6 materials found
Keywords:
Python
Tomwer – add a python script
Tutorial on how user can add their own processing into the workflow through a python script (advanced usage).
Scientific topics: tomography
Keywords: tomography, tomotools, tomwer, nabu, Python, canvas
Resource type: video
Tomwer – add a python script
https://www.youtube.com/watch?v=VGv628AIgn8
https://pan-training.eu/materials/tomwer-add-a-python-script
Tutorial on how user can add their own processing into the workflow through a python script (advanced usage).
tomography
tomography, tomotools, tomwer, nabu, Python, canvas
TANGO tutorials
Documentation and tutorials to understand what Tango Controls is, guide your first steps as a user, developer or administrator of Tango.
Keywords: synchrotron control, TANGO, c++, Python, tango-controls, arduino, scada
Resource type: documenation
TANGO tutorials
https://tango-controls.readthedocs.io/en/latest/tutorials-and-howtos/tutorials/index.html
https://pan-training.eu/materials/tango-tutorials
Documentation and tutorials to understand what Tango Controls is, guide your first steps as a user, developer or administrator of Tango.
synchrotron control, TANGO, c++, Python, tango-controls, arduino, scada
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 Workshop (IKON21)
If you have self enrolled onto the course please wait 5 minutes before launching the JupyterHub
Access the course by clicking on the JupyterHub link.
Click Start My Server > Start and your container will launch.
In the folder called Notebooks you will find the following:
1. Jupyter...
Keywords: data analysis library pandas, jupyter, Python, numpy, matplotlib, Ipywidgets, scipy, mcstas script
Resource type: Moodle course, e-learning
Python Workshop (IKON21)
https://pan-learning.org/moodle/course/view.php?id=89
https://pan-training.eu/materials/python-workshop-ikon21
If you have self enrolled onto the course please wait 5 minutes before launching the JupyterHub
Access the course by clicking on the JupyterHub link.
Click Start My Server > Start and your container will launch.
In the folder called Notebooks you will find the following:
1. Jupyter basics: Jupyter notebook introduction.
2. Python basics: Basic language principles, Sequence data types, Control structures, Working with functions, Using modules, Input and output, Python 2 vs 3, Python classes.
3. Using external Libraries: Scientific libraries numpy, Plotting with matplotlib, Ipywidgets, Fitting scipy, Data analysis library pandas, Testing.
4. Molecular visualization: Visualization tutorial, Atomistic simulation environment.
5. McStas script
6. SCIPP
You can find a copy of the notebooks at https://github.com/ess-dmsc-dram/python-course-ikon/tree/master/notebooks
This course was created by the Data Reduction, Analysis and Modelling group of the ESS.
This version of the course was specifically created for IKON21 in September 2021.
data analysis library pandas, jupyter, Python, numpy, matplotlib, Ipywidgets, scipy, mcstas script
Python Workshop (IKON20)
THIS IS THE PREVIOUS IKON PYTHON COURSE FROM MARCH 2021 - The new one can be found [here](https://pan-learning.org/moodle/course/view.php?id=89)
AS OF 16/09/2021 THERE IS AN ISSUE WITH THE LINK - THIS WILL BE FIXED SOON
This course has something for all levels of python and is split into 7...
Keywords: data analysis library pandas, jupyter, Python, numpy, matplotlib, Ipywidgets, scipy, mcstas script
Resource type: Moodle course, e-learning
Python Workshop (IKON20)
https://pan-learning.org/moodle/course/view.php?id=36
https://pan-training.eu/materials/python-workshop-ikon20
THIS IS THE PREVIOUS IKON PYTHON COURSE FROM MARCH 2021 - The new one can be found [here](https://pan-learning.org/moodle/course/view.php?id=89)
AS OF 16/09/2021 THERE IS AN ISSUE WITH THE LINK - THIS WILL BE FIXED SOON
This course has something for all levels of python and is split into 7 sections.
The first four contain a set of jupyter notebooks that are designed to be worked through individually. You are encouraged to pick and choose which sections you are interested in.
The other three contain notebooks to help you learn how to use python based McStas script and SCIPP along with an extra module with an example of Covid data anlysis.
1. Jupyter basics: Jupyter notebook introduction.
2. Python basics: Basic language principles, Sequence data types, Control structures, Working with functions, Using modules, Input and output, Python 2 vs 3, Python classes.
3. Using external Libraries: Scientific libraries numpy, Plotting with matplotlib, Ipywidgets, Fitting scipy, Data analysis library pandas, Testing.
4. Molecular visualization: Visualization tutorial, Atomistic simulation environment.
5. McStas script
6. Extras
7. SCIPP
The notebooks can accessed and run via the Jupyter hub link. A new window will open, which will ask you to Start My Server.
You can then chose which environment you would like to use (Basic Jupyter with McStas or Jupyter with SCIPP). Note that both include all the notebooks.
To access the notebooks please navigate to python-course-ikon > notebooks.
This course was created by the Data Reduction, Analysis and Modelling Group of the ESS. This version of the course was specifically created for IKON20 in March 2021.
data analysis library pandas, jupyter, Python, numpy, matplotlib, Ipywidgets, scipy, mcstas script
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
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