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README.md

@@ -8,7 +8,6 @@
 
 Package for the analysis of transcripts outside segmented cells in python
 
-
 ![Alt text][images/logo_fish.png]
 
 ## Getting started
@@ -37,8 +36,8 @@ pip install troutpy
 pip install git+https://github.com/theislab/troutpy.git@main
 ```
 
-
 ## Usage
+
 Please have a look at the [Usage documentation](https://troutpy.readthedocs.io/en/latest/) and the [tutorials](https://troutpy.readthedocs.io/en/latest/).
 
 ```python

notebooks/spatialdata_tutorials/0_format_Xenium_sdata.ipynb

@@ -42,8 +42,9 @@
     }
    ],
    "source": [
-    "import spatialdata_io\n",
     "import spatialdata as sd\n",
+    "import spatialdata_io\n",
+    "\n",
     "import troutpy"
    ]
   },
@@ -244,7 +245,7 @@
    "outputs": [],
    "source": [
     "xenium_path_cropped = \"/media/sergio/Meninges/troutpy/xenium_msbrain/mousebrain_prime_crop_communication.zarr\"\n",
-    "sdata=sd.read_zarr(xenium_path_cropped)"
+    "sdata = sd.read_zarr(xenium_path_cropped)"
    ]
   },
   {
@@ -387,7 +388,7 @@
     }
    ],
    "source": [
-    "converted_sdata['transcripts']"
+    "converted_sdata[\"transcripts\"]"
    ]
   },
   {

notebooks/spatialdata_tutorials/1_segmentation.ipynb

@@ -40,7 +40,7 @@
    "source": [
     "import scanpy as sc\n",
     "import sopa\n",
-    "import spatialdata as sd\n"
+    "import spatialdata as sd"
    ]
   },
   {

notebooks/spatialdata_tutorials/2_run_segmentation_free.ipynb

@@ -41,6 +41,7 @@
    ],
    "source": [
     "import spatialdata as sd\n",
+    "\n",
     "import troutpy"
    ]
   },
@@ -332,9 +333,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "troutpy.pp.segmentation_free_sainsc(sdata,binsize=3,celltype_key='leiden',\n",
-    "                                    background_filter=0.4,gaussian_kernel_key=2.5,\n",
-    "                                    n_threads=16)"
+    "troutpy.pp.segmentation_free_sainsc(sdata, binsize=3, celltype_key=\"leiden\", background_filter=0.4, gaussian_kernel_key=2.5, n_threads=16)"
    ]
   },
   {
@@ -352,10 +351,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "troutpy.pp.define_extracellular(\n",
-    "    sdata,layer = \"transcripts\",method= \"sainsc\",\n",
-    "    unassigned_tag = \"UNASSIGNED\",\n",
-    "    copy = False, percentile_threshold = 2)"
+    "troutpy.pp.define_extracellular(sdata, layer=\"transcripts\", method=\"sainsc\", unassigned_tag=\"UNASSIGNED\", copy=False, percentile_threshold=2)"
    ]
   },
   {
@@ -383,7 +379,7 @@
     }
    ],
    "source": [
-    "troutpy.pl.pie(sdata, groupby=\"extracellular\",group_key='overlaps_cell')"
+    "troutpy.pl.pie(sdata, groupby=\"extracellular\", group_key=\"overlaps_cell\")"
    ]
   },
   {
@@ -412,7 +408,7 @@
     }
    ],
    "source": [
-    "troutpy.pl.crosstab(sdata,yvar='extracellular',xvar='overlaps_cell',normalize=True, cmap='troutpy',kind='barh',stacked=True)"
+    "troutpy.pl.crosstab(sdata, yvar=\"extracellular\", xvar=\"overlaps_cell\", normalize=True, cmap=\"troutpy\", kind=\"barh\", stacked=True)"
    ]
   },
   {
@@ -432,7 +428,7 @@
     }
    ],
    "source": [
-    "troutpy.pl.crosstab(sdata,yvar='extracellular',xvar='overlaps_cell',normalize=True, cmap='Aquas',kind='heatmap',stacked=True)"
+    "troutpy.pl.crosstab(sdata, yvar=\"extracellular\", xvar=\"overlaps_cell\", normalize=True, cmap=\"Aquas\", kind=\"heatmap\", stacked=True)"
    ]
   }
  ],