R/auto.analyses.coral.R
In Alexmerciere/RespiroRS: Respirometry data analyses
Defines functions
auto.analyses.coral
auto.analyses.coral<-function(Data,Datablank,Volcoral,position,ID,blankposition,wayout,startday,endday,Nnoise=NULL,Nnoiseblk=NULL,correctFirstendslope=NULL,Nnoisestartdev=NULL,equalVolume=NULL,buffertime=NULL,acclimatationtime=NULL){
if (is.null(Nnoise)) {Nnoise<- 5 }
if (is.null(Nnoise)) {Nnoiseblk<- 5 }
if (is.null(correctFirstendslope)) { chamberfirstslope <-1 }
if (!is.null(correctFirstendslope)) { chamberfirstslope <-correctFirstendslope }
if (is.null(Nnoisestartdev)) {Nnoisestartdev<- 2 }
if (is.null(equalVolume)) {equalVolume<- T }
if (is.null(buffertime)) {buffertime<- 3600 }
if (is.null(acclimatationtime)) {acclimatationtime<- 0 }
ifelse (blankposition==1,deltaBlankposition<-1,deltaBlankposition<-0)
ifelse (chamberfirstslope==1,corfirstslope<-0,corfirstslope<-chamberfirstslope-1)
#################Experiment Settings##############
##fish record
closetime <- as.numeric(readline(prompt="closetime (s): ")) #s
opentime <- as.numeric(readline(prompt="opentime (s): ")) #s
waittime <- as.numeric(readline(prompt="waittime (s): ")) #s
enddiscard <- as.numeric(readline(prompt="enddiscard (s): ")) #s
ifelse (equalVolume==F,{ChamberVolume <- as.numeric(unlist(strsplit(readline(prompt="list of Chambers Volumes (L): "), ","))) }, {ChamberVolume <- as.numeric(readline(prompt="Chamber Volume (L): "));ChamberVolume <- rep(ChamberVolume,length(position)+1)})
#ChamberVolume <- as.numeric(readline(prompt="ChamberVolume (L): ")) #L
##blank record
closetimeblc <- as.numeric(readline(prompt="closetimeblank (s): ")) #s
opentimeblc <- as.numeric(readline(prompt="opentimeblank (s): ")) #s
waittimeblc <- as.numeric(readline(prompt="waittimeblank (s): ")) #s
enddiscardblc <- as.numeric(readline(prompt="enddiscardblank (s): ")) #s
nsdevsrsquared<-2
unit<-"mg/L"
O2column<-c(4,5,6,7,13,14,15,16,22,23,24,25,31,32,33,34)
Tempcolumn<-c(8,9,10,11,17,18,19,20,26,27,28,29,35,36,37,38)
period<-opentime+closetime
measureperiod<-closetime-waittime-enddiscard
periodblc<-opentimeblc+closetimeblc
measureperiodblc<-closetimeblc-waittimeblc-enddiscardblc
ifelse(chamberfirstslope==1,adustfirstslope<-0, adustfirstslope<-chamberfirstslope*(period/2))
timecolumn<-grep("Timeabsolu2", colnames(Data))
numdmyhms<-grep("dmyhms", colnames(Data))
Data<-arrange(Data, Timeabsolu2)
############################File with Fish record######################
#########Moving average############
testdata<-data.frame(subset(Data,Timeabsolu2<10000))
testdata<-na.omit(testdata[,c(timecolumn,O2column[chamberfirstslope])])
testdata$movavg<-movavg(testdata[,2],13,type=c("s"))
##Calculate dif
testdata$dif<-NA
for (row in 1:nrow(testdata)){
ifelse(testdata[row,1]>testdata[1,1]+99+adustfirstslope & testdata[row,1]<testdata[1,1]+4900+adustfirstslope,testdata[row,4]<-(testdata[(row+50),3]-testdata[row,3]-(testdata[row,3]-testdata[(row-50),3])),testdata[row,4]<-NA)
}
##graphic dif
c<-ggplot(testdata)+geom_point(aes(x=Timeabsolu2,y=dif))
print(c)
##noise
noise<-sd(na.omit(subset(Data,Timeabsolu2>testdata[1,1]+100&Timeabsolu2<testdata[1,1]+200)[,O2column[chamberfirstslope]]))
print(noise)
##Find first endslope
Toppos<-list()
for (row in 1:nrow(testdata)){
ifelse(testdata[row,1]>testdata[1,1]+99+adustfirstslope & testdata[row,1]<testdata[1,1]+1900+adustfirstslope,ifelse(testdata[row,4]>testdata[(row-1),4] & testdata[row,4]>testdata[(row-5),4] & testdata[row,4]>testdata[(row-7),4] & testdata[row,4]>testdata[(row+1),4] & testdata[row,4]>testdata[(row+5),4] & testdata[row,4]>testdata[(row+7),4] & testdata[row,4]>(Nnoise*noise),Toppos<-list.append(Toppos,testdata[row,1]),NA),NA)
}
#Time of the first end slope
Firstend<-as.numeric(Toppos[[1]])
print(Firstend)
#graph with end slope
c<-ggplot(Data,environment = environment())+geom_point(aes(x=Timeabsolu2,y=Data[,O2column[chamberfirstslope]]))+ylab(paste(colnames(Data[O2column[chamberfirstslope]]),unit)) +xlab("Time (sec)")+xlim(testdata[1,1],testdata[1,1]+10000) +
geom_vline(aes(xintercept = Firstend),color="red")
print(c)
ggsave(c,filename="firstslope.pdf",path = wayout,width=20, height=4)
question2 <- readline(prompt="First end slope is at the good position ?(YES or NO) : ")
ifelse(question2=="YES",NA,{nperiod <-as.numeric(readline(prompt="How many periode do you want add (+) or delete (-) ? "));
Firstend<-(nperiod*period)+Firstend;
print(Firstend);
c<-ggplot(Data,environment = environment())+geom_point(aes(x=Timeabsolu2,y=Data[,O2column[chamberfirstslope]]))+ylab(paste(colnames(Data[O2column[chamberfirstslope]]),unit)) +xlab("Time (sec)")+xlim(testdata[1,1],testdata[1,1]+10000) +geom_vline(aes(xintercept = Firstend),color="red") ;
ggsave(c,filename="firstslopecorrected.pdf",path = wayout,width=20, height=4);NA})
Firstend<-Firstend-(corfirstslope*period)
firstmidpoint<-Firstend-enddiscard-(measureperiod/2)
wholeperiods<-(max(na.omit(Data$Timeabsolu2))-firstmidpoint)/period
numberoflowvalues<-wholeperiods/10 ####10 pourcent of point
numbperiods<-round(wholeperiods)
###########################################################################################################
####################################File with Fishblank record#############################################
#########Moving average############
testdata<-Datablank[1:1000,]
testdata<-na.omit(testdata[,c(timecolumn,O2column[position[1]])])
library("pracma", lib.loc="/Library/Frameworks/R.framework/Versions/3.0/Resources/library")
testdata$movavg<-movavg(testdata[,2],13,type=c("s"))
##Calculate dif
testdata$dif<-NA
for (x in c(51:950)){
testdata[x,4]<-(testdata[(x+50),3]-testdata[x,3]-(testdata[x,3]-testdata[(x-50),3]))
}
##graphic dif
ggplot(testdata)+geom_point(aes(x=Timeabsolu2,y=dif))
##noise
noise<-sd(testdata[c(51:100),4])
print(noise)
##Find first endslope
Toppos<-list()
for (row in c(51:950)){
ifelse(testdata[row,4]>testdata[(row-1),4] & testdata[row,4]>testdata[(row-5),4] & testdata[row,4]>testdata[(row-7),4] & testdata[row,4]>testdata[(row+1),4] & testdata[row,4]>testdata[(row+5),4] & testdata[row,4]>testdata[(row+7),4] & testdata[row,4]>(Nnoiseblk*noise),Toppos<-list.append(Toppos,testdata[row,1]),NA)
}
#Time of the first end slope
Firstendblank<-as.numeric(Toppos[[1]])
print(Firstendblank)
#graph with end slope and mean temperature during experiment
c<-ggplot(Datablank,environment = environment())+geom_point(aes(x=Timeabsolu2,y=Datablank[,O2column[position[1]]]))+ylab(paste(colnames(Datablank[O2column[position[1]]]),unit)) +xlab("Time (sec)") + geom_vline(aes(xintercept = Firstendblank,color="red"))
print(c)
ggsave(c,filename="firstslopeblank.pdf",path = wayout,width=20, height=4)
ifelse(question1<-"YES",NA,{Firstendblank <-as.numeric(readline(prompt="Give a new value of First end "))+Firstendblank;c<-ggplot(Datablank,environment = environment())+geom_point(aes(x=Timeabsolu2,y=Datablank[,4]))+ylab(paste(colnames(Datablank[4]),unit)) +xlab("Time (sec)") + geom_vline(aes(xintercept = Firstendblank,color="red"));ggsave(c,filename="firstslopeblankcorrected.pdf",path = wayout,width=20, height=4)})
question1 <- readline(prompt="First end slope blank is at the good position ?(YES or NO) : ")
ifelse(question1=="YES",NA,{nperiod <-as.numeric(readline(prompt="How many periode do you want add (+) or delete (-) ? "));
Firstendblank<-(nperiod*periodblc)+Firstendblank;
print(Firstendblank);
c<-ggplot(Datablank,environment = environment())+geom_point(aes(x=Timeabsolu2,y=Datablank[,4]))+ylab(paste(colnames(Datablank[4]),unit)) +xlab("Time (sec)") + geom_vline(aes(xintercept = Firstendblank,color="red"))
ggsave(c,filename="firstslopeblankcorrected.pdf",path = wayout,width=20, height=4);NA})
firstmidpointblank<-Firstendblank-enddiscardblc-(measureperiodblc/2)
###########################################################################################################
####################################RESULT CHAMBER BLANK######################################################
res<-data.frame(matrix(ncol=10,nrow=0))
colnames(res)<- c("MidTime (sec)", "StartTime (sec)", "EndTime (sec)","linear coeff","MO2 (mg/h)","Temp(°C)","Date","SE","p-value","Rsquared")
numbperiods<-round(wholeperiods)-(blankposition-1) + deltaBlankposition
##Create table with mid time measurment, start and end per chamber
for (i in 1:numbperiods){
res[i,1]<-firstmidpoint+(i-1+(blankposition-1))*period -(deltaBlankposition*period) #### blank chamber position to find start firstmid slope
res[i,2]<-res[i,1]-(measureperiod/2)
res[i,3]<-res[i,1]+(measureperiod/2)
merge(res,Data[,c(numdmyhms,timecolumn)],by.x="MidTime (sec)",by.y="Timeabsolu2",all.x = T)
Datachamberindv<-na.omit(Data[,c(timecolumn,O2column[blankposition],Tempcolumn[blankposition],1)])
linearreg<-subset(Datachamberindv, Datachamberindv$Timeabsolu2>=res[i,2] & Datachamberindv$Timeabsolu2<=res[i,3])
b<-lm(linearreg[,2]~linearreg[,1])
res[i,4]<-b$coefficients[2]
res[i,5]<-(-b$coefficients[2]*(ChamberVolume[blankposition])*3600)
res[i,6]<-Datachamberindv[i,3]
res[i,7]<-as.character(Datachamberindv[1,4])
res[i,8]<-summary(b)$coefficients["linearreg[, 1]","Std. Error"]
res[i,9]<-summary(b)$coefficients["linearreg[, 1]","Pr(>|t|)"]
res[i,10]<-summary(b)$r.squared
}
e<-lm(res[,5] ~ poly(res[,1], 4, raw=TRUE))
polyblank <- function(x) {e$coefficient[5]*x^4 + e$coefficient[4]*x^3 + e$coefficient[3]*x^2 + e$coefficient[2]*x + e$coefficient[1]}
res$Poly<-polyblank(res[,1])
c<-ggplot(res,environment = environment())+geom_point(aes(x=res[,1]/3600,y=res[,5]))+ylab(colnames(res[5])) +xlab("Time (h)")+ stat_smooth(aes(x=res[,1]/3600,y=res[,5]),method="lm", se=TRUE, fill=NA,formula=y ~ poly(x, 4, raw=TRUE),colour="blue") +geom_point(aes(x=res[,1]/3600,y=res[,11],colour="red"))
Resultblank<-res
write.table(Resultblank, paste(wayout, "/resultchamberblank.csv", sep = ""), sep = ";", dec = ".", row.names = F, qmethod = "double")
ggsave(c,filename="Blank.pdf",path = wayout,width=20, height=4)
print(c)
#################SLOPE BLANK RESPIRATION##############
#######################################Find start of slope deviation##################################
noise<-sd(Resultblank[c(1:10),5])
mean<-mean(Resultblank[c(1:10),5])
Toppos<-list()
for (row in 1:nrow(Resultblank)){
ifelse(Resultblank[row,11]>mean+Nnoisestartdev*noise,Toppos<-list.append(Toppos,Resultblank[row,1]),NA)
}
#Time of the start slope deviation
Firststart<-as.numeric(Toppos[1])
print(Firststart)
c<-ggplot(Resultblank,environment=environment())+geom_point(aes(x=Resultblank[,1]/3600,y=Resultblank[,5]))+ylab(paste(colnames(Resultblank[5]))) +xlab("Time (sec)")+geom_point(aes(x=Resultblank[,1]/3600,y=Resultblank[,11],colour="red"))+ geom_vline(aes(xintercept =Firststart/3600 ,color="red"))
ggsave(c,filename="Blank_slope_start.pdf",path = wayout,width=20, height=4)
print(c)
########################################################################################
####################################RESULT CHAMBER FISH###############################################
Result<-data.frame(matrix(ncol=13,nrow=0))
colnames(Result)<- c("ID","Date", "Chamber","MinMRDay","sdMinMRDay","MaxMRNight","sdMaxMRNight","MeanMRDay","MeanMRNight","PhotoProduction","MeanTemp (°C)","Volume (L)","Chamber Volume (L)")
for (l in position){
res<-data.frame(matrix(ncol=11,nrow=0))
colnames(res)<- c("MidTime (sec)", "StartTime (sec)", "EndTime (sec)","linear coeff","MO2 (mg/h)","Temp(°C)","Date","SE","p-value","Rsquared","MO2cor")
numbperiods<-round(wholeperiods)-(position[l]-1) - deltaBlankposition
resblc<-data.frame(matrix(ncol=11,nrow=0))
colnames(resblc)<- c("MidTime (sec)", "StartTime (sec)", "EndTime (sec)","linear coeff","MO2 (mg/h)","Temp(°C)","Date","SE","p-value","Rsquared","MO2cor")
##Record Fish Chamber
##Create table with mid time measurment, start and end per chamber
for (i in 1:numbperiods){
res[i,1]<-firstmidpoint+(i-1+(l-1))*period -(deltaBlankposition*period)###remove l-1 if you start all the chamber in the same time
res[i,2]<-res[i,1]-(measureperiod/2)
res[i,3]<-res[i,1]+(measureperiod/2)
Datachamberindv<-na.omit(Data[,c(timecolumn,O2column[l],Tempcolumn[l],1)])
linearreg<-subset(Datachamberindv, Datachamberindv$Timeabsolu2>=res[i,2] & Datachamberindv$Timeabsolu2<=res[i,3])
b<-lm(linearreg[,2]~linearreg[,1])
res[i,4]<-b$coefficients[2]
res[i,5]<-(-b$coefficients[2]*(ChamberVolume[l]-Volcoral[l])*3600)
res[i,6]<-Datachamberindv[i,3]
res[i,7]<-as.character(Datachamberindv[1,4])
res[i,8]<-summary(b)$coefficients["linearreg[, 1]","Std. Error"]
res[i,9]<-summary(b)$coefficients["linearreg[, 1]","Pr(>|t|)"]
res[i,10]<-summary(b)$r.squared
}
##Blank Fish Chamber
for (i in c(1:3)){
resblc[i,1]<-(firstmidpointblank+(i-1)*periodblc)
resblc[i,2]<-resblc[i,1]-(measureperiodblc/2)
resblc[i,3]<-resblc[i,1]+(measureperiodblc/2)
merge(resblc,Datablank[,c(numdmyhms,timecolumn)],by.x="MidTime (sec)",by.y="Timeabsolu2",all.x = T) ###A voir les colonnes datablank
Datachamberindvblc<-na.omit(Datablank[,c(timecolumn,O2column[l],Tempcolumn[l],1)])
linearregblc<-subset(Datachamberindvblc, Datachamberindvblc$Timeabsolu2>=resblc[i,2] & Datachamberindvblc$Timeabsolu2<=resblc[i,3])
b<-lm(linearregblc[,2]~linearregblc[,1])
resblc[i,4]<-b$coefficients[2]
resblc[i,5]<-(-b$coefficients[2]*(ChamberVolume[l])*3600)
resblc[i,6]<-Datachamberindvblc[i,3]
resblc[i,7]<-as.character(Datachamberindv[1,4])
resblc[i,8]<-summary(b)$coefficients["linearregblc[, 1]","Std. Error"]
resblc[i,9]<-summary(b)$coefficients["linearregblc[, 1]","Pr(>|t|)"]
resblc[i,10]<-summary(b)$r.squared
}
##mean end point for fish blank O2 en Absolu Time
Blanktailfish02<- mean(tail(resblc[,5],3))########### mean of three point in resblc
BlanktailfishTime<- mean(tail(resblc[,1],3))
##Blank blank Chamber
resblcblc<-data.frame(matrix(ncol=11,nrow=0))
colnames(resblcblc)<- c("MidTime (sec)", "StartTime (sec)", "EndTime (sec)","linear coeff","MO2 (mg/h)","Temp(°C)","Date","SE","p-value","Rsquared","MO2cor")
for (i in c(1:3)){
resblcblc[i,1]<-(firstmidpointblank+(i-1)*periodblc)
resblcblc[i,2]<-resblcblc[i,1]-(measureperiodblc/2)
resblcblc[i,3]<-resblcblc[i,1]+(measureperiodblc/2)
merge(resblcblc,Datablank[,c(numdmyhms,timecolumn)],by.x="MidTime (sec)",by.y="Timeabsolu2",all.x = T) ###A voir les colonnes datablank
Datachamberindvblc<-na.omit(Datablank[,c(timecolumn,O2column[blankposition],Tempcolumn[blankposition],1)])
linearregblc<-subset(Datachamberindvblc, Datachamberindvblc$Timeabsolu2>=resblcblc[i,2] & Datachamberindvblc$Timeabsolu2<=resblcblc[i,3])
b<-lm(linearregblc[,2]~linearregblc[,1])
resblcblc[i,4]<-b$coefficients[2]
resblcblc[i,5]<-(-b$coefficients[2]*(ChamberVolume[blankposition])*3600)
resblcblc[i,6]<-Datachamberindvblc[i,3]
resblcblc[i,7]<-as.character(Datachamberindvblc[1,4])
resblcblc[i,8]<-summary(b)$coefficients["linearregblc[, 1]","Std. Error"]
resblcblc[i,9]<-summary(b)$coefficients["linearregblc[, 1]","Pr(>|t|)"]
resblcblc[i,10]<-summary(b)$r.squared
}
##mean end point for blank O2 en Absolu Time
BlanktailblankO2<<-mean(tail(resblcblc[,5],3))
BlanktailTime<-mean(tail(resblcblc[,1],3))
##Create linear regression with start and end point of blank slope
blankcorrectionreg<-subset(Resultblank[,c(1,5)],Resultblank[,1]==Firststart)
blankcorrectionreg[2,]<-c(BlanktailTime,BlanktailblankO2)
reg1<-lm(blankcorrectionreg[,2]~blankcorrectionreg[,1])
regblank <- function(x) reg1$coefficient[2]*x + reg1$coefficient[1]
##Create linear regression with start point of blank slope and end point blank fish chamber
chambercorrectionreg<-subset(Resultblank[,c(1,5)],Resultblank[,1]==Firststart)
chambercorrectionreg[2,]<-c(BlanktailfishTime,Blanktailfish02)
reg2<-lm(chambercorrectionreg[,2]~chambercorrectionreg[,1])
regchamber <- function(x) reg2$coefficient[2]*x + reg2$coefficient[1]
d<-ggplot(res,environment=environment())+geom_point(aes(x=res[,1],y=regchamber(res[,1])),colour="red")+geom_point(aes(x=res[,1],y=regblank(res[,1]))) +xlab("Time (h)") +ylab("MO2 (mg/h)") +xlim(Firststart,max(res[,1]))
ggsave(d,filename=paste("Chamber",l,"Deltaregression.pdf",sep=""),path = wayout,width=20, height=4)
res$deltablankfish<-ifelse(res[,1]>Firststart,regchamber(res[,1])-regblank(res[,1]),0)
res$Poly<-polyblank(res[,1])
res$MO2cor<-ifelse(res[,1]>Firststart,res[,5] - (res$Poly+res$deltablankfish),res[,5])
# layer SMR
#Rsquared layer
meanRsquared <- mean(res$Rsquared)
SdRsquared <- sd(res$Rsquared)
resstep1 <- subset(res, res[, 10] > (meanRsquared - (nsdevsrsquared * SdRsquared)))
#lowest value layer
LowestO2valueOutlier <- sort(res[, 11], decreasing = F)[1:numberoflowvalues]
resstep2 <- subset(resstep1, resstep1[, 11] %in% c(LowestO2valueOutlier))
#Mean lowest value layer
meanLowestO2values <- mean(resstep2$MO2cor)
SdLowestO2values <- sd(resstep2$MO2cor)
resstep3 <- subset(resstep2, resstep2[, 11] > (meanLowestO2values - (2 * SdLowestO2values)) & resstep2[, 11] < (meanLowestO2values + (2 * SdLowestO2values)))
res$selection <- ifelse(res[, 11] %in% resstep3[, 11] & res[, 10] %in% resstep3[, 10], "SMR", ifelse(res[, 11] %in% resstep2[, 11] & res[, 10] %in% resstep2[, 10],"meanLowestO2valueOutlier", ifelse(res[, 11] %in% resstep1[, 11] & res[, 10] %in% resstep1[, 10], "NotUsedInSMRcalculation", "RsquaredOutlier")))
res<-merge(res,Data[,c(numdmyhms,timecolumn,2)],by.x="MidTime (sec)",by.y="Timeabsolu2",all.x = T)
res$selection2<-ifelse(as.numeric(hms(res[,"Time"]))>as.numeric(hms(startday))+buffertime & as.numeric(hms(res[,"Time"]))<as.numeric(hms(endday))-buffertime,"Day",ifelse(as.numeric(hms(res[,"Time"]))<as.numeric(hms(startday))-buffertime,"Night",ifelse(as.numeric(hms(res[,"Time"]))>as.numeric(hms(endday))+buffertime,"Night","Transition")))
res$selection2<-ifelse(res[,2]>res[1,2]+acclimatationtime,as.character(res$selection2),"Acclimatation")
res$selection3<-ifelse(res$selection2 %in% c("Day","Night","Transition"),as.character(res$selection2),"Acclimatation")
#lowest value day
day<-subset(res,res[,"selection2"]=="Day")
daylow<-subset(day,day[, 11] %in% c(sort(day[, 11], decreasing = F)[1:round(length(day[,11])*0.20)]))
#max value night
night<-subset(res,res[,"selection2"]=="Night")
nightmax<-subset(night,night[, 11] %in% c(sort(night[, 11], decreasing = T)[1:round(length(night[,11])*0.20)]))
res$selection4 <- ifelse(res[, 11] %in% daylow[, 11] & res[, 10] %in% daylow[, 10], "LowestO2valueDay", ifelse(res[, 11] %in% nightmax[, 11] & res[, 10] %in% nightmax[, 10],"MaxO2valueNight", ifelse(res[, 11] %in% resstep1[, 11] & res[, 10] %in% resstep1[, 10], res$selection3, "RsquaredOutlier")))
#write Table
write.table(res, paste(wayout, "/", "resultchamber", l, ".csv", sep = ""), sep = ";", dec = ".", row.names = F, qmethod = "double")
write.table(resblc, paste(wayout, "/", "resultblankchamber", l,".csv", sep = ""), sep = ";", dec = ".", row.names = F, qmethod = "double")
c<-ggplot(res,environment = environment())+geom_point(aes(x=res[,1]/3600,y=res[,5]),alpha=0.1)+ylab(colnames(res[5])) +xlab("Time (h)") +geom_point(aes(x=res[,1]/3600,y=MO2cor,colour=selection4)) #+scale_color_manual(values = c("NotUsedInSMRcalculation" = "black","RsquaredOutlier" = "red","meanLowestO2valueOutlier"="blue","SMR" = "green"))
print(c)
ggsave(c,filename=paste("Chamber",l,".pdf",sep=""),path = wayout,width=20, height=4)
#####################################Final Table###################################################
Result[l,1]<-ID[[l]]
Result[l,2]<-res$Date[[1]]
Result[l,3]<-position[[l]]
Result[l,4]<-mean(subset(res,res$selection4=="LowestO2valueDay")$MO2cor)
Result[l,5]<-sd(subset(res,res$selection4=="LowestO2valueDay")$MO2cor)
Result[l,6]<-mean(subset(res,res$selection4=="MaxO2valueNight")$MO2cor)
Result[l,7]<-sd(subset(res,res$selection4=="MaxO2valueNight")$MO2cor)
Result[l,8]<-mean(subset(res,res$selection4 %in% c("LowestO2valueDay","Day"))$MO2cor)
Result[l,9]<-mean(subset(res,res$selection4 %in% c("MaxO2valueNight","Night"))$MO2cor)
Result[l,10]<-(-(Result[l,8]-Result[l,9]))
Result[l,11]<-mean(res[,6])
Result[l,12]<-Volcoral[[l]]
Result[l,13]<-ChamberVolume[l]
}
write.table(Result, paste(wayout, "/", "ResultRun.csv", sep = ""), sep = ";", dec = ".", row.names = F, qmethod = "double")
ResultRun<<-Result
}
Alexmerciere/RespiroRS documentation built on Nov. 3, 2021, 1:07 p.m.
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Defines functions auto.analyses.coral
auto.analyses.coral<-function(Data,Datablank,Volcoral,position,ID,blankposition,wayout,startday,endday,Nnoise=NULL,Nnoiseblk=NULL,correctFirstendslope=NULL,Nnoisestartdev=NULL,equalVolume=NULL,buffertime=NULL,acclimatationtime=NULL){
if (is.null(Nnoise)) {Nnoise<- 5 }
if (is.null(Nnoise)) {Nnoiseblk<- 5 }
if (is.null(correctFirstendslope)) { chamberfirstslope <-1 }
if (!is.null(correctFirstendslope)) { chamberfirstslope <-correctFirstendslope }
if (is.null(Nnoisestartdev)) {Nnoisestartdev<- 2 }
if (is.null(equalVolume)) {equalVolume<- T }
if (is.null(buffertime)) {buffertime<- 3600 }
if (is.null(acclimatationtime)) {acclimatationtime<- 0 }
ifelse (blankposition==1,deltaBlankposition<-1,deltaBlankposition<-0)
ifelse (chamberfirstslope==1,corfirstslope<-0,corfirstslope<-chamberfirstslope-1)
#################Experiment Settings##############
##fish record
closetime <- as.numeric(readline(prompt="closetime (s): ")) #s
opentime <- as.numeric(readline(prompt="opentime (s): ")) #s
waittime <- as.numeric(readline(prompt="waittime (s): ")) #s
enddiscard <- as.numeric(readline(prompt="enddiscard (s): ")) #s
ifelse (equalVolume==F,{ChamberVolume <- as.numeric(unlist(strsplit(readline(prompt="list of Chambers Volumes (L): "), ","))) }, {ChamberVolume <- as.numeric(readline(prompt="Chamber Volume (L): "));ChamberVolume <- rep(ChamberVolume,length(position)+1)})
#ChamberVolume <- as.numeric(readline(prompt="ChamberVolume (L): ")) #L
##blank record
closetimeblc <- as.numeric(readline(prompt="closetimeblank (s): ")) #s
opentimeblc <- as.numeric(readline(prompt="opentimeblank (s): ")) #s
waittimeblc <- as.numeric(readline(prompt="waittimeblank (s): ")) #s
enddiscardblc <- as.numeric(readline(prompt="enddiscardblank (s): ")) #s
nsdevsrsquared<-2
unit<-"mg/L"
O2column<-c(4,5,6,7,13,14,15,16,22,23,24,25,31,32,33,34)
Tempcolumn<-c(8,9,10,11,17,18,19,20,26,27,28,29,35,36,37,38)
period<-opentime+closetime
measureperiod<-closetime-waittime-enddiscard
periodblc<-opentimeblc+closetimeblc
measureperiodblc<-closetimeblc-waittimeblc-enddiscardblc
ifelse(chamberfirstslope==1,adustfirstslope<-0, adustfirstslope<-chamberfirstslope*(period/2))
timecolumn<-grep("Timeabsolu2", colnames(Data))
numdmyhms<-grep("dmyhms", colnames(Data))
Data<-arrange(Data, Timeabsolu2)
############################File with Fish record######################
#########Moving average############
testdata<-data.frame(subset(Data,Timeabsolu2<10000))
testdata<-na.omit(testdata[,c(timecolumn,O2column[chamberfirstslope])])
testdata$movavg<-movavg(testdata[,2],13,type=c("s"))
##Calculate dif
testdata$dif<-NA
for (row in 1:nrow(testdata)){
ifelse(testdata[row,1]>testdata[1,1]+99+adustfirstslope & testdata[row,1]<testdata[1,1]+4900+adustfirstslope,testdata[row,4]<-(testdata[(row+50),3]-testdata[row,3]-(testdata[row,3]-testdata[(row-50),3])),testdata[row,4]<-NA)
}
##graphic dif
c<-ggplot(testdata)+geom_point(aes(x=Timeabsolu2,y=dif))
print(c)
##noise
noise<-sd(na.omit(subset(Data,Timeabsolu2>testdata[1,1]+100&Timeabsolu2<testdata[1,1]+200)[,O2column[chamberfirstslope]]))
print(noise)
##Find first endslope
Toppos<-list()
for (row in 1:nrow(testdata)){
ifelse(testdata[row,1]>testdata[1,1]+99+adustfirstslope & testdata[row,1]<testdata[1,1]+1900+adustfirstslope,ifelse(testdata[row,4]>testdata[(row-1),4] & testdata[row,4]>testdata[(row-5),4] & testdata[row,4]>testdata[(row-7),4] & testdata[row,4]>testdata[(row+1),4] & testdata[row,4]>testdata[(row+5),4] & testdata[row,4]>testdata[(row+7),4] & testdata[row,4]>(Nnoise*noise),Toppos<-list.append(Toppos,testdata[row,1]),NA),NA)
}
#Time of the first end slope
Firstend<-as.numeric(Toppos[[1]])
print(Firstend)
#graph with end slope
c<-ggplot(Data,environment = environment())+geom_point(aes(x=Timeabsolu2,y=Data[,O2column[chamberfirstslope]]))+ylab(paste(colnames(Data[O2column[chamberfirstslope]]),unit)) +xlab("Time (sec)")+xlim(testdata[1,1],testdata[1,1]+10000) +
geom_vline(aes(xintercept = Firstend),color="red")
print(c)
ggsave(c,filename="firstslope.pdf",path = wayout,width=20, height=4)
question2 <- readline(prompt="First end slope is at the good position ?(YES or NO) : ")
ifelse(question2=="YES",NA,{nperiod <-as.numeric(readline(prompt="How many periode do you want add (+) or delete (-) ? "));
Firstend<-(nperiod*period)+Firstend;
print(Firstend);
c<-ggplot(Data,environment = environment())+geom_point(aes(x=Timeabsolu2,y=Data[,O2column[chamberfirstslope]]))+ylab(paste(colnames(Data[O2column[chamberfirstslope]]),unit)) +xlab("Time (sec)")+xlim(testdata[1,1],testdata[1,1]+10000) +geom_vline(aes(xintercept = Firstend),color="red") ;
ggsave(c,filename="firstslopecorrected.pdf",path = wayout,width=20, height=4);NA})
Firstend<-Firstend-(corfirstslope*period)
firstmidpoint<-Firstend-enddiscard-(measureperiod/2)
wholeperiods<-(max(na.omit(Data$Timeabsolu2))-firstmidpoint)/period
numberoflowvalues<-wholeperiods/10 ####10 pourcent of point
numbperiods<-round(wholeperiods)
###########################################################################################################
####################################File with Fishblank record#############################################
#########Moving average############
testdata<-Datablank[1:1000,]
testdata<-na.omit(testdata[,c(timecolumn,O2column[position[1]])])
library("pracma", lib.loc="/Library/Frameworks/R.framework/Versions/3.0/Resources/library")
testdata$movavg<-movavg(testdata[,2],13,type=c("s"))
##Calculate dif
testdata$dif<-NA
for (x in c(51:950)){
testdata[x,4]<-(testdata[(x+50),3]-testdata[x,3]-(testdata[x,3]-testdata[(x-50),3]))
}
##graphic dif
ggplot(testdata)+geom_point(aes(x=Timeabsolu2,y=dif))
##noise
noise<-sd(testdata[c(51:100),4])
print(noise)
##Find first endslope
Toppos<-list()
for (row in c(51:950)){
ifelse(testdata[row,4]>testdata[(row-1),4] & testdata[row,4]>testdata[(row-5),4] & testdata[row,4]>testdata[(row-7),4] & testdata[row,4]>testdata[(row+1),4] & testdata[row,4]>testdata[(row+5),4] & testdata[row,4]>testdata[(row+7),4] & testdata[row,4]>(Nnoiseblk*noise),Toppos<-list.append(Toppos,testdata[row,1]),NA)
}
#Time of the first end slope
Firstendblank<-as.numeric(Toppos[[1]])
print(Firstendblank)
#graph with end slope and mean temperature during experiment
c<-ggplot(Datablank,environment = environment())+geom_point(aes(x=Timeabsolu2,y=Datablank[,O2column[position[1]]]))+ylab(paste(colnames(Datablank[O2column[position[1]]]),unit)) +xlab("Time (sec)") + geom_vline(aes(xintercept = Firstendblank,color="red"))
print(c)
ggsave(c,filename="firstslopeblank.pdf",path = wayout,width=20, height=4)
ifelse(question1<-"YES",NA,{Firstendblank <-as.numeric(readline(prompt="Give a new value of First end "))+Firstendblank;c<-ggplot(Datablank,environment = environment())+geom_point(aes(x=Timeabsolu2,y=Datablank[,4]))+ylab(paste(colnames(Datablank[4]),unit)) +xlab("Time (sec)") + geom_vline(aes(xintercept = Firstendblank,color="red"));ggsave(c,filename="firstslopeblankcorrected.pdf",path = wayout,width=20, height=4)})
question1 <- readline(prompt="First end slope blank is at the good position ?(YES or NO) : ")
ifelse(question1=="YES",NA,{nperiod <-as.numeric(readline(prompt="How many periode do you want add (+) or delete (-) ? "));
Firstendblank<-(nperiod*periodblc)+Firstendblank;
print(Firstendblank);
c<-ggplot(Datablank,environment = environment())+geom_point(aes(x=Timeabsolu2,y=Datablank[,4]))+ylab(paste(colnames(Datablank[4]),unit)) +xlab("Time (sec)") + geom_vline(aes(xintercept = Firstendblank,color="red"))
ggsave(c,filename="firstslopeblankcorrected.pdf",path = wayout,width=20, height=4);NA})
firstmidpointblank<-Firstendblank-enddiscardblc-(measureperiodblc/2)
###########################################################################################################
####################################RESULT CHAMBER BLANK######################################################
res<-data.frame(matrix(ncol=10,nrow=0))
colnames(res)<- c("MidTime (sec)", "StartTime (sec)", "EndTime (sec)","linear coeff","MO2 (mg/h)","Temp(°C)","Date","SE","p-value","Rsquared")
numbperiods<-round(wholeperiods)-(blankposition-1) + deltaBlankposition
##Create table with mid time measurment, start and end per chamber
for (i in 1:numbperiods){
res[i,1]<-firstmidpoint+(i-1+(blankposition-1))*period -(deltaBlankposition*period) #### blank chamber position to find start firstmid slope
res[i,2]<-res[i,1]-(measureperiod/2)
res[i,3]<-res[i,1]+(measureperiod/2)
merge(res,Data[,c(numdmyhms,timecolumn)],by.x="MidTime (sec)",by.y="Timeabsolu2",all.x = T)
Datachamberindv<-na.omit(Data[,c(timecolumn,O2column[blankposition],Tempcolumn[blankposition],1)])
linearreg<-subset(Datachamberindv, Datachamberindv$Timeabsolu2>=res[i,2] & Datachamberindv$Timeabsolu2<=res[i,3])
b<-lm(linearreg[,2]~linearreg[,1])
res[i,4]<-b$coefficients[2]
res[i,5]<-(-b$coefficients[2]*(ChamberVolume[blankposition])*3600)
res[i,6]<-Datachamberindv[i,3]
res[i,7]<-as.character(Datachamberindv[1,4])
res[i,8]<-summary(b)$coefficients["linearreg[, 1]","Std. Error"]
res[i,9]<-summary(b)$coefficients["linearreg[, 1]","Pr(>|t|)"]
res[i,10]<-summary(b)$r.squared
}
e<-lm(res[,5] ~ poly(res[,1], 4, raw=TRUE))
polyblank <- function(x) {e$coefficient[5]*x^4 + e$coefficient[4]*x^3 + e$coefficient[3]*x^2 + e$coefficient[2]*x + e$coefficient[1]}
res$Poly<-polyblank(res[,1])
c<-ggplot(res,environment = environment())+geom_point(aes(x=res[,1]/3600,y=res[,5]))+ylab(colnames(res[5])) +xlab("Time (h)")+ stat_smooth(aes(x=res[,1]/3600,y=res[,5]),method="lm", se=TRUE, fill=NA,formula=y ~ poly(x, 4, raw=TRUE),colour="blue") +geom_point(aes(x=res[,1]/3600,y=res[,11],colour="red"))
Resultblank<-res
write.table(Resultblank, paste(wayout, "/resultchamberblank.csv", sep = ""), sep = ";", dec = ".", row.names = F, qmethod = "double")
ggsave(c,filename="Blank.pdf",path = wayout,width=20, height=4)
print(c)
#################SLOPE BLANK RESPIRATION##############
#######################################Find start of slope deviation##################################
noise<-sd(Resultblank[c(1:10),5])
mean<-mean(Resultblank[c(1:10),5])
Toppos<-list()
for (row in 1:nrow(Resultblank)){
ifelse(Resultblank[row,11]>mean+Nnoisestartdev*noise,Toppos<-list.append(Toppos,Resultblank[row,1]),NA)
}
#Time of the start slope deviation
Firststart<-as.numeric(Toppos[1])
print(Firststart)
c<-ggplot(Resultblank,environment=environment())+geom_point(aes(x=Resultblank[,1]/3600,y=Resultblank[,5]))+ylab(paste(colnames(Resultblank[5]))) +xlab("Time (sec)")+geom_point(aes(x=Resultblank[,1]/3600,y=Resultblank[,11],colour="red"))+ geom_vline(aes(xintercept =Firststart/3600 ,color="red"))
ggsave(c,filename="Blank_slope_start.pdf",path = wayout,width=20, height=4)
print(c)
########################################################################################
####################################RESULT CHAMBER FISH###############################################
Result<-data.frame(matrix(ncol=13,nrow=0))
colnames(Result)<- c("ID","Date", "Chamber","MinMRDay","sdMinMRDay","MaxMRNight","sdMaxMRNight","MeanMRDay","MeanMRNight","PhotoProduction","MeanTemp (°C)","Volume (L)","Chamber Volume (L)")
for (l in position){
res<-data.frame(matrix(ncol=11,nrow=0))
colnames(res)<- c("MidTime (sec)", "StartTime (sec)", "EndTime (sec)","linear coeff","MO2 (mg/h)","Temp(°C)","Date","SE","p-value","Rsquared","MO2cor")
numbperiods<-round(wholeperiods)-(position[l]-1) - deltaBlankposition
resblc<-data.frame(matrix(ncol=11,nrow=0))
colnames(resblc)<- c("MidTime (sec)", "StartTime (sec)", "EndTime (sec)","linear coeff","MO2 (mg/h)","Temp(°C)","Date","SE","p-value","Rsquared","MO2cor")
##Record Fish Chamber
##Create table with mid time measurment, start and end per chamber
for (i in 1:numbperiods){
res[i,1]<-firstmidpoint+(i-1+(l-1))*period -(deltaBlankposition*period)###remove l-1 if you start all the chamber in the same time
res[i,2]<-res[i,1]-(measureperiod/2)
res[i,3]<-res[i,1]+(measureperiod/2)
Datachamberindv<-na.omit(Data[,c(timecolumn,O2column[l],Tempcolumn[l],1)])
linearreg<-subset(Datachamberindv, Datachamberindv$Timeabsolu2>=res[i,2] & Datachamberindv$Timeabsolu2<=res[i,3])
b<-lm(linearreg[,2]~linearreg[,1])
res[i,4]<-b$coefficients[2]
res[i,5]<-(-b$coefficients[2]*(ChamberVolume[l]-Volcoral[l])*3600)
res[i,6]<-Datachamberindv[i,3]
res[i,7]<-as.character(Datachamberindv[1,4])
res[i,8]<-summary(b)$coefficients["linearreg[, 1]","Std. Error"]
res[i,9]<-summary(b)$coefficients["linearreg[, 1]","Pr(>|t|)"]
res[i,10]<-summary(b)$r.squared
}
##Blank Fish Chamber
for (i in c(1:3)){
resblc[i,1]<-(firstmidpointblank+(i-1)*periodblc)
resblc[i,2]<-resblc[i,1]-(measureperiodblc/2)
resblc[i,3]<-resblc[i,1]+(measureperiodblc/2)
merge(resblc,Datablank[,c(numdmyhms,timecolumn)],by.x="MidTime (sec)",by.y="Timeabsolu2",all.x = T) ###A voir les colonnes datablank
Datachamberindvblc<-na.omit(Datablank[,c(timecolumn,O2column[l],Tempcolumn[l],1)])
linearregblc<-subset(Datachamberindvblc, Datachamberindvblc$Timeabsolu2>=resblc[i,2] & Datachamberindvblc$Timeabsolu2<=resblc[i,3])
b<-lm(linearregblc[,2]~linearregblc[,1])
resblc[i,4]<-b$coefficients[2]
resblc[i,5]<-(-b$coefficients[2]*(ChamberVolume[l])*3600)
resblc[i,6]<-Datachamberindvblc[i,3]
resblc[i,7]<-as.character(Datachamberindv[1,4])
resblc[i,8]<-summary(b)$coefficients["linearregblc[, 1]","Std. Error"]
resblc[i,9]<-summary(b)$coefficients["linearregblc[, 1]","Pr(>|t|)"]
resblc[i,10]<-summary(b)$r.squared
}
##mean end point for fish blank O2 en Absolu Time
Blanktailfish02<- mean(tail(resblc[,5],3))########### mean of three point in resblc
BlanktailfishTime<- mean(tail(resblc[,1],3))
##Blank blank Chamber
resblcblc<-data.frame(matrix(ncol=11,nrow=0))
colnames(resblcblc)<- c("MidTime (sec)", "StartTime (sec)", "EndTime (sec)","linear coeff","MO2 (mg/h)","Temp(°C)","Date","SE","p-value","Rsquared","MO2cor")
for (i in c(1:3)){
resblcblc[i,1]<-(firstmidpointblank+(i-1)*periodblc)
resblcblc[i,2]<-resblcblc[i,1]-(measureperiodblc/2)
resblcblc[i,3]<-resblcblc[i,1]+(measureperiodblc/2)
merge(resblcblc,Datablank[,c(numdmyhms,timecolumn)],by.x="MidTime (sec)",by.y="Timeabsolu2",all.x = T) ###A voir les colonnes datablank
Datachamberindvblc<-na.omit(Datablank[,c(timecolumn,O2column[blankposition],Tempcolumn[blankposition],1)])
linearregblc<-subset(Datachamberindvblc, Datachamberindvblc$Timeabsolu2>=resblcblc[i,2] & Datachamberindvblc$Timeabsolu2<=resblcblc[i,3])
b<-lm(linearregblc[,2]~linearregblc[,1])
resblcblc[i,4]<-b$coefficients[2]
resblcblc[i,5]<-(-b$coefficients[2]*(ChamberVolume[blankposition])*3600)
resblcblc[i,6]<-Datachamberindvblc[i,3]
resblcblc[i,7]<-as.character(Datachamberindvblc[1,4])
resblcblc[i,8]<-summary(b)$coefficients["linearregblc[, 1]","Std. Error"]
resblcblc[i,9]<-summary(b)$coefficients["linearregblc[, 1]","Pr(>|t|)"]
resblcblc[i,10]<-summary(b)$r.squared
}
##mean end point for blank O2 en Absolu Time
BlanktailblankO2<<-mean(tail(resblcblc[,5],3))
BlanktailTime<-mean(tail(resblcblc[,1],3))
##Create linear regression with start and end point of blank slope
blankcorrectionreg<-subset(Resultblank[,c(1,5)],Resultblank[,1]==Firststart)
blankcorrectionreg[2,]<-c(BlanktailTime,BlanktailblankO2)
reg1<-lm(blankcorrectionreg[,2]~blankcorrectionreg[,1])
regblank <- function(x) reg1$coefficient[2]*x + reg1$coefficient[1]
##Create linear regression with start point of blank slope and end point blank fish chamber
chambercorrectionreg<-subset(Resultblank[,c(1,5)],Resultblank[,1]==Firststart)
chambercorrectionreg[2,]<-c(BlanktailfishTime,Blanktailfish02)
reg2<-lm(chambercorrectionreg[,2]~chambercorrectionreg[,1])
regchamber <- function(x) reg2$coefficient[2]*x + reg2$coefficient[1]
d<-ggplot(res,environment=environment())+geom_point(aes(x=res[,1],y=regchamber(res[,1])),colour="red")+geom_point(aes(x=res[,1],y=regblank(res[,1]))) +xlab("Time (h)") +ylab("MO2 (mg/h)") +xlim(Firststart,max(res[,1]))
ggsave(d,filename=paste("Chamber",l,"Deltaregression.pdf",sep=""),path = wayout,width=20, height=4)
res$deltablankfish<-ifelse(res[,1]>Firststart,regchamber(res[,1])-regblank(res[,1]),0)
res$Poly<-polyblank(res[,1])
res$MO2cor<-ifelse(res[,1]>Firststart,res[,5] - (res$Poly+res$deltablankfish),res[,5])
# layer SMR
#Rsquared layer
meanRsquared <- mean(res$Rsquared)
SdRsquared <- sd(res$Rsquared)
resstep1 <- subset(res, res[, 10] > (meanRsquared - (nsdevsrsquared * SdRsquared)))
#lowest value layer
LowestO2valueOutlier <- sort(res[, 11], decreasing = F)[1:numberoflowvalues]
resstep2 <- subset(resstep1, resstep1[, 11] %in% c(LowestO2valueOutlier))
#Mean lowest value layer
meanLowestO2values <- mean(resstep2$MO2cor)
SdLowestO2values <- sd(resstep2$MO2cor)
resstep3 <- subset(resstep2, resstep2[, 11] > (meanLowestO2values - (2 * SdLowestO2values)) & resstep2[, 11] < (meanLowestO2values + (2 * SdLowestO2values)))
res$selection <- ifelse(res[, 11] %in% resstep3[, 11] & res[, 10] %in% resstep3[, 10], "SMR", ifelse(res[, 11] %in% resstep2[, 11] & res[, 10] %in% resstep2[, 10],"meanLowestO2valueOutlier", ifelse(res[, 11] %in% resstep1[, 11] & res[, 10] %in% resstep1[, 10], "NotUsedInSMRcalculation", "RsquaredOutlier")))
res<-merge(res,Data[,c(numdmyhms,timecolumn,2)],by.x="MidTime (sec)",by.y="Timeabsolu2",all.x = T)
res$selection2<-ifelse(as.numeric(hms(res[,"Time"]))>as.numeric(hms(startday))+buffertime & as.numeric(hms(res[,"Time"]))<as.numeric(hms(endday))-buffertime,"Day",ifelse(as.numeric(hms(res[,"Time"]))<as.numeric(hms(startday))-buffertime,"Night",ifelse(as.numeric(hms(res[,"Time"]))>as.numeric(hms(endday))+buffertime,"Night","Transition")))
res$selection2<-ifelse(res[,2]>res[1,2]+acclimatationtime,as.character(res$selection2),"Acclimatation")
res$selection3<-ifelse(res$selection2 %in% c("Day","Night","Transition"),as.character(res$selection2),"Acclimatation")
#lowest value day
day<-subset(res,res[,"selection2"]=="Day")
daylow<-subset(day,day[, 11] %in% c(sort(day[, 11], decreasing = F)[1:round(length(day[,11])*0.20)]))
#max value night
night<-subset(res,res[,"selection2"]=="Night")
nightmax<-subset(night,night[, 11] %in% c(sort(night[, 11], decreasing = T)[1:round(length(night[,11])*0.20)]))
res$selection4 <- ifelse(res[, 11] %in% daylow[, 11] & res[, 10] %in% daylow[, 10], "LowestO2valueDay", ifelse(res[, 11] %in% nightmax[, 11] & res[, 10] %in% nightmax[, 10],"MaxO2valueNight", ifelse(res[, 11] %in% resstep1[, 11] & res[, 10] %in% resstep1[, 10], res$selection3, "RsquaredOutlier")))
#write Table
write.table(res, paste(wayout, "/", "resultchamber", l, ".csv", sep = ""), sep = ";", dec = ".", row.names = F, qmethod = "double")
write.table(resblc, paste(wayout, "/", "resultblankchamber", l,".csv", sep = ""), sep = ";", dec = ".", row.names = F, qmethod = "double")
c<-ggplot(res,environment = environment())+geom_point(aes(x=res[,1]/3600,y=res[,5]),alpha=0.1)+ylab(colnames(res[5])) +xlab("Time (h)") +geom_point(aes(x=res[,1]/3600,y=MO2cor,colour=selection4)) #+scale_color_manual(values = c("NotUsedInSMRcalculation" = "black","RsquaredOutlier" = "red","meanLowestO2valueOutlier"="blue","SMR" = "green"))
print(c)
ggsave(c,filename=paste("Chamber",l,".pdf",sep=""),path = wayout,width=20, height=4)
#####################################Final Table###################################################
Result[l,1]<-ID[[l]]
Result[l,2]<-res$Date[[1]]
Result[l,3]<-position[[l]]
Result[l,4]<-mean(subset(res,res$selection4=="LowestO2valueDay")$MO2cor)
Result[l,5]<-sd(subset(res,res$selection4=="LowestO2valueDay")$MO2cor)
Result[l,6]<-mean(subset(res,res$selection4=="MaxO2valueNight")$MO2cor)
Result[l,7]<-sd(subset(res,res$selection4=="MaxO2valueNight")$MO2cor)
Result[l,8]<-mean(subset(res,res$selection4 %in% c("LowestO2valueDay","Day"))$MO2cor)
Result[l,9]<-mean(subset(res,res$selection4 %in% c("MaxO2valueNight","Night"))$MO2cor)
Result[l,10]<-(-(Result[l,8]-Result[l,9]))
Result[l,11]<-mean(res[,6])
Result[l,12]<-Volcoral[[l]]
Result[l,13]<-ChamberVolume[l]
}
write.table(Result, paste(wayout, "/", "ResultRun.csv", sep = ""), sep = ";", dec = ".", row.names = F, qmethod = "double")
ResultRun<<-Result
}
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