docs: format ipynb with ruff

pycytominer/__about__.py

@@ -1,4 +1,5 @@
 """Pycytominer package metadata."""
+
 __project__ = "pycytominer"
 # These version placeholders are updated during build by poetry-dynamic-versioning
 __version__ = "0.0.0"

pycytominer/__init__.py

@@ -1,4 +1,5 @@
 """Pycytominer is a suite of common functions used to process high dimensional readouts from high-throughput cell experiments."""
+
 from pycytominer import __about__
 
 from .aggregate import aggregate

pycytominer/cyto_utils/cells.py

@@ -914,13 +914,17 @@ def _sqlite_strata_conditions(df, dtypes, n=1):
         [3]         | [1, 2]
         [4]         | [1]
 
-    >>> _sqlite_strata_conditions(df, dtypes={'TableNumber': 'integer', 'ImageNumber': 'integer'}, n=1)
+    >>> _sqlite_strata_conditions(
+    ...     df, dtypes={"TableNumber": "integer", "ImageNumber": "integer"}, n=1
+    ... )
     ["(TableNumber in (1) and ImageNumber in (1))",
      "(TableNumber in (2) and ImageNumber in (1, 2, 3))",
      "(TableNumber in (3) and ImageNumber in (1, 2))",
      "(TableNumber in (4) and ImageNumber in (1))"]
 
-    >>> _sqlite_strata_conditions(df, dtypes={'TableNumber': 'text', 'ImageNumber': 'integer'}, n=2)
+    >>> _sqlite_strata_conditions(
+    ...     df, dtypes={"TableNumber": "text", "ImageNumber": "integer"}, n=2
+    ... )
     ["(TableNumber in ('1') and ImageNumber in (1))
       or (TableNumber in ('2') and ImageNumber in (1, 2, 3))",
      "(TableNumber in ('3') and ImageNumber in (1, 2))

pyproject.toml

@@ -117,6 +117,7 @@ version_files = [
 target-version = "py38"
 line-length = 88
 fix = true
+extend-include = ["*.ipynb"]
 
 [tool.ruff.lint]
 select = [
@@ -160,6 +161,7 @@ ignore = [
     # DoNotAssignLambda
     "E731",
 ]
+exclude = ["*.ipynb"]
 
 [tool.ruff.lint.pydocstyle]
 # Use Google-style docstrings.

walkthroughs/single_cell_usage.ipynb

@@ -35,7 +35,7 @@
     "# ignore mix type warnings from pandas\n",
     "import warnings\n",
     "\n",
-    "warnings.filterwarnings(\"ignore\")\n"
+    "warnings.filterwarnings(\"ignore\")"
    ]
   },
   {
@@ -86,7 +86,7 @@
     "sc_profiles_path = out_dir / \"nf1_single_cell_profile.csv.gz\"\n",
     "anno_profiles_path = out_dir / \"nf1_annotated_profile.csv.gz\"\n",
     "norm_profiles_path = out_dir / \"nf1_normalized_profile.csv.gz\"\n",
-    "feat_profiles_path = out_dir / \"nf1_features_profile.csv.gz\"\n"
+    "feat_profiles_path = out_dir / \"nf1_features_profile.csv.gz\""
    ]
   },
   {
@@ -128,7 +128,7 @@
     "    },\n",
     "    \"Per_Cells\": {\"Per_Cytoplasm\": \"Cells_Number_Object_Number\"},\n",
     "    \"Per_Nuclei\": {\"Per_Cytoplasm\": \"Nuclei_Number_Object_Number\"},\n",
-    "}\n"
+    "}"
    ]
   },
   {
@@ -177,7 +177,7 @@
     "# compressed csv file\n",
     "single_cell_profile.merge_single_cells(\n",
     "    sc_output_file=sc_profiles_path, compression_options=\"gzip\"\n",
-    ")\n"
+    ")"
    ]
   },
   {
@@ -208,7 +208,7 @@
     "platemap_df = pd.read_csv(plate_map)\n",
     "\n",
     "# displaying platemap\n",
-    "print(platemap_df.columns.tolist())\n"
+    "print(platemap_df.columns.tolist())"
    ]
   },
   {
@@ -249,7 +249,7 @@
     ")\n",
     "\n",
     "# save message display\n",
-    "print(f\"Annotated profile saved in: {anno_profiles_path}\")\n"
+    "print(f\"Annotated profile saved in: {anno_profiles_path}\")"
    ]
   },
   {
@@ -296,7 +296,7 @@
     ")\n",
     "\n",
     "# save message display\n",
-    "print(f\"Normalized profile saved in: {norm_profiles_path}\")\n"
+    "print(f\"Normalized profile saved in: {norm_profiles_path}\")"
    ]
   },
   {
@@ -341,7 +341,7 @@
     ")\n",
     "\n",
     "# save message display\n",
-    "print(f\"Selected features profile saved in: {feat_profiles_path}\")\n"
+    "print(f\"Selected features profile saved in: {feat_profiles_path}\")"
    ]
   },
   {