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| author | Christian Kolset <christian.kolset@gmail.com> | 2025-11-01 16:07:06 -0600 |
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| committer | Christian Kolset <christian.kolset@gmail.com> | 2025-11-01 16:07:06 -0600 |
| commit | 81da658b3000aa02bd72771b06dfdcd726c0a075 (patch) | |
| tree | d3ddec6882a1fdbf9f8e2c6bea114cda84df98d8 /admin | |
| parent | 0fa588700aa9d222cc8f3e562a7b30e9fb75e287 (diff) | |
Added outline and statistical distribution image
Diffstat (limited to 'admin')
| -rw-r--r-- | admin/meeting-notes/2025-11-3.md | 29 |
1 files changed, 29 insertions, 0 deletions
diff --git a/admin/meeting-notes/2025-11-3.md b/admin/meeting-notes/2025-11-3.md new file mode 100644 index 0000000..1190484 --- /dev/null +++ b/admin/meeting-notes/2025-11-3.md @@ -0,0 +1,29 @@ +## Updates +- https://pythonnumericalmethods.studentorg.berkeley.edu/notebooks/Index.html +- Numerical Methods for Engineers Steven C Chapra + +--- +## Topics +and questions + +- [ ] Decide on textbook +- [ ] Module 4: Revise lecture order for 4.2 plotting philosophy +- [ ] Module 5: Go over outline +- [ ] Waiting on experimental/supplementary data from lab engineers (MECH 338) + +--- +## Discussion + + +--- +## Actions + +Module 4: Data Analysis and Processing + +- 4.1. Introduction to Data Analysis (describe the Panda Toolbox) -> One Lecture +- 4.2. We should focus on effective ways of looking at data (philosophy of making that make sense) -> One Lecture +- 4.3. I/Ofile handling (different types of data files: ASCII, CSV, TXT, JPEG,...) -> Here they will learn how to read/handle: datasets including images. -> One Lecture +- 4.4. Statistical Anasis (mean/averaging, standard deviation, variance...) -> **_Reminder: Ciprian to send application from Spectroscopy and CFD -> One Lecture_** +- 4.5. Data Cleaning (linear regression, least square fitting, extrapolation, moving average) -> One Lecture +- 4.6. Data Filtering & Signal Processing (filters: Gaussian Filter, Sobel edge detection, Kalman, Butterworth, FFT) -> We need to give a lecture of what is/how it works Digital filter design (lowpass, highpass, bandpass, filter response curves, how does one select a given filter). One lecture all theory so that in the second lecture they learn how to select different filters. -> Two lectures +- 4.7 Image processing: apply some of the filtering to make images sharper/crispier, teach them how to make videos/gifs out of images. -> One Lecture. Possible application: **_from CFD density data obtain Synthetic Schlieren images (Ciprian will send you this!)_** |