|
| 1 | +{ |
| 2 | + "cells": [ |
| 3 | + { |
| 4 | + "cell_type": "markdown", |
| 5 | + "metadata": { |
| 6 | + "nbsphinx": "hidden" |
| 7 | + }, |
| 8 | + "source": [ |
| 9 | + "# Vitessce Widget Tutorial" |
| 10 | + ] |
| 11 | + }, |
| 12 | + { |
| 13 | + "cell_type": "markdown", |
| 14 | + "metadata": {}, |
| 15 | + "source": [ |
| 16 | + "# Visualization of Multi-Modal Imaging Data\n", |
| 17 | + "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." |
| 18 | + ] |
| 19 | + }, |
| 20 | + { |
| 21 | + "cell_type": "code", |
| 22 | + "execution_count": 1, |
| 23 | + "metadata": {}, |
| 24 | + "outputs": [], |
| 25 | + "source": [ |
| 26 | + "from vitessce import (\n", |
| 27 | + " VitessceConfig,\n", |
| 28 | + " Component as cm,\n", |
| 29 | + " CoordinationType as ct,\n", |
| 30 | + " OmeTiffWrapper,\n", |
| 31 | + " MultiImageWrapper,\n", |
| 32 | + " CoordinationLevel as CL,\n", |
| 33 | + ")\n", |
| 34 | + "from os.path import join" |
| 35 | + ] |
| 36 | + }, |
| 37 | + { |
| 38 | + "cell_type": "markdown", |
| 39 | + "metadata": {}, |
| 40 | + "source": [ |
| 41 | + "## 1. Configure Vitessce\n", |
| 42 | + "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." |
| 43 | + ] |
| 44 | + }, |
| 45 | + { |
| 46 | + "cell_type": "code", |
| 47 | + "execution_count": 2, |
| 48 | + "metadata": {}, |
| 49 | + "outputs": [], |
| 50 | + "source": [ |
| 51 | + "vc = VitessceConfig(schema_version=\"1.0.16\", name='Spraggins Multi-Modal', description='PAS + IMS + AF From https://portal.hubmapconsortium.org/browse/collection/6a6efd0c1a2681dc7d2faab8e4ab0bca')\n", |
| 52 | + "dataset = vc.add_dataset(name='Spraggins').add_file(\n", |
| 53 | + " 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", |
| 54 | + " file_type=\"image.ome-tiff\",\n", |
| 55 | + " coordination_values={\n", |
| 56 | + " \"fileUid\": \"PAS\",\n", |
| 57 | + " },\n", |
| 58 | + ")\n", |
| 59 | + "\n", |
| 60 | + "imageScopes = vc.add_coordination_by_dict({\n", |
| 61 | + " \"imageLayer\": CL([\n", |
| 62 | + " {\n", |
| 63 | + " \"fileUid\": 'PAS',\n", |
| 64 | + " \"spatialLayerOpacity\": 1,\n", |
| 65 | + " \"spatialLayerVisible\": True,\n", |
| 66 | + " \"photometricInterpretation\": 'RGB',\n", |
| 67 | + " \"imageChannel\": CL([\n", |
| 68 | + " {\n", |
| 69 | + " \"spatialTargetC\": 0,\n", |
| 70 | + " \"spatialChannelColor\": [255, 0, 0],\n", |
| 71 | + " \"spatialChannelVisible\": True,\n", |
| 72 | + " \"spatialChannelOpacity\": 1.0,\n", |
| 73 | + " \"spatialChannelWindow\": [0, 255],\n", |
| 74 | + " },\n", |
| 75 | + " {\n", |
| 76 | + " \"spatialTargetC\": 1,\n", |
| 77 | + " \"spatialChannelColor\": [0, 255, 0],\n", |
| 78 | + " \"spatialChannelVisible\": True,\n", |
| 79 | + " \"spatialChannelOpacity\": 1.0,\n", |
| 80 | + " \"spatialChannelWindow\": [0, 255],\n", |
| 81 | + " },\n", |
| 82 | + " {\n", |
| 83 | + " \"spatialTargetC\": 2,\n", |
| 84 | + " \"spatialChannelColor\": [0, 0, 255],\n", |
| 85 | + " \"spatialChannelVisible\": True,\n", |
| 86 | + " \"spatialChannelOpacity\": 1.0,\n", |
| 87 | + " \"spatialChannelWindow\": [0, 255],\n", |
| 88 | + " },\n", |
| 89 | + " ]),\n", |
| 90 | + " }\n", |
| 91 | + " ])\n", |
| 92 | + "})\n", |
| 93 | + "\n", |
| 94 | + "metaCoordinationScope = vc.add_meta_coordination()\n", |
| 95 | + "metaCoordinationScope.use_coordination_by_dict(imageScopes)\n", |
| 96 | + "\n", |
| 97 | + "spatial = vc.add_view(\"spatialBeta\", dataset=dataset)\n", |
| 98 | + "lc = vc.add_view(\"layerControllerBeta\", dataset=dataset)\n", |
| 99 | + "\n", |
| 100 | + "spatial.use_meta_coordination(metaCoordinationScope)\n", |
| 101 | + "lc.use_meta_coordination(metaCoordinationScope)\n", |
| 102 | + "\n", |
| 103 | + "vc.layout(spatial | lc);" |
| 104 | + ] |
| 105 | + }, |
| 106 | + { |
| 107 | + "cell_type": "markdown", |
| 108 | + "metadata": {}, |
| 109 | + "source": [ |
| 110 | + "## 2. Create the Vitessce widget" |
| 111 | + ] |
| 112 | + }, |
| 113 | + { |
| 114 | + "cell_type": "code", |
| 115 | + "execution_count": 3, |
| 116 | + "metadata": {}, |
| 117 | + "outputs": [ |
| 118 | + { |
| 119 | + "data": { |
| 120 | + "application/vnd.jupyter.widget-view+json": { |
| 121 | + "model_id": "a5efa92286df4ad58cf94cfb3d12b703", |
| 122 | + "version_major": 2, |
| 123 | + "version_minor": 0 |
| 124 | + }, |
| 125 | + "text/plain": [ |
| 126 | + "VitessceWidget(config={'version': '1.0.16', 'name': 'Spraggins Multi-Modal', 'description': 'PAS + IMS + AF Fr…" |
| 127 | + ] |
| 128 | + }, |
| 129 | + "execution_count": 3, |
| 130 | + "metadata": {}, |
| 131 | + "output_type": "execute_result" |
| 132 | + } |
| 133 | + ], |
| 134 | + "source": [ |
| 135 | + "vw = vc.widget(custom_js_url='http://localhost:8000/packages/main/prod/dist/index.min.js')\n", |
| 136 | + "vw" |
| 137 | + ] |
| 138 | + }, |
| 139 | + { |
| 140 | + "cell_type": "code", |
| 141 | + "execution_count": null, |
| 142 | + "metadata": {}, |
| 143 | + "outputs": [], |
| 144 | + "source": [] |
| 145 | + } |
| 146 | + ], |
| 147 | + "metadata": { |
| 148 | + "kernelspec": { |
| 149 | + "display_name": "Python 3 (ipykernel)", |
| 150 | + "language": "python", |
| 151 | + "name": "python3" |
| 152 | + }, |
| 153 | + "language_info": { |
| 154 | + "codemirror_mode": { |
| 155 | + "name": "ipython", |
| 156 | + "version": 3 |
| 157 | + }, |
| 158 | + "file_extension": ".py", |
| 159 | + "mimetype": "text/x-python", |
| 160 | + "name": "python", |
| 161 | + "nbconvert_exporter": "python", |
| 162 | + "pygments_lexer": "ipython3", |
| 163 | + "version": "3.9.0" |
| 164 | + } |
| 165 | + }, |
| 166 | + "nbformat": 4, |
| 167 | + "nbformat_minor": 4 |
| 168 | +} |
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