changed name from rapids_singlecell to rapids-singlecell Added ability to install from pipy Added updated yaml recipes for Conda environments
Minor Changes: * minor fix for rapids-23.02 in `rank_genes_groups_logreg` * accelerated `_get_mean_var` * improvements for `tl.tsne`: * added `method` argument * added `metric` argument
0.3.3
cunndata: * switchted to anndata's __getitem__ function
cunndata_funcs: * added `.layers` support for: * `regress_out` * `scale` * `normalize_total` * changed `mean` and `var` calcuations to make them more memory efficent
scanpy_gpu * changed `TSNE` defaults
0.3.2
cunndata *added `.varm` *added `.__repr__`
cunndata_funcs *added `pca` *added TSVD and Incremental PCA support *added support for `.varm`
scanpy_gpu *added TSVD and Incremental PCA support *added `.uns` support for `leiden` and `louvain`
0.3.1
* fixed Louvain and Leiden Clustering for rapids version > 22.08. * added support for `use_weights` for `leiden` and `louvain` clustering * added support for `neighbors_key` for `leiden` and `louvain` clustering * added possibility to use different neighbourhood graphs * added support multi_target_regresion in `cudata_funcs.regress_out` * added support for `__getitem__` to be used on `.var` * added support for slices to be used on `__getitem__`
0.3.0
v.0.3.0 cunnData * added support for spatial transcriptomics * added `.obsm` to cunnData * moved methods from class to `cunnData_funcs`
cunnData_funcs * most methods of cunnData are now functions the can be used on the cunnData object.
scanpy_gpu * split functions into separate files
decoupler_gpu * added first two accelerated `decoupler` functions: * `run_mlm` * `run_wsum`