Activity log
antoine
antoine
created
Learning path: Metadata catalogue services including PaN ontologies at 2022-05-06 15:43:54 UTC.
Someone
changed Short description
to: This course is split into two sections:
Theoretical background to SANS
Case study of nanodisks using the LOKI instrument
Useful links:
[SasView course](https://pan-learning.org/moodle/course/view.php?id=19)
[Wiki page on SANS](https://pan-learning.org/wiki/index.php/Small_angle_neutron_scattering,_SANS)
[Wiki problems (exercises with solutions) on SANS](https://pan-learning.org/wiki/index.php/Page_of_all_exercises#Exercises_in_Small_angle_neutron_scattering)
[Wiki simulation project (based on SANS-2 at PSI)](https://pan-learning.org/wiki/index.php/Simulation_project_SANS-2:_A_small_angle_neutron_scattering_instrument)
[McStas Simulation Tool](https://sim.e-neutrons.esss.dk/instrument-menu/intro-ns)
Someone
changed Language
to: English
Someone
changed Keywords
to: ["SANS", "nanodisks", "LoKi"]
Someone
changed Doi
to:
Someone
changed Short description
to: This course is split into two sections:
Theoretical background to SANS
Case study of nanodisks using the LOKI instrument
Useful links:
SasView course
Wiki page on SANS
Wiki problems (exercises with solutions) on SANS
Wiki simulation project (based on SANS-2 at PSI)
McStas Simulation Tool: Use the same login details as for pan-learning.org. There are currently two instruments: SANSsimple and SANSsimpleSpheres
[SasView course](https://pan-learning.org/moodle/course/view.php?id=19)
[Wiki page on SANS](https://pan-learning.org/wiki/index.php/Small_angle_neutron_scattering,_SANS)
[Wiki problems (exercises with solutions) on SANS](https://pan-learning.org/wiki/index.php/Page_of_all_exercises#Exercises_in_Small_angle_neutron_scattering)
[Wiki simulation project (based on SANS-2 at PSI)](https://pan-learning.org/wiki/index.php/Simulation_project_SANS-2:_A_small_angle_neutron_scattering_instrument)
[McStas Simulation Tool](https://sim.e-neutrons.esss.dk/instrument-menu/intro-ns)
Someone
changed Language
to: English
Someone
changed Keywords
to: ["small angle scattering ", "SAS"]
Someone
changed Doi
to:
Someone
changed Short description
to: Introduction to small angle scattering.
List of resources.
Someone
changed Language
to: English
Someone
changed Keywords
to: ["calculating source characteristics", "calculating heat-load", "simulation beamline optics", "coherence"]
Someone
changed Doi
to:
Someone
changed Short description
to: Welcome to the Hercules 2022 Oasys tutorial written by Manuel Sanchez del Rio and Juan Reyes Herrera.
The aim of this course is to learn the following:
Calculate main characteristics of synchrotron source (Bending magnets and Insertion devices).
Calculate the heat-load on different beamline components.
Simulating beamline optics by ray-tracing to obtain main parameters of the beam, e. g., size and divergence, energy resolution, intensity/flux.
Understand basic principles of X-ray optics: Mirrors and Crystals.
Basic concepts about coherence.
And it is split into four sections:
1. Introduction
2. Power Transport
3. Photon Transport
4. Coherence Transport
Someone
changed Short description
to: As a teacher, you can link a JupyterHub instance to your course that runs on our e-learning servers.The JupyterHub instance runs as a docker container that is launched when a student clicks on the link. The container will clone your chosen github repository where you can edit and store Jupyter notebooks.Students will be able to open these Jupyter notebooks and execute them remotely.
Crucially students do not require Jupyter to be installed on their computers or have prior knowledge of python. Examples where this might be useful:
- Show students how to reduce and analyse experimental data themselves using python.
- Introduce students to python modules or software used in data reduction and analysis.
- Allow students to virtually explore large scale facility instruments. For example by using McStas (neutron instrument simulator).
- Teach students data modelling and simulation techniques that use python.
Requirements:
What the student will interact with must be in the form of a Jupyter notebook.
Your notebooks must be on a public github repository.
Note that the entire repository you provide will be cloned not just selected notebooks. However it does not have to be the master branch.
Our containers already include common scientific python modules such as numpy, matplotlib and ipython. In addition we have containers with the following software installed:
1. McStas, McXtrace, SCIPP, SasVIew
2. Crispy
3. SimEx
If you require a container with other software to be installed it is possible to have a custom container created. Please email admin@pan-learning.org for help.
Useful Links:
- [Jupyter notebooks](https://jupyter.org/)
- [What is a docker container](https://www.docker.com/resources/what-container)? (and the [wiki page](https://en.wikipedia.org/wiki/Docker_(software)))
- [Docker and Jupyterhub](https://hub.docker.com/r/jupyterhub/jupyterhub/#help-and-resources)
If you wish to include a link to a Jupyterhub container for your course.
Please fill the form: Information to set up your container
Once you have filled in the form you will receive an email to let you know the JupyterHub link is being set up and any further instructions that are required.
Please note it may take a few days to be up and running.
Someone
changed Language
to: English
Someone
changed Keywords
to: ["jupyter notebooks", "docker container", "moodle", "e-teaching"]
Someone
changed Doi
to:
Someone
changed Short description
to: As a teacher, you can link a JupyterHub instance to your course that runs on our e-learning servers.The JupyterHub instance runs as a docker container that is launched when a student clicks on the link. The container will clone your chosen github repository where you can edit and store Jupyter notebooks.Students will be able to open these Jupyter notebooks and execute them remotely.
Crucially students do not require Jupyter to be installed on their computers or have prior knowledge of python. Examples where this might be useful:
- Show students how to reduce and analyse experimental data themselves using python.
- Introduce students to python modules or software used in data reduction and analysis.
- Allow students to virtually explore large scale facility instruments. For example by using McStas (neutron instrument simulator).
- Teach students data modelling and simulation techniques that use python.
Requirements:
What the student will interact with must be in the form of a Jupyter notebook.
Your notebooks must be on a public github repository.
Note that the entire repository you provide will be cloned not just selected notebooks. However it does not have to be the master branch.
Our containers already include common scientific python modules such as numpy, matplotlib and ipython. In addition we have containers with the following software installed:
1. McStas, McXtrace, SCIPP, SasVIew
2. Crispy
3. SimEx
If you require a container with other software to be installed it is possible to have a custom container created. Please email admin@pan-learning.org for help.
Useful Links:
- [Jupyter notebooks](https://jupyter.org/)
- [What is a docker container](https://www.docker.com/resources/what-container)? (and the [wiki page](https://en.wikipedia.org/wiki/Docker_(software)))
- [Docker and Jupyterhub](https://hub.docker.com/r/jupyterhub/jupyterhub/#help-and-resources)
If you wish to include a link to a Jupyterhub container for your course.
Please fill the form: Information to set up your container
Once you have filled in the form you will receive an email to let you know the JupyterHub link is being set up and any further instructions that are required.
Please note it may take a few days to be up and running.
Someone
changed Language
to: English
Someone
changed Keywords
to: []
Someone
changed Doi
to:
Someone
changed Short description
to: This course has the notebooks from the first four chapters of the IKON python course:
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.
To access click on Illumidesk →Start My Server → Assignments →pythoncourse (drop down menu) → fetch
Any notebooks you fetch will be visible on your illumidesk files tab.
Do not submit the notebooks for feedback.
Someone
changed Language
to: English
Someone
changed Doi
to:
Someone
changed Short description
to: We will learn with James Lord about semiconductors, muonium spectroscopy, molecular radical states at different temperatures, energy levels and spin polarization.
Rui Vilao will introduce us to muons in Semiconductors.
Rui Vilao continues the discussion on using µSR on semiconductors.
Someone
changed Language
to: English
Someone
changed Doi
to:
Someone
changed Short description
to: 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 (bellow).
Click Start My Server > Start and your container will launch.
antoine
antoine
updated
Small Angle Scattering Data Analysis using SasView at 2022-05-06 13:51:07 UTC.
Someone
changed Language
to: English
Someone
changed Doi
to:
Someone
changed Short description
to: Small Angle Scattering Data Analysis using SasView
Someone
changed Language
to: English
Someone
changed Doi
to:
Someone
changed Short description
to: This module is divided into 10 sections. First nine will teach you about QENS instruments and theory. A case study is presented in the last section.
Estimated Completion Time: 1 Hour
antoine
antoine
updated
Quasielastic Neutron Scattering Course (1st iteration) at 2022-05-06 13:47:30 UTC.
Someone
changed Language
to: English
Someone
changed Keywords
to: ["QENS", "neutron"]
Someone
changed Doi
to: