| Title: | Terrestrial Water Cycle |
| Version: | 0.0.2 |
| Description: | An open-access tool/framework that constitutes the core functions to analyze terrestrial water cycle data across various spatio-temporal scales. |
| Depends: | R (≥ 4.0.0) |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.2 |
| Imports: | data.table, doParallel, foreach, lubridate, magrittr, methods, ncdf4, parallel, raster, sf, sp, stats, utils |
| URL: | https://github.com/imarkonis/twc |
| BugReports: | https://github.com/imarkonis/twc/issues |
| SystemRequirements: | PROJ (>= 6, https://proj.org/download.html), GDAL (>= 3, https://gdal.org/download.html), NetCDF(>= 4, https://www.unidata.ucar.edu/software/netcdf/). |
| Suggests: | testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2025-04-02 14:24:21 UTC; mirovago |
| Author: | Mijael Rodrigo Vargas Godoy
 [aut, cre],
Yannis Markonis
[aut] |
| Maintainer: | Mijael Rodrigo Vargas Godoy <mirovago@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2025-04-02 15:50:02 UTC |
twc: Terrestrial Water Cycle
Description
twc is an R package that that constitutes the core functions to analyze terrestrial water cycle data across various spatio-temporal scales.
Author(s)
Coded by: Mijael Rodrigo Vargas Godoy vargas_godoy@fzp.czu.cz
Conceptual design by: Mijael Rodrigo Vargas Godoy vargas_godoy@fzp.czu.cz and Yannis Markonis markonis@fzp.czu.cz
See Also
Useful links:
Pipe operator
Description
See magrittr::%>% for details.
Usage
lhs %>% rhs
Arguments
lhs |
A value or the magrittr placeholder. |
rhs |
A function call using the magrittr semantics. |
Value
The result of calling 'rhs(lhs)'.
Ensure getZ output are dates
Description
Function to fix dates
Usage
aux_date(x)
Arguments
x |
output from getZ() |
Value
Date
Crop precipitation data sets
Description
The function crop_data crops the data sets using a shapefile mask.
Usage
crop_data(x, y)
## S4 method for signature 'Raster'
crop_data(x, y)
## S4 method for signature 'data.table'
crop_data(x, y)
## S4 method for signature 'character'
crop_data(x, y)
Arguments
x |
Raster* object; data.table (see details); filename (character; see details) |
y |
filename (character). Path to a *.shp file |
Details
If 'x' is a data.table, its columns should be named: "lon", "lat", "date", and "value"
If 'x' is a filename, it should point to a *.nc file.
Value
Raster* object; data.table
Examples
## Not run:
download_data("gldas-vic", tempdir(), timestep = "yearly")
r <- raster::brick(paste0(tempdir(),
"/gldas-vic_tp_mm_land_194801_201412_025_yearly.nc"))
s <- crop_data(r, "cze.shp")
## End(Not run)
Field mean
Description
The function fldmean computes the spatial weighted average for each timestep.
Usage
fldmean(x)
## S4 method for signature 'Raster'
fldmean(x)
## S4 method for signature 'data.table'
fldmean(x)
## S4 method for signature 'character'
fldmean(x)
Arguments
x |
Raster* object; data.table (see details); filename (character, see details) |
Details
If 'x' is a data.table, its columns should be named: "lon", "lat", "date", and "value"
If 'x' is a filename, it should point to a *.nc file.
Value
data.table
Examples
## Not run:
download_data("gldas-vic", tempdir(), timestep = "yearly")
r <- raster::brick(paste0(tempdir(),
"/gldas-vic_tp_mm_land_194801_201412_025_yearly.nc"))
s <- fldmean(r)
## End(Not run)
Show data content
Description
The function infoNC displays the specification of the desired file.
Usage
infoNC(x)
## S4 method for signature 'Raster'
infoNC(x)
## S4 method for signature 'character'
infoNC(x)
Arguments
x |
Raster* Object; character |
Value
character
Multiply by days per month
Description
The function muldpm multiplies the value by days per month.
Usage
muldpm(x)
## S4 method for signature 'Raster'
muldpm(x)
## S4 method for signature 'data.table'
muldpm(x)
## S4 method for signature 'character'
muldpm(x)
Arguments
x |
Raster* object; data.table (see details); filename (character, see details) |
Details
'x' object with monthly data in [units/day]
If 'x' is a data.table, its columns should be named: "lon", "lat", "date", and "value"
If 'x' is a filename, it should point to a *.nc file.
Value
Raster* object; data.table
Examples
## Not run:
tavg_brick <- raster::brick('terraclimate_tavg.nc')
pet_od <- pet(method = "od", tavg = tavg_brick)
pet_od <- muldpm(pet_od)
## End(Not run)
Nash–Sutcliffe Efficiency
Description
Function for calculating the Nash–Sutcliffe efficiency.
Usage
nse(x, ref)
Arguments
x |
a data.table generated by |
ref |
a data.table with data used for evaluation |
Value
numeric
Masks data
Description
Function for various masks.
Usage
pRecipe_masks()
Value
data.table
Ensemble representativeness ranking
Description
The function rank_repres ranks the elements of a dataset ensemble in terms of a representativeness metric.
Usage
rank_repres(data, method = "all", ensemble = "median")
Arguments
data |
data.table with three variables: dataset, date, value |
method |
character with seven options: mean, var (variance), slope, kge (Kling–Gupta Efficiency), tss (Taylor Skill Score), kld (Kullback–Leibler Divergence), all (default) |
ensemble |
character with two options: mean, median (default) |
Details
data is a data.table (time, value) method relates to the metric used to estimate the similarity to the ensemble mean/median. Can be mean, variance, correlation, slope, Kling–Gupta efficiency, Taylor skill score, Kullback–Leibler divergence, and all (for returning all of them)
Value
data.table 2-column (dataset, repres_metric) or 8-column (dataset, mean, variance, ...) in case of method = all
Examples
## Not run:
download_data("gldas-vic", tempdir(), timestep = "yearly")
download_data("gpcc", tempdir(), timestep = "yearly")
download_data("ghcn", tempdir(), timestep = "yearly")
r1 <- raster::brick(paste0(tempdir(),
"/gldas-vic-v2-0_tp_mm_land_194801_201412_025_yearly.nc"))
s1 <- fldmean(r1)
s1$dataset <- "gldas-vic"
r2 <- raster::brick(paste0(tempdir(),
"/gpcc-v2022_tp_mm_land_198201_202012_025_yearly.nc"))
s2 <- fldmean(r2)
s2$dataset <- "gpcc"
r3 <- raster::brick(paste0(tempdir(),
"/ghcn-v2_tp_mm_land_190001_201505_025_yearly.nc"))
s3 <- fldmean(r2)
s3$dataset <- "ghcn"
dt <- rbind(r1, r2, r3)
dr <- rank_repres(dt[year(date) >= 1991 & year(date) <= 2012, .(dataset, date, value)])
## End(Not run)
Spatial aggregation
Description
The function remap aggregates data into a new grid resolution.
Usage
remap(x, y)
## S4 method for signature 'Raster'
remap(x, y)
## S4 method for signature 'data.table'
remap(x, y)
## S4 method for signature 'character'
remap(x, y)
Arguments
x |
Raster* object; data.table (see details); filename (character, see details) |
y |
numeric |
Details
If 'x' is a data.table, its columns should be named: "lon", "lat", "date", and "value"
If 'x' is a filename, it should point to a *.nc file.
Value
Raster* object; data.table
Examples
## Not run:
download_data("gldas-vic", tempdir(), timestep = "yearly")
r <- raster::brick(paste0(tempdir(),
"/gldas-vic_tp_mm_land_194801_201412_025_yearly.nc"))
s <- remap(r, 1)
## End(Not run)
Save .nc file
Description
Function to save data compatible with pRecipe in .nc file
Usage
saveNC(x, file, name = "tp", longname = "Total precipitation", units = "mm")
Arguments
x |
Raster* object |
file |
character |
name |
character |
longname |
character |
units |
character |
Value
No return value, called to save a file
Examples
## Not run:
save_nc(dummie_brick, "gpcp_tp_mm_global_197901_202205_025_monthly.nc")
## End(Not run)
Select Longitude Latitude Box
Description
The function sellonlatbox subsets the data in space within a bounding box.
Usage
sellonlatbox(x, y)
## S4 method for signature 'Raster'
sellonlatbox(x, y)
## S4 method for signature 'data.table'
sellonlatbox(x, y)
## S4 method for signature 'character'
sellonlatbox(x, y)
Arguments
x |
Raster* object; data.table (see details); filename (character, see details) |
y |
numeric. Bounding box in the form: (xmin, xmax, ymin, ymax) |
Details
If 'x' is a data.table, its columns should be named: "lon", "lat", "date", and "value"
If 'x' is a filename, it should point to a *.nc file.
Value
Raster* object; data.table
Select Years
Description
The function selyear subsets the data in time within a year range.
Usage
selyear(x, y)
## S4 method for signature 'Raster'
selyear(x, y)
## S4 method for signature 'data.table'
selyear(x, y)
## S4 method for signature 'character'
selyear(x, y)
Arguments
x |
Raster* object; data.table (see details); filename (character, see details) |
y |
numeric. Time range in the form: (start_year, end_year) |
Details
If 'x' is a data.table, its columns should be named: "lon", "lat", "date", and "value"
If 'x' is a filename, it should point to a *.nc file.
Value
Raster* object; data.table
Subset data in space and time
Description
The function subset_data subsets the data in space within a bounding box, and/or in time within a year range.
Usage
subset_data(x, box = NULL, yrs = NULL)
## S4 method for signature 'Raster'
subset_data(x, box = NULL, yrs = NULL)
## S4 method for signature 'data.table'
subset_data(x, box = NULL, yrs = NULL)
## S4 method for signature 'character'
subset_data(x, box = NULL, yrs = NULL)
Arguments
x |
Raster* object; data.table (see details); filename (character, see details) |
box |
numeric. Bounding box in the form: (xmin, xmax, ymin, ymax) |
yrs |
numeric. Time range in the form: (start_year, end_year) |
Details
If 'x' is a data.table, its columns should be named: "lon", "lat", "date", and "value"
If 'x' is a filename, it should point to a *.nc file.
If subsetting only in space or time then the arguments must be passed by name. I.e., subset_data(x, box = ...) (space) or subset_data(x, yrs = ...) (time)
Value
Raster* object; data.table
Examples
## Not run:
download_data("gldas-vic", tempdir(), timestep = "yearly")
r <- raster::brick(paste0(tempdir(),
"/gldas-vic_tp_mm_land_194801_201412_025_yearly.nc"))
sd <- subset_data(r, c(12.24, 18.85, 48.56, 51.12), c(2000, 2010))
ss <- subset_data(r, box = c(12.24, 18.85, 48.56, 51.12))
st <- subset_data(r, yrs = c(2000, 2010))
## End(Not run)
Transform raster into data.table
Description
Function to transform a raster brick into a data.table
Usage
tabular(x)
## S4 method for signature 'Raster'
tabular(x)
## S4 method for signature 'character'
tabular(x)
Arguments
x |
Raster* object; filename (character, see details) |
Value
data.table
Examples
## Not run:
download_data("gldas-vic", tempdir(), timestep = "yearly")
r <- raster::brick(paste0(tempdir(),
"/gldas-vic_tp_mm_land_194801_201412_025_yearly.nc"))
s <- tabular(r)
## End(Not run)
Trends
Description
The function trend computes linear slope.
Usage
trend(x)
## S4 method for signature 'Raster'
trend(x)
## S4 method for signature 'data.table'
trend(x)
## S4 method for signature 'character'
trend(x)
Arguments
x |
Raster* object; data.table (see details); filename (character, see details) |
Details
If 'x' is a data.table, its columns should be named: "lon", "lat", "date", and "value"
If 'x' is a filename, it should point to a *.nc file.
Value
Raster* object; data.table
Yearly <stat>
Description
The function yearstat aggregates the data from monthly to yearly.
Usage
yearstat(x, stat = "sum")
## S4 method for signature 'Raster'
yearstat(x, stat = "sum")
## S4 method for signature 'data.table'
yearstat(x, stat = "sum")
## S4 method for signature 'character'
yearstat(x, stat = "sum")
Arguments
x |
Raster* object; data.table (see details); filename (character, see details) |
stat |
character |
Details
If 'x' is a data.table, its columns should be named: "lon", "lat", "date", and "value"
If 'x' is a filename, it should point to a *.nc file.
'stat' is a character string describing the desired aggregation function. Suitable options are:
"max"
"mean"
"median"
"min"
"sum" (default)
Value
Raster* object; data.table
Examples
## Not run:
download_data("gldas-vic", path = tempdir())
r <- raster::brick(paste0(tempdir(),
"/gldas-vic_tp_mm_land_194801_201412_025_monthly.nc"))
s <- yearstat(r, "mean")
## End(Not run)