fix: Removed unnecessary methods, ruff lint

Author: ilaykav

benchmarks/benchmarks/preprocessing_log.py

@@ -40,8 +40,6 @@ def setup_cache(self) -> None:
 
     def setup(self, dataset, layer) -> None:
         self.adata = ad.read_h5ad(f"{dataset}_{layer}.h5ad")
-        if "X_pca" not in self.adata.obsm:
-            sc.pp.pca(self.adata)
 
     def time_pca(self, *_) -> None:
         sc.pp.pca(self.adata, svd_solver="arpack")
@@ -69,12 +67,6 @@ def time_regress_out(self, *_) -> None:
     def peakmem_regress_out(self, *_) -> None:
         sc.pp.regress_out(self.adata, ["total_counts", "pct_counts_mt"])
 
-    def time_neighbors(self, *_) -> None:
-        sc.pp.neighbors(self.adata, n_neighbors=10, n_pcs=40)
-
-    def peakmem_neighbors(self, *_) -> None:
-        sc.pp.neighbors(self.adata, n_neighbors=10, n_pcs=40)
-
     def time_scale(self, *_) -> None:
         sc.pp.scale(self.adata, max_value=10)
 

src/scanpy/preprocessing/_combat.py

@@ -220,7 +220,6 @@ def combat(  # noqa: PLR0915
             "within-batch variance. Filter these batches before running combat."
         )
         raise ValueError(msg)
-    n_array = float(sum(n_batches))
 
     # standardize across genes using a pooled variance estimator
     logg.info("Standardizing Data across genes.\n")
@@ -273,7 +272,7 @@ def combat(  # noqa: PLR0915
 
     # we now apply the parametric adjustment to the standardized data from above
     # loop over all batches in the data
-    bayesdata_arr = bayesdata.values
+    bayesdata_arr = bayesdata.to_numpy(copy=True)
     batch_design_arr = batch_design.values
     for j, batch_idxs in enumerate(batch_info.values()):
         # we basically subtract the additive batch effect, rescale by the ratio