The curriculum of the numerics part of the course are covered by the Jupyter notebooks and the exercises.
About programming on the exam: You are supposed to be able to read and understand simple python code, and to do small modifications on a given code. Minor syntax errors will have no influence on the grade.
How to use Jupyterhub
The Jupyterhub gives you the option to read and use the Jupyter Notebooks in the course directly from your computer or mobile devices. The only thing required is a reasonable standard web browser.
- Go to Jupyterhub.
- Log in, use your standard NTNU user and password (it may take some time)
- You should now have the
Homepage in Jupyter open. Go to
Shared notebooks, click
Useon the notebook of your interest, and it will open. What you see open is your local copy of the file, so you can use it and modify it without making any harm.
- When you are finished with your session, please stop the kernel (see
Control panelin the upper right corner), and log out.
- All of you should have a user at the hub already. But if you don't (you can not log in), please send an email to firstname.lastname@example.org, and he will help you to get access.
- The system can sometimes be a bit slow. If it seems to have stopped completely, go to
Control panelin the upper right corner, stop the server, log out and log in again.
- Report severe problems with the hub to email@example.com, use Jupyterhub in the subject heading, and describe the problem as accurate as you can.
Local use of the Jupyter notebooks
If you prefer, the notebooks can be downloaded and used on your own computer, see How to install and use Anaconda . There is also a section about the use of Jupyter there.
There will also be generated pdf-files without any code. These should be used with the corresponding python files, as all examples, figure etc. are actually based on code to be executed.
NB! You are supposed to use either the Jupyter notebooks or (the pdf-notes + python code). The pdf-documents alone are not sufficient.
Typos etc. will be corrected when we are made aware of it, so you are recommended always to download a fresh copy of the files before using them.
|Introduction to Jupyter and Python||.ipynb|
|Polynomial interpolation||.ipynb||.py||Updated with Newton interpolation|
|Ordinary differential equations||.ipynb||.py|
|Stiff ordinary differential equations||.ipynb||as above|
|Finite difference methods for PDEs||.ipynb||.py|