Commit 98657240 authored by Georges Kunstler's avatar Georges Kunstler
Browse files

start explore results with MAT and CAT

parent 6fd5b3c4
#!/usr/bin/env Rscript
rm(list = ls())
source("R/analysis/lmer.output-fun.R")
source("R/analysis/lmer.run.nolog.all.R")
source("R/utils/plot.R")
source('R/utils/mem.R')
library(pander)
## test function to plot param in function of MAP
fm.MAT.MAP <- readRDS('output/lmer/all.no.log/SLA/species/lmer.LOGLIN.ER.AD.Tf.MAT.MAP/results.nolog.all.rds')
plot.fun.ci.param.var.climate(fm.MAT.MAP, 'SLA',
param.vec = c('sumTfBn', 'sumTnBn',
'sumTnTfBn.abs', 'Tf'),
var.vec = c('MAT', 'MAP'))
## load results all
list.all.results <- readRDS('output/list.lmer.out.no.log.all.temp.rds')
list.all.results <- readRDS('output/list.lmer.out.nolog.all.old.rds')
list.all.results <- readRDS('output/list.lmer.out.nolog.all.rds')
names.param <- unique(unlist(lapply(list.all.results, function(x) names(x$lmer.summary$fixed.coeff.E))))
names.param <- unique(unlist(lapply(list.all.results,
function(x) names(x$lmer.summary$fixed.coeff.E))))
names.param2 <- names.param
names.param2[names.param2 == "sumBn:MAT"] <- "MAT:sumBn"
names.param2[names.param2 == "sumBn:MAP"] <- "MAP:sumBn"
......@@ -33,8 +48,8 @@ print(pander(res))
## plot the parameters
pdf('figs/param.global.model.ER.AD.pdf')
par(mfrow = c(2,2))
par(mfrow = c(2,2))
for (i in c('Wood.density', 'SLA', 'Leaf.N', 'Max.height')){
DF.t <- DF.global[DF.global$trait == i, ]
print(i)
......@@ -53,11 +68,11 @@ fun.plot.error.bar(1:length(param.vec),
dev.off()
par(mfrow = c(2,2))
for (i in c('Wood.density', 'SLA', 'Leaf.N', 'Max.height')){
DF.t <- DF.global[DF.global$trait == i, ]
print(i)
param.vec <- c("Tf", 'MAT.Tf', 'MAP.Tf', "logD","sumBn", 'MAT.sumBn', 'MAP.sumBn',
param.vec <- c("Tf", 'MAT.Tf', 'MAP.Tf', 'MAT', 'MAP', "logD","sumBn", 'MAT.sumBn', 'MAP.sumBn',
"sumTnBn", 'MAT.sumTnBn', 'MAP.sumTnBn', "sumTfBn", 'MAT.sumTfBn',
'MAP.sumTfBn', "sumTnTfBn.abs" , 'MAT.sumTnTfBn.abs',
'MAP.sumTnTfBn.abs')
......@@ -73,3 +88,26 @@ fun.plot.error.bar(1:length(param.vec),
}
## cat
## TODO
par(mfrow = c(2,2))
for (i in c('Wood.density', 'SLA', 'Leaf.N', 'Max.height')){
DF.t <- DF.global[DF.global$trait == i, ]
print(i)
param.vec <- c("Tf.A_EV", "Tf.A_D", 'Tf.C',"logD","sumBn",
"sumTnBn.A_EV", "sumTnBn.A_D", "sumTnBn.C",
"sumTfBn.A_EV", "sumTfBn.A_D","sumTfBn.C",
"sumTnTfBn.abs.A_EV" , "sumTnTfBn.abs.A_D", "sumTnTfBn.abs.C")
param.vec.std <- paste(param.vec, 'Std.Error', sep = '.')
mode.selected <- 'lmer.LOGLIN.ER.AD.Tf.norandom'
plot(unlist(DF.t[DF.t$model == mode.selected, param.vec]),
xaxt = 'n', ylab = 'std parameters', xlab = NA,
main = i, ylim = c(-1, 1))
abline(h = 0)
axis(1, 1:length(param.vec), labels = param.vec, las = 3)
fun.plot.error.bar(1:length(param.vec),
DF.t[DF.t$model == mode.selected, param.vec],
DF.t[DF.t$model == mode.selected, param.vec.std])
}
......@@ -620,11 +620,17 @@ return(list(sp = list.sp, ge = list.ge))
## start code to predict regression line with CI
library(lme4)
library(ggplot2) # Plotting
data("Orthodont",package="MEMSS")
fm1 <- lmer(
formula = distance ~ age*Sex + (age|Subject)
, data = Orthodont)
## library(ggplot2) # Plotting
## data("Orthodont",package="MEMSS")
## fm1 <- lmer(
## formula = distance ~ age*Sex + (age|Subject)
## , data = Orthodont)
## df.lmer <- load.and.prepare.data.for.lmer(trait = 'Wood.density',
## min.obs = 10, sample.size = NA,
## type.filling = 'species',
## fname = 'data.all.no.std.csv',
## cat.TF = FALSE)
fun.prepare.data.pred <- function(data, var, n.length = 100){
......@@ -649,24 +655,94 @@ return(new.data)
fun.predict.ci.lmer <- function(fm, newdata){
mm <- model.matrix(terms(fm1),newdat)
newdat$distance <- mm %*% fixef(fm1)
pvar1 <- diag(mm %*% tcrossprod(vcov(fm1),mm))
newdat <- data.frame(newdat,
plo = newdat$distance-1.96*sqrt(pvar1),
phi = newdat$distance+1.96*sqrt(pvar1))
return(newdat)
fun.predict.ci.lmer <- function(fm, newdat, param, param.var){
newdat[[param]] <- 1
mm <- model.matrix(terms(fm),newdat)
mm2 <- mm
mm2[,!colnames(mm2) %in% c(param,param.var)] <- 0
pred <- (mm2 %*% fixef(fm))/mean(mm[,param])
pvar1 <- diag(mm2 %*% tcrossprod(vcov(fm),mm))
dat <- data.frame(pred = pred,
plo = pred-1.96*sqrt(pvar1),
phi = pred+1.96*sqrt(pvar1))
return(dat)
}
## newdat <- fun.prepare.data.pred(data = df.lmer, 'MAT', n.length= 100)
## newdat <- fun.predict.ci.lmer(fm.MAT.MAP, newdat, param = 'sumTfBn', param.var = 'MAT:sumTfBn')
fun.generate.pred.dat <- function(n.length = 100){
list.res.MAT <- list(logG = 0,
logD = 0,
MAT = seq(-1.89, 2.84,length = n.length),
MAP = 0,
species.id = 1,
tree.id = 1,
set.id = 1,
ecocode.id = 1,
plot.id = 1,
sumTnTfBn.diff = 0,
sumTnTfBn.abs= 0,
Tf = 0,
sumTnBn = 0,
sumTfBn = 0,
sumBn = 0)
list.res.MAP <- list(logG = 0,
logD = 0,
MAT = 0,
MAP = seq(-1.36, 4.02, length = n.length),
species.id = 1,
tree.id = 1,
set.id = 1,
ecocode.id = 1,
plot.id = 1,
sumTnTfBn.diff = 0,
sumTnTfBn.abs= 0,
Tf = 0,
sumTnBn = 0,
sumTfBn = 0,
sumBn = 0)
new.data.MAT <- expand.grid(list.res.MAT)
new.data.MAP <- expand.grid(list.res.MAP)
list.new.data <- list(MAT = new.data.MAT, MAP = new.data.MAP)
return(list.new.data)
}
plot.fun.ci.param.var.climate <- function(fm, trait, param.vec, var.vec,
n.length = 100){
list.new.data <- fun.generate.pred.dat(n.length = 100)
par(mfrow=c(length(var.vec), length(param.vec)))
for (var in var.vec){
newdat <- list.new.data[[var]]
for(param in param.vec){
param.var = paste(var, param, sep = ':')
if(param == 'Tf') param.var = paste(param, var, sep = ':')
dat.pred <- fun.predict.ci.lmer(fm.MAT.MAP, newdat,
param, param.var)
plot(newdat[[var]], dat.pred$pred, type = 'l',
ylim = c(-1,1), xlab = var, ylab = param)
lines(newdat[[var]], dat.pred$plo, lty = 2)
lines(newdat[[var]], dat.pred$phi, lty = 2)
abline(h = 0, lwd = 2)
param.est <- fixef(fm)
param.sd <- sqrt(diag(vcov(fm)))
names(param.sd) <- names(param.est)
abline(h = param.est[param], col = 'grey')
abline(h = param.est[param] + 1.96*param.sd[param],
lty = 2, col = 'grey')
abline(h = param.est[param] - 1.96*param.sd[param],
lty = 2, col = 'grey')
}
}
}
newdat <- fun.prepare.data.pred(data = newdat, 'age')
newdat <- fun.predict.ci.lmer(fm1, newdat)
## TODO TES THAT !
#plot confidence
## # test
## fm.MAT.MAP <- readRDS('output/lmer/all.no.log/Wood.density/species/lmer.LOGLIN.ER.AD.Tf.MAT.MAP/results.nolog.all.rds')
## fun.ci.param.var.climate(fm.MAT.MAP, 'Wood.density', param = 'sumTfBn', var = 'MAT')
g0 <- ggplot(newdat, aes(x=age, y=distance, colour=Sex))+geom_point()
g0 + geom_errorbar(aes(ymin = plo, ymax = phi))+
opts(title="CI based on fixed-effects uncertainty ONLY")
......@@ -3,26 +3,18 @@
### FUNCTION TO RUN LMER ESTIMATION WITH NO logBA for all in one big model
library(lme4)
run.models.for.set.all.traits <- function(model.file, fun.model, traits =
c("SLA", "Wood.density", "Max.height", "Leaf.N", "Seed.mass"),
type.filling, ...){
for(trait in traits)
run.multiple.model.for.set.one.trait(model.file, fun.model, trait,
type.filling = type.filling, ...)
}
run.multiple.model.for.set.one.trait <- function(model.files, fun.model, trait,
type.filling, cat.TF, ...){
type.filling, cat.TF = FALSE, fname = 'data.all.no.std.csv' , ...){
for (m in model.files)
(run.model.for.set.one.trait (m, fun.model, trait,
type.filling = type.filling, cat.TF = cat.TF, ...))
type.filling = type.filling, cat.TF = cat.TF, fname, ...))
}
run.model.for.set.one.trait <- function(model.file, fun.model, trait,
type.filling, cat.TF, ...){
type.filling, cat.TF, fname, ...){
fun.model <- match.fun(fun.model)
try(fun.model(model.file, trait, type.filling = type.filling,cat.TF = cat.TF, ...))
try(fun.model(model.file, trait, type.filling = type.filling,cat.TF = cat.TF, fname = fname, ...))
}
......@@ -51,8 +43,13 @@ model.files.lmer.Tf.4 <-
"R/analysis/model.lmer.all/model.lmer.LOGLIN.HD.Tf.MAT.MAP.R",
"R/analysis/model.lmer.all/model.lmer.LOGLIN.simplecomp.Tf.MAT.MAP.R")
model.files.lmer.Tf.5 <-
c("R/analysis/model.lmer.all/model.lmer.LOGLIN.ER.AD.Tf.norandom.R")
model.files.lmer.Tf.6 <-
c("R/analysis/model.lmer.all/model.lmer.LOGLIN.ER.AD.Tf.CAT.norandom.R")
fun.call.lmer.and.save <- function(formula, df.lmer, path.out){
lmer.output <- lmer(formula = formula, data = df.lmer, REML = FALSE,
control = lmerControl(optCtrl = list(maxfun = 40000) ) )
......@@ -118,8 +115,13 @@ load.and.prepare.data.for.lmer <- function(trait,
min.obs, sample.size, type.filling,
cat.TF,
fname = 'data.all.no.std.csv',
base.dir = "output/processed"){
data.tree.tot <- fun.load.data.all(base.dir,fname)
base.dir = "output/processed",
data.table.TF = FALSE){
if(!data.table.TF) data.tree.tot <- fun.load.data.all(base.dir,fname)
if(data.table.TF) {
require(data.table)
data.tree.tot <- fread(file.path(base.dir, fname))
}
fun.data.for.lmer(data.tree.tot, trait, type.filling = type.filling, cat.TF = cat.TF)
}
......
load.model <- function () {
list(name="lmer.LOGLIN.E.Tf.MAT.MAP",
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+Tf:MAT+Tf:MAP+logD+MAT+MAP+sumBn+sumBn:MAT+sumBn:MAP+sumTnBn+sumTnBn:MAT+sumTnBn:MAP+(logD-1|species.id)+(Tf-1|set.id)+(sumBn-1|set.id)+(sumTnBn-1|set.id)") )
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+Tf:MAT+Tf:MAP+MAT+MAP+logD+sumBn+sumBn:MAT+sumBn:MAP+sumTnBn+sumTnBn:MAT+sumTnBn:MAP+(logD-1|species.id)+(Tf-1|set.id)+(sumBn-1|set.id)+(sumTnBn-1|set.id)") )
}
......
load.model <- function () {
list(name="lmer.LOGLIN.ER.Tf",
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+logD+sumTfBn+sumBn+sumTnBn+sumTnTfBn.abs+(logD-1|species.id)+(Tf-1|set.id)+(sumTfBn-1|set.id)+(sumBn-1|set.id)+(sumTnBn-1|set.id)+(sumTnTfBn.abs-1|set.id)"))
}
load.model <- function () {
list(name="lmer.LOGLIN.ER.AD.Tf.norandom",
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf.A_EV+Tf.A_D+Tf.C+logD+sumTfBn.A_EV+sumTfBn.A_D+sumTfBn.C+sumBn+sumTnBn.A_EV+sumTnBn.A_D+sumTnBn.C+sumTnTfBn.abs.A_EV+sumTnTfBn.abs.A_D+sumTnTfBn.abs.C+(logD-1|species.id)"))
list(name="lmer.LOGLIN.ER.AD.Tf.CAT.norandom",
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf.A_EV+Tf.A_D+Tf.C+logD+sumBn+sumTfBn.A_EV+sumTfBn.A_D+sumTfBn.C+sumTnBn.A_EV+sumTnBn.A_D+sumTnBn.C+sumTnTfBn.abs.A_EV+sumTnTfBn.abs.A_D+sumTnTfBn.abs.C+(logD-1|species.id)"))
}
......
load.model <- function () {
list(name="lmer.LOGLIN.ER.AD.Tf.MAT.MAP",
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+Tf:MAT+Tf:MAP+MAT+MAP+logD+sumBn+sumBn:MAT+sumBn:MAP+sumTfBn+sumTfBn:MAT+sumTfBn:MAP+sumTnBn+sumTnBn:MAT+sumTnBn:MAP+sumTnTfBn.abs+sumTnTfBn.abs:MAT+sumTnTfBn.abs:MAP+(logD-1|species.id)+(Tf-1|set.id)+(sumTfBn-1|set.id)+(sumBn-1|set.id)+(sumTnBn-1|set.id)+(sumTnTfBn.abs-1|set.id)"))
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+Tf:MAT+Tf:MAP+MAT+MAP+logD+sumBn+sumBn:MAT+sumBn:MAP+sumTfBn+sumTfBn:MAT+sumTfBn:MAP+sumTnBn+sumTnBn:MAT+sumTnBn:MAP+sumTnTfBn.abs+sumTnTfBn.abs:MAT+sumTnTfBn.abs:MAP+(logD-1|species.id)+(Tf-1|set.id)+(sumBn-1|set.id)+(sumTfBn-1|set.id)+(sumTnBn-1|set.id)+(sumTnTfBn.abs-1|set.id)"))
}
......
load.model <- function () {
list(name="lmer.LOGLIN.ER.AD.Tf",
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+logD+sumTfBn+sumBn+sumTnBn+sumTnTfBn.abs+(logD-1|species.id)+(Tf-1|set.id)+(sumTfBn-1|set.id)+(sumBn-1|set.id)+(sumTnBn-1|set.id)+(sumTnTfBn.abs-1|set.id)"))
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+logD+sumBn+sumTfBn+sumTnBn+sumTnTfBn.abs+(logD-1|species.id)+(Tf-1|set.id)+(sumBn-1|set.id)+(sumTfBn-1|set.id)+(sumTnBn-1|set.id)+(sumTnTfBn.abs-1|set.id)"))
}
......
load.model <- function () {
list(name="lmer.LOGLIN.ER.Tf.MAT.MAP",
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+Tf:MAT+Tf:MAP+MAT+MAP+logD+sumTfBn+sumTfBn:MAT+sumTfBn:MAP+sumBn+sumBn:MAT+sumBn:MAP+sumTnBn+sumTnBn:MAT+sumTnBn:MAP+(logD-1|species.id)+(Tf-1|set.id)+(sumTfBn-1|set.id)+(sumBn-1|set.id)+(sumTnBn-1|set.id)"))
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+Tf:MAT+Tf:MAP+MAT+MAP+logD+sumBn+sumBn:MAT+sumBn:MAP+sumTfBn+sumTfBn:MAT+sumTfBn:MAP+sumTnBn+sumTnBn:MAT+sumTnBn:MAP+(logD-1|species.id)+(Tf-1|set.id)+(sumBn-1|set.id)+(sumTfBn-1|set.id)+(sumTnBn-1|set.id)"))
}
......
load.model <- function () {
list(name="lmer.LOGLIN.ER.Tf",
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+logD+sumTfBn+sumBn+sumTnBn+(logD-1|species.id)+(Tf-1|set.id)+(sumTfBn-1|set.id)+(sumBn-1|set.id)+(sumTnBn-1|set.id)"))
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+logD+sumBn+sumTfBn+sumTnBn+(logD-1|species.id)+(Tf-1|set.id)+(sumBn-1|set.id)+(sumTfBn-1|set.id)+(sumTnBn-1|set.id)"))
}
load.model <- function () {
list(name="lmer.LOGLIN.R.Tf.MAT.MAP",
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+logD+MAT+MAP+sumBn+Tf:MAT+Tf:MAP+sumBn:MAT+sumBn:MAP+sumTfBn+sumTfBn:MAT+sumTfBn:MAP+(logD-1|species.id)+(Tf-1|set.id)+(sumBn-1|set.id)+(sumTfBn-1|set.id)"))
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+Tf:MAT+Tf:MAP+MAT+MAP+logD+sumBn+sumBn:MAT+sumBn:MAP+sumTfBn+sumTfBn:MAT+sumTfBn:MAP+(logD-1|species.id)+(Tf-1|set.id)+(sumBn-1|set.id)+(sumTfBn-1|set.id)"))
}
......
load.model <- function () {
list(name="lmer.LOGLIN.nocomp.Tf.MAT.MAP",
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+logD+MAT+MAP+Tf:MAT+Tf:MAP+(logD-1|species.id)+(Tf-1|set.id)"))
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+Tf:MAT+Tf:MAP+MAT+MAP+logD+(logD-1|species.id)+(Tf-1|set.id)"))
}
......
load.model <- function () {
list(name="lmer.LOGLIN.simplecomp.Tf.MAT.MAP",
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+logD+MAT+MAP+Tf:MAT+Tf:MAP+sumBn+sumBn:MAT+sumBn:MAP+(logD-1|species.id)+(Tf-1|set.id)+(sumBn-1|set.id)"))
lmer.formula.tree.id=formula("logG~1+(1|set.id)+(1|species.id)+(1|plot.id)+Tf+Tf:MAT+Tf:MAP+MAT+MAP+logD+sumBn+sumBn:MAT+sumBn:MAP+(logD-1|species.id)+(Tf-1|set.id)+(sumBn-1|set.id)"))
}
......
......@@ -10,3 +10,34 @@ mem <- function() {
usage <- gc()
sum(usage[, 1] * c(node_size, 8)) / (1024 ^ 2)
}
# improved list of objects
.ls.objects <- function (pos = 1, pattern, order.by,
decreasing=FALSE, head=FALSE, n=5) {
napply <- function(names, fn) sapply(names, function(x)
fn(get(x, pos = pos)))
names <- ls(pos = pos, pattern = pattern)
obj.class <- napply(names, function(x) as.character(class(x))[1])
obj.mode <- napply(names, mode)
obj.type <- ifelse(is.na(obj.class), obj.mode, obj.class)
obj.prettysize <- napply(names, function(x) {
capture.output(print(object.size(x), units = "auto")) })
obj.size <- napply(names, object.size)
obj.dim <- t(napply(names, function(x)
as.numeric(dim(x))[1:2]))
vec <- is.na(obj.dim)[, 1] & (obj.type != "function")
obj.dim[vec, 1] <- napply(names, length)[vec]
out <- data.frame(obj.type, obj.size, obj.prettysize, obj.dim)
names(out) <- c("Type", "Size", "PrettySize", "Rows", "Columns")
if (!missing(order.by))
out <- out[order(out[[order.by]], decreasing=decreasing), ]
if (head)
out <- head(out, n)
out
}
# shorthand
lsos <- function(..., n=10) {
.ls.objects(..., order.by="Size", decreasing=TRUE, head=TRUE, n=n)
}
......@@ -6,18 +6,24 @@ mkdir -p trait.workshop
for trait in "'SLA'" "'Leaf.N'" "'Wood.density'" "'Max.height'" "'Seed.mass'"; do
echo "/usr/local/R/R-3.0.1/bin/Rscript -e \"source('R/analysis/lmer.run.nolog.all.R');;print('done')\"" > trait.workshop/species1$trait.sh
echo "/usr/local/R/R-3.0.1/bin/Rscript -e \"source('R/analysis/lmer.run.nolog.all.R');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.1[3], run.lmer,$trait,type.filling='species', fname = 'data.all.csv');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.1[3], run.lmer,$trait,type.filling='species');print('done')\"" > trait.workshop/species1$trait.sh
qsub trait.workshop/species1$trait.sh -l nodes=1:ppn=1 -N "lmerall1$trait" -q opt32G -j oe
echo "/usr/local/R/R-3.0.1/bin/Rscript -e \"source('R/analysis/lmer.run.nolog.all.R');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.2[3], run.lmer,$trait,type.filling='species');print('done')\"" > trait.workshop/species2$trait.sh
echo "/usr/local/R/R-3.0.1/bin/Rscript -e \"source('R/analysis/lmer.run.nolog.all.R');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.2[3], run.lmer,$trait,type.filling='species', fname = 'data.all.csv');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.2[3], run.lmer,$trait,type.filling='species');print('done')\"" > trait.workshop/species2$trait.sh
qsub trait.workshop/species2$trait.sh -l nodes=1:ppn=1 -N "lmerall2$trait" -q opt32G -j oe
echo "/usr/local/R/R-3.0.1/bin/Rscript -e \"source('R/analysis/lmer.run.nolog.all.R');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.3[3], run.lmer,$trait,type.filling='species');print('done')\"" > trait.workshop/species3$trait.sh
echo "/usr/local/R/R-3.0.1/bin/Rscript -e \"source('R/analysis/lmer.run.nolog.all.R');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.3[3], run.lmer,$trait,type.filling='species', fname = 'data.all.csv');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.3[3], run.lmer,$trait,type.filling='species');print('done')\"" > trait.workshop/species3$trait.sh
qsub trait.workshop/species3$trait.sh -l nodes=1:ppn=1 -N "lmerall3$trait" -q opt32G -j oe
echo "/usr/local/R/R-3.0.1/bin/Rscript -e \"source('R/analysis/lmer.run.nolog.all.R');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.4[3], run.lmer,$trait,type.filling='species');print('done')\"" > trait.workshop/species4$trait.sh
echo "/usr/local/R/R-3.0.1/bin/Rscript -e \"source('R/analysis/lmer.run.nolog.all.R');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.4[3], run.lmer,$trait,type.filling='species', fname = 'data.all.csv');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.4[3], run.lmer,$trait,type.filling='species');print('done')\"" > trait.workshop/species4$trait.sh
qsub trait.workshop/species4$trait.sh -l nodes=1:ppn=1 -N "lmerall4$trait" -q opt32G -j oe
echo "/usr/local/R/R-3.0.1/bin/Rscript -e \"source('R/analysis/lmer.run.nolog.all.R');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.5, run.lmer,$trait,type.filling='species', fname = 'data.all.csv');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.5, run.lmer,$trait,type.filling='species');print('done')\"" > trait.workshop/species5$trait.sh
qsub trait.workshop/species5$trait.sh -l nodes=1:ppn=1 -N "lmerall5$trait" -q opt32G -j oe
echo "/usr/local/R/R-3.0.1/bin/Rscript -e \"source('R/analysis/lmer.run.nolog.all.R');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.6, run.lmer,$trait,type.filling='species', cat.TF = TRUE, fname = 'data.all.csv');run.multiple.model.for.set.one.trait(model.files.lmer.Tf.6, run.lmer,$trait,type.filling='species', cat.TF = TRUE);print('done')\"" > trait.workshop/species6$trait.sh
qsub trait.workshop/species6$trait.sh -l nodes=1:ppn=1 -N "lmerall6$trait" -q opt32G -j oe
done
......
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