Difference between revisions of "SRGS 2022"
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<s>July 4</s> ''Independence Day'' | <s>July 4</s> ''Independence Day'' | ||
| − | July | + | July 5 - Will S. |
| − | July | + | July 6 - Colin W. |
| − | July | + | July 7 - Anna R. |
| − | July | + | July 8 - Dhruv B. |
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| + | == Useful Links (General) == | ||
| + | * [https://github.com/nathanwbrei/shallow_water/blob/master/Paper.ipynb Shallow Water Jupyter Notebook example] | ||
== PHASM: neural net models of PDE solvers== | == PHASM: neural net models of PDE solvers== | ||
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=== Useful links/info: === | === Useful links/info: === | ||
| − | * [https://github.com/ws-kj/SpectrometerAngleRecogntion GitHub Repository] | + | * [https://github.com/ws-kj/SpectrometerAngleRecogntion Spectreye GitHub Repository] |
| + | * [https://github.com/arosnerd/GovSchoolGauge Gauge Reader Repository] | ||
* [[Media:angle-cam-image-recognition.pdf | angle-cam-image-recognition.pdf]] | * [[Media:angle-cam-image-recognition.pdf | angle-cam-image-recognition.pdf]] | ||
* Location of example images: '''/work/hallc/shms/spring17_angle_snaps/''' | * Location of example images: '''/work/hallc/shms/spring17_angle_snaps/''' | ||
Latest revision as of 20:32, 15 July 2022
General Info
Zoom Connection Info:
You can connect using https://jlab-org.zoomgov.com (Meeting ID: 160 808 1515). (Click "Expand" to the right for details -->):
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Presentation Schedule
June 27 - orientation
June 28 - Will S.
June 29 - Dhruv B.
June 30 - Anna R.
July 1 - Hari G.
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July 11 - Hari G.
July 12 - Will S.
July 13 - Colin W.
July 14 - Anna R.
July 15 - Dhruv B.
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July 18 - Hari G.
July 19 - Will S.
July 20 - Colin W.
July 21 - Anna R.
July 22 - Dhruv B.
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Useful Links (General)
PHASM: neural net models of PDE solvers
Students:
- Dhruv Bejugam
- Hari Gopal
- Colin Wolfe
Useful links:
- Phasm Intro Slides.pdf
- SciML curriculum
- PHASM repository: [1]
AI Feature Recognition: Extract Spectrometer Angle from Image
Students:
- Anna Rosner
- William Savage
Useful links/info:
- Spectreye GitHub Repository
- Gauge Reader Repository
- angle-cam-image-recognition.pdf
- Location of example images: /work/hallc/shms/spring17_angle_snaps/
- Time the image was acquired is embedded in the image file
- The numbers in the snapshot filenames are the run numbers
- 4,265 images ; ~92kB/file ; 391MB total
- The value of the encoders are stored in the MYA EPICS archive
- PV names are:
- ecSHMS_Angle
- ecHMS_Angle
- PV names are:
- Example logbook entry
- Location of gas gauge images: Google Drive
Initial thoughts from Brad
Brad's initial thoughts on approaching the problem (Click "Expand" to the right for details -->):
I had been imagining splitting the photos into two regions: one with the digits, and a second with the vernier scale. Each region would be evaluated/interpreted separately with some 'optimized' algorithms. 'Real' errors/discrepancies would be best indicated by a scanning for a mismatch between MYA and the analysis database record and/or the value flagged in the logbook which has generally been vetted and updated by a human. The simplest way to test 'bad' angles would be just to (randomly) shift the truth angle by a small amount -- that would be indistinguishable from an observed drift in the EPICS encoder system. I (or the students) can also look for angle shifts in the 'real' data, but that will take some poking around. It should be indicated by a sharp (small) jump in the MYA value as an offset is changed to bring the EPICS value in agreement with the camera readback. One other dataset that I could obtain is a movie of the angle changing over a range (the movie is just a compilation of frame grabs). The individual frames could be pulled out of the mp4 and evaluated individually over a continuously varying range of angles.