Pyfar Tutorial Videos
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- Dominant language
- Python
- Stars
- 3
- Forks
- 2
- Avg merge
- 2d 3h
- Merged PRs (30d)
- 3
Description
Idea
- Produce tutorial videos based on example notebooks to post on youtube
- Target audience: students and researchers in acoustics
- Produce short and focused videos (e.g. one for signal and one for filters instead of one introducing multiple aspects at once)
- Organize a 2-3 day retreat in spring 2027 to produce the videos at TU Berlin with the help of the Team digit (Video studio with green screen and light board available)
- Get funding from DEGA or EAA
List of videos
- Intro-video for the pyfar ecosystem:
- multiple open source and cross-insitutue packages
- super short intro for each package
- installation and trouble shooting
- contributing
- Working with Audio Objects (with link to FFT and arithmetics notebook)4. Plotting and interactive plots
- Filtering
- RIR measurement
- RIR parameters
- Coordinates and Rotation
- Binaural synthesis
- ...?
Tips from TUB team digit
- Have rather short videos up to 10 minutes (more might be fine for our target audience)
- Prepare a story board in advance
- Add interactive aspects, e.g.
- small task beyond what is shown in the notebook at the middle/end of a tutorial
- suggestions for further tutorials
ToDo
- Decide on date
- Secure funding
- Finalize list of tutorials
- Assign persons to tutorials
- ...
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the example notebooks that are proposed as the basis for the tutorials. Use the listed video topics and planning checklist to define the scope, participants, schedule, and funding needs; done means the tutorial list and production plan are agreed.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- content, documentation
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100