Bug fix to avoid archive when dependencies are updated.
Resolves: https://github.com/yihui/knitr/issues/2057 https://github.com/yihui/knitr/pull/2306
Minor update to pass CRAN checks
removed deprecated method to create sparse matrices
correct links in citations and vignettes
migrates bug fixes to conda environment and limit on total cells to refactored package
allows calling igraph::community_leiden for supported parameters (requires igraph v1.2.7 or later)
automatically calls native R version of leiden rather than Python to improve performance
updates vignettes and unit tests to ensure consistent results with past versions
migrate to calling community_leiden in igraph
updates the benchmarking vignette to compare performance to legacy versions using reticulate
removes limitation on number of cells (disables scientific notation within function call): resolves #12
resolves conflict between base and r-reticulate conda environments on loading: resolves #20
updates conda environment in interactive sessions only for compliance to CRAN checks
resolves formatting error in Rmarkdown vignettes (https://github.com/yihui/knitr/issues/2057)
update testing for bipartite graphs for compatibility with newer version
Updates maintainer contact details.
add methods for multiplex community detection from a list of graphs (requires leidenalg 0.7.1)
add support for maximum community size (depends on leidenalg 0.8.2), if available
add support for bipartite graphs (requires leidenalg 0.6.1 or later)
changes to install python leidenalg from vtraag channel on Windows
bug fixes to install documentation
improve automated conda configuration in background on loading library
optionally derive edge weights from the Laplacian matrix
see development version: https://bugs.r-project.org/bugzilla/show_bug.cgi?id=16223
added support for passing weighted igraph objects
improved handling of sparse matrices
bug fixes to ensure same results from matrix and igraph methods
method for sparse matrices that passes to igraph without casting to dense
added seed and n_iterations to find_partitions
Implements calling leiden directly on an igraph object
Separate methods for igraph objects and adjacency matrices
Support for sparse matrices
Benchmarking added to vignettes