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Very long T_solve times for some areas of RA/Dec space #30
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Iain, I have a (temporary) fork of Tetra3 that, among other things, improves how patterns are selected during database construction. As you have found, Tetra3's current database construction approach misses out on a lot of bright stars; the fork solves this problem such that even a much smaller database yields better solve rates. There are also other solve-time improvements that speed up solves in many cases. I would be really interested to see your results applied to the fork. It is at https://github.com/smroid/cedar-solve. Thanks, |
Hi Iain, I ran exercise_tetra3.py against the cedar-solve fork of Tetra3 on my Rpi4. Results: I don't have the visualizations as I was not running on a graphical system. It does seem that the cedar-solve fork of Tetra3 exhibits greater uniformity of solve times, and it accomplishes this with 1/8 database size. |
I've made some further improvements on cedar-solve. Results: pattern_catalog length: 1424136 |
Hi:
Please see description and code in attached .txt file.
late_sol_patterns.txt
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