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
