Package: chopin 0.9.3

Insang Song
chopin: Computation of Spatial Data by Hierarchical and Objective Partitioning of Inputs for Parallel Processing
Geospatial data computation is parallelized by grid, hierarchy, or raster files. Based on 'future' (Bengtsson, 2024 <doi:10.32614/CRAN.package.future>) and 'mirai' (Gao et al., 2025 <doi:10.32614/CRAN.package.mirai>) parallel back-ends, 'terra' (Hijmans et al., 2025 <doi:10.32614/CRAN.package.terra>) and 'sf' (Pebesma et al., 2024 <doi:10.32614/CRAN.package.sf>) functions as well as convenience functions in the package can be distributed over multiple threads. The simplest way of parallelizing generic geospatial computation is to start from 'par_pad_*()' functions to 'par_grid()', 'par_hierarchy()', or 'par_multirasters()' functions. Virtually any functions accepting classes in 'terra' or 'sf' packages can be used in the three parallelization functions. A common raster-vector overlay operation is provided as a function 'extract_at()', which uses 'exactextractr' (Baston, 2023 <doi:10.32614/CRAN.package.exactextractr>), with options for kernel weights for summarizing raster values at vector geometries. Other convenience functions for vector-vector operations including simple areal interpolation ('summarize_aw()') and summation of exponentially decaying weights ('summarize_sedc()') are also provided.
Authors:
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chopin/json (API)
NEWS
# Install 'chopin' in R: |
install.packages('chopin', repos = c('https://packages.ropensci.org', 'https://cloud.r-project.org')) |
Reviews:rOpenSci Software Review #638
Bug tracker:https://github.com/ropensci/chopin/issues
Pkgdown site:https://docs.ropensci.org
- ncpoints - Mildly clustered points in North Carolina, United States
- prediction_grid - Regular grid points in the mainland United States at 1km spatial resolution
Last updated 2 days ago from:722392f21d (on main). Checks:11 OK. Indexed: yes.
Target | Result | Total time | Artifact |
---|---|---|---|
linux-devel-x86_64 | OK | 291 | |
pkgdown docs | OK | 443 | |
source / vignettes | OK | 351 | |
linux-release-x86_64 | OK | 286 | |
macos-release-arm64 | OK | 145 | |
macos-oldrel-arm64 | OK | 168 | |
windows-devel | OK | 259 | |
windows-release | OK | 262 | |
windows-oldrel | OK | 233 | |
wasm-release | OK | 185 | |
wasm-oldrel | OK | 231 |
Exports:extract_atkernelfunctionpar_convert_fpar_gridpar_grid_miraipar_hierarchypar_hierarchy_miraipar_merge_gridpar_multirasterspar_multirasters_miraipar_pad_balancedpar_pad_gridpar_split_listsummarize_awsummarize_sedc
Dependencies:abindanticlustclassclassIntclicodetoolscollapsecpp11DBIdigestdplyre1071exactextractrfuturefuture.applygenericsglobalsglueigraphKernSmoothlatticelifecyclelistenvlpSolvemagrittrMASSMatrixmirainanonextparallellypillarpkgconfigproxyR6RANNrasterRcpprlangs2sfspstarsterratibbletidyselectunitsutf8vctrswithrwk
Extracting Weather/Climate Geospatial Data with chopin
Rendered fromv04_climate_examples.Rmd
usingknitr::rmarkdown
on Jul 09 2025.Last update: 2025-02-13
Started: 2024-08-09
Generate computational grids
Rendered fromv03_par_pad_grid.Rmd
usingknitr::rmarkdown
on Jul 09 2025.Last update: 2025-02-13
Started: 2024-08-09
Getting started with chopin
Rendered fromv01_start.Rmd
usingknitr::rmarkdown
on Jul 09 2025.Last update: 2025-07-09
Started: 2024-08-09
Good practice of using chopin
Rendered fromv02_good_practice.Rmd
usingknitr::rmarkdown
on Jul 09 2025.Last update: 2025-02-13
Started: 2024-08-09
targets and grid objects
Rendered fromv05_targets.Rmd
usingknitr::rmarkdown
on Jul 09 2025.Last update: 2024-08-09
Started: 2024-08-09