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

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src/scvi/model/_multivi.py

@@ -2,7 +2,6 @@
 
 import logging
 import warnings
-from collections.abc import Iterable as IterableClass
 from functools import partial
 from typing import TYPE_CHECKING
 
@@ -46,7 +45,7 @@
     from anndata import AnnData
     from mudata import MuData
 
-    from scvi._types import Number, AnnOrMuData
+    from scvi._types import AnnOrMuData, Number
 
 logger = logging.getLogger(__name__)
 
@@ -590,8 +589,9 @@ def get_accessibility_estimates(
             return pd.DataFrame(
                 imputed,
                 index=adata.obs_names[indices],
-                columns=adata["rna"].var_names[self.n_genes :][region_mask] if
-                type(adata).__name__ == "MuData" else adata.var_names[self.n_genes :][region_mask],
+                columns=adata["rna"].var_names[self.n_genes :][region_mask]
+                if type(adata).__name__ == "MuData"
+                else adata.var_names[self.n_genes :][region_mask],
             )
 
     @torch.inference_mode()
@@ -1089,7 +1089,8 @@ def setup_mudata(
                     mod_key=modalities.rna_layer,
                     is_count_data=True,
                     mod_required=True,
-                ))
+                )
+            )
         if modalities.atac_layer is not None:
             mudata_fields.append(
                 fields.MuDataLayerField(
@@ -1098,7 +1099,8 @@ def setup_mudata(
                     mod_key=modalities.atac_layer,
                     is_count_data=True,
                     mod_required=True,
-                ))
+                )
+            )
         if modalities.protein_layer is not None:
             mudata_fields.append(
                 fields.MuDataProteinLayerField(
@@ -1109,7 +1111,8 @@ def setup_mudata(
                     batch_field=batch_field,
                     is_count_data=True,
                     mod_required=True,
-                ))
+                )
+            )
         adata_manager = AnnDataManager(fields=mudata_fields, setup_method_args=setup_method_args)
         adata_manager.register_fields(mdata, **kwargs)
         cls.register_manager(adata_manager)

src/scvi/model/_totalvi.py

@@ -35,7 +35,7 @@
     from anndata import AnnData
     from mudata import MuData
 
-    from scvi._types import Number, AnnOrMuData
+    from scvi._types import AnnOrMuData, Number
 
 logger = logging.getLogger(__name__)
 

tests/model/test_multivi.py

@@ -1,14 +1,16 @@
+import os
+
+import anndata as ad
 import muon
 import numpy as np
 import pytest
-from mudata import MuData
 import scanpy as sc
-import anndata as ad
+from mudata import MuData
+
 import scvi
-import os
+from scvi import REGISTRY_KEYS
 from scvi.data import synthetic_iid
 from scvi.model import MULTIVI
-from scvi import REGISTRY_KEYS
 from scvi.utils import attrdict
 
 
@@ -145,13 +147,15 @@ def test_multivi_mudata_rna_atac_external():
         n_top_genes=4000,
         flavor="seurat_v3",
     )
-    mdata.mod["atac_subset"] = (mdata.mod["atac"][:, mdata.mod["atac"].var["highly_variable"]].
-                                copy())
+    mdata.mod["atac_subset"] = mdata.mod["atac"][
+        :, mdata.mod["atac"].var["highly_variable"]
+    ].copy()
     mdata.update()
     # mdata
     # mdata.mod
-    MULTIVI.setup_mudata(mdata, modalities={"rna_layer": "rna_subset",
-                                            "atac_layer": "atac_subset"})
+    MULTIVI.setup_mudata(
+        mdata, modalities={"rna_layer": "rna_subset", "atac_layer": "atac_subset"}
+    )
     model = MULTIVI(mdata, n_genes=50, n_regions=50)
     model.train(1, train_size=0.9)
 
@@ -178,8 +182,11 @@ def test_multivi_mudata():
     MULTIVI.setup_mudata(
         mdata,
         batch_key="batch",
-        modalities={"rna_layer": "rna", "protein_layer": "protein_expression",
-                    "atac_layer": "accessibility"},
+        modalities={
+            "rna_layer": "rna",
+            "protein_layer": "protein_expression",
+            "atac_layer": "accessibility",
+        },
     )
     n_obs = mdata.n_obs
     # n_genes = np.min([mdata.n_vars, mdata["protein_expression"].n_vars])
@@ -354,7 +361,7 @@ def test_multivi_size_factor_mudata():
     model.train(1, train_size=0.5)
 
 
-def test_multivi_saving_and_loading_mudata(save_path: str="."):
+def test_multivi_saving_and_loading_mudata(save_path: str = "."):
     adata = synthetic_iid()
     protein_adata = synthetic_iid(n_genes=50)
     mdata = MuData({"rna": adata, "protein": protein_adata})
@@ -415,7 +422,7 @@ def test_multivi_saving_and_loading_mudata(save_path: str="."):
     )
 
 
-def test_scarches_mudata_prep_layer(save_path: str="."):
+def test_scarches_mudata_prep_layer(save_path: str = "."):
     n_latent = 5
     mdata1 = synthetic_iid(return_mudata=True)
 
@@ -463,7 +470,7 @@ def test_scarches_mudata_prep_layer(save_path: str="."):
     MULTIVI.load_query_data(mdata2, dir_path)
 
 
-def test_multivi_save_load_mudata_format(save_path: str="."):
+def test_multivi_save_load_mudata_format(save_path: str = "."):
     mdata = synthetic_iid(return_mudata=True, protein_expression_key="protein")
     invalid_mdata = mdata.copy()
     invalid_mdata.mod["protein"] = invalid_mdata.mod["protein"][:, :10].copy()