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Commit b1004931 authored by Jentsch, Helge's avatar Jentsch, Helge
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230814: Update Chelsa Timeseries Download. Note: Stacking is not available for... 

230814: Update Chelsa Timeseries Download. Note: Stacking is not available for Chelsa.timeseries.download()-function at the moment.
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DESCRIPTION
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− 2
View file @ b1004931
Package: ClimDatDownloadR
Type: Package
Title: Downloads Climate Data from Chelsa and WorldClim
Version: 0.1.7-3
Version: 0.1.7-4
Authors@R: c(person("Helge", "Jentsch",
email = "helge.marc.ole.jentsch@uni-hamburg.de",
role = c("aut", "cre"),
......@@ -45,7 +45,7 @@ Suggests: knitr, testthat, usethis, rmarkdown
VignetteBuilder: knitr
SystemRequirements: Tested with at least 4 GB RAM.
NeedsCompilation: no
Packaged: 2023-07-18 09:50:31 UTC; helge
Packaged: 2023-08-14 18:54:05 UTC; helge
Author: Helge Jentsch [aut, cre],
Maria Bobrowski [aut],
Johannes Weidinger [aut],
......
R/Chelsa_Download_functions.R
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......@@ -1138,7 +1138,6 @@ Chelsa.lgm.download <- function(save.location = "./",
#'@param clip.extent numeric (vector). Input vector with four numeric values. This is following the input order c("xleft", "xright", "ybottom", "ytop").\cr Default: \code{c(-180, 180, -90, 90)}
#'@param buffer numeric. Input of decimal degrees of buffer around the shapefile and/or extent. \cr Default: \code{0}
#'@param convert.files.to.asc logical. Input whether files should be converted into the ASCII format.\cr If \code{TRUE}: a new subdirectory is created and the rawdata is saved there. \cr If \code{clipping} is \code{TRUE}: the clipped raster files are also saved as ASCII grids. \cr Default: \code{FALSE}
#'@param stacking.data logical. Input whether the downloaded data should be stacked as a netCDF-rasterstack. \cr Default: \code{FALSE}
#'@param combine.raw.zip logical. Should the downloaded raw-data be "zipped". \cr Default: \code{FALSE}
#'@param delete.raw.data logical. Should the downloaded raw-data be deleted. If \code{combine.raw.zip} is \code{TRUE}: raw-data is still available in the zipped file. \cr Default: \code{FALSE}
#'@param save.bib.file logical. Whether a BibTex-citation file of the dataset should be provided in the Working directory. \cr Default: \code{TRUE}
......@@ -1166,7 +1165,7 @@ Chelsa.lgm.download <- function(save.location = "./",
#'@importFrom utils unzip download.file setTxtProgressBar txtProgressBar
#'
#'
#'@export
#'
Chelsa.timeseries.download <- function(save.location = "./",
parameter = c("prec", "tmax", "tmin"),
start.year.var = 1979,
......
R/Chelsa_new_download_functions.R
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......@@ -875,3 +875,649 @@ Chelsa.CMIP_6.download <- function(save.location = "./",
# delete all temporary files
unlink(list.files(tempdir(), recursive = T, full.names =T))
}
#'@title CHELSA Timeseries Download
#'@author Helge Jentsch
#'@description This function supports a download of the CHELSA Timeseries dataset (Jan. 1979 - Dec. 2013). This includes precipitation sums (mm) and temperature (average, maximum, minimum; °C) parameters. For further information, please regard \url{http://chelsa-climate.org/timeseries/}.\cr To allow pre-processing, clipping and buffering, conversion to ASCII-grids and stacking options are included.\cr Optional an output of a .bib-file of the cited literature can be retrieved.\cr For user convenience, saving directories will be created automatically. Also options to "zip" and/or delete the RAW-files are included.
#'
#'@note Please note that the downloaded data for temperature are processed to °C with one significant decimal without offset and factor. Processing and conversion to other file-formats on a global dataset may take some time.
#'
#'@param save.location string. Input where the datasets should be saved. \cr Default: Working Directory.
#'@param parameter string (vector). Input of parameters which should be downloaded. \cr Default: \code{c("prec", "tmax", "tmin")}
#'@param start.year.var integer. Input year the download timeseries starts. \cr Default: 1979 (minimum)
#'@param start.month.var integer. Input month the download timeseries starts. \cr Default: 1 (minimum)
#'@param end.year.var integer. Input year the download timeseries ends. \cr Default: 2013 (maximum)
#'@param end.month.var integer. Input month the download timeseries ends. \cr Default: 12 (maximum)
#'@param include.month.var integer (vector). Input which monthly data should be downloaded. \cr Default: \code{c(1:12)}
#'@param version.var string (vector). Input which version of the dataset should be downloaded. Multiple selection is _not_ possible. Select between version _1.2_ and _2.1_.\cr Default: \code{c("1.2")}
#'@param clipping logical. Input whether the downloaded data should be clipped.\cr If \code{FALSE}: \code{clip.shapefile}, \code{buffer}, \code{clip.extent} will be ignored. \cr Default: \code{FALSE}
#'@param clip.shapefile string. Input which shapefile should be used for clipping. \cr Default: \code{NULL}
#'@param clip.extent numeric (vector). Input vector with four numeric values. This is following the input order c("xleft", "xright", "ybottom", "ytop").\cr Default: \code{c(-180, 180, -90, 90)}
#'@param buffer numeric. Input of decimal degrees of buffer around the shapefile and/or extent. \cr Default: \code{0}
#'@param convert.files.to.asc logical. Input whether files should be converted into the ASCII format.\cr If \code{TRUE}: a new subdirectory is created and the rawdata is saved there. \cr If \code{clipping} is \code{TRUE}: the clipped raster files are also saved as ASCII grids. \cr Default: \code{FALSE}
#'@param combine.raw.zip logical. Should the downloaded raw-data be "zipped". \cr Default: \code{FALSE}
#'@param delete.raw.data logical. Should the downloaded raw-data be deleted. If \code{combine.raw.zip} is \code{TRUE}: raw-data is still available in the zipped file. \cr Default: \code{FALSE}
#'@param save.bib.file logical. Whether a BibTex-citation file of the dataset should be provided in the Working directory. \cr Default: \code{TRUE}
#'
#'@return Custom dataset of CHELSA Timeseries for a chosen timeseries.
#'
#'@references D. N. Karger, O. Conrad, J. B{\"o}hner , et al. "Climatologies at high resolution for the earth's land surface areas". In: _Scientific Data_ 4.1 (Sep. 2017). DOI: 10.1038/sdata.2017.122. <URL: https://doi.org/10.1038/sdata.2017.122>.
#'@references D. N. Karger, O. Conrad, J. B{\"o}hner , et al. _Data from: Climatologies at high resolution for the earth's land surface areas_. En. 2018. DOI: 10.5061/DRYAD.KD1D4. <URL: http://datadryad.org/stash/dataset/doi:10.5061/dryad.kd1d4>.
#'
#'@examples
#' \dontrun{
#' Chelsa.timeseries.download(parameter = "prec",
#' start.year.var = 2000,
#' start.month.var = 1,
#' end.year.var = 2002,
#' end.month.var = 12,
#' version.var = "1.2",
#' include.month.var = c(1,12))
#' }
#'
#'@import stringr
#'@import RCurl
#'@import ncdf4
#'@import terra
#'@import httr
#'@importFrom utils unzip download.file setTxtProgressBar txtProgressBar
#'
#'
#'@export
Chelsa.timeseries.download <- function(save.location = "./",
parameter = c("prec", "temp", "tmax", "tmin"),
start.year.var = 1979,
start.month.var = 1,
end.year.var = 2013,
end.month.var = 12,
include.month.var = c(1:12),
version.var = c("1.2"),
clipping = FALSE,
clip.shapefile = NULL,
buffer = 0,
clip.extent = c(-180, 180, -90, 90),
convert.files.to.asc = FALSE,
combine.raw.zip = FALSE,
delete.raw.data = FALSE,
save.bib.file = TRUE){
gc()
call.time <- stringr::str_replace_all(stringr::str_replace_all(paste0(Sys.time()),
pattern = ":",
replacement = "-"),
pattern = " ",
replacement = "_")
# initial check -----------------------------------------------------------
# normalize Path for easier application later
save.location <- normalizePath(save.location,
winslash = "/")
if(length(version.var) != 1) stop("Version variable 'version.var' should only have either '1.2' or '2.1'.")
if(!is.null(version.var) & version.var == "1.2"){
# Check which parameters are put in and if the connected
# month/bio-variables are correctly input
if(is.element("prec", parameter)|
is.element("tmax", parameter)|
is.element("temp", parameter)|
is.element("tmin", parameter)){
include.month.var <- c(include.month.var)
if(!is.numeric(include.month.var)) stop()
include.month.var <- str_pad(include.month.var,
2,
'left',
pad = "0")
# print(include.month.var)
}
if(start.year.var < 1979 | end.year.var > 2013 | end.year.var < 1979 | start.year.var > 2013) {
stop("Timeseries only available from 01.1979 to 12.2013. \n Please check input!")
}
# check for consistent timeseries
if(end.year.var < start.year.var) stop("Endyear is before the startyear. Please correct the input!")
if(start.year.var == end.year.var){
if(start.month.var > end.month.var) stop("End is before the start. Please correct the input!")
}
ts_string <- seq.Date(as.Date(paste(start.year.var,
start.month.var, "01", sep = "-")),
as.Date(paste(end.year.var,
end.month.var, "01", sep = "-")),
by = "month")
ts_string <- format.Date(ts_string, format = "%Y_%m")
# ts_string <- str_sub(ts_string, 1, end = str_length(ts_string)-3)
# ts_string <- str_replace_all(ts_string, pattern = "-", replacement = "_")
if(length(include.month.var)!=12){
ts.string.temp <- c()
for (incl.month in include.month.var) {
# print(incl.month)
ts.string.temp <- c(ts.string.temp,
ts_string[grep(pattern = paste0("_", incl.month)
, ts_string)]
)
}
ts_string <- ts.string.temp
}
}
if(!is.null(version.var) & version.var == "2.1"){
# Check which parameters are put in and if the connected
# month/bio-variables are correctly input
if(is.element("prec", parameter)|
is.element("tmax", parameter)|
is.element("temp", parameter)|
is.element("tmin", parameter)){
include.month.var <- c(include.month.var)
if(!is.numeric(include.month.var)) stop()
include.month.var <- str_pad(include.month.var,
2,
'left',
pad = "0")
# print(include.month.var)
}
if(start.year.var < 1979 | end.year.var > 2019 | end.year.var < 1979 | start.year.var > 2019) {
stop("Timeseries only available from 02.1979 to 12.2019. \n Please check input!")
}
# check for consistent timeseries
if(end.year.var < start.year.var) stop("Endyear is before the startyear. Please correct the input!")
if(start.year.var == end.year.var){
if(start.month.var > end.month.var) stop("End is before the start. Please correct the input!")
}
ts_string <- seq.Date(as.Date(paste(start.year.var,
start.month.var, "01", sep = "-")),
as.Date(paste(end.year.var,
end.month.var, "01", sep = "-")),
by = "month")
ts_string <- format.Date(ts_string, format = "%m_%Y")
# ts_string <- str_sub(ts_string, 1, end = str_length(ts_string)-3)
# ts_string <- str_replace_all(ts_string, pattern = "-", replacement = "_")
if(length(include.month.var)!=12){
ts.string.temp <- c()
for (incl.month in include.month.var) {
# print(incl.month)
ts.string.temp <- c(ts.string.temp,
ts_string[grep(pattern = paste0("_", incl.month)
, ts_string)]
)
}
ts_string <- ts.string.temp
}
}
# Preparations ------------------------------------------------------------
# parameter
parameter <- base::sort(parameter)
DLTparameter <- c(base::rep(parameter[parameter!="bio"],
base::length(ts_string)))
DLTparameter <- base::sort(DLTparameter)
# variables
DLTvariable <- NULL
for(parm in parameter){
DLTvariable <- c(DLTvariable,
switch(parm,
"prec" = ts_string,
"tmax" = ts_string,
"temp" = ts_string,
"tmin" = ts_string,
stop()
)
)
}
# Combine search into large dataframe -------------------------------------
dataDF <- data.frame("parameter" = base::sort(DLTparameter),
"variable" = DLTvariable
)
if(length(version.var)==1){
dataDF$version <- base::rep(version.var, length(DLTvariable))
}
# v1.2
if(is.element("1.2", dataDF$version)){
# dataDF$parmLong[dataDF$version == "1.2"] <- base::paste0(dataDF$parameter[dataDF$version == "1.2"],"10")
dataDF$parmLong[dataDF$version == "1.2"] <-
base::paste0(dataDF$parameter[dataDF$version == "1.2"])
dataDF$parmLong[dataDF$version == "1.2" & dataDF$parameter == "prec"] <-
base::paste0("prec")
dataDF$parmLong[dataDF$version == "1.2" & dataDF$parameter == "tmean"] <-
base::paste0("tmean")
dataDF$parmLong[dataDF$version == "1.2" & dataDF$parameter == "tmax"] <-
base::paste0("tmax")
dataDF$parmLong[dataDF$version == "1.2" & dataDF$parameter == "tmin"] <-
base::paste0("tmin")
dataDF$parameter[dataDF$version == "1.2" & dataDF$parameter == "temp"] <- base::paste0("tmean")
# dataDF$years[dataDF$version =="1.2"] <- "_1979-2013"
# dataDF$years[dataDF$version == "1.2" &
# (dataDF$parameter == "prec" | dataDF$parameter == "bio")] <- base::paste0("")
# Adding the URL stings
# https://os.zhdk.cloud.switch.ch/envicloud/chelsa/chelsa_V1/timeseries/tmax/CHELSA_tmax_1979_01_V1.2.1.tif
dataDF$URL[dataDF$version == "1.2" & dataDF$parameter != "bio"] <-
# https://os.zhdk.cloud.switch.ch/envicloud/chelsa/chelsa_V1/timeseries/
paste0("https://os.zhdk.cloud.switch.ch/envicloud/chelsa/chelsa_V1/timeseries/",
# tmax
dataDF$parameter[dataDF$version == "1.2" & dataDF$parameter != "bio"],
# /CHELSA_
"/CHELSA_",
# tmax
dataDF$parameter[dataDF$version == "1.2" & dataDF$parameter != "bio"],
# _
"_",
# 1979_01
dataDF$variable[dataDF$version == "1.2" & dataDF$parameter != "bio"],
#_V1.2.1.tif
"_V1.2.1.tif")
}
# v2.1
if(is.element("2.1", dataDF$version)){
dataDF$parmLong[dataDF$version == "2.1" &
dataDF$parameter == "prec"] <- base::paste0("pr")
dataDF$parmLong[dataDF$version == "2.1" &
dataDF$parameter == "temp"] <- base::paste0("tas")
dataDF$parmLong[dataDF$version == "2.1" &
dataDF$parameter == "tmin"] <- base::paste0("tasmin")
dataDF$parmLong[dataDF$version == "2.1" &
dataDF$parameter == "tmax"] <- base::paste0("tasmax")
# dataDF$years[dataDF$version =="2.1"] <- "_1981-2010"
# https://os.zhdk.cloud.switch.ch/envicloud/chelsa/chelsa_V2/GLOBAL/monthly/tas/CHELSA_tas_11_2007_V.2.1.tif
dataDF$URL[dataDF$version == "2.1" & dataDF$parameter != "bio"] <-
paste0("https://os.zhdk.cloud.switch.ch/envicloud/chelsa/chelsa_V2/GLOBAL/monthly/",
dataDF$parmLong[dataDF$version == "2.1" & dataDF$parameter != "bio"],
"/CHELSA_",
dataDF$parmLong[dataDF$version == "2.1" & dataDF$parameter != "bio"],
"_",
dataDF$variable[dataDF$version == "2.1" & dataDF$parameter != "bio"],
"_V.2.1.tif")
}
write.table(x = dataDF,
file = normalizePath(paste0(save.location, "/", call.time, "_downloadDataframe.csv"), winslash = "/"),
sep = ";",
dec = ".",
row.names = F,
append = F)
# Check if URL exists!
for(urlexists in dataDF$URL){ # loop through all URLs
if(!RCurl::url.exists(urlexists)){ # if not, print warning!
cat(paste(urlexists,
" does not exist, please check the website of Chelsa. \n")
)
if(urlexists == dataDF$URL[1]){
cat(paste("\t If any of these download warnings was prompted incorrectly, we apprecheate a feedback on this at helge.marc.ole.jentsch@uni-hamburg.de\n")
)}
next
}
}
# print the amount of data to be downloaded and processed.
print(paste0(getDownloadSize(dataDF$URL), " MB will be downloaded."))
# Progressbar setup
PGBsum <- nrow(dataDF) + length(unique(dataDF$parameter)) + 1
PGB <- utils::txtProgressBar(min = 0, max = PGBsum, style = 3)
PGBstate <- 0
# Preparation of save location stack
locationSack <- NULL
# loop through every instance and save the location.
# HINT FOR RUNTIME IMPROVEMENT!!!
for(parm in dataDF$parameter){
if (!dir.exists(paste0(save.location, "/", parm))){
dir.create(paste0(save.location, "/", parm))
}
if("1.2" %in% dataDF$version){
if (!dir.exists(paste0(save.location, "/", parm, "/ChelsaV1.2Timeseries"))){
dir.create(paste0(save.location, "/", parm, "/ChelsaV1.2Timeseries"))
}
locationSack <- c(locationSack, paste0(save.location, "/", parm, "/ChelsaV1.2Timeseries/"))
}
if("2.1" %in% dataDF$version){
if (!dir.exists(paste0(save.location, "/", parm, "/ChelsaV2.1Timeseries"))){
dir.create(paste0(save.location, "/", parm, "/ChelsaV2.1Timeseries"))
}
locationSack <- c(locationSack, paste0(save.location, "/", parm, "/ChelsaV2.1Timeseries/"))
}
}
print(locationSack)
dataDF$filepath[dataDF$version == "1.2"] <-
paste0(save.location,"/",
dataDF$parameter, "/ChelsaV1.2Timeseries",
"/CHELSA_", dataDF$parmLong , "_", dataDF$variable, dataDF$years,
"_V1.2.tif")
dataDF$filepath[dataDF$version == "2.1"] <-
paste0(save.location,"/",
dataDF$parameter, "/ChelsaV2.1Timeseries",
"/CHELSA_", dataDF$parmLong , "_", dataDF$variable, dataDF$years,
"_V2.1.tif")
# check for file existance - if not already present - download file
for(fileexists in dataDF$filepath){
if(!file.exists(fileexists)){
unlink(list.files(tempdir(), recursive = TRUE, full.names = TRUE))
download.file(url = dataDF$URL[dataDF$filepath == fileexists],
destfile = fileexists,
# overwrite is TRUE otherwise a error is caused
overwrite = TRUE,
# From the description file:
# The choice of binary transfer (mode = "wb" or "ab")
# is important on Windows, since unlike Unix-alikes
# it does distinguish between text and binary files and
# for text transfers changes
# \n line endings to \r\n (aka ‘CRLF’).
mode = 'wb',
# to show progression bar
quiet = TRUE,
cacheOK = FALSE)
}
setTxtProgressBar(PGB, PGBstate+1)
PGBstate <- PGBstate+1
}
if(is.element("1.2", dataDF$version)){
# https://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification.pdf
rescaleDF_V12 <- dataDF[dataDF$version == "1.2" &
dataDF$parameter != "prec"
,]
if(nrow(rescaleDF_V12)>0){
for(rescale_i in 1:nrow(rescaleDF_V12)){
gc()
tempRast <- terra::rast(rescaleDF_V12$filepath[rescale_i])
tempRast <- process.raster.int.doub(tempRast)
tempFilePath <- tempfile(tmpdir = tempdir(), fileext = ".tif")
terra::writeRaster(x = tempRast,
filename = tempFilePath
)
terra::writeRaster(x = terra::rast(x = tempFilePath),
filename = rescaleDF_V12$filepath[rescale_i],
overwrite = TRUE)
rm(tempFilePath)
gc()
}
rm(rescale_i)
unlink(list.files(tempdir(), recursive = T, full.names =T))
}
}
if(is.element("2.1", dataDF$version)){
# https://chelsa-climate.org/wp-admin/download-page/CHELSA_tech_specification_V2.pdf
rescaleDF_V21 <- dataDF[dataDF$version == "2.1",]
if(nrow(rescaleDF_V21)>0){
for(rescale_i in 1:nrow(rescaleDF_V21)){
gc()
tempRast <- terra::rast(rescaleDF_V21$filepath[rescale_i])
tempRast <- process.raster.int.doub(tempRast)
tempFilePath <- tempfile(tmpdir = tempdir(), fileext = ".tif")
terra::writeRaster(x = tempRast,
filename = tempFilePath
)
terra::writeRaster(x = terra::rast(x = tempFilePath),
filename = rescaleDF_V21$filepath[rescale_i],
overwrite = TRUE)
rm(tempFilePath)
gc()
}
rm(rescale_i)
unlink(list.files(tempdir(), recursive = T, full.names =T))
}
offsetDF_V21 <- dataDF[dataDF$version == "2.1" &
dataDF$parameter != "prec"]
if(nrow(offsetDF_V21)>0){
for(rescale_i in 1:nrow(offsetDF_V21)){
gc()
tempRast <- terra::rast(offsetDF_V21$filepath[rescale_i])
tempRast <- process.raster.offset(tempRast)
tempFilePath <- tempfile(tmpdir = tempdir(), fileext = ".tif")
terra::writeRaster(x = tempRast,
filename = tempFilePath
)
terra::writeRaster(x = terra::rast(x = tempFilePath),
filename = offsetDF_V21$filepath[rescale_i],
overwrite = TRUE)
rm(tempFilePath)
gc()
}
rm(rescale_i)
unlink(list.files(tempdir(), recursive = T, full.names =T))
}
}
locationSack <- unique(locationSack)
for (temp.temp.save.location in locationSack) {
run <- grep(temp.temp.save.location, locationSack)
for(i in run){
# print(ls())
# variable.numbers <- dataDF$variable[dataDF$parameter == parameter[i]]
# stop()
# if clipping is TRUE ...
if(clipping == TRUE){
# the function "clipping.tif" (found in the auxiliary.R-File)
# is executed. The clip.save.location is the same location as the
# "current" save location
clipping.tif(clip.save.location = temp.temp.save.location,
# the clip-shapefile is passed
# default "NULL" does not produce error
clip.shapefile = clip.shapefile,
# Clip.extent is passed
# default "c(-180, 180, -90, 90)" does not produce errors
# simply clips the whole world.
clip.extent = clip.extent,
# buffer is passed
# default: 0. Unit is arc-degrees
buffer = buffer,
# conversion to ASCII format here integrated into the
# clipping function. Since it can be assumed that
# they should be converted lateron anyway.
convert.files.to.asc = convert.files.to.asc,
time.stamp.var = call.time)
}
# if converting.files.to.asc is TRUE ...
if(convert.files.to.asc == TRUE){
# the function "convert.to.asc" (found in the auxiliary.R-File)
# is executed. The save.location is the same location as the
# "current" save location. Also another new subdirectory will
# be created with the name "ASCII" .
convert.to.asc(save.location = temp.temp.save.location,
time.stamp.var = call.time)
}
# if stacking.data is TRUE ...
# if(stacking.data == TRUE){
# # the function "stacking.downloaded.data"
# # (found in the auxiliary.R-File) is executed.
# # The save.location is the same location as the
# # "current" save location.
# if(clipping==TRUE){
# stacking.downloaded.data(stack.save.location = temp.temp.save.location,
# parameter.var = parameter[i],
# variable.numbers = variable.numbers,
# stack.clipped = TRUE,
# time.stamp.var = call.time)
# }else{
# stacking.downloaded.data(stack.save.location = temp.temp.save.location,
# parameter.var = parameter[i],
# variable.numbers = variable.numbers,
# stack.clipped = FALSE,
# time.stamp.var = call.time)
# }
# }
# if combine.raw.zip is TRUE ...
if(combine.raw.zip == TRUE){
# the function "combine.raw.in.zip"
# (found in the auxiliary.R-File) is executed.
# The save.location is the same location as the
# "current" save location. The name of the zip-file is also
# passed with the current parameter in it.
combine.raw.in.zip(save.location = temp.temp.save.location,
zip.name = paste0("CHELSAClim_", parameter[i], ""),
time.stamp.var = call.time)
}
# if delete.raw.data is TRUE ...
if(delete.raw.data == TRUE){
# All .tif raster files in the current 2nd order subdirectory are
# unlinked (deleted).
unlink(list.files(temp.temp.save.location,
pattern = ".tif",
include.dirs = FALSE,
full.names = T),
force = TRUE)
}
}
# delete all temporary files
unlink(list.files(tempdir(), recursive = T, full.names =T))
setTxtProgressBar(PGB, PGBstate+1)
PGBstate <- PGBstate+1
}
if(save.bib.file == TRUE) {
save.citation(save.location = save.location, dataSetName = "CHELSA")
}
setTxtProgressBar(PGB, PGBstate+1)
close(PGB)
# delete all temporary files
unlink(list.files(tempdir(), recursive = T, full.names =T))
}
# stop()
# # Parameter and directories -----------------------------------------------
# # work through paramerters
# for(i in parameter){
# # clear up the temporary directory
# unlink(list.files(tempdir(), recursive = T, full.names=T))
#
# # create intermediate strings for later use
# interm <- switch(i,
# "prec" = "prec/",
# "temp" = "tmean/",
# "tmax" = "tmax/",
# "tmin" = "tmin/",
# # "bio" = "bio/",
# stop())
#
# variable.numbers <- switch(i,
# # "bio" = bio.var,
# "tmin" = include.month.var,
# "tmax" = include.month.var,
# "temp" = include.month.var,
# "prec" = include.month.var,
# stop())
#
# # create new directory
# if(!dir.exists(paste0(save.location, "/", i))){
# dir.create(paste0(save.location, "/", i), showWarnings = FALSE)
# }
# temp.save.location <- paste0(save.location, "/", i, "/")
# # to go analog to the functions before
# temp.temp.save.location <- paste0(temp.save.location,
# stringr::str_replace_all(interm,
# pattern = "/",
# "_"),
# "timeseries","/")
# # print(str_sub(temp.temp.save.location, end=-2))
# if(!dir.exists(temp.temp.save.location)){
# dir.create(str_sub(temp.temp.save.location, end=-2))
# }
#
# # temp.temp.save.location <- normalizePath(temp.temp.save.location,
# # winslash = "/")
# # if(i == "temp"){
# # i <- "tmean"
# # }
# # print(interm)
# # Download ----------------------------------------------------------------
# # if(i != "bio"){
# for (year_month in ts_string){
# URL.temp <-
# paste0("https://os.zhdk.cloud.switch.ch/envicloud/chelsa/chelsa_V1/timeseries/",
# interm, "CHELSA_", i,"_",year_month,
# "_V1.2.1.tif")
# # check if URL is available
# if(!http_error(URL.temp)){
# # clear up the temporary directory
# unlink(list.files(tempdir(), recursive = T, full.names=T))
#
# dest.file <- paste0(temp.temp.save.location, "CHELSA_", i,
# "_", year_month, "_V1.2.1.tif")
# if(!file.exists(dest.file)){
# # download file to save location
# download.file(url = URL.temp,
# destfile = dest.file,
# overwrite = TRUE,
# mode = 'wb',
# quiet = FALSE)
#
#
# if(i != "prec"){
# raster.temp <- terra::rast(dest.file)
#
# raster.temp <- terra::clamp(raster.temp, lower = -1000, useValues = FALSE)
# gc()
#
# raster.temp <- process.raster.int.doub(raster.temp)
# raster.temp <- process.raster.offset(raster.layer = raster.temp)
#
# terra::writeRaster(x = raster.temp,
# filename = dest.file,
# overwrite = TRUE)
# rm(raster.temp)
# gc()
# }
# }
# }else{
# # Warning message
# warning(paste0("File does not exist. Did not download: \n", URL.temp, "\n\n"),
# call. = TRUE, immediate. = FALSE)
# }
# if(year_month == ts_string[length(ts_string)] &
# length(list.files(temp.temp.save.location,
# pattern = ".tif",
# include.dirs = FALSE)) != 0){
# if(clipping == TRUE){
# clipping.tif(clip.save.location = temp.temp.save.location,
# clip.shapefile = clip.shapefile,
# clip.extent = clip.extent,
# convert.files.to.asc = convert.files.to.asc,
# buffer = buffer,
# time.stamp.var = call.time)
# }
# if(convert.files.to.asc == TRUE){
# convert.to.asc(temp.temp.save.location,
# time.stamp.var = call.time)
# }
# if(stacking.data == TRUE){
# if(clipping==TRUE){
# stacking.downloaded.data(stack.save.location = temp.temp.save.location,
# parameter.var = i,
# variable.numbers = variable.numbers,
# stack.clipped = TRUE,
# stack.time.series = TRUE,
# time.series = ts_string,
# time.stamp.var = call.time)
# }else{
# stacking.downloaded.data(stack.save.location = temp.temp.save.location,
# parameter.var = i,
# variable.numbers = variable.numbers,
# stack.time.series = TRUE,
# time.series = ts_string,
# time.stamp.var = call.time)
# }
# }
# if(combine.raw.zip == TRUE){
# combine.raw.in.zip(save.location = temp.temp.save.location,
# zip.name = paste0("CHELSATimeseries_", i, ""),
# time.stamp.var = call.time)
# }
# if(delete.raw.data == TRUE){
# unlink(list.files(temp.temp.save.location,
# pattern = ".tif",
# include.dirs = FALSE, full.names = T), force = TRUE)
# }
# }
# }
#
# # Clean up, if no data was downloaded. ------------------------------------
#
#
# if(length(list.files(temp.temp.save.location,
# include.dirs = TRUE)) == 0){
# unlink(str_sub(temp.temp.save.location, 1, end = str_length(temp.temp.save.location)-1),
# force = T, recursive = TRUE)
# }
# }
# # Saving BIB File
# if(save.bib.file == TRUE) save.citation(save.location = save.location, dataSetName = "CHELSA")
# }
R/auxiliary.R
+ 4
− 0
View file @ b1004931
......@@ -592,6 +592,10 @@ getDownloadSize <- function(URLVector){
filesizes <- sum(filesizes,fileISize)
# return(Downloadsize)
}
availDiscSpaceMB <- as.numeric(stringr::str_remove(base::system("wmic logicaldisk get freespace", inter=TRUE)[2], pattern = " \r"))/1024/1024
# if(availDiscSpaceMB < round(filesizes*0.000001, 2)){
# print(paste0(round(filesizes*0.000001, 2),"MB will be downloaded. These is only ", availDiscSpaceMB, "MB available. Please consider another download location."))
# }
return(round(filesizes*0.000001, 2))
# Download size in MB
......
inst/doc/ClimDatDownloadR.html
+ 12
− 12
View file @ b1004931
......@@ -350,18 +350,18 @@ provided by <a href="http://chelsa-climate.org/">Chelsa</a> and <a href="https:/
<p>To start, you’ll have to install the package and it’s dependencies
first, if not already done. Then you can activate the package with the
<code>library</code>-function.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="co"># install.packages(&quot;ClimDatDownloadR&quot;, dependencies = TRUE)</span></span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(ClimDatDownloadR)</span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Loading required package: terra</span></span>
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; terra 1.7.39</span></span>
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; The legacy packages maptools, rgdal, and rgeos, underpinning the sp package,</span></span>
<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; which was just loaded, will retire in October 2023.</span></span>
<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; Please refer to R-spatial evolution reports for details, especially</span></span>
<span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; https://r-spatial.org/r/2023/05/15/evolution4.html.</span></span>
<span id="cb1-9"><a href="#cb1-9" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; It may be desirable to make the sf package available;</span></span>
<span id="cb1-10"><a href="#cb1-10" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; package maintainers should consider adding sf to Suggests:.</span></span>
<span id="cb1-11"><a href="#cb1-11" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; The sp package is now running under evolution status 2</span></span>
<span id="cb1-12"><a href="#cb1-12" aria-hidden="true" tabindex="-1"></a><span class="co">#&gt; (status 2 uses the sf package in place of rgdal)</span></span></code></pre></div>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" tabindex="-1"></a><span class="co"># install.packages(&quot;ClimDatDownloadR&quot;, dependencies = TRUE)</span></span>
<span id="cb1-2"><a href="#cb1-2" tabindex="-1"></a><span class="fu">library</span>(ClimDatDownloadR)</span>
<span id="cb1-3"><a href="#cb1-3" tabindex="-1"></a><span class="co">#&gt; Loading required package: terra</span></span>
<span id="cb1-4"><a href="#cb1-4" tabindex="-1"></a><span class="co">#&gt; terra 1.7.39</span></span>
<span id="cb1-5"><a href="#cb1-5" tabindex="-1"></a><span class="co">#&gt; The legacy packages maptools, rgdal, and rgeos, underpinning the sp package,</span></span>
<span id="cb1-6"><a href="#cb1-6" tabindex="-1"></a><span class="co">#&gt; which was just loaded, will retire in October 2023.</span></span>
<span id="cb1-7"><a href="#cb1-7" tabindex="-1"></a><span class="co">#&gt; Please refer to R-spatial evolution reports for details, especially</span></span>
<span id="cb1-8"><a href="#cb1-8" tabindex="-1"></a><span class="co">#&gt; https://r-spatial.org/r/2023/05/15/evolution4.html.</span></span>
<span id="cb1-9"><a href="#cb1-9" tabindex="-1"></a><span class="co">#&gt; It may be desirable to make the sf package available;</span></span>
<span id="cb1-10"><a href="#cb1-10" tabindex="-1"></a><span class="co">#&gt; package maintainers should consider adding sf to Suggests:.</span></span>
<span id="cb1-11"><a href="#cb1-11" tabindex="-1"></a><span class="co">#&gt; The sp package is now running under evolution status 2</span></span>
<span id="cb1-12"><a href="#cb1-12" tabindex="-1"></a><span class="co">#&gt; (status 2 uses the sf package in place of rgdal)</span></span></code></pre></div>
<p>Very well, now that you have the package installed and attached,
let’s start with the data sets of the climatologies of Chelsa and
WorldClim.</p>
......
man/Chelsa.timeseries.download.Rd
+ 45
− 5
View file @ b1004931
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Chelsa_Download_functions.R
% Please edit documentation in R/Chelsa_Download_functions.R,
% R/Chelsa_new_download_functions.R
\name{Chelsa.timeseries.download}
\alias{Chelsa.timeseries.download}
\title{CHELSA Timeseries Download}
\usage{
Chelsa.timeseries.download(
save.location = "./",
parameter = c("prec", "tmax", "tmin"),
parameter = c("prec", "temp", "tmax", "tmin"),
start.year.var = 1979,
start.month.var = 1,
end.year.var = 2013,
end.month.var = 12,
include.month.var = c(1:12),
version.var = c("1.2"),
clipping = FALSE,
clip.shapefile = NULL,
buffer = 0,
clip.extent = c(-180, 180, -90, 90),
convert.files.to.asc = FALSE,
combine.raw.zip = FALSE,
delete.raw.data = FALSE,
save.bib.file = TRUE
)
Chelsa.timeseries.download(
save.location = "./",
parameter = c("prec", "temp", "tmax", "tmin"),
start.year.var = 1979,
start.month.var = 1,
end.year.var = 2013,
end.month.var = 12,
include.month.var = c(1:12),
version.var = c("1.2"),
clipping = FALSE,
clip.shapefile = NULL,
buffer = 0,
clip.extent = c(-180, 180, -90, 90),
convert.files.to.asc = FALSE,
stacking.data = FALSE,
combine.raw.zip = FALSE,
delete.raw.data = FALSE,
save.bib.file = TRUE
......@@ -38,6 +58,8 @@ Chelsa.timeseries.download(
\item{include.month.var}{integer (vector). Input which monthly data should be downloaded. \cr Default: \code{c(1:12)}}
\item{version.var}{string (vector). Input which version of the dataset should be downloaded. Multiple selection is _not_ possible. Select between version _1.2_ and _2.1_.\cr Default: \code{c("1.2")}}
\item{clipping}{logical. Input whether the downloaded data should be clipped.\cr If \code{FALSE}: \code{clip.shapefile}, \code{buffer}, \code{clip.extent} will be ignored. \cr Default: \code{FALSE}}
\item{clip.shapefile}{string. Input which shapefile should be used for clipping. \cr Default: \code{NULL}}
......@@ -48,8 +70,6 @@ Chelsa.timeseries.download(
\item{convert.files.to.asc}{logical. Input whether files should be converted into the ASCII format.\cr If \code{TRUE}: a new subdirectory is created and the rawdata is saved there. \cr If \code{clipping} is \code{TRUE}: the clipped raster files are also saved as ASCII grids. \cr Default: \code{FALSE}}
\item{stacking.data}{logical. Input whether the downloaded data should be stacked as a netCDF-rasterstack. \cr Default: \code{FALSE}}
\item{combine.raw.zip}{logical. Should the downloaded raw-data be "zipped". \cr Default: \code{FALSE}}
\item{delete.raw.data}{logical. Should the downloaded raw-data be deleted. If \code{combine.raw.zip} is \code{TRUE}: raw-data is still available in the zipped file. \cr Default: \code{FALSE}}
......@@ -57,12 +77,18 @@ Chelsa.timeseries.download(
\item{save.bib.file}{logical. Whether a BibTex-citation file of the dataset should be provided in the Working directory. \cr Default: \code{TRUE}}
}
\value{
Custom dataset of CHELSA Timeseries for a chosen timeseries.
Custom dataset of CHELSA Timeseries for a chosen timeseries.
}
\description{
This function supports a download of the CHELSA Timeseries dataset (Jan. 1979 - Dec. 2013). This includes precipitation sums (mm) and temperature (average, maximum, minimum; °C) parameters. For further information, please regard \url{http://chelsa-climate.org/timeseries/}.\cr To allow pre-processing, clipping and buffering, conversion to ASCII-grids and stacking options are included.\cr Optional an output of a .bib-file of the cited literature can be retrieved.\cr For user convenience, saving directories will be created automatically. Also options to "zip" and/or delete the RAW-files are included.
This function supports a download of the CHELSA Timeseries dataset (Jan. 1979 - Dec. 2013). This includes precipitation sums (mm) and temperature (average, maximum, minimum; °C) parameters. For further information, please regard \url{http://chelsa-climate.org/timeseries/}.\cr To allow pre-processing, clipping and buffering, conversion to ASCII-grids and stacking options are included.\cr Optional an output of a .bib-file of the cited literature can be retrieved.\cr For user convenience, saving directories will be created automatically. Also options to "zip" and/or delete the RAW-files are included.
}
\note{
Please note that the downloaded data for temperature are processed to °C with one significant decimal without offset and factor. Processing and conversion to other file-formats on a global dataset may take some time.
Please note that the downloaded data for temperature are processed to °C with one significant decimal without offset and factor. Processing and conversion to other file-formats on a global dataset may take some time.
}
\examples{
......@@ -75,10 +101,24 @@ Chelsa.timeseries.download(parameter = "prec",
include.month.var = c(1,12))
}
\dontrun{
Chelsa.timeseries.download(parameter = "prec",
start.year.var = 2000,
start.month.var = 1,
end.year.var = 2002,
end.month.var = 12,
version.var = "1.2",
include.month.var = c(1,12))
}
}
\references{
D. N. Karger, O. Conrad, J. B{\"o}hner , et al. "Climatologies at high resolution for the earth's land surface areas". In: _Scientific Data_ 4.1 (Sep. 2017). DOI: 10.1038/sdata.2017.122. <URL: https://doi.org/10.1038/sdata.2017.122>.
D. N. Karger, O. Conrad, J. B{\"o}hner , et al. _Data from: Climatologies at high resolution for the earth's land surface areas_. En. 2018. DOI: 10.5061/DRYAD.KD1D4. <URL: http://datadryad.org/stash/dataset/doi:10.5061/dryad.kd1d4>.
D. N. Karger, O. Conrad, J. B{\"o}hner , et al. "Climatologies at high resolution for the earth's land surface areas". In: _Scientific Data_ 4.1 (Sep. 2017). DOI: 10.1038/sdata.2017.122. <URL: https://doi.org/10.1038/sdata.2017.122>.
D. N. Karger, O. Conrad, J. B{\"o}hner , et al. _Data from: Climatologies at high resolution for the earth's land surface areas_. En. 2018. DOI: 10.5061/DRYAD.KD1D4. <URL: http://datadryad.org/stash/dataset/doi:10.5061/dryad.kd1d4>.
}
\author{
......
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