rapids-25.02

.github/workflows/docker.yml

@@ -27,7 +27,7 @@ jobs:
     strategy:
       matrix:
         RAPIDS_VER:
-          - 24.12
+          - 25.02
     name: Build Docker images
     runs-on: ubuntu-latest
     permissions:

conda/rsc_rapids_24.08.yml → conda/rsc_rapids_25.02.yml

@@ -5,9 +5,9 @@ channels:
  - conda-forge
  - bioconda
 dependencies:
- - rapids=24.08
- - python=3.11
- - cuda-version=12.5
+ - rapids=25.02
+ - python=3.12
+ - cuda-version=12.8
  - cudnn
  - cutensor
  - cusparselt

docker/Dockerfile.deps

@@ -1,4 +1,4 @@
-ARG CUDA_VER=12.5.0
+ARG CUDA_VER=12.8.0
 ARG LINUX_VER=ubuntu22.04
 
 FROM nvidia/cuda:${CUDA_VER}-base-${LINUX_VER}

docker/docker-push.sh

@@ -2,7 +2,7 @@
 set -euxo pipefail
 
 docker_account=scverse
-rapids_version=24.12
+rapids_version=25.02
 grep -v -- '- rapids-singlecell' conda/rsc_rapids_${rapids_version}.yml > rsc_rapids.yml
 docker build -t rapids-singlecell-deps:latest -f docker/Dockerfile.deps .
 rm rsc_rapids.yml

docs/Installation.md

@@ -2,7 +2,7 @@
 ## Conda
 The easiest way to install *rapids-singlecell* is to use one of the *yaml* file provided in the [conda](https://github.com/scverse/rapids_singlecell/tree/main/conda) folder. These *yaml* files install everything needed to run the example notebooks and get you started.
 ```
-conda env create -f conda/rsc_rapids_24.08.yml #default CUDA-11.8
+conda env create -f conda/rsc_rapids_25.02.yml #default CUDA-12.5
 # or
 mamba env create -f conda/rsc_rapids_24.12.yml #default CUDA-12.5
 ```

docs/release-notes/0.12.0.md

@@ -2,7 +2,7 @@
 
 ```{rubric} Features
 ```
-* Updates `pp.filter_genes` & `pp.filter_cells` to be closer to the `scanpy` implementation {pr}`324` {smaller}`S Dicks`
+* Updates `pp.filter_genes` & `pp.filter_cells` API to be closer to the `scanpy` implementation {pr}`324` {smaller}`S Dicks`
 
 ```{rubric} Performance
 ```
@@ -13,3 +13,5 @@
 
 ```{rubric} Misc
 ```
+* Adds support for `rapids-25.02` {pr}`329` {smaller}`S Dicks`
+* Updates the docker for `rapids-25.02` {pr}`329` {smaller}`S Dicks`

pyproject.toml

@@ -26,8 +26,8 @@ dependencies = [
 ]
 
 [project.optional-dependencies]
-rapids11 = [ "cupy-cuda11x", "cudf-cu11==24.12.*", "cuml-cu11==24.12.*", "cugraph-cu11==24.12.*", "numba < 0.61.0" ]
-rapids12 = [ "cupy-cuda12x", "cudf-cu12==24.12.*", "cuml-cu12==24.12.*", "cugraph-cu12==24.12.*", "numba < 0.61.0" ]
+rapids11 = [ "cupy-cuda11x", "cudf-cu11==25.02.*", "cuml-cu11==25.02.*", "cugraph-cu11==25.02.*" ]
+rapids12 = [ "cupy-cuda12x", "cudf-cu12==25.02.*", "cuml-cu12==25.02.*", "cugraph-cu12==25.02.*" ]
 doc = [
     "sphinx>=4.5.0",
     "sphinx-copybutton",

tests/test_neighbors.py

@@ -32,14 +32,20 @@
 ]
 
 
-@pytest.mark.parametrize("algo", ["brute", "cagra", "ivfflat"])
+@pytest.mark.parametrize("algo", ["brute", "ivfflat"])
 def test_umap_connectivities_euclidean(algo):
     adata = AnnData(X=X)
     neighbors(adata, n_neighbors=3, algorithm=algo)
     assert np.allclose(adata.obsp["distances"].toarray(), distances_euclidean)
     assert np.allclose(adata.obsp["connectivities"].toarray(), connectivities_umap)
 
 
+@pytest.mark.parametrize("algo", ["brute", "ivfflat", "cagra", "ivfpq"])
+def test_algo(algo):
+    adata = pbmc68k_reduced()
+    neighbors(adata, n_neighbors=5, algorithm=algo)
+
+
 key = "test"