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BUG: Update vedo notebook for package name change from vtkplotter
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‎README.rst‎

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@@ -49,7 +49,7 @@ Interactive Jupyter_ widgets to visualize images, point sets, and meshes on the
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- `Dask array <https://docs.dask.org/en/latest/array.html>`_ images
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- `vtk.vtkImageData <https://vtk.org>`_
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- `pyvista.UniformGrid <https://pyvista.org>`_
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- `vtkplotter.Volume <https://vtkplotter.embl.es/index.html>`_
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- `vedo.Volume <https://vedo.embl.es/index.html>`_
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- `pyimagej ImageJ / Fiji / ImageJ2 images <https://github.com/imagej/pyimagej>`_
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- Additional NumPy array-like objects
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- `SimpleITK.Image <https://simpleitk-prototype.readthedocs.io/en/latest/user_guide/plot_image.html#sphx-glr-user-guide-plot-image-py>`_
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- `pyvista.PolyData <https://docs.pyvista.org/core/points.html>`_
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- `pyvista.StructuredGrid <https://docs.pyvista.org/core/point-grids.html#structured-grid-creation>`_
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- `pyvista.UnstructuredGrid <https://docs.pyvista.org/core/point-grids.html#unstructured-grid-creation>`_
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- `vtkplotter.Actor <https://vtkplotter.embl.es/index.html>`_
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- `vtkplotter.Assembly <https://vtkplotter.embl.es/index.html>`_
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- `vedo.Actor <https://vedo.embl.es/index.html>`_
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- `vedo.Assembly <https://vedo.embl.es/index.html>`_
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- `skan.csr.Skeleton <https://jni.github.io/skan/api/skan.csr.html#module-skan.csr>`_
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- Exquisite volume rendering
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- `pyvista StructuredGrid <https://github.com/InsightSoftwareConsortium/itkwidgets/blob/master/examples/pyvista.StructuredGrid.ipynb>`_
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- `pyvista UnstructuredGrid <https://github.com/InsightSoftwareConsortium/itkwidgets/blob/master/examples/pyvista.UnstructuredGrid.ipynb>`_
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- `pyvista LiDAR <https://github.com/InsightSoftwareConsortium/itkwidgets/blob/master/examples/pyvistaLiDAR.ipynb>`_
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- `vtkplotter actors and volumes <https://github.com/InsightSoftwareConsortium/itkwidgets/blob/master/examples/vtkplotter.ipynb>`_
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- `vedo actors and volumes <https://github.com/InsightSoftwareConsortium/itkwidgets/blob/master/examples/vedo.ipynb>`_
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- `skan segmentation skeleton <https://github.com/InsightSoftwareConsortium/itkwidgets/blob/master/examples/SegmentationSkeleton.ipynb>`_
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or how to:

‎examples/vedo.ipynb‎

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Collecting vedo\n",
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" Downloading vedo-2021.0.3.tar.gz (9.3 MB)\n",
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"\u001b[K |████████████████████████████████| 9.3 MB 7.0 MB/s eta 0:00:01\n",
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"\u001b[?25hRequirement already satisfied: vtk in /home/matt/bin/miniconda/envs/itkwidgets/lib/python3.8/site-packages (from vedo) (9.0.1)\n",
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"Requirement already satisfied: numpy in /home/matt/bin/miniconda/envs/itkwidgets/lib/python3.8/site-packages (from vedo) (1.20.2)\n",
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"Building wheels for collected packages: vedo\n",
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" Building wheel for vedo (setup.py) ... \u001b[?25ldone\n",
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"\u001b[?25h Created wheel for vedo: filename=vedo-2021.0.3-py3-none-any.whl size=9384218 sha256=a1d8ecc77dc48f4c4584c09d436170d04fd291ce4f864bb60ed6a9514b6ace30\n",
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" Stored in directory: /home/matt/.cache/pip/wheels/9c/6f/7c/c8f69d87d6f20bfd65e4af01498ac78836e12308ee46cbad58\n",
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"Successfully built vedo\n",
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"Installing collected packages: vedo\n",
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"Successfully installed vedo-2021.0.3\n"
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]
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}
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],
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"source": [
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"# Note: This example currently does not work in MyBinder.\n",
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"\n",
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"# Install dependencies for this example\n",
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"# Note: This does not include itkwidgets, itself\n",
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"import sys\n",
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"!{sys.executable} -m pip install -U vedo"
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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": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"embedWindow(verbose=True): could not load ipyvtk_simple try:\n",
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"> pip install -U git+https://github.com/Kitware/ipyvtk-simple.git\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"(Sphere)0x7f185a66fc40"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"from vedo import load, datadir, Sphere\n",
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"from itkwidgets import view\n",
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"\n",
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"embryo = load(datadir+'embryo.slc')\n",
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"\n",
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"sph = Sphere(r=50).pos(10,20,30)\n",
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"scals = sph.points()[:,2] # scalars are z coords\n",
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"sph.pointColors(scals)"
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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": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\u001b[34;1m_________________________________________________________________\u001b[0m\n",
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"\u001b[7m\u001b[1m\u001b[34;1mVolume\u001b[0m\n",
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"\u001b[1m\u001b[34;1m position: \u001b[0m\u001b[34;1m(0.0, 0.0, 0.0)\u001b[0m\n",
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"\u001b[1m\u001b[34;1m dimensions: \u001b[0m\u001b[34;1m(256, 256, 256)\u001b[0m\n",
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"\u001b[1m\u001b[34;1m spacing: \u001b[0m\u001b[34;1m(1.0, 1.0, 1.0)\u001b[0m\n",
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"\u001b[1m\u001b[34;1m data dimension: \u001b[0m\u001b[34;1m3\u001b[0m\n",
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"\u001b[1m\u001b[34;1m memory size: \u001b[0m\u001b[34;1m16 MB\u001b[0m\n",
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"\u001b[1m\u001b[34;1m scalar #bytes: \u001b[0m\u001b[34;1m1\u001b[0m\n",
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"\u001b[1m\u001b[34;1m bounds: \u001b[0m\u001b[34;1mx=(0, 255)\u001b[0m\u001b[34;1m y=(0, 255)\u001b[0m\u001b[34;1m z=(0, 255)\u001b[0m\n",
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"\u001b[1m\u001b[34;1m scalar range: \u001b[0m\u001b[34;1m(0.0, 197.0)\u001b[0m\n",
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"\u001b[34;1m(logscale) Histogram\t(entries=100000)\n",
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" 4.97\n",
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"23.12 | ▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆\n",
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"46.25 | ▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆\n",
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"69.38 | ▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆\n",
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"92.50 | ▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆▆\n",
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"115.62| ▆▆▆▆▆▆▆▆▆▆▆▆\n",
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"138.75| ▆▆▆▆▆▆▆\n",
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"161.88| ▆▆\n",
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"\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"(Volume)0x7f185a66f9a0"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"embryo.printInfo()"
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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": 5,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "a29de347ee554ab5a2dbd5225f5a12d4",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Viewer(geometries=[{'vtkClass': 'vtkPolyData', 'points': {'vtkClass': 'vtkPoints', 'name': '_points', 'numberO…"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"view(actors=[embryo, sph])"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.8"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

‎examples/vtkplotter.ipynb‎

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