Update rapids 24 04 (#166)

* removes notebooks from docs

* adds notebooks

* adds the folder

* updates notebooks

* adds the submodule to rtd

* adds links

* adds release note

* update pandas dep

* update ligrec for pandas

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* updates installers

* added date

* unpin pandas

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

README.md

@@ -22,7 +22,7 @@ The easiest way to install *rapids-singlecell* is to use one of the *yaml* file
 ```
 conda env create -f conda/rsc_rapids_24.02.yml
 # or
-mamba env create -f conda/rsc_rapids_23.12.yml
+mamba env create -f conda/rsc_rapids_24.04.yml
 ```
 ### PyPI
 ```

conda/rsc_rapids_23.12.yml → conda/rsc_rapids_24.04.yml

@@ -5,7 +5,7 @@ channels:
  - conda-forge
  - bioconda
 dependencies:
- - rapids=23.12
+ - rapids=24.04
  - python=3.10
  - cuda-version=11.8
  - cudnn

docs/Installation.md

@@ -4,7 +4,7 @@ The easiest way to install *rapids-singlecell* is to use one of the *yaml* file
 ```
 conda env create -f conda/rsc_rapids_24.02.yml
 # or
-mamba env create -f conda/rsc_rapids_23.12.yml
+mamba env create -f conda/rsc_rapids_24.04.yml
 ```
 ## PyPI
 As of version 0.4.0 *rapids-singlecell* is now on PyPI.

docs/release-notes/0.10.2.md

@@ -1,8 +1,9 @@
-### 0.10.2 {small}`the future`
+### 0.10.2 {small}`2024-04-15`
 
 ```{rubric} Features
 ```
 * adds the option to return the results for `get.aggregate` as sparse matrices if the input is sparse {pr}`160` {smaller}`S Dicks`
+* adds support for `rapids-24.04` {pr}`166` {smaller}`S Dicks`
 
 
 ```{rubric} Performance
@@ -12,7 +13,11 @@
 
 ```{rubric} Bug fixes
 ```
+* fixes small bugs with pandas in `ligrec` {pr}`166` {smaller}`S Dicks`
+
 
 ```{rubric} Misc
 ```
 * moves the notebooks from docs into a submodule {pr}`164` {smaller}`S Dicks`
+* moves tests to rapids-24.04 {pr}`166` {smaller}`S Dicks`
+* unpinned pandas version {pr}`166` {smaller}`S Dicks`

pyproject.toml

@@ -17,7 +17,7 @@ dependencies = [
     "numpy>=1.17.0",
     "decoupler>=1.3.2",
     "scipy>=1.4",
-    "pandas<2.0.0",
+    "pandas",
     "natsort",
     "scikit-misc>=0.1.3",
     "matplotlib>=3.4",
@@ -26,8 +26,8 @@ dependencies = [
 ]
 
 [project.optional-dependencies]
-rapids11 = ["cudf-cu11==24.2.*", "cuml-cu11==24.2.*", "cugraph-cu11==24.2.*"]
-rapids12 = ["cudf-cu12==24.2.*", "cuml-cu12==24.2.*", "cugraph-cu12==24.2.*"]
+rapids11 = ["cudf-cu11==24.4.*", "cuml-cu11==24.4.*", "cugraph-cu11==24.4.*"]
+rapids12 = ["cudf-cu12==24.4.*", "cuml-cu12==24.4.*", "cugraph-cu12==24.4.*"]
 doc = [
     "sphinx>=4.5.0",
     "sphinx-copybutton",

src/rapids_singlecell/squidpy_gpu/_ligrec.py

@@ -345,7 +345,13 @@ def find_min_gene_in_complex(_complex: str | None) -> str | None:
             return complexes[0]
 
         df = data[complexes].mean()
-        return str(df.index[df.argmin()])
+        try:
+            return str(df.index[df.argmin()])
+        except ValueError as e:
+            if "attempt to get argmin of an empty sequence" in str(e):
+                return str(df.index[0])
+            else:
+                raise ValueError(e)
 
     if complex_policy == "min":
         interactions[SOURCE] = interactions[SOURCE].apply(find_min_gene_in_complex)

tests/test_ligrec.py

@@ -40,8 +40,7 @@ def paul15() -> AnnData:
 
 @pytest.fixture()
 def paul15_means() -> pd.DataFrame:
-    file = Path(__file__).parent / Path("_data/paul15_means.pickle")
-    with open(file, "rb") as fin:
+    with open("tests/_data/paul15_means.pickle", "rb") as fin:
         return pickle.load(fin)
 
 
@@ -185,19 +184,6 @@ def test_fdr_axis_works(self, adata: AnnData, interactions: Interactions_t):
 
         assert not np.allclose(rc["pvalues"].values[mask], ri["pvalues"].values[mask])
 
-    """
-    def test_inplace_default_key(self, adata: AnnData, interactions: Interactions_t):
-        res = ligrec(adata, _CK, interactions=interactions, n_perms=5, copy=False)
-
-        assert res is None
-        assert isinstance(adata.uns[key], dict)
-        r = adata.uns[key]
-        assert len(r) == 3
-        assert isinstance(r["means"], pd.DataFrame)
-        assert isinstance(r["pvalues"], pd.DataFrame)
-        assert isinstance(r["metadata"], pd.DataFrame)
-    """
-
     def test_inplace_key_added(self, adata: AnnData, interactions: Interactions_t):
         assert "foobar" not in adata.uns
         res = ligrec(