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functionsCenturyToCerrado.R
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functionsCenturyToCerrado.R
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#####################################################################
#####################################################################
#'funcoes consolidadas para processamento no grid por blocos
#'
getReferenceRaster <- function(inputDir, pattern) {
imageFiles = Sys.glob(file.path(inputDir, pattern))
rasterFile <- raster(imageFiles[1])
rasterFile
}
getBlocksOffset <- function(colOffset, rowOffset, nBlock, nColBlock = NULL, nRowBlock = NULL) {
if(!is.null(nColBlock)){
print("blocos por colunas")
#blocks by col
blocksOffset <- data.frame(iBlock = 1, colOffset, rowOffset)
for(iBlock in 2:nBlock){
blockOffset_i <- c(iBlock, (colOffset + ((iBlock-1) * nColBlock)), rowOffset)
blocksOffset <-rbind(blocksOffset, blockOffset_i)
}
return(blocksOffset)
} else if(!is.null(nRowBlock)){
print("blocos por linhas")
#blocks by col
blocksOffset <- data.frame(iBlock = 1, colOffset, rowOffset)
for(iBlock in 2:nBlock){
blockOffset_i <- c(iBlock, colOffset, (rowOffset + ((iBlock-1) * nRowBlock)))
blocksOffset <-rbind(blocksOffset, blockOffset_i)
}
return(blocksOffset)
} else {
print("O numero de linhas ou colunas por blocks nao informado")
}
}
getOutputExtent <- function(referenceRaster, blockOffset, blockSize) {
extentBlock <- extent(referenceRaster, blockOffset[2], c((blockOffset[2]-1) + blockSize[2]),
blockOffset[1], c((blockOffset[1]-1) + blockSize[1]))
return(extentBlock)
}
readBlockImages = function(inputDir, outputExtent, pattern) {
imageFiles <- mixedsort(Sys.glob(file.path(inputDir, pattern)))
# print(imageFiles)
rasterBlock_img1 <- (crop(raster(imageFiles[1]), outputExtent))
imageDataList <- data.frame(cellNumber = 1:ncell(rasterBlock_img1))
imageDataList[,2:(length(imageFiles)+1)] <- NA
names(imageDataList)[2:ncol(imageDataList)] <- paste0('band',1:(ncol(imageDataList)-1))
imageDataList[,2:ncol(imageDataList)] <- lapply(imageFiles, function(x){crop(raster(x), outputExtent)[]})
return(imageDataList[,-1]) #nao gravar cellNumber
}
saveImage <- function(outputData, outputfile, blockOffset, outputExtent, referenceRaster) {
outputfile = paste0(outputfile, 'rowcolOffset_', blockOffset[2], '_', blockOffset[1], '.tif') ###
outputRaster <- crop(referenceRaster, outputExtent)
outputRaster[] <- outputData
writeRaster(outputRaster, filename=outputfile, overwrite=TRUE)
}
#####################################################################
#####################################################################
#'CENTURY Soil Organic Matter Model Environment
#'funções par rodar o modelo century para o bioma cerrado
runCenturyCerrado <- function(pixel){
pixel <- as.numeric(pixel)
if(is.na(pixel[2])){
OUT <- as.numeric(rep(NA, 960))
} else if(!length(pixel) == 1447){
print("o comprimento do pixel deve ser 1375")
} else{
STi <- Sys.time()
DTym <- seq.Date(from = ymd('1980-01-01'),
to = ymd('2019-12-01'),
by = 'month')
cellNumber <- pixel[1]
###
###
#'criar arquivo wth
climateData <- data.frame(
t(
rbind(pixel[8:487]/10,
pixel[488:967],
pixel[968:1447])
)
)
names(climateData) <- c('prec', 'tmin', 'tmax')
climateData$ano = year(DTym)
climateData$mes = month(DTym)
#reshape data (long to wide)
reshapeClimateData = as.data.frame(
t(
stats::reshape(climateData,
idvar = c("mes"),
v.names = c("prec", "tmin", "tmax"),
timevar = "ano",
direction = "wide")
)
)
names(reshapeClimateData) = 1:12
reshapeClimateData$Var = substr(rownames(reshapeClimateData), 1, 4)
reshapeClimateData$ano = substr(rownames(reshapeClimateData), 6, 9)
reshapeClimateData = reshapeClimateData[-1, c(13:14,1:12)]
# Format rows output to the same number of character
rowsClimateData = list()
for (i in 1:nrow(reshapeClimateData))
{
linha = reshapeClimateData[i,]
v_linha = as.vector(linha)
v_linha[,3:14] = sprintf("%.2f", round(v_linha[,3:14], 2))
v_linha = as.vector(as.character(v_linha))
for (j in 3:14) {
v_linha[j] = ifelse(nchar(v_linha[j]) < 5,
paste0(" ", v_linha[j]),
v_linha[j] )
}
v_linha = paste(v_linha, collapse = " ")
rowsClimateData[[i]] = v_linha
}
dfClimateData = do.call("rbind", rowsClimateData)
write.table(dfClimateData,
file = paste0("lu_site_", cellNumber, ".wth"),
row.names = FALSE,
col.names = FALSE,
sep = " ",
quote = FALSE)
###
###
#'criar arquivo sch e 100
meanCD <- doBy::summaryBy(prec + tmin + tmax ~ mes, data = climateData)
meanCD[,2:4] <- round(meanCD[,2:4] + 0.00001, 5)
names(meanCD) <- c('mes', 'prec', 'tmin', 'tmax')
###
###
#' prepare file land use site.100
lu_site_100 <- readLines('template/Lu_site.100')
lu_site_100[1:15]
#' ppt
lu_site_100[3] <- gsub('0.000000', meanCD[1, 'prec'], lu_site_100[3])
lu_site_100[4] <- gsub('0.000000', meanCD[2, 'prec'], lu_site_100[4])
lu_site_100[5] <- gsub('0.000000', meanCD[3, 'prec'], lu_site_100[5])
lu_site_100[6] <- gsub('0.000000', meanCD[4, 'prec'], lu_site_100[6])
lu_site_100[7] <- gsub('0.000000', meanCD[5, 'prec'], lu_site_100[7])
lu_site_100[8] <- gsub('0.000000', meanCD[6, 'prec'], lu_site_100[8])
lu_site_100[9] <- gsub('0.000000', meanCD[7, 'prec'], lu_site_100[9])
lu_site_100[10] <- gsub('0.000000', meanCD[8, 'prec'], lu_site_100[10])
lu_site_100[11] <- gsub('0.000000', meanCD[9, 'prec'], lu_site_100[11])
lu_site_100[12] <- gsub('0.000000', meanCD[10, 'prec'], lu_site_100[12])
lu_site_100[13] <- gsub('0.000000', meanCD[11, 'prec'], lu_site_100[13])
lu_site_100[14] <- gsub('0.000000', meanCD[12, 'prec'], lu_site_100[14])
#' tmmn
lu_site_100[39] <- gsub('0.000000', meanCD[1, 'tmin'], lu_site_100[39])
lu_site_100[40] <- gsub('0.000000', meanCD[2, 'tmin'], lu_site_100[40])
lu_site_100[41] <- gsub('0.000000', meanCD[3, 'tmin'], lu_site_100[41])
lu_site_100[42] <- gsub('0.000000', meanCD[4, 'tmin'], lu_site_100[42])
lu_site_100[43] <- gsub('0.000000', meanCD[5, 'tmin'], lu_site_100[43])
lu_site_100[44] <- gsub('0.000000', meanCD[6, 'tmin'], lu_site_100[44])
lu_site_100[45] <- gsub('0.000000', meanCD[7, 'tmin'], lu_site_100[45])
lu_site_100[46] <- gsub('0.000000', meanCD[8, 'tmin'], lu_site_100[46])
lu_site_100[47] <- gsub('0.000000', meanCD[9, 'tmin'], lu_site_100[47])
lu_site_100[48] <- gsub('0.000000', meanCD[10, 'tmin'], lu_site_100[48])
lu_site_100[49] <- gsub('0.000000', meanCD[11, 'tmin'], lu_site_100[49])
lu_site_100[50] <- gsub('0.000000', meanCD[12, 'tmin'], lu_site_100[50])
#' tmmx
lu_site_100[51] <- gsub('0.000000', meanCD[1, 'tmax'], lu_site_100[51])
lu_site_100[52] <- gsub('0.000000', meanCD[2, 'tmax'], lu_site_100[52])
lu_site_100[53] <- gsub('0.000000', meanCD[3, 'tmax'], lu_site_100[53])
lu_site_100[54] <- gsub('0.000000', meanCD[4, 'tmax'], lu_site_100[54])
lu_site_100[55] <- gsub('0.000000', meanCD[5, 'tmax'], lu_site_100[55])
lu_site_100[56] <- gsub('0.000000', meanCD[6, 'tmax'], lu_site_100[56])
lu_site_100[57] <- gsub('0.000000', meanCD[7, 'tmax'], lu_site_100[57])
lu_site_100[58] <- gsub('0.000000', meanCD[8, 'tmax'], lu_site_100[58])
lu_site_100[59] <- gsub('0.000000', meanCD[9, 'tmax'], lu_site_100[59])
lu_site_100[60] <- gsub('0.000000', meanCD[10, 'tmax'], lu_site_100[60])
lu_site_100[61] <- gsub('0.000000', meanCD[11, 'tmax'], lu_site_100[61])
lu_site_100[62] <- gsub('0.000000', meanCD[12, 'tmax'], lu_site_100[62])
#' soil
soilData <- pixel[3:7]
soilData[1:3] <- round((soilData[1:3]/100) + 0.00001, 5)
soilData[4] <- round((soilData[4]/1000) + 0.00001, 5)
soilData[5] <- round((soilData[5]/10) + 0.00001, 5)
lu_site_100[68] <- gsub('0.00000', soilData[1], lu_site_100[68])
lu_site_100[69] <- gsub('0.00000', soilData[2], lu_site_100[69])
lu_site_100[70] <- gsub('0.00000', soilData[3], lu_site_100[70])
lu_site_100[72] <- gsub('1.00000', soilData[4], lu_site_100[72])
lu_site_100[101] <- gsub('0.00000', soilData[5], lu_site_100[101])
lu_site_100_name <- paste0("lu_site_", cellNumber, ".100")
write.table(lu_site_100,
file = lu_site_100_name,
quote = FALSE,
row.names = FALSE,
col.names = FALSE)
#'prepare file land use site.sch
lu_site_sch <- readLines('template/Lu_site.sch')
lu_site_sch_name <- paste0("lu_site_", cellNumber, ".sch")
lu_site_sch[3] <- gsub('lu_site.100', lu_site_100_name, lu_site_sch[3])
# ano_conv <- 1984 + pixel[2] # ano de convers?o para pastagem
ano_conv <- pixel[2] # ano de convers?o para pastagem
lu_site_sch[1] <- gsub('1982', ano_conv - 3, lu_site_sch[1])
lu_site_sch[19] <- gsub('1983', ano_conv - 2, lu_site_sch[19])
lu_site_sch[21] <- gsub('1982', ano_conv - 3, lu_site_sch[21])
lu_site_sch[49] <- gsub('1984', ano_conv - 1, lu_site_sch[49])
lu_site_sch[51] <- gsub('1984', ano_conv - 1, lu_site_sch[51])
lu_site_sch[65] <- gsub('1985', ano_conv, lu_site_sch[65])
lu_site_sch[69] <- gsub('lu_site.wth',
paste0("lu_site_", cellNumber, ".wth"),
lu_site_sch[69])
write.table(lu_site_sch,
file = lu_site_sch_name,
quote = FALSE,
row.names = FALSE,
col.names = FALSE)
###
###
#'prepare file equilibrio site.100 e sch
eq_site_100 <- lu_site_100
eq_site_100_name <- paste0("eq_site_", cellNumber, ".100")
write.table(eq_site_100,
file = eq_site_100_name,
quote = FALSE,
row.names = FALSE,
col.names = FALSE)
#'prepare file equilibrio site.100 e sch
eq_site_sch <- readLines('template/Eq_site.sch')
eq_site_sch[3] <- gsub('eq_site.100', eq_site_100_name, eq_site_sch[3])
eq_site_sch_name <- paste0("eq_site_", cellNumber, ".sch")
write.table(eq_site_sch,
file = eq_site_sch_name,
quote = FALSE,
row.names = FALSE,
col.names = FALSE)
####
####
##'rodar o modelo century
equilibrio <- paste0('century -s eq_site_',
cellNumber,
' -n eq_site_',
cellNumber)
system(equilibrio)
land_use <- paste0('century -s lu_site_',
cellNumber,
' -n result/lu_site_',
cellNumber,
' -e eq_site_',
cellNumber)
system(land_use)
lis_file <- paste0('list100 result/lu_site_',
cellNumber,
' result/lu_site_',
cellNumber, ' output.txt')
system(lis_file)
###
###
#' vari?veis a ser utilizadas
#' checar se o arquivo tem 240 linhas, caso n?o, acresntar NA no in?cio'
lis_lu <- read.table(paste0("result/lu_site_", cellNumber, ".lis"), h = T)
lis_lu <- lis_lu[lis_lu$time > 2000.01 & lis_lu$time < 2020.01, ]
if(nrow(lis_lu) < 240){
VecNA <- as.numeric(rep(NA, (240 - nrow(lis_lu))))
aglivc <- as.numeric(c(VecNA, lis_lu$aglivc))
bglivc <- as.numeric(c(VecNA, lis_lu$bglivc))
somsc <- as.numeric(c(VecNA, lis_lu$somsc))
stdedc <- as.numeric(c(VecNA, lis_lu$stdedc))
} else {
aglivc <- as.numeric(lis_lu$aglivc)
bglivc <- as.numeric(lis_lu$bglivc)
somsc <- as.numeric(lis_lu$somsc)
stdedc <- as.numeric(lis_lu$stdedc)
}
OUT <- as.numeric(c(aglivc, bglivc, somsc, stdedc))
###
###
#' remove files
Sys.sleep(1)
file.remove(paste0("eq_site_", cellNumber, ".100"),
paste0("eq_site_", cellNumber, ".sch"),
paste0("eq_site_", cellNumber, ".bin"),
paste0("lu_site_", cellNumber, ".sch"),
paste0("lu_site_", cellNumber, ".100"),
# paste0("result/lu_site_", cellNumber, ".bin"),
# paste0("result/lu_site_", cellNumber, ".lis"),
paste0("lu_site_", cellNumber, ".wth")
)
# print(Sys.time() - STi)
}
return(OUT)
}
#####################################################################
#####################################################################
procRasterBlocks <- function(inputDir, outputDir, fileToExtent, pattern, nColBlock = NULL, nRowBlock = NULL, ncores = NULL) {
STTot <- Sys.time()
DTym <- seq.Date(from = ymd('1980-01-01'), to = ymd('2019-12-01'), by = 'month') # col names
ncores <- ifelse(is.null(ncores), detectCores(), ncores)
print(ncores)
clusterPool <- makeCluster(ncores)
clusterEvalQ(clusterPool, {
require(doBy)
require(dplyr)
require(lubridate)
})
#preparing blocks
referenceRaster <- getReferenceRaster(inputDir, pattern)
rowMin <- rowFromY(referenceRaster, ymax(fileToExtent))
rowMax <- rowFromY(referenceRaster, ymin(fileToExtent))
colMin <- colFromX(referenceRaster, xmin(fileToExtent))
colMax <- colFromX(referenceRaster, xmax(fileToExtent))
nRow <- rowMax - rowMin
nCol <- colMax - colMin
colOffset <- colMin
rowOffset <- rowMin
nRowBlock <- ifelse(is.null(nRowBlock), nRow, nRowBlock)
nColBlock <- ifelse(is.null(nColBlock), nCol, nColBlock)
nBlock <- ifelse(is.null(nRowBlock),
ceiling(nCol / nColBlock),
ceiling(nRow / nRowBlock) )
print(paste0("Numero de blocos = ", nBlock))
iBlockSize <- c(nColBlock, nRowBlock)
blocksOffset <- getBlocksOffset(colOffset, rowOffset, nBlock, nColBlock = NULL, nRowBlock)
#process data by blocks
for (bloco in blocFirst:blocEnd){
print(paste0("executing block = ", bloco))
iBlockOffset <- as.numeric(blocksOffset[bloco, 2:3])
print(iBlockOffset)
STBloco <- Sys.time()
outputExtent <- getOutputExtent(referenceRaster, iBlockOffset, iBlockSize)
###
###
#'ler as cinco bases de dados (mapa de pastagem, solo, precipitacao, temp. maxima e temp. minima)
#'read data of the block
STRead <- Sys.time()
#'mapa de pastagem
blockData_pasture = readBlockImages(paste0(inputDir,"pasture_map"), outputExtent, pattern)
names(blockData_pasture) <- c('cellNumber', 'pastMask')
#'solos
blockData_soil = readBlockImages(paste0(inputDir,"soil_grid_br_1km"), outputExtent, pattern)
names(blockData_soil) <- c('sand', 'silte', 'clay', 'bkrd', 'ph')
#'precipitacao
blockData_prec = readBlockImages(paste0(inputDir,"pr_1km"), outputExtent, pattern)
names(blockData_prec) <- DTym
#'temperatura minima
blockData_tmmn = readBlockImages(paste0(inputDir,"tmmn_1km"), outputExtent, pattern)
names(blockData_tmmn) <- DTym
#'temperatura maxima
blockData_tmmx = readBlockImages(paste0(inputDir,"tmmx_1km"), outputExtent, pattern)
names(blockData_tmmx) <- DTym
#'juntar blocos de ados
blockData <- cbind(blockData_pasture, blockData_soil, blockData_prec, blockData_tmmn, blockData_tmmx)
#'gravar o bloco de dados
#write.csv(blockData, file = paste0(inputDir, '/blockdata_', bloco,'.csv'), row.names = F)
totSTRead <- paste0("time to read block ", bloco, " = ", Sys.time() - STRead)
print(totSTRead)
#run function
DTym <- seq.Date(from = ymd('2000-01-01'),
to = ymd('2019-12-01'),
by = 'month')
colNames <- c(paste0("aglivc_", DTym),
paste0("bglivs_", DTym),
paste0("somsc_", DTym),
paste0("stdeadc_", DTym)
)
STRun <- Sys.time()
centuryCerradoResult <- as.data.frame(t(parApply(cl = clusterPool, blockData, 1, runCenturyCerrado)))
names(centuryCerradoResult) <- colNames
totSTRun <- paste0("time to run function for block i = ", Sys.time() - STRun)
print(totSTRun)
#Write results
for (i in 1:ncol(centuryCerradoResult)) {
outputfile <- paste0(outputDir, "/", names(centuryCerradoResult)[i], '_block_', bloco, '_')
outputData <- centuryCerradoResult[, i]
saveImage(outputData, outputfile, iBlockOffset, outputExtent, referenceRaster)
}
totSTBloco <- paste0("time to execute block = ", bloco, " = ", Sys.time() - STBloco)
print(totSTBloco)
rm(centuryCerradoResult, blockData)
gc(reset = TRUE)
}
print(paste0("time to execute all blocks = ", Sys.time() - STTot))
stopCluster(clusterPool)
}
#####################################################################
#####################################################################
#'pacotes necessários
suppressWarnings(suppressMessages(library(gtools)))
suppressWarnings(suppressMessages(library(raster)))
suppressWarnings(suppressMessages(library(parallel)))
suppressWarnings(suppressMessages(library(lubridate)))
suppressWarnings(suppressMessages(library(stats)))
suppressWarnings(suppressMessages(library(doBy)))
#' definir pasta century como diretório
setwd("H:\\run_century_goiasvelho/century")
inputDir <- "H:\\run_century_goiasvelho/dados/"
outputDir <- "H:\\run_century_goiasvelho/mu_goias_century_2000_2020_1km"
fileToExtent <- raster("H:\\run_century_goiasvelho/dados/2_mu_goias_first_year_pasture_col5_2017_lapig_1km_mask17.tif")
pattern <- "*.tif"
nColBlock <- NULL
nRowBlock <- 5
ncores <- 5
blocFirst <- as.numeric(1)
blocEnd <- as.numeric(14)
procRasterBlocks(inputDir, outputDir, fileToExtent, pattern, nColBlock = NULL, nRowBlock, ncores = ncores)
#####################################################################
#####################################################################