Merge pull request #200 from scverse/pc_fix

Fixed precomit issues

Author: PauBadiaM

docs/conf.py

@@ -97,7 +97,7 @@
     "scanpy": ("https://scanpy.readthedocs.io/en/stable/", None),
     "numpy": ("https://numpy.org/doc/stable/", None),
     "matplotlib": ("https://matplotlib.org/stable/", None),
-    'pandas': ('https://pandas.pydata.org/pandas-docs/stable/', None),
+    "pandas": ("https://pandas.pydata.org/pandas-docs/stable/", None),
 }
 
 # List of patterns, relative to source directory, that match files and
@@ -115,8 +115,8 @@
 html_static_path = ["_static"]
 html_css_files = ["css/custom.css"]
 html_title = project_name
-html_logo = '_static/images/logo.png'
-html_favicon = '_static/images/logo.png'
+html_logo = "_static/images/logo.png"
+html_favicon = "_static/images/logo.png"
 
 html_theme_options = {
     "repository_url": repository_url,

docs/notebooks/bench/rna.ipynb

@@ -406,18 +406,14 @@
    "outputs": [],
    "source": [
     "def random(x, w):\n",
+    "    \"\"\"Random baseline method\"\"\"\n",
     "    return np.random.rand(1)[0]\n",
     "\n",
+    "\n",
     "df = dc.bm.benchmark(\n",
     "    adata=adata,\n",
     "    net=net,\n",
-    "    kws_decouple={\n",
-    "        'cons': True,\n",
-    "        'tmin': 3,\n",
-    "        'args':{\n",
-    "            'waggr': {'fun': random}\n",
-    "        }\n",
-    "    },\n",
+    "    kws_decouple={\"cons\": True, \"tmin\": 3, \"args\": {\"waggr\": {\"fun\": random}}},\n",
     ")"
    ]
   },
@@ -578,7 +574,7 @@
     }
    ],
    "source": [
-    "dc.bm.pl.auc(df, hue='method')"
+    "dc.bm.pl.auc(df, hue=\"method\")"
    ]
   },
   {
@@ -614,7 +610,7 @@
     }
    ],
    "source": [
-    "dc.bm.pl.fscore(df, hue='method')"
+    "dc.bm.pl.fscore(df, hue=\"method\")"
    ]
   },
   {
@@ -650,7 +646,7 @@
     }
    ],
    "source": [
-    "dc.bm.pl.qrank(df, hue='method')"
+    "dc.bm.pl.qrank(df, hue=\"method\")"
    ]
   },
   {
@@ -968,9 +964,9 @@
     }
    ],
    "source": [
-    "dc.bm.pl.bar(df=hdf, x='H(auroc, auprc)', y='method', hue='method')\n",
-    "dc.bm.pl.bar(df=hdf, x='F-score', y='method', hue='method')\n",
-    "dc.bm.pl.bar(df=hdf, x='H(1-qrank, -log10(pval))', y='method', hue='method')"
+    "dc.bm.pl.bar(df=hdf, x=\"H(auroc, auprc)\", y=\"method\", hue=\"method\")\n",
+    "dc.bm.pl.bar(df=hdf, x=\"F-score\", y=\"method\", hue=\"method\")\n",
+    "dc.bm.pl.bar(df=hdf, x=\"H(1-qrank, -log10(pval))\", y=\"method\", hue=\"method\")"
    ]
   },
   {
@@ -1000,7 +996,7 @@
     }
    ],
    "source": [
-    "dc.bm.pl.summary(df=hdf, y='method', figsize=(6, 3))"
+    "dc.bm.pl.summary(df=hdf, y=\"method\", figsize=(6, 3))"
    ]
   },
   {
@@ -1644,8 +1640,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "unw_ct = ct.drop(columns='weight')\n",
-    "unw_do = do.drop(columns='weight')"
+    "unw_ct = ct.drop(columns=\"weight\")\n",
+    "unw_do = do.drop(columns=\"weight\")"
    ]
   },
   {
@@ -1667,15 +1663,15 @@
     "df = dc.bm.benchmark(\n",
     "    adata=adata,\n",
     "    net={\n",
-    "        'collectri': ct,\n",
-    "        'dorothea': do,\n",
-    "        'unw_collectri': unw_ct,\n",
-    "        'unw_dorothea': unw_do,\n",
-    "        'r_collectri': rct,\n",
-    "        'r_dorothea': rdo,\n",
+    "        \"collectri\": ct,\n",
+    "        \"dorothea\": do,\n",
+    "        \"unw_collectri\": unw_ct,\n",
+    "        \"unw_dorothea\": unw_do,\n",
+    "        \"r_collectri\": rct,\n",
+    "        \"r_dorothea\": rdo,\n",
     "    },\n",
     "    kws_decouple={\n",
-    "        'methods': 'ulm',\n",
+    "        \"methods\": \"ulm\",\n",
     "    },\n",
     ")"
    ]
@@ -1897,7 +1893,7 @@
     }
    ],
    "source": [
-    "dc.bm.pl.auc(df, hue='net')"
+    "dc.bm.pl.auc(df, hue=\"net\")"
    ]
   },
   {
@@ -1926,7 +1922,7 @@
     }
    ],
    "source": [
-    "dc.bm.pl.fscore(df, hue='net')"
+    "dc.bm.pl.fscore(df, hue=\"net\")"
    ]
   },
   {
@@ -1955,7 +1951,7 @@
     }
    ],
    "source": [
-    "dc.bm.pl.qrank(df, hue='net')"
+    "dc.bm.pl.qrank(df, hue=\"net\")"
    ]
   },
   {
@@ -2172,9 +2168,9 @@
     }
    ],
    "source": [
-    "dc.bm.pl.bar(df=hdf, x='H(auroc, auprc)', y='net', hue='net')\n",
-    "dc.bm.pl.bar(df=hdf, x='F-score', y='net', hue='net')\n",
-    "dc.bm.pl.bar(df=hdf, x='H(1-qrank, -log10(pval))', y='net', hue='net')"
+    "dc.bm.pl.bar(df=hdf, x=\"H(auroc, auprc)\", y=\"net\", hue=\"net\")\n",
+    "dc.bm.pl.bar(df=hdf, x=\"F-score\", y=\"net\", hue=\"net\")\n",
+    "dc.bm.pl.bar(df=hdf, x=\"H(1-qrank, -log10(pval))\", y=\"net\", hue=\"net\")"
    ]
   },
   {
@@ -2204,7 +2200,7 @@
     }
    ],
    "source": [
-    "dc.bm.pl.summary(df=hdf, y='net', figsize=(7, 3))"
+    "dc.bm.pl.summary(df=hdf, y=\"net\", figsize=(7, 3))"
    ]
   },
   {