Merge pull request #56 from scverse/fix/remove_napari

Author: LucaMarconato

conf.py

@@ -131,6 +131,7 @@
 html_theme_options = {
     "repository_url": repository_url,
     "use_repository_button": True,
+    "navigation_with_keys": True,
 }
 
 pygments_style = "default"

notebooks/examples/aggregation.ipynb

@@ -1183,7 +1183,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.10.12"
   },
   "vscode": {
    "interpreter": {

notebooks/examples/alignment_using_landmarks.ipynb

@@ -48,28 +48,12 @@
     },
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/macbook/miniconda3/envs/ome/lib/python3.10/site-packages/geopandas/_compat.py:123: UserWarning: The Shapely GEOS version (3.11.1-CAPI-1.17.1) is incompatible with the GEOS version PyGEOS was compiled with (3.10.4-CAPI-1.16.2). Conversions between both will be slow.\n",
-      "  warnings.warn(\n",
-      "/Users/macbook/embl/projects/basel/spatialdata/src/spatialdata/__init__.py:9: UserWarning: Geopandas was set to use PyGEOS, changing to shapely 2.0 with:\n",
-      "\n",
-      "\tgeopandas.options.use_pygeos = True\n",
-      "\n",
-      "If you intended to use PyGEOS, set the option to False.\n",
-      "  _check_geopandas_using_shapely()\n",
-      "/Users/macbook/miniconda3/envs/ome/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
-      "  from .autonotebook import tqdm as notebook_tqdm\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import numpy as np\n",
     "import spatialdata as sd\n",
-    "from napari_spatialdata import Interactive"
+    "\n",
+    "# from napari_spatialdata import Interactive"
    ]
   },
   {
@@ -85,10 +69,11 @@
    },
    "outputs": [
     {
-     "name": "stdout",
+     "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\u001b[34mINFO    \u001b[0m Instance key `cell_id` could be of type `pd.Categorical`. Consider casting it.                            \n"
+      "/Users/macbook/miniconda3/envs/ome/lib/python3.10/site-packages/anndata/_core/anndata.py:183: ImplicitModificationWarning: Transforming to str index.\n",
+      "  warnings.warn(\"Transforming to str index.\", ImplicitModificationWarning)\n"
      ]
     },
     {
@@ -99,24 +84,23 @@
        "│     ├── 'morphology_focus': MultiscaleSpatialImage[cyx] (1, 25778, 35416), (1, 12889, 17708), (1, 6444, 8854), (1, 3222, 4427), (1, 1611, 2213)\n",
        "│     └── 'morphology_mip': MultiscaleSpatialImage[cyx] (1, 25778, 35416), (1, 12889, 17708), (1, 6444, 8854), (1, 3222, 4427), (1, 1611, 2213)\n",
        "├── Points\n",
-       "│     └── 'transcripts': DataFrame with shape: (42638083, 9) (3D points)\n",
+       "│     └── 'transcripts': DataFrame with shape: (42638083, 8) (3D points)\n",
        "├── Shapes\n",
        "│     ├── 'cell_boundaries': GeoDataFrame shape: (167780, 1) (2D shapes)\n",
        "│     ├── 'cell_circles': GeoDataFrame shape: (167780, 2) (2D shapes)\n",
        "│     ├── 'nucleus_boundaries': GeoDataFrame shape: (167780, 1) (2D shapes)\n",
-       "│     ├── 'visium_landmarks': GeoDataFrame shape: (3, 2) (2D shapes)\n",
        "│     └── 'xenium_landmarks': GeoDataFrame shape: (3, 2) (2D shapes)\n",
        "└── Table\n",
        "      └── AnnData object with n_obs × n_vars = 167780 × 313\n",
-       "    obs: 'cell_id', 'transcript_counts', 'control_probe_counts', 'control_codeword_counts', 'total_counts', 'cell_area', 'nucleus_area', 'region', 'dataset', 'celltype_major', 'celltype_minor'\n",
+       "    obs: 'cell_id', 'transcript_counts', 'control_probe_counts', 'control_codeword_counts', 'total_counts', 'cell_area', 'nucleus_area', 'region'\n",
        "    var: 'gene_ids', 'feature_types', 'genome'\n",
        "    uns: 'spatialdata_attrs'\n",
        "    obsm: 'spatial': AnnData (167780, 313)\n",
        "with coordinate systems:\n",
        "▸ 'aligned', with elements:\n",
-       "        morphology_focus (Images), morphology_mip (Images), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), nucleus_boundaries (Shapes)\n",
+       "        morphology_mip (Images)\n",
        "▸ 'global', with elements:\n",
-       "        morphology_focus (Images), morphology_mip (Images), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), nucleus_boundaries (Shapes), visium_landmarks (Shapes), xenium_landmarks (Shapes)"
+       "        morphology_focus (Images), morphology_mip (Images), transcripts (Points), cell_boundaries (Shapes), cell_circles (Shapes), nucleus_boundaries (Shapes), xenium_landmarks (Shapes)"
       ]
      },
      "execution_count": 2,
@@ -149,23 +133,27 @@
        "│     ├── 'CytAssist_FFPE_Human_Breast_Cancer_full_image': MultiscaleSpatialImage[cyx] (3, 21571, 19505), (3, 10785, 9752), (3, 5392, 4876), (3, 2696, 2438), (3, 1348, 1219)\n",
        "│     ├── 'CytAssist_FFPE_Human_Breast_Cancer_hires_image': SpatialImage[cyx] (3, 2000, 1809)\n",
        "│     └── 'CytAssist_FFPE_Human_Breast_Cancer_lowres_image': SpatialImage[cyx] (3, 600, 543)\n",
+       "├── Points\n",
+       "│     ├── 'Points': DataFrame with shape: (3, 2) (2D points)\n",
+       "│     └── 'Points_1': DataFrame with shape: (1, 2) (2D points)\n",
        "├── Shapes\n",
-       "│     └── 'CytAssist_FFPE_Human_Breast_Cancer': GeoDataFrame shape: (4992, 2) (2D shapes)\n",
+       "│     ├── 'CytAssist_FFPE_Human_Breast_Cancer': GeoDataFrame shape: (4992, 2) (2D shapes)\n",
+       "│     └── 'visium_landmarks': GeoDataFrame shape: (3, 2) (2D shapes)\n",
        "└── Table\n",
        "      └── AnnData object with n_obs × n_vars = 4992 × 18085\n",
        "    obs: 'in_tissue', 'array_row', 'array_col', 'spot_id', 'region', 'dataset', 'clone'\n",
        "    var: 'gene_ids', 'feature_types', 'genome'\n",
-       "    uns: 'clone_colors', 'region_colors', 'spatial', 'spatialdata_attrs'\n",
+       "    uns: 'spatial', 'spatialdata_attrs'\n",
        "    obsm: 'spatial': AnnData (4992, 18085)\n",
        "with coordinate systems:\n",
        "▸ 'aligned', with elements:\n",
-       "        CytAssist_FFPE_Human_Breast_Cancer_full_image (Images), CytAssist_FFPE_Human_Breast_Cancer (Shapes)\n",
+       "        CytAssist_FFPE_Human_Breast_Cancer_full_image (Images), Points (Points), Points_1 (Points), CytAssist_FFPE_Human_Breast_Cancer (Shapes), visium_landmarks (Shapes)\n",
        "▸ 'downscaled_hires', with elements:\n",
        "        CytAssist_FFPE_Human_Breast_Cancer_hires_image (Images), CytAssist_FFPE_Human_Breast_Cancer (Shapes)\n",
        "▸ 'downscaled_lowres', with elements:\n",
        "        CytAssist_FFPE_Human_Breast_Cancer_lowres_image (Images), CytAssist_FFPE_Human_Breast_Cancer (Shapes)\n",
        "▸ 'global', with elements:\n",
-       "        CytAssist_FFPE_Human_Breast_Cancer_full_image (Images), CytAssist_FFPE_Human_Breast_Cancer (Shapes)"
+       "        CytAssist_FFPE_Human_Breast_Cancer_full_image (Images), CytAssist_FFPE_Human_Breast_Cancer (Shapes), visium_landmarks (Shapes)"
       ]
      },
      "execution_count": 3,
@@ -196,6 +184,7 @@
      "end_time": "2023-04-10T18:59:26.909684Z",
      "start_time": "2023-04-10T18:59:25.642148Z"
     },
+    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -254,7 +243,7 @@
    "id": "5890a6dc",
    "metadata": {},
    "source": [
-    "For reproducibility, we hardcoded in this notebook the landmark annotations for the Visium and Xenium data. We will add them to the respective `SpatialData` objects, as if they were were saved with napari."
+    "For reproducibility, we hardcoded in this notebook the landmark annotations for the Visium and Xenium data. We will add them to the respective `SpatialData` objects, both in-memory and on-disk, as if they were were saved with napari."
    ]
   },
   {
@@ -275,12 +264,12 @@
     "visium_landmarks = ShapesModel.parse(\n",
     "    np.array([[10556.699, 7829.764], [13959.155, 13522.025], [10621.200, 17392.116]]), geometry=0, radius=500\n",
     ")\n",
-    "visium_sdata.shapes[\"visium_landmarks\"] = visium_landmarks\n",
+    "visium_sdata.add_shapes(\"visium_landmarks\", visium_landmarks, overwrite=True)\n",
     "\n",
     "xenium_landmarks = ShapesModel.parse(\n",
     "    np.array([[9438.385, 13933.017], [24847.866, 5948.002], [34082.584, 15234.235]]), geometry=0, radius=500\n",
     ")\n",
-    "xenium_sdata.shapes[\"xenium_landmarks\"] = xenium_landmarks"
+    "xenium_sdata.add_shapes(\"xenium_landmarks\", xenium_landmarks, overwrite=True)"
    ]
   },
   {
@@ -444,7 +433,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "id": "5c442fdb-94a9-488c-8d87-cfcc109f9388",
    "metadata": {
     "tags": []
@@ -528,22 +517,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "id": "076fa9b5-452e-4228-994c-f4be656b9d6b",
+   "execution_count": 8,
+   "id": "474410bd-2d02-45c1-b073-eba1152ab615",
    "metadata": {
     "tags": []
    },
    "outputs": [],
    "source": [
     "from spatialdata import save_transformations\n",
     "\n",
-    "save_transformations(visium_sdata)"
+    "save_transformations(visium_sdata)\n",
+    "save_transformations(xenium_sdata)"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "base",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -557,7 +547,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.8 | packaged by conda-forge | (main, Nov 22 2022, 08:25:13) [Clang 14.0.6 ]"
+   "version": "3.10.12"
   },
   "vscode": {
    "interpreter": {