code/07.0_fun_extract.R
In lanl/bci.elm.fates.hydrology: Hydrology outputs from ELM-FATES calibrated at BCI
## works both for for vars like H2OSOI that have a vector of values (by depth) and also vars with one with a single value
extractres_h0 <-
function(sam.start,
sam.end,
outdir,
filebase,
var.vec,
scale.vec,
filterFile,
start.year,
end.year,
current.folder) {
nmonth <- 12
nyears <- end.year - start.year + 1
ncol <- nmonth * nyears
# filter.arr <-
# read.table(file.path(wd, filterFile), header = F) # on server
filter.arr <-
read.table(file.path("data-raw/extract/", current.folder, filterFile), header = F) # on desktop
# sam.vec <-
# c(sam.start:sam.end)[filter.arr$V1[c(sam.start:sam.end)]]
sam.vec <-
c(sam.start:sam.end)[filter.arr$V1]
nsam <- length(sam.vec)
## to get the length of value vector (for H2OSOI the number of depths)#-----
casename <- paste(filebase, sam.vec[1], sep = "")
filetag <- paste0("clm2.h0.", start.year, "-")
monstr <- sprintf("%02d", 1)
filename <-
paste0(outdir,
"/",
casename,
"/run/",
casename,
".",
filetag,
monstr,
".nc")
nc <- nc_open(filename, write = F)
res.arr <- vector("list", length = length(var.vec))
var.length <- vector()
for (v in 1:length(var.vec)) {
var.name <- var.vec[v]
val <- ncvar_get(nc, var.name)
var.length[v] <- length(val)
for (k in 1:var.length[v]) {
res.arr[[v]][[k]] <- matrix(NA, nsam, ncol)
}
}
##----
pb <- txtProgressBar(min = 0, max = nsam, style = 3)
cnames <- NULL
for (yr in start.year:end.year) {
for (j in 1:12) {
cnames <- c(cnames, paste0(yr, "-", sprintf("%02d", j)))
}
}
for (i in 1:nsam) {
sample <- sam.vec[i]
setTxtProgressBar(pb, i)
casename <- paste(filebase, sample, sep = "")
for (yr in start.year:end.year) {
filetag <- paste("clm2.h0.", yr, "-", sep = "")
for (j in 1:nmonth) {
#months
monstr <- sprintf("%02d", j)
filename <-
paste0(outdir,
"/",
casename,
"/run/",
casename,
".",
filetag,
monstr,
".nc")
nc <- nc_open(filename, write = F)
for (v in 1:length(var.vec)) {
var.name <- var.vec[v]
scale <- scale.vec[v]
val <- ncvar_get(nc, var.name)
yri <- yr - start.year
indx <- j + nmonth * yri
for (k in 1:var.length[v]) {
res.arr[[v]][[k]][i, indx] <- val[k] * scale
}
}
nc_close(nc)
}
}
if(i %% 50 == 0) print(i)
}
for (v in 1:length(var.vec)) {
var.name <- var.vec[v]
for (k in 1:var.length[v]) {
res.arr[[v]][[k]] <- as.data.frame(res.arr[[v]][[k]])
colnames(res.arr[[v]][[k]]) <- cnames
rownames(res.arr[[v]][[k]]) <- sam.vec
}
# data is stored as a list
var.res.arr <- res.arr[[v]]
out.file.name <- paste0(var.name, ".h0.extract.Rdata")
# save(var.res.arr, file = file.path(wd, "extract", out.file.name)) # on server
save(var.res.arr, file = file.path("data-raw", "extract", current.folder, "extract", out.file.name)) # on desktop
}
}
### FOR DAILY output -------
extractres_h1 <-
function(sam.start,
sam.end,
outdir,
filebase,
var.vec,
scale.vec,
filterFile,
start.year,
end.year,
current.folder) {
cnames <- seq(from = as.Date(paste0(start.year, "-01-01")),
to = as.Date(paste0(end.year, "-12-31")),
by = 1)
## removing Feb 29 because CLM only produces output for 365 days not 366
cnames <- cnames[format(cnames, "%m-%d") != "02-29"]
ncol <- length(cnames)
# filter.arr <- read.table(file.path(wd, filterFile), header = F) # on server
filter.arr <-
read.table(file.path("data-raw/extract/", current.folder, filterFile), header = F) # on desktop
### temporarily turning some cases off, since some cases from 1:100 are not well run:
#filter.arr$V1[c(1:100, 740)] <- FALSE
sam.vec <-
c(sam.start:sam.end)#[filter.arr$V1[c(sam.start:sam.end)]] # turn this on after trial is finished
nsam <- length(sam.vec)
## to get the length of value vector (for H2OSOI the number of depths)#-----
casename <- paste(filebase, sam.vec[1], sep = "")
filetag <- paste0("clm2.h1.", start.year, "-")
filename <- paste0(outdir,
"/",
casename,
"/run/",
casename,
".",
filetag,
"01-01-00000.nc")
nc <- nc_open(filename, write = F)
res.arr <- vector("list", length = length(var.vec))
var.dim <- vector()
for (v in 1:length(var.vec)) {
var.name <- var.vec[v]
val <- ncvar_get(nc, var.name)
if (length(dim(val)) == 1) {
var.dim[v] <- 1
} else {
var.dim[v] <- dim(val)[1]
}
for (k in 1:var.dim[v]) {
res.arr[[v]][[k]] <- matrix(NA, nsam, ncol)
}
}
##----
#pb <- txtProgressBar(min = 0, max = nsam, style = 3)
for (i in 1:nsam) {
sample <- sam.vec[i]
#setTxtProgressBar(pb, i)
casename <- paste(filebase, sample, sep = "")
for (yr in start.year:end.year) {
filetag <- paste("clm2.h1.", yr, "-", sep = "")
filename <-
paste0(outdir,
"/",
casename,
"/run/",
casename,
".",
filetag,
"01-01-00000.nc")
nc <- nc_open(filename, write = F)
for (v in 1:length(var.vec)) {
var.name <- var.vec[v]
scale <- scale.vec[v]
val <- ncvar_get(nc, var.name)
index.start <- (yr - start.year) * 365 + 1
index.end <- index.start + 365 - 1
if (var.dim[v] == 1) {
res.arr[[v]][[1]][i, index.start:index.end] <- val * scale
} else {
for (k in 1:var.dim[v]) {
res.arr[[v]][[k]][i, index.start:index.end] <- val[k,] * scale
}
}
}
nc_close(nc)
}
print(sample)
# if (i %% 200 == 0)
# print(sample)
}
for (v in 1:length(var.vec)) {
var.name <- var.vec[v]
for (k in 1:var.dim[v]) {
res.arr[[v]][[k]] <- as.data.frame(res.arr[[v]][[k]])
colnames(res.arr[[v]][[k]]) <- cnames
rownames(res.arr[[v]][[k]]) <- sam.vec
}
# data is stored as a list
var.res.arr <- res.arr[[v]]
out.file.name <- paste0(var.name, ".h1.extract.Rdata")
# save(var.res.arr, file = file.path(wd, "extract", out.file.name)) # on server
save(var.res.arr, file = file.path("data-raw", "extract", current.folder, "extract", out.file.name)) # on desktop
}
}
# load(file.path(wd, "data-raw", "extract", out.file.name))
### FOR HOURLY output -------
extractres_h2 <-
function(sam.start,
sam.end,
outdir,
filebase,
var.vec,
scale.vec,
start.year,
end.year,
current.folder) {
cnames <-
seq(from = as.POSIXct(paste0(start.year, "-01-01 00:00:00", tz = "UTC")),
to = as.POSIXct(paste0(end.year, "-12-31 23:00:00", tz = "UTC")),
by = "hour")
cnames <- cnames[format(cnames, "%m-%d") != "02-29"]
ncol <- length(cnames)
# filter.arr <-
# read.table(file.path(wd, filterFile), header = F) # on server
filter.arr <-
read.table(file.path("data-raw/extract/", current.folder, filterFile), header = F) # on desktop
sam.vec <-
sam.vector[filter.arr$V1[sam.vector]]
nsam <- length(sam.vec)
## to get the length of value vector (for H2OSOI the number of depths)#-----
casename <- paste(filebase, sam.vec[1], sep = "")
filetag <- paste0("clm2.h2.", start.year, "-")
filename <- paste0(outdir,
"/",
casename,
"/run/",
casename,
".",
filetag,
"01-01-00000.nc")
nc <- nc_open(filename, write = F)
val <- ncvar_get(nc, var.name)
res.arr <- list()
if (length(dim(val)) == 1) {
var.dim <- 1
} else {
var.dim <- dim(val)[1]
}
for (k in 1:var.dim) {
res.arr[[k]] <- as.data.frame(matrix(NA, nsam, ncol))
}
##----
pb <- txtProgressBar(min = 0, max = nsam, style = 3)
# days_in_year <- function(year) {
# 365 + (year %% 4 == 0) - (year %% 100 == 0) + (year %% 400 == 0)
# }
for (i in 1:nsam) {
sample <- sam.vec[sample]
setTxtProgressBar(pb, i)
casename <- paste(filebase, sample, sep = "")
for (yr in start.year:end.year) {
filetag <- paste("clm2.h2.", yr, "-", sep = "")
filename <-
paste0(outdir,
"/",
casename,
"/run/",
casename,
".",
filetag,
"01-01-00000.nc")
nc <- nc_open(filename, write = F)
val <- ncvar_get(nc, var.name)
index.start <- 24 * (yr - start.year) * 365 + 1
index.end <- index.start + 365 * 24 - 1
if (var.dim == 1) {
res.arr[[1]][i, index.start:index.end] <- val * scale
} else {
for (k in 1:var.dim) {
res.arr[[k]][i, index.start:index.end] <- val[k,] * scale
}
}
nc_close(nc)
}
if (i %% 50 == 0) print(i)
}
for (k in 1:var.dim) {
colnames(res.arr[[k]]) <- cnames
rownames(res.arr[[k]]) <- sam.vec
# data is stored as a list
var.res.arr <- res.arr[[v]]
out.file.name <- paste0(var.name, ".h2.extract.Rdata")
# save(var.res.arr, file = file.path(wd, "extract", out.file.name)) # on server
save(var.res.arr, file = file.path("data-raw", "extract", current.folder, "extract", out.file.name)) # on desktop
}
}
###-------
# load(file.path(wd, "data-raw", "extract", out.file.name))
## old code which only works for vars with single value and stores into tables by nsam
# extractres_h0 <- function(nsam, outdir, filebase, var.name, filterFile, ###----
# scale, start.year, end.year, out.file.name){
# #outdir<-"/lustre/scratch3/tursampleuoise/rutuja/ACME/cases"
# #filebase<-"BCI.ICLM45ED.badger.intel.Cabfd064cb-Fc47f968e."
# #nsam<-8
# nmonth <- 12
# nyears <- end.year - start.year + 1
# ncol <- nmonth*nyears
# #scale = 30*24*3600 #rain from mm/s -> mm/month
# #filter.arr<-rep(F,nsam)
# res.arr <- as.data.frame(matrix(0, nsam, ncol))
# pb <- txtProgressBar(min = 0, max = nsam, style = 3)
# cnames <- NULL
# for (yr in start.year: end.year){
# for(j in 1:12){
# cnames <- c(cnames, paste(var.name, "y", yr, "m", j, sep=""));
# }
# }
# #filter.arr <- read.table(file.path(wd, filterFile), header = F)
# filter.arr <- read.table(file.path(wd, "data-raw", filterFile), header = F)
# filter.range <- filter.arr[1: nsam, 1] == 1
#
# for(i in 1: nsam){
# setTxtProgressBar(pb, i)
# casename <- paste(filebase, i, sep ="")
# for (yr in start.year:end.year){
# filetag <- paste("clm2.h0.", yr, "-", sep = "")
# for(j in 1:nmonth){ #months
# monstr <- sprintf("%02d", j)
# filename <- paste(outdir, "/", casename, "/run/", casename, ".",
# filetag, monstr,".nc", sep = "")
# nc <- nc_open(filename, write = F)
# val <- ncvar_get(nc, var.name)
# yri <- yr - start.year
# indx <- j + nmonth*yri
# res.arr[i, indx] <- val*scale
# nc_close(nc)
# }
# }
# }
# colnames(res.arr) <- cnames
# #write.table(res.arr[filter.range,],file.path(wd,"extract",out.file.name),sep="\t",row.names=F,col.names=T)
# write.table(res.arr[filter.range,], file.path(wd, "data-raw", "extract", out.file.name),
# sep="\t", row.names = F, col.names = T)
# }
lanl/bci.elm.fates.hydrology documentation built on Dec. 21, 2021, 8:50 a.m.
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## works both for for vars like H2OSOI that have a vector of values (by depth) and also vars with one with a single value
extractres_h0 <-
function(sam.start,
sam.end,
outdir,
filebase,
var.vec,
scale.vec,
filterFile,
start.year,
end.year,
current.folder) {
nmonth <- 12
nyears <- end.year - start.year + 1
ncol <- nmonth * nyears
# filter.arr <-
# read.table(file.path(wd, filterFile), header = F) # on server
filter.arr <-
read.table(file.path("data-raw/extract/", current.folder, filterFile), header = F) # on desktop
# sam.vec <-
# c(sam.start:sam.end)[filter.arr$V1[c(sam.start:sam.end)]]
sam.vec <-
c(sam.start:sam.end)[filter.arr$V1]
nsam <- length(sam.vec)
## to get the length of value vector (for H2OSOI the number of depths)#-----
casename <- paste(filebase, sam.vec[1], sep = "")
filetag <- paste0("clm2.h0.", start.year, "-")
monstr <- sprintf("%02d", 1)
filename <-
paste0(outdir,
"/",
casename,
"/run/",
casename,
".",
filetag,
monstr,
".nc")
nc <- nc_open(filename, write = F)
res.arr <- vector("list", length = length(var.vec))
var.length <- vector()
for (v in 1:length(var.vec)) {
var.name <- var.vec[v]
val <- ncvar_get(nc, var.name)
var.length[v] <- length(val)
for (k in 1:var.length[v]) {
res.arr[[v]][[k]] <- matrix(NA, nsam, ncol)
}
}
##----
pb <- txtProgressBar(min = 0, max = nsam, style = 3)
cnames <- NULL
for (yr in start.year:end.year) {
for (j in 1:12) {
cnames <- c(cnames, paste0(yr, "-", sprintf("%02d", j)))
}
}
for (i in 1:nsam) {
sample <- sam.vec[i]
setTxtProgressBar(pb, i)
casename <- paste(filebase, sample, sep = "")
for (yr in start.year:end.year) {
filetag <- paste("clm2.h0.", yr, "-", sep = "")
for (j in 1:nmonth) {
#months
monstr <- sprintf("%02d", j)
filename <-
paste0(outdir,
"/",
casename,
"/run/",
casename,
".",
filetag,
monstr,
".nc")
nc <- nc_open(filename, write = F)
for (v in 1:length(var.vec)) {
var.name <- var.vec[v]
scale <- scale.vec[v]
val <- ncvar_get(nc, var.name)
yri <- yr - start.year
indx <- j + nmonth * yri
for (k in 1:var.length[v]) {
res.arr[[v]][[k]][i, indx] <- val[k] * scale
}
}
nc_close(nc)
}
}
if(i %% 50 == 0) print(i)
}
for (v in 1:length(var.vec)) {
var.name <- var.vec[v]
for (k in 1:var.length[v]) {
res.arr[[v]][[k]] <- as.data.frame(res.arr[[v]][[k]])
colnames(res.arr[[v]][[k]]) <- cnames
rownames(res.arr[[v]][[k]]) <- sam.vec
}
# data is stored as a list
var.res.arr <- res.arr[[v]]
out.file.name <- paste0(var.name, ".h0.extract.Rdata")
# save(var.res.arr, file = file.path(wd, "extract", out.file.name)) # on server
save(var.res.arr, file = file.path("data-raw", "extract", current.folder, "extract", out.file.name)) # on desktop
}
}
### FOR DAILY output -------
extractres_h1 <-
function(sam.start,
sam.end,
outdir,
filebase,
var.vec,
scale.vec,
filterFile,
start.year,
end.year,
current.folder) {
cnames <- seq(from = as.Date(paste0(start.year, "-01-01")),
to = as.Date(paste0(end.year, "-12-31")),
by = 1)
## removing Feb 29 because CLM only produces output for 365 days not 366
cnames <- cnames[format(cnames, "%m-%d") != "02-29"]
ncol <- length(cnames)
# filter.arr <- read.table(file.path(wd, filterFile), header = F) # on server
filter.arr <-
read.table(file.path("data-raw/extract/", current.folder, filterFile), header = F) # on desktop
### temporarily turning some cases off, since some cases from 1:100 are not well run:
#filter.arr$V1[c(1:100, 740)] <- FALSE
sam.vec <-
c(sam.start:sam.end)#[filter.arr$V1[c(sam.start:sam.end)]] # turn this on after trial is finished
nsam <- length(sam.vec)
## to get the length of value vector (for H2OSOI the number of depths)#-----
casename <- paste(filebase, sam.vec[1], sep = "")
filetag <- paste0("clm2.h1.", start.year, "-")
filename <- paste0(outdir,
"/",
casename,
"/run/",
casename,
".",
filetag,
"01-01-00000.nc")
nc <- nc_open(filename, write = F)
res.arr <- vector("list", length = length(var.vec))
var.dim <- vector()
for (v in 1:length(var.vec)) {
var.name <- var.vec[v]
val <- ncvar_get(nc, var.name)
if (length(dim(val)) == 1) {
var.dim[v] <- 1
} else {
var.dim[v] <- dim(val)[1]
}
for (k in 1:var.dim[v]) {
res.arr[[v]][[k]] <- matrix(NA, nsam, ncol)
}
}
##----
#pb <- txtProgressBar(min = 0, max = nsam, style = 3)
for (i in 1:nsam) {
sample <- sam.vec[i]
#setTxtProgressBar(pb, i)
casename <- paste(filebase, sample, sep = "")
for (yr in start.year:end.year) {
filetag <- paste("clm2.h1.", yr, "-", sep = "")
filename <-
paste0(outdir,
"/",
casename,
"/run/",
casename,
".",
filetag,
"01-01-00000.nc")
nc <- nc_open(filename, write = F)
for (v in 1:length(var.vec)) {
var.name <- var.vec[v]
scale <- scale.vec[v]
val <- ncvar_get(nc, var.name)
index.start <- (yr - start.year) * 365 + 1
index.end <- index.start + 365 - 1
if (var.dim[v] == 1) {
res.arr[[v]][[1]][i, index.start:index.end] <- val * scale
} else {
for (k in 1:var.dim[v]) {
res.arr[[v]][[k]][i, index.start:index.end] <- val[k,] * scale
}
}
}
nc_close(nc)
}
print(sample)
# if (i %% 200 == 0)
# print(sample)
}
for (v in 1:length(var.vec)) {
var.name <- var.vec[v]
for (k in 1:var.dim[v]) {
res.arr[[v]][[k]] <- as.data.frame(res.arr[[v]][[k]])
colnames(res.arr[[v]][[k]]) <- cnames
rownames(res.arr[[v]][[k]]) <- sam.vec
}
# data is stored as a list
var.res.arr <- res.arr[[v]]
out.file.name <- paste0(var.name, ".h1.extract.Rdata")
# save(var.res.arr, file = file.path(wd, "extract", out.file.name)) # on server
save(var.res.arr, file = file.path("data-raw", "extract", current.folder, "extract", out.file.name)) # on desktop
}
}
# load(file.path(wd, "data-raw", "extract", out.file.name))
### FOR HOURLY output -------
extractres_h2 <-
function(sam.start,
sam.end,
outdir,
filebase,
var.vec,
scale.vec,
start.year,
end.year,
current.folder) {
cnames <-
seq(from = as.POSIXct(paste0(start.year, "-01-01 00:00:00", tz = "UTC")),
to = as.POSIXct(paste0(end.year, "-12-31 23:00:00", tz = "UTC")),
by = "hour")
cnames <- cnames[format(cnames, "%m-%d") != "02-29"]
ncol <- length(cnames)
# filter.arr <-
# read.table(file.path(wd, filterFile), header = F) # on server
filter.arr <-
read.table(file.path("data-raw/extract/", current.folder, filterFile), header = F) # on desktop
sam.vec <-
sam.vector[filter.arr$V1[sam.vector]]
nsam <- length(sam.vec)
## to get the length of value vector (for H2OSOI the number of depths)#-----
casename <- paste(filebase, sam.vec[1], sep = "")
filetag <- paste0("clm2.h2.", start.year, "-")
filename <- paste0(outdir,
"/",
casename,
"/run/",
casename,
".",
filetag,
"01-01-00000.nc")
nc <- nc_open(filename, write = F)
val <- ncvar_get(nc, var.name)
res.arr <- list()
if (length(dim(val)) == 1) {
var.dim <- 1
} else {
var.dim <- dim(val)[1]
}
for (k in 1:var.dim) {
res.arr[[k]] <- as.data.frame(matrix(NA, nsam, ncol))
}
##----
pb <- txtProgressBar(min = 0, max = nsam, style = 3)
# days_in_year <- function(year) {
# 365 + (year %% 4 == 0) - (year %% 100 == 0) + (year %% 400 == 0)
# }
for (i in 1:nsam) {
sample <- sam.vec[sample]
setTxtProgressBar(pb, i)
casename <- paste(filebase, sample, sep = "")
for (yr in start.year:end.year) {
filetag <- paste("clm2.h2.", yr, "-", sep = "")
filename <-
paste0(outdir,
"/",
casename,
"/run/",
casename,
".",
filetag,
"01-01-00000.nc")
nc <- nc_open(filename, write = F)
val <- ncvar_get(nc, var.name)
index.start <- 24 * (yr - start.year) * 365 + 1
index.end <- index.start + 365 * 24 - 1
if (var.dim == 1) {
res.arr[[1]][i, index.start:index.end] <- val * scale
} else {
for (k in 1:var.dim) {
res.arr[[k]][i, index.start:index.end] <- val[k,] * scale
}
}
nc_close(nc)
}
if (i %% 50 == 0) print(i)
}
for (k in 1:var.dim) {
colnames(res.arr[[k]]) <- cnames
rownames(res.arr[[k]]) <- sam.vec
# data is stored as a list
var.res.arr <- res.arr[[v]]
out.file.name <- paste0(var.name, ".h2.extract.Rdata")
# save(var.res.arr, file = file.path(wd, "extract", out.file.name)) # on server
save(var.res.arr, file = file.path("data-raw", "extract", current.folder, "extract", out.file.name)) # on desktop
}
}
###-------
# load(file.path(wd, "data-raw", "extract", out.file.name))
## old code which only works for vars with single value and stores into tables by nsam
# extractres_h0 <- function(nsam, outdir, filebase, var.name, filterFile, ###----
# scale, start.year, end.year, out.file.name){
# #outdir<-"/lustre/scratch3/tursampleuoise/rutuja/ACME/cases"
# #filebase<-"BCI.ICLM45ED.badger.intel.Cabfd064cb-Fc47f968e."
# #nsam<-8
# nmonth <- 12
# nyears <- end.year - start.year + 1
# ncol <- nmonth*nyears
# #scale = 30*24*3600 #rain from mm/s -> mm/month
# #filter.arr<-rep(F,nsam)
# res.arr <- as.data.frame(matrix(0, nsam, ncol))
# pb <- txtProgressBar(min = 0, max = nsam, style = 3)
# cnames <- NULL
# for (yr in start.year: end.year){
# for(j in 1:12){
# cnames <- c(cnames, paste(var.name, "y", yr, "m", j, sep=""));
# }
# }
# #filter.arr <- read.table(file.path(wd, filterFile), header = F)
# filter.arr <- read.table(file.path(wd, "data-raw", filterFile), header = F)
# filter.range <- filter.arr[1: nsam, 1] == 1
#
# for(i in 1: nsam){
# setTxtProgressBar(pb, i)
# casename <- paste(filebase, i, sep ="")
# for (yr in start.year:end.year){
# filetag <- paste("clm2.h0.", yr, "-", sep = "")
# for(j in 1:nmonth){ #months
# monstr <- sprintf("%02d", j)
# filename <- paste(outdir, "/", casename, "/run/", casename, ".",
# filetag, monstr,".nc", sep = "")
# nc <- nc_open(filename, write = F)
# val <- ncvar_get(nc, var.name)
# yri <- yr - start.year
# indx <- j + nmonth*yri
# res.arr[i, indx] <- val*scale
# nc_close(nc)
# }
# }
# }
# colnames(res.arr) <- cnames
# #write.table(res.arr[filter.range,],file.path(wd,"extract",out.file.name),sep="\t",row.names=F,col.names=T)
# write.table(res.arr[filter.range,], file.path(wd, "data-raw", "extract", out.file.name),
# sep="\t", row.names = F, col.names = T)
# }
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