Loading calibration extremely slow when using many segments

[silbe]

Describe the bug
When using many segments (e.g. ~50) loading the calibration (and probably saving it — don't remember right now) takes over an hour with 100% CPU load even on a reasonably beefy PC. Performing the calibration also takes a long time of 100% CPU load between measurements.

This is probably caused by having each calibration point represented as a separate instance in Python rather than using a single instance and storing the coefficients in a NumPy array.

In the long run it would probably be a good idea to use the calibration classes from scikit-rf instead. That would also make it easier to support additional calibration methods like TRL.

To Reproduce
Steps to reproduce the behavior:

1. Set number of points to 1023.
2. Set number of segments to 50.
3. Perform calibration using assistant.
4. Save calibration.
5. Load calibration again.

Expected behavior
Loading a calibration file with a couple thousand points should only take a few seconds.

Screenshots
n/a

Desktop (please complete the following information):

• OS: Linux
• Python version: 3.9.2
• NanoVNA-Saver version: v0.4.0-pre

Additional context
See description.

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[silbe]

I've tried this again with current main (commit fb50f4a) and loading large calibration files still takes at least several minutes (didn't wait longer). Please reopen this ticket.

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[silbe]

I don't see any changes in main that I expect to significantly improve calibration loading performance so this should still be applicable.

[github-actions]

There hasn't been any activity on this issue recently, and in order to prioritize active issues, it will be marked as stale.
Please make sure to update to the latest version and check if that solves the issue. Let us know if that works for you by leaving a 👍
Because this issue is marked as stale, it will be closed and locked in 7 days if no further activity occurs.
Thank you for your contributions!