global format and functoin to remove growth outlier

Makefile

@@ -27,7 +27,7 @@ $(D2)/TRY/data.TRY.std.rds:
 BCI: $(D3)/BCI/Done.txt
 
 $(D3)/BCI/Done.txt: R/process.data/process-fun.R $(D2)/BCI/traits.csv
-	Rscript -e "source('$<'); process_bigplot_dataset('BCI', Rlim=15,std.traits='local'); process_bigplot_dataset('BCI', Rlim=15,std.traits='no'); process_bigplot_dataset('BCI', Rlim=15,std.traits='global');"
+	Rscript -e "source('$<'); process_bigplot_dataset('BCI', Rlim=15,std.traits='local'); process_bigplot_dataset('BCI', Rlim=15,std.traits='global'); process_bigplot_dataset('BCI', Rlim=15,std.traits='no');"
 
 $(D2)/BCI/traits.csv: R/find.trait/BCI.R R/find.trait/trait-fun.R $(D2)/BCI/tree.csv 
 	Rscript $<
@@ -40,7 +40,7 @@ $(D2)/BCI/tree.csv: R/format.data/BCI.R $(shell find $(D1)/BCI -type f)
 Japan: $(D3)/Japan/Done.txt
 
 $(D3)/Japan/Done.txt: R/process.data/process-fun.R $(D2)/Japan/traits.csv
-	Rscript -e "source('$<'); process_bigplot_dataset('Japan', Rlim=15,std.traits='local');  process_bigplot_dataset('Japan', Rlim=15,std.traits='no'); process_bigplot_dataset('Japan', Rlim=15,std.traits='global');"
+	Rscript -e "source('$<'); process_bigplot_dataset('Japan', Rlim=15,std.traits='local');  process_bigplot_dataset('Japan', Rlim=15,std.traits='global'); process_bigplot_dataset('Japan', Rlim=15,std.traits='no');"
 
 $(D2)/Japan/traits.csv: R/find.trait/Japan.R R/find.trait/trait-fun.R $(D2)/Japan/tree.csv 
 	Rscript $<
@@ -65,7 +65,7 @@ $(D2)/Luquillo/tree.csv: R/format.data/Luquillo.R $(shell find $(D1)/Luquillo -t
 Mbaiki: $(D3)/Mbaiki/Done.txt
 
 $(D3)/Mbaiki/Done.txt: R/process.data/process-fun.R $(D2)/Mbaiki/traits.csv
-	Rscript -e "source('$<'); process_bigplot_dataset('Mbaiki', Rlim=15,std.traits='local'); process_bigplot_dataset('Mbaiki', Rlim=15,std.traits='no'); process_bigplot_dataset('Mbaiki', Rlim=15,std.traits='global');"
+	Rscript -e "source('$<'); process_bigplot_dataset('Mbaiki', Rlim=15,std.traits='local'); process_bigplot_dataset('Mbaiki', Rlim=15,std.traits='global'); process_bigplot_dataset('Mbaiki', Rlim=15,std.traits='no');"
 
 $(D2)/Mbaiki/traits.csv: R/find.trait/Mbaiki.R R/find.trait/trait-fun.R $(D2)/Mbaiki/tree.csv 
 	Rscript $<
@@ -90,7 +90,7 @@ $(D2)/Canada/tree.csv: R/format.data/Canada.R $(shell find $(D1)/Canada -type f)
 France: $(D3)/France/Done.txt
 
 $(D3)/France/Done.txt: R/process.data/process-fun.R $(D2)/France/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('France',std.traits='local'); process_inventory_dataset('France',std.traits='no');process_inventory_dataset('France',std.traits='global');"
+	Rscript -e "source('$<'); process_inventory_dataset('France',std.traits='local'); process_inventory_dataset('France',std.traits='global');process_inventory_dataset('France',std.traits='no');"
 
 $(D2)/France/traits.csv: R/find.trait/France.R R/find.trait/trait-fun.R $(D2)/France/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -103,7 +103,7 @@ $(D2)/France/tree.csv: R/format.data/France.R $(shell find $(D1)/France -type f)
 Fushan: $(D3)/Fushan/Done.txt
 
 $(D3)/Fushan/Done.txt: R/process.data/process-fun.R $(D2)/Fushan/traits.csv
-	Rscript -e "source('$<'); process_bigplot_dataset('Fushan', Rlim=15,std.traits='local'); process_bigplot_dataset('Fushan', Rlim=15,std.traits='no');process_bigplot_dataset('Fushan', Rlim=15,std.traits='global');"
+	Rscript -e "source('$<'); process_bigplot_dataset('Fushan', Rlim=15,std.traits='local'); process_bigplot_dataset('Fushan', Rlim=15,std.traits='global');process_bigplot_dataset('Fushan', Rlim=15,std.traits='no');"
 
 
 $(D2)/Fushan/traits.csv: R/find.trait/Fushan.R R/find.trait/trait-fun.R $(D2)/Fushan/tree.csv 
@@ -117,7 +117,7 @@ $(D2)/Fushan/tree.csv: R/format.data/Fushan.R $(shell find $(D1)/Fushan -type f)
 NSW: $(D3)/NSW/Done.txt
 
 $(D3)/NSW/Done.txt: R/process.data/process-fun.R $(D2)/NSW/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('NSW',std.traits='local');  process_inventory_dataset('NSW',std.traits='no');process_inventory_dataset('NSW',std.traits='global');"
+	Rscript -e "source('$<'); process_inventory_dataset('NSW',std.traits='local');  process_inventory_dataset('NSW',std.traits='global');process_inventory_dataset('NSW',std.traits='no');"
 
 $(D2)/NSW/traits.csv: R/find.trait/NSW.R R/find.trait/trait-fun.R $(D2)/NSW/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -130,7 +130,7 @@ $(D2)/NSW/tree.csv: R/format.data/NSW.R $(shell find $(D1)/NSW -type f)
 NVS: $(D3)/NVS/Done.txt
 
 $(D3)/NVS/Done.txt: R/process.data/process-fun.R $(D2)/NVS/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('NVS',std.traits='local');  process_inventory_dataset('NVS',std.traits='no'); process_inventory_dataset('NVS',std.traits='global');"
+	Rscript -e "source('$<'); process_inventory_dataset('NVS',std.traits='local');  process_inventory_dataset('NVS',std.traits='global'); process_inventory_dataset('NVS',std.traits='no');"
 
 $(D2)/NVS/traits.csv: R/find.trait/NVS.R R/find.trait/trait-fun.R $(D2)/NVS/tree.csv 
 	Rscript $<
@@ -143,7 +143,7 @@ $(D2)/NVS/tree.csv: R/format.data/NVS.R $(shell find $(D1)/NVS -type f)
 Paracou: $(D3)/Paracou/Done.txt
 
 $(D3)/Paracou/Done.txt: R/process.data/process-fun.R $(D2)/Paracou/traits.csv
-	Rscript -e "source('$<'); process_bigplot_dataset('Paracou', Rlim=15,std.traits='local');  process_bigplot_dataset('Paracou', Rlim=15,std.traits='no');  process_bigplot_dataset('Paracou', Rlim=15,std.traits='global');"
+	Rscript -e "source('$<'); process_bigplot_dataset('Paracou', Rlim=15,std.traits='local');  process_bigplot_dataset('Paracou', Rlim=15,std.traits='global');  process_bigplot_dataset('Paracou', Rlim=15,std.traits='no');"
 
 $(D2)/Paracou/traits.csv: R/find.trait/Paracou.R R/find.trait/trait-fun.R $(D2)/Paracou/tree.csv 
 	Rscript $<
@@ -156,7 +156,7 @@ $(D2)/Paracou/tree.csv: R/format.data/Paracou.R $(shell find $(D1)/Paracou -type
 Spain: $(D3)/Spain/Done.txt
 
 $(D3)/Spain/Done.txt: R/process.data/process-fun.R $(D2)/Spain/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('Spain',std.traits='local');  process_inventory_dataset('Spain',std.traits='no'); process_inventory_dataset('Spain',std.traits='global');"
+	Rscript -e "source('$<'); process_inventory_dataset('Spain',std.traits='local');  process_inventory_dataset('Spain',std.traits='global'); process_inventory_dataset('Spain',std.traits='no');"
 
 $(D2)/Spain/traits.csv: R/find.trait/Spain.R R/find.trait/trait-fun.R $(D2)/Spain/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -169,7 +169,7 @@ $(D2)/Spain/tree.csv: R/format.data/Spain.R $(shell find $(D1)/Spain -type f)
 Sweden: $(D3)/Sweden/Done.txt
 
 $(D3)/Sweden/Done.txt: R/process.data/process-fun.R  $(D2)/Sweden/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('Sweden',std.traits='local');  process_inventory_dataset('Sweden',std.traits='no'); process_inventory_dataset('Sweden',std.traits='global');"
+	Rscript -e "source('$<'); process_inventory_dataset('Sweden',std.traits='local');  process_inventory_dataset('Sweden',std.traits='global'); process_inventory_dataset('Sweden',std.traits='no');"
 
 $(D2)/Sweden/traits.csv: R/find.trait/Sweden.R R/find.trait/trait-fun.R $(D2)/Sweden/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -182,7 +182,7 @@ $(D2)/Sweden/tree.csv: R/format.data/Sweden.R $(shell find $(D1)/Sweden -type f)
 Swiss: $(D3)/Swiss/Done.txt
 
 $(D3)/Swiss/Done.txt: R/process.data/process-fun.R $(D2)/Swiss/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('Swiss',std.traits='local');  process_inventory_dataset('Swiss',std.traits='no'); process_inventory_dataset('Swiss',std.traits='global');"
+	Rscript -e "source('$<'); process_inventory_dataset('Swiss',std.traits='local');  process_inventory_dataset('Swiss',std.traits='global'); process_inventory_dataset('Swiss',std.traits='no');"
 
 $(D2)/Swiss/traits.csv: R/find.trait/Swiss.R R/find.trait/trait-fun.R $(D2)/Swiss/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<
@@ -195,7 +195,7 @@ $(D2)/Swiss/tree.csv: R/format.data/Swiss.R $(shell find $(D1)/Swiss -type f)
 US: $(D3)/US/Done.txt
 
 $(D3)/US/Done.txt: R/process.data/process-fun.R  $(D2)/US/traits.csv
-	Rscript -e "source('$<'); process_inventory_dataset('US',std.traits='global'); process_inventory_dataset('US',std.traits='local'); process_inventory_dataset('US',std.traits='no');"
+	Rscript -e "source('$<'); process_inventory_dataset('US',std.traits='local'); process_inventory_dataset('US',std.traits='global'); process_inventory_dataset('US',std.traits='no');"
 
 $(D2)/US/traits.csv: R/find.trait/US.R R/find.trait/trait-fun.R $(D2)/US/tree.csv $(D2)/TRY/data.TRY.std.rds
 	Rscript $<

R/format.data/BCI.R

@@ -97,10 +97,12 @@ data.bci$y <- data.bci$gy; data.bci$gy <- NULL
 data.bci$G <-  (data.bci$DBH2 - data.bci$DBH1)/data.bci$year  ## diameter growth in mm per year - BASED ON UNROUNDED YEARS
 data.bci$BA.G <- (pi*(data.bci$DBH2/20)^2 -pi*(data.bci$DBH1/20)^2)/data.bci$year ## BA growth in cm2/yr
 data.bci$G[data.bci$Status1=="missing" | data.bci$Status2=="missing"] <- NA
-data.bci$G[abs(data.bci$HOM2-data.bci$HOM1)>0.005 & !is.na(data.bci$HOM2-data.bci$HOM1)] <- NA
+data.bci$G[abs(data.bci$HOM2-data.bci$HOM1)>0.005 &
+           !is.na(data.bci$HOM2-data.bci$HOM1)] <- NA
 data.bci$G[data.bci$Codes2 %in% c('RF','RP','RT','R')] <- NA
 data.bci$BA.G[data.bci$Status1=="missing" | data.bci$Status2=="missing"] <- NA
-data.bci$BA.G[abs(data.bci$HOM2-data.bci$HOM1)>0.005 & !is.na(data.bci$HOM2-data.bci$HOM1)] <- NA
+data.bci$BA.G[abs(data.bci$HOM2-data.bci$HOM1)>0.005 &
+              !is.na(data.bci$HOM2-data.bci$HOM1)] <- NA
 data.bci$BA.G[data.bci$Codes2 %in% c('RF','RP','RT','R')] <- NA
 data.bci$G[data.bci$Latin %in% sp.palm.fern] <-  NA ## remove fern and palm
 data.bci$BA.G[data.bci$Latin %in% sp.palm.fern] <-  NA ## remove fern and palm
@@ -113,10 +115,18 @@ data.bci$Latin <- NULL
 data.bci$census <- data.bci$Census
 data.bci$Census <- NULL
 
+
+
 ## LIMIT TO TREES > 10CM dbh
 data.bci <- subset(data.bci,subset=data.bci[["D"]]>=10 & !is.na(data.bci[["D"]])) ### select only tree above 10cm of dbh at census 1
-## data.bci <- subset(data.bci,subset=data.bci[["census"]] %in% c(6,5)) ### select only census 6
 
+## remove plot sherman
+data.bci <- subset(data.bci,subset=data.bci[["cluster"]] != 'sherman')
+
+## remove bci census 1 because too much error
+data.bci <- subset(data.bci,subset=!(data.bci[["cluster"]] == 'bci' & data.bci[["census"]] ==1))
+# rename census from 1
+data.bci[['census']][data.bci[['cluster']]=='bci'] <- data.bci[['census']][data.bci[['cluster']]=='bci'] -1
 
 ## read plots coordinates
 coord <- read.csv('data/raw/BCI/Cndt_1ha_coordinates.csv', header = TRUE, stringsAsFactors = FALSE)
@@ -155,7 +165,8 @@ data.bci$MAP <- clim$MAP
 data.bci[["ecocode"]] <- "tropical"
 
 ###################### PLOT SELECTION FOR THE ANALYSIS
-vec.basic.var <- c("obs.id","tree.id", "sp", "sp.name", "cluster","plot", "ecocode", "D", "G","BA.G", "dead",
+vec.basic.var <- c("obs.id","tree.id", "sp", "sp.name",
+                   "cluster","plot", "ecocode", "D", "G","BA.G", "dead",
     'Lon','Lat',"x", "y", "census",'MAT','MAP')
 
 data.tree <- subset(data.bci, select = c(vec.basic.var))
@@ -165,7 +176,6 @@ data.tree <- fun.convert.type.B(data.tree)
 write.csv(data.tree,file="output/formatted/BCI/tree.csv",row.names = FALSE)
   
 ### write data plot with variables only at the plot level. I should delete them from the tree table but so far I keep them to not distroy later code
-
 vec.basic.var.p <- c("plot", "cluster", "Lon","Lat","ecocode","MAT","MAP")
 data.plot <- subset(data.tree, subset=!duplicated(data.tree$cluster),select = c(vec.basic.var.p))
 write.csv(data.plot,file="output/formatted/BCI/plot.csv",row.names = FALSE)

R/format.data/format-fun.R

@@ -122,3 +122,39 @@ symbols(x.t,y.t,circles=D.t ,main=plot.select,inches=inches,fg=fg,...)
 }
 
 
+##' .. remove too negative growth based on Condit R package with param fitted to BCI ..
+##'
+##' .. taken from trim.growth function in CTFS.R ..
+##' @title trim.negative.growth
+##' @param dbh1 in mm
+##' @param dbh2 in mm
+##' @param slope not to be changed
+##' @param intercept 
+##' @param err.limit 
+##' @return a vector TRUE FALSE with FALSE outlier to be removed
+##' @author Kunstler
+trim.negative.growth <- function(dbh1,dbh2,slope=0.006214,
+                        intercept=.9036,err.limit=5){
+stdev.dbh1 <- slope*dbh1+intercept
+bad.grow <- which(dbh2<=(dbh1-err.limit*stdev.dbh1))
+accept <- rep(TRUE,length(dbh1))
+accept[bad.grow] <- FALSE
+accept[is.na(dbh1) | is.na(dbh2) | dbh2<=0 | dbh1<=0] <- FALSE
+return(accept)
+}
+
+##' .. remove too high growth ..
+##'
+##' .. taken from trim.growth in Condit CTFS R package ..
+##' @title trim.positive.growth
+##' @param growth in mm
+##' @param maxgrow in mm 
+##' @return TRUE FALSE vector with FALSE outlier
+##' @author Kunstler
+trim.positive.growth <- function(growth,maxgrow=75){
+bad.grow <- which(growth>maxgrow)
+accept <- rep(TRUE,length(growth))
+accept[bad.grow] <- FALSE
+accept[is.na(growth)] <- FALSE
+return(accept)
+}    

R/process.data/test.tree.CWM-fun.R

-####
+################################
 ## function for test.tree.CWM
+source("R/utils/plot.R")
+
 
 load.processed.data <- function(path,file.name="data.tree.tot.csv"){
     fname <- file.path(path,file.name )
@@ -228,37 +230,7 @@ fun.test.value.one.ecoregion.B <- function(data.CWM,set,ecocode.select,path.form
 }
 
 
-
-
-## plot CWM
-fun.hist.var <- function(var,set,data){
-hist(data[[var]],xlab=var,main=set)
- }   
-
-fun.plot.plot.CWM <- function(data.CWM,set){
-trait.name <- c("Leaf.N","Seed.mass","SLA","Wood.density","Max.height")
-name.var <- c("focal",
-              "CWM.fill",
-              "abs.CWM.fill")
-   png(paste("figs/test.processed/fig",set,"BATOT.G.BA.B","png",sep="."))
-   par( mfrow=c(1,2))
-   plot(data.CWM[["BATOT"]],data.CWM[["G"]],xlab="BATOT",ylab="G")
-   plot(data.CWM[["BATOT"]],data.CWM[["BA.G"]],xlab="BATOT",ylab="BA.G")
-   dev.off()
-
-   pdf(paste("figs/test.processed/fig",set,"CWM","pdf",sep="."))
-   par(mfrow=c(5,3))
-   for (i in trait.name){
-   try(histt <- lapply(paste(i,name.var,sep="."),fun.hist.var,set,data.CWM))
-    }
-   dev.off()
-
-   pdf(paste("figs/test.processed/fig",set,"perc","pdf",sep="."))
-   par(mfrow=c(2,3))
-   try(histt <- lapply(paste(trait.name,"perc.species",sep="."),fun.hist.var,set,data.CWM))
-   dev.off()
-}
-
+#### compute description of each table
 fun.perc.non.missing <- function(i,var.name,var.names.perc,data){
 sel <- data[[var.names.perc[i]]]>0.9 & !is.na(data[[var.names.perc[i]]])
   return(  sum(!is.na((data[[var.name[i]]])[sel]))/length(data[[var.name[i]]][sel]))
@@ -323,7 +295,6 @@ fun.test.set.tree.CWM.I <- function(set,filedir){
     fun.test.set.ecocode.tree.CWM.I(data.temp,set,ecocode.select)
     list.perc[[ecocode.select]] <- fun.compute.percentage.species.genus(data.temp)
     fun.test.range.vars.q(data.temp,paste(set,ecocode.select))
-    ## fun.plot.plot.CWM (data.temp,paste(set,ecocode.select))
      }
 mat.perc <- do.call("rbind",list.perc)
 df.perc <-  data.frame(set=rep(set,nrow(mat.perc)),ecocode=rownames(mat.perc),
@@ -348,7 +319,6 @@ fun.test.set.tree.CWM.B <- function(set,filedir){
     fun.test.set.ecocode.tree.CWM.B(data.temp,set,ecocode.select)
     list.perc[[ecocode.select]] <- fun.compute.percentage.species.genus(data.temp)
     fun.test.range.vars.q(data.temp,paste(set,ecocode.select))
-    ## fun.plot.plot.CWM (data.temp,paste(set,ecocode.select))
      }
 mat.perc <- do.call("rbind",list.perc)
 df.perc <-  data.frame(set=rep(set,nrow(mat.perc)),ecocode=rownames(mat.perc),mat.perc)
@@ -384,3 +354,99 @@ if (type=='I'){
   }
 return(data.all)
 }    
+
+
+#### PLOT VAR PER SET
+
+## plot hist of each var 
+fun.hist.var <- function(data,var,...){
+tryCatch(hist(data[[var]],xlab=var,main=unique(data[['set']]),...),
+         warning=function(w) print('warnings'),
+         error=function(e){print(paste(unique(data[['set']]),'do not have value for',var));
+                           plot(0,0,main=unique(data[['set']]))})
+ }   
+
+fun.hist.var.set <- function(data,var,...){
+par(mfrow=c(5,3),mar=c(4.5,3.5,0.5,0.5),mgp=c(1.5,0.5,0))
+by(data,INDICES=data[['set']],FUN=fun.hist.var,var=var,xlim=range(data[[var]],na.rm=TRUE),...)
+}
+
+fun.plot.xy <- function(data,var.x,var.y,...){
+tryCatch(plot(data[[var.x]],data[[var.y]],xlab=var.x,ylab=var.y,main=unique(data[['set']]),...),
+         warning=function(w) print('warnings'),
+         error=function(e){print(paste(unique(data[['set']]),'do not have value for',var.x,'or',var.y));
+                           plot(0,0,main=unique(data[['set']]))})
+
+ }   
+
+
+fun.plot.xy.set <- function(data,var.x,var.y,...){
+       par(mfrow=c(5,3),mar=c(4.5,3.5,0.5,0.5),mgp=c(1.5,0.5,0))
+       by(data,INDICES=data[['set']],FUN=fun.plot.xy,var.x=var.x,var.y=var.y,
+          xlim=range(data[[var.x]],na.rm=TRUE),
+          ylim=range(data[[var.y]],na.rm=TRUE),...)
+      } 
+
+
+fun.plot.hist.trait.per.set <- function(data){
+trait.name <- c("Leaf.N","Seed.mass","SLA","Wood.density","Max.height")
+name.var <- c("focal",
+              "CWM.fill",
+              "abs.CWM.fill")
+   for (i in name.var){
+      for (t in trait.name){
+       var.temp <- paste(t,i,sep=".")
+       to.pdf(fun.hist.var.set(data,var=var.temp),
+              paste("figs/test.processed/fig",t,i,"pdf",sep="."))
+      } 
+    }
+}
+
+
+## remove growth outliers
+
+##' .. remove too negative growth based on Condit R package with param fitted to BCI ..
+##'
+##' .. taken from trim.growth function in CTFS.R ..
+##' @title trim.negative.growth
+##' @param dbh1 in mm
+##' @param dbh2 in mm
+##' @param slope not to be changed
+##' @param intercept 
+##' @param err.limit 
+##' @return a vector TRUE FALSE with FALSE outlier to be removed
+##' @author Kunstler
+trim.negative.growth <- function(dbh1,dbh2,slope=0.006214,
+                        intercept=.9036,err.limit=5){
+stdev.dbh1 <- slope*dbh1+intercept
+bad.grow <- which(dbh2<=(dbh1-err.limit*stdev.dbh1))
+accept <- rep(TRUE,length(dbh1))
+accept[bad.grow] <- FALSE
+accept[is.na(dbh1) | is.na(dbh2) | dbh2<=0 | dbh1<=0] <- FALSE
+return(accept)
+}
+
+##' .. remove too high growth ..
+##'
+##' .. taken from trim.growth in Condit CTFS R package ..
+##' @title trim.positive.growth
+##' @param growth in mm
+##' @param maxgrow in mm 
+##' @return TRUE FALSE vector with FALSE outlier
+##' @author Kunstler
+trim.positive.growth <- function(growth,maxgrow=75){
+bad.grow <- which(growth>maxgrow)
+accept <- rep(TRUE,length(growth))
+accept[bad.grow] <- FALSE
+accept[is.na(growth)] <- FALSE
+return(accept)
+}    
+
+
+#####
+## function compute FD per plot
+## TODO
+fun.compute.sd.var.cluster <- function(data,var){
+cluster.unique.id <- paste(data[['set'],data[['ecocode']],data[['cluster']])
+tapply(data[[var]],INDEX=cluster.unique.id,FUN=sd,na.rm=TRUE)       
+}

R/process.data/test.tree.CWM.R

@@ -28,7 +28,7 @@ rm(data.all)
 ## test all set
 library(doParallel)
 registerDoParallel(cores=5)
-lmat.perc.I <- lapply(sets.I, fun.test.set.tree.CWM.I,filedir=filedir)
+
 lmat.perc.I <- mclapply(sets.I, fun.test.set.tree.CWM.I,filedir=filedir,mc.cores= getOption("mc.cores", 5))
 mat.perc.I <- do.call("rbind", lmat.perc.I)
 
@@ -37,23 +37,28 @@ mat.perc.B <- do.call("rbind",lmat.perc.B)
 
 mat.perc <- data.frame(rbind(mat.perc.I,mat.perc.B),stringsAsFactors=FALSE)
 mat.perc <- data.frame(lapply(mat.perc, function(x) (unlist(x))))
-write.csv(mat.perc,file=file.path(filedir, "all.sites.perc.traits.csv"), row.names=FALSE)
+write.csv(mat.perc,file=file.path(filedir, "all.sites.perc.traits.csv"),
+          row.names=FALSE)
 
 ## format table for report
-mat.perc <- read.csv(file=file.path(filedir, "all.sites.perc.traits.csv"))
 ## genus perc
 mat.num.g <- mat.perc[,c(1:3,9:13)]
 mat.num.g[,4:8] <- mat.perc[,9:13]/mat.perc[,3]
 
-names(mat.num.g) <- c('set','ecoregion','P obs total','P Leaf N','P Seed mass','P SLA','P Wood density','P Max height')
+names(mat.num.g) <- c('set','ecoregion','P obs total','P Leaf N',
+                      'P Seed mass','P SLA','P Wood density','P Max height')
 
 library('pander')
-pandoc.table(mat.num.g,caption="Number of tree radial growth observation per data sets and ecoregion.",split.tables='Inf')
+pandoc.table(mat.num.g,
+             caption="Number of tree radial growth observation per data sets and ecoregion.",
+             split.tables='Inf')
 
 ## species perc
 mat.num.sp <- mat.perc[,c(1:8)]
 mat.num.sp[,4:8] <- mat.perc[,4:8]/mat.perc[,3]
-pandoc.table(mat.num.sp,caption="Number of tree radial growth observation per data sets and ecoregion.",split.tables='Inf')
+pandoc.table(mat.num.sp,
+             caption="Number of tree radial growth observation per data sets and ecoregion.",
+             split.tables='Inf')
 
 
 ### read all data
@@ -61,6 +66,39 @@ data.all <- read.csv(file=file.path(filedir, "data.all.csv"))
  if(dim(data.all)[1] != sum(mat.perc[['num.obs']])) stop('error not same dimension per ecoregion and total')
 
 
+data.all[['G']][!(trim.positive.growth(data.all[['G']]) &
+trim.negative.growth(dbh1=data.all[['D']]*10,
+                     dbh2=data.all[['D']]*10 +data.all[['year']]*data.all[['G']]))] <- NA
+
+data.all[['BA.G']][!(trim.positive.growth(data.all[['G']]) &
+trim.negative.growth(data.all[['D']]*10,dbh2=data.all[['D']]*10 +data.all[['year']]*data.all[['G']]))] <- NA
+
+
+## plot
+
+fun.plot.hist.trait.per.set(data.all)
+
+to.pdf(fun.hist.var.set(data.all,var='BATOT',cex=0.6),
+       filename="figs/test.processed/fig.BATOT.set.pdf") 
+to.pdf(fun.hist.var.set(data.all,var='G',cex=0.6),
+       filename="figs/test.processed/fig.G.set.pdf") 
+to.pdf(fun.hist.var.set(data.all,var='BA.G',cex=0.6),
+       filename="figs/test.processed/fig.BA.G.set.pdf") 
+to.pdf(fun.hist.var.set(data.all,var='D',cex=0.6),
+       filename="figs/test.processed/fig.D.set.pdf") 
+to.dev(fun.plot.xy.set(data.all,var.x='BATOT',var.y='BA.G',cex=0.6),dev=png,
+       filename="figs/test.processed/fig.xy.BATOT.BA.G.set.png") 
+to.dev(fun.plot.xy.set(data.all,var.x='D',var.y='BA.G',cex=0.6),dev=png,
+       filename="figs/test.processed/fig.xy.D.BA.G.set.png") 
+to.dev(fun.plot.xy.set(data.all,var.x='D',var.y='G',cex=0.6),dev=png,
+       filename="figs/test.processed/fig.xy.D.G.set.png") 
+
+
+
+
+
+fun.plot.xy.trait.per.set(data.all,var.x='BATOT',var.y='BA.G')
+