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‎docs/notebooks/spatial_data_kpmp_vis.ipynb‎

Lines changed: 48 additions & 163 deletions
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@@ -16,137 +16,13 @@
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"## Import dependencies\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"https://github.com/vitessce/vitessce/blob/main/examples/configs/src/view-configs/spatial-beta/kpmp.js"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from os.path import join"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"base_dir = join(\"..\", \"..\", \"..\", \"kpmp-f2f-march-2023\", \"S-1905-017737\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"sdata_path = join(base_dir, \"sdata.zarr\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from spatialdata import read_zarr, to_polygons"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"sdata = read_zarr(sdata_path)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"sdata"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"sdata.tables[\"table_tubules\"].var"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"sdata.tables[\"table_tubules\"].obs"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"sdata.tables[\"table_peritubular_capillaries\"].obs"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"sdata.tables[\"table_globally_sclerotic_glomeruli\"].obs"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"!ls {sdata_path}/images"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"!ls {sdata_path}/labels"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"!ls {sdata_path}/tables"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"!ls {sdata_path}/tables/table_cortical_interstitia/obs"
25+
"# Reference: https://github.com/vitessce/vitessce/blob/main/examples/configs/src/view-configs/spatial-beta/kpmp.js"
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]
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},
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{
@@ -168,7 +44,24 @@
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" get_initial_coordination_scope_prefix,\n",
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" hconcat,\n",
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" vconcat,\n",
171-
")"
47+
")\n",
48+
"from os.path import join"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Configure Vitessce"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"sdata_url = \"https://storage.googleapis.com/vitessce-demo-data/kpmp-f2f-march-2023/S-1905-017737/sdata.zarr\""
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]
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},
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{
@@ -180,17 +73,25 @@
18073
"# Create a VitessceConfig instance.\n",
18174
"vc = VitessceConfig(schema_version=\"1.0.17\", name=\"SpatialData\")\n",
18275
"\n",
76+
"t_obstype = \"Tubule\"\n",
77+
"a_obstype = \"Artery\"\n",
78+
"ci_obstype = \"Cortical Interstitium\"\n",
79+
"gsg_obstype = \"G. S. Glomerulus\"\n",
80+
"ngsg_obstype = \"Non-G. S. Glomerulus\"\n",
81+
"ifta_obstype = \"Interstitial Fibrosis and Tubular Atrophy\"\n",
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"ptc_obstype = \"Peritubular Capillaries\"\n",
83+
"\n",
18384
"# Add a new dataset to the Vitessce configuration,\n",
18485
"# then add the wrapper class instance to this dataset.\n",
18586
"dataset = vc.add_dataset(name='KPMP').add_object(\n",
18687
" SpatialDataWrapper(\n",
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" sdata_path=sdata_path,\n",
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" sdata_url=sdata_url,\n",
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" image_path=\"images/image\",\n",
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" coordinate_system=\"global\",\n",
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" )\n",
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").add_object(\n",
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" SpatialDataWrapper(\n",
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" sdata_path=sdata_path,\n",
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" sdata_url=sdata_url,\n",
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" table_path=\"tables/table_tubules\",\n",
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" labels_path=\"labels/labels_tubules\",\n",
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" obs_feature_matrix_path=\"tables/table_tubules/X\",\n",
@@ -201,14 +102,14 @@
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" coordinate_system=\"global\",\n",
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" coordination_values={\n",
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" \"fileUid\": \"labels_tubules\",\n",
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" \"obsType\": \"Tubule\",\n",
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" \"obsType\": t_obstype,\n",
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" \"featureType\": 'feature',\n",
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" \"featureValueType\": 'value',\n",
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" }\n",
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" )\n",
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").add_object(\n",
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" SpatialDataWrapper(\n",
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" sdata_path=sdata_path,\n",
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" sdata_url=sdata_url,\n",
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" labels_path=\"labels/labels_arteries_arterioles\",\n",
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" #obs_feature_matrix_path=\"tables/table/X\",\n",
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" #obs_set_paths=[\"tables/table/obs/annotation\"],\n",
@@ -217,14 +118,14 @@
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" coordinate_system=\"global\",\n",
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" coordination_values={\n",
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" \"fileUid\": \"labels_arteries_arterioles\",\n",
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" \"obsType\": \"Artery\",\n",
121+
" \"obsType\": a_obstype,\n",
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" \"featureType\": 'feature',\n",
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" \"featureValueType\": 'value',\n",
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" }\n",
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" )\n",
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").add_object(\n",
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" SpatialDataWrapper(\n",
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" sdata_path=sdata_path,\n",
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" sdata_url=sdata_url,\n",
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" table_path=\"tables/table_cortical_interstitia\",\n",
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" labels_path=\"labels/labels_cortical_interstitia\",\n",
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" obs_feature_matrix_path=\"tables/table_cortical_interstitia/X\",\n",
@@ -236,14 +137,14 @@
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" coordinate_system=\"global\",\n",
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" coordination_values={\n",
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" \"fileUid\": \"labels_cortical_interstitia\",\n",
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" \"obsType\": \"Cortical Interstitium\",\n",
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" \"obsType\": ci_obstype,\n",
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" \"featureType\": 'feature',\n",
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" \"featureValueType\": 'value',\n",
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" }\n",
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" )\n",
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").add_object(\n",
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" SpatialDataWrapper(\n",
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" sdata_path=sdata_path,\n",
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" sdata_url=sdata_url,\n",
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" table_path=\"tables/table_globally_sclerotic_glomeruli\",\n",
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" labels_path=\"labels/labels_globally_sclerotic_glomeruli\",\n",
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" obs_feature_matrix_path=\"tables/table_globally_sclerotic_glomeruli/X\",\n",
@@ -254,14 +155,14 @@
254155
" coordinate_system=\"global\",\n",
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" coordination_values={\n",
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" \"fileUid\": \"labels_globally_sclerotic_glomeruli\",\n",
257-
" \"obsType\": \"Globally Sclerotic Glomerulus\",\n",
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" \"obsType\": gsg_obstype,\n",
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" \"featureType\": 'feature',\n",
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" \"featureValueType\": 'value',\n",
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" }\n",
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" )\n",
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").add_object(\n",
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" SpatialDataWrapper(\n",
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" sdata_path=sdata_path,\n",
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" sdata_url=sdata_url,\n",
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" table_path=\"tables/table_non_globally_sclerotic_glomeruli\",\n",
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" labels_path=\"labels/labels_non_globally_sclerotic_glomeruli\",\n",
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" obs_feature_matrix_path=\"tables/table_non_globally_sclerotic_glomeruli/X\",\n",
@@ -272,14 +173,14 @@
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" coordinate_system=\"global\",\n",
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" coordination_values={\n",
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" \"fileUid\": \"labels_non_globally_sclerotic_glomeruli\",\n",
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" \"obsType\": \"Non-Globally Sclerotic Glomerulus\",\n",
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" \"obsType\": ngsg_obstype,\n",
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" \"featureType\": 'feature',\n",
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" \"featureValueType\": 'value',\n",
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" }\n",
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" )\n",
280181
").add_object(\n",
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" SpatialDataWrapper(\n",
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" sdata_path=sdata_path,\n",
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" sdata_url=sdata_url,\n",
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" table_path=\"tables/table_interstitialfibrosis_and_tubular_atrophy\",\n",
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" labels_path=\"labels/labels_interstitialfibrosis_and_tubular_atrophy\",\n",
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" #obs_feature_matrix_path=\"tables/table/X\",\n",
@@ -289,14 +190,14 @@
289190
" coordinate_system=\"global\",\n",
290191
" coordination_values={\n",
291192
" \"fileUid\": \"labels_interstitialfibrosis_and_tubular_atrophy\",\n",
292-
" \"obsType\": \"Interstitial Fibrosis and Tubular Atrophy\",\n",
193+
" \"obsType\": ifta_obstype,\n",
293194
" \"featureType\": 'feature',\n",
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" \"featureValueType\": 'value',\n",
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" }\n",
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" )\n",
297198
").add_object(\n",
298199
" SpatialDataWrapper(\n",
299-
" sdata_path=sdata_path,\n",
200+
" sdata_url=sdata_url,\n",
300201
" table_path=\"tables/table_peritubular_capillaries\",\n",
301202
" labels_path=\"labels/labels_peritubular_capillaries\",\n",
302203
" obs_feature_matrix_path=\"tables/table_peritubular_capillaries/X\",\n",
@@ -307,7 +208,7 @@
307208
" coordinate_system=\"global\",\n",
308209
" coordination_values={\n",
309210
" \"fileUid\": \"labels_peritubular_capillaries\",\n",
310-
" \"obsType\": \"Peritubular Capillaries\",\n",
211+
" \"obsType\": ptc_obstype,\n",
311212
" \"featureType\": 'feature',\n",
312213
" \"featureValueType\": 'value',\n",
313214
" }\n",
@@ -326,39 +227,34 @@
326227
"# GSG\n",
327228
"gsg_feature_list = vc.add_view(\"featureList\", dataset=dataset).set_props(title=\"Globally Sclerotic Glomeruli\")\n",
328229
"gsg_histogram = vc.add_view(\"featureValueHistogram\", dataset=dataset)\n",
329-
"\n",
330230
"# NGSG\n",
331231
"ngsg_feature_list = vc.add_view(\"featureList\", dataset=dataset).set_props(title=\"Non-Globally Sclerotic Glomeruli\")\n",
332232
"ngsg_histogram = vc.add_view(\"featureValueHistogram\", dataset=dataset)\n",
333233
"\n",
334-
"\n",
335-
"#obs_sets = vc.add_view(\"obsSets\", dataset=dataset)\n",
336-
"#heatmap = vc.add_view(\"heatmap\", dataset=dataset)\n",
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"\n",
234+
"# Coordination of views.\n",
338235
"[ft_scope, fvt_scope] = vc.add_coordination(\"featureType\", \"featureValueType\")\n",
339236
"ft_scope.set_value(\"feature\")\n",
340237
"fvt_scope.set_value(\"value\")\n",
341238
"\n",
342239
"[t_ot_scope, t_fs_scope, t_oce_scope] = vc.add_coordination(\"obsType\", \"featureSelection\", \"obsColorEncoding\")\n",
343-
"t_ot_scope.set_value(\"Tubule\")\n",
240+
"t_ot_scope.set_value(t_obstype)\n",
344241
"t_oce_scope.set_value(\"spatialChannelColor\")\n",
345242
"\n",
346243
"[pt_ot_scope, pt_fs_scope, pt_oce_scope] = vc.add_coordination(\"obsType\", \"featureSelection\", \"obsColorEncoding\")\n",
347-
"pt_ot_scope.set_value(\"Peritubular Capillaries\")\n",
244+
"pt_ot_scope.set_value(ptc_obstype)\n",
348245
"pt_oce_scope.set_value(\"spatialChannelColor\")\n",
349246
"\n",
350247
"\n",
351248
"[gsg_ot_scope, gsg_fs_scope, gsg_oce_scope, gsg_fvcr_scope] = vc.add_coordination(\"obsType\", \"featureSelection\", \"obsColorEncoding\", \"featureValueColormapRange\")\n",
352-
"gsg_ot_scope.set_value(\"Globally Sclerotic Glomerulus\")\n",
249+
"gsg_ot_scope.set_value(gsg_obstype)\n",
353250
"gsg_oce_scope.set_value(\"spatialChannelColor\")\n",
354251
"gsg_fvcr_scope.set_value([(3077 - 2333) / (29911 - 2333), 1.0])\n",
355252
"\n",
356253
"[ngsg_ot_scope, ngsg_fs_scope, ngsg_oce_scope, ngsg_fvcr_scope] = vc.add_coordination(\"obsType\", \"featureSelection\", \"obsColorEncoding\", \"featureValueColormapRange\")\n",
357-
"ngsg_ot_scope.set_value(\"Non-Globally Sclerotic Glomerulus\")\n",
254+
"ngsg_ot_scope.set_value(ngsg_obstype)\n",
358255
"ngsg_oce_scope.set_value(\"spatialChannelColor\")\n",
359256
"ngsg_fvcr_scope.set_value([0.0, 1 - (59451 - 29911) / (59451 - 3077)])\n",
360257
"\n",
361-
"\n",
362258
"vc.link_views_by_dict([spatial, layer_controller], {\n",
363259
" \"imageLayer\": CL([{\n",
364260
" \"photometricInterpretation\": \"RGB\",\n",
@@ -486,7 +382,6 @@
486382
" ]),\n",
487383
"}, meta=True, scope_prefix=get_initial_coordination_scope_prefix(\"A\", \"obsSegmentations\"))\n",
488384
"\n",
489-
"#vc.link_views([spatial, layer_controller, feature_list, obs_sets, heatmap], [], [])\n",
490385
"tubules_feature_list.use_coordination(t_ot_scope, ft_scope, fvt_scope, t_fs_scope, t_oce_scope)\n",
491386
"tubules_histogram.use_coordination(t_ot_scope, ft_scope, fvt_scope, t_fs_scope, t_oce_scope)\n",
492387
"\n",
@@ -509,16 +404,6 @@
509404
")));"
510405
]
511406
},
512-
{
513-
"cell_type": "code",
514-
"execution_count": null,
515-
"metadata": {},
516-
"outputs": [],
517-
"source": [
518-
"#import json\n",
519-
"#print(json.dumps(vc.to_dict(base_url=\"http://localhost:8003\")))"
520-
]
521-
},
522407
{
523408
"cell_type": "code",
524409
"execution_count": null,
@@ -527,7 +412,7 @@
527412
},
528413
"outputs": [],
529414
"source": [
530-
"vw = vc.widget(js_package_version=\"3.6.3\")\n",
415+
"vw = vc.widget(height=1000)\n",
531416
"vw"
532417
]
533418
},

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