Package: ICvectorfields 0.1.2
ICvectorfields: Vector Fields from Spatial Time Series of Population Abundance
Functions for converting time series of spatial abundance or density data in raster format to vector fields of population movement using the digital image correlation technique. More specifically, the functions in the package compute cross-covariance using discrete fast Fourier transforms for computational efficiency. Vectors in vector fields point in the direction of highest two dimensional cross-covariance. The package has a novel implementation of the digital image correlation algorithm that is designed to detect persistent directional movement when image time series extend beyond a sequence of two raster images.
Authors:
ICvectorfields_0.1.2.tar.gz
ICvectorfields_0.1.2.zip(r-4.5)ICvectorfields_0.1.2.zip(r-4.4)ICvectorfields_0.1.2.zip(r-4.3)
ICvectorfields_0.1.2.tgz(r-4.4-x86_64)ICvectorfields_0.1.2.tgz(r-4.4-arm64)ICvectorfields_0.1.2.tgz(r-4.3-x86_64)ICvectorfields_0.1.2.tgz(r-4.3-arm64)
ICvectorfields_0.1.2.tar.gz(r-4.5-noble)ICvectorfields_0.1.2.tar.gz(r-4.4-noble)
ICvectorfields_0.1.2.tgz(r-4.4-emscripten)ICvectorfields_0.1.2.tgz(r-4.3-emscripten)
ICvectorfields.pdf |ICvectorfields.html✨
ICvectorfields/json (API)
NEWS
# Install 'ICvectorfields' in R: |
install.packages('ICvectorfields', repos = c('https://goodsman.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/goodsman/icvectorfields/issues
- SimData - Simulated movement data
Last updated 3 years agofrom:8769e9e5f6. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 27 2024 |
R-4.5-win-x86_64 | OK | Oct 27 2024 |
R-4.5-linux-x86_64 | OK | Oct 27 2024 |
R-4.4-win-x86_64 | OK | Oct 27 2024 |
R-4.4-mac-x86_64 | OK | Oct 27 2024 |
R-4.4-mac-aarch64 | OK | Oct 27 2024 |
R-4.3-win-x86_64 | OK | Oct 27 2024 |
R-4.3-mac-x86_64 | OK | Oct 27 2024 |
R-4.3-mac-aarch64 | OK | Oct 27 2024 |
Exports:DispFieldDispFieldbbDispFieldSTDispFieldSTallDispFieldSTbbDispFieldSTbballDispMoransIDispStatsGetRowColMoransIPatternDetectPixelCtRastStackDataRooksGradientRooksNeighCtRooksNeighFindRotationDetectSubgridMoransISubgridStatsXcov2D