EndDLC[i,2]<-"DLC"
}
for(i in 1:(nrow(TM)-1)){
  SpeedM[i,1]<-as.numeric(TM$Speed[i+1])
  SpeedM[i,2]<-"M"
}
for(i in 1:(nrow(TF)-1)){
  SpeedF[i,1]<-as.numeric(TF$Speed[i+1])
  SpeedF[i,2]<-"F"
}
for(i in 1:(nrow(TS)-1)){
  SpeedS[i,1]<-as.numeric(TS$Speed[i+1])
  SpeedS[i,2]<-"S"
}
for(i in 1:(nrow(TDLC1)-1)){
  SpeedDLC[i,1]<-as.numeric(TDLC1$Speed[i+1])
  SpeedDLC[i,2]<-"DLC"
}

Start<-rbind(StartM, StartF, StartS, StartTDLC1)
End<-rbind(EndM, EndF, EndS, EndDLC)
Speed<-rbind(SpeedM, SpeedF, SpeedS, SpeedDLC)



agostino<-data.frame()
colnamesagostino<-c("Rater", "Start", "End", "Speed", "HLD")
for(i in colnamesagostino){agostino[[i]]<-as.character()}
for(i in 1:length(Rater)){agostino[i,1]=Rater[i]}
agostino[1,2]=round(agostino.test(as.numeric(TM$Start[2:nrow(TM)]))$p.value, digits = 4)
agostino[2,2]=round(agostino.test(as.numeric(TF$Start[2:nrow(TF)]))$p.value, digits = 4)
agostino[3,2]=round(agostino.test(as.numeric(TS$Start[2:nrow(TS)]))$p.value, digits = 4)
agostino[4,2]=round(agostino.test(as.numeric(TDLC1$Start[2:nrow(TDLC1)]))$p.value, digits = 4)
agostino[1,3]=round(agostino.test(as.numeric(TM$End[2:nrow(TM)]))$p.value, digits = 4)
agostino[2,3]=round(agostino.test(as.numeric(TF$End[2:nrow(TF)]))$p.value, digits = 4)
agostino[3,3]=round(agostino.test(as.numeric(TS$End[2:nrow(TS)]))$p.value, digits = 4)
agostino[4,3]=round(agostino.test(as.numeric(TDLC1$End[2:nrow(TDLC1)]))$p.value, digits = 4)
agostino[1,4]=round(agostino.test(as.numeric(TM$Speed[2:nrow(TM)]))$p.value, digits = 4)
agostino[2,4]=round(agostino.test(as.numeric(TF$Speed[2:nrow(TF)]))$p.value, digits = 4)
agostino[3,4]=round(agostino.test(as.numeric(TS$Speed[2:nrow(TS)]))$p.value, digits = 4)
agostino[4,4]=round(agostino.test(as.numeric(TDLC1$Speed[2:nrow(TDLC1)]))$p.value, digits = 4)
agostino[1,5]=round(agostino.test(as.numeric(HLDM[,1]))$p.value, digits = 4)
agostino[2,5]=round(agostino.test(as.numeric(HLDF[,1]))$p.value, digits = 4)
agostino[3,5]=round(agostino.test(as.numeric(HLDS[,1]))$p.value, digits = 4)
agostino[4,5]=round(agostino.test(as.numeric(HLDDLC[,1]))$p.value, digits = 4)
png(paste0(PicFolder, "p-values Normality Test D'Agostino"), height = 28*nrow(agostino), width = 50*ncol(agostino))
grid.table(agostino, rows=NULL)
dev.off()

VH<-data.frame()
colnamesVH<-c("Start", "End", "Speed", "HLD")
for(i in colnamesVH){VH[[i]]<-as.character()}
VH[1,1]=round(leveneTest(Start[,1], as.factor(Start[,2]))$`Pr(>F)`[1], digits = 4)
VH[1,2]=round(leveneTest(End[,1], as.factor(End[,2]))$`Pr(>F)`[1], digits = 4)
VH[1,3]=round(bartlett.test(Speed[,1], Speed[,2])$p.value, digits = 4)
VH[1,4]=round(leveneTest(HLD[,1], as.factor(HLD[,2]))$`Pr(>F)`[1], digits = 4)
png(paste0(PicFolder, "p-values Variance Homogeneity"), height = 45*nrow(VH), width = 50*ncol(VH))
grid.table(VH, rows=NULL)
dev.off()

cStartS1=cor.test(StartM$V1, StartF$V1, method="spearman")
cStartS2=cor.test(StartM$V1, StartS$V1, method="spearman")
cStartS3=cor.test(StartM$V1, StartTDLC1$V1, method="spearman")
cStartS4=cor.test(StartF$V1, StartS$V1, method="spearman")
cStartS5=cor.test(StartF$V1, StartTDLC1$V1, method="spearman")
cStartS6=cor.test(StartS$V1, StartTDLC1$V1, method="spearman")

cStartP1=cor.test(StartM$V1, StartF$V1, method="pearson")
cStartP2=cor.test(StartM$V1, StartS$V1, method="pearson")
cStartP3=cor.test(StartM$V1, StartTDLC1$V1, method="pearson")
cStartP4=cor.test(StartF$V1, StartS$V1, method="pearson")
cStartP5=cor.test(StartF$V1, StartTDLC1$V1, method="pearson")
cStartP6=cor.test(StartS$V1, StartTDLC1$V1, method="pearson")

cEndS1=cor.test(EndM$V1, EndF$V1, method="spearman")
cEndS2=cor.test(EndM$V1, EndS$V1, method="spearman")
cEndS3=cor.test(EndM$V1, EndDLC$V1, method="spearman")
cEndS4=cor.test(EndF$V1, EndS$V1, method="spearman")
cEndS5=cor.test(EndF$V1, EndDLC$V1, method="spearman")
cEndS6=cor.test(EndS$V1, EndDLC$V1, method="spearman")

cEndP1=cor.test(EndM$V1, EndF$V1, method="pearson")
cEndP2=cor.test(EndM$V1, EndS$V1, method="pearson")
cEndP3=cor.test(EndM$V1, EndDLC$V1, method="pearson")
cEndP4=cor.test(EndF$V1, EndS$V1, method="pearson")
cEndP5=cor.test(EndF$V1, EndDLC$V1, method="pearson")
cEndP6=cor.test(EndS$V1, EndDLC$V1, method="pearson")

cSpeed1=cor.test(SpeedM$V1, SpeedF$V1, method="pearson")
cSpeed2=cor.test(SpeedM$V1, SpeedS$V1, method="pearson")
cSpeed3=cor.test(SpeedM$V1, SpeedDLC$V1, method="pearson")
cSpeed4=cor.test(SpeedF$V1, SpeedS$V1, method="pearson")
cSpeed5=cor.test(SpeedF$V1, SpeedDLC$V1, method="pearson")
cSpeed6=cor.test(SpeedS$V1, SpeedDLC$V1, method="pearson")

cHLDS1=cor.test(HLDM[,1], HLDF[,1], method="spearman")
cHLDS2=cor.test(HLDM[,1], HLDS[,1], method="spearman")
cHLDS3=cor.test(HLDM[,1], HLDDLC[,1], method="spearman")
cHLDS4=cor.test(HLDF[,1], HLDS[,1], method="spearman")
cHLDS5=cor.test(HLDF[,1], HLDDLC[,1], method="spearman")
cHLDS6=cor.test(HLDS[,1], HLDDLC[,1], method="spearman")

cHLDP1=cor.test(HLDM[,1], HLDF[,1], method="pearson")
cHLDP2=cor.test(HLDM[,1], HLDS[,1], method="pearson")
cHLDP3=cor.test(HLDM[,1], HLDDLC[,1], method="pearson")
cHLDP4=cor.test(HLDF[,1], HLDS[,1], method="pearson")
cHLDP5=cor.test(HLDF[,1], HLDDLC[,1], method="pearson")
cHLDP6=cor.test(HLDS[,1], HLDDLC[,1], method="pearson")


for(i in 1:(nrow(TM)-1)){
  ICCStart[i,1]<-as.numeric(TM$Start[i+1])
  ICCStart[i,2]<-as.numeric(TF$Start[i+1])
  ICCStart[i,3]<-as.numeric(TS$Start[i+1])
  ICCStart[i,4]<-as.numeric(TDLC1$Start[i+1])
}
for(i in 1:(nrow(TM)-1)){
  ICCEnd[i,1]<-as.numeric(TM$End[i+1])
  ICCEnd[i,2]<-as.numeric(TF$End[i+1])
  ICCEnd[i,3]<-as.numeric(TS$End[i+1])
  ICCEnd[i,4]<-as.numeric(TDLC1$End[i+1])
}
for(i in 1:(nrow(TM)-1)){
  ICCSpeed[i,1]<-as.numeric(TM$Speed[i+1])
  ICCSpeed[i,2]<-as.numeric(TF$Speed[i+1])
  ICCSpeed[i,3]<-as.numeric(TS$Speed[i+1])
  ICCSpeed[i,4]<-as.numeric(TDLC1$Speed[i+1])
}
for(i in 1:(nrow(HLDM))){
  ICCHLD[i,1]<-as.numeric(HLDM[i,1])
  ICCHLD[i,2]<-as.numeric(HLDF[i,1])
  ICCHLD[i,3]<-as.numeric(HLDS[i,1])
  ICCHLD[i,4]<-as.numeric(HLDDLC[i,1])
}

ICC<-data.frame()
colnamesICC<-c("Start", "End", "Speed", "HLD")
for(i in colnamesICC){ICC[[i]]<-as.character()}
ICC[1,1]=round(icc(ICCStart, model="twoway", type="agreement", unit="single")$value, digits = 4)
ICC[2,1]=round(icc(ICCStart, model="twoway", type="agreement", unit="single")$p.value, digits = 6)
ICC[1,2]=round(icc(ICCEnd, model="twoway", type="agreement", unit="single")$value, digits = 4)
ICC[2,2]=round(icc(ICCEnd, model="twoway", type="agreement", unit="single")$p.value, digits = 6)
ICC[1,3]=round(icc(ICCSpeed, model="twoway", type="agreement", unit="single")$value, digits = 4)
ICC[2,3]=round(icc(ICCSpeed, model="twoway", type="agreement", unit="single")$p.value, digits = 6)
ICC[1,4]=round(icc(ICCHLD, model="twoway", type="agreement", unit="single")$value, digits = 4)
ICC[2,4]=round(icc(ICCHLD, model="twoway", type="agreement", unit="single")$p.value, digits = 6)
png(paste0(PicFolder, "Correlation values ICC"), height = 45*nrow(ICC), width = 50*ncol(ICC))
grid.table(ICC, rows=NULL)
dev.off()




Rater<-c("Rater_1", "Rater_2", "Rater_3", "DLC")
Rater2<-c("Rater_1", "Rater_2", "Rater_3", "DLC")
RvsRStart<-expand.grid(X=Rater, Y=Rater2)
RvsRStart$value<-c(1, cStartS1$estimate, cStartS2$estimate, cStartS3$estimate, cStartS1$estimate, 1, cStartS4$estimate, cStartS4$estimate, cStartS2$estimate, cStartS4$estimate, 1, cStartS6$estimate, cStartS3$estimate, cStartS5$estimate, cStartS6$estimate, 1)
ggplot(RvsRStart, aes(X, Y, fill= value)) + 
  geom_tile(aes(fill = value))+
  geom_text(aes(label = round(value, 3)), colour=("gray100"), size=9)+
  scale_colour_manual(values=c("gray100"))+
  scale_fill_gradient(limits=c(0,1))+
  theme(panel.background = element_blank(), axis.title=element_blank(), legend.position="none", text = element_text(size=25))
ggsave(paste0(PicFolder, "Spearman_Correlation_Start.png"))
StartSp<-data.frame()
Rater_1<-c(1, round(cStartS1$p.value, digits=5), round(cStartS2$p.value, digits=5), round(cStartS3$p.value, digits=5))
Rater_2<-c(0,1, round(cStartS4$p.value, digits=5), round(cStartS5$p.value, digits=5))
Rater_3<-c(0,0,1, round(cStartS5$p.value, digits=5))
DLC<-c(0,0,0,1)
StartSp<-rbind(StartSp, Rater_1, Rater_2, Rater_3, DLC)
StartSp=`row.names<-`(StartSp, Rater)
colnames(StartSp)<-c("Rater_1", "Rater_2", "Rater_3", "DLC")
png(paste0(PicFolder, "Start_Spearman_p-values.png"), height = 30*nrow(StartSp), width = 70*ncol(StartSp))
grid.table(StartSp, rows=NULL)
dev.off()

RvsRStart<-expand.grid(X=Rater, Y=Rater2)
RvsRStart$value<-c(1, cStartP1$estimate, cStartP2$estimate, cStartP3$estimate, cStartP1$estimate, 1, cStartP4$estimate, cStartP5$estimate, cStartP2$estimate, cStartP4$estimate, 1, cStartP6$estimate, cStartP3$estimate, cStartP5$estimate, cStartP6$estimate, 1)
ggplot(RvsRStart, aes(X, Y, fill= value)) + 
  geom_tile(aes(fill = value))+
  geom_text(aes(label = round(value, 3)), colour=("gray100"), size=9)+
  scale_colour_manual(values=c("gray100"))+
  scale_fill_gradient(limits=c(0,1))+
  theme(panel.background = element_blank(), axis.title=element_blank(), legend.position="none", text = element_text(size=25))
ggsave(paste0(PicFolder, "Pearson_Correlation_Start.png"))
StartPp<-data.frame()
Rater_1<-c(1, round(cStartP1$p.value, digits=5), round(cStartP2$p.value, digits=5), round(cStartP3$p.value, digits=5))
Rater_2<-c(0,1, round(cStartP4$p.value, digits=5), round(cStartP5$p.value, digits=5))
Rater_3<-c(0,0,1, round(cStartP5$p.value, digits=5))
DLC<-c(0,0,0,1)
StartPp<-rbind(StartPp, Rater_1, Rater_2, Rater_3, DLC)
StartPp=`row.names<-`(StartPp, Rater)
colnames(StartPp)<-c("Rater_1", "Rater_2", "Rater_3", "DLC")
png(paste0(PicFolder, "Start_Pearson_p-values.png"), height = 30*nrow(StartPp), width = 70*ncol(StartPp))
grid.table(StartPp, rows=NULL)
dev.off()

RvsREnd<-expand.grid(X=Rater, Y=Rater2)
RvsREnd$value<-c(1, cEndS1$estimate, cEndS2$estimate, cEndS3$estimate, cEndS1$estimate, 1, cEndS4$estimate, cEndS5$estimate, cEndS2$estimate, cEndS4$estimate, 1, cEndS6$estimate, cEndS3$estimate, cEndS5$estimate, cEndS6$estimate, 1)
ggplot(RvsREnd, aes(X, Y, fill= value))+ 
  geom_tile(aes(fill = value))+
  geom_text(aes(label = round(value, 3)), colour=("gray100"), size=9)+
  scale_colour_manual(values=c("gray100"))+
  scale_fill_gradient(limits=c(0,1))+
  theme(panel.background = element_blank(), axis.title=element_blank(), legend.position="none", text = element_text(size=25))
ggsave(paste0(PicFolder, "Spearman_Correlation_End.png"))
EndSp<-data.frame()
Rater_1<-c(1, round(cEndS1$p.value, digits=5), round(cEndS2$p.value, digits=5), round(cEndS3$p.value, digits=5))
Rater_2<-c(0,1, round(cEndS4$p.value, digits=5), round(cEndS5$p.value, digits=5))
Rater_3<-c(0,0,1, round(cEndS5$p.value, digits=5))
DLC<-c(0,0,0,1)
EndSp<-rbind(EndSp, Rater_1, Rater_2, Rater_3, DLC)
EndSp=`row.names<-`(EndSp, Rater)
colnames(EndSp)<-c("Rater_1", "Rater_2", "Rater_3", "DLC")
png(paste0(PicFolder, "End_Spearman_p-values.png"), height = 30*nrow(EndSp), width = 70*ncol(EndSp))
grid.table(EndSp, rows=NULL)
dev.off()


RvsREnd<-expand.grid(X=Rater, Y=Rater2)
RvsREnd$value<-c(1, cEndP1$estimate, cEndP2$estimate, cEndP3$estimate, cEndP1$estimate, 1, cEndP4$estimate, cEndP5$estimate, cEndP2$estimate, cEndP4$estimate, 1, cEndP6$estimate, cEndP3$estimate, cEndP5$estimate, cEndP6$estimate, 1)
ggplot(RvsREnd, aes(X, Y, fill= value))+ 
  geom_tile(aes(fill = value))+
  geom_text(aes(label = round(value, 3)), colour=("gray100"), size=9)+
  scale_colour_manual(values=c("gray100"))+
  scale_fill_gradient(limits=c(0,1))+
  theme(panel.background = element_blank(), axis.title=element_blank(), legend.position="none", text = element_text(size=25))
ggsave(paste0(PicFolder, "Pearson_Correlation_End.png"))
EndPp<-data.frame()
Rater_1<-c(1, round(cEndP1$p.value, digits=5), round(cEndP2$p.value, digits=5), round(cEndP3$p.value, digits=5))
Rater_2<-c(0,1, round(cEndP4$p.value, digits=5), round(cEndP5$p.value, digits=5))
Rater_3<-c(0,0,1, round(cEndP5$p.value, digits=5))
DLC<-c(0,0,0,1)
EndPp<-rbind(EndPp, Rater_1, Rater_2, Rater_3, DLC)
EndPp=`row.names<-`(EndPp, Rater)
colnames(EndPp)<-c("Rater_1", "Rater_2", "Rater_3", "DLC")
png(paste0(PicFolder, "End_Pearson_p-values.png"), height = 30*nrow(EndPp), width = 70*ncol(EndPp))
grid.table(EndPp, rows=NULL)
dev.off()


RvsRSpeed<-expand.grid(X=Rater, Y=Rater2)
RvsRSpeed$value<-c(1, cSpeed1$estimate, cSpeed2$estimate, cSpeed3$estimate, cSpeed1$estimate, 1, cSpeed4$estimate, cSpeed5$estimate, cSpeed2$estimate, cSpeed4$estimate, 1, cSpeed6$estimate, cSpeed3$estimate, cSpeed5$estimate, cSpeed6$estimate, 1)
ggplot(RvsRSpeed, aes(X, Y, fill= value))+ 
  geom_tile(aes(fill = value))+
  geom_text(aes(label = round(value, 3)), colour=("gray100"), size=9)+
  scale_colour_manual(values=c("gray100"))+
  scale_fill_gradient(limits=c(0,1))+
  theme(panel.background = element_blank(), axis.title=element_blank(), legend.position="none", text = element_text(size=25))
ggsave(paste0(PicFolder, "Pearson_Correlation_Speed.png"))
Speedp<-data.frame()
Rater_1<-c(1, round(cSpeed1$p.value, digits=5), round(cSpeed2$p.value, digits=5), round(cSpeed3$p.value, digits=5))
Rater_2<-c(0,1, round(cSpeed4$p.value, digits=5), round(cSpeed5$p.value, digits=5))
Rater_3<-c(0,0,1, round(cSpeed5$p.value, digits=5))
DLC<-c(0,0,0,1)
Speedp<-rbind(Speedp, Rater_1, Rater_2, Rater_3, DLC)
Speedp=`row.names<-`(Speedp, Rater)
colnames(Speedp)<-c("Rater_1", "Rater_2", "Rater_3", "DLC")
png(paste0(PicFolder, "Speed_Pearson_p-values.png"), height = 30*nrow(Speedp), width = 70*ncol(Speedp))
grid.table(Speedp, rows=NULL)
dev.off()


HLD<-data.frame()
HLDM<-data.frame()
HLDF<-data.frame()
HLDS<-data.frame()
HLDDLC<-data.frame()
for(i in 1:(nrow(TM)-1)){
  for(j in seq(8, max(cols), 2)){
    hld<-list(as.numeric(TM[i+1,j]), "M")
    HLDM=rbind(HLDM, hld)
  }
}
for(i in 1:(nrow(TF)-1)){
  for(j in seq(8, max(cols), 2)){
    hld<-list(as.numeric(TF[i+1,j]), "F")
    HLDF=rbind(HLDF, hld)
  }
}
for(i in 1:(nrow(TS)-1)){
  for(j in seq(8, max(cols), 2)){
    hld<-list(as.numeric(TS[i+1,j]), "S")
    HLDS=rbind(HLDS, hld)
  }
}
for(i in 2:(nrow(TDLC1))){
  for(j in 8:(8+((max(cols)-8)/2))){
    hld<-list(as.numeric(TDLC1[i,j]), "DLC")
    HLDDLC=rbind(HLDDLC, hld)
  }
}
colnames(HLDM)<-c(1,2)
colnames(HLDF)<-c(1,2)
colnames(HLDS)<-c(1,2)
colnames(HLDDLC)<-c(1,2)
HLD<-rbind(HLDM, HLDF, HLDS, HLDDLC)
cHLDS1=cor.test(HLDM[,1], HLDF[,1], method="spearman")
cHLDS2=cor.test(HLDM[,1], HLDS[,1], method="spearman")
cHLDS3=cor.test(HLDM[,1], HLDDLC[,1], method="spearman")
cHLDS4=cor.test(HLDF[,1], HLDS[,1], method="spearman")
cHLDS5=cor.test(HLDF[,1], HLDDLC[,1], method="spearman")
cHLDS6=cor.test(HLDS[,1], HLDDLC[,1], method="spearman")

cHLDP1=cor.test(HLDM[,1], HLDF[,1], method="pearson")
cHLDP2=cor.test(HLDM[,1], HLDS[,1], method="pearson")
cHLDP3=cor.test(HLDM[,1], HLDDLC[,1], method="pearson")
cHLDP4=cor.test(HLDF[,1], HLDS[,1], method="pearson")
cHLDP5=cor.test(HLDF[,1], HLDDLC[,1], method="pearson")
cHLDP6=cor.test(HLDS[,1], HLDDLC[,1], method="pearson")
RvsRHLD<-expand.grid(X=Rater, Y=Rater2)
RvsRHLD$value<-c(1, cHLDS1$estimate, cHLDS2$estimate, cHLDS3$estimate, cHLDS1$estimate, 1, cHLDS4$estimate, cHLDS5$estimate, cHLDS2$estimate, cHLDS4$estimate, 1, cHLDS6$estimate, cHLDS3$estimate, cHLDS5$estimate, cHLDS6$estimate, 1)
ggplot(RvsRHLD, aes(X, Y, fill= value))+ 
  geom_tile(aes(fill = value))+
  geom_text(aes(label = round(value, 3)), colour=("gray100"), size=9)+
  scale_colour_manual(values=c("gray100"))+
  scale_fill_gradient(limits=c(0,1))+
  theme(panel.background = element_blank(), axis.title=element_blank(), legend.position="none", text = element_text(size=25))
ggsave(paste0(PicFolder, "Spearman_Correlation_HLD1.png"))
HLDSp<-data.frame()
Rater_1<-c(1, round(cHLDS1$p.value, digits=5), round(cHLDS2$p.value, digits=5), round(cHLDS3$p.value, digits=5))
Rater_2<-c(0,1, round(cHLDS4$p.value, digits=5), round(cHLDS5$p.value, digits=5))
Rater_3<-c(0,0,1, round(cHLDS5$p.value, digits=5))
DLC<-c(0,0,0,1)
HLDSp<-rbind(HLDSp, Rater_1, Rater_2, Rater_3, DLC)
HLDSp=`row.names<-`(HLDSp, Rater)
colnames(HLDSp)<-c("Rater_1", "Rater_2", "Rater_3", "DLC")
png(paste0(PicFolder, "HLD_Spearman_p-values_1.png"), height = 30*nrow(HLDSp), width = 70*ncol(HLDSp))
grid.table(HLDSp, rows=NULL)
dev.off()

RvsRHLD<-expand.grid(X=Rater, Y=Rater2)
RvsRHLD$value<-c(1, cHLDP1$estimate, cHLDP2$estimate, cHLDP3$estimate, cHLDP1$estimate, 1, cHLDP4$estimate, cHLDP5$estimate, cHLDP2$estimate, cHLDP4$estimate, 1, cHLDP6$estimate, cHLDP3$estimate, cHLDP5$estimate, cHLDP6$estimate, 1)
ggplot(RvsRHLD, aes(X, Y, fill= value))+ 
  geom_tile(aes(fill = value))+
  geom_text(aes(label = round(value, 3)), colour=("gray100"), size=9)+
  scale_colour_manual(values=c("gray100"))+
  scale_fill_gradient(limits=c(0,1))+
  theme(panel.background = element_blank(), axis.title=element_blank(), legend.position="none", text = element_text(size=25))
ggsave(paste0(PicFolder, "Pearson_Correlation_HLD1.png"))
HLDPp<-data.frame()
Rater_1<-c(1, round(cHLDP1$p.value, digits=5), round(cHLDP2$p.value, digits=5), round(cHLDP3$p.value, digits=5))
Rater_2<-c(0,1, round(cHLDP4$p.value, digits=5), round(cHLDP5$p.value, digits=5))
Rater_3<-c(0,0,1, round(cHLDP5$p.value, digits=5))
DLC<-c(0,0,0,1)
HLDPp<-rbind(HLDPp, Rater_1, Rater_2, Rater_3, DLC)
HLDPp=`row.names<-`(HLDPp, Rater)
colnames(HLDPp)<-c("Rater_1", "Rater_2", "Rater_3", "DLC")
png(paste0(PicFolder, "HLD_Pearson_p-values_1.png"), height = 30*nrow(HLDPp), width = 70*ncol(HLDPp))
grid.table(HLDPp, rows=NULL)
dev.off()

HLD<-data.frame()
HLDM<-data.frame()
HLDF<-data.frame()
HLDS<-data.frame()
HLDDLC<-data.frame()
for(i in 1:(nrow(TM)-1)){
  for(j in seq(8, max(cols), 2)){
    hld<-list(as.numeric(TM[i+1,j]), "M")
    HLDM=rbind(HLDM, hld)
  }
}
for(i in 1:(nrow(TF)-1)){
  for(j in seq(8, max(cols), 2)){
    hld<-list(as.numeric(TF[i+1,j]), "F")
    HLDF=rbind(HLDF, hld)
  }
}
for(i in 1:(nrow(TS)-1)){
  for(j in seq(8, max(cols), 2)){
    hld<-list(as.numeric(TS[i+1,j]), "S")
    HLDS=rbind(HLDS, hld)
  }
}
for(i in 2:(nrow(TDLC1))){
  for(j in 8:(8+((max(cols)-8)/2))){
    hld<-list(as.numeric(TDLC1[i,j]), "DLC")
    HLDDLC=rbind(HLDDLC, hld)
  }
}
colnames(HLDM)<-c(1,2)
colnames(HLDF)<-c(1,2)
colnames(HLDS)<-c(1,2)
colnames(HLDDLC)<-c(1,2)
HLDRater<-list(HLDM, HLDF, HLDS, HLDDLC)
lengthmean<-c()
for(e in 1:length(DLCnames)){
  lengthmean[e]=nrow(DLCnames[[e]])
}
for(g in 1:length(HLDRater)){
  for(h in 1:nrow(HLDRater[[g]])){
    for(f in 1:length(HLDRater)){
      if(is.na(HLDRater[[g]][h,1])==F && is.na(HLDRater[[f]][h,1])==T){
        HLDRater[[f]][h,1]<-0
      }
    }
  }
}
HLDM<-HLDRater[[1]]
HLDF<-HLDRater[[2]]
HLDS<-HLDRater[[3]]
HLDDLC<-HLDRater[[4]]
HLD<-rbind(HLDM, HLDF, HLDS, HLDDLC)
cHLDS1=cor.test(HLDM[,1], HLDF[,1], method="spearman")
cHLDS2=cor.test(HLDM[,1], HLDS[,1], method="spearman")
cHLDS3=cor.test(HLDM[,1], HLDDLC[,1], method="spearman")
cHLDS4=cor.test(HLDF[,1], HLDS[,1], method="spearman")
cHLDS5=cor.test(HLDF[,1], HLDDLC[,1], method="spearman")
cHLDS6=cor.test(HLDS[,1], HLDDLC[,1], method="spearman")

cHLDP1=cor.test(HLDM[,1], HLDF[,1], method="pearson")
cHLDP2=cor.test(HLDM[,1], HLDS[,1], method="pearson")
cHLDP3=cor.test(HLDM[,1], HLDDLC[,1], method="pearson")
cHLDP4=cor.test(HLDF[,1], HLDS[,1], method="pearson")
cHLDP5=cor.test(HLDF[,1], HLDDLC[,1], method="pearson")
cHLDP6=cor.test(HLDS[,1], HLDDLC[,1], method="pearson")
RvsRHLD<-expand.grid(X=Rater, Y=Rater2)
RvsRHLD$value<-c(1, cHLDS1$estimate, cHLDS2$estimate, cHLDS3$estimate, cHLDS1$estimate, 1, cHLDS4$estimate, cHLDS5$estimate, cHLDS2$estimate, cHLDS4$estimate, 1, cHLDS6$estimate, cHLDS3$estimate, cHLDS5$estimate, cHLDS6$estimate, 1)
ggplot(RvsRHLD, aes(X, Y, fill= value))+ 
  geom_tile(aes(fill = value))+
  geom_text(aes(label = round(value, 3)), colour=("gray100"), size=9)+
  scale_colour_manual(values=c("gray100"))+
  scale_fill_gradient(limits=c(0,1))+
  theme(panel.background = element_blank(), axis.title=element_blank(), legend.position="none", text = element_text(size=25))
ggsave(paste0(PicFolder, "Spearman_Correlation_HLD2.png"))
HLDSp<-data.frame()
Rater_1<-c(1, round(cHLDS1$p.value, digits=5), round(cHLDS2$p.value, digits=5), round(cHLDS3$p.value, digits=5))
Rater_2<-c(0,1, round(cHLDS4$p.value, digits=5), round(cHLDS5$p.value, digits=5))
Rater_3<-c(0,0,1, round(cHLDS5$p.value, digits=5))
DLC<-c(0,0,0,1)
HLDSp<-rbind(HLDSp, Rater_1, Rater_2, Rater_3, DLC)
HLDSp=`row.names<-`(HLDSp, Rater)
colnames(HLDSp)<-c("Rater_1", "Rater_2", "Rater_3", "DLC")
png(paste0(PicFolder, "HLD_Spearman_p-values_2.png"), height = 30*nrow(HLDSp), width = 70*ncol(HLDSp))
grid.table(HLDSp, rows=NULL)
dev.off()

RvsRHLD<-expand.grid(X=Rater, Y=Rater2)
RvsRHLD$value<-c(1, cHLDP1$estimate, cHLDP2$estimate, cHLDP3$estimate, cHLDP1$estimate, 1, cHLDP4$estimate, cHLDP5$estimate, cHLDP2$estimate, cHLDP4$estimate, 1, cHLDP6$estimate, cHLDP3$estimate, cHLDP5$estimate, cHLDP6$estimate, 1)
ggplot(RvsRHLD, aes(X, Y, fill= value))+ 
  geom_tile(aes(fill = value))+
  geom_text(aes(label = round(value, 3)), colour=("gray100"), size=9)+
  scale_colour_manual(values=c("gray100"))+
  scale_fill_gradient(limits=c(0,1))+
  theme(panel.background = element_blank(), axis.title=element_blank(), legend.position="none", text = element_text(size=25))
ggsave(paste0(PicFolder, "Pearson_Correlation_HLD2.png"))
HLDPp<-data.frame()
Rater_1<-c(1, round(cHLDP1$p.value, digits=5), round(cHLDP2$p.value, digits=5), round(cHLDP3$p.value, digits=5))
Rater_2<-c(0,1, round(cHLDP4$p.value, digits=5), round(cHLDP5$p.value, digits=5))
Rater_3<-c(0,0,1, round(cHLDP5$p.value, digits=5))
DLC<-c(0,0,0,1)
HLDPp<-rbind(HLDPp, Rater_1, Rater_2, Rater_3, DLC)
HLDPp=`row.names<-`(HLDPp, Rater)
colnames(HLDPp)<-c("Rater_1", "Rater_2", "Rater_3", "DLC")
png(paste0(PicFolder, "HLD_Pearson_p-values_2.png"), height = 30*nrow(HLDPp), width = 70*ncol(HLDPp))
grid.table(HLDPp, rows=NULL)
dev.off()

HLD<-data.frame()
HLDM<-data.frame()
HLDF<-data.frame()
HLDS<-data.frame()
HLDDLC<-data.frame()
for(i in 1:(nrow(TM)-1)){
  for(j in seq(8, max(cols), 2)){
    hld<-list(as.numeric(TM[i+1,j]), "M")
    HLDM=rbind(HLDM, hld)
  }
}
for(i in 1:(nrow(TF)-1)){
  for(j in seq(8, max(cols), 2)){
    hld<-list(as.numeric(TF[i+1,j]), "F")
    HLDF=rbind(HLDF, hld)
  }
}
for(i in 1:(nrow(TS)-1)){
  for(j in seq(8, max(cols), 2)){
    hld<-list(as.numeric(TS[i+1,j]), "S")
    HLDS=rbind(HLDS, hld)
  }
}
for(i in 2:(nrow(TDLC1))){
  for(j in 8:(8+((max(cols)-8)/2))){
    hld<-list(as.numeric(TDLC1[i,j]), "DLC")
    HLDDLC=rbind(HLDDLC, hld)
  }
}
colnames(HLDM)<-c(1,2)
colnames(HLDF)<-c(1,2)
colnames(HLDS)<-c(1,2)
colnames(HLDDLC)<-c(1,2)
HLDRater<-list(HLDM, HLDF, HLDS, HLDDLC)
lengthmean<-c()
for(e in 1:length(DLCnames)){
  lengthmean[e]=nrow(DLCnames[[e]])
}
for(g in 1:length(HLDRater)){
  for(h in 1:nrow(HLDRater[[g]])){
    for(f in 1:length(HLDRater)){
      if(is.na(HLDRater[[g]][h,1])==F && is.na(HLDRater[[f]][h,1])==T){
        HLDRater[[f]][h,1]<-mean(lengthmean)
      }
    }
  }
}
HLDM<-HLDRater[[1]]
HLDF<-HLDRater[[2]]
HLDS<-HLDRater[[3]]
HLDDLC<-HLDRater[[4]]
HLD<-rbind(HLDM, HLDF, HLDS, HLDDLC)
cHLDS1=cor.test(HLDM[,1], HLDF[,1], method="spearman")
cHLDS2=cor.test(HLDM[,1], HLDS[,1], method="spearman")
cHLDS3=cor.test(HLDM[,1], HLDDLC[,1], method="spearman")
cHLDS4=cor.test(HLDF[,1], HLDS[,1], method="spearman")
cHLDS5=cor.test(HLDF[,1], HLDDLC[,1], method="spearman")
cHLDS6=cor.test(HLDS[,1], HLDDLC[,1], method="spearman")

cHLDP1=cor.test(HLDM[,1], HLDF[,1], method="pearson")
cHLDP2=cor.test(HLDM[,1], HLDS[,1], method="pearson")
cHLDP3=cor.test(HLDM[,1], HLDDLC[,1], method="pearson")
cHLDP4=cor.test(HLDF[,1], HLDS[,1], method="pearson")
cHLDP5=cor.test(HLDF[,1], HLDDLC[,1], method="pearson")
cHLDP6=cor.test(HLDS[,1], HLDDLC[,1], method="pearson")
RvsRHLD<-expand.grid(X=Rater, Y=Rater2)
RvsRHLD$value<-c(1, cHLDS1$estimate, cHLDS2$estimate, cHLDS3$estimate, cHLDS1$estimate, 1, cHLDS4$estimate, cHLDS5$estimate, cHLDS2$estimate, cHLDS4$estimate, 1, cHLDS6$estimate, cHLDS3$estimate, cHLDS5$estimate, cHLDS6$estimate, 1)
ggplot(RvsRHLD, aes(X, Y, fill= value))+ 
  geom_tile(aes(fill = value))+
  geom_text(aes(label = round(value, 3)), colour=("gray100"), size=9)+
  scale_colour_manual(values=c("gray100"))+
  scale_fill_gradient(limits=c(0,1))+
  theme(panel.background = element_blank(), axis.title=element_blank(), legend.position="none", text = element_text(size=25))
ggsave(paste0(PicFolder, "Spearman_Correlation_HLD3.png"))
HLDSp<-data.frame()
Rater_1<-c(1, round(cHLDS1$p.value, digits=5), round(cHLDS2$p.value, digits=5), round(cHLDS3$p.value, digits=5))
Rater_2<-c(0,1, round(cHLDS4$p.value, digits=5), round(cHLDS5$p.value, digits=5))
Rater_3<-c(0,0,1, round(cHLDS5$p.value, digits=5))
DLC<-c(0,0,0,1)
HLDSp<-rbind(HLDSp, Rater_1, Rater_2, Rater_3, DLC)
HLDSp=`row.names<-`(HLDSp, Rater)
colnames(HLDSp)<-c("Rater_1", "Rater_2", "Rater_3", "DLC")
png(paste0(PicFolder, "HLD_Spearman_p-values_3.png"), height = 30*nrow(HLDSp), width = 70*ncol(HLDSp))
grid.table(HLDSp, rows=NULL)
dev.off()

RvsRHLD<-expand.grid(X=Rater, Y=Rater2)
RvsRHLD$value<-c(1, cHLDP1$estimate, cHLDP2$estimate, cHLDP3$estimate, cHLDP1$estimate, 1, cHLDP4$estimate, cHLDP5$estimate, cHLDP2$estimate, cHLDP4$estimate, 1, cHLDP6$estimate, cHLDP3$estimate, cHLDP5$estimate, cHLDP6$estimate, 1)
ggplot(RvsRHLD, aes(X, Y, fill= value))+ 
  geom_tile(aes(fill = value))+
  geom_text(aes(label = round(value, 3)), colour=("gray100"), size=9)+
  scale_colour_manual(values=c("gray100"))+
  scale_fill_gradient(limits=c(0,1))+
  theme(panel.background = element_blank(), axis.title=element_blank(), legend.position="none", text = element_text(size=25))
ggsave(paste0(PicFolder, "Pearson_Correlation_HLD3.png"))
HLDPp<-data.frame()
Rater_1<-c(1, round(cHLDP1$p.value, digits=5), round(cHLDP2$p.value, digits=5), round(cHLDP3$p.value, digits=5))
Rater_2<-c(0,1, round(cHLDP4$p.value, digits=5), round(cHLDP5$p.value, digits=5))
Rater_3<-c(0,0,1, round(cHLDP5$p.value, digits=5))
DLC<-c(0,0,0,1)
HLDPp<-rbind(HLDPp, Rater_1, Rater_2, Rater_3, DLC)
HLDPp=`row.names<-`(HLDPp, Rater)
colnames(HLDPp)<-c("Rater_1", "Rater_2", "Rater_3", "DLC")
png(paste0(PicFolder, "HLD_Pearson_p-values_3.png"), height = 30*nrow(HLDPp), width = 70*ncol(HLDPp))
grid.table(HLDPp, rows=NULL)
dev.off()