Package: osc 1.0.5
osc: Orthodromic Spatial Clustering
Allows distance based spatial clustering of georeferenced data by implementing the City Clustering Algorithm - CCA. Multiple versions allow clustering for a matrix, raster and single coordinates on a plain (Euclidean distance) or on a sphere (great-circle or orthodromic distance).
Authors:
osc_1.0.5.tar.gz
osc_1.0.5.zip(r-4.5)osc_1.0.5.zip(r-4.4)osc_1.0.5.zip(r-4.3)
osc_1.0.5.tgz(r-4.5-x86_64)osc_1.0.5.tgz(r-4.5-arm64)osc_1.0.5.tgz(r-4.4-x86_64)osc_1.0.5.tgz(r-4.4-arm64)osc_1.0.5.tgz(r-4.3-x86_64)osc_1.0.5.tgz(r-4.3-arm64)
osc_1.0.5.tar.gz(r-4.5-noble)osc_1.0.5.tar.gz(r-4.4-noble)
osc_1.0.5.tgz(r-4.4-emscripten)osc_1.0.5.tgz(r-4.3-emscripten)
osc.pdf |osc.html✨
osc/json (API)
| # Install 'osc' in R: |
| install.packages('osc', repos = c('https://steffenkriewald.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/steffenkriewald/osc/issues
- exampledata - Example data for the clustering algorithm.
- landcover - Fictional landcover data to demonstrate the cca for Raster-Data
- population - Example population data for the city clustering algorithm
Last updated 5 years agofrom:211b0e6c20. Checks:1 OK, 10 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Feb 22 2025 |
| R-4.5-win-x86_64 | NOTE | Feb 22 2025 |
| R-4.5-mac-x86_64 | NOTE | Feb 22 2025 |
| R-4.5-mac-aarch64 | NOTE | Feb 22 2025 |
| R-4.5-linux-x86_64 | NOTE | Feb 22 2025 |
| R-4.4-win-x86_64 | NOTE | Feb 22 2025 |
| R-4.4-mac-x86_64 | NOTE | Feb 22 2025 |
| R-4.4-mac-aarch64 | NOTE | Feb 22 2025 |
| R-4.3-win-x86_64 | NOTE | Feb 22 2025 |
| R-4.3-mac-x86_64 | NOTE | Feb 22 2025 |
| R-4.3-mac-aarch64 | NOTE | Feb 22 2025 |
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Assign data to clusters | assign.data |
| City Clustering Algorithm (CCA) | cca cca.single |
| List of coordinates for clustering | coordinate.list |
| Example data for the clustering algorithm. | exampledata |
| Fictional landcover data to demonstrate the cca for Raster-Data | landcover |
| Simple Buffer algorithm | osc.buffer |
| Example population data for the city clustering algorithm | population |
