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aewallin avatar aewallin commented on August 21, 2024

IIRC all current tests are with fixed datasets and against xDEV values from Stable32 or another program.

Testing with random data against theoretical predictions is a good idea, but note that:

  • you are also testing the noise-generator and underlying random number source at the same time. is it clear that different platforms (win, mac, linux, x86, arm, etc.) produce the same random numbers?
  • the assertion needs to be "soft" to some extent, i.e. accept a confidence-interval at some give confidence-level. How do you set the level? Would it be OK if one in 1000 or a million tests fail although the algorithm is correct?
  • testing with random data with a new seed every time could be used to validate the confidence intervals produced by allantools. This would be a new and useful addition. Generate many new datasets, produce an xDEV histogram, and check that the confidence-interval agrees with the width of the histogram.

The confidence interval work is unfinished. I worked on the noise-ID algorithms in January, but didn't settle on how (in what order etc) the noise-ID should be done:
http://www.anderswallin.net/2018/01/power-law-noise-identification-for-allantools/
In principle the Stable32 source is now available if one wanted the same behavior as this "golden" code..

from allantools.

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