Add wave PVD files - #3
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* add FORGE data * add large volume * add delaunay points * add embryo * add antarctica_velocity.vtp * add translucent room sruface mesh * added tree.ply * converted tree.ply to binary * added ensight example file * add skybox2 * add GPR example data * add thermal probes * add turbineblade * add carburetor * add lobster.ply * add woman.stl * Add urn.stl * add tigerfighter.obj * add pepper.ply and pepper.obj * add man_face.stl * renamed pepper.obj to drill.obj * add mars and stars * make mars smaller * add notch stress FEA example * add notch displacement * notch_disp.vtk --> notch_disp.vtu * actually add file * add louis * add nefertiti ply * name change * add geo sample data * add cylinder in crossflow dataset * add context to data * add hdr files * add wave PVD files (#3) * add osmnx graph * add pvd files from paraview data * add lucy * Add `DICOM_Stack` dataset This dataset will be used to test improved volume rendering and DICOM stack reading per pyvista/pyvista-support issue #500. The Cancer Imaging Archive (TCIA) is a service which de-identifies and hosts a large archive of medical images of cancer accessible for public download. The data are organized as “collections”; typically patients’ imaging related by a common disease (e.g. lung cancer), image modality or type (MRI, CT, digital histopathology, etc) or research focus. DICOM is the primary file format used by TCIA for radiology imaging. Supporting data related to the images such as patient outcomes, treatment details, genomics and expert analyses are also provided when available. This dataset is a member of the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium Sarcomas (CPTAC-SAR) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology and pathology images from CPTAC patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes which may correlate to corresponding proteomic, genomic and clinical data. This data has been published under the `Creative Commons Attribution 3.0 Unported License` and must adhere to the CPTAC Data Use Agreement. Per the TCIA Data Usage Policy (see License file), all oral or written presentations, disclosures, or publications must acknowledge the specific dataset(s) or applicable accession number(s) and the NIH-designated data repositories through which the investigator accessed any data. The appropriate citations are included in the CITATIONS file. The metadata for this dataset is included in metadata.csv. Questions may be directed to <help@cancerimagingarchive.net>. Title: Forearm Sarcoma DataDescription URI: https://doi.org/10.7937/TCIA.2019.9bt23r95 Number of Images: 3 Total Size: 1.51 MB File Format: DICOM Co-authored-by: banesullivan <banesulli@gmail.com> Co-authored-by: Alex Kaszynski <akascap@gmail.com> Co-authored-by: Bane Sullivan <banesullivan@gmail.com> Co-authored-by: Flamm, Matthew H <matthewhflamm@gmail.com> Co-authored-by: MatthewFlamm <39341281+MatthewFlamm@users.noreply.github.com>
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* add FORGE data * add large volume * add delaunay points * add embryo * add antarctica_velocity.vtp * add translucent room sruface mesh * added tree.ply * converted tree.ply to binary * added ensight example file * add skybox2 * add GPR example data * add thermal probes * add turbineblade * add carburetor * add lobster.ply * add woman.stl * Add urn.stl * add tigerfighter.obj * add pepper.ply and pepper.obj * add man_face.stl * renamed pepper.obj to drill.obj * add mars and stars * make mars smaller * add notch stress FEA example * add notch displacement * notch_disp.vtk --> notch_disp.vtu * actually add file * add louis * add nefertiti ply * name change * add geo sample data * add cylinder in crossflow dataset * add context to data * add hdr files * add wave PVD files (#3) * add osmnx graph * add pvd files from paraview data * add lucy * Put `.dcm` files in separate `data` subfolder `vtk.vtkDICOMImageReader` cannot parse non-dcm files in a folder. * Replace `data` folder with `.zip` file Folders cannot be downloaded using the GitHub API, which is causing DICOM Reader tests to fail in `pyvista`. Instead, zip the folder. This will be unzipped when downloaded. Co-authored-by: banesullivan <banesulli@gmail.com> Co-authored-by: Alex Kaszynski <akascap@gmail.com> Co-authored-by: Bane Sullivan <banesullivan@gmail.com> Co-authored-by: Flamm, Matthew H <matthewhflamm@gmail.com> Co-authored-by: MatthewFlamm <39341281+MatthewFlamm@users.noreply.github.com>
user27182
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Sep 6, 2026
`PVD/wavy.zip` was swept up by the `PVD/**` glob and inherited a ParaView attribution it never had. Pull request #3 publishes the PyVista script that wrote its frames, and the grids in the archive match what that script produces, so it is PyVista's own data under MIT. `vtu_series`, which the pull request that added it says is a conversion of that archive, follows. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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This is a zip file with the following structure:
The
.vtsfiles were generated with the following script:The
.pvdfile was created manually.wavy.pvd
This is being used for pyvista/pyvista#1564.
The .pvd file can be read by Paraview:
