Full-field Tomography at PSI
This workflow has some details on the instrument the data is produced from (TOMCAT beamline) and the infrastructure PSI has concerning their data.
If you are more interested in the science and want to reproduce the data and not bother with the surrounding details/context, please refer to the...
Keywords: synchrotron, imaging, Jupyter notebooks, Python, Pulmonary arterial hypertension
Resource type: workflow
Full-field Tomography at PSI
https://pan-training.eu/workflows/backup-fork-of-full-field-tomography-at-psi-wip#workflow
https://pan-training.eu/materials/full-field-tomography-at-psi
This workflow has some details on the instrument the data is produced from (TOMCAT beamline) and the infrastructure PSI has concerning their data.
If you are more interested in the science and want to reproduce the data and not bother with the surrounding details/context, please refer to the Pulmonary arterial hypertension research workflow.
Full-field Tomography at PSI
Tomography datasets often present large volumes (100 GBs - few TBs) difficult to compress and transfer. The tomographic reconstruction is highly demanding on compute (GPU) and storage resources for the intermediate and/or final result. In addition, the optional image segmentation step may be demanding on computer memory.
The offline analysis (after experiment) could be performed remotely by users at home making it attractive for deployment as a cloud-like use case. Finally, this technique is applied at many facilities and in different scientific domains - therefore a portable result is more useful.
This entire process is illustrated with a typical experiment.
synchrotron, imaging, Jupyter notebooks, Python, Pulmonary arterial hypertension
research data scientist
life scientists
Python Laser Image Visualization
Tool showing pictures from different cameras (directories) in a grid and a stepwise counter-based scroll functionality. Most of the layout and (future) filter options are defined by command line to allow an easy integration into an workflow based on CWL, OWL (or Knime). In future developments...
Keywords: Python, Laser, Visualization, Cameras, Laser Ion Acceleration, Qt5
Resource type: software, git
Python Laser Image Visualization
https://gitlab.hzdr.de/fwcc/data-management/user-project-documentation/laserviztool
https://pan-training.eu/materials/python-laser-image-visualization
Tool showing pictures from different cameras (directories) in a grid and a stepwise counter-based scroll functionality. Most of the layout and (future) filter options are defined by command line to allow an easy integration into an workflow based on CWL, OWL (or Knime). In future developments most of the parameters can be changed interactive and saved to a json file which can be used to describe the next workflow inputs, so that an interactive workflow development is possible.
Python, Laser, Visualization, Cameras, Laser Ion Acceleration, Qt5
PaN Community
Photon Community
