Package: MapperAlgo 1.0.2
MapperAlgo: Topological Data Analysis: Mapper Algorithm
The Mapper algorithm from Topological Data Analysis, the steps are as follows 1. Define a filter (lens) function on the data. 2. Perform clustering within each level set. 3. Generate a complex from the clustering results.
Authors:
MapperAlgo_1.0.2.tar.gz
MapperAlgo_1.0.2.zip(r-4.5)MapperAlgo_1.0.2.zip(r-4.4)MapperAlgo_1.0.2.zip(r-4.3)
MapperAlgo_1.0.2.tgz(r-4.5-any)MapperAlgo_1.0.2.tgz(r-4.4-any)MapperAlgo_1.0.2.tgz(r-4.3-any)
MapperAlgo_1.0.2.tar.gz(r-4.5-noble)MapperAlgo_1.0.2.tar.gz(r-4.4-noble)
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MapperAlgo.pdf |MapperAlgo.html✨
MapperAlgo/json (API)
| # Install 'MapperAlgo' in R: |
| install.packages('MapperAlgo', repos = c('https://kennywang112.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/kennywang112/mapperalgo/issues
Last updated 20 days agofrom:d9ad69fe98. Checks:8 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Feb 15 2025 |
| R-4.5-win | OK | Feb 15 2025 |
| R-4.5-mac | OK | Feb 15 2025 |
| R-4.5-linux | OK | Feb 15 2025 |
| R-4.4-win | OK | Feb 15 2025 |
| R-4.4-mac | OK | Feb 15 2025 |
| R-4.3-win | OK | Feb 15 2025 |
| R-4.3-mac | OK | Feb 15 2025 |
Exports:cluster_cutoff_at_first_empty_bincover_pointsfind_best_k_for_kmeansMapperAlgomapperEdgesmapperVerticesperform_clusteringsimplcial_complexto_lsfito_lsmi
Dependencies:codetoolsdoParallelforeachiterators
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Cut the hierarchical clustering tree to define clusters | cluster_cutoff_at_first_empty_bin |
| Cover points based on intervals and overlap | cover_points |
| Find the optimal number of clusters for k-means | find_best_k_for_kmeans |
| Mapper Algorithm | MapperAlgo |
| Create Mapper Edges | mapperEdges |
| Create Mapper Vertices | mapperVertices |
| Perform clustering within a level set | perform_clustering |
| Construct adjacency matrix of the simplicial complex | simplcial_complex |
| Convert level set multi-index (lsmi) to flat index (lsfi) | to_lsfi |
| Convert level set flat index (lsfi) to multi-index (lsmi) | to_lsmi |
