For greater confidence in Allan Variance measurements I decided to perform some experiments whose results I will share with you below.
All tests are carried out in Python with the package allantools found at
https://github.com/aewallin/allantools/Overlapping Allan Deviation is chosen so that the results can be compared with other measurements in this thread.
First test is carried out with the 9-point test set from
http://www.ieee-uffc.org/frequency-control/learning-riley.asp (ieee-uffc)
The 9-point test set is normalised by subtracting the mean from each sample. The calculated result for tau=1 and tau=2 is identical to the values listed in table II(ieee-uffc). Here follows the code:
The algorithm for a 1000 point pseudo random integer sequence from section "Test Data" in (ieee-uffc) was implemented and executed. The results for tau=1, tau=10 and and tau=100 are identical to the values listed in table III(ieee-uffc). Here follows the code:
Confidence in the allantools python library, and its use, is hereby present.
Moving on to the data file from Dr. Frank: Ltz5_tc_9.txt (find it earlier in this thread and remember to remove "zero" samples)
As can be seen from the plot it is almost identical to Andreas plot from reply #429. Only difference is that Andreas uses tau0=1 as time unit and thus you have to know the sample spacing in order to interpret the graph. I prefer to use rate=0.25 corresponding to tau0=4 seconds (2s acquire (100 NPLC) + 2s auto zero) between samples.
However confidence in the tool (afair DF6JB Plotter) that Andreas uses for allan deviation calculation and graphing is present.
@brandic: hope you agree, no factor 10 error here :-)
Allan deviation plots of my own reference follows in part II
-Jorn