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Copy pathTestTableJustEFv2.R
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TestTableJustEFv2.R
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# Do ER or do EF
source("Table1.R")
source("speciateSpecies.R")
q1=0.25; q2=0.75
`%notin%` <- Negate(`%in%`)
doER = 0
doEF = 1
dowheatshrub =1
options(scipen = 1, digits=3)
cornfrac = table1$fires[1]/sum(table1$fires[1:4])
ricefrac = table1$fires[2]/sum(table1$fires[1:4])
soyfrac = table1$fires[3]/sum(table1$fires[1:4])
wheatfrac = table1$fires[4]/sum(table1$fires[1:4])
slashfrac = table1$fires[6]/sum(table1$fires[6:8])
pilefrac = table1$fires[7]/sum(table1$fires[6:8])
shrubfrac = table1$fires[8]/sum(table1$fires[6:8])
#
allBOTH.filter.median = aggregate(allBOTH.filter, by=list(allBOTH.filter$variable), FUN='median', na.rm=TRUE)
propertiesSpecies = as.data.frame(cbind(allBOTH.filter.median$Group.1,
allBOTH.filter.median$names,allBOTH.filter.median$PI,
allBOTH.filter.median$mWs,allBOTH.filter.median$OHrate.1hz,
allBOTH.filter.median$OHrate.5hz, allBOTH.filter.median$lifetime))
ind = which(allBOTH.filter.median$USEME != 0)
write.csv(propertiesSpecies[ind,],file='propertiesSpecies.csv')
library(htmlTable); library(plyr)
library(magrittr)
# --------------
ind = which(allBOTH.filter$fire == 'BlackwaterRiver')
allBOTH.filter$fuel[ind] = 'Blackwater'
# Make larger fuel categories
allBOTH.filter$fuelORIG = allBOTH.filter$fuel
allBOTH.filter$fuel2 = allBOTH.filter$fuel
ind = which(allBOTH.filter$fuel2 == 'corn' | allBOTH.filter$fuel2 == 'soybean' | allBOTH.filter$fuel2 == 'rice' |
allBOTH.filter$fuel2 == 'winter wheat')
allBOTH.filter$fuel2[ind] = 'agriculture'
ind = which(allBOTH.filter$fuel2 == 'pile' | allBOTH.filter$fuel2 == 'slash' | allBOTH.filter$fuel2 == 'shrub')
allBOTH.filter$fuel2[ind] = 'prescribed'
#ind = which(allBOTH.filter$fire == 'Blackwater')
#allBOTH.filter$fuel2[ind] = 'Blackwater'
#ind = which(allBOTH.filter.median.fuel$fire == 'BlackwaterRiver')
#allBOTH.filter.median.fuel$fuel[ind] = 'Blackwater'
allBOTH.filter.median.fuel = aggregate(allBOTH.filter, by=list(allBOTH.filter$fuel,allBOTH.filter$variable), FUN='median', na.rm=TRUE)
allBOTH.filter.mean.fuel = aggregate(allBOTH.filter, by=list(allBOTH.filter$fuel,allBOTH.filter$variable), FUN='mean', na.rm=TRUE)
allBOTH.filter.sd.fuel = aggregate(allBOTH.filter, by=list(allBOTH.filter$fuel,allBOTH.filter$variable), FUN='sd', na.rm=TRUE)
allBOTH.filter.median.fuel$FinalEF_mean = allBOTH.filter.mean.fuel$FinalEF
allBOTH.filter.median.fuel$FinalEF_sd = allBOTH.filter.sd.fuel$FinalEF
allBOTH.filter.median.fuel$FinalERtoCO_mean = allBOTH.filter.mean.fuel$FinalERtoCO*1E3
allBOTH.filter.median.fuel$FinalERtoCO_sd = allBOTH.filter.sd.fuel$FinalERtoCO*1E3
allBOTH.filter.25.fuel = aggregate(allBOTH.filter$FinalEF, by=list(allBOTH.filter$fuel,allBOTH.filter$variable), 'quantile',probs=c(q1),na.rm=TRUE)
allBOTH.filter.75.fuel = aggregate(allBOTH.filter$FinalEF, by=list(allBOTH.filter$fuel,allBOTH.filter$variable), 'quantile',probs=c(q2),na.rm=TRUE)
allBOTH.filter.25.fuelER = aggregate(allBOTH.filter$FinalERtoCO, by=list(allBOTH.filter$fuel,allBOTH.filter$variable), 'quantile',probs=c(q1),na.rm=TRUE)
allBOTH.filter.75.fuelER = aggregate(allBOTH.filter$FinalERtoCO, by=list(allBOTH.filter$fuel,allBOTH.filter$variable), 'quantile',probs=c(q2),na.rm=TRUE)
allBOTH.filter.median.fuel$FinalEF_25 = allBOTH.filter.25.fuel$x
allBOTH.filter.median.fuel$FinalEF_75 = allBOTH.filter.75.fuel$x
allBOTH.filter.median.fuel$FinalERtoCO_25 = allBOTH.filter.25.fuelER$x*1E3
allBOTH.filter.median.fuel$FinalERtoCO_75 = allBOTH.filter.75.fuelER$x*1E3
# need to recover fire, kind, formula, and names
allBOTH.filter.median.fuel$fuel = allBOTH.filter.median.fuel$Group.1
allBOTH.filter.median.fuel$variable = allBOTH.filter.median.fuel$Group.2
for (i in 1:length(allBOTH.filter.median.fuel$kind)){
ind = which(allBOTH.filter$variable == allBOTH.filter.median.fuel$Group.2[i])
allBOTH.filter.median.fuel$kind[i] = allBOTH.filter$kind[ind[1]]
allBOTH.filter.median.fuel$formula[i] = allBOTH.filter$formula[ind[1]]
allBOTH.filter.median.fuel$names[i] = allBOTH.filter$names[ind[1]]
allBOTH.filter.median.fuel$PI[i] = allBOTH.filter$PI[ind[1]]
# print(c(allBOTH.filter$variable[ind[1]], allBOTH.filter.median.fuel$Group.2[i]))
}
allBOTH.filter.median.fuel= getplumesANDmcebyfuel(allBOTH.filter.median.fuel, allBOTH.filter )
#allBOTH.filter.median.fuel = speciateSpecies(allBOTH.filter.median.fuel)
tmpTABLE = speciateSpecies(allBOTH.filter.median.fuel)
# Here add kludge for headers
newLine = tmpTABLE
# ok want to put C9 aromatics and monoterpenes together regardless of lifetime
ind = which(tmpTABLE$formula == 'C9H12')
tmpTABLE$LifetimeCat[ind] = 1
ind = which(tmpTABLE$formula == 'C10H16')
tmpTABLE$LifetimeCat[ind] = 1
ind =which(tmpTABLE$LifetimeCat == 2 & tmpTABLE$Category == 1)
tmpTABLE$Category[ind] = 1.5
# get rid of stuff without a category, category = 5 (oxidation products) and with USEME = 1
# decided to report H2O2
ind = which(tmpTABLE$formula == 'H2O2')
tmpTABLE$Category[ind] = 7
ind = which(tmpTABLE$formula == 'NOy')
tmpTABLE$Category[ind] = 2
ind = which(tmpTABLE$PI == 'MOORE')
tmpTABLE$Category[ind] = 4.5
ind = which(is.finite(tmpTABLE$Category) & tmpTABLE$Category != 5 & tmpTABLE$USEME > 0)
tmpTABLE=tmpTABLE[ind,]
ind = which(tmpTABLE$variable == 'Short-lived NMVOC' | tmpTABLE$variable == 'Long-lived NMVOC')
tmpTABLE$Category[ind] = 1.5
# ----- get fuel specific species -------
ind = which(tmpTABLE$Group.1 == 'corn' )
new.data.frame = tmpTABLE[ind,]
ind = which(tmpTABLE$Group.1 == 'rice' )
new.data.frame.rice = tmpTABLE[ind,]
ind = which(tmpTABLE$Group.1 == 'soybean' )
new.data.frame.soybean = tmpTABLE[ind,]
ind = which(tmpTABLE$Group.1 == 'winter wheat' )
new.data.frame.wheat = tmpTABLE[ind,]
ind = which(tmpTABLE$Group.1 == 'grass' )
new.data.frame.grass = tmpTABLE[ind,]
ind = which(tmpTABLE$Group.1 == 'slash' )
new.data.frame.slash = tmpTABLE[ind,]
ind = which(tmpTABLE$Group.1 == 'pile' )
new.data.frame.pile = tmpTABLE[ind,]
ind = which(tmpTABLE$Group.1 == 'shrub' )
new.data.frame.shrub = tmpTABLE[ind,]
ind = which(tmpTABLE$Group.1 == 'Blackwater' )
new.data.frame.blackwater = tmpTABLE[ind,]
# ------- Make average ag --------
# but account for zeros by replacing with corn which has complete EFs
dothis=1
new.data.frame.ag=new.data.frame
new.data.frame.presc=new.data.frame
if (dothis == 1){
new.data.frame.ag = new.data.frame
new.data.frame.wheat2 = new.data.frame.wheat
ind = which(!is.finite(new.data.frame.wheat2$FinalEF_mean))
new.data.frame.wheat2$FinalEF_mean[ind] = new.data.frame$FinalEF_mean[ind]
new.data.frame.wheat2$FinalERtoCO_mean[ind] = new.data.frame$FinalERtoCO_mean[ind]
ind = which(!is.finite(new.data.frame.wheat2$FinalEF_mean) | !is.finite(new.data.frame.wheat$FinalEF_sd))
new.data.frame.wheat2$FinalEF_sd[ind] = new.data.frame$FinalEF_sd[ind]
new.data.frame.wheat2$FinalERtoCO_sd[ind] = new.data.frame$FinalERtoCO_sd[ind]
new.data.frame.soybean2 = new.data.frame.soybean
ind = which(!is.finite(new.data.frame.soybean2$FinalEF_mean))
new.data.frame.soybean2$FinalEF_mean[ind] = new.data.frame$FinalEF_mean[ind]
new.data.frame.soybean2$FinalERtoCO_mean[ind] = new.data.frame$FinalERtoCO_mean[ind]
ind = which(!is.finite(new.data.frame.soybean2$FinalEF_mean) | !is.finite(new.data.frame.soybean2$FinalEF_sd))
new.data.frame.soybean2$FinalEF_sd[ind] = new.data.frame$FinalEF_sd[ind]
new.data.frame.soybean2$FinalERtoCO_sd[ind] = new.data.frame$FinalERtoCO_sd[ind]
new.data.frame.rice2 = new.data.frame.rice
ind = which(!is.finite(new.data.frame.rice2$FinalEF_mean))
new.data.frame.rice2$FinalEF_mean[ind] = new.data.frame$FinalEF_mean[ind]
new.data.frame.rice2$FinalERtoCO_mean[ind] = new.data.frame$FinalEF_mean[ind]
ind = which(!is.finite(new.data.frame.rice2$FinalEF_mean) |!is.finite(new.data.frame.rice2$FinalEF_sd) )
new.data.frame.rice2$FinalEF_sd[ind] = new.data.frame$FinalEF_sd[ind]
new.data.frame.rice2$FinalERtoCO_sd[ind] = new.data.frame$FinalERtoCO_sd[ind]
new.data.frame.ag$FinalEF_mean = new.data.frame$FinalEF_mean*cornfrac + new.data.frame.rice2$FinalEF_mean*ricefrac + new.data.frame.soybean2$FinalEF_mean*soyfrac + new.data.frame.wheat2$FinalEF_mean*wheatfrac
new.data.frame.ag$FinalERtoCO_mean = new.data.frame$FinalERtoCO_mean*cornfrac + new.data.frame.rice2$FinalERtoCO_mean*ricefrac + new.data.frame.soybean2$FinalERtoCO_mean*soyfrac + new.data.frame.wheat2$FinalERtoCO_mean*wheatfrac
new.data.frame.ag$COUNT_EFFINAL = new.data.frame$COUNT_EFFINAL+new.data.frame.rice2$COUNT_EFFINAL + new.data.frame.soybean2$COUNT_EFFINAL + new.data.frame.wheat2$COUNT_EFFINAL
new.data.frame.ag$FinalEF_sd = sqrt(((new.data.frame$FinalEF_sd*cornfrac)^2 +(new.data.frame.rice2$FinalEF_sd*ricefrac)^2 +(new.data.frame.soybean2$FinalEF_sd*soyfrac)^2 + (new.data.frame.wheat2$FinalEF_sd*wheatfrac)^2)/4)
new.data.frame.ag$FinalERtoCO_sd = sqrt(((new.data.frame$FinalERtoCO_sd*cornfrac)^2 +(new.data.frame.rice2$FinalERtoCO_sd*ricefrac)^2 +(new.data.frame.soybean2$FinalERtoCO_sd*soyfrac)^2 + (new.data.frame.wheat2$FinalERtoCO_sd*wheatfrac)^2)/4)
# ---- Make average presc ------------
new.data.frame.presc = new.data.frame.pile
new.data.frame.pile2 = new.data.frame.pile
ind = which(!is.finite(new.data.frame.pile$FinalEF_mean) & is.finite(new.data.frame.slash$FinalEF_mean))
new.data.frame.pile2$FinalEF_mean[ind] = new.data.frame.slash$FinalEF_mean[ind]
new.data.frame.pile2$FinalERtoCO_mean[ind] = new.data.frame.slash$FinalERtoCO_mean[ind]
ind = which(!is.finite(new.data.frame.pile$FinalEF_sd) & is.finite(new.data.frame.slash$FinalEF_sd))
new.data.frame.pile2$FinalEF_sd[ind] = new.data.frame.slash$FinalEF_sd[ind]
new.data.frame.pile2$FinalERtoCO_sd[ind] = new.data.frame.slash$FinalERtoCO_sd[ind]
new.data.frame.slash2 = new.data.frame.slash
ind = which(is.finite(new.data.frame.pile2$FinalEF_mean) & !is.finite(new.data.frame.slash$FinalEF_mean))
new.data.frame.slash2$FinalEF_mean[ind] = new.data.frame.pile$FinalEF_mean[ind]
new.data.frame.slash2$FinalERtoCO_mean[ind] = new.data.frame.pile$FinalERtoCO_mean[ind]
ind = which(is.finite(new.data.frame.pile2$FinalEF_sd) & !is.finite(new.data.frame.slash$FinalEF_sd))
new.data.frame.slash2$FinalEF_sd[ind] = new.data.frame.pile$FinalEF_sd[ind]
new.data.frame.slash2$FinalERtoCO_sd[ind] = new.data.frame.pile$FinalERtoCO_sd[ind]
new.data.frame.shrub2 = new.data.frame.shrub
tmp = new.data.frame.pile2
tmp$FinalEF_mean = (tmp$FinalEF_mean +new.data.frame.slash2$FinalEF_mean)/2
tmp$FinalERtoCO_mean = (tmp$FinalERtoCO_mean +new.data.frame.slash2$FinalERtoCO_mean)/2
tmp$FinalEF_sd= sqrt((tmp$FinalEF_sd^2 +new.data.frame.slash2$FinalEF_sd^2)/2)
tmp$FinalERtoCO_sd= sqrt((tmp$FinalERtoCO_sd^2 +new.data.frame.slash2$FinalERtoCO_sd^2)/2)
ind = which(is.finite(tmp$FinalEF_mean) & !is.finite(new.data.frame.shrub2$FinalEF_mean))
new.data.frame.shrub2$FinalEF_mean[ind] = (tmp$FinalEF_mean[ind])/2
new.data.frame.shrub2$FinalERtoCO_mean[ind] = (tmp$FinalERtoCO_mean[ind])/2
ind = which(is.finite(tmp$FinalEF_sd) & !is.finite(new.data.frame.shrub2$FinalEF_sd))
new.data.frame.shrub2$FinalEF_sd[ind] = tmp$FinalEF_sd[ind]
new.data.frame.shrub2$FinalERtoCO_sd[ind] = tmp$FinalERtoCO_sd[ind]
new.data.frame.presc$FinalEF_mean = new.data.frame.pile2$FinalEF_mean*pilefrac+new.data.frame.slash2$FinalEF_mean*slashfrac + new.data.frame.shrub2$FinalEF_mean*shrubfrac
new.data.frame.presc$FinalEF_sd = sqrt(((new.data.frame.pile2$FinalEF_sd*pilefrac)^2 +(new.data.frame.slash2$FinalEF_sd*slashfrac)^2 +(new.data.frame.shrub2$FinalEF_sd*shrubfrac)^2 )/3)
new.data.frame.presc$FinalERtoCO_mean = new.data.frame.pile2$FinalERtoCO_mean*pilefrac+new.data.frame.slash2$FinalERtoCO_mean*slashfrac + new.data.frame.shrub2$FinalERtoCO_mean*shrubfrac
new.data.frame.presc$FinalERtoCO_sd = sqrt(((new.data.frame.pile2$FinalERtoCO_sd*pilefrac)^2 +(new.data.frame.slash2$FinalERtoCO_sd*slashfrac)^2 +(new.data.frame.shrub2$FinalERtoCO_sd*shrubfrac)^2 )/3)
new.data.frame.presc$COUNT_EFFINAL = new.data.frame.pile2$COUNT_EFFINAL+new.data.frame.slash2$COUNT_EFFINAL + new.data.frame.shrub2$COUNT_EFFINAL
}
# --- fix PIs -------
ind= which(new.data.frame$PI == "ppt")
new.data.frame$PI[ind] = "APEL"
ind= which(new.data.frame$PI == "ppb")
new.data.frame$PI[ind] = "DISKIN"
setupdataEF = as.data.frame(cbind(new.data.frame$Category, new.data.frame$LifetimeCat,new.data.frame$mWs,
new.data.frame$names,new.data.frame$formula,new.data.frame$PI,
new.data.frame$FinalEF_mean, new.data.frame$FinalEF_sd, new.data.frame$COUNT_EFFINAL,
new.data.frame.rice$FinalEF_mean, new.data.frame.rice$FinalEF_sd, new.data.frame.rice$COUNT_EFFINAL,
new.data.frame.soybean$FinalEF_mean, new.data.frame.soybean$FinalEF_sd, new.data.frame.soybean$COUNT_EFFINAL,
new.data.frame.ag$FinalEF_mean, new.data.frame.ag$FinalEF_sd, new.data.frame.ag$COUNT_EFFINAL,
new.data.frame.slash$FinalEF_mean, new.data.frame.slash$FinalEF_sd, new.data.frame.slash$COUNT_EFFINAL,
new.data.frame.pile$FinalEF_mean, new.data.frame.pile$FinalEF_sd, new.data.frame.pile$COUNT_EFFINAL,
new.data.frame.presc$FinalEF_mean, new.data.frame.presc$FinalEF_sd, new.data.frame.presc$COUNT_EFFINAL,
new.data.frame.grass$FinalEF_mean, new.data.frame.grass$FinalEF_sd, new.data.frame.grass$COUNT_EFFINAL))
# Save for comparison to Akagi and Andreae
if (doEF == 1){save(setupdataEF,file='setupdataEF.RData')}
# Ok, don't want to order nitrogen compounds by lifetimecat
ind = which(setupdataEF$V1 == 2 | setupdataEF$V1 == 3)
setupdataEF$V2[ind] = 1
#setupdataEF =setupdataEF[ with(setupdataEF, order(V1,V2, as.numeric(V3), -as.numeric(V7) )),]#mWs,names, )),]
attach(setupdataEF)
setupdataEF <- setupdataEF[order(V1,V2, as.numeric(V3),-as.numeric(V7)),]
detach(setupdataEF)
#setupdataEF =setupdataEF[ with(setupdataEF, order(Category,LifetimeCat, -FinalEF )),]#mWs,names, )),]
setupdataEF= subset(setupdataEF, select = -c( V1, V2,V3))
# ------ ERs -----
setupdataER = as.data.frame(cbind(new.data.frame$Category, new.data.frame$LifetimeCat,new.data.frame$mWs,
new.data.frame$names,new.data.frame$formula,new.data.frame$PI,
new.data.frame$FinalERtoCO_mean, new.data.frame$FinalERtoCO_sd, new.data.frame$COUNT_EFFINAL,
new.data.frame.rice$FinalERtoCO_mean, new.data.frame.rice$FinalERtoCO_sd, new.data.frame.rice$COUNT_EFFINAL,
new.data.frame.soybean$FinalERtoCO_mean, new.data.frame.soybean$FinalERtoCO_sd, new.data.frame.soybean$COUNT_EFFINAL,
new.data.frame.ag$FinalERtoCO_mean, new.data.frame.ag$FinalERtoCO_sd, new.data.frame.ag$COUNT_EFFINAL,
new.data.frame.slash$FinalERtoCO_mean, new.data.frame.slash$FinalERtoCO_sd, new.data.frame.slash$COUNT_EFFINAL,
new.data.frame.pile$FinalERtoCO_mean, new.data.frame.pile$FinalERtoCO_sd, new.data.frame.pile$COUNT_EFFINAL,
new.data.frame.presc$FinalERtoCO_mean, new.data.frame.presc$FinalERtoCO_sd, new.data.frame.presc$COUNT_EFFINAL,
new.data.frame.grass$FinalERtoCO_mean, new.data.frame.grass$FinalERtoCO_sd, new.data.frame.grass$COUNT_EFFINAL))
# Ok, don't want to order nitrogen compounds by lifetimecat
ind = which(setupdataER$V1 == 2 | setupdataER$V1 == 3)
setupdataER$V2[ind] = 1
setupdataER =setupdataER[ with(setupdataER, order(V1,V2, as.numeric(V3) )),]#mWs,names, )),]
#setupdataER =setupdataER[ with(setupdataER, order(Category,LifetimeCat, -FinalER )),]#mWs,names, )),]
setupdataER= subset(setupdataER, select = -c( V1, V2,V3))
# ----------- wheat and shrub + blackwater
setupdataWHEATSHRUB = as.data.frame(cbind(new.data.frame.wheat$Category, new.data.frame.wheat$LifetimeCat,new.data.frame$mWs,
new.data.frame.wheat$names,new.data.frame.wheat$formula,new.data.frame.wheat$PI,
new.data.frame.wheat$FinalEF, new.data.frame.wheat$FinalEF_25, new.data.frame.wheat$FinalEF_75,
new.data.frame.wheat$FinalERtoCO, new.data.frame.wheat$FinalERtoCO_25, new.data.frame.wheat$FinalERtoCO_75,
new.data.frame.wheat$COUNT_EFFINAL,
new.data.frame.shrub$FinalEF, new.data.frame.shrub$FinalEF_25, new.data.frame.shrub$FinalEF_75,
new.data.frame.shrub$FinalERtoCO, new.data.frame.shrub$FinalERtoCO_25, new.data.frame.shrub$FinalERtoCO_75,
new.data.frame.shrub$COUNT_EFFINAL))
setupdataWHEATSHRUB =setupdataWHEATSHRUB[ with(setupdataWHEATSHRUB, order(V1,V2, -as.numeric(V3) )),]#mWs,names, )),]
#setupdataEF =setupdataEF[ with(setupdataEF, order(Category,LifetimeCat, -FinalEF )),]#mWs,names, )),]
setupdataWHEATSHRUB = subset(setupdataWHEATSHRUB, select = -c( V1, V2, V3))
# ------------
#rownames(setupdata) = new.data.frame$Group.2
#colnames(setupdata)= c("EF, g/kg","25%","75%","ERtoCO, ppt/ppb","n", "EF, g/kg","25%","75%","ERtoCO, ppt/ppb","n")
save(setupdataEF, file='setupdataEF.RData')
save(setupdataER, file='setupdataER.RData')
require(stringr)
if (doEF == 1){ setupdata = setupdataEF}
if (doER == 1){ setupdata = setupdataER}
setupdata2 = setupdata
dd=dim(setupdata2)
for (i in 1:length(setupdata2$V6)){
for (j in 4:dd[2]){
tt = as.numeric(setupdata2[i,j])
if(is.finite(tt)){
if (tt == 0){
setupdata2[i,j] = "NA"
}
}
if (j != 6 & j != 9 & j != 12 & j != 15 & j != 18 & j != 21 & j != 24 & j != 27){
tt = as.numeric(setupdata2[i,j])
if (is.na(tt)){
setupdata2[i,j] = "NA"
# } else if {
# setupdata2[i,j]=sprintf('%1.3g',tt)
# }
} else if (tt >= 1E13){
setupdata2[i,j] = sprintf('%1.2e',tt)
} else if (tt >= 50 & tt <1E13){
setupdata2[i,j] = sprintf('%1.0f',tt)
} else if (tt >=1 & tt <= 50){
setupdata2[i,j] = sprintf('%1.2f',tt)
}else if (tt >= 0.001 & tt < 1){
setupdata2[i,j] = sprintf('%0.3f',tt)
}else {#if (tt <= 0.001){
setupdata2[i,j] = sprintf('%0.2e',tt)
}
}
#print(c(i,j,tt, setupdata[i,j]))
}
}
# make sure formats match for sd
for (i in 1:length(setupdata2$V7)){
if (setupdata2$V8[i] != "NA" & setupdata2$V7[i] != "NA"){
if (as.numeric(setupdata2$V8[i]) < 0.001 & as.numeric(setupdata2$V7[i]) >= 0.001){
setupdata2$V8[i] = sprintf('%0.4f',as.numeric(setupdata2$V8[i]))
}
}
if (setupdata2$V11[i] != "NA" & setupdata2$V10[i] != "NA"){
if (as.numeric(setupdata2$V11[i]) < 0.001 & as.numeric(setupdata2$V10[i]) >= 0.001){
setupdata2$V11[i] = sprintf('%0.4f',as.numeric(setupdata2$V11[i]))
}
}
if (setupdata2$V14[i] != "NA" & setupdata2$V13[i] != "NA"){
if (as.numeric(setupdata2$V14[i]) < 0.001 & as.numeric(setupdata2$V13[i]) >= 0.001){
setupdata2$V14[i] = sprintf('%0.4f',as.numeric(setupdata2$V14[i]))
}
}
if (setupdata2$V17[i] != "NA" & setupdata2$V16[i] != "NA"){
if (as.numeric(setupdata2$V17[i]) < 0.001 & as.numeric(setupdata2$V16[i]) >= 0.001){
setupdata2$V17[i] = sprintf('%0.4f',as.numeric(setupdata2$V17[i]))
}
}
if (setupdata2$V20[i] != "NA" & setupdata2$V19[i] != "NA"){
if (as.numeric(setupdata2$V20[i]) < 0.001 & as.numeric(setupdata2$V19[i]) >= 0.001){
setupdata2$V20[i] = sprintf('%0.4f',as.numeric(setupdata2$V20[i]))
}
}
if (setupdata2$V23[i] != "NA" & setupdata2$V22[i] != "NA"){
if (as.numeric(setupdata2$V23[i]) < 0.001 & as.numeric(setupdata2$V22[i]) >= 0.001){
setupdata2$V23[i] = sprintf('%0.4f',as.numeric(setupdata2$V23[i]))
}
}
if (setupdata2$V25[i] != "NA" & setupdata2$V26[i] != "NA"){
if (as.numeric(setupdata2$V26[i]) < 0.001 & as.numeric(setupdata2$V25[i]) >= 0.001){
setupdata2$V26[i] = sprintf('%0.4f',as.numeric(setupdata2$V26[i]))
}
}
if (setupdata2$V28[i] != "NA" & setupdata2$V29[i] != "NA"){
if (as.numeric(setupdata2$V29[i]) < 0.001 & as.numeric(setupdata2$V28[i]) >= 0.001){
setupdata2$V29[i] = sprintf('%0.4f',as.numeric(setupdata2$V29[i]))
}
}
}
# Clean up format
dd=dim(setupdata2)
for (i in 1:length(setupdata2$V6)){
for (j in 4:dd[2]){
setupdata2[i,j]= str_replace_all(setupdata2[i,j],"0.0e+00","")
setupdata2[i,j]= str_replace_all(setupdata2[i,j],"e-0","e-")
}
}
# fixcolnames
tct = seq(3,dd[2]+2)
colnames(setupdata2) = paste0('V',tct)
ind = which(setupdata2$V6 != "NA" & is.finite(as.numeric(setupdata2$V7) ))
setupdata2$V6[ind] = paste(as.numeric(setupdata2$V6[ind])," (",as.numeric(setupdata2$V7[ind]),")", sep='')
setupdata2= subset(setupdata2, select = -c(V7) )
# -------- V8 is count
ind = which(setupdata2$V9 != "NA" & is.finite(as.numeric(setupdata2$V10) ))
setupdata2$V9[ind] = paste(setupdata2$V9[ind]," (",setupdata2$V10[ind],")", sep='')
setupdata2= subset(setupdata2, select = -c(V10) )
# -------- V11 is count
ind = which(setupdata2$V12 != "NA" & is.finite(as.numeric(setupdata2$V13) ))
setupdata2$V12[ind] = paste(setupdata2$V12[ind]," (",setupdata2$V13[ind],")", sep='')
setupdata2= subset(setupdata2, select = -c(V13) )
# -------- V14 is count
ind = which(setupdata2$V15 != "NA" & is.finite(as.numeric(setupdata2$V16) ))
setupdata2$V15[ind] = paste(setupdata2$V15[ind]," (",setupdata2$V16[ind],")", sep='')
setupdata2= subset(setupdata2, select = -c(V16) )
# -------- V17 is count
ind = which(setupdata2$V18 != "NA" & is.finite(as.numeric(setupdata2$V19) ))
setupdata2$V18[ind] = paste(setupdata2$V18[ind]," (",setupdata2$V19[ind],")", sep='')
setupdata2= subset(setupdata2, select = -c(V19) )
# -------- V20 is count
ind = which(setupdata2$V21 != "NA" & is.finite(as.numeric(setupdata2$V22) ))
setupdata2$V21[ind] = paste(setupdata2$V21[ind]," (",setupdata2$V22[ind], ")",sep='')
setupdata2= subset(setupdata2, select = -c(V22) )
# -------- V23 is count
ind = which(setupdata2$V24 != "NA" & is.finite(as.numeric(setupdata2$V25) ))
setupdata2$V24[ind] = paste(setupdata2$V24[ind]," (",setupdata2$V25[ind], ")",sep='')
setupdata2= subset(setupdata2, select = -c(V25) )
# -------- V26 is count
ind = which(setupdata2$V27 != "NA" & is.finite(as.numeric(setupdata2$V28) ))
setupdata2$V27[ind] = paste(setupdata2$V27[ind]," (",setupdata2$V28[ind], ")",sep='')
setupdata2= subset(setupdata2, select = -c(V28) )
setHtmlTableTheme(theme = "Google docs")
# wheat shrub
tct = seq(3,19)
colnames(setupdataWHEATSHRUB) = paste0('V',tct)
ind = which(setupdataWHEATSHRUB$V6 != "NA" & setupdataWHEATSHRUB$V7 != setupdataWHEATSHRUB$V8 & is.finite(as.numeric(setupdataWHEATSHRUB$V7) ))
setupdataWHEATSHRUB$V6[ind] = paste(setupdataWHEATSHRUB$V6[ind]," [",setupdataWHEATSHRUB$V7[ind], '-',setupdataWHEATSHRUB$V8[ind],"]", sep='')
setupdataWHEATSHRUB= subset(setupdataWHEATSHRUB, select = -c(V7,V8) )
ind = which(setupdataWHEATSHRUB$V9 != "NA" & setupdataWHEATSHRUB$V10 != setupdataWHEATSHRUB$V11 & is.finite(as.numeric(setupdataWHEATSHRUB$V10) ))
setupdataWHEATSHRUB$V9[ind] = paste(setupdataWHEATSHRUB$V9[ind]," [",setupdataWHEATSHRUB$V10[ind], '-',setupdataWHEATSHRUB$V11[ind],"]", sep='')
setupdataWHEATSHRUB= subset(setupdataWHEATSHRUB, select = -c(V10,V11) )
ind = which(setupdataWHEATSHRUB$V13 != "NA" & setupdataWHEATSHRUB$V14 != setupdataWHEATSHRUB$V15 & is.finite(as.numeric(setupdataWHEATSHRUB$V14) ))
setupdataWHEATSHRUB$V13[ind] = paste(setupdataWHEATSHRUB$V13[ind]," [",setupdataWHEATSHRUB$V14[ind], '-',setupdataWHEATSHRUB$V15[ind],"]", sep='')
setupdataWHEATSHRUB= subset(setupdataWHEATSHRUB, select = -c(V14,V15) )
ind = which(setupdataWHEATSHRUB$V16 != "NA" & setupdataWHEATSHRUB$V17 != setupdataWHEATSHRUB$V18 & is.finite(as.numeric(setupdataWHEATSHRUB$V17) ))
setupdataWHEATSHRUB$V16[ind] = paste(setupdataWHEATSHRUB$V16[ind]," [",setupdataWHEATSHRUB$V17[ind], '-',setupdataWHEATSHRUB$V18[ind],"]", sep='')
setupdataWHEATSHRUB= subset(setupdataWHEATSHRUB, select = -c(V17,V18) )
tt=unique(new.data.frame$Category)
test = aggregate(new.data.frame$Category, by=list(new.data.frame$Category), FUN='sum', na.rm=TRUE)
test$val = test$x/test$Group.1; test$val[1] = 3
output <-
matrix(nrow=length(new.data.frame$Group.2),ncol = 20, byrow = TRUE)
print('Fix instrument names ')
# ------ Fix instrument names -----------
ind = which(setupdata2$V5 == 'BLAKE')
setupdata2$V5[ind] = 'WAS'
setupdata2$V5[3] = 'NIR spect.'
ind = which(setupdata2$V5 == 'DISKIN')
setupdata2$V5[ind] = 'DACOM'
ind = which(setupdata2$V5 == 'JIMENEZ')
setupdata2$V5[ind] = 'AMS'
ind = which(setupdata2$V5 == 'ppt')
setupdata2$V5[ind] = 'TOGA'
ind = which(setupdata2$V5 == 'ppt+BLAKE+GILMAN')
setupdata2$V5[ind] = 'TOGA, iWAS, WAS'
ind = which(setupdata2$V5 == 'BLAKE+ppt+GILMAN')
setupdata2$V5[ind] = 'TOGA, iWAS, WAS'
ind = which(setupdata2$V5 == 'GILMAN+ppt')
setupdata2$V5[ind] = 'TOGA, iWAS'
ind = which(setupdata2$V5 == 'ppt+GILMAN')
setupdata2$V5[ind] = 'TOGA, iWAS'
ind = which(setupdata2$V5 == 'GILMAN+BLAKE')
setupdata2$V5[ind] = 'iWAS, WAS'
ind = which(setupdata2$V5 == 'BLAKE+GILMAN')
setupdata2$V5[ind] = 'iWAS, WAS'
ind = which(setupdata2$V5 == 'APEL+BLAKE')
setupdata2$V5[ind] = 'TOGA, WAS'
ind = which(setupdata2$V5 == 'BLAKE+ppt')
setupdata2$V5[ind] = 'TOGA, WAS'
ind = which(setupdata2$V5 == 'ppt+BLAKE')
setupdata2$V5[ind] = 'TOGA, WAS'
ind = which(setupdata2$V5 == 'ppt+BLAKE+WARNEKE')
setupdata2$V5[ind] = 'PTRMS*, TOGA, WAS'
ind = which(setupdata2$V5 == 'VERES')
setupdata2$V5[ind] = 'NOAA CIMS'
ind = which(setupdata2$V5 == 'WISTHALER')
setupdata2$V5[ind] = 'OSLO PTRMS'
ind = which(setupdata2$V5 == 'FRIED')
setupdata2$V5[ind] = 'CAMS'
ind = which(setupdata2$V5 == 'GILMAN')
setupdata2$V5[ind] = 'iWAS'
ind = which(setupdata2$V5 == 'FRIED+HANISCO')
setupdata2$V5[ind] = 'CAMS, ISAF'
ind = which(setupdata2$V5 == 'GILMAN+FRIED')
setupdata2$V5[ind] = 'iWAS, CAMS'
ind = which(setupdata2$V5 == 'VERES+WARKEKE')
setupdata2$V5[ind] = 'NOAA CIMS, PTRMS*'
ind = which(setupdata2$V5 == 'WARNEKE' | setupdata2$V5 == 'ppbv')
setupdata2$V5[ind] = 'PTRMS*'
ind = which(setupdata2$V5 == 'WOMACK')
setupdata2$V5[ind] = 'ACES'
ind = which(setupdata2$V5 == 'WOMACK+RYERSON')
setupdata2$V5[ind] = 'ACES, NOAA NOyO3'
ind = which(setupdata2$V5 == 'WOMACK+VERES')
setupdata2$V5[ind] = 'ACES, NOAA CIMS'
ind = which(setupdata2$V5 == 'Warneke w/Blake+GILMAN+APEL')
setupdata2$V5[ind] = 'PTRMS*, TOGA+WAS+iWAS spec.'
ind = which(setupdata2$V5 == 'Warneke w/APEL')
setupdata2$V5[ind] = 'PTRMS*, TOGA spec.'
ind = which(setupdata2$V5 == 'WENNBERG')
setupdata2$V5[ind] = 'CIT-CIMS'
ind = which(setupdata2$V5 == 'WARNEKE+ppt+GILMAN')
setupdata2$V5[ind] = 'PTRMS*, TOGA, iWAS'
ind = which(setupdata2$V5 == 'WARNEKE+BLAKE+ppt')
setupdata2$V5[ind] = 'PTRMS*, TOGA, WAS'
ind = which(setupdata2$V5 == 'VERES+WENNBERG+WARNEKE+ppt')
setupdata2$V5[ind] = 'NOAA CIMS, CIT-CIMS, PTRMS*, TOGA'
ind = which(setupdata2$V5 == 'VERES+WENNBERG+ppt+WARNEKE')
setupdata2$V5[ind] = 'NOAA CIMS, CIT-CIMS, PTRMS*, TOGA'
ind = which(setupdata2$V5 == 'VERES+WARNEKE')
setupdata2$V5[ind] = 'NOAA CIMS, PTRMS*'
ind = which(setupdata2$V5 == 'ROLLINS+RYERSON')
setupdata2$V5[ind] = 'NOAA LIF, NOAA NOyO3'
ind = which(setupdata2$V5 == 'ROLLINS')
setupdata2$V5[ind] = 'NOAA LIF'
ind = which(setupdata2$V5 == 'RYERSON')
setupdata2$V5[ind] = 'NOAA NOyO3'
ind = which(setupdata2$V5 == 'SCHWARZ')
setupdata2$V5[ind] = 'NOAA SP2'
ind = which(setupdata2$V5 == 'APEL')
setupdata2$V5[ind] = 'TOGA'
ind = which(setupdata2$V5 == 'BLAKE+GILMAN+FRIED')
setupdata2$V5[ind] = 'CAMS, WAS, iWAS'
ind = which(setupdata2$V5 == 'VERES+WENNBERG+ppt')
setupdata2$V5[ind] = 'NOAA CIMS, CIT-CIMS, TOGA'
ind = which(setupdata2$V5 == 'WARNEKE+ppt+GILMAN+BLAKE')
setupdata2$V5[ind] = 'PTRMS*, TOGA, WAS, iWAS'
# ------ Fix instrument names -----------
ind = which(setupdataWHEATSHRUB$V5 == 'BLAKE')
setupdataWHEATSHRUB$V5[ind] = 'WAS'
setupdataWHEATSHRUB$V5[3] = 'NIR spect.'
ind = which(setupdataWHEATSHRUB$V5 == 'DISKIN')
setupdataWHEATSHRUB$V5[ind] = 'DACOM'
ind = which(setupdataWHEATSHRUB$V5 == 'JIMENEZ')
setupdataWHEATSHRUB$V5[ind] = 'AMS'
ind = which(setupdataWHEATSHRUB$V5 == 'ppt')
setupdataWHEATSHRUB$V5[ind] = 'TOGA'
ind = which(setupdataWHEATSHRUB$V5 == 'ppt+BLAKE+GILMAN')
setupdataWHEATSHRUB$V5[ind] = 'TOGA, iWAS, WAS'
ind = which(setupdataWHEATSHRUB$V5 == 'GILMAN+ppt')
setupdataWHEATSHRUB$V5[ind] = 'TOGA, iWAS'
ind = which(setupdataWHEATSHRUB$V5 == 'GILMAN+BLAKE')
setupdataWHEATSHRUB$V5[ind] = 'iWAS, WAS'
ind = which(setupdataWHEATSHRUB$V5 == 'BLAKE+GILMAN')
setupdataWHEATSHRUB$V5[ind] = 'iWAS, WAS'
ind = which(setupdataWHEATSHRUB$V5 == 'APEL+BLAKE')
setupdataWHEATSHRUB$V5[ind] = 'TOGA, WAS'
ind = which(setupdataWHEATSHRUB$V5 == 'BLAKE+ppt')
setupdataWHEATSHRUB$V5[ind] = 'TOGA, WAS'
ind = which(setupdataWHEATSHRUB$V5 == 'ppt+BLAKE')
setupdataWHEATSHRUB$V5[ind] = 'TOGA, WAS'
ind = which(setupdataWHEATSHRUB$V5 == 'ppt+BLAKE+WARNEKE')
setupdataWHEATSHRUB$V5[ind] = 'PTRMS*, TOGA, WAS'
ind = which(setupdataWHEATSHRUB$V5 == 'VERES')
setupdataWHEATSHRUB$V5[ind] = 'NOAA CIMS'
ind = which(setupdataWHEATSHRUB$V5 == 'WISTHALER')
setupdataWHEATSHRUB$V5[ind] = 'OSLO PTRMS'
ind = which(setupdataWHEATSHRUB$V5 == 'FRIED')
setupdataWHEATSHRUB$V5[ind] = 'CAMS'
ind = which(setupdataWHEATSHRUB$V5 == 'GILMAN')
setupdataWHEATSHRUB$V5[ind] = 'iWAS'
ind = which(setupdataWHEATSHRUB$V5 == 'FRIED+HANISCO')
setupdataWHEATSHRUB$V5[ind] = 'CAMS, ISAF'
ind = which(setupdataWHEATSHRUB$V5 == 'GILMAN+FRIED')
setupdataWHEATSHRUB$V5[ind] = 'iWAS, CAMS'
ind = which(setupdataWHEATSHRUB$V5 == 'VERES+WARKEKE')
setupdataWHEATSHRUB$V5[ind] = 'NOAA CIMS, PTRMS*'
ind = which(setupdataWHEATSHRUB$V5 == 'WARNEKE' | setupdataWHEATSHRUB$V5 == 'ppbv')
setupdataWHEATSHRUB$V5[ind] = 'PTRMS*'
ind = which(setupdataWHEATSHRUB$V5 == 'WOMACK')
setupdataWHEATSHRUB$V5[ind] = 'ACES'
ind = which(setupdataWHEATSHRUB$V5 == 'WOMACK+RYERSON')
setupdataWHEATSHRUB$V5[ind] = 'ACES, NOAA NOyO3'
ind = which(setupdataWHEATSHRUB$V5 == 'WOMACK+VERES')
setupdataWHEATSHRUB$V5[ind] = 'ACES, NOAA CIMS'
ind = which(setupdataWHEATSHRUB$V5 == 'Warneke w/Blake+GILMAN+APEL')
setupdataWHEATSHRUB$V5[ind] = 'PTRMS*, TOGA+WAS+iWAS spec.'
ind = which(setupdataWHEATSHRUB$V5 == 'Warneke w/APEL')
setupdataWHEATSHRUB$V5[ind] = 'PTRMS*, TOGA spec.'
ind = which(setupdataWHEATSHRUB$V5 == 'WENNBERG')
setupdataWHEATSHRUB$V5[ind] = 'CIT-CIMS'
ind = which(setupdataWHEATSHRUB$V5 == 'WARNEKE+ppt+GILMAN')
setupdataWHEATSHRUB$V5[ind] = 'PTRMS*, TOGA, iWAS'
ind = which(setupdataWHEATSHRUB$V5 == 'WARNEKE+BLAKE+ppt')
setupdataWHEATSHRUB$V5[ind] = 'PTRMS*, TOGA, WAS'
ind = which(setupdataWHEATSHRUB$V5 == 'VERES+WENNBERG+WARNEKE+ppt')
setupdataWHEATSHRUB$V5[ind] = 'NOAA CIMS, CIT-CIMS, PTRMS*, TOGA'
ind = which(setupdataWHEATSHRUB$V5 == 'VERES+WARNEKE')
setupdataWHEATSHRUB$V5[ind] = 'NOAA CIMS, PTRMS*'
ind = which(setupdataWHEATSHRUB$V5 == 'ROLLINS+RYERSON')
setupdataWHEATSHRUB$V5[ind] = 'NOAA LIF, NOAA NOyO3'
ind = which(setupdataWHEATSHRUB$V5 == 'ROLLINS')
setupdataWHEATSHRUB$V5[ind] = 'NOAA LIF'
ind = which(setupdataWHEATSHRUB$V5 == 'RYERSON')
setupdataWHEATSHRUB$V5[ind] = 'NOAA NOyO3'
ind = which(setupdataWHEATSHRUB$V5 == 'SCHWARZ')
setupdataWHEATSHRUB$V5[ind] = 'NOAA SP2'
ind = which(setupdataWHEATSHRUB$V5 == 'APEL')
setupdataWHEATSHRUB$V5[ind] = 'TOGA'
ind = which(setupdataWHEATSHRUB$V5 == 'BLAKE+GILMAN+FRIED')
setupdataWHEATSHRUB$V5[ind] = 'CAMS, WAS, iWAS'
ind = which(setupdataWHEATSHRUB$V5 == 'VERES+WENNBERG+ppt')
setupdataWHEATSHRUB$V5[ind] = 'NOAA CIMS, CIT-CIMS, TOGA'
ind = which(setupdataWHEATSHRUB$V5 == 'WARNEKE+ppt+GILMAN+BLAKE')
setupdataWHEATSHRUB$V5[ind] = 'PTRMS*, TOGA, WAS, iWAS'
output=setupdata[,c(2:15)]
headerR = c("Formula","Instrument","EF, g/kg","n", "EF, g/kg","n","EF, g/kg","n","EF, g/kg","n","EF, g/kg","n","EF, g/kg","n")
#
# oldtry = output %>%
# htmlTable(header = headerR,
# rnames = new.data.frame$names,
# rgroup = c("", "Short-lived VOCs","Long-lived VOCs","Nitrogen Containing","Halogen","Aerosol","Sulfur-containing"),
# n.rgroup = c(test$val),
# cgroup = list(c("","","Agricultural Residue","Land Clearing"),
# c("","","Corn", "Rice","Soybean","Grass","Slash","Pile")),
# n.cgroup = list(c(1,1,6,6),
# c(1,1,2, 2,2,2,2,2)),
# caption = "Basic table with both column spanners (groups) and row groups",
# tfoot = "† PM1 includes conversion of OC to OA using the median OA/OC ratio for each pass (~2.0)" ,
# compatibility = getOption("htmlTableCompat", "LibreOffice"))
#
# Try flex table
require(flextable); require(officer)
headerR = c("Names","Formula","Instrument","EF1, g/kg","n1", "EF2, g/kg","n2","EF3, g/kg","n3","EF4, g/kg","n4","EF5, g/kg","n5","EF6, g/kg","n6","EF7, g/kg","n7","EF8, g/kg", "n8")
setupdata=setupdata2
colnames(setupdata) = headerR
colnames(setupdataWHEATSHRUB) = c("Names","Formula","Instrument","EF1, g/kg","ER, ppt/ppb", "n1","EF2, g/kg","ER2, ppt/ppb", "n2")
print('Main table ')
# --------------------------------------- Main table ---------------
ind = which(setupdata$Names == 'Carbon Dioxide')
newrow = setupdata[ind,]; newrow$`EF1, g/kg`=''; newrow$`EF2, g/kg`='';newrow$`EF3, g/kg`=''; newrow$`EF4, g/kg`=''
newrow$`EF5, g/kg`='';newrow$`EF6, g/kg` = ''; newrow$`EF7, g/kg`='';newrow$`EF8, g/kg` = ''; newrow$Formula=''; newrow$Instrument='';newrow$Names = 'Short-lived NMVOC'
newrow$n1=''; newrow$n2=''; newrow$n3 = ''; newrow$n4=''; newrow$n5=''; newrow$n6 = '' ; newrow$n7=''; newrow$n8=''
setupdata = rbind(setupdata[1:ind,],newrow,setupdata[-(1:ind),])
ind = which(setupdata$Names == 'Ethyne'); ind = ind-1
newrow = setupdata[ind,]; newrow$`EF1, g/kg`=''; newrow$`EF2, g/kg`='';newrow$`EF3, g/kg`=''; newrow$`EF4, g/kg`=''
newrow$`EF5, g/kg`='';newrow$`EF6, g/kg` = ''; newrow$`EF7, g/kg`='';newrow$`EF8, g/kg` = ''; newrow$Formula=''; newrow$Instrument='';newrow$Names = 'Long-lived NMVOC'
newrow$n1=''; newrow$n2=''; newrow$n3 = ''; newrow$n4=''; newrow$n5=''; newrow$n6 = '' ; newrow$n7=''; newrow$n8=''
setupdata = rbind(setupdata[1:ind,],newrow,setupdata[-(1:ind),])
ind = which(setupdata$Names == 'Methanethiol'); ind = ind-1
newrow = setupdata[ind,]; newrow$`EF1, g/kg`=''; newrow$`EF2, g/kg`='';newrow$`EF3, g/kg`=''; newrow$`EF4, g/kg`=''
newrow$`EF5, g/kg`='';newrow$`EF6, g/kg` = ''; newrow$`EF7, g/kg`='';newrow$`EF8, g/kg` = ''; newrow$Formula=''; newrow$Instrument='';newrow$Names = 'Sulfur-containing Species'
newrow$n1=''; newrow$n2=''; newrow$n3 = ''; newrow$n4=''; newrow$n5=''; newrow$n6 = '' ; newrow$n7=''; newrow$n8=''
setupdata = rbind(setupdata[1:ind,],newrow,setupdata[-(1:ind),])
ind = which(setupdata$Names == 'Black carbon'); ind = ind-1
newrow = setupdata[ind,]; newrow$`EF1, g/kg`=''; newrow$`EF2, g/kg`='';newrow$`EF3, g/kg`=''; newrow$`EF4, g/kg`=''
newrow$`EF5, g/kg`='';newrow$`EF6, g/kg` = ''; newrow$`EF7, g/kg`='';newrow$`EF8, g/kg` = ''; newrow$Formula=''; newrow$Instrument='';newrow$Names = 'Aerosols'
newrow$n1=''; newrow$n2=''; newrow$n3 = ''; newrow$n4=''; newrow$n5=''; newrow$n6 = '' ; newrow$n7=''; newrow$n8=''
setupdata = rbind(setupdata[1:ind,],newrow,setupdata[-(1:ind),])
ind = which(setupdata$Names == 'Methyl chloride'); ind = ind-1
newrow = setupdata[ind,]; newrow$`EF1, g/kg`=''; newrow$`EF2, g/kg`='';newrow$`EF3, g/kg`=''; newrow$`EF4, g/kg`=''
newrow$`EF5, g/kg`='';newrow$`EF6, g/kg` = ''; newrow$`EF7, g/kg`='';newrow$`EF8, g/kg` = ''; newrow$Formula=''; newrow$Instrument='';newrow$Names = 'Halogenated Species'
newrow$n1=''; newrow$n2=''; newrow$n3 = ''; newrow$n4=''; newrow$n5=''; newrow$n6 = '' ; newrow$n7=''; newrow$n8=''
setupdata = rbind(setupdata[1:ind,],newrow,setupdata[-(1:ind),])
ind = which(setupdata$Names == 'Hydrogen cyanide'); ind = ind-1
newrow = setupdata[ind,]; newrow$`EF1, g/kg`=''; newrow$`EF2, g/kg`='';newrow$`EF3, g/kg`=''; newrow$`EF4, g/kg`=''
newrow$`EF5, g/kg`='';newrow$`EF6, g/kg` = ''; newrow$`EF7, g/kg`='';newrow$`EF8, g/kg` = ''; newrow$Formula=''; newrow$Instrument='';newrow$Names = 'Nitrogen-containing Species'
newrow$n1=''; newrow$n2=''; newrow$n3 = ''; newrow$n4=''; newrow$n5=''; newrow$n6 = '' ; newrow$n7=''; newrow$n8=''
setupdata = rbind(setupdata[1:ind,],newrow,setupdata[-(1:ind),])
print("Wheat shrub table")
# ---------- Wheat shrub table-----------------
ind = which(setupdataWHEATSHRUB$Names == 'Carbon Dioxide')
newrow = setupdataWHEATSHRUB[ind,]; newrow$`EF1, g/kg`=''; newrow$`EF2, g/kg`='';newrow$`ER, ppt/ppb`=''; newrow$`ER2, ppt/ppb`=''
newrow$Formula=''; newrow$Instrument='';newrow$Names = 'Short-lived VOC'; newrow$n1=''; newrow$n2=''
setupdataWHEATSHRUB = rbind(setupdataWHEATSHRUB[1:ind,],newrow,setupdataWHEATSHRUB[-(1:ind),])
ind = which(setupdataWHEATSHRUB$Names == 'Ethyne'); ind = ind-1
newrow = setupdataWHEATSHRUB[ind,]; newrow$`EF1, g/kg`=''; newrow$`EF2, g/kg`='';newrow$`ER, ppt/ppb`=''; newrow$`ER2, ppt/ppb`=''
newrow$Formula=''; newrow$Instrument='';newrow$Names = 'Long-lived VOC'; newrow$n1=''; newrow$n2=''
setupdataWHEATSHRUB = rbind(setupdataWHEATSHRUB[1:ind,],newrow,setupdataWHEATSHRUB[-(1:ind),])
ind = which(setupdataWHEATSHRUB$Names == 'Methanethiol'); ind = ind-1
newrow = setupdataWHEATSHRUB[ind,]; newrow$`EF1, g/kg`=''; newrow$`EF2, g/kg`='';newrow$`ER, ppt/ppb`=''; newrow$`ER2, ppt/ppb`=''
newrow$Formula=''; newrow$Instrument='';newrow$Names = 'Sulfur-containing Species'; newrow$n1=''; newrow$n2=''
setupdataWHEATSHRUB = rbind(setupdataWHEATSHRUB[1:ind,],newrow,setupdataWHEATSHRUB[-(1:ind),])
ind = which(setupdataWHEATSHRUB$Names == 'Black carbon'); ind = ind-1
newrow = setupdataWHEATSHRUB[ind,]; newrow$`EF1, g/kg`=''; newrow$`EF2, g/kg`='';newrow$`ER, ppt/ppb`=''; newrow$`ER2, ppt/ppb`=''
newrow$Formula=''; newrow$Instrument='';newrow$Names = 'Aerosols'; newrow$n1=''; newrow$n2=''
setupdataWHEATSHRUB = rbind(setupdataWHEATSHRUB[1:ind,],newrow,setupdataWHEATSHRUB[-(1:ind),])
ind = which(setupdataWHEATSHRUB$Names == 'Methyl chloride'); ind = ind-1
newrow = setupdataWHEATSHRUB[ind,]; newrow$`EF1, g/kg`=''; newrow$`EF2, g/kg`='';newrow$`ER, ppt/ppb`=''; newrow$`ER2, ppt/ppb`=''
newrow$Formula=''; newrow$Instrument='';newrow$Names = 'Halogenated Species'; newrow$n1=''; newrow$n2=''
setupdataWHEATSHRUB = rbind(setupdataWHEATSHRUB[1:ind,],newrow,setupdataWHEATSHRUB[-(1:ind),])
ind = which(setupdataWHEATSHRUB$Names == 'Hydrogen cyanide'); ind = ind-1
newrow = setupdataWHEATSHRUB[ind,]; newrow$`EF1, g/kg`=''; newrow$`EF2, g/kg`='';newrow$`ER, ppt/ppb`=''; newrow$`ER2, ppt/ppb`=''
newrow$Formula=''; newrow$Instrument='';newrow$Names = 'Nitrogen-containing Species'; newrow$n1=''; newrow$n2=''
setupdataWHEATSHRUB = rbind(setupdataWHEATSHRUB[1:ind,],newrow,setupdataWHEATSHRUB[-(1:ind),])
# -------- Main table -----
ft <- flextable(setupdata)
ft <- theme_vanilla(ft)
ft <- add_header_row(ft,
colwidths = c(1,1,1,2,2,2,2,2,2,2,2),
values = c("A","B","C","Corn", "Rice","Soybean","Ag","Slash","Pile","Presc","Grass"))
ft <- add_header_row(ft,
colwidths = c(1,1,1,8,8),
values = c('','','','Agricultural Residue','Land Clearing'))
ft = fontsize(ft,part="body", size=6)
ft = fontsize(ft,part="header", size=6)
ft <- line_spacing(ft, space = 1, part = "all")
ft = align(ft,part="header",align="center")
ww=.7; ww2= 0.3
sc = 1
ft = width(ft,j=c(2,3,4,6,8,10,12,14,16,18),width = ww*sc)
ft = width(ft,j=c(5,7,9,11,13,15,17,19),width = ww2*sc)
ft = width(ft,j=1,width = 1)
#ft <- autofit(ft)
#save_as_docx(ft,path='/Users/ktravis1/OneDrive - NASA/FIREX/test.docx')
#ft = fit_to_width(ft,max_width = 2, max_iter = 5)
sect_properties <- prop_section(
page_size = page_size(orient = "landscape",
width = 8.3, height = 11.7),
type = "continuous",
page_margins = page_mar()
)
# ------------ Wheat Shrub -----
ftWHEATSHRUB <- flextable(setupdataWHEATSHRUB)
ftWHEATSHRUB <- theme_vanilla(ftWHEATSHRUB)
ftWHEATSHRUB <- add_header_row(ftWHEATSHRUB,
colwidths = c(1,1,1,3,3),
values = c("A","B","C","Wheat", "Shrub"))
ftWHEATSHRUB = fontsize(ftWHEATSHRUB,part="body", size=6)
ftWHEATSHRUB = fontsize(ftWHEATSHRUB,part="header", size=6)
ftWHEATSHRUB <- line_spacing(ftWHEATSHRUB, space = 1, part = "all")
ftWHEATSHRUB = align(ftWHEATSHRUB,part="header",align="center")
ww=1; ww2= 0.3
ftWHEATSHRUB = width(ftWHEATSHRUB,j=c(2,3,4),width = ww)
ftWHEATSHRUB = width(ftWHEATSHRUB,j=1,width = 1)
#ftWHEATSHRUB <- autofit(ftWHEATSHRUB)
#save_as_docx(ftWHEATSHRUB,path='/Users/ktravis1/OneDrive - NASA/FIREX/test.docx')
#ftWHEATSHRUB = fit_to_width(ftWHEATSHRUB,max_width = 2, max_iter = 5)
sect_properties <- prop_section(
page_size = page_size(orient = "landscape",
width = 8.3, height = 11.7),
type = "continuous",
page_margins = page_mar()
)
if (doEF == 1){ save_as_docx(`Emission Factors` = ft, path ='FIREXAQEFmean.docx', pr_section = sect_properties)}
if (doER == 1){ save_as_docx(`Emission Ratios` = ft, path ='FIREXAQERmean.docx', pr_section = sect_properties)}
if (dowheatshrub == 1){
save_as_docx(`WheatShrub` = ftWHEATSHRUB, path='testWheatShrub.docx', pr_section = sect_properties)
}
#ft <- add_footer_lines(ft, "Daily air quality measurements in New York, May to September 1973.")
##ft <- color(ft, part = "footer", color = "#666666")
#ft <- set_caption(ft, caption = "New York Air Quality Measurements")
#setupdata$Lifetime = NaN
#for (i in 1:length(setupdata$Names)){
# ind = which(allBOTH.filter$names == setupdata$Names[i])
# setupdata$Lifetime[i] = allBOTH.filter$lifetime[ind[1]]
#}
# Supplemental Table
# Include R2 to CO