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rspatial
terra:Spatial Data Analysis
Methods for spatial data analysis with vector (points, lines, polygons) and raster (grid) data. Methods for vector data include geometric operations such as intersect and buffer. Raster methods include local, focal, global, zonal and geometric operations. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/> to get started. 'terra' replaces the 'raster' package ('terra' can do more, and it is faster and easier to use).
Maintained by Robert J. Hijmans. Last updated 9 hours ago.
geospatialrasterspatialvectoronetbbprojgdalgeoscpp
560 stars 17.65 score 17k scripts 856 dependents
bioc
SpatialFeatureExperiment:Integrating SpatialExperiment with Simple Features in sf
A new S4 class integrating Simple Features with the R package sf to bring geospatial data analysis methods based on vector data to spatial transcriptomics. Also implements management of spatial neighborhood graphs and geometric operations. This pakage builds upon SpatialExperiment and SingleCellExperiment, hence methods for these parent classes can still be used.
Maintained by Lambda Moses. Last updated 2 months ago.
datarepresentationtranscriptomicsspatial
49 stars 9.40 score 322 scripts 1 dependents
arcadeantics
this.path:Get Executing Script's Path
Determine the path of the executing script. Compatible with several popular GUIs: 'Rgui', 'RStudio', 'Positron', 'VSCode', 'Jupyter', 'Emacs', and 'Rscript' (shell). Compatible with several functions and packages: 'source()', 'sys.source()', 'debugSource()' in 'RStudio', 'compiler::loadcmp()', 'utils::Sweave()', 'box::use()', 'knitr::knit()', 'plumber::plumb()', 'shiny::runApp()', 'package:targets', and 'testthat::source_file()'.
Maintained by Iris Simmons. Last updated 6 days ago.
48 stars 8.73 score 388 scripts 3 dependents
courtiol
IsoriX:Isoscape Computation and Inference of Spatial Origins using Mixed Models
Building isoscapes using mixed models and inferring the geographic origin of samples based on their isotopic ratios. This package is essentially a simplified interface to several other packages which implements a new statistical framework based on mixed models. It uses 'spaMM' for fitting and predicting isoscapes, and assigning an organism's origin depending on its isotopic ratio. 'IsoriX' also relies heavily on the package 'rasterVis' for plotting the maps produced with 'terra' using 'lattice'.
Maintained by Alexandre Courtiol. Last updated 7 months ago.
14 stars 5.59 score 56 scripts