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* Complex coordination port * Lint * Lint * Rename functions * Add docstrings for new functions * Lint * Implement link_views_by_dict
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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": { | ||
"nbsphinx": "hidden" | ||
}, | ||
"source": [ | ||
"# Vitessce Widget Tutorial" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"# Visualization of Multi-Modal Imaging Data\n", | ||
"We visualize IMS, PAS, and AF imaging data overlaid from the Spraggins Lab of the Biomolecular Multimodal Imaging Center (BIOMC) at Vanderbilt University, uploaded to the HuBMAP data portal." | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 1, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"from vitessce import (\n", | ||
" VitessceConfig,\n", | ||
" Component as cm,\n", | ||
" CoordinationType as ct,\n", | ||
" OmeTiffWrapper,\n", | ||
" MultiImageWrapper,\n", | ||
" CoordinationLevel as CL,\n", | ||
")\n", | ||
"from os.path import join" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"## 1. Configure Vitessce\n", | ||
"Set up the images from the three different assays, with the `use_physical_size_scaling` set to `True` so that the IMS image scales to the other images based on their physical sizes." | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 2, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"vc = VitessceConfig(schema_version=\"1.0.16\", name='Spraggins Multi-Modal', description='PAS + IMS + AF From https://portal.hubmapconsortium.org/browse/collection/6a6efd0c1a2681dc7d2faab8e4ab0bca')\n", | ||
"dataset = vc.add_dataset(name='Spraggins').add_file(\n", | ||
" url='https://assets.hubmapconsortium.org/f4188a148e4c759092d19369d310883b/ometiff-pyramids/processedMicroscopy/VAN0006-LK-2-85-PAS_images/VAN0006-LK-2-85-PAS_registered.ome.tif?token=',\n", | ||
" file_type=\"image.ome-tiff\",\n", | ||
" coordination_values={\n", | ||
" \"fileUid\": \"PAS\",\n", | ||
" },\n", | ||
")\n", | ||
"\n", | ||
"imageScopes = vc.add_coordination_by_dict({\n", | ||
" \"imageLayer\": CL([\n", | ||
" {\n", | ||
" \"fileUid\": 'PAS',\n", | ||
" \"spatialLayerOpacity\": 1,\n", | ||
" \"spatialLayerVisible\": True,\n", | ||
" \"photometricInterpretation\": 'RGB',\n", | ||
" \"imageChannel\": CL([\n", | ||
" {\n", | ||
" \"spatialTargetC\": 0,\n", | ||
" \"spatialChannelColor\": [255, 0, 0],\n", | ||
" \"spatialChannelVisible\": True,\n", | ||
" \"spatialChannelOpacity\": 1.0,\n", | ||
" \"spatialChannelWindow\": [0, 255],\n", | ||
" },\n", | ||
" {\n", | ||
" \"spatialTargetC\": 1,\n", | ||
" \"spatialChannelColor\": [0, 255, 0],\n", | ||
" \"spatialChannelVisible\": True,\n", | ||
" \"spatialChannelOpacity\": 1.0,\n", | ||
" \"spatialChannelWindow\": [0, 255],\n", | ||
" },\n", | ||
" {\n", | ||
" \"spatialTargetC\": 2,\n", | ||
" \"spatialChannelColor\": [0, 0, 255],\n", | ||
" \"spatialChannelVisible\": True,\n", | ||
" \"spatialChannelOpacity\": 1.0,\n", | ||
" \"spatialChannelWindow\": [0, 255],\n", | ||
" },\n", | ||
" ]),\n", | ||
" }\n", | ||
" ])\n", | ||
"})\n", | ||
"\n", | ||
"metaCoordinationScope = vc.add_meta_coordination()\n", | ||
"metaCoordinationScope.use_coordination_by_dict(imageScopes)\n", | ||
"\n", | ||
"spatial = vc.add_view(\"spatialBeta\", dataset=dataset)\n", | ||
"lc = vc.add_view(\"layerControllerBeta\", dataset=dataset)\n", | ||
"\n", | ||
"spatial.use_meta_coordination(metaCoordinationScope)\n", | ||
"lc.use_meta_coordination(metaCoordinationScope)\n", | ||
"\n", | ||
"vc.layout(spatial | lc);" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"## 2. Create the Vitessce widget" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 3, | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"data": { | ||
"application/vnd.jupyter.widget-view+json": { | ||
"model_id": "a5efa92286df4ad58cf94cfb3d12b703", | ||
"version_major": 2, | ||
"version_minor": 0 | ||
}, | ||
"text/plain": [ | ||
"VitessceWidget(config={'version': '1.0.16', 'name': 'Spraggins Multi-Modal', 'description': 'PAS + IMS + AF Fr…" | ||
] | ||
}, | ||
"execution_count": 3, | ||
"metadata": {}, | ||
"output_type": "execute_result" | ||
} | ||
], | ||
"source": [ | ||
"vw = vc.widget(custom_js_url='http://localhost:8000/packages/main/prod/dist/index.min.js')\n", | ||
"vw" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [] | ||
} | ||
], | ||
"metadata": { | ||
"kernelspec": { | ||
"display_name": "Python 3 (ipykernel)", | ||
"language": "python", | ||
"name": "python3" | ||
}, | ||
"language_info": { | ||
"codemirror_mode": { | ||
"name": "ipython", | ||
"version": 3 | ||
}, | ||
"file_extension": ".py", | ||
"mimetype": "text/x-python", | ||
"name": "python", | ||
"nbconvert_exporter": "python", | ||
"pygments_lexer": "ipython3", | ||
"version": "3.9.0" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 4 | ||
} |
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