diff --git a/R/format.function.R b/R/format.function.R
index f7657876bee6f8a9f42c486a2b7aaeb3e6aa79b1..bba7c64ef3e55e1c7733d1de876fbfb5486ddb2b 100644
--- a/R/format.function.R
+++ b/R/format.function.R
@@ -1,305 +1,1021 @@
-################################################### FUNCTION TO FORMAT DATA FOR THE WORKSHOP ANALYSIS
-
-
-###### FUNCTION TO PLOT MAP OF TREE
-##' .. Function to plot map of tree with circle function of their dbh..
-##'
-##' .. content for \details{} ..
-##' @title
-##' @param plot.select the plot for which draw the map
-##' @param x
-##' @param y
-##' @param plot vectore of plot id for each tree
-##' @param D diameter in cm
-##' @param inches controling the circle size
-##' @param ...
-##' @return
-##' @author Kunstler
-fun.circles.plot <- function(plot.select, x, y, plot, D, inches, ...) {
- x.t <- x[plot == plot.select]
- y.t <- y[plot == plot.select]
- D.t <- D[plot == plot.select]
- D.t[is.na(D.t)] <- 0
- symbols(x.t, y.t, circles = D.t, main = plot.select, inches = inches, ...)
-}
-
-
-
-#########################
-##' .. Compute the basal area of competitor in a plot..
-##'
-##' .. content for \details{} ..
-##' @title
-##' @param diam diameters of each individuals in cm
-##' @param weights weight to compute the basal area in cm^2/m^2
-##' @return basal area in cm^2/m^2
-##' @author Kunstler
-BA.fun <- function(diam, weights) {
- ((diam/2)^2) * pi * weights
-}
-
-
-
-
-####
-##' .. function to compute the basal area of neighborood tree in plots ..
-##'
-##' .. content for \details{} ..
-##' @title
-##' @param obs.id tree obs identifier
-##' @param diam diam of tree in cm
-##' @param sp species name or code
-##' @param id.plot identifier of the plot
-##' @param weights weights to compute basal area in cm^2/m^2 SO THE 1/AREA of teh plot (or subplot) with area in m^2
-##' @param weights.full.plot weights for the whole plot to compute basal area in cm^2/m^2 or if NA use weights of the individuals (for simple plots)
-##' @return data frame with tree.id and one column per species with basal area of the species (without the target tree)
-##' @author Kunstler
-BA.SP.FUN <- function(obs.id, diam, sp, id.plot, weights, weight.full.plot) {
- require(data.table, quietly=TRUE)
- id.plot <- as.character(id.plot)
- obs.id <- as.character(obs.id)
+
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- ## check equal length
- if (!(length(obs.id) == length(diam) & length(obs.id) == length(sp) & length(obs.id) ==
- length(id.plot) & length(obs.id) == length(weights)))
- stop("length of obs.id diam,sp id.plot & weights need to be the same")
- ## check sp is not numeric
- if (is.numeric(sp))
- stop("sp can not be numeric need to be charatcer do paste('sp',sp,sep='.')")
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- # compute BA tot per species per plot
- BASP <- tapply(BA.fun(diam, weights), INDEX = list(id.plot, sp), FUN = sum, na.rm = T)
- print(dim(BASP))
- DATA.BASP <- data.table(id.plot = rownames(BASP), BASP)
- setnames(DATA.BASP, old = 1:ncol(DATA.BASP), c("id.plot", colnames(BASP)))
- setkeyv(DATA.BASP, c("id.plot"))
- sp.name <- colnames(BASP)
- rm(BASP)
- print("first table created")
- #### MERGE with indivudal tree use library(data.table)
- if (!is.na(weight.full.plot)) {
- data.indiv <- data.table(obs.id = obs.id, sp = sp, id.plot = id.plot, diam = diam,
- BA.indiv = BA.fun(diam, rep(weight.full.plot, length(diam))))
- setkeyv(data.indiv, "id.plot")
- print("second table created")
- data.merge <- merge(data.indiv, DATA.BASP)
- print("merge done")
- # substract target BA
- for (i in (sp.name)) {
- eval(parse(text = paste("data.merge[sp=='", i, "',", i, ":=", i, "-BA.indiv]",
- sep = "")))
- }
-
- } else {
- data.indiv <- data.table(obs.id = obs.id, sp = sp, id.plot = id.plot, diam = diam,
- weights = weights, BA.indiv = BA.fun(diam, weights))
- setkeyv(data.indiv, "id.plot")
- print("second table created")
- data.merge <- merge(data.indiv, DATA.BASP)
- print("merge done")
- for (i in (sp.name)) {
- eval(parse(text = paste("data.merge[sp=='", i, "',", i, ":=", i, "-BA.indiv]",
- sep = "")))
- }
- }
- print("replacment done")
- data.merge[, `:=`(BA.indiv, NULL)]
- print("first column removed")
- #### delete column not used
- data.merge[, `:=`(sp, NULL)]
- data.merge[, `:=`(diam, NULL)]
- data.merge[, `:=`(id.plot, NULL)]
- data.merge[, `:=`(weights, NULL)]
- print("columns removed")
- return((data.merge))
-}
-
-####
-##' .. function compute competition index with X Y coordinates based on a neighborhood of radius R ..
-##'
-##' .. content for \details{} ..
-##' @title
-##' @param obs.id id of the observation (if one tree as multiple growth measurement one obs.id per measurment
-##' @param xy.table table with x.y of teh individual
-##' @param diam diam in cm
-##' @param sp species
-##' @param Rlim radius of neighborhood search
-##' @param parallel run in paralle or not ?
-##' @param rpuDist run with GPU distance computation
-##' @return a data frame with nrow = length of obs.id and ncol =unique(sp)
-##' @author Kunstler
-BA.SP.FUN.XY <- function(obs.id, xy.table, diam, sp, Rlim, parallel = FALSE, rpuDist = FALSE) {
- rownames(xy.table) <- obs.id
- if (rpuDist) {
- require(rpud, quietly=TRUE)
- dist.mat <- rpuDist(xy.table, upper = TRUE, diag = TRUE)
- } else {
- dist.mat <- as.matrix(dist(xy.table, upper = TRUE, diag = TRUE))
- }
- print("distance matrix computed")
- dist.mat[dist.mat < Rlim] <- 1
- dist.mat[dist.mat > Rlim] <- 0
- diag(dist.mat) <- 0
- print("distance matrix set to 0 1")
- BA <- BA.fun(diam, weights = 1/(pi * Rlim^2))
- BA.mat <- matrix(rep(BA, length(BA)), nrow = length(BA), byrow = TRUE)
- print("starting tapply over species")
- fun.sum.sp <- function(x, sp) tapply(x, INDEX = sp, FUN = sum, na.rm = TRUE)
- if (parallel) {
- ## parallel version
- require(doParallel, quietly=TRUE)
- registerDoParallel(cores = 4)
- mat <- dist.mat * BA.mat
- res.temp <- foreach(i = 1:nrow(mat), .combine = rbind) %dopar% {
- fun.sum.sp(mat[i, ], sp)
- }
- rownames(res.temp) <- obs.id
- return((res.temp))
- } else {
- res.temp <- t(apply(dist.mat * BA.mat, MARGIN = 1, FUN = fun.sum.sp, sp))
- return(res.temp)
- }
-}
-
-
-############################ FUNCTION remove trailing white space
-trim.trailing <- function(x) sub("\\s+$", "", x)
-
-## clean species.tab
-fun.clean.species.tab <- function(species.tab) {
- species.tab2 <- species.tab[!is.na(species.tab$Latin_name), ]
+
- ### species IFN reformat names clean species names and synonyme names
- species.tab2$Latin_name <- (gsub("_", " ", species.tab2$Latin_name))
- species.tab2$Latin_name_syn <- (gsub("_", " ", species.tab2$Latin_name_syn))
- ## remove trailing white space
- species.tab2$Latin_name_syn <- trim.trailing(species.tab2$Latin_name_syn)
- species.clean <- species.tab2[!duplicated(species.tab2$Latin_name), c("code",
- "Latin_name", "Exotic_Native_cultivated")]
- return(species.clean)
-}
-
-
-### compute quantile 99% and sd with a bootstrap
-
-library(boot, quietly=TRUE)
-
-f.quantile <- function(x, ind, probs) {
- quantile(x[ind], probs = probs, na.rm = TRUE)
-}
-
-f.quantile.boot <- function(i, x, fac, R, probs = 0.99) {
- require(boot, quietly=TRUE)
- if (length(na.exclude(x[fac == i])) > 0) {
- quant.boot <- boot(x[fac == i], f.quantile, R = R, probs = probs)
- return(as.matrix(c(mean = mean(quant.boot$t), sd = sd(quant.boot$t), nobs = length(na.exclude(x[fac ==
- i]))), ncol = 3, nrow = 1))
- } else {
- return(as.matrix(c(mean = NA, sd = NA, nobs = NA), ncol = 3, nrow = 1))
- }
-}
-
-####################### function to compute number of dead per plot
-function.perc.dead <- function(dead) {
- sum(dead)/length(dead)
-}
-
-
-function.perc.dead2 <- function(dead) {
- out <- sum(dead, na.rm = T)/length(dead[!is.na(dead)])
- if (!is.finite(out))
- out <- NA
- return(out)
-}
-
-
-########################## GENERATE A R.object per ecoregion
-
-function.replace.NA.negative <- function(data.BA.SP) {
- for (i in 2:ncol(data.BA.SP)) {
- eval(parse(text = paste("data.BA.SP[is.na(", names(data.BA.SP)[i], "),",
- names(data.BA.SP)[i], ":=0]", sep = "")))
- eval(parse(text = paste("data.BA.SP[", names(data.BA.SP)[i], "<0,", names(data.BA.SP)[i],
- ":=0]", sep = "")))
- }
- print("NA and negative replaced")
- return(data.BA.SP)
-}
-
-############################################################## function to generate data in good format per ecoregion
-fun.data.per.ecoregion <- function(ecoregion, data.tot, plot.name, weight.full.plot,
- name.country, data.TRY = NA, species.lookup = NA, output.dir = "./data/process") {
- require(data.table, quietly=TRUE)
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- print(paste("Working on Ecoregion %s", ecoregion))
- data <- data.table(data.tot)[ecocode == ecoregion, ]
- data.BA.SP <- BA.SP.FUN(obs.id = as.vector(data[["obs.id"]]), diam = as.vector(data[["D"]]),
- sp = as.vector(data[["sp"]]), id.plot = as.vector(data[[plot.name]]), weights = data[["weights"]],
- weight.full.plot = weight.full.plot)
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- print("competition index computed")
- ## change NA and <0 data for 0
- data.BA.SP <- function.replace.NA.negative(data.BA.SP)
- ### CHECK IF sp and sp name for column are the same
- if (sum(!(names(data.BA.SP)[-1] %in% unique(data[["sp"]]))) > 0)
- stop("competition index sp name not the same as in data")
- #### compute BA tot for all competitors data.BA.SP[,BATOT:=sum(.SD),by=obs.id] ##
- #### slower than apply why??
- BATOT.s <- apply(data.frame(data.BA.SP)[, -1], MARGIN = 1, FUN = sum)
- data.BA.SP[, `:=`(BATOT, BATOT.s)]
- print("BATOT COMPUTED")
- ### create data frame
- DT.temp <- data.table(obs.id = data[["obs.id"]], ecocode = data[["ecocode"]])
- setkeyv(DT.temp, "obs.id")
- setkeyv(data.BA.SP, "obs.id")
- print("starting last merge")
- data.BA.sp <- merge(DT.temp, data.BA.SP)
- ## reorder data
- data <- data.table(data)
- setkeyv(data, "obs.id")
- ## test if same order
- if (sum(!data.BA.sp[["obs.id"]] == data[["obs.id"]]) > 0)
- stop("competition index not in the same order than data")
- ##### ADD TRY DATA OR TRAITS IF NEEDED
- data.traits = NA
- if (!is.na(data.TRY)) {
- sp.extract <- species.lookup[species.lookup[["sp"]] %in% unique(data[["sp"]]), ]
- data.traits <- fun.extract.format.sp.traits.TRY(sp = sp.extract[["sp"]],
- sp.syno.table = sp.extract, data.TRY)
- }
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- ## save everything as a list
- list.temp <- list(data.tree = data, data.BA.SP = data.BA.sp, data.traits = data.traits)
- save(list.temp, file = file.path(output.dir,paste("list", name.country, ecoregion,
- "Rdata", sep = ".")))
-}
-
-
-##################################### FUNCTION TO COMPUTE BA.SP.XY PER PLOT AND MERGE TOGETHER function to be apply
-##################################### per site
-fun.compute.BA.SP.XY.per.plot <- function(i, data.tree, Rlim, xy.name = c("x", "y"),
- parallel = FALSE, rpuDist = FALSE) {
- data.tree.s <- subset(data.tree, subset = data.tree[["plot"]] == i)
- BA.SP.temp <- BA.SP.FUN.XY(obs.id = data.tree.s[["obs.id"]], xy.table = data.tree.s[,
- xy.name], diam = data.tree.s[["D"]], sp = (data.tree.s[["sp"]]), Rlim = 15,
- parallel = FALSE, rpuDist = FALSE)
+ </div>
+</div>
+
+
+
+
+
+
+
+
+ <div class="site" itemscope itemtype="http://schema.org/WebPage">
- ## replace NA per zero
- print("replacing NA per zero")
- BA.SP.temp[is.na(BA.SP.temp)] <- 0
- print("done")
- ### rpud installation very cumbersome not needed ? longer in parallel why ?
- if (sum(!rownames(BA.SP.temp) == data.tree.s[["obs.id"]]) > 0)
- stop("rows not in the good order")
- if (sum(!colnames(BA.SP.temp) == as.character((levels(data.tree.s[["sp"]])))) >
- 0)
- stop("colnames does mot match species name")
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+<span id="L346" rel="#L346">346</span>
+
+ </td>
+ <td class="blob-line-code">
+ <div class="highlight"><pre><div class='line' id='LC1'><br/></div><div class='line' id='LC2'><span class="c1">###################################################</span></div><div class='line' id='LC3'><span class="c1">###################################################</span></div><div class='line' id='LC4'><span class="c1">###################################################</span></div><div class='line' id='LC5'><span class="c1">##### FUNCTION TO FORMAT DATA FOR THE WORKSHOP ANALYSIS</span></div><div class='line' id='LC6'><br/></div><div class='line' id='LC7'><br/></div><div class='line' id='LC8'><span class="c1">######</span></div><div class='line' id='LC9'><span class="c1">######</span></div><div class='line' id='LC10'><span class="c1">## FUNCTION TO PLOT MAP OF TREE</span></div><div class='line' id='LC11'><span class="c1">##' .. Function to plot map of tree with circle function of their dbh..</span></div><div class='line' id='LC12'><span class="c1">##'</span></div><div class='line' id='LC13'><span class="c1">##' .. content for \details{} ..</span></div><div class='line' id='LC14'><span class="c1">##' @title </span></div><div class='line' id='LC15'><span class="c1">##' @param plot.select the plot for which draw the map</span></div><div class='line' id='LC16'><span class="c1">##' @param x </span></div><div class='line' id='LC17'><span class="c1">##' @param y </span></div><div class='line' id='LC18'><span class="c1">##' @param plot vectore of plot id for each tree</span></div><div class='line' id='LC19'><span class="c1">##' @param D diameter in cm</span></div><div class='line' id='LC20'><span class="c1">##' @param inches controling the circle size</span></div><div class='line' id='LC21'><span class="c1">##' @param ... </span></div><div class='line' id='LC22'><span class="c1">##' @return </span></div><div class='line' id='LC23'><span class="c1">##' @author Kunstler</span></div><div class='line' id='LC24'>fun.circles.plot <span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>plot.select<span class="p">,</span>x<span class="p">,</span>y<span class="p">,</span>plot<span class="p">,</span>D<span class="p">,</span>inches<span class="p">,</span><span class="kc">...</span><span class="p">){</span></div><div class='line' id='LC25'>x.t <span class="o"><-</span> x<span class="p">[</span>plot<span class="o">==</span>plot.select<span class="p">]</span></div><div class='line' id='LC26'>y.t <span class="o"><-</span> y<span class="p">[</span>plot<span class="o">==</span>plot.select<span class="p">]</span></div><div class='line' id='LC27'>D.t <span class="o"><-</span> D<span class="p">[</span>plot<span class="o">==</span>plot.select<span class="p">]</span></div><div class='line' id='LC28'>D.t<span class="p">[</span>is.na<span class="p">(</span>D.t<span class="p">)]</span> <span class="o"><-</span> <span class="m">0</span></div><div class='line' id='LC29'>symbols<span class="p">(</span>x.t<span class="p">,</span>y.t<span class="p">,</span>circles<span class="o">=</span>D.t <span class="p">,</span>main<span class="o">=</span>plot.select<span class="p">,</span>inches<span class="o">=</span>inches<span class="p">,</span><span class="kc">...</span><span class="p">)</span></div><div class='line' id='LC30'><span class="p">}</span></div><div class='line' id='LC31'><br/></div><div class='line' id='LC32'><br/></div><div class='line' id='LC33'><br/></div><div class='line' id='LC34'><span class="c1">#########################</span></div><div class='line' id='LC35'><span class="c1">## </span></div><div class='line' id='LC36'><span class="c1">##' .. Compute the basal area of competitor in a plot..</span></div><div class='line' id='LC37'><span class="c1">##'</span></div><div class='line' id='LC38'><span class="c1">##' .. content for \details{} ..</span></div><div class='line' id='LC39'><span class="c1">##' @title </span></div><div class='line' id='LC40'><span class="c1">##' @param diam diameters of each individuals in cm</span></div><div class='line' id='LC41'><span class="c1">##' @param weights weight to compute the basal area in cm^2/m^2</span></div><div class='line' id='LC42'><span class="c1">##' @return basal area in cm^2/m^2 </span></div><div class='line' id='LC43'><span class="c1">##' @author Kunstler</span></div><div class='line' id='LC44'>BA.fun <span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>diam<span class="p">,</span>weights<span class="p">){</span></div><div class='line' id='LC45'><span class="p">((</span>diam<span class="o">/</span><span class="m">2</span><span class="p">)</span><span class="o">^</span><span class="m">2</span><span class="p">)</span><span class="o">*</span>pi<span class="o">*</span>weights</div><div class='line' id='LC46'><span class="p">}</span></div><div class='line' id='LC47'><br/></div><div class='line' id='LC48'><br/></div><div class='line' id='LC49'><br/></div><div class='line' id='LC50'><br/></div><div class='line' id='LC51'><span class="c1">#### </span></div><div class='line' id='LC52'><span class="c1">##' .. function to compute the basal area of neighborood tree in plots ..</span></div><div class='line' id='LC53'><span class="c1">##'</span></div><div class='line' id='LC54'><span class="c1">##' .. content for \details{} ..</span></div><div class='line' id='LC55'><span class="c1">##' @title </span></div><div class='line' id='LC56'><span class="c1">##' @param obs.id tree obs identifier</span></div><div class='line' id='LC57'><span class="c1">##' @param diam diam of tree in cm</span></div><div class='line' id='LC58'><span class="c1">##' @param sp species name or code</span></div><div class='line' id='LC59'><span class="c1">##' @param id.plot identifier of the plot</span></div><div class='line' id='LC60'><span class="c1">##' @param weights weights to compute basal area in cm^2/m^2 SO THE 1/AREA of teh plot (or subplot) with area in m^2</span></div><div class='line' id='LC61'><span class="c1">##' @param weights.full.plot weights for the whole plot to compute basal area in cm^2/m^2 or if NA use weights of the individuals (for simple plots)</span></div><div class='line' id='LC62'><span class="c1">##' @return data frame with obs.id and one column per species with basal area of the species (without the target tree)</span></div><div class='line' id='LC63'><span class="c1">##' @author Kunstler</span></div><div class='line' id='LC64'>BA.SP.FUN <span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>obs.id<span class="p">,</span>diam<span class="p">,</span>sp<span class="p">,</span>id.plot<span class="p">,</span>weights<span class="p">,</span>weight.full.plot<span class="p">){</span></div><div class='line' id='LC65'>require<span class="p">(</span>data.table<span class="p">)</span></div><div class='line' id='LC66'>id.plot <span class="o"><-</span> as.character<span class="p">(</span>id.plot<span class="p">)</span></div><div class='line' id='LC67'>obs.id <span class="o"><-</span> as.character<span class="p">(</span>obs.id<span class="p">)</span></div><div class='line' id='LC68'><span class="c1">## check equal length</span></div><div class='line' id='LC69'><span class="kr">if</span><span class="p">(</span><span class="o">!</span><span class="p">(</span>length<span class="p">(</span>obs.id<span class="p">)</span><span class="o">==</span>length<span class="p">(</span>diam<span class="p">)</span> <span class="o">&</span> length<span class="p">(</span>obs.id<span class="p">)</span><span class="o">==</span>length<span class="p">(</span>sp<span class="p">)</span> <span class="o">&</span> length<span class="p">(</span>obs.id<span class="p">)</span><span class="o">==</span>length<span class="p">(</span>id.plot<span class="p">)</span> <span class="o">&</span> length<span class="p">(</span>obs.id<span class="p">)</span><span class="o">==</span>length<span class="p">(</span>weights<span class="p">)))</span></div><div class='line' id='LC70'> stop<span class="p">(</span><span class="s">"length of obs.id diam,sp id.plot & weights need to be the same"</span><span class="p">)</span></div><div class='line' id='LC71'><br/></div><div class='line' id='LC72'><span class="c1">## check sp is not numeric</span></div><div class='line' id='LC73'><span class="kr">if</span><span class="p">(</span>is.numeric<span class="p">(</span>sp<span class="p">))</span> stop<span class="p">(</span><span class="s">"sp can not be numeric need to be charatcer do paste('sp',sp,sep='.')"</span><span class="p">)</span></div><div class='line' id='LC74'><br/></div><div class='line' id='LC75'><span class="c1"># compute BA tot per species per plot</span></div><div class='line' id='LC76'>BASP <span class="o"><-</span> tapply<span class="p">(</span>BA.fun<span class="p">(</span>diam<span class="p">,</span>weights<span class="p">),</span>INDEX<span class="o">=</span>list<span class="p">(</span>id.plot<span class="p">,</span>sp<span class="p">),</span>FUN<span class="o">=</span>sum<span class="p">,</span>na.rm<span class="o">=</span><span class="k-Variable">T</span><span class="p">)</span></div><div class='line' id='LC77'>print<span class="p">(</span>dim<span class="p">(</span>BASP<span class="p">))</span></div><div class='line' id='LC78'>DATA.BASP <span class="o"><-</span> data.table<span class="p">(</span>id.plot<span class="o">=</span> rownames<span class="p">(</span>BASP<span class="p">),</span>BASP<span class="p">)</span></div><div class='line' id='LC79'>setnames<span class="p">(</span> DATA.BASP<span class="p">,</span>old<span class="o">=</span><span class="m">1</span><span class="o">:</span>ncol<span class="p">(</span>DATA.BASP<span class="p">),</span> c<span class="p">(</span><span class="s">"id.plot"</span><span class="p">,</span>colnames<span class="p">(</span>BASP<span class="p">)))</span></div><div class='line' id='LC80'>setkeyv<span class="p">(</span>DATA.BASP<span class="p">,</span>c<span class="p">(</span><span class="s">"id.plot"</span><span class="p">))</span></div><div class='line' id='LC81'>sp.name <span class="o"><-</span> colnames<span class="p">(</span>BASP<span class="p">)</span></div><div class='line' id='LC82'>rm<span class="p">(</span>BASP<span class="p">)</span></div><div class='line' id='LC83'>print<span class="p">(</span><span class="s">"first table created"</span><span class="p">)</span></div><div class='line' id='LC84'><span class="c1">#### MERGE with indivudal tree</span></div><div class='line' id='LC85'><span class="c1">## use library(data.table)</span></div><div class='line' id='LC86'><span class="kr">if</span><span class="p">(</span><span class="o">!</span>is.na<span class="p">(</span>weight.full.plot<span class="p">)){</span></div><div class='line' id='LC87'> data.indiv <span class="o"><-</span> data.table<span class="p">(</span>obs.id<span class="o">=</span>obs.id<span class="p">,</span>sp<span class="o">=</span>sp<span class="p">,</span></div><div class='line' id='LC88'> id.plot<span class="o">=</span>id.plot<span class="p">,</span>diam<span class="o">=</span>diam<span class="p">,</span></div><div class='line' id='LC89'> BA.indiv<span class="o">=</span>BA.fun<span class="p">(</span>diam<span class="p">,</span>rep<span class="p">(</span>weight.full.plot<span class="p">,</span>length<span class="p">(</span>diam<span class="p">))))</span></div><div class='line' id='LC90'> setkeyv<span class="p">(</span>data.indiv<span class="p">,</span><span class="s">"id.plot"</span><span class="p">)</span></div><div class='line' id='LC91'> print<span class="p">(</span><span class="s">"second table created"</span><span class="p">)</span></div><div class='line' id='LC92'> data.merge <span class="o"><-</span> merge<span class="p">(</span>data.indiv<span class="p">,</span>DATA.BASP<span class="p">)</span></div><div class='line' id='LC93'> print<span class="p">(</span><span class="s">"merge done"</span><span class="p">)</span></div><div class='line' id='LC94'> <span class="c1"># substract target BA</span></div><div class='line' id='LC95'> <span class="kr">for</span> <span class="p">(</span>i <span class="kr">in</span> <span class="p">(</span>sp.name<span class="p">)){</span></div><div class='line' id='LC96'> eval<span class="p">(</span>parse<span class="p">(</span>text<span class="o">=</span>paste<span class="p">(</span><span class="s">"data.merge[sp==\'"</span><span class="p">,</span>i<span class="p">,</span><span class="s">"\',"</span><span class="p">,</span>i<span class="p">,</span><span class="s">":="</span><span class="p">,</span>i<span class="p">,</span><span class="s">"-BA.indiv]"</span><span class="p">,</span>sep<span class="o">=</span><span class="s">""</span><span class="p">)))</span></div><div class='line' id='LC97'> <span class="p">}</span></div><div class='line' id='LC98'><br/></div><div class='line' id='LC99'><span class="p">}</span><span class="kr">else</span><span class="p">{</span></div><div class='line' id='LC100'> data.indiv <span class="o"><-</span> data.table<span class="p">(</span>obs.id<span class="o">=</span>obs.id<span class="p">,</span>sp<span class="o">=</span>sp<span class="p">,</span>id.plot<span class="o">=</span>id.plot<span class="p">,</span></div><div class='line' id='LC101'> diam<span class="o">=</span>diam<span class="p">,</span>weights<span class="o">=</span>weights<span class="p">,</span></div><div class='line' id='LC102'> BA.indiv<span class="o">=</span>BA.fun<span class="p">(</span>diam<span class="p">,</span>weights<span class="p">))</span></div><div class='line' id='LC103'> setkeyv<span class="p">(</span>data.indiv<span class="p">,</span><span class="s">"id.plot"</span><span class="p">)</span></div><div class='line' id='LC104'> print<span class="p">(</span><span class="s">"second table created"</span><span class="p">)</span></div><div class='line' id='LC105'> data.merge <span class="o"><-</span> merge<span class="p">(</span>data.indiv<span class="p">,</span>DATA.BASP<span class="p">)</span></div><div class='line' id='LC106'> print<span class="p">(</span><span class="s">"merge done"</span><span class="p">)</span></div><div class='line' id='LC107'> <span class="kr">for</span> <span class="p">(</span>i <span class="kr">in</span> <span class="p">(</span>sp.name<span class="p">)){</span></div><div class='line' id='LC108'> eval<span class="p">(</span>parse<span class="p">(</span>text<span class="o">=</span>paste<span class="p">(</span><span class="s">"data.merge[sp==\'"</span><span class="p">,</span>i<span class="p">,</span><span class="s">"\',"</span><span class="p">,</span>i<span class="p">,</span><span class="s">":="</span><span class="p">,</span>i<span class="p">,</span><span class="s">"-BA.indiv]"</span><span class="p">,</span>sep<span class="o">=</span><span class="s">""</span><span class="p">)))</span></div><div class='line' id='LC109'> <span class="p">}</span></div><div class='line' id='LC110'><span class="p">}</span></div><div class='line' id='LC111'>print<span class="p">(</span><span class="s">"replacment done"</span><span class="p">)</span></div><div class='line' id='LC112'>data.merge<span class="p">[,</span>BA.indiv<span class="o">:=</span><span class="kc">NULL</span><span class="p">]</span></div><div class='line' id='LC113'>print<span class="p">(</span><span class="s">"first column removed"</span><span class="p">)</span></div><div class='line' id='LC114'><span class="c1">#### delete column not used</span></div><div class='line' id='LC115'>data.merge<span class="p">[,</span>sp<span class="o">:=</span><span class="kc">NULL</span><span class="p">]</span></div><div class='line' id='LC116'>data.merge<span class="p">[,</span>diam<span class="o">:=</span><span class="kc">NULL</span><span class="p">]</span></div><div class='line' id='LC117'>data.merge<span class="p">[,</span>id.plot<span class="o">:=</span><span class="kc">NULL</span><span class="p">]</span></div><div class='line' id='LC118'>data.merge<span class="p">[,</span>weights<span class="o">:=</span><span class="kc">NULL</span><span class="p">]</span></div><div class='line' id='LC119'>print<span class="p">(</span><span class="s">"columns removed"</span><span class="p">)</span></div><div class='line' id='LC120'><span class="kr">return</span><span class="p">(</span> <span class="p">(</span>data.merge<span class="p">))</span></div><div class='line' id='LC121'><span class="p">}</span></div><div class='line' id='LC122'><br/></div><div class='line' id='LC123'><span class="c1">######################</span></div><div class='line' id='LC124'><span class="c1">#### apply BA.SP.FUN per census</span></div><div class='line' id='LC125'><span class="c1"># function to run on a subset to only one census </span></div><div class='line' id='LC126'>BA.SP.FUN.l<span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>census.id<span class="p">,</span>census<span class="p">,</span>obs.id<span class="p">,</span>diam<span class="p">,</span>sp<span class="p">,</span>id.plot<span class="p">,</span>weights<span class="p">,</span>weight.full.plot<span class="p">){</span></div><div class='line' id='LC127'><span class="kr">return</span><span class="p">(</span>BA.SP.FUN<span class="p">(</span>obs.id<span class="o">=</span>obs.id<span class="p">[</span>census<span class="o">==</span>census.id<span class="p">],</span>diam<span class="o">=</span>diam<span class="p">[</span>census<span class="o">==</span>census.id<span class="p">],</span>sp<span class="o">=</span>sp<span class="p">[</span>census<span class="o">==</span>census.id<span class="p">],</span>id.plot<span class="o">=</span>id.plot<span class="p">[</span>census<span class="o">==</span>census.id<span class="p">],</span>weights<span class="o">=</span>weights<span class="p">[</span>census<span class="o">==</span>census.id<span class="p">],</span>weight.full.plot<span class="o">=</span>weight.full.plot<span class="p">))</span></div><div class='line' id='LC128'><span class="p">}</span></div><div class='line' id='LC129'><span class="c1">## function to apply over all census and merge back together</span></div><div class='line' id='LC130'>BA.SP.FUN.census<span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>census<span class="p">,</span>obs.id<span class="p">,</span>diam<span class="p">,</span>sp<span class="p">,</span>id.plot<span class="p">,</span>weights<span class="p">,</span>weight.full.plot<span class="p">){</span></div><div class='line' id='LC131'>require<span class="p">(</span>data.table<span class="p">)</span></div><div class='line' id='LC132'>unique.census <span class="o"><-</span> unique<span class="p">(</span>census<span class="p">)</span></div><div class='line' id='LC133'>res.list <span class="o"><-</span> lapply<span class="p">(</span>unique.census<span class="p">,</span>FUN<span class="o">=</span>BA.SP.FUN.l<span class="p">,</span>census<span class="p">,</span>obs.id<span class="p">,</span>diam<span class="p">,</span>sp<span class="p">,</span>id.plot<span class="p">,</span>weights<span class="p">,</span>weight.full.plot<span class="p">)</span></div><div class='line' id='LC134'>res.mat <span class="o"><-</span> rbind.fill<span class="p">(</span>res.list <span class="p">)</span></div><div class='line' id='LC135'>res.mat <span class="o"><-</span> data.table<span class="p">(</span>res.mat<span class="p">[</span>match<span class="p">(</span>obs.id<span class="p">,</span>res.mat<span class="p">[,</span><span class="s">"obs.id"</span><span class="p">]),])</span></div><div class='line' id='LC136'><span class="kr">return</span><span class="p">(</span>res.mat<span class="p">)</span></div><div class='line' id='LC137'><span class="p">}</span></div><div class='line' id='LC138'><br/></div><div class='line' id='LC139'><br/></div><div class='line' id='LC140'><span class="c1">#### </span></div><div class='line' id='LC141'><span class="c1">##' .. function compute competition index with X Y coordinates based on a neighborhood of radius R ..</span></div><div class='line' id='LC142'><span class="c1">##'</span></div><div class='line' id='LC143'><span class="c1">##' .. content for \details{} ..</span></div><div class='line' id='LC144'><span class="c1">##' @title </span></div><div class='line' id='LC145'><span class="c1">##' @param obs.id id of the observation (if one tree as multiple growth measurement one obs.id per measurment</span></div><div class='line' id='LC146'><span class="c1">##' @param xy.table table with x.y of teh individual</span></div><div class='line' id='LC147'><span class="c1">##' @param diam diam in cm</span></div><div class='line' id='LC148'><span class="c1">##' @param sp species</span></div><div class='line' id='LC149'><span class="c1">##' @param Rlim radius of neighborhood search</span></div><div class='line' id='LC150'><span class="c1">##' @param parallel run in paralle or not ?</span></div><div class='line' id='LC151'><span class="c1">##' @param rpuDist run with GPU distance computation</span></div><div class='line' id='LC152'><span class="c1">##' @return a data frame with nrow = length of obs.id and ncol =unique(sp)</span></div><div class='line' id='LC153'><span class="c1">##' @author Kunstler</span></div><div class='line' id='LC154'>BA.SP.FUN.XY <span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>obs.id<span class="p">,</span>xy.table<span class="p">,</span>diam<span class="p">,</span>sp<span class="p">,</span>Rlim<span class="p">,</span>parallel<span class="o">=</span><span class="kc">FALSE</span><span class="p">,</span>rpuDist<span class="o">=</span><span class="kc">FALSE</span><span class="p">){</span></div><div class='line' id='LC155'>rownames<span class="p">(</span>xy.table<span class="p">)</span> <span class="o"><-</span> obs.id</div><div class='line' id='LC156'><span class="kr">if</span><span class="p">(</span>rpuDist<span class="p">){</span></div><div class='line' id='LC157'> require<span class="p">(</span>rpud<span class="p">)</span></div><div class='line' id='LC158'> dist.mat <span class="o"><-</span> rpuDist<span class="p">(</span>xy.table<span class="p">,</span>upper<span class="o">=</span><span class="kc">TRUE</span><span class="p">,</span>diag<span class="o">=</span><span class="kc">TRUE</span><span class="p">)</span></div><div class='line' id='LC159'><span class="p">}</span><span class="kr">else</span><span class="p">{</span></div><div class='line' id='LC160'> dist.mat <span class="o"><-</span> as.matrix<span class="p">(</span>dist<span class="p">(</span>xy.table<span class="p">,</span>upper<span class="o">=</span><span class="kc">TRUE</span><span class="p">,</span>diag<span class="o">=</span><span class="kc">TRUE</span><span class="p">))</span></div><div class='line' id='LC161'><span class="p">}</span></div><div class='line' id='LC162'>print<span class="p">(</span><span class="s">'distance matrix computed'</span><span class="p">)</span></div><div class='line' id='LC163'>dist.mat<span class="p">[</span>dist.mat <span class="o"><</span>Rlim<span class="p">]</span> <span class="o"><-</span> <span class="m">1</span></div><div class='line' id='LC164'>dist.mat<span class="p">[</span>dist.mat <span class="o">></span>Rlim<span class="p">]</span> <span class="o"><-</span> <span class="m">0</span></div><div class='line' id='LC165'>diag<span class="p">(</span>dist.mat<span class="p">)</span> <span class="o"><-</span> <span class="m">0</span></div><div class='line' id='LC166'>print<span class="p">(</span><span class="s">'distance matrix set to 0 1'</span><span class="p">)</span></div><div class='line' id='LC167'>BA <span class="o"><-</span> BA.fun<span class="p">(</span>diam<span class="p">,</span>weights<span class="o">=</span><span class="m">1</span><span class="o">/</span><span class="p">(</span>pi<span class="o">*</span>Rlim<span class="o">^</span><span class="m">2</span><span class="p">))</span></div><div class='line' id='LC168'>BA.mat <span class="o"><-</span> matrix<span class="p">(</span>rep<span class="p">(</span>BA<span class="p">,</span>length<span class="p">(</span>BA<span class="p">)),</span>nrow<span class="o">=</span>length<span class="p">(</span>BA<span class="p">),</span>byrow<span class="o">=</span><span class="kc">TRUE</span><span class="p">)</span></div><div class='line' id='LC169'>print<span class="p">(</span><span class="s">'starting tapply over species'</span><span class="p">)</span></div><div class='line' id='LC170'>fun.sum.sp <span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>x<span class="p">,</span>sp<span class="p">)</span> tapply<span class="p">(</span>x<span class="p">,</span>INDEX<span class="o">=</span>sp<span class="p">,</span>FUN<span class="o">=</span>sum<span class="p">,</span>na.rm<span class="o">=</span><span class="kc">TRUE</span><span class="p">)</span></div><div class='line' id='LC171'> <span class="kr">if</span><span class="p">(</span>parallel<span class="p">){</span></div><div class='line' id='LC172'> <span class="c1">## parallel version</span></div><div class='line' id='LC173'> require<span class="p">(</span>doParallel<span class="p">)</span></div><div class='line' id='LC174'> registerDoParallel<span class="p">(</span>cores<span class="o">=</span><span class="m">4</span><span class="p">)</span></div><div class='line' id='LC175'> mat <span class="o"><-</span> dist.mat<span class="o">*</span>BA.mat</div><div class='line' id='LC176'> res.temp <span class="o"><-</span> foreach<span class="p">(</span>i<span class="o">=</span><span class="m">1</span><span class="o">:</span>nrow<span class="p">(</span>mat<span class="p">),</span> .combine<span class="o">=</span>rbind<span class="p">)</span> <span class="o">%dopar%</span> <span class="p">{</span></div><div class='line' id='LC177'> fun.sum.sp<span class="p">(</span>mat<span class="p">[</span>i<span class="p">,],</span>sp<span class="p">)</span></div><div class='line' id='LC178'> <span class="p">}</span></div><div class='line' id='LC179'> rownames<span class="p">(</span>res.temp<span class="p">)</span> <span class="o"><-</span> obs.id</div><div class='line' id='LC180'> <span class="kr">return</span><span class="p">((</span>res.temp<span class="p">))</span></div><div class='line' id='LC181'> <span class="p">}</span><span class="kr">else</span><span class="p">{</span></div><div class='line' id='LC182'> res.temp <span class="o"><-</span> t<span class="p">(</span>apply<span class="p">(</span>dist.mat<span class="o">*</span>BA.mat<span class="p">,</span>MARGIN<span class="o">=</span><span class="m">1</span><span class="p">,</span>FUN<span class="o">=</span>fun.sum.sp <span class="p">,</span>sp<span class="p">))</span></div><div class='line' id='LC183'> <span class="kr">return</span><span class="p">(</span>res.temp<span class="p">)</span></div><div class='line' id='LC184'> <span class="p">}</span></div><div class='line' id='LC185'><span class="p">}</span></div><div class='line' id='LC186'><br/></div><div class='line' id='LC187'><span class="c1">## function for lapply per census</span></div><div class='line' id='LC188'>BA.SP.FUN.XY.l <span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>census.id<span class="p">,</span>census<span class="p">,</span>obs.id<span class="p">,</span>xy.table<span class="p">,</span>diam<span class="p">,</span>sp<span class="p">,</span>Rlim<span class="p">,</span>parallel<span class="o">=</span><span class="kc">FALSE</span><span class="p">,</span>rpuDist<span class="o">=</span><span class="kc">FALSE</span><span class="p">){</span></div><div class='line' id='LC189'><br/></div><div class='line' id='LC190'><span class="kr">return</span><span class="p">(</span>BA.SP.FUN.XY<span class="p">(</span>obs.id<span class="p">[</span>census<span class="o">==</span>census.id<span class="p">],</span>xy.table<span class="p">[</span>census<span class="o">==</span>census.id<span class="p">,],</span>diam<span class="p">[</span>census<span class="o">==</span>census.id<span class="p">],</span>sp<span class="p">[</span>census<span class="o">==</span>census.id<span class="p">],</span>Rlim<span class="p">,</span>parallel<span class="p">,</span>rpuDist<span class="p">))</span></div><div class='line' id='LC191'><br/></div><div class='line' id='LC192'><span class="p">}</span></div><div class='line' id='LC193'><br/></div><div class='line' id='LC194'><span class="c1">### wrapping function to run BA.SP.FUN.XY per census</span></div><div class='line' id='LC195'>BA.SP.FUN.XY.census <span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>census<span class="p">,</span>obs.id<span class="p">,</span>xy.table<span class="p">,</span>diam<span class="p">,</span>sp<span class="p">,</span>Rlim<span class="p">,</span>parallel<span class="o">=</span><span class="kc">FALSE</span><span class="p">,</span>rpuDist<span class="o">=</span><span class="kc">FALSE</span><span class="p">){</span></div><div class='line' id='LC196'>unique.census <span class="o"><-</span> unique<span class="p">(</span>census<span class="p">)</span></div><div class='line' id='LC197'>res.list <span class="o"><-</span> lapply<span class="p">(</span>unique.census<span class="p">,</span>FUN<span class="o">=</span>BA.SP.FUN.XY.l<span class="p">,</span>obs.id<span class="p">,</span>xy.table<span class="p">,</span>diam<span class="p">,</span>sp<span class="p">,</span>Rlim<span class="p">,</span>parallel<span class="p">,</span>rpuDist<span class="p">)</span></div><div class='line' id='LC198'>res.mat <span class="o"><-</span> rbind.fill<span class="p">(</span>res.list <span class="p">)</span></div><div class='line' id='LC199'>res.mat <span class="o"><-</span> res.mat<span class="p">[</span>match<span class="p">(</span>obs.id<span class="p">,</span>rownames<span class="p">(</span>res.mat<span class="p">)),]</span></div><div class='line' id='LC200'><span class="kr">return</span><span class="p">(</span>res.mat<span class="p">)</span></div><div class='line' id='LC201'><span class="p">}</span></div><div class='line' id='LC202'><br/></div><div class='line' id='LC203'><span class="c1">############################</span></div><div class='line' id='LC204'><span class="c1">## FUNCTION remove trailing white space</span></div><div class='line' id='LC205'>trim.trailing <span class="o"><-</span> <span class="kr">function</span> <span class="p">(</span>x<span class="p">)</span> sub<span class="p">(</span><span class="s">"\\s+$"</span><span class="p">,</span> <span class="s">""</span><span class="p">,</span> x<span class="p">)</span></div><div class='line' id='LC206'><br/></div><div class='line' id='LC207'><span class="c1">## clean species.tab</span></div><div class='line' id='LC208'>fun.clean.species.tab <span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>species.tab<span class="p">){</span></div><div class='line' id='LC209'>species.tab2 <span class="o"><-</span> species.tab<span class="p">[</span><span class="o">!</span>is.na<span class="p">(</span>species.tab<span class="o">$</span>Latin_name<span class="p">),]</span></div><div class='line' id='LC210'> </div><div class='line' id='LC211'><span class="c1">### species IFN reformat names</span></div><div class='line' id='LC212'><span class="c1">## clean species names and synonyme names</span></div><div class='line' id='LC213'>species.tab2<span class="o">$</span>Latin_name <span class="o"><-</span> <span class="p">(</span>gsub<span class="p">(</span><span class="s">"_"</span><span class="p">,</span> <span class="s">" "</span><span class="p">,</span> species.tab2<span class="o">$</span>Latin_name<span class="p">))</span></div><div class='line' id='LC214'>species.tab2<span class="o">$</span>Latin_name_syn<span class="o"><-</span> <span class="p">(</span>gsub<span class="p">(</span><span class="s">"_"</span><span class="p">,</span> <span class="s">" "</span><span class="p">,</span> species.tab2<span class="o">$</span>Latin_name_syn<span class="p">))</span></div><div class='line' id='LC215'><span class="c1">## remove trailing white space</span></div><div class='line' id='LC216'>species.tab2<span class="o">$</span>Latin_name_syn<span class="o"><-</span> trim.trailing<span class="p">(</span>species.tab2<span class="o">$</span>Latin_name_syn<span class="p">)</span></div><div class='line' id='LC217'><br/></div><div class='line' id='LC218'>species.clean <span class="o"><-</span> species.tab2<span class="p">[</span><span class="o">!</span>duplicated<span class="p">(</span>species.tab2<span class="o">$</span>Latin_name<span class="p">),</span></div><div class='line' id='LC219'> c<span class="p">(</span><span class="s">"code"</span><span class="p">,</span><span class="s">"Latin_name"</span><span class="p">,</span><span class="s">"Exotic_Native_cultivated"</span><span class="p">)]</span></div><div class='line' id='LC220'><span class="kr">return</span><span class="p">(</span>species.clean<span class="p">)}</span></div><div class='line' id='LC221'><br/></div><div class='line' id='LC222'><br/></div><div class='line' id='LC223'><span class="c1">### compute quantile 99% and sd with a bootstrap</span></div><div class='line' id='LC224'><br/></div><div class='line' id='LC225'>library<span class="p">(</span>boot<span class="p">)</span></div><div class='line' id='LC226'><br/></div><div class='line' id='LC227'>f.quantile <span class="o"><-</span> <span class="kr">function</span> <span class="p">(</span>x<span class="p">,</span>ind<span class="p">,</span>probs<span class="p">){</span>quantile<span class="p">(</span>x<span class="p">[</span>ind<span class="p">],</span>probs<span class="o">=</span>probs<span class="p">,</span>na.rm<span class="o">=</span><span class="kc">TRUE</span><span class="p">)}</span></div><div class='line' id='LC228'><br/></div><div class='line' id='LC229'>f.quantile.boot <span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>i<span class="p">,</span>x<span class="p">,</span>fac<span class="p">,</span>R<span class="p">,</span>probs<span class="o">=</span><span class="m">0.99</span><span class="p">){</span></div><div class='line' id='LC230'> require<span class="p">(</span>boot<span class="p">)</span></div><div class='line' id='LC231'> <span class="kr">if</span><span class="p">(</span>length<span class="p">(</span>na.exclude<span class="p">(</span>x<span class="p">[</span>fac<span class="o">==</span>i<span class="p">]))</span><span class="o">></span><span class="m">0</span><span class="p">){</span></div><div class='line' id='LC232'>quant.boot <span class="o"><-</span> boot<span class="p">(</span>x<span class="p">[</span>fac<span class="o">==</span>i<span class="p">],</span>f.quantile<span class="p">,</span>R<span class="o">=</span>R<span class="p">,</span>probs<span class="o">=</span>probs<span class="p">)</span></div><div class='line' id='LC233'><span class="kr">return</span><span class="p">(</span>as.matrix<span class="p">(</span>c<span class="p">(</span>mean<span class="o">=</span>mean<span class="p">(</span>quant.boot<span class="o">$</span>t<span class="p">),</span>sd<span class="o">=</span>sd<span class="p">(</span>quant.boot<span class="o">$</span>t<span class="p">),</span>nobs<span class="o">=</span>length<span class="p">(</span>na.exclude<span class="p">(</span>x<span class="p">[</span>fac<span class="o">==</span>i<span class="p">]))),</span>ncol<span class="o">=</span><span class="m">3</span><span class="p">,</span>nrow<span class="o">=</span><span class="m">1</span><span class="p">))</span></div><div class='line' id='LC234'><span class="p">}</span><span class="kr">else</span><span class="p">{</span></div><div class='line' id='LC235'><span class="kr">return</span><span class="p">(</span>as.matrix<span class="p">(</span>c<span class="p">(</span>mean<span class="o">=</span><span class="kc">NA</span><span class="p">,</span>sd<span class="o">=</span><span class="kc">NA</span><span class="p">,</span>nobs<span class="o">=</span><span class="kc">NA</span><span class="p">),</span>ncol<span class="o">=</span><span class="m">3</span><span class="p">,</span>nrow<span class="o">=</span><span class="m">1</span><span class="p">))</span></div><div class='line' id='LC236'><span class="p">}</span></div><div class='line' id='LC237'><span class="p">}</span></div><div class='line' id='LC238'><br/></div><div class='line' id='LC239'><span class="c1">#######################</span></div><div class='line' id='LC240'><span class="c1">### function to compute number of dead per plot </span></div><div class='line' id='LC241'>function.perc.dead <span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>dead<span class="p">){</span></div><div class='line' id='LC242'> sum<span class="p">(</span>dead<span class="p">)</span><span class="o">/</span>length<span class="p">(</span>dead<span class="p">)}</span></div><div class='line' id='LC243'><br/></div><div class='line' id='LC244'><br/></div><div class='line' id='LC245'>function.perc.dead2 <span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>dead<span class="p">)</span> <span class="p">{</span> out <span class="o"><-</span> sum<span class="p">(</span>dead<span class="p">,</span>na.rm<span class="o">=</span><span class="k-Variable">T</span><span class="p">)</span><span class="o">/</span>length<span class="p">(</span>dead<span class="p">[</span><span class="o">!</span>is.na<span class="p">(</span>dead<span class="p">)]);</span> <span class="kr">if</span><span class="p">(</span><span class="o">!</span>is.finite<span class="p">(</span>out<span class="p">))</span> out <span class="o"><-</span> <span class="kc">NA</span><span class="p">;</span> <span class="kr">return</span><span class="p">(</span>out<span class="p">)</span> <span class="p">}</span></div><div class='line' id='LC246'><br/></div><div class='line' id='LC247'><br/></div><div class='line' id='LC248'><span class="c1">##########################</span></div><div class='line' id='LC249'><span class="c1">### GENERATE A R.object per ecoregion</span></div><div class='line' id='LC250'><br/></div><div class='line' id='LC251'>function.replace.NA.negative <span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>data.BA.SP<span class="p">){</span></div><div class='line' id='LC252'> <span class="kr">for</span> <span class="p">(</span>i <span class="kr">in</span> <span class="m">2</span><span class="o">:</span>ncol<span class="p">(</span>data.BA.SP<span class="p">)){</span></div><div class='line' id='LC253'>eval<span class="p">(</span>parse<span class="p">(</span>text<span class="o">=</span>paste<span class="p">(</span><span class="s">"data.BA.SP[is.na("</span><span class="p">,</span>names<span class="p">(</span>data.BA.SP<span class="p">)[</span>i<span class="p">],</span><span class="s">"),"</span><span class="p">,</span>names<span class="p">(</span>data.BA.SP<span class="p">)[</span>i<span class="p">],</span><span class="s">":=0]"</span><span class="p">,</span>sep<span class="o">=</span><span class="s">""</span><span class="p">)))</span></div><div class='line' id='LC254'>eval<span class="p">(</span>parse<span class="p">(</span>text<span class="o">=</span>paste<span class="p">(</span><span class="s">"data.BA.SP["</span><span class="p">,</span>names<span class="p">(</span>data.BA.SP<span class="p">)[</span>i<span class="p">],</span><span class="s">"<0,"</span><span class="p">,</span>names<span class="p">(</span>data.BA.SP<span class="p">)[</span>i<span class="p">],</span><span class="s">":=0]"</span><span class="p">,</span>sep<span class="o">=</span><span class="s">""</span><span class="p">)))</span></div><div class='line' id='LC255'><span class="p">}</span></div><div class='line' id='LC256'>print<span class="p">(</span><span class="s">'NA and negative replaced'</span><span class="p">)</span></div><div class='line' id='LC257'><span class="kr">return</span><span class="p">(</span>data.BA.SP<span class="p">)</span></div><div class='line' id='LC258'><span class="p">}</span> </div><div class='line' id='LC259'><br/></div><div class='line' id='LC260'><span class="c1">##############################################################</span></div><div class='line' id='LC261'><span class="c1">##function to generate data in good format per ecoregion</span></div><div class='line' id='LC262'>fun.data.per.ecoregion <span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>ecoregion<span class="p">,</span>data.tot<span class="p">,</span>plot.name<span class="p">,</span>weight.full.plot<span class="p">,</span>name.country<span class="p">,</span>data.TRY<span class="o">=</span><span class="kc">NA</span><span class="p">,</span>species.lookup<span class="o">=</span><span class="kc">NA</span><span class="p">){</span></div><div class='line' id='LC263'><span class="kr">if</span><span class="p">(</span>is.null<span class="p">(</span>data.tot<span class="p">[[</span><span class="s">'weights'</span><span class="p">]]))</span> stop<span class="p">(</span><span class="s">"Please create a weights vector, even if it is completely NA"</span><span class="p">)</span></div><div class='line' id='LC264'>require<span class="p">(</span>data.table<span class="p">)</span></div><div class='line' id='LC265'>data.tot <span class="o"><-</span> data.table<span class="p">(</span>data.tot<span class="p">)</span></div><div class='line' id='LC266'>data <span class="o"><-</span> data.tot<span class="p">[</span>ecocode<span class="o">==</span>ecoregion<span class="p">,]</span></div><div class='line' id='LC267'>rm<span class="p">(</span>data.tot<span class="p">)</span></div><div class='line' id='LC268'>data.BA.SP <span class="o"><-</span> BA.SP.FUN.census<span class="p">(</span>census<span class="o">=</span>data<span class="p">[[</span><span class="s">'census'</span><span class="p">]],</span></div><div class='line' id='LC269'> obs.id<span class="o">=</span>as.vector<span class="p">(</span>data<span class="p">[[</span><span class="s">'obs.id'</span><span class="p">]]),</span></div><div class='line' id='LC270'> diam<span class="o">=</span>as.vector<span class="p">(</span>data<span class="p">[[</span><span class="s">'D'</span><span class="p">]]),</span></div><div class='line' id='LC271'> sp<span class="o">=</span>as.vector<span class="p">(</span>data<span class="p">[[</span><span class="s">'sp'</span><span class="p">]]),</span></div><div class='line' id='LC272'> id.plot<span class="o">=</span>as.vector<span class="p">(</span>data<span class="p">[[</span><span class="s">'plot'</span><span class="p">]]),</span></div><div class='line' id='LC273'> weights<span class="o">=</span>data<span class="p">[[</span><span class="s">'weights'</span><span class="p">]],</span></div><div class='line' id='LC274'> weight.full.plot<span class="o">=</span>weight.full.plot<span class="p">)</span></div><div class='line' id='LC275'><br/></div><div class='line' id='LC276'>print<span class="p">(</span><span class="s">'competition index computed'</span><span class="p">)</span></div><div class='line' id='LC277'><span class="c1">## change NA and <0 data for 0</span></div><div class='line' id='LC278'>data.BA.SP <span class="o"><-</span> function.replace.NA.negative<span class="p">(</span>data.BA.SP<span class="p">)</span></div><div class='line' id='LC279'><span class="c1">### CHECK IF sp and sp name for column are the same</span></div><div class='line' id='LC280'><span class="kr">if</span><span class="p">(</span>sum<span class="p">(</span><span class="o">!</span><span class="p">(</span>names<span class="p">(</span>data.BA.SP<span class="p">)[</span><span class="m">-1</span><span class="p">]</span> <span class="o">%in%</span> unique<span class="p">(</span>data<span class="p">[[</span><span class="s">"sp"</span><span class="p">]])))</span> <span class="o">></span><span class="m">0</span><span class="p">)</span> stop<span class="p">(</span><span class="s">"competition index sp name not the same as in data"</span><span class="p">)</span></div><div class='line' id='LC281'><span class="c1">#### compute BA tot for all competitors</span></div><div class='line' id='LC282'><span class="c1">## data.BA.SP[,BATOT:=sum(.SD),by=obs.id] ## slower than apply why?? </span></div><div class='line' id='LC283'>BATOT.s <span class="o"><-</span> apply<span class="p">(</span>data.frame<span class="p">(</span>data.BA.SP<span class="p">)[,</span><span class="m">-1</span><span class="p">],</span>MARGIN<span class="o">=</span><span class="m">1</span><span class="p">,</span>FUN<span class="o">=</span>sum<span class="p">)</span></div><div class='line' id='LC284'>data.BA.SP<span class="p">[,</span>BATOT<span class="o">:=</span>BATOT.s<span class="p">]</span></div><div class='line' id='LC285'>print<span class="p">(</span><span class="s">'BATOT COMPUTED'</span><span class="p">)</span></div><div class='line' id='LC286'><span class="c1">### create data frame</span></div><div class='line' id='LC287'>DT.temp <span class="o"><-</span> data.table<span class="p">(</span>obs.id<span class="o">=</span>data<span class="p">[[</span><span class="s">"obs.id"</span><span class="p">]],</span>ecocode<span class="o">=</span>data<span class="p">[[</span><span class="s">"ecocode"</span><span class="p">]])</span></div><div class='line' id='LC288'>setkeyv<span class="p">(</span>DT.temp<span class="p">,</span><span class="s">"obs.id"</span><span class="p">)</span></div><div class='line' id='LC289'>setkeyv<span class="p">(</span>data.BA.SP<span class="p">,</span><span class="s">"obs.id"</span><span class="p">)</span></div><div class='line' id='LC290'>print<span class="p">(</span><span class="s">'starting last merge'</span><span class="p">)</span></div><div class='line' id='LC291'>data.BA.sp <span class="o"><-</span> merge<span class="p">(</span>DT.temp<span class="p">,</span>data.BA.SP<span class="p">)</span></div><div class='line' id='LC292'><span class="c1">## reorder data</span></div><div class='line' id='LC293'>data <span class="o"><-</span> data.table<span class="p">(</span>data<span class="p">)</span></div><div class='line' id='LC294'>setkeyv<span class="p">(</span>data<span class="p">,</span><span class="s">"obs.id"</span><span class="p">)</span></div><div class='line' id='LC295'><span class="c1">## test if same order</span></div><div class='line' id='LC296'><span class="kr">if</span><span class="p">(</span>sum<span class="p">(</span><span class="o">!</span>data.BA.sp<span class="p">[[</span><span class="s">"obs.id"</span><span class="p">]]</span> <span class="o">==</span> data<span class="p">[[</span><span class="s">"obs.id"</span><span class="p">]])</span> <span class="o">></span><span class="m">0</span><span class="p">)</span> stop<span class="p">(</span><span class="s">"competition index not in the same order than data"</span><span class="p">)</span></div><div class='line' id='LC297'><span class="c1">#####</span></div><div class='line' id='LC298'><span class="c1">## ADD TRY DATA OR TRAITS IF NEEDED</span></div><div class='line' id='LC299'><span class="kr">if</span><span class="p">(</span><span class="o">!</span>is.na<span class="p">(</span>data.TRY<span class="p">)){</span></div><div class='line' id='LC300'>sp.extract <span class="o"><-</span> species.lookup<span class="p">[</span>species.lookup<span class="p">[[</span><span class="s">"sp"</span><span class="p">]]</span> <span class="o">%in%</span> unique<span class="p">(</span>data<span class="p">[[</span><span class="s">"sp"</span><span class="p">]]),]</span></div><div class='line' id='LC301'>data.traits <span class="o"><-</span> fun.extract.format.sp.traits.TRY<span class="p">(</span>sp<span class="o">=</span>sp.extract<span class="p">[[</span><span class="s">"sp"</span><span class="p">]],</span>sp.syno.table<span class="o">=</span>sp.extract<span class="p">,</span>data.TRY<span class="p">)</span></div><div class='line' id='LC302'><span class="c1">### TO DO ADD OPTION TO INCLUE OTHER DATA on MAX HEIGHT</span></div><div class='line' id='LC303'><span class="c1">## save everything as a list</span></div><div class='line' id='LC304'>print<span class="p">(</span>dim<span class="p">(</span>data.traits<span class="p">))</span></div><div class='line' id='LC305'>list.temp <span class="o"><-</span> list<span class="p">(</span>data.tree<span class="o">=</span>data<span class="p">,</span>data.BA.SP<span class="o">=</span>data.BA.sp<span class="p">,</span>data.traits<span class="o">=</span>data.traits<span class="p">)</span></div><div class='line' id='LC306'>save<span class="p">(</span>list.temp<span class="p">,</span>file<span class="o">=</span>paste<span class="p">(</span><span class="s">"./data/process/list"</span><span class="p">,</span>name.country<span class="p">,</span>ecoregion<span class="p">,</span><span class="s">"Rdata"</span><span class="p">,</span>sep<span class="o">=</span><span class="s">"."</span><span class="p">))</span></div><div class='line' id='LC307'><span class="p">}</span><span class="kr">else</span><span class="p">{</span></div><div class='line' id='LC308'>list.temp <span class="o"><-</span> list<span class="p">(</span>data.tree<span class="o">=</span>data<span class="p">,</span>data.BA.SP<span class="o">=</span>data.BA.sp<span class="p">,</span>data.traits<span class="o">=</span><span class="kc">NA</span><span class="p">)</span></div><div class='line' id='LC309'>saveRDS<span class="p">(</span>list.temp<span class="p">,</span>file<span class="o">=</span>paste<span class="p">(</span><span class="s">"./data/process/list"</span><span class="p">,</span>name.country<span class="p">,</span>ecoregion<span class="p">,</span><span class="s">"Rdata"</span><span class="p">,</span>sep<span class="o">=</span><span class="s">"."</span><span class="p">))</span></div><div class='line' id='LC310'><span class="p">}</span></div><div class='line' id='LC311'><span class="p">}</span> </div><div class='line' id='LC312'><br/></div><div class='line' id='LC313'><br/></div><div class='line' id='LC314'><span class="c1">#####################################</span></div><div class='line' id='LC315'><span class="c1">#####################################</span></div><div class='line' id='LC316'><span class="c1">### FUNCTION TO COMPUTE BA.SP.XY PER PLOT AND MERGE TOGETHER</span></div><div class='line' id='LC317'><span class="c1">#### function to be apply per site</span></div><div class='line' id='LC318'>fun.compute.BA.SP.XY.per.plot <span class="o"><-</span> <span class="kr">function</span><span class="p">(</span>i<span class="p">,</span>data.tree<span class="p">,</span>Rlim<span class="p">,</span>xy.name<span class="o">=</span>c<span class="p">(</span><span class="s">'x'</span><span class="p">,</span><span class="s">'y'</span><span class="p">),</span>parallel<span class="o">=</span><span class="kc">FALSE</span><span class="p">,</span>rpuDist<span class="o">=</span><span class="kc">FALSE</span><span class="p">){</span></div><div class='line' id='LC319'>data.tree.s <span class="o"><-</span> subset<span class="p">(</span>data.tree<span class="p">,</span>subset<span class="o">=</span>data.tree<span class="p">[[</span><span class="s">"plot"</span><span class="p">]]</span> <span class="o">==</span>i<span class="p">)</span></div><div class='line' id='LC320'>BA.SP.temp <span class="o"><-</span> BA.SP.FUN.XY<span class="p">(</span>obs.id<span class="o">=</span>data.tree.s<span class="p">[[</span><span class="s">'obs.id'</span><span class="p">]],</span></div><div class='line' id='LC321'> xy.table<span class="o">=</span>data.tree.s<span class="p">[,</span>xy.name<span class="p">],</span></div><div class='line' id='LC322'> diam<span class="o">=</span>data.tree.s<span class="p">[[</span><span class="s">'D'</span><span class="p">]],</span></div><div class='line' id='LC323'> sp<span class="o">=</span><span class="p">(</span>data.tree.s<span class="p">[[</span><span class="s">'sp'</span><span class="p">]]),</span></div><div class='line' id='LC324'> Rlim<span class="o">=</span><span class="m">15</span><span class="p">,</span></div><div class='line' id='LC325'> parallel<span class="o">=</span><span class="kc">FALSE</span><span class="p">,</span></div><div class='line' id='LC326'> rpuDist<span class="o">=</span><span class="kc">FALSE</span><span class="p">)</span></div><div class='line' id='LC327'><br/></div><div class='line' id='LC328'><span class="c1">## replace NA per zero</span></div><div class='line' id='LC329'>print<span class="p">(</span><span class="s">'replacing NA per zero'</span><span class="p">)</span></div><div class='line' id='LC330'>BA.SP.temp<span class="p">[</span>is.na<span class="p">(</span>BA.SP.temp<span class="p">)]</span> <span class="o"><-</span> <span class="m">0</span></div><div class='line' id='LC331'>print<span class="p">(</span><span class="s">'done'</span><span class="p">)</span></div><div class='line' id='LC332'><span class="c1">### rpud installation very cumbersome not needed ?</span></div><div class='line' id='LC333'><span class="c1">### longer in parallel why ?</span></div><div class='line' id='LC334'><span class="kr">if</span><span class="p">(</span>sum<span class="p">(</span><span class="o">!</span> rownames<span class="p">(</span>BA.SP.temp<span class="p">)</span><span class="o">==</span>data.tree.s<span class="p">[[</span><span class="s">'obs.id'</span><span class="p">]])</span> <span class="o">></span><span class="m">0</span><span class="p">)</span> stop<span class="p">(</span><span class="s">'rows not in the good order'</span><span class="p">)</span></div><div class='line' id='LC335'><span class="kr">if</span><span class="p">(</span>sum<span class="p">(</span><span class="o">!</span>colnames<span class="p">(</span>BA.SP.temp<span class="p">)</span><span class="o">==</span>as.character<span class="p">((</span>levels<span class="p">(</span>data.tree.s<span class="p">[[</span><span class="s">'sp'</span><span class="p">]]))))</span><span class="o">></span><span class="m">0</span><span class="p">)</span> stop<span class="p">(</span><span class="s">'colnames does mot match species name'</span><span class="p">)</span></div><div class='line' id='LC336'><br/></div><div class='line' id='LC337'><span class="c1">### compute sum per row</span></div><div class='line' id='LC338'>BATOT <span class="o"><-</span> apply<span class="p">(</span>BA.SP.temp<span class="p">,</span>MARGIN<span class="o">=</span><span class="m">1</span><span class="p">,</span>FUN<span class="o">=</span>sum<span class="p">)</span></div><div class='line' id='LC339'>data.res <span class="o"><-</span> data.frame<span class="p">(</span>obs.id<span class="o">=</span>data.tree.s<span class="p">[[</span><span class="s">'obs.id'</span><span class="p">]],</span>BA.SP.temp<span class="p">,</span>BATOT<span class="o">=</span>BATOT<span class="p">)</span></div><div class='line' id='LC340'><span class="kr">return</span><span class="p">(</span>data.res<span class="p">)</span></div><div class='line' id='LC341'><span class="p">}</span></div><div class='line' id='LC342'><br/></div><div class='line' id='LC343'><br/></div><div class='line' id='LC344'><br/></div><div class='line' id='LC345'><br/></div><div class='line' id='LC346'><br/></div></pre></div>
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+
- ### compute sum per row
- BATOT <- apply(BA.SP.temp, MARGIN = 1, FUN = sum)
- data.res <- data.frame(obs.id = data.tree.s[["obs.id"]], BA.SP.temp, BATOT = BATOT)
- return(data.res)
-}
+ </body>
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+
diff --git a/merge.data.US.R b/merge.data.US.R
index 275c7c10b3b411573e04403500fd8ffcf12c2854..7d68e412a7364c9bba189286644297079ae17000 100644
--- a/merge.data.US.R
+++ b/merge.data.US.R
@@ -1,57 +1,63 @@
+#!/usr/bin/env Rscript
+
### MERGE us DATA Edited by FH
-rm(list = ls())
+library(reshape, quietly=TRUE)
source("./R/format.function.R")
-library(reshape)
source("./R/FUN.TRY.R")
-######################### READ DATA read individuals tree data
-data.us <- read.csv("./data/raw/DataUS/FIA51_trees_w_supp.csv", header = TRUE, stringsAsFactors = FALSE)
-
### read species names
-species.clean <- read.csv("./data/species.list/REF_SPECIES.CSV", stringsAsFactors = FALSE)
-## select column to keep
-species.clean <- subset(species.clean, select = c("SPCD", "GENUS", "SPECIES", "VARIETY",
- "SUBSPECIES", "SPECIES_SYMBOL"))
-species.clean$Latin_name <- paste(species.clean[["GENUS"]], species.clean[["SPECIES"]],
- sep = " ")
-species.clean$Latin_name_syn <- paste(species.clean[["GENUS"]], species.clean[["SPECIES"]],
- sep = " ")
-
-names(species.clean)[1] <- "sp"
-species.clean[["sp"]] <- paste("sp", species.clean[["sp"]], sep = ".")
-
-###################################### MASSAGE TRAIT DATA HEIGHT DATA FOR TREE MISSING BRING US DATA FOR HEIGHT OVER
-###################################### WHEN WE ANALYZE THAT DATASET LATER ON
-
-##################################### FORMAT INDIVIDUAL TREE DATA
-
-## change unit and names of variables to be the same in all data for the tree
-data.us$G <- 10 * (data.us$FinalDbh - data.us$InitDbh)/data.us$Interval ## diameter growth in mm per year
-data.us$G[which(data.us$InitDbh == 0 | data.us$FinalDbh == -999)] <- NA
-data.us$year <- data.us$Interval ## number of year between measuremen
-data.us$D <- data.us[["InitDbh"]]
-data.us$D[data.us$D == 0] <- NA
-## diameter in cm
-data.us$dead <- as.numeric(data.us$FinalDbh > 0) ## dummy variable for dead tree 0 alive 1 dead
-data.us$sp <- as.character(data.us[["Species"]]) ## species code
-data.us$plot <- as.character(data.us[["PlotID"]]) ## plot code
-data.us$subplot <- paste(as.character(data.us[["PlotID"]]), as.character(data.us[["SubplotNumber"]]),
- sep = ".") ## plot code
-data.us$htot <- rep(NA, length(data.us[["Species"]])) ## height of tree in m - MISSING
-data.us$tree.id <- as.character(data.us$TreeID)
-## tree unique id
-data.us$sp.name <- NA
-
-### add plot weights for computation of competition index (in 1/m^2)
-data.us$weights <- 1/(10000 * data.us[["PlotSize"]])
-
-###################### ECOREGION merge greco to have no ecoregion with low number of observation
+load_species_list <- function(filename = "./data/raw/DataUS/REF_SPECIES.CSV"){
+ data <- read.csv(filename, stringsAsFactors = FALSE)
+ ## select column to keep
+ data <- subset(data, select = c("SPCD", "GENUS", "SPECIES", "VARIETY",
+ "SUBSPECIES", "SPECIES_SYMBOL"))
+ data$Latin_name <- paste(data[["GENUS"]], data[["SPECIES"]], sep = " ")
+ data$Latin_name_syn <- paste(data[["GENUS"]], data[["SPECIES"]], sep = " ")
+
+ names(data)[1] <- "sp"
+ data[["sp"]] <- paste("sp", data[["sp"]], sep = ".")
+ data
+}
+
+load_inventory_data <- function(filename = "./data/raw/DataUS/FIA51_trees_w_supp.csv"){
+ ## READ DATA read individuals tree data
+ data <- read.csv(filename, header = TRUE, stringsAsFactors = FALSE)
+
+ ####### MASSAGE TRAIT DATA HEIGHT DATA FOR TREE MISSING BRING US DATA FOR HEIGHT OVER
+ ####### WHEN WE ANALYZE THAT DATASET LATER ON
+
+ ###### FORMAT INDIVIDUAL TREE DATA
+
+ ## change unit and names of variables to be the same in all data for the tree
+ data$G <- 10 * (data$FinalDbh - data$InitDbh)/data$Interval ## diameter growth in mm per year
+ data$G[which(data$InitDbh == 0 | data$FinalDbh == -999)] <- NA
+ data$year <- data$Interval ## number of year between measuremen
+ data$D <- data[["InitDbh"]] ## diameter in cm
+ data$D[data$D == 0] <- NA
+ data$dead <- as.numeric(data$FinalDbh > 0) ## dummy variable for dead tree 0 alive 1 dead
+ data$sp <- as.character(data[["Species"]]) ## species code
+ data$plot <- as.character(data[["PlotID"]]) ## plot code
+ data$subplot <- paste(as.character(data[["PlotID"]]), as.character(data[["SubplotNumber"]]),
+ sep = ".") ## plot code
+ data$htot <- rep(NA, length(data[["Species"]])) ## height of tree in m - MISSING
+ data$tree.id <- as.character(data$TreeID) ## unique id
+ data$sp.name <- NA
+
+ ### add plot weights for computation of competition index (in 1/m^2)
+ data$weights <- 1/(10000 * data.us[["PlotSize"]])
+ data
+}
+
+data.us <- load_inventory_data()
+
+###### ECOREGION merge greco to have no ecoregion with low number of observation
greco <- read.csv(file = "./data/raw/DataUS/EcoregionCodes.csv", header = T)
colnames(greco)[1] <- "Ecocode"
table(data.us$Ecocode)
data.us <- merge(data.us, greco[, -4], by = "Ecocode")
data.us$DIVISION <- factor(data.us$DIVISION)
+
## Some ecoregions still have small # of individuals, so create a variable which
## does division if # ind < 10000 else it reads Domain
data.us$eco_codemerged <- as.character(data.us$DIVISION)
@@ -63,8 +69,8 @@ for (i in 1:length(sel.small.div)) {
data.us$eco_codemerged[find.ind] <- as.character(data.us$DOMAIN)[find.ind]
}
-###################### PERCENT DEAD variable percent dead/cannot do with since dead variable is
-###################### missing compute numer of dead per plot to remove plot with disturbance
+###### PERCENT DEAD variable percent dead/cannot do with since dead variable is
+###### missing compute numer of dead per plot to remove plot with disturbance
perc.dead <- tapply(data.us[["dead"]], INDEX = data.us[["plot"]], FUN = function.perc.dead)
# ## VARIABLE TO SELECT PLOT WITH NOT BIG DISTURBANCE KEEP OFTHER VARIABLES IF
# AVAILABLE (disturbance record)
@@ -72,8 +78,7 @@ data.us <- merge(data.us, data.frame(plot = names(perc.dead), perc.dead = perc.d
by = "plot", sort = FALSE)
-########################################################### PLOT SELECTION FOR THE ANALYSIS
-
+##### PLOT SELECTION FOR THE ANALYSIS
## remove everything from memory not need before computation
rm(greco, perc.dead, tab.small.div, sel.small.div)
@@ -89,6 +94,7 @@ vec.basic.var <- c("tree.id", "sp", "plot", "subplot", "ecocode", "D", "G", "dea
"year", "htot", "Lon", "Lat", "perc.dead", "weights")
data.tree <- subset(data.us, select = c(vec.basic.var, vec.abio.var.names))
rm(data.us)
+
## creat row unique id
data.tree$obs.id <- as.character(1:nrow(data.tree))
gc()
@@ -96,13 +102,17 @@ gc()
### read TRY data
TRY.DATA.FORMATED <- readRDS("./data/process/TRY.DATA.FORMATED.rds")
-#################### GENERATE ONE OBJECT PER ECOREGION
+#### GENERATE ONE OBJECT PER ECOREGION
# vector of ecoregion name
ecoregion.unique <- unique(data.tree[["ecocode"]])
-
-#### lapply function
-system.time(lapply(ecoregion.unique, FUN = fun.data.per.ecoregion, data.tot = data.tree,
- plot.name = "subplot", weight.full.plot = NA, name.country = "US", data.TRY = TRY.DATA.FORMATED,
- species.lookup = species.clean))
+#### split data by ecoregion and save to file
+system.time(lapply(ecoregion.unique, FUN = fun.data.per.ecoregion,
+ data.tot = data.tree,
+ plot.name = "subplot",
+ weight.full.plot = NA,
+ name.country = "US",
+ data.TRY = TRY.DATA.FORMATED,
+ species.lookup = load_species_list(),
+ output.dir = "output"))