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r-spatial
Croping a stars object takes 16.89 hours while terra takes 0.16 seconds
Croping a stars object takes 16.89 hours while terra takes 0.16 seconds. I just installed sf and stars from GitHub.
library(stars)
#> Loading required package: abind
#> Loading required package: sf
#> Linking to GEOS 3.12.1, GDAL 3.8.4, PROJ 9.3.1; sf_use_s2() is TRUE
library(terra)
#> terra 1.7.78
library(sf)
myurl = "http://geocorp.co/wind/MWP_2017242_090W040N_3D3OT.tif"
the_40n_file = "./MWP_2017242_090W040N_3D3OT.tif"
download.file(myurl, the_40n_file, mode = "wb")
myurl = "http://geocorp.co/wind/MWP_2017242_090W030N_3D3OT.tif"
the_30n_file = "./MWP_2017242_090W030N_3D3OT.tif"
download.file(myurl, the_30n_file, mode = "wb")
myurl = "http://geocorp.co/wind/counties_florida.zip"
download.file(myurl, "counties_florida.zip", mode = "wb")
unzip("counties_florida.zip")
the_florida_file = "./counties_florida.shp"
#read the shapefile
sf_florida <- sf::st_read(the_florida_file, quiet = TRUE)
#transform st_florida to 4326
sf_florida <- sf::st_transform(sf_florida, 4326)
#read th files with stars
st_30n <- stars::read_stars(the_30n_file, quiet = TRUE, proxy = FALSE)
st_40n <- stars::read_stars(the_40n_file, quiet = TRUE, proxy = FALSE)
#convert the files to terra
r_30n <- terra::rast(the_30n_file)
r_40n <- terra::rast(the_40n_file)
#mosaic the files the files with stars
system.time({
st_mosaic <- stars::st_mosaic(st_30n, st_40n)
})
#> user system elapsed
#> 2.46 0.68 3.73
#plot st_mosaic
plot(st_mosaic)
#> downsample set to 10
#mosaic the files the files with terra
system.time({
r_mosaic <- terra::mosaic(r_30n, r_40n)
})
#> user system elapsed
#> 1.57 1.39 5.19
#crop the files with stars
#it is taking 16.89 hours
#system.time({
# st_crop <- sf::st_crop(st_mosaic, sf_florida)
#})
#system.time({
# st_crop <- st_mosaic[sf_florida, as_points = T]
#})
# user system elapsed
#21499.75 39246.67 60792.59
#
#crop the files with terra
system.time({
r_crop <- terra::crop(r_mosaic, sf_florida)
})
#> user system elapsed
#> 0.11 0.05 0.16
plot(r_crop)
Created on 2024-07-04 with reprex v2.1.0
Session info
sessionInfo()
#> R version 4.4.1 (2024-06-14 ucrt)
#> Platform: x86_64-w64-mingw32/x64
#> Running under: Windows 10 x64 (build 19045)
#>
#> Matrix products: default
#>
#>
#> locale:
#> [1] LC_COLLATE=English_United States.utf8
#> [2] LC_CTYPE=English_United States.utf8
#> [3] LC_MONETARY=English_United States.utf8
#> [4] LC_NUMERIC=C
#> [5] LC_TIME=English_United States.utf8
#>
#> time zone: America/New_York
#> tzcode source: internal
#>
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] terra_1.7-78 stars_0.6-6 sf_1.0-17 abind_1.4-5
#>
#> loaded via a namespace (and not attached):
#> [1] vctrs_0.6.5 cli_3.6.3 knitr_1.47 rlang_1.1.4
#> [5] xfun_0.45 highr_0.11 KernSmooth_2.23-24 DBI_1.2.3
#> [9] purrr_1.0.2 styler_1.10.3 glue_1.7.0 htmltools_0.5.8.1
#> [13] e1071_1.7-14 rmarkdown_2.27 grid_4.4.1 R.cache_0.16.0
#> [17] evaluate_0.24.0 classInt_0.4-10 fastmap_1.2.0 yaml_2.3.8
#> [21] lifecycle_1.0.4 compiler_4.4.1 codetools_0.2-20 fs_1.6.4
#> [25] Rcpp_1.0.12 R.oo_1.26.0 R.utils_2.12.3 digest_0.6.36
#> [29] class_7.3-22 reprex_2.1.0 curl_5.2.1 parallel_4.4.1
#> [33] magrittr_2.0.3 R.methodsS3_1.8.2 tools_4.4.1 withr_3.0.0
#> [37] proxy_0.4-27 xml2_1.3.6 units_0.8-5
Did you try cutting to the bounding box? Then it should work fast. See also this issue.
st_crop <- st_crop(st_mosaic, st_bbox(sf_florida))
In my initial code, I was comparing two different types of crops. So the time comparison was not valid. If we compare the crop to the bounding box, stars is 1.41 times faster.