formatting

setup.py

@@ -1,9 +1,9 @@
 from setuptools import setup, find_packages
 
 setup(
-    name='starling',
-    version='0.1.0',
-    url='https://github.com/camlab-bioml/starling',
+    name="starling",
+    version="0.1.0",
+    url="https://github.com/camlab-bioml/starling",
     project_urls={
         "Issues": "https://github.com/camlab-bioml/starling/issues",
         "Source": "https://github.com/camlab-bioml/starling",
@@ -12,18 +12,22 @@
     author_email="[email protected]",
     packages=find_packages(),
     package_dir={"starling": "starling"},
-    package_data={'': ['*.json', "*.html", "*.css"]},
+    package_data={"": ["*.json", "*.html", "*.css"]},
     include_package_data=True,
     description="",
     long_description=open("README.md").read(),
     long_description_content_type="text/markdown",
     keywords=["imaging cytometry classifier single-cell"],
     classifiers=[
         "Intended Audience :: Science/Research",
-        "Programming Language :: Python :: 3.8"
+        "Programming Language :: Python :: 3.8",
     ],
     license="MIT",
-    install_requires=["pip==23.2.1" "torch==1.12.1", "tensorflow==2.14.0", 
-                      "pytorch-lightning==2.1.0", "scanpy==1.9.5"],
+    install_requires=[
+        "pip==23.2.1" "torch==1.12.1",
+        "tensorflow==2.14.0",
+        "pytorch-lightning==2.1.0",
+        "scanpy==1.9.5",
+    ],
     python_requires=">=3.9.0",
 )

starling/starling.py

@@ -234,9 +234,9 @@ def result(self, threshold=0.5) -> None:
         # else:
         c = self.model_params["log_mu"].detach().exp().cpu().numpy()
         # v = self.model_params['log_sigma'].cpu().detach().exp().cpu().numpy()
-        self.adata.varm[
-            "st_exp_centroids"
-        ] = c.T  # pd.DataFrame(c, columns=self.adata.var_names)
+        self.adata.varm["st_exp_centroids"] = (
+            c.T
+        )  # pd.DataFrame(c, columns=self.adata.var_names)
 
         if self.model_cell_size:
             self.adata.uns["st_cell_size_centroids"] = (

starling/utility.py

@@ -7,7 +7,7 @@
 import torch
 from flowsom import flowsom
 from scanpy import AnnData
-from sklearn.cluster import KMeans, AgglomerativeClustering
+from sklearn.cluster import AgglomerativeClustering, KMeans
 from sklearn.mixture import GaussianMixture
 from torch.utils.data import DataLoader, Dataset
 

tests/test_starling.py

@@ -8,13 +8,15 @@ def test_can_instantiate(simple_adata_with_size):
     assert type(st.X) == torch.Tensor
     assert type(st.S) == torch.Tensor
 
+
 def test_can_instantiate_without_size(simple_adata):
     st = ST(simple_adata, model_cell_size=False)
     assert type(st.X) == torch.Tensor
     assert st.S is None
 
+
 def test_prepare_data(simple_adata_km_initialized):
     st = ST(simple_adata_km_initialized, model_cell_size=True)
-    assert getattr(st, 'model_params', None) is None
+    assert getattr(st, "model_params", None) is None
     st.prepare_data()
     assert st.model_params is not None